diff --git a/InternVL-main/internvl_chat/work_dirs/internvl_chat_v2_5/ak/100/added_tokens.json b/InternVL-main/internvl_chat/work_dirs/internvl_chat_v2_5/ak/100/added_tokens.json new file mode 100644 index 0000000000000000000000000000000000000000..35f5893c8e29d6102945a953529819a2d56c62a9 --- /dev/null +++ b/InternVL-main/internvl_chat/work_dirs/internvl_chat_v2_5/ak/100/added_tokens.json @@ -0,0 +1,11 @@ +{ + "": 92552, + "": 92545, + "": 92548, + "": 92550, + "": 92546, + "": 92551, + "": 92544, + "": 92547, + "": 92549 +} diff --git a/InternVL-main/internvl_chat/work_dirs/internvl_chat_v2_5/ak/100/config.json b/InternVL-main/internvl_chat/work_dirs/internvl_chat_v2_5/ak/100/config.json new file mode 100644 index 0000000000000000000000000000000000000000..9ab1c21946689b81f232b2900131670bea74b77b --- /dev/null +++ b/InternVL-main/internvl_chat/work_dirs/internvl_chat_v2_5/ak/100/config.json @@ -0,0 +1,204 @@ +{ + "_commit_hash": null, + "_name_or_path": "/home1/gmh/InternVL-main/internvl_chat/work_dirs/internvl_chat_v2_5/ak/checkpoint-100", + "architectures": [ + "InternVLChatModel" + ], + "auto_map": { + "AutoConfig": "OpenGVLab/InternVL2_5-2B--configuration_internvl_chat.InternVLChatConfig", + "AutoModel": "OpenGVLab/InternVL2_5-2B--modeling_internvl_chat.InternVLChatModel", + "AutoModelForCausalLM": "OpenGVLab/InternVL2_5-2B--modeling_internvl_chat.InternVLChatModel" + }, + "downsample_ratio": 0.5, + "dynamic_image_size": true, + "force_image_size": 448, + "hidden_size": 2048, + "llm_config": { + "_name_or_path": "internlm/internlm2_5-1_8b-chat", + "add_cross_attention": false, + "architectures": [ + "InternLM2ForCausalLM" + ], + "attn_implementation": "flash_attention_2", + "auto_map": { + "AutoConfig": "configuration_internlm2.InternLM2Config", + "AutoModel": "modeling_internlm2.InternLM2ForCausalLM", + "AutoModelForCausalLM": "modeling_internlm2.InternLM2ForCausalLM", + "AutoModelForSequenceClassification": "modeling_internlm2.InternLM2ForSequenceClassification" + }, + "bad_words_ids": null, + "begin_suppress_tokens": null, + "bias": false, + "bos_token_id": 1, + "chunk_size_feed_forward": 0, + "cross_attention_hidden_size": null, + "decoder_start_token_id": null, + "diversity_penalty": 0.0, + "do_sample": false, + "early_stopping": false, + "encoder_no_repeat_ngram_size": 0, + "eos_token_id": 2, + "exponential_decay_length_penalty": null, + "finetuning_task": null, + "forced_bos_token_id": null, + "forced_eos_token_id": null, + "hidden_act": "silu", + "hidden_size": 2048, + "id2label": { + "0": "LABEL_0", + "1": "LABEL_1" + }, + "initializer_range": 0.02, + "intermediate_size": 8192, + "is_decoder": false, + "is_encoder_decoder": false, + "label2id": { + "LABEL_0": 0, + "LABEL_1": 1 + }, + "length_penalty": 1.0, + "max_length": 20, + "max_position_embeddings": 32768, + "min_length": 0, + "model_type": "internlm2", + "no_repeat_ngram_size": 0, + "num_attention_heads": 16, + "num_beam_groups": 1, + "num_beams": 1, + "num_hidden_layers": 24, + "num_key_value_heads": 8, + "num_return_sequences": 1, + "output_attentions": false, + "output_hidden_states": false, + "output_scores": false, + "pad_token_id": 2, + "prefix": null, + "pretraining_tp": 1, + "problem_type": null, + "pruned_heads": {}, + "remove_invalid_values": false, + "repetition_penalty": 1.0, + "return_dict": true, + "return_dict_in_generate": false, + "rms_norm_eps": 1e-05, + "rope_scaling": { + "factor": 2.0, + "type": "dynamic" + }, + "rope_theta": 1000000, + "sep_token_id": null, + "suppress_tokens": null, + "task_specific_params": null, + "temperature": 1.0, + "tf_legacy_loss": false, + "tie_encoder_decoder": false, + "tie_word_embeddings": false, + "tokenizer_class": null, + "top_k": 50, + "top_p": 1.0, + "torch_dtype": "bfloat16", + "torchscript": false, + "transformers_version": "4.43.2", + "typical_p": 1.0, + "use_bfloat16": true, + "use_cache": false, + "vocab_size": 92553 + }, + "max_dynamic_patch": 6, + "min_dynamic_patch": 1, + "model_type": "internvl_chat", + "pad2square": false, + "ps_version": "v2", + "select_layer": -1, + "template": "internvl2_5", + "tie_word_embeddings": false, + "torch_dtype": "bfloat16", + "transformers_version": null, + "use_backbone_lora": 0, + "use_llm_lora": 0, + "use_thumbnail": true, + "vision_config": { + "_name_or_path": "", + "add_cross_attention": false, + "architectures": [ + "InternVisionModel" + ], + "attention_dropout": 0.0, + "bad_words_ids": null, + "begin_suppress_tokens": null, + "bos_token_id": null, + "chunk_size_feed_forward": 0, + "cross_attention_hidden_size": null, + "decoder_start_token_id": null, + "diversity_penalty": 0.0, + "do_sample": false, + "drop_path_rate": 0.0, + "dropout": 0.0, + "early_stopping": false, + "encoder_no_repeat_ngram_size": 0, + "eos_token_id": null, + "exponential_decay_length_penalty": null, + "finetuning_task": null, + "forced_bos_token_id": null, + "forced_eos_token_id": null, + "hidden_act": "gelu", + "hidden_size": 1024, + "id2label": { + "0": "LABEL_0", + "1": "LABEL_1" + }, + "image_size": 448, + "initializer_factor": 1.0, + "initializer_range": 0.02, + "intermediate_size": 4096, + "is_decoder": false, + "is_encoder_decoder": false, + "label2id": { + "LABEL_0": 0, + "LABEL_1": 1 + }, + "layer_norm_eps": 1e-06, + "length_penalty": 1.0, + "max_length": 20, + "min_length": 0, + "model_type": "intern_vit_6b", + "no_repeat_ngram_size": 0, + "norm_type": "layer_norm", + "num_attention_heads": 16, + "num_beam_groups": 1, + "num_beams": 1, + "num_channels": 3, + "num_hidden_layers": 24, + "num_return_sequences": 1, + "output_attentions": false, + "output_hidden_states": false, + "output_scores": false, + "pad_token_id": null, + "patch_size": 14, + "prefix": null, + "problem_type": null, + "pruned_heads": {}, + "qk_normalization": false, + "qkv_bias": true, + "remove_invalid_values": false, + "repetition_penalty": 1.0, + "return_dict": true, + "return_dict_in_generate": false, + "sep_token_id": null, + "suppress_tokens": null, + "task_specific_params": null, + "temperature": 1.0, + "tf_legacy_loss": false, + "tie_encoder_decoder": false, + "tie_word_embeddings": true, + "tokenizer_class": null, + "top_k": 50, + "top_p": 1.0, + "torch_dtype": "bfloat16", + "torchscript": false, + "transformers_version": "4.43.2", + "typical_p": 1.0, + "use_bfloat16": true, + "use_flash_attn": true + } +} diff --git a/InternVL-main/internvl_chat/work_dirs/internvl_chat_v2_5/ak/100/generation_config.json b/InternVL-main/internvl_chat/work_dirs/internvl_chat_v2_5/ak/100/generation_config.json new file mode 100644 index 0000000000000000000000000000000000000000..918fe50c5a6fd362e537376348091b2bc5f51820 --- /dev/null +++ b/InternVL-main/internvl_chat/work_dirs/internvl_chat_v2_5/ak/100/generation_config.json @@ -0,0 +1,8 @@ +{ + "_from_model_config": true, + "eos_token_id": [ + 92542, + 92543 + ], + "transformers_version": "4.43.2" +} diff --git a/InternVL-main/internvl_chat/work_dirs/internvl_chat_v2_5/ak/100/special_tokens_map.json b/InternVL-main/internvl_chat/work_dirs/internvl_chat_v2_5/ak/100/special_tokens_map.json new file mode 100644 index 0000000000000000000000000000000000000000..cbf34a50d27c43ed8d1e2823b800b4e6f66e637a --- /dev/null +++ b/InternVL-main/internvl_chat/work_dirs/internvl_chat_v2_5/ak/100/special_tokens_map.json @@ -0,0 +1,47 @@ +{ + "additional_special_tokens": [ + "<|im_start|>", + "<|im_end|>", + "<|action_start|>", + "<|action_end|>", + "<|interpreter|>", + "<|plugin|>", + "", + "", + "", + "", + "", + "", + "", + "", + "" + ], + "bos_token": { + "content": "", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false + }, + "eos_token": { + "content": "", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false + }, + "pad_token": { + "content": "", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false + }, + "unk_token": { + "content": "", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false + } +} diff --git a/InternVL-main/internvl_chat/work_dirs/internvl_chat_v2_5/ak/100/tokenization_internlm2.py b/InternVL-main/internvl_chat/work_dirs/internvl_chat_v2_5/ak/100/tokenization_internlm2.py new file mode 100644 index 0000000000000000000000000000000000000000..1be581da37ef678de65f2737493fc0ed7160446e --- /dev/null +++ b/InternVL-main/internvl_chat/work_dirs/internvl_chat_v2_5/ak/100/tokenization_internlm2.py @@ -0,0 +1,235 @@ +# Copyright (c) The InternLM team and The HuggingFace Inc. team. All rights reserved. +# +# This code is based on transformers/src/transformers/models/llama/tokenization_llama.py +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +"""Tokenization classes for InternLM.""" +import os +from shutil import copyfile +from typing import Any, Dict, List, Optional, Tuple + +import sentencepiece as spm +from transformers.tokenization_utils import PreTrainedTokenizer +from transformers.utils import logging + +logger = logging.get_logger(__name__) + +VOCAB_FILES_NAMES = {'vocab_file': './tokenizer.model'} + +PRETRAINED_VOCAB_FILES_MAP = {} + + +# Modified from transformers.model.llama.tokenization_llama.LlamaTokenizer +class InternLM2Tokenizer(PreTrainedTokenizer): + """ + Construct a InternLM2 tokenizer. Based on byte-level Byte-Pair-Encoding. + + Args: + vocab_file (`str`): + Path to the vocabulary file. + """ + + vocab_files_names = VOCAB_FILES_NAMES + pretrained_vocab_files_map = PRETRAINED_VOCAB_FILES_MAP + model_input_names = ['input_ids', 'attention_mask'] + _auto_class = 'AutoTokenizer' + + def __init__( + self, + vocab_file, + unk_token='', + bos_token='', + eos_token='', + pad_token='', + sp_model_kwargs: Optional[Dict[str, Any]] = None, + add_bos_token=True, + add_eos_token=False, + decode_with_prefix_space=False, + clean_up_tokenization_spaces=False, + **kwargs, + ): + self.sp_model_kwargs = {} if sp_model_kwargs is None else sp_model_kwargs + self.vocab_file = vocab_file + self.add_bos_token = add_bos_token + self.add_eos_token = add_eos_token + self.decode_with_prefix_space = decode_with_prefix_space + self.sp_model = spm.SentencePieceProcessor(**self.sp_model_kwargs) + self.sp_model.Load(vocab_file) + self._no_prefix_space_tokens = None + super().__init__( + bos_token=bos_token, + eos_token=eos_token, + unk_token=unk_token, + pad_token=pad_token, + clean_up_tokenization_spaces=clean_up_tokenization_spaces, + **kwargs, + ) + + @property + def no_prefix_space_tokens(self): + if self._no_prefix_space_tokens is None: + vocab = self.convert_ids_to_tokens(list(range(self.vocab_size))) + self._no_prefix_space_tokens = {i for i, tok in enumerate(vocab) if not tok.startswith('▁')} + return self._no_prefix_space_tokens + + @property + def vocab_size(self): + """Returns vocab size""" + return self.sp_model.get_piece_size() + + @property + def bos_token_id(self) -> Optional[int]: + return self.sp_model.bos_id() + + @property + def eos_token_id(self) -> Optional[int]: + return self.sp_model.eos_id() + + def get_vocab(self): + """Returns vocab as a dict""" + vocab = {self.convert_ids_to_tokens(i): i for i in range(self.vocab_size)} + vocab.update(self.added_tokens_encoder) + return vocab + + def _tokenize(self, text): + """Returns a tokenized string.""" + return self.sp_model.encode(text, out_type=str) + + def _convert_token_to_id(self, token): + """Converts a token (str) in an id using the vocab.""" + return self.sp_model.piece_to_id(token) + + def _convert_id_to_token(self, index): + """Converts an index (integer) in a token (str) using the vocab.""" + token = self.sp_model.IdToPiece(index) + return token + + def _maybe_add_prefix_space(self, tokens, decoded): + if tokens and tokens[0] not in self.no_prefix_space_tokens: + return ' ' + decoded + else: + return decoded + + def convert_tokens_to_string(self, tokens): + """Converts a sequence of tokens (string) in a single string.""" + current_sub_tokens = [] + out_string = '' + prev_is_special = False + for token in tokens: + # make sure that special tokens are not decoded using sentencepiece model + if token in self.all_special_tokens: + if not prev_is_special: + out_string += ' ' + out_string += self.sp_model.decode(current_sub_tokens) + token + prev_is_special = True + current_sub_tokens = [] + else: + current_sub_tokens.append(token) + prev_is_special = False + out_string += self.sp_model.decode(current_sub_tokens) + out_string = self.clean_up_tokenization(out_string) + out_string = self._maybe_add_prefix_space(tokens=tokens, decoded=out_string) + return out_string[1:] + + def save_vocabulary(self, save_directory, filename_prefix: Optional[str] = None) -> Tuple[str]: + """ + Save the vocabulary and special tokens file to a directory. + + Args: + save_directory (`str`): + The directory in which to save the vocabulary. + + Returns: + `Tuple(str)`: Paths to the files saved. + """ + if not os.path.isdir(save_directory): + logger.error(f'Vocabulary path ({save_directory}) should be a directory') + return + out_vocab_file = os.path.join( + save_directory, (filename_prefix + '-' if filename_prefix else '') + VOCAB_FILES_NAMES['vocab_file'] + ) + + if os.path.abspath(self.vocab_file) != os.path.abspath(out_vocab_file) and os.path.isfile(self.vocab_file): + copyfile(self.vocab_file, out_vocab_file) + elif not os.path.isfile(self.vocab_file): + with open(out_vocab_file, 'wb') as fi: + content_spiece_model = self.sp_model.serialized_model_proto() + fi.write(content_spiece_model) + + return (out_vocab_file,) + + def build_inputs_with_special_tokens(self, token_ids_0, token_ids_1=None): + if self.add_bos_token: + bos_token_ids = [self.bos_token_id] + else: + bos_token_ids = [] + + output = bos_token_ids + token_ids_0 + + if token_ids_1 is not None: + output = output + token_ids_1 + + if self.add_eos_token: + output = output + [self.eos_token_id] + + return output + + def get_special_tokens_mask( + self, token_ids_0: List[int], token_ids_1: Optional[List[int]] = None, already_has_special_tokens: bool = False + ) -> List[int]: + """ + Retrieve sequence ids from a token list that has no special tokens added. This method is called when adding + special tokens using the tokenizer `prepare_for_model` method. + + Args: + token_ids_0 (`List[int]`): + List of IDs. + token_ids_1 (`List[int]`, *optional*): + Optional second list of IDs for sequence pairs. + already_has_special_tokens (`bool`, *optional*, defaults to `False`): + Whether or not the token list is already formatted with special tokens for the model. + + Returns: + `List[int]`: A list of integers in the range [0, 1]: 1 for a special token, 0 for a sequence token. + """ + if already_has_special_tokens: + return super().get_special_tokens_mask( + token_ids_0=token_ids_0, token_ids_1=token_ids_1, already_has_special_tokens=True + ) + + if token_ids_1 is None: + return [1] + ([0] * len(token_ids_0)) + [1] + return [1] + ([0] * len(token_ids_0)) + [1, 1] + ([0] * len(token_ids_1)) + [1] + + def create_token_type_ids_from_sequences( + self, token_ids_0: List[int], token_ids_1: Optional[List[int]] = None + ) -> List[int]: + """ + Create a mask from the two sequences passed to be used in a sequence-pair classification task. T5 does not make + use of token type ids, therefore a list of zeros is returned. + + Args: + token_ids_0 (`List[int]`): + List of IDs. + token_ids_1 (`List[int]`, *optional*): + Optional second list of IDs for sequence pairs. + + Returns: + `List[int]`: List of zeros. + """ + eos = [self.eos_token_id] + + if token_ids_1 is None: + return len(token_ids_0 + eos) * [0] + return len(token_ids_0 + eos + token_ids_1 + eos) * [0] diff --git a/InternVL-main/internvl_chat/work_dirs/internvl_chat_v2_5/ak/100/tokenizer_config.json b/InternVL-main/internvl_chat/work_dirs/internvl_chat_v2_5/ak/100/tokenizer_config.json new file mode 100644 index 0000000000000000000000000000000000000000..1f32946df0f56d92ddbc1df79cabb4477b622480 --- /dev/null +++ b/InternVL-main/internvl_chat/work_dirs/internvl_chat_v2_5/ak/100/tokenizer_config.json @@ -0,0 +1,179 @@ +{ + "added_tokens_decoder": { + "0": { + "content": "", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "1": { + "content": "", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "2": { + "content": "", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "92538": { + "content": "<|plugin|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "92539": { + "content": "<|interpreter|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "92540": { + "content": "<|action_end|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "92541": { + "content": "<|action_start|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "92542": { + "content": "<|im_end|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "92543": { + "content": "<|im_start|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "92544": { + "content": "", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "92545": { + "content": "", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "92546": { + "content": "", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "92547": { + "content": "", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "92548": { + "content": "", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "92549": { + "content": "", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "92550": { + "content": "", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "92551": { + "content": "", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "92552": { + "content": "", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + } + }, + "additional_special_tokens": [ + "<|im_start|>", + "<|im_end|>", + "<|action_start|>", + "<|action_end|>", + "<|interpreter|>", + "<|plugin|>", + "", + "", + "", + "", + "", + "", + "", + "", + "" + ], + "auto_map": { + "AutoTokenizer": [ + "tokenization_internlm2.InternLM2Tokenizer", + null + ] + }, + "bos_token": "", + "chat_template": "{{ bos_token }}{% for message in messages %}{{'<|im_start|>' + message['role'] + '\n' + message['content'] + '<|im_end|>' + '\n'}}{% endfor %}{% if add_generation_prompt %}{{ '<|im_start|>assistant\n' }}{% endif %}", + "clean_up_tokenization_spaces": false, + "eos_token": "", + "model_max_length": 8192, + "pad_token": "", + "tokenizer_class": "InternLM2Tokenizer", + "unk_token": "" +} diff --git a/InternVL-main/internvl_chat/work_dirs/internvl_chat_v2_5/ak/checkpoint-100/added_tokens.json b/InternVL-main/internvl_chat/work_dirs/internvl_chat_v2_5/ak/checkpoint-100/added_tokens.json new file mode 100644 index 0000000000000000000000000000000000000000..35f5893c8e29d6102945a953529819a2d56c62a9 --- /dev/null +++ b/InternVL-main/internvl_chat/work_dirs/internvl_chat_v2_5/ak/checkpoint-100/added_tokens.json @@ -0,0 +1,11 @@ +{ + "": 92552, + "": 92545, + "": 92548, + "": 92550, + "": 92546, + "": 92551, + "": 92544, + "": 92547, + "": 92549 +} diff --git a/InternVL-main/internvl_chat/work_dirs/internvl_chat_v2_5/ak/checkpoint-100/config.json b/InternVL-main/internvl_chat/work_dirs/internvl_chat_v2_5/ak/checkpoint-100/config.json new file mode 100644 index 0000000000000000000000000000000000000000..7a80bcc23044620a2be8191b38a9a23053c41e98 --- /dev/null +++ b/InternVL-main/internvl_chat/work_dirs/internvl_chat_v2_5/ak/checkpoint-100/config.json @@ -0,0 +1,204 @@ +{ + "_commit_hash": "573169ee54df216786bb9a189e9a32a060a008cf", + "_name_or_path": "OpenGVLab/InternVL2_5-2B", + "architectures": [ + "InternVLChatModel" + ], + "auto_map": { + "AutoConfig": "OpenGVLab/InternVL2_5-2B--configuration_internvl_chat.InternVLChatConfig", + "AutoModel": "OpenGVLab/InternVL2_5-2B--modeling_internvl_chat.InternVLChatModel", + "AutoModelForCausalLM": "OpenGVLab/InternVL2_5-2B--modeling_internvl_chat.InternVLChatModel" + }, + "downsample_ratio": 0.5, + "dynamic_image_size": true, + "force_image_size": 448, + "hidden_size": 2048, + "llm_config": { + "_name_or_path": "internlm/internlm2_5-1_8b-chat", + "add_cross_attention": false, + "architectures": [ + "InternLM2ForCausalLM" + ], + "attn_implementation": "flash_attention_2", + "auto_map": { + "AutoConfig": "configuration_internlm2.InternLM2Config", + "AutoModel": "modeling_internlm2.InternLM2ForCausalLM", + "AutoModelForCausalLM": "modeling_internlm2.InternLM2ForCausalLM", + "AutoModelForSequenceClassification": "modeling_internlm2.InternLM2ForSequenceClassification" + }, + "bad_words_ids": null, + "begin_suppress_tokens": null, + "bias": false, + "bos_token_id": 1, + "chunk_size_feed_forward": 0, + "cross_attention_hidden_size": null, + "decoder_start_token_id": null, + "diversity_penalty": 0.0, + "do_sample": false, + "early_stopping": false, + "encoder_no_repeat_ngram_size": 0, + "eos_token_id": 2, + "exponential_decay_length_penalty": null, + "finetuning_task": null, + "forced_bos_token_id": null, + "forced_eos_token_id": null, + "hidden_act": "silu", + "hidden_size": 2048, + "id2label": { + "0": "LABEL_0", + "1": "LABEL_1" + }, + "initializer_range": 0.02, + "intermediate_size": 8192, + "is_decoder": false, + "is_encoder_decoder": false, + "label2id": { + "LABEL_0": 0, + "LABEL_1": 1 + }, + "length_penalty": 1.0, + "max_length": 20, + "max_position_embeddings": 32768, + "min_length": 0, + "model_type": "internlm2", + "no_repeat_ngram_size": 0, + "num_attention_heads": 16, + "num_beam_groups": 1, + "num_beams": 1, + "num_hidden_layers": 24, + "num_key_value_heads": 8, + "num_return_sequences": 1, + "output_attentions": false, + "output_hidden_states": false, + "output_scores": false, + "pad_token_id": 2, + "prefix": null, + "pretraining_tp": 1, + "problem_type": null, + "pruned_heads": {}, + "remove_invalid_values": false, + "repetition_penalty": 1.0, + "return_dict": true, + "return_dict_in_generate": false, + "rms_norm_eps": 1e-05, + "rope_scaling": { + "factor": 2.0, + "type": "dynamic" + }, + "rope_theta": 1000000, + "sep_token_id": null, + "suppress_tokens": null, + "task_specific_params": null, + "temperature": 1.0, + "tf_legacy_loss": false, + "tie_encoder_decoder": false, + "tie_word_embeddings": false, + "tokenizer_class": null, + "top_k": 50, + "top_p": 1.0, + "torch_dtype": "bfloat16", + "torchscript": false, + "transformers_version": "4.43.2", + "typical_p": 1.0, + "use_bfloat16": true, + "use_cache": false, + "vocab_size": 92553 + }, + "max_dynamic_patch": 6, + "min_dynamic_patch": 1, + "model_type": "internvl_chat", + "pad2square": false, + "ps_version": "v2", + "select_layer": -1, + "template": "internvl2_5", + "tie_word_embeddings": false, + "torch_dtype": "bfloat16", + "transformers_version": null, + "use_backbone_lora": 0, + "use_llm_lora": 8, + "use_thumbnail": true, + "vision_config": { + "_name_or_path": "", + "add_cross_attention": false, + "architectures": [ + "InternVisionModel" + ], + "attention_dropout": 0.0, + "bad_words_ids": null, + "begin_suppress_tokens": null, + "bos_token_id": null, + "chunk_size_feed_forward": 0, + "cross_attention_hidden_size": null, + "decoder_start_token_id": null, + "diversity_penalty": 0.0, + "do_sample": false, + "drop_path_rate": 0.0, + "dropout": 0.0, + "early_stopping": false, + "encoder_no_repeat_ngram_size": 0, + "eos_token_id": null, + "exponential_decay_length_penalty": null, + "finetuning_task": null, + "forced_bos_token_id": null, + "forced_eos_token_id": null, + "hidden_act": "gelu", + "hidden_size": 1024, + "id2label": { + "0": "LABEL_0", + "1": "LABEL_1" + }, + "image_size": 448, + "initializer_factor": 1.0, + "initializer_range": 0.02, + "intermediate_size": 4096, + "is_decoder": false, + "is_encoder_decoder": false, + "label2id": { + "LABEL_0": 0, + "LABEL_1": 1 + }, + "layer_norm_eps": 1e-06, + "length_penalty": 1.0, + "max_length": 20, + "min_length": 0, + "model_type": "intern_vit_6b", + "no_repeat_ngram_size": 0, + "norm_type": "layer_norm", + "num_attention_heads": 16, + "num_beam_groups": 1, + "num_beams": 1, + "num_channels": 3, + "num_hidden_layers": 24, + "num_return_sequences": 1, + "output_attentions": false, + "output_hidden_states": false, + "output_scores": false, + "pad_token_id": null, + "patch_size": 14, + "prefix": null, + "problem_type": null, + "pruned_heads": {}, + "qk_normalization": false, + "qkv_bias": true, + "remove_invalid_values": false, + "repetition_penalty": 1.0, + "return_dict": true, + "return_dict_in_generate": false, + "sep_token_id": null, + "suppress_tokens": null, + "task_specific_params": null, + "temperature": 1.0, + "tf_legacy_loss": false, + "tie_encoder_decoder": false, + "tie_word_embeddings": true, + "tokenizer_class": null, + "top_k": 50, + "top_p": 1.0, + "torch_dtype": "bfloat16", + "torchscript": false, + "transformers_version": "4.43.2", + "typical_p": 1.0, + "use_bfloat16": true, + "use_flash_attn": true + } +} diff --git a/InternVL-main/internvl_chat/work_dirs/internvl_chat_v2_5/ak/checkpoint-100/generation_config.json b/InternVL-main/internvl_chat/work_dirs/internvl_chat_v2_5/ak/checkpoint-100/generation_config.json new file mode 100644 index 0000000000000000000000000000000000000000..918fe50c5a6fd362e537376348091b2bc5f51820 --- /dev/null +++ b/InternVL-main/internvl_chat/work_dirs/internvl_chat_v2_5/ak/checkpoint-100/generation_config.json @@ -0,0 +1,8 @@ +{ + "_from_model_config": true, + "eos_token_id": [ + 92542, + 92543 + ], + "transformers_version": "4.43.2" +} diff --git a/InternVL-main/internvl_chat/work_dirs/internvl_chat_v2_5/ak/checkpoint-100/latest b/InternVL-main/internvl_chat/work_dirs/internvl_chat_v2_5/ak/checkpoint-100/latest new file mode 100644 index 0000000000000000000000000000000000000000..744ae7dbad571b6f37ec6c7066549494261bb59e --- /dev/null +++ b/InternVL-main/internvl_chat/work_dirs/internvl_chat_v2_5/ak/checkpoint-100/latest @@ -0,0 +1 @@ +global_step100 \ No newline at end of file diff --git a/InternVL-main/internvl_chat/work_dirs/internvl_chat_v2_5/ak/checkpoint-100/special_tokens_map.json b/InternVL-main/internvl_chat/work_dirs/internvl_chat_v2_5/ak/checkpoint-100/special_tokens_map.json new file mode 100644 index 0000000000000000000000000000000000000000..cbf34a50d27c43ed8d1e2823b800b4e6f66e637a --- /dev/null +++ b/InternVL-main/internvl_chat/work_dirs/internvl_chat_v2_5/ak/checkpoint-100/special_tokens_map.json @@ -0,0 +1,47 @@ +{ + "additional_special_tokens": [ + "<|im_start|>", + "<|im_end|>", + "<|action_start|>", + "<|action_end|>", + "<|interpreter|>", + "<|plugin|>", + "", + "", + "", + "", + "", + "", + "", + "", + "" + ], + "bos_token": { + "content": "", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false + }, + "eos_token": { + "content": "", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false + }, + "pad_token": { + "content": "", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false + }, + "unk_token": { + "content": "", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false + } +} diff --git a/InternVL-main/internvl_chat/work_dirs/internvl_chat_v2_5/ak/checkpoint-100/tokenization_internlm2.py b/InternVL-main/internvl_chat/work_dirs/internvl_chat_v2_5/ak/checkpoint-100/tokenization_internlm2.py new file mode 100644 index 0000000000000000000000000000000000000000..1be581da37ef678de65f2737493fc0ed7160446e --- /dev/null +++ b/InternVL-main/internvl_chat/work_dirs/internvl_chat_v2_5/ak/checkpoint-100/tokenization_internlm2.py @@ -0,0 +1,235 @@ +# Copyright (c) The InternLM team and The HuggingFace Inc. team. All rights reserved. +# +# This code is based on transformers/src/transformers/models/llama/tokenization_llama.py +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +"""Tokenization classes for InternLM.""" +import os +from shutil import copyfile +from typing import Any, Dict, List, Optional, Tuple + +import sentencepiece as spm +from transformers.tokenization_utils import PreTrainedTokenizer +from transformers.utils import logging + +logger = logging.get_logger(__name__) + +VOCAB_FILES_NAMES = {'vocab_file': './tokenizer.model'} + +PRETRAINED_VOCAB_FILES_MAP = {} + + +# Modified from transformers.model.llama.tokenization_llama.LlamaTokenizer +class InternLM2Tokenizer(PreTrainedTokenizer): + """ + Construct a InternLM2 tokenizer. Based on byte-level Byte-Pair-Encoding. + + Args: + vocab_file (`str`): + Path to the vocabulary file. + """ + + vocab_files_names = VOCAB_FILES_NAMES + pretrained_vocab_files_map = PRETRAINED_VOCAB_FILES_MAP + model_input_names = ['input_ids', 'attention_mask'] + _auto_class = 'AutoTokenizer' + + def __init__( + self, + vocab_file, + unk_token='', + bos_token='', + eos_token='', + pad_token='', + sp_model_kwargs: Optional[Dict[str, Any]] = None, + add_bos_token=True, + add_eos_token=False, + decode_with_prefix_space=False, + clean_up_tokenization_spaces=False, + **kwargs, + ): + self.sp_model_kwargs = {} if sp_model_kwargs is None else sp_model_kwargs + self.vocab_file = vocab_file + self.add_bos_token = add_bos_token + self.add_eos_token = add_eos_token + self.decode_with_prefix_space = decode_with_prefix_space + self.sp_model = spm.SentencePieceProcessor(**self.sp_model_kwargs) + self.sp_model.Load(vocab_file) + self._no_prefix_space_tokens = None + super().__init__( + bos_token=bos_token, + eos_token=eos_token, + unk_token=unk_token, + pad_token=pad_token, + clean_up_tokenization_spaces=clean_up_tokenization_spaces, + **kwargs, + ) + + @property + def no_prefix_space_tokens(self): + if self._no_prefix_space_tokens is None: + vocab = self.convert_ids_to_tokens(list(range(self.vocab_size))) + self._no_prefix_space_tokens = {i for i, tok in enumerate(vocab) if not tok.startswith('▁')} + return self._no_prefix_space_tokens + + @property + def vocab_size(self): + """Returns vocab size""" + return self.sp_model.get_piece_size() + + @property + def bos_token_id(self) -> Optional[int]: + return self.sp_model.bos_id() + + @property + def eos_token_id(self) -> Optional[int]: + return self.sp_model.eos_id() + + def get_vocab(self): + """Returns vocab as a dict""" + vocab = {self.convert_ids_to_tokens(i): i for i in range(self.vocab_size)} + vocab.update(self.added_tokens_encoder) + return vocab + + def _tokenize(self, text): + """Returns a tokenized string.""" + return self.sp_model.encode(text, out_type=str) + + def _convert_token_to_id(self, token): + """Converts a token (str) in an id using the vocab.""" + return self.sp_model.piece_to_id(token) + + def _convert_id_to_token(self, index): + """Converts an index (integer) in a token (str) using the vocab.""" + token = self.sp_model.IdToPiece(index) + return token + + def _maybe_add_prefix_space(self, tokens, decoded): + if tokens and tokens[0] not in self.no_prefix_space_tokens: + return ' ' + decoded + else: + return decoded + + def convert_tokens_to_string(self, tokens): + """Converts a sequence of tokens (string) in a single string.""" + current_sub_tokens = [] + out_string = '' + prev_is_special = False + for token in tokens: + # make sure that special tokens are not decoded using sentencepiece model + if token in self.all_special_tokens: + if not prev_is_special: + out_string += ' ' + out_string += self.sp_model.decode(current_sub_tokens) + token + prev_is_special = True + current_sub_tokens = [] + else: + current_sub_tokens.append(token) + prev_is_special = False + out_string += self.sp_model.decode(current_sub_tokens) + out_string = self.clean_up_tokenization(out_string) + out_string = self._maybe_add_prefix_space(tokens=tokens, decoded=out_string) + return out_string[1:] + + def save_vocabulary(self, save_directory, filename_prefix: Optional[str] = None) -> Tuple[str]: + """ + Save the vocabulary and special tokens file to a directory. + + Args: + save_directory (`str`): + The directory in which to save the vocabulary. + + Returns: + `Tuple(str)`: Paths to the files saved. + """ + if not os.path.isdir(save_directory): + logger.error(f'Vocabulary path ({save_directory}) should be a directory') + return + out_vocab_file = os.path.join( + save_directory, (filename_prefix + '-' if filename_prefix else '') + VOCAB_FILES_NAMES['vocab_file'] + ) + + if os.path.abspath(self.vocab_file) != os.path.abspath(out_vocab_file) and os.path.isfile(self.vocab_file): + copyfile(self.vocab_file, out_vocab_file) + elif not os.path.isfile(self.vocab_file): + with open(out_vocab_file, 'wb') as fi: + content_spiece_model = self.sp_model.serialized_model_proto() + fi.write(content_spiece_model) + + return (out_vocab_file,) + + def build_inputs_with_special_tokens(self, token_ids_0, token_ids_1=None): + if self.add_bos_token: + bos_token_ids = [self.bos_token_id] + else: + bos_token_ids = [] + + output = bos_token_ids + token_ids_0 + + if token_ids_1 is not None: + output = output + token_ids_1 + + if self.add_eos_token: + output = output + [self.eos_token_id] + + return output + + def get_special_tokens_mask( + self, token_ids_0: List[int], token_ids_1: Optional[List[int]] = None, already_has_special_tokens: bool = False + ) -> List[int]: + """ + Retrieve sequence ids from a token list that has no special tokens added. This method is called when adding + special tokens using the tokenizer `prepare_for_model` method. + + Args: + token_ids_0 (`List[int]`): + List of IDs. + token_ids_1 (`List[int]`, *optional*): + Optional second list of IDs for sequence pairs. + already_has_special_tokens (`bool`, *optional*, defaults to `False`): + Whether or not the token list is already formatted with special tokens for the model. + + Returns: + `List[int]`: A list of integers in the range [0, 1]: 1 for a special token, 0 for a sequence token. + """ + if already_has_special_tokens: + return super().get_special_tokens_mask( + token_ids_0=token_ids_0, token_ids_1=token_ids_1, already_has_special_tokens=True + ) + + if token_ids_1 is None: + return [1] + ([0] * len(token_ids_0)) + [1] + return [1] + ([0] * len(token_ids_0)) + [1, 1] + ([0] * len(token_ids_1)) + [1] + + def create_token_type_ids_from_sequences( + self, token_ids_0: List[int], token_ids_1: Optional[List[int]] = None + ) -> List[int]: + """ + Create a mask from the two sequences passed to be used in a sequence-pair classification task. T5 does not make + use of token type ids, therefore a list of zeros is returned. + + Args: + token_ids_0 (`List[int]`): + List of IDs. + token_ids_1 (`List[int]`, *optional*): + Optional second list of IDs for sequence pairs. + + Returns: + `List[int]`: List of zeros. + """ + eos = [self.eos_token_id] + + if token_ids_1 is None: + return len(token_ids_0 + eos) * [0] + return len(token_ids_0 + eos + token_ids_1 + eos) * [0] diff --git a/InternVL-main/internvl_chat/work_dirs/internvl_chat_v2_5/ak/checkpoint-100/tokenizer_config.json b/InternVL-main/internvl_chat/work_dirs/internvl_chat_v2_5/ak/checkpoint-100/tokenizer_config.json new file mode 100644 index 0000000000000000000000000000000000000000..1f32946df0f56d92ddbc1df79cabb4477b622480 --- /dev/null +++ b/InternVL-main/internvl_chat/work_dirs/internvl_chat_v2_5/ak/checkpoint-100/tokenizer_config.json @@ -0,0 +1,179 @@ +{ + "added_tokens_decoder": { + "0": { + "content": "", + "lstrip": false, + "normalized": false, + "rstrip": false, + 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false, + "rstrip": false, + "single_word": false, + "special": true + }, + "92543": { + "content": "<|im_start|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "92544": { + "content": "", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "92545": { + "content": "", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "92546": { + "content": "", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "92547": { + "content": "", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "92548": { + "content": "", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "92549": { + "content": "", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "92550": { + "content": "", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "92551": { + "content": "", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "92552": { + "content": "", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + } + }, + "additional_special_tokens": [ + "<|im_start|>", + "<|im_end|>", + "<|action_start|>", + "<|action_end|>", + "<|interpreter|>", + "<|plugin|>", + "", + "", + "", + "", + "", + "", + "", + "", + "" + ], + "auto_map": { + "AutoTokenizer": [ + "tokenization_internlm2.InternLM2Tokenizer", + null + ] + }, + "bos_token": "", + "chat_template": "{{ bos_token }}{% for message in messages %}{{'<|im_start|>' + message['role'] + '\n' + message['content'] + '<|im_end|>' + '\n'}}{% endfor %}{% if add_generation_prompt %}{{ 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extracts fp32 consolidated weights from a zero 1, 2 and 3 DeepSpeed checkpoints. It gets +# copied into the top level checkpoint dir, so the user can easily do the conversion at any point in +# the future. Once extracted, the weights don't require DeepSpeed and can be used in any +# application. +# +# example: python zero_to_fp32.py . pytorch_model.bin + +import argparse +import torch +import glob +import math +import os +import re +from collections import OrderedDict +from dataclasses import dataclass + +# while this script doesn't use deepspeed to recover data, since the checkpoints are pickled with +# DeepSpeed data structures it has to be available in the current python environment. +from deepspeed.utils import logger +from deepspeed.checkpoint.constants import (DS_VERSION, OPTIMIZER_STATE_DICT, SINGLE_PARTITION_OF_FP32_GROUPS, + FP32_FLAT_GROUPS, ZERO_STAGE, PARTITION_COUNT, PARAM_SHAPES, BUFFER_NAMES, + FROZEN_PARAM_SHAPES, FROZEN_PARAM_FRAGMENTS) + + +@dataclass +class zero_model_state: + buffers: dict() + param_shapes: dict() + shared_params: list + ds_version: int + frozen_param_shapes: dict() + frozen_param_fragments: dict() + + +debug = 0 + +# load to cpu +device = torch.device('cpu') + + +def atoi(text): + return int(text) if text.isdigit() else text + + +def natural_keys(text): + ''' + alist.sort(key=natural_keys) sorts in human order + http://nedbatchelder.com/blog/200712/human_sorting.html + (See Toothy's implementation in the comments) + ''' + return [atoi(c) for c in re.split(r'(\d+)', text)] + + +def get_model_state_file(checkpoint_dir, zero_stage): + if not os.path.isdir(checkpoint_dir): + raise FileNotFoundError(f"Directory '{checkpoint_dir}' doesn't exist") + + # there should be only one file + if zero_stage <= 2: + file = os.path.join(checkpoint_dir, "mp_rank_00_model_states.pt") + elif zero_stage == 3: + file = os.path.join(checkpoint_dir, "zero_pp_rank_0_mp_rank_00_model_states.pt") + + if not os.path.exists(file): + raise FileNotFoundError(f"can't find model states file at '{file}'") + + return file + + +def get_checkpoint_files(checkpoint_dir, glob_pattern): + # XXX: need to test that this simple glob rule works for multi-node setup too + ckpt_files = sorted(glob.glob(os.path.join(checkpoint_dir, glob_pattern)), key=natural_keys) + + if len(ckpt_files) == 0: + raise FileNotFoundError(f"can't find {glob_pattern} files in directory '{checkpoint_dir}'") + + return ckpt_files + + +def get_optim_files(checkpoint_dir): + return get_checkpoint_files(checkpoint_dir, "*_optim_states.pt") + + +def get_model_state_files(checkpoint_dir): + return get_checkpoint_files(checkpoint_dir, "*_model_states.pt") + + +def parse_model_states(files): + zero_model_states = [] + for file in files: + state_dict = torch.load(file, map_location=device) + + if BUFFER_NAMES not in state_dict: + raise ValueError(f"{file} is not a model state checkpoint") + buffer_names = state_dict[BUFFER_NAMES] + if debug: + print("Found buffers:", buffer_names) + + # recover just the buffers while restoring them to fp32 if they were saved in fp16 + buffers = {k: v.float() for k, v in state_dict["module"].items() if k in buffer_names} + param_shapes = state_dict[PARAM_SHAPES] + + # collect parameters that are included in param_shapes + param_names = [] + for s in param_shapes: + for name in s.keys(): + param_names.append(name) + + # update with frozen parameters + frozen_param_shapes = state_dict.get(FROZEN_PARAM_SHAPES, None) + if frozen_param_shapes is not None: + if debug: + print(f"Found frozen_param_shapes: {frozen_param_shapes}") + param_names += list(frozen_param_shapes.keys()) + + # handle shared params + shared_params = [[k, v] for k, v in state_dict["shared_params"].items()] + + ds_version = state_dict.get(DS_VERSION, None) + + frozen_param_fragments = state_dict.get(FROZEN_PARAM_FRAGMENTS, None) + + z_model_state = zero_model_state(buffers=buffers, + param_shapes=param_shapes, + shared_params=shared_params, + ds_version=ds_version, + frozen_param_shapes=frozen_param_shapes, + frozen_param_fragments=frozen_param_fragments) + zero_model_states.append(z_model_state) + + return zero_model_states + + +def parse_optim_states(files, ds_checkpoint_dir): + + total_files = len(files) + state_dicts = [] + for f in files: + state_dict = torch.load(f, map_location=device) + # immediately discard the potentially huge 2 optimizer states as we only care for fp32 master weights + # and also handle the case where it was already removed by another helper script + state_dict["optimizer_state_dict"].pop("optimizer_state_dict", None) + state_dicts.append(state_dict) + + if not ZERO_STAGE in state_dicts[0][OPTIMIZER_STATE_DICT]: + raise ValueError(f"{files[0]} is not a zero checkpoint") + zero_stage = state_dicts[0][OPTIMIZER_STATE_DICT][ZERO_STAGE] + world_size = state_dicts[0][OPTIMIZER_STATE_DICT][PARTITION_COUNT] + + # For ZeRO-2 each param group can have different partition_count as data parallelism for expert + # parameters can be different from data parallelism for non-expert parameters. So we can just + # use the max of the partition_count to get the dp world_size. + + if type(world_size) is list: + world_size = max(world_size) + + if world_size != total_files: + raise ValueError( + f"Expected {world_size} of '*_optim_states.pt' under '{ds_checkpoint_dir}' but found {total_files} files. " + "Possibly due to an overwrite of an old checkpoint, or a checkpoint didn't get saved by one or more processes." + ) + + # the groups are named differently in each stage + if zero_stage <= 2: + fp32_groups_key = SINGLE_PARTITION_OF_FP32_GROUPS + elif zero_stage == 3: + fp32_groups_key = FP32_FLAT_GROUPS + else: + raise ValueError(f"unknown zero stage {zero_stage}") + + if zero_stage <= 2: + fp32_flat_groups = [state_dicts[i][OPTIMIZER_STATE_DICT][fp32_groups_key] for i in range(len(state_dicts))] + elif zero_stage == 3: + # if there is more than one param group, there will be multiple flattened tensors - one + # flattened tensor per group - for simplicity merge them into a single tensor + # + # XXX: could make the script more memory efficient for when there are multiple groups - it + # will require matching the sub-lists of param_shapes for each param group flattened tensor + + fp32_flat_groups = [ + torch.cat(state_dicts[i][OPTIMIZER_STATE_DICT][fp32_groups_key], 0) for i in range(len(state_dicts)) + ] + + return zero_stage, world_size, fp32_flat_groups + + +def _get_fp32_state_dict_from_zero_checkpoint(ds_checkpoint_dir, exclude_frozen_parameters): + """ + Returns fp32 state_dict reconstructed from ds checkpoint + + Args: + - ``ds_checkpoint_dir``: path to the deepspeed checkpoint folder (where the optimizer files are) + + """ + print(f"Processing zero checkpoint '{ds_checkpoint_dir}'") + + optim_files = get_optim_files(ds_checkpoint_dir) + zero_stage, world_size, fp32_flat_groups = parse_optim_states(optim_files, ds_checkpoint_dir) + print(f"Detected checkpoint of type zero stage {zero_stage}, world_size: {world_size}") + + model_files = get_model_state_files(ds_checkpoint_dir) + + zero_model_states = parse_model_states(model_files) + print(f'Parsing checkpoint created by deepspeed=={zero_model_states[0].ds_version}') + + if zero_stage <= 2: + return _get_fp32_state_dict_from_zero2_checkpoint(world_size, fp32_flat_groups, zero_model_states, + exclude_frozen_parameters) + elif zero_stage == 3: + return _get_fp32_state_dict_from_zero3_checkpoint(world_size, fp32_flat_groups, zero_model_states, + exclude_frozen_parameters) + + +def _zero2_merge_frozen_params(state_dict, zero_model_states): + if zero_model_states[0].frozen_param_shapes is None or len(zero_model_states[0].frozen_param_shapes) == 0: + return + + frozen_param_shapes = zero_model_states[0].frozen_param_shapes + frozen_param_fragments = zero_model_states[0].frozen_param_fragments + + if debug: + num_elem = sum(s.numel() for s in frozen_param_shapes.values()) + print(f'rank 0: {FROZEN_PARAM_SHAPES}.numel = {num_elem}') + + wanted_params = len(frozen_param_shapes) + wanted_numel = sum(s.numel() for s in frozen_param_shapes.values()) + avail_numel = sum([p.numel() for p in frozen_param_fragments.values()]) + print(f'Frozen params: Have {avail_numel} numels to process.') + print(f'Frozen params: Need {wanted_numel} numels in {wanted_params} params') + + total_params = 0 + total_numel = 0 + for name, shape in frozen_param_shapes.items(): + total_params += 1 + unpartitioned_numel = shape.numel() + total_numel += unpartitioned_numel + + state_dict[name] = frozen_param_fragments[name] + + if debug: + print(f"{name} full shape: {shape} unpartitioned numel {unpartitioned_numel} ") + + print(f"Reconstructed Frozen fp32 state dict with {total_params} params {total_numel} elements") + + +def _has_callable(obj, fn): + attr = getattr(obj, fn, None) + return callable(attr) + + +def _zero2_merge_trainable_params(state_dict, world_size, fp32_flat_groups, zero_model_states): + param_shapes = zero_model_states[0].param_shapes + + # Reconstruction protocol: + # + # XXX: document this + + if debug: + for i in range(world_size): + for j in range(len(fp32_flat_groups[0])): + print(f"{FP32_FLAT_GROUPS}[{i}][{j}].shape={fp32_flat_groups[i][j].shape}") + + # XXX: memory usage doubles here (zero2) + num_param_groups = len(fp32_flat_groups[0]) + merged_single_partition_of_fp32_groups = [] + for i in range(num_param_groups): + merged_partitions = [sd[i] for sd in fp32_flat_groups] + full_single_fp32_vector = torch.cat(merged_partitions, 0) + merged_single_partition_of_fp32_groups.append(full_single_fp32_vector) + avail_numel = sum( + [full_single_fp32_vector.numel() for full_single_fp32_vector in merged_single_partition_of_fp32_groups]) + + if debug: + wanted_params = sum([len(shapes) for shapes in param_shapes]) + wanted_numel = sum([sum(shape.numel() for shape in shapes.values()) for shapes in param_shapes]) + # not asserting if there is a mismatch due to possible padding + print(f"Have {avail_numel} numels to process.") + print(f"Need {wanted_numel} numels in {wanted_params} params.") + + # params + # XXX: for huge models that can't fit into the host's RAM we will have to recode this to support + # out-of-core computing solution + total_numel = 0 + total_params = 0 + for shapes, full_single_fp32_vector in zip(param_shapes, merged_single_partition_of_fp32_groups): + offset = 0 + avail_numel = full_single_fp32_vector.numel() + for name, shape in shapes.items(): + + unpartitioned_numel = shape.numel() if _has_callable(shape, 'numel') else math.prod(shape) + total_numel += unpartitioned_numel + total_params += 1 + + if debug: + print(f"{name} full shape: {shape} unpartitioned numel {unpartitioned_numel} ") + state_dict[name] = full_single_fp32_vector.narrow(0, offset, unpartitioned_numel).view(shape) + offset += unpartitioned_numel + + # Z2 started to align to 2*world_size to improve nccl performance. Therefore both offset and + # avail_numel can differ by anywhere between 0..2*world_size. Due to two unrelated complex + # paddings performed in the code it's almost impossible to predict the exact numbers w/o the + # live optimizer object, so we are checking that the numbers are within the right range + align_to = 2 * world_size + + def zero2_align(x): + return align_to * math.ceil(x / align_to) + + if debug: + print(f"original offset={offset}, avail_numel={avail_numel}") + + offset = zero2_align(offset) + avail_numel = zero2_align(avail_numel) + + if debug: + print(f"aligned offset={offset}, avail_numel={avail_numel}") + + # Sanity check + if offset != avail_numel: + raise ValueError(f"consumed {offset} numels out of {avail_numel} - something is wrong") + + print(f"Reconstructed fp32 state dict with {total_params} params {total_numel} elements") + + +def _get_fp32_state_dict_from_zero2_checkpoint(world_size, fp32_flat_groups, zero_model_states, + exclude_frozen_parameters): + state_dict = OrderedDict() + + # buffers + buffers = zero_model_states[0].buffers + state_dict.update(buffers) + if debug: + print(f"added {len(buffers)} buffers") + + if not exclude_frozen_parameters: + _zero2_merge_frozen_params(state_dict, zero_model_states) + + _zero2_merge_trainable_params(state_dict, world_size, fp32_flat_groups, zero_model_states) + + # recover shared parameters + for pair in zero_model_states[0].shared_params: + if pair[1] in state_dict: + state_dict[pair[0]] = state_dict[pair[1]] + + return state_dict + + +def zero3_partitioned_param_info(unpartitioned_numel, world_size): + remainder = unpartitioned_numel % world_size + padding_numel = (world_size - remainder) if remainder else 0 + partitioned_numel = math.ceil(unpartitioned_numel / world_size) + return partitioned_numel, padding_numel + + +def _zero3_merge_frozen_params(state_dict, world_size, zero_model_states): + if zero_model_states[0].frozen_param_shapes is None or len(zero_model_states[0].frozen_param_shapes) == 0: + return + + if debug: + for i in range(world_size): + num_elem = sum(s.numel() for s in zero_model_states[i].frozen_param_fragments.values()) + print(f'rank {i}: {FROZEN_PARAM_SHAPES}.numel = {num_elem}') + + frozen_param_shapes = zero_model_states[0].frozen_param_shapes + wanted_params = len(frozen_param_shapes) + wanted_numel = sum(s.numel() for s in frozen_param_shapes.values()) + avail_numel = sum([p.numel() for p in zero_model_states[0].frozen_param_fragments.values()]) * world_size + print(f'Frozen params: Have {avail_numel} numels to process.') + print(f'Frozen params: Need {wanted_numel} numels in {wanted_params} params') + + total_params = 0 + total_numel = 0 + for name, shape in zero_model_states[0].frozen_param_shapes.items(): + total_params += 1 + unpartitioned_numel = shape.numel() + total_numel += unpartitioned_numel + + param_frags = tuple(model_state.frozen_param_fragments[name] for model_state in zero_model_states) + state_dict[name] = torch.cat(param_frags, 0).narrow(0, 0, unpartitioned_numel).view(shape) + + partitioned_numel, partitioned_padding_numel = zero3_partitioned_param_info(unpartitioned_numel, world_size) + + if debug: + print( + f"Frozen params: {total_params} {name} full shape: {shape} partition0 numel={partitioned_numel} partitioned_padding_numel={partitioned_padding_numel}" + ) + + print(f"Reconstructed Frozen fp32 state dict with {total_params} params {total_numel} elements") + + +def _zero3_merge_trainable_params(state_dict, world_size, fp32_flat_groups, zero_model_states): + param_shapes = zero_model_states[0].param_shapes + avail_numel = fp32_flat_groups[0].numel() * world_size + # Reconstruction protocol: For zero3 we need to zip the partitions together at boundary of each + # param, re-consolidating each param, while dealing with padding if any + + # merge list of dicts, preserving order + param_shapes = {k: v for d in param_shapes for k, v in d.items()} + + if debug: + for i in range(world_size): + print(f"{FP32_FLAT_GROUPS}[{i}].shape={fp32_flat_groups[i].shape}") + + wanted_params = len(param_shapes) + wanted_numel = sum(shape.numel() for shape in param_shapes.values()) + # not asserting if there is a mismatch due to possible padding + avail_numel = fp32_flat_groups[0].numel() * world_size + print(f"Trainable params: Have {avail_numel} numels to process.") + print(f"Trainable params: Need {wanted_numel} numels in {wanted_params} params.") + + # params + # XXX: for huge models that can't fit into the host's RAM we will have to recode this to support + # out-of-core computing solution + offset = 0 + total_numel = 0 + total_params = 0 + for name, shape in param_shapes.items(): + + unpartitioned_numel = shape.numel() + total_numel += unpartitioned_numel + total_params += 1 + + partitioned_numel, partitioned_padding_numel = zero3_partitioned_param_info(unpartitioned_numel, world_size) + + if debug: + print( + f"Trainable params: {total_params} {name} full shape: {shape} partition0 numel={partitioned_numel} partitioned_padding_numel={partitioned_padding_numel}" + ) + + # XXX: memory usage doubles here + state_dict[name] = torch.cat( + tuple(fp32_flat_groups[i].narrow(0, offset, partitioned_numel) for i in range(world_size)), + 0).narrow(0, 0, unpartitioned_numel).view(shape) + offset += partitioned_numel + + offset *= world_size + + # Sanity check + if offset != avail_numel: + raise ValueError(f"consumed {offset} numels out of {avail_numel} - something is wrong") + + print(f"Reconstructed Trainable fp32 state dict with {total_params} params {total_numel} elements") + + +def _get_fp32_state_dict_from_zero3_checkpoint(world_size, fp32_flat_groups, zero_model_states, + exclude_frozen_parameters): + state_dict = OrderedDict() + + # buffers + buffers = zero_model_states[0].buffers + state_dict.update(buffers) + if debug: + print(f"added {len(buffers)} buffers") + + if not exclude_frozen_parameters: + _zero3_merge_frozen_params(state_dict, world_size, zero_model_states) + + _zero3_merge_trainable_params(state_dict, world_size, fp32_flat_groups, zero_model_states) + + # recover shared parameters + for pair in zero_model_states[0].shared_params: + if pair[1] in state_dict: + state_dict[pair[0]] = state_dict[pair[1]] + + return state_dict + + +def get_fp32_state_dict_from_zero_checkpoint(checkpoint_dir, tag=None, exclude_frozen_parameters=False): + """ + Convert ZeRO 2 or 3 checkpoint into a single fp32 consolidated state_dict that can be loaded with + ``load_state_dict()`` and used for training without DeepSpeed or shared with others, for example + via a model hub. + + Args: + - ``checkpoint_dir``: path to the desired checkpoint folder + - ``tag``: checkpoint tag used as a unique identifier for checkpoint. If not provided will attempt to load tag in 'latest' file. e.g., ``global_step14`` + - ``exclude_frozen_parameters``: exclude frozen parameters + + Returns: + - pytorch ``state_dict`` + + Note: this approach may not work if your application doesn't have sufficient free CPU memory and + you may need to use the offline approach using the ``zero_to_fp32.py`` script that is saved with + the checkpoint. + + A typical usage might be :: + + from deepspeed.utils.zero_to_fp32 import get_fp32_state_dict_from_zero_checkpoint + # do the training and checkpoint saving + state_dict = get_fp32_state_dict_from_zero_checkpoint(checkpoint_dir) # already on cpu + model = model.cpu() # move to cpu + model.load_state_dict(state_dict) + # submit to model hub or save the model to share with others + + In this example the ``model`` will no longer be usable in the deepspeed context of the same + application. i.e. you will need to re-initialize the deepspeed engine, since + ``model.load_state_dict(state_dict)`` will remove all the deepspeed magic from it. + + If you want it all done for you, use ``load_state_dict_from_zero_checkpoint`` instead. + + """ + if tag is None: + latest_path = os.path.join(checkpoint_dir, 'latest') + if os.path.isfile(latest_path): + with open(latest_path, 'r') as fd: + tag = fd.read().strip() + else: + raise ValueError(f"Unable to find 'latest' file at {latest_path}") + + ds_checkpoint_dir = os.path.join(checkpoint_dir, tag) + + if not os.path.isdir(ds_checkpoint_dir): + raise FileNotFoundError(f"Directory '{ds_checkpoint_dir}' doesn't exist") + + return _get_fp32_state_dict_from_zero_checkpoint(ds_checkpoint_dir, exclude_frozen_parameters) + + +def convert_zero_checkpoint_to_fp32_state_dict(checkpoint_dir, output_file, tag=None, exclude_frozen_parameters=False): + """ + Convert ZeRO 2 or 3 checkpoint into a single fp32 consolidated ``state_dict`` file that can be + loaded with ``torch.load(file)`` + ``load_state_dict()`` and used for training without DeepSpeed. + + Args: + - ``checkpoint_dir``: path to the desired checkpoint folder. (one that contains the tag-folder, like ``global_step14``) + - ``output_file``: path to the pytorch fp32 state_dict output file (e.g. path/pytorch_model.bin) + - ``tag``: checkpoint tag used as a unique identifier for checkpoint. If not provided will attempt to load tag in the file named ``latest`` in the checkpoint folder, e.g., ``global_step14`` + - ``exclude_frozen_parameters``: exclude frozen parameters + """ + + state_dict = get_fp32_state_dict_from_zero_checkpoint(checkpoint_dir, tag, exclude_frozen_parameters) + print(f"Saving fp32 state dict to {output_file}") + torch.save(state_dict, output_file) + + +def load_state_dict_from_zero_checkpoint(model, checkpoint_dir, tag=None): + """ + 1. Put the provided model to cpu + 2. Convert ZeRO 2 or 3 checkpoint into a single fp32 consolidated ``state_dict`` + 3. Load it into the provided model + + Args: + - ``model``: the model object to update + - ``checkpoint_dir``: path to the desired checkpoint folder. (one that contains the tag-folder, like ``global_step14``) + - ``tag``: checkpoint tag used as a unique identifier for checkpoint. If not provided will attempt to load tag in the file named ``latest`` in the checkpoint folder, e.g., ``global_step14`` + + Returns: + - ``model`: modified model + + Make sure you have plenty of CPU memory available before you call this function. If you don't + have enough use the ``zero_to_fp32.py`` utility to do the conversion. You will find it + conveniently placed for you in the checkpoint folder. + + A typical usage might be :: + + from deepspeed.utils.zero_to_fp32 import load_state_dict_from_zero_checkpoint + model = load_state_dict_from_zero_checkpoint(trainer.model, checkpoint_dir) + # submit to model hub or save the model to share with others + + Note, that once this was run, the ``model`` will no longer be usable in the deepspeed context + of the same application. i.e. you will need to re-initialize the deepspeed engine, since + ``model.load_state_dict(state_dict)`` will remove all the deepspeed magic from it. + + """ + logger.info(f"Extracting fp32 weights") + state_dict = get_fp32_state_dict_from_zero_checkpoint(checkpoint_dir, tag) + + logger.info(f"Overwriting model with fp32 weights") + model = model.cpu() + model.load_state_dict(state_dict, strict=False) + + return model + + +if __name__ == "__main__": + + parser = argparse.ArgumentParser() + parser.add_argument("checkpoint_dir", + type=str, + help="path to the desired checkpoint folder, e.g., path/checkpoint-12") + parser.add_argument( + "output_file", + type=str, + help="path to the pytorch fp32 state_dict output file (e.g. path/checkpoint-12/pytorch_model.bin)") + parser.add_argument("-t", + "--tag", + type=str, + default=None, + help="checkpoint tag used as a unique identifier for checkpoint. e.g., global_step1") + parser.add_argument("--exclude_frozen_parameters", action='store_true', help="exclude frozen parameters") + parser.add_argument("-d", "--debug", action='store_true', help="enable debug") + args = parser.parse_args() + + debug = args.debug + + convert_zero_checkpoint_to_fp32_state_dict(args.checkpoint_dir, + args.output_file, + tag=args.tag, + exclude_frozen_parameters=args.exclude_frozen_parameters) diff --git a/InternVL-main/internvl_chat/work_dirs/internvl_chat_v2_5/ak/checkpoint-700/added_tokens.json b/InternVL-main/internvl_chat/work_dirs/internvl_chat_v2_5/ak/checkpoint-700/added_tokens.json new file mode 100644 index 0000000000000000000000000000000000000000..35f5893c8e29d6102945a953529819a2d56c62a9 --- /dev/null +++ b/InternVL-main/internvl_chat/work_dirs/internvl_chat_v2_5/ak/checkpoint-700/added_tokens.json @@ -0,0 +1,11 @@ +{ + "": 92552, + "": 92545, + "": 92548, + "": 92550, + "": 92546, + "": 92551, + "": 92544, + "": 92547, + "": 92549 +} diff --git a/InternVL-main/internvl_chat/work_dirs/internvl_chat_v2_5/ak/checkpoint-700/config.json b/InternVL-main/internvl_chat/work_dirs/internvl_chat_v2_5/ak/checkpoint-700/config.json new file mode 100644 index 0000000000000000000000000000000000000000..86bf981c85f56fd09cddabb85b5c07819bb8fa44 --- /dev/null +++ b/InternVL-main/internvl_chat/work_dirs/internvl_chat_v2_5/ak/checkpoint-700/config.json @@ -0,0 +1,204 @@ +{ + "_commit_hash": null, + "_name_or_path": "/home1/gmh/InternVL-main/internvl_chat/work_dirs/internvl_chat_v2_5/ak/checkpoint-700", + "architectures": [ + "InternVLChatModel" + ], + "auto_map": { + "AutoConfig": "OpenGVLab/InternVL2_5-2B--configuration_internvl_chat.InternVLChatConfig", + "AutoModel": "OpenGVLab/InternVL2_5-2B--modeling_internvl_chat.InternVLChatModel", + "AutoModelForCausalLM": "OpenGVLab/InternVL2_5-2B--modeling_internvl_chat.InternVLChatModel" + }, + "downsample_ratio": 0.5, + "dynamic_image_size": true, + "force_image_size": 448, + "hidden_size": 2048, + "llm_config": { + "_name_or_path": "internlm/internlm2_5-1_8b-chat", + "add_cross_attention": false, + "architectures": [ + "InternLM2ForCausalLM" + ], + "attn_implementation": "flash_attention_2", + "auto_map": { + "AutoConfig": "configuration_internlm2.InternLM2Config", + "AutoModel": "modeling_internlm2.InternLM2ForCausalLM", + "AutoModelForCausalLM": "modeling_internlm2.InternLM2ForCausalLM", + "AutoModelForSequenceClassification": "modeling_internlm2.InternLM2ForSequenceClassification" + }, + "bad_words_ids": null, + "begin_suppress_tokens": null, + "bias": false, + "bos_token_id": 1, + "chunk_size_feed_forward": 0, + 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"torch_dtype": "bfloat16", + "transformers_version": null, + "use_backbone_lora": 0, + "use_llm_lora": 0, + "use_thumbnail": true, + "vision_config": { + "_name_or_path": "", + "add_cross_attention": false, + "architectures": [ + "InternVisionModel" + ], + "attention_dropout": 0.0, + "bad_words_ids": null, + "begin_suppress_tokens": null, + "bos_token_id": null, + "chunk_size_feed_forward": 0, + "cross_attention_hidden_size": null, + "decoder_start_token_id": null, + "diversity_penalty": 0.0, + "do_sample": false, + "drop_path_rate": 0.0, + "dropout": 0.0, + "early_stopping": false, + "encoder_no_repeat_ngram_size": 0, + "eos_token_id": null, + "exponential_decay_length_penalty": null, + "finetuning_task": null, + "forced_bos_token_id": null, + "forced_eos_token_id": null, + "hidden_act": "gelu", + "hidden_size": 1024, + "id2label": { + "0": "LABEL_0", + "1": "LABEL_1" + }, + "image_size": 448, + "initializer_factor": 1.0, + "initializer_range": 0.02, + "intermediate_size": 4096, + "is_decoder": false, + "is_encoder_decoder": false, + "label2id": { + "LABEL_0": 0, + "LABEL_1": 1 + }, + "layer_norm_eps": 1e-06, + "length_penalty": 1.0, + "max_length": 20, + "min_length": 0, + "model_type": "intern_vit_6b", + "no_repeat_ngram_size": 0, + "norm_type": "layer_norm", + "num_attention_heads": 16, + "num_beam_groups": 1, + "num_beams": 1, + "num_channels": 3, + "num_hidden_layers": 24, + "num_return_sequences": 1, + "output_attentions": false, + "output_hidden_states": false, + "output_scores": false, + "pad_token_id": null, + "patch_size": 14, + "prefix": null, + "problem_type": null, + "pruned_heads": {}, + "qk_normalization": false, + "qkv_bias": true, + "remove_invalid_values": false, + "repetition_penalty": 1.0, + "return_dict": true, + "return_dict_in_generate": false, + "sep_token_id": null, + "suppress_tokens": null, + "task_specific_params": null, + "temperature": 1.0, + "tf_legacy_loss": false, + "tie_encoder_decoder": false, + "tie_word_embeddings": true, + "tokenizer_class": null, + "top_k": 50, + "top_p": 1.0, + "torch_dtype": "bfloat16", + "torchscript": false, + "transformers_version": "4.43.2", + "typical_p": 1.0, + "use_bfloat16": true, + "use_flash_attn": true + } +} diff --git a/InternVL-main/internvl_chat/work_dirs/internvl_chat_v2_5/ak/checkpoint-700/generation_config.json b/InternVL-main/internvl_chat/work_dirs/internvl_chat_v2_5/ak/checkpoint-700/generation_config.json new file mode 100644 index 0000000000000000000000000000000000000000..918fe50c5a6fd362e537376348091b2bc5f51820 --- /dev/null +++ b/InternVL-main/internvl_chat/work_dirs/internvl_chat_v2_5/ak/checkpoint-700/generation_config.json @@ -0,0 +1,8 @@ +{ + "_from_model_config": true, + "eos_token_id": [ + 92542, + 92543 + ], + "transformers_version": "4.43.2" +} diff --git a/InternVL-main/internvl_chat/work_dirs/internvl_chat_v2_5/ak/checkpoint-700/special_tokens_map.json b/InternVL-main/internvl_chat/work_dirs/internvl_chat_v2_5/ak/checkpoint-700/special_tokens_map.json new file mode 100644 index 0000000000000000000000000000000000000000..cbf34a50d27c43ed8d1e2823b800b4e6f66e637a --- /dev/null +++ b/InternVL-main/internvl_chat/work_dirs/internvl_chat_v2_5/ak/checkpoint-700/special_tokens_map.json @@ -0,0 +1,47 @@ +{ + "additional_special_tokens": [ + "<|im_start|>", + "<|im_end|>", + "<|action_start|>", + "<|action_end|>", + "<|interpreter|>", + "<|plugin|>", + "", + "", + "", + "", + "", + "", + "", + "", + "" + ], + "bos_token": { + "content": "", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false + }, + "eos_token": { + "content": "", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false + }, + "pad_token": { + "content": "", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false + }, + "unk_token": { + "content": "", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false + } +} diff --git a/InternVL-main/internvl_chat/work_dirs/internvl_chat_v2_5/ak/checkpoint-700/tokenization_internlm2.py b/InternVL-main/internvl_chat/work_dirs/internvl_chat_v2_5/ak/checkpoint-700/tokenization_internlm2.py new file mode 100644 index 0000000000000000000000000000000000000000..1be581da37ef678de65f2737493fc0ed7160446e --- /dev/null +++ b/InternVL-main/internvl_chat/work_dirs/internvl_chat_v2_5/ak/checkpoint-700/tokenization_internlm2.py @@ -0,0 +1,235 @@ +# Copyright (c) The InternLM team and The HuggingFace Inc. team. All rights reserved. +# +# This code is based on transformers/src/transformers/models/llama/tokenization_llama.py +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +"""Tokenization classes for InternLM.""" +import os +from shutil import copyfile +from typing import Any, Dict, List, Optional, Tuple + +import sentencepiece as spm +from transformers.tokenization_utils import PreTrainedTokenizer +from transformers.utils import logging + +logger = logging.get_logger(__name__) + +VOCAB_FILES_NAMES = {'vocab_file': './tokenizer.model'} + +PRETRAINED_VOCAB_FILES_MAP = {} + + +# Modified from transformers.model.llama.tokenization_llama.LlamaTokenizer +class InternLM2Tokenizer(PreTrainedTokenizer): + """ + Construct a InternLM2 tokenizer. Based on byte-level Byte-Pair-Encoding. + + Args: + vocab_file (`str`): + Path to the vocabulary file. + """ + + vocab_files_names = VOCAB_FILES_NAMES + pretrained_vocab_files_map = PRETRAINED_VOCAB_FILES_MAP + model_input_names = ['input_ids', 'attention_mask'] + _auto_class = 'AutoTokenizer' + + def __init__( + self, + vocab_file, + unk_token='', + bos_token='', + eos_token='', + pad_token='', + sp_model_kwargs: Optional[Dict[str, Any]] = None, + add_bos_token=True, + add_eos_token=False, + decode_with_prefix_space=False, + clean_up_tokenization_spaces=False, + **kwargs, + ): + self.sp_model_kwargs = {} if sp_model_kwargs is None else sp_model_kwargs + self.vocab_file = vocab_file + self.add_bos_token = add_bos_token + self.add_eos_token = add_eos_token + self.decode_with_prefix_space = decode_with_prefix_space + self.sp_model = spm.SentencePieceProcessor(**self.sp_model_kwargs) + self.sp_model.Load(vocab_file) + self._no_prefix_space_tokens = None + super().__init__( + bos_token=bos_token, + eos_token=eos_token, + unk_token=unk_token, + pad_token=pad_token, + clean_up_tokenization_spaces=clean_up_tokenization_spaces, + **kwargs, + ) + + @property + def no_prefix_space_tokens(self): + if self._no_prefix_space_tokens is None: + vocab = self.convert_ids_to_tokens(list(range(self.vocab_size))) + self._no_prefix_space_tokens = {i for i, tok in enumerate(vocab) if not tok.startswith('▁')} + return self._no_prefix_space_tokens + + @property + def vocab_size(self): + """Returns vocab size""" + return self.sp_model.get_piece_size() + + @property + def bos_token_id(self) -> Optional[int]: + return self.sp_model.bos_id() + + @property + def eos_token_id(self) -> Optional[int]: + return self.sp_model.eos_id() + + def get_vocab(self): + """Returns vocab as a dict""" + vocab = {self.convert_ids_to_tokens(i): i for i in range(self.vocab_size)} + vocab.update(self.added_tokens_encoder) + return vocab + + def _tokenize(self, text): + """Returns a tokenized string.""" + return self.sp_model.encode(text, out_type=str) + + def _convert_token_to_id(self, token): + """Converts a token (str) in an id using the vocab.""" + return self.sp_model.piece_to_id(token) + + def _convert_id_to_token(self, index): + """Converts an index (integer) in a token (str) using the vocab.""" + token = self.sp_model.IdToPiece(index) + return token + + def _maybe_add_prefix_space(self, tokens, decoded): + if tokens and tokens[0] not in self.no_prefix_space_tokens: + return ' ' + decoded + else: + return decoded + + def convert_tokens_to_string(self, tokens): + """Converts a sequence of tokens (string) in a single string.""" + current_sub_tokens = [] + out_string = '' + prev_is_special = False + for token in tokens: + # make sure that special tokens are not decoded using sentencepiece model + if token in self.all_special_tokens: + if not prev_is_special: + out_string += ' ' + out_string += self.sp_model.decode(current_sub_tokens) + token + prev_is_special = True + current_sub_tokens = [] + else: + current_sub_tokens.append(token) + prev_is_special = False + out_string += self.sp_model.decode(current_sub_tokens) + out_string = self.clean_up_tokenization(out_string) + out_string = self._maybe_add_prefix_space(tokens=tokens, decoded=out_string) + return out_string[1:] + + def save_vocabulary(self, save_directory, filename_prefix: Optional[str] = None) -> Tuple[str]: + """ + Save the vocabulary and special tokens file to a directory. + + Args: + save_directory (`str`): + The directory in which to save the vocabulary. + + Returns: + `Tuple(str)`: Paths to the files saved. + """ + if not os.path.isdir(save_directory): + logger.error(f'Vocabulary path ({save_directory}) should be a directory') + return + out_vocab_file = os.path.join( + save_directory, (filename_prefix + '-' if filename_prefix else '') + VOCAB_FILES_NAMES['vocab_file'] + ) + + if os.path.abspath(self.vocab_file) != os.path.abspath(out_vocab_file) and os.path.isfile(self.vocab_file): + copyfile(self.vocab_file, out_vocab_file) + elif not os.path.isfile(self.vocab_file): + with open(out_vocab_file, 'wb') as fi: + content_spiece_model = self.sp_model.serialized_model_proto() + fi.write(content_spiece_model) + + return (out_vocab_file,) + + def build_inputs_with_special_tokens(self, token_ids_0, token_ids_1=None): + if self.add_bos_token: + bos_token_ids = [self.bos_token_id] + else: + bos_token_ids = [] + + output = bos_token_ids + token_ids_0 + + if token_ids_1 is not None: + output = output + token_ids_1 + + if self.add_eos_token: + output = output + [self.eos_token_id] + + return output + + def get_special_tokens_mask( + self, token_ids_0: List[int], token_ids_1: Optional[List[int]] = None, already_has_special_tokens: bool = False + ) -> List[int]: + """ + Retrieve sequence ids from a token list that has no special tokens added. This method is called when adding + special tokens using the tokenizer `prepare_for_model` method. + + Args: + token_ids_0 (`List[int]`): + List of IDs. + token_ids_1 (`List[int]`, *optional*): + Optional second list of IDs for sequence pairs. + already_has_special_tokens (`bool`, *optional*, defaults to `False`): + Whether or not the token list is already formatted with special tokens for the model. + + Returns: + `List[int]`: A list of integers in the range [0, 1]: 1 for a special token, 0 for a sequence token. + """ + if already_has_special_tokens: + return super().get_special_tokens_mask( + token_ids_0=token_ids_0, token_ids_1=token_ids_1, already_has_special_tokens=True + ) + + if token_ids_1 is None: + return [1] + ([0] * len(token_ids_0)) + [1] + return [1] + ([0] * len(token_ids_0)) + [1, 1] + ([0] * len(token_ids_1)) + [1] + + def create_token_type_ids_from_sequences( + self, token_ids_0: List[int], token_ids_1: Optional[List[int]] = None + ) -> List[int]: + """ + Create a mask from the two sequences passed to be used in a sequence-pair classification task. T5 does not make + use of token type ids, therefore a list of zeros is returned. + + Args: + token_ids_0 (`List[int]`): + List of IDs. + token_ids_1 (`List[int]`, *optional*): + Optional second list of IDs for sequence pairs. + + Returns: + `List[int]`: List of zeros. + """ + eos = [self.eos_token_id] + + if token_ids_1 is None: + return len(token_ids_0 + eos) * [0] + return len(token_ids_0 + eos + token_ids_1 + eos) * [0] diff --git a/InternVL-main/internvl_chat/work_dirs/internvl_chat_v2_5/ak/checkpoint-700/tokenizer_config.json b/InternVL-main/internvl_chat/work_dirs/internvl_chat_v2_5/ak/checkpoint-700/tokenizer_config.json new file mode 100644 index 0000000000000000000000000000000000000000..1f32946df0f56d92ddbc1df79cabb4477b622480 --- /dev/null +++ b/InternVL-main/internvl_chat/work_dirs/internvl_chat_v2_5/ak/checkpoint-700/tokenizer_config.json @@ -0,0 +1,179 @@ +{ + "added_tokens_decoder": { + "0": { + "content": "", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "1": { + "content": "", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "2": { + "content": "", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "92538": { + "content": "<|plugin|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "92539": { + "content": "<|interpreter|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "92540": { + "content": "<|action_end|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "92541": { + "content": "<|action_start|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "92542": { + "content": "<|im_end|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "92543": { + "content": "<|im_start|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "92544": { + "content": "", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "92545": { + "content": "", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "92546": { + "content": "", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "92547": { + "content": "", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "92548": { + "content": "", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "92549": { + "content": "", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "92550": { + "content": "", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "92551": { + "content": "", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "92552": { + "content": "", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + } + }, + "additional_special_tokens": [ + "<|im_start|>", + "<|im_end|>", + "<|action_start|>", + "<|action_end|>", + "<|interpreter|>", + "<|plugin|>", + "", + "", + "", + "", + "", + "", + "", + "", + "" + ], + "auto_map": { + "AutoTokenizer": [ + "tokenization_internlm2.InternLM2Tokenizer", + null + ] + }, + "bos_token": "", + "chat_template": "{{ bos_token }}{% for message in messages %}{{'<|im_start|>' + message['role'] + '\n' + message['content'] + '<|im_end|>' + '\n'}}{% endfor %}{% if add_generation_prompt %}{{ '<|im_start|>assistant\n' }}{% endif %}", + "clean_up_tokenization_spaces": false, + "eos_token": "", + "model_max_length": 8192, + "pad_token": "", + "tokenizer_class": "InternLM2Tokenizer", + "unk_token": "" +} diff --git a/InternVL-main/internvl_chat/work_dirs/internvl_chat_v2_5/ak/training_log.txt b/InternVL-main/internvl_chat/work_dirs/internvl_chat_v2_5/ak/training_log.txt new file mode 100644 index 0000000000000000000000000000000000000000..d408a73b8263d0aa691f99b8d1b2d7dfa5b4374a --- /dev/null +++ b/InternVL-main/internvl_chat/work_dirs/internvl_chat_v2_5/ak/training_log.txt @@ -0,0 +1,70344 @@ +[2025-05-01 21:42:12,602] [INFO] [real_accelerator.py:203:get_accelerator] Setting ds_accelerator to cuda (auto detect) +/home1/gmh/anaconda3/envs/promptbench/lib/python3.9/site-packages/timm/models/layers/__init__.py:48: FutureWarning: Importing from timm.models.layers is deprecated, please import via timm.layers + warnings.warn(f"Importing from {__name__} is deprecated, please import via timm.layers", FutureWarning) +petrel_client is not installed. If you read data locally instead of from ceph, ignore it. +petrel_client is not installed. Using PIL to load images. +[2025-05-01 21:42:16,759] [INFO] [comm.py:652:init_distributed] cdb=None +[2025-05-01 21:42:16,759] [INFO] [comm.py:683:init_distributed] Initializing TorchBackend in DeepSpeed with backend nccl +05/01/2025 21:42:16 - WARNING - __main__ - Process rank: 0, device: cuda:0, n_gpu: 1distributed training: True, 16-bits training: False +05/01/2025 21:42:16 - INFO - __main__ - Training/evaluation parameters TrainingArguments( +_n_gpu=1, +accelerator_config={'split_batches': False, 'dispatch_batches': None, 'even_batches': True, 'use_seedable_sampler': True, 'non_blocking': False, 'gradient_accumulation_kwargs': None, 'use_configured_state': False}, +adafactor=False, +adam_beta1=0.9, +adam_beta2=0.999, +adam_epsilon=1e-08, +auto_find_batch_size=False, +batch_eval_metrics=False, +bf16=True, +bf16_full_eval=False, +data_seed=None, +dataloader_drop_last=False, +dataloader_num_workers=4, +dataloader_persistent_workers=False, +dataloader_pin_memory=True, +dataloader_prefetch_factor=None, +ddp_backend=None, +ddp_broadcast_buffers=None, +ddp_bucket_cap_mb=None, +ddp_find_unused_parameters=None, +ddp_timeout=1800, +debug=[], +deepspeed=zero_stage1_config.json, +disable_tqdm=False, +dispatch_batches=None, +do_eval=False, +do_predict=False, +do_train=True, +eval_accumulation_steps=None, +eval_delay=0, +eval_do_concat_batches=True, +eval_on_start=False, +eval_steps=None, +eval_strategy=no, +eval_use_gather_object=False, +evaluation_strategy=no, +fp16=False, +fp16_backend=auto, +fp16_full_eval=False, +fp16_opt_level=O1, +fsdp=[], +fsdp_config={'min_num_params': 0, 'xla': False, 'xla_fsdp_v2': False, 'xla_fsdp_grad_ckpt': False}, +fsdp_min_num_params=0, +fsdp_transformer_layer_cls_to_wrap=None, +full_determinism=False, +gradient_accumulation_steps=16, +gradient_checkpointing=False, +gradient_checkpointing_kwargs=None, +greater_is_better=None, +group_by_length=True, +half_precision_backend=auto, +hub_always_push=False, +hub_model_id=None, +hub_private_repo=False, +hub_strategy=every_save, +hub_token=, +ignore_data_skip=False, +include_inputs_for_metrics=False, +include_num_input_tokens_seen=False, +include_tokens_per_second=False, +jit_mode_eval=False, +label_names=None, +label_smoothing_factor=0.0, +learning_rate=1e-05, +length_column_name=length, +load_best_model_at_end=False, +local_rank=0, +log_level=passive, +log_level_replica=warning, +log_on_each_node=True, +logging_dir=work_dirs/internvl_chat_v2_5/ak/runs/May01_21-42-16_9007, +logging_first_step=False, +logging_nan_inf_filter=True, +logging_steps=1.0, +logging_strategy=steps, +lr_scheduler_kwargs={}, +lr_scheduler_type=cosine, +max_grad_norm=1.0, +max_steps=-1, +metric_for_best_model=None, +mp_parameters=, +neftune_noise_alpha=None, +no_cuda=False, +num_train_epochs=10.0, +optim=adamw_torch, +optim_args=None, +optim_target_modules=None, +output_dir=work_dirs/internvl_chat_v2_5/ak, +overwrite_output_dir=True, +past_index=-1, +per_device_eval_batch_size=8, +per_device_train_batch_size=1, +prediction_loss_only=False, +push_to_hub=False, +push_to_hub_model_id=None, +push_to_hub_organization=None, +push_to_hub_token=, +ray_scope=last, +remove_unused_columns=True, +report_to=['tensorboard'], +restore_callback_states_from_checkpoint=False, +resume_from_checkpoint=None, +run_name=work_dirs/internvl_chat_v2_5/ak, +save_on_each_node=False, +save_only_model=False, +save_safetensors=True, +save_steps=100, +save_strategy=steps, +save_total_limit=100, +seed=42, +skip_memory_metrics=True, +split_batches=None, +tf32=None, +torch_compile=False, +torch_compile_backend=None, +torch_compile_mode=None, +torch_empty_cache_steps=None, +torchdynamo=None, +tpu_metrics_debug=False, +tpu_num_cores=None, +use_cpu=False, +use_ipex=False, +use_legacy_prediction_loop=False, +use_mps_device=False, +warmup_ratio=0.03, +warmup_steps=0, +weight_decay=0.01, +) +05/01/2025 21:42:16 - INFO - __main__ - Loading Tokenizer: OpenGVLab/InternVL2_5-2B +[INFO|tokenization_utils_base.py:2289] 2025-05-01 21:42:36,908 >> loading file ./tokenizer.model from cache at /home1/gmh/.cache/huggingface/hub/models--OpenGVLab--InternVL2_5-2B/snapshots/573169ee54df216786bb9a189e9a32a060a008cf/./tokenizer.model +[INFO|tokenization_utils_base.py:2289] 2025-05-01 21:42:36,908 >> loading file added_tokens.json from cache at /home1/gmh/.cache/huggingface/hub/models--OpenGVLab--InternVL2_5-2B/snapshots/573169ee54df216786bb9a189e9a32a060a008cf/added_tokens.json +[INFO|tokenization_utils_base.py:2289] 2025-05-01 21:42:36,908 >> loading file special_tokens_map.json from cache at /home1/gmh/.cache/huggingface/hub/models--OpenGVLab--InternVL2_5-2B/snapshots/573169ee54df216786bb9a189e9a32a060a008cf/special_tokens_map.json +[INFO|tokenization_utils_base.py:2289] 2025-05-01 21:42:36,908 >> loading file tokenizer_config.json from cache at /home1/gmh/.cache/huggingface/hub/models--OpenGVLab--InternVL2_5-2B/snapshots/573169ee54df216786bb9a189e9a32a060a008cf/tokenizer_config.json +[INFO|tokenization_utils_base.py:2289] 2025-05-01 21:42:36,908 >> loading file tokenizer.json from cache at None +[INFO|tokenization_utils_base.py:2533] 2025-05-01 21:42:37,151 >> Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained. +05/01/2025 21:42:37 - INFO - __main__ - Loading InternVLChatModel... +[INFO|configuration_utils.py:733] 2025-05-01 21:42:47,340 >> loading configuration file config.json from cache at /home1/gmh/.cache/huggingface/hub/models--OpenGVLab--InternVL2_5-2B/snapshots/573169ee54df216786bb9a189e9a32a060a008cf/config.json +[INFO|configuration_utils.py:800] 2025-05-01 21:42:47,342 >> Model config InternVLChatConfig { + "_commit_hash": "573169ee54df216786bb9a189e9a32a060a008cf", + "architectures": [ + "InternVLChatModel" + ], + "auto_map": { + "AutoConfig": "OpenGVLab/InternVL2_5-2B--configuration_internvl_chat.InternVLChatConfig", + "AutoModel": "OpenGVLab/InternVL2_5-2B--modeling_internvl_chat.InternVLChatModel", + "AutoModelForCausalLM": "OpenGVLab/InternVL2_5-2B--modeling_internvl_chat.InternVLChatModel" + }, + "downsample_ratio": 0.5, + "dynamic_image_size": true, + "force_image_size": 448, + "hidden_size": 2048, + "llm_config": { + "_name_or_path": "internlm/internlm2_5-1_8b-chat", + "add_cross_attention": false, + "architectures": [ + "InternLM2ForCausalLM" + ], + "attn_implementation": "flash_attention_2", + "auto_map": { + "AutoConfig": "configuration_internlm2.InternLM2Config", + "AutoModel": "modeling_internlm2.InternLM2ForCausalLM", + "AutoModelForCausalLM": "modeling_internlm2.InternLM2ForCausalLM", + "AutoModelForSequenceClassification": "modeling_internlm2.InternLM2ForSequenceClassification" + }, + "bad_words_ids": null, + "begin_suppress_tokens": null, + "bias": false, + "bos_token_id": 1, + "chunk_size_feed_forward": 0, + "cross_attention_hidden_size": null, + "decoder_start_token_id": null, + "diversity_penalty": 0.0, + "do_sample": false, + "early_stopping": false, + "encoder_no_repeat_ngram_size": 0, + "eos_token_id": 2, + "exponential_decay_length_penalty": null, + "finetuning_task": null, + "forced_bos_token_id": null, + "forced_eos_token_id": null, + "hidden_act": "silu", + "hidden_size": 2048, + "id2label": { + "0": "LABEL_0", + "1": "LABEL_1" + }, + "initializer_range": 0.02, + "intermediate_size": 8192, + "is_decoder": false, + "is_encoder_decoder": false, + "label2id": { + "LABEL_0": 0, + "LABEL_1": 1 + }, + "length_penalty": 1.0, + "max_length": 20, + "max_position_embeddings": 32768, + "min_length": 0, + "model_type": "internlm2", + "no_repeat_ngram_size": 0, + "num_attention_heads": 16, + "num_beam_groups": 1, + "num_beams": 1, + "num_hidden_layers": 24, + "num_key_value_heads": 8, + "num_return_sequences": 1, + "output_attentions": false, + "output_hidden_states": false, + "output_scores": false, + "pad_token_id": 2, + "prefix": null, + "pretraining_tp": 1, + "problem_type": null, + "pruned_heads": {}, + "remove_invalid_values": false, + "repetition_penalty": 1.0, + "return_dict": true, + "return_dict_in_generate": false, + "rms_norm_eps": 1e-05, + "rope_scaling": { + "factor": 2.0, + "type": "dynamic" + }, + "rope_theta": 1000000, + "sep_token_id": null, + "suppress_tokens": null, + "task_specific_params": null, + "temperature": 1.0, + "tf_legacy_loss": false, + "tie_encoder_decoder": false, + "tie_word_embeddings": false, + "tokenizer_class": null, + "top_k": 50, + "top_p": 1.0, + "torch_dtype": "bfloat16", + "torchscript": false, + "transformers_version": "4.43.2", + "typical_p": 1.0, + "use_bfloat16": true, + "use_cache": true, + "vocab_size": 92553 + }, + "max_dynamic_patch": 12, + "min_dynamic_patch": 1, + "model_type": "internvl_chat", + "pad2square": false, + "ps_version": "v2", + "select_layer": -1, + "template": "internvl2_5", + "tie_word_embeddings": false, + "torch_dtype": "bfloat16", + "transformers_version": null, + "use_backbone_lora": 0, + "use_llm_lora": 0, + "use_thumbnail": true, + "vision_config": { + "_name_or_path": "", + "add_cross_attention": false, + "architectures": [ + "InternVisionModel" + ], + "attention_dropout": 0.0, + "bad_words_ids": null, + "begin_suppress_tokens": null, + "bos_token_id": null, + "chunk_size_feed_forward": 0, + "cross_attention_hidden_size": null, + "decoder_start_token_id": null, + "diversity_penalty": 0.0, + "do_sample": false, + "drop_path_rate": 0.0, + "dropout": 0.0, + "early_stopping": false, + "encoder_no_repeat_ngram_size": 0, + "eos_token_id": null, + "exponential_decay_length_penalty": null, + "finetuning_task": null, + "forced_bos_token_id": null, + "forced_eos_token_id": null, + "hidden_act": "gelu", + "hidden_size": 1024, + "id2label": { + "0": "LABEL_0", + "1": "LABEL_1" + }, + "image_size": 448, + "initializer_factor": 1.0, + "initializer_range": 0.02, + "intermediate_size": 4096, + "is_decoder": false, + "is_encoder_decoder": false, + "label2id": { + "LABEL_0": 0, + "LABEL_1": 1 + }, + "layer_norm_eps": 1e-06, + "length_penalty": 1.0, + "max_length": 20, + "min_length": 0, + "model_type": "intern_vit_6b", + "no_repeat_ngram_size": 0, + "norm_type": "layer_norm", + "num_attention_heads": 16, + "num_beam_groups": 1, + "num_beams": 1, + "num_channels": 3, + "num_hidden_layers": 24, + "num_return_sequences": 1, + "output_attentions": false, + "output_hidden_states": false, + "output_scores": false, + "pad_token_id": null, + "patch_size": 14, + "prefix": null, + "problem_type": null, + "pruned_heads": {}, + "qk_normalization": false, + "qkv_bias": true, + "remove_invalid_values": false, + "repetition_penalty": 1.0, + "return_dict": true, + "return_dict_in_generate": false, + "sep_token_id": null, + "suppress_tokens": null, + "task_specific_params": null, + "temperature": 1.0, + "tf_legacy_loss": false, + "tie_encoder_decoder": false, + "tie_word_embeddings": true, + "tokenizer_class": null, + "top_k": 50, + "top_p": 1.0, + "torch_dtype": "bfloat16", + "torchscript": false, + "transformers_version": "4.43.2", + "typical_p": 1.0, + "use_bfloat16": true, + "use_flash_attn": true + } +} + +05/01/2025 21:42:47 - INFO - __main__ - Using flash_attention_2 for InternLM +[INFO|modeling_utils.py:3634] 2025-05-01 21:42:47,343 >> loading weights file model.safetensors from cache at /home1/gmh/.cache/huggingface/hub/models--OpenGVLab--InternVL2_5-2B/snapshots/573169ee54df216786bb9a189e9a32a060a008cf/model.safetensors +[INFO|modeling_utils.py:1572] 2025-05-01 21:42:47,362 >> Instantiating InternVLChatModel model under default dtype torch.bfloat16. +[INFO|configuration_utils.py:1038] 2025-05-01 21:42:47,364 >> Generate config GenerationConfig {} + +[INFO|configuration_utils.py:1038] 2025-05-01 21:42:47,425 >> Generate config GenerationConfig { + "bos_token_id": 1, + "eos_token_id": 2, + "pad_token_id": 2 +} + +[INFO|modeling_utils.py:4463] 2025-05-01 21:42:47,757 >> All model checkpoint weights were used when initializing InternVLChatModel. + +[INFO|modeling_utils.py:4471] 2025-05-01 21:42:47,757 >> All the weights of InternVLChatModel were initialized from the model checkpoint at OpenGVLab/InternVL2_5-2B. +If your task is similar to the task the model of the checkpoint was trained on, you can already use InternVLChatModel for predictions without further training. +[INFO|configuration_utils.py:993] 2025-05-01 21:42:57,773 >> loading configuration file generation_config.json from cache at /home1/gmh/.cache/huggingface/hub/models--OpenGVLab--InternVL2_5-2B/snapshots/573169ee54df216786bb9a189e9a32a060a008cf/generation_config.json +[INFO|configuration_utils.py:1038] 2025-05-01 21:42:57,780 >> Generate config GenerationConfig { + "eos_token_id": [ + 92542, + 92543 + ] +} + +05/01/2025 21:42:57 - INFO - __main__ - Finished +05/01/2025 21:42:57 - INFO - __main__ - model.config.force_image_size: 448 +05/01/2025 21:42:57 - INFO - __main__ - data_args.force_image_size: 448 +05/01/2025 21:42:57 - INFO - __main__ - model.config.vision_config.image_size: 448 +05/01/2025 21:42:57 - INFO - __main__ - [Dataset] num_image_token: 256 +05/01/2025 21:42:57 - INFO - __main__ - [Dataset] dynamic_image_size: True +05/01/2025 21:42:57 - INFO - __main__ - [Dataset] use_thumbnail: True +05/01/2025 21:42:57 - INFO - __main__ - [Dataset] min_dynamic_patch: 1, max_dynamic_patch: 6 +05/01/2025 21:42:57 - INFO - __main__ - Formatting inputs...Skip in lazy mode +05/01/2025 21:42:58 - INFO - __main__ - Add dataset: profused_benchmark with length: 13953 +trainable params: 7,864,320 || all params: 1,897,011,200 || trainable%: 0.4146 +05/01/2025 21:42:58 - INFO - __main__ - language_model.base_model.model.model.layers.0.attention.wqkv.lora_A.default.weight +05/01/2025 21:42:58 - INFO - __main__ - language_model.base_model.model.model.layers.0.attention.wqkv.lora_B.default.weight +05/01/2025 21:42:58 - INFO - __main__ - language_model.base_model.model.model.layers.0.attention.wo.lora_A.default.weight +05/01/2025 21:42:58 - INFO - __main__ - language_model.base_model.model.model.layers.0.attention.wo.lora_B.default.weight +05/01/2025 21:42:58 - INFO - __main__ - language_model.base_model.model.model.layers.0.feed_forward.w1.lora_A.default.weight +05/01/2025 21:42:58 - INFO - __main__ - language_model.base_model.model.model.layers.0.feed_forward.w1.lora_B.default.weight +05/01/2025 21:42:58 - INFO - __main__ - language_model.base_model.model.model.layers.0.feed_forward.w3.lora_A.default.weight +05/01/2025 21:42:58 - INFO - __main__ - language_model.base_model.model.model.layers.0.feed_forward.w3.lora_B.default.weight +05/01/2025 21:42:58 - INFO - __main__ - language_model.base_model.model.model.layers.0.feed_forward.w2.lora_A.default.weight +05/01/2025 21:42:58 - INFO - __main__ - language_model.base_model.model.model.layers.0.feed_forward.w2.lora_B.default.weight +05/01/2025 21:42:58 - INFO - __main__ - language_model.base_model.model.model.layers.1.attention.wqkv.lora_A.default.weight +05/01/2025 21:42:58 - INFO - __main__ - language_model.base_model.model.model.layers.1.attention.wqkv.lora_B.default.weight +05/01/2025 21:42:58 - INFO - __main__ - language_model.base_model.model.model.layers.1.attention.wo.lora_A.default.weight +05/01/2025 21:42:58 - INFO - __main__ - language_model.base_model.model.model.layers.1.attention.wo.lora_B.default.weight +05/01/2025 21:42:58 - INFO - __main__ - language_model.base_model.model.model.layers.1.feed_forward.w1.lora_A.default.weight +05/01/2025 21:42:58 - INFO - __main__ - language_model.base_model.model.model.layers.1.feed_forward.w1.lora_B.default.weight +05/01/2025 21:42:58 - INFO - __main__ - language_model.base_model.model.model.layers.1.feed_forward.w3.lora_A.default.weight +05/01/2025 21:42:58 - INFO - __main__ - language_model.base_model.model.model.layers.1.feed_forward.w3.lora_B.default.weight +05/01/2025 21:42:58 - INFO - __main__ - language_model.base_model.model.model.layers.1.feed_forward.w2.lora_A.default.weight +05/01/2025 21:42:58 - INFO - __main__ - language_model.base_model.model.model.layers.1.feed_forward.w2.lora_B.default.weight +05/01/2025 21:42:58 - INFO - __main__ - language_model.base_model.model.model.layers.2.attention.wqkv.lora_A.default.weight +05/01/2025 21:42:58 - INFO - __main__ - language_model.base_model.model.model.layers.2.attention.wqkv.lora_B.default.weight +05/01/2025 21:42:58 - INFO - __main__ - language_model.base_model.model.model.layers.2.attention.wo.lora_A.default.weight +05/01/2025 21:42:58 - INFO - __main__ - language_model.base_model.model.model.layers.2.attention.wo.lora_B.default.weight +05/01/2025 21:42:58 - INFO - __main__ - language_model.base_model.model.model.layers.2.feed_forward.w1.lora_A.default.weight +05/01/2025 21:42:58 - INFO - __main__ - language_model.base_model.model.model.layers.2.feed_forward.w1.lora_B.default.weight +05/01/2025 21:42:58 - INFO - __main__ - language_model.base_model.model.model.layers.2.feed_forward.w3.lora_A.default.weight +05/01/2025 21:42:58 - INFO - __main__ - language_model.base_model.model.model.layers.2.feed_forward.w3.lora_B.default.weight +05/01/2025 21:42:58 - INFO - __main__ - language_model.base_model.model.model.layers.2.feed_forward.w2.lora_A.default.weight +05/01/2025 21:42:58 - INFO - __main__ - language_model.base_model.model.model.layers.2.feed_forward.w2.lora_B.default.weight +05/01/2025 21:42:58 - INFO - __main__ - language_model.base_model.model.model.layers.3.attention.wqkv.lora_A.default.weight +05/01/2025 21:42:58 - INFO - __main__ - language_model.base_model.model.model.layers.3.attention.wqkv.lora_B.default.weight +05/01/2025 21:42:58 - INFO - __main__ - language_model.base_model.model.model.layers.3.attention.wo.lora_A.default.weight +05/01/2025 21:42:58 - INFO - __main__ - language_model.base_model.model.model.layers.3.attention.wo.lora_B.default.weight +05/01/2025 21:42:58 - INFO - __main__ - language_model.base_model.model.model.layers.3.feed_forward.w1.lora_A.default.weight +05/01/2025 21:42:58 - INFO - __main__ - language_model.base_model.model.model.layers.3.feed_forward.w1.lora_B.default.weight +05/01/2025 21:42:58 - INFO - __main__ - language_model.base_model.model.model.layers.3.feed_forward.w3.lora_A.default.weight +05/01/2025 21:42:58 - INFO - __main__ - language_model.base_model.model.model.layers.3.feed_forward.w3.lora_B.default.weight +05/01/2025 21:42:58 - INFO - __main__ - language_model.base_model.model.model.layers.3.feed_forward.w2.lora_A.default.weight +05/01/2025 21:42:58 - INFO - __main__ - language_model.base_model.model.model.layers.3.feed_forward.w2.lora_B.default.weight +05/01/2025 21:42:58 - INFO - __main__ - language_model.base_model.model.model.layers.4.attention.wqkv.lora_A.default.weight +05/01/2025 21:42:58 - INFO - __main__ - language_model.base_model.model.model.layers.4.attention.wqkv.lora_B.default.weight +05/01/2025 21:42:58 - INFO - 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21:42:58 - INFO - __main__ - language_model.base_model.model.model.layers.21.feed_forward.w1.lora_B.default.weight +05/01/2025 21:42:58 - INFO - __main__ - language_model.base_model.model.model.layers.21.feed_forward.w3.lora_A.default.weight +05/01/2025 21:42:58 - INFO - __main__ - language_model.base_model.model.model.layers.21.feed_forward.w3.lora_B.default.weight +05/01/2025 21:42:58 - INFO - __main__ - language_model.base_model.model.model.layers.21.feed_forward.w2.lora_A.default.weight +05/01/2025 21:42:58 - INFO - __main__ - language_model.base_model.model.model.layers.21.feed_forward.w2.lora_B.default.weight +05/01/2025 21:42:58 - INFO - __main__ - language_model.base_model.model.model.layers.22.attention.wqkv.lora_A.default.weight +05/01/2025 21:42:58 - INFO - __main__ - language_model.base_model.model.model.layers.22.attention.wqkv.lora_B.default.weight +05/01/2025 21:42:58 - INFO - __main__ - language_model.base_model.model.model.layers.22.attention.wo.lora_A.default.weight +05/01/2025 21:42:58 - INFO - __main__ - language_model.base_model.model.model.layers.22.attention.wo.lora_B.default.weight +05/01/2025 21:42:58 - INFO - __main__ - language_model.base_model.model.model.layers.22.feed_forward.w1.lora_A.default.weight +05/01/2025 21:42:58 - INFO - __main__ - language_model.base_model.model.model.layers.22.feed_forward.w1.lora_B.default.weight +05/01/2025 21:42:58 - INFO - __main__ - language_model.base_model.model.model.layers.22.feed_forward.w3.lora_A.default.weight +05/01/2025 21:42:58 - INFO - __main__ - language_model.base_model.model.model.layers.22.feed_forward.w3.lora_B.default.weight +05/01/2025 21:42:58 - INFO - __main__ - language_model.base_model.model.model.layers.22.feed_forward.w2.lora_A.default.weight +05/01/2025 21:42:58 - INFO - __main__ - language_model.base_model.model.model.layers.22.feed_forward.w2.lora_B.default.weight +05/01/2025 21:42:58 - INFO - __main__ - language_model.base_model.model.model.layers.23.attention.wqkv.lora_A.default.weight +05/01/2025 21:42:58 - INFO - __main__ - language_model.base_model.model.model.layers.23.attention.wqkv.lora_B.default.weight +05/01/2025 21:42:58 - INFO - __main__ - language_model.base_model.model.model.layers.23.attention.wo.lora_A.default.weight +05/01/2025 21:42:58 - INFO - __main__ - language_model.base_model.model.model.layers.23.attention.wo.lora_B.default.weight +05/01/2025 21:42:58 - INFO - __main__ - language_model.base_model.model.model.layers.23.feed_forward.w1.lora_A.default.weight +05/01/2025 21:42:58 - INFO - __main__ - language_model.base_model.model.model.layers.23.feed_forward.w1.lora_B.default.weight +05/01/2025 21:42:58 - INFO - __main__ - language_model.base_model.model.model.layers.23.feed_forward.w3.lora_A.default.weight +05/01/2025 21:42:58 - INFO - __main__ - language_model.base_model.model.model.layers.23.feed_forward.w3.lora_B.default.weight +05/01/2025 21:42:58 - INFO - __main__ - language_model.base_model.model.model.layers.23.feed_forward.w2.lora_A.default.weight +05/01/2025 21:42:58 - INFO - __main__ - language_model.base_model.model.model.layers.23.feed_forward.w2.lora_B.default.weight +05/01/2025 21:42:58 - INFO - __main__ - mlp1.0.weight +05/01/2025 21:42:58 - INFO - __main__ - mlp1.0.bias +05/01/2025 21:42:58 - INFO - __main__ - mlp1.1.weight +05/01/2025 21:42:58 - INFO - __main__ - mlp1.1.bias +05/01/2025 21:42:58 - INFO - __main__ - mlp1.3.weight +05/01/2025 21:42:58 - INFO - __main__ - mlp1.3.bias +[INFO|trainer.py:648] 2025-05-01 21:42:58,558 >> Using auto half precision backend +[2025-05-01 21:42:59,021] [INFO] [logging.py:96:log_dist] [Rank 0] DeepSpeed info: version=0.15.1, git-hash=unknown, git-branch=unknown +[2025-05-01 21:42:59,021] [INFO] [config.py:733:__init__] Config mesh_device None world_size = 1 +[2025-05-01 21:43:01,025] [INFO] [logging.py:96:log_dist] [Rank 0] DeepSpeed Flops Profiler Enabled: False +Using /home1/gmh/.cache/torch_extensions/py39_cu121 as PyTorch extensions root... +Emitting ninja build file /home1/gmh/.cache/torch_extensions/py39_cu121/cpu_adam/build.ninja... +Building extension module cpu_adam... +Allowing ninja to set a default number of workers... (overridable by setting the environment variable MAX_JOBS=N) +ninja: no work to do. +Loading extension module cpu_adam... +Time to load cpu_adam op: 3.1843090057373047 seconds +Adam Optimizer #0 is created with AVX512 arithmetic capability. +Config: alpha=0.000010, betas=(0.900000, 0.999000), weight_decay=0.010000, adam_w=1 +[2025-05-01 21:43:05,471] [INFO] [logging.py:96:log_dist] [Rank 0] Using DeepSpeed Optimizer param name adamw as basic optimizer +[2025-05-01 21:43:05,471] [INFO] [logging.py:96:log_dist] [Rank 0] Removing param_group that has no 'params' in the basic Optimizer +[2025-05-01 21:43:05,526] [INFO] [logging.py:96:log_dist] [Rank 0] DeepSpeed Basic Optimizer = DeepSpeedCPUAdam +[2025-05-01 21:43:05,526] [INFO] [utils.py:59:is_zero_supported_optimizer] Checking ZeRO support for optimizer=DeepSpeedCPUAdam type= +[2025-05-01 21:43:05,526] [INFO] [logging.py:96:log_dist] [Rank 0] Creating torch.bfloat16 ZeRO stage 1 optimizer +[2025-05-01 21:43:05,526] [INFO] [stage_1_and_2.py:148:__init__] Reduce bucket size 1000000000 +[2025-05-01 21:43:05,526] [INFO] [stage_1_and_2.py:149:__init__] Allgather bucket size 1000000000 +[2025-05-01 21:43:05,526] [INFO] [stage_1_and_2.py:150:__init__] CPU Offload: True +[2025-05-01 21:43:05,526] [INFO] [stage_1_and_2.py:151:__init__] Round robin gradient partitioning: False +[2025-05-01 21:43:05,935] [INFO] [utils.py:781:see_memory_usage] Before initializing optimizer states +[2025-05-01 21:43:05,936] [INFO] [utils.py:782:see_memory_usage] MA 4.52 GB Max_MA 4.52 GB CA 4.71 GB Max_CA 5 GB +[2025-05-01 21:43:05,936] [INFO] [utils.py:789:see_memory_usage] CPU Virtual Memory: used = 75.1 GB, percent = 10.0% +[2025-05-01 21:43:06,212] [INFO] [utils.py:781:see_memory_usage] After initializing optimizer states +[2025-05-01 21:43:06,212] [INFO] [utils.py:782:see_memory_usage] MA 4.52 GB Max_MA 4.52 GB CA 4.71 GB Max_CA 5 GB +[2025-05-01 21:43:06,213] [INFO] [utils.py:789:see_memory_usage] CPU Virtual Memory: used = 75.26 GB, percent = 10.0% +[2025-05-01 21:43:06,213] [INFO] [stage_1_and_2.py:543:__init__] optimizer state initialized +[2025-05-01 21:43:06,415] [INFO] [utils.py:781:see_memory_usage] After initializing ZeRO optimizer +[2025-05-01 21:43:06,416] [INFO] [utils.py:782:see_memory_usage] MA 4.52 GB Max_MA 4.52 GB CA 4.71 GB Max_CA 5 GB +[2025-05-01 21:43:06,416] [INFO] [utils.py:789:see_memory_usage] CPU Virtual Memory: used = 75.25 GB, percent = 10.0% +[2025-05-01 21:43:06,422] [INFO] [logging.py:96:log_dist] [Rank 0] DeepSpeed Final Optimizer = DeepSpeedZeroOptimizer +[2025-05-01 21:43:06,422] [INFO] [logging.py:96:log_dist] [Rank 0] DeepSpeed using client callable to create LR scheduler +[2025-05-01 21:43:06,422] [INFO] [logging.py:96:log_dist] [Rank 0] DeepSpeed LR Scheduler = +[2025-05-01 21:43:06,422] [INFO] [logging.py:96:log_dist] [Rank 0] step=0, skipped=0, lr=[0.0], mom=[[0.9, 0.999]] +[2025-05-01 21:43:06,427] [INFO] [config.py:999:print] DeepSpeedEngine configuration: +[2025-05-01 21:43:06,428] [INFO] [config.py:1003:print] activation_checkpointing_config { + "partition_activations": false, + "contiguous_memory_optimization": false, + "cpu_checkpointing": false, + "number_checkpoints": null, + "synchronize_checkpoint_boundary": false, + "profile": false +} +[2025-05-01 21:43:06,428] [INFO] [config.py:1003:print] aio_config ................... {'block_size': 1048576, 'queue_depth': 8, 'thread_count': 1, 'single_submit': False, 'overlap_events': True, 'use_gds': False} +[2025-05-01 21:43:06,428] [INFO] [config.py:1003:print] amp_enabled .................. False +[2025-05-01 21:43:06,428] [INFO] [config.py:1003:print] amp_params ................... False +[2025-05-01 21:43:06,428] [INFO] [config.py:1003:print] autotuning_config ............ { + "enabled": false, + "start_step": null, + "end_step": null, + "metric_path": null, + "arg_mappings": null, + "metric": "throughput", + "model_info": null, + "results_dir": "autotuning_results", + "exps_dir": "autotuning_exps", + "overwrite": true, + "fast": true, + "start_profile_step": 3, + "end_profile_step": 5, + "tuner_type": "gridsearch", + "tuner_early_stopping": 5, + "tuner_num_trials": 50, + "model_info_path": null, + "mp_size": 1, + "max_train_batch_size": null, + "min_train_batch_size": 1, + "max_train_micro_batch_size_per_gpu": 1.024000e+03, + "min_train_micro_batch_size_per_gpu": 1, + "num_tuning_micro_batch_sizes": 3 +} +[2025-05-01 21:43:06,428] [INFO] [config.py:1003:print] bfloat16_enabled ............. True +[2025-05-01 21:43:06,428] [INFO] [config.py:1003:print] bfloat16_immediate_grad_update False +[2025-05-01 21:43:06,428] [INFO] [config.py:1003:print] checkpoint_parallel_write_pipeline False +[2025-05-01 21:43:06,428] [INFO] [config.py:1003:print] checkpoint_tag_validation_enabled True +[2025-05-01 21:43:06,428] [INFO] [config.py:1003:print] checkpoint_tag_validation_fail False +[2025-05-01 21:43:06,428] [INFO] [config.py:1003:print] comms_config ................. +[2025-05-01 21:43:06,428] [INFO] [config.py:1003:print] communication_data_type ...... None +[2025-05-01 21:43:06,428] [INFO] [config.py:1003:print] compression_config ........... {'weight_quantization': {'shared_parameters': {'enabled': False, 'quantizer_kernel': False, 'schedule_offset': 0, 'quantize_groups': 1, 'quantize_verbose': False, 'quantization_type': 'symmetric', 'quantize_weight_in_forward': False, 'rounding': 'nearest', 'fp16_mixed_quantize': False, 'quantize_change_ratio': 0.001}, 'different_groups': {}}, 'activation_quantization': {'shared_parameters': {'enabled': False, 'quantization_type': 'symmetric', 'range_calibration': 'dynamic', 'schedule_offset': 1000}, 'different_groups': {}}, 'sparse_pruning': {'shared_parameters': {'enabled': False, 'method': 'l1', 'schedule_offset': 1000}, 'different_groups': {}}, 'row_pruning': {'shared_parameters': {'enabled': False, 'method': 'l1', 'schedule_offset': 1000}, 'different_groups': {}}, 'head_pruning': {'shared_parameters': {'enabled': False, 'method': 'topk', 'schedule_offset': 1000}, 'different_groups': {}}, 'channel_pruning': {'shared_parameters': {'enabled': False, 'method': 'l1', 'schedule_offset': 1000}, 'different_groups': {}}, 'layer_reduction': {'enabled': False}} +[2025-05-01 21:43:06,428] [INFO] [config.py:1003:print] curriculum_enabled_legacy .... False +[2025-05-01 21:43:06,429] [INFO] [config.py:1003:print] curriculum_params_legacy ..... False +[2025-05-01 21:43:06,429] [INFO] [config.py:1003:print] data_efficiency_config ....... {'enabled': False, 'seed': 1234, 'data_sampling': {'enabled': False, 'num_epochs': 1000, 'num_workers': 0, 'curriculum_learning': {'enabled': False}}, 'data_routing': {'enabled': False, 'random_ltd': {'enabled': False, 'layer_token_lr_schedule': {'enabled': False}}}} +[2025-05-01 21:43:06,429] [INFO] [config.py:1003:print] data_efficiency_enabled ...... False +[2025-05-01 21:43:06,429] [INFO] [config.py:1003:print] dataloader_drop_last ......... False +[2025-05-01 21:43:06,429] [INFO] [config.py:1003:print] disable_allgather ............ False +[2025-05-01 21:43:06,429] [INFO] [config.py:1003:print] dump_state ................... False +[2025-05-01 21:43:06,429] [INFO] [config.py:1003:print] dynamic_loss_scale_args ...... None +[2025-05-01 21:43:06,429] [INFO] [config.py:1003:print] eigenvalue_enabled ........... False +[2025-05-01 21:43:06,429] [INFO] [config.py:1003:print] eigenvalue_gas_boundary_resolution 1 +[2025-05-01 21:43:06,429] [INFO] [config.py:1003:print] eigenvalue_layer_name ........ bert.encoder.layer +[2025-05-01 21:43:06,429] [INFO] [config.py:1003:print] eigenvalue_layer_num ......... 0 +[2025-05-01 21:43:06,429] [INFO] [config.py:1003:print] eigenvalue_max_iter .......... 100 +[2025-05-01 21:43:06,429] [INFO] [config.py:1003:print] eigenvalue_stability ......... 1e-06 +[2025-05-01 21:43:06,429] [INFO] [config.py:1003:print] eigenvalue_tol ............... 0.01 +[2025-05-01 21:43:06,429] [INFO] [config.py:1003:print] eigenvalue_verbose ........... False +[2025-05-01 21:43:06,429] [INFO] [config.py:1003:print] elasticity_enabled ........... False +[2025-05-01 21:43:06,429] [INFO] [config.py:1003:print] flops_profiler_config ........ { + "enabled": false, + "recompute_fwd_factor": 0.0, + "profile_step": 1, + "module_depth": -1, + "top_modules": 1, + "detailed": true, + "output_file": null +} +[2025-05-01 21:43:06,429] [INFO] [config.py:1003:print] fp16_auto_cast ............... None +[2025-05-01 21:43:06,429] [INFO] [config.py:1003:print] fp16_enabled ................. False +[2025-05-01 21:43:06,429] [INFO] [config.py:1003:print] fp16_master_weights_and_gradients False +[2025-05-01 21:43:06,429] [INFO] [config.py:1003:print] global_rank .................. 0 +[2025-05-01 21:43:06,429] [INFO] [config.py:1003:print] grad_accum_dtype ............. None +[2025-05-01 21:43:06,429] [INFO] [config.py:1003:print] gradient_accumulation_steps .. 16 +[2025-05-01 21:43:06,429] [INFO] [config.py:1003:print] gradient_clipping ............ 1.0 +[2025-05-01 21:43:06,429] [INFO] [config.py:1003:print] gradient_predivide_factor .... 1.0 +[2025-05-01 21:43:06,429] [INFO] [config.py:1003:print] graph_harvesting ............. False +[2025-05-01 21:43:06,429] [INFO] [config.py:1003:print] hybrid_engine ................ enabled=False max_out_tokens=512 inference_tp_size=1 release_inference_cache=False pin_parameters=True tp_gather_partition_size=8 +[2025-05-01 21:43:06,429] [INFO] [config.py:1003:print] initial_dynamic_scale ........ 1 +[2025-05-01 21:43:06,429] [INFO] [config.py:1003:print] load_universal_checkpoint .... False +[2025-05-01 21:43:06,429] [INFO] [config.py:1003:print] loss_scale ................... 1.0 +[2025-05-01 21:43:06,429] [INFO] [config.py:1003:print] memory_breakdown ............. False +[2025-05-01 21:43:06,429] [INFO] [config.py:1003:print] mics_hierarchial_params_gather False +[2025-05-01 21:43:06,429] [INFO] [config.py:1003:print] mics_shard_size .............. -1 +[2025-05-01 21:43:06,429] [INFO] [config.py:1003:print] monitor_config ............... tensorboard=TensorBoardConfig(enabled=False, output_path='', job_name='DeepSpeedJobName') comet=CometConfig(enabled=False, samples_log_interval=100, project=None, workspace=None, api_key=None, experiment_name=None, experiment_key=None, online=None, mode=None) wandb=WandbConfig(enabled=False, group=None, team=None, project='deepspeed') csv_monitor=CSVConfig(enabled=False, output_path='', job_name='DeepSpeedJobName') +[2025-05-01 21:43:06,429] [INFO] [config.py:1003:print] nebula_config ................ { + "enabled": false, + "persistent_storage_path": null, + "persistent_time_interval": 100, + "num_of_version_in_retention": 2, + "enable_nebula_load": true, + "load_path": null +} +[2025-05-01 21:43:06,429] [INFO] [config.py:1003:print] optimizer_legacy_fusion ...... False +[2025-05-01 21:43:06,429] [INFO] [config.py:1003:print] optimizer_name ............... adamw +[2025-05-01 21:43:06,429] [INFO] [config.py:1003:print] optimizer_params ............. {'lr': 1e-05, 'betas': [0.9, 0.999], 'eps': 1e-08, 'weight_decay': 0.01} +[2025-05-01 21:43:06,429] [INFO] [config.py:1003:print] pipeline ..................... {'stages': 'auto', 'partition': 'best', 'seed_layers': False, 'activation_checkpoint_interval': 0, 'pipe_partitioned': True, 'grad_partitioned': True} +[2025-05-01 21:43:06,429] [INFO] [config.py:1003:print] pld_enabled .................. False +[2025-05-01 21:43:06,429] [INFO] [config.py:1003:print] pld_params ................... False +[2025-05-01 21:43:06,429] [INFO] [config.py:1003:print] prescale_gradients ........... False +[2025-05-01 21:43:06,429] [INFO] [config.py:1003:print] scheduler_name ............... None +[2025-05-01 21:43:06,429] [INFO] [config.py:1003:print] scheduler_params ............. None +[2025-05-01 21:43:06,429] [INFO] [config.py:1003:print] seq_parallel_communication_data_type torch.float32 +[2025-05-01 21:43:06,429] [INFO] [config.py:1003:print] sparse_attention ............. None +[2025-05-01 21:43:06,430] [INFO] [config.py:1003:print] sparse_gradients_enabled ..... False +[2025-05-01 21:43:06,430] [INFO] [config.py:1003:print] steps_per_print .............. inf +[2025-05-01 21:43:06,430] [INFO] [config.py:1003:print] timers_config ................ enabled=True synchronized=True +[2025-05-01 21:43:06,430] [INFO] [config.py:1003:print] train_batch_size ............. 16 +[2025-05-01 21:43:06,430] [INFO] [config.py:1003:print] train_micro_batch_size_per_gpu 1 +[2025-05-01 21:43:06,430] [INFO] [config.py:1003:print] use_data_before_expert_parallel_ False +[2025-05-01 21:43:06,430] [INFO] [config.py:1003:print] use_node_local_storage ....... False +[2025-05-01 21:43:06,430] [INFO] [config.py:1003:print] wall_clock_breakdown ......... True +[2025-05-01 21:43:06,430] [INFO] [config.py:1003:print] weight_quantization_config ... None +[2025-05-01 21:43:06,430] [INFO] [config.py:1003:print] world_size ................... 1 +[2025-05-01 21:43:06,430] [INFO] [config.py:1003:print] zero_allow_untested_optimizer False +[2025-05-01 21:43:06,430] [INFO] [config.py:1003:print] zero_config .................. stage=1 contiguous_gradients=True reduce_scatter=True reduce_bucket_size=1000000000 use_multi_rank_bucket_allreduce=True allgather_partitions=True allgather_bucket_size=1000000000 overlap_comm=True load_from_fp32_weights=True elastic_checkpoint=False offload_param=DeepSpeedZeroOffloadParamConfig(device='cpu', nvme_path=None, buffer_count=5, buffer_size=100000000, max_in_cpu=1000000000, pin_memory=True) offload_optimizer=DeepSpeedZeroOffloadOptimizerConfig(device='cpu', nvme_path=None, buffer_count=4, pin_memory=True, pipeline_read=False, pipeline_write=False, fast_init=False, ratio=1.0) sub_group_size=1000000000 cpu_offload_param=None cpu_offload_use_pin_memory=None cpu_offload=None prefetch_bucket_size=50000000 param_persistence_threshold=100000 model_persistence_threshold=9223372036854775807 max_live_parameters=1000000000 max_reuse_distance=1000000000 gather_16bit_weights_on_model_save=False use_all_reduce_for_fetch_params=False stage3_gather_fp16_weights_on_model_save=False ignore_unused_parameters=True legacy_stage1=False round_robin_gradients=False zero_hpz_partition_size=1 zero_quantized_weights=False zero_quantized_nontrainable_weights=False zero_quantized_gradients=False mics_shard_size=-1 mics_hierarchical_params_gather=False memory_efficient_linear=True pipeline_loading_checkpoint=False override_module_apply=True +[2025-05-01 21:43:06,430] [INFO] [config.py:1003:print] zero_enabled ................. True +[2025-05-01 21:43:06,430] [INFO] [config.py:1003:print] zero_force_ds_cpu_optimizer .. True +[2025-05-01 21:43:06,430] [INFO] [config.py:1003:print] zero_optimization_stage ...... 1 +[2025-05-01 21:43:06,430] [INFO] [config.py:989:print_user_config] json = { + "zero_optimization": { + "stage": 1, + "allgather_partitions": true, + "allgather_bucket_size": 1.000000e+09, + "overlap_comm": true, + "reduce_scatter": true, + "reduce_bucket_size": 1.000000e+09, + "contiguous_gradients": true, + "offload_param": { + "device": "cpu", + "pin_memory": true + }, + "offload_optimizer": { + "device": "cpu", + "pin_memory": true + } + }, + "fp16": { + "enabled": false, + "auto_cast": true, + "loss_scale": 0, + "initial_scale_power": 32, + "loss_scale_window": 1000, + "hysteresis": 2, + "min_loss_scale": 1 + }, + "bf16": { + "enabled": true + }, + "optimizer": { + "type": "AdamW", + "params": { + "lr": 1e-05, + "betas": [0.9, 0.999], + "eps": 1e-08, + "weight_decay": 0.01 + } + }, + "gradient_accumulation_steps": 16, + "gradient_clipping": 1.0, + "steps_per_print": inf, + "train_batch_size": 16, + "train_micro_batch_size_per_gpu": 1, + "wall_clock_breakdown": true +} +[INFO|trainer.py:2134] 2025-05-01 21:43:06,430 >> ***** Running training ***** +[INFO|trainer.py:2135] 2025-05-01 21:43:06,430 >> Num examples = 13,953 +[INFO|trainer.py:2136] 2025-05-01 21:43:06,430 >> Num Epochs = 10 +[INFO|trainer.py:2137] 2025-05-01 21:43:06,430 >> Instantaneous batch size per device = 1 +[INFO|trainer.py:2140] 2025-05-01 21:43:06,430 >> Total train batch size (w. parallel, distributed & accumulation) = 16 +[INFO|trainer.py:2141] 2025-05-01 21:43:06,430 >> Gradient Accumulation steps = 16 +[INFO|trainer.py:2142] 2025-05-01 21:43:06,430 >> Total optimization steps = 8,720 +[INFO|trainer.py:2143] 2025-05-01 21:43:06,434 >> Number of trainable parameters = 20,459,520 + 0%| | 0/8720 [00:00> Saving model checkpoint to work_dirs/internvl_chat_v2_5/ak/checkpoint-100 +[INFO|configuration_utils.py:472] 2025-05-01 22:02:47,636 >> Configuration saved in work_dirs/internvl_chat_v2_5/ak/checkpoint-100/config.json +[INFO|configuration_utils.py:807] 2025-05-01 22:02:47,636 >> Configuration saved in work_dirs/internvl_chat_v2_5/ak/checkpoint-100/generation_config.json +[INFO|modeling_utils.py:2755] 2025-05-01 22:02:53,106 >> Model weights saved in work_dirs/internvl_chat_v2_5/ak/checkpoint-100/model.safetensors +[INFO|tokenization_utils_base.py:2702] 2025-05-01 22:02:53,108 >> tokenizer config file saved in work_dirs/internvl_chat_v2_5/ak/checkpoint-100/tokenizer_config.json +[INFO|tokenization_utils_base.py:2711] 2025-05-01 22:02:53,108 >> Special tokens file saved in work_dirs/internvl_chat_v2_5/ak/checkpoint-100/special_tokens_map.json +[INFO|tokenization_utils_base.py:2762] 2025-05-01 22:02:53,109 >> added tokens file saved in work_dirs/internvl_chat_v2_5/ak/checkpoint-100/added_tokens.json +[2025-05-01 22:02:53,343] [INFO] [logging.py:96:log_dist] [Rank 0] [Torch] Checkpoint global_step100 is about to be saved! +[2025-05-01 22:02:53,366] [INFO] [logging.py:96:log_dist] [Rank 0] Saving model checkpoint: work_dirs/internvl_chat_v2_5/ak/checkpoint-100/global_step100/mp_rank_00_model_states.pt +[2025-05-01 22:02:53,366] [INFO] [torch_checkpoint_engine.py:21:save] [Torch] Saving work_dirs/internvl_chat_v2_5/ak/checkpoint-100/global_step100/mp_rank_00_model_states.pt... +[2025-05-01 22:02:58,018] [INFO] [torch_checkpoint_engine.py:23:save] [Torch] Saved work_dirs/internvl_chat_v2_5/ak/checkpoint-100/global_step100/mp_rank_00_model_states.pt. +[2025-05-01 22:02:58,020] [INFO] [torch_checkpoint_engine.py:21:save] [Torch] Saving work_dirs/internvl_chat_v2_5/ak/checkpoint-100/global_step100/bf16_zero_pp_rank_0_mp_rank_00_optim_states.pt... +[2025-05-01 22:02:58,229] [INFO] [torch_checkpoint_engine.py:23:save] [Torch] Saved work_dirs/internvl_chat_v2_5/ak/checkpoint-100/global_step100/bf16_zero_pp_rank_0_mp_rank_00_optim_states.pt. +[2025-05-01 22:02:58,229] [INFO] [engine.py:3536:_save_zero_checkpoint] zero checkpoint saved work_dirs/internvl_chat_v2_5/ak/checkpoint-100/global_step100/bf16_zero_pp_rank_0_mp_rank_00_optim_states.pt +[2025-05-01 22:02:58,230] [INFO] [torch_checkpoint_engine.py:33:commit] [Torch] Checkpoint global_step100 is ready now! +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 488 +[2025-05-01 22:02:58,452] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 71.62 | bwd_microstep: 137.65 | bwd_inner_microstep: 137.52 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 389 +[2025-05-01 22:02:58,676] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 71.62 | bwd_microstep: 139.14 | bwd_inner_microstep: 138.82 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-01 22:02:59,153] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.55 | bwd_microstep: 273.25 | bwd_inner_microstep: 273.23 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1896 +[2025-05-01 22:03:00,018] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 341.72 | bwd_microstep: 504.37 | bwd_inner_microstep: 504.35 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.31 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 345 +[2025-05-01 22:03:00,241] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 75.23 | bwd_microstep: 123.22 | bwd_inner_microstep: 123.09 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-01 22:03:00,716] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.90 | bwd_microstep: 272.86 | bwd_inner_microstep: 272.85 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-01 22:03:01,348] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.11 | bwd_microstep: 426.08 | bwd_inner_microstep: 426.06 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.31 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-01 22:03:02,181] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 294.33 | bwd_microstep: 504.29 | bwd_inner_microstep: 504.27 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.53 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 22:03:03,039] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 321.54 | bwd_microstep: 502.46 | bwd_inner_microstep: 502.44 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.47 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 22:03:03,894] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 320.38 | bwd_microstep: 502.65 | bwd_inner_microstep: 502.63 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.23 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 22:03:04,763] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 327.91 | bwd_microstep: 508.58 | bwd_inner_microstep: 508.56 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.75 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 22:03:05,632] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 330.11 | bwd_microstep: 508.54 | bwd_inner_microstep: 508.52 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.28 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 22:03:06,497] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 330.18 | bwd_microstep: 506.55 | bwd_inner_microstep: 506.53 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 22:03:07,358] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 331.79 | bwd_microstep: 496.45 | bwd_inner_microstep: 496.43 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.33 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 22:03:08,218] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 327.67 | bwd_microstep: 506.38 | bwd_inner_microstep: 506.36 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.48 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 924 +[2025-05-01 22:03:08,976] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.30 | optimizer_step: 17.31 +[2025-05-01 22:03:08,978] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 220.93 | bwd_microstep: 481.75 | bwd_inner_microstep: 241.88 | bwd_allreduce_microstep: 239.85 | step_microstep: 29.16 +[2025-05-01 22:03:08,980] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 3929.48 | bwd: 6394.25 | bwd_inner: 6153.67 | bwd_allreduce: 240.13 | step: 49.59 + 1%| | 101/8720 [20:02<41:04:09, 17.15s/it] {'loss': 3.1523, 'grad_norm': 10.398177146911621, 'learning_rate': 3.8549618320610685e-06, 'epoch': 0.12} + 1%| | 101/8720 [20:02<41:04:09, 17.15s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1926 +[2025-05-01 22:03:09,891] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 340.71 | bwd_microstep: 528.78 | bwd_inner_microstep: 528.77 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.31 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 388 +[2025-05-01 22:03:10,169] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 102.06 | bwd_microstep: 142.05 | bwd_inner_microstep: 142.03 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1910 +[2025-05-01 22:03:11,055] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 328.79 | bwd_microstep: 522.92 | bwd_inner_microstep: 522.90 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 873 +[2025-05-01 22:03:11,506] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 210.83 | bwd_microstep: 212.34 | bwd_inner_microstep: 212.14 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1886 +[2025-05-01 22:03:12,381] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 331.04 | bwd_microstep: 512.77 | bwd_inner_microstep: 512.75 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.22 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-01 22:03:13,257] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 334.77 | bwd_microstep: 513.74 | bwd_inner_microstep: 513.73 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 338 +[2025-05-01 22:03:13,540] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 114.70 | bwd_microstep: 127.16 | bwd_inner_microstep: 127.14 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-01 22:03:14,407] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 327.17 | bwd_microstep: 507.93 | bwd_inner_microstep: 507.91 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-01 22:03:15,268] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 329.43 | bwd_microstep: 495.69 | bwd_inner_microstep: 495.67 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1353 +[2025-05-01 22:03:15,973] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 296.04 | bwd_microstep: 376.46 | bwd_inner_microstep: 376.44 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-01 22:03:16,839] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 318.68 | bwd_microstep: 516.97 | bwd_inner_microstep: 516.95 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.31 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 22:03:17,698] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 311.21 | bwd_microstep: 514.58 | bwd_inner_microstep: 514.57 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.49 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 22:03:18,556] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 312.56 | bwd_microstep: 512.23 | bwd_inner_microstep: 512.21 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-01 22:03:19,409] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 318.52 | bwd_microstep: 501.96 | bwd_inner_microstep: 501.94 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 22:03:20,261] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 323.85 | bwd_microstep: 495.87 | bwd_inner_microstep: 495.85 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 22:03:21,398] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.29 | optimizer_step: 23.05 +[2025-05-01 22:03:21,400] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 325.43 | bwd_microstep: 749.80 | bwd_inner_microstep: 511.21 | bwd_allreduce_microstep: 238.58 | step_microstep: 32.58 +[2025-05-01 22:03:21,401] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4625.77 | bwd: 7231.26 | bwd_inner: 6992.23 | bwd_allreduce: 238.82 | step: 61.26 + 1%| | 102/8720 [20:14<37:39:48, 15.73s/it] {'loss': 2.8351, 'grad_norm': 8.270498275756836, 'learning_rate': 3.893129770992366e-06, 'epoch': 0.12} + 1%| | 102/8720 [20:14<37:39:48, 15.73s/it]dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1450 +[2025-05-01 22:03:22,095] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 235.89 | bwd_microstep: 422.77 | bwd_inner_microstep: 422.76 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-01 22:03:22,992] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 387.43 | bwd_microstep: 491.87 | bwd_inner_microstep: 491.85 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 349 +[2025-05-01 22:03:23,216] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 82.41 | bwd_microstep: 126.29 | bwd_inner_microstep: 126.27 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.48 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-01 22:03:24,076] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 317.90 | bwd_microstep: 511.16 | bwd_inner_microstep: 511.15 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.58 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 22:03:24,946] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 329.57 | bwd_microstep: 510.32 | bwd_inner_microstep: 510.30 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.52 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-01 22:03:25,819] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 331.03 | bwd_microstep: 514.48 | bwd_inner_microstep: 514.46 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 22:03:26,691] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 329.74 | bwd_microstep: 513.75 | bwd_inner_microstep: 513.74 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 836 +[2025-05-01 22:03:27,114] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.75 | bwd_microstep: 205.33 | bwd_inner_microstep: 205.13 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-01 22:03:27,984] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 327.52 | bwd_microstep: 503.68 | bwd_inner_microstep: 503.67 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.22 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 839 +[2025-05-01 22:03:28,413] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 177.73 | bwd_microstep: 216.47 | bwd_inner_microstep: 216.45 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 22:03:29,275] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 326.62 | bwd_microstep: 501.30 | bwd_inner_microstep: 501.28 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.18 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 835 +[2025-05-01 22:03:29,693] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.15 | bwd_microstep: 204.70 | bwd_inner_microstep: 204.50 | bwd_allreduce_microstep: 0.19 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 22:03:30,559] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 329.93 | bwd_microstep: 506.78 | bwd_inner_microstep: 506.77 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 831 +[2025-05-01 22:03:30,995] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 192.56 | bwd_microstep: 212.93 | bwd_inner_microstep: 212.91 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.33 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-01 22:03:31,855] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 318.98 | bwd_microstep: 509.82 | bwd_inner_microstep: 509.80 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-01 22:03:32,994] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.22 | optimizer_step: 18.74 +[2025-05-01 22:03:32,997] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 326.98 | bwd_microstep: 757.55 | bwd_inner_microstep: 518.20 | bwd_allreduce_microstep: 239.34 | step_microstep: 28.15 +[2025-05-01 22:03:32,998] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4393.13 | bwd: 6709.20 | bwd_inner: 6469.23 | bwd_allreduce: 239.41 | step: 47.47 + 1%| | 103/8720 [20:26<34:41:26, 14.49s/it] {'loss': 4.2011, 'grad_norm': 17.112030029296875, 'learning_rate': 3.931297709923664e-06, 'epoch': 0.12} + 1%| | 103/8720 [20:26<34:41:26, 14.49s/it]dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1375 +[2025-05-01 22:03:33,692] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 241.89 | bwd_microstep: 412.70 | bwd_inner_microstep: 412.62 | bwd_allreduce_microstep: 0.04 | step_microstep: 0.10 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 864 +[2025-05-01 22:03:34,141] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 169.02 | bwd_microstep: 265.86 | bwd_inner_microstep: 265.80 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.09 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1121 +[2025-05-01 22:03:34,645] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 192.45 | bwd_microstep: 294.46 | bwd_inner_microstep: 294.28 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1887 +[2025-05-01 22:03:35,539] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 394.96 | bwd_microstep: 484.15 | bwd_inner_microstep: 484.13 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-01 22:03:36,441] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 385.76 | bwd_microstep: 495.55 | bwd_inner_microstep: 495.53 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1357 +[2025-05-01 22:03:37,074] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 233.46 | bwd_microstep: 380.17 | bwd_inner_microstep: 380.15 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 22:03:37,945] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 332.44 | bwd_microstep: 513.71 | bwd_inner_microstep: 513.70 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 22:03:38,818] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 327.07 | bwd_microstep: 513.79 | bwd_inner_microstep: 513.77 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 22:03:39,693] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 334.08 | bwd_microstep: 511.47 | bwd_inner_microstep: 511.46 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 22:03:40,574] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 333.12 | bwd_microstep: 517.24 | bwd_inner_microstep: 517.22 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.33 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 319 +[2025-05-01 22:03:40,803] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.34 | bwd_microstep: 116.17 | bwd_inner_microstep: 115.84 | bwd_allreduce_microstep: 0.14 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 22:03:41,676] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 339.55 | bwd_microstep: 512.71 | bwd_inner_microstep: 512.69 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 321 +[2025-05-01 22:03:41,898] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 71.19 | bwd_microstep: 128.95 | bwd_inner_microstep: 128.93 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.32 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 22:03:42,772] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 330.59 | bwd_microstep: 513.46 | bwd_inner_microstep: 513.44 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 22:03:43,636] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 328.02 | bwd_microstep: 507.12 | bwd_inner_microstep: 507.11 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 22:03:44,765] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.22 | optimizer_step: 18.83 +[2025-05-01 22:03:44,767] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 330.97 | bwd_microstep: 742.85 | bwd_inner_microstep: 509.24 | bwd_allreduce_microstep: 233.60 | step_microstep: 28.37 +[2025-05-01 22:03:44,768] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4438.81 | bwd: 6910.45 | bwd_inner: 6676.01 | bwd_allreduce: 233.93 | step: 48.71 + 1%| | 104/8720 [20:38<32:43:54, 13.68s/it] {'loss': 3.8683, 'grad_norm': 17.879745483398438, 'learning_rate': 3.969465648854962e-06, 'epoch': 0.12} + 1%| | 104/8720 [20:38<32:43:54, 13.68s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1984 +[2025-05-01 22:03:45,701] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 352.23 | bwd_microstep: 539.25 | bwd_inner_microstep: 539.23 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.49 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 348 +[2025-05-01 22:03:45,939] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 100.49 | bwd_microstep: 109.34 | bwd_inner_microstep: 109.15 | bwd_allreduce_microstep: 0.09 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-01 22:03:46,817] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 361.60 | bwd_microstep: 486.83 | bwd_inner_microstep: 486.81 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1360 +[2025-05-01 22:03:47,523] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 310.99 | bwd_microstep: 366.91 | bwd_inner_microstep: 366.90 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.32 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-01 22:03:48,395] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 317.17 | bwd_microstep: 520.99 | bwd_inner_microstep: 520.97 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.28 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1361 +[2025-05-01 22:03:49,016] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 218.56 | bwd_microstep: 373.85 | bwd_inner_microstep: 373.57 | bwd_allreduce_microstep: 0.15 | step_microstep: 0.23 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-01 22:03:49,904] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 384.31 | bwd_microstep: 484.73 | bwd_inner_microstep: 484.71 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.28 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 845 +[2025-05-01 22:03:50,353] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 172.66 | bwd_microstep: 259.41 | bwd_inner_microstep: 259.15 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-01 22:03:51,253] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 381.03 | bwd_microstep: 499.41 | bwd_inner_microstep: 499.40 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-01 22:03:52,136] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 347.00 | bwd_microstep: 516.99 | bwd_inner_microstep: 516.97 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.52 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1089 +[2025-05-01 22:03:52,641] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 170.01 | bwd_microstep: 318.07 | bwd_inner_microstep: 317.85 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.19 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 325 +[2025-05-01 22:03:52,867] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 86.76 | bwd_microstep: 122.49 | bwd_inner_microstep: 122.47 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.33 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 22:03:53,724] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 324.34 | bwd_microstep: 502.41 | bwd_inner_microstep: 502.39 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.23 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 22:03:54,590] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 323.15 | bwd_microstep: 513.47 | bwd_inner_microstep: 513.45 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.60 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 22:03:55,458] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 329.49 | bwd_microstep: 508.92 | bwd_inner_microstep: 508.90 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.33 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1340 +[2025-05-01 22:03:56,452] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.28 | optimizer_step: 30.12 +[2025-05-01 22:03:56,453] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 243.48 | bwd_microstep: 689.47 | bwd_inner_microstep: 411.01 | bwd_allreduce_microstep: 278.36 | step_microstep: 37.88 +[2025-05-01 22:03:56,454] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4423.19 | bwd: 6812.71 | bwd_inner: 6532.96 | bwd_allreduce: 278.92 | step: 54.12 + 1%| | 105/8720 [20:49<31:17:54, 13.08s/it] {'loss': 3.5895, 'grad_norm': 18.57619285583496, 'learning_rate': 4.0076335877862595e-06, 'epoch': 0.12} + 1%| | 105/8720 [20:49<31:17:54, 13.08s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1909 +[2025-05-01 22:03:57,364] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 398.56 | bwd_microstep: 488.81 | bwd_inner_microstep: 488.79 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1886 +[2025-05-01 22:03:58,266] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 379.49 | bwd_microstep: 502.51 | bwd_inner_microstep: 502.49 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.31 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-01 22:03:59,144] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 341.85 | bwd_microstep: 517.49 | bwd_inner_microstep: 517.47 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-01 22:04:00,007] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 318.64 | bwd_microstep: 520.76 | bwd_inner_microstep: 520.74 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1883 +[2025-05-01 22:04:00,887] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 322.80 | bwd_microstep: 523.51 | bwd_inner_microstep: 523.49 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 338 +[2025-05-01 22:04:01,121] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 72.67 | bwd_microstep: 129.87 | bwd_inner_microstep: 129.86 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-01 22:04:02,003] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 331.70 | bwd_microstep: 516.79 | bwd_inner_microstep: 516.77 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1347 +[2025-05-01 22:04:02,685] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 243.15 | bwd_microstep: 412.58 | bwd_inner_microstep: 412.56 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 22:04:03,572] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 362.60 | bwd_microstep: 506.47 | bwd_inner_microstep: 506.45 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.68 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-01 22:04:04,434] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 320.41 | bwd_microstep: 521.32 | bwd_inner_microstep: 521.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.31 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 22:04:05,302] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 320.24 | bwd_microstep: 514.81 | bwd_inner_microstep: 514.79 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 22:04:06,168] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 314.94 | bwd_microstep: 518.56 | bwd_inner_microstep: 518.55 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.45 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 318 +[2025-05-01 22:04:06,405] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 80.96 | bwd_microstep: 126.72 | bwd_inner_microstep: 126.70 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 827 +[2025-05-01 22:04:06,849] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 208.33 | bwd_microstep: 206.37 | bwd_inner_microstep: 206.14 | bwd_allreduce_microstep: 0.22 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-01 22:04:07,724] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 322.39 | bwd_microstep: 518.34 | bwd_inner_microstep: 518.32 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.33 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 843 +[2025-05-01 22:04:08,518] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.29 | optimizer_step: 18.69 +[2025-05-01 22:04:08,521] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 182.61 | bwd_microstep: 552.79 | bwd_inner_microstep: 228.72 | bwd_allreduce_microstep: 324.06 | step_microstep: 28.15 +[2025-05-01 22:04:08,522] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4521.30 | bwd: 7077.70 | bwd_inner: 6753.15 | bwd_allreduce: 324.34 | step: 53.91 + 1%| | 106/8720 [21:02<30:34:12, 12.78s/it] {'loss': 2.7331, 'grad_norm': 12.227348327636719, 'learning_rate': 4.045801526717557e-06, 'epoch': 0.12} + 1%| | 106/8720 [21:02<30:34:12, 12.78s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2054 +[2025-05-01 22:04:09,466] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 352.55 | bwd_microstep: 564.62 | bwd_inner_microstep: 564.60 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.88 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 337 +[2025-05-01 22:04:09,701] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 89.55 | bwd_microstep: 125.79 | bwd_inner_microstep: 125.77 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.33 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-01 22:04:10,573] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 324.75 | bwd_microstep: 515.35 | bwd_inner_microstep: 515.34 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-01 22:04:11,445] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 330.87 | bwd_microstep: 511.81 | bwd_inner_microstep: 511.79 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 837 +[2025-05-01 22:04:11,871] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 191.38 | bwd_microstep: 205.86 | bwd_inner_microstep: 205.66 | bwd_allreduce_microstep: 0.18 | step_microstep: 0.19 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1350 +[2025-05-01 22:04:12,547] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 232.99 | bwd_microstep: 413.13 | bwd_inner_microstep: 413.11 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-01 22:04:13,443] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 372.39 | bwd_microstep: 503.76 | bwd_inner_microstep: 503.74 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.93 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 22:04:14,315] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 330.77 | bwd_microstep: 520.31 | bwd_inner_microstep: 520.29 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.51 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-01 22:04:15,186] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 320.79 | bwd_microstep: 521.10 | bwd_inner_microstep: 521.08 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.31 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 22:04:16,050] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 315.24 | bwd_microstep: 514.78 | bwd_inner_microstep: 514.76 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.28 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-01 22:04:16,917] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 312.40 | bwd_microstep: 519.87 | bwd_inner_microstep: 519.85 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.31 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 22:04:17,778] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 312.69 | bwd_microstep: 515.03 | bwd_inner_microstep: 515.02 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.28 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 22:04:18,634] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 316.83 | bwd_microstep: 505.31 | bwd_inner_microstep: 505.29 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.31 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-01 22:04:19,493] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 329.31 | bwd_microstep: 495.33 | bwd_inner_microstep: 495.31 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.33 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 22:04:20,352] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 325.31 | bwd_microstep: 502.09 | bwd_inner_microstep: 502.07 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 22:04:21,484] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.22 | optimizer_step: 18.82 +[2025-05-01 22:04:21,486] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 329.97 | bwd_microstep: 749.37 | bwd_inner_microstep: 513.41 | bwd_allreduce_microstep: 235.95 | step_microstep: 28.20 +[2025-05-01 22:04:21,487] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4787.72 | bwd: 7683.68 | bwd_inner: 7447.11 | bwd_allreduce: 236.20 | step: 51.63 + 1%| | 107/8720 [21:15<30:42:07, 12.83s/it] {'loss': 3.2821, 'grad_norm': 18.8054141998291, 'learning_rate': 4.083969465648855e-06, 'epoch': 0.12} + 1%| | 107/8720 [21:15<30:42:07, 12.83s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2142 +[2025-05-01 22:04:22,501] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 368.88 | bwd_microstep: 601.21 | bwd_inner_microstep: 601.19 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.53 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1925 +[2025-05-01 22:04:23,407] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 325.17 | bwd_microstep: 547.21 | bwd_inner_microstep: 547.19 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.32 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-01 22:04:24,269] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 313.44 | bwd_microstep: 514.46 | bwd_inner_microstep: 514.45 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1883 +[2025-05-01 22:04:25,130] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 308.92 | bwd_microstep: 517.75 | bwd_inner_microstep: 517.74 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1887 +[2025-05-01 22:04:26,002] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 314.28 | bwd_microstep: 523.29 | bwd_inner_microstep: 523.27 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.46 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-01 22:04:26,870] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 319.43 | bwd_microstep: 513.64 | bwd_inner_microstep: 513.62 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-01 22:04:27,729] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 325.29 | bwd_microstep: 500.70 | bwd_inner_microstep: 500.68 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-01 22:04:28,590] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 321.56 | bwd_microstep: 506.54 | bwd_inner_microstep: 506.52 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-01 22:04:29,464] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 327.81 | bwd_microstep: 515.97 | bwd_inner_microstep: 515.96 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-01 22:04:30,341] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 330.72 | bwd_microstep: 515.64 | bwd_inner_microstep: 515.62 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.52 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-01 22:04:31,215] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 332.91 | bwd_microstep: 512.92 | bwd_inner_microstep: 512.90 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 22:04:32,082] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 332.15 | bwd_microstep: 504.56 | bwd_inner_microstep: 504.54 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1349 +[2025-05-01 22:04:32,773] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 245.59 | bwd_microstep: 416.25 | bwd_inner_microstep: 416.23 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-01 22:04:33,661] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 356.37 | bwd_microstep: 511.27 | bwd_inner_microstep: 511.25 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 22:04:34,513] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 314.40 | bwd_microstep: 515.51 | bwd_inner_microstep: 515.49 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.33 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1086 +[2025-05-01 22:04:35,366] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.81 | optimizer_step: 30.29 +[2025-05-01 22:04:35,366] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 160.47 | bwd_microstep: 624.21 | bwd_inner_microstep: 345.82 | bwd_allreduce_microstep: 278.38 | step_microstep: 38.86 +[2025-05-01 22:04:35,368] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4997.35 | bwd: 8341.14 | bwd_inner: 8062.50 | bwd_allreduce: 278.44 | step: 65.71 + 1%| | 108/8720 [21:28<31:26:53, 13.15s/it] {'loss': 2.8647, 'grad_norm': 10.90075397491455, 'learning_rate': 4.122137404580153e-06, 'epoch': 0.12} + 1%| | 108/8720 [21:28<31:26:53, 13.15s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1917 +[2025-05-01 22:04:36,279] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 390.31 | bwd_microstep: 498.53 | bwd_inner_microstep: 498.52 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1362 +[2025-05-01 22:04:36,922] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 243.38 | bwd_microstep: 380.64 | bwd_inner_microstep: 380.62 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-01 22:04:37,799] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 332.38 | bwd_microstep: 512.38 | bwd_inner_microstep: 512.36 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-01 22:04:38,670] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 327.17 | bwd_microstep: 515.26 | bwd_inner_microstep: 515.24 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.49 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-01 22:04:39,547] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 330.31 | bwd_microstep: 516.64 | bwd_inner_microstep: 516.63 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.26 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-01 22:04:40,422] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 330.04 | bwd_microstep: 513.81 | bwd_inner_microstep: 513.79 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.16 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 333 +[2025-05-01 22:04:40,653] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 99.49 | bwd_microstep: 106.72 | bwd_inner_microstep: 106.59 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-01 22:04:41,545] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 382.80 | bwd_microstep: 493.95 | bwd_inner_microstep: 493.93 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-01 22:04:42,430] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 351.49 | bwd_microstep: 512.44 | bwd_inner_microstep: 512.42 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.47 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1096 +[2025-05-01 22:04:42,937] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 170.90 | bwd_microstep: 319.34 | bwd_inner_microstep: 319.21 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 22:04:43,826] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 371.35 | bwd_microstep: 498.50 | bwd_inner_microstep: 498.48 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.97 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 22:04:44,706] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 341.21 | bwd_microstep: 512.33 | bwd_inner_microstep: 512.32 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 22:04:45,569] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 319.57 | bwd_microstep: 518.48 | bwd_inner_microstep: 518.46 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 22:04:46,432] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 317.42 | bwd_microstep: 512.26 | bwd_inner_microstep: 512.24 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.33 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 22:04:47,278] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 306.55 | bwd_microstep: 504.82 | bwd_inner_microstep: 504.80 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1131 +[2025-05-01 22:04:48,069] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.18 | optimizer_step: 18.76 +[2025-05-01 22:04:48,071] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 166.25 | bwd_microstep: 568.80 | bwd_inner_microstep: 358.25 | bwd_allreduce_microstep: 210.53 | step_microstep: 28.11 +[2025-05-01 22:04:48,072] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4780.50 | bwd: 7484.93 | bwd_inner: 7273.93 | bwd_allreduce: 210.69 | step: 48.65 + 1%|▏ | 109/8720 [21:41<31:07:46, 13.01s/it] {'loss': 4.3374, 'grad_norm': 18.473133087158203, 'learning_rate': 4.1603053435114506e-06, 'epoch': 0.12} + 1%|▏ | 109/8720 [21:41<31:07:46, 13.01s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1974 +[2025-05-01 22:04:49,011] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 341.18 | bwd_microstep: 556.66 | bwd_inner_microstep: 556.64 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1895 +[2025-05-01 22:04:49,878] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 319.89 | bwd_microstep: 526.08 | bwd_inner_microstep: 526.07 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.50 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-01 22:04:50,752] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 321.52 | bwd_microstep: 521.70 | bwd_inner_microstep: 521.68 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-01 22:04:51,606] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 306.62 | bwd_microstep: 514.44 | bwd_inner_microstep: 514.42 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.49 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-01 22:04:52,469] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 312.60 | bwd_microstep: 515.64 | bwd_inner_microstep: 515.62 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.31 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-01 22:04:53,331] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 315.80 | bwd_microstep: 512.30 | bwd_inner_microstep: 512.28 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.52 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 22:04:54,200] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 324.24 | bwd_microstep: 504.25 | bwd_inner_microstep: 504.23 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 843 +[2025-05-01 22:04:54,645] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 162.63 | bwd_microstep: 250.16 | bwd_inner_microstep: 250.14 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 22:04:55,497] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 321.24 | bwd_microstep: 499.20 | bwd_inner_microstep: 499.19 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.43 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 22:04:56,356] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 324.46 | bwd_microstep: 504.88 | bwd_inner_microstep: 504.86 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 22:04:57,224] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 331.04 | bwd_microstep: 506.56 | bwd_inner_microstep: 506.54 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 22:04:58,101] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 333.16 | bwd_microstep: 514.34 | bwd_inner_microstep: 514.31 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.78 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 319 +[2025-05-01 22:04:58,398] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 104.40 | bwd_microstep: 163.15 | bwd_inner_microstep: 163.13 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 22:04:59,256] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 330.18 | bwd_microstep: 496.26 | bwd_inner_microstep: 496.24 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-01 22:05:00,115] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 341.79 | bwd_microstep: 485.04 | bwd_inner_microstep: 485.02 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 22:05:01,310] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.21 | optimizer_step: 22.31 +[2025-05-01 22:05:01,312] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 365.95 | bwd_microstep: 772.74 | bwd_inner_microstep: 483.44 | bwd_allreduce_microstep: 289.26 | step_microstep: 29.97 +[2025-05-01 22:05:01,313] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4856.67 | bwd: 7843.41 | bwd_inner: 7553.84 | bwd_allreduce: 289.34 | step: 59.64 + 1%|▏ | 110/8720 [21:54<31:17:18, 13.08s/it] {'loss': 3.9771, 'grad_norm': 14.656530380249023, 'learning_rate': 4.198473282442748e-06, 'epoch': 0.13} + 1%|▏ | 110/8720 [21:54<31:17:18, 13.08s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 3522 +[2025-05-01 22:05:02,822] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 530.48 | bwd_microstep: 943.84 | bwd_inner_microstep: 943.82 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1925 +[2025-05-01 22:05:03,733] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 341.90 | bwd_microstep: 534.37 | bwd_inner_microstep: 534.35 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.33 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 388 +[2025-05-01 22:05:03,997] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 102.62 | bwd_microstep: 132.05 | bwd_inner_microstep: 132.03 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 388 +[2025-05-01 22:05:04,277] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 99.86 | bwd_microstep: 152.21 | bwd_inner_microstep: 152.03 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-01 22:05:05,161] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 346.33 | bwd_microstep: 518.30 | bwd_inner_microstep: 518.28 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.53 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-01 22:05:06,027] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 322.27 | bwd_microstep: 525.17 | bwd_inner_microstep: 525.15 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-01 22:05:06,899] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 322.55 | bwd_microstep: 515.69 | bwd_inner_microstep: 515.67 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.31 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-01 22:05:07,756] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 310.22 | bwd_microstep: 514.68 | bwd_inner_microstep: 514.66 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-01 22:05:08,619] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 318.15 | bwd_microstep: 511.22 | bwd_inner_microstep: 511.21 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-01 22:05:09,479] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 317.82 | bwd_microstep: 507.45 | bwd_inner_microstep: 507.43 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 22:05:10,335] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 326.68 | bwd_microstep: 497.80 | bwd_inner_microstep: 497.78 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 22:05:11,195] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 326.50 | bwd_microstep: 502.01 | bwd_inner_microstep: 502.00 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 22:05:12,060] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 331.44 | bwd_microstep: 504.12 | bwd_inner_microstep: 504.11 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.30 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 830 +[2025-05-01 22:05:12,492] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 192.58 | bwd_microstep: 210.18 | bwd_inner_microstep: 207.82 | bwd_allreduce_microstep: 2.34 | step_microstep: 2.30 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 437 +[2025-05-01 22:05:12,794] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 116.69 | bwd_microstep: 146.76 | bwd_inner_microstep: 146.74 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-01 22:05:13,967] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.25 | optimizer_step: 18.90 +[2025-05-01 22:05:13,970] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 321.13 | bwd_microstep: 793.45 | bwd_inner_microstep: 524.54 | bwd_allreduce_microstep: 268.90 | step_microstep: 28.55 +[2025-05-01 22:05:13,971] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4627.20 | bwd: 7509.32 | bwd_inner: 7237.70 | bwd_allreduce: 271.35 | step: 59.34 + 1%|▏ | 111/8720 [22:07<30:58:49, 12.96s/it] {'loss': 2.4813, 'grad_norm': 12.604723930358887, 'learning_rate': 4.236641221374046e-06, 'epoch': 0.13} + 1%|▏ | 111/8720 [22:07<30:58:49, 12.96s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1954 +[2025-05-01 22:05:14,892] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 354.29 | bwd_microstep: 528.34 | bwd_inner_microstep: 528.32 | bwd_allreduce_microstep: 0.00 | step_microstep: 4.68 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1890 +[2025-05-01 22:05:15,767] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 327.11 | bwd_microstep: 516.05 | bwd_inner_microstep: 516.03 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-01 22:05:16,640] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 333.60 | bwd_microstep: 513.13 | bwd_inner_microstep: 513.12 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-01 22:05:17,505] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 321.76 | bwd_microstep: 514.09 | bwd_inner_microstep: 511.57 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 22:05:18,384] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 333.98 | bwd_microstep: 512.73 | bwd_inner_microstep: 512.71 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-01 22:05:19,259] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 331.38 | bwd_microstep: 513.88 | bwd_inner_microstep: 513.86 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.53 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 22:05:20,135] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 335.33 | bwd_microstep: 509.70 | bwd_inner_microstep: 509.69 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 22:05:21,008] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 332.68 | bwd_microstep: 513.60 | bwd_inner_microstep: 513.58 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.22 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-01 22:05:21,882] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 328.16 | bwd_microstep: 515.05 | bwd_inner_microstep: 515.04 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-01 22:05:22,760] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 329.78 | bwd_microstep: 517.39 | bwd_inner_microstep: 517.38 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-01 22:05:23,637] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 332.67 | bwd_microstep: 515.38 | bwd_inner_microstep: 515.36 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-01 22:05:24,511] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 332.59 | bwd_microstep: 513.87 | bwd_inner_microstep: 513.86 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 22:05:25,386] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 332.04 | bwd_microstep: 515.37 | bwd_inner_microstep: 515.36 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.72 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 22:05:26,252] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 321.52 | bwd_microstep: 514.77 | bwd_inner_microstep: 514.75 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 830 +[2025-05-01 22:05:26,688] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 194.34 | bwd_microstep: 212.24 | bwd_inner_microstep: 212.22 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.31 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-01 22:05:27,814] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.31 | optimizer_step: 18.85 +[2025-05-01 22:05:27,816] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 325.02 | bwd_microstep: 743.04 | bwd_inner_microstep: 509.54 | bwd_allreduce_microstep: 233.48 | step_microstep: 28.33 +[2025-05-01 22:05:27,817] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 5166.24 | bwd: 8168.64 | bwd_inner: 7932.38 | bwd_allreduce: 233.55 | step: 47.89 + 1%|▏ | 112/8720 [22:21<31:37:00, 13.22s/it] {'loss': 3.6927, 'grad_norm': 16.026527404785156, 'learning_rate': 4.274809160305344e-06, 'epoch': 0.13} + 1%|▏ | 112/8720 [22:21<31:37:00, 13.22s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1946 +[2025-05-01 22:05:28,741] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 352.12 | bwd_microstep: 527.16 | bwd_inner_microstep: 527.14 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1914 +[2025-05-01 22:05:29,619] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 335.61 | bwd_microstep: 509.25 | bwd_inner_microstep: 509.23 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1895 +[2025-05-01 22:05:30,491] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 322.47 | bwd_microstep: 516.89 | bwd_inner_microstep: 516.88 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1893 +[2025-05-01 22:05:31,368] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 333.17 | bwd_microstep: 516.41 | bwd_inner_microstep: 516.39 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-01 22:05:32,241] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 332.93 | bwd_microstep: 512.72 | bwd_inner_microstep: 512.70 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.22 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 334 +[2025-05-01 22:05:32,489] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 100.09 | bwd_microstep: 122.28 | bwd_inner_microstep: 122.16 | bwd_allreduce_microstep: 0.04 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-01 22:05:33,388] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 398.70 | bwd_microstep: 484.50 | bwd_inner_microstep: 484.47 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.19 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1109 +[2025-05-01 22:05:33,895] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 208.42 | bwd_microstep: 279.90 | bwd_inner_microstep: 279.85 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 22:05:34,775] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 368.41 | bwd_microstep: 482.64 | bwd_inner_microstep: 482.63 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-01 22:05:35,672] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 397.18 | bwd_microstep: 484.28 | bwd_inner_microstep: 484.26 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-01 22:05:36,571] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 378.51 | bwd_microstep: 500.27 | bwd_inner_microstep: 500.25 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.91 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 22:05:37,450] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 345.15 | bwd_microstep: 513.98 | bwd_inner_microstep: 513.97 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 22:05:38,307] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 320.17 | bwd_microstep: 513.47 | bwd_inner_microstep: 513.45 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.32 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 22:05:39,169] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 317.13 | bwd_microstep: 509.25 | bwd_inner_microstep: 509.23 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.32 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 22:05:40,033] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 317.68 | bwd_microstep: 511.88 | bwd_inner_microstep: 511.86 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.51 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 344 +[2025-05-01 22:05:40,609] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.22 | optimizer_step: 18.80 +[2025-05-01 22:05:40,612] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 90.08 | bwd_microstep: 429.95 | bwd_inner_microstep: 160.78 | bwd_allreduce_microstep: 269.15 | step_microstep: 27.06 +[2025-05-01 22:05:40,613] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4917.70 | bwd: 7414.85 | bwd_inner: 7145.28 | bwd_allreduce: 269.27 | step: 43.06 + 1%|▏ | 113/8720 [22:34<31:18:22, 13.09s/it] {'loss': 2.2276, 'grad_norm': 9.476103782653809, 'learning_rate': 4.312977099236642e-06, 'epoch': 0.13} + 1%|▏ | 113/8720 [22:34<31:18:22, 13.09s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1949 +[2025-05-01 22:05:41,543] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 335.28 | bwd_microstep: 552.62 | bwd_inner_microstep: 552.60 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1934 +[2025-05-01 22:05:42,462] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 335.22 | bwd_microstep: 550.26 | bwd_inner_microstep: 550.24 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.31 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-01 22:05:43,337] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 327.27 | bwd_microstep: 513.08 | bwd_inner_microstep: 513.06 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.31 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-01 22:05:44,211] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 317.09 | bwd_microstep: 522.77 | bwd_inner_microstep: 522.75 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-01 22:05:45,090] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 318.39 | bwd_microstep: 526.80 | bwd_inner_microstep: 526.78 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-01 22:05:45,963] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 314.83 | bwd_microstep: 525.57 | bwd_inner_microstep: 525.55 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1359 +[2025-05-01 22:05:46,589] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 227.30 | bwd_microstep: 367.09 | bwd_inner_microstep: 367.07 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 22:05:47,458] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 352.04 | bwd_microstep: 484.39 | bwd_inner_microstep: 484.37 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 836 +[2025-05-01 22:05:47,886] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 197.18 | bwd_microstep: 205.56 | bwd_inner_microstep: 205.22 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-01 22:05:48,768] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 371.07 | bwd_microstep: 484.97 | bwd_inner_microstep: 484.90 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.28 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 22:05:49,662] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 394.01 | bwd_microstep: 483.35 | bwd_inner_microstep: 483.33 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 22:05:50,559] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 388.52 | bwd_microstep: 492.39 | bwd_inner_microstep: 492.38 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 322 +[2025-05-01 22:05:50,817] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 81.02 | bwd_microstep: 160.13 | bwd_inner_microstep: 160.11 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 22:05:51,677] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 311.80 | bwd_microstep: 515.08 | bwd_inner_microstep: 515.06 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.28 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-01 22:05:52,537] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 312.90 | bwd_microstep: 512.31 | bwd_inner_microstep: 512.29 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.45 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 22:05:53,660] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.54 | optimizer_step: 18.49 +[2025-05-01 22:05:53,661] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 329.42 | bwd_microstep: 734.82 | bwd_inner_microstep: 505.12 | bwd_allreduce_microstep: 229.68 | step_microstep: 28.23 +[2025-05-01 22:05:53,662] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4913.29 | bwd: 7631.22 | bwd_inner: 7400.92 | bwd_allreduce: 229.90 | step: 52.29 + 1%|▏ | 114/8720 [22:47<31:16:14, 13.08s/it] {'loss': 3.7348, 'grad_norm': 13.295928001403809, 'learning_rate': 4.351145038167939e-06, 'epoch': 0.13} + 1%|▏ | 114/8720 [22:47<31:16:14, 13.08s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1894 +[2025-05-01 22:05:54,540] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 334.71 | bwd_microstep: 502.38 | bwd_inner_microstep: 502.37 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.19 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1105 +[2025-05-01 22:05:55,098] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 213.20 | bwd_microstep: 317.96 | bwd_inner_microstep: 317.94 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.45 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-01 22:05:55,970] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 316.44 | bwd_microstep: 521.22 | bwd_inner_microstep: 521.21 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-01 22:05:56,835] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 309.69 | bwd_microstep: 521.63 | bwd_inner_microstep: 521.61 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.32 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-01 22:05:57,707] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 315.30 | bwd_microstep: 522.54 | bwd_inner_microstep: 522.52 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.28 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-01 22:05:58,564] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 315.84 | bwd_microstep: 507.67 | bwd_inner_microstep: 507.66 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1355 +[2025-05-01 22:05:59,214] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 221.79 | bwd_microstep: 398.07 | bwd_inner_microstep: 397.87 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-01 22:06:00,107] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 391.26 | bwd_microstep: 485.73 | bwd_inner_microstep: 485.71 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 22:06:00,997] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 368.76 | bwd_microstep: 503.53 | bwd_inner_microstep: 503.51 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.60 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 22:06:01,856] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 325.16 | bwd_microstep: 514.32 | bwd_inner_microstep: 514.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.48 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 22:06:02,723] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 316.37 | bwd_microstep: 518.43 | bwd_inner_microstep: 518.41 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.28 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 22:06:03,579] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 310.21 | bwd_microstep: 514.02 | bwd_inner_microstep: 514.01 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 835 +[2025-05-01 22:06:04,004] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 131.56 | bwd_microstep: 261.01 | bwd_inner_microstep: 260.99 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.51 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 22:06:04,874] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 317.07 | bwd_microstep: 518.63 | bwd_inner_microstep: 518.61 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.50 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2141 +[2025-05-01 22:06:05,855] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 341.58 | bwd_microstep: 607.86 | bwd_inner_microstep: 607.84 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1886 +[2025-05-01 22:06:06,979] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.43 | optimizer_step: 18.48 +[2025-05-01 22:06:06,981] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 321.28 | bwd_microstep: 755.10 | bwd_inner_microstep: 522.96 | bwd_allreduce_microstep: 232.12 | step_microstep: 28.32 +[2025-05-01 22:06:06,982] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4850.19 | bwd: 7970.12 | bwd_inner: 7737.54 | bwd_allreduce: 232.30 | step: 55.44 + 1%|▏ | 115/8720 [23:00<31:26:17, 13.15s/it] {'loss': 3.3521, 'grad_norm': 11.994383811950684, 'learning_rate': 4.389312977099237e-06, 'epoch': 0.13} + 1%|▏ | 115/8720 [23:00<31:26:17, 13.15s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1921 +[2025-05-01 22:06:07,901] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 334.61 | bwd_microstep: 542.00 | bwd_inner_microstep: 541.98 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1918 +[2025-05-01 22:06:08,788] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 327.34 | bwd_microstep: 527.97 | bwd_inner_microstep: 527.96 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1913 +[2025-05-01 22:06:09,663] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 322.49 | bwd_microstep: 521.30 | bwd_inner_microstep: 521.28 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.50 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1112 +[2025-05-01 22:06:10,201] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 161.77 | bwd_microstep: 345.59 | bwd_inner_microstep: 345.31 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-01 22:06:11,089] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 353.91 | bwd_microstep: 514.73 | bwd_inner_microstep: 514.71 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.65 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-01 22:06:11,958] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 325.06 | bwd_microstep: 524.89 | bwd_inner_microstep: 524.87 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.28 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-01 22:06:12,824] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 322.05 | bwd_microstep: 510.57 | bwd_inner_microstep: 510.55 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.33 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-01 22:06:13,693] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 315.58 | bwd_microstep: 517.32 | bwd_inner_microstep: 517.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-01 22:06:14,561] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 313.03 | bwd_microstep: 520.50 | bwd_inner_microstep: 520.48 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.51 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-01 22:06:15,423] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 313.61 | bwd_microstep: 516.61 | bwd_inner_microstep: 516.59 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-01 22:06:16,285] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 322.82 | bwd_microstep: 505.91 | bwd_inner_microstep: 505.89 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-01 22:06:17,141] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 324.00 | bwd_microstep: 499.98 | bwd_inner_microstep: 499.96 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-01 22:06:18,016] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 328.83 | bwd_microstep: 515.10 | bwd_inner_microstep: 515.08 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-01 22:06:18,886] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 327.05 | bwd_microstep: 514.87 | bwd_inner_microstep: 514.85 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.96 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-01 22:06:19,760] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 332.42 | bwd_microstep: 513.42 | bwd_inner_microstep: 513.40 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.16 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 22:06:20,893] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.25 | optimizer_step: 18.76 +[2025-05-01 22:06:20,896] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 332.14 | bwd_microstep: 747.47 | bwd_inner_microstep: 513.11 | bwd_allreduce_microstep: 234.12 | step_microstep: 28.20 +[2025-05-01 22:06:20,897] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 5056.68 | bwd: 8338.24 | bwd_inner: 8103.66 | bwd_allreduce: 234.26 | step: 52.79 + 1%|▏ | 116/8720 [23:14<31:58:51, 13.38s/it] {'loss': 2.4111, 'grad_norm': 8.103692054748535, 'learning_rate': 4.427480916030535e-06, 'epoch': 0.13} + 1%|▏ | 116/8720 [23:14<31:58:51, 13.38s/it]dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 993 +[2025-05-01 22:06:21,410] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 201.24 | bwd_microstep: 271.98 | bwd_inner_microstep: 271.96 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1915 +[2025-05-01 22:06:22,286] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 320.71 | bwd_microstep: 522.98 | bwd_inner_microstep: 522.96 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 378 +[2025-05-01 22:06:22,535] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 98.48 | bwd_microstep: 120.05 | bwd_inner_microstep: 120.03 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-01 22:06:23,395] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 326.42 | bwd_microstep: 501.86 | bwd_inner_microstep: 501.84 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 22:06:24,267] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 342.02 | bwd_microstep: 495.41 | bwd_inner_microstep: 495.40 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.32 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 330 +[2025-05-01 22:06:24,536] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 100.61 | bwd_microstep: 138.52 | bwd_inner_microstep: 138.51 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.33 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 22:06:25,403] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 323.90 | bwd_microstep: 520.31 | bwd_inner_microstep: 520.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.52 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-01 22:06:26,274] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 320.39 | bwd_microstep: 517.71 | bwd_inner_microstep: 517.69 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 22:06:27,140] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 316.10 | bwd_microstep: 515.51 | bwd_inner_microstep: 515.49 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-01 22:06:28,015] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 316.98 | bwd_microstep: 524.54 | bwd_inner_microstep: 524.52 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 22:06:28,882] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 315.09 | bwd_microstep: 518.21 | bwd_inner_microstep: 518.19 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.31 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 22:06:29,756] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 320.37 | bwd_microstep: 519.54 | bwd_inner_microstep: 519.52 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.33 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 22:06:30,621] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 312.07 | bwd_microstep: 518.49 | bwd_inner_microstep: 518.47 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.32 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 22:06:31,475] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 313.90 | bwd_microstep: 505.63 | bwd_inner_microstep: 505.61 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 828 +[2025-05-01 22:06:31,914] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 156.54 | bwd_microstep: 249.40 | bwd_inner_microstep: 249.38 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.50 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1214 +[2025-05-01 22:06:32,819] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 3.10 | optimizer_step: 26.33 +[2025-05-01 22:06:32,819] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 175.00 | bwd_microstep: 668.01 | bwd_inner_microstep: 380.06 | bwd_allreduce_microstep: 287.07 | step_microstep: 34.74 +[2025-05-01 22:06:32,820] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4259.81 | bwd: 7108.16 | bwd_inner: 6820.77 | bwd_allreduce: 287.16 | step: 70.14 + 1%|▏ | 117/8720 [23:26<30:55:51, 12.94s/it] {'loss': 3.6294, 'grad_norm': 15.264835357666016, 'learning_rate': 4.465648854961833e-06, 'epoch': 0.13} + 1%|▏ | 117/8720 [23:26<30:55:51, 12.94s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 366 +[2025-05-01 22:06:33,076] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 98.64 | bwd_microstep: 134.01 | bwd_inner_microstep: 133.99 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1369 +[2025-05-01 22:06:33,702] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 221.96 | bwd_microstep: 376.43 | bwd_inner_microstep: 376.33 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.11 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 864 +[2025-05-01 22:06:34,147] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 205.87 | bwd_microstep: 224.65 | bwd_inner_microstep: 224.33 | bwd_allreduce_microstep: 0.14 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-01 22:06:35,032] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 368.61 | bwd_microstep: 484.88 | bwd_inner_microstep: 484.86 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.15 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 853 +[2025-05-01 22:06:35,478] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 193.11 | bwd_microstep: 238.58 | bwd_inner_microstep: 238.32 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-01 22:06:36,378] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 387.84 | bwd_microstep: 493.00 | bwd_inner_microstep: 492.99 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 22:06:37,267] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 363.89 | bwd_microstep: 506.57 | bwd_inner_microstep: 506.55 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.67 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-01 22:06:38,131] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 324.91 | bwd_microstep: 518.27 | bwd_inner_microstep: 518.25 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.54 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1356 +[2025-05-01 22:06:38,753] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 226.87 | bwd_microstep: 364.10 | bwd_inner_microstep: 364.08 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 22:06:39,625] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 332.46 | bwd_microstep: 505.14 | bwd_inner_microstep: 505.12 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 22:06:40,487] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 339.44 | bwd_microstep: 488.45 | bwd_inner_microstep: 488.43 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.48 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 22:06:41,358] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 355.28 | bwd_microstep: 483.49 | bwd_inner_microstep: 483.48 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 22:06:42,234] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 361.52 | bwd_microstep: 480.53 | bwd_inner_microstep: 480.47 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-01 22:06:43,128] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 394.89 | bwd_microstep: 482.33 | bwd_inner_microstep: 482.31 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 22:06:44,030] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 386.91 | bwd_microstep: 494.30 | bwd_inner_microstep: 494.28 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1849 +[2025-05-01 22:06:45,105] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.13 | optimizer_step: 18.96 +[2025-05-01 22:06:45,108] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 344.56 | bwd_microstep: 688.74 | bwd_inner_microstep: 512.30 | bwd_allreduce_microstep: 176.42 | step_microstep: 27.52 +[2025-05-01 22:06:45,109] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4906.62 | bwd: 6963.54 | bwd_inner: 6785.97 | bwd_allreduce: 176.83 | step: 41.11 + 1%|▏ | 118/8720 [23:38<30:27:25, 12.75s/it] {'loss': 2.6714, 'grad_norm': 17.025197982788086, 'learning_rate': 4.5038167938931296e-06, 'epoch': 0.14} + 1%|▏ | 118/8720 [23:38<30:27:25, 12.75s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1883 +[2025-05-01 22:06:45,593] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.16 | bwd_microstep: 274.12 | bwd_inner_microstep: 274.11 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-01 22:06:46,176] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 198.31 | bwd_microstep: 369.00 | bwd_inner_microstep: 368.99 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-01 22:06:47,065] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 358.30 | bwd_microstep: 511.52 | bwd_inner_microstep: 511.51 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.62 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1368 +[2025-05-01 22:06:47,683] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 224.16 | bwd_microstep: 374.75 | bwd_inner_microstep: 374.73 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.33 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-01 22:06:48,552] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 322.03 | bwd_microstep: 514.66 | bwd_inner_microstep: 514.64 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-01 22:06:49,430] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 329.05 | bwd_microstep: 514.59 | bwd_inner_microstep: 514.57 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-01 22:06:50,301] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 327.43 | bwd_microstep: 507.76 | bwd_inner_microstep: 507.74 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.32 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-01 22:06:51,173] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 339.39 | bwd_microstep: 497.82 | bwd_inner_microstep: 497.80 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-01 22:06:52,043] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 344.37 | bwd_microstep: 491.52 | bwd_inner_microstep: 491.48 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.49 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1348 +[2025-05-01 22:06:52,747] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 298.06 | bwd_microstep: 374.50 | bwd_inner_microstep: 374.48 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.47 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-01 22:06:53,619] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 323.86 | bwd_microstep: 515.96 | bwd_inner_microstep: 515.94 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-01 22:06:54,479] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 314.45 | bwd_microstep: 511.51 | bwd_inner_microstep: 511.49 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.48 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1349 +[2025-05-01 22:06:55,104] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 217.36 | bwd_microstep: 377.53 | bwd_inner_microstep: 377.51 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 22:06:55,991] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 387.19 | bwd_microstep: 482.02 | bwd_inner_microstep: 482.00 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 22:06:56,888] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 385.80 | bwd_microstep: 493.81 | bwd_inner_microstep: 493.79 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 22:06:58,002] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.23 | optimizer_step: 18.87 +[2025-05-01 22:06:58,004] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 356.65 | bwd_microstep: 711.64 | bwd_inner_microstep: 508.09 | bwd_allreduce_microstep: 203.53 | step_microstep: 28.49 +[2025-05-01 22:06:58,005] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4916.49 | bwd: 7522.70 | bwd_inner: 7318.88 | bwd_allreduce: 203.60 | step: 50.92 + 1%|▏ | 119/8720 [23:51<30:33:50, 12.79s/it] {'loss': 2.7604, 'grad_norm': 7.9428839683532715, 'learning_rate': 4.541984732824427e-06, 'epoch': 0.14} + 1%|▏ | 119/8720 [23:51<30:33:50, 12.79s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2013 +[2025-05-01 22:06:58,951] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 338.84 | bwd_microstep: 562.81 | bwd_inner_microstep: 562.79 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1957 +[2025-05-01 22:06:59,869] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 337.10 | bwd_microstep: 556.15 | bwd_inner_microstep: 556.13 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1436 +[2025-05-01 22:07:00,510] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 229.23 | bwd_microstep: 388.40 | bwd_inner_microstep: 388.38 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1891 +[2025-05-01 22:07:01,396] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 334.80 | bwd_microstep: 517.10 | bwd_inner_microstep: 517.08 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 867 +[2025-05-01 22:07:01,851] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 213.72 | bwd_microstep: 212.25 | bwd_inner_microstep: 212.05 | bwd_allreduce_microstep: 0.18 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-01 22:07:02,726] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 333.94 | bwd_microstep: 511.88 | bwd_inner_microstep: 511.86 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.22 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-01 22:07:03,602] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 328.49 | bwd_microstep: 518.92 | bwd_inner_microstep: 518.91 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 22:07:04,467] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 332.07 | bwd_microstep: 502.91 | bwd_inner_microstep: 502.89 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-01 22:07:05,343] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 331.19 | bwd_microstep: 511.82 | bwd_inner_microstep: 511.80 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 838 +[2025-05-01 22:07:05,770] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.41 | bwd_microstep: 205.88 | bwd_inner_microstep: 205.63 | bwd_allreduce_microstep: 0.23 | step_microstep: 1.10 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 833 +[2025-05-01 22:07:06,196] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 180.41 | bwd_microstep: 214.24 | bwd_inner_microstep: 214.22 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.48 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 22:07:07,062] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 328.89 | bwd_microstep: 504.52 | bwd_inner_microstep: 504.50 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 22:07:07,932] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 326.77 | bwd_microstep: 514.02 | bwd_inner_microstep: 513.99 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.02 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 22:07:08,806] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 334.40 | bwd_microstep: 511.69 | bwd_inner_microstep: 511.68 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 22:07:09,678] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 337.43 | bwd_microstep: 508.05 | bwd_inner_microstep: 508.03 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 22:07:10,820] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.26 | optimizer_step: 18.91 +[2025-05-01 22:07:10,822] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 329.96 | bwd_microstep: 758.41 | bwd_inner_microstep: 511.76 | bwd_allreduce_microstep: 246.64 | step_microstep: 28.54 +[2025-05-01 22:07:10,823] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4807.64 | bwd: 7499.05 | bwd_inner: 7251.72 | bwd_allreduce: 247.11 | step: 48.36 + 1%|▏ | 120/8720 [24:04<30:34:42, 12.80s/it] {'loss': 2.9643, 'grad_norm': 11.26155948638916, 'learning_rate': 4.580152671755725e-06, 'epoch': 0.14} + 1%|▏ | 120/8720 [24:04<30:34:42, 12.80s/it]dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 993 +[2025-05-01 22:07:11,339] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 193.39 | bwd_microstep: 281.90 | bwd_inner_microstep: 281.88 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.28 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-01 22:07:12,205] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 314.56 | bwd_microstep: 515.75 | bwd_inner_microstep: 515.73 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1361 +[2025-05-01 22:07:12,841] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 220.59 | bwd_microstep: 383.24 | bwd_inner_microstep: 383.12 | bwd_allreduce_microstep: 0.08 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-01 22:07:13,743] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 396.21 | bwd_microstep: 486.62 | bwd_inner_microstep: 486.60 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-01 22:07:14,641] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 386.98 | bwd_microstep: 495.21 | bwd_inner_microstep: 495.19 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-01 22:07:15,531] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 355.04 | bwd_microstep: 516.79 | bwd_inner_microstep: 516.77 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-01 22:07:16,378] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 316.91 | bwd_microstep: 510.10 | bwd_inner_microstep: 510.08 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.28 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-01 22:07:17,238] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 314.85 | bwd_microstep: 513.51 | bwd_inner_microstep: 513.49 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-01 22:07:18,106] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 315.93 | bwd_microstep: 515.35 | bwd_inner_microstep: 515.33 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.31 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-01 22:07:18,974] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 318.93 | bwd_microstep: 515.43 | bwd_inner_microstep: 515.41 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.51 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 22:07:19,844] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 325.31 | bwd_microstep: 509.60 | bwd_inner_microstep: 509.58 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.33 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-01 22:07:20,698] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 327.24 | bwd_microstep: 493.24 | bwd_inner_microstep: 493.22 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 22:07:21,571] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 333.52 | bwd_microstep: 509.55 | bwd_inner_microstep: 509.53 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-01 22:07:22,445] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 336.80 | bwd_microstep: 509.36 | bwd_inner_microstep: 509.34 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-01 22:07:23,322] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 336.12 | bwd_microstep: 513.73 | bwd_inner_microstep: 513.71 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1894 +[2025-05-01 22:07:24,488] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.25 | optimizer_step: 17.12 +[2025-05-01 22:07:24,489] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 338.89 | bwd_microstep: 773.53 | bwd_inner_microstep: 513.06 | bwd_allreduce_microstep: 260.46 | step_microstep: 26.83 +[2025-05-01 22:07:24,490] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 5131.24 | bwd: 8042.93 | bwd_inner: 7782.08 | bwd_allreduce: 260.60 | step: 46.50 + 1%|▏ | 121/8720 [24:18<31:11:41, 13.06s/it] {'loss': 3.6096, 'grad_norm': 11.294764518737793, 'learning_rate': 4.618320610687023e-06, 'epoch': 0.14} + 1%|▏ | 121/8720 [24:18<31:11:41, 13.06s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1909 +[2025-05-01 22:07:25,369] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 329.97 | bwd_microstep: 506.59 | bwd_inner_microstep: 506.57 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.33 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1896 +[2025-05-01 22:07:26,242] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 336.23 | bwd_microstep: 502.56 | bwd_inner_microstep: 502.54 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1900 +[2025-05-01 22:07:27,115] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 330.08 | bwd_microstep: 511.66 | bwd_inner_microstep: 511.64 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1934 +[2025-05-01 22:07:28,031] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 354.02 | bwd_microstep: 534.09 | bwd_inner_microstep: 534.07 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.32 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 353 +[2025-05-01 22:07:28,291] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 102.74 | bwd_microstep: 125.27 | bwd_inner_microstep: 125.25 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.49 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1883 +[2025-05-01 22:07:29,170] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 342.33 | bwd_microstep: 504.35 | bwd_inner_microstep: 504.33 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-01 22:07:30,047] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 341.50 | bwd_microstep: 501.86 | bwd_inner_microstep: 501.84 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 22:07:30,921] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 343.11 | bwd_microstep: 496.61 | bwd_inner_microstep: 496.59 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.32 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 22:07:31,796] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 349.21 | bwd_microstep: 492.02 | bwd_inner_microstep: 491.99 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-01 22:07:32,668] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 353.64 | bwd_microstep: 485.78 | bwd_inner_microstep: 485.76 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 22:07:33,544] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 365.82 | bwd_microstep: 482.27 | bwd_inner_microstep: 482.25 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.14 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 22:07:34,441] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 392.22 | bwd_microstep: 485.42 | bwd_inner_microstep: 485.40 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 22:07:35,342] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 387.78 | bwd_microstep: 493.12 | bwd_inner_microstep: 493.10 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 22:07:36,227] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 353.72 | bwd_microstep: 511.53 | bwd_inner_microstep: 511.51 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-01 22:07:37,081] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 317.34 | bwd_microstep: 517.12 | bwd_inner_microstep: 517.10 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.45 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 22:07:38,138] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.39 | optimizer_step: 18.63 +[2025-05-01 22:07:38,140] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 318.11 | bwd_microstep: 681.79 | bwd_inner_microstep: 510.91 | bwd_allreduce_microstep: 170.87 | step_microstep: 28.31 +[2025-05-01 22:07:38,141] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 5317.77 | bwd: 7832.03 | bwd_inner: 7660.89 | bwd_allreduce: 170.93 | step: 50.42 + 1%|▏ | 122/8720 [24:31<31:36:55, 13.24s/it] {'loss': 3.189, 'grad_norm': 18.397933959960938, 'learning_rate': 4.656488549618321e-06, 'epoch': 0.14} + 1%|▏ | 122/8720 [24:31<31:36:55, 13.24s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1925 +[2025-05-01 22:07:39,064] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 349.92 | bwd_microstep: 530.42 | bwd_inner_microstep: 530.41 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 348 +[2025-05-01 22:07:39,322] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 99.26 | bwd_microstep: 126.87 | bwd_inner_microstep: 126.85 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.32 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 343 +[2025-05-01 22:07:39,590] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 99.19 | bwd_microstep: 138.75 | bwd_inner_microstep: 138.73 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.33 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1372 +[2025-05-01 22:07:40,211] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 225.90 | bwd_microstep: 375.32 | bwd_inner_microstep: 375.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-01 22:07:41,084] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 324.33 | bwd_microstep: 514.91 | bwd_inner_microstep: 514.89 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 842 +[2025-05-01 22:07:41,526] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 207.49 | bwd_microstep: 202.51 | bwd_inner_microstep: 202.49 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-01 22:07:42,405] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 335.14 | bwd_microstep: 512.77 | bwd_inner_microstep: 512.75 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 22:07:43,280] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 333.16 | bwd_microstep: 510.71 | bwd_inner_microstep: 510.69 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 22:07:44,162] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 335.04 | bwd_microstep: 515.59 | bwd_inner_microstep: 515.57 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 22:07:45,039] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 333.97 | bwd_microstep: 517.37 | bwd_inner_microstep: 517.35 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 22:07:45,915] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 331.81 | bwd_microstep: 517.98 | bwd_inner_microstep: 517.96 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.33 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 22:07:46,781] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 332.11 | bwd_microstep: 507.06 | bwd_inner_microstep: 507.04 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.42 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 22:07:47,661] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 334.20 | bwd_microstep: 513.60 | bwd_inner_microstep: 513.58 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.48 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 22:07:48,534] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 332.77 | bwd_microstep: 513.64 | bwd_inner_microstep: 513.63 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-01 22:07:49,412] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 328.96 | bwd_microstep: 520.11 | bwd_inner_microstep: 520.10 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1895 +[2025-05-01 22:07:50,591] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.48 | optimizer_step: 19.20 +[2025-05-01 22:07:50,594] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 334.21 | bwd_microstep: 794.25 | bwd_inner_microstep: 516.31 | bwd_allreduce_microstep: 277.92 | step_microstep: 28.88 +[2025-05-01 22:07:50,595] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4637.44 | bwd: 7311.86 | bwd_inner: 7033.67 | bwd_allreduce: 277.99 | step: 64.25 + 1%|▏ | 123/8720 [24:44<31:03:00, 13.00s/it] {'loss': 5.0748, 'grad_norm': 18.23569679260254, 'learning_rate': 4.694656488549618e-06, 'epoch': 0.14} + 1%|▏ | 123/8720 [24:44<31:03:00, 13.00s/it]dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1181 +[2025-05-01 22:07:51,184] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 185.31 | bwd_microstep: 365.81 | bwd_inner_microstep: 365.48 | bwd_allreduce_microstep: 0.32 | step_microstep: 0.60 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 912 +[2025-05-01 22:07:51,647] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 136.67 | bwd_microstep: 309.50 | bwd_inner_microstep: 308.89 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.40 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1372 +[2025-05-01 22:07:52,267] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 223.76 | bwd_microstep: 376.94 | bwd_inner_microstep: 376.92 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-01 22:07:53,136] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 322.44 | bwd_microstep: 515.11 | bwd_inner_microstep: 515.09 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-01 22:07:54,014] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 326.82 | bwd_microstep: 517.05 | bwd_inner_microstep: 517.03 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 845 +[2025-05-01 22:07:54,460] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 205.86 | bwd_microstep: 208.30 | bwd_inner_microstep: 208.29 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 22:07:55,337] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 334.15 | bwd_microstep: 511.14 | bwd_inner_microstep: 511.13 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-01 22:07:56,194] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 335.08 | bwd_microstep: 489.72 | bwd_inner_microstep: 489.70 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 22:07:57,065] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 327.69 | bwd_microstep: 509.41 | bwd_inner_microstep: 509.39 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-01 22:07:57,932] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 335.02 | bwd_microstep: 497.62 | bwd_inner_microstep: 497.60 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 22:07:58,788] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 343.07 | bwd_microstep: 484.00 | bwd_inner_microstep: 483.98 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 22:07:59,669] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 367.02 | bwd_microstep: 487.57 | bwd_inner_microstep: 487.56 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-01 22:08:00,569] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 394.53 | bwd_microstep: 487.01 | bwd_inner_microstep: 486.99 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-01 22:08:01,458] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 368.18 | bwd_microstep: 501.46 | bwd_inner_microstep: 501.44 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 22:08:02,316] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 325.48 | bwd_microstep: 512.35 | bwd_inner_microstep: 512.33 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.48 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 400 +[2025-05-01 22:08:02,844] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.48 | optimizer_step: 18.47 +[2025-05-01 22:08:02,845] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 73.44 | bwd_microstep: 398.63 | bwd_inner_microstep: 155.01 | bwd_allreduce_microstep: 243.43 | step_microstep: 27.59 +[2025-05-01 22:08:02,846] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4604.46 | bwd: 7171.64 | bwd_inner: 6927.45 | bwd_allreduce: 243.50 | step: 51.00 + 1%|▏ | 124/8720 [24:56<30:30:23, 12.78s/it] {'loss': 2.6644, 'grad_norm': 12.616983413696289, 'learning_rate': 4.732824427480917e-06, 'epoch': 0.14} + 1%|▏ | 124/8720 [24:56<30:30:23, 12.78s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1984 +[2025-05-01 22:08:03,774] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 349.50 | bwd_microstep: 539.62 | bwd_inner_microstep: 539.60 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1900 +[2025-05-01 22:08:04,632] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 321.48 | bwd_microstep: 501.98 | bwd_inner_microstep: 501.96 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-01 22:08:05,506] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 330.41 | bwd_microstep: 511.88 | bwd_inner_microstep: 511.86 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.25 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1887 +[2025-05-01 22:08:06,386] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 333.32 | bwd_microstep: 515.53 | bwd_inner_microstep: 515.52 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-01 22:08:07,265] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 335.75 | bwd_microstep: 515.09 | bwd_inner_microstep: 515.08 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-01 22:08:08,140] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 335.07 | bwd_microstep: 513.57 | bwd_inner_microstep: 513.55 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 22:08:09,012] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 326.45 | bwd_microstep: 515.39 | bwd_inner_microstep: 515.37 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.48 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-01 22:08:09,886] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 329.98 | bwd_microstep: 515.68 | bwd_inner_microstep: 515.67 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 22:08:10,761] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 333.37 | bwd_microstep: 513.09 | bwd_inner_microstep: 513.07 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 22:08:11,635] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 328.40 | bwd_microstep: 517.94 | bwd_inner_microstep: 517.92 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.97 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 22:08:12,509] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 330.43 | bwd_microstep: 514.53 | bwd_inner_microstep: 514.51 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.84 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 323 +[2025-05-01 22:08:12,756] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 99.34 | bwd_microstep: 121.52 | bwd_inner_microstep: 121.23 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 22:08:13,650] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 388.22 | bwd_microstep: 490.55 | bwd_inner_microstep: 490.53 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 22:08:14,542] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 367.29 | bwd_microstep: 504.58 | bwd_inner_microstep: 504.56 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.89 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-01 22:08:15,406] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 329.63 | bwd_microstep: 514.73 | bwd_inner_microstep: 514.71 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1347 +[2025-05-01 22:08:16,327] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.31 | optimizer_step: 18.60 +[2025-05-01 22:08:16,329] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 224.48 | bwd_microstep: 640.43 | bwd_inner_microstep: 363.64 | bwd_allreduce_microstep: 276.78 | step_microstep: 28.34 +[2025-05-01 22:08:16,331] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 5063.05 | bwd: 7946.11 | bwd_inner: 7668.85 | bwd_allreduce: 276.94 | step: 41.89 + 1%|▏ | 125/8720 [25:09<31:00:46, 12.99s/it] {'loss': 4.1547, 'grad_norm': 13.027426719665527, 'learning_rate': 4.770992366412215e-06, 'epoch': 0.14} + 1%|▏ | 125/8720 [25:09<31:00:46, 12.99s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-01 22:08:17,217] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 338.06 | bwd_microstep: 514.92 | bwd_inner_microstep: 514.90 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.54 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1352 +[2025-05-01 22:08:17,907] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 245.83 | bwd_microstep: 414.62 | bwd_inner_microstep: 414.45 | bwd_allreduce_microstep: 0.10 | step_microstep: 0.10 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 841 +[2025-05-01 22:08:18,354] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 169.40 | bwd_microstep: 260.97 | bwd_inner_microstep: 260.90 | bwd_allreduce_microstep: 0.03 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 22:08:19,247] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 366.90 | bwd_microstep: 504.71 | bwd_inner_microstep: 504.69 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.94 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-01 22:08:20,114] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 329.29 | bwd_microstep: 518.82 | bwd_inner_microstep: 518.80 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 22:08:20,994] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 325.85 | bwd_microstep: 523.52 | bwd_inner_microstep: 523.51 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 22:08:21,869] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 325.94 | bwd_microstep: 516.57 | bwd_inner_microstep: 516.56 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.33 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-01 22:08:22,754] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 325.73 | bwd_microstep: 522.69 | bwd_inner_microstep: 522.67 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.33 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 22:08:23,622] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 317.52 | bwd_microstep: 517.19 | bwd_inner_microstep: 517.18 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 22:08:24,499] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 322.18 | bwd_microstep: 519.83 | bwd_inner_microstep: 519.82 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 22:08:25,368] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 317.27 | bwd_microstep: 520.08 | bwd_inner_microstep: 520.06 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.31 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 22:08:26,219] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 315.01 | bwd_microstep: 502.03 | bwd_inner_microstep: 502.01 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 22:08:27,075] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 315.95 | bwd_microstep: 505.96 | bwd_inner_microstep: 505.94 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.51 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 22:08:27,934] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 328.14 | bwd_microstep: 493.33 | bwd_inner_microstep: 493.31 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.43 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 22:08:28,797] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 323.83 | bwd_microstep: 505.43 | bwd_inner_microstep: 505.41 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1850 +[2025-05-01 22:08:29,962] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.31 | optimizer_step: 18.41 +[2025-05-01 22:08:29,964] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 328.85 | bwd_microstep: 782.30 | bwd_inner_microstep: 510.93 | bwd_allreduce_microstep: 271.35 | step_microstep: 27.95 +[2025-05-01 22:08:29,965] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4995.72 | bwd: 8123.01 | bwd_inner: 7851.15 | bwd_allreduce: 271.59 | step: 55.47 + 1%|▏ | 126/8720 [25:23<31:28:24, 13.18s/it] {'loss': 2.9189, 'grad_norm': 12.813634872436523, 'learning_rate': 4.8091603053435125e-06, 'epoch': 0.14} + 1%|▏ | 126/8720 [25:23<31:28:24, 13.18s/it]dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1708 +[2025-05-01 22:08:30,753] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 257.77 | bwd_microstep: 483.49 | bwd_inner_microstep: 483.47 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 384 +[2025-05-01 22:08:31,002] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 109.37 | bwd_microstep: 117.56 | bwd_inner_microstep: 117.34 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1883 +[2025-05-01 22:08:31,906] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 373.11 | bwd_microstep: 511.95 | bwd_inner_microstep: 511.93 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-01 22:08:32,795] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 354.42 | bwd_microstep: 515.76 | bwd_inner_microstep: 515.74 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.92 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-01 22:08:33,664] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 330.62 | bwd_microstep: 517.47 | bwd_inner_microstep: 517.45 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.50 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-01 22:08:34,534] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 320.43 | bwd_microstep: 519.85 | bwd_inner_microstep: 519.83 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.28 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 327 +[2025-05-01 22:08:34,774] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 74.08 | bwd_microstep: 133.54 | bwd_inner_microstep: 133.52 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 22:08:35,656] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 333.31 | bwd_microstep: 518.20 | bwd_inner_microstep: 518.18 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 835 +[2025-05-01 22:08:36,077] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.03 | bwd_microstep: 207.50 | bwd_inner_microstep: 207.48 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.67 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 22:08:36,951] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 331.50 | bwd_microstep: 510.75 | bwd_inner_microstep: 510.73 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 22:08:37,822] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 331.92 | bwd_microstep: 513.10 | bwd_inner_microstep: 513.08 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.22 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 22:08:38,697] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 333.07 | bwd_microstep: 513.88 | bwd_inner_microstep: 513.86 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.22 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 22:08:39,572] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 330.40 | bwd_microstep: 517.36 | bwd_inner_microstep: 517.34 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1850 +[2025-05-01 22:08:40,450] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 333.38 | bwd_microstep: 515.64 | bwd_inner_microstep: 515.62 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.15 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2005 +[2025-05-01 22:08:41,390] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 358.28 | bwd_microstep: 552.75 | bwd_inner_microstep: 552.73 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.50 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1952 +[2025-05-01 22:08:42,601] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.28 | optimizer_step: 18.71 +[2025-05-01 22:08:42,603] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 343.05 | bwd_microstep: 811.83 | bwd_inner_microstep: 543.62 | bwd_allreduce_microstep: 268.20 | step_microstep: 28.20 +[2025-05-01 22:08:42,604] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4701.68 | bwd: 7460.64 | bwd_inner: 7192.01 | bwd_allreduce: 268.32 | step: 45.06 + 1%|▏ | 127/8720 [25:36<31:04:35, 13.02s/it] {'loss': 2.5507, 'grad_norm': 13.341757774353027, 'learning_rate': 4.847328244274809e-06, 'epoch': 0.15} + 1%|▏ | 127/8720 [25:36<31:04:35, 13.02s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2024 +[2025-05-01 22:08:43,553] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 338.66 | bwd_microstep: 567.41 | bwd_inner_microstep: 567.39 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1941 +[2025-05-01 22:08:44,473] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 341.69 | bwd_microstep: 554.75 | bwd_inner_microstep: 554.73 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.93 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1903 +[2025-05-01 22:08:45,352] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 331.80 | bwd_microstep: 526.04 | bwd_inner_microstep: 526.02 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.31 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1894 +[2025-05-01 22:08:46,230] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 326.42 | bwd_microstep: 522.47 | bwd_inner_microstep: 522.45 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-01 22:08:47,107] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 323.72 | bwd_microstep: 522.33 | bwd_inner_microstep: 522.31 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.31 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 839 +[2025-05-01 22:08:47,530] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 111.72 | bwd_microstep: 278.96 | bwd_inner_microstep: 278.94 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.31 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 22:08:48,389] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 315.97 | bwd_microstep: 511.80 | bwd_inner_microstep: 511.78 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 22:08:49,258] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 314.06 | bwd_microstep: 517.87 | bwd_inner_microstep: 517.85 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.28 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 22:08:50,123] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 314.08 | bwd_microstep: 516.88 | bwd_inner_microstep: 516.86 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.32 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 22:08:50,985] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 316.99 | bwd_microstep: 512.41 | bwd_inner_microstep: 512.39 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 322 +[2025-05-01 22:08:51,234] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 92.15 | bwd_microstep: 125.76 | bwd_inner_microstep: 125.74 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 22:08:52,093] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 326.27 | bwd_microstep: 498.53 | bwd_inner_microstep: 498.51 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 22:08:52,952] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 347.23 | bwd_microstep: 481.60 | bwd_inner_microstep: 481.59 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 22:08:53,826] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 367.97 | bwd_microstep: 479.47 | bwd_inner_microstep: 479.39 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 22:08:54,726] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 398.10 | bwd_microstep: 486.45 | bwd_inner_microstep: 486.44 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1903 +[2025-05-01 22:08:55,952] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.23 | optimizer_step: 26.55 +[2025-05-01 22:08:55,953] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 378.72 | bwd_microstep: 795.17 | bwd_inner_microstep: 509.21 | bwd_allreduce_microstep: 285.91 | step_microstep: 34.12 +[2025-05-01 22:08:55,954] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4945.51 | bwd: 7897.92 | bwd_inner: 7611.62 | bwd_allreduce: 286.01 | step: 60.80 + 1%|▏ | 128/8720 [25:49<31:18:25, 13.12s/it] {'loss': 2.8759, 'grad_norm': 13.929717063903809, 'learning_rate': 4.885496183206107e-06, 'epoch': 0.15} + 1%|▏ | 128/8720 [25:49<31:18:25, 13.12s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1944 +[2025-05-01 22:08:56,881] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 403.08 | bwd_microstep: 502.29 | bwd_inner_microstep: 502.28 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1903 +[2025-05-01 22:08:57,784] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 390.11 | bwd_microstep: 494.98 | bwd_inner_microstep: 494.96 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-01 22:08:58,680] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 364.17 | bwd_microstep: 513.06 | bwd_inner_microstep: 513.04 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.90 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-01 22:08:59,542] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 320.83 | bwd_microstep: 521.48 | bwd_inner_microstep: 521.46 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-01 22:09:00,411] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 317.18 | bwd_microstep: 518.59 | bwd_inner_microstep: 518.57 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.49 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-01 22:09:01,266] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 311.63 | bwd_microstep: 509.21 | bwd_inner_microstep: 509.19 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.32 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 22:09:02,131] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 314.87 | bwd_microstep: 517.75 | bwd_inner_microstep: 517.73 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 836 +[2025-05-01 22:09:02,551] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 143.32 | bwd_microstep: 244.97 | bwd_inner_microstep: 244.95 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 22:09:03,410] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 320.92 | bwd_microstep: 506.12 | bwd_inner_microstep: 506.11 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 22:09:04,274] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 329.71 | bwd_microstep: 501.86 | bwd_inner_microstep: 501.85 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1346 +[2025-05-01 22:09:04,944] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 224.40 | bwd_microstep: 415.70 | bwd_inner_microstep: 415.53 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 22:09:05,841] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 379.41 | bwd_microstep: 496.18 | bwd_inner_microstep: 496.16 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.89 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 22:09:06,718] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 343.90 | bwd_microstep: 513.18 | bwd_inner_microstep: 513.16 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 22:09:07,581] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 325.19 | bwd_microstep: 514.33 | bwd_inner_microstep: 514.32 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.52 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 22:09:08,448] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 320.71 | bwd_microstep: 513.35 | bwd_inner_microstep: 513.33 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.50 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 22:09:09,594] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.28 | optimizer_step: 18.42 +[2025-05-01 22:09:09,596] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 321.50 | bwd_microstep: 762.63 | bwd_inner_microstep: 515.45 | bwd_allreduce_microstep: 247.17 | step_microstep: 28.15 +[2025-05-01 22:09:09,597] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 5130.84 | bwd: 8045.70 | bwd_inner: 7798.10 | bwd_allreduce: 247.32 | step: 54.03 + 1%|▏ | 129/8720 [26:03<31:40:57, 13.28s/it] {'loss': 2.7612, 'grad_norm': 19.748401641845703, 'learning_rate': 4.923664122137405e-06, 'epoch': 0.15} + 1%|▏ | 129/8720 [26:03<31:40:57, 13.28s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2053 +[2025-05-01 22:09:10,545] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 330.45 | bwd_microstep: 575.27 | bwd_inner_microstep: 575.25 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-01 22:09:11,417] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 323.87 | bwd_microstep: 526.23 | bwd_inner_microstep: 526.21 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.31 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1379 +[2025-05-01 22:09:12,048] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 229.65 | bwd_microstep: 371.57 | bwd_inner_microstep: 371.55 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-01 22:09:12,929] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 327.77 | bwd_microstep: 516.96 | bwd_inner_microstep: 516.94 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.49 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 338 +[2025-05-01 22:09:13,181] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 86.40 | bwd_microstep: 135.93 | bwd_inner_microstep: 135.68 | bwd_allreduce_microstep: 0.24 | step_microstep: 0.20 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 847 +[2025-05-01 22:09:13,617] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 124.77 | bwd_microstep: 293.11 | bwd_inner_microstep: 293.09 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.52 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 844 +[2025-05-01 22:09:14,046] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 119.56 | bwd_microstep: 291.61 | bwd_inner_microstep: 291.59 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.33 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-01 22:09:14,904] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 317.81 | bwd_microstep: 516.95 | bwd_inner_microstep: 516.94 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.32 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-01 22:09:15,775] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 317.88 | bwd_microstep: 518.09 | bwd_inner_microstep: 518.07 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.30 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 22:09:16,637] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 313.71 | bwd_microstep: 517.11 | bwd_inner_microstep: 517.09 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 22:09:17,502] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 314.83 | bwd_microstep: 517.94 | bwd_inner_microstep: 517.92 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.32 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-01 22:09:18,369] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 320.63 | bwd_microstep: 514.27 | bwd_inner_microstep: 514.25 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 22:09:19,226] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 325.75 | bwd_microstep: 497.10 | bwd_inner_microstep: 497.08 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 22:09:20,087] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 325.01 | bwd_microstep: 505.91 | bwd_inner_microstep: 505.89 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 22:09:20,960] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 333.10 | bwd_microstep: 510.45 | bwd_inner_microstep: 510.43 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 22:09:22,089] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.21 | optimizer_step: 18.80 +[2025-05-01 22:09:22,091] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 330.84 | bwd_microstep: 745.22 | bwd_inner_microstep: 511.17 | bwd_allreduce_microstep: 234.04 | step_microstep: 28.19 +[2025-05-01 22:09:22,092] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4442.02 | bwd: 7553.72 | bwd_inner: 7319.18 | bwd_allreduce: 234.34 | step: 57.09 + 1%|▏ | 130/8720 [26:15<31:07:08, 13.04s/it] {'loss': 3.5225, 'grad_norm': 18.609188079833984, 'learning_rate': 4.961832061068703e-06, 'epoch': 0.15} + 1%|▏ | 130/8720 [26:15<31:07:08, 13.04s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1920 +[2025-05-01 22:09:22,990] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 336.22 | bwd_microstep: 523.25 | bwd_inner_microstep: 523.23 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1921 +[2025-05-01 22:09:23,900] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 346.51 | bwd_microstep: 533.38 | bwd_inner_microstep: 533.36 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 867 +[2025-05-01 22:09:24,345] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 176.22 | bwd_microstep: 238.64 | bwd_inner_microstep: 238.62 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-01 22:09:25,208] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 328.17 | bwd_microstep: 502.33 | bwd_inner_microstep: 502.31 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.51 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-01 22:09:26,073] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 323.78 | bwd_microstep: 510.20 | bwd_inner_microstep: 510.18 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-01 22:09:26,948] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 334.41 | bwd_microstep: 513.94 | bwd_inner_microstep: 513.92 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 22:09:27,823] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 329.44 | bwd_microstep: 518.50 | bwd_inner_microstep: 518.48 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-01 22:09:28,699] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 335.10 | bwd_microstep: 513.05 | bwd_inner_microstep: 513.04 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.22 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 22:09:29,572] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 331.15 | bwd_microstep: 516.52 | bwd_inner_microstep: 516.50 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-01 22:09:30,450] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 335.60 | bwd_microstep: 514.43 | bwd_inner_microstep: 514.41 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 22:09:31,319] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 330.32 | bwd_microstep: 510.46 | bwd_inner_microstep: 510.44 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 22:09:32,192] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 325.37 | bwd_microstep: 516.56 | bwd_inner_microstep: 516.55 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 22:09:33,066] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 329.43 | bwd_microstep: 511.93 | bwd_inner_microstep: 511.91 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 22:09:33,937] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 326.51 | bwd_microstep: 507.99 | bwd_inner_microstep: 507.97 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 22:09:34,809] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 325.26 | bwd_microstep: 513.54 | bwd_inner_microstep: 513.52 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1888 +[2025-05-01 22:09:35,940] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.28 | optimizer_step: 21.60 +[2025-05-01 22:09:35,942] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 343.80 | bwd_microstep: 729.72 | bwd_inner_microstep: 478.53 | bwd_allreduce_microstep: 251.18 | step_microstep: 29.25 +[2025-05-01 22:09:35,943] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 5157.28 | bwd: 8174.44 | bwd_inner: 7923.00 | bwd_allreduce: 251.24 | step: 50.54 + 2%|▏ | 131/8720 [26:29<31:41:43, 13.28s/it] {'loss': 3.1301, 'grad_norm': 12.659941673278809, 'learning_rate': 5e-06, 'epoch': 0.15} + 2%|▏ | 131/8720 [26:29<31:41:43, 13.28s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1931 +[2025-05-01 22:09:36,832] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 344.50 | bwd_microstep: 506.99 | bwd_inner_microstep: 506.98 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1144 +[2025-05-01 22:09:37,345] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 220.26 | bwd_microstep: 275.53 | bwd_inner_microstep: 273.21 | bwd_allreduce_microstep: 2.30 | step_microstep: 2.50 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-01 22:09:38,201] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 321.56 | bwd_microstep: 502.69 | bwd_inner_microstep: 502.67 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1896 +[2025-05-01 22:09:39,080] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 334.25 | bwd_microstep: 514.45 | bwd_inner_microstep: 514.43 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1367 +[2025-05-01 22:09:39,756] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 234.71 | bwd_microstep: 412.17 | bwd_inner_microstep: 412.14 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-01 22:09:40,661] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 382.21 | bwd_microstep: 503.35 | bwd_inner_microstep: 503.33 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-01 22:09:41,548] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 345.36 | bwd_microstep: 521.76 | bwd_inner_microstep: 521.74 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.58 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-01 22:09:42,413] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 323.60 | bwd_microstep: 520.97 | bwd_inner_microstep: 520.95 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-01 22:09:43,284] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 317.28 | bwd_microstep: 520.13 | bwd_inner_microstep: 520.12 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.48 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-01 22:09:44,153] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 318.12 | bwd_microstep: 517.33 | bwd_inner_microstep: 517.31 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 333 +[2025-05-01 22:09:44,398] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 80.91 | bwd_microstep: 131.67 | bwd_inner_microstep: 131.65 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 22:09:45,280] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 336.26 | bwd_microstep: 516.38 | bwd_inner_microstep: 516.36 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 22:09:46,163] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 334.17 | bwd_microstep: 515.53 | bwd_inner_microstep: 515.51 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 22:09:47,036] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 334.07 | bwd_microstep: 508.30 | bwd_inner_microstep: 508.28 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 22:09:47,914] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 333.41 | bwd_microstep: 514.02 | bwd_inner_microstep: 514.01 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.16 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1939 +[2025-05-01 22:09:49,103] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.32 | optimizer_step: 18.41 +[2025-05-01 22:09:49,105] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 341.50 | bwd_microstep: 796.36 | bwd_inner_microstep: 532.74 | bwd_allreduce_microstep: 263.61 | step_microstep: 27.95 +[2025-05-01 22:09:49,106] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4902.12 | bwd: 7777.65 | bwd_inner: 7511.45 | bwd_allreduce: 263.68 | step: 50.40 + 2%|▏ | 132/8720 [26:42<31:36:14, 13.25s/it] {'loss': 2.8798, 'grad_norm': 11.390873908996582, 'learning_rate': 5.038167938931297e-06, 'epoch': 0.15} + 2%|▏ | 132/8720 [26:42<31:36:14, 13.25s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 388 +[2025-05-01 22:09:49,367] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 106.55 | bwd_microstep: 113.81 | bwd_inner_microstep: 113.79 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.32 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1396 +[2025-05-01 22:09:50,072] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 286.71 | bwd_microstep: 388.81 | bwd_inner_microstep: 388.79 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1887 +[2025-05-01 22:09:50,940] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 320.67 | bwd_microstep: 523.73 | bwd_inner_microstep: 523.71 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.32 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 333 +[2025-05-01 22:09:51,182] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 75.37 | bwd_microstep: 134.18 | bwd_inner_microstep: 134.16 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-01 22:09:52,064] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 331.25 | bwd_microstep: 518.19 | bwd_inner_microstep: 518.17 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.51 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-01 22:09:52,940] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 331.11 | bwd_microstep: 516.50 | bwd_inner_microstep: 516.48 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 22:09:53,817] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 333.10 | bwd_microstep: 516.57 | bwd_inner_microstep: 516.55 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 22:09:54,692] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 330.38 | bwd_microstep: 514.58 | bwd_inner_microstep: 514.56 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.28 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-01 22:09:55,560] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 332.60 | bwd_microstep: 505.38 | bwd_inner_microstep: 505.36 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-01 22:09:56,439] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 330.27 | bwd_microstep: 515.15 | bwd_inner_microstep: 515.13 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.31 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-01 22:09:57,316] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 327.90 | bwd_microstep: 516.91 | bwd_inner_microstep: 516.90 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.46 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 22:09:58,187] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 331.16 | bwd_microstep: 509.83 | bwd_inner_microstep: 509.81 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 22:09:59,060] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 329.68 | bwd_microstep: 510.02 | bwd_inner_microstep: 510.01 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.50 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 22:09:59,545] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.21 | bwd_microstep: 271.34 | bwd_inner_microstep: 271.33 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1902 +[2025-05-01 22:10:00,151] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 194.02 | bwd_microstep: 396.40 | bwd_inner_microstep: 396.39 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 22:10:01,332] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.68 | optimizer_step: 18.32 +[2025-05-01 22:10:01,333] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 374.70 | bwd_microstep: 761.01 | bwd_inner_microstep: 499.22 | bwd_allreduce_microstep: 261.78 | step_microstep: 28.02 +[2025-05-01 22:10:01,334] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4524.62 | bwd: 7212.42 | bwd_inner: 6950.37 | bwd_allreduce: 261.84 | step: 55.74 + 2%|▏ | 133/8720 [26:54<30:52:05, 12.94s/it] {'loss': 2.5771, 'grad_norm': 14.282988548278809, 'learning_rate': 5.076335877862596e-06, 'epoch': 0.15} + 2%|▏ | 133/8720 [26:54<30:52:05, 12.94s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1925 +[2025-05-01 22:10:02,249] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 353.76 | bwd_microstep: 539.06 | bwd_inner_microstep: 539.04 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.79 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1911 +[2025-05-01 22:10:03,042] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 330.56 | bwd_microstep: 438.04 | bwd_inner_microstep: 438.02 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1902 +[2025-05-01 22:10:03,528] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.67 | bwd_microstep: 280.35 | bwd_inner_microstep: 280.34 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-01 22:10:04,173] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 198.91 | bwd_microstep: 428.41 | bwd_inner_microstep: 428.40 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.33 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-01 22:10:05,042] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 318.62 | bwd_microstep: 519.36 | bwd_inner_microstep: 519.35 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-01 22:10:05,884] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 324.32 | bwd_microstep: 485.70 | bwd_inner_microstep: 485.68 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 22:10:06,367] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.87 | bwd_microstep: 272.62 | bwd_inner_microstep: 272.60 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 327 +[2025-05-01 22:10:06,585] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 82.36 | bwd_microstep: 115.25 | bwd_inner_microstep: 114.93 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.21 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-01 22:10:07,271] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.32 | bwd_microstep: 481.88 | bwd_inner_microstep: 481.86 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 834 +[2025-05-01 22:10:07,503] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 91.81 | bwd_microstep: 125.97 | bwd_inner_microstep: 125.75 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 22:10:07,977] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.22 | bwd_microstep: 271.25 | bwd_inner_microstep: 271.24 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 22:10:08,685] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.29 | bwd_microstep: 500.85 | bwd_inner_microstep: 500.83 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 22:10:09,539] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 342.24 | bwd_microstep: 481.60 | bwd_inner_microstep: 481.56 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1759 +[2025-05-01 22:10:09,974] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 162.16 | bwd_microstep: 256.19 | bwd_inner_microstep: 256.14 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1957 +[2025-05-01 22:10:10,477] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 196.27 | bwd_microstep: 290.31 | bwd_inner_microstep: 290.29 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-01 22:10:11,586] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.45 | optimizer_step: 18.53 +[2025-05-01 22:10:11,588] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 270.18 | bwd_microstep: 795.22 | bwd_inner_microstep: 496.80 | bwd_allreduce_microstep: 298.40 | step_microstep: 28.21 +[2025-05-01 22:10:11,589] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 3616.33 | bwd: 6282.11 | bwd_inner: 5982.89 | bwd_allreduce: 298.73 | step: 36.77 + 2%|▏ | 134/8720 [27:05<28:56:44, 12.14s/it] {'loss': 2.5227, 'grad_norm': 8.555620193481445, 'learning_rate': 5.114503816793893e-06, 'epoch': 0.15} + 2%|▏ | 134/8720 [27:05<28:56:44, 12.14s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 439 +[2025-05-01 22:10:11,865] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 83.57 | bwd_microstep: 152.99 | bwd_inner_microstep: 152.56 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 879 +[2025-05-01 22:10:12,317] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.19 | bwd_microstep: 232.47 | bwd_inner_microstep: 232.45 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.31 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-01 22:10:13,174] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 329.43 | bwd_microstep: 496.37 | bwd_inner_microstep: 496.35 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.23 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 344 +[2025-05-01 22:10:13,417] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 99.95 | bwd_microstep: 110.55 | bwd_inner_microstep: 110.22 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-01 22:10:14,316] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 395.49 | bwd_microstep: 488.14 | bwd_inner_microstep: 488.12 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.10 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1368 +[2025-05-01 22:10:14,971] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 272.08 | bwd_microstep: 364.43 | bwd_inner_microstep: 362.07 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.32 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-01 22:10:15,843] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 330.09 | bwd_microstep: 511.83 | bwd_inner_microstep: 511.81 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 347 +[2025-05-01 22:10:16,079] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 102.32 | bwd_microstep: 108.09 | bwd_inner_microstep: 107.96 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-01 22:10:16,976] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 384.69 | bwd_microstep: 497.09 | bwd_inner_microstep: 497.08 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 22:10:17,815] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 340.14 | bwd_microstep: 481.87 | bwd_inner_microstep: 481.85 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-01 22:10:18,670] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 335.45 | bwd_microstep: 492.71 | bwd_inner_microstep: 492.70 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-01 22:10:19,515] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 337.57 | bwd_microstep: 488.99 | bwd_inner_microstep: 488.97 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 22:10:20,359] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 332.33 | bwd_microstep: 484.71 | bwd_inner_microstep: 484.69 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1349 +[2025-05-01 22:10:21,024] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 279.58 | bwd_microstep: 367.97 | bwd_inner_microstep: 367.95 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.31 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 22:10:21,895] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 331.96 | bwd_microstep: 502.38 | bwd_inner_microstep: 502.36 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 318 +[2025-05-01 22:10:22,462] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.20 | optimizer_step: 18.82 +[2025-05-01 22:10:22,464] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.64 | bwd_microstep: 416.86 | bwd_inner_microstep: 130.75 | bwd_allreduce_microstep: 286.09 | step_microstep: 28.19 +[2025-05-01 22:10:22,465] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4239.39 | bwd: 6197.47 | bwd_inner: 5908.05 | bwd_allreduce: 286.31 | step: 39.01 + 2%|▏ | 135/8720 [27:15<28:02:22, 11.76s/it] {'loss': 3.5307, 'grad_norm': 15.801783561706543, 'learning_rate': 5.1526717557251914e-06, 'epoch': 0.15} + 2%|▏ | 135/8720 [27:15<28:02:22, 11.76s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1990 +[2025-05-01 22:10:23,420] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 366.47 | bwd_microstep: 545.60 | bwd_inner_microstep: 545.58 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.48 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 411 +[2025-05-01 22:10:23,675] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 103.94 | bwd_microstep: 119.04 | bwd_inner_microstep: 119.02 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.51 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 377 +[2025-05-01 22:10:23,940] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.47 | bwd_microstep: 141.79 | bwd_inner_microstep: 141.29 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.24 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1899 +[2025-05-01 22:10:24,806] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 323.18 | bwd_microstep: 523.18 | bwd_inner_microstep: 523.16 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.28 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1892 +[2025-05-01 22:10:25,684] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 323.89 | bwd_microstep: 524.03 | bwd_inner_microstep: 524.01 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.44 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-01 22:10:26,552] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 318.57 | bwd_microstep: 515.72 | bwd_inner_microstep: 515.70 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1098 +[2025-05-01 22:10:27,085] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 162.95 | bwd_microstep: 339.77 | bwd_inner_microstep: 339.68 | bwd_allreduce_microstep: 0.04 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-01 22:10:27,973] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 351.43 | bwd_microstep: 518.56 | bwd_inner_microstep: 518.54 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 22:10:28,826] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 324.08 | bwd_microstep: 510.39 | bwd_inner_microstep: 510.37 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 22:10:29,656] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 318.22 | bwd_microstep: 481.98 | bwd_inner_microstep: 481.97 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 22:10:30,495] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 341.68 | bwd_microstep: 474.63 | bwd_inner_microstep: 474.61 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.53 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 832 +[2025-05-01 22:10:30,910] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 150.58 | bwd_microstep: 229.90 | bwd_inner_microstep: 229.88 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.33 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 22:10:31,767] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 350.12 | bwd_microstep: 483.67 | bwd_inner_microstep: 483.65 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.27 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-01 22:10:32,575] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 305.23 | bwd_microstep: 484.83 | bwd_inner_microstep: 484.81 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 22:10:33,409] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 334.72 | bwd_microstep: 483.25 | bwd_inner_microstep: 483.23 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1953 +[2025-05-01 22:10:34,514] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.20 | optimizer_step: 18.51 +[2025-05-01 22:10:34,516] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 341.03 | bwd_microstep: 711.95 | bwd_inner_microstep: 506.46 | bwd_allreduce_microstep: 205.47 | step_microstep: 28.01 +[2025-05-01 22:10:34,517] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4511.49 | bwd: 7088.28 | bwd_inner: 6882.46 | bwd_allreduce: 205.59 | step: 49.37 + 2%|▏ | 136/8720 [27:28<28:14:48, 11.85s/it] {'loss': 1.7412, 'grad_norm': 7.395293235778809, 'learning_rate': 5.190839694656488e-06, 'epoch': 0.16} + 2%|▏ | 136/8720 [27:28<28:14:48, 11.85s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2066 +[2025-05-01 22:10:35,430] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 335.54 | bwd_microstep: 543.02 | bwd_inner_microstep: 543.01 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1924 +[2025-05-01 22:10:36,303] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 339.27 | bwd_microstep: 506.44 | bwd_inner_microstep: 506.42 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1888 +[2025-05-01 22:10:37,137] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 330.93 | bwd_microstep: 483.16 | bwd_inner_microstep: 483.14 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-01 22:10:37,997] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 346.43 | bwd_microstep: 489.36 | bwd_inner_microstep: 489.34 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.85 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-01 22:10:38,808] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 310.69 | bwd_microstep: 482.05 | bwd_inner_microstep: 482.03 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-01 22:10:39,647] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 340.81 | bwd_microstep: 469.15 | bwd_inner_microstep: 469.13 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.51 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-01 22:10:40,533] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 336.83 | bwd_microstep: 517.72 | bwd_inner_microstep: 517.70 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-01 22:10:41,424] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 334.52 | bwd_microstep: 513.94 | bwd_inner_microstep: 513.92 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 22:10:42,297] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 331.62 | bwd_microstep: 513.20 | bwd_inner_microstep: 513.18 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.33 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 22:10:43,173] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 337.94 | bwd_microstep: 511.18 | bwd_inner_microstep: 511.16 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.23 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 22:10:44,049] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 331.19 | bwd_microstep: 518.58 | bwd_inner_microstep: 518.56 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.01 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 22:10:44,923] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 332.95 | bwd_microstep: 512.90 | bwd_inner_microstep: 512.88 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 22:10:45,796] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 332.85 | bwd_microstep: 512.79 | bwd_inner_microstep: 512.77 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.22 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 22:10:46,654] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 323.32 | bwd_microstep: 506.60 | bwd_inner_microstep: 506.58 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 22:10:47,525] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 327.60 | bwd_microstep: 518.61 | bwd_inner_microstep: 518.59 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.31 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 22:10:48,674] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.22 | optimizer_step: 18.72 +[2025-05-01 22:10:48,677] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 332.03 | bwd_microstep: 765.79 | bwd_inner_microstep: 519.55 | bwd_allreduce_microstep: 246.23 | step_microstep: 28.16 +[2025-05-01 22:10:48,678] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 5324.49 | bwd: 8364.49 | bwd_inner: 8117.98 | bwd_allreduce: 246.29 | step: 45.31 + 2%|▏ | 137/8720 [27:42<29:53:54, 12.54s/it] {'loss': 1.6228, 'grad_norm': 9.102470397949219, 'learning_rate': 5.229007633587787e-06, 'epoch': 0.16} + 2%|▏ | 137/8720 [27:42<29:53:54, 12.54s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1928 +[2025-05-01 22:10:49,601] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 350.99 | bwd_microstep: 538.95 | bwd_inner_microstep: 538.94 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1897 +[2025-05-01 22:10:50,481] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 334.24 | bwd_microstep: 517.11 | bwd_inner_microstep: 517.09 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1892 +[2025-05-01 22:10:51,354] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 327.62 | bwd_microstep: 516.87 | bwd_inner_microstep: 516.86 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 864 +[2025-05-01 22:10:51,803] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 194.52 | bwd_microstep: 224.63 | bwd_inner_microstep: 224.61 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.51 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-01 22:10:52,665] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 325.24 | bwd_microstep: 506.94 | bwd_inner_microstep: 506.92 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-01 22:10:53,538] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 332.85 | bwd_microstep: 511.35 | bwd_inner_microstep: 511.33 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-01 22:10:54,416] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 332.63 | bwd_microstep: 517.30 | bwd_inner_microstep: 517.28 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.22 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1365 +[2025-05-01 22:10:55,096] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 242.05 | bwd_microstep: 414.44 | bwd_inner_microstep: 414.42 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-01 22:10:55,985] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 363.15 | bwd_microstep: 507.60 | bwd_inner_microstep: 507.58 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.91 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 839 +[2025-05-01 22:10:56,400] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 112.91 | bwd_microstep: 282.81 | bwd_inner_microstep: 282.79 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 322 +[2025-05-01 22:10:56,632] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 72.75 | bwd_microstep: 135.56 | bwd_inner_microstep: 135.54 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 22:10:57,427] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 330.34 | bwd_microstep: 437.00 | bwd_inner_microstep: 436.99 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 22:10:58,306] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 367.51 | bwd_microstep: 484.87 | bwd_inner_microstep: 484.85 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 22:10:59,199] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 383.59 | bwd_microstep: 483.66 | bwd_inner_microstep: 483.64 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 318 +[2025-05-01 22:10:59,431] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.50 | bwd_microstep: 119.66 | bwd_inner_microstep: 119.64 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.32 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 22:11:00,526] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.45 | optimizer_step: 18.58 +[2025-05-01 22:11:00,528] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 318.98 | bwd_microstep: 719.70 | bwd_inner_microstep: 500.36 | bwd_allreduce_microstep: 219.32 | step_microstep: 28.23 +[2025-05-01 22:11:00,529] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4484.83 | bwd: 6918.44 | bwd_inner: 6698.85 | bwd_allreduce: 219.39 | step: 40.02 + 2%|▏ | 138/8720 [27:54<29:24:09, 12.33s/it] {'loss': 2.244, 'grad_norm': 11.078019142150879, 'learning_rate': 5.267175572519084e-06, 'epoch': 0.16} + 2%|▏ | 138/8720 [27:54<29:24:09, 12.33s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2103 +[2025-05-01 22:11:01,515] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 360.46 | bwd_microstep: 582.46 | bwd_inner_microstep: 582.44 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1908 +[2025-05-01 22:11:02,389] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 321.93 | bwd_microstep: 520.25 | bwd_inner_microstep: 520.23 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.31 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1893 +[2025-05-01 22:11:03,257] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 327.70 | bwd_microstep: 505.84 | bwd_inner_microstep: 505.82 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.31 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1893 +[2025-05-01 22:11:04,121] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 327.73 | bwd_microstep: 502.86 | bwd_inner_microstep: 502.85 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1893 +[2025-05-01 22:11:04,999] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 330.55 | bwd_microstep: 515.00 | bwd_inner_microstep: 514.80 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-01 22:11:05,879] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 333.55 | bwd_microstep: 512.79 | bwd_inner_microstep: 512.77 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-01 22:11:06,758] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 336.40 | bwd_microstep: 515.58 | bwd_inner_microstep: 515.56 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.18 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 840 +[2025-05-01 22:11:07,181] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.25 | bwd_microstep: 208.62 | bwd_inner_microstep: 208.60 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 22:11:08,057] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 332.75 | bwd_microstep: 514.34 | bwd_inner_microstep: 514.33 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1348 +[2025-05-01 22:11:08,740] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 240.22 | bwd_microstep: 415.99 | bwd_inner_microstep: 415.89 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 22:11:09,630] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 364.28 | bwd_microstep: 506.11 | bwd_inner_microstep: 506.09 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.91 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 22:11:10,493] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 326.58 | bwd_microstep: 516.76 | bwd_inner_microstep: 516.75 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 22:11:11,359] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 318.50 | bwd_microstep: 514.13 | bwd_inner_microstep: 514.11 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 22:11:12,222] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 314.75 | bwd_microstep: 515.68 | bwd_inner_microstep: 515.66 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 22:11:13,077] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 313.58 | bwd_microstep: 509.18 | bwd_inner_microstep: 509.16 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.32 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1850 +[2025-05-01 22:11:14,183] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.32 | optimizer_step: 18.71 +[2025-05-01 22:11:14,185] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 326.49 | bwd_microstep: 723.68 | bwd_inner_microstep: 499.98 | bwd_allreduce_microstep: 223.69 | step_microstep: 28.37 +[2025-05-01 22:11:14,186] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 5062.68 | bwd: 8079.48 | bwd_inner: 7855.04 | bwd_allreduce: 224.00 | step: 49.88 + 2%|▏ | 139/8720 [28:07<30:20:41, 12.73s/it] {'loss': 1.6477, 'grad_norm': 9.930752754211426, 'learning_rate': 5.3053435114503825e-06, 'epoch': 0.16} + 2%|▏ | 139/8720 [28:07<30:20:41, 12.73s/it]dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1128 +[2025-05-01 22:11:14,758] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 214.33 | bwd_microstep: 317.17 | bwd_inner_microstep: 317.15 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.31 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1887 +[2025-05-01 22:11:15,625] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 315.06 | bwd_microstep: 517.68 | bwd_inner_microstep: 517.65 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.53 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-01 22:11:16,502] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 317.56 | bwd_microstep: 525.00 | bwd_inner_microstep: 524.98 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-01 22:11:17,369] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 321.45 | bwd_microstep: 512.10 | bwd_inner_microstep: 512.09 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.45 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1357 +[2025-05-01 22:11:18,012] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 220.57 | bwd_microstep: 392.98 | bwd_inner_microstep: 392.86 | bwd_allreduce_microstep: 0.03 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 22:11:18,915] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 397.86 | bwd_microstep: 487.09 | bwd_inner_microstep: 487.07 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-01 22:11:19,814] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 375.32 | bwd_microstep: 504.61 | bwd_inner_microstep: 504.59 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.90 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 22:11:20,692] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 335.89 | bwd_microstep: 521.36 | bwd_inner_microstep: 521.34 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 22:11:21,550] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 318.67 | bwd_microstep: 516.02 | bwd_inner_microstep: 516.00 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 22:11:22,415] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 315.16 | bwd_microstep: 516.53 | bwd_inner_microstep: 516.51 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.32 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 22:11:23,275] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 312.12 | bwd_microstep: 513.29 | bwd_inner_microstep: 513.27 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.28 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 22:11:24,138] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 318.27 | bwd_microstep: 510.48 | bwd_inner_microstep: 510.47 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.28 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 22:11:24,995] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 327.58 | bwd_microstep: 495.54 | bwd_inner_microstep: 495.52 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 22:11:25,859] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 324.60 | bwd_microstep: 507.33 | bwd_inner_microstep: 507.31 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 22:11:26,732] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 329.60 | bwd_microstep: 512.82 | bwd_inner_microstep: 512.80 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 459 +[2025-05-01 22:11:27,329] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.34 | optimizer_step: 18.69 +[2025-05-01 22:11:27,331] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 117.03 | bwd_microstep: 427.54 | bwd_inner_microstep: 125.49 | bwd_allreduce_microstep: 301.96 | step_microstep: 28.19 +[2025-05-01 22:11:27,333] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4861.00 | bwd: 7777.56 | bwd_inner: 7475.18 | bwd_allreduce: 302.07 | step: 55.41 + 2%|▏ | 140/8720 [28:20<30:38:19, 12.86s/it] {'loss': 2.2777, 'grad_norm': 10.793413162231445, 'learning_rate': 5.34351145038168e-06, 'epoch': 0.16} + 2%|▏ | 140/8720 [28:20<30:38:19, 12.86s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1904 +[2025-05-01 22:11:28,209] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 318.76 | bwd_microstep: 524.94 | bwd_inner_microstep: 524.92 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-01 22:11:29,091] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 331.88 | bwd_microstep: 516.16 | bwd_inner_microstep: 516.14 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.31 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-01 22:11:29,943] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 321.66 | bwd_microstep: 501.35 | bwd_inner_microstep: 501.33 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.32 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-01 22:11:30,811] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 333.47 | bwd_microstep: 500.06 | bwd_inner_microstep: 500.04 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-01 22:11:31,689] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 346.53 | bwd_microstep: 497.35 | bwd_inner_microstep: 497.33 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.51 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-01 22:11:32,557] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 350.82 | bwd_microstep: 485.44 | bwd_inner_microstep: 485.42 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 856 +[2025-05-01 22:11:32,992] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 205.52 | bwd_microstep: 203.64 | bwd_inner_microstep: 203.54 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-01 22:11:33,871] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 362.07 | bwd_microstep: 487.25 | bwd_inner_microstep: 487.24 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-01 22:11:34,762] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 387.75 | bwd_microstep: 485.15 | bwd_inner_microstep: 485.13 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.12 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1109 +[2025-05-01 22:11:35,278] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 216.80 | bwd_microstep: 280.14 | bwd_inner_microstep: 280.12 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.48 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 22:11:36,139] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 345.49 | bwd_microstep: 485.67 | bwd_inner_microstep: 485.63 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 838 +[2025-05-01 22:11:36,570] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 203.61 | bwd_microstep: 195.43 | bwd_inner_microstep: 195.42 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-01 22:11:37,438] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 347.19 | bwd_microstep: 486.62 | bwd_inner_microstep: 486.61 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.31 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 323 +[2025-05-01 22:11:37,703] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 97.74 | bwd_microstep: 137.24 | bwd_inner_microstep: 137.22 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 22:11:38,558] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 321.48 | bwd_microstep: 511.67 | bwd_inner_microstep: 511.65 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.28 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 22:11:39,664] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.34 | optimizer_step: 18.64 +[2025-05-01 22:11:39,665] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 295.43 | bwd_microstep: 751.82 | bwd_inner_microstep: 505.69 | bwd_allreduce_microstep: 246.09 | step_microstep: 27.88 +[2025-05-01 22:11:39,667] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4786.18 | bwd: 7049.95 | bwd_inner: 6803.43 | bwd_allreduce: 246.22 | step: 51.98 + 2%|▏ | 141/8720 [28:33<30:15:48, 12.70s/it] {'loss': 2.3963, 'grad_norm': 13.744758605957031, 'learning_rate': 5.381679389312977e-06, 'epoch': 0.16} + 2%|▏ | 141/8720 [28:33<30:15:48, 12.70s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 388 +[2025-05-01 22:11:39,926] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 96.28 | bwd_microstep: 121.28 | bwd_inner_microstep: 121.26 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 368 +[2025-05-01 22:11:40,192] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 99.07 | bwd_microstep: 136.37 | bwd_inner_microstep: 136.05 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.19 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1364 +[2025-05-01 22:11:40,839] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 239.23 | bwd_microstep: 388.59 | bwd_inner_microstep: 388.57 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1096 +[2025-05-01 22:11:41,397] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 218.92 | bwd_microstep: 308.65 | bwd_inner_microstep: 308.63 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.31 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 845 +[2025-05-01 22:11:41,831] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 120.40 | bwd_microstep: 283.88 | bwd_inner_microstep: 283.86 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.47 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-01 22:11:42,712] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 322.46 | bwd_microstep: 523.83 | bwd_inner_microstep: 523.81 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.48 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 839 +[2025-05-01 22:11:43,130] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 113.81 | bwd_microstep: 272.03 | bwd_inner_microstep: 272.01 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.33 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 844 +[2025-05-01 22:11:43,566] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 119.51 | bwd_microstep: 284.58 | bwd_inner_microstep: 284.56 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.32 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-01 22:11:44,430] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 316.75 | bwd_microstep: 514.25 | bwd_inner_microstep: 514.23 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-01 22:11:45,290] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 313.00 | bwd_microstep: 513.72 | bwd_inner_microstep: 513.70 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 22:11:46,154] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 321.79 | bwd_microstep: 509.74 | bwd_inner_microstep: 509.73 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.31 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 22:11:47,022] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 330.86 | bwd_microstep: 500.77 | bwd_inner_microstep: 500.75 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.31 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 22:11:47,881] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 331.12 | bwd_microstep: 493.56 | bwd_inner_microstep: 493.55 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 22:11:48,753] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 333.10 | bwd_microstep: 506.57 | bwd_inner_microstep: 506.55 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 22:11:49,628] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 335.06 | bwd_microstep: 512.71 | bwd_inner_microstep: 512.69 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-01 22:11:50,787] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.22 | optimizer_step: 17.12 +[2025-05-01 22:11:50,788] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 331.45 | bwd_microstep: 774.43 | bwd_inner_microstep: 517.03 | bwd_allreduce_microstep: 257.38 | step_microstep: 26.74 +[2025-05-01 22:11:50,789] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 3942.80 | bwd: 6645.00 | bwd_inner: 6387.07 | bwd_allreduce: 257.57 | step: 53.42 + 2%|▏ | 142/8720 [28:44<29:07:54, 12.23s/it] {'loss': 2.9542, 'grad_norm': 16.288944244384766, 'learning_rate': 5.419847328244276e-06, 'epoch': 0.16} + 2%|▏ | 142/8720 [28:44<29:07:54, 12.23s/it]dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 993 +[2025-05-01 22:11:51,308] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 177.52 | bwd_microstep: 301.05 | bwd_inner_microstep: 301.03 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.48 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1966 +[2025-05-01 22:11:52,232] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 337.58 | bwd_microstep: 553.73 | bwd_inner_microstep: 553.71 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2043 +[2025-05-01 22:11:53,180] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 346.49 | bwd_microstep: 570.00 | bwd_inner_microstep: 569.98 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.63 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1935 +[2025-05-01 22:11:54,092] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 345.67 | bwd_microstep: 546.37 | bwd_inner_microstep: 546.35 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.49 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 368 +[2025-05-01 22:11:54,322] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 74.74 | bwd_microstep: 138.00 | bwd_inner_microstep: 137.87 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.18 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 362 +[2025-05-01 22:11:54,561] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 106.89 | bwd_microstep: 108.31 | bwd_inner_microstep: 108.12 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 340 +[2025-05-01 22:11:54,805] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 99.36 | bwd_microstep: 126.20 | bwd_inner_microstep: 126.18 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.33 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 834 +[2025-05-01 22:11:55,222] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 139.60 | bwd_microstep: 247.68 | bwd_inner_microstep: 247.66 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-01 22:11:56,092] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 318.78 | bwd_microstep: 517.06 | bwd_inner_microstep: 517.04 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.33 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 22:11:56,951] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 321.91 | bwd_microstep: 502.12 | bwd_inner_microstep: 502.10 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.33 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 22:11:57,816] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 325.37 | bwd_microstep: 509.37 | bwd_inner_microstep: 509.35 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 22:11:58,692] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 333.38 | bwd_microstep: 514.15 | bwd_inner_microstep: 514.14 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 22:11:59,566] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 331.44 | bwd_microstep: 513.76 | bwd_inner_microstep: 513.74 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.33 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 22:12:00,444] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 336.54 | bwd_microstep: 514.91 | bwd_inner_microstep: 514.89 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 22:12:01,316] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 329.41 | bwd_microstep: 512.63 | bwd_inner_microstep: 512.61 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 22:12:02,449] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.21 | optimizer_step: 18.83 +[2025-05-01 22:12:02,451] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 332.66 | bwd_microstep: 745.35 | bwd_inner_microstep: 504.71 | bwd_allreduce_microstep: 240.63 | step_microstep: 28.21 +[2025-05-01 22:12:02,452] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4257.31 | bwd: 6920.70 | bwd_inner: 6679.57 | bwd_allreduce: 240.79 | step: 51.00 + 2%|▏ | 143/8720 [28:55<28:43:32, 12.06s/it] {'loss': 2.301, 'grad_norm': 9.870163917541504, 'learning_rate': 5.458015267175573e-06, 'epoch': 0.16} + 2%|▏ | 143/8720 [28:55<28:43:32, 12.06s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 383 +[2025-05-01 22:12:02,704] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 111.84 | bwd_microstep: 103.07 | bwd_inner_microstep: 102.94 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-01 22:12:03,607] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 386.59 | bwd_microstep: 500.81 | bwd_inner_microstep: 500.79 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 359 +[2025-05-01 22:12:03,843] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 87.13 | bwd_microstep: 132.12 | bwd_inner_microstep: 132.10 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 352 +[2025-05-01 22:12:04,102] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 104.60 | bwd_microstep: 124.67 | bwd_inner_microstep: 124.65 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.33 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1904 +[2025-05-01 22:12:04,967] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 341.37 | bwd_microstep: 490.88 | bwd_inner_microstep: 490.86 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-01 22:12:05,842] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 358.13 | bwd_microstep: 487.14 | bwd_inner_microstep: 487.12 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-01 22:12:06,725] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 368.73 | bwd_microstep: 487.30 | bwd_inner_microstep: 487.22 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-01 22:12:07,627] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 397.04 | bwd_microstep: 487.05 | bwd_inner_microstep: 487.03 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-01 22:12:08,527] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 388.02 | bwd_microstep: 495.42 | bwd_inner_microstep: 495.41 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 840 +[2025-05-01 22:12:08,956] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 145.58 | bwd_microstep: 268.53 | bwd_inner_microstep: 268.17 | bwd_allreduce_microstep: 0.34 | step_microstep: 0.22 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-01 22:12:09,792] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 299.42 | bwd_microstep: 517.04 | bwd_inner_microstep: 517.02 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.39 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-01 22:12:10,665] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 319.97 | bwd_microstep: 518.48 | bwd_inner_microstep: 518.46 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.51 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1350 +[2025-05-01 22:12:11,294] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 224.25 | bwd_microstep: 377.30 | bwd_inner_microstep: 377.29 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1341 +[2025-05-01 22:12:11,987] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 307.57 | bwd_microstep: 368.66 | bwd_inner_microstep: 368.64 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.31 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 22:12:12,844] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 317.86 | bwd_microstep: 506.70 | bwd_inner_microstep: 506.68 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-01 22:12:13,933] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.23 | optimizer_step: 18.89 +[2025-05-01 22:12:13,936] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 321.48 | bwd_microstep: 709.61 | bwd_inner_microstep: 504.17 | bwd_allreduce_microstep: 205.42 | step_microstep: 28.47 +[2025-05-01 22:12:13,937] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4479.52 | bwd: 6574.78 | bwd_inner: 6368.59 | bwd_allreduce: 205.89 | step: 45.62 + 2%|▏ | 144/8720 [29:07<28:18:48, 11.89s/it] {'loss': 2.3755, 'grad_norm': 10.555292129516602, 'learning_rate': 5.496183206106871e-06, 'epoch': 0.17} + 2%|▏ | 144/8720 [29:07<28:18:48, 11.89s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2027 +[2025-05-01 22:12:14,880] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 356.23 | bwd_microstep: 554.75 | bwd_inner_microstep: 554.73 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.28 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 987 +[2025-05-01 22:12:15,389] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 183.04 | bwd_microstep: 295.53 | bwd_inner_microstep: 295.51 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.29 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1946 +[2025-05-01 22:12:16,303] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 331.24 | bwd_microstep: 550.67 | bwd_inner_microstep: 550.65 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.46 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1970 +[2025-05-01 22:12:17,230] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 339.85 | bwd_microstep: 553.30 | bwd_inner_microstep: 553.28 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 860 +[2025-05-01 22:12:17,663] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 119.82 | bwd_microstep: 291.65 | bwd_inner_microstep: 291.63 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-01 22:12:18,514] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 322.58 | bwd_microstep: 505.88 | bwd_inner_microstep: 505.86 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1354 +[2025-05-01 22:12:19,139] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 225.97 | bwd_microstep: 366.82 | bwd_inner_microstep: 366.80 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.33 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 22:12:19,997] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 347.18 | bwd_microstep: 481.18 | bwd_inner_microstep: 481.17 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 22:12:20,870] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 357.09 | bwd_microstep: 480.75 | bwd_inner_microstep: 480.73 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-01 22:12:21,756] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 378.38 | bwd_microstep: 483.06 | bwd_inner_microstep: 483.04 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 835 +[2025-05-01 22:12:22,197] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 183.31 | bwd_microstep: 239.00 | bwd_inner_microstep: 238.85 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 22:12:23,095] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 385.36 | bwd_microstep: 491.71 | bwd_inner_microstep: 491.69 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.90 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 22:12:23,964] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 336.84 | bwd_microstep: 510.66 | bwd_inner_microstep: 510.65 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 22:12:24,807] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 312.67 | bwd_microstep: 507.23 | bwd_inner_microstep: 507.21 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 22:12:25,674] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 315.24 | bwd_microstep: 513.91 | bwd_inner_microstep: 513.89 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.48 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 22:12:26,762] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.29 | optimizer_step: 18.65 +[2025-05-01 22:12:26,764] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 315.03 | bwd_microstep: 715.06 | bwd_inner_microstep: 511.70 | bwd_allreduce_microstep: 203.34 | step_microstep: 28.35 +[2025-05-01 22:12:26,766] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4809.76 | bwd: 7541.18 | bwd_inner: 7337.46 | bwd_allreduce: 203.46 | step: 53.19 + 2%|▏ | 145/8720 [29:20<28:59:04, 12.17s/it] {'loss': 1.8741, 'grad_norm': 9.377681732177734, 'learning_rate': 5.534351145038168e-06, 'epoch': 0.17} + 2%|▏ | 145/8720 [29:20<28:59:04, 12.17s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1971 +[2025-05-01 22:12:27,678] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 338.62 | bwd_microstep: 531.81 | bwd_inner_microstep: 531.79 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.32 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1892 +[2025-05-01 22:12:28,547] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 325.14 | bwd_microstep: 511.70 | bwd_inner_microstep: 511.68 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.18 +dynamic ViT batch size: 6, images per sample: 6.0, dynamic token length: 1615 +[2025-05-01 22:12:29,313] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 283.56 | bwd_microstep: 450.96 | bwd_inner_microstep: 450.94 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1361 +[2025-05-01 22:12:30,025] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 284.82 | bwd_microstep: 391.45 | bwd_inner_microstep: 391.43 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.33 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-01 22:12:30,883] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 322.23 | bwd_microstep: 510.09 | bwd_inner_microstep: 510.07 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.30 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-01 22:12:31,741] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 313.39 | bwd_microstep: 508.82 | bwd_inner_microstep: 508.80 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.30 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 334 +[2025-05-01 22:12:32,007] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 91.25 | bwd_microstep: 140.10 | bwd_inner_microstep: 140.08 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-01 22:12:32,890] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 330.10 | bwd_microstep: 518.77 | bwd_inner_microstep: 518.75 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1357 +[2025-05-01 22:12:33,572] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 241.46 | bwd_microstep: 415.25 | bwd_inner_microstep: 415.23 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-01 22:12:34,458] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 364.60 | bwd_microstep: 502.73 | bwd_inner_microstep: 502.71 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-01 22:12:35,310] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 325.85 | bwd_microstep: 507.40 | bwd_inner_microstep: 507.39 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 22:12:36,159] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 313.18 | bwd_microstep: 501.49 | bwd_inner_microstep: 501.47 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.31 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 22:12:37,027] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 314.18 | bwd_microstep: 519.64 | bwd_inner_microstep: 519.62 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 22:12:37,886] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 316.38 | bwd_microstep: 508.22 | bwd_inner_microstep: 508.20 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.50 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 22:12:38,750] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 328.78 | bwd_microstep: 500.86 | bwd_inner_microstep: 500.84 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 22:12:39,871] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.26 | optimizer_step: 18.75 +[2025-05-01 22:12:39,873] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 322.72 | bwd_microstep: 740.80 | bwd_inner_microstep: 505.46 | bwd_allreduce_microstep: 235.32 | step_microstep: 28.21 +[2025-05-01 22:12:39,874] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4816.22 | bwd: 7760.09 | bwd_inner: 7524.50 | bwd_allreduce: 235.39 | step: 54.64 + 2%|▏ | 146/8720 [29:33<29:39:11, 12.45s/it] {'loss': 3.8732, 'grad_norm': 13.496726989746094, 'learning_rate': 5.572519083969467e-06, 'epoch': 0.17} + 2%|▏ | 146/8720 [29:33<29:39:11, 12.45s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1908 +[2025-05-01 22:12:40,764] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 325.84 | bwd_microstep: 522.34 | bwd_inner_microstep: 522.32 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.22 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1941 +[2025-05-01 22:12:41,670] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 347.03 | bwd_microstep: 528.04 | bwd_inner_microstep: 528.02 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.47 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1889 +[2025-05-01 22:12:42,543] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 329.46 | bwd_microstep: 510.40 | bwd_inner_microstep: 510.39 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-01 22:12:43,418] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 331.83 | bwd_microstep: 514.70 | bwd_inner_microstep: 514.68 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-01 22:12:44,289] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 327.58 | bwd_microstep: 513.50 | bwd_inner_microstep: 513.48 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.14 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-01 22:12:45,089] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 334.46 | bwd_microstep: 437.18 | bwd_inner_microstep: 437.16 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.78 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 330 +[2025-05-01 22:12:45,309] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 87.40 | bwd_microstep: 117.70 | bwd_inner_microstep: 117.02 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.21 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 22:12:46,055] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 300.08 | bwd_microstep: 428.02 | bwd_inner_microstep: 428.00 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.80 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-01 22:12:46,809] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 299.40 | bwd_microstep: 437.09 | bwd_inner_microstep: 437.07 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 22:12:47,564] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 301.33 | bwd_microstep: 434.58 | bwd_inner_microstep: 434.57 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1350 +[2025-05-01 22:12:48,126] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 212.48 | bwd_microstep: 331.63 | bwd_inner_microstep: 331.61 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.21 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-01 22:12:48,888] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 306.06 | bwd_microstep: 435.43 | bwd_inner_microstep: 435.41 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.65 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 326 +[2025-05-01 22:12:49,139] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 109.88 | bwd_microstep: 121.89 | bwd_inner_microstep: 121.87 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 22:12:49,974] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 309.04 | bwd_microstep: 492.00 | bwd_inner_microstep: 491.98 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1341 +[2025-05-01 22:12:50,618] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 245.13 | bwd_microstep: 379.13 | bwd_inner_microstep: 379.11 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 22:12:51,723] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.19 | optimizer_step: 24.08 +[2025-05-01 22:12:51,724] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 303.59 | bwd_microstep: 739.52 | bwd_inner_microstep: 489.24 | bwd_allreduce_microstep: 250.26 | step_microstep: 31.79 +[2025-05-01 22:12:51,725] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4470.55 | bwd: 6943.14 | bwd_inner: 6692.22 | bwd_allreduce: 250.33 | step: 43.62 + 2%|▏ | 147/8720 [29:45<29:13:07, 12.27s/it] {'loss': 2.302, 'grad_norm': 13.149182319641113, 'learning_rate': 5.610687022900764e-06, 'epoch': 0.17} + 2%|▏ | 147/8720 [29:45<29:13:07, 12.27s/it]dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1408 +[2025-05-01 22:12:52,401] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 274.09 | bwd_microstep: 375.04 | bwd_inner_microstep: 375.02 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.52 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1910 +[2025-05-01 22:12:53,274] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 330.19 | bwd_microstep: 510.92 | bwd_inner_microstep: 510.91 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.20 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1385 +[2025-05-01 22:12:53,955] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 235.47 | bwd_microstep: 415.04 | bwd_inner_microstep: 414.86 | bwd_allreduce_microstep: 0.08 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1893 +[2025-05-01 22:12:54,858] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 381.08 | bwd_microstep: 503.93 | bwd_inner_microstep: 503.91 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-01 22:12:55,748] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 347.04 | bwd_microstep: 519.19 | bwd_inner_microstep: 519.18 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.53 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1889 +[2025-05-01 22:12:56,604] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 314.51 | bwd_microstep: 519.36 | bwd_inner_microstep: 519.34 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1894 +[2025-05-01 22:12:57,469] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 313.96 | bwd_microstep: 519.88 | bwd_inner_microstep: 519.86 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.44 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-01 22:12:58,341] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 319.60 | bwd_microstep: 518.02 | bwd_inner_microstep: 518.00 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.28 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-01 22:12:59,204] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 308.65 | bwd_microstep: 519.80 | bwd_inner_microstep: 519.78 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-01 22:13:00,062] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 321.59 | bwd_microstep: 503.74 | bwd_inner_microstep: 503.72 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.51 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-01 22:13:00,922] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 323.92 | bwd_microstep: 504.38 | bwd_inner_microstep: 504.36 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.23 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-01 22:13:01,797] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 334.01 | bwd_microstep: 510.37 | bwd_inner_microstep: 510.36 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-01 22:13:02,673] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 330.74 | bwd_microstep: 515.43 | bwd_inner_microstep: 515.41 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.45 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 22:13:03,549] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 334.17 | bwd_microstep: 513.04 | bwd_inner_microstep: 513.02 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.44 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 22:13:04,412] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 322.86 | bwd_microstep: 511.80 | bwd_inner_microstep: 511.79 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 22:13:05,651] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.20 | optimizer_step: 18.75 +[2025-05-01 22:13:05,654] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 333.18 | bwd_microstep: 841.10 | bwd_inner_microstep: 513.17 | bwd_allreduce_microstep: 327.91 | step_microstep: 28.12 +[2025-05-01 22:13:05,655] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 5124.99 | bwd: 8301.06 | bwd_inner: 7972.71 | bwd_allreduce: 328.09 | step: 53.09 + 2%|▏ | 148/8720 [29:59<30:24:11, 12.77s/it] {'loss': 2.2281, 'grad_norm': 9.370696067810059, 'learning_rate': 5.648854961832062e-06, 'epoch': 0.17} + 2%|▏ | 148/8720 [29:59<30:24:11, 12.77s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2141 +[2025-05-01 22:13:06,634] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 351.89 | bwd_microstep: 591.98 | bwd_inner_microstep: 591.97 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.31 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1967 +[2025-05-01 22:13:07,557] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 366.90 | bwd_microstep: 539.18 | bwd_inner_microstep: 539.17 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1954 +[2025-05-01 22:13:08,470] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 367.12 | bwd_microstep: 526.67 | bwd_inner_microstep: 526.65 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1914 +[2025-05-01 22:13:09,334] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 319.28 | bwd_microstep: 525.26 | bwd_inner_microstep: 525.24 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.33 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1909 +[2025-05-01 22:13:10,167] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 337.87 | bwd_microstep: 463.85 | bwd_inner_microstep: 463.84 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1899 +[2025-05-01 22:13:11,039] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 337.50 | bwd_microstep: 515.16 | bwd_inner_microstep: 515.14 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.30 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-01 22:13:11,895] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 329.05 | bwd_microstep: 491.23 | bwd_inner_microstep: 491.21 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-01 22:13:12,746] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 345.22 | bwd_microstep: 483.31 | bwd_inner_microstep: 483.29 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-01 22:13:13,631] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 325.68 | bwd_microstep: 519.87 | bwd_inner_microstep: 519.85 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.88 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-01 22:13:14,456] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 347.17 | bwd_microstep: 456.04 | bwd_inner_microstep: 456.02 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.43 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 22:13:15,353] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 344.83 | bwd_microstep: 516.84 | bwd_inner_microstep: 516.82 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 22:13:16,157] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 325.89 | bwd_microstep: 458.91 | bwd_inner_microstep: 458.89 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-01 22:13:17,010] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 346.09 | bwd_microstep: 490.69 | bwd_inner_microstep: 490.67 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 22:13:17,882] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 325.15 | bwd_microstep: 515.73 | bwd_inner_microstep: 515.71 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.89 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 22:13:18,684] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 338.62 | bwd_microstep: 445.17 | bwd_inner_microstep: 445.15 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 22:13:19,819] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.21 | optimizer_step: 17.34 +[2025-05-01 22:13:19,820] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 328.76 | bwd_microstep: 749.82 | bwd_inner_microstep: 498.21 | bwd_allreduce_microstep: 251.60 | step_microstep: 27.01 +[2025-05-01 22:13:19,821] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 5436.92 | bwd: 8289.70 | bwd_inner: 8037.83 | bwd_allreduce: 251.66 | step: 45.72 + 2%|▏ | 149/8720 [30:13<31:23:52, 13.19s/it] {'loss': 2.346, 'grad_norm': 8.651248931884766, 'learning_rate': 5.687022900763359e-06, 'epoch': 0.17} + 2%|▏ | 149/8720 [30:13<31:23:52, 13.19s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 367 +[2025-05-01 22:13:20,091] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 103.91 | bwd_microstep: 126.37 | bwd_inner_microstep: 126.36 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.33 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-01 22:13:20,973] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 331.95 | bwd_microstep: 516.14 | bwd_inner_microstep: 516.12 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.32 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 334 +[2025-05-01 22:13:21,234] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.63 | bwd_microstep: 136.73 | bwd_inner_microstep: 136.71 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-01 22:13:22,092] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 325.46 | bwd_microstep: 514.37 | bwd_inner_microstep: 514.35 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.51 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 22:13:22,969] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 324.34 | bwd_microstep: 518.58 | bwd_inner_microstep: 518.56 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.49 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 22:13:23,821] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 304.65 | bwd_microstep: 515.77 | bwd_inner_microstep: 515.76 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.48 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 326 +[2025-05-01 22:13:24,081] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 86.86 | bwd_microstep: 140.55 | bwd_inner_microstep: 140.53 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 836 +[2025-05-01 22:13:24,523] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 206.49 | bwd_microstep: 210.21 | bwd_inner_microstep: 210.20 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 22:13:25,397] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 335.17 | bwd_microstep: 511.24 | bwd_inner_microstep: 511.22 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 22:13:26,275] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 333.01 | bwd_microstep: 516.84 | bwd_inner_microstep: 516.82 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 22:13:27,150] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 330.34 | bwd_microstep: 516.69 | bwd_inner_microstep: 516.67 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.87 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 317 +[2025-05-01 22:13:27,385] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.38 | bwd_microstep: 113.56 | bwd_inner_microstep: 113.29 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1341 +[2025-05-01 22:13:28,033] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 263.65 | bwd_microstep: 370.07 | bwd_inner_microstep: 369.87 | bwd_allreduce_microstep: 0.18 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-01 22:13:28,908] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 331.49 | bwd_microstep: 514.02 | bwd_inner_microstep: 514.00 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.47 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 22:13:29,782] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 331.07 | bwd_microstep: 514.02 | bwd_inner_microstep: 514.00 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 22:13:30,922] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.20 | optimizer_step: 18.69 +[2025-05-01 22:13:30,924] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 332.18 | bwd_microstep: 754.47 | bwd_inner_microstep: 516.00 | bwd_allreduce_microstep: 238.46 | step_microstep: 28.32 +[2025-05-01 22:13:30,925] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4131.55 | bwd: 6489.64 | bwd_inner: 6250.52 | bwd_allreduce: 238.80 | step: 50.54 + 2%|▏ | 150/8720 [30:24<29:54:24, 12.56s/it] {'loss': 2.178, 'grad_norm': 13.605570793151855, 'learning_rate': 5.725190839694656e-06, 'epoch': 0.17} + 2%|▏ | 150/8720 [30:24<29:54:24, 12.56s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1967 +[2025-05-01 22:13:31,848] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 350.02 | bwd_microstep: 528.97 | bwd_inner_microstep: 528.95 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1926 +[2025-05-01 22:13:32,762] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 348.64 | bwd_microstep: 531.80 | bwd_inner_microstep: 531.78 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1928 +[2025-05-01 22:13:33,673] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 337.61 | bwd_microstep: 539.48 | bwd_inner_microstep: 539.46 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1903 +[2025-05-01 22:13:34,548] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 322.85 | bwd_microstep: 520.22 | bwd_inner_microstep: 520.20 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.31 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1894 +[2025-05-01 22:13:35,423] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 328.59 | bwd_microstep: 511.68 | bwd_inner_microstep: 511.66 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.47 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-01 22:13:36,284] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 334.51 | bwd_microstep: 492.33 | bwd_inner_microstep: 492.31 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 856 +[2025-05-01 22:13:36,732] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 181.14 | bwd_microstep: 235.43 | bwd_inner_microstep: 235.41 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.33 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1883 +[2025-05-01 22:13:37,602] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 330.04 | bwd_microstep: 505.80 | bwd_inner_microstep: 505.78 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 334 +[2025-05-01 22:13:37,854] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 98.95 | bwd_microstep: 121.01 | bwd_inner_microstep: 120.99 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.33 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-01 22:13:38,723] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 345.80 | bwd_microstep: 488.61 | bwd_inner_microstep: 488.59 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 22:13:39,593] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 354.46 | bwd_microstep: 483.04 | bwd_inner_microstep: 483.02 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1354 +[2025-05-01 22:13:40,301] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 312.01 | bwd_microstep: 368.79 | bwd_inner_microstep: 368.77 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.52 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 22:13:41,155] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 304.80 | bwd_microstep: 517.18 | bwd_inner_microstep: 517.16 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.50 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 832 +[2025-05-01 22:13:41,576] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 136.04 | bwd_microstep: 250.68 | bwd_inner_microstep: 250.66 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 828 +[2025-05-01 22:13:42,008] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 135.99 | bwd_microstep: 259.49 | bwd_inner_microstep: 259.48 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.28 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 22:13:43,156] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.25 | optimizer_step: 18.67 +[2025-05-01 22:13:43,158] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 309.75 | bwd_microstep: 780.59 | bwd_inner_microstep: 518.28 | bwd_allreduce_microstep: 262.30 | step_microstep: 28.33 +[2025-05-01 22:13:43,159] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4531.18 | bwd: 7135.09 | bwd_inner: 6872.52 | bwd_allreduce: 262.36 | step: 61.52 + 2%|▏ | 151/8720 [30:36<29:40:06, 12.46s/it] {'loss': 1.7978, 'grad_norm': 8.043210983276367, 'learning_rate': 5.763358778625955e-06, 'epoch': 0.17} + 2%|▏ | 151/8720 [30:36<29:40:06, 12.46s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1997 +[2025-05-01 22:13:44,097] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 335.15 | bwd_microstep: 560.72 | bwd_inner_microstep: 560.71 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.32 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 884 +[2025-05-01 22:13:44,547] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 120.67 | bwd_microstep: 297.59 | bwd_inner_microstep: 297.57 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.33 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 855 +[2025-05-01 22:13:45,009] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 147.99 | bwd_microstep: 289.20 | bwd_inner_microstep: 289.18 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-01 22:13:45,875] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 321.57 | bwd_microstep: 522.68 | bwd_inner_microstep: 522.66 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.33 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-01 22:13:46,750] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 322.04 | bwd_microstep: 518.65 | bwd_inner_microstep: 518.63 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-01 22:13:47,622] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 318.70 | bwd_microstep: 519.11 | bwd_inner_microstep: 519.09 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-01 22:13:48,499] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 318.48 | bwd_microstep: 524.82 | bwd_inner_microstep: 524.80 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.49 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-01 22:14:31,209] [INFO] [real_accelerator.py:203:get_accelerator] Setting ds_accelerator to cuda (auto detect) +/home1/gmh/anaconda3/envs/promptbench/lib/python3.9/site-packages/timm/models/layers/__init__.py:48: FutureWarning: Importing from timm.models.layers is deprecated, please import via timm.layers + warnings.warn(f"Importing from {__name__} is deprecated, please import via timm.layers", FutureWarning) +petrel_client is not installed. If you read data locally instead of from ceph, ignore it. +petrel_client is not installed. Using PIL to load images. +[2025-05-01 22:14:35,499] [INFO] [comm.py:652:init_distributed] cdb=None +[2025-05-01 22:14:35,500] [INFO] [comm.py:683:init_distributed] Initializing TorchBackend in DeepSpeed with backend nccl +05/01/2025 22:14:35 - WARNING - __main__ - Process rank: 0, device: cuda:0, n_gpu: 1distributed training: True, 16-bits training: False +05/01/2025 22:14:35 - INFO - __main__ - Training/evaluation parameters TrainingArguments( +_n_gpu=1, +accelerator_config={'split_batches': False, 'dispatch_batches': None, 'even_batches': True, 'use_seedable_sampler': True, 'non_blocking': False, 'gradient_accumulation_kwargs': None, 'use_configured_state': False}, +adafactor=False, +adam_beta1=0.9, +adam_beta2=0.999, +adam_epsilon=1e-08, +auto_find_batch_size=False, +batch_eval_metrics=False, +bf16=True, +bf16_full_eval=False, +data_seed=None, +dataloader_drop_last=False, +dataloader_num_workers=4, +dataloader_persistent_workers=False, +dataloader_pin_memory=True, +dataloader_prefetch_factor=None, +ddp_backend=None, +ddp_broadcast_buffers=None, +ddp_bucket_cap_mb=None, +ddp_find_unused_parameters=None, +ddp_timeout=1800, +debug=[], +deepspeed=zero_stage1_config.json, +disable_tqdm=False, +dispatch_batches=None, +do_eval=False, +do_predict=False, +do_train=True, +eval_accumulation_steps=None, +eval_delay=0, +eval_do_concat_batches=True, +eval_on_start=False, +eval_steps=None, +eval_strategy=no, +eval_use_gather_object=False, +evaluation_strategy=no, +fp16=False, +fp16_backend=auto, +fp16_full_eval=False, +fp16_opt_level=O1, +fsdp=[], +fsdp_config={'min_num_params': 0, 'xla': False, 'xla_fsdp_v2': False, 'xla_fsdp_grad_ckpt': False}, +fsdp_min_num_params=0, +fsdp_transformer_layer_cls_to_wrap=None, +full_determinism=False, +gradient_accumulation_steps=16, +gradient_checkpointing=False, +gradient_checkpointing_kwargs=None, +greater_is_better=None, +group_by_length=True, +half_precision_backend=auto, +hub_always_push=False, +hub_model_id=None, +hub_private_repo=False, +hub_strategy=every_save, +hub_token=, +ignore_data_skip=False, +include_inputs_for_metrics=False, +include_num_input_tokens_seen=False, +include_tokens_per_second=False, +jit_mode_eval=False, +label_names=None, +label_smoothing_factor=0.0, +learning_rate=1e-05, +length_column_name=length, +load_best_model_at_end=False, +local_rank=0, +log_level=passive, +log_level_replica=warning, +log_on_each_node=True, +logging_dir=work_dirs/internvl_chat_v2_5/ak/runs/May01_22-14-35_9007, +logging_first_step=False, +logging_nan_inf_filter=True, +logging_steps=1.0, +logging_strategy=steps, +lr_scheduler_kwargs={}, +lr_scheduler_type=cosine, +max_grad_norm=1.0, +max_steps=-1, +metric_for_best_model=None, +mp_parameters=, +neftune_noise_alpha=None, +no_cuda=False, +num_train_epochs=10.0, +optim=adamw_torch, +optim_args=None, +optim_target_modules=None, +output_dir=work_dirs/internvl_chat_v2_5/ak, +overwrite_output_dir=True, +past_index=-1, +per_device_eval_batch_size=8, +per_device_train_batch_size=1, +prediction_loss_only=False, +push_to_hub=False, +push_to_hub_model_id=None, +push_to_hub_organization=None, +push_to_hub_token=, +ray_scope=last, +remove_unused_columns=True, +report_to=['tensorboard'], +restore_callback_states_from_checkpoint=False, +resume_from_checkpoint=None, +run_name=work_dirs/internvl_chat_v2_5/ak, +save_on_each_node=False, +save_only_model=False, +save_safetensors=True, +save_steps=100, +save_strategy=steps, +save_total_limit=100, +seed=42, +skip_memory_metrics=True, +split_batches=None, +tf32=None, +torch_compile=False, +torch_compile_backend=None, +torch_compile_mode=None, +torch_empty_cache_steps=None, +torchdynamo=None, +tpu_metrics_debug=False, +tpu_num_cores=None, +use_cpu=False, +use_ipex=False, +use_legacy_prediction_loop=False, +use_mps_device=False, +warmup_ratio=0.03, +warmup_steps=0, +weight_decay=0.01, +) +05/01/2025 22:14:35 - INFO - __main__ - Loading Tokenizer: OpenGVLab/InternVL2_5-2B +[INFO|tokenization_utils_base.py:2289] 2025-05-01 22:14:55,684 >> loading file ./tokenizer.model from cache at /home1/gmh/.cache/huggingface/hub/models--OpenGVLab--InternVL2_5-2B/snapshots/573169ee54df216786bb9a189e9a32a060a008cf/./tokenizer.model +[INFO|tokenization_utils_base.py:2289] 2025-05-01 22:14:55,684 >> loading file added_tokens.json from cache at /home1/gmh/.cache/huggingface/hub/models--OpenGVLab--InternVL2_5-2B/snapshots/573169ee54df216786bb9a189e9a32a060a008cf/added_tokens.json +[INFO|tokenization_utils_base.py:2289] 2025-05-01 22:14:55,684 >> loading file special_tokens_map.json from cache at /home1/gmh/.cache/huggingface/hub/models--OpenGVLab--InternVL2_5-2B/snapshots/573169ee54df216786bb9a189e9a32a060a008cf/special_tokens_map.json +[INFO|tokenization_utils_base.py:2289] 2025-05-01 22:14:55,684 >> loading file tokenizer_config.json from cache at /home1/gmh/.cache/huggingface/hub/models--OpenGVLab--InternVL2_5-2B/snapshots/573169ee54df216786bb9a189e9a32a060a008cf/tokenizer_config.json +[INFO|tokenization_utils_base.py:2289] 2025-05-01 22:14:55,684 >> loading file tokenizer.json from cache at None +[INFO|tokenization_utils_base.py:2533] 2025-05-01 22:14:55,935 >> Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained. +05/01/2025 22:14:56 - INFO - __main__ - Loading InternVLChatModel... +[INFO|configuration_utils.py:733] 2025-05-01 22:15:06,128 >> loading configuration file config.json from cache at /home1/gmh/.cache/huggingface/hub/models--OpenGVLab--InternVL2_5-2B/snapshots/573169ee54df216786bb9a189e9a32a060a008cf/config.json +[INFO|configuration_utils.py:800] 2025-05-01 22:15:06,131 >> Model config InternVLChatConfig { + "_commit_hash": "573169ee54df216786bb9a189e9a32a060a008cf", + "architectures": [ + "InternVLChatModel" + ], + "auto_map": { + "AutoConfig": "OpenGVLab/InternVL2_5-2B--configuration_internvl_chat.InternVLChatConfig", + "AutoModel": "OpenGVLab/InternVL2_5-2B--modeling_internvl_chat.InternVLChatModel", + "AutoModelForCausalLM": "OpenGVLab/InternVL2_5-2B--modeling_internvl_chat.InternVLChatModel" + }, + "downsample_ratio": 0.5, + "dynamic_image_size": true, + "force_image_size": 448, + "hidden_size": 2048, + "llm_config": { + "_name_or_path": "internlm/internlm2_5-1_8b-chat", + "add_cross_attention": false, + "architectures": [ + "InternLM2ForCausalLM" + ], + "attn_implementation": "flash_attention_2", + "auto_map": { + "AutoConfig": "configuration_internlm2.InternLM2Config", + "AutoModel": "modeling_internlm2.InternLM2ForCausalLM", + "AutoModelForCausalLM": "modeling_internlm2.InternLM2ForCausalLM", + "AutoModelForSequenceClassification": "modeling_internlm2.InternLM2ForSequenceClassification" + }, + "bad_words_ids": null, + "begin_suppress_tokens": null, + "bias": false, + "bos_token_id": 1, + "chunk_size_feed_forward": 0, + "cross_attention_hidden_size": null, + "decoder_start_token_id": null, + "diversity_penalty": 0.0, + "do_sample": false, + "early_stopping": false, + "encoder_no_repeat_ngram_size": 0, + "eos_token_id": 2, + "exponential_decay_length_penalty": null, + "finetuning_task": null, + "forced_bos_token_id": null, + "forced_eos_token_id": null, + "hidden_act": "silu", + "hidden_size": 2048, + "id2label": { + "0": "LABEL_0", + "1": "LABEL_1" + }, + "initializer_range": 0.02, + "intermediate_size": 8192, + "is_decoder": false, + "is_encoder_decoder": false, + "label2id": { + "LABEL_0": 0, + "LABEL_1": 1 + }, + "length_penalty": 1.0, + "max_length": 20, + "max_position_embeddings": 32768, + "min_length": 0, + "model_type": "internlm2", + "no_repeat_ngram_size": 0, + "num_attention_heads": 16, + "num_beam_groups": 1, + "num_beams": 1, + "num_hidden_layers": 24, + "num_key_value_heads": 8, + "num_return_sequences": 1, + "output_attentions": false, + "output_hidden_states": false, + "output_scores": false, + "pad_token_id": 2, + "prefix": null, + "pretraining_tp": 1, + "problem_type": null, + "pruned_heads": {}, + "remove_invalid_values": false, + "repetition_penalty": 1.0, + "return_dict": true, + "return_dict_in_generate": false, + "rms_norm_eps": 1e-05, + "rope_scaling": { + "factor": 2.0, + "type": "dynamic" + }, + "rope_theta": 1000000, + "sep_token_id": null, + "suppress_tokens": null, + "task_specific_params": null, + "temperature": 1.0, + "tf_legacy_loss": false, + "tie_encoder_decoder": false, + "tie_word_embeddings": false, + "tokenizer_class": null, + "top_k": 50, + "top_p": 1.0, + "torch_dtype": "bfloat16", + "torchscript": false, + "transformers_version": "4.43.2", + "typical_p": 1.0, + "use_bfloat16": true, + "use_cache": true, + "vocab_size": 92553 + }, + "max_dynamic_patch": 12, + "min_dynamic_patch": 1, + "model_type": "internvl_chat", + "pad2square": false, + "ps_version": "v2", + "select_layer": -1, + "template": "internvl2_5", + "tie_word_embeddings": false, + "torch_dtype": "bfloat16", + "transformers_version": null, + "use_backbone_lora": 0, + "use_llm_lora": 0, + "use_thumbnail": true, + "vision_config": { + "_name_or_path": "", + "add_cross_attention": false, + "architectures": [ + "InternVisionModel" + ], + "attention_dropout": 0.0, + "bad_words_ids": null, + "begin_suppress_tokens": null, + "bos_token_id": null, + "chunk_size_feed_forward": 0, + "cross_attention_hidden_size": null, + "decoder_start_token_id": null, + "diversity_penalty": 0.0, + "do_sample": false, + "drop_path_rate": 0.0, + "dropout": 0.0, + "early_stopping": false, + "encoder_no_repeat_ngram_size": 0, + "eos_token_id": null, + "exponential_decay_length_penalty": null, + "finetuning_task": null, + "forced_bos_token_id": null, + "forced_eos_token_id": null, + "hidden_act": "gelu", + "hidden_size": 1024, + "id2label": { + "0": "LABEL_0", + "1": "LABEL_1" + }, + "image_size": 448, + "initializer_factor": 1.0, + "initializer_range": 0.02, + "intermediate_size": 4096, + "is_decoder": false, + "is_encoder_decoder": false, + "label2id": { + "LABEL_0": 0, + "LABEL_1": 1 + }, + "layer_norm_eps": 1e-06, + "length_penalty": 1.0, + "max_length": 20, + "min_length": 0, + "model_type": "intern_vit_6b", + "no_repeat_ngram_size": 0, + "norm_type": "layer_norm", + "num_attention_heads": 16, + "num_beam_groups": 1, + "num_beams": 1, + "num_channels": 3, + "num_hidden_layers": 24, + "num_return_sequences": 1, + "output_attentions": false, + "output_hidden_states": false, + "output_scores": false, + "pad_token_id": null, + "patch_size": 14, + "prefix": null, + "problem_type": null, + "pruned_heads": {}, + "qk_normalization": false, + "qkv_bias": true, + "remove_invalid_values": false, + "repetition_penalty": 1.0, + "return_dict": true, + "return_dict_in_generate": false, + "sep_token_id": null, + "suppress_tokens": null, + "task_specific_params": null, + "temperature": 1.0, + "tf_legacy_loss": false, + "tie_encoder_decoder": false, + "tie_word_embeddings": true, + "tokenizer_class": null, + "top_k": 50, + "top_p": 1.0, + "torch_dtype": "bfloat16", + "torchscript": false, + "transformers_version": "4.43.2", + "typical_p": 1.0, + "use_bfloat16": true, + "use_flash_attn": true + } +} + +05/01/2025 22:15:06 - INFO - __main__ - Using flash_attention_2 for InternLM +[INFO|modeling_utils.py:3634] 2025-05-01 22:15:06,132 >> loading weights file model.safetensors from cache at /home1/gmh/.cache/huggingface/hub/models--OpenGVLab--InternVL2_5-2B/snapshots/573169ee54df216786bb9a189e9a32a060a008cf/model.safetensors +[INFO|modeling_utils.py:1572] 2025-05-01 22:15:06,155 >> Instantiating InternVLChatModel model under default dtype torch.bfloat16. +[INFO|configuration_utils.py:1038] 2025-05-01 22:15:06,157 >> Generate config GenerationConfig {} + +[INFO|configuration_utils.py:1038] 2025-05-01 22:15:06,218 >> Generate config GenerationConfig { + "bos_token_id": 1, + "eos_token_id": 2, + "pad_token_id": 2 +} + +[INFO|modeling_utils.py:4463] 2025-05-01 22:15:06,542 >> All model checkpoint weights were used when initializing InternVLChatModel. + +[INFO|modeling_utils.py:4471] 2025-05-01 22:15:06,542 >> All the weights of InternVLChatModel were initialized from the model checkpoint at OpenGVLab/InternVL2_5-2B. +If your task is similar to the task the model of the checkpoint was trained on, you can already use InternVLChatModel for predictions without further training. +[INFO|configuration_utils.py:993] 2025-05-01 22:15:16,552 >> loading configuration file generation_config.json from cache at /home1/gmh/.cache/huggingface/hub/models--OpenGVLab--InternVL2_5-2B/snapshots/573169ee54df216786bb9a189e9a32a060a008cf/generation_config.json +[INFO|configuration_utils.py:1038] 2025-05-01 22:15:16,553 >> Generate config GenerationConfig { + "eos_token_id": [ + 92542, + 92543 + ] +} + +05/01/2025 22:15:16 - INFO - __main__ - Finished +05/01/2025 22:15:16 - INFO - __main__ - model.config.force_image_size: 448 +05/01/2025 22:15:16 - INFO - __main__ - data_args.force_image_size: 448 +05/01/2025 22:15:16 - INFO - __main__ - model.config.vision_config.image_size: 448 +05/01/2025 22:15:16 - INFO - __main__ - [Dataset] num_image_token: 256 +05/01/2025 22:15:16 - INFO - __main__ - [Dataset] dynamic_image_size: True +05/01/2025 22:15:16 - INFO - __main__ - [Dataset] use_thumbnail: True +05/01/2025 22:15:16 - INFO - __main__ - [Dataset] min_dynamic_patch: 1, max_dynamic_patch: 6 +05/01/2025 22:15:16 - INFO - __main__ - Formatting inputs...Skip in lazy mode +05/01/2025 22:15:16 - INFO - __main__ - Add dataset: profused_benchmark with length: 13953 +trainable params: 7,864,320 || all params: 1,897,011,200 || trainable%: 0.4146 +05/01/2025 22:15:17 - INFO - __main__ - language_model.base_model.model.model.layers.0.attention.wqkv.lora_A.default.weight +05/01/2025 22:15:17 - INFO - __main__ - language_model.base_model.model.model.layers.0.attention.wqkv.lora_B.default.weight +05/01/2025 22:15:17 - INFO - __main__ - 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__main__ - language_model.base_model.model.model.layers.23.feed_forward.w2.lora_A.default.weight +05/01/2025 22:15:17 - INFO - __main__ - language_model.base_model.model.model.layers.23.feed_forward.w2.lora_B.default.weight +05/01/2025 22:15:17 - INFO - __main__ - mlp1.0.weight +05/01/2025 22:15:17 - INFO - __main__ - mlp1.0.bias +05/01/2025 22:15:17 - INFO - __main__ - mlp1.1.weight +05/01/2025 22:15:17 - INFO - __main__ - mlp1.1.bias +05/01/2025 22:15:17 - INFO - __main__ - mlp1.3.weight +05/01/2025 22:15:17 - INFO - __main__ - mlp1.3.bias +[INFO|trainer.py:648] 2025-05-01 22:15:17,347 >> Using auto half precision backend +[2025-05-01 22:15:17,824] [INFO] [logging.py:96:log_dist] [Rank 0] DeepSpeed info: version=0.15.1, git-hash=unknown, git-branch=unknown +[2025-05-01 22:15:17,824] [INFO] [config.py:733:__init__] Config mesh_device None world_size = 1 +[2025-05-01 22:15:20,809] [INFO] [logging.py:96:log_dist] [Rank 0] DeepSpeed Flops Profiler Enabled: False +Using /home1/gmh/.cache/torch_extensions/py39_cu121 as PyTorch extensions root... +Emitting ninja build file /home1/gmh/.cache/torch_extensions/py39_cu121/cpu_adam/build.ninja... +Building extension module cpu_adam... +Allowing ninja to set a default number of workers... (overridable by setting the environment variable MAX_JOBS=N) +ninja: no work to do. +Loading extension module cpu_adam... +Time to load cpu_adam op: 3.0324764251708984 seconds +Adam Optimizer #0 is created with AVX512 arithmetic capability. +Config: alpha=0.000010, betas=(0.900000, 0.999000), weight_decay=0.010000, adam_w=1 +[2025-05-01 22:15:25,056] [INFO] [logging.py:96:log_dist] [Rank 0] Using DeepSpeed Optimizer param name adamw as basic optimizer +[2025-05-01 22:15:25,056] [INFO] [logging.py:96:log_dist] [Rank 0] Removing param_group that has no 'params' in the basic Optimizer +[2025-05-01 22:15:25,102] [INFO] [logging.py:96:log_dist] [Rank 0] DeepSpeed Basic Optimizer = DeepSpeedCPUAdam +[2025-05-01 22:15:25,103] [INFO] [utils.py:59:is_zero_supported_optimizer] Checking ZeRO support for optimizer=DeepSpeedCPUAdam type= +[2025-05-01 22:15:25,103] [INFO] [logging.py:96:log_dist] [Rank 0] Creating torch.bfloat16 ZeRO stage 1 optimizer +[2025-05-01 22:15:25,103] [INFO] [stage_1_and_2.py:148:__init__] Reduce bucket size 1000000000 +[2025-05-01 22:15:25,103] [INFO] [stage_1_and_2.py:149:__init__] Allgather bucket size 1000000000 +[2025-05-01 22:15:25,103] [INFO] [stage_1_and_2.py:150:__init__] CPU Offload: True +[2025-05-01 22:15:25,103] [INFO] [stage_1_and_2.py:151:__init__] Round robin gradient partitioning: False +[2025-05-01 22:15:25,685] [INFO] [utils.py:781:see_memory_usage] Before initializing optimizer states +[2025-05-01 22:15:25,686] [INFO] [utils.py:782:see_memory_usage] MA 4.52 GB Max_MA 4.52 GB CA 4.71 GB Max_CA 5 GB +[2025-05-01 22:15:25,686] [INFO] [utils.py:789:see_memory_usage] CPU Virtual Memory: used = 82.77 GB, percent = 11.0% +[2025-05-01 22:15:25,972] [INFO] [utils.py:781:see_memory_usage] After initializing optimizer states +[2025-05-01 22:15:25,973] [INFO] [utils.py:782:see_memory_usage] MA 4.52 GB Max_MA 4.52 GB CA 4.71 GB Max_CA 5 GB +[2025-05-01 22:15:25,973] [INFO] [utils.py:789:see_memory_usage] CPU Virtual Memory: used = 81.96 GB, percent = 10.9% +[2025-05-01 22:15:25,973] [INFO] [stage_1_and_2.py:543:__init__] optimizer state initialized +[2025-05-01 22:15:26,186] [INFO] [utils.py:781:see_memory_usage] After initializing ZeRO optimizer +[2025-05-01 22:15:26,187] [INFO] [utils.py:782:see_memory_usage] MA 4.52 GB Max_MA 4.52 GB CA 4.71 GB Max_CA 5 GB +[2025-05-01 22:15:26,187] [INFO] [utils.py:789:see_memory_usage] CPU Virtual Memory: used = 81.33 GB, percent = 10.8% +[2025-05-01 22:15:26,196] [INFO] [logging.py:96:log_dist] [Rank 0] DeepSpeed Final Optimizer = DeepSpeedZeroOptimizer +[2025-05-01 22:15:26,196] [INFO] [logging.py:96:log_dist] [Rank 0] DeepSpeed using client callable to create LR scheduler +[2025-05-01 22:15:26,196] [INFO] [logging.py:96:log_dist] [Rank 0] DeepSpeed LR Scheduler = +[2025-05-01 22:15:26,196] [INFO] [logging.py:96:log_dist] [Rank 0] step=0, skipped=0, lr=[0.0], mom=[[0.9, 0.999]] +[2025-05-01 22:15:26,201] [INFO] [config.py:999:print] DeepSpeedEngine configuration: +[2025-05-01 22:15:26,202] [INFO] [config.py:1003:print] activation_checkpointing_config { + "partition_activations": false, + "contiguous_memory_optimization": false, + "cpu_checkpointing": false, + "number_checkpoints": null, + "synchronize_checkpoint_boundary": false, + "profile": false +} +[2025-05-01 22:15:26,202] [INFO] [config.py:1003:print] aio_config ................... {'block_size': 1048576, 'queue_depth': 8, 'thread_count': 1, 'single_submit': False, 'overlap_events': True, 'use_gds': False} +[2025-05-01 22:15:26,202] [INFO] [config.py:1003:print] amp_enabled .................. False +[2025-05-01 22:15:26,202] [INFO] [config.py:1003:print] amp_params ................... False +[2025-05-01 22:15:26,202] [INFO] [config.py:1003:print] autotuning_config ............ { + "enabled": false, + "start_step": null, + "end_step": null, + "metric_path": null, + "arg_mappings": null, + "metric": "throughput", + "model_info": null, + "results_dir": "autotuning_results", + "exps_dir": "autotuning_exps", + "overwrite": true, + "fast": true, + "start_profile_step": 3, + "end_profile_step": 5, + "tuner_type": "gridsearch", + "tuner_early_stopping": 5, + "tuner_num_trials": 50, + "model_info_path": null, + "mp_size": 1, + "max_train_batch_size": null, + "min_train_batch_size": 1, + "max_train_micro_batch_size_per_gpu": 1.024000e+03, + "min_train_micro_batch_size_per_gpu": 1, + "num_tuning_micro_batch_sizes": 3 +} +[2025-05-01 22:15:26,202] [INFO] [config.py:1003:print] bfloat16_enabled ............. True +[2025-05-01 22:15:26,202] [INFO] [config.py:1003:print] bfloat16_immediate_grad_update False +[2025-05-01 22:15:26,202] [INFO] [config.py:1003:print] checkpoint_parallel_write_pipeline False +[2025-05-01 22:15:26,202] [INFO] [config.py:1003:print] checkpoint_tag_validation_enabled True +[2025-05-01 22:15:26,202] [INFO] [config.py:1003:print] checkpoint_tag_validation_fail False +[2025-05-01 22:15:26,202] [INFO] [config.py:1003:print] comms_config ................. +[2025-05-01 22:15:26,202] [INFO] [config.py:1003:print] communication_data_type ...... None +[2025-05-01 22:15:26,202] [INFO] [config.py:1003:print] compression_config ........... {'weight_quantization': {'shared_parameters': {'enabled': False, 'quantizer_kernel': False, 'schedule_offset': 0, 'quantize_groups': 1, 'quantize_verbose': False, 'quantization_type': 'symmetric', 'quantize_weight_in_forward': False, 'rounding': 'nearest', 'fp16_mixed_quantize': False, 'quantize_change_ratio': 0.001}, 'different_groups': {}}, 'activation_quantization': {'shared_parameters': {'enabled': False, 'quantization_type': 'symmetric', 'range_calibration': 'dynamic', 'schedule_offset': 1000}, 'different_groups': {}}, 'sparse_pruning': {'shared_parameters': {'enabled': False, 'method': 'l1', 'schedule_offset': 1000}, 'different_groups': {}}, 'row_pruning': {'shared_parameters': {'enabled': False, 'method': 'l1', 'schedule_offset': 1000}, 'different_groups': {}}, 'head_pruning': {'shared_parameters': {'enabled': False, 'method': 'topk', 'schedule_offset': 1000}, 'different_groups': {}}, 'channel_pruning': {'shared_parameters': {'enabled': False, 'method': 'l1', 'schedule_offset': 1000}, 'different_groups': {}}, 'layer_reduction': {'enabled': False}} +[2025-05-01 22:15:26,203] [INFO] [config.py:1003:print] curriculum_enabled_legacy .... False +[2025-05-01 22:15:26,203] [INFO] [config.py:1003:print] curriculum_params_legacy ..... False +[2025-05-01 22:15:26,203] [INFO] [config.py:1003:print] data_efficiency_config ....... {'enabled': False, 'seed': 1234, 'data_sampling': {'enabled': False, 'num_epochs': 1000, 'num_workers': 0, 'curriculum_learning': {'enabled': False}}, 'data_routing': {'enabled': False, 'random_ltd': {'enabled': False, 'layer_token_lr_schedule': {'enabled': False}}}} +[2025-05-01 22:15:26,203] [INFO] [config.py:1003:print] data_efficiency_enabled ...... False +[2025-05-01 22:15:26,203] [INFO] [config.py:1003:print] dataloader_drop_last ......... False +[2025-05-01 22:15:26,203] [INFO] [config.py:1003:print] disable_allgather ............ False +[2025-05-01 22:15:26,203] [INFO] [config.py:1003:print] dump_state ................... False +[2025-05-01 22:15:26,203] [INFO] [config.py:1003:print] dynamic_loss_scale_args ...... None +[2025-05-01 22:15:26,203] [INFO] [config.py:1003:print] eigenvalue_enabled ........... False +[2025-05-01 22:15:26,203] [INFO] [config.py:1003:print] eigenvalue_gas_boundary_resolution 1 +[2025-05-01 22:15:26,203] [INFO] [config.py:1003:print] eigenvalue_layer_name ........ bert.encoder.layer +[2025-05-01 22:15:26,203] [INFO] [config.py:1003:print] eigenvalue_layer_num ......... 0 +[2025-05-01 22:15:26,203] [INFO] [config.py:1003:print] eigenvalue_max_iter .......... 100 +[2025-05-01 22:15:26,203] [INFO] [config.py:1003:print] eigenvalue_stability ......... 1e-06 +[2025-05-01 22:15:26,203] [INFO] [config.py:1003:print] eigenvalue_tol ............... 0.01 +[2025-05-01 22:15:26,203] [INFO] [config.py:1003:print] eigenvalue_verbose ........... False +[2025-05-01 22:15:26,203] [INFO] [config.py:1003:print] elasticity_enabled ........... False +[2025-05-01 22:15:26,203] [INFO] [config.py:1003:print] flops_profiler_config ........ { + "enabled": false, + "recompute_fwd_factor": 0.0, + "profile_step": 1, + "module_depth": -1, + "top_modules": 1, + "detailed": true, + "output_file": null +} +[2025-05-01 22:15:26,203] [INFO] [config.py:1003:print] fp16_auto_cast ............... None +[2025-05-01 22:15:26,203] [INFO] [config.py:1003:print] fp16_enabled ................. False +[2025-05-01 22:15:26,203] [INFO] [config.py:1003:print] fp16_master_weights_and_gradients False +[2025-05-01 22:15:26,203] [INFO] [config.py:1003:print] global_rank .................. 0 +[2025-05-01 22:15:26,203] [INFO] [config.py:1003:print] grad_accum_dtype ............. None +[2025-05-01 22:15:26,203] [INFO] [config.py:1003:print] gradient_accumulation_steps .. 16 +[2025-05-01 22:15:26,203] [INFO] [config.py:1003:print] gradient_clipping ............ 1.0 +[2025-05-01 22:15:26,203] [INFO] [config.py:1003:print] gradient_predivide_factor .... 1.0 +[2025-05-01 22:15:26,203] [INFO] [config.py:1003:print] graph_harvesting ............. False +[2025-05-01 22:15:26,203] [INFO] [config.py:1003:print] hybrid_engine ................ enabled=False max_out_tokens=512 inference_tp_size=1 release_inference_cache=False pin_parameters=True tp_gather_partition_size=8 +[2025-05-01 22:15:26,203] [INFO] [config.py:1003:print] initial_dynamic_scale ........ 1 +[2025-05-01 22:15:26,203] [INFO] [config.py:1003:print] load_universal_checkpoint .... False +[2025-05-01 22:15:26,203] [INFO] [config.py:1003:print] loss_scale ................... 1.0 +[2025-05-01 22:15:26,203] [INFO] [config.py:1003:print] memory_breakdown ............. False +[2025-05-01 22:15:26,203] [INFO] [config.py:1003:print] mics_hierarchial_params_gather False +[2025-05-01 22:15:26,203] [INFO] [config.py:1003:print] mics_shard_size .............. -1 +[2025-05-01 22:15:26,203] [INFO] [config.py:1003:print] monitor_config ............... tensorboard=TensorBoardConfig(enabled=False, output_path='', job_name='DeepSpeedJobName') comet=CometConfig(enabled=False, samples_log_interval=100, project=None, workspace=None, api_key=None, experiment_name=None, experiment_key=None, online=None, mode=None) wandb=WandbConfig(enabled=False, group=None, team=None, project='deepspeed') csv_monitor=CSVConfig(enabled=False, output_path='', job_name='DeepSpeedJobName') +[2025-05-01 22:15:26,203] [INFO] [config.py:1003:print] nebula_config ................ { + "enabled": false, + "persistent_storage_path": null, + "persistent_time_interval": 100, + "num_of_version_in_retention": 2, + "enable_nebula_load": true, + "load_path": null +} +[2025-05-01 22:15:26,203] [INFO] [config.py:1003:print] optimizer_legacy_fusion ...... False +[2025-05-01 22:15:26,203] [INFO] [config.py:1003:print] optimizer_name ............... adamw +[2025-05-01 22:15:26,203] [INFO] [config.py:1003:print] optimizer_params ............. {'lr': 1e-05, 'betas': [0.9, 0.999], 'eps': 1e-08, 'weight_decay': 0.01} +[2025-05-01 22:15:26,203] [INFO] [config.py:1003:print] pipeline ..................... {'stages': 'auto', 'partition': 'best', 'seed_layers': False, 'activation_checkpoint_interval': 0, 'pipe_partitioned': True, 'grad_partitioned': True} +[2025-05-01 22:15:26,203] [INFO] [config.py:1003:print] pld_enabled .................. False +[2025-05-01 22:15:26,203] [INFO] [config.py:1003:print] pld_params ................... False +[2025-05-01 22:15:26,203] [INFO] [config.py:1003:print] prescale_gradients ........... False +[2025-05-01 22:15:26,204] [INFO] [config.py:1003:print] scheduler_name ............... None +[2025-05-01 22:15:26,204] [INFO] [config.py:1003:print] scheduler_params ............. None +[2025-05-01 22:15:26,204] [INFO] [config.py:1003:print] seq_parallel_communication_data_type torch.float32 +[2025-05-01 22:15:26,204] [INFO] [config.py:1003:print] sparse_attention ............. None +[2025-05-01 22:15:26,204] [INFO] [config.py:1003:print] sparse_gradients_enabled ..... False +[2025-05-01 22:15:26,204] [INFO] [config.py:1003:print] steps_per_print .............. inf +[2025-05-01 22:15:26,204] [INFO] [config.py:1003:print] timers_config ................ enabled=True synchronized=True +[2025-05-01 22:15:26,204] [INFO] [config.py:1003:print] train_batch_size ............. 16 +[2025-05-01 22:15:26,204] [INFO] [config.py:1003:print] train_micro_batch_size_per_gpu 1 +[2025-05-01 22:15:26,204] [INFO] [config.py:1003:print] use_data_before_expert_parallel_ False +[2025-05-01 22:15:26,204] [INFO] [config.py:1003:print] use_node_local_storage ....... False +[2025-05-01 22:15:26,204] [INFO] [config.py:1003:print] wall_clock_breakdown ......... True +[2025-05-01 22:15:26,204] [INFO] [config.py:1003:print] weight_quantization_config ... None +[2025-05-01 22:15:26,204] [INFO] [config.py:1003:print] world_size ................... 1 +[2025-05-01 22:15:26,204] [INFO] [config.py:1003:print] zero_allow_untested_optimizer False +[2025-05-01 22:15:26,204] [INFO] [config.py:1003:print] zero_config .................. stage=1 contiguous_gradients=True reduce_scatter=True reduce_bucket_size=1000000000 use_multi_rank_bucket_allreduce=True allgather_partitions=True allgather_bucket_size=1000000000 overlap_comm=True load_from_fp32_weights=True elastic_checkpoint=False offload_param=DeepSpeedZeroOffloadParamConfig(device='cpu', nvme_path=None, buffer_count=5, buffer_size=100000000, max_in_cpu=1000000000, pin_memory=True) offload_optimizer=DeepSpeedZeroOffloadOptimizerConfig(device='cpu', nvme_path=None, buffer_count=4, pin_memory=True, pipeline_read=False, pipeline_write=False, fast_init=False, ratio=1.0) sub_group_size=1000000000 cpu_offload_param=None cpu_offload_use_pin_memory=None cpu_offload=None prefetch_bucket_size=50000000 param_persistence_threshold=100000 model_persistence_threshold=9223372036854775807 max_live_parameters=1000000000 max_reuse_distance=1000000000 gather_16bit_weights_on_model_save=False use_all_reduce_for_fetch_params=False stage3_gather_fp16_weights_on_model_save=False ignore_unused_parameters=True legacy_stage1=False round_robin_gradients=False zero_hpz_partition_size=1 zero_quantized_weights=False zero_quantized_nontrainable_weights=False zero_quantized_gradients=False mics_shard_size=-1 mics_hierarchical_params_gather=False memory_efficient_linear=True pipeline_loading_checkpoint=False override_module_apply=True +[2025-05-01 22:15:26,204] [INFO] [config.py:1003:print] zero_enabled ................. True +[2025-05-01 22:15:26,204] [INFO] [config.py:1003:print] zero_force_ds_cpu_optimizer .. True +[2025-05-01 22:15:26,204] [INFO] [config.py:1003:print] zero_optimization_stage ...... 1 +[2025-05-01 22:15:26,204] [INFO] [config.py:989:print_user_config] json = { + "zero_optimization": { + "stage": 1, + "allgather_partitions": true, + "allgather_bucket_size": 1.000000e+09, + "overlap_comm": true, + "reduce_scatter": true, + "reduce_bucket_size": 1.000000e+09, + "contiguous_gradients": true, + "offload_param": { + "device": "cpu", + "pin_memory": true + }, + "offload_optimizer": { + "device": "cpu", + "pin_memory": true + } + }, + "fp16": { + "enabled": false, + "auto_cast": true, + "loss_scale": 0, + "initial_scale_power": 32, + "loss_scale_window": 1000, + "hysteresis": 2, + "min_loss_scale": 1 + }, + "bf16": { + "enabled": true + }, + "optimizer": { + "type": "AdamW", + "params": { + "lr": 1e-05, + "betas": [0.9, 0.999], + "eps": 1e-08, + "weight_decay": 0.01 + } + }, + "gradient_accumulation_steps": 16, + "gradient_clipping": 1.0, + "steps_per_print": inf, + "train_batch_size": 16, + "train_micro_batch_size_per_gpu": 1, + "wall_clock_breakdown": true +} +[INFO|trainer.py:2134] 2025-05-01 22:15:26,204 >> ***** Running training ***** +[INFO|trainer.py:2135] 2025-05-01 22:15:26,204 >> Num examples = 13,953 +[INFO|trainer.py:2136] 2025-05-01 22:15:26,204 >> Num Epochs = 10 +[INFO|trainer.py:2137] 2025-05-01 22:15:26,204 >> Instantaneous batch size per device = 1 +[INFO|trainer.py:2140] 2025-05-01 22:15:26,204 >> Total train batch size (w. parallel, distributed & accumulation) = 16 +[INFO|trainer.py:2141] 2025-05-01 22:15:26,204 >> Gradient Accumulation steps = 16 +[INFO|trainer.py:2142] 2025-05-01 22:15:26,204 >> Total optimization steps = 8,720 +[INFO|trainer.py:2143] 2025-05-01 22:15:26,208 >> Number of trainable parameters = 20,459,520 + 0%| | 0/8720 [00:00> Saving model checkpoint to work_dirs/internvl_chat_v2_5/ak/checkpoint-100 +[INFO|configuration_utils.py:472] 2025-05-01 22:30:47,608 >> Configuration saved in work_dirs/internvl_chat_v2_5/ak/checkpoint-100/config.json +[INFO|configuration_utils.py:807] 2025-05-01 22:30:47,609 >> Configuration saved in work_dirs/internvl_chat_v2_5/ak/checkpoint-100/generation_config.json +[INFO|modeling_utils.py:2755] 2025-05-01 22:30:55,859 >> Model weights saved in work_dirs/internvl_chat_v2_5/ak/checkpoint-100/model.safetensors +[INFO|tokenization_utils_base.py:2702] 2025-05-01 22:30:55,862 >> tokenizer config file saved in work_dirs/internvl_chat_v2_5/ak/checkpoint-100/tokenizer_config.json +[INFO|tokenization_utils_base.py:2711] 2025-05-01 22:30:55,862 >> Special tokens file saved in work_dirs/internvl_chat_v2_5/ak/checkpoint-100/special_tokens_map.json +[INFO|tokenization_utils_base.py:2762] 2025-05-01 22:30:55,862 >> added tokens file saved in work_dirs/internvl_chat_v2_5/ak/checkpoint-100/added_tokens.json +[2025-05-01 22:30:56,091] [INFO] [logging.py:96:log_dist] [Rank 0] [Torch] Checkpoint global_step100 is about to be saved! +[2025-05-01 22:30:56,111] [INFO] [logging.py:96:log_dist] [Rank 0] Saving model checkpoint: work_dirs/internvl_chat_v2_5/ak/checkpoint-100/global_step100/mp_rank_00_model_states.pt +[2025-05-01 22:30:56,111] [INFO] [torch_checkpoint_engine.py:21:save] [Torch] Saving work_dirs/internvl_chat_v2_5/ak/checkpoint-100/global_step100/mp_rank_00_model_states.pt... +[2025-05-01 22:31:04,047] [INFO] [torch_checkpoint_engine.py:23:save] [Torch] Saved work_dirs/internvl_chat_v2_5/ak/checkpoint-100/global_step100/mp_rank_00_model_states.pt. +[2025-05-01 22:31:04,048] [INFO] [torch_checkpoint_engine.py:21:save] [Torch] Saving work_dirs/internvl_chat_v2_5/ak/checkpoint-100/global_step100/bf16_zero_pp_rank_0_mp_rank_00_optim_states.pt... +[2025-05-01 22:31:04,395] [INFO] [torch_checkpoint_engine.py:23:save] [Torch] Saved work_dirs/internvl_chat_v2_5/ak/checkpoint-100/global_step100/bf16_zero_pp_rank_0_mp_rank_00_optim_states.pt. +[2025-05-01 22:31:04,395] [INFO] [engine.py:3536:_save_zero_checkpoint] zero checkpoint saved work_dirs/internvl_chat_v2_5/ak/checkpoint-100/global_step100/bf16_zero_pp_rank_0_mp_rank_00_optim_states.pt +[2025-05-01 22:31:04,395] [INFO] [torch_checkpoint_engine.py:33:commit] [Torch] Checkpoint global_step100 is ready now! +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 488 +[2025-05-01 22:31:04,614] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 69.26 | bwd_microstep: 137.80 | bwd_inner_microstep: 137.60 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.09 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 389 +[2025-05-01 22:31:04,812] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 66.61 | bwd_microstep: 117.41 | bwd_inner_microstep: 117.09 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-01 22:31:05,286] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.06 | bwd_microstep: 271.58 | bwd_inner_microstep: 271.56 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1896 +[2025-05-01 22:31:05,761] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.92 | bwd_microstep: 272.52 | bwd_inner_microstep: 272.51 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 345 +[2025-05-01 22:31:05,966] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 73.49 | bwd_microstep: 118.24 | bwd_inner_microstep: 117.96 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-01 22:31:06,438] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.18 | bwd_microstep: 270.72 | bwd_inner_microstep: 270.70 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-01 22:31:06,911] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.71 | bwd_microstep: 271.07 | bwd_inner_microstep: 271.05 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-01 22:31:07,384] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.68 | bwd_microstep: 270.52 | bwd_inner_microstep: 270.50 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 22:31:07,857] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.34 | bwd_microstep: 270.59 | bwd_inner_microstep: 270.57 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 22:31:08,331] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.67 | bwd_microstep: 270.84 | bwd_inner_microstep: 270.82 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 22:31:08,802] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.52 | bwd_microstep: 269.67 | bwd_inner_microstep: 269.65 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 22:31:09,276] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.47 | bwd_microstep: 270.43 | bwd_inner_microstep: 270.41 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 22:31:09,751] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.78 | bwd_microstep: 270.66 | bwd_inner_microstep: 270.65 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 22:31:10,224] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.54 | bwd_microstep: 269.35 | bwd_inner_microstep: 269.33 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 22:31:10,693] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 184.43 | bwd_microstep: 269.31 | bwd_inner_microstep: 269.29 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 924 +[2025-05-01 22:31:11,041] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.19 | optimizer_step: 16.64 +[2025-05-01 22:31:11,042] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 100.91 | bwd_microstep: 210.87 | bwd_inner_microstep: 144.98 | bwd_allreduce_microstep: 65.80 | step_microstep: 23.60 +[2025-05-01 22:31:11,043] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2549.31 | bwd: 3831.64 | bwd_inner: 3764.90 | bwd_allreduce: 66.16 | step: 24.48 + 1%| | 101/8720 [15:44<30:53:06, 12.90s/it] {'loss': 3.1355, 'grad_norm': 10.370892524719238, 'learning_rate': 3.8549618320610685e-06, 'epoch': 0.12} + 1%| | 101/8720 [15:44<30:53:06, 12.90s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1926 +[2025-05-01 22:31:11,541] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 193.12 | bwd_microstep: 284.91 | bwd_inner_microstep: 284.90 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 388 +[2025-05-01 22:31:11,746] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 74.90 | bwd_microstep: 116.81 | bwd_inner_microstep: 116.67 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1910 +[2025-05-01 22:31:12,227] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.84 | bwd_microstep: 275.23 | bwd_inner_microstep: 275.21 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 873 +[2025-05-01 22:31:12,469] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.66 | bwd_microstep: 133.92 | bwd_inner_microstep: 133.90 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1886 +[2025-05-01 22:31:12,944] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.11 | bwd_microstep: 273.32 | bwd_inner_microstep: 273.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-01 22:31:13,421] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.42 | bwd_microstep: 272.89 | bwd_inner_microstep: 272.88 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 338 +[2025-05-01 22:31:13,637] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 84.04 | bwd_microstep: 118.02 | bwd_inner_microstep: 117.81 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-01 22:31:14,114] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.63 | bwd_microstep: 272.01 | bwd_inner_microstep: 271.99 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-01 22:31:14,593] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.70 | bwd_microstep: 272.02 | bwd_inner_microstep: 272.00 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1353 +[2025-05-01 22:31:14,958] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.08 | bwd_microstep: 204.76 | bwd_inner_microstep: 204.64 | bwd_allreduce_microstep: 0.08 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-01 22:31:15,434] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.41 | bwd_microstep: 271.00 | bwd_inner_microstep: 270.98 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 22:31:15,913] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.98 | bwd_microstep: 271.03 | bwd_inner_microstep: 271.01 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 22:31:16,392] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.10 | bwd_microstep: 270.79 | bwd_inner_microstep: 270.77 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-01 22:31:16,871] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.23 | bwd_microstep: 271.17 | bwd_inner_microstep: 271.15 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 22:31:17,345] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.47 | bwd_microstep: 269.69 | bwd_inner_microstep: 269.67 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 22:31:17,911] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.27 | optimizer_step: 16.86 +[2025-05-01 22:31:17,911] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.26 | bwd_microstep: 338.20 | bwd_inner_microstep: 269.75 | bwd_allreduce_microstep: 68.40 | step_microstep: 24.23 +[2025-05-01 22:31:17,913] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2646.58 | bwd: 3915.82 | bwd_inner: 3846.72 | bwd_allreduce: 68.68 | step: 25.20 + 1%| | 102/8720 [15:51<26:33:03, 11.09s/it] {'loss': 2.8273, 'grad_norm': 8.240579605102539, 'learning_rate': 3.893129770992366e-06, 'epoch': 0.12} + 1%| | 102/8720 [15:51<26:33:03, 11.09s/it]dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1450 +[2025-05-01 22:31:18,293] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 145.02 | bwd_microstep: 214.53 | bwd_inner_microstep: 214.43 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-01 22:31:18,767] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.05 | bwd_microstep: 271.93 | bwd_inner_microstep: 271.91 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 349 +[2025-05-01 22:31:18,985] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 79.30 | bwd_microstep: 124.69 | bwd_inner_microstep: 124.56 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-01 22:31:19,460] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.41 | bwd_microstep: 272.64 | bwd_inner_microstep: 272.62 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 22:31:19,935] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.89 | bwd_microstep: 271.68 | bwd_inner_microstep: 271.66 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-01 22:31:20,411] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.53 | bwd_microstep: 272.18 | bwd_inner_microstep: 272.17 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 22:31:20,887] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.56 | bwd_microstep: 271.88 | bwd_inner_microstep: 271.86 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 836 +[2025-05-01 22:31:21,118] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 90.63 | bwd_microstep: 126.04 | bwd_inner_microstep: 125.76 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-01 22:31:21,593] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.55 | bwd_microstep: 271.82 | bwd_inner_microstep: 271.81 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 839 +[2025-05-01 22:31:21,826] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 92.41 | bwd_microstep: 126.15 | bwd_inner_microstep: 125.95 | bwd_allreduce_microstep: 0.09 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 22:31:22,302] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.57 | bwd_microstep: 271.64 | bwd_inner_microstep: 271.62 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 835 +[2025-05-01 22:31:22,532] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 89.96 | bwd_microstep: 125.43 | bwd_inner_microstep: 125.41 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 22:31:23,006] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.99 | bwd_microstep: 269.93 | bwd_inner_microstep: 269.91 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 831 +[2025-05-01 22:31:23,242] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 92.06 | bwd_microstep: 129.43 | bwd_inner_microstep: 129.41 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-01 22:31:23,714] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 185.88 | bwd_microstep: 269.54 | bwd_inner_microstep: 269.52 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-01 22:31:24,282] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.23 | optimizer_step: 17.02 +[2025-05-01 22:31:24,282] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.15 | bwd_microstep: 340.22 | bwd_inner_microstep: 273.30 | bwd_allreduce_microstep: 66.87 | step_microstep: 24.61 +[2025-05-01 22:31:24,284] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2464.71 | bwd: 3629.81 | bwd_inner: 3561.98 | bwd_allreduce: 67.26 | step: 25.57 + 1%| | 103/8720 [15:58<23:09:31, 9.68s/it] {'loss': 4.2068, 'grad_norm': 17.11176109313965, 'learning_rate': 3.931297709923664e-06, 'epoch': 0.12} + 1%| | 103/8720 [15:58<23:09:31, 9.68s/it]dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1375 +[2025-05-01 22:31:24,652] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.95 | bwd_microstep: 207.02 | bwd_inner_microstep: 206.85 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 864 +[2025-05-01 22:31:24,894] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.93 | bwd_microstep: 133.03 | bwd_inner_microstep: 133.01 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1121 +[2025-05-01 22:31:25,187] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 115.01 | bwd_microstep: 162.82 | bwd_inner_microstep: 162.66 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1887 +[2025-05-01 22:31:25,665] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.16 | bwd_microstep: 273.95 | bwd_inner_microstep: 273.93 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-01 22:31:26,141] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.88 | bwd_microstep: 272.66 | bwd_inner_microstep: 272.65 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1357 +[2025-05-01 22:31:26,502] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 139.92 | bwd_microstep: 205.83 | bwd_inner_microstep: 205.81 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 22:31:26,978] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.22 | bwd_microstep: 271.84 | bwd_inner_microstep: 271.82 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 22:31:27,453] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.10 | bwd_microstep: 271.60 | bwd_inner_microstep: 271.58 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 22:31:27,929] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.28 | bwd_microstep: 271.96 | bwd_inner_microstep: 271.94 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 22:31:28,406] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.77 | bwd_microstep: 271.90 | bwd_inner_microstep: 271.88 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 319 +[2025-05-01 22:31:28,625] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 78.40 | bwd_microstep: 123.88 | bwd_inner_microstep: 123.56 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 22:31:29,097] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.00 | bwd_microstep: 270.63 | bwd_inner_microstep: 270.61 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 321 +[2025-05-01 22:31:29,297] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 67.89 | bwd_microstep: 118.20 | bwd_inner_microstep: 117.88 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 22:31:29,770] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.35 | bwd_microstep: 270.54 | bwd_inner_microstep: 270.52 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 22:31:30,246] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.31 | bwd_microstep: 270.62 | bwd_inner_microstep: 270.61 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 22:31:30,811] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.28 | optimizer_step: 17.04 +[2025-05-01 22:31:30,812] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.01 | bwd_microstep: 336.71 | bwd_inner_microstep: 270.90 | bwd_allreduce_microstep: 65.76 | step_microstep: 24.11 +[2025-05-01 22:31:30,813] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2513.90 | bwd: 3733.30 | bwd_inner: 3666.37 | bwd_allreduce: 66.22 | step: 25.41 + 1%| | 104/8720 [16:04<20:53:47, 8.73s/it] {'loss': 3.8761, 'grad_norm': 18.00096893310547, 'learning_rate': 3.969465648854962e-06, 'epoch': 0.12} + 1%| | 104/8720 [16:04<20:53:47, 8.73s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1984 +[2025-05-01 22:31:31,319] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.90 | bwd_microstep: 290.28 | bwd_inner_microstep: 290.27 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 348 +[2025-05-01 22:31:31,530] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 80.83 | bwd_microstep: 116.36 | bwd_inner_microstep: 116.09 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-01 22:31:32,007] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.50 | bwd_microstep: 273.06 | bwd_inner_microstep: 273.04 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1360 +[2025-05-01 22:31:32,368] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.58 | bwd_microstep: 206.02 | bwd_inner_microstep: 205.88 | bwd_allreduce_microstep: 0.03 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-01 22:31:32,846] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.13 | bwd_microstep: 273.55 | bwd_inner_microstep: 273.54 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1361 +[2025-05-01 22:31:33,208] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.36 | bwd_microstep: 206.28 | bwd_inner_microstep: 206.21 | bwd_allreduce_microstep: 0.03 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-01 22:31:33,684] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.70 | bwd_microstep: 272.33 | bwd_inner_microstep: 272.32 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 845 +[2025-05-01 22:31:33,924] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.96 | bwd_microstep: 132.38 | bwd_inner_microstep: 132.14 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-01 22:31:34,400] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.90 | bwd_microstep: 272.13 | bwd_inner_microstep: 272.12 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-01 22:31:34,876] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.93 | bwd_microstep: 272.28 | bwd_inner_microstep: 272.26 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1089 +[2025-05-01 22:31:35,166] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 114.46 | bwd_microstep: 160.58 | bwd_inner_microstep: 160.57 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 325 +[2025-05-01 22:31:35,385] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 78.31 | bwd_microstep: 126.39 | bwd_inner_microstep: 126.20 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 22:31:35,861] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.90 | bwd_microstep: 271.94 | bwd_inner_microstep: 271.92 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 22:31:36,335] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.26 | bwd_microstep: 270.69 | bwd_inner_microstep: 270.67 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 22:31:36,809] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.82 | bwd_microstep: 270.60 | bwd_inner_microstep: 270.58 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1340 +[2025-05-01 22:31:37,260] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.21 | optimizer_step: 16.87 +[2025-05-01 22:31:37,261] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.76 | bwd_microstep: 270.90 | bwd_inner_microstep: 204.04 | bwd_allreduce_microstep: 66.71 | step_microstep: 25.19 +[2025-05-01 22:31:37,262] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2491.02 | bwd: 3685.85 | bwd_inner: 3618.02 | bwd_allreduce: 67.12 | step: 26.12 + 1%| | 105/8720 [16:11<19:15:22, 8.05s/it] {'loss': 3.5923, 'grad_norm': 18.7642765045166, 'learning_rate': 4.0076335877862595e-06, 'epoch': 0.12} + 1%| | 105/8720 [16:11<19:15:22, 8.05s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1909 +[2025-05-01 22:31:37,748] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.44 | bwd_microstep: 275.17 | bwd_inner_microstep: 275.15 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1886 +[2025-05-01 22:31:38,227] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.29 | bwd_microstep: 273.86 | bwd_inner_microstep: 273.85 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-01 22:31:38,706] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.84 | bwd_microstep: 273.40 | bwd_inner_microstep: 273.38 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-01 22:31:39,184] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.15 | bwd_microstep: 273.54 | bwd_inner_microstep: 273.52 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1883 +[2025-05-01 22:31:39,662] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.15 | bwd_microstep: 273.93 | bwd_inner_microstep: 273.91 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 338 +[2025-05-01 22:31:39,874] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 70.33 | bwd_microstep: 127.58 | bwd_inner_microstep: 127.41 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-01 22:31:40,349] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.65 | bwd_microstep: 272.45 | bwd_inner_microstep: 272.43 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1347 +[2025-05-01 22:31:40,711] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.38 | bwd_microstep: 205.29 | bwd_inner_microstep: 205.27 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 22:31:41,187] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.83 | bwd_microstep: 271.86 | bwd_inner_microstep: 271.85 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-01 22:31:41,665] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.22 | bwd_microstep: 272.84 | bwd_inner_microstep: 272.83 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 22:31:42,146] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.08 | bwd_microstep: 272.47 | bwd_inner_microstep: 272.45 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 22:31:42,624] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.02 | bwd_microstep: 271.55 | bwd_inner_microstep: 271.53 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 318 +[2025-05-01 22:31:42,838] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 75.63 | bwd_microstep: 122.97 | bwd_inner_microstep: 122.84 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 827 +[2025-05-01 22:31:43,074] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 90.82 | bwd_microstep: 130.98 | bwd_inner_microstep: 130.80 | bwd_allreduce_microstep: 0.08 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-01 22:31:43,551] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.79 | bwd_microstep: 272.50 | bwd_inner_microstep: 272.48 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 843 +[2025-05-01 22:31:43,882] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.28 | optimizer_step: 17.05 +[2025-05-01 22:31:43,883] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.57 | bwd_microstep: 198.90 | bwd_inner_microstep: 132.57 | bwd_allreduce_microstep: 66.23 | step_microstep: 24.20 +[2025-05-01 22:31:43,884] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2549.90 | bwd: 3789.34 | bwd_inner: 3722.40 | bwd_allreduce: 66.48 | step: 25.09 + 1%| | 106/8720 [16:17<18:13:51, 7.62s/it] {'loss': 2.7306, 'grad_norm': 12.207282066345215, 'learning_rate': 4.045801526717557e-06, 'epoch': 0.12} + 1%| | 106/8720 [16:17<18:13:51, 7.62s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2054 +[2025-05-01 22:31:44,406] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 201.49 | bwd_microstep: 300.64 | bwd_inner_microstep: 300.62 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 337 +[2025-05-01 22:31:44,607] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 67.99 | bwd_microstep: 119.42 | bwd_inner_microstep: 119.29 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-01 22:31:45,084] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.74 | bwd_microstep: 272.78 | bwd_inner_microstep: 272.76 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-01 22:31:45,562] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.40 | bwd_microstep: 272.59 | bwd_inner_microstep: 272.58 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 837 +[2025-05-01 22:31:45,793] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 91.02 | bwd_microstep: 126.48 | bwd_inner_microstep: 126.46 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1350 +[2025-05-01 22:31:46,156] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.27 | bwd_microstep: 206.06 | bwd_inner_microstep: 205.92 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-01 22:31:46,631] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.13 | bwd_microstep: 272.56 | bwd_inner_microstep: 272.54 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 22:31:47,106] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.71 | bwd_microstep: 272.30 | bwd_inner_microstep: 272.28 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-01 22:31:47,582] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.68 | bwd_microstep: 272.82 | bwd_inner_microstep: 272.81 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 22:31:48,059] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.53 | bwd_microstep: 272.23 | bwd_inner_microstep: 272.22 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-01 22:31:48,537] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.66 | bwd_microstep: 272.74 | bwd_inner_microstep: 272.73 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 22:31:49,016] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.13 | bwd_microstep: 271.15 | bwd_inner_microstep: 271.13 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 22:31:49,498] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.41 | bwd_microstep: 271.20 | bwd_inner_microstep: 271.18 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-01 22:31:49,975] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.02 | bwd_microstep: 270.94 | bwd_inner_microstep: 270.92 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 22:31:50,453] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.95 | bwd_microstep: 270.88 | bwd_inner_microstep: 270.86 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 22:31:51,028] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.19 | optimizer_step: 16.69 +[2025-05-01 22:31:51,028] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.55 | bwd_microstep: 346.92 | bwd_inner_microstep: 271.43 | bwd_allreduce_microstep: 75.44 | step_microstep: 23.80 +[2025-05-01 22:31:51,030] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2761.36 | bwd: 4091.73 | bwd_inner: 4015.75 | bwd_allreduce: 75.65 | step: 24.64 + 1%| | 107/8720 [16:24<17:53:19, 7.48s/it] {'loss': 3.275, 'grad_norm': 18.828922271728516, 'learning_rate': 4.083969465648855e-06, 'epoch': 0.12} + 1%| | 107/8720 [16:24<17:53:19, 7.48s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2142 +[2025-05-01 22:31:51,567] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 204.46 | bwd_microstep: 313.54 | bwd_inner_microstep: 313.52 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1925 +[2025-05-01 22:31:52,065] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 194.98 | bwd_microstep: 286.90 | bwd_inner_microstep: 286.88 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-01 22:31:52,544] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.59 | bwd_microstep: 273.12 | bwd_inner_microstep: 273.10 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1883 +[2025-05-01 22:31:53,024] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.47 | bwd_microstep: 274.38 | bwd_inner_microstep: 274.36 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1887 +[2025-05-01 22:31:53,507] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.69 | bwd_microstep: 275.06 | bwd_inner_microstep: 275.05 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-01 22:31:53,986] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.93 | bwd_microstep: 273.13 | bwd_inner_microstep: 273.11 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-01 22:31:54,467] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.20 | bwd_microstep: 273.33 | bwd_inner_microstep: 273.31 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-01 22:31:54,946] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.75 | bwd_microstep: 273.22 | bwd_inner_microstep: 273.20 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-01 22:31:55,427] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.54 | bwd_microstep: 272.52 | bwd_inner_microstep: 272.50 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-01 22:31:55,907] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.50 | bwd_microstep: 272.51 | bwd_inner_microstep: 272.49 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-01 22:31:56,386] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.17 | bwd_microstep: 272.57 | bwd_inner_microstep: 272.56 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 22:31:56,866] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.79 | bwd_microstep: 272.09 | bwd_inner_microstep: 272.07 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1349 +[2025-05-01 22:31:57,231] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.32 | bwd_microstep: 205.95 | bwd_inner_microstep: 205.80 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-01 22:31:57,709] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.59 | bwd_microstep: 272.75 | bwd_inner_microstep: 272.73 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 22:31:58,186] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.06 | bwd_microstep: 272.08 | bwd_inner_microstep: 272.06 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1086 +[2025-05-01 22:31:58,577] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.04 | optimizer_gradients: 2.22 | optimizer_step: 16.52 +[2025-05-01 22:31:58,578] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 115.27 | bwd_microstep: 236.55 | bwd_inner_microstep: 160.45 | bwd_allreduce_microstep: 75.95 | step_microstep: 23.59 +[2025-05-01 22:31:58,579] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2916.94 | bwd: 4319.70 | bwd_inner: 4243.25 | bwd_allreduce: 76.08 | step: 24.56 + 1%| | 108/8720 [16:32<17:56:19, 7.50s/it] {'loss': 2.8596, 'grad_norm': 10.798736572265625, 'learning_rate': 4.122137404580153e-06, 'epoch': 0.12} + 1%| | 108/8720 [16:32<17:56:19, 7.50s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1917 +[2025-05-01 22:31:59,066] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.63 | bwd_microstep: 276.26 | bwd_inner_microstep: 276.25 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1362 +[2025-05-01 22:31:59,429] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.52 | bwd_microstep: 206.58 | bwd_inner_microstep: 206.43 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-01 22:31:59,908] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.88 | bwd_microstep: 274.75 | bwd_inner_microstep: 274.73 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-01 22:32:00,386] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.76 | bwd_microstep: 273.17 | bwd_inner_microstep: 273.15 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-01 22:32:00,866] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.05 | bwd_microstep: 273.82 | bwd_inner_microstep: 273.81 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-01 22:32:01,344] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.97 | bwd_microstep: 273.30 | bwd_inner_microstep: 273.28 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 333 +[2025-05-01 22:32:01,543] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 70.46 | bwd_microstep: 115.76 | bwd_inner_microstep: 115.57 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-01 22:32:02,020] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.78 | bwd_microstep: 273.27 | bwd_inner_microstep: 273.25 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-01 22:32:02,500] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.03 | bwd_microstep: 273.60 | bwd_inner_microstep: 273.58 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1096 +[2025-05-01 22:32:02,793] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 116.24 | bwd_microstep: 161.46 | bwd_inner_microstep: 161.24 | bwd_allreduce_microstep: 0.14 | step_microstep: 0.21 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 22:32:03,271] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.45 | bwd_microstep: 272.98 | bwd_inner_microstep: 272.96 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.15 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 22:32:03,750] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.80 | bwd_microstep: 272.67 | bwd_inner_microstep: 272.65 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 22:32:04,230] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.96 | bwd_microstep: 272.95 | bwd_inner_microstep: 272.93 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.14 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 22:32:04,711] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.88 | bwd_microstep: 272.87 | bwd_inner_microstep: 272.86 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 22:32:05,189] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.94 | bwd_microstep: 271.40 | bwd_inner_microstep: 271.39 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1131 +[2025-05-01 22:32:05,586] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.18 | optimizer_step: 16.56 +[2025-05-01 22:32:05,586] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 116.12 | bwd_microstep: 240.81 | bwd_inner_microstep: 164.55 | bwd_allreduce_microstep: 76.18 | step_microstep: 23.68 +[2025-05-01 22:32:05,587] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2712.17 | bwd: 4005.72 | bwd_inner: 3928.71 | bwd_allreduce: 76.54 | step: 24.94 + 1%|▏ | 109/8720 [16:39<17:35:04, 7.35s/it] {'loss': 4.3417, 'grad_norm': 18.52494239807129, 'learning_rate': 4.1603053435114506e-06, 'epoch': 0.12} + 1%|▏ | 109/8720 [16:39<17:35:04, 7.35s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1974 +[2025-05-01 22:32:06,094] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 196.35 | bwd_microstep: 291.07 | bwd_inner_microstep: 291.06 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1895 +[2025-05-01 22:32:06,574] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.54 | bwd_microstep: 275.20 | bwd_inner_microstep: 275.19 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-01 22:32:07,053] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.05 | bwd_microstep: 274.37 | bwd_inner_microstep: 274.35 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-01 22:32:07,531] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.66 | bwd_microstep: 272.75 | bwd_inner_microstep: 272.74 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-01 22:32:08,008] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.88 | bwd_microstep: 273.51 | bwd_inner_microstep: 273.49 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-01 22:32:08,486] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.37 | bwd_microstep: 273.13 | bwd_inner_microstep: 273.11 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 22:32:08,963] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.25 | bwd_microstep: 272.35 | bwd_inner_microstep: 272.34 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 843 +[2025-05-01 22:32:09,204] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.54 | bwd_microstep: 132.30 | bwd_inner_microstep: 132.28 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 22:32:09,682] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.89 | bwd_microstep: 272.47 | bwd_inner_microstep: 272.45 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 22:32:10,159] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.57 | bwd_microstep: 272.33 | bwd_inner_microstep: 272.31 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 22:32:10,635] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.11 | bwd_microstep: 271.46 | bwd_inner_microstep: 271.44 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 22:32:11,113] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.12 | bwd_microstep: 271.41 | bwd_inner_microstep: 271.39 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 319 +[2025-05-01 22:32:11,320] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 72.58 | bwd_microstep: 119.54 | bwd_inner_microstep: 119.39 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 22:32:11,795] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.82 | bwd_microstep: 271.46 | bwd_inner_microstep: 271.44 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-01 22:32:12,271] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.58 | bwd_microstep: 271.20 | bwd_inner_microstep: 271.19 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 22:32:12,855] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.16 | optimizer_step: 24.17 +[2025-05-01 22:32:12,855] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.15 | bwd_microstep: 347.39 | bwd_inner_microstep: 271.56 | bwd_allreduce_microstep: 75.78 | step_microstep: 31.96 +[2025-05-01 22:32:12,857] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2813.20 | bwd: 4162.00 | bwd_inner: 4085.77 | bwd_allreduce: 75.91 | step: 32.76 + 1%|▏ | 110/8720 [16:46<17:31:29, 7.33s/it] {'loss': 3.9854, 'grad_norm': 14.68717098236084, 'learning_rate': 4.198473282442748e-06, 'epoch': 0.13} + 1%|▏ | 110/8720 [16:46<17:31:29, 7.33s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 3522 +[2025-05-01 22:32:13,673] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 289.74 | bwd_microstep: 503.58 | bwd_inner_microstep: 503.57 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1925 +[2025-05-01 22:32:14,172] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.90 | bwd_microstep: 287.38 | bwd_inner_microstep: 287.36 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 388 +[2025-05-01 22:32:14,371] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 68.10 | bwd_microstep: 116.86 | bwd_inner_microstep: 116.54 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.18 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 388 +[2025-05-01 22:32:14,579] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 77.71 | bwd_microstep: 115.88 | bwd_inner_microstep: 115.53 | bwd_allreduce_microstep: 0.14 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-01 22:32:15,057] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.57 | bwd_microstep: 273.96 | bwd_inner_microstep: 273.95 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-01 22:32:15,536] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.24 | bwd_microstep: 273.83 | bwd_inner_microstep: 273.81 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-01 22:32:16,016] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.75 | bwd_microstep: 273.64 | bwd_inner_microstep: 273.63 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-01 22:32:16,496] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.66 | bwd_microstep: 273.03 | bwd_inner_microstep: 273.01 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-01 22:32:16,976] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.39 | bwd_microstep: 272.82 | bwd_inner_microstep: 272.80 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-01 22:32:17,457] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.06 | bwd_microstep: 272.62 | bwd_inner_microstep: 272.61 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 22:32:17,936] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.63 | bwd_microstep: 272.42 | bwd_inner_microstep: 272.41 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 22:32:18,413] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.51 | bwd_microstep: 271.39 | bwd_inner_microstep: 271.38 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 22:32:18,892] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.74 | bwd_microstep: 271.58 | bwd_inner_microstep: 271.56 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 830 +[2025-05-01 22:32:19,136] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.53 | bwd_microstep: 130.71 | bwd_inner_microstep: 130.38 | bwd_allreduce_microstep: 0.15 | step_microstep: 0.10 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 437 +[2025-05-01 22:32:19,355] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 84.64 | bwd_microstep: 117.49 | bwd_inner_microstep: 117.34 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-01 22:32:19,940] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.19 | optimizer_step: 19.66 +[2025-05-01 22:32:19,941] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.03 | bwd_microstep: 351.77 | bwd_inner_microstep: 275.16 | bwd_allreduce_microstep: 76.55 | step_microstep: 27.34 +[2025-05-01 22:32:19,942] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2701.86 | bwd: 4079.07 | bwd_inner: 4001.25 | bwd_allreduce: 77.10 | step: 28.41 + 1%|▏ | 111/8720 [16:53<17:20:57, 7.25s/it] {'loss': 2.4793, 'grad_norm': 12.803359985351562, 'learning_rate': 4.236641221374046e-06, 'epoch': 0.13} + 1%|▏ | 111/8720 [16:53<17:20:57, 7.25s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1954 +[2025-05-01 22:32:20,450] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 196.38 | bwd_microstep: 289.12 | bwd_inner_microstep: 289.10 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.13 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1890 +[2025-05-01 22:32:20,933] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.32 | bwd_microstep: 274.82 | bwd_inner_microstep: 274.80 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-01 22:32:21,417] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.45 | bwd_microstep: 273.43 | bwd_inner_microstep: 273.41 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-01 22:32:21,896] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.82 | bwd_microstep: 272.47 | bwd_inner_microstep: 272.45 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 22:32:22,377] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.70 | bwd_microstep: 272.22 | bwd_inner_microstep: 272.21 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.21 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-01 22:32:22,857] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.92 | bwd_microstep: 272.58 | bwd_inner_microstep: 272.56 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 22:32:23,336] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.53 | bwd_microstep: 272.46 | bwd_inner_microstep: 272.45 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 22:32:23,816] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.56 | bwd_microstep: 272.51 | bwd_inner_microstep: 272.50 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-01 22:32:24,299] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.45 | bwd_microstep: 272.71 | bwd_inner_microstep: 272.69 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-01 22:32:24,785] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.69 | bwd_microstep: 273.22 | bwd_inner_microstep: 273.21 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-01 22:32:25,266] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.84 | bwd_microstep: 272.82 | bwd_inner_microstep: 272.80 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-01 22:32:25,749] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.36 | bwd_microstep: 272.87 | bwd_inner_microstep: 272.85 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 22:32:26,228] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.82 | bwd_microstep: 272.51 | bwd_inner_microstep: 272.49 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 22:32:26,705] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.44 | bwd_microstep: 271.46 | bwd_inner_microstep: 271.44 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 830 +[2025-05-01 22:32:26,949] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 98.18 | bwd_microstep: 129.86 | bwd_inner_microstep: 129.82 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-01 22:32:27,536] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.18 | optimizer_step: 24.27 +[2025-05-01 22:32:27,536] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.57 | bwd_microstep: 348.23 | bwd_inner_microstep: 271.71 | bwd_allreduce_microstep: 76.46 | step_microstep: 31.91 +[2025-05-01 22:32:27,537] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2937.64 | bwd: 4313.32 | bwd_inner: 4236.49 | bwd_allreduce: 76.56 | step: 32.99 + 1%|▏ | 112/8720 [17:01<17:35:29, 7.36s/it] {'loss': 3.6916, 'grad_norm': 16.084043502807617, 'learning_rate': 4.274809160305344e-06, 'epoch': 0.13} + 1%|▏ | 112/8720 [17:01<17:35:29, 7.36s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1946 +[2025-05-01 22:32:28,044] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.54 | bwd_microstep: 288.79 | bwd_inner_microstep: 288.77 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1914 +[2025-05-01 22:32:28,526] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.82 | bwd_microstep: 276.19 | bwd_inner_microstep: 276.17 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1895 +[2025-05-01 22:32:29,010] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.13 | bwd_microstep: 275.26 | bwd_inner_microstep: 275.24 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1893 +[2025-05-01 22:32:29,495] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.28 | bwd_microstep: 275.41 | bwd_inner_microstep: 275.40 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-01 22:32:29,976] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.99 | bwd_microstep: 273.56 | bwd_inner_microstep: 273.54 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 334 +[2025-05-01 22:32:30,208] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 88.69 | bwd_microstep: 126.32 | bwd_inner_microstep: 126.04 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-01 22:32:30,688] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.63 | bwd_microstep: 273.30 | bwd_inner_microstep: 273.28 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1109 +[2025-05-01 22:32:30,982] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 116.15 | bwd_microstep: 162.00 | bwd_inner_microstep: 161.98 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 22:32:31,460] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.07 | bwd_microstep: 272.51 | bwd_inner_microstep: 272.49 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-01 22:32:31,941] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.43 | bwd_microstep: 272.96 | bwd_inner_microstep: 272.94 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-01 22:32:32,419] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.43 | bwd_microstep: 272.81 | bwd_inner_microstep: 272.79 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 22:32:32,896] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.77 | bwd_microstep: 271.27 | bwd_inner_microstep: 271.25 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 22:32:33,373] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.80 | bwd_microstep: 271.23 | bwd_inner_microstep: 271.21 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 22:32:33,852] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.48 | bwd_microstep: 271.17 | bwd_inner_microstep: 271.15 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.13 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 22:32:34,330] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.48 | bwd_microstep: 270.86 | bwd_inner_microstep: 270.84 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 344 +[2025-05-01 22:32:34,673] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.18 | optimizer_step: 16.33 +[2025-05-01 22:32:34,673] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.92 | bwd_microstep: 207.60 | bwd_inner_microstep: 130.84 | bwd_allreduce_microstep: 76.60 | step_microstep: 23.91 +[2025-05-01 22:32:34,675] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2761.26 | bwd: 4061.26 | bwd_inner: 3984.08 | bwd_allreduce: 76.76 | step: 24.83 + 1%|▏ | 113/8720 [17:08<17:25:53, 7.29s/it] {'loss': 2.2253, 'grad_norm': 9.4818696975708, 'learning_rate': 4.312977099236642e-06, 'epoch': 0.13} + 1%|▏ | 113/8720 [17:08<17:25:53, 7.29s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1949 +[2025-05-01 22:32:35,182] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.70 | bwd_microstep: 288.82 | bwd_inner_microstep: 288.80 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1934 +[2025-05-01 22:32:35,685] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.83 | bwd_microstep: 288.35 | bwd_inner_microstep: 288.34 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-01 22:32:36,166] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.41 | bwd_microstep: 273.82 | bwd_inner_microstep: 273.80 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-01 22:32:36,645] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.90 | bwd_microstep: 273.38 | bwd_inner_microstep: 273.36 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-01 22:32:37,126] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.52 | bwd_microstep: 273.80 | bwd_inner_microstep: 273.78 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-01 22:32:37,607] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.37 | bwd_microstep: 273.74 | bwd_inner_microstep: 273.73 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1359 +[2025-05-01 22:32:37,972] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 142.07 | bwd_microstep: 206.85 | bwd_inner_microstep: 206.75 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 22:32:38,450] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.20 | bwd_microstep: 272.62 | bwd_inner_microstep: 272.60 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 836 +[2025-05-01 22:32:38,685] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.51 | bwd_microstep: 125.89 | bwd_inner_microstep: 125.84 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-01 22:32:39,163] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.12 | bwd_microstep: 273.19 | bwd_inner_microstep: 273.17 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 22:32:39,640] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.22 | bwd_microstep: 272.84 | bwd_inner_microstep: 272.61 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 22:32:40,120] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.49 | bwd_microstep: 272.50 | bwd_inner_microstep: 272.49 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 322 +[2025-05-01 22:32:40,364] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.21 | bwd_microstep: 131.76 | bwd_inner_microstep: 131.55 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 22:32:40,841] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.14 | bwd_microstep: 271.36 | bwd_inner_microstep: 271.35 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-01 22:32:41,319] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.84 | bwd_microstep: 271.27 | bwd_inner_microstep: 271.25 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 22:32:41,893] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 8.34 | optimizer_step: 16.54 +[2025-05-01 22:32:41,894] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.66 | bwd_microstep: 341.36 | bwd_inner_microstep: 271.49 | bwd_allreduce_microstep: 69.83 | step_microstep: 29.92 +[2025-05-01 22:32:41,895] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2795.85 | bwd: 4111.63 | bwd_inner: 4040.98 | bwd_allreduce: 70.13 | step: 31.13 + 1%|▏ | 114/8720 [17:15<17:22:41, 7.27s/it] {'loss': 3.7281, 'grad_norm': 13.13780403137207, 'learning_rate': 4.351145038167939e-06, 'epoch': 0.13} + 1%|▏ | 114/8720 [17:15<17:22:41, 7.27s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1894 +[2025-05-01 22:32:42,379] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.94 | bwd_microstep: 274.35 | bwd_inner_microstep: 274.33 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1105 +[2025-05-01 22:32:42,672] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 115.37 | bwd_microstep: 161.85 | bwd_inner_microstep: 161.84 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-01 22:32:43,151] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.81 | bwd_microstep: 273.48 | bwd_inner_microstep: 273.47 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-01 22:32:43,631] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.45 | bwd_microstep: 274.05 | bwd_inner_microstep: 274.03 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-01 22:32:44,108] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.73 | bwd_microstep: 273.09 | bwd_inner_microstep: 273.08 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-01 22:32:44,586] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.12 | bwd_microstep: 273.05 | bwd_inner_microstep: 273.04 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1355 +[2025-05-01 22:32:44,950] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 142.03 | bwd_microstep: 206.64 | bwd_inner_microstep: 206.63 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-01 22:32:45,427] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.97 | bwd_microstep: 273.34 | bwd_inner_microstep: 273.32 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 22:32:45,906] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.43 | bwd_microstep: 273.26 | bwd_inner_microstep: 273.25 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 22:32:46,385] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.60 | bwd_microstep: 273.20 | bwd_inner_microstep: 273.19 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 22:32:46,864] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.47 | bwd_microstep: 273.16 | bwd_inner_microstep: 273.14 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 22:32:47,342] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.30 | bwd_microstep: 271.83 | bwd_inner_microstep: 271.81 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 835 +[2025-05-01 22:32:47,583] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 97.46 | bwd_microstep: 126.10 | bwd_inner_microstep: 125.85 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 22:32:48,062] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.36 | bwd_microstep: 271.58 | bwd_inner_microstep: 271.56 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2141 +[2025-05-01 22:32:48,601] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 205.62 | bwd_microstep: 314.77 | bwd_inner_microstep: 314.75 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1886 +[2025-05-01 22:32:49,194] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.29 | optimizer_step: 16.58 +[2025-05-01 22:32:49,195] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.80 | bwd_microstep: 359.13 | bwd_inner_microstep: 274.90 | bwd_allreduce_microstep: 84.19 | step_microstep: 24.59 +[2025-05-01 22:32:49,196] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2830.14 | bwd: 4172.93 | bwd_inner: 4088.22 | bwd_allreduce: 84.36 | step: 25.40 + 1%|▏ | 115/8720 [17:22<17:24:01, 7.28s/it] {'loss': 3.3487, 'grad_norm': 12.136261940002441, 'learning_rate': 4.389312977099237e-06, 'epoch': 0.13} + 1%|▏ | 115/8720 [17:22<17:24:01, 7.28s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1921 +[2025-05-01 22:32:49,702] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.68 | bwd_microstep: 285.83 | bwd_inner_microstep: 285.81 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1918 +[2025-05-01 22:32:50,189] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.47 | bwd_microstep: 276.38 | bwd_inner_microstep: 276.36 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1913 +[2025-05-01 22:32:50,674] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.07 | bwd_microstep: 275.91 | bwd_inner_microstep: 275.89 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1112 +[2025-05-01 22:32:50,969] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 116.03 | bwd_microstep: 162.40 | bwd_inner_microstep: 162.19 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-01 22:32:51,448] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.24 | bwd_microstep: 272.82 | bwd_inner_microstep: 272.80 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-01 22:32:51,929] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.47 | bwd_microstep: 273.24 | bwd_inner_microstep: 273.22 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-01 22:32:52,407] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.55 | bwd_microstep: 272.89 | bwd_inner_microstep: 272.87 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-01 22:32:52,887] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.34 | bwd_microstep: 272.55 | bwd_inner_microstep: 272.53 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-01 22:32:53,367] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.76 | bwd_microstep: 273.26 | bwd_inner_microstep: 273.24 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-01 22:32:53,845] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.88 | bwd_microstep: 272.60 | bwd_inner_microstep: 272.59 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-01 22:32:54,325] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.52 | bwd_microstep: 272.96 | bwd_inner_microstep: 272.94 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-01 22:32:54,806] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.71 | bwd_microstep: 272.42 | bwd_inner_microstep: 272.40 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-01 22:32:55,286] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.25 | bwd_microstep: 272.70 | bwd_inner_microstep: 272.68 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-01 22:32:55,765] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.56 | bwd_microstep: 272.72 | bwd_inner_microstep: 272.70 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-01 22:32:56,244] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.17 | bwd_microstep: 272.58 | bwd_inner_microstep: 272.56 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 22:32:56,823] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.25 | optimizer_step: 16.62 +[2025-05-01 22:32:56,823] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.13 | bwd_microstep: 348.71 | bwd_inner_microstep: 271.37 | bwd_allreduce_microstep: 77.29 | step_microstep: 24.40 +[2025-05-01 22:32:56,825] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2951.47 | bwd: 4349.98 | bwd_inner: 4272.17 | bwd_allreduce: 77.46 | step: 25.35 + 1%|▏ | 116/8720 [17:30<17:38:48, 7.38s/it] {'loss': 2.4101, 'grad_norm': 8.114419937133789, 'learning_rate': 4.427480916030535e-06, 'epoch': 0.13} + 1%|▏ | 116/8720 [17:30<17:38:48, 7.38s/it]dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 993 +[2025-05-01 22:32:57,097] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 102.27 | bwd_microstep: 150.56 | bwd_inner_microstep: 150.33 | bwd_allreduce_microstep: 0.09 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1915 +[2025-05-01 22:32:57,580] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.03 | bwd_microstep: 276.43 | bwd_inner_microstep: 276.41 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 378 +[2025-05-01 22:32:57,797] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 76.53 | bwd_microstep: 126.16 | bwd_inner_microstep: 126.02 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-01 22:32:58,274] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.25 | bwd_microstep: 272.82 | bwd_inner_microstep: 272.80 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 22:32:58,753] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.09 | bwd_microstep: 272.61 | bwd_inner_microstep: 272.59 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.14 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 330 +[2025-05-01 22:32:58,989] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.91 | bwd_microstep: 124.17 | bwd_inner_microstep: 123.86 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 22:32:59,468] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.42 | bwd_microstep: 272.62 | bwd_inner_microstep: 272.61 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.21 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-01 22:32:59,947] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.11 | bwd_microstep: 272.78 | bwd_inner_microstep: 272.76 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 22:33:00,425] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.59 | bwd_microstep: 272.63 | bwd_inner_microstep: 272.61 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-01 22:33:00,902] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.97 | bwd_microstep: 272.92 | bwd_inner_microstep: 272.91 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 22:33:01,379] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.15 | bwd_microstep: 272.39 | bwd_inner_microstep: 272.37 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 22:33:01,859] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.02 | bwd_microstep: 272.53 | bwd_inner_microstep: 272.51 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 22:33:02,337] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.03 | bwd_microstep: 272.58 | bwd_inner_microstep: 272.57 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 22:33:02,814] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.64 | bwd_microstep: 271.49 | bwd_inner_microstep: 271.48 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 828 +[2025-05-01 22:33:03,056] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.53 | bwd_microstep: 129.77 | bwd_inner_microstep: 129.65 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1214 +[2025-05-01 22:33:03,472] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 3.53 | optimizer_step: 17.03 +[2025-05-01 22:33:03,473] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 121.03 | bwd_microstep: 252.92 | bwd_inner_microstep: 175.94 | bwd_allreduce_microstep: 76.88 | step_microstep: 26.08 +[2025-05-01 22:33:03,474] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2564.29 | bwd: 3785.48 | bwd_inner: 3707.61 | bwd_allreduce: 77.22 | step: 27.51 + 1%|▏ | 117/8720 [17:37<17:07:10, 7.16s/it] {'loss': 3.6349, 'grad_norm': 15.333476066589355, 'learning_rate': 4.465648854961833e-06, 'epoch': 0.13} + 1%|▏ | 117/8720 [17:37<17:07:10, 7.16s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 366 +[2025-05-01 22:33:03,721] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 79.75 | bwd_microstep: 146.17 | bwd_inner_microstep: 145.94 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1369 +[2025-05-01 22:33:04,088] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.84 | bwd_microstep: 207.60 | bwd_inner_microstep: 207.58 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 864 +[2025-05-01 22:33:04,333] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.30 | bwd_microstep: 133.70 | bwd_inner_microstep: 133.57 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-01 22:33:04,813] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.83 | bwd_microstep: 273.57 | bwd_inner_microstep: 273.56 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 853 +[2025-05-01 22:33:05,064] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 97.85 | bwd_microstep: 133.58 | bwd_inner_microstep: 133.38 | bwd_allreduce_microstep: 0.09 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-01 22:33:05,543] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.70 | bwd_microstep: 273.03 | bwd_inner_microstep: 273.01 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 22:33:06,024] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.59 | bwd_microstep: 272.13 | bwd_inner_microstep: 272.11 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-01 22:33:06,504] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.54 | bwd_microstep: 273.18 | bwd_inner_microstep: 273.16 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1356 +[2025-05-01 22:33:06,870] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.79 | bwd_microstep: 206.43 | bwd_inner_microstep: 206.36 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 22:33:07,349] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.01 | bwd_microstep: 272.25 | bwd_inner_microstep: 272.24 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 22:33:07,825] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.44 | bwd_microstep: 271.08 | bwd_inner_microstep: 271.06 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 22:33:08,301] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.57 | bwd_microstep: 271.05 | bwd_inner_microstep: 271.04 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 22:33:08,778] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.32 | bwd_microstep: 271.08 | bwd_inner_microstep: 271.06 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-01 22:33:09,254] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.62 | bwd_microstep: 271.02 | bwd_inner_microstep: 271.00 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 22:33:09,729] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.04 | bwd_microstep: 270.96 | bwd_inner_microstep: 270.95 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1849 +[2025-05-01 22:33:10,292] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.19 | optimizer_step: 16.97 +[2025-05-01 22:33:10,293] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.22 | bwd_microstep: 337.56 | bwd_inner_microstep: 271.05 | bwd_allreduce_microstep: 66.46 | step_microstep: 24.12 +[2025-05-01 22:33:10,294] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2625.06 | bwd: 3884.49 | bwd_inner: 3817.16 | bwd_allreduce: 66.74 | step: 25.12 + 1%|▏ | 118/8720 [17:44<16:52:10, 7.06s/it] {'loss': 2.6495, 'grad_norm': 16.71503257751465, 'learning_rate': 4.5038167938931296e-06, 'epoch': 0.14} + 1%|▏ | 118/8720 [17:44<16:52:10, 7.06s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1883 +[2025-05-01 22:33:10,778] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.91 | bwd_microstep: 273.70 | bwd_inner_microstep: 273.69 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-01 22:33:11,256] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.81 | bwd_microstep: 273.79 | bwd_inner_microstep: 273.77 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.16 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-01 22:33:11,736] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.65 | bwd_microstep: 273.72 | bwd_inner_microstep: 273.70 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1368 +[2025-05-01 22:33:12,099] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.93 | bwd_microstep: 207.17 | bwd_inner_microstep: 207.16 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-01 22:33:12,577] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.80 | bwd_microstep: 273.34 | bwd_inner_microstep: 273.32 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-01 22:33:13,055] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.68 | bwd_microstep: 273.13 | bwd_inner_microstep: 273.11 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-01 22:33:13,533] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.40 | bwd_microstep: 273.41 | bwd_inner_microstep: 273.39 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-01 22:33:14,012] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.21 | bwd_microstep: 273.83 | bwd_inner_microstep: 273.81 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-01 22:33:14,488] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.63 | bwd_microstep: 272.99 | bwd_inner_microstep: 272.97 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1348 +[2025-05-01 22:33:14,850] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.67 | bwd_microstep: 205.84 | bwd_inner_microstep: 205.82 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-01 22:33:15,328] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.43 | bwd_microstep: 273.19 | bwd_inner_microstep: 273.17 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-01 22:33:15,804] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.12 | bwd_microstep: 272.54 | bwd_inner_microstep: 272.52 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1349 +[2025-05-01 22:33:16,164] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.42 | bwd_microstep: 205.82 | bwd_inner_microstep: 205.80 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 22:33:16,638] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.73 | bwd_microstep: 271.34 | bwd_inner_microstep: 271.33 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 22:33:17,113] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.55 | bwd_microstep: 271.59 | bwd_inner_microstep: 271.57 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 22:33:17,678] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 3.12 | optimizer_step: 16.37 +[2025-05-01 22:33:17,679] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.67 | bwd_microstep: 337.40 | bwd_inner_microstep: 271.74 | bwd_allreduce_microstep: 65.63 | step_microstep: 24.28 +[2025-05-01 22:33:17,680] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2880.36 | bwd: 4232.82 | bwd_inner: 4166.88 | bwd_allreduce: 65.71 | step: 25.11 + 1%|▏ | 119/8720 [17:51<17:06:03, 7.16s/it] {'loss': 2.7531, 'grad_norm': 7.847023963928223, 'learning_rate': 4.541984732824427e-06, 'epoch': 0.14} + 1%|▏ | 119/8720 [17:51<17:06:03, 7.16s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2013 +[2025-05-01 22:33:18,193] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 198.03 | bwd_microstep: 295.22 | bwd_inner_microstep: 295.20 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1957 +[2025-05-01 22:33:18,695] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 196.84 | bwd_microstep: 290.23 | bwd_inner_microstep: 290.21 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1436 +[2025-05-01 22:33:19,070] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 145.39 | bwd_microstep: 214.51 | bwd_inner_microstep: 214.50 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1891 +[2025-05-01 22:33:19,550] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.79 | bwd_microstep: 275.43 | bwd_inner_microstep: 275.41 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 867 +[2025-05-01 22:33:19,796] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.59 | bwd_microstep: 133.91 | bwd_inner_microstep: 133.78 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-01 22:33:20,277] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.99 | bwd_microstep: 273.56 | bwd_inner_microstep: 273.54 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-01 22:33:20,767] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.96 | bwd_microstep: 272.98 | bwd_inner_microstep: 272.97 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 22:33:21,243] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.95 | bwd_microstep: 272.54 | bwd_inner_microstep: 272.52 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-01 22:33:21,720] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.40 | bwd_microstep: 273.49 | bwd_inner_microstep: 273.47 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 838 +[2025-05-01 22:33:21,958] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.94 | bwd_microstep: 126.16 | bwd_inner_microstep: 125.92 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.15 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 833 +[2025-05-01 22:33:22,193] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.41 | bwd_microstep: 125.67 | bwd_inner_microstep: 125.47 | bwd_allreduce_microstep: 0.09 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 22:33:22,671] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.81 | bwd_microstep: 271.24 | bwd_inner_microstep: 271.23 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 22:33:23,151] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.65 | bwd_microstep: 271.28 | bwd_inner_microstep: 271.26 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 22:33:23,631] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.54 | bwd_microstep: 271.18 | bwd_inner_microstep: 271.16 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 22:33:24,111] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.52 | bwd_microstep: 271.08 | bwd_inner_microstep: 271.06 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 22:33:24,697] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.23 | optimizer_step: 16.39 +[2025-05-01 22:33:24,697] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.67 | bwd_microstep: 354.62 | bwd_inner_microstep: 271.39 | bwd_allreduce_microstep: 83.18 | step_microstep: 24.16 +[2025-05-01 22:33:24,699] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2711.11 | bwd: 3993.17 | bwd_inner: 3909.11 | bwd_allreduce: 83.50 | step: 25.28 + 1%|▏ | 120/8720 [17:58<17:00:03, 7.12s/it] {'loss': 2.954, 'grad_norm': 11.293940544128418, 'learning_rate': 4.580152671755725e-06, 'epoch': 0.14} + 1%|▏ | 120/8720 [17:58<17:00:03, 7.12s/it]dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 993 +[2025-05-01 22:33:24,973] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 101.95 | bwd_microstep: 150.68 | bwd_inner_microstep: 150.54 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-01 22:33:25,454] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.24 | bwd_microstep: 273.85 | bwd_inner_microstep: 273.83 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1361 +[2025-05-01 22:33:25,819] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 142.18 | bwd_microstep: 206.84 | bwd_inner_microstep: 206.82 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-01 22:33:26,299] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.50 | bwd_microstep: 273.64 | bwd_inner_microstep: 273.62 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-01 22:33:26,777] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.91 | bwd_microstep: 273.63 | bwd_inner_microstep: 273.61 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-01 22:33:27,256] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.23 | bwd_microstep: 273.13 | bwd_inner_microstep: 273.12 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-01 22:33:27,734] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.18 | bwd_microstep: 273.30 | bwd_inner_microstep: 273.29 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-01 22:33:28,212] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.32 | bwd_microstep: 273.62 | bwd_inner_microstep: 273.61 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.16 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-01 22:33:28,690] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.54 | bwd_microstep: 273.08 | bwd_inner_microstep: 273.06 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-01 22:33:29,167] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.12 | bwd_microstep: 272.95 | bwd_inner_microstep: 272.93 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 22:33:29,643] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.37 | bwd_microstep: 272.67 | bwd_inner_microstep: 272.66 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-01 22:33:30,119] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.00 | bwd_microstep: 272.92 | bwd_inner_microstep: 272.90 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 22:33:30,595] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.77 | bwd_microstep: 272.50 | bwd_inner_microstep: 272.49 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-01 22:33:31,073] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.36 | bwd_microstep: 273.08 | bwd_inner_microstep: 273.07 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-01 22:33:31,551] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.97 | bwd_microstep: 273.04 | bwd_inner_microstep: 273.02 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1894 +[2025-05-01 22:33:32,122] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.18 | optimizer_step: 16.43 +[2025-05-01 22:33:32,123] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.29 | bwd_microstep: 343.59 | bwd_inner_microstep: 275.70 | bwd_allreduce_microstep: 67.85 | step_microstep: 23.32 +[2025-05-01 22:33:32,124] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2890.65 | bwd: 4252.59 | bwd_inner: 4184.29 | bwd_allreduce: 67.98 | step: 24.21 + 1%|▏ | 121/8720 [18:05<17:13:07, 7.21s/it] {'loss': 3.6077, 'grad_norm': 11.30330753326416, 'learning_rate': 4.618320610687023e-06, 'epoch': 0.14} + 1%|▏ | 121/8720 [18:05<17:13:07, 7.21s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1909 +[2025-05-01 22:33:32,609] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.79 | bwd_microstep: 275.96 | bwd_inner_microstep: 275.95 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1896 +[2025-05-01 22:33:33,091] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.32 | bwd_microstep: 275.41 | bwd_inner_microstep: 275.40 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1900 +[2025-05-01 22:33:33,573] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.27 | bwd_microstep: 275.68 | bwd_inner_microstep: 275.66 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1934 +[2025-05-01 22:33:34,075] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 196.39 | bwd_microstep: 288.95 | bwd_inner_microstep: 288.93 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 353 +[2025-05-01 22:33:34,296] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 85.13 | bwd_microstep: 120.02 | bwd_inner_microstep: 119.86 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1883 +[2025-05-01 22:33:34,778] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.96 | bwd_microstep: 274.78 | bwd_inner_microstep: 274.76 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-01 22:33:35,262] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.36 | bwd_microstep: 274.01 | bwd_inner_microstep: 273.99 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 22:33:35,742] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.31 | bwd_microstep: 273.23 | bwd_inner_microstep: 273.22 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 22:33:36,223] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.92 | bwd_microstep: 273.15 | bwd_inner_microstep: 273.14 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-01 22:33:36,704] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.43 | bwd_microstep: 273.76 | bwd_inner_microstep: 273.75 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 22:33:37,184] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.51 | bwd_microstep: 273.10 | bwd_inner_microstep: 273.08 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 22:33:37,664] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.44 | bwd_microstep: 272.91 | bwd_inner_microstep: 272.89 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 22:33:38,149] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.05 | bwd_microstep: 273.52 | bwd_inner_microstep: 273.46 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 22:33:38,631] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.91 | bwd_microstep: 274.19 | bwd_inner_microstep: 274.17 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-01 22:33:39,113] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.90 | bwd_microstep: 273.73 | bwd_inner_microstep: 273.67 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 22:33:39,704] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.26 | optimizer_step: 21.73 +[2025-05-01 22:33:39,705] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.43 | bwd_microstep: 352.84 | bwd_inner_microstep: 274.25 | bwd_allreduce_microstep: 78.53 | step_microstep: 30.10 +[2025-05-01 22:33:39,706] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2935.80 | bwd: 4325.28 | bwd_inner: 4246.23 | bwd_allreduce: 78.69 | step: 30.94 + 1%|▏ | 122/8720 [18:13<17:29:08, 7.32s/it] {'loss': 3.1932, 'grad_norm': 18.693767547607422, 'learning_rate': 4.656488549618321e-06, 'epoch': 0.14} + 1%|▏ | 122/8720 [18:13<17:29:08, 7.32s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1925 +[2025-05-01 22:33:40,213] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 196.00 | bwd_microstep: 287.12 | bwd_inner_microstep: 287.11 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 348 +[2025-05-01 22:33:40,421] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 72.65 | bwd_microstep: 121.38 | bwd_inner_microstep: 121.17 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.10 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 343 +[2025-05-01 22:33:40,621] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 67.80 | bwd_microstep: 118.94 | bwd_inner_microstep: 118.81 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1372 +[2025-05-01 22:33:40,984] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.04 | bwd_microstep: 207.93 | bwd_inner_microstep: 207.91 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-01 22:33:41,460] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.37 | bwd_microstep: 272.75 | bwd_inner_microstep: 272.73 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 842 +[2025-05-01 22:33:41,700] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.55 | bwd_microstep: 132.03 | bwd_inner_microstep: 131.77 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-01 22:33:42,175] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.83 | bwd_microstep: 272.58 | bwd_inner_microstep: 272.56 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 22:33:42,651] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.54 | bwd_microstep: 272.41 | bwd_inner_microstep: 272.39 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 22:33:43,127] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.93 | bwd_microstep: 272.68 | bwd_inner_microstep: 272.66 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 22:33:43,604] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.31 | bwd_microstep: 272.59 | bwd_inner_microstep: 272.57 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 22:33:44,080] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.48 | bwd_microstep: 272.39 | bwd_inner_microstep: 272.38 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 22:33:44,557] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.22 | bwd_microstep: 272.21 | bwd_inner_microstep: 272.19 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 22:33:45,031] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.50 | bwd_microstep: 271.23 | bwd_inner_microstep: 271.21 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 22:33:45,507] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.80 | bwd_microstep: 271.31 | bwd_inner_microstep: 271.29 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-01 22:33:45,986] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.83 | bwd_microstep: 271.26 | bwd_inner_microstep: 271.24 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.15 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1895 +[2025-05-01 22:33:46,574] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.20 | optimizer_step: 16.51 +[2025-05-01 22:33:46,575] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.34 | bwd_microstep: 353.43 | bwd_inner_microstep: 275.75 | bwd_allreduce_microstep: 77.64 | step_microstep: 24.21 +[2025-05-01 22:33:46,576] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2645.91 | bwd: 3942.30 | bwd_inner: 3863.85 | bwd_allreduce: 77.93 | step: 25.15 + 1%|▏ | 123/8720 [18:20<17:09:37, 7.19s/it] {'loss': 5.0693, 'grad_norm': 18.227622985839844, 'learning_rate': 4.694656488549618e-06, 'epoch': 0.14} + 1%|▏ | 123/8720 [18:20<17:09:37, 7.19s/it]dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1181 +[2025-05-01 22:33:46,892] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 120.42 | bwd_microstep: 172.86 | bwd_inner_microstep: 172.72 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 912 +[2025-05-01 22:33:47,154] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 100.91 | bwd_microstep: 144.88 | bwd_inner_microstep: 144.67 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.18 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1372 +[2025-05-01 22:33:47,520] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.86 | bwd_microstep: 207.88 | bwd_inner_microstep: 207.86 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-01 22:33:48,004] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.28 | bwd_microstep: 273.74 | bwd_inner_microstep: 273.72 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-01 22:33:48,487] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.68 | bwd_microstep: 273.06 | bwd_inner_microstep: 273.04 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.13 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 845 +[2025-05-01 22:33:48,735] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 97.77 | bwd_microstep: 132.15 | bwd_inner_microstep: 132.00 | bwd_allreduce_microstep: 0.08 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 22:33:49,216] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.76 | bwd_microstep: 272.51 | bwd_inner_microstep: 272.49 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-01 22:33:49,695] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.46 | bwd_microstep: 272.79 | bwd_inner_microstep: 272.77 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 22:33:50,176] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.39 | bwd_microstep: 272.48 | bwd_inner_microstep: 272.46 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-01 22:33:50,655] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.55 | bwd_microstep: 272.76 | bwd_inner_microstep: 272.74 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 22:33:51,134] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.22 | bwd_microstep: 272.41 | bwd_inner_microstep: 272.39 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 22:33:51,616] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.58 | bwd_microstep: 272.64 | bwd_inner_microstep: 272.62 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.14 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-01 22:33:52,095] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.31 | bwd_microstep: 271.18 | bwd_inner_microstep: 271.16 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-01 22:33:52,574] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.11 | bwd_microstep: 271.17 | bwd_inner_microstep: 271.15 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 22:33:53,050] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.93 | bwd_microstep: 271.00 | bwd_inner_microstep: 270.98 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.15 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 400 +[2025-05-01 22:33:53,405] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.21 | optimizer_step: 17.65 +[2025-05-01 22:33:53,405] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 89.62 | bwd_microstep: 222.14 | bwd_inner_microstep: 145.72 | bwd_allreduce_microstep: 76.32 | step_microstep: 25.47 +[2025-05-01 22:33:53,407] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2622.44 | bwd: 3875.75 | bwd_inner: 3798.57 | bwd_allreduce: 76.63 | step: 26.88 + 1%|▏ | 124/8720 [18:27<16:54:14, 7.08s/it] {'loss': 2.6767, 'grad_norm': 12.606186866760254, 'learning_rate': 4.732824427480917e-06, 'epoch': 0.14} + 1%|▏ | 124/8720 [18:27<16:54:14, 7.08s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1984 +[2025-05-01 22:33:53,919] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 196.69 | bwd_microstep: 292.04 | bwd_inner_microstep: 292.02 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1900 +[2025-05-01 22:33:54,401] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.60 | bwd_microstep: 275.58 | bwd_inner_microstep: 275.56 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-01 22:33:54,882] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.61 | bwd_microstep: 274.77 | bwd_inner_microstep: 274.75 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1887 +[2025-05-01 22:33:55,361] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.00 | bwd_microstep: 275.18 | bwd_inner_microstep: 275.16 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-01 22:33:55,842] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.80 | bwd_microstep: 274.31 | bwd_inner_microstep: 274.29 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-01 22:33:56,320] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.48 | bwd_microstep: 273.33 | bwd_inner_microstep: 273.31 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 22:33:56,799] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.33 | bwd_microstep: 272.57 | bwd_inner_microstep: 272.55 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-01 22:33:57,279] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.19 | bwd_microstep: 272.93 | bwd_inner_microstep: 272.91 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 22:33:57,760] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.25 | bwd_microstep: 272.77 | bwd_inner_microstep: 272.75 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 22:33:58,242] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.05 | bwd_microstep: 272.76 | bwd_inner_microstep: 272.74 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 22:33:58,723] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.08 | bwd_microstep: 272.85 | bwd_inner_microstep: 272.83 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 323 +[2025-05-01 22:33:58,939] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 79.18 | bwd_microstep: 120.95 | bwd_inner_microstep: 120.71 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 22:33:59,419] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.67 | bwd_microstep: 272.76 | bwd_inner_microstep: 272.74 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 22:33:59,897] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.30 | bwd_microstep: 272.49 | bwd_inner_microstep: 272.47 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-01 22:34:00,372] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.89 | bwd_microstep: 271.08 | bwd_inner_microstep: 271.06 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1347 +[2025-05-01 22:34:00,844] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.29 | optimizer_step: 16.72 +[2025-05-01 22:34:00,845] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.51 | bwd_microstep: 289.05 | bwd_inner_microstep: 206.10 | bwd_allreduce_microstep: 82.77 | step_microstep: 24.75 +[2025-05-01 22:34:00,846] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2877.32 | bwd: 4255.43 | bwd_inner: 4172.12 | bwd_allreduce: 82.87 | step: 25.72 + 1%|▏ | 125/8720 [18:34<17:09:38, 7.19s/it] {'loss': 4.1567, 'grad_norm': 13.125513076782227, 'learning_rate': 4.770992366412215e-06, 'epoch': 0.14} + 1%|▏ | 125/8720 [18:34<17:09:38, 7.19s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-01 22:34:01,333] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.84 | bwd_microstep: 272.88 | bwd_inner_microstep: 272.86 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1352 +[2025-05-01 22:34:01,699] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.18 | bwd_microstep: 206.01 | bwd_inner_microstep: 205.99 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.09 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 841 +[2025-05-01 22:34:01,946] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 98.22 | bwd_microstep: 131.86 | bwd_inner_microstep: 131.69 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 22:34:02,427] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.92 | bwd_microstep: 273.12 | bwd_inner_microstep: 273.10 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-01 22:34:02,908] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.45 | bwd_microstep: 273.09 | bwd_inner_microstep: 273.07 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 22:34:03,386] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.33 | bwd_microstep: 272.38 | bwd_inner_microstep: 272.36 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 22:34:03,866] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.26 | bwd_microstep: 272.21 | bwd_inner_microstep: 272.19 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-01 22:34:04,347] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.55 | bwd_microstep: 272.80 | bwd_inner_microstep: 272.78 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 22:34:04,827] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.86 | bwd_microstep: 272.41 | bwd_inner_microstep: 272.39 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 22:34:05,306] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.33 | bwd_microstep: 272.28 | bwd_inner_microstep: 272.26 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 22:34:05,784] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.65 | bwd_microstep: 272.29 | bwd_inner_microstep: 272.27 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 22:34:06,264] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.29 | bwd_microstep: 271.10 | bwd_inner_microstep: 271.09 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.16 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 22:34:06,743] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.53 | bwd_microstep: 271.17 | bwd_inner_microstep: 271.16 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 22:34:07,226] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.93 | bwd_microstep: 271.06 | bwd_inner_microstep: 271.04 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 22:34:07,703] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.16 | bwd_microstep: 271.04 | bwd_inner_microstep: 271.03 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1850 +[2025-05-01 22:34:08,282] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.24 | optimizer_step: 16.70 +[2025-05-01 22:34:08,283] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.53 | bwd_microstep: 348.05 | bwd_inner_microstep: 271.55 | bwd_allreduce_microstep: 76.45 | step_microstep: 24.64 +[2025-05-01 22:34:08,284] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2875.66 | bwd: 4223.77 | bwd_inner: 4146.86 | bwd_allreduce: 76.59 | step: 25.69 + 1%|▏ | 126/8720 [18:42<17:20:16, 7.26s/it] {'loss': 2.919, 'grad_norm': 12.796950340270996, 'learning_rate': 4.8091603053435125e-06, 'epoch': 0.14} + 1%|▏ | 126/8720 [18:42<17:20:16, 7.26s/it]dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1708 +[2025-05-01 22:34:08,725] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 160.00 | bwd_microstep: 256.47 | bwd_inner_microstep: 256.38 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 384 +[2025-05-01 22:34:08,938] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 73.13 | bwd_microstep: 126.37 | bwd_inner_microstep: 126.05 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1883 +[2025-05-01 22:34:09,420] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.51 | bwd_microstep: 274.56 | bwd_inner_microstep: 274.55 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.15 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-01 22:34:09,902] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.46 | bwd_microstep: 273.87 | bwd_inner_microstep: 273.85 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-01 22:34:10,381] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.91 | bwd_microstep: 273.25 | bwd_inner_microstep: 273.24 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-01 22:34:10,860] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.97 | bwd_microstep: 272.82 | bwd_inner_microstep: 272.80 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 327 +[2025-05-01 22:34:11,079] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 78.07 | bwd_microstep: 126.88 | bwd_inner_microstep: 126.74 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 22:34:11,556] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.34 | bwd_microstep: 272.79 | bwd_inner_microstep: 272.77 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 835 +[2025-05-01 22:34:11,796] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 91.48 | bwd_microstep: 133.94 | bwd_inner_microstep: 133.92 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 22:34:12,273] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.76 | bwd_microstep: 272.91 | bwd_inner_microstep: 272.89 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 22:34:12,750] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.00 | bwd_microstep: 271.50 | bwd_inner_microstep: 271.49 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.16 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 22:34:13,226] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.77 | bwd_microstep: 271.35 | bwd_inner_microstep: 271.34 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 22:34:13,700] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.87 | bwd_microstep: 271.19 | bwd_inner_microstep: 271.17 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1850 +[2025-05-01 22:34:14,175] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.61 | bwd_microstep: 271.14 | bwd_inner_microstep: 271.12 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2005 +[2025-05-01 22:34:14,685] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 198.78 | bwd_microstep: 295.37 | bwd_inner_microstep: 295.36 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1952 +[2025-05-01 22:34:15,285] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.30 | optimizer_step: 16.90 +[2025-05-01 22:34:15,285] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 197.34 | bwd_microstep: 356.59 | bwd_inner_microstep: 290.61 | bwd_allreduce_microstep: 65.93 | step_microstep: 24.01 +[2025-05-01 22:34:15,286] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2685.70 | bwd: 4021.07 | bwd_inner: 3954.37 | bwd_allreduce: 66.25 | step: 25.14 + 1%|▏ | 127/8720 [18:49<17:08:50, 7.18s/it] {'loss': 2.568, 'grad_norm': 13.371537208557129, 'learning_rate': 4.847328244274809e-06, 'epoch': 0.15} + 1%|▏ | 127/8720 [18:49<17:08:50, 7.18s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2024 +[2025-05-01 22:34:15,802] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 199.20 | bwd_microstep: 295.97 | bwd_inner_microstep: 295.95 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1941 +[2025-05-01 22:34:16,302] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.90 | bwd_microstep: 288.88 | bwd_inner_microstep: 288.86 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.23 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1903 +[2025-05-01 22:34:16,786] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.13 | bwd_microstep: 275.95 | bwd_inner_microstep: 275.93 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1894 +[2025-05-01 22:34:17,273] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.23 | bwd_microstep: 275.33 | bwd_inner_microstep: 275.31 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-01 22:34:17,761] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.49 | bwd_microstep: 274.28 | bwd_inner_microstep: 274.26 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 839 +[2025-05-01 22:34:18,021] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 116.12 | bwd_microstep: 125.51 | bwd_inner_microstep: 125.32 | bwd_allreduce_microstep: 0.08 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 22:34:18,504] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.22 | bwd_microstep: 272.44 | bwd_inner_microstep: 272.42 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 22:34:18,985] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.55 | bwd_microstep: 272.63 | bwd_inner_microstep: 272.58 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.15 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 22:34:19,475] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.18 | bwd_microstep: 272.41 | bwd_inner_microstep: 272.40 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.22 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 22:34:19,954] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.11 | bwd_microstep: 272.81 | bwd_inner_microstep: 272.79 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 322 +[2025-05-01 22:34:20,199] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.95 | bwd_microstep: 136.00 | bwd_inner_microstep: 135.83 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 22:34:20,675] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.89 | bwd_microstep: 271.56 | bwd_inner_microstep: 271.54 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 22:34:21,153] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.15 | bwd_microstep: 271.56 | bwd_inner_microstep: 271.54 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 22:34:21,630] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.05 | bwd_microstep: 271.54 | bwd_inner_microstep: 271.52 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 22:34:22,105] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.13 | bwd_microstep: 271.42 | bwd_inner_microstep: 271.41 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.22 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1903 +[2025-05-01 22:34:22,697] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.26 | optimizer_step: 16.82 +[2025-05-01 22:34:22,698] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.73 | bwd_microstep: 361.86 | bwd_inner_microstep: 276.21 | bwd_allreduce_microstep: 85.60 | step_microstep: 25.56 +[2025-05-01 22:34:22,699] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2875.66 | bwd: 4210.23 | bwd_inner: 4123.93 | bwd_allreduce: 85.82 | step: 27.04 + 1%|▏ | 128/8720 [18:56<17:18:34, 7.25s/it] {'loss': 2.8608, 'grad_norm': 13.787858963012695, 'learning_rate': 4.885496183206107e-06, 'epoch': 0.15} + 1%|▏ | 128/8720 [18:56<17:18:34, 7.25s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1944 +[2025-05-01 22:34:23,205] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.55 | bwd_microstep: 288.46 | bwd_inner_microstep: 288.45 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1903 +[2025-05-01 22:34:23,686] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.65 | bwd_microstep: 275.76 | bwd_inner_microstep: 275.75 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-01 22:34:24,164] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.01 | bwd_microstep: 273.91 | bwd_inner_microstep: 273.89 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-01 22:34:24,642] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.04 | bwd_microstep: 274.31 | bwd_inner_microstep: 274.29 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-01 22:34:25,121] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.21 | bwd_microstep: 272.54 | bwd_inner_microstep: 272.52 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-01 22:34:25,601] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.39 | bwd_microstep: 272.89 | bwd_inner_microstep: 272.88 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 22:34:26,083] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.13 | bwd_microstep: 272.39 | bwd_inner_microstep: 272.38 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 836 +[2025-05-01 22:34:26,322] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.39 | bwd_microstep: 125.95 | bwd_inner_microstep: 125.86 | bwd_allreduce_microstep: 0.04 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 22:34:26,800] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.02 | bwd_microstep: 272.35 | bwd_inner_microstep: 272.33 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 22:34:27,280] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.95 | bwd_microstep: 272.20 | bwd_inner_microstep: 272.18 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1346 +[2025-05-01 22:34:27,645] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.42 | bwd_microstep: 205.42 | bwd_inner_microstep: 205.40 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 22:34:28,121] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.37 | bwd_microstep: 271.46 | bwd_inner_microstep: 271.44 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 22:34:28,598] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.52 | bwd_microstep: 271.37 | bwd_inner_microstep: 271.35 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 22:34:29,075] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.98 | bwd_microstep: 271.23 | bwd_inner_microstep: 271.21 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.17 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 22:34:29,553] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.00 | bwd_microstep: 271.48 | bwd_inner_microstep: 271.47 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 22:34:30,129] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.15 | optimizer_step: 16.57 +[2025-05-01 22:34:30,129] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.69 | bwd_microstep: 346.88 | bwd_inner_microstep: 271.99 | bwd_allreduce_microstep: 74.85 | step_microstep: 23.51 +[2025-05-01 22:34:30,130] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2880.00 | bwd: 4238.65 | bwd_inner: 4163.39 | bwd_allreduce: 75.00 | step: 24.49 + 1%|▏ | 129/8720 [19:03<17:26:06, 7.31s/it] {'loss': 2.7609, 'grad_norm': 19.77717399597168, 'learning_rate': 4.923664122137405e-06, 'epoch': 0.15} + 1%|▏ | 129/8720 [19:03<17:26:06, 7.31s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2053 +[2025-05-01 22:34:30,653] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 201.31 | bwd_microstep: 301.40 | bwd_inner_microstep: 301.38 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-01 22:34:31,133] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.53 | bwd_microstep: 274.47 | bwd_inner_microstep: 274.45 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1379 +[2025-05-01 22:34:31,500] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 142.61 | bwd_microstep: 208.28 | bwd_inner_microstep: 208.26 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-01 22:34:31,980] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.31 | bwd_microstep: 273.60 | bwd_inner_microstep: 273.58 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 338 +[2025-05-01 22:34:32,178] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 67.95 | bwd_microstep: 117.20 | bwd_inner_microstep: 117.07 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 847 +[2025-05-01 22:34:32,418] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.05 | bwd_microstep: 133.00 | bwd_inner_microstep: 132.82 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.08 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 844 +[2025-05-01 22:34:32,658] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.34 | bwd_microstep: 132.45 | bwd_inner_microstep: 132.39 | bwd_allreduce_microstep: 0.03 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-01 22:34:33,135] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.62 | bwd_microstep: 272.78 | bwd_inner_microstep: 272.76 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-01 22:34:33,612] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.36 | bwd_microstep: 272.86 | bwd_inner_microstep: 272.84 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 22:34:34,088] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.25 | bwd_microstep: 272.39 | bwd_inner_microstep: 272.37 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 22:34:34,566] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.07 | bwd_microstep: 272.66 | bwd_inner_microstep: 272.64 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-01 22:34:35,042] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.87 | bwd_microstep: 272.85 | bwd_inner_microstep: 272.83 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 22:34:35,518] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.84 | bwd_microstep: 272.08 | bwd_inner_microstep: 272.07 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 22:34:35,994] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.45 | bwd_microstep: 272.44 | bwd_inner_microstep: 272.42 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 22:34:36,472] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.24 | bwd_microstep: 272.57 | bwd_inner_microstep: 272.55 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 22:34:37,039] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.04 | optimizer_gradients: 2.19 | optimizer_step: 16.51 +[2025-05-01 22:34:37,040] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.96 | bwd_microstep: 339.74 | bwd_inner_microstep: 273.03 | bwd_allreduce_microstep: 66.68 | step_microstep: 23.43 +[2025-05-01 22:34:37,041] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2675.50 | bwd: 3960.82 | bwd_inner: 3893.55 | bwd_allreduce: 66.89 | step: 24.36 + 1%|▏ | 130/8720 [19:10<17:08:57, 7.19s/it] {'loss': 3.5079, 'grad_norm': 18.638925552368164, 'learning_rate': 4.961832061068703e-06, 'epoch': 0.15} + 1%|▏ | 130/8720 [19:10<17:08:57, 7.19s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1920 +[2025-05-01 22:34:37,526] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.82 | bwd_microstep: 276.07 | bwd_inner_microstep: 276.06 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1921 +[2025-05-01 22:34:38,024] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.12 | bwd_microstep: 287.32 | bwd_inner_microstep: 287.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 867 +[2025-05-01 22:34:38,268] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.90 | bwd_microstep: 134.74 | bwd_inner_microstep: 134.47 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-01 22:34:38,747] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.21 | bwd_microstep: 274.48 | bwd_inner_microstep: 274.47 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-01 22:34:39,227] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.62 | bwd_microstep: 274.02 | bwd_inner_microstep: 274.00 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-01 22:34:39,706] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.56 | bwd_microstep: 273.71 | bwd_inner_microstep: 273.69 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 22:34:40,184] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.11 | bwd_microstep: 272.62 | bwd_inner_microstep: 272.61 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-01 22:34:40,660] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.59 | bwd_microstep: 272.73 | bwd_inner_microstep: 272.71 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 22:34:41,135] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.83 | bwd_microstep: 272.40 | bwd_inner_microstep: 272.38 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-01 22:34:41,612] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.54 | bwd_microstep: 272.76 | bwd_inner_microstep: 272.75 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 22:34:42,088] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.89 | bwd_microstep: 272.49 | bwd_inner_microstep: 272.47 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 22:34:42,567] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.53 | bwd_microstep: 272.42 | bwd_inner_microstep: 272.40 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 22:34:43,043] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.72 | bwd_microstep: 271.47 | bwd_inner_microstep: 271.45 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 22:34:43,518] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.96 | bwd_microstep: 271.12 | bwd_inner_microstep: 271.10 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 22:34:43,992] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.56 | bwd_microstep: 271.08 | bwd_inner_microstep: 271.06 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1888 +[2025-05-01 22:34:44,563] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.04 | optimizer_gradients: 2.18 | optimizer_step: 16.48 +[2025-05-01 22:34:44,563] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.29 | bwd_microstep: 341.95 | bwd_inner_microstep: 275.29 | bwd_allreduce_microstep: 66.61 | step_microstep: 23.38 +[2025-05-01 22:34:44,564] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2934.99 | bwd: 4311.40 | bwd_inner: 4244.21 | bwd_allreduce: 66.81 | step: 24.32 + 2%|▏ | 131/8720 [19:18<17:23:17, 7.29s/it] {'loss': 3.1254, 'grad_norm': 12.677240371704102, 'learning_rate': 5e-06, 'epoch': 0.15} + 2%|▏ | 131/8720 [19:18<17:23:17, 7.29s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1931 +[2025-05-01 22:34:45,068] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 196.56 | bwd_microstep: 287.34 | bwd_inner_microstep: 287.33 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1144 +[2025-05-01 22:34:45,363] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 116.70 | bwd_microstep: 164.87 | bwd_inner_microstep: 164.85 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-01 22:34:45,842] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.96 | bwd_microstep: 273.92 | bwd_inner_microstep: 273.91 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1896 +[2025-05-01 22:34:46,323] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.54 | bwd_microstep: 275.21 | bwd_inner_microstep: 275.19 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1367 +[2025-05-01 22:34:46,686] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.14 | bwd_microstep: 207.29 | bwd_inner_microstep: 207.21 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-01 22:34:47,164] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.31 | bwd_microstep: 273.91 | bwd_inner_microstep: 273.90 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-01 22:34:47,643] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.60 | bwd_microstep: 273.75 | bwd_inner_microstep: 273.73 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-01 22:34:48,123] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.07 | bwd_microstep: 273.40 | bwd_inner_microstep: 273.39 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-01 22:34:48,603] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.22 | bwd_microstep: 273.18 | bwd_inner_microstep: 273.16 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-01 22:34:49,084] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.47 | bwd_microstep: 273.05 | bwd_inner_microstep: 273.03 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 333 +[2025-05-01 22:34:49,318] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 100.38 | bwd_microstep: 115.98 | bwd_inner_microstep: 115.75 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 22:34:49,797] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.10 | bwd_microstep: 272.61 | bwd_inner_microstep: 272.59 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 22:34:50,277] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.63 | bwd_microstep: 272.70 | bwd_inner_microstep: 272.68 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 22:34:50,756] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.09 | bwd_microstep: 271.44 | bwd_inner_microstep: 271.42 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 22:34:51,235] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.19 | bwd_microstep: 271.29 | bwd_inner_microstep: 271.27 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1939 +[2025-05-01 22:34:51,840] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.20 | optimizer_step: 16.48 +[2025-05-01 22:34:51,841] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.31 | bwd_microstep: 366.56 | bwd_inner_microstep: 289.51 | bwd_allreduce_microstep: 77.00 | step_microstep: 24.16 +[2025-05-01 22:34:51,842] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2827.93 | bwd: 4146.58 | bwd_inner: 4068.98 | bwd_allreduce: 77.18 | step: 25.19 + 2%|▏ | 132/8720 [19:25<17:22:49, 7.29s/it] {'loss': 2.897, 'grad_norm': 11.275993347167969, 'learning_rate': 5.038167938931297e-06, 'epoch': 0.15} + 2%|▏ | 132/8720 [19:25<17:22:49, 7.29s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 388 +[2025-05-01 22:34:52,065] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 79.79 | bwd_microstep: 121.37 | bwd_inner_microstep: 121.21 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1396 +[2025-05-01 22:34:52,435] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 143.06 | bwd_microstep: 209.87 | bwd_inner_microstep: 209.72 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1887 +[2025-05-01 22:34:52,916] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.95 | bwd_microstep: 274.60 | bwd_inner_microstep: 274.59 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 333 +[2025-05-01 22:34:53,144] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 92.40 | bwd_microstep: 117.01 | bwd_inner_microstep: 116.70 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-01 22:34:53,624] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.65 | bwd_microstep: 272.96 | bwd_inner_microstep: 272.94 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-01 22:34:54,107] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.57 | bwd_microstep: 273.12 | bwd_inner_microstep: 273.10 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 22:34:54,587] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.00 | bwd_microstep: 272.37 | bwd_inner_microstep: 272.35 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 22:34:55,068] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.14 | bwd_microstep: 272.71 | bwd_inner_microstep: 272.70 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-01 22:34:55,552] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.52 | bwd_microstep: 273.00 | bwd_inner_microstep: 272.98 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-01 22:34:56,035] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.63 | bwd_microstep: 272.91 | bwd_inner_microstep: 272.89 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-01 22:34:56,517] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.77 | bwd_microstep: 272.77 | bwd_inner_microstep: 272.75 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 22:34:56,999] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.83 | bwd_microstep: 272.29 | bwd_inner_microstep: 272.28 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 22:34:57,481] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.16 | bwd_microstep: 272.49 | bwd_inner_microstep: 272.47 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 22:34:57,963] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.16 | bwd_microstep: 271.27 | bwd_inner_microstep: 271.25 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1902 +[2025-05-01 22:34:58,452] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.99 | bwd_microstep: 275.63 | bwd_inner_microstep: 275.61 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.07 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 22:34:59,031] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.18 | optimizer_step: 16.51 +[2025-05-01 22:34:59,032] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.18 | bwd_microstep: 349.93 | bwd_inner_microstep: 272.92 | bwd_allreduce_microstep: 76.95 | step_microstep: 24.15 +[2025-05-01 22:34:59,033] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2771.39 | bwd: 4074.35 | bwd_inner: 3996.58 | bwd_allreduce: 77.30 | step: 25.37 + 2%|▏ | 133/8720 [19:32<17:18:36, 7.26s/it] {'loss': 2.5911, 'grad_norm': 14.18047046661377, 'learning_rate': 5.076335877862596e-06, 'epoch': 0.15} + 2%|▏ | 133/8720 [19:32<17:18:36, 7.26s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1925 +[2025-05-01 22:34:59,537] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 194.87 | bwd_microstep: 287.43 | bwd_inner_microstep: 287.41 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1911 +[2025-05-01 22:35:00,020] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.46 | bwd_microstep: 277.64 | bwd_inner_microstep: 277.63 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1902 +[2025-05-01 22:35:00,503] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.48 | bwd_microstep: 276.50 | bwd_inner_microstep: 276.49 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-01 22:35:00,984] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.52 | bwd_microstep: 273.91 | bwd_inner_microstep: 273.90 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-01 22:35:01,464] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.15 | bwd_microstep: 273.91 | bwd_inner_microstep: 273.89 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-01 22:35:01,943] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.73 | bwd_microstep: 273.67 | bwd_inner_microstep: 273.65 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.14 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 22:35:02,422] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.64 | bwd_microstep: 273.23 | bwd_inner_microstep: 273.21 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 327 +[2025-05-01 22:35:02,621] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 70.48 | bwd_microstep: 114.96 | bwd_inner_microstep: 114.83 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-01 22:35:03,097] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.64 | bwd_microstep: 273.39 | bwd_inner_microstep: 273.37 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 834 +[2025-05-01 22:35:03,329] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 91.26 | bwd_microstep: 126.34 | bwd_inner_microstep: 126.10 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 22:35:03,804] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.64 | bwd_microstep: 271.91 | bwd_inner_microstep: 271.89 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 22:35:04,281] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.39 | bwd_microstep: 272.06 | bwd_inner_microstep: 272.04 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 22:35:04,758] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.86 | bwd_microstep: 271.83 | bwd_inner_microstep: 271.81 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1759 +[2025-05-01 22:35:05,190] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 162.52 | bwd_microstep: 255.55 | bwd_inner_microstep: 255.53 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1957 +[2025-05-01 22:35:05,692] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 196.42 | bwd_microstep: 289.91 | bwd_inner_microstep: 289.89 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-01 22:35:06,258] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.04 | optimizer_gradients: 2.17 | optimizer_step: 16.46 +[2025-05-01 22:35:06,259] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.10 | bwd_microstep: 339.79 | bwd_inner_microstep: 273.37 | bwd_allreduce_microstep: 66.38 | step_microstep: 23.40 +[2025-05-01 22:35:06,260] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2800.87 | bwd: 4152.07 | bwd_inner: 4085.04 | bwd_allreduce: 66.62 | step: 24.27 + 2%|▏ | 134/8720 [19:40<17:17:07, 7.25s/it] {'loss': 2.5218, 'grad_norm': 8.553028106689453, 'learning_rate': 5.114503816793893e-06, 'epoch': 0.15} + 2%|▏ | 134/8720 [19:40<17:17:07, 7.25s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 439 +[2025-05-01 22:35:06,465] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 69.81 | bwd_microstep: 117.75 | bwd_inner_microstep: 117.63 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.08 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 879 +[2025-05-01 22:35:06,710] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.89 | bwd_microstep: 135.66 | bwd_inner_microstep: 135.61 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-01 22:35:07,187] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.38 | bwd_microstep: 273.98 | bwd_inner_microstep: 273.96 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 344 +[2025-05-01 22:35:07,402] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 68.23 | bwd_microstep: 133.75 | bwd_inner_microstep: 133.61 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-01 22:35:07,881] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.01 | bwd_microstep: 273.95 | bwd_inner_microstep: 273.94 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1368 +[2025-05-01 22:35:08,245] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 142.19 | bwd_microstep: 207.46 | bwd_inner_microstep: 207.33 | bwd_allreduce_microstep: 0.04 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-01 22:35:08,725] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.65 | bwd_microstep: 273.83 | bwd_inner_microstep: 273.81 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 347 +[2025-05-01 22:35:08,938] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 81.03 | bwd_microstep: 118.08 | bwd_inner_microstep: 117.90 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-01 22:35:09,418] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.08 | bwd_microstep: 273.35 | bwd_inner_microstep: 273.33 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 22:35:09,897] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.01 | bwd_microstep: 272.85 | bwd_inner_microstep: 272.83 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-01 22:35:10,376] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.18 | bwd_microstep: 273.16 | bwd_inner_microstep: 273.15 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-01 22:35:10,854] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.91 | bwd_microstep: 273.16 | bwd_inner_microstep: 273.14 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 22:35:11,331] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.47 | bwd_microstep: 272.70 | bwd_inner_microstep: 272.69 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.12 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1349 +[2025-05-01 22:35:11,696] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.84 | bwd_microstep: 205.99 | bwd_inner_microstep: 205.98 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 22:35:12,175] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.85 | bwd_microstep: 272.39 | bwd_inner_microstep: 272.37 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 318 +[2025-05-01 22:35:12,518] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.22 | optimizer_step: 16.53 +[2025-05-01 22:35:12,518] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 91.08 | bwd_microstep: 209.93 | bwd_inner_microstep: 132.91 | bwd_allreduce_microstep: 76.91 | step_microstep: 24.35 +[2025-05-01 22:35:12,520] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2387.32 | bwd: 3588.12 | bwd_inner: 3510.34 | bwd_allreduce: 77.21 | step: 25.55 + 2%|▏ | 135/8720 [19:46<16:34:41, 6.95s/it] {'loss': 3.5358, 'grad_norm': 15.865287780761719, 'learning_rate': 5.1526717557251914e-06, 'epoch': 0.15} + 2%|▏ | 135/8720 [19:46<16:34:41, 6.95s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1990 +[2025-05-01 22:35:13,033] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 197.54 | bwd_microstep: 293.27 | bwd_inner_microstep: 293.25 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 411 +[2025-05-01 22:35:13,267] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 97.79 | bwd_microstep: 117.08 | bwd_inner_microstep: 116.77 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 377 +[2025-05-01 22:35:13,490] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 90.66 | bwd_microstep: 115.86 | bwd_inner_microstep: 115.51 | bwd_allreduce_microstep: 0.16 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1899 +[2025-05-01 22:35:13,972] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.22 | bwd_microstep: 275.55 | bwd_inner_microstep: 275.53 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1892 +[2025-05-01 22:35:14,456] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.74 | bwd_microstep: 274.97 | bwd_inner_microstep: 274.95 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-01 22:35:14,937] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.69 | bwd_microstep: 273.63 | bwd_inner_microstep: 273.61 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1098 +[2025-05-01 22:35:15,232] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 116.23 | bwd_microstep: 161.38 | bwd_inner_microstep: 161.17 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-01 22:35:15,711] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.52 | bwd_microstep: 272.77 | bwd_inner_microstep: 272.75 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 22:35:16,190] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.29 | bwd_microstep: 272.34 | bwd_inner_microstep: 272.33 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 22:35:16,668] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.26 | bwd_microstep: 271.33 | bwd_inner_microstep: 271.31 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 22:35:17,145] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.32 | bwd_microstep: 272.12 | bwd_inner_microstep: 272.10 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 832 +[2025-05-01 22:35:17,394] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 97.93 | bwd_microstep: 129.99 | bwd_inner_microstep: 129.78 | bwd_allreduce_microstep: 0.08 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 22:35:17,870] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.63 | bwd_microstep: 271.37 | bwd_inner_microstep: 271.35 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-01 22:35:18,348] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.14 | bwd_microstep: 271.20 | bwd_inner_microstep: 271.19 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 22:35:18,825] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.76 | bwd_microstep: 271.19 | bwd_inner_microstep: 271.17 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1953 +[2025-05-01 22:35:19,434] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.29 | optimizer_step: 16.66 +[2025-05-01 22:35:19,435] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.85 | bwd_microstep: 368.63 | bwd_inner_microstep: 290.70 | bwd_allreduce_microstep: 77.87 | step_microstep: 24.76 +[2025-05-01 22:35:19,436] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2681.18 | bwd: 3912.80 | bwd_inner: 3833.65 | bwd_allreduce: 78.40 | step: 25.92 + 2%|▏ | 136/8720 [19:53<16:33:05, 6.94s/it] {'loss': 1.7434, 'grad_norm': 7.33637809753418, 'learning_rate': 5.190839694656488e-06, 'epoch': 0.16} + 2%|▏ | 136/8720 [19:53<16:33:05, 6.94s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2066 +[2025-05-01 22:35:19,964] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 201.68 | bwd_microstep: 302.28 | bwd_inner_microstep: 302.27 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1924 +[2025-05-01 22:35:20,466] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 194.48 | bwd_microstep: 287.47 | bwd_inner_microstep: 287.45 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1888 +[2025-05-01 22:35:20,951] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.02 | bwd_microstep: 274.73 | bwd_inner_microstep: 274.71 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-01 22:35:21,437] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.77 | bwd_microstep: 274.64 | bwd_inner_microstep: 274.62 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.17 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-01 22:35:21,921] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.19 | bwd_microstep: 273.72 | bwd_inner_microstep: 273.71 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-01 22:35:22,404] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.62 | bwd_microstep: 273.43 | bwd_inner_microstep: 273.42 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-01 22:35:22,886] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.29 | bwd_microstep: 273.37 | bwd_inner_microstep: 273.35 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-01 22:35:23,368] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.43 | bwd_microstep: 272.99 | bwd_inner_microstep: 272.97 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 22:35:23,851] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.92 | bwd_microstep: 272.52 | bwd_inner_microstep: 272.50 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 22:35:24,334] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.21 | bwd_microstep: 272.77 | bwd_inner_microstep: 272.75 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 22:35:24,814] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.03 | bwd_microstep: 272.40 | bwd_inner_microstep: 272.38 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 22:35:25,292] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.95 | bwd_microstep: 271.44 | bwd_inner_microstep: 271.42 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 22:35:25,772] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.20 | bwd_microstep: 271.52 | bwd_inner_microstep: 271.50 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 22:35:26,250] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.49 | bwd_microstep: 271.48 | bwd_inner_microstep: 271.47 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 22:35:26,726] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.19 | bwd_microstep: 271.41 | bwd_inner_microstep: 271.39 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 22:35:27,292] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.26 | optimizer_step: 16.69 +[2025-05-01 22:35:27,292] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.46 | bwd_microstep: 339.21 | bwd_inner_microstep: 271.60 | bwd_allreduce_microstep: 67.55 | step_microstep: 24.12 +[2025-05-01 22:35:27,294] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 3039.56 | bwd: 4475.40 | bwd_inner: 4407.51 | bwd_allreduce: 67.63 | step: 25.15 + 2%|▏ | 137/8720 [20:01<17:12:11, 7.22s/it] {'loss': 1.6197, 'grad_norm': 9.152923583984375, 'learning_rate': 5.229007633587787e-06, 'epoch': 0.16} + 2%|▏ | 137/8720 [20:01<17:12:11, 7.22s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1928 +[2025-05-01 22:35:27,799] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 194.95 | bwd_microstep: 287.40 | bwd_inner_microstep: 287.39 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1897 +[2025-05-01 22:35:28,283] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.77 | bwd_microstep: 275.95 | bwd_inner_microstep: 275.93 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1892 +[2025-05-01 22:35:28,767] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.96 | bwd_microstep: 275.41 | bwd_inner_microstep: 275.39 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 864 +[2025-05-01 22:35:29,021] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 101.26 | bwd_microstep: 133.70 | bwd_inner_microstep: 133.59 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-01 22:35:29,504] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.36 | bwd_microstep: 273.47 | bwd_inner_microstep: 273.46 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-01 22:35:29,987] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.94 | bwd_microstep: 273.78 | bwd_inner_microstep: 273.76 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-01 22:35:30,469] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.26 | bwd_microstep: 274.00 | bwd_inner_microstep: 273.98 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1365 +[2025-05-01 22:35:30,837] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.85 | bwd_microstep: 207.38 | bwd_inner_microstep: 207.27 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-01 22:35:31,320] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.04 | bwd_microstep: 273.49 | bwd_inner_microstep: 273.47 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 839 +[2025-05-01 22:35:31,569] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 101.07 | bwd_microstep: 127.10 | bwd_inner_microstep: 126.85 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 322 +[2025-05-01 22:35:31,800] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 88.36 | bwd_microstep: 126.54 | bwd_inner_microstep: 126.26 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 22:35:32,280] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.25 | bwd_microstep: 272.67 | bwd_inner_microstep: 272.65 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 22:35:32,762] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.53 | bwd_microstep: 272.85 | bwd_inner_microstep: 272.83 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 22:35:33,244] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.47 | bwd_microstep: 271.91 | bwd_inner_microstep: 271.89 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.15 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 318 +[2025-05-01 22:35:33,491] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 105.48 | bwd_microstep: 119.76 | bwd_inner_microstep: 119.61 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 22:35:34,070] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.32 | optimizer_step: 16.85 +[2025-05-01 22:35:34,071] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.87 | bwd_microstep: 349.24 | bwd_inner_microstep: 272.14 | bwd_allreduce_microstep: 77.04 | step_microstep: 24.64 +[2025-05-01 22:35:34,072] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2622.03 | bwd: 3814.74 | bwd_inner: 3736.58 | bwd_allreduce: 77.53 | step: 25.91 + 2%|▏ | 138/8720 [20:07<16:53:23, 7.08s/it] {'loss': 2.2471, 'grad_norm': 11.111794471740723, 'learning_rate': 5.267175572519084e-06, 'epoch': 0.16} + 2%|▏ | 138/8720 [20:07<16:53:23, 7.08s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2103 +[2025-05-01 22:35:34,609] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 203.23 | bwd_microstep: 309.93 | bwd_inner_microstep: 309.91 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1908 +[2025-05-01 22:35:35,090] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.87 | bwd_microstep: 276.32 | bwd_inner_microstep: 276.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1893 +[2025-05-01 22:35:35,571] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.06 | bwd_microstep: 275.12 | bwd_inner_microstep: 275.10 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1893 +[2025-05-01 22:35:36,055] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.17 | bwd_microstep: 275.07 | bwd_inner_microstep: 275.05 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1893 +[2025-05-01 22:35:36,540] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.52 | bwd_microstep: 274.84 | bwd_inner_microstep: 274.82 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-01 22:35:37,022] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.51 | bwd_microstep: 273.25 | bwd_inner_microstep: 273.23 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-01 22:35:37,504] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.92 | bwd_microstep: 273.69 | bwd_inner_microstep: 273.67 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 840 +[2025-05-01 22:35:37,748] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 100.37 | bwd_microstep: 126.45 | bwd_inner_microstep: 126.29 | bwd_allreduce_microstep: 0.10 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 22:35:38,227] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.72 | bwd_microstep: 272.58 | bwd_inner_microstep: 272.56 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1348 +[2025-05-01 22:35:38,593] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.71 | bwd_microstep: 205.95 | bwd_inner_microstep: 205.93 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 22:35:39,074] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.34 | bwd_microstep: 272.33 | bwd_inner_microstep: 272.32 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 22:35:39,553] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.64 | bwd_microstep: 272.50 | bwd_inner_microstep: 272.48 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 22:35:40,032] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.44 | bwd_microstep: 271.29 | bwd_inner_microstep: 271.27 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 22:35:40,515] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.57 | bwd_microstep: 272.54 | bwd_inner_microstep: 272.52 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 22:35:40,995] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.78 | bwd_microstep: 271.32 | bwd_inner_microstep: 271.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.13 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1850 +[2025-05-01 22:35:41,580] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.22 | optimizer_step: 16.69 +[2025-05-01 22:35:41,581] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.84 | bwd_microstep: 353.08 | bwd_inner_microstep: 271.43 | bwd_allreduce_microstep: 81.59 | step_microstep: 24.73 +[2025-05-01 22:35:41,582] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2900.31 | bwd: 4276.30 | bwd_inner: 4194.22 | bwd_allreduce: 81.75 | step: 25.84 + 2%|▏ | 139/8720 [20:15<17:11:32, 7.21s/it] {'loss': 1.6586, 'grad_norm': 9.90803050994873, 'learning_rate': 5.3053435114503825e-06, 'epoch': 0.16} + 2%|▏ | 139/8720 [20:15<17:11:32, 7.21s/it]dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1128 +[2025-05-01 22:35:41,887] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 117.23 | bwd_microstep: 163.40 | bwd_inner_microstep: 163.23 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1887 +[2025-05-01 22:35:42,370] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.79 | bwd_microstep: 274.72 | bwd_inner_microstep: 274.70 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-01 22:35:42,853] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.28 | bwd_microstep: 273.93 | bwd_inner_microstep: 273.91 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-01 22:35:43,336] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.79 | bwd_microstep: 273.03 | bwd_inner_microstep: 273.01 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1357 +[2025-05-01 22:35:43,702] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.92 | bwd_microstep: 206.65 | bwd_inner_microstep: 206.63 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 22:35:44,181] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.32 | bwd_microstep: 272.69 | bwd_inner_microstep: 272.67 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-01 22:35:44,662] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.33 | bwd_microstep: 273.23 | bwd_inner_microstep: 273.21 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 22:35:45,141] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.42 | bwd_microstep: 272.61 | bwd_inner_microstep: 272.59 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 22:35:45,619] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.60 | bwd_microstep: 272.56 | bwd_inner_microstep: 272.54 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 22:35:46,097] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.02 | bwd_microstep: 272.58 | bwd_inner_microstep: 272.56 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 22:35:46,574] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.06 | bwd_microstep: 272.30 | bwd_inner_microstep: 272.28 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 22:35:47,052] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.47 | bwd_microstep: 272.66 | bwd_inner_microstep: 272.64 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 22:35:47,531] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.01 | bwd_microstep: 271.04 | bwd_inner_microstep: 271.02 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 22:35:48,006] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.23 | bwd_microstep: 271.24 | bwd_inner_microstep: 271.22 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 22:35:48,481] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.62 | bwd_microstep: 271.24 | bwd_inner_microstep: 271.22 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 459 +[2025-05-01 22:35:48,793] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.15 | optimizer_step: 16.38 +[2025-05-01 22:35:48,794] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 77.84 | bwd_microstep: 197.95 | bwd_inner_microstep: 131.19 | bwd_allreduce_microstep: 66.61 | step_microstep: 23.40 +[2025-05-01 22:35:48,795] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2786.62 | bwd: 4111.85 | bwd_inner: 4044.74 | bwd_allreduce: 66.72 | step: 24.39 + 2%|▏ | 140/8720 [20:22<17:11:17, 7.21s/it] {'loss': 2.2755, 'grad_norm': 10.773575782775879, 'learning_rate': 5.34351145038168e-06, 'epoch': 0.16} + 2%|▏ | 140/8720 [20:22<17:11:17, 7.21s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1904 +[2025-05-01 22:35:49,280] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.87 | bwd_microstep: 275.18 | bwd_inner_microstep: 275.16 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-01 22:35:49,758] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.03 | bwd_microstep: 274.10 | bwd_inner_microstep: 274.08 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-01 22:35:50,236] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.73 | bwd_microstep: 274.14 | bwd_inner_microstep: 274.12 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-01 22:35:50,713] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.62 | bwd_microstep: 273.37 | bwd_inner_microstep: 273.35 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-01 22:35:51,190] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.41 | bwd_microstep: 273.44 | bwd_inner_microstep: 273.42 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-01 22:35:51,668] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.31 | bwd_microstep: 273.66 | bwd_inner_microstep: 273.65 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 856 +[2025-05-01 22:35:51,911] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.21 | bwd_microstep: 133.48 | bwd_inner_microstep: 133.35 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-01 22:35:52,388] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.69 | bwd_microstep: 273.44 | bwd_inner_microstep: 273.42 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-01 22:35:52,866] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.13 | bwd_microstep: 273.01 | bwd_inner_microstep: 272.99 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1109 +[2025-05-01 22:35:53,158] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 116.30 | bwd_microstep: 162.15 | bwd_inner_microstep: 161.95 | bwd_allreduce_microstep: 0.10 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 22:35:53,632] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.23 | bwd_microstep: 271.25 | bwd_inner_microstep: 271.23 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 838 +[2025-05-01 22:35:53,869] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 96.42 | bwd_microstep: 126.26 | bwd_inner_microstep: 126.13 | bwd_allreduce_microstep: 0.08 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-01 22:35:54,346] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.92 | bwd_microstep: 273.02 | bwd_inner_microstep: 273.01 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 323 +[2025-05-01 22:35:54,546] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 70.68 | bwd_microstep: 116.15 | bwd_inner_microstep: 115.95 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 22:35:55,021] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.19 | bwd_microstep: 271.40 | bwd_inner_microstep: 271.38 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 22:35:55,585] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.15 | optimizer_step: 16.45 +[2025-05-01 22:35:55,585] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.89 | bwd_microstep: 338.11 | bwd_inner_microstep: 271.90 | bwd_allreduce_microstep: 66.16 | step_microstep: 23.41 +[2025-05-01 22:35:55,586] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2642.40 | bwd: 3882.23 | bwd_inner: 3815.14 | bwd_allreduce: 66.52 | step: 24.33 + 2%|▏ | 141/8720 [20:29<16:53:07, 7.09s/it] {'loss': 2.3931, 'grad_norm': 13.709222793579102, 'learning_rate': 5.381679389312977e-06, 'epoch': 0.16} + 2%|▏ | 141/8720 [20:29<16:53:07, 7.09s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 388 +[2025-05-01 22:35:55,787] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 67.99 | bwd_microstep: 115.38 | bwd_inner_microstep: 115.25 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 368 +[2025-05-01 22:35:55,987] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 67.98 | bwd_microstep: 118.15 | bwd_inner_microstep: 118.01 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.09 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1364 +[2025-05-01 22:35:56,350] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.92 | bwd_microstep: 207.29 | bwd_inner_microstep: 207.22 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.09 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1096 +[2025-05-01 22:35:56,641] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 114.77 | bwd_microstep: 161.42 | bwd_inner_microstep: 161.29 | bwd_allreduce_microstep: 0.10 | step_microstep: 0.09 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 845 +[2025-05-01 22:35:56,882] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.35 | bwd_microstep: 132.74 | bwd_inner_microstep: 132.52 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-01 22:35:57,360] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.54 | bwd_microstep: 273.57 | bwd_inner_microstep: 273.55 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 839 +[2025-05-01 22:35:57,592] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 91.27 | bwd_microstep: 126.45 | bwd_inner_microstep: 126.32 | bwd_allreduce_microstep: 0.10 | step_microstep: 0.09 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 844 +[2025-05-01 22:35:57,836] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 97.47 | bwd_microstep: 132.31 | bwd_inner_microstep: 132.04 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-01 22:35:58,312] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.62 | bwd_microstep: 272.76 | bwd_inner_microstep: 272.75 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-01 22:35:58,791] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.35 | bwd_microstep: 272.48 | bwd_inner_microstep: 272.46 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.14 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 22:35:59,273] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.10 | bwd_microstep: 272.39 | bwd_inner_microstep: 272.37 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 22:35:59,756] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.29 | bwd_microstep: 272.41 | bwd_inner_microstep: 272.39 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 22:36:00,233] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.07 | bwd_microstep: 271.22 | bwd_inner_microstep: 271.20 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 22:36:00,710] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.98 | bwd_microstep: 271.32 | bwd_inner_microstep: 271.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 22:36:01,186] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.71 | bwd_microstep: 270.92 | bwd_inner_microstep: 270.90 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-01 22:36:01,773] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.07 | optimizer_gradients: 2.21 | optimizer_step: 16.55 +[2025-05-01 22:36:01,774] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.59 | bwd_microstep: 355.55 | bwd_inner_microstep: 273.58 | bwd_allreduce_microstep: 81.91 | step_microstep: 24.61 +[2025-05-01 22:36:01,775] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2368.73 | bwd: 3526.52 | bwd_inner: 3443.22 | bwd_allreduce: 82.52 | step: 26.12 + 2%|▏ | 142/8720 [20:35<16:14:40, 6.82s/it] {'loss': 2.9405, 'grad_norm': 15.98763370513916, 'learning_rate': 5.419847328244276e-06, 'epoch': 0.16} + 2%|▏ | 142/8720 [20:35<16:14:40, 6.82s/it]dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 993 +[2025-05-01 22:36:02,053] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 103.20 | bwd_microstep: 151.36 | bwd_inner_microstep: 151.07 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1966 +[2025-05-01 22:36:02,557] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 196.66 | bwd_microstep: 291.51 | bwd_inner_microstep: 291.49 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2043 +[2025-05-01 22:36:03,073] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 200.08 | bwd_microstep: 298.52 | bwd_inner_microstep: 298.50 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1935 +[2025-05-01 22:36:03,576] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 196.81 | bwd_microstep: 288.50 | bwd_inner_microstep: 288.49 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 368 +[2025-05-01 22:36:03,802] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 91.45 | bwd_microstep: 118.93 | bwd_inner_microstep: 118.66 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 362 +[2025-05-01 22:36:04,021] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 83.71 | bwd_microstep: 118.74 | bwd_inner_microstep: 118.46 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.10 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 340 +[2025-05-01 22:36:04,247] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 86.95 | bwd_microstep: 122.35 | bwd_inner_microstep: 122.13 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 834 +[2025-05-01 22:36:04,484] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.68 | bwd_microstep: 126.05 | bwd_inner_microstep: 125.95 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-01 22:36:04,965] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.54 | bwd_microstep: 272.76 | bwd_inner_microstep: 272.74 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.14 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 22:36:05,445] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.80 | bwd_microstep: 272.38 | bwd_inner_microstep: 272.37 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 22:36:05,924] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.42 | bwd_microstep: 272.53 | bwd_inner_microstep: 272.51 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 22:36:06,403] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.57 | bwd_microstep: 271.48 | bwd_inner_microstep: 271.47 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 22:36:06,882] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.97 | bwd_microstep: 271.50 | bwd_inner_microstep: 271.48 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 22:36:07,363] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.44 | bwd_microstep: 272.32 | bwd_inner_microstep: 272.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 22:36:07,843] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.36 | bwd_microstep: 271.31 | bwd_inner_microstep: 271.29 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 22:36:08,425] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.17 | optimizer_step: 16.58 +[2025-05-01 22:36:08,426] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.75 | bwd_microstep: 350.04 | bwd_inner_microstep: 272.12 | bwd_allreduce_microstep: 77.87 | step_microstep: 24.27 +[2025-05-01 22:36:08,427] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2565.06 | bwd: 3770.37 | bwd_inner: 3691.28 | bwd_allreduce: 78.37 | step: 25.46 + 2%|▏ | 143/8720 [20:42<16:07:25, 6.77s/it] {'loss': 2.3122, 'grad_norm': 9.694761276245117, 'learning_rate': 5.458015267175573e-06, 'epoch': 0.16} + 2%|▏ | 143/8720 [20:42<16:07:25, 6.77s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 383 +[2025-05-01 22:36:08,650] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 84.21 | bwd_microstep: 117.17 | bwd_inner_microstep: 116.84 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-01 22:36:09,131] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.92 | bwd_microstep: 274.20 | bwd_inner_microstep: 274.19 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 359 +[2025-05-01 22:36:09,371] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 89.97 | bwd_microstep: 132.73 | bwd_inner_microstep: 132.42 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.11 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 352 +[2025-05-01 22:36:09,614] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 101.70 | bwd_microstep: 121.05 | bwd_inner_microstep: 120.74 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1904 +[2025-05-01 22:36:10,101] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.02 | bwd_microstep: 275.82 | bwd_inner_microstep: 275.80 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-01 22:36:10,585] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.02 | bwd_microstep: 274.26 | bwd_inner_microstep: 274.24 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-01 22:36:11,066] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.32 | bwd_microstep: 273.28 | bwd_inner_microstep: 273.27 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-01 22:36:11,546] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.39 | bwd_microstep: 274.18 | bwd_inner_microstep: 274.17 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-01 22:36:12,036] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.08 | bwd_microstep: 273.20 | bwd_inner_microstep: 273.19 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 840 +[2025-05-01 22:36:12,269] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 91.52 | bwd_microstep: 126.80 | bwd_inner_microstep: 126.52 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-01 22:36:12,747] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.45 | bwd_microstep: 272.91 | bwd_inner_microstep: 272.89 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-01 22:36:13,226] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.28 | bwd_microstep: 272.80 | bwd_inner_microstep: 272.78 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1350 +[2025-05-01 22:36:13,589] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.22 | bwd_microstep: 206.35 | bwd_inner_microstep: 206.16 | bwd_allreduce_microstep: 0.10 | step_microstep: 0.19 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1341 +[2025-05-01 22:36:13,950] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 139.92 | bwd_microstep: 204.71 | bwd_inner_microstep: 204.70 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 22:36:14,426] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.82 | bwd_microstep: 271.33 | bwd_inner_microstep: 271.31 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-01 22:36:15,012] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.21 | optimizer_step: 16.61 +[2025-05-01 22:36:15,013] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.73 | bwd_microstep: 354.82 | bwd_inner_microstep: 271.62 | bwd_allreduce_microstep: 83.15 | step_microstep: 24.50 +[2025-05-01 22:36:15,014] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2538.22 | bwd: 3725.78 | bwd_inner: 3641.05 | bwd_allreduce: 83.84 | step: 25.79 + 2%|▏ | 144/8720 [20:48<15:59:35, 6.71s/it] {'loss': 2.3744, 'grad_norm': 10.57349967956543, 'learning_rate': 5.496183206106871e-06, 'epoch': 0.17} + 2%|▏ | 144/8720 [20:48<15:59:35, 6.71s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2027 +[2025-05-01 22:36:15,534] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 199.27 | bwd_microstep: 296.52 | bwd_inner_microstep: 296.51 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 987 +[2025-05-01 22:36:15,807] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 103.73 | bwd_microstep: 150.42 | bwd_inner_microstep: 150.19 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1946 +[2025-05-01 22:36:16,309] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.17 | bwd_microstep: 289.34 | bwd_inner_microstep: 289.32 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1970 +[2025-05-01 22:36:16,818] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 196.69 | bwd_microstep: 291.75 | bwd_inner_microstep: 291.73 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.23 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 860 +[2025-05-01 22:36:17,065] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.58 | bwd_microstep: 134.17 | bwd_inner_microstep: 133.87 | bwd_allreduce_microstep: 0.14 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-01 22:36:17,546] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.38 | bwd_microstep: 273.82 | bwd_inner_microstep: 273.80 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1354 +[2025-05-01 22:36:17,912] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 142.76 | bwd_microstep: 206.23 | bwd_inner_microstep: 206.21 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 22:36:18,389] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.19 | bwd_microstep: 272.67 | bwd_inner_microstep: 272.65 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 22:36:18,865] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.94 | bwd_microstep: 272.68 | bwd_inner_microstep: 272.66 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-01 22:36:19,344] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.88 | bwd_microstep: 272.72 | bwd_inner_microstep: 272.70 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 835 +[2025-05-01 22:36:19,576] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 90.87 | bwd_microstep: 126.23 | bwd_inner_microstep: 125.95 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 22:36:20,051] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.55 | bwd_microstep: 271.34 | bwd_inner_microstep: 271.32 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 22:36:20,526] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.96 | bwd_microstep: 271.52 | bwd_inner_microstep: 271.50 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 22:36:21,001] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.03 | bwd_microstep: 271.42 | bwd_inner_microstep: 271.41 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 22:36:21,480] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.06 | bwd_microstep: 272.95 | bwd_inner_microstep: 272.94 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 22:36:22,045] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.14 | optimizer_step: 16.75 +[2025-05-01 22:36:22,046] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.40 | bwd_microstep: 338.12 | bwd_inner_microstep: 271.79 | bwd_allreduce_microstep: 66.29 | step_microstep: 24.02 +[2025-05-01 22:36:22,047] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2720.17 | bwd: 4011.95 | bwd_inner: 3944.64 | bwd_allreduce: 66.69 | step: 25.08 + 2%|▏ | 145/8720 [20:55<16:13:03, 6.81s/it] {'loss': 1.8729, 'grad_norm': 9.323738098144531, 'learning_rate': 5.534351145038168e-06, 'epoch': 0.17} + 2%|▏ | 145/8720 [20:55<16:13:03, 6.81s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1971 +[2025-05-01 22:36:22,556] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 198.58 | bwd_microstep: 290.62 | bwd_inner_microstep: 290.61 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.14 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1892 +[2025-05-01 22:36:23,038] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 191.16 | bwd_microstep: 274.90 | bwd_inner_microstep: 274.88 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 6, images per sample: 6.0, dynamic token length: 1615 +[2025-05-01 22:36:23,471] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 169.31 | bwd_microstep: 247.86 | bwd_inner_microstep: 247.54 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.20 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1361 +[2025-05-01 22:36:23,835] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.13 | bwd_microstep: 207.15 | bwd_inner_microstep: 207.13 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-01 22:36:24,313] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.45 | bwd_microstep: 273.56 | bwd_inner_microstep: 273.55 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-01 22:36:24,794] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.00 | bwd_microstep: 274.07 | bwd_inner_microstep: 274.05 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 334 +[2025-05-01 22:36:24,995] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 67.70 | bwd_microstep: 119.04 | bwd_inner_microstep: 118.76 | bwd_allreduce_microstep: 0.10 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-01 22:36:25,471] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.46 | bwd_microstep: 273.40 | bwd_inner_microstep: 273.39 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1357 +[2025-05-01 22:36:25,835] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.42 | bwd_microstep: 206.94 | bwd_inner_microstep: 206.93 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-01 22:36:26,314] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.77 | bwd_microstep: 273.95 | bwd_inner_microstep: 273.93 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-01 22:36:26,796] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.10 | bwd_microstep: 273.63 | bwd_inner_microstep: 273.61 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 22:36:27,275] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.90 | bwd_microstep: 273.15 | bwd_inner_microstep: 273.13 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 22:36:27,753] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.74 | bwd_microstep: 273.15 | bwd_inner_microstep: 273.13 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 22:36:28,230] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.16 | bwd_microstep: 272.89 | bwd_inner_microstep: 272.87 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 22:36:28,707] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.03 | bwd_microstep: 272.80 | bwd_inner_microstep: 272.78 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 22:36:29,275] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.17 | optimizer_step: 16.72 +[2025-05-01 22:36:29,276] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.17 | bwd_microstep: 339.94 | bwd_inner_microstep: 271.96 | bwd_allreduce_microstep: 67.94 | step_microstep: 23.90 +[2025-05-01 22:36:29,277] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2802.84 | bwd: 4147.13 | bwd_inner: 4078.37 | bwd_allreduce: 68.24 | step: 24.99 + 2%|▏ | 146/8720 [21:03<16:31:00, 6.94s/it] {'loss': 3.8787, 'grad_norm': 13.533605575561523, 'learning_rate': 5.572519083969467e-06, 'epoch': 0.17} + 2%|▏ | 146/8720 [21:03<16:31:00, 6.94s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1908 +[2025-05-01 22:36:29,762] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.80 | bwd_microstep: 275.55 | bwd_inner_microstep: 275.54 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1941 +[2025-05-01 22:36:30,262] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.84 | bwd_microstep: 288.89 | bwd_inner_microstep: 288.87 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1889 +[2025-05-01 22:36:30,742] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.33 | bwd_microstep: 274.92 | bwd_inner_microstep: 274.90 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.17 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-01 22:36:31,219] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.52 | bwd_microstep: 273.95 | bwd_inner_microstep: 273.93 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-01 22:36:31,696] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.01 | bwd_microstep: 272.81 | bwd_inner_microstep: 272.79 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-01 22:36:32,174] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.39 | bwd_microstep: 273.15 | bwd_inner_microstep: 273.13 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 330 +[2025-05-01 22:36:32,373] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 67.27 | bwd_microstep: 118.19 | bwd_inner_microstep: 117.87 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 22:36:32,850] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.42 | bwd_microstep: 272.68 | bwd_inner_microstep: 272.67 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-01 22:36:33,327] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.04 | bwd_microstep: 272.92 | bwd_inner_microstep: 272.90 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 22:36:33,803] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.27 | bwd_microstep: 272.80 | bwd_inner_microstep: 272.78 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1350 +[2025-05-01 22:36:34,165] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.23 | bwd_microstep: 206.07 | bwd_inner_microstep: 206.05 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-01 22:36:34,642] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.00 | bwd_microstep: 272.74 | bwd_inner_microstep: 272.72 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 326 +[2025-05-01 22:36:34,858] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 82.01 | bwd_microstep: 118.10 | bwd_inner_microstep: 117.77 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.22 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 22:36:35,335] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.49 | bwd_microstep: 271.36 | bwd_inner_microstep: 271.34 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1341 +[2025-05-01 22:36:35,698] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.02 | bwd_microstep: 204.42 | bwd_inner_microstep: 204.40 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 22:36:36,275] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.25 | optimizer_step: 16.76 +[2025-05-01 22:36:36,275] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.72 | bwd_microstep: 347.04 | bwd_inner_microstep: 271.86 | bwd_allreduce_microstep: 75.14 | step_microstep: 24.28 +[2025-05-01 22:36:36,276] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2701.07 | bwd: 4015.64 | bwd_inner: 3939.67 | bwd_allreduce: 75.45 | step: 25.43 + 2%|▏ | 147/8720 [21:10<16:33:40, 6.95s/it] {'loss': 2.2945, 'grad_norm': 13.149470329284668, 'learning_rate': 5.610687022900764e-06, 'epoch': 0.17} + 2%|▏ | 147/8720 [21:10<16:33:40, 6.95s/it]dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1408 +[2025-05-01 22:36:36,651] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 144.66 | bwd_microstep: 209.80 | bwd_inner_microstep: 209.77 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1910 +[2025-05-01 22:36:37,134] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.79 | bwd_microstep: 277.34 | bwd_inner_microstep: 277.32 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1385 +[2025-05-01 22:36:37,502] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 143.17 | bwd_microstep: 208.57 | bwd_inner_microstep: 208.50 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1893 +[2025-05-01 22:36:37,983] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.54 | bwd_microstep: 275.14 | bwd_inner_microstep: 275.12 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-01 22:36:38,460] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.36 | bwd_microstep: 273.45 | bwd_inner_microstep: 273.44 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1889 +[2025-05-01 22:36:38,940] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.96 | bwd_microstep: 274.71 | bwd_inner_microstep: 274.69 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1894 +[2025-05-01 22:36:39,420] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.07 | bwd_microstep: 275.01 | bwd_inner_microstep: 274.99 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-01 22:36:39,899] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.73 | bwd_microstep: 274.08 | bwd_inner_microstep: 274.06 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-01 22:36:40,378] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.96 | bwd_microstep: 273.54 | bwd_inner_microstep: 273.52 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-01 22:36:40,856] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.83 | bwd_microstep: 273.28 | bwd_inner_microstep: 273.26 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-01 22:36:41,334] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.04 | bwd_microstep: 272.79 | bwd_inner_microstep: 272.77 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-01 22:36:41,812] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.23 | bwd_microstep: 273.05 | bwd_inner_microstep: 273.04 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-01 22:36:42,297] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.30 | bwd_microstep: 272.69 | bwd_inner_microstep: 272.67 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.15 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 22:36:42,773] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.29 | bwd_microstep: 272.50 | bwd_inner_microstep: 272.49 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 22:36:43,250] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.18 | bwd_microstep: 272.32 | bwd_inner_microstep: 272.30 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 22:36:43,819] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.47 | optimizer_step: 17.28 +[2025-05-01 22:36:43,820] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.09 | bwd_microstep: 338.77 | bwd_inner_microstep: 272.05 | bwd_allreduce_microstep: 66.67 | step_microstep: 24.86 +[2025-05-01 22:36:43,821] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2932.92 | bwd: 4317.09 | bwd_inner: 4250.01 | bwd_allreduce: 66.77 | step: 25.89 + 2%|▏ | 148/8720 [21:17<16:58:51, 7.13s/it] {'loss': 2.2331, 'grad_norm': 9.48447036743164, 'learning_rate': 5.648854961832062e-06, 'epoch': 0.17} + 2%|▏ | 148/8720 [21:17<16:58:51, 7.13s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2141 +[2025-05-01 22:36:44,361] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 204.65 | bwd_microstep: 314.34 | bwd_inner_microstep: 314.32 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.21 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1967 +[2025-05-01 22:36:44,867] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 198.05 | bwd_microstep: 291.32 | bwd_inner_microstep: 291.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1954 +[2025-05-01 22:36:45,370] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 196.62 | bwd_microstep: 289.95 | bwd_inner_microstep: 289.93 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1914 +[2025-05-01 22:36:45,853] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.71 | bwd_microstep: 276.39 | bwd_inner_microstep: 276.37 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1909 +[2025-05-01 22:36:46,338] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.49 | bwd_microstep: 276.48 | bwd_inner_microstep: 276.46 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1899 +[2025-05-01 22:36:46,820] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.18 | bwd_microstep: 275.45 | bwd_inner_microstep: 275.43 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-01 22:36:47,305] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.18 | bwd_microstep: 273.95 | bwd_inner_microstep: 273.93 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-01 22:36:47,787] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.36 | bwd_microstep: 274.58 | bwd_inner_microstep: 274.56 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-01 22:36:48,266] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.19 | bwd_microstep: 273.16 | bwd_inner_microstep: 273.14 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-01 22:36:48,744] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.09 | bwd_microstep: 272.92 | bwd_inner_microstep: 272.90 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 22:36:49,221] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.46 | bwd_microstep: 272.84 | bwd_inner_microstep: 272.82 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 22:36:49,698] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.33 | bwd_microstep: 272.20 | bwd_inner_microstep: 272.18 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-01 22:36:50,175] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.27 | bwd_microstep: 272.85 | bwd_inner_microstep: 272.83 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 22:36:50,651] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.34 | bwd_microstep: 272.35 | bwd_inner_microstep: 272.33 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 22:36:51,129] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.92 | bwd_microstep: 272.46 | bwd_inner_microstep: 272.44 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 22:36:51,697] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.25 | optimizer_step: 16.82 +[2025-05-01 22:36:51,697] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.66 | bwd_microstep: 338.89 | bwd_inner_microstep: 272.11 | bwd_allreduce_microstep: 66.73 | step_microstep: 24.17 +[2025-05-01 22:36:51,698] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 3057.23 | bwd: 4520.14 | bwd_inner: 4453.09 | bwd_allreduce: 66.82 | step: 25.19 + 2%|▏ | 149/8720 [21:25<17:30:42, 7.36s/it] {'loss': 2.3451, 'grad_norm': 8.622315406799316, 'learning_rate': 5.687022900763359e-06, 'epoch': 0.17} + 2%|▏ | 149/8720 [21:25<17:30:42, 7.36s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 367 +[2025-05-01 22:36:51,912] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 70.75 | bwd_microstep: 123.58 | bwd_inner_microstep: 123.44 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-01 22:36:52,391] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.25 | bwd_microstep: 274.36 | bwd_inner_microstep: 274.35 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.20 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 334 +[2025-05-01 22:36:52,615] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 84.58 | bwd_microstep: 125.16 | bwd_inner_microstep: 124.85 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-01 22:36:53,094] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.57 | bwd_microstep: 272.58 | bwd_inner_microstep: 272.56 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 22:36:53,571] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.87 | bwd_microstep: 272.71 | bwd_inner_microstep: 272.69 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 22:36:54,049] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.28 | bwd_microstep: 272.36 | bwd_inner_microstep: 272.35 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 326 +[2025-05-01 22:36:54,261] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 79.83 | bwd_microstep: 117.84 | bwd_inner_microstep: 117.62 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.09 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 836 +[2025-05-01 22:36:54,492] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 91.14 | bwd_microstep: 126.78 | bwd_inner_microstep: 126.54 | bwd_allreduce_microstep: 0.16 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 22:36:54,969] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.61 | bwd_microstep: 272.32 | bwd_inner_microstep: 272.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 22:36:55,446] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.15 | bwd_microstep: 272.73 | bwd_inner_microstep: 272.71 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 22:36:55,924] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.20 | bwd_microstep: 272.41 | bwd_inner_microstep: 272.39 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 317 +[2025-05-01 22:36:56,141] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 80.49 | bwd_microstep: 120.83 | bwd_inner_microstep: 120.58 | bwd_allreduce_microstep: 0.09 | step_microstep: 0.09 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1341 +[2025-05-01 22:36:56,501] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 139.98 | bwd_microstep: 204.65 | bwd_inner_microstep: 204.51 | bwd_allreduce_microstep: 0.04 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-01 22:36:56,978] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.11 | bwd_microstep: 271.14 | bwd_inner_microstep: 271.13 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 22:36:57,454] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.59 | bwd_microstep: 271.26 | bwd_inner_microstep: 271.24 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 22:36:58,021] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.04 | optimizer_gradients: 2.27 | optimizer_step: 16.91 +[2025-05-01 22:36:58,021] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.32 | bwd_microstep: 337.97 | bwd_inner_microstep: 271.47 | bwd_allreduce_microstep: 66.45 | step_microstep: 23.98 +[2025-05-01 22:36:58,023] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2431.42 | bwd: 3608.78 | bwd_inner: 3540.94 | bwd_allreduce: 67.06 | step: 25.34 + 2%|▏ | 150/8720 [21:31<16:46:22, 7.05s/it] {'loss': 2.1822, 'grad_norm': 13.52921199798584, 'learning_rate': 5.725190839694656e-06, 'epoch': 0.17} + 2%|▏ | 150/8720 [21:31<16:46:22, 7.05s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1967 +[2025-05-01 22:36:58,530] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 197.05 | bwd_microstep: 290.42 | bwd_inner_microstep: 290.41 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.17 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1926 +[2025-05-01 22:36:59,030] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.56 | bwd_microstep: 287.51 | bwd_inner_microstep: 287.49 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1928 +[2025-05-01 22:36:59,529] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.39 | bwd_microstep: 287.63 | bwd_inner_microstep: 287.61 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1903 +[2025-05-01 22:37:00,013] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.25 | bwd_microstep: 275.97 | bwd_inner_microstep: 275.95 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1894 +[2025-05-01 22:37:00,496] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.53 | bwd_microstep: 274.81 | bwd_inner_microstep: 274.79 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-01 22:37:00,976] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.86 | bwd_microstep: 274.27 | bwd_inner_microstep: 274.26 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 856 +[2025-05-01 22:37:01,222] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.09 | bwd_microstep: 133.56 | bwd_inner_microstep: 133.43 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1883 +[2025-05-01 22:37:01,705] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.49 | bwd_microstep: 274.95 | bwd_inner_microstep: 274.93 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 334 +[2025-05-01 22:37:01,946] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 97.65 | bwd_microstep: 124.01 | bwd_inner_microstep: 123.74 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-01 22:37:02,429] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.06 | bwd_microstep: 272.79 | bwd_inner_microstep: 272.77 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 22:37:02,908] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.71 | bwd_microstep: 272.78 | bwd_inner_microstep: 272.76 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1354 +[2025-05-01 22:37:03,275] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.31 | bwd_microstep: 206.48 | bwd_inner_microstep: 206.32 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 22:37:03,760] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.57 | bwd_microstep: 272.66 | bwd_inner_microstep: 272.65 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 832 +[2025-05-01 22:37:04,022] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 105.85 | bwd_microstep: 132.34 | bwd_inner_microstep: 132.16 | bwd_allreduce_microstep: 0.08 | step_microstep: 0.12 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 828 +[2025-05-01 22:37:04,281] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 105.59 | bwd_microstep: 129.44 | bwd_inner_microstep: 129.23 | bwd_allreduce_microstep: 0.10 | step_microstep: 0.13 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 22:37:04,879] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.26 | optimizer_step: 17.43 +[2025-05-01 22:37:04,879] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.82 | bwd_microstep: 358.86 | bwd_inner_microstep: 271.52 | bwd_allreduce_microstep: 87.28 | step_microstep: 25.54 +[2025-05-01 22:37:04,881] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2645.38 | bwd: 3868.59 | bwd_inner: 3780.10 | bwd_allreduce: 87.75 | step: 26.88 + 2%|▏ | 151/8720 [21:38<16:38:19, 6.99s/it] {'loss': 1.7958, 'grad_norm': 8.05593204498291, 'learning_rate': 5.763358778625955e-06, 'epoch': 0.17} + 2%|▏ | 151/8720 [21:38<16:38:19, 6.99s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1997 +[2025-05-01 22:37:05,397] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 198.38 | bwd_microstep: 293.88 | bwd_inner_microstep: 293.87 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 884 +[2025-05-01 22:37:05,646] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.93 | bwd_microstep: 135.81 | bwd_inner_microstep: 135.75 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.10 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 855 +[2025-05-01 22:37:05,893] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 96.89 | bwd_microstep: 133.28 | bwd_inner_microstep: 133.22 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-01 22:37:06,378] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.96 | bwd_microstep: 273.73 | bwd_inner_microstep: 273.71 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-01 22:37:06,859] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.19 | bwd_microstep: 274.00 | bwd_inner_microstep: 273.98 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-01 22:37:07,340] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.23 | bwd_microstep: 273.66 | bwd_inner_microstep: 273.64 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-01 22:37:07,819] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.31 | bwd_microstep: 274.31 | bwd_inner_microstep: 274.29 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-01 22:37:08,297] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.03 | bwd_microstep: 273.48 | bwd_inner_microstep: 273.47 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-01 22:37:08,774] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.79 | bwd_microstep: 273.15 | bwd_inner_microstep: 273.13 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 325 +[2025-05-01 22:37:08,974] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 67.56 | bwd_microstep: 118.95 | bwd_inner_microstep: 118.82 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-01 22:37:09,449] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.58 | bwd_microstep: 272.77 | bwd_inner_microstep: 272.75 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-01 22:37:09,927] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.47 | bwd_microstep: 272.78 | bwd_inner_microstep: 272.76 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-01 22:37:10,405] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.26 | bwd_microstep: 273.12 | bwd_inner_microstep: 273.10 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 22:37:10,881] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.96 | bwd_microstep: 271.43 | bwd_inner_microstep: 271.41 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-01 22:37:11,358] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.05 | bwd_microstep: 271.41 | bwd_inner_microstep: 271.39 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1381 +[2025-05-01 22:37:11,815] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.23 | optimizer_step: 16.66 +[2025-05-01 22:37:11,815] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 143.61 | bwd_microstep: 275.23 | bwd_inner_microstep: 209.08 | bwd_allreduce_microstep: 66.07 | step_microstep: 23.84 +[2025-05-01 22:37:11,817] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2679.92 | bwd: 3961.05 | bwd_inner: 3894.42 | bwd_allreduce: 66.24 | step: 24.85 + 2%|▏ | 152/8720 [21:45<16:35:46, 6.97s/it] {'loss': 3.0813, 'grad_norm': 8.504134178161621, 'learning_rate': 5.801526717557252e-06, 'epoch': 0.17} + 2%|▏ | 152/8720 [21:45<16:35:46, 6.97s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1907 +[2025-05-01 22:37:12,302] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.23 | bwd_microstep: 275.66 | bwd_inner_microstep: 275.64 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1886 +[2025-05-01 22:37:12,783] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.12 | bwd_microstep: 274.79 | bwd_inner_microstep: 274.77 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-01 22:37:13,262] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.72 | bwd_microstep: 273.93 | bwd_inner_microstep: 273.91 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-01 22:37:13,741] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.67 | bwd_microstep: 273.46 | bwd_inner_microstep: 273.44 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 847 +[2025-05-01 22:37:13,982] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.19 | bwd_microstep: 132.91 | bwd_inner_microstep: 132.76 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.09 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1357 +[2025-05-01 22:37:14,345] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.51 | bwd_microstep: 206.56 | bwd_inner_microstep: 206.55 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-01 22:37:14,822] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.93 | bwd_microstep: 272.99 | bwd_inner_microstep: 272.97 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-01 22:37:15,301] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.35 | bwd_microstep: 272.83 | bwd_inner_microstep: 272.81 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 22:37:15,778] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.43 | bwd_microstep: 272.70 | bwd_inner_microstep: 272.68 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 323 +[2025-05-01 22:37:15,983] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 75.18 | bwd_microstep: 115.30 | bwd_inner_microstep: 115.17 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 22:37:16,459] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.22 | bwd_microstep: 271.73 | bwd_inner_microstep: 271.71 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-01 22:37:16,939] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.03 | bwd_microstep: 271.43 | bwd_inner_microstep: 271.41 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-01 22:37:17,419] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.07 | bwd_microstep: 271.38 | bwd_inner_microstep: 271.36 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 22:37:17,900] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.83 | bwd_microstep: 271.49 | bwd_inner_microstep: 271.48 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1849 +[2025-05-01 22:37:18,379] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.43 | bwd_microstep: 271.34 | bwd_inner_microstep: 271.32 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2098 +[2025-05-01 22:37:19,008] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.18 | optimizer_step: 16.55 +[2025-05-01 22:37:19,009] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 205.60 | bwd_microstep: 382.29 | bwd_inner_microstep: 306.54 | bwd_allreduce_microstep: 75.69 | step_microstep: 24.31 +[2025-05-01 22:37:19,010] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2787.21 | bwd: 4110.82 | bwd_inner: 4034.56 | bwd_allreduce: 75.88 | step: 25.35 + 2%|▏ | 153/8720 [21:52<16:45:10, 7.04s/it] {'loss': 2.163, 'grad_norm': 10.962547302246094, 'learning_rate': 5.83969465648855e-06, 'epoch': 0.18} + 2%|▏ | 153/8720 [21:52<16:45:10, 7.04s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1887 +[2025-05-01 22:37:19,497] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.94 | bwd_microstep: 274.24 | bwd_inner_microstep: 274.23 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-01 22:37:19,977] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.75 | bwd_microstep: 273.55 | bwd_inner_microstep: 273.53 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 338 +[2025-05-01 22:37:20,233] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 69.14 | bwd_microstep: 171.99 | bwd_inner_microstep: 171.61 | bwd_allreduce_microstep: 0.23 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-01 22:37:20,722] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.63 | bwd_microstep: 274.04 | bwd_inner_microstep: 274.02 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1354 +[2025-05-01 22:37:21,118] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 149.11 | bwd_microstep: 232.08 | bwd_inner_microstep: 232.06 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.17 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 22:37:21,648] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 212.96 | bwd_microstep: 300.50 | bwd_inner_microstep: 300.48 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1094 +[2025-05-01 22:37:21,950] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 119.36 | bwd_microstep: 167.65 | bwd_inner_microstep: 167.45 | bwd_allreduce_microstep: 0.10 | step_microstep: 0.09 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 321 +[2025-05-01 22:37:22,166] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 85.58 | bwd_microstep: 115.48 | bwd_inner_microstep: 115.21 | bwd_allreduce_microstep: 0.10 | step_microstep: 0.13 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1344 +[2025-05-01 22:37:22,538] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 142.12 | bwd_microstep: 213.17 | bwd_inner_microstep: 212.90 | bwd_allreduce_microstep: 0.14 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 22:37:23,025] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 194.43 | bwd_microstep: 274.04 | bwd_inner_microstep: 274.00 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 22:37:23,528] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.88 | bwd_microstep: 292.96 | bwd_inner_microstep: 292.94 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 22:37:24,510] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 408.10 | bwd_microstep: 551.52 | bwd_inner_microstep: 551.50 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.53 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 317 +[2025-05-01 22:37:24,750] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 88.70 | bwd_microstep: 119.86 | bwd_inner_microstep: 119.55 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 22:37:25,228] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.69 | bwd_microstep: 273.01 | bwd_inner_microstep: 272.99 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 22:37:26,225] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 423.36 | bwd_microstep: 546.27 | bwd_inner_microstep: 546.25 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 829 +[2025-05-01 22:37:26,564] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.91 | optimizer_step: 17.02 +[2025-05-01 22:37:26,565] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.85 | bwd_microstep: 203.79 | bwd_inner_microstep: 133.61 | bwd_allreduce_microstep: 70.07 | step_microstep: 25.25 +[2025-05-01 22:37:26,566] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2937.35 | bwd: 4284.25 | bwd_inner: 4212.51 | bwd_allreduce: 70.84 | step: 29.26 + 2%|▏ | 154/8720 [22:00<17:07:05, 7.19s/it] {'loss': 2.3793, 'grad_norm': 11.44915771484375, 'learning_rate': 5.877862595419848e-06, 'epoch': 0.18} + 2%|▏ | 154/8720 [22:00<17:07:05, 7.19s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 377 +[2025-05-01 22:37:26,849] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 108.64 | bwd_microstep: 151.78 | bwd_inner_microstep: 151.76 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.30 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-01 22:37:27,745] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 430.95 | bwd_microstep: 432.90 | bwd_inner_microstep: 432.88 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-01 22:37:28,524] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.84 | bwd_microstep: 571.59 | bwd_inner_microstep: 571.57 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.31 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 328 +[2025-05-01 22:37:28,804] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 100.36 | bwd_microstep: 149.12 | bwd_inner_microstep: 149.10 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-01 22:37:29,446] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 203.82 | bwd_microstep: 405.36 | bwd_inner_microstep: 405.34 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-01 22:37:30,259] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 422.08 | bwd_microstep: 358.24 | bwd_inner_microstep: 358.22 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.20 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 840 +[2025-05-01 22:37:30,580] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.34 | bwd_microstep: 207.15 | bwd_inner_microstep: 207.13 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-01 22:37:31,496] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 423.98 | bwd_microstep: 461.07 | bwd_inner_microstep: 461.05 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-01 22:37:32,248] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.77 | bwd_microstep: 539.05 | bwd_inner_microstep: 539.03 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 22:37:32,933] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 375.11 | bwd_microstep: 276.93 | bwd_inner_microstep: 276.91 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-01 22:37:33,901] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 327.44 | bwd_microstep: 621.12 | bwd_inner_microstep: 621.11 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.45 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 22:37:34,531] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 271.68 | bwd_microstep: 325.19 | bwd_inner_microstep: 325.17 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 22:37:35,475] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 424.47 | bwd_microstep: 487.47 | bwd_inner_microstep: 487.45 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 22:37:36,205] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.27 | bwd_microstep: 518.83 | bwd_inner_microstep: 518.80 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 22:37:36,956] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 433.83 | bwd_microstep: 287.20 | bwd_inner_microstep: 287.19 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 365 +[2025-05-01 22:37:37,783] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.39 | optimizer_step: 17.19 +[2025-05-01 22:37:37,784] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 78.80 | bwd_microstep: 708.80 | bwd_inner_microstep: 150.52 | bwd_allreduce_microstep: 558.23 | step_microstep: 25.01 +[2025-05-01 22:37:37,785] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4267.28 | bwd: 6501.82 | bwd_inner: 5943.26 | bwd_allreduce: 558.31 | step: 46.72 + 2%|▏ | 155/8720 [22:11<19:59:19, 8.40s/it] {'loss': 2.4595, 'grad_norm': 12.711187362670898, 'learning_rate': 5.916030534351146e-06, 'epoch': 0.18} + 2%|▏ | 155/8720 [22:11<19:59:19, 8.40s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 451 +[2025-05-01 22:37:37,997] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 70.62 | bwd_microstep: 123.36 | bwd_inner_microstep: 122.97 | bwd_allreduce_microstep: 0.15 | step_microstep: 0.15 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1896 +[2025-05-01 22:37:39,042] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 390.80 | bwd_microstep: 633.97 | bwd_inner_microstep: 633.95 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1886 +[2025-05-01 22:37:39,637] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 203.64 | bwd_microstep: 359.66 | bwd_inner_microstep: 359.64 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-01 22:37:40,549] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 423.66 | bwd_microstep: 456.60 | bwd_inner_microstep: 456.58 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 839 +[2025-05-01 22:37:40,802] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 92.14 | bwd_microstep: 144.65 | bwd_inner_microstep: 144.63 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 328 +[2025-05-01 22:37:41,060] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 103.31 | bwd_microstep: 122.18 | bwd_inner_microstep: 122.16 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-01 22:37:41,704] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 338.94 | bwd_microstep: 275.14 | bwd_inner_microstep: 275.13 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 22:37:42,669] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 336.53 | bwd_microstep: 612.02 | bwd_inner_microstep: 612.00 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.91 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 22:37:43,154] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 193.99 | bwd_microstep: 274.50 | bwd_inner_microstep: 274.49 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 22:37:44,091] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 421.81 | bwd_microstep: 489.57 | bwd_inner_microstep: 489.55 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 22:37:44,830] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.58 | bwd_microstep: 530.46 | bwd_inner_microstep: 530.45 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 22:37:45,566] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 428.33 | bwd_microstep: 276.02 | bwd_inner_microstep: 276.00 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 22:37:46,440] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 236.89 | bwd_microstep: 619.39 | bwd_inner_microstep: 619.37 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.51 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 22:37:47,009] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 215.35 | bwd_microstep: 319.30 | bwd_inner_microstep: 319.28 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 22:37:48,017] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 423.80 | bwd_microstep: 552.49 | bwd_inner_microstep: 552.47 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 22:37:49,180] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.14 | optimizer_step: 16.57 +[2025-05-01 22:37:49,181] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.32 | bwd_microstep: 931.60 | bwd_inner_microstep: 482.96 | bwd_allreduce_microstep: 448.60 | step_microstep: 24.05 +[2025-05-01 22:37:49,182] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4259.58 | bwd: 6720.96 | bwd_inner: 6271.71 | bwd_allreduce: 448.82 | step: 41.97 + 2%|▏ | 156/8720 [22:22<22:07:26, 9.30s/it] {'loss': 2.1166, 'grad_norm': 11.490949630737305, 'learning_rate': 5.9541984732824435e-06, 'epoch': 0.18} + 2%|▏ | 156/8720 [22:22<22:07:26, 9.30s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 353 +[2025-05-01 22:37:49,398] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 69.60 | bwd_microstep: 127.76 | bwd_inner_microstep: 127.63 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-01 22:37:50,432] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 390.96 | bwd_microstep: 625.85 | bwd_inner_microstep: 625.83 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-01 22:37:50,982] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 204.94 | bwd_microstep: 311.05 | bwd_inner_microstep: 311.03 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-01 22:37:51,774] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 426.06 | bwd_microstep: 333.76 | bwd_inner_microstep: 333.74 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 330 +[2025-05-01 22:37:51,995] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 80.39 | bwd_microstep: 124.93 | bwd_inner_microstep: 124.91 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 841 +[2025-05-01 22:37:52,545] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 211.89 | bwd_microstep: 305.93 | bwd_inner_microstep: 305.91 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-01 22:37:53,153] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 299.77 | bwd_microstep: 275.46 | bwd_inner_microstep: 275.44 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 22:37:54,166] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 402.24 | bwd_microstep: 594.35 | bwd_inner_microstep: 594.33 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 327 +[2025-05-01 22:37:54,410] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 106.90 | bwd_microstep: 119.85 | bwd_inner_microstep: 119.72 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 22:37:55,339] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 290.15 | bwd_microstep: 620.24 | bwd_inner_microstep: 620.22 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.48 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 831 +[2025-05-01 22:37:55,640] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 128.78 | bwd_microstep: 131.83 | bwd_inner_microstep: 131.81 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 22:37:56,444] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.69 | bwd_microstep: 596.74 | bwd_inner_microstep: 596.72 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.49 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 316 +[2025-05-01 22:37:56,708] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 97.10 | bwd_microstep: 135.09 | bwd_inner_microstep: 135.07 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 827 +[2025-05-01 22:37:57,023] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 154.69 | bwd_microstep: 132.71 | bwd_inner_microstep: 132.69 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 314 +[2025-05-01 22:37:57,243] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 72.00 | bwd_microstep: 131.64 | bwd_inner_microstep: 131.62 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.33 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-01 22:37:58,342] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 5.08 | optimizer_step: 24.16 +[2025-05-01 22:37:58,343] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 427.98 | bwd_microstep: 603.26 | bwd_inner_microstep: 511.47 | bwd_allreduce_microstep: 91.74 | step_microstep: 34.53 +[2025-05-01 22:37:58,344] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 3551.94 | bwd: 5170.47 | bwd_inner: 5078.20 | bwd_allreduce: 91.92 | step: 54.09 + 2%|▏ | 157/8720 [22:32<22:01:22, 9.26s/it] {'loss': 2.0067, 'grad_norm': 7.949142932891846, 'learning_rate': 5.992366412213741e-06, 'epoch': 0.18} + 2%|▏ | 157/8720 [22:32<22:01:22, 9.26s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1904 +[2025-05-01 22:37:59,238] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 236.62 | bwd_microstep: 635.78 | bwd_inner_microstep: 635.76 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1888 +[2025-05-01 22:37:59,853] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 234.63 | bwd_microstep: 338.79 | bwd_inner_microstep: 338.77 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1889 +[2025-05-01 22:38:00,794] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 428.38 | bwd_microstep: 474.40 | bwd_inner_microstep: 474.38 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1883 +[2025-05-01 22:38:01,510] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.40 | bwd_microstep: 506.41 | bwd_inner_microstep: 506.39 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.51 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 859 +[2025-05-01 22:38:02,085] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 226.60 | bwd_microstep: 317.60 | bwd_inner_microstep: 317.58 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.93 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1889 +[2025-05-01 22:38:02,740] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 199.77 | bwd_microstep: 432.21 | bwd_inner_microstep: 432.19 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 858 +[2025-05-01 22:38:03,292] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 225.79 | bwd_microstep: 295.11 | bwd_inner_microstep: 295.09 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.24 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-01 22:38:03,878] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.36 | bwd_microstep: 375.14 | bwd_inner_microstep: 375.12 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 845 +[2025-05-01 22:38:04,435] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 208.04 | bwd_microstep: 316.54 | bwd_inner_microstep: 316.52 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.51 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-01 22:38:05,056] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 315.62 | bwd_microstep: 275.88 | bwd_inner_microstep: 275.86 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-01 22:38:06,089] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 382.83 | bwd_microstep: 627.04 | bwd_inner_microstep: 627.02 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 22:38:06,750] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 208.41 | bwd_microstep: 418.81 | bwd_inner_microstep: 418.78 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1089 +[2025-05-01 22:38:07,307] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 264.90 | bwd_microstep: 271.29 | bwd_inner_microstep: 271.25 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 22:38:08,019] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.76 | bwd_microstep: 500.54 | bwd_inner_microstep: 500.52 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 22:38:08,684] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 357.70 | bwd_microstep: 274.33 | bwd_inner_microstep: 274.32 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.17 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1935 +[2025-05-01 22:38:09,894] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.07 | optimizer_gradients: 3.32 | optimizer_step: 19.14 +[2025-05-01 22:38:09,895] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 407.41 | bwd_microstep: 754.88 | bwd_inner_microstep: 617.28 | bwd_allreduce_microstep: 137.55 | step_microstep: 28.77 +[2025-05-01 22:38:09,896] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4267.11 | bwd: 6814.78 | bwd_inner: 6676.85 | bwd_allreduce: 137.64 | step: 51.81 + 2%|▏ | 158/8720 [22:43<23:39:33, 9.95s/it] {'loss': 2.3421, 'grad_norm': 12.576521873474121, 'learning_rate': 6.030534351145039e-06, 'epoch': 0.18} + 2%|▏ | 158/8720 [22:43<23:39:33, 9.95s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1949 +[2025-05-01 22:38:10,808] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 224.22 | bwd_microstep: 661.06 | bwd_inner_microstep: 661.04 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 865 +[2025-05-01 22:38:11,168] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 193.05 | bwd_microstep: 136.47 | bwd_inner_microstep: 136.32 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.11 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1355 +[2025-05-01 22:38:11,533] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.10 | bwd_microstep: 207.41 | bwd_inner_microstep: 207.28 | bwd_allreduce_microstep: 0.04 | step_microstep: 0.19 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 334 +[2025-05-01 22:38:11,808] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 104.50 | bwd_microstep: 141.54 | bwd_inner_microstep: 141.52 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-01 22:38:12,626] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 440.68 | bwd_microstep: 348.78 | bwd_inner_microstep: 348.77 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-01 22:38:13,509] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 242.35 | bwd_microstep: 622.38 | bwd_inner_microstep: 622.36 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.31 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 326 +[2025-05-01 22:38:13,755] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 100.17 | bwd_microstep: 115.92 | bwd_inner_microstep: 115.78 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 22:38:14,395] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.91 | bwd_microstep: 428.46 | bwd_inner_microstep: 428.44 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 22:38:15,271] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 245.05 | bwd_microstep: 595.18 | bwd_inner_microstep: 595.16 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 22:38:15,896] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 203.15 | bwd_microstep: 398.48 | bwd_inner_microstep: 398.46 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 834 +[2025-05-01 22:38:16,427] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 200.10 | bwd_microstep: 298.32 | bwd_inner_microstep: 298.31 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 22:38:17,013] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 201.37 | bwd_microstep: 351.32 | bwd_inner_microstep: 351.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-01 22:38:17,880] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 428.17 | bwd_microstep: 408.74 | bwd_inner_microstep: 408.73 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 22:38:18,690] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.26 | bwd_microstep: 602.50 | bwd_inner_microstep: 602.48 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 22:38:19,355] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 356.70 | bwd_microstep: 274.56 | bwd_inner_microstep: 274.54 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1849 +[2025-05-01 22:38:20,547] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.97 | optimizer_step: 17.24 +[2025-05-01 22:38:20,547] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 394.98 | bwd_microstep: 754.18 | bwd_inner_microstep: 596.16 | bwd_allreduce_microstep: 157.97 | step_microstep: 25.60 +[2025-05-01 22:38:20,548] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 3855.63 | bwd: 6345.39 | bwd_inner: 6186.72 | bwd_allreduce: 158.23 | step: 47.25 + 2%|▏ | 159/8720 [22:54<24:09:34, 10.16s/it] {'loss': 1.9453, 'grad_norm': 11.26313591003418, 'learning_rate': 6.068702290076336e-06, 'epoch': 0.18} + 2%|▏ | 159/8720 [22:54<24:09:34, 10.16s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1988 +[2025-05-01 22:38:21,425] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 199.41 | bwd_microstep: 649.25 | bwd_inner_microstep: 649.23 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.50 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1914 +[2025-05-01 22:38:22,127] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 389.95 | bwd_microstep: 280.72 | bwd_inner_microstep: 280.71 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-01 22:38:23,039] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 353.78 | bwd_microstep: 541.58 | bwd_inner_microstep: 541.56 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-01 22:38:23,738] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 191.76 | bwd_microstep: 486.85 | bwd_inner_microstep: 486.83 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-01 22:38:24,521] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 438.87 | bwd_microstep: 314.07 | bwd_inner_microstep: 314.05 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1116 +[2025-05-01 22:38:24,949] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 116.83 | bwd_microstep: 293.52 | bwd_inner_microstep: 293.50 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-01 22:38:25,878] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 426.38 | bwd_microstep: 470.62 | bwd_inner_microstep: 470.60 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 332 +[2025-05-01 22:38:26,090] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 76.30 | bwd_microstep: 120.86 | bwd_inner_microstep: 120.67 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.09 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 847 +[2025-05-01 22:38:26,545] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 138.44 | bwd_microstep: 299.42 | bwd_inner_microstep: 299.40 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 22:38:27,273] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 416.43 | bwd_microstep: 276.31 | bwd_inner_microstep: 276.29 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 22:38:28,231] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 317.46 | bwd_microstep: 620.25 | bwd_inner_microstep: 620.23 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.48 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 835 +[2025-05-01 22:38:28,508] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 118.20 | bwd_microstep: 128.26 | bwd_inner_microstep: 128.01 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 22:38:29,351] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 202.23 | bwd_microstep: 621.85 | bwd_inner_microstep: 621.83 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 22:38:29,979] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 319.51 | bwd_microstep: 274.43 | bwd_inner_microstep: 274.41 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 22:38:30,946] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 376.75 | bwd_microstep: 571.73 | bwd_inner_microstep: 571.71 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1963 +[2025-05-01 22:38:32,084] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 3.17 | optimizer_step: 17.15 +[2025-05-01 22:38:32,085] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 199.00 | bwd_microstep: 895.69 | bwd_inner_microstep: 447.37 | bwd_allreduce_microstep: 448.27 | step_microstep: 25.60 +[2025-05-01 22:38:32,086] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4281.11 | bwd: 6845.48 | bwd_inner: 6396.59 | bwd_allreduce: 448.47 | step: 40.65 + 2%|▏ | 160/8720 [23:05<25:08:12, 10.57s/it] {'loss': 1.7477, 'grad_norm': 11.631389617919922, 'learning_rate': 6.1068702290076346e-06, 'epoch': 0.18} + 2%|▏ | 160/8720 [23:05<25:08:12, 10.57s/it]dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1443 +[2025-05-01 22:38:32,661] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 147.15 | bwd_microstep: 406.53 | bwd_inner_microstep: 406.51 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-01 22:38:33,465] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 439.77 | bwd_microstep: 341.74 | bwd_inner_microstep: 341.73 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 335 +[2025-05-01 22:38:33,699] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 81.26 | bwd_microstep: 131.91 | bwd_inner_microstep: 131.89 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.55 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 849 +[2025-05-01 22:38:34,262] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 228.03 | bwd_microstep: 300.78 | bwd_inner_microstep: 300.76 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 322 +[2025-05-01 22:38:34,536] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 101.62 | bwd_microstep: 140.69 | bwd_inner_microstep: 140.68 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 323 +[2025-05-01 22:38:34,757] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 73.31 | bwd_microstep: 121.05 | bwd_inner_microstep: 120.92 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 22:38:35,559] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.67 | bwd_microstep: 591.97 | bwd_inner_microstep: 591.95 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.53 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 326 +[2025-05-01 22:38:35,838] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 101.18 | bwd_microstep: 143.58 | bwd_inner_microstep: 143.56 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 22:38:36,389] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 244.19 | bwd_microstep: 274.44 | bwd_inner_microstep: 274.42 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 323 +[2025-05-01 22:38:36,647] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 101.99 | bwd_microstep: 139.67 | bwd_inner_microstep: 139.65 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 22:38:37,558] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 421.92 | bwd_microstep: 458.43 | bwd_inner_microstep: 458.41 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 22:38:38,315] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.80 | bwd_microstep: 549.25 | bwd_inner_microstep: 549.23 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.53 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 22:38:38,929] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 306.82 | bwd_microstep: 273.48 | bwd_inner_microstep: 273.47 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 22:38:39,965] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 389.41 | bwd_microstep: 623.01 | bwd_inner_microstep: 622.99 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-01 22:38:40,512] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 207.87 | bwd_microstep: 306.51 | bwd_inner_microstep: 306.49 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2114 +[2025-05-01 22:38:41,713] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.30 | optimizer_step: 17.07 +[2025-05-01 22:38:41,714] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 455.73 | bwd_microstep: 689.52 | bwd_inner_microstep: 591.45 | bwd_allreduce_microstep: 97.96 | step_microstep: 24.60 +[2025-05-01 22:38:41,715] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 3680.64 | bwd: 5492.58 | bwd_inner: 5394.15 | bwd_allreduce: 98.06 | step: 48.94 + 2%|▏ | 161/8720 [23:15<24:27:49, 10.29s/it] {'loss': 1.788, 'grad_norm': 9.975839614868164, 'learning_rate': 6.1450381679389315e-06, 'epoch': 0.18} + 2%|▏ | 161/8720 [23:15<24:27:49, 10.29s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1895 +[2025-05-01 22:38:42,496] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.09 | bwd_microstep: 564.22 | bwd_inner_microstep: 564.20 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.54 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1892 +[2025-05-01 22:38:43,271] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 447.95 | bwd_microstep: 296.30 | bwd_inner_microstep: 296.29 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-01 22:38:44,158] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 240.53 | bwd_microstep: 628.60 | bwd_inner_microstep: 628.58 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.47 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-01 22:38:44,733] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 238.86 | bwd_microstep: 301.99 | bwd_inner_microstep: 301.97 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.28 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-01 22:38:45,768] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 423.09 | bwd_microstep: 579.81 | bwd_inner_microstep: 579.79 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-01 22:38:46,394] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 191.14 | bwd_microstep: 414.96 | bwd_inner_microstep: 414.94 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-01 22:38:47,201] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 425.10 | bwd_microstep: 348.32 | bwd_inner_microstep: 348.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.22 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-01 22:38:48,069] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 222.07 | bwd_microstep: 626.92 | bwd_inner_microstep: 626.90 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.53 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-01 22:38:48,743] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 367.49 | bwd_microstep: 276.34 | bwd_inner_microstep: 276.33 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 22:38:49,778] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 385.50 | bwd_microstep: 628.59 | bwd_inner_microstep: 628.57 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 22:38:50,386] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 206.39 | bwd_microstep: 367.73 | bwd_inner_microstep: 367.71 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 325 +[2025-05-01 22:38:50,642] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 101.64 | bwd_microstep: 122.57 | bwd_inner_microstep: 122.55 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 320 +[2025-05-01 22:38:50,902] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 96.42 | bwd_microstep: 133.50 | bwd_inner_microstep: 133.48 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 22:38:51,484] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 257.55 | bwd_microstep: 292.77 | bwd_inner_microstep: 292.75 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-01 22:38:52,464] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 430.78 | bwd_microstep: 516.50 | bwd_inner_microstep: 516.48 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1849 +[2025-05-01 22:38:53,684] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.43 | optimizer_step: 17.13 +[2025-05-01 22:38:53,684] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.20 | bwd_microstep: 988.34 | bwd_inner_microstep: 465.99 | bwd_allreduce_microstep: 522.30 | step_microstep: 24.86 +[2025-05-01 22:38:53,685] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4413.70 | bwd: 7087.54 | bwd_inner: 6564.86 | bwd_allreduce: 522.38 | step: 49.25 + 2%|▏ | 162/8720 [23:27<25:39:26, 10.79s/it] {'loss': 2.1522, 'grad_norm': 9.859027862548828, 'learning_rate': 6.18320610687023e-06, 'epoch': 0.19} + 2%|▏ | 162/8720 [23:27<25:39:26, 10.79s/it]dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 1105 +[2025-05-01 22:38:54,030] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 108.36 | bwd_microstep: 215.81 | bwd_inner_microstep: 215.79 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-01 22:38:54,971] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 421.63 | bwd_microstep: 486.88 | bwd_inner_microstep: 486.86 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1377 +[2025-05-01 22:38:55,467] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 143.52 | bwd_microstep: 332.90 | bwd_inner_microstep: 332.87 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-01 22:38:56,336] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 422.00 | bwd_microstep: 414.32 | bwd_inner_microstep: 414.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-01 22:38:57,134] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.84 | bwd_microstep: 587.88 | bwd_inner_microstep: 587.86 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.51 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-01 22:38:57,880] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 434.00 | bwd_microstep: 280.39 | bwd_inner_microstep: 280.37 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-01 22:38:58,832] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 303.89 | bwd_microstep: 630.21 | bwd_inner_microstep: 630.19 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1096 +[2025-05-01 22:38:59,239] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 215.06 | bwd_microstep: 164.69 | bwd_inner_microstep: 164.65 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.11 +dynamic ViT batch size: 6, images per sample: 6.0, dynamic token length: 1618 +[2025-05-01 22:38:59,968] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 166.83 | bwd_microstep: 544.86 | bwd_inner_microstep: 544.84 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.48 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-01 22:39:00,733] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 441.24 | bwd_microstep: 292.66 | bwd_inner_microstep: 292.64 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 22:39:01,692] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 318.49 | bwd_microstep: 622.75 | bwd_inner_microstep: 622.73 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.33 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 22:39:02,265] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 208.67 | bwd_microstep: 325.71 | bwd_inner_microstep: 325.69 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 316 +[2025-05-01 22:39:02,513] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 98.93 | bwd_microstep: 116.97 | bwd_inner_microstep: 114.61 | bwd_allreduce_microstep: 2.34 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 22:39:03,293] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 438.07 | bwd_microstep: 312.55 | bwd_inner_microstep: 312.53 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 22:39:04,169] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 239.88 | bwd_microstep: 617.48 | bwd_inner_microstep: 617.46 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.46 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-01 22:39:05,276] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.32 | optimizer_step: 17.55 +[2025-05-01 22:39:05,277] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 244.41 | bwd_microstep: 807.95 | bwd_inner_microstep: 319.68 | bwd_allreduce_microstep: 488.22 | step_microstep: 25.15 +[2025-05-01 22:39:05,278] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4394.65 | bwd: 6754.04 | bwd_inner: 6260.77 | bwd_allreduce: 490.65 | step: 47.33 + 2%|▏ | 163/8720 [23:39<26:13:28, 11.03s/it] {'loss': 1.9834, 'grad_norm': 7.457055568695068, 'learning_rate': 6.221374045801527e-06, 'epoch': 0.19} + 2%|▏ | 163/8720 [23:39<26:13:28, 11.03s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-01 22:39:06,049] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.61 | bwd_microstep: 558.23 | bwd_inner_microstep: 558.21 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-01 22:39:06,826] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 442.67 | bwd_microstep: 302.52 | bwd_inner_microstep: 302.50 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-01 22:39:07,747] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 275.75 | bwd_microstep: 619.84 | bwd_inner_microstep: 619.82 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.53 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 336 +[2025-05-01 22:39:07,993] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 97.64 | bwd_microstep: 117.88 | bwd_inner_microstep: 117.74 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-01 22:39:08,745] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.67 | bwd_microstep: 545.30 | bwd_inner_microstep: 545.28 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-01 22:39:09,467] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 413.13 | bwd_microstep: 276.84 | bwd_inner_microstep: 276.82 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 22:39:10,466] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 367.28 | bwd_microstep: 616.50 | bwd_inner_microstep: 616.48 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 22:39:11,031] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 198.08 | bwd_microstep: 346.92 | bwd_inner_microstep: 346.90 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.31 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1353 +[2025-05-01 22:39:11,832] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 313.69 | bwd_microstep: 457.82 | bwd_inner_microstep: 457.81 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.13 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 22:39:12,499] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.00 | bwd_microstep: 452.03 | bwd_inner_microstep: 452.02 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 22:39:13,315] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 435.82 | bwd_microstep: 348.86 | bwd_inner_microstep: 348.84 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 22:39:14,136] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.60 | bwd_microstep: 613.89 | bwd_inner_microstep: 613.87 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.49 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 22:39:14,852] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 409.67 | bwd_microstep: 275.51 | bwd_inner_microstep: 275.49 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.14 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1954 +[2025-05-01 22:39:15,865] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 343.18 | bwd_microstep: 652.10 | bwd_inner_microstep: 652.08 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1893 +[2025-05-01 22:39:16,434] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 199.69 | bwd_microstep: 346.84 | bwd_inner_microstep: 346.82 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-01 22:39:17,563] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.49 | optimizer_step: 17.42 +[2025-05-01 22:39:17,563] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 423.59 | bwd_microstep: 647.66 | bwd_inner_microstep: 534.19 | bwd_allreduce_microstep: 113.42 | step_microstep: 25.48 +[2025-05-01 22:39:17,564] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4678.92 | bwd: 7178.78 | bwd_inner: 7064.93 | bwd_allreduce: 113.54 | step: 45.26 + 2%|▏ | 164/8720 [23:51<27:06:55, 11.41s/it] {'loss': 1.8455, 'grad_norm': 9.844802856445312, 'learning_rate': 6.259541984732826e-06, 'epoch': 0.19} + 2%|▏ | 164/8720 [23:51<27:06:55, 11.41s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1942 +[2025-05-01 22:39:18,465] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 225.99 | bwd_microstep: 652.58 | bwd_inner_microstep: 652.56 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.49 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 388 +[2025-05-01 22:39:18,772] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 114.96 | bwd_microstep: 161.34 | bwd_inner_microstep: 161.32 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.26 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1913 +[2025-05-01 22:39:19,368] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 194.82 | bwd_microstep: 382.25 | bwd_inner_microstep: 382.23 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 348 +[2025-05-01 22:39:19,632] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 104.04 | bwd_microstep: 128.29 | bwd_inner_microstep: 128.28 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-01 22:39:20,417] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 443.14 | bwd_microstep: 309.78 | bwd_inner_microstep: 309.76 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-01 22:39:21,303] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 253.95 | bwd_microstep: 613.46 | bwd_inner_microstep: 613.44 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-01 22:39:21,851] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 198.93 | bwd_microstep: 325.53 | bwd_inner_microstep: 325.51 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 22:39:22,859] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 421.80 | bwd_microstep: 553.33 | bwd_inner_microstep: 553.31 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-01 22:39:23,509] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.70 | bwd_microstep: 440.83 | bwd_inner_microstep: 440.81 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 22:39:24,404] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 426.62 | bwd_microstep: 436.42 | bwd_inner_microstep: 436.41 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-01 22:39:25,123] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.55 | bwd_microstep: 510.04 | bwd_inner_microstep: 510.02 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.53 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-01 22:39:25,940] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 442.77 | bwd_microstep: 341.74 | bwd_inner_microstep: 341.72 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-01 22:39:26,747] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.28 | bwd_microstep: 598.13 | bwd_inner_microstep: 598.11 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.28 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1953 +[2025-05-01 22:39:27,505] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 433.30 | bwd_microstep: 292.99 | bwd_inner_microstep: 292.97 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 368 +[2025-05-01 22:39:27,741] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 79.08 | bwd_microstep: 137.42 | bwd_inner_microstep: 137.40 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-01 22:39:28,752] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.53 | optimizer_step: 17.67 +[2025-05-01 22:39:28,753] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 425.89 | bwd_microstep: 527.61 | bwd_inner_microstep: 459.19 | bwd_allreduce_microstep: 68.33 | step_microstep: 25.58 +[2025-05-01 22:39:28,754] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4335.71 | bwd: 6411.75 | bwd_inner: 6343.07 | bwd_allreduce: 68.37 | step: 47.53 + 2%|▏ | 165/8720 [24:02<26:57:22, 11.34s/it] {'loss': 1.8976, 'grad_norm': 6.432587146759033, 'learning_rate': 6.2977099236641225e-06, 'epoch': 0.19} + 2%|▏ | 165/8720 [24:02<26:57:22, 11.34s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1953 +[2025-05-01 22:39:29,670] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 238.30 | bwd_microstep: 654.75 | bwd_inner_microstep: 654.74 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.30 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-01 22:39:30,257] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 280.16 | bwd_microstep: 276.50 | bwd_inner_microstep: 276.48 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.22 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 347 +[2025-05-01 22:39:30,526] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 102.04 | bwd_microstep: 139.64 | bwd_inner_microstep: 139.63 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1109 +[2025-05-01 22:39:31,155] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 247.72 | bwd_microstep: 352.72 | bwd_inner_microstep: 352.58 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-01 22:39:31,794] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 191.36 | bwd_microstep: 427.55 | bwd_inner_microstep: 427.54 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-01 22:39:32,639] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 429.62 | bwd_microstep: 380.36 | bwd_inner_microstep: 380.34 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-01 22:39:33,456] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.68 | bwd_microstep: 605.95 | bwd_inner_microstep: 605.93 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.50 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 22:39:34,177] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 411.94 | bwd_microstep: 276.96 | bwd_inner_microstep: 276.94 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 328 +[2025-05-01 22:39:34,422] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 87.48 | bwd_microstep: 141.14 | bwd_inner_microstep: 141.12 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 22:39:35,321] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 424.08 | bwd_microstep: 440.81 | bwd_inner_microstep: 440.79 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 22:39:36,084] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.87 | bwd_microstep: 554.96 | bwd_inner_microstep: 554.94 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 321 +[2025-05-01 22:39:36,353] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 103.24 | bwd_microstep: 135.82 | bwd_inner_microstep: 135.80 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 22:39:36,927] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 227.26 | bwd_microstep: 312.53 | bwd_inner_microstep: 312.51 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 22:39:37,833] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 425.67 | bwd_microstep: 448.00 | bwd_inner_microstep: 447.98 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 832 +[2025-05-01 22:39:38,073] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.02 | bwd_microstep: 132.12 | bwd_inner_microstep: 131.96 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 22:39:39,165] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.45 | optimizer_step: 17.50 +[2025-05-01 22:39:39,165] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 409.61 | bwd_microstep: 641.08 | bwd_inner_microstep: 538.16 | bwd_allreduce_microstep: 102.87 | step_microstep: 25.25 +[2025-05-01 22:39:39,167] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4052.93 | bwd: 5920.95 | bwd_inner: 5817.50 | bwd_allreduce: 103.07 | step: 44.82 + 2%|▏ | 166/8720 [24:12<26:17:24, 11.06s/it] {'loss': 2.2392, 'grad_norm': 10.010208129882812, 'learning_rate': 6.335877862595419e-06, 'epoch': 0.19} + 2%|▏ | 166/8720 [24:12<26:17:24, 11.06s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1949 +[2025-05-01 22:39:40,011] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 198.46 | bwd_microstep: 619.65 | bwd_inner_microstep: 619.63 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.48 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1128 +[2025-05-01 22:39:40,548] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 276.66 | bwd_microstep: 230.18 | bwd_inner_microstep: 229.89 | bwd_allreduce_microstep: 0.14 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-01 22:39:41,263] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.49 | bwd_microstep: 504.51 | bwd_inner_microstep: 504.49 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 865 +[2025-05-01 22:39:41,791] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 224.50 | bwd_microstep: 271.54 | bwd_inner_microstep: 271.23 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.23 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-01 22:39:42,428] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 191.23 | bwd_microstep: 424.66 | bwd_inner_microstep: 424.64 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-01 22:39:43,273] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 423.44 | bwd_microstep: 390.23 | bwd_inner_microstep: 390.21 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-01 22:39:44,086] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.11 | bwd_microstep: 602.02 | bwd_inner_microstep: 602.00 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-01 22:39:44,758] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 363.53 | bwd_microstep: 275.66 | bwd_inner_microstep: 275.64 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.23 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-01 22:39:45,762] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 361.11 | bwd_microstep: 621.99 | bwd_inner_microstep: 621.97 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-01 22:39:46,331] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 228.92 | bwd_microstep: 306.27 | bwd_inner_microstep: 306.25 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-01 22:39:47,296] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 423.64 | bwd_microstep: 506.29 | bwd_inner_microstep: 506.27 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-01 22:39:47,980] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.58 | bwd_microstep: 474.70 | bwd_inner_microstep: 474.68 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 22:39:48,841] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 444.42 | bwd_microstep: 385.21 | bwd_inner_microstep: 385.14 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.33 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 22:39:49,709] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 227.72 | bwd_microstep: 618.57 | bwd_inner_microstep: 618.55 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 22:39:50,289] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 250.31 | bwd_microstep: 295.84 | bwd_inner_microstep: 295.82 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 317 +[2025-05-01 22:39:51,091] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.38 | optimizer_step: 17.13 +[2025-05-01 22:39:51,091] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 97.81 | bwd_microstep: 651.79 | bwd_inner_microstep: 133.54 | bwd_allreduce_microstep: 518.20 | step_microstep: 24.76 +[2025-05-01 22:39:51,092] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4280.76 | bwd: 7179.26 | bwd_inner: 6660.02 | bwd_allreduce: 518.55 | step: 47.02 + 2%|▏ | 167/8720 [24:24<26:53:59, 11.32s/it] {'loss': 2.295, 'grad_norm': 7.297492027282715, 'learning_rate': 6.374045801526718e-06, 'epoch': 0.19} + 2%|▏ | 167/8720 [24:24<26:53:59, 11.32s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 365 +[2025-05-01 22:39:51,299] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 68.29 | bwd_microstep: 119.60 | bwd_inner_microstep: 119.30 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.10 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 851 +[2025-05-01 22:39:51,785] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 173.57 | bwd_microstep: 294.22 | bwd_inner_microstep: 294.20 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.31 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-01 22:39:52,532] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 432.04 | bwd_microstep: 284.85 | bwd_inner_microstep: 284.83 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-01 22:39:53,442] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 286.36 | bwd_microstep: 604.84 | bwd_inner_microstep: 604.82 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.84 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-01 22:39:53,994] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.56 | bwd_microstep: 341.10 | bwd_inner_microstep: 341.08 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.31 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1347 +[2025-05-01 22:39:54,823] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 311.58 | bwd_microstep: 483.60 | bwd_inner_microstep: 483.58 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-01 22:39:55,407] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 201.73 | bwd_microstep: 350.66 | bwd_inner_microstep: 350.64 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.52 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-01 22:39:56,322] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 422.61 | bwd_microstep: 459.81 | bwd_inner_microstep: 459.79 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-01 22:39:57,026] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.76 | bwd_microstep: 499.22 | bwd_inner_microstep: 499.21 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-01 22:39:57,925] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 446.80 | bwd_microstep: 422.14 | bwd_inner_microstep: 422.12 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-01 22:39:58,761] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 399.15 | bwd_microstep: 405.96 | bwd_inner_microstep: 405.94 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-01 22:39:59,607] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 377.01 | bwd_microstep: 439.50 | bwd_inner_microstep: 439.48 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 22:40:00,419] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 339.78 | bwd_microstep: 438.53 | bwd_inner_microstep: 438.51 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 22:40:01,234] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 385.58 | bwd_microstep: 396.94 | bwd_inner_microstep: 396.92 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.52 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 22:40:02,054] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 364.55 | bwd_microstep: 428.72 | bwd_inner_microstep: 428.71 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 22:40:03,257] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 3.11 | optimizer_step: 25.16 +[2025-05-01 22:40:03,258] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 409.41 | bwd_microstep: 735.35 | bwd_inner_microstep: 407.34 | bwd_allreduce_microstep: 327.96 | step_microstep: 33.63 +[2025-05-01 22:40:03,259] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4998.69 | bwd: 6705.07 | bwd_inner: 6376.55 | bwd_allreduce: 328.15 | step: 52.26 + 2%|▏ | 168/8720 [24:37<27:29:54, 11.58s/it] {'loss': 2.2559, 'grad_norm': 10.309900283813477, 'learning_rate': 6.412213740458016e-06, 'epoch': 0.19} + 2%|▏ | 168/8720 [24:37<27:29:54, 11.58s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-01 22:40:04,023] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 382.52 | bwd_microstep: 358.72 | bwd_inner_microstep: 358.70 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-01 22:40:04,858] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 418.74 | bwd_microstep: 381.90 | bwd_inner_microstep: 381.89 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-01 22:40:05,625] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 423.21 | bwd_microstep: 313.64 | bwd_inner_microstep: 313.63 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.22 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-01 22:40:06,480] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 418.56 | bwd_microstep: 398.74 | bwd_inner_microstep: 398.73 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-01 22:40:07,346] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 409.83 | bwd_microstep: 422.72 | bwd_inner_microstep: 422.70 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-01 22:40:08,213] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 307.51 | bwd_microstep: 524.98 | bwd_inner_microstep: 524.96 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 22:40:09,001] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 276.58 | bwd_microstep: 495.31 | bwd_inner_microstep: 495.29 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 22:40:09,882] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 318.63 | bwd_microstep: 546.00 | bwd_inner_microstep: 545.96 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 22:40:10,721] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 285.47 | bwd_microstep: 534.16 | bwd_inner_microstep: 534.14 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 22:40:11,537] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 223.52 | bwd_microstep: 570.78 | bwd_inner_microstep: 570.77 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-01 22:40:12,277] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 302.71 | bwd_microstep: 415.37 | bwd_inner_microstep: 415.35 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 22:40:13,112] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 419.59 | bwd_microstep: 394.47 | bwd_inner_microstep: 394.46 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 22:40:13,996] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 415.66 | bwd_microstep: 450.55 | bwd_inner_microstep: 450.53 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-01 22:40:14,877] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 362.31 | bwd_microstep: 500.98 | bwd_inner_microstep: 500.96 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 22:40:15,714] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 319.97 | bwd_microstep: 496.16 | bwd_inner_microstep: 496.15 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1889 +[2025-05-01 22:40:16,624] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.39 | optimizer_step: 32.94 +[2025-05-01 22:40:16,626] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 301.74 | bwd_microstep: 551.51 | bwd_inner_microstep: 469.58 | bwd_allreduce_microstep: 81.86 | step_microstep: 41.10 +[2025-05-01 22:40:16,627] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 5586.33 | bwd: 7356.05 | bwd_inner: 7273.80 | bwd_allreduce: 81.91 | step: 51.58 + 2%|▏ | 169/8720 [24:50<28:46:34, 12.11s/it] {'loss': 1.9813, 'grad_norm': 5.906993865966797, 'learning_rate': 6.4503816793893135e-06, 'epoch': 0.19} + 2%|▏ | 169/8720 [24:50<28:46:34, 12.11s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1906 +[2025-05-01 22:40:17,508] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 403.86 | bwd_microstep: 434.45 | bwd_inner_microstep: 434.43 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-01 22:40:18,346] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 347.64 | bwd_microstep: 456.86 | bwd_inner_microstep: 456.84 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.31 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 22:40:19,206] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 272.69 | bwd_microstep: 552.90 | bwd_inner_microstep: 552.88 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.52 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1358 +[2025-05-01 22:40:19,813] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 182.00 | bwd_microstep: 391.69 | bwd_inner_microstep: 391.67 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-01 22:40:20,641] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 321.07 | bwd_microstep: 473.10 | bwd_inner_microstep: 473.08 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.28 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 22:40:21,524] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 253.55 | bwd_microstep: 597.02 | bwd_inner_microstep: 597.00 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.71 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 322 +[2025-05-01 22:40:21,746] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 79.22 | bwd_microstep: 125.68 | bwd_inner_microstep: 125.66 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.33 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 321 +[2025-05-01 22:40:22,009] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 104.11 | bwd_microstep: 124.37 | bwd_inner_microstep: 124.35 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 320 +[2025-05-01 22:40:22,269] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 96.90 | bwd_microstep: 133.02 | bwd_inner_microstep: 133.00 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 22:40:23,107] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 201.54 | bwd_microstep: 607.33 | bwd_inner_microstep: 607.31 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 22:40:23,915] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 197.20 | bwd_microstep: 588.17 | bwd_inner_microstep: 588.15 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-01 22:40:24,763] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 238.03 | bwd_microstep: 575.72 | bwd_inner_microstep: 575.71 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 22:40:25,601] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 250.20 | bwd_microstep: 555.69 | bwd_inner_microstep: 555.67 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.33 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 317 +[2025-05-01 22:40:25,837] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 84.79 | bwd_microstep: 121.35 | bwd_inner_microstep: 121.20 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.09 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 827 +[2025-05-01 22:40:26,325] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 171.05 | bwd_microstep: 296.26 | bwd_inner_microstep: 296.24 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 435 +[2025-05-01 22:40:26,752] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.07 | optimizer_gradients: 2.33 | optimizer_step: 36.75 +[2025-05-01 22:40:26,752] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 119.46 | bwd_microstep: 230.66 | bwd_inner_microstep: 124.64 | bwd_allreduce_microstep: 105.85 | step_microstep: 45.01 +[2025-05-01 22:40:26,753] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 3323.27 | bwd: 6264.28 | bwd_inner: 6157.94 | bwd_allreduce: 105.95 | step: 76.35 + 2%|▏ | 170/8720 [25:00<27:21:08, 11.52s/it] {'loss': 1.988, 'grad_norm': 9.908615112304688, 'learning_rate': 6.488549618320611e-06, 'epoch': 0.19} + 2%|▏ | 170/8720 [25:00<27:21:08, 11.52s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1921 +[2025-05-01 22:40:27,662] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 420.56 | bwd_microstep: 467.77 | bwd_inner_microstep: 467.76 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1915 +[2025-05-01 22:40:28,552] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 367.25 | bwd_microstep: 507.09 | bwd_inner_microstep: 507.07 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1367 +[2025-05-01 22:40:29,259] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 230.81 | bwd_microstep: 458.84 | bwd_inner_microstep: 458.82 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.23 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 345 +[2025-05-01 22:40:29,479] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 80.27 | bwd_microstep: 123.70 | bwd_inner_microstep: 123.54 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-01 22:40:30,336] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 423.81 | bwd_microstep: 400.55 | bwd_inner_microstep: 400.53 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 22:40:31,167] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 423.37 | bwd_microstep: 371.66 | bwd_inner_microstep: 371.65 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.53 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 22:40:32,008] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 424.71 | bwd_microstep: 381.62 | bwd_inner_microstep: 381.60 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 327 +[2025-05-01 22:40:32,274] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.02 | bwd_microstep: 139.15 | bwd_inner_microstep: 139.13 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 22:40:33,130] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 246.14 | bwd_microstep: 577.21 | bwd_inner_microstep: 577.17 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 22:40:33,981] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 203.53 | bwd_microstep: 614.95 | bwd_inner_microstep: 614.94 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 22:40:34,813] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 201.95 | bwd_microstep: 611.04 | bwd_inner_microstep: 611.02 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.66 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1346 +[2025-05-01 22:40:35,393] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 148.09 | bwd_microstep: 412.79 | bwd_inner_microstep: 412.77 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.32 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1342 +[2025-05-01 22:40:35,984] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 253.91 | bwd_microstep: 306.77 | bwd_inner_microstep: 306.75 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 22:40:36,838] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 403.37 | bwd_microstep: 419.39 | bwd_inner_microstep: 419.37 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.32 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 22:40:37,702] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 358.26 | bwd_microstep: 472.99 | bwd_inner_microstep: 472.97 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.70 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 22:40:38,745] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.08 | optimizer_gradients: 2.38 | optimizer_step: 16.78 +[2025-05-01 22:40:38,746] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 224.03 | bwd_microstep: 778.31 | bwd_inner_microstep: 624.20 | bwd_allreduce_microstep: 154.07 | step_microstep: 25.69 +[2025-05-01 22:40:38,747] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4505.01 | bwd: 7044.40 | bwd_inner: 6889.31 | bwd_allreduce: 154.21 | step: 47.57 + 2%|▏ | 171/8720 [25:12<27:41:24, 11.66s/it] {'loss': 1.7833, 'grad_norm': 13.529335021972656, 'learning_rate': 6.526717557251909e-06, 'epoch': 0.2} + 2%|▏ | 171/8720 [25:12<27:41:24, 11.66s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-01 22:40:39,636] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 400.86 | bwd_microstep: 467.08 | bwd_inner_microstep: 467.06 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-01 22:40:40,478] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 378.77 | bwd_microstep: 447.10 | bwd_inner_microstep: 447.08 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-01 22:40:41,263] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 377.61 | bwd_microstep: 391.82 | bwd_inner_microstep: 391.80 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-01 22:40:42,139] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 421.28 | bwd_microstep: 438.84 | bwd_inner_microstep: 438.82 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 22:40:42,925] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 340.31 | bwd_microstep: 429.53 | bwd_inner_microstep: 429.52 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 22:40:43,804] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 376.50 | bwd_microstep: 485.43 | bwd_inner_microstep: 485.41 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 22:40:44,589] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 371.68 | bwd_microstep: 397.56 | bwd_inner_microstep: 397.55 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 22:40:45,426] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 402.29 | bwd_microstep: 416.71 | bwd_inner_microstep: 416.70 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.28 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 22:40:46,252] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 371.24 | bwd_microstep: 427.36 | bwd_inner_microstep: 427.34 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 22:40:47,087] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 405.32 | bwd_microstep: 398.98 | bwd_inner_microstep: 398.96 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 22:40:47,938] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 423.51 | bwd_microstep: 394.04 | bwd_inner_microstep: 394.02 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 321 +[2025-05-01 22:40:48,201] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.04 | bwd_microstep: 137.88 | bwd_inner_microstep: 137.86 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 22:40:49,020] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 266.68 | bwd_microstep: 519.63 | bwd_inner_microstep: 519.61 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.49 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-01 22:40:49,892] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 305.47 | bwd_microstep: 532.18 | bwd_inner_microstep: 532.16 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.31 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 313 +[2025-05-01 22:40:50,133] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 76.46 | bwd_microstep: 135.22 | bwd_inner_microstep: 135.08 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1907 +[2025-05-01 22:40:51,112] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.35 | optimizer_step: 18.66 +[2025-05-01 22:40:51,114] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 410.22 | bwd_microstep: 527.54 | bwd_inner_microstep: 460.28 | bwd_allreduce_microstep: 67.21 | step_microstep: 27.50 +[2025-05-01 22:40:51,115] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 5421.12 | bwd: 6546.91 | bwd_inner: 6479.28 | bwd_allreduce: 67.34 | step: 42.22 + 2%|▏ | 172/8720 [25:24<28:11:32, 11.87s/it] {'loss': 2.231, 'grad_norm': 10.90117359161377, 'learning_rate': 6.564885496183207e-06, 'epoch': 0.2} + 2%|▏ | 172/8720 [25:24<28:11:32, 11.87s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1924 +[2025-05-01 22:40:51,997] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 442.56 | bwd_microstep: 397.39 | bwd_inner_microstep: 397.37 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-01 22:40:52,856] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 417.85 | bwd_microstep: 406.58 | bwd_inner_microstep: 406.56 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-01 22:40:53,695] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 427.27 | bwd_microstep: 376.13 | bwd_inner_microstep: 376.11 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-01 22:40:54,552] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 305.74 | bwd_microstep: 518.18 | bwd_inner_microstep: 518.14 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.67 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 349 +[2025-05-01 22:40:54,789] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 76.69 | bwd_microstep: 143.00 | bwd_inner_microstep: 142.98 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.33 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-01 22:40:55,639] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 428.03 | bwd_microstep: 388.30 | bwd_inner_microstep: 388.28 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-01 22:40:56,489] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 422.46 | bwd_microstep: 393.27 | bwd_inner_microstep: 393.25 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-01 22:40:57,349] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 421.81 | bwd_microstep: 404.05 | bwd_inner_microstep: 404.03 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 22:40:58,194] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 413.38 | bwd_microstep: 397.95 | bwd_inner_microstep: 397.93 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.33 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-01 22:40:59,061] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 424.39 | bwd_microstep: 407.55 | bwd_inner_microstep: 407.53 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 22:40:59,914] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 338.57 | bwd_microstep: 480.45 | bwd_inner_microstep: 480.43 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.31 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 22:41:00,749] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 244.82 | bwd_microstep: 554.68 | bwd_inner_microstep: 554.66 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 835 +[2025-05-01 22:41:01,082] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 173.29 | bwd_microstep: 128.43 | bwd_inner_microstep: 128.11 | bwd_allreduce_microstep: 0.14 | step_microstep: 0.19 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 320 +[2025-05-01 22:41:01,306] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 82.57 | bwd_microstep: 126.39 | bwd_inner_microstep: 126.19 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 22:41:02,126] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 309.00 | bwd_microstep: 479.64 | bwd_inner_microstep: 479.62 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 315 +[2025-05-01 22:41:02,571] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.35 | optimizer_step: 16.70 +[2025-05-01 22:41:02,572] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 98.19 | bwd_microstep: 292.79 | bwd_inner_microstep: 136.26 | bwd_allreduce_microstep: 156.48 | step_microstep: 24.32 +[2025-05-01 22:41:02,573] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 5026.60 | bwd: 5894.99 | bwd_inner: 5737.52 | bwd_allreduce: 156.70 | step: 53.36 + 2%|▏ | 173/8720 [25:36<27:53:31, 11.75s/it] {'loss': 2.4349, 'grad_norm': 7.9057135581970215, 'learning_rate': 6.6030534351145046e-06, 'epoch': 0.2} + 2%|▏ | 173/8720 [25:36<27:53:31, 11.75s/it]dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1403 +[2025-05-01 22:41:03,199] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 303.11 | bwd_microstep: 300.62 | bwd_inner_microstep: 300.48 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 344 +[2025-05-01 22:41:03,446] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 85.33 | bwd_microstep: 142.61 | bwd_inner_microstep: 142.59 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-01 22:41:04,289] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 428.93 | bwd_microstep: 379.79 | bwd_inner_microstep: 379.77 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-01 22:41:05,128] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 423.16 | bwd_microstep: 382.29 | bwd_inner_microstep: 382.27 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-01 22:41:06,015] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 419.39 | bwd_microstep: 432.78 | bwd_inner_microstep: 432.76 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 841 +[2025-05-01 22:41:06,395] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 209.89 | bwd_microstep: 140.66 | bwd_inner_microstep: 140.35 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-01 22:41:07,235] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 368.45 | bwd_microstep: 455.70 | bwd_inner_microstep: 455.69 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 22:41:08,116] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 343.39 | bwd_microstep: 521.99 | bwd_inner_microstep: 521.98 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.11 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 857 +[2025-05-01 22:41:08,568] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 131.47 | bwd_microstep: 299.21 | bwd_inner_microstep: 299.19 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.32 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-01 22:41:09,413] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 307.21 | bwd_microstep: 503.49 | bwd_inner_microstep: 503.47 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 334 +[2025-05-01 22:41:09,677] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 101.37 | bwd_microstep: 132.72 | bwd_inner_microstep: 132.27 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.26 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-01 22:41:10,497] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.11 | bwd_microstep: 611.55 | bwd_inner_microstep: 611.53 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.49 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 22:41:11,308] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 217.89 | bwd_microstep: 558.39 | bwd_inner_microstep: 558.37 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 22:41:12,151] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 197.91 | bwd_microstep: 623.27 | bwd_inner_microstep: 623.25 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.47 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 22:41:12,984] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 204.19 | bwd_microstep: 595.03 | bwd_inner_microstep: 595.01 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 22:41:13,995] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 4.35 | optimizer_step: 24.08 +[2025-05-01 22:41:13,996] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 201.68 | bwd_microstep: 752.91 | bwd_inner_microstep: 611.09 | bwd_allreduce_microstep: 141.76 | step_microstep: 35.04 +[2025-05-01 22:41:13,997] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4133.37 | bwd: 6833.05 | bwd_inner: 6690.18 | bwd_allreduce: 142.04 | step: 59.34 + 2%|▏ | 174/8720 [25:47<27:39:24, 11.65s/it] {'loss': 2.5133, 'grad_norm': 11.355188369750977, 'learning_rate': 6.641221374045802e-06, 'epoch': 0.2} + 2%|▏ | 174/8720 [25:47<27:39:24, 11.65s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1917 +[2025-05-01 22:41:14,889] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 370.15 | bwd_microstep: 501.16 | bwd_inner_microstep: 501.14 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1889 +[2025-05-01 22:41:15,683] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 327.69 | bwd_microstep: 449.12 | bwd_inner_microstep: 449.10 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-01 22:41:16,466] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 409.43 | bwd_microstep: 358.62 | bwd_inner_microstep: 358.60 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-01 22:41:17,279] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 421.79 | bwd_microstep: 373.14 | bwd_inner_microstep: 373.12 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-01 22:41:18,148] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 428.96 | bwd_microstep: 412.94 | bwd_inner_microstep: 412.81 | bwd_allreduce_microstep: 0.08 | step_microstep: 0.15 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-01 22:41:19,031] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 395.46 | bwd_microstep: 470.81 | bwd_inner_microstep: 470.69 | bwd_allreduce_microstep: 0.03 | step_microstep: 0.33 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-01 22:41:19,866] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 359.96 | bwd_microstep: 457.53 | bwd_inner_microstep: 457.51 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 22:41:20,751] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 344.91 | bwd_microstep: 525.05 | bwd_inner_microstep: 525.03 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.05 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 329 +[2025-05-01 22:41:20,985] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 75.15 | bwd_microstep: 141.33 | bwd_inner_microstep: 141.31 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 22:41:21,826] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 424.21 | bwd_microstep: 383.77 | bwd_inner_microstep: 383.75 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.53 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-01 22:41:22,681] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 426.83 | bwd_microstep: 396.04 | bwd_inner_microstep: 396.03 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-01 22:41:23,545] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 420.64 | bwd_microstep: 410.27 | bwd_inner_microstep: 410.25 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 22:41:24,402] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 411.71 | bwd_microstep: 410.42 | bwd_inner_microstep: 410.40 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 22:41:25,242] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 425.44 | bwd_microstep: 379.62 | bwd_inner_microstep: 379.60 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 22:41:26,050] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 349.12 | bwd_microstep: 427.25 | bwd_inner_microstep: 427.23 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2027 +[2025-05-01 22:41:27,176] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.07 | optimizer_gradients: 2.33 | optimizer_step: 29.45 +[2025-05-01 22:41:27,176] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 337.78 | bwd_microstep: 719.40 | bwd_inner_microstep: 550.66 | bwd_allreduce_microstep: 168.69 | step_microstep: 37.24 +[2025-05-01 22:41:27,177] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 5929.09 | bwd: 6816.53 | bwd_inner: 6647.26 | bwd_allreduce: 168.92 | step: 54.69 + 2%|▏ | 175/8720 [26:00<28:44:34, 12.11s/it] {'loss': 1.4429, 'grad_norm': 9.908421516418457, 'learning_rate': 6.679389312977099e-06, 'epoch': 0.2} + 2%|▏ | 175/8720 [26:00<28:44:34, 12.11s/it]dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 859 +[2025-05-01 22:41:27,677] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 172.26 | bwd_microstep: 302.97 | bwd_inner_microstep: 302.95 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-01 22:41:28,546] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 302.50 | bwd_microstep: 532.53 | bwd_inner_microstep: 532.51 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-01 22:41:29,383] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 294.15 | bwd_microstep: 507.87 | bwd_inner_microstep: 507.85 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.46 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-01 22:41:30,192] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 325.13 | bwd_microstep: 449.13 | bwd_inner_microstep: 449.11 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.45 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-01 22:41:31,039] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 275.98 | bwd_microstep: 535.16 | bwd_inner_microstep: 535.15 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 326 +[2025-05-01 22:41:31,274] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 103.26 | bwd_microstep: 103.60 | bwd_inner_microstep: 103.47 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 22:41:32,128] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 211.85 | bwd_microstep: 622.24 | bwd_inner_microstep: 622.22 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 22:41:32,957] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 201.60 | bwd_microstep: 601.93 | bwd_inner_microstep: 601.91 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 322 +[2025-05-01 22:41:33,183] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 84.42 | bwd_microstep: 117.32 | bwd_inner_microstep: 117.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.33 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 22:41:34,041] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 428.44 | bwd_microstep: 399.60 | bwd_inner_microstep: 399.58 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1350 +[2025-05-01 22:41:34,742] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 311.11 | bwd_microstep: 365.55 | bwd_inner_microstep: 365.53 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 22:41:35,579] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 322.96 | bwd_microstep: 498.42 | bwd_inner_microstep: 498.40 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 22:41:36,418] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 321.80 | bwd_microstep: 496.82 | bwd_inner_microstep: 496.80 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-01 22:41:37,198] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 340.31 | bwd_microstep: 424.59 | bwd_inner_microstep: 424.58 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.28 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 22:41:38,075] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 396.68 | bwd_microstep: 465.31 | bwd_inner_microstep: 465.29 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1908 +[2025-05-01 22:41:38,973] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.34 | optimizer_step: 18.69 +[2025-05-01 22:41:38,974] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 273.59 | bwd_microstep: 581.93 | bwd_inner_microstep: 449.91 | bwd_allreduce_microstep: 132.00 | step_microstep: 28.25 +[2025-05-01 22:41:38,976] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4365.92 | bwd: 7004.97 | bwd_inner: 6872.60 | bwd_allreduce: 132.11 | step: 47.81 + 2%|▏ | 176/8720 [26:12<28:31:17, 12.02s/it] {'loss': 1.5049, 'grad_norm': 11.480724334716797, 'learning_rate': 6.717557251908398e-06, 'epoch': 0.2} + 2%|▏ | 176/8720 [26:12<28:31:17, 12.02s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 464 +[2025-05-01 22:41:39,317] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 124.91 | bwd_microstep: 175.22 | bwd_inner_microstep: 175.20 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1122 +[2025-05-01 22:41:39,738] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 138.70 | bwd_microstep: 248.58 | bwd_inner_microstep: 248.56 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-01 22:41:40,593] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 423.67 | bwd_microstep: 398.71 | bwd_inner_microstep: 398.69 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-01 22:41:41,448] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 420.82 | bwd_microstep: 402.74 | bwd_inner_microstep: 402.72 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-01 22:41:42,344] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 423.55 | bwd_microstep: 439.63 | bwd_inner_microstep: 439.62 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-01 22:41:43,235] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 399.49 | bwd_microstep: 458.20 | bwd_inner_microstep: 458.18 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-01 22:41:44,133] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 364.67 | bwd_microstep: 499.38 | bwd_inner_microstep: 499.36 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1347 +[2025-05-01 22:41:44,770] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 274.80 | bwd_microstep: 329.70 | bwd_inner_microstep: 329.68 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 840 +[2025-05-01 22:41:45,256] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 216.39 | bwd_microstep: 239.09 | bwd_inner_microstep: 239.07 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-01 22:41:46,136] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 313.99 | bwd_microstep: 548.55 | bwd_inner_microstep: 548.53 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1092 +[2025-05-01 22:41:46,669] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 144.07 | bwd_microstep: 367.54 | bwd_inner_microstep: 367.52 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-01 22:41:47,568] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 311.77 | bwd_microstep: 551.29 | bwd_inner_microstep: 551.27 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.28 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-01 22:41:48,447] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 270.95 | bwd_microstep: 573.84 | bwd_inner_microstep: 573.82 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 22:41:49,344] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 251.56 | bwd_microstep: 611.80 | bwd_inner_microstep: 611.78 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.50 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 22:41:50,226] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 226.61 | bwd_microstep: 621.98 | bwd_inner_microstep: 621.96 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 316 +[2025-05-01 22:41:50,966] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.09 | optimizer_gradients: 2.45 | optimizer_step: 29.84 +[2025-05-01 22:41:50,966] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 70.88 | bwd_microstep: 606.75 | bwd_inner_microstep: 143.23 | bwd_allreduce_microstep: 463.47 | step_microstep: 38.89 +[2025-05-01 22:41:50,968] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4376.77 | bwd: 7073.01 | bwd_inner: 6609.22 | bwd_allreduce: 463.55 | step: 69.66 + 2%|▏ | 177/8720 [26:24<28:29:51, 12.01s/it] {'loss': 1.6945, 'grad_norm': 9.568573951721191, 'learning_rate': 6.755725190839695e-06, 'epoch': 0.2} + 2%|▏ | 177/8720 [26:24<28:29:51, 12.01s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1994 +[2025-05-01 22:41:51,903] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 422.71 | bwd_microstep: 488.55 | bwd_inner_microstep: 488.53 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.43 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 365 +[2025-05-01 22:41:52,177] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 109.54 | bwd_microstep: 134.00 | bwd_inner_microstep: 133.98 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-01 22:41:53,050] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 353.45 | bwd_microstep: 486.20 | bwd_inner_microstep: 486.18 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.50 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-01 22:41:53,951] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 340.95 | bwd_microstep: 527.14 | bwd_inner_microstep: 527.12 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.54 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-01 22:41:54,844] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 293.18 | bwd_microstep: 565.82 | bwd_inner_microstep: 565.80 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.32 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 853 +[2025-05-01 22:41:55,220] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 158.45 | bwd_microstep: 185.57 | bwd_inner_microstep: 185.55 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-01 22:41:56,115] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 425.25 | bwd_microstep: 437.99 | bwd_inner_microstep: 437.97 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 328 +[2025-05-01 22:41:56,385] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 101.39 | bwd_microstep: 138.27 | bwd_inner_microstep: 138.25 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 22:41:57,283] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 278.64 | bwd_microstep: 587.10 | bwd_inner_microstep: 587.08 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-01 22:41:58,164] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 238.04 | bwd_microstep: 611.46 | bwd_inner_microstep: 611.45 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.53 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 22:41:59,039] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 221.88 | bwd_microstep: 618.92 | bwd_inner_microstep: 618.90 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 22:41:59,924] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 235.32 | bwd_microstep: 621.91 | bwd_inner_microstep: 621.89 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.75 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 22:42:00,799] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 247.71 | bwd_microstep: 609.78 | bwd_inner_microstep: 609.76 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 22:42:01,665] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 238.00 | bwd_microstep: 609.26 | bwd_inner_microstep: 609.24 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-01 22:42:02,541] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 247.84 | bwd_microstep: 610.55 | bwd_inner_microstep: 610.53 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.02 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1936 +[2025-05-01 22:42:03,617] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.33 | optimizer_step: 18.75 +[2025-05-01 22:42:03,619] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 262.24 | bwd_microstep: 768.39 | bwd_inner_microstep: 623.81 | bwd_allreduce_microstep: 144.57 | step_microstep: 28.31 +[2025-05-01 22:42:03,620] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4174.51 | bwd: 8000.91 | bwd_inner: 7856.07 | bwd_allreduce: 144.64 | step: 58.73 + 2%|▏ | 178/8720 [26:37<28:57:13, 12.20s/it] {'loss': 2.067, 'grad_norm': 8.821222305297852, 'learning_rate': 6.793893129770993e-06, 'epoch': 0.2} + 2%|▏ | 178/8720 [26:37<28:57:13, 12.20s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1928 +[2025-05-01 22:42:04,577] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 441.81 | bwd_microstep: 472.25 | bwd_inner_microstep: 472.23 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1887 +[2025-05-01 22:42:05,489] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 421.22 | bwd_microstep: 458.01 | bwd_inner_microstep: 457.99 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.51 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-01 22:42:06,386] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 369.30 | bwd_microstep: 492.84 | bwd_inner_microstep: 492.82 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 864 +[2025-05-01 22:42:06,787] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 219.73 | bwd_microstep: 149.07 | bwd_inner_microstep: 148.96 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 338 +[2025-05-01 22:42:07,042] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.68 | bwd_microstep: 143.05 | bwd_inner_microstep: 143.03 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 850 +[2025-05-01 22:42:07,512] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 223.93 | bwd_microstep: 216.93 | bwd_inner_microstep: 216.56 | bwd_allreduce_microstep: 0.16 | step_microstep: 0.13 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-01 22:42:08,395] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 339.70 | bwd_microstep: 521.05 | bwd_inner_microstep: 521.03 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-01 22:42:09,276] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 343.94 | bwd_microstep: 517.70 | bwd_inner_microstep: 517.68 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 22:42:10,154] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 354.26 | bwd_microstep: 503.68 | bwd_inner_microstep: 503.66 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-01 22:42:11,034] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 376.44 | bwd_microstep: 481.84 | bwd_inner_microstep: 481.74 | bwd_allreduce_microstep: 0.04 | step_microstep: 0.16 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 22:42:11,913] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 399.30 | bwd_microstep: 459.65 | bwd_inner_microstep: 459.63 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 22:42:12,787] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 423.57 | bwd_microstep: 433.92 | bwd_inner_microstep: 433.91 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1094 +[2025-05-01 22:42:13,441] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 251.74 | bwd_microstep: 373.13 | bwd_inner_microstep: 373.11 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.31 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 22:42:14,315] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 247.25 | bwd_microstep: 608.11 | bwd_inner_microstep: 608.09 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.01 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 22:42:15,183] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 240.25 | bwd_microstep: 609.24 | bwd_inner_microstep: 609.22 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1849 +[2025-05-01 22:42:16,238] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.39 | optimizer_step: 30.33 +[2025-05-01 22:42:16,240] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 246.05 | bwd_microstep: 753.17 | bwd_inner_microstep: 608.15 | bwd_allreduce_microstep: 144.97 | step_microstep: 40.48 +[2025-05-01 22:42:16,241] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4994.04 | bwd: 7193.68 | bwd_inner: 7047.91 | bwd_allreduce: 145.25 | step: 53.29 + 2%|▏ | 179/8720 [26:49<29:14:54, 12.33s/it] {'loss': 1.4124, 'grad_norm': 5.202735424041748, 'learning_rate': 6.83206106870229e-06, 'epoch': 0.21} + 2%|▏ | 179/8720 [26:49<29:14:54, 12.33s/it]dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 911 +[2025-05-01 22:42:16,843] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 223.82 | bwd_microstep: 337.52 | bwd_inner_microstep: 337.51 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1941 +[2025-05-01 22:42:17,753] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 265.44 | bwd_microstep: 623.46 | bwd_inner_microstep: 623.45 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1928 +[2025-05-01 22:42:18,652] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 292.04 | bwd_microstep: 589.03 | bwd_inner_microstep: 589.01 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1907 +[2025-05-01 22:42:19,539] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 316.46 | bwd_microstep: 553.26 | bwd_inner_microstep: 553.24 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1899 +[2025-05-01 22:42:20,431] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 342.70 | bwd_microstep: 523.57 | bwd_inner_microstep: 523.55 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1886 +[2025-05-01 22:42:21,311] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 356.21 | bwd_microstep: 504.55 | bwd_inner_microstep: 504.53 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-01 22:42:22,196] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 380.65 | bwd_microstep: 483.51 | bwd_inner_microstep: 483.22 | bwd_allreduce_microstep: 0.28 | step_microstep: 0.23 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1365 +[2025-05-01 22:42:22,950] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 292.44 | bwd_microstep: 446.04 | bwd_inner_microstep: 446.02 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-01 22:42:23,834] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 279.77 | bwd_microstep: 585.52 | bwd_inner_microstep: 585.51 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 833 +[2025-05-01 22:42:24,225] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 99.46 | bwd_microstep: 276.64 | bwd_inner_microstep: 276.63 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 22:42:25,116] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 396.12 | bwd_microstep: 462.37 | bwd_inner_microstep: 462.35 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-01 22:42:26,018] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 357.63 | bwd_microstep: 509.69 | bwd_inner_microstep: 509.67 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-01 22:42:26,912] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 309.97 | bwd_microstep: 550.30 | bwd_inner_microstep: 550.28 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 843 +[2025-05-01 22:42:27,281] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 177.45 | bwd_microstep: 158.44 | bwd_inner_microstep: 158.42 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.48 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 22:42:28,172] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 426.47 | bwd_microstep: 430.39 | bwd_inner_microstep: 430.38 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-01 22:42:29,506] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.09 | optimizer_gradients: 4.70 | optimizer_step: 28.75 +[2025-05-01 22:42:29,508] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 421.71 | bwd_microstep: 837.86 | bwd_inner_microstep: 446.43 | bwd_allreduce_microstep: 391.36 | step_microstep: 43.05 +[2025-05-01 22:42:29,510] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4938.18 | bwd: 7872.22 | bwd_inner: 7480.20 | bwd_allreduce: 391.74 | step: 58.21 + 2%|▏ | 180/8720 [27:03<29:54:59, 12.61s/it] {'loss': 2.1092, 'grad_norm': 12.786334037780762, 'learning_rate': 6.870229007633589e-06, 'epoch': 0.21} + 2%|▏ | 180/8720 [27:03<29:54:59, 12.61s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1907 +[2025-05-01 22:42:30,441] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 431.86 | bwd_microstep: 452.70 | bwd_inner_microstep: 452.68 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1891 +[2025-05-01 22:42:31,358] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 423.00 | bwd_microstep: 458.01 | bwd_inner_microstep: 457.99 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.36 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1362 +[2025-05-01 22:42:32,009] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 330.48 | bwd_microstep: 293.66 | bwd_inner_microstep: 293.64 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1888 +[2025-05-01 22:42:32,921] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 429.03 | bwd_microstep: 449.23 | bwd_inner_microstep: 449.21 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-01 22:42:33,829] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 423.83 | bwd_microstep: 449.56 | bwd_inner_microstep: 449.54 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-01 22:42:34,743] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 402.96 | bwd_microstep: 480.12 | bwd_inner_microstep: 480.10 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-01 22:42:35,649] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 344.73 | bwd_microstep: 529.31 | bwd_inner_microstep: 529.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-01 22:42:36,557] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 294.53 | bwd_microstep: 578.68 | bwd_inner_microstep: 578.66 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.49 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 22:42:37,453] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 243.12 | bwd_microstep: 618.42 | bwd_inner_microstep: 618.40 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1345 +[2025-05-01 22:42:38,091] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 156.29 | bwd_microstep: 448.12 | bwd_inner_microstep: 448.10 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 22:42:38,999] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 302.94 | bwd_microstep: 572.49 | bwd_inner_microstep: 572.47 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.28 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 22:42:39,896] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 251.96 | bwd_microstep: 612.58 | bwd_inner_microstep: 612.56 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-01 22:42:40,799] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 241.69 | bwd_microstep: 631.37 | bwd_inner_microstep: 631.35 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.89 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 830 +[2025-05-01 22:42:41,155] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 99.56 | bwd_microstep: 237.45 | bwd_inner_microstep: 237.43 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-01 22:42:42,055] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 424.16 | bwd_microstep: 443.82 | bwd_inner_microstep: 443.81 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-01 22:42:43,297] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 4.15 | optimizer_step: 22.05 +[2025-05-01 22:42:43,298] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 397.97 | bwd_microstep: 787.89 | bwd_inner_microstep: 467.34 | bwd_allreduce_microstep: 320.50 | step_microstep: 31.85 +[2025-05-01 22:42:43,299] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 5198.11 | bwd: 8043.41 | bwd_inner: 7722.59 | bwd_allreduce: 320.58 | step: 63.55 + 2%|▏ | 181/8720 [27:17<30:44:52, 12.96s/it] {'loss': 1.9363, 'grad_norm': 5.796255588531494, 'learning_rate': 6.908396946564886e-06, 'epoch': 0.21} + 2%|▏ | 181/8720 [27:17<30:44:52, 12.96s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1893 +[2025-05-01 22:42:44,224] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 431.13 | bwd_microstep: 449.81 | bwd_inner_microstep: 449.80 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-01 22:42:45,141] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 431.87 | bwd_microstep: 448.75 | bwd_inner_microstep: 448.74 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-01 22:42:46,055] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 428.96 | bwd_microstep: 451.34 | bwd_inner_microstep: 451.32 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-01 22:42:46,966] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 372.98 | bwd_microstep: 503.93 | bwd_inner_microstep: 503.91 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-01 22:42:47,855] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 323.82 | bwd_microstep: 530.23 | bwd_inner_microstep: 530.21 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.28 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1103 +[2025-05-01 22:42:48,341] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 218.43 | bwd_microstep: 235.86 | bwd_inner_microstep: 235.84 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.32 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 333 +[2025-05-01 22:42:48,622] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 106.61 | bwd_microstep: 139.30 | bwd_inner_microstep: 139.28 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.54 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 339 +[2025-05-01 22:42:48,867] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 105.80 | bwd_microstep: 107.41 | bwd_inner_microstep: 107.10 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 22:42:49,751] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 344.37 | bwd_microstep: 518.42 | bwd_inner_microstep: 518.40 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.22 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-01 22:42:50,634] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 358.65 | bwd_microstep: 504.87 | bwd_inner_microstep: 504.86 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 22:42:51,513] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 382.29 | bwd_microstep: 479.02 | bwd_inner_microstep: 479.00 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 839 +[2025-05-01 22:42:52,010] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 194.95 | bwd_microstep: 285.74 | bwd_inner_microstep: 285.72 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.39 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 22:42:52,913] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 284.66 | bwd_microstep: 585.97 | bwd_inner_microstep: 585.95 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 22:42:53,816] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 241.89 | bwd_microstep: 627.36 | bwd_inner_microstep: 627.34 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 831 +[2025-05-01 22:42:54,184] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 104.26 | bwd_microstep: 231.69 | bwd_inner_microstep: 231.67 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.53 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 22:42:55,469] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 5.73 | optimizer_step: 17.96 +[2025-05-01 22:42:55,469] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 423.92 | bwd_microstep: 802.49 | bwd_inner_microstep: 445.66 | bwd_allreduce_microstep: 356.77 | step_microstep: 29.69 +[2025-05-01 22:42:55,471] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4754.51 | bwd: 6902.25 | bwd_inner: 6544.87 | bwd_allreduce: 356.97 | step: 56.38 + 2%|▏ | 182/8720 [27:29<30:10:46, 12.73s/it] {'loss': 2.0286, 'grad_norm': 7.932190418243408, 'learning_rate': 6.946564885496184e-06, 'epoch': 0.21} + 2%|▏ | 182/8720 [27:29<30:10:46, 12.73s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1971 +[2025-05-01 22:42:56,448] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 448.48 | bwd_microstep: 489.98 | bwd_inner_microstep: 489.96 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1891 +[2025-05-01 22:42:57,364] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 428.54 | bwd_microstep: 453.53 | bwd_inner_microstep: 453.51 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-01 22:42:58,276] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 408.52 | bwd_microstep: 469.73 | bwd_inner_microstep: 469.71 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.47 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1365 +[2025-05-01 22:42:58,932] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 309.40 | bwd_microstep: 314.39 | bwd_inner_microstep: 314.38 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-01 22:42:59,833] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 423.70 | bwd_microstep: 445.34 | bwd_inner_microstep: 445.32 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-01 22:43:00,732] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 403.28 | bwd_microstep: 467.67 | bwd_inner_microstep: 467.65 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.46 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 22:43:01,639] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 358.10 | bwd_microstep: 516.74 | bwd_inner_microstep: 516.72 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.32 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-01 22:43:02,551] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 306.22 | bwd_microstep: 571.17 | bwd_inner_microstep: 571.16 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 22:43:03,438] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 252.84 | bwd_microstep: 600.39 | bwd_inner_microstep: 600.37 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.31 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 22:43:04,338] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 236.01 | bwd_microstep: 629.35 | bwd_inner_microstep: 629.33 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 321 +[2025-05-01 22:43:04,565] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 73.12 | bwd_microstep: 130.63 | bwd_inner_microstep: 130.61 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 22:43:05,458] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 426.99 | bwd_microstep: 431.90 | bwd_inner_microstep: 431.89 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 22:43:06,357] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 421.69 | bwd_microstep: 442.56 | bwd_inner_microstep: 442.54 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 22:43:07,246] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 420.96 | bwd_microstep: 437.09 | bwd_inner_microstep: 437.07 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.02 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 830 +[2025-05-01 22:43:07,706] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 219.50 | bwd_microstep: 215.02 | bwd_inner_microstep: 214.76 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.13 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 22:43:08,699] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.45 | optimizer_step: 18.60 +[2025-05-01 22:43:08,701] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 345.11 | bwd_microstep: 600.72 | bwd_inner_microstep: 515.41 | bwd_allreduce_microstep: 85.29 | step_microstep: 28.20 +[2025-05-01 22:43:08,702] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 5482.43 | bwd: 7216.23 | bwd_inner: 7130.50 | bwd_allreduce: 85.42 | step: 58.90 + 2%|▏ | 183/8720 [27:42<30:32:19, 12.88s/it] {'loss': 2.1244, 'grad_norm': 10.006179809570312, 'learning_rate': 6.984732824427481e-06, 'epoch': 0.21} + 2%|▏ | 183/8720 [27:42<30:32:19, 12.88s/it]dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1387 +[2025-05-01 22:43:09,387] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 322.29 | bwd_microstep: 324.43 | bwd_inner_microstep: 324.30 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-01 22:43:10,268] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 416.41 | bwd_microstep: 448.48 | bwd_inner_microstep: 448.47 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-01 22:43:11,176] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 427.61 | bwd_microstep: 449.86 | bwd_inner_microstep: 449.84 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-01 22:43:12,082] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 429.01 | bwd_microstep: 442.47 | bwd_inner_microstep: 442.45 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-01 22:43:12,996] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 424.23 | bwd_microstep: 456.15 | bwd_inner_microstep: 456.13 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 324 +[2025-05-01 22:43:13,268] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 100.42 | bwd_microstep: 139.78 | bwd_inner_microstep: 139.77 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-01 22:43:14,164] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 235.52 | bwd_microstep: 628.25 | bwd_inner_microstep: 628.23 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-01 22:43:15,059] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 251.81 | bwd_microstep: 613.53 | bwd_inner_microstep: 613.51 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.02 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 22:43:15,928] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 237.29 | bwd_microstep: 613.82 | bwd_inner_microstep: 613.80 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 22:43:16,807] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 248.23 | bwd_microstep: 612.38 | bwd_inner_microstep: 612.36 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.20 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 320 +[2025-05-01 22:43:17,026] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 77.41 | bwd_microstep: 125.96 | bwd_inner_microstep: 125.92 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 22:43:17,932] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 423.73 | bwd_microstep: 450.23 | bwd_inner_microstep: 450.21 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 22:43:18,831] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 424.65 | bwd_microstep: 440.05 | bwd_inner_microstep: 440.03 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 22:43:19,727] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 419.65 | bwd_microstep: 448.44 | bwd_inner_microstep: 448.42 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1934 +[2025-05-01 22:43:20,667] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 381.37 | bwd_microstep: 526.35 | bwd_inner_microstep: 526.33 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 324 +[2025-05-01 22:43:21,079] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 6.07 | optimizer_step: 25.74 +[2025-05-01 22:43:21,080] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 100.97 | bwd_microstep: 244.79 | bwd_inner_microstep: 118.38 | bwd_allreduce_microstep: 126.30 | step_microstep: 37.27 +[2025-05-01 22:43:21,081] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4920.56 | bwd: 6964.99 | bwd_inner: 6838.22 | bwd_allreduce: 126.42 | step: 64.26 + 2%|▏ | 184/8720 [27:54<30:10:49, 12.73s/it] {'loss': 1.6808, 'grad_norm': 7.68690824508667, 'learning_rate': 7.022900763358779e-06, 'epoch': 0.21} + 2%|▏ | 184/8720 [27:54<30:10:49, 12.73s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1909 +[2025-05-01 22:43:22,000] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 428.76 | bwd_microstep: 447.26 | bwd_inner_microstep: 447.24 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1912 +[2025-05-01 22:43:22,917] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 429.56 | bwd_microstep: 455.18 | bwd_inner_microstep: 455.16 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1921 +[2025-05-01 22:43:23,853] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 405.97 | bwd_microstep: 500.14 | bwd_inner_microstep: 500.12 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1899 +[2025-05-01 22:43:24,765] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 338.32 | bwd_microstep: 541.56 | bwd_inner_microstep: 541.54 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.47 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1887 +[2025-05-01 22:43:25,658] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 284.53 | bwd_microstep: 573.85 | bwd_inner_microstep: 573.83 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.52 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-01 22:43:26,569] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 249.93 | bwd_microstep: 626.83 | bwd_inner_microstep: 626.81 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-01 22:43:27,464] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 231.43 | bwd_microstep: 630.59 | bwd_inner_microstep: 630.57 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.40 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-01 22:43:28,343] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 248.49 | bwd_microstep: 611.88 | bwd_inner_microstep: 611.86 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.02 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-01 22:43:29,221] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 246.95 | bwd_microstep: 612.36 | bwd_inner_microstep: 612.35 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.01 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 22:43:30,107] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 262.39 | bwd_microstep: 601.14 | bwd_inner_microstep: 601.12 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 842 +[2025-05-01 22:43:30,504] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 97.98 | bwd_microstep: 278.09 | bwd_inner_microstep: 278.07 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.32 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-01 22:43:31,406] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 395.17 | bwd_microstep: 472.66 | bwd_inner_microstep: 472.64 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 836 +[2025-05-01 22:43:31,816] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 214.45 | bwd_microstep: 166.17 | bwd_inner_microstep: 166.08 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 22:43:32,717] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 400.43 | bwd_microstep: 482.18 | bwd_inner_microstep: 482.16 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.38 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-01 22:43:33,475] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 274.89 | bwd_microstep: 463.43 | bwd_inner_microstep: 463.41 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 315 +[2025-05-01 22:43:33,960] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.55 | optimizer_step: 18.47 +[2025-05-01 22:43:33,962] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 100.92 | bwd_microstep: 328.24 | bwd_inner_microstep: 149.50 | bwd_allreduce_microstep: 178.61 | step_microstep: 28.27 +[2025-05-01 22:43:33,963] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4610.12 | bwd: 7791.57 | bwd_inner: 7612.56 | bwd_allreduce: 178.70 | step: 51.31 + 2%|▏ | 185/8720 [28:07<30:17:10, 12.77s/it] {'loss': 2.0273, 'grad_norm': 8.367592811584473, 'learning_rate': 7.061068702290077e-06, 'epoch': 0.21} + 2%|▏ | 185/8720 [28:07<30:17:10, 12.77s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2067 +[2025-05-01 22:43:34,857] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 322.14 | bwd_microstep: 529.13 | bwd_inner_microstep: 529.12 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1982 +[2025-05-01 22:43:35,700] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 298.31 | bwd_microstep: 511.04 | bwd_inner_microstep: 511.02 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.32 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1944 +[2025-05-01 22:43:36,349] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 230.22 | bwd_microstep: 385.78 | bwd_inner_microstep: 385.76 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.69 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-01 22:43:37,130] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 293.92 | bwd_microstep: 470.44 | bwd_inner_microstep: 470.42 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.23 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-01 22:43:37,839] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 288.17 | bwd_microstep: 386.50 | bwd_inner_microstep: 386.48 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-01 22:43:38,606] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 253.91 | bwd_microstep: 480.42 | bwd_inner_microstep: 480.40 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.72 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-01 22:43:39,330] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 297.11 | bwd_microstep: 407.53 | bwd_inner_microstep: 407.51 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 22:43:40,199] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 345.30 | bwd_microstep: 491.78 | bwd_inner_microstep: 491.76 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 22:43:41,054] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 372.79 | bwd_microstep: 463.18 | bwd_inner_microstep: 463.16 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.33 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 22:43:41,833] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 283.34 | bwd_microstep: 461.76 | bwd_inner_microstep: 461.74 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.36 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 834 +[2025-05-01 22:43:42,220] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 196.43 | bwd_microstep: 160.00 | bwd_inner_microstep: 159.83 | bwd_allreduce_microstep: 0.08 | step_microstep: 0.13 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1350 +[2025-05-01 22:43:42,869] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 302.93 | bwd_microstep: 329.44 | bwd_inner_microstep: 329.42 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.51 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 835 +[2025-05-01 22:43:43,258] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 196.22 | bwd_microstep: 163.39 | bwd_inner_microstep: 163.37 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 22:43:44,115] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 333.35 | bwd_microstep: 490.56 | bwd_inner_microstep: 490.54 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 22:43:44,970] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 341.53 | bwd_microstep: 493.79 | bwd_inner_microstep: 493.77 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1919 +[2025-05-01 22:43:46,039] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.07 | optimizer_gradients: 2.51 | optimizer_step: 16.89 +[2025-05-01 22:43:46,040] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 283.17 | bwd_microstep: 729.81 | bwd_inner_microstep: 473.20 | bwd_allreduce_microstep: 256.56 | step_microstep: 25.50 +[2025-05-01 22:43:46,042] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4638.78 | bwd: 6954.59 | bwd_inner: 6697.55 | bwd_allreduce: 256.72 | step: 48.63 + 2%|▏ | 186/8720 [28:19<29:47:18, 12.57s/it] {'loss': 1.7994, 'grad_norm': 8.477560997009277, 'learning_rate': 7.0992366412213746e-06, 'epoch': 0.21} + 2%|▏ | 186/8720 [28:19<29:47:18, 12.57s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-01 22:43:46,955] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 398.00 | bwd_microstep: 489.20 | bwd_inner_microstep: 489.18 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.56 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-01 22:43:47,729] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 274.39 | bwd_microstep: 479.52 | bwd_inner_microstep: 479.50 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1883 +[2025-05-01 22:43:48,558] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 302.46 | bwd_microstep: 495.09 | bwd_inner_microstep: 495.07 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-01 22:43:49,469] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 398.50 | bwd_microstep: 492.05 | bwd_inner_microstep: 492.03 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.88 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-01 22:43:50,246] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 274.33 | bwd_microstep: 483.77 | bwd_inner_microstep: 483.74 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.33 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-01 22:43:51,065] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 294.35 | bwd_microstep: 493.03 | bwd_inner_microstep: 492.97 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.23 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1351 +[2025-05-01 22:43:51,717] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 307.00 | bwd_microstep: 327.71 | bwd_inner_microstep: 327.70 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-01 22:43:52,529] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 291.79 | bwd_microstep: 491.39 | bwd_inner_microstep: 491.37 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-01 22:43:53,408] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 392.88 | bwd_microstep: 465.69 | bwd_inner_microstep: 465.67 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-01 22:43:54,191] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 278.59 | bwd_microstep: 471.91 | bwd_inner_microstep: 471.89 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 22:43:55,024] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 312.98 | bwd_microstep: 494.02 | bwd_inner_microstep: 493.91 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.13 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 22:43:55,902] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 393.04 | bwd_microstep: 463.32 | bwd_inner_microstep: 463.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 832 +[2025-05-01 22:43:56,281] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 102.59 | bwd_microstep: 245.51 | bwd_inner_microstep: 245.49 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.47 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 832 +[2025-05-01 22:43:56,690] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 153.05 | bwd_microstep: 226.19 | bwd_inner_microstep: 226.17 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 22:43:57,486] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 276.29 | bwd_microstep: 487.84 | bwd_inner_microstep: 487.83 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.47 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 22:43:58,491] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.35 | optimizer_step: 31.26 +[2025-05-01 22:43:58,492] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 363.20 | bwd_microstep: 571.83 | bwd_inner_microstep: 490.39 | bwd_allreduce_microstep: 81.31 | step_microstep: 39.14 +[2025-05-01 22:43:58,493] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4813.17 | bwd: 7178.14 | bwd_inner: 7096.28 | bwd_allreduce: 81.43 | step: 60.24 + 2%|▏ | 187/8720 [28:32<29:42:08, 12.53s/it] {'loss': 1.4001, 'grad_norm': 6.676255226135254, 'learning_rate': 7.137404580152672e-06, 'epoch': 0.21} + 2%|▏ | 187/8720 [28:32<29:42:08, 12.53s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2168 +[2025-05-01 22:43:59,445] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 331.15 | bwd_microstep: 579.55 | bwd_inner_microstep: 579.53 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.33 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1895 +[2025-05-01 22:44:00,299] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 328.86 | bwd_microstep: 496.49 | bwd_inner_microstep: 496.47 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-01 22:44:01,142] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 353.47 | bwd_microstep: 471.49 | bwd_inner_microstep: 471.47 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.31 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-01 22:44:01,930] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 285.23 | bwd_microstep: 468.09 | bwd_inner_microstep: 468.07 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 346 +[2025-05-01 22:44:02,191] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.13 | bwd_microstep: 137.94 | bwd_inner_microstep: 137.92 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.20 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1109 +[2025-05-01 22:44:02,693] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 121.70 | bwd_microstep: 363.60 | bwd_inner_microstep: 363.58 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-01 22:44:03,471] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 276.56 | bwd_microstep: 482.24 | bwd_inner_microstep: 482.22 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-01 22:44:04,296] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 287.46 | bwd_microstep: 497.61 | bwd_inner_microstep: 497.59 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1352 +[2025-05-01 22:44:04,944] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 287.27 | bwd_microstep: 341.33 | bwd_inner_microstep: 341.31 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 22:44:05,765] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 295.04 | bwd_microstep: 491.69 | bwd_inner_microstep: 491.62 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.11 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 835 +[2025-05-01 22:44:06,214] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.30 | bwd_microstep: 243.44 | bwd_inner_microstep: 243.29 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 22:44:07,044] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 341.42 | bwd_microstep: 465.25 | bwd_inner_microstep: 465.23 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.30 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 22:44:07,811] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 273.09 | bwd_microstep: 462.55 | bwd_inner_microstep: 462.53 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 315 +[2025-05-01 22:44:08,056] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 90.91 | bwd_microstep: 126.11 | bwd_inner_microstep: 126.09 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-01 22:44:08,861] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 296.21 | bwd_microstep: 476.42 | bwd_inner_microstep: 476.40 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 22:44:10,021] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.08 | optimizer_gradients: 2.39 | optimizer_step: 30.13 +[2025-05-01 22:44:10,022] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 300.69 | bwd_microstep: 790.34 | bwd_inner_microstep: 492.24 | bwd_allreduce_microstep: 298.04 | step_microstep: 39.05 +[2025-05-01 22:44:10,023] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4150.39 | bwd: 6894.18 | bwd_inner: 6595.62 | bwd_allreduce: 298.21 | step: 58.66 + 2%|▏ | 188/8720 [28:43<28:59:06, 12.23s/it] {'loss': 1.7111, 'grad_norm': 5.203697681427002, 'learning_rate': 7.17557251908397e-06, 'epoch': 0.22} + 2%|▏ | 188/8720 [28:43<28:59:06, 12.23s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1888 +[2025-05-01 22:44:10,831] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 280.94 | bwd_microstep: 489.53 | bwd_inner_microstep: 489.51 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-01 22:44:11,743] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 403.71 | bwd_microstep: 490.00 | bwd_inner_microstep: 489.98 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.93 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-01 22:44:12,519] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 277.44 | bwd_microstep: 481.08 | bwd_inner_microstep: 481.06 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.16 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-01 22:44:13,332] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 296.24 | bwd_microstep: 490.34 | bwd_inner_microstep: 490.31 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-01 22:44:14,241] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 408.37 | bwd_microstep: 480.80 | bwd_inner_microstep: 480.78 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.32 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-01 22:44:15,018] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 274.82 | bwd_microstep: 482.80 | bwd_inner_microstep: 482.79 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-01 22:44:15,844] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 299.36 | bwd_microstep: 496.05 | bwd_inner_microstep: 496.04 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-01 22:44:16,729] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 371.79 | bwd_microstep: 495.32 | bwd_inner_microstep: 495.31 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-01 22:44:17,505] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 279.34 | bwd_microstep: 470.58 | bwd_inner_microstep: 470.56 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 22:44:18,338] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 311.16 | bwd_microstep: 495.17 | bwd_inner_microstep: 495.15 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-01 22:44:19,225] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 396.38 | bwd_microstep: 467.94 | bwd_inner_microstep: 467.92 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 22:44:20,048] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 315.08 | bwd_microstep: 482.09 | bwd_inner_microstep: 482.07 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-01 22:44:20,866] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 315.53 | bwd_microstep: 484.51 | bwd_inner_microstep: 484.49 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 22:44:21,647] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 273.40 | bwd_microstep: 488.87 | bwd_inner_microstep: 488.85 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 22:44:22,456] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 287.40 | bwd_microstep: 487.82 | bwd_inner_microstep: 487.79 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.13 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1910 +[2025-05-01 22:44:23,507] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.78 | optimizer_step: 20.12 +[2025-05-01 22:44:23,509] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 401.12 | bwd_microstep: 599.28 | bwd_inner_microstep: 474.12 | bwd_allreduce_microstep: 125.10 | step_microstep: 31.53 +[2025-05-01 22:44:23,510] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 5191.95 | bwd: 7882.22 | bwd_inner: 7756.75 | bwd_allreduce: 125.19 | step: 46.28 + 2%|▏ | 189/8720 [28:57<29:52:37, 12.61s/it] {'loss': 1.9482, 'grad_norm': 6.871744155883789, 'learning_rate': 7.213740458015268e-06, 'epoch': 0.22} + 2%|▏ | 189/8720 [28:57<29:52:37, 12.61s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1914 +[2025-05-01 22:44:24,394] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 349.94 | bwd_microstep: 494.19 | bwd_inner_microstep: 494.17 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-01 22:44:25,212] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 320.66 | bwd_microstep: 475.41 | bwd_inner_microstep: 475.39 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-01 22:44:25,996] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 271.74 | bwd_microstep: 482.44 | bwd_inner_microstep: 482.42 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1883 +[2025-05-01 22:44:26,895] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 396.39 | bwd_microstep: 482.81 | bwd_inner_microstep: 482.79 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.91 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-01 22:44:27,667] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 275.19 | bwd_microstep: 477.83 | bwd_inner_microstep: 477.81 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1365 +[2025-05-01 22:44:28,344] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 252.57 | bwd_microstep: 393.36 | bwd_inner_microstep: 393.34 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-01 22:44:29,143] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 297.38 | bwd_microstep: 477.83 | bwd_inner_microstep: 477.81 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-01 22:44:29,911] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 275.98 | bwd_microstep: 457.66 | bwd_inner_microstep: 457.64 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.49 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 22:44:30,792] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 358.19 | bwd_microstep: 491.17 | bwd_inner_microstep: 491.15 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 22:44:31,598] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 301.52 | bwd_microstep: 483.81 | bwd_inner_microstep: 483.79 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.54 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 22:44:32,380] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 306.72 | bwd_microstep: 457.56 | bwd_inner_microstep: 457.54 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 22:44:33,209] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 302.85 | bwd_microstep: 493.63 | bwd_inner_microstep: 493.61 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.48 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 830 +[2025-05-01 22:44:33,625] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 201.28 | bwd_microstep: 186.24 | bwd_inner_microstep: 186.11 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.12 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 827 +[2025-05-01 22:44:34,078] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 180.49 | bwd_microstep: 252.69 | bwd_inner_microstep: 252.54 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 22:44:34,896] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 335.16 | bwd_microstep: 461.48 | bwd_inner_microstep: 461.46 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.15 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 22:44:36,007] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.39 | optimizer_step: 17.20 +[2025-05-01 22:44:36,007] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 369.19 | bwd_microstep: 687.98 | bwd_inner_microstep: 474.25 | bwd_allreduce_microstep: 213.68 | step_microstep: 25.86 +[2025-05-01 22:44:36,009] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4795.12 | bwd: 7256.15 | bwd_inner: 7041.89 | bwd_allreduce: 213.89 | step: 45.41 + 2%|▏ | 190/8720 [29:09<29:47:43, 12.57s/it] {'loss': 1.1794, 'grad_norm': 5.482785701751709, 'learning_rate': 7.251908396946566e-06, 'epoch': 0.22} + 2%|▏ | 190/8720 [29:09<29:47:43, 12.57s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1934 +[2025-05-01 22:44:36,943] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 411.74 | bwd_microstep: 499.46 | bwd_inner_microstep: 499.44 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.89 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 348 +[2025-05-01 22:44:37,149] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 67.56 | bwd_microstep: 123.13 | bwd_inner_microstep: 122.86 | bwd_allreduce_microstep: 0.10 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1893 +[2025-05-01 22:44:38,030] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 415.62 | bwd_microstep: 448.85 | bwd_inner_microstep: 448.84 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1367 +[2025-05-01 22:44:38,766] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 250.04 | bwd_microstep: 468.24 | bwd_inner_microstep: 468.22 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-01 22:44:39,581] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.65 | bwd_microstep: 596.48 | bwd_inner_microstep: 596.46 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1105 +[2025-05-01 22:44:39,985] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 152.66 | bwd_microstep: 218.70 | bwd_inner_microstep: 218.69 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-01 22:44:40,806] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 420.90 | bwd_microstep: 368.33 | bwd_inner_microstep: 368.31 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.49 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-01 22:44:41,640] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 428.82 | bwd_microstep: 372.66 | bwd_inner_microstep: 372.64 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1351 +[2025-05-01 22:44:42,384] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 310.86 | bwd_microstep: 407.86 | bwd_inner_microstep: 407.71 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.21 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 22:44:43,266] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 264.88 | bwd_microstep: 597.79 | bwd_inner_microstep: 597.77 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 22:44:44,106] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 198.10 | bwd_microstep: 621.26 | bwd_inner_microstep: 621.24 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 22:44:44,931] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 201.21 | bwd_microstep: 593.48 | bwd_inner_microstep: 593.46 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 22:44:45,735] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 232.14 | bwd_microstep: 538.91 | bwd_inner_microstep: 538.90 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.33 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 22:44:46,536] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 281.50 | bwd_microstep: 485.80 | bwd_inner_microstep: 485.78 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.47 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 22:44:47,334] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 337.65 | bwd_microstep: 426.40 | bwd_inner_microstep: 426.38 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 22:44:48,562] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.07 | optimizer_gradients: 2.37 | optimizer_step: 16.78 +[2025-05-01 22:44:48,563] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 391.64 | bwd_microstep: 779.06 | bwd_inner_microstep: 427.24 | bwd_allreduce_microstep: 351.78 | step_microstep: 25.45 +[2025-05-01 22:44:48,564] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4560.90 | bwd: 7546.51 | bwd_inner: 7194.02 | bwd_allreduce: 352.04 | step: 48.28 + 2%|▏ | 191/8720 [29:22<29:46:43, 12.57s/it] {'loss': 1.581, 'grad_norm': 8.441939353942871, 'learning_rate': 7.290076335877863e-06, 'epoch': 0.22} + 2%|▏ | 191/8720 [29:22<29:46:43, 12.57s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1950 +[2025-05-01 22:44:49,467] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 413.51 | bwd_microstep: 465.64 | bwd_inner_microstep: 465.62 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 866 +[2025-05-01 22:44:49,974] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.63 | bwd_microstep: 300.01 | bwd_inner_microstep: 299.99 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 875 +[2025-05-01 22:44:50,331] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.07 | bwd_microstep: 136.49 | bwd_inner_microstep: 136.32 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.12 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 351 +[2025-05-01 22:44:50,594] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 98.54 | bwd_microstep: 143.51 | bwd_inner_microstep: 143.49 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-01 22:44:51,431] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 419.84 | bwd_microstep: 392.19 | bwd_inner_microstep: 392.17 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.49 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-01 22:44:51,945] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 193.05 | bwd_microstep: 288.79 | bwd_inner_microstep: 288.77 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-01 22:44:52,439] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.95 | bwd_microstep: 289.25 | bwd_inner_microstep: 289.23 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1353 +[2025-05-01 22:44:53,012] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 301.65 | bwd_microstep: 255.71 | bwd_inner_microstep: 255.54 | bwd_allreduce_microstep: 0.09 | step_microstep: 0.10 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1347 +[2025-05-01 22:44:53,737] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 238.50 | bwd_microstep: 469.05 | bwd_inner_microstep: 469.03 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-01 22:44:54,537] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 200.08 | bwd_microstep: 574.77 | bwd_inner_microstep: 574.75 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-01 22:44:55,281] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 250.85 | bwd_microstep: 461.09 | bwd_inner_microstep: 461.07 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 22:44:55,970] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 283.30 | bwd_microstep: 387.13 | bwd_inner_microstep: 387.11 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-01 22:44:56,843] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 426.76 | bwd_microstep: 427.68 | bwd_inner_microstep: 427.66 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 22:44:57,723] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 378.48 | bwd_microstep: 482.93 | bwd_inner_microstep: 482.91 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-01 22:44:58,603] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 342.02 | bwd_microstep: 519.75 | bwd_inner_microstep: 519.73 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 22:44:59,625] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.35 | optimizer_step: 16.60 +[2025-05-01 22:44:59,626] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 285.91 | bwd_microstep: 693.42 | bwd_inner_microstep: 576.08 | bwd_allreduce_microstep: 117.29 | step_microstep: 24.25 +[2025-05-01 22:44:59,627] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4397.97 | bwd: 6287.46 | bwd_inner: 6169.53 | bwd_allreduce: 117.55 | step: 37.08 + 2%|▏ | 192/8720 [29:33<28:42:10, 12.12s/it] {'loss': 1.9053, 'grad_norm': 8.358100891113281, 'learning_rate': 7.328244274809161e-06, 'epoch': 0.22} + 2%|▏ | 192/8720 [29:33<28:42:10, 12.12s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 420 +[2025-05-01 22:44:59,929] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 102.33 | bwd_microstep: 178.78 | bwd_inner_microstep: 178.76 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1906 +[2025-05-01 22:45:00,770] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 403.29 | bwd_microstep: 408.64 | bwd_inner_microstep: 408.62 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1901 +[2025-05-01 22:45:01,599] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 422.69 | bwd_microstep: 374.16 | bwd_inner_microstep: 374.14 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-01 22:45:02,408] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 422.68 | bwd_microstep: 352.94 | bwd_inner_microstep: 352.92 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-01 22:45:03,222] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 429.64 | bwd_microstep: 352.35 | bwd_inner_microstep: 352.33 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-01 22:45:04,085] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 423.17 | bwd_microstep: 411.83 | bwd_inner_microstep: 411.81 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.22 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-01 22:45:04,961] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 425.00 | bwd_microstep: 415.03 | bwd_inner_microstep: 415.01 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 22:45:05,841] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 428.37 | bwd_microstep: 418.21 | bwd_inner_microstep: 418.19 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.31 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1344 +[2025-05-01 22:45:06,538] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 315.83 | bwd_microstep: 351.12 | bwd_inner_microstep: 351.00 | bwd_allreduce_microstep: 0.08 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 22:45:07,414] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 309.20 | bwd_microstep: 551.12 | bwd_inner_microstep: 551.11 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 830 +[2025-05-01 22:45:07,765] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.00 | bwd_microstep: 238.22 | bwd_inner_microstep: 238.20 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.32 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 319 +[2025-05-01 22:45:08,012] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 80.64 | bwd_microstep: 133.31 | bwd_inner_microstep: 133.29 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1343 +[2025-05-01 22:45:08,584] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 230.34 | bwd_microstep: 309.73 | bwd_inner_microstep: 309.71 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 22:45:09,444] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 418.85 | bwd_microstep: 407.50 | bwd_inner_microstep: 407.49 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 22:45:10,314] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 419.10 | bwd_microstep: 417.08 | bwd_inner_microstep: 417.06 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 22:45:11,573] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.07 | optimizer_gradients: 5.32 | optimizer_step: 20.28 +[2025-05-01 22:45:11,574] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 420.33 | bwd_microstep: 778.24 | bwd_inner_microstep: 424.33 | bwd_allreduce_microstep: 353.84 | step_microstep: 32.27 +[2025-05-01 22:45:11,575] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 5345.39 | bwd: 6098.29 | bwd_inner: 5743.99 | bwd_allreduce: 354.01 | step: 57.16 + 2%|▏ | 193/8720 [29:45<28:34:47, 12.07s/it] {'loss': 1.2815, 'grad_norm': 5.857755184173584, 'learning_rate': 7.366412213740458e-06, 'epoch': 0.22} + 2%|▏ | 193/8720 [29:45<28:34:47, 12.07s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-01 22:45:12,458] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 362.82 | bwd_microstep: 498.23 | bwd_inner_microstep: 498.21 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-01 22:45:13,341] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 321.43 | bwd_microstep: 542.52 | bwd_inner_microstep: 542.50 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1883 +[2025-05-01 22:45:14,222] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 271.46 | bwd_microstep: 591.00 | bwd_inner_microstep: 590.98 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-01 22:45:15,068] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 204.40 | bwd_microstep: 620.79 | bwd_inner_microstep: 620.77 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-01 22:45:15,878] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 199.45 | bwd_microstep: 582.03 | bwd_inner_microstep: 582.01 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-01 22:45:16,704] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 246.26 | bwd_microstep: 544.38 | bwd_inner_microstep: 544.36 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.56 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 22:45:17,523] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 283.73 | bwd_microstep: 503.72 | bwd_inner_microstep: 503.70 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 22:45:18,357] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 323.24 | bwd_microstep: 477.16 | bwd_inner_microstep: 477.14 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.51 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-01 22:45:19,181] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 347.89 | bwd_microstep: 444.60 | bwd_inner_microstep: 444.58 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 22:45:20,004] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 378.42 | bwd_microstep: 409.94 | bwd_inner_microstep: 409.92 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 834 +[2025-05-01 22:45:20,476] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 215.25 | bwd_microstep: 234.14 | bwd_inner_microstep: 233.89 | bwd_allreduce_microstep: 0.14 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 22:45:21,347] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 231.11 | bwd_microstep: 620.22 | bwd_inner_microstep: 620.20 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.32 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 22:45:22,150] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 193.53 | bwd_microstep: 588.40 | bwd_inner_microstep: 588.38 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 22:45:22,963] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 230.49 | bwd_microstep: 545.89 | bwd_inner_microstep: 545.87 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 22:45:23,767] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 277.82 | bwd_microstep: 494.29 | bwd_inner_microstep: 494.27 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2116 +[2025-05-01 22:45:25,010] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 5.39 | optimizer_step: 23.80 +[2025-05-01 22:45:25,010] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 341.80 | bwd_microstep: 834.34 | bwd_inner_microstep: 620.04 | bwd_allreduce_microstep: 214.25 | step_microstep: 34.87 +[2025-05-01 22:45:25,011] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4428.99 | bwd: 8531.67 | bwd_inner: 8316.84 | bwd_allreduce: 214.45 | step: 59.34 + 2%|▏ | 194/8720 [29:58<29:32:58, 12.48s/it] {'loss': 1.7602, 'grad_norm': 10.46890926361084, 'learning_rate': 7.404580152671757e-06, 'epoch': 0.22} + 2%|▏ | 194/8720 [29:58<29:32:58, 12.48s/it]dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1150 +[2025-05-01 22:45:25,658] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 250.91 | bwd_microstep: 374.06 | bwd_inner_microstep: 374.04 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.54 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1924 +[2025-05-01 22:45:26,569] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 226.72 | bwd_microstep: 651.13 | bwd_inner_microstep: 651.11 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.43 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-01 22:45:27,389] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 196.12 | bwd_microstep: 604.61 | bwd_inner_microstep: 604.59 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 848 +[2025-05-01 22:45:27,681] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 127.56 | bwd_microstep: 134.59 | bwd_inner_microstep: 134.47 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-01 22:45:28,553] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 428.50 | bwd_microstep: 425.77 | bwd_inner_microstep: 425.75 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-01 22:45:29,435] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 380.03 | bwd_microstep: 485.20 | bwd_inner_microstep: 485.18 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-01 22:45:30,313] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 349.81 | bwd_microstep: 511.93 | bwd_inner_microstep: 511.86 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.04 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1101 +[2025-05-01 22:45:30,891] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.98 | bwd_microstep: 368.97 | bwd_inner_microstep: 368.95 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 22:45:31,763] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 269.05 | bwd_microstep: 571.79 | bwd_inner_microstep: 571.77 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 331 +[2025-05-01 22:45:32,025] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 98.38 | bwd_microstep: 132.12 | bwd_inner_microstep: 131.76 | bwd_allreduce_microstep: 0.14 | step_microstep: 0.23 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 22:45:32,898] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 338.21 | bwd_microstep: 518.45 | bwd_inner_microstep: 518.43 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 6, images per sample: 6.0, dynamic token length: 1607 +[2025-05-01 22:45:33,725] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 264.07 | bwd_microstep: 545.72 | bwd_inner_microstep: 545.70 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 22:45:34,597] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 234.53 | bwd_microstep: 617.05 | bwd_inner_microstep: 617.03 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.99 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 22:45:35,446] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 206.63 | bwd_microstep: 622.39 | bwd_inner_microstep: 622.37 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 22:45:36,277] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 199.48 | bwd_microstep: 601.86 | bwd_inner_microstep: 601.84 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 22:45:37,346] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.59 | optimizer_step: 17.38 +[2025-05-01 22:45:37,347] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 214.46 | bwd_microstep: 796.02 | bwd_inner_microstep: 578.60 | bwd_allreduce_microstep: 217.37 | step_microstep: 25.31 +[2025-05-01 22:45:37,348] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 3975.30 | bwd: 7961.73 | bwd_inner: 7743.56 | bwd_allreduce: 217.67 | step: 42.87 + 2%|▏ | 195/8720 [30:11<29:26:46, 12.43s/it] {'loss': 1.3241, 'grad_norm': 7.816981792449951, 'learning_rate': 7.4427480916030536e-06, 'epoch': 0.22} + 2%|▏ | 195/8720 [30:11<29:26:46, 12.43s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 488 +[2025-05-01 22:45:37,643] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 91.10 | bwd_microstep: 183.52 | bwd_inner_microstep: 183.50 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1915 +[2025-05-01 22:45:38,514] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 402.95 | bwd_microstep: 430.94 | bwd_inner_microstep: 430.92 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.33 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 378 +[2025-05-01 22:45:38,802] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 108.67 | bwd_microstep: 152.19 | bwd_inner_microstep: 152.17 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-01 22:45:39,628] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 208.69 | bwd_microstep: 583.01 | bwd_inner_microstep: 582.99 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.52 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-01 22:45:40,459] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 239.95 | bwd_microstep: 557.25 | bwd_inner_microstep: 557.23 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.33 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 845 +[2025-05-01 22:45:40,793] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 168.79 | bwd_microstep: 134.71 | bwd_inner_microstep: 134.67 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-01 22:45:41,674] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 385.72 | bwd_microstep: 475.86 | bwd_inner_microstep: 475.84 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.27 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-01 22:45:42,552] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 335.91 | bwd_microstep: 524.25 | bwd_inner_microstep: 524.23 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-01 22:45:43,437] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 272.24 | bwd_microstep: 592.14 | bwd_inner_microstep: 592.13 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1094 +[2025-05-01 22:45:43,877] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 117.05 | bwd_microstep: 301.13 | bwd_inner_microstep: 301.12 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 834 +[2025-05-01 22:45:44,340] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 215.92 | bwd_microstep: 214.29 | bwd_inner_microstep: 214.14 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 22:45:45,223] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 255.72 | bwd_microstep: 606.15 | bwd_inner_microstep: 606.13 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 22:45:46,051] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.74 | bwd_microstep: 614.84 | bwd_inner_microstep: 614.82 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.53 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 22:45:46,756] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 204.71 | bwd_microstep: 465.99 | bwd_inner_microstep: 465.97 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-01 22:45:47,494] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 323.59 | bwd_microstep: 395.34 | bwd_inner_microstep: 395.32 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-01 22:45:48,526] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 4.32 | optimizer_step: 17.44 +[2025-05-01 22:45:48,526] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 282.45 | bwd_microstep: 692.88 | bwd_inner_microstep: 575.41 | bwd_allreduce_microstep: 117.42 | step_microstep: 27.30 +[2025-05-01 22:45:48,527] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 3804.03 | bwd: 6924.55 | bwd_inner: 6806.64 | bwd_allreduce: 117.57 | step: 47.08 + 2%|▏ | 196/8720 [30:22<28:33:06, 12.06s/it] {'loss': 1.4713, 'grad_norm': 5.388935089111328, 'learning_rate': 7.480916030534352e-06, 'epoch': 0.22} + 2%|▏ | 196/8720 [30:22<28:33:06, 12.06s/it]dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1389 +[2025-05-01 22:45:49,195] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 294.22 | bwd_microstep: 351.88 | bwd_inner_microstep: 351.72 | bwd_allreduce_microstep: 0.08 | step_microstep: 0.10 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1396 +[2025-05-01 22:45:49,856] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 261.19 | bwd_microstep: 385.17 | bwd_inner_microstep: 385.15 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1895 +[2025-05-01 22:45:50,743] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 299.16 | bwd_microstep: 569.87 | bwd_inner_microstep: 569.85 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.15 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1894 +[2025-05-01 22:45:51,632] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 257.67 | bwd_microstep: 609.23 | bwd_inner_microstep: 609.22 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.21 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1887 +[2025-05-01 22:45:52,506] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 220.81 | bwd_microstep: 627.10 | bwd_inner_microstep: 627.08 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.48 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 345 +[2025-05-01 22:45:52,737] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 92.58 | bwd_microstep: 115.94 | bwd_inner_microstep: 115.60 | bwd_allreduce_microstep: 0.14 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-01 22:45:53,608] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 428.61 | bwd_microstep: 419.68 | bwd_inner_microstep: 419.66 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1352 +[2025-05-01 22:45:54,366] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 290.60 | bwd_microstep: 446.14 | bwd_inner_microstep: 446.11 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 22:45:55,200] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.66 | bwd_microstep: 621.78 | bwd_inner_microstep: 621.76 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 22:45:55,904] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 203.63 | bwd_microstep: 469.64 | bwd_inner_microstep: 469.62 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 22:45:56,663] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 340.18 | bwd_microstep: 398.75 | bwd_inner_microstep: 398.74 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 22:45:57,500] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 259.09 | bwd_microstep: 542.14 | bwd_inner_microstep: 542.12 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.32 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 22:45:58,316] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 277.02 | bwd_microstep: 504.87 | bwd_inner_microstep: 504.85 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-01 22:45:59,141] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 315.54 | bwd_microstep: 475.17 | bwd_inner_microstep: 475.15 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.51 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1341 +[2025-05-01 22:45:59,702] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 299.63 | bwd_microstep: 230.91 | bwd_inner_microstep: 230.89 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 22:46:01,034] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.37 | optimizer_step: 29.70 +[2025-05-01 22:46:01,034] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 427.55 | bwd_microstep: 835.44 | bwd_inner_microstep: 368.92 | bwd_allreduce_microstep: 466.36 | step_microstep: 37.52 +[2025-05-01 22:46:01,036] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4457.99 | bwd: 7603.81 | bwd_inner: 7136.61 | bwd_allreduce: 466.58 | step: 55.45 + 2%|▏ | 197/8720 [30:34<28:52:01, 12.19s/it] {'loss': 1.9375, 'grad_norm': 9.052539825439453, 'learning_rate': 7.519083969465649e-06, 'epoch': 0.23} + 2%|▏ | 197/8720 [30:34<28:52:01, 12.19s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 389 +[2025-05-01 22:46:01,274] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 71.97 | bwd_microstep: 145.57 | bwd_inner_microstep: 145.55 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1923 +[2025-05-01 22:46:02,139] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 436.55 | bwd_microstep: 394.53 | bwd_inner_microstep: 394.52 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1922 +[2025-05-01 22:46:03,005] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 435.14 | bwd_microstep: 398.19 | bwd_inner_microstep: 398.17 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1886 +[2025-05-01 22:46:03,843] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 428.69 | bwd_microstep: 374.80 | bwd_inner_microstep: 374.78 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.52 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-01 22:46:04,665] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 429.46 | bwd_microstep: 361.09 | bwd_inner_microstep: 361.07 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1362 +[2025-05-01 22:46:05,353] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 287.53 | bwd_microstep: 384.15 | bwd_inner_microstep: 383.98 | bwd_allreduce_microstep: 0.10 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-01 22:46:06,236] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 269.67 | bwd_microstep: 595.78 | bwd_inner_microstep: 595.76 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-01 22:46:07,089] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 207.98 | bwd_microstep: 625.26 | bwd_inner_microstep: 625.24 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 22:46:07,902] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 199.37 | bwd_microstep: 590.58 | bwd_inner_microstep: 590.56 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.52 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 839 +[2025-05-01 22:46:08,197] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 137.40 | bwd_microstep: 129.01 | bwd_inner_microstep: 129.00 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 328 +[2025-05-01 22:46:08,457] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 104.23 | bwd_microstep: 141.04 | bwd_inner_microstep: 141.03 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 22:46:09,292] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 399.03 | bwd_microstep: 406.85 | bwd_inner_microstep: 406.83 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-01 22:46:10,105] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 418.77 | bwd_microstep: 365.99 | bwd_inner_microstep: 365.97 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 22:46:10,839] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 232.48 | bwd_microstep: 466.78 | bwd_inner_microstep: 466.76 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 22:46:11,641] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 198.74 | bwd_microstep: 576.41 | bwd_inner_microstep: 576.37 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 22:46:12,729] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.07 | optimizer_gradients: 2.45 | optimizer_step: 16.77 +[2025-05-01 22:46:12,729] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 244.62 | bwd_microstep: 787.59 | bwd_inner_microstep: 511.90 | bwd_allreduce_microstep: 275.64 | step_microstep: 24.63 +[2025-05-01 22:46:12,730] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4501.56 | bwd: 6743.63 | bwd_inner: 6467.51 | bwd_allreduce: 275.81 | step: 48.97 + 2%|▏ | 198/8720 [30:46<28:30:37, 12.04s/it] {'loss': 1.6007, 'grad_norm': 6.6840362548828125, 'learning_rate': 7.557251908396948e-06, 'epoch': 0.23} + 2%|▏ | 198/8720 [30:46<28:30:37, 12.04s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1886 +[2025-05-01 22:46:13,617] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 368.09 | bwd_microstep: 497.15 | bwd_inner_microstep: 497.13 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 867 +[2025-05-01 22:46:14,036] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 98.29 | bwd_microstep: 304.06 | bwd_inner_microstep: 304.04 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 345 +[2025-05-01 22:46:14,311] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 101.40 | bwd_microstep: 143.39 | bwd_inner_microstep: 143.37 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 22:46:15,143] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 201.73 | bwd_microstep: 599.26 | bwd_inner_microstep: 599.24 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 22:46:15,959] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 222.55 | bwd_microstep: 560.05 | bwd_inner_microstep: 560.03 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 22:46:16,794] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 263.31 | bwd_microstep: 538.27 | bwd_inner_microstep: 538.25 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.54 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-01 22:46:17,618] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 285.80 | bwd_microstep: 504.84 | bwd_inner_microstep: 504.82 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.48 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 22:46:18,496] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 316.17 | bwd_microstep: 525.42 | bwd_inner_microstep: 525.40 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 22:46:19,365] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 297.05 | bwd_microstep: 537.67 | bwd_inner_microstep: 537.65 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.47 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 22:46:20,226] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 284.07 | bwd_microstep: 542.36 | bwd_inner_microstep: 542.34 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1345 +[2025-05-01 22:46:20,788] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 231.56 | bwd_microstep: 297.58 | bwd_inner_microstep: 297.56 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.50 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 321 +[2025-05-01 22:46:21,061] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 102.82 | bwd_microstep: 138.99 | bwd_inner_microstep: 138.97 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.33 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 22:46:21,856] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 273.43 | bwd_microstep: 487.90 | bwd_inner_microstep: 487.88 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-01 22:46:22,666] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 336.47 | bwd_microstep: 439.13 | bwd_inner_microstep: 439.11 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 22:46:23,488] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 381.78 | bwd_microstep: 404.98 | bwd_inner_microstep: 404.97 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1994 +[2025-05-01 22:46:24,795] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 5.20 | optimizer_step: 34.93 +[2025-05-01 22:46:24,796] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 429.39 | bwd_microstep: 802.86 | bwd_inner_microstep: 448.69 | bwd_allreduce_microstep: 354.12 | step_microstep: 45.97 +[2025-05-01 22:46:24,797] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4193.88 | bwd: 7323.93 | bwd_inner: 6969.49 | bwd_allreduce: 354.20 | step: 79.46 + 2%|▏ | 199/8720 [30:58<28:31:21, 12.05s/it] {'loss': 1.4296, 'grad_norm': 8.189401626586914, 'learning_rate': 7.595419847328245e-06, 'epoch': 0.23} + 2%|▏ | 199/8720 [30:58<28:31:21, 12.05s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1894 +[2025-05-01 22:46:25,678] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 346.74 | bwd_microstep: 514.46 | bwd_inner_microstep: 514.44 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-01 22:46:26,561] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 328.43 | bwd_microstep: 535.68 | bwd_inner_microstep: 535.66 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-01 22:46:27,447] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 279.21 | bwd_microstep: 585.10 | bwd_inner_microstep: 585.08 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-01 22:46:28,318] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 236.05 | bwd_microstep: 615.11 | bwd_inner_microstep: 615.09 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.22 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-01 22:46:29,175] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 209.82 | bwd_microstep: 627.79 | bwd_inner_microstep: 627.77 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-01 22:46:30,029] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 209.87 | bwd_microstep: 621.70 | bwd_inner_microstep: 621.68 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 840 +[2025-05-01 22:46:30,346] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 102.19 | bwd_microstep: 184.07 | bwd_inner_microstep: 184.05 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.32 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-01 22:46:31,172] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 424.87 | bwd_microstep: 364.94 | bwd_inner_microstep: 364.92 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 22:46:32,006] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 427.36 | bwd_microstep: 372.66 | bwd_inner_microstep: 372.64 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.31 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 835 +[2025-05-01 22:46:32,537] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 206.35 | bwd_microstep: 292.80 | bwd_inner_microstep: 292.78 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 22:46:33,354] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 218.99 | bwd_microstep: 561.19 | bwd_inner_microstep: 561.17 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 831 +[2025-05-01 22:46:33,693] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 161.14 | bwd_microstep: 145.27 | bwd_inner_microstep: 145.25 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 22:46:34,542] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 419.30 | bwd_microstep: 397.88 | bwd_inner_microstep: 397.86 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 22:46:35,396] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 345.21 | bwd_microstep: 479.01 | bwd_inner_microstep: 478.99 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.32 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 22:46:36,210] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 243.47 | bwd_microstep: 536.39 | bwd_inner_microstep: 536.37 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2244 +[2025-05-01 22:46:37,419] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.07 | optimizer_gradients: 2.48 | optimizer_step: 17.25 +[2025-05-01 22:46:37,419] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 304.19 | bwd_microstep: 847.14 | bwd_inner_microstep: 639.44 | bwd_allreduce_microstep: 207.63 | step_microstep: 26.30 +[2025-05-01 22:46:37,420] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4463.11 | bwd: 7681.20 | bwd_inner: 7473.22 | bwd_allreduce: 207.72 | step: 51.19 + 2%|▏ | 200/8720 [31:11<28:55:34, 12.22s/it] {'loss': 1.9004, 'grad_norm': 7.4916605949401855, 'learning_rate': 7.633587786259543e-06, 'epoch': 0.23} + 2%|▏ | 200/8720 [31:11<28:55:34, 12.22s/it][INFO|trainer.py:3503] 2025-05-01 22:46:40,629 >> Saving model checkpoint to work_dirs/internvl_chat_v2_5/ak/checkpoint-200 +[INFO|configuration_utils.py:472] 2025-05-01 22:46:40,632 >> Configuration saved in work_dirs/internvl_chat_v2_5/ak/checkpoint-200/config.json +[INFO|configuration_utils.py:807] 2025-05-01 22:46:40,633 >> Configuration saved in work_dirs/internvl_chat_v2_5/ak/checkpoint-200/generation_config.json +[INFO|modeling_utils.py:2755] 2025-05-01 22:46:46,012 >> Model weights saved in work_dirs/internvl_chat_v2_5/ak/checkpoint-200/model.safetensors +[INFO|tokenization_utils_base.py:2702] 2025-05-01 22:46:46,014 >> tokenizer config file saved in work_dirs/internvl_chat_v2_5/ak/checkpoint-200/tokenizer_config.json +[INFO|tokenization_utils_base.py:2711] 2025-05-01 22:46:46,014 >> Special tokens file saved in work_dirs/internvl_chat_v2_5/ak/checkpoint-200/special_tokens_map.json +[INFO|tokenization_utils_base.py:2762] 2025-05-01 22:46:46,014 >> added tokens file saved in work_dirs/internvl_chat_v2_5/ak/checkpoint-200/added_tokens.json +[2025-05-01 22:46:46,176] [INFO] [logging.py:96:log_dist] [Rank 0] [Torch] Checkpoint global_step200 is about to be saved! +[2025-05-01 22:46:46,197] [INFO] [logging.py:96:log_dist] [Rank 0] Saving model checkpoint: work_dirs/internvl_chat_v2_5/ak/checkpoint-200/global_step200/mp_rank_00_model_states.pt +[2025-05-01 22:46:46,197] [INFO] [torch_checkpoint_engine.py:21:save] [Torch] Saving work_dirs/internvl_chat_v2_5/ak/checkpoint-200/global_step200/mp_rank_00_model_states.pt... +[2025-05-01 22:46:51,058] [INFO] [torch_checkpoint_engine.py:23:save] [Torch] Saved work_dirs/internvl_chat_v2_5/ak/checkpoint-200/global_step200/mp_rank_00_model_states.pt. +[2025-05-01 22:46:51,059] [INFO] [torch_checkpoint_engine.py:21:save] [Torch] Saving work_dirs/internvl_chat_v2_5/ak/checkpoint-200/global_step200/bf16_zero_pp_rank_0_mp_rank_00_optim_states.pt... +[2025-05-01 22:46:51,262] [INFO] [torch_checkpoint_engine.py:23:save] [Torch] Saved work_dirs/internvl_chat_v2_5/ak/checkpoint-200/global_step200/bf16_zero_pp_rank_0_mp_rank_00_optim_states.pt. +[2025-05-01 22:46:51,262] [INFO] [engine.py:3536:_save_zero_checkpoint] zero checkpoint saved work_dirs/internvl_chat_v2_5/ak/checkpoint-200/global_step200/bf16_zero_pp_rank_0_mp_rank_00_optim_states.pt +[2025-05-01 22:46:51,262] [INFO] [torch_checkpoint_engine.py:33:commit] [Torch] Checkpoint global_step200 is ready now! +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1935 +[2025-05-01 22:46:52,156] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 414.91 | bwd_microstep: 463.91 | bwd_inner_microstep: 463.90 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 341 +[2025-05-01 22:46:52,399] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 83.72 | bwd_microstep: 143.01 | bwd_inner_microstep: 142.99 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-01 22:46:53,290] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 427.33 | bwd_microstep: 430.27 | bwd_inner_microstep: 430.25 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 846 +[2025-05-01 22:46:53,760] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 226.13 | bwd_microstep: 214.64 | bwd_inner_microstep: 214.62 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-01 22:46:54,642] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 319.07 | bwd_microstep: 544.30 | bwd_inner_microstep: 544.28 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-01 22:46:55,521] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 315.22 | bwd_microstep: 545.39 | bwd_inner_microstep: 545.37 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.13 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 22:46:56,406] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 250.31 | bwd_microstep: 613.94 | bwd_inner_microstep: 613.92 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 22:46:57,227] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.90 | bwd_microstep: 609.22 | bwd_inner_microstep: 609.20 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1351 +[2025-05-01 22:46:57,840] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 200.54 | bwd_microstep: 378.65 | bwd_inner_microstep: 378.57 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 22:46:58,744] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 393.17 | bwd_microstep: 488.98 | bwd_inner_microstep: 488.96 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.19 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 834 +[2025-05-01 22:46:59,185] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 173.02 | bwd_microstep: 248.70 | bwd_inner_microstep: 248.47 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 22:47:00,090] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 377.32 | bwd_microstep: 503.37 | bwd_inner_microstep: 503.35 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.91 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 22:47:00,962] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 336.42 | bwd_microstep: 513.99 | bwd_inner_microstep: 513.97 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 22:47:01,822] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 317.85 | bwd_microstep: 514.37 | bwd_inner_microstep: 514.35 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.49 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 315 +[2025-05-01 22:47:02,064] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 83.63 | bwd_microstep: 124.42 | bwd_inner_microstep: 124.40 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-01 22:47:03,214] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.38 | optimizer_step: 18.66 +[2025-05-01 22:47:03,217] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 319.60 | bwd_microstep: 778.28 | bwd_inner_microstep: 513.92 | bwd_allreduce_microstep: 264.35 | step_microstep: 28.13 +[2025-05-01 22:47:03,218] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4428.96 | bwd: 7115.48 | bwd_inner: 6850.56 | bwd_allreduce: 264.55 | step: 44.12 + 2%|▏ | 201/8720 [31:36<38:33:43, 16.30s/it] {'loss': 0.9499, 'grad_norm': 5.236041069030762, 'learning_rate': 7.671755725190841e-06, 'epoch': 0.23} + 2%|▏ | 201/8720 [31:36<38:33:43, 16.30s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1887 +[2025-05-01 22:47:04,096] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 313.57 | bwd_microstep: 522.32 | bwd_inner_microstep: 522.30 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.33 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1904 +[2025-05-01 22:47:04,977] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 332.99 | bwd_microstep: 519.89 | bwd_inner_microstep: 519.87 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.55 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1099 +[2025-05-01 22:47:05,537] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 232.63 | bwd_microstep: 300.38 | bwd_inner_microstep: 300.36 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.50 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-01 22:47:06,391] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 315.31 | bwd_microstep: 506.59 | bwd_inner_microstep: 506.57 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-01 22:47:07,224] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 378.53 | bwd_microstep: 437.02 | bwd_inner_microstep: 437.00 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 22:47:08,100] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 328.71 | bwd_microstep: 512.22 | bwd_inner_microstep: 512.21 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 325 +[2025-05-01 22:47:08,337] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 100.30 | bwd_microstep: 110.46 | bwd_inner_microstep: 110.31 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.09 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1093 +[2025-05-01 22:47:08,844] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 216.58 | bwd_microstep: 270.26 | bwd_inner_microstep: 270.24 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 328 +[2025-05-01 22:47:09,109] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.90 | bwd_microstep: 138.69 | bwd_inner_microstep: 138.67 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.28 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 22:47:09,960] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 311.30 | bwd_microstep: 513.46 | bwd_inner_microstep: 513.44 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.31 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 834 +[2025-05-01 22:47:10,375] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 120.54 | bwd_microstep: 261.22 | bwd_inner_microstep: 261.20 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 22:47:11,234] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 312.44 | bwd_microstep: 514.30 | bwd_inner_microstep: 514.28 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 22:47:12,056] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 303.91 | bwd_microstep: 486.00 | bwd_inner_microstep: 485.98 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-01 22:47:12,961] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 398.62 | bwd_microstep: 487.31 | bwd_inner_microstep: 487.29 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 22:47:13,791] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 361.95 | bwd_microstep: 450.40 | bwd_inner_microstep: 450.38 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 22:47:15,014] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.07 | optimizer_gradients: 5.28 | optimizer_step: 22.66 +[2025-05-01 22:47:15,014] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 389.79 | bwd_microstep: 781.67 | bwd_inner_microstep: 486.78 | bwd_allreduce_microstep: 294.85 | step_microstep: 33.54 +[2025-05-01 22:47:15,016] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4510.99 | bwd: 6812.22 | bwd_inner: 6516.95 | bwd_allreduce: 294.99 | step: 57.61 + 2%|▏ | 202/8720 [31:48<35:21:45, 14.95s/it] {'loss': 1.7564, 'grad_norm': 7.370326042175293, 'learning_rate': 7.709923664122137e-06, 'epoch': 0.23} + 2%|▏ | 202/8720 [31:48<35:21:45, 14.95s/it]dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1377 +[2025-05-01 22:47:15,715] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 312.47 | bwd_microstep: 364.46 | bwd_inner_microstep: 364.44 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1889 +[2025-05-01 22:47:16,582] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 317.35 | bwd_microstep: 514.59 | bwd_inner_microstep: 514.57 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 346 +[2025-05-01 22:47:16,830] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.84 | bwd_microstep: 120.33 | bwd_inner_microstep: 120.31 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-01 22:47:17,702] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 337.34 | bwd_microstep: 501.10 | bwd_inner_microstep: 501.08 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1349 +[2025-05-01 22:47:18,399] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 296.22 | bwd_microstep: 368.08 | bwd_inner_microstep: 368.06 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-01 22:47:19,200] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 306.95 | bwd_microstep: 461.27 | bwd_inner_microstep: 461.25 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-01 22:47:20,050] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 334.28 | bwd_microstep: 485.45 | bwd_inner_microstep: 485.43 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-01 22:47:20,531] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.94 | bwd_microstep: 273.20 | bwd_inner_microstep: 273.19 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 22:47:21,330] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 274.09 | bwd_microstep: 505.01 | bwd_inner_microstep: 504.99 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 834 +[2025-05-01 22:47:21,753] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 155.93 | bwd_microstep: 238.41 | bwd_inner_microstep: 238.13 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.19 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1346 +[2025-05-01 22:47:22,404] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 256.11 | bwd_microstep: 373.08 | bwd_inner_microstep: 373.06 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.31 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 22:47:23,274] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 331.55 | bwd_microstep: 509.23 | bwd_inner_microstep: 509.21 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 22:47:24,135] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 325.98 | bwd_microstep: 503.35 | bwd_inner_microstep: 503.33 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.21 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 22:47:24,954] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 299.50 | bwd_microstep: 501.60 | bwd_inner_microstep: 501.59 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 22:47:25,813] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 337.40 | bwd_microstep: 485.19 | bwd_inner_microstep: 485.17 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 22:47:27,040] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 4.44 | optimizer_step: 28.43 +[2025-05-01 22:47:27,040] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 396.78 | bwd_microstep: 774.34 | bwd_inner_microstep: 486.08 | bwd_allreduce_microstep: 288.22 | step_microstep: 38.52 +[2025-05-01 22:47:27,041] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4567.64 | bwd: 6978.77 | bwd_inner: 6689.92 | bwd_allreduce: 288.42 | step: 62.51 + 2%|▏ | 203/8720 [32:00<33:17:10, 14.07s/it] {'loss': 2.1007, 'grad_norm': 7.429559230804443, 'learning_rate': 7.748091603053436e-06, 'epoch': 0.23} + 2%|▏ | 203/8720 [32:00<33:17:10, 14.07s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1896 +[2025-05-01 22:47:27,939] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 374.65 | bwd_microstep: 488.65 | bwd_inner_microstep: 488.63 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.33 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 356 +[2025-05-01 22:47:28,193] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 104.70 | bwd_microstep: 117.15 | bwd_inner_microstep: 117.13 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.33 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-01 22:47:29,093] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 334.48 | bwd_microstep: 526.77 | bwd_inner_microstep: 526.75 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.32 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-01 22:47:29,941] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 307.05 | bwd_microstep: 510.00 | bwd_inner_microstep: 509.98 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.28 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1366 +[2025-05-01 22:47:30,595] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 221.56 | bwd_microstep: 405.38 | bwd_inner_microstep: 405.27 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-01 22:47:31,500] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 384.83 | bwd_microstep: 501.95 | bwd_inner_microstep: 501.93 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.16 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-01 22:47:32,391] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 352.84 | bwd_microstep: 514.62 | bwd_inner_microstep: 514.59 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.55 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-01 22:47:33,234] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 314.28 | bwd_microstep: 507.51 | bwd_inner_microstep: 507.49 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.47 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-01 22:47:34,087] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 305.99 | bwd_microstep: 513.05 | bwd_inner_microstep: 513.03 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-01 22:47:34,952] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 320.58 | bwd_microstep: 510.56 | bwd_inner_microstep: 510.54 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.33 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-01 22:47:35,824] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 325.54 | bwd_microstep: 505.30 | bwd_inner_microstep: 505.28 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 22:47:36,686] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 316.71 | bwd_microstep: 511.44 | bwd_inner_microstep: 511.42 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.33 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 22:47:37,553] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 325.00 | bwd_microstep: 510.92 | bwd_inner_microstep: 510.90 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.51 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 22:47:38,419] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 318.94 | bwd_microstep: 514.62 | bwd_inner_microstep: 514.60 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.29 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 22:47:39,297] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 330.26 | bwd_microstep: 515.36 | bwd_inner_microstep: 515.34 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 22:47:40,469] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 9.71 | optimizer_step: 23.89 +[2025-05-01 22:47:40,470] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 329.13 | bwd_microstep: 776.65 | bwd_inner_microstep: 507.51 | bwd_allreduce_microstep: 269.12 | step_microstep: 40.21 +[2025-05-01 22:47:40,471] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4966.48 | bwd: 7929.91 | bwd_inner: 7660.41 | bwd_allreduce: 269.23 | step: 71.28 + 2%|▏ | 204/8720 [32:14<32:49:54, 13.88s/it] {'loss': 1.6046, 'grad_norm': 5.6798858642578125, 'learning_rate': 7.786259541984733e-06, 'epoch': 0.23} + 2%|▏ | 204/8720 [32:14<32:49:54, 13.88s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1978 +[2025-05-01 22:47:41,401] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 346.72 | bwd_microstep: 539.45 | bwd_inner_microstep: 539.43 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.33 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 368 +[2025-05-01 22:47:41,654] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 100.84 | bwd_microstep: 120.84 | bwd_inner_microstep: 120.82 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.33 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1926 +[2025-05-01 22:47:42,567] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 345.77 | bwd_microstep: 532.33 | bwd_inner_microstep: 532.31 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1890 +[2025-05-01 22:47:43,460] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 348.02 | bwd_microstep: 511.99 | bwd_inner_microstep: 511.97 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.96 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1889 +[2025-05-01 22:47:44,321] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 321.02 | bwd_microstep: 518.37 | bwd_inner_microstep: 518.35 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.54 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-01 22:47:45,195] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 314.77 | bwd_microstep: 521.79 | bwd_inner_microstep: 521.78 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-01 22:47:46,059] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 307.45 | bwd_microstep: 522.42 | bwd_inner_microstep: 522.40 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-01 22:47:46,919] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 314.01 | bwd_microstep: 511.80 | bwd_inner_microstep: 511.78 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 326 +[2025-05-01 22:47:47,174] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.79 | bwd_microstep: 126.99 | bwd_inner_microstep: 126.97 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1349 +[2025-05-01 22:47:47,884] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 288.69 | bwd_microstep: 391.34 | bwd_inner_microstep: 391.32 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 22:47:48,706] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 310.79 | bwd_microstep: 489.84 | bwd_inner_microstep: 489.83 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.18 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 842 +[2025-05-01 22:47:49,150] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 196.73 | bwd_microstep: 227.73 | bwd_inner_microstep: 227.71 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.28 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 320 +[2025-05-01 22:47:49,380] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 84.71 | bwd_microstep: 122.31 | bwd_inner_microstep: 122.29 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1342 +[2025-05-01 22:47:50,023] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 239.29 | bwd_microstep: 379.23 | bwd_inner_microstep: 379.21 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-01 22:47:50,888] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 318.36 | bwd_microstep: 514.84 | bwd_inner_microstep: 514.82 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.49 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 22:47:52,044] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.38 | optimizer_step: 23.53 +[2025-05-01 22:47:52,045] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 334.24 | bwd_microstep: 761.48 | bwd_inner_microstep: 466.30 | bwd_allreduce_microstep: 295.14 | step_microstep: 31.39 +[2025-05-01 22:47:52,046] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4267.17 | bwd: 6792.76 | bwd_inner: 6497.31 | bwd_allreduce: 295.22 | step: 64.26 + 2%|▏ | 205/8720 [32:25<31:11:23, 13.19s/it] {'loss': 2.0492, 'grad_norm': 5.466915130615234, 'learning_rate': 7.824427480916032e-06, 'epoch': 0.24} + 2%|▏ | 205/8720 [32:25<31:11:23, 13.19s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 362 +[2025-05-01 22:47:52,291] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 97.18 | bwd_microstep: 112.14 | bwd_inner_microstep: 112.00 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1890 +[2025-05-01 22:47:53,156] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 377.93 | bwd_microstep: 467.04 | bwd_inner_microstep: 467.02 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 346 +[2025-05-01 22:47:53,415] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 99.42 | bwd_microstep: 130.71 | bwd_inner_microstep: 130.69 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.49 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-01 22:47:54,319] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 347.77 | bwd_microstep: 523.32 | bwd_inner_microstep: 523.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.83 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 322 +[2025-05-01 22:47:54,547] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 86.35 | bwd_microstep: 123.92 | bwd_inner_microstep: 123.90 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.50 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 22:47:55,410] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 322.73 | bwd_microstep: 506.08 | bwd_inner_microstep: 506.06 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 22:47:56,278] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 327.36 | bwd_microstep: 519.64 | bwd_inner_microstep: 519.62 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 22:47:57,113] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 334.66 | bwd_microstep: 463.68 | bwd_inner_microstep: 463.66 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-01 22:47:57,971] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 343.00 | bwd_microstep: 481.03 | bwd_inner_microstep: 481.01 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 22:47:58,834] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 324.03 | bwd_microstep: 505.40 | bwd_inner_microstep: 505.38 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.84 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 22:47:59,671] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 315.93 | bwd_microstep: 504.09 | bwd_inner_microstep: 504.07 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.14 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 22:48:00,530] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 318.91 | bwd_microstep: 520.20 | bwd_inner_microstep: 520.18 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.30 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 22:48:01,396] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 343.91 | bwd_microstep: 487.24 | bwd_inner_microstep: 487.22 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.51 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 827 +[2025-05-01 22:48:01,799] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 145.56 | bwd_microstep: 228.37 | bwd_inner_microstep: 227.99 | bwd_allreduce_microstep: 0.15 | step_microstep: 0.22 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 3522 +[2025-05-01 22:48:03,260] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 509.44 | bwd_microstep: 928.61 | bwd_inner_microstep: 928.59 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.88 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-01 22:48:04,332] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.33 | optimizer_step: 18.72 +[2025-05-01 22:48:04,335] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 327.56 | bwd_microstep: 701.69 | bwd_inner_microstep: 466.03 | bwd_allreduce_microstep: 235.64 | step_microstep: 28.20 +[2025-05-01 22:48:04,336] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4621.64 | bwd: 7203.21 | bwd_inner: 6966.84 | bwd_allreduce: 235.91 | step: 50.49 + 2%|▏ | 206/8720 [32:38<30:33:02, 12.92s/it] {'loss': 1.372, 'grad_norm': 6.033512115478516, 'learning_rate': 7.862595419847328e-06, 'epoch': 0.24} + 2%|▏ | 206/8720 [32:38<30:33:02, 12.92s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1939 +[2025-05-01 22:48:05,190] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 339.96 | bwd_microstep: 488.56 | bwd_inner_microstep: 488.54 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1905 +[2025-05-01 22:48:06,088] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 344.32 | bwd_microstep: 524.00 | bwd_inner_microstep: 523.98 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-01 22:48:06,887] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 330.20 | bwd_microstep: 448.30 | bwd_inner_microstep: 448.23 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-01 22:48:07,745] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 401.52 | bwd_microstep: 439.44 | bwd_inner_microstep: 439.42 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-01 22:48:08,560] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 285.30 | bwd_microstep: 500.15 | bwd_inner_microstep: 500.13 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 837 +[2025-05-01 22:48:08,948] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 132.08 | bwd_microstep: 223.78 | bwd_inner_microstep: 223.76 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1096 +[2025-05-01 22:48:09,468] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 199.25 | bwd_microstep: 290.98 | bwd_inner_microstep: 290.96 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.32 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 325 +[2025-05-01 22:48:09,722] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 87.22 | bwd_microstep: 136.94 | bwd_inner_microstep: 136.74 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.20 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 837 +[2025-05-01 22:48:10,130] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 137.10 | bwd_microstep: 244.06 | bwd_inner_microstep: 244.05 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 22:48:10,977] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 336.03 | bwd_microstep: 476.91 | bwd_inner_microstep: 476.89 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.32 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 22:48:11,726] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 323.76 | bwd_microstep: 393.50 | bwd_inner_microstep: 393.48 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 22:48:12,421] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.34 | bwd_microstep: 490.27 | bwd_inner_microstep: 490.25 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 22:48:13,282] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 329.67 | bwd_microstep: 501.37 | bwd_inner_microstep: 501.35 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 22:48:14,152] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 328.13 | bwd_microstep: 523.92 | bwd_inner_microstep: 523.90 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-01 22:48:14,994] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 335.83 | bwd_microstep: 483.21 | bwd_inner_microstep: 483.19 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 22:48:16,140] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.36 | optimizer_step: 18.00 +[2025-05-01 22:48:16,140] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 322.06 | bwd_microstep: 766.43 | bwd_inner_microstep: 492.84 | bwd_allreduce_microstep: 273.54 | step_microstep: 26.33 +[2025-05-01 22:48:16,142] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4420.71 | bwd: 6931.85 | bwd_inner: 6657.75 | bwd_allreduce: 273.64 | step: 48.04 + 2%|▏ | 207/8720 [32:49<29:45:30, 12.58s/it] {'loss': 1.3226, 'grad_norm': 8.484189987182617, 'learning_rate': 7.900763358778627e-06, 'epoch': 0.24} + 2%|▏ | 207/8720 [32:49<29:45:30, 12.58s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1904 +[2025-05-01 22:48:17,018] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 330.40 | bwd_microstep: 520.52 | bwd_inner_microstep: 520.50 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 867 +[2025-05-01 22:48:17,398] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 101.28 | bwd_microstep: 258.66 | bwd_inner_microstep: 258.64 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-01 22:48:18,219] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 325.25 | bwd_microstep: 478.16 | bwd_inner_microstep: 478.14 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-01 22:48:19,039] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 317.68 | bwd_microstep: 482.51 | bwd_inner_microstep: 482.50 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-01 22:48:19,933] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 333.75 | bwd_microstep: 532.80 | bwd_inner_microstep: 532.78 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 22:48:20,695] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 274.20 | bwd_microstep: 465.35 | bwd_inner_microstep: 465.33 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 835 +[2025-05-01 22:48:21,050] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 145.61 | bwd_microstep: 177.98 | bwd_inner_microstep: 177.96 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 22:48:21,805] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 273.25 | bwd_microstep: 450.22 | bwd_inner_microstep: 450.20 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.32 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 22:48:22,658] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 328.93 | bwd_microstep: 490.20 | bwd_inner_microstep: 490.18 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.46 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 22:48:23,508] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 302.68 | bwd_microstep: 514.27 | bwd_inner_microstep: 514.25 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 22:48:24,317] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 322.66 | bwd_microstep: 453.93 | bwd_inner_microstep: 453.91 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 22:48:25,142] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 385.27 | bwd_microstep: 420.86 | bwd_inner_microstep: 420.84 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 316 +[2025-05-01 22:48:25,380] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.95 | bwd_microstep: 116.33 | bwd_inner_microstep: 116.16 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 22:48:26,273] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 370.05 | bwd_microstep: 503.56 | bwd_inner_microstep: 503.54 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 22:48:27,112] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 348.23 | bwd_microstep: 472.92 | bwd_inner_microstep: 472.90 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1988 +[2025-05-01 22:48:28,179] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 3.51 | optimizer_step: 19.13 +[2025-05-01 22:48:28,180] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 300.31 | bwd_microstep: 716.88 | bwd_inner_microstep: 567.40 | bwd_allreduce_microstep: 149.43 | step_microstep: 28.61 +[2025-05-01 22:48:28,181] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4554.42 | bwd: 7055.19 | bwd_inner: 6905.34 | bwd_allreduce: 149.56 | step: 45.96 + 2%|▏ | 208/8720 [33:01<29:22:04, 12.42s/it] {'loss': 1.4053, 'grad_norm': 7.475559711456299, 'learning_rate': 7.938931297709924e-06, 'epoch': 0.24} + 2%|▏ | 208/8720 [33:01<29:22:04, 12.42s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2113 +[2025-05-01 22:48:29,189] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 417.51 | bwd_microstep: 565.26 | bwd_inner_microstep: 565.24 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 457 +[2025-05-01 22:48:29,455] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.60 | bwd_microstep: 143.02 | bwd_inner_microstep: 142.69 | bwd_allreduce_microstep: 0.31 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1909 +[2025-05-01 22:48:30,357] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 343.58 | bwd_microstep: 526.61 | bwd_inner_microstep: 526.60 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.94 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1890 +[2025-05-01 22:48:31,194] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 323.95 | bwd_microstep: 494.31 | bwd_inner_microstep: 494.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-01 22:48:31,994] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 293.64 | bwd_microstep: 482.08 | bwd_inner_microstep: 482.06 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-01 22:48:32,849] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 353.70 | bwd_microstep: 482.50 | bwd_inner_microstep: 482.48 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.47 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 22:48:33,681] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 340.70 | bwd_microstep: 459.78 | bwd_inner_microstep: 459.76 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-01 22:48:34,565] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 337.50 | bwd_microstep: 512.02 | bwd_inner_microstep: 512.00 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 22:48:35,451] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 324.95 | bwd_microstep: 526.98 | bwd_inner_microstep: 526.96 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.31 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 22:48:36,314] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 306.17 | bwd_microstep: 523.00 | bwd_inner_microstep: 522.98 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.28 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 22:48:37,127] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 321.29 | bwd_microstep: 458.39 | bwd_inner_microstep: 458.37 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 22:48:37,984] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 324.72 | bwd_microstep: 501.12 | bwd_inner_microstep: 501.10 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.48 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 22:48:38,869] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 326.51 | bwd_microstep: 525.81 | bwd_inner_microstep: 525.80 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.32 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 829 +[2025-05-01 22:48:39,303] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 115.16 | bwd_microstep: 290.27 | bwd_inner_microstep: 290.25 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 318 +[2025-05-01 22:48:39,543] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 70.25 | bwd_microstep: 141.36 | bwd_inner_microstep: 141.34 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.75 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 22:48:40,736] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.29 | optimizer_step: 16.59 +[2025-05-01 22:48:40,737] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 317.59 | bwd_microstep: 823.56 | bwd_inner_microstep: 513.61 | bwd_allreduce_microstep: 309.91 | step_microstep: 25.04 +[2025-05-01 22:48:40,739] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4612.76 | bwd: 7456.10 | bwd_inner: 7145.56 | bwd_allreduce: 310.25 | step: 51.75 + 2%|▏ | 209/8720 [33:14<29:27:46, 12.46s/it] {'loss': 1.7657, 'grad_norm': 8.382423400878906, 'learning_rate': 7.977099236641223e-06, 'epoch': 0.24} + 2%|▏ | 209/8720 [33:14<29:27:46, 12.46s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 388 +[2025-05-01 22:48:41,026] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 109.14 | bwd_microstep: 154.09 | bwd_inner_microstep: 154.07 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.32 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 364 +[2025-05-01 22:48:41,280] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 77.92 | bwd_microstep: 146.85 | bwd_inner_microstep: 146.83 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1899 +[2025-05-01 22:48:42,151] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 325.34 | bwd_microstep: 521.28 | bwd_inner_microstep: 521.26 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1371 +[2025-05-01 22:48:42,790] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 281.20 | bwd_microstep: 327.19 | bwd_inner_microstep: 326.95 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.19 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1362 +[2025-05-01 22:48:43,483] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 306.48 | bwd_microstep: 359.39 | bwd_inner_microstep: 359.37 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.32 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-01 22:48:44,357] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 334.12 | bwd_microstep: 507.10 | bwd_inner_microstep: 507.08 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.92 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-01 22:48:45,175] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 307.67 | bwd_microstep: 492.71 | bwd_inner_microstep: 492.69 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-01 22:48:46,081] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 383.65 | bwd_microstep: 502.41 | bwd_inner_microstep: 502.39 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.20 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1098 +[2025-05-01 22:48:46,591] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 161.55 | bwd_microstep: 332.65 | bwd_inner_microstep: 332.61 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-01 22:48:47,460] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 339.33 | bwd_microstep: 509.60 | bwd_inner_microstep: 509.58 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1349 +[2025-05-01 22:48:48,068] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 215.96 | bwd_microstep: 362.66 | bwd_inner_microstep: 362.47 | bwd_allreduce_microstep: 0.10 | step_microstep: 0.17 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1089 +[2025-05-01 22:48:48,621] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 254.82 | bwd_microstep: 271.98 | bwd_inner_microstep: 271.96 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.70 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 22:48:49,482] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 334.21 | bwd_microstep: 506.72 | bwd_inner_microstep: 506.71 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 22:48:50,294] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 268.59 | bwd_microstep: 509.76 | bwd_inner_microstep: 509.74 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 22:48:51,128] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 315.56 | bwd_microstep: 492.47 | bwd_inner_microstep: 492.45 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-01 22:48:52,279] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.55 | optimizer_step: 18.47 +[2025-05-01 22:48:52,281] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 311.97 | bwd_microstep: 793.62 | bwd_inner_microstep: 500.71 | bwd_allreduce_microstep: 292.89 | step_microstep: 28.19 +[2025-05-01 22:48:52,282] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4327.43 | bwd: 6790.57 | bwd_inner: 6496.90 | bwd_allreduce: 293.24 | step: 46.41 + 2%|▏ | 210/8720 [33:26<28:48:28, 12.19s/it] {'loss': 1.7376, 'grad_norm': 8.640520095825195, 'learning_rate': 8.015267175572519e-06, 'epoch': 0.24} + 2%|▏ | 210/8720 [33:26<28:48:28, 12.19s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2136 +[2025-05-01 22:48:53,261] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 362.19 | bwd_microstep: 580.91 | bwd_inner_microstep: 580.89 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.50 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1917 +[2025-05-01 22:48:54,146] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 323.14 | bwd_microstep: 527.04 | bwd_inner_microstep: 527.02 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.36 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 357 +[2025-05-01 22:48:54,399] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 108.54 | bwd_microstep: 115.50 | bwd_inner_microstep: 115.32 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-01 22:48:55,307] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 379.96 | bwd_microstep: 508.62 | bwd_inner_microstep: 508.60 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.39 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1896 +[2025-05-01 22:48:56,151] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 311.72 | bwd_microstep: 512.95 | bwd_inner_microstep: 512.93 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.31 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 347 +[2025-05-01 22:48:56,408] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 90.38 | bwd_microstep: 134.68 | bwd_inner_microstep: 134.66 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-01 22:48:57,275] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 321.51 | bwd_microstep: 511.15 | bwd_inner_microstep: 511.13 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.53 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 841 +[2025-05-01 22:48:57,713] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 203.48 | bwd_microstep: 202.64 | bwd_inner_microstep: 202.62 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.32 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 22:48:58,573] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 337.12 | bwd_microstep: 491.25 | bwd_inner_microstep: 491.23 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.22 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-01 22:48:59,430] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 402.41 | bwd_microstep: 436.35 | bwd_inner_microstep: 436.33 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 22:49:00,308] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 374.87 | bwd_microstep: 475.50 | bwd_inner_microstep: 475.48 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 22:49:01,139] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 333.83 | bwd_microstep: 467.36 | bwd_inner_microstep: 467.34 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.31 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 22:49:02,002] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 328.81 | bwd_microstep: 501.88 | bwd_inner_microstep: 501.86 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.17 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1344 +[2025-05-01 22:49:02,693] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 247.61 | bwd_microstep: 417.67 | bwd_inner_microstep: 417.65 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.80 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 829 +[2025-05-01 22:49:03,119] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 123.23 | bwd_microstep: 284.60 | bwd_inner_microstep: 284.58 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 22:49:04,211] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.32 | optimizer_step: 17.30 +[2025-05-01 22:49:04,211] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 311.12 | bwd_microstep: 734.82 | bwd_inner_microstep: 503.93 | bwd_allreduce_microstep: 230.84 | step_microstep: 24.88 +[2025-05-01 22:49:04,212] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4559.86 | bwd: 6902.93 | bwd_inner: 6671.65 | bwd_allreduce: 230.97 | step: 47.83 + 2%|▏ | 211/8720 [33:37<28:37:14, 12.11s/it] {'loss': 1.8728, 'grad_norm': 7.1636271476745605, 'learning_rate': 8.053435114503817e-06, 'epoch': 0.24} + 2%|▏ | 211/8720 [33:37<28:37:14, 12.11s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1940 +[2025-05-01 22:49:04,845] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 198.77 | bwd_microstep: 410.39 | bwd_inner_microstep: 410.37 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1912 +[2025-05-01 22:49:05,706] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 323.87 | bwd_microstep: 505.85 | bwd_inner_microstep: 505.83 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1904 +[2025-05-01 22:49:06,581] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 331.24 | bwd_microstep: 513.10 | bwd_inner_microstep: 513.08 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1903 +[2025-05-01 22:49:07,464] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 328.91 | bwd_microstep: 523.93 | bwd_inner_microstep: 523.91 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.49 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1895 +[2025-05-01 22:49:08,325] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 320.05 | bwd_microstep: 507.60 | bwd_inner_microstep: 507.58 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.30 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 856 +[2025-05-01 22:49:08,774] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 201.69 | bwd_microstep: 211.13 | bwd_inner_microstep: 210.88 | bwd_allreduce_microstep: 0.23 | step_microstep: 2.33 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-01 22:49:09,648] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 341.16 | bwd_microstep: 501.13 | bwd_inner_microstep: 501.11 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-01 22:49:10,520] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 347.20 | bwd_microstep: 503.92 | bwd_inner_microstep: 503.90 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-01 22:49:11,387] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 319.35 | bwd_microstep: 513.63 | bwd_inner_microstep: 513.61 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1354 +[2025-05-01 22:49:12,011] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 225.41 | bwd_microstep: 363.94 | bwd_inner_microstep: 363.92 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.29 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 326 +[2025-05-01 22:49:12,244] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 99.30 | bwd_microstep: 104.27 | bwd_inner_microstep: 104.15 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 22:49:13,152] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 390.87 | bwd_microstep: 497.47 | bwd_inner_microstep: 497.45 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.97 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 22:49:13,989] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 314.07 | bwd_microstep: 503.08 | bwd_inner_microstep: 503.06 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 22:49:14,834] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 307.96 | bwd_microstep: 502.62 | bwd_inner_microstep: 502.60 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-01 22:49:15,684] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 312.88 | bwd_microstep: 503.47 | bwd_inner_microstep: 503.46 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 22:49:16,750] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.45 | optimizer_step: 18.54 +[2025-05-01 22:49:16,752] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 317.55 | bwd_microstep: 691.44 | bwd_inner_microstep: 526.54 | bwd_allreduce_microstep: 164.88 | step_microstep: 28.27 +[2025-05-01 22:49:16,753] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4680.21 | bwd: 7356.98 | bwd_inner: 7191.51 | bwd_allreduce: 164.99 | step: 55.41 + 2%|▏ | 212/8720 [33:50<28:55:32, 12.24s/it] {'loss': 1.2749, 'grad_norm': 5.375995635986328, 'learning_rate': 8.091603053435115e-06, 'epoch': 0.24} + 2%|▏ | 212/8720 [33:50<28:55:32, 12.24s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1927 +[2025-05-01 22:49:17,662] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 338.28 | bwd_microstep: 533.04 | bwd_inner_microstep: 533.02 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1912 +[2025-05-01 22:49:18,535] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 323.15 | bwd_microstep: 514.15 | bwd_inner_microstep: 514.14 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.28 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1899 +[2025-05-01 22:49:19,414] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 348.54 | bwd_microstep: 499.00 | bwd_inner_microstep: 498.98 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1131 +[2025-05-01 22:49:19,978] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 261.58 | bwd_microstep: 274.33 | bwd_inner_microstep: 274.31 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.33 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1381 +[2025-05-01 22:49:20,682] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 256.81 | bwd_microstep: 415.86 | bwd_inner_microstep: 415.84 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.06 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 349 +[2025-05-01 22:49:20,902] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 71.22 | bwd_microstep: 132.47 | bwd_inner_microstep: 132.45 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.87 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-01 22:49:21,768] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 324.81 | bwd_microstep: 511.44 | bwd_inner_microstep: 511.42 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-01 22:49:22,639] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 328.32 | bwd_microstep: 512.20 | bwd_inner_microstep: 512.18 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.33 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 850 +[2025-05-01 22:49:23,080] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 204.28 | bwd_microstep: 204.07 | bwd_inner_microstep: 204.05 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.49 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-01 22:49:23,945] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 334.33 | bwd_microstep: 498.00 | bwd_inner_microstep: 497.99 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 22:49:24,851] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 396.18 | bwd_microstep: 492.35 | bwd_inner_microstep: 492.33 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 22:49:25,747] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 371.92 | bwd_microstep: 501.77 | bwd_inner_microstep: 501.75 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 22:49:26,531] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 260.22 | bwd_microstep: 500.37 | bwd_inner_microstep: 500.35 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.32 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 22:49:27,415] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 359.33 | bwd_microstep: 492.37 | bwd_inner_microstep: 492.36 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-01 22:49:28,232] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 389.11 | bwd_microstep: 406.54 | bwd_inner_microstep: 406.52 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 319 +[2025-05-01 22:49:28,696] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.32 | optimizer_step: 17.19 +[2025-05-01 22:49:28,697] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 98.85 | bwd_microstep: 312.04 | bwd_inner_microstep: 134.68 | bwd_allreduce_microstep: 177.31 | step_microstep: 25.19 +[2025-05-01 22:49:28,698] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4666.87 | bwd: 6800.02 | bwd_inner: 6622.39 | bwd_allreduce: 177.39 | step: 48.65 + 2%|▏ | 213/8720 [34:02<28:42:49, 12.15s/it] {'loss': 1.6226, 'grad_norm': 4.648715019226074, 'learning_rate': 8.129770992366412e-06, 'epoch': 0.24} + 2%|▏ | 213/8720 [34:02<28:42:49, 12.15s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 435 +[2025-05-01 22:49:29,000] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 99.08 | bwd_microstep: 178.40 | bwd_inner_microstep: 178.38 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.95 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-01 22:49:29,878] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 403.65 | bwd_microstep: 445.93 | bwd_inner_microstep: 445.91 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 343 +[2025-05-01 22:49:30,152] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 100.03 | bwd_microstep: 141.81 | bwd_inner_microstep: 141.79 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.28 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1359 +[2025-05-01 22:49:30,728] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 158.56 | bwd_microstep: 387.90 | bwd_inner_microstep: 387.88 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-01 22:49:31,564] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 371.13 | bwd_microstep: 434.53 | bwd_inner_microstep: 434.52 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.19 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 842 +[2025-05-01 22:49:32,028] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 223.30 | bwd_microstep: 208.60 | bwd_inner_microstep: 208.32 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-01 22:49:32,912] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 283.68 | bwd_microstep: 582.28 | bwd_inner_microstep: 582.27 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 835 +[2025-05-01 22:49:33,258] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.23 | bwd_microstep: 235.38 | bwd_inner_microstep: 235.36 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.49 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-01 22:49:34,062] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 424.88 | bwd_microstep: 347.49 | bwd_inner_microstep: 347.47 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-01 22:49:34,918] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 427.36 | bwd_microstep: 394.37 | bwd_inner_microstep: 394.35 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 22:49:35,756] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 422.32 | bwd_microstep: 382.01 | bwd_inner_microstep: 381.99 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.36 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 321 +[2025-05-01 22:49:36,024] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 96.99 | bwd_microstep: 139.06 | bwd_inner_microstep: 139.04 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 22:49:36,847] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 293.38 | bwd_microstep: 497.17 | bwd_inner_microstep: 497.15 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.50 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 22:49:37,693] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 329.73 | bwd_microstep: 483.94 | bwd_inner_microstep: 483.92 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 1008 +[2025-05-01 22:49:38,133] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 241.25 | bwd_microstep: 168.59 | bwd_inner_microstep: 168.44 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1408 +[2025-05-01 22:49:39,059] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.65 | optimizer_step: 16.46 +[2025-05-01 22:49:39,060] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 249.25 | bwd_microstep: 638.54 | bwd_inner_microstep: 482.86 | bwd_allreduce_microstep: 155.63 | step_microstep: 24.57 +[2025-05-01 22:49:39,061] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4217.73 | bwd: 5666.05 | bwd_inner: 5509.73 | bwd_allreduce: 155.91 | step: 49.68 + 2%|▏ | 214/8720 [34:12<27:26:24, 11.61s/it] {'loss': 1.5249, 'grad_norm': 5.683568954467773, 'learning_rate': 8.16793893129771e-06, 'epoch': 0.25} + 2%|▏ | 214/8720 [34:12<27:26:24, 11.61s/it]dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1370 +[2025-05-01 22:49:39,823] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 282.50 | bwd_microstep: 457.95 | bwd_inner_microstep: 457.93 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.79 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-01 22:49:40,655] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 191.94 | bwd_microstep: 621.24 | bwd_inner_microstep: 621.22 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-01 22:49:41,459] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 210.95 | bwd_microstep: 559.06 | bwd_inner_microstep: 559.05 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-01 22:49:42,271] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 268.31 | bwd_microstep: 509.50 | bwd_inner_microstep: 509.48 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 22:49:43,105] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 318.67 | bwd_microstep: 482.23 | bwd_inner_microstep: 482.21 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.53 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 857 +[2025-05-01 22:49:43,460] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.13 | bwd_microstep: 135.41 | bwd_inner_microstep: 135.32 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.10 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1351 +[2025-05-01 22:49:44,212] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 277.96 | bwd_microstep: 455.52 | bwd_inner_microstep: 455.50 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.96 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-01 22:49:45,035] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.90 | bwd_microstep: 612.71 | bwd_inner_microstep: 612.69 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.50 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 847 +[2025-05-01 22:49:45,336] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 119.18 | bwd_microstep: 149.14 | bwd_inner_microstep: 149.13 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-01 22:49:46,198] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 428.51 | bwd_microstep: 401.94 | bwd_inner_microstep: 401.92 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 832 +[2025-05-01 22:49:46,751] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 209.97 | bwd_microstep: 310.62 | bwd_inner_microstep: 310.60 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 22:49:47,569] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 204.06 | bwd_microstep: 583.44 | bwd_inner_microstep: 583.42 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.28 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 22:49:48,380] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 241.84 | bwd_microstep: 535.35 | bwd_inner_microstep: 535.33 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.50 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 22:49:49,230] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 289.36 | bwd_microstep: 527.79 | bwd_inner_microstep: 527.77 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.32 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 22:49:50,026] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 247.53 | bwd_microstep: 516.99 | bwd_inner_microstep: 516.97 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 22:49:51,180] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.33 | optimizer_step: 16.89 +[2025-05-01 22:49:51,181] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 308.92 | bwd_microstep: 790.99 | bwd_inner_microstep: 473.19 | bwd_allreduce_microstep: 317.76 | step_microstep: 24.49 +[2025-05-01 22:49:51,182] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 3980.67 | bwd: 7649.90 | bwd_inner: 7331.74 | bwd_allreduce: 317.89 | step: 54.88 + 2%|▏ | 215/8720 [34:24<27:47:54, 11.77s/it] {'loss': 1.5376, 'grad_norm': 7.302038192749023, 'learning_rate': 8.206106870229008e-06, 'epoch': 0.25} + 2%|▏ | 215/8720 [34:24<27:47:54, 11.77s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1913 +[2025-05-01 22:49:52,075] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 382.05 | bwd_microstep: 486.72 | bwd_inner_microstep: 486.70 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 341 +[2025-05-01 22:49:52,319] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 83.46 | bwd_microstep: 142.03 | bwd_inner_microstep: 142.02 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.47 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-01 22:49:53,144] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 387.72 | bwd_microstep: 412.19 | bwd_inner_microstep: 412.17 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-01 22:49:53,976] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 423.23 | bwd_microstep: 380.64 | bwd_inner_microstep: 380.62 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-01 22:49:54,800] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 425.58 | bwd_microstep: 364.08 | bwd_inner_microstep: 364.06 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-01 22:49:55,652] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 427.60 | bwd_microstep: 391.19 | bwd_inner_microstep: 391.18 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.32 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-01 22:49:56,504] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 429.30 | bwd_microstep: 390.29 | bwd_inner_microstep: 390.27 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 22:49:57,320] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 425.57 | bwd_microstep: 357.32 | bwd_inner_microstep: 357.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-01 22:49:58,183] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 425.87 | bwd_microstep: 405.18 | bwd_inner_microstep: 405.16 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-01 22:49:59,060] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 401.83 | bwd_microstep: 458.91 | bwd_inner_microstep: 458.90 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 22:49:59,940] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 367.17 | bwd_microstep: 496.10 | bwd_inner_microstep: 496.08 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 22:50:00,825] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 326.52 | bwd_microstep: 534.13 | bwd_inner_microstep: 534.12 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.18 +dynamic ViT batch size: 6, images per sample: 6.0, dynamic token length: 1603 +[2025-05-01 22:50:01,612] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 207.06 | bwd_microstep: 558.25 | bwd_inner_microstep: 558.24 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 22:50:02,435] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 202.57 | bwd_microstep: 585.42 | bwd_inner_microstep: 585.40 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.55 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 22:50:03,243] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 235.62 | bwd_microstep: 536.09 | bwd_inner_microstep: 536.07 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 22:50:04,325] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 6.31 | optimizer_step: 19.42 +[2025-05-01 22:50:04,326] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 282.32 | bwd_microstep: 734.24 | bwd_inner_microstep: 515.98 | bwd_allreduce_microstep: 218.22 | step_microstep: 32.06 +[2025-05-01 22:50:04,327] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 5433.32 | bwd: 7232.81 | bwd_inner: 7014.27 | bwd_allreduce: 218.30 | step: 54.28 + 2%|▏ | 216/8720 [34:38<28:46:12, 12.18s/it] {'loss': 1.6428, 'grad_norm': 6.215485095977783, 'learning_rate': 8.244274809160306e-06, 'epoch': 0.25} + 2%|▏ | 216/8720 [34:38<28:46:12, 12.18s/it]dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 860 +[2025-05-01 22:50:04,824] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 183.33 | bwd_microstep: 292.25 | bwd_inner_microstep: 292.23 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1893 +[2025-05-01 22:50:05,642] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 240.31 | bwd_microstep: 543.90 | bwd_inner_microstep: 543.88 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.49 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-01 22:50:06,470] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 286.95 | bwd_microstep: 506.26 | bwd_inner_microstep: 506.24 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-01 22:50:07,322] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 318.27 | bwd_microstep: 499.95 | bwd_inner_microstep: 499.93 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.44 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-01 22:50:08,168] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 272.45 | bwd_microstep: 538.75 | bwd_inner_microstep: 538.73 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.51 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-01 22:50:08,979] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 230.69 | bwd_microstep: 546.48 | bwd_inner_microstep: 546.46 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-01 22:50:09,566] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 279.92 | bwd_microstep: 276.81 | bwd_inner_microstep: 276.79 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-01 22:50:10,442] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 423.30 | bwd_microstep: 436.38 | bwd_inner_microstep: 436.36 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-01 22:50:11,325] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 369.15 | bwd_microstep: 497.61 | bwd_inner_microstep: 497.59 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 329 +[2025-05-01 22:50:11,581] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 92.36 | bwd_microstep: 142.05 | bwd_inner_microstep: 142.03 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 22:50:12,398] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 422.75 | bwd_microstep: 360.15 | bwd_inner_microstep: 360.13 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.54 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-01 22:50:13,212] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 425.20 | bwd_microstep: 354.08 | bwd_inner_microstep: 354.06 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 22:50:14,058] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 426.50 | bwd_microstep: 387.45 | bwd_inner_microstep: 387.44 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.22 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 22:50:14,939] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 409.94 | bwd_microstep: 450.40 | bwd_inner_microstep: 450.38 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 22:50:15,819] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 351.01 | bwd_microstep: 512.09 | bwd_inner_microstep: 512.07 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1910 +[2025-05-01 22:50:16,843] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.50 | optimizer_step: 17.13 +[2025-05-01 22:50:16,844] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 305.42 | bwd_microstep: 676.76 | bwd_inner_microstep: 570.03 | bwd_allreduce_microstep: 106.68 | step_microstep: 25.06 +[2025-05-01 22:50:16,845] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 5037.43 | bwd: 7021.37 | bwd_inner: 6914.37 | bwd_allreduce: 106.76 | step: 47.43 + 2%|▏ | 217/8720 [34:50<29:00:27, 12.28s/it] {'loss': 2.0163, 'grad_norm': 9.899005889892578, 'learning_rate': 8.282442748091603e-06, 'epoch': 0.25} + 2%|▏ | 217/8720 [34:50<29:00:27, 12.28s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2013 +[2025-05-01 22:50:17,765] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 404.36 | bwd_microstep: 493.13 | bwd_inner_microstep: 493.11 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1909 +[2025-05-01 22:50:18,652] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 421.91 | bwd_microstep: 446.30 | bwd_inner_microstep: 446.28 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 860 +[2025-05-01 22:50:19,122] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 150.52 | bwd_microstep: 299.89 | bwd_inner_microstep: 299.87 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.46 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1911 +[2025-05-01 22:50:19,965] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 324.10 | bwd_microstep: 483.03 | bwd_inner_microstep: 483.01 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1889 +[2025-05-01 22:50:20,800] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 347.75 | bwd_microstep: 452.48 | bwd_inner_microstep: 452.46 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-01 22:50:21,613] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 375.77 | bwd_microstep: 403.31 | bwd_inner_microstep: 403.29 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.36 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1368 +[2025-05-01 22:50:22,229] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 329.00 | bwd_microstep: 253.79 | bwd_inner_microstep: 253.77 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-01 22:50:23,060] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 409.85 | bwd_microstep: 402.86 | bwd_inner_microstep: 402.84 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-01 22:50:23,942] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 428.70 | bwd_microstep: 435.64 | bwd_inner_microstep: 435.63 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1353 +[2025-05-01 22:50:24,698] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 283.05 | bwd_microstep: 453.86 | bwd_inner_microstep: 453.84 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.87 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1356 +[2025-05-01 22:50:25,276] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 143.05 | bwd_microstep: 415.40 | bwd_inner_microstep: 415.38 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 22:50:26,128] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 334.82 | bwd_microstep: 480.46 | bwd_inner_microstep: 480.44 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 22:50:26,967] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 346.58 | bwd_microstep: 457.51 | bwd_inner_microstep: 457.50 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-01 22:50:27,851] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 312.38 | bwd_microstep: 535.16 | bwd_inner_microstep: 535.14 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.52 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 22:50:28,651] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 290.47 | bwd_microstep: 475.50 | bwd_inner_microstep: 475.48 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 22:50:29,848] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 5.27 | optimizer_step: 20.88 +[2025-05-01 22:50:29,849] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 347.49 | bwd_microstep: 784.50 | bwd_inner_microstep: 428.81 | bwd_allreduce_microstep: 355.64 | step_microstep: 32.84 +[2025-05-01 22:50:29,850] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 5249.71 | bwd: 7272.85 | bwd_inner: 6916.89 | bwd_allreduce: 355.72 | step: 55.47 + 2%|▎ | 218/8720 [35:03<29:31:12, 12.50s/it] {'loss': 2.2242, 'grad_norm': 6.4850754737854, 'learning_rate': 8.320610687022901e-06, 'epoch': 0.25} + 2%|▎ | 218/8720 [35:03<29:31:12, 12.50s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1893 +[2025-05-01 22:50:30,747] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 400.30 | bwd_microstep: 468.21 | bwd_inner_microstep: 468.19 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-01 22:50:31,633] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 369.86 | bwd_microstep: 500.61 | bwd_inner_microstep: 500.59 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 866 +[2025-05-01 22:50:32,055] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 100.81 | bwd_microstep: 301.43 | bwd_inner_microstep: 301.41 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-01 22:50:32,896] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 378.89 | bwd_microstep: 431.24 | bwd_inner_microstep: 431.23 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.26 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-01 22:50:33,739] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 402.87 | bwd_microstep: 409.34 | bwd_inner_microstep: 409.32 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-01 22:50:34,607] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 425.36 | bwd_microstep: 414.13 | bwd_inner_microstep: 414.11 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-01 22:50:35,458] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 424.57 | bwd_microstep: 402.55 | bwd_inner_microstep: 402.53 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1353 +[2025-05-01 22:50:36,074] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 328.14 | bwd_microstep: 256.88 | bwd_inner_microstep: 256.86 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.25 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 840 +[2025-05-01 22:50:36,579] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 199.03 | bwd_microstep: 284.69 | bwd_inner_microstep: 284.67 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 22:50:37,399] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 227.79 | bwd_microstep: 557.99 | bwd_inner_microstep: 557.97 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.50 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-01 22:50:38,225] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 261.43 | bwd_microstep: 523.75 | bwd_inner_microstep: 523.73 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.48 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 22:50:39,045] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 299.80 | bwd_microstep: 486.50 | bwd_inner_microstep: 486.48 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.52 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 837 +[2025-05-01 22:50:39,442] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 213.48 | bwd_microstep: 149.03 | bwd_inner_microstep: 148.93 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 22:50:40,320] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 358.76 | bwd_microstep: 502.46 | bwd_inner_microstep: 502.44 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 22:50:41,200] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 304.01 | bwd_microstep: 559.17 | bwd_inner_microstep: 559.15 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1346 +[2025-05-01 22:50:42,118] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.56 | optimizer_step: 17.64 +[2025-05-01 22:50:42,118] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 156.49 | bwd_microstep: 717.08 | bwd_inner_microstep: 473.87 | bwd_allreduce_microstep: 243.16 | step_microstep: 26.73 +[2025-05-01 22:50:42,120] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4851.42 | bwd: 6965.08 | bwd_inner: 6721.51 | bwd_allreduce: 243.28 | step: 46.86 + 3%|▎ | 219/8720 [35:15<29:20:59, 12.43s/it] {'loss': 1.8693, 'grad_norm': 6.02712869644165, 'learning_rate': 8.358778625954199e-06, 'epoch': 0.25} + 3%|▎ | 219/8720 [35:15<29:20:59, 12.43s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1957 +[2025-05-01 22:50:43,033] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 382.98 | bwd_microstep: 509.98 | bwd_inner_microstep: 509.97 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 879 +[2025-05-01 22:50:43,504] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 151.52 | bwd_microstep: 302.81 | bwd_inner_microstep: 302.79 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-01 22:50:44,320] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 271.18 | bwd_microstep: 510.42 | bwd_inner_microstep: 510.40 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-01 22:50:45,180] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 314.04 | bwd_microstep: 507.09 | bwd_inner_microstep: 507.07 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.52 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-01 22:50:46,004] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 321.20 | bwd_microstep: 468.86 | bwd_inner_microstep: 468.84 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.44 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-01 22:50:46,845] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 358.32 | bwd_microstep: 450.36 | bwd_inner_microstep: 450.34 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.54 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-01 22:50:47,651] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 323.93 | bwd_microstep: 449.50 | bwd_inner_microstep: 449.48 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 22:50:48,484] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 368.92 | bwd_microstep: 427.43 | bwd_inner_microstep: 427.41 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 328 +[2025-05-01 22:50:48,758] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 101.09 | bwd_microstep: 142.50 | bwd_inner_microstep: 142.48 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.33 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1351 +[2025-05-01 22:50:49,322] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 175.14 | bwd_microstep: 360.37 | bwd_inner_microstep: 360.17 | bwd_allreduce_microstep: 0.19 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-01 22:50:50,184] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 401.70 | bwd_microstep: 432.98 | bwd_inner_microstep: 432.96 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 22:50:51,027] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 398.67 | bwd_microstep: 411.74 | bwd_inner_microstep: 411.72 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1343 +[2025-05-01 22:50:51,629] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 325.78 | bwd_microstep: 253.92 | bwd_inner_microstep: 253.75 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.13 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 22:50:52,509] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 392.10 | bwd_microstep: 469.86 | bwd_inner_microstep: 469.84 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 22:50:53,389] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 347.43 | bwd_microstep: 516.85 | bwd_inner_microstep: 516.84 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1935 +[2025-05-01 22:50:54,414] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.45 | optimizer_step: 18.12 +[2025-05-01 22:50:54,416] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 321.63 | bwd_microstep: 662.97 | bwd_inner_microstep: 565.87 | bwd_allreduce_microstep: 97.06 | step_microstep: 25.92 +[2025-05-01 22:50:54,417] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4955.54 | bwd: 6877.65 | bwd_inner: 6779.94 | bwd_allreduce: 97.39 | step: 45.98 + 3%|▎ | 220/8720 [35:28<29:15:19, 12.39s/it] {'loss': 1.3452, 'grad_norm': 5.268129348754883, 'learning_rate': 8.396946564885497e-06, 'epoch': 0.25} + 3%|▎ | 220/8720 [35:28<29:15:19, 12.39s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2142 +[2025-05-01 22:50:55,432] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 458.26 | bwd_microstep: 514.12 | bwd_inner_microstep: 514.10 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1896 +[2025-05-01 22:50:56,265] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 394.33 | bwd_microstep: 407.31 | bwd_inner_microstep: 407.29 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-01 22:50:57,112] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 423.08 | bwd_microstep: 390.89 | bwd_inner_microstep: 390.87 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.29 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 843 +[2025-05-01 22:50:57,616] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 208.63 | bwd_microstep: 263.33 | bwd_inner_microstep: 263.28 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-01 22:50:58,493] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 233.11 | bwd_microstep: 621.33 | bwd_inner_microstep: 621.31 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.76 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 22:50:59,306] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 192.87 | bwd_microstep: 597.98 | bwd_inner_microstep: 597.96 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.53 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-01 22:51:00,163] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 224.20 | bwd_microstep: 595.85 | bwd_inner_microstep: 595.83 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 22:51:01,008] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 225.82 | bwd_microstep: 583.39 | bwd_inner_microstep: 583.35 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-01 22:51:01,889] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 221.33 | bwd_microstep: 628.46 | bwd_inner_microstep: 628.44 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 22:51:02,720] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 201.04 | bwd_microstep: 607.88 | bwd_inner_microstep: 607.86 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.02 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 22:51:03,531] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 193.22 | bwd_microstep: 597.91 | bwd_inner_microstep: 597.90 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 22:51:04,350] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 228.98 | bwd_microstep: 553.39 | bwd_inner_microstep: 553.37 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.51 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 22:51:05,162] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 268.59 | bwd_microstep: 506.60 | bwd_inner_microstep: 506.58 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1343 +[2025-05-01 22:51:05,720] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 264.26 | bwd_microstep: 260.06 | bwd_inner_microstep: 260.04 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 22:51:06,563] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 426.90 | bwd_microstep: 383.07 | bwd_inner_microstep: 383.05 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 22:51:07,917] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 4.07 | optimizer_step: 22.90 +[2025-05-01 22:51:07,917] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 428.14 | bwd_microstep: 860.99 | bwd_inner_microstep: 389.78 | bwd_allreduce_microstep: 471.15 | step_microstep: 33.45 +[2025-05-01 22:51:07,919] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4592.73 | bwd: 8372.58 | bwd_inner: 7901.02 | bwd_allreduce: 471.26 | step: 63.79 + 3%|▎ | 221/8720 [35:41<30:02:11, 12.72s/it] {'loss': 1.3379, 'grad_norm': 5.666141510009766, 'learning_rate': 8.435114503816794e-06, 'epoch': 0.25} + 3%|▎ | 221/8720 [35:41<30:02:11, 12.72s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2066 +[2025-05-01 22:51:08,849] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 360.45 | bwd_microstep: 549.59 | bwd_inner_microstep: 549.57 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1924 +[2025-05-01 22:51:09,750] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 362.46 | bwd_microstep: 518.43 | bwd_inner_microstep: 518.41 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1908 +[2025-05-01 22:51:10,640] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 344.71 | bwd_microstep: 526.31 | bwd_inner_microstep: 526.29 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-01 22:51:11,478] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 318.50 | bwd_microstep: 500.58 | bwd_inner_microstep: 500.56 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 861 +[2025-05-01 22:51:11,897] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 99.83 | bwd_microstep: 300.71 | bwd_inner_microstep: 300.69 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-01 22:51:12,727] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 379.17 | bwd_microstep: 414.86 | bwd_inner_microstep: 414.84 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-01 22:51:13,595] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 411.16 | bwd_microstep: 423.63 | bwd_inner_microstep: 423.61 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 22:51:14,426] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 404.08 | bwd_microstep: 396.13 | bwd_inner_microstep: 396.11 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-01 22:51:15,266] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 431.69 | bwd_microstep: 374.65 | bwd_inner_microstep: 374.63 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-01 22:51:16,121] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 425.33 | bwd_microstep: 395.12 | bwd_inner_microstep: 395.10 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 22:51:16,943] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 418.75 | bwd_microstep: 371.81 | bwd_inner_microstep: 371.79 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 22:51:17,757] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 424.53 | bwd_microstep: 354.38 | bwd_inner_microstep: 354.36 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.32 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 318 +[2025-05-01 22:51:18,004] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 96.56 | bwd_microstep: 120.62 | bwd_inner_microstep: 120.60 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.31 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 22:51:18,869] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 385.67 | bwd_microstep: 447.31 | bwd_inner_microstep: 447.29 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 22:51:19,689] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 324.95 | bwd_microstep: 459.85 | bwd_inner_microstep: 459.83 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.28 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1906 +[2025-05-01 22:51:20,900] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.45 | optimizer_step: 17.18 +[2025-05-01 22:51:20,900] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 362.14 | bwd_microstep: 791.49 | bwd_inner_microstep: 459.86 | bwd_allreduce_microstep: 331.59 | step_microstep: 25.66 +[2025-05-01 22:51:20,902] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 5549.86 | bwd: 6945.48 | bwd_inner: 6613.57 | bwd_allreduce: 331.67 | step: 51.67 + 3%|▎ | 222/8720 [35:54<30:13:12, 12.80s/it] {'loss': 1.4552, 'grad_norm': 4.840289115905762, 'learning_rate': 8.473282442748092e-06, 'epoch': 0.25} + 3%|▎ | 222/8720 [35:54<30:13:12, 12.80s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-01 22:51:21,751] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 397.92 | bwd_microstep: 424.68 | bwd_inner_microstep: 424.66 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-01 22:51:22,622] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 421.15 | bwd_microstep: 418.16 | bwd_inner_microstep: 418.14 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-01 22:51:23,470] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 432.92 | bwd_microstep: 380.53 | bwd_inner_microstep: 380.51 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-01 22:51:24,325] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 429.41 | bwd_microstep: 391.67 | bwd_inner_microstep: 391.66 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-01 22:51:25,160] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 428.37 | bwd_microstep: 370.37 | bwd_inner_microstep: 370.35 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.36 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 336 +[2025-05-01 22:51:25,424] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.22 | bwd_microstep: 137.61 | bwd_inner_microstep: 137.60 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 846 +[2025-05-01 22:51:25,809] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 214.02 | bwd_microstep: 142.11 | bwd_inner_microstep: 141.98 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 327 +[2025-05-01 22:51:26,052] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 85.01 | bwd_microstep: 141.77 | bwd_inner_microstep: 141.75 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 328 +[2025-05-01 22:51:26,318] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 92.22 | bwd_microstep: 141.99 | bwd_inner_microstep: 141.97 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.52 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-01 22:51:27,175] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 276.19 | bwd_microstep: 546.57 | bwd_inner_microstep: 546.55 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.48 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 22:51:28,017] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 276.63 | bwd_microstep: 531.04 | bwd_inner_microstep: 531.02 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 22:51:28,865] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 294.65 | bwd_microstep: 518.34 | bwd_inner_microstep: 518.32 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 22:51:29,716] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 339.58 | bwd_microstep: 477.21 | bwd_inner_microstep: 477.19 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 318 +[2025-05-01 22:51:29,974] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.90 | bwd_microstep: 132.16 | bwd_inner_microstep: 132.14 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 22:51:30,812] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 211.68 | bwd_microstep: 595.18 | bwd_inner_microstep: 595.16 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.31 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1891 +[2025-05-01 22:51:31,981] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.08 | optimizer_gradients: 2.72 | optimizer_step: 35.03 +[2025-05-01 22:51:31,981] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 261.83 | bwd_microstep: 831.99 | bwd_inner_microstep: 554.90 | bwd_allreduce_microstep: 277.05 | step_microstep: 45.10 +[2025-05-01 22:51:31,983] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4352.64 | bwd: 6181.43 | bwd_inner: 5903.95 | bwd_allreduce: 277.19 | step: 78.35 + 3%|▎ | 223/8720 [36:05<28:59:42, 12.28s/it] {'loss': 1.5179, 'grad_norm': 5.157609462738037, 'learning_rate': 8.51145038167939e-06, 'epoch': 0.26} + 3%|▎ | 223/8720 [36:05<28:59:42, 12.28s/it]dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1134 +[2025-05-01 22:51:32,630] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 251.87 | bwd_microstep: 372.52 | bwd_inner_microstep: 372.50 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-01 22:51:33,487] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 233.96 | bwd_microstep: 586.95 | bwd_inner_microstep: 586.93 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 856 +[2025-05-01 22:51:33,830] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 175.27 | bwd_microstep: 136.72 | bwd_inner_microstep: 136.39 | bwd_allreduce_microstep: 0.14 | step_microstep: 0.15 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1100 +[2025-05-01 22:51:34,477] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 265.29 | bwd_microstep: 365.24 | bwd_inner_microstep: 365.22 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.53 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-01 22:51:35,328] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 226.39 | bwd_microstep: 589.80 | bwd_inner_microstep: 589.78 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-01 22:51:36,168] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 269.98 | bwd_microstep: 535.91 | bwd_inner_microstep: 535.89 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-01 22:51:37,014] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 322.13 | bwd_microstep: 489.99 | bwd_inner_microstep: 489.97 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-01 22:51:37,859] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 366.99 | bwd_microstep: 443.77 | bwd_inner_microstep: 443.75 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.31 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1352 +[2025-05-01 22:51:38,468] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 328.12 | bwd_microstep: 251.34 | bwd_inner_microstep: 251.32 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-01 22:51:39,374] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 424.69 | bwd_microstep: 463.83 | bwd_inner_microstep: 463.81 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 22:51:40,287] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 365.63 | bwd_microstep: 531.33 | bwd_inner_microstep: 531.31 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-01 22:51:41,203] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 311.23 | bwd_microstep: 586.32 | bwd_inner_microstep: 586.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 22:51:42,087] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 241.49 | bwd_microstep: 619.04 | bwd_inner_microstep: 619.02 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 832 +[2025-05-01 22:51:42,389] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 102.86 | bwd_microstep: 171.63 | bwd_inner_microstep: 171.61 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-01 22:51:43,235] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 418.45 | bwd_microstep: 395.83 | bwd_inner_microstep: 395.76 | bwd_allreduce_microstep: 0.03 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 22:51:44,268] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.37 | optimizer_step: 18.63 +[2025-05-01 22:51:44,270] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 421.85 | bwd_microstep: 564.38 | bwd_inner_microstep: 459.24 | bwd_allreduce_microstep: 105.12 | step_microstep: 28.22 +[2025-05-01 22:51:44,271] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4726.10 | bwd: 7104.65 | bwd_inner: 6998.86 | bwd_allreduce: 105.32 | step: 50.08 + 3%|▎ | 224/8720 [36:18<28:59:49, 12.29s/it] {'loss': 1.2214, 'grad_norm': 7.684805393218994, 'learning_rate': 8.549618320610688e-06, 'epoch': 0.26} + 3%|▎ | 224/8720 [36:18<28:59:49, 12.29s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1896 +[2025-05-01 22:51:45,131] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 424.25 | bwd_microstep: 390.88 | bwd_inner_microstep: 390.86 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1883 +[2025-05-01 22:51:45,982] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 427.85 | bwd_microstep: 388.38 | bwd_inner_microstep: 388.36 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.31 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-01 22:51:46,869] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 422.52 | bwd_microstep: 432.40 | bwd_inner_microstep: 432.38 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.14 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-01 22:51:47,786] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 400.63 | bwd_microstep: 499.02 | bwd_inner_microstep: 499.00 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.21 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-01 22:51:48,703] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 350.47 | bwd_microstep: 546.92 | bwd_inner_microstep: 546.91 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-01 22:51:49,614] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 277.60 | bwd_microstep: 613.16 | bwd_inner_microstep: 613.14 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-01 22:51:50,462] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 204.87 | bwd_microstep: 624.74 | bwd_inner_microstep: 624.72 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-01 22:51:51,300] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 223.42 | bwd_microstep: 582.28 | bwd_inner_microstep: 582.26 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.28 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-01 22:51:52,143] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 272.97 | bwd_microstep: 535.33 | bwd_inner_microstep: 535.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 841 +[2025-05-01 22:51:52,531] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 216.70 | bwd_microstep: 139.69 | bwd_inner_microstep: 139.61 | bwd_allreduce_microstep: 0.04 | step_microstep: 0.10 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 843 +[2025-05-01 22:51:53,000] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 158.55 | bwd_microstep: 293.75 | bwd_inner_microstep: 293.73 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 22:51:53,854] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 351.43 | bwd_microstep: 467.47 | bwd_inner_microstep: 467.45 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 22:51:54,716] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 392.25 | bwd_microstep: 435.28 | bwd_inner_microstep: 435.27 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.13 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 22:51:55,582] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 428.61 | bwd_microstep: 409.12 | bwd_inner_microstep: 409.10 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 22:51:56,440] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 438.39 | bwd_microstep: 386.24 | bwd_inner_microstep: 386.22 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.52 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 22:51:57,789] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.42 | optimizer_step: 21.10 +[2025-05-01 22:51:57,789] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 417.30 | bwd_microstep: 870.55 | bwd_inner_microstep: 393.92 | bwd_allreduce_microstep: 476.58 | step_microstep: 29.11 +[2025-05-01 22:51:57,790] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 5407.73 | bwd: 7615.23 | bwd_inner: 7138.24 | bwd_allreduce: 476.71 | step: 54.12 + 3%|▎ | 225/8720 [36:31<29:51:49, 12.66s/it] {'loss': 1.3206, 'grad_norm': 7.973294734954834, 'learning_rate': 8.587786259541985e-06, 'epoch': 0.26} + 3%|▎ | 225/8720 [36:31<29:51:49, 12.66s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 404 +[2025-05-01 22:51:58,080] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.70 | bwd_microstep: 173.45 | bwd_inner_microstep: 173.43 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1894 +[2025-05-01 22:51:58,954] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 439.18 | bwd_microstep: 402.77 | bwd_inner_microstep: 402.75 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1899 +[2025-05-01 22:51:59,812] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 422.23 | bwd_microstep: 401.17 | bwd_inner_microstep: 401.15 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.32 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-01 22:52:00,659] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 421.49 | bwd_microstep: 391.24 | bwd_inner_microstep: 391.22 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.41 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-01 22:52:01,524] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 424.93 | bwd_microstep: 407.36 | bwd_inner_microstep: 407.34 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-01 22:52:02,431] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 422.15 | bwd_microstep: 466.72 | bwd_inner_microstep: 466.71 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-01 22:52:03,344] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 379.16 | bwd_microstep: 517.60 | bwd_inner_microstep: 517.58 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-01 22:52:04,259] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 323.65 | bwd_microstep: 571.65 | bwd_inner_microstep: 571.63 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1349 +[2025-05-01 22:52:04,883] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 142.82 | bwd_microstep: 462.37 | bwd_inner_microstep: 462.36 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.30 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-01 22:52:05,733] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 323.01 | bwd_microstep: 492.48 | bwd_inner_microstep: 492.46 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.31 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 322 +[2025-05-01 22:52:06,007] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 102.55 | bwd_microstep: 137.70 | bwd_inner_microstep: 137.68 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 22:52:06,843] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 200.21 | bwd_microstep: 612.55 | bwd_inner_microstep: 612.53 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.31 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 322 +[2025-05-01 22:52:07,083] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 89.41 | bwd_microstep: 121.00 | bwd_inner_microstep: 120.73 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 22:52:07,994] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 363.74 | bwd_microstep: 530.88 | bwd_inner_microstep: 530.86 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 22:52:08,908] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 312.10 | bwd_microstep: 582.32 | bwd_inner_microstep: 582.30 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 315 +[2025-05-01 22:52:09,659] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.07 | optimizer_gradients: 4.15 | optimizer_step: 25.89 +[2025-05-01 22:52:09,660] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 69.37 | bwd_microstep: 631.51 | bwd_inner_microstep: 143.50 | bwd_allreduce_microstep: 487.96 | step_microstep: 36.14 +[2025-05-01 22:52:09,661] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4530.55 | bwd: 6902.81 | bwd_inner: 6414.31 | bwd_allreduce: 488.10 | step: 55.36 + 3%|▎ | 226/8720 [36:43<29:18:16, 12.42s/it] {'loss': 1.6641, 'grad_norm': 5.238696098327637, 'learning_rate': 8.625954198473283e-06, 'epoch': 0.26} + 3%|▎ | 226/8720 [36:43<29:18:16, 12.42s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2201 +[2025-05-01 22:52:10,646] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 405.70 | bwd_microstep: 558.31 | bwd_inner_microstep: 558.29 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-01 22:52:11,562] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 389.12 | bwd_microstep: 509.56 | bwd_inner_microstep: 509.55 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1891 +[2025-05-01 22:52:12,480] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 340.59 | bwd_microstep: 561.41 | bwd_inner_microstep: 561.39 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1888 +[2025-05-01 22:52:13,386] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 269.97 | bwd_microstep: 615.51 | bwd_inner_microstep: 615.49 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-01 22:52:14,226] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 194.64 | bwd_microstep: 624.87 | bwd_inner_microstep: 624.85 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-01 22:52:15,084] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 234.59 | bwd_microstep: 587.25 | bwd_inner_microstep: 587.24 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 845 +[2025-05-01 22:52:15,426] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 173.57 | bwd_microstep: 136.16 | bwd_inner_microstep: 136.06 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-01 22:52:16,334] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 422.07 | bwd_microstep: 467.19 | bwd_inner_microstep: 467.17 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-01 22:52:17,251] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 370.32 | bwd_microstep: 527.66 | bwd_inner_microstep: 527.64 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-01 22:52:18,167] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 321.27 | bwd_microstep: 575.35 | bwd_inner_microstep: 575.34 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-01 22:52:19,054] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 242.04 | bwd_microstep: 623.15 | bwd_inner_microstep: 623.13 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-01 22:52:19,889] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 200.34 | bwd_microstep: 612.36 | bwd_inner_microstep: 612.34 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 22:52:20,740] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 242.05 | bwd_microstep: 574.45 | bwd_inner_microstep: 574.43 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.52 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 22:52:21,584] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 282.15 | bwd_microstep: 527.67 | bwd_inner_microstep: 527.65 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.30 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 22:52:22,440] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 328.68 | bwd_microstep: 493.12 | bwd_inner_microstep: 493.10 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 22:52:23,693] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 4.24 | optimizer_step: 21.76 +[2025-05-01 22:52:23,693] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 368.53 | bwd_microstep: 819.37 | bwd_inner_microstep: 445.46 | bwd_allreduce_microstep: 373.83 | step_microstep: 33.37 +[2025-05-01 22:52:23,695] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4785.52 | bwd: 8813.44 | bwd_inner: 8439.16 | bwd_allreduce: 373.99 | step: 51.41 + 3%|▎ | 227/8720 [36:57<30:26:37, 12.90s/it] {'loss': 1.4538, 'grad_norm': 3.8188893795013428, 'learning_rate': 8.664122137404581e-06, 'epoch': 0.26} + 3%|▎ | 227/8720 [36:57<30:26:37, 12.90s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1892 +[2025-05-01 22:52:24,617] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 403.48 | bwd_microstep: 496.85 | bwd_inner_microstep: 496.83 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1893 +[2025-05-01 22:52:25,534] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 355.50 | bwd_microstep: 542.89 | bwd_inner_microstep: 542.88 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1371 +[2025-05-01 22:52:26,223] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.66 | bwd_microstep: 471.54 | bwd_inner_microstep: 471.52 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-01 22:52:27,064] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 265.66 | bwd_microstep: 543.92 | bwd_inner_microstep: 543.91 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.45 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-01 22:52:27,919] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 311.02 | bwd_microstep: 509.02 | bwd_inner_microstep: 509.00 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-01 22:52:28,771] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 351.69 | bwd_microstep: 467.11 | bwd_inner_microstep: 467.09 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-01 22:52:29,635] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 390.35 | bwd_microstep: 440.64 | bwd_inner_microstep: 440.63 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-01 22:52:30,495] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 424.27 | bwd_microstep: 406.32 | bwd_inner_microstep: 406.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-01 22:52:31,367] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 437.17 | bwd_microstep: 400.34 | bwd_inner_microstep: 400.32 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.36 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 331 +[2025-05-01 22:52:31,636] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 97.35 | bwd_microstep: 139.08 | bwd_inner_microstep: 139.06 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.53 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 22:52:32,490] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 300.62 | bwd_microstep: 520.75 | bwd_inner_microstep: 520.73 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.51 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 22:52:33,343] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 333.05 | bwd_microstep: 485.72 | bwd_inner_microstep: 485.70 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.51 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 22:52:34,192] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 368.80 | bwd_microstep: 446.43 | bwd_inner_microstep: 446.41 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.31 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 22:52:35,051] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 414.87 | bwd_microstep: 411.93 | bwd_inner_microstep: 411.91 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 22:52:35,912] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 434.17 | bwd_microstep: 392.72 | bwd_inner_microstep: 392.70 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 22:52:37,258] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 9.08 | optimizer_step: 16.71 +[2025-05-01 22:52:37,258] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 424.94 | bwd_microstep: 857.86 | bwd_inner_microstep: 396.84 | bwd_allreduce_microstep: 460.97 | step_microstep: 31.73 +[2025-05-01 22:52:37,259] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 5508.55 | bwd: 7533.15 | bwd_inner: 7071.86 | bwd_allreduce: 461.05 | step: 60.93 + 3%|▎ | 228/8720 [37:11<30:54:22, 13.10s/it] {'loss': 1.7508, 'grad_norm': 5.384164333343506, 'learning_rate': 8.702290076335879e-06, 'epoch': 0.26} + 3%|▎ | 228/8720 [37:11<30:54:22, 13.10s/it]dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1386 +[2025-05-01 22:52:38,041] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 292.09 | bwd_microstep: 466.51 | bwd_inner_microstep: 466.49 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.54 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-01 22:52:38,884] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 197.81 | bwd_microstep: 625.21 | bwd_inner_microstep: 625.19 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 864 +[2025-05-01 22:52:39,208] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.38 | bwd_microstep: 151.36 | bwd_inner_microstep: 151.34 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.51 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1889 +[2025-05-01 22:52:40,086] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 427.81 | bwd_microstep: 417.85 | bwd_inner_microstep: 417.83 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1883 +[2025-05-01 22:52:41,001] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 422.60 | bwd_microstep: 476.67 | bwd_inner_microstep: 476.65 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-01 22:52:41,912] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 352.65 | bwd_microstep: 542.73 | bwd_inner_microstep: 542.71 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 844 +[2025-05-01 22:52:42,317] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 96.57 | bwd_microstep: 293.18 | bwd_inner_microstep: 292.98 | bwd_allreduce_microstep: 0.18 | step_microstep: 0.18 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1098 +[2025-05-01 22:52:42,852] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 263.66 | bwd_microstep: 247.81 | bwd_inner_microstep: 247.58 | bwd_allreduce_microstep: 0.10 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-01 22:52:43,767] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 351.03 | bwd_microstep: 545.22 | bwd_inner_microstep: 545.20 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-01 22:52:44,677] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 287.86 | bwd_microstep: 603.39 | bwd_inner_microstep: 603.37 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 22:52:45,532] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 210.40 | bwd_microstep: 622.94 | bwd_inner_microstep: 622.92 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 22:52:46,394] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 213.20 | bwd_microstep: 611.90 | bwd_inner_microstep: 611.88 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.52 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 22:52:47,239] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 241.60 | bwd_microstep: 567.80 | bwd_inner_microstep: 567.79 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 22:52:48,089] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 290.68 | bwd_microstep: 526.32 | bwd_inner_microstep: 526.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.51 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 315 +[2025-05-01 22:52:48,338] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.61 | bwd_microstep: 124.13 | bwd_inner_microstep: 124.11 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.41 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1945 +[2025-05-01 22:52:49,436] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.37 | optimizer_step: 16.60 +[2025-05-01 22:52:49,437] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 217.61 | bwd_microstep: 839.22 | bwd_inner_microstep: 655.16 | bwd_allreduce_microstep: 184.01 | step_microstep: 24.92 +[2025-05-01 22:52:49,438] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4100.44 | bwd: 7662.59 | bwd_inner: 7477.58 | bwd_allreduce: 184.34 | step: 44.11 + 3%|▎ | 229/8720 [37:23<30:15:03, 12.83s/it] {'loss': 1.6549, 'grad_norm': 4.45286750793457, 'learning_rate': 8.740458015267176e-06, 'epoch': 0.26} + 3%|▎ | 229/8720 [37:23<30:15:03, 12.83s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-01 22:52:50,359] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 384.50 | bwd_microstep: 510.81 | bwd_inner_microstep: 510.79 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 860 +[2025-05-01 22:52:50,796] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 119.72 | bwd_microstep: 299.80 | bwd_inner_microstep: 299.79 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.49 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-01 22:52:51,661] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 388.84 | bwd_microstep: 444.95 | bwd_inner_microstep: 444.93 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-01 22:52:52,532] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 424.34 | bwd_microstep: 415.88 | bwd_inner_microstep: 415.86 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-01 22:52:53,406] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 435.14 | bwd_microstep: 404.97 | bwd_inner_microstep: 404.95 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-01 22:52:54,260] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 423.35 | bwd_microstep: 395.87 | bwd_inner_microstep: 395.85 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 844 +[2025-05-01 22:52:54,811] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 209.58 | bwd_microstep: 311.30 | bwd_inner_microstep: 311.28 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-01 22:52:55,654] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 198.53 | bwd_microstep: 620.57 | bwd_inner_microstep: 620.55 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 832 +[2025-05-01 22:52:55,960] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.34 | bwd_microstep: 135.64 | bwd_inner_microstep: 135.62 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.53 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 22:52:56,847] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 424.80 | bwd_microstep: 429.88 | bwd_inner_microstep: 429.86 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 22:52:57,761] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 394.07 | bwd_microstep: 502.39 | bwd_inner_microstep: 502.37 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 22:52:58,671] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 347.81 | bwd_microstep: 546.01 | bwd_inner_microstep: 545.99 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 22:52:59,574] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 266.05 | bwd_microstep: 614.72 | bwd_inner_microstep: 614.70 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.81 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 22:53:00,402] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 194.14 | bwd_microstep: 612.27 | bwd_inner_microstep: 612.25 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.30 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 22:53:01,242] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 235.73 | bwd_microstep: 568.06 | bwd_inner_microstep: 568.04 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.31 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 22:53:02,410] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.62 | optimizer_step: 17.45 +[2025-05-01 22:53:02,411] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 284.82 | bwd_microstep: 823.67 | bwd_inner_microstep: 525.99 | bwd_allreduce_microstep: 297.63 | step_microstep: 26.09 +[2025-05-01 22:53:02,412] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4871.67 | bwd: 7636.80 | bwd_inner: 7338.86 | bwd_allreduce: 297.71 | step: 48.68 + 3%|▎ | 230/8720 [37:36<30:21:03, 12.87s/it] {'loss': 1.5155, 'grad_norm': 5.693798542022705, 'learning_rate': 8.778625954198474e-06, 'epoch': 0.26} + 3%|▎ | 230/8720 [37:36<30:21:03, 12.87s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-01 22:53:03,332] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 385.96 | bwd_microstep: 511.34 | bwd_inner_microstep: 511.32 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.21 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-01 22:53:04,242] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 327.36 | bwd_microstep: 565.30 | bwd_inner_microstep: 565.28 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1883 +[2025-05-01 22:53:05,146] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 271.05 | bwd_microstep: 612.84 | bwd_inner_microstep: 612.82 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.68 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-01 22:53:05,988] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 197.05 | bwd_microstep: 625.31 | bwd_inner_microstep: 625.29 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-01 22:53:06,832] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 233.30 | bwd_microstep: 576.77 | bwd_inner_microstep: 576.75 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.52 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-01 22:53:07,679] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 282.50 | bwd_microstep: 530.37 | bwd_inner_microstep: 530.35 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-01 22:53:08,539] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 326.05 | bwd_microstep: 499.23 | bwd_inner_microstep: 499.21 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.51 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 22:53:09,391] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 361.68 | bwd_microstep: 456.56 | bwd_inner_microstep: 456.54 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.28 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 839 +[2025-05-01 22:53:09,848] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 213.17 | bwd_microstep: 213.77 | bwd_inner_microstep: 213.74 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-01 22:53:10,763] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 290.72 | bwd_microstep: 605.51 | bwd_inner_microstep: 605.49 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 22:53:11,624] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 218.16 | bwd_microstep: 623.12 | bwd_inner_microstep: 623.10 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 22:53:12,472] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 210.03 | bwd_microstep: 604.38 | bwd_inner_microstep: 604.36 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1346 +[2025-05-01 22:53:13,071] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 207.16 | bwd_microstep: 358.63 | bwd_inner_microstep: 358.61 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 22:53:13,935] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 427.45 | bwd_microstep: 404.41 | bwd_inner_microstep: 404.39 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 22:53:14,808] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 439.86 | bwd_microstep: 399.37 | bwd_inner_microstep: 399.35 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 318 +[2025-05-01 22:53:15,367] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 4.07 | optimizer_step: 18.85 +[2025-05-01 22:53:15,368] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 96.15 | bwd_microstep: 404.96 | bwd_inner_microstep: 130.31 | bwd_allreduce_microstep: 274.61 | step_microstep: 28.39 +[2025-05-01 22:53:15,369] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4487.57 | bwd: 7991.90 | bwd_inner: 7716.95 | bwd_allreduce: 274.69 | step: 53.21 + 3%|▎ | 231/8720 [37:49<30:24:32, 12.90s/it] {'loss': 1.5309, 'grad_norm': 5.423489093780518, 'learning_rate': 8.816793893129772e-06, 'epoch': 0.26} + 3%|▎ | 231/8720 [37:49<30:24:32, 12.90s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1912 +[2025-05-01 22:53:16,292] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 396.51 | bwd_microstep: 505.36 | bwd_inner_microstep: 505.34 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-01 22:53:17,207] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 349.45 | bwd_microstep: 549.72 | bwd_inner_microstep: 549.71 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-01 22:53:18,117] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 277.01 | bwd_microstep: 613.17 | bwd_inner_microstep: 613.15 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-01 22:53:18,969] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 207.94 | bwd_microstep: 624.30 | bwd_inner_microstep: 624.28 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-01 22:53:19,810] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 220.06 | bwd_microstep: 589.07 | bwd_inner_microstep: 589.05 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-01 22:53:20,649] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 268.80 | bwd_microstep: 536.05 | bwd_inner_microstep: 536.04 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 845 +[2025-05-01 22:53:21,036] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 216.80 | bwd_microstep: 139.93 | bwd_inner_microstep: 139.91 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-01 22:53:21,949] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 371.23 | bwd_microstep: 526.20 | bwd_inner_microstep: 526.18 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 22:53:22,867] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 316.98 | bwd_microstep: 581.65 | bwd_inner_microstep: 581.63 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 22:53:23,747] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 239.68 | bwd_microstep: 620.54 | bwd_inner_microstep: 620.52 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 321 +[2025-05-01 22:53:23,962] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 71.89 | bwd_microstep: 120.41 | bwd_inner_microstep: 120.28 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-01 22:53:24,864] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 423.96 | bwd_microstep: 461.40 | bwd_inner_microstep: 461.38 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 827 +[2025-05-01 22:53:25,333] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 160.59 | bwd_microstep: 291.84 | bwd_inner_microstep: 291.82 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 826 +[2025-05-01 22:53:25,747] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 220.05 | bwd_microstep: 166.56 | bwd_inner_microstep: 166.54 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.11 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1122 +[2025-05-01 22:53:26,304] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 171.44 | bwd_microstep: 368.46 | bwd_inner_microstep: 368.45 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.54 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-01 22:53:27,508] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 5.05 | optimizer_step: 18.88 +[2025-05-01 22:53:27,509] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 316.78 | bwd_microstep: 826.10 | bwd_inner_microstep: 503.63 | bwd_allreduce_microstep: 322.42 | step_microstep: 29.41 +[2025-05-01 22:53:27,510] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4229.02 | bwd: 7520.81 | bwd_inner: 7197.96 | bwd_allreduce: 322.55 | step: 45.30 + 3%|▎ | 232/8720 [38:01<29:52:25, 12.67s/it] {'loss': 1.8859, 'grad_norm': 5.951263427734375, 'learning_rate': 8.85496183206107e-06, 'epoch': 0.27} + 3%|▎ | 232/8720 [38:01<29:52:25, 12.67s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-01 22:53:28,429] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 396.97 | bwd_microstep: 498.57 | bwd_inner_microstep: 498.56 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1883 +[2025-05-01 22:53:29,347] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 341.21 | bwd_microstep: 559.92 | bwd_inner_microstep: 559.90 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.17 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-01 22:53:30,254] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 272.48 | bwd_microstep: 614.68 | bwd_inner_microstep: 614.67 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.02 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-01 22:53:31,093] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 197.49 | bwd_microstep: 621.64 | bwd_inner_microstep: 621.62 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-01 22:53:31,938] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 231.17 | bwd_microstep: 577.09 | bwd_inner_microstep: 577.05 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.54 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 22:53:32,790] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 279.12 | bwd_microstep: 537.09 | bwd_inner_microstep: 537.07 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 22:53:33,654] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 327.30 | bwd_microstep: 502.53 | bwd_inner_microstep: 502.51 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.28 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-01 22:53:34,444] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 325.84 | bwd_microstep: 433.11 | bwd_inner_microstep: 433.09 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.21 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 834 +[2025-05-01 22:53:34,859] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 202.11 | bwd_microstep: 196.87 | bwd_inner_microstep: 196.65 | bwd_allreduce_microstep: 0.21 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 22:53:35,686] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 314.10 | bwd_microstep: 486.22 | bwd_inner_microstep: 486.20 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 22:53:36,497] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 326.96 | bwd_microstep: 465.96 | bwd_inner_microstep: 465.94 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.93 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 22:53:37,325] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 312.07 | bwd_microstep: 486.81 | bwd_inner_microstep: 486.79 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 22:53:38,140] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 328.47 | bwd_microstep: 466.10 | bwd_inner_microstep: 466.08 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.25 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-01 22:53:38,964] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 315.76 | bwd_microstep: 481.31 | bwd_inner_microstep: 481.29 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 828 +[2025-05-01 22:53:39,338] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 144.95 | bwd_microstep: 214.27 | bwd_inner_microstep: 214.06 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1890 +[2025-05-01 22:53:40,362] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.42 | optimizer_step: 17.21 +[2025-05-01 22:53:40,364] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 322.63 | bwd_microstep: 655.90 | bwd_inner_microstep: 505.29 | bwd_allreduce_microstep: 150.59 | step_microstep: 27.94 +[2025-05-01 22:53:40,365] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4638.51 | bwd: 7798.09 | bwd_inner: 7646.86 | bwd_allreduce: 150.72 | step: 41.51 + 3%|▎ | 233/8720 [38:14<30:00:03, 12.73s/it] {'loss': 1.4763, 'grad_norm': 5.731655597686768, 'learning_rate': 8.893129770992368e-06, 'epoch': 0.27} + 3%|▎ | 233/8720 [38:14<30:00:03, 12.73s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1889 +[2025-05-01 22:53:41,194] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 317.29 | bwd_microstep: 470.94 | bwd_inner_microstep: 470.92 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-01 22:53:42,024] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 328.75 | bwd_microstep: 479.97 | bwd_inner_microstep: 479.95 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1355 +[2025-05-01 22:53:42,637] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 227.55 | bwd_microstep: 355.84 | bwd_inner_microstep: 355.64 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-01 22:53:43,466] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 312.78 | bwd_microstep: 487.95 | bwd_inner_microstep: 487.93 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-01 22:53:44,278] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 327.55 | bwd_microstep: 466.15 | bwd_inner_microstep: 466.14 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-01 22:53:45,107] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 317.58 | bwd_microstep: 484.83 | bwd_inner_microstep: 484.81 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-01 22:53:45,915] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 330.84 | bwd_microstep: 455.98 | bwd_inner_microstep: 455.96 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 22:53:46,756] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 311.11 | bwd_microstep: 498.36 | bwd_inner_microstep: 498.34 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-01 22:53:47,542] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 328.31 | bwd_microstep: 436.69 | bwd_inner_microstep: 436.67 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.30 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 22:53:48,392] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 322.41 | bwd_microstep: 497.73 | bwd_inner_microstep: 497.72 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.87 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 22:53:49,176] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 327.79 | bwd_microstep: 433.41 | bwd_inner_microstep: 433.39 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 22:53:50,029] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 323.45 | bwd_microstep: 496.43 | bwd_inner_microstep: 496.41 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.87 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-01 22:53:50,791] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 325.52 | bwd_microstep: 419.36 | bwd_inner_microstep: 419.34 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 22:53:51,632] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 317.16 | bwd_microstep: 494.32 | bwd_inner_microstep: 494.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.30 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 22:53:52,408] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 324.49 | bwd_microstep: 426.65 | bwd_inner_microstep: 426.63 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1120 +[2025-05-01 22:53:53,098] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.41 | optimizer_step: 17.20 +[2025-05-01 22:53:53,101] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 246.70 | bwd_microstep: 399.98 | bwd_inner_microstep: 273.31 | bwd_allreduce_microstep: 126.66 | step_microstep: 28.19 +[2025-05-01 22:53:53,102] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4989.18 | bwd: 7304.59 | bwd_inner: 7177.48 | bwd_allreduce: 126.91 | step: 42.07 + 3%|▎ | 234/8720 [38:26<30:00:17, 12.73s/it] {'loss': 1.7771, 'grad_norm': 8.354982376098633, 'learning_rate': 8.931297709923665e-06, 'epoch': 0.27} + 3%|▎ | 234/8720 [38:26<30:00:17, 12.73s/it]dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 941 +[2025-05-01 22:53:53,571] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 146.16 | bwd_microstep: 284.79 | bwd_inner_microstep: 284.50 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.09 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 392 +[2025-05-01 22:53:53,838] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 100.42 | bwd_microstep: 149.19 | bwd_inner_microstep: 149.17 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 362 +[2025-05-01 22:53:54,103] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 100.71 | bwd_microstep: 139.91 | bwd_inner_microstep: 139.89 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.29 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-01 22:53:54,893] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 322.75 | bwd_microstep: 438.65 | bwd_inner_microstep: 438.63 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 22:53:55,730] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 326.92 | bwd_microstep: 490.58 | bwd_inner_microstep: 490.56 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1350 +[2025-05-01 22:53:56,331] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 221.00 | bwd_microstep: 351.91 | bwd_inner_microstep: 351.89 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.68 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-01 22:53:57,156] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 311.79 | bwd_microstep: 478.52 | bwd_inner_microstep: 478.50 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.13 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 22:53:57,961] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 323.04 | bwd_microstep: 464.57 | bwd_inner_microstep: 464.55 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.73 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 22:53:58,792] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 314.42 | bwd_microstep: 488.35 | bwd_inner_microstep: 488.34 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 22:53:59,591] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 326.87 | bwd_microstep: 452.15 | bwd_inner_microstep: 452.13 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.31 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 22:54:00,429] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 314.82 | bwd_microstep: 491.04 | bwd_inner_microstep: 491.03 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 22:54:01,224] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 326.41 | bwd_microstep: 446.00 | bwd_inner_microstep: 445.98 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 22:54:02,066] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 315.62 | bwd_microstep: 497.58 | bwd_inner_microstep: 497.56 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.88 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 22:54:02,852] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 327.58 | bwd_microstep: 436.94 | bwd_inner_microstep: 436.92 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.30 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-01 22:54:03,699] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 323.06 | bwd_microstep: 492.36 | bwd_inner_microstep: 492.34 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.87 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 1105 +[2025-05-01 22:54:04,380] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.54 | optimizer_step: 18.50 +[2025-05-01 22:54:04,382] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 154.67 | bwd_microstep: 481.97 | bwd_inner_microstep: 259.46 | bwd_allreduce_microstep: 222.49 | step_microstep: 28.14 +[2025-05-01 22:54:04,383] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4256.11 | bwd: 6584.53 | bwd_inner: 6361.50 | bwd_allreduce: 222.69 | step: 45.93 + 3%|▎ | 235/8720 [38:38<28:58:31, 12.29s/it] {'loss': 1.2082, 'grad_norm': 5.58733606338501, 'learning_rate': 8.969465648854963e-06, 'epoch': 0.27} + 3%|▎ | 235/8720 [38:38<28:58:31, 12.29s/it]dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1427 +[2025-05-01 22:54:05,023] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 236.13 | bwd_microstep: 368.85 | bwd_inner_microstep: 368.83 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.67 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1906 +[2025-05-01 22:54:05,853] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 318.98 | bwd_microstep: 479.80 | bwd_inner_microstep: 479.78 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-01 22:54:06,662] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 326.24 | bwd_microstep: 464.49 | bwd_inner_microstep: 464.47 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.27 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1353 +[2025-05-01 22:54:07,278] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 220.85 | bwd_microstep: 367.27 | bwd_inner_microstep: 367.25 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.48 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1361 +[2025-05-01 22:54:07,895] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 219.77 | bwd_microstep: 365.92 | bwd_inner_microstep: 365.90 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.48 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-01 22:54:08,737] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 317.08 | bwd_microstep: 501.89 | bwd_inner_microstep: 501.87 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.88 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 22:54:09,516] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 326.31 | bwd_microstep: 432.95 | bwd_inner_microstep: 432.93 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.50 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-01 22:54:10,401] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 370.34 | bwd_microstep: 482.13 | bwd_inner_microstep: 482.11 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 22:54:11,216] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 327.69 | bwd_microstep: 462.53 | bwd_inner_microstep: 462.51 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.33 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 834 +[2025-05-01 22:54:11,632] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 146.27 | bwd_microstep: 239.64 | bwd_inner_microstep: 239.61 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1090 +[2025-05-01 22:54:12,094] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 175.43 | bwd_microstep: 262.02 | bwd_inner_microstep: 262.00 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.31 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 833 +[2025-05-01 22:54:12,506] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 178.31 | bwd_microstep: 201.82 | bwd_inner_microstep: 201.80 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 22:54:13,309] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 318.22 | bwd_microstep: 450.78 | bwd_inner_microstep: 450.77 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 22:54:14,134] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 325.00 | bwd_microstep: 476.57 | bwd_inner_microstep: 476.55 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.33 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 829 +[2025-05-01 22:54:14,551] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 127.70 | bwd_microstep: 256.32 | bwd_inner_microstep: 256.31 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.58 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2323 +[2025-05-01 22:54:15,675] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.33 | optimizer_step: 17.91 +[2025-05-01 22:54:15,676] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 358.46 | bwd_microstep: 723.27 | bwd_inner_microstep: 586.17 | bwd_allreduce_microstep: 137.09 | step_microstep: 27.40 +[2025-05-01 22:54:15,677] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4292.67 | bwd: 6536.25 | bwd_inner: 6398.88 | bwd_allreduce: 137.15 | step: 50.10 + 3%|▎ | 236/8720 [38:49<28:16:03, 11.99s/it] {'loss': 1.6919, 'grad_norm': 4.255095481872559, 'learning_rate': 9.007633587786259e-06, 'epoch': 0.27} + 3%|▎ | 236/8720 [38:49<28:16:03, 11.99s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2141 +[2025-05-01 22:54:16,571] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 339.10 | bwd_microstep: 512.18 | bwd_inner_microstep: 512.16 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1911 +[2025-05-01 22:54:17,596] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 432.77 | bwd_microstep: 554.00 | bwd_inner_microstep: 553.99 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1886 +[2025-05-01 22:54:18,492] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 383.50 | bwd_microstep: 490.06 | bwd_inner_microstep: 490.05 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.52 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 345 +[2025-05-01 22:54:18,757] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 106.35 | bwd_microstep: 127.93 | bwd_inner_microstep: 127.73 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-01 22:54:19,703] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 420.94 | bwd_microstep: 495.80 | bwd_inner_microstep: 495.78 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.47 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-01 22:54:20,576] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 209.29 | bwd_microstep: 629.44 | bwd_inner_microstep: 629.42 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.45 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 22:54:21,532] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 387.51 | bwd_microstep: 529.62 | bwd_inner_microstep: 529.60 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.64 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-01 22:54:22,351] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 299.39 | bwd_microstep: 499.81 | bwd_inner_microstep: 499.79 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 22:54:23,279] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 353.85 | bwd_microstep: 540.97 | bwd_inner_microstep: 540.95 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 22:54:24,132] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 327.91 | bwd_microstep: 502.63 | bwd_inner_microstep: 502.61 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.83 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1342 +[2025-05-01 22:54:24,830] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 262.87 | bwd_microstep: 399.35 | bwd_inner_microstep: 399.33 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 317 +[2025-05-01 22:54:25,095] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 91.28 | bwd_microstep: 138.60 | bwd_inner_microstep: 138.58 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 22:54:26,019] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 356.94 | bwd_microstep: 532.62 | bwd_inner_microstep: 532.60 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.95 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1935 +[2025-05-01 22:54:26,892] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 317.11 | bwd_microstep: 537.60 | bwd_inner_microstep: 537.59 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 391 +[2025-05-01 22:54:27,172] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 119.00 | bwd_microstep: 134.01 | bwd_inner_microstep: 133.70 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1899 +[2025-05-01 22:54:28,653] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 3.18 | optimizer_step: 19.81 +[2025-05-01 22:54:28,655] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 365.18 | bwd_microstep: 1067.73 | bwd_inner_microstep: 422.37 | bwd_allreduce_microstep: 645.31 | step_microstep: 30.22 +[2025-05-01 22:54:28,656] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4772.91 | bwd: 7692.43 | bwd_inner: 7046.39 | bwd_allreduce: 645.57 | step: 51.22 + 3%|▎ | 237/8720 [39:02<28:57:38, 12.29s/it] {'loss': 1.5876, 'grad_norm': 5.662167549133301, 'learning_rate': 9.045801526717559e-06, 'epoch': 0.27} + 3%|▎ | 237/8720 [39:02<28:57:38, 12.29s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2142 +[2025-05-01 22:54:29,667] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 391.55 | bwd_microstep: 578.86 | bwd_inner_microstep: 578.82 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1940 +[2025-05-01 22:54:30,604] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 385.68 | bwd_microstep: 525.89 | bwd_inner_microstep: 525.87 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 389 +[2025-05-01 22:54:30,874] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 107.64 | bwd_microstep: 130.49 | bwd_inner_microstep: 130.47 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1896 +[2025-05-01 22:54:31,835] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 395.11 | bwd_microstep: 532.77 | bwd_inner_microstep: 532.75 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.30 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-01 22:54:32,662] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 299.69 | bwd_microstep: 508.89 | bwd_inner_microstep: 508.87 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-01 22:54:33,584] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 343.98 | bwd_microstep: 542.32 | bwd_inner_microstep: 542.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-01 22:54:34,456] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 356.15 | bwd_microstep: 491.53 | bwd_inner_microstep: 491.51 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-01 22:54:35,326] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 310.16 | bwd_microstep: 528.37 | bwd_inner_microstep: 528.36 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-01 22:54:36,237] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 397.30 | bwd_microstep: 490.62 | bwd_inner_microstep: 490.60 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.33 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 22:54:37,067] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 300.67 | bwd_microstep: 497.62 | bwd_inner_microstep: 497.60 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 22:54:38,052] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 339.05 | bwd_microstep: 624.61 | bwd_inner_microstep: 624.59 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.54 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 22:54:38,881] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 281.32 | bwd_microstep: 516.18 | bwd_inner_microstep: 516.16 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 22:54:39,795] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 407.01 | bwd_microstep: 487.36 | bwd_inner_microstep: 487.35 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.51 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 22:54:40,616] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 297.48 | bwd_microstep: 490.83 | bwd_inner_microstep: 490.81 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 22:54:41,483] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 416.39 | bwd_microstep: 420.77 | bwd_inner_microstep: 420.76 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1850 +[2025-05-01 22:54:42,787] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.39 | optimizer_step: 18.63 +[2025-05-01 22:54:42,789] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 421.37 | bwd_microstep: 824.69 | bwd_inner_microstep: 494.35 | bwd_allreduce_microstep: 330.30 | step_microstep: 28.06 +[2025-05-01 22:54:42,790] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 5450.46 | bwd: 8191.79 | bwd_inner: 7858.82 | bwd_allreduce: 330.38 | step: 48.78 + 3%|▎ | 238/8720 [39:16<30:15:36, 12.84s/it] {'loss': 1.9569, 'grad_norm': 6.887767791748047, 'learning_rate': 9.083969465648855e-06, 'epoch': 0.27} + 3%|▎ | 238/8720 [39:16<30:15:36, 12.84s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 400 +[2025-05-01 22:54:43,112] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 113.23 | bwd_microstep: 168.60 | bwd_inner_microstep: 168.58 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1933 +[2025-05-01 22:54:43,986] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 315.47 | bwd_microstep: 537.21 | bwd_inner_microstep: 537.19 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1894 +[2025-05-01 22:54:44,886] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 326.22 | bwd_microstep: 542.22 | bwd_inner_microstep: 542.20 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-01 22:54:45,692] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 367.61 | bwd_microstep: 417.23 | bwd_inner_microstep: 417.21 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-01 22:54:46,697] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 423.65 | bwd_microstep: 547.80 | bwd_inner_microstep: 547.78 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-01 22:54:47,599] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 387.31 | bwd_microstep: 489.82 | bwd_inner_microstep: 489.80 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.53 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 336 +[2025-05-01 22:54:47,851] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 100.73 | bwd_microstep: 122.94 | bwd_inner_microstep: 122.87 | bwd_allreduce_microstep: 0.03 | step_microstep: 0.10 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 323 +[2025-05-01 22:54:48,093] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 92.72 | bwd_microstep: 133.17 | bwd_inner_microstep: 133.15 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.32 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 22:54:48,948] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 299.23 | bwd_microstep: 522.15 | bwd_inner_microstep: 522.13 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 22:54:49,870] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 408.33 | bwd_microstep: 491.52 | bwd_inner_microstep: 491.50 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.32 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 323 +[2025-05-01 22:54:50,108] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.49 | bwd_microstep: 114.66 | bwd_inner_microstep: 114.48 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 22:54:51,131] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 381.57 | bwd_microstep: 619.87 | bwd_inner_microstep: 619.85 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-01 22:54:51,937] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 284.70 | bwd_microstep: 487.24 | bwd_inner_microstep: 487.22 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 22:54:52,882] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 385.99 | bwd_microstep: 520.84 | bwd_inner_microstep: 520.82 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.31 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 827 +[2025-05-01 22:54:53,206] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 99.14 | bwd_microstep: 205.25 | bwd_inner_microstep: 205.23 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.30 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1921 +[2025-05-01 22:54:54,595] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.70 | optimizer_step: 17.04 +[2025-05-01 22:54:54,596] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 441.08 | bwd_microstep: 891.16 | bwd_inner_microstep: 533.20 | bwd_allreduce_microstep: 357.91 | step_microstep: 25.09 +[2025-05-01 22:54:54,597] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4520.36 | bwd: 6811.71 | bwd_inner: 6453.28 | bwd_allreduce: 358.10 | step: 48.94 + 3%|▎ | 239/8720 [39:28<29:31:25, 12.53s/it] {'loss': 1.483, 'grad_norm': 4.173028945922852, 'learning_rate': 9.122137404580154e-06, 'epoch': 0.27} + 3%|▎ | 239/8720 [39:28<29:31:25, 12.53s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-01 22:54:55,558] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 390.67 | bwd_microstep: 527.64 | bwd_inner_microstep: 527.62 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.50 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-01 22:54:56,368] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 299.30 | bwd_microstep: 491.66 | bwd_inner_microstep: 491.64 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 845 +[2025-05-01 22:54:56,800] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 206.47 | bwd_microstep: 195.03 | bwd_inner_microstep: 194.65 | bwd_allreduce_microstep: 0.14 | step_microstep: 0.22 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-01 22:54:57,735] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 418.85 | bwd_microstep: 496.20 | bwd_inner_microstep: 496.18 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 6, images per sample: 6.0, dynamic token length: 1613 +[2025-05-01 22:54:58,475] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 248.42 | bwd_microstep: 461.52 | bwd_inner_microstep: 461.50 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 22:54:59,446] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 317.95 | bwd_microstep: 633.20 | bwd_inner_microstep: 633.18 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1358 +[2025-05-01 22:55:00,130] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 227.19 | bwd_microstep: 426.52 | bwd_inner_microstep: 426.50 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-01 22:55:00,996] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 213.96 | bwd_microstep: 620.91 | bwd_inner_microstep: 620.89 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.28 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 22:55:01,945] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 389.54 | bwd_microstep: 526.55 | bwd_inner_microstep: 526.53 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.26 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 22:55:02,752] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 295.47 | bwd_microstep: 492.19 | bwd_inner_microstep: 492.17 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.30 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 833 +[2025-05-01 22:55:03,173] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 198.68 | bwd_microstep: 190.34 | bwd_inner_microstep: 190.19 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.12 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1350 +[2025-05-01 22:55:03,839] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 297.70 | bwd_microstep: 350.09 | bwd_inner_microstep: 350.08 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 22:55:04,775] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 373.89 | bwd_microstep: 529.65 | bwd_inner_microstep: 529.64 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.71 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 22:55:05,588] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 297.53 | bwd_microstep: 496.12 | bwd_inner_microstep: 496.10 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-01 22:55:06,514] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 355.24 | bwd_microstep: 538.50 | bwd_inner_microstep: 538.48 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.38 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1897 +[2025-05-01 22:55:07,776] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.24 | optimizer_step: 18.78 +[2025-05-01 22:55:07,778] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 240.41 | bwd_microstep: 978.09 | bwd_inner_microstep: 633.35 | bwd_allreduce_microstep: 342.41 | step_microstep: 28.18 +[2025-05-01 22:55:07,779] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4771.22 | bwd: 7954.27 | bwd_inner: 7608.80 | bwd_allreduce: 342.69 | step: 54.12 + 3%|▎ | 240/8720 [39:41<29:58:47, 12.73s/it] {'loss': 1.1563, 'grad_norm': 6.30047082901001, 'learning_rate': 9.16030534351145e-06, 'epoch': 0.28} + 3%|▎ | 240/8720 [39:41<29:58:47, 12.73s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2141 +[2025-05-01 22:55:08,783] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 384.00 | bwd_microstep: 579.41 | bwd_inner_microstep: 579.39 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2041 +[2025-05-01 22:55:09,827] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 328.15 | bwd_microstep: 686.42 | bwd_inner_microstep: 686.40 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.46 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1893 +[2025-05-01 22:55:10,652] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 289.35 | bwd_microstep: 500.90 | bwd_inner_microstep: 500.88 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-01 22:55:11,606] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 416.90 | bwd_microstep: 505.69 | bwd_inner_microstep: 505.67 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.33 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-01 22:55:12,439] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 301.96 | bwd_microstep: 497.21 | bwd_inner_microstep: 497.19 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 22:55:13,370] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 355.42 | bwd_microstep: 541.20 | bwd_inner_microstep: 541.16 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 842 +[2025-05-01 22:55:13,802] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 119.88 | bwd_microstep: 293.00 | bwd_inner_microstep: 292.98 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 22:55:14,605] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 305.78 | bwd_microstep: 462.89 | bwd_inner_microstep: 462.87 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 22:55:15,644] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 390.86 | bwd_microstep: 625.15 | bwd_inner_microstep: 625.13 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 22:55:16,448] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 287.77 | bwd_microstep: 482.76 | bwd_inner_microstep: 482.74 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 22:55:17,390] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 389.28 | bwd_microstep: 518.96 | bwd_inner_microstep: 518.94 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 22:55:18,242] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 212.38 | bwd_microstep: 617.09 | bwd_inner_microstep: 617.07 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 22:55:19,106] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 386.78 | bwd_microstep: 445.47 | bwd_inner_microstep: 445.45 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 22:55:19,999] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 427.40 | bwd_microstep: 432.90 | bwd_inner_microstep: 432.88 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 367 +[2025-05-01 22:55:20,265] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.27 | bwd_microstep: 156.38 | bwd_inner_microstep: 156.36 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 22:55:21,573] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.28 | optimizer_step: 18.73 +[2025-05-01 22:55:21,575] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 422.26 | bwd_microstep: 830.58 | bwd_inner_microstep: 500.05 | bwd_allreduce_microstep: 330.49 | step_microstep: 27.58 +[2025-05-01 22:55:21,577] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 5112.37 | bwd: 8176.02 | bwd_inner: 7845.21 | bwd_allreduce: 330.57 | step: 51.47 + 3%|▎ | 241/8720 [39:55<30:43:55, 13.05s/it] {'loss': 1.203, 'grad_norm': 4.038529396057129, 'learning_rate': 9.19847328244275e-06, 'epoch': 0.28} + 3%|▎ | 241/8720 [39:55<30:43:55, 13.05s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1952 +[2025-05-01 22:55:22,553] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 381.26 | bwd_microstep: 555.24 | bwd_inner_microstep: 555.22 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1887 +[2025-05-01 22:55:23,306] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 327.25 | bwd_microstep: 408.01 | bwd_inner_microstep: 407.99 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-01 22:55:24,200] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 380.15 | bwd_microstep: 496.04 | bwd_inner_microstep: 496.02 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 834 +[2025-05-01 22:55:24,528] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 171.57 | bwd_microstep: 128.33 | bwd_inner_microstep: 128.23 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-01 22:55:25,596] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 424.73 | bwd_microstep: 625.07 | bwd_inner_microstep: 625.06 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-01 22:55:26,422] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 299.78 | bwd_microstep: 506.51 | bwd_inner_microstep: 506.49 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 22:55:27,339] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 344.90 | bwd_microstep: 540.89 | bwd_inner_microstep: 540.87 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 318 +[2025-05-01 22:55:27,556] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 77.18 | bwd_microstep: 123.45 | bwd_inner_microstep: 123.44 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 22:55:28,566] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 428.08 | bwd_microstep: 550.34 | bwd_inner_microstep: 550.33 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 22:55:29,503] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 291.21 | bwd_microstep: 621.43 | bwd_inner_microstep: 621.41 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 317 +[2025-05-01 22:55:29,740] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 97.05 | bwd_microstep: 110.35 | bwd_inner_microstep: 110.22 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 22:55:30,605] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 228.09 | bwd_microstep: 615.65 | bwd_inner_microstep: 615.63 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.53 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1850 +[2025-05-01 22:55:31,463] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 366.28 | bwd_microstep: 459.82 | bwd_inner_microstep: 459.80 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1908 +[2025-05-01 22:55:32,349] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 433.40 | bwd_microstep: 422.55 | bwd_inner_microstep: 422.53 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1899 +[2025-05-01 22:55:33,420] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 417.19 | bwd_microstep: 635.40 | bwd_inner_microstep: 635.38 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-01 22:55:34,708] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.26 | optimizer_step: 16.69 +[2025-05-01 22:55:34,711] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 292.18 | bwd_microstep: 950.71 | bwd_inner_microstep: 445.99 | bwd_allreduce_microstep: 504.71 | step_microstep: 28.40 +[2025-05-01 22:55:34,712] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4960.18 | bwd: 7749.81 | bwd_inner: 7244.64 | bwd_allreduce: 504.87 | step: 44.18 + 3%|▎ | 242/8720 [40:08<30:47:24, 13.07s/it] {'loss': 1.9632, 'grad_norm': 6.638192176818848, 'learning_rate': 9.236641221374046e-06, 'epoch': 0.28} + 3%|▎ | 242/8720 [40:08<30:47:24, 13.07s/it]dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 987 +[2025-05-01 22:55:35,179] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 129.62 | bwd_microstep: 297.58 | bwd_inner_microstep: 297.56 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1893 +[2025-05-01 22:55:36,021] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 301.73 | bwd_microstep: 508.20 | bwd_inner_microstep: 508.19 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1889 +[2025-05-01 22:55:36,883] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 423.16 | bwd_microstep: 420.88 | bwd_inner_microstep: 420.86 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1368 +[2025-05-01 22:55:37,702] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 313.86 | bwd_microstep: 473.49 | bwd_inner_microstep: 473.47 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-01 22:55:38,551] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 205.20 | bwd_microstep: 623.53 | bwd_inner_microstep: 623.51 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.50 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-01 22:55:39,408] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 385.98 | bwd_microstep: 436.57 | bwd_inner_microstep: 436.55 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-01 22:55:40,365] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 428.44 | bwd_microstep: 490.82 | bwd_inner_microstep: 490.80 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.32 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-01 22:55:41,299] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 360.40 | bwd_microstep: 540.34 | bwd_inner_microstep: 540.32 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-01 22:55:42,134] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 308.00 | bwd_microstep: 506.63 | bwd_inner_microstep: 506.61 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 22:55:43,040] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 342.51 | bwd_microstep: 541.26 | bwd_inner_microstep: 541.24 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 22:55:43,908] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 357.23 | bwd_microstep: 488.17 | bwd_inner_microstep: 488.15 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 839 +[2025-05-01 22:55:44,321] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 201.23 | bwd_microstep: 179.56 | bwd_inner_microstep: 179.54 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 22:55:45,258] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 360.03 | bwd_microstep: 542.69 | bwd_inner_microstep: 542.67 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 22:55:46,114] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 328.56 | bwd_microstep: 501.84 | bwd_inner_microstep: 501.82 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 22:55:47,003] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 323.20 | bwd_microstep: 538.37 | bwd_inner_microstep: 538.35 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 22:55:48,160] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 3.25 | optimizer_step: 17.71 +[2025-05-01 22:55:48,161] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 373.16 | bwd_microstep: 733.98 | bwd_inner_microstep: 488.33 | bwd_allreduce_microstep: 245.64 | step_microstep: 28.15 +[2025-05-01 22:55:48,162] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 5142.20 | bwd: 7823.92 | bwd_inner: 7578.00 | bwd_allreduce: 245.71 | step: 48.91 + 3%|▎ | 243/8720 [40:21<31:03:08, 13.19s/it] {'loss': 1.9269, 'grad_norm': 4.548322677612305, 'learning_rate': 9.274809160305345e-06, 'epoch': 0.28} + 3%|▎ | 243/8720 [40:21<31:03:08, 13.19s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1942 +[2025-05-01 22:55:49,086] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 367.26 | bwd_microstep: 517.12 | bwd_inner_microstep: 517.10 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 895 +[2025-05-01 22:55:49,669] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 228.95 | bwd_microstep: 326.71 | bwd_inner_microstep: 326.69 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.86 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1902 +[2025-05-01 22:55:50,435] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 298.84 | bwd_microstep: 449.26 | bwd_inner_microstep: 449.24 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1909 +[2025-05-01 22:55:51,505] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 414.41 | bwd_microstep: 637.52 | bwd_inner_microstep: 637.50 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.53 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-01 22:55:52,316] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 295.46 | bwd_microstep: 491.70 | bwd_inner_microstep: 491.69 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.50 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-01 22:55:53,256] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 369.60 | bwd_microstep: 537.38 | bwd_inner_microstep: 537.36 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.98 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-01 22:55:54,085] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 299.69 | bwd_microstep: 510.51 | bwd_inner_microstep: 510.49 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-01 22:55:54,966] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 342.14 | bwd_microstep: 504.08 | bwd_inner_microstep: 504.06 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-01 22:55:55,926] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 444.62 | bwd_microstep: 481.09 | bwd_inner_microstep: 481.07 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 22:55:56,795] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 309.38 | bwd_microstep: 527.16 | bwd_inner_microstep: 527.09 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.07 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1352 +[2025-05-01 22:55:57,451] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 283.60 | bwd_microstep: 354.65 | bwd_inner_microstep: 354.63 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1093 +[2025-05-01 22:55:57,993] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 252.62 | bwd_microstep: 257.38 | bwd_inner_microstep: 257.36 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.33 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 22:55:58,852] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 323.35 | bwd_microstep: 499.67 | bwd_inner_microstep: 499.65 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 22:55:59,718] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 347.59 | bwd_microstep: 486.71 | bwd_inner_microstep: 486.69 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 22:56:00,604] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 369.98 | bwd_microstep: 487.92 | bwd_inner_microstep: 487.90 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 22:56:01,828] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.25 | optimizer_step: 26.68 +[2025-05-01 22:56:01,829] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 394.09 | bwd_microstep: 779.96 | bwd_inner_microstep: 492.19 | bwd_allreduce_microstep: 287.72 | step_microstep: 34.25 +[2025-05-01 22:56:01,830] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 5341.48 | bwd: 7848.85 | bwd_inner: 7560.77 | bwd_allreduce: 287.81 | step: 56.60 + 3%|▎ | 244/8720 [40:35<31:23:10, 13.33s/it] {'loss': 1.3617, 'grad_norm': 5.065046310424805, 'learning_rate': 9.312977099236641e-06, 'epoch': 0.28} + 3%|▎ | 244/8720 [40:35<31:23:10, 13.33s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1897 +[2025-05-01 22:56:02,738] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 395.89 | bwd_microstep: 489.96 | bwd_inner_microstep: 489.94 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1358 +[2025-05-01 22:56:03,371] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 251.80 | bwd_microstep: 364.28 | bwd_inner_microstep: 364.14 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-01 22:56:04,264] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 371.39 | bwd_microstep: 504.57 | bwd_inner_microstep: 504.55 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.91 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1110 +[2025-05-01 22:56:04,772] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 169.84 | bwd_microstep: 321.07 | bwd_inner_microstep: 320.96 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 22:56:05,617] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 371.86 | bwd_microstep: 452.17 | bwd_inner_microstep: 452.15 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1353 +[2025-05-01 22:56:06,328] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 275.69 | bwd_microstep: 403.26 | bwd_inner_microstep: 403.24 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.54 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 847 +[2025-05-01 22:56:06,758] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 117.50 | bwd_microstep: 293.90 | bwd_inner_microstep: 293.88 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 22:56:07,615] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 322.31 | bwd_microstep: 511.41 | bwd_inner_microstep: 511.39 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.28 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 22:56:08,480] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 315.65 | bwd_microstep: 514.68 | bwd_inner_microstep: 514.67 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.48 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-01 22:56:09,279] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 317.93 | bwd_microstep: 449.21 | bwd_inner_microstep: 449.19 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 22:56:10,165] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 369.73 | bwd_microstep: 488.21 | bwd_inner_microstep: 488.16 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.13 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 22:56:11,069] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 400.74 | bwd_microstep: 485.98 | bwd_inner_microstep: 485.96 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 22:56:11,957] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 365.37 | bwd_microstep: 505.54 | bwd_inner_microstep: 505.53 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.92 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 22:56:12,749] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 263.86 | bwd_microstep: 508.50 | bwd_inner_microstep: 508.48 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.36 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 993 +[2025-05-01 22:56:13,246] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 224.17 | bwd_microstep: 244.43 | bwd_inner_microstep: 244.06 | bwd_allreduce_microstep: 0.18 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-01 22:56:14,462] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 2.33 | optimizer_gradients: 2.20 | optimizer_step: 16.74 +[2025-05-01 22:56:14,465] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 332.16 | bwd_microstep: 831.81 | bwd_inner_microstep: 524.14 | bwd_allreduce_microstep: 307.66 | step_microstep: 28.53 +[2025-05-01 22:56:14,466] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4865.79 | bwd: 7369.05 | bwd_inner: 7060.63 | bwd_allreduce: 308.03 | step: 45.43 + 3%|▎ | 245/8720 [40:48<30:53:36, 13.12s/it] {'loss': 1.958, 'grad_norm': 5.688141345977783, 'learning_rate': 9.351145038167939e-06, 'epoch': 0.28} + 3%|▎ | 245/8720 [40:48<30:53:36, 13.12s/it]dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1759 +[2025-05-01 22:56:15,240] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 264.74 | bwd_microstep: 470.71 | bwd_inner_microstep: 470.52 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1898 +[2025-05-01 22:56:16,108] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 350.93 | bwd_microstep: 491.45 | bwd_inner_microstep: 491.43 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1369 +[2025-05-01 22:56:16,763] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 271.28 | bwd_microstep: 368.06 | bwd_inner_microstep: 368.04 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 855 +[2025-05-01 22:56:17,219] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.01 | bwd_microstep: 234.70 | bwd_inner_microstep: 234.68 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.48 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-01 22:56:18,081] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 324.88 | bwd_microstep: 506.11 | bwd_inner_microstep: 506.09 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-01 22:56:18,943] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 337.94 | bwd_microstep: 492.10 | bwd_inner_microstep: 492.08 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 22:56:19,836] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 376.40 | bwd_microstep: 500.32 | bwd_inner_microstep: 500.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.95 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 22:56:20,658] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 299.19 | bwd_microstep: 505.76 | bwd_inner_microstep: 505.74 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-01 22:56:21,498] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 309.02 | bwd_microstep: 509.43 | bwd_inner_microstep: 509.41 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 22:56:22,360] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 315.74 | bwd_microstep: 512.38 | bwd_inner_microstep: 512.37 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.33 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 22:56:23,222] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 327.69 | bwd_microstep: 500.02 | bwd_inner_microstep: 500.00 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 22:56:24,091] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 327.83 | bwd_microstep: 510.05 | bwd_inner_microstep: 510.03 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 832 +[2025-05-01 22:56:24,523] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.98 | bwd_microstep: 214.82 | bwd_inner_microstep: 212.46 | bwd_allreduce_microstep: 2.34 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-01 22:56:25,383] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 318.54 | bwd_microstep: 507.65 | bwd_inner_microstep: 507.63 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1952 +[2025-05-01 22:56:26,303] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 350.28 | bwd_microstep: 536.56 | bwd_inner_microstep: 536.54 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1919 +[2025-05-01 22:56:27,549] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 4.15 | optimizer_step: 24.76 +[2025-05-01 22:56:27,549] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 321.20 | bwd_microstep: 857.99 | bwd_inner_microstep: 524.44 | bwd_allreduce_microstep: 333.51 | step_microstep: 34.93 +[2025-05-01 22:56:27,551] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4872.58 | bwd: 7718.12 | bwd_inner: 7381.78 | bwd_allreduce: 336.10 | step: 53.32 + 3%|▎ | 246/8720 [41:01<30:51:44, 13.11s/it] {'loss': 1.3911, 'grad_norm': 3.317754030227661, 'learning_rate': 9.389312977099237e-06, 'epoch': 0.28} + 3%|▎ | 246/8720 [41:01<30:51:44, 13.11s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1925 +[2025-05-01 22:56:28,478] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 397.09 | bwd_microstep: 507.79 | bwd_inner_microstep: 507.77 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-01 22:56:29,308] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 361.14 | bwd_microstep: 450.76 | bwd_inner_microstep: 450.74 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-01 22:56:30,186] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 327.17 | bwd_microstep: 521.36 | bwd_inner_microstep: 521.34 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-01 22:56:31,062] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 327.87 | bwd_microstep: 515.14 | bwd_inner_microstep: 515.13 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.51 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-01 22:56:31,940] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 330.22 | bwd_microstep: 515.93 | bwd_inner_microstep: 515.91 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-01 22:56:32,827] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 333.94 | bwd_microstep: 521.40 | bwd_inner_microstep: 521.38 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.22 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-01 22:56:33,704] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 331.47 | bwd_microstep: 518.20 | bwd_inner_microstep: 518.18 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.24 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 22:56:34,583] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 333.44 | bwd_microstep: 517.95 | bwd_inner_microstep: 517.93 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 323 +[2025-05-01 22:56:34,820] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 99.52 | bwd_microstep: 109.39 | bwd_inner_microstep: 109.26 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 22:56:35,719] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 390.32 | bwd_microstep: 493.21 | bwd_inner_microstep: 493.19 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 22:56:36,616] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 351.48 | bwd_microstep: 523.95 | bwd_inner_microstep: 523.93 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 22:56:37,423] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 307.22 | bwd_microstep: 484.07 | bwd_inner_microstep: 484.05 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.22 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 22:56:38,321] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 395.45 | bwd_microstep: 484.75 | bwd_inner_microstep: 484.73 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 22:56:39,120] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 388.77 | bwd_microstep: 391.65 | bwd_inner_microstep: 391.63 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 22:56:39,828] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 242.72 | bwd_microstep: 445.01 | bwd_inner_microstep: 444.99 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 460 +[2025-05-01 22:56:40,417] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 3.88 | optimizer_step: 25.98 +[2025-05-01 22:56:40,419] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 120.41 | bwd_microstep: 410.90 | bwd_inner_microstep: 123.29 | bwd_allreduce_microstep: 287.45 | step_microstep: 36.28 +[2025-05-01 22:56:40,420] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 5038.14 | bwd: 7411.50 | bwd_inner: 7123.56 | bwd_allreduce: 287.54 | step: 51.33 + 3%|▎ | 247/8720 [41:14<30:41:18, 13.04s/it] {'loss': 1.0681, 'grad_norm': 3.092055320739746, 'learning_rate': 9.427480916030534e-06, 'epoch': 0.28} + 3%|▎ | 247/8720 [41:14<30:41:18, 13.04s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1896 +[2025-05-01 22:56:41,311] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 349.36 | bwd_microstep: 499.60 | bwd_inner_microstep: 499.57 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.32 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-01 22:56:42,206] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 353.14 | bwd_microstep: 507.51 | bwd_inner_microstep: 507.49 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.28 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1370 +[2025-05-01 22:56:42,851] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 241.99 | bwd_microstep: 371.63 | bwd_inner_microstep: 371.61 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-01 22:56:43,724] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 316.15 | bwd_microstep: 522.55 | bwd_inner_microstep: 522.53 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-01 22:56:44,594] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 313.87 | bwd_microstep: 522.69 | bwd_inner_microstep: 522.67 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.32 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 22:56:45,409] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 298.86 | bwd_microstep: 486.13 | bwd_inner_microstep: 486.12 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 843 +[2025-05-01 22:56:45,860] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 192.45 | bwd_microstep: 243.38 | bwd_inner_microstep: 243.35 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 22:56:46,722] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 393.07 | bwd_microstep: 445.22 | bwd_inner_microstep: 445.20 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.51 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-01 22:56:47,581] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 325.36 | bwd_microstep: 498.77 | bwd_inner_microstep: 498.75 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 22:56:48,460] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 326.41 | bwd_microstep: 518.58 | bwd_inner_microstep: 518.56 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.75 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 22:56:49,299] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 348.25 | bwd_microstep: 461.26 | bwd_inner_microstep: 461.24 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 22:56:50,149] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 314.53 | bwd_microstep: 501.60 | bwd_inner_microstep: 501.58 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 830 +[2025-05-01 22:56:50,585] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 170.86 | bwd_microstep: 232.68 | bwd_inner_microstep: 232.67 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 22:56:51,436] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 317.30 | bwd_microstep: 501.72 | bwd_inner_microstep: 501.70 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 22:56:52,295] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 324.38 | bwd_microstep: 506.02 | bwd_inner_microstep: 506.01 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1915 +[2025-05-01 22:56:53,457] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.34 | optimizer_step: 18.69 +[2025-05-01 22:56:53,459] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 329.25 | bwd_microstep: 782.72 | bwd_inner_microstep: 521.20 | bwd_allreduce_microstep: 261.50 | step_microstep: 28.18 +[2025-05-01 22:56:53,460] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4915.21 | bwd: 7602.08 | bwd_inner: 7340.25 | bwd_allreduce: 261.57 | step: 56.10 + 3%|▎ | 248/8720 [41:27<30:41:09, 13.04s/it] {'loss': 1.7974, 'grad_norm': 5.409745693206787, 'learning_rate': 9.465648854961834e-06, 'epoch': 0.28} + 3%|▎ | 248/8720 [41:27<30:41:09, 13.04s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2128 +[2025-05-01 22:56:54,460] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 369.87 | bwd_microstep: 587.97 | bwd_inner_microstep: 587.95 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1883 +[2025-05-01 22:56:55,323] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 314.94 | bwd_microstep: 514.32 | bwd_inner_microstep: 514.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.49 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1116 +[2025-05-01 22:56:55,816] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 199.93 | bwd_microstep: 260.70 | bwd_inner_microstep: 260.68 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.32 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-01 22:56:56,671] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 322.67 | bwd_microstep: 507.04 | bwd_inner_microstep: 507.02 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-01 22:56:57,525] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 322.30 | bwd_microstep: 497.75 | bwd_inner_microstep: 497.73 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.49 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-01 22:56:58,396] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 349.80 | bwd_microstep: 486.45 | bwd_inner_microstep: 486.43 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-01 22:56:59,283] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 371.38 | bwd_microstep: 488.40 | bwd_inner_microstep: 488.39 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 22:57:00,092] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 353.28 | bwd_microstep: 435.76 | bwd_inner_microstep: 435.75 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 22:57:00,990] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 394.29 | bwd_microstep: 486.44 | bwd_inner_microstep: 486.42 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 22:57:01,886] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 370.81 | bwd_microstep: 505.62 | bwd_inner_microstep: 505.60 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.82 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 22:57:02,660] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 316.83 | bwd_microstep: 437.70 | bwd_inner_microstep: 437.68 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 22:57:03,515] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 334.55 | bwd_microstep: 484.17 | bwd_inner_microstep: 484.15 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 22:57:04,404] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 376.19 | bwd_microstep: 484.89 | bwd_inner_microstep: 484.87 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 22:57:05,299] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 381.93 | bwd_microstep: 496.88 | bwd_inner_microstep: 496.86 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.89 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 22:57:06,156] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 328.80 | bwd_microstep: 505.71 | bwd_inner_microstep: 505.69 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.31 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1947 +[2025-05-01 22:57:07,284] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.47 | optimizer_step: 19.85 +[2025-05-01 22:57:07,286] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 337.01 | bwd_microstep: 731.32 | bwd_inner_microstep: 548.91 | bwd_allreduce_microstep: 182.39 | step_microstep: 29.53 +[2025-05-01 22:57:07,287] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 5444.51 | bwd: 7911.12 | bwd_inner: 7728.45 | bwd_allreduce: 182.46 | step: 48.17 + 3%|▎ | 249/8720 [41:41<31:14:19, 13.28s/it] {'loss': 1.2878, 'grad_norm': 3.889023780822754, 'learning_rate': 9.50381679389313e-06, 'epoch': 0.29} + 3%|▎ | 249/8720 [41:41<31:14:19, 13.28s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2341 +[2025-05-01 22:57:08,365] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 378.48 | bwd_microstep: 658.98 | bwd_inner_microstep: 658.96 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1408 +[2025-05-01 22:57:08,992] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 204.00 | bwd_microstep: 405.17 | bwd_inner_microstep: 405.16 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.59 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1380 +[2025-05-01 22:57:09,594] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 222.28 | bwd_microstep: 360.41 | bwd_inner_microstep: 360.39 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.33 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-01 22:57:10,479] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 343.40 | bwd_microstep: 507.41 | bwd_inner_microstep: 507.39 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 342 +[2025-05-01 22:57:10,724] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 82.32 | bwd_microstep: 143.16 | bwd_inner_microstep: 143.14 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.33 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-01 22:57:11,594] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 327.18 | bwd_microstep: 513.04 | bwd_inner_microstep: 513.03 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-01 22:57:12,476] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 352.40 | bwd_microstep: 510.97 | bwd_inner_microstep: 510.95 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 22:57:13,317] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 307.65 | bwd_microstep: 510.83 | bwd_inner_microstep: 510.81 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-01 22:57:14,172] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 311.06 | bwd_microstep: 510.03 | bwd_inner_microstep: 510.01 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.52 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 832 +[2025-05-01 22:57:14,604] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 153.43 | bwd_microstep: 246.34 | bwd_inner_microstep: 246.33 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.31 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 22:57:15,425] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 324.79 | bwd_microstep: 466.48 | bwd_inner_microstep: 466.47 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 22:57:16,280] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 390.97 | bwd_microstep: 447.48 | bwd_inner_microstep: 447.46 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.17 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 22:57:17,181] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 393.77 | bwd_microstep: 489.17 | bwd_inner_microstep: 489.15 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 22:57:18,051] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 342.27 | bwd_microstep: 507.48 | bwd_inner_microstep: 507.46 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 827 +[2025-05-01 22:57:18,483] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 112.97 | bwd_microstep: 288.58 | bwd_inner_microstep: 288.57 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.32 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 827 +[2025-05-01 22:57:19,165] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.45 | optimizer_step: 18.71 +[2025-05-01 22:57:19,166] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 108.39 | bwd_microstep: 518.72 | bwd_inner_microstep: 286.99 | bwd_allreduce_microstep: 231.71 | step_microstep: 28.31 +[2025-05-01 22:57:19,167] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4355.29 | bwd: 7084.27 | bwd_inner: 6852.29 | bwd_allreduce: 231.77 | step: 48.42 + 3%|▎ | 250/8720 [41:52<30:15:00, 12.86s/it] {'loss': 1.4318, 'grad_norm': 4.309286594390869, 'learning_rate': 9.54198473282443e-06, 'epoch': 0.29} + 3%|▎ | 250/8720 [41:52<30:15:00, 12.86s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1894 +[2025-05-01 22:57:20,031] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 305.14 | bwd_microstep: 515.90 | bwd_inner_microstep: 515.88 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.46 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1897 +[2025-05-01 22:57:20,876] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 314.10 | bwd_microstep: 498.41 | bwd_inner_microstep: 498.39 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.23 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-01 22:57:21,751] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 323.94 | bwd_microstep: 515.02 | bwd_inner_microstep: 515.00 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1356 +[2025-05-01 22:57:22,440] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 243.77 | bwd_microstep: 416.67 | bwd_inner_microstep: 416.65 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 22:57:23,330] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 355.92 | bwd_microstep: 512.65 | bwd_inner_microstep: 512.63 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 22:57:24,178] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 312.21 | bwd_microstep: 509.51 | bwd_inner_microstep: 509.49 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1349 +[2025-05-01 22:57:24,793] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 205.40 | bwd_microstep: 380.70 | bwd_inner_microstep: 380.68 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 22:57:25,694] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 397.07 | bwd_microstep: 488.25 | bwd_inner_microstep: 488.23 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1345 +[2025-05-01 22:57:26,318] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 231.57 | bwd_microstep: 373.33 | bwd_inner_microstep: 373.31 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 22:57:27,197] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 326.38 | bwd_microstep: 518.62 | bwd_inner_microstep: 518.60 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.80 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 22:57:28,057] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 337.19 | bwd_microstep: 504.55 | bwd_inner_microstep: 504.54 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.50 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-01 22:57:28,901] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 305.83 | bwd_microstep: 504.77 | bwd_inner_microstep: 504.75 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 22:57:29,747] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 316.00 | bwd_microstep: 497.13 | bwd_inner_microstep: 497.11 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 22:57:30,588] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 323.94 | bwd_microstep: 485.05 | bwd_inner_microstep: 485.03 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2092 +[2025-05-01 22:57:31,527] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 394.64 | bwd_microstep: 523.81 | bwd_inner_microstep: 523.79 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.31 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-01 22:57:32,571] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 3.27 | optimizer_step: 17.75 +[2025-05-01 22:57:32,572] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 316.81 | bwd_microstep: 679.74 | bwd_inner_microstep: 515.24 | bwd_allreduce_microstep: 164.48 | step_microstep: 28.16 +[2025-05-01 22:57:32,573] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 5009.84 | bwd: 7924.12 | bwd_inner: 7759.36 | bwd_allreduce: 164.54 | step: 50.78 + 3%|▎ | 251/8720 [42:06<30:37:57, 13.02s/it] {'loss': 1.2666, 'grad_norm': 4.766699314117432, 'learning_rate': 9.580152671755725e-06, 'epoch': 0.29} + 3%|▎ | 251/8720 [42:06<30:37:57, 13.02s/it]dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1131 +[2025-05-01 22:57:33,130] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 234.83 | bwd_microstep: 287.53 | bwd_inner_microstep: 287.51 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-01 22:57:33,986] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 316.61 | bwd_microstep: 505.17 | bwd_inner_microstep: 505.15 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.32 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 843 +[2025-05-01 22:57:34,429] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 158.39 | bwd_microstep: 245.92 | bwd_inner_microstep: 245.90 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.50 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-01 22:57:35,278] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 319.20 | bwd_microstep: 495.68 | bwd_inner_microstep: 495.66 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-01 22:57:36,098] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 328.97 | bwd_microstep: 456.05 | bwd_inner_microstep: 456.03 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.31 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-01 22:57:36,946] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 315.77 | bwd_microstep: 498.14 | bwd_inner_microstep: 498.13 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-01 22:57:37,814] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 330.00 | bwd_microstep: 498.16 | bwd_inner_microstep: 498.14 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-01 22:57:38,673] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 323.99 | bwd_microstep: 502.79 | bwd_inner_microstep: 502.77 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-01 22:57:39,532] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 325.73 | bwd_microstep: 494.61 | bwd_inner_microstep: 494.59 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 22:57:40,389] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 318.01 | bwd_microstep: 504.41 | bwd_inner_microstep: 504.39 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1351 +[2025-05-01 22:57:41,032] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 262.14 | bwd_microstep: 349.94 | bwd_inner_microstep: 349.92 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.51 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 22:57:41,884] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 320.51 | bwd_microstep: 501.72 | bwd_inner_microstep: 501.70 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.22 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1345 +[2025-05-01 22:57:42,566] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 240.82 | bwd_microstep: 415.97 | bwd_inner_microstep: 415.84 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-01 22:57:43,389] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 352.38 | bwd_microstep: 450.29 | bwd_inner_microstep: 450.27 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.33 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 22:57:44,247] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 322.63 | bwd_microstep: 505.78 | bwd_inner_microstep: 505.76 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1390 +[2025-05-01 22:57:45,260] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.34 | optimizer_step: 23.74 +[2025-05-01 22:57:45,260] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 262.98 | bwd_microstep: 692.82 | bwd_inner_microstep: 416.44 | bwd_allreduce_microstep: 276.37 | step_microstep: 31.39 +[2025-05-01 22:57:45,262] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4732.92 | bwd: 7404.99 | bwd_inner: 7128.23 | bwd_allreduce: 276.50 | step: 58.19 + 3%|▎ | 252/8720 [42:19<30:23:32, 12.92s/it] {'loss': 1.7254, 'grad_norm': 3.96087384223938, 'learning_rate': 9.618320610687025e-06, 'epoch': 0.29} + 3%|▎ | 252/8720 [42:19<30:23:32, 12.92s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1899 +[2025-05-01 22:57:46,164] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 358.31 | bwd_microstep: 521.50 | bwd_inner_microstep: 521.48 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.20 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1387 +[2025-05-01 22:57:46,765] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 220.51 | bwd_microstep: 363.10 | bwd_inner_microstep: 363.08 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-01 22:57:47,628] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 341.75 | bwd_microstep: 488.71 | bwd_inner_microstep: 488.69 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1098 +[2025-05-01 22:57:48,114] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 255.18 | bwd_microstep: 206.15 | bwd_inner_microstep: 206.13 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-01 22:57:48,593] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.26 | bwd_microstep: 273.93 | bwd_inner_microstep: 273.91 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-01 22:57:49,071] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.31 | bwd_microstep: 273.80 | bwd_inner_microstep: 273.78 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-01 22:57:49,548] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.03 | bwd_microstep: 273.55 | bwd_inner_microstep: 273.54 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 22:57:50,025] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.46 | bwd_microstep: 272.56 | bwd_inner_microstep: 272.54 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-01 22:57:50,502] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.59 | bwd_microstep: 273.42 | bwd_inner_microstep: 273.40 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 321 +[2025-05-01 22:57:50,707] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 74.38 | bwd_microstep: 116.50 | bwd_inner_microstep: 116.38 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 22:57:51,183] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.05 | bwd_microstep: 272.57 | bwd_inner_microstep: 272.55 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-01 22:57:51,665] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.73 | bwd_microstep: 277.74 | bwd_inner_microstep: 277.72 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 22:57:52,139] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.81 | bwd_microstep: 271.23 | bwd_inner_microstep: 271.21 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 832 +[2025-05-01 22:57:52,376] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 92.83 | bwd_microstep: 130.57 | bwd_inner_microstep: 130.55 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 22:57:52,851] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.57 | bwd_microstep: 271.52 | bwd_inner_microstep: 271.50 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-01 22:57:53,420] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.26 | optimizer_step: 17.19 +[2025-05-01 22:57:53,420] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.57 | bwd_microstep: 340.24 | bwd_inner_microstep: 274.27 | bwd_allreduce_microstep: 65.93 | step_microstep: 24.34 +[2025-05-01 22:57:53,421] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 3230.14 | bwd: 4627.11 | bwd_inner: 4560.77 | bwd_allreduce: 66.05 | step: 27.48 + 3%|▎ | 253/8720 [42:27<27:01:46, 11.49s/it] {'loss': 2.3807, 'grad_norm': 7.571465015411377, 'learning_rate': 9.656488549618321e-06, 'epoch': 0.29} + 3%|▎ | 253/8720 [42:27<27:01:46, 11.49s/it]dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1116 +[2025-05-01 22:57:53,718] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 115.18 | bwd_microstep: 162.36 | bwd_inner_microstep: 162.34 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1889 +[2025-05-01 22:57:54,197] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.81 | bwd_microstep: 274.94 | bwd_inner_microstep: 274.92 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 344 +[2025-05-01 22:57:54,399] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 71.44 | bwd_microstep: 117.57 | bwd_inner_microstep: 117.45 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-01 22:57:54,877] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.65 | bwd_microstep: 273.73 | bwd_inner_microstep: 273.71 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 860 +[2025-05-01 22:57:55,119] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.96 | bwd_microstep: 133.82 | bwd_inner_microstep: 133.81 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-01 22:57:55,598] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.49 | bwd_microstep: 273.84 | bwd_inner_microstep: 273.82 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 838 +[2025-05-01 22:57:55,829] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 91.16 | bwd_microstep: 126.54 | bwd_inner_microstep: 126.53 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 22:57:56,306] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.30 | bwd_microstep: 272.65 | bwd_inner_microstep: 272.63 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 22:57:56,784] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.54 | bwd_microstep: 273.41 | bwd_inner_microstep: 273.39 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 22:57:57,259] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.16 | bwd_microstep: 272.68 | bwd_inner_microstep: 272.66 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 22:57:57,736] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.19 | bwd_microstep: 272.74 | bwd_inner_microstep: 272.72 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 22:57:58,213] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.17 | bwd_microstep: 272.47 | bwd_inner_microstep: 272.46 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 22:57:58,690] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.53 | bwd_microstep: 272.55 | bwd_inner_microstep: 272.53 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 22:57:59,167] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.85 | bwd_microstep: 272.60 | bwd_inner_microstep: 272.58 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 22:57:59,642] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.19 | bwd_microstep: 271.58 | bwd_inner_microstep: 271.56 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 317 +[2025-05-01 22:57:59,947] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.39 | optimizer_step: 16.80 +[2025-05-01 22:57:59,948] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 71.01 | bwd_microstep: 197.46 | bwd_inner_microstep: 131.64 | bwd_allreduce_microstep: 65.73 | step_microstep: 24.07 +[2025-05-01 22:57:59,949] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2522.39 | bwd: 3740.97 | bwd_inner: 3674.79 | bwd_allreduce: 65.84 | step: 24.75 + 3%|▎ | 254/8720 [42:33<23:31:25, 10.00s/it] {'loss': 1.2965, 'grad_norm': 5.40993070602417, 'learning_rate': 9.694656488549619e-06, 'epoch': 0.29} + 3%|▎ | 254/8720 [42:33<23:31:25, 10.00s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1904 +[2025-05-01 22:58:00,436] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.64 | bwd_microstep: 275.97 | bwd_inner_microstep: 275.95 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1889 +[2025-05-01 22:58:00,916] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.21 | bwd_microstep: 274.91 | bwd_inner_microstep: 274.89 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 859 +[2025-05-01 22:58:01,158] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.39 | bwd_microstep: 133.74 | bwd_inner_microstep: 133.72 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1368 +[2025-05-01 22:58:01,521] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.88 | bwd_microstep: 207.48 | bwd_inner_microstep: 207.47 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-01 22:58:01,999] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.00 | bwd_microstep: 274.53 | bwd_inner_microstep: 274.52 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-01 22:58:02,476] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.85 | bwd_microstep: 273.01 | bwd_inner_microstep: 273.00 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 22:58:02,953] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.13 | bwd_microstep: 273.15 | bwd_inner_microstep: 273.13 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-01 22:58:03,431] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.47 | bwd_microstep: 273.50 | bwd_inner_microstep: 273.48 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-01 22:58:03,909] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.03 | bwd_microstep: 273.04 | bwd_inner_microstep: 273.02 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-01 22:58:04,386] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.31 | bwd_microstep: 273.40 | bwd_inner_microstep: 273.38 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 22:58:04,866] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.22 | bwd_microstep: 272.80 | bwd_inner_microstep: 272.78 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 22:58:05,349] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.65 | bwd_microstep: 272.74 | bwd_inner_microstep: 272.73 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 320 +[2025-05-01 22:58:05,572] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 82.31 | bwd_microstep: 124.70 | bwd_inner_microstep: 124.39 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 22:58:06,051] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.35 | bwd_microstep: 272.07 | bwd_inner_microstep: 272.06 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-01 22:58:06,531] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.25 | bwd_microstep: 271.28 | bwd_inner_microstep: 271.27 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-01 22:58:07,114] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.42 | optimizer_step: 16.87 +[2025-05-01 22:58:07,114] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.87 | bwd_microstep: 348.99 | bwd_inner_microstep: 271.85 | bwd_allreduce_microstep: 77.08 | step_microstep: 24.87 +[2025-05-01 22:58:07,116] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2779.28 | bwd: 4095.37 | bwd_inner: 4017.70 | bwd_allreduce: 77.28 | step: 25.68 + 3%|▎ | 255/8720 [42:40<21:31:16, 9.15s/it] {'loss': 1.6973, 'grad_norm': 4.473517417907715, 'learning_rate': 9.732824427480917e-06, 'epoch': 0.29} + 3%|▎ | 255/8720 [42:40<21:31:16, 9.15s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-01 22:58:07,601] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.84 | bwd_microstep: 274.01 | bwd_inner_microstep: 273.99 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-01 22:58:08,081] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.05 | bwd_microstep: 273.21 | bwd_inner_microstep: 273.19 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-01 22:58:08,563] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.13 | bwd_microstep: 273.64 | bwd_inner_microstep: 273.63 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.15 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-01 22:58:09,048] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.48 | bwd_microstep: 273.07 | bwd_inner_microstep: 273.05 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 342 +[2025-05-01 22:58:09,263] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 79.79 | bwd_microstep: 120.10 | bwd_inner_microstep: 119.90 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-01 22:58:09,742] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.69 | bwd_microstep: 273.14 | bwd_inner_microstep: 273.12 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-01 22:58:10,220] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.53 | bwd_microstep: 273.48 | bwd_inner_microstep: 273.46 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-01 22:58:10,698] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.90 | bwd_microstep: 272.83 | bwd_inner_microstep: 272.81 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-01 22:58:11,175] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.54 | bwd_microstep: 273.40 | bwd_inner_microstep: 273.38 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 22:58:11,652] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.13 | bwd_microstep: 272.67 | bwd_inner_microstep: 272.66 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-01 22:58:12,130] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.22 | bwd_microstep: 272.92 | bwd_inner_microstep: 272.91 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-01 22:58:12,611] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.98 | bwd_microstep: 273.43 | bwd_inner_microstep: 273.41 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 22:58:13,092] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.12 | bwd_microstep: 272.77 | bwd_inner_microstep: 272.76 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 22:58:13,574] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.31 | bwd_microstep: 272.54 | bwd_inner_microstep: 272.52 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.15 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 22:58:14,053] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.99 | bwd_microstep: 271.53 | bwd_inner_microstep: 271.51 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 22:58:14,637] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.44 | optimizer_step: 17.54 +[2025-05-01 22:58:14,637] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.08 | bwd_microstep: 349.59 | bwd_inner_microstep: 271.78 | bwd_allreduce_microstep: 77.76 | step_microstep: 25.59 +[2025-05-01 22:58:14,639] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2912.43 | bwd: 4292.35 | bwd_inner: 4214.15 | bwd_allreduce: 77.90 | step: 26.63 + 3%|▎ | 256/8720 [42:48<20:22:09, 8.66s/it] {'loss': 1.2832, 'grad_norm': 3.516568183898926, 'learning_rate': 9.770992366412214e-06, 'epoch': 0.29} + 3%|▎ | 256/8720 [42:48<20:22:09, 8.66s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 388 +[2025-05-01 22:58:14,858] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 79.79 | bwd_microstep: 118.26 | bwd_inner_microstep: 118.09 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1896 +[2025-05-01 22:58:15,340] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.29 | bwd_microstep: 275.52 | bwd_inner_microstep: 275.51 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-01 22:58:15,822] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.24 | bwd_microstep: 273.83 | bwd_inner_microstep: 273.81 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-01 22:58:16,302] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.20 | bwd_microstep: 273.23 | bwd_inner_microstep: 273.21 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1355 +[2025-05-01 22:58:16,668] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.78 | bwd_microstep: 206.86 | bwd_inner_microstep: 206.84 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-01 22:58:17,151] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.06 | bwd_microstep: 273.62 | bwd_inner_microstep: 273.60 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 22:58:17,632] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.26 | bwd_microstep: 273.35 | bwd_inner_microstep: 273.34 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 22:58:18,113] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.05 | bwd_microstep: 273.17 | bwd_inner_microstep: 273.15 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 22:58:18,596] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.06 | bwd_microstep: 272.94 | bwd_inner_microstep: 272.92 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 22:58:19,078] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.90 | bwd_microstep: 273.01 | bwd_inner_microstep: 272.99 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 22:58:19,558] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.05 | bwd_microstep: 273.08 | bwd_inner_microstep: 273.07 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 22:58:20,038] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.89 | bwd_microstep: 271.90 | bwd_inner_microstep: 271.88 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-01 22:58:20,516] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.49 | bwd_microstep: 271.82 | bwd_inner_microstep: 271.80 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-01 22:58:20,992] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.28 | bwd_microstep: 271.74 | bwd_inner_microstep: 271.72 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-01 22:58:21,470] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.03 | bwd_microstep: 271.54 | bwd_inner_microstep: 271.52 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1954 +[2025-05-01 22:58:22,065] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.45 | optimizer_step: 16.80 +[2025-05-01 22:58:22,066] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 196.84 | bwd_microstep: 358.11 | bwd_inner_microstep: 290.68 | bwd_allreduce_microstep: 67.38 | step_microstep: 24.33 +[2025-05-01 22:58:22,067] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2875.83 | bwd: 4232.00 | bwd_inner: 4164.18 | bwd_allreduce: 67.52 | step: 25.23 + 3%|▎ | 257/8720 [42:55<19:29:41, 8.29s/it] {'loss': 2.0836, 'grad_norm': 8.746747970581055, 'learning_rate': 9.809160305343512e-06, 'epoch': 0.29} + 3%|▎ | 257/8720 [42:55<19:29:41, 8.29s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1903 +[2025-05-01 22:58:22,553] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.69 | bwd_microstep: 275.19 | bwd_inner_microstep: 275.17 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1892 +[2025-05-01 22:58:23,033] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.30 | bwd_microstep: 274.89 | bwd_inner_microstep: 274.88 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 866 +[2025-05-01 22:58:23,276] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.18 | bwd_microstep: 134.53 | bwd_inner_microstep: 134.24 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-01 22:58:23,754] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.27 | bwd_microstep: 273.78 | bwd_inner_microstep: 273.76 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1357 +[2025-05-01 22:58:24,117] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.80 | bwd_microstep: 206.70 | bwd_inner_microstep: 206.68 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-01 22:58:24,595] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.40 | bwd_microstep: 273.30 | bwd_inner_microstep: 273.29 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 22:58:25,071] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.32 | bwd_microstep: 272.58 | bwd_inner_microstep: 272.56 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 22:58:25,548] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.39 | bwd_microstep: 272.75 | bwd_inner_microstep: 272.73 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-01 22:58:26,027] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.98 | bwd_microstep: 273.01 | bwd_inner_microstep: 272.99 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 22:58:26,505] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.23 | bwd_microstep: 273.18 | bwd_inner_microstep: 273.16 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 22:58:26,983] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.48 | bwd_microstep: 272.53 | bwd_inner_microstep: 272.51 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 22:58:27,462] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.39 | bwd_microstep: 272.59 | bwd_inner_microstep: 272.57 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 22:58:27,940] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.48 | bwd_microstep: 271.43 | bwd_inner_microstep: 271.42 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-01 22:58:28,420] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.11 | bwd_microstep: 271.27 | bwd_inner_microstep: 271.25 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-01 22:58:28,898] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.00 | bwd_microstep: 271.29 | bwd_inner_microstep: 271.27 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 464 +[2025-05-01 22:58:29,248] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.52 | optimizer_step: 17.17 +[2025-05-01 22:58:29,248] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 91.44 | bwd_microstep: 215.33 | bwd_inner_microstep: 137.46 | bwd_allreduce_microstep: 77.71 | step_microstep: 25.50 +[2025-05-01 22:58:29,250] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2783.16 | bwd: 4104.38 | bwd_inner: 4026.03 | bwd_allreduce: 77.87 | step: 26.34 + 3%|▎ | 258/8720 [43:02<18:42:40, 7.96s/it] {'loss': 1.7353, 'grad_norm': 5.272639751434326, 'learning_rate': 9.84732824427481e-06, 'epoch': 0.3} + 3%|▎ | 258/8720 [43:03<18:42:40, 7.96s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1914 +[2025-05-01 22:58:29,740] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.04 | bwd_microstep: 275.79 | bwd_inner_microstep: 275.77 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1901 +[2025-05-01 22:58:30,224] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.40 | bwd_microstep: 275.94 | bwd_inner_microstep: 275.92 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-01 22:58:30,704] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.71 | bwd_microstep: 273.91 | bwd_inner_microstep: 273.89 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1109 +[2025-05-01 22:58:30,997] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 116.02 | bwd_microstep: 162.23 | bwd_inner_microstep: 162.07 | bwd_allreduce_microstep: 0.08 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-01 22:58:31,475] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.90 | bwd_microstep: 273.54 | bwd_inner_microstep: 273.52 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-01 22:58:31,953] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.75 | bwd_microstep: 273.60 | bwd_inner_microstep: 273.59 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-01 22:58:32,432] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.83 | bwd_microstep: 273.65 | bwd_inner_microstep: 273.63 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-01 22:58:32,910] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.82 | bwd_microstep: 273.34 | bwd_inner_microstep: 273.32 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-01 22:58:33,389] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.62 | bwd_microstep: 273.56 | bwd_inner_microstep: 273.54 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-01 22:58:33,866] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.57 | bwd_microstep: 272.94 | bwd_inner_microstep: 272.92 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.17 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 22:58:34,344] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.68 | bwd_microstep: 272.66 | bwd_inner_microstep: 272.65 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 327 +[2025-05-01 22:58:34,571] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 84.30 | bwd_microstep: 127.07 | bwd_inner_microstep: 126.76 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.18 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1354 +[2025-05-01 22:58:34,937] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.65 | bwd_microstep: 206.51 | bwd_inner_microstep: 206.36 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-01 22:58:35,417] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.03 | bwd_microstep: 273.27 | bwd_inner_microstep: 273.25 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.15 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1089 +[2025-05-01 22:58:35,712] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 116.09 | bwd_microstep: 161.42 | bwd_inner_microstep: 161.20 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.10 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 389 +[2025-05-01 22:58:36,044] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.42 | optimizer_step: 17.83 +[2025-05-01 22:58:36,045] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 84.08 | bwd_microstep: 205.51 | bwd_inner_microstep: 128.19 | bwd_allreduce_microstep: 77.16 | step_microstep: 26.06 +[2025-05-01 22:58:36,046] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2621.20 | bwd: 3875.11 | bwd_inner: 3796.71 | bwd_allreduce: 77.66 | step: 27.52 + 3%|▎ | 259/8720 [43:09<17:53:16, 7.61s/it] {'loss': 1.3015, 'grad_norm': 3.3129491806030273, 'learning_rate': 9.885496183206108e-06, 'epoch': 0.3} + 3%|▎ | 259/8720 [43:09<17:53:16, 7.61s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1922 +[2025-05-01 22:58:36,551] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 194.97 | bwd_microstep: 286.56 | bwd_inner_microstep: 286.54 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1895 +[2025-05-01 22:58:37,035] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.62 | bwd_microstep: 275.19 | bwd_inner_microstep: 275.17 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1891 +[2025-05-01 22:58:37,523] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.02 | bwd_microstep: 275.28 | bwd_inner_microstep: 275.26 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 359 +[2025-05-01 22:58:37,761] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.34 | bwd_microstep: 123.03 | bwd_inner_microstep: 122.78 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-01 22:58:38,242] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.32 | bwd_microstep: 274.46 | bwd_inner_microstep: 274.44 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-01 22:58:38,725] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.72 | bwd_microstep: 273.92 | bwd_inner_microstep: 273.90 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-01 22:58:39,208] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.74 | bwd_microstep: 273.49 | bwd_inner_microstep: 273.47 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-01 22:58:39,692] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.76 | bwd_microstep: 273.04 | bwd_inner_microstep: 273.02 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.06 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1354 +[2025-05-01 22:58:40,062] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 142.06 | bwd_microstep: 206.27 | bwd_inner_microstep: 206.19 | bwd_allreduce_microstep: 0.04 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-01 22:58:40,542] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.73 | bwd_microstep: 272.75 | bwd_inner_microstep: 272.74 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 22:58:41,023] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.14 | bwd_microstep: 272.25 | bwd_inner_microstep: 272.23 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-01 22:58:41,503] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.66 | bwd_microstep: 272.84 | bwd_inner_microstep: 272.83 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 22:58:41,983] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.52 | bwd_microstep: 272.60 | bwd_inner_microstep: 272.58 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 22:58:42,463] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.06 | bwd_microstep: 272.18 | bwd_inner_microstep: 272.17 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 22:58:42,942] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.98 | bwd_microstep: 272.29 | bwd_inner_microstep: 272.28 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 22:58:43,521] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.77 | optimizer_step: 17.00 +[2025-05-01 22:58:43,521] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.09 | bwd_microstep: 347.88 | bwd_inner_microstep: 271.56 | bwd_allreduce_microstep: 76.27 | step_microstep: 24.89 +[2025-05-01 22:58:43,522] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2885.31 | bwd: 4244.07 | bwd_inner: 4167.20 | bwd_allreduce: 76.49 | step: 25.83 + 3%|▎ | 260/8720 [43:17<17:47:23, 7.57s/it] {'loss': 1.6821, 'grad_norm': 4.7947468757629395, 'learning_rate': 9.923664122137405e-06, 'epoch': 0.3} + 3%|▎ | 260/8720 [43:17<17:47:23, 7.57s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1919 +[2025-05-01 22:58:44,010] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.84 | bwd_microstep: 276.67 | bwd_inner_microstep: 276.65 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-01 22:58:44,488] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.91 | bwd_microstep: 273.81 | bwd_inner_microstep: 273.80 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1888 +[2025-05-01 22:58:44,967] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.00 | bwd_microstep: 274.62 | bwd_inner_microstep: 274.60 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-01 22:58:45,445] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.16 | bwd_microstep: 274.21 | bwd_inner_microstep: 274.19 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-01 22:58:45,924] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.11 | bwd_microstep: 273.82 | bwd_inner_microstep: 273.80 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-01 22:58:46,403] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.45 | bwd_microstep: 273.91 | bwd_inner_microstep: 273.90 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-01 22:58:46,881] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.30 | bwd_microstep: 273.39 | bwd_inner_microstep: 273.37 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 333 +[2025-05-01 22:58:47,093] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 82.83 | bwd_microstep: 115.99 | bwd_inner_microstep: 115.67 | bwd_allreduce_microstep: 0.14 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-01 22:58:47,571] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.53 | bwd_microstep: 272.94 | bwd_inner_microstep: 272.92 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-01 22:58:48,049] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.85 | bwd_microstep: 272.99 | bwd_inner_microstep: 272.97 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 22:58:48,526] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.49 | bwd_microstep: 272.83 | bwd_inner_microstep: 272.81 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 22:58:49,004] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.39 | bwd_microstep: 272.31 | bwd_inner_microstep: 272.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 22:58:49,480] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.60 | bwd_microstep: 272.35 | bwd_inner_microstep: 272.33 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 22:58:49,958] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.99 | bwd_microstep: 272.54 | bwd_inner_microstep: 272.52 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 22:58:50,436] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.30 | bwd_microstep: 271.53 | bwd_inner_microstep: 271.51 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1849 +[2025-05-01 22:58:51,017] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.04 | optimizer_gradients: 2.33 | optimizer_step: 16.91 +[2025-05-01 22:58:51,017] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.97 | bwd_microstep: 348.64 | bwd_inner_microstep: 271.53 | bwd_allreduce_microstep: 77.07 | step_microstep: 23.98 +[2025-05-01 22:58:51,019] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2917.45 | bwd: 4292.56 | bwd_inner: 4214.93 | bwd_allreduce: 77.26 | step: 24.90 + 3%|▎ | 261/8720 [43:24<17:44:06, 7.55s/it] {'loss': 1.6997, 'grad_norm': 4.181746482849121, 'learning_rate': 9.961832061068703e-06, 'epoch': 0.3} + 3%|▎ | 261/8720 [43:24<17:44:06, 7.55s/it]dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 922 +[2025-05-01 22:58:51,286] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 103.25 | bwd_microstep: 146.00 | bwd_inner_microstep: 145.66 | bwd_allreduce_microstep: 0.17 | step_microstep: 0.09 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1422 +[2025-05-01 22:58:51,660] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 145.59 | bwd_microstep: 213.40 | bwd_inner_microstep: 213.38 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1883 +[2025-05-01 22:58:52,139] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.83 | bwd_microstep: 274.27 | bwd_inner_microstep: 274.25 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 864 +[2025-05-01 22:58:52,393] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 96.69 | bwd_microstep: 134.33 | bwd_inner_microstep: 134.04 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-01 22:58:52,874] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.11 | bwd_microstep: 274.60 | bwd_inner_microstep: 274.59 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.16 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-01 22:58:53,353] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.55 | bwd_microstep: 274.11 | bwd_inner_microstep: 274.09 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-01 22:58:53,832] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.16 | bwd_microstep: 273.49 | bwd_inner_microstep: 273.47 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-01 22:58:54,312] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.29 | bwd_microstep: 273.02 | bwd_inner_microstep: 273.00 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-01 22:58:54,793] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.55 | bwd_microstep: 272.76 | bwd_inner_microstep: 272.75 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.21 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 22:58:55,274] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.08 | bwd_microstep: 272.58 | bwd_inner_microstep: 272.57 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 22:58:55,754] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.13 | bwd_microstep: 272.53 | bwd_inner_microstep: 272.51 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 322 +[2025-05-01 22:58:55,983] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 90.28 | bwd_microstep: 120.77 | bwd_inner_microstep: 120.45 | bwd_allreduce_microstep: 0.14 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 22:58:56,462] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.03 | bwd_microstep: 272.55 | bwd_inner_microstep: 272.53 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 832 +[2025-05-01 22:58:56,716] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.41 | bwd_microstep: 130.74 | bwd_inner_microstep: 130.53 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-01 22:58:57,193] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.55 | bwd_microstep: 271.29 | bwd_inner_microstep: 271.27 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-01 22:58:57,763] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.38 | optimizer_step: 17.08 +[2025-05-01 22:58:57,763] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.02 | bwd_microstep: 338.85 | bwd_inner_microstep: 271.88 | bwd_allreduce_microstep: 66.93 | step_microstep: 24.42 +[2025-05-01 22:58:57,765] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2611.18 | bwd: 3815.36 | bwd_inner: 3747.19 | bwd_allreduce: 67.51 | step: 25.71 + 3%|▎ | 262/8720 [43:31<17:10:05, 7.31s/it] {'loss': 1.7699, 'grad_norm': 7.254358291625977, 'learning_rate': 1e-05, 'epoch': 0.3} + 3%|▎ | 262/8720 [43:31<17:10:05, 7.31s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1947 +[2025-05-01 22:58:58,269] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 196.09 | bwd_microstep: 288.61 | bwd_inner_microstep: 288.59 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1939 +[2025-05-01 22:58:58,769] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.68 | bwd_microstep: 288.90 | bwd_inner_microstep: 288.88 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 888 +[2025-05-01 22:58:59,018] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 98.34 | bwd_microstep: 135.57 | bwd_inner_microstep: 135.31 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-01 22:58:59,496] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.11 | bwd_microstep: 274.10 | bwd_inner_microstep: 274.08 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-01 22:58:59,976] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.62 | bwd_microstep: 273.69 | bwd_inner_microstep: 273.68 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-01 22:59:00,455] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.50 | bwd_microstep: 273.53 | bwd_inner_microstep: 273.52 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-01 22:59:00,933] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.68 | bwd_microstep: 273.66 | bwd_inner_microstep: 273.64 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-01 22:59:01,411] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.58 | bwd_microstep: 272.96 | bwd_inner_microstep: 272.95 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-01 22:59:01,889] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.35 | bwd_microstep: 273.57 | bwd_inner_microstep: 273.55 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-01 22:59:02,366] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.84 | bwd_microstep: 272.74 | bwd_inner_microstep: 272.72 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 22:59:02,842] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.14 | bwd_microstep: 272.53 | bwd_inner_microstep: 272.51 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 22:59:03,320] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.73 | bwd_microstep: 272.51 | bwd_inner_microstep: 272.49 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 22:59:03,801] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.67 | bwd_microstep: 272.87 | bwd_inner_microstep: 272.85 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 22:59:04,278] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.70 | bwd_microstep: 271.35 | bwd_inner_microstep: 271.33 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.13 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 22:59:04,757] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.35 | bwd_microstep: 271.25 | bwd_inner_microstep: 271.24 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 22:59:05,339] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.29 | optimizer_step: 16.96 +[2025-05-01 22:59:05,340] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.00 | bwd_microstep: 352.24 | bwd_inner_microstep: 271.90 | bwd_allreduce_microstep: 80.28 | step_microstep: 25.06 +[2025-05-01 22:59:05,341] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2943.08 | bwd: 4340.16 | bwd_inner: 4259.26 | bwd_allreduce: 80.49 | step: 26.00 + 3%|▎ | 263/8720 [43:39<17:21:26, 7.39s/it] {'loss': 1.7104, 'grad_norm': 5.475947380065918, 'learning_rate': 9.999999655091112e-06, 'epoch': 0.3} + 3%|▎ | 263/8720 [43:39<17:21:26, 7.39s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1938 +[2025-05-01 22:59:05,850] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 197.80 | bwd_microstep: 287.65 | bwd_inner_microstep: 287.64 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1911 +[2025-05-01 22:59:06,336] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.64 | bwd_microstep: 277.10 | bwd_inner_microstep: 277.08 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-01 22:59:06,817] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.46 | bwd_microstep: 272.48 | bwd_inner_microstep: 272.46 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-01 22:59:07,301] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.67 | bwd_microstep: 273.68 | bwd_inner_microstep: 273.65 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 22:59:07,782] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.40 | bwd_microstep: 272.83 | bwd_inner_microstep: 272.81 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 838 +[2025-05-01 22:59:08,020] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.65 | bwd_microstep: 126.22 | bwd_inner_microstep: 126.16 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 22:59:08,497] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.89 | bwd_microstep: 272.07 | bwd_inner_microstep: 272.06 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 841 +[2025-05-01 22:59:08,740] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.65 | bwd_microstep: 131.89 | bwd_inner_microstep: 131.66 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-01 22:59:09,220] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.57 | bwd_microstep: 273.03 | bwd_inner_microstep: 273.01 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 22:59:09,698] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.01 | bwd_microstep: 272.37 | bwd_inner_microstep: 272.35 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-01 22:59:10,185] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.74 | bwd_microstep: 273.04 | bwd_inner_microstep: 273.03 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 22:59:10,667] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.29 | bwd_microstep: 272.50 | bwd_inner_microstep: 272.49 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.16 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 22:59:11,150] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.72 | bwd_microstep: 271.28 | bwd_inner_microstep: 271.26 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 22:59:11,635] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.34 | bwd_microstep: 271.08 | bwd_inner_microstep: 271.06 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 22:59:12,112] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.63 | bwd_microstep: 271.03 | bwd_inner_microstep: 271.01 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.05 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 827 +[2025-05-01 22:59:12,463] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.33 | optimizer_step: 17.64 +[2025-05-01 22:59:12,463] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.84 | bwd_microstep: 212.39 | bwd_inner_microstep: 135.01 | bwd_allreduce_microstep: 77.29 | step_microstep: 25.61 +[2025-05-01 22:59:12,465] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2742.94 | bwd: 4030.72 | bwd_inner: 3952.77 | bwd_allreduce: 77.47 | step: 26.86 + 3%|▎ | 264/8720 [43:46<17:10:05, 7.31s/it] {'loss': 1.3969, 'grad_norm': 4.207176685333252, 'learning_rate': 9.999998620364491e-06, 'epoch': 0.3} + 3%|▎ | 264/8720 [43:46<17:10:05, 7.31s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1919 +[2025-05-01 22:59:12,955] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 191.04 | bwd_microstep: 276.10 | bwd_inner_microstep: 276.09 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1917 +[2025-05-01 22:59:13,440] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.10 | bwd_microstep: 276.62 | bwd_inner_microstep: 276.60 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1907 +[2025-05-01 22:59:13,925] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.07 | bwd_microstep: 276.46 | bwd_inner_microstep: 276.44 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1899 +[2025-05-01 22:59:14,409] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.02 | bwd_microstep: 275.94 | bwd_inner_microstep: 275.92 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1903 +[2025-05-01 22:59:14,894] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 191.25 | bwd_microstep: 276.35 | bwd_inner_microstep: 276.33 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-01 22:59:15,377] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.13 | bwd_microstep: 274.42 | bwd_inner_microstep: 274.41 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-01 22:59:15,860] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.98 | bwd_microstep: 274.35 | bwd_inner_microstep: 274.33 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 851 +[2025-05-01 22:59:16,107] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.83 | bwd_microstep: 133.30 | bwd_inner_microstep: 133.09 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-01 22:59:16,589] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.84 | bwd_microstep: 274.36 | bwd_inner_microstep: 274.35 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.24 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-01 22:59:17,071] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.99 | bwd_microstep: 273.34 | bwd_inner_microstep: 273.32 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-01 22:59:17,552] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.15 | bwd_microstep: 274.02 | bwd_inner_microstep: 274.00 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-01 22:59:18,032] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.17 | bwd_microstep: 273.39 | bwd_inner_microstep: 273.38 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 330 +[2025-05-01 22:59:18,234] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 68.72 | bwd_microstep: 119.56 | bwd_inner_microstep: 119.40 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-01 22:59:18,710] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.30 | bwd_microstep: 272.84 | bwd_inner_microstep: 272.82 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-01 22:59:19,189] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.87 | bwd_microstep: 273.29 | bwd_inner_microstep: 273.27 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1343 +[2025-05-01 22:59:19,642] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.66 | optimizer_step: 16.72 +[2025-05-01 22:59:19,642] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.17 | bwd_microstep: 273.42 | bwd_inner_microstep: 205.52 | bwd_allreduce_microstep: 67.75 | step_microstep: 24.40 +[2025-05-01 22:59:19,643] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2773.29 | bwd: 4097.82 | bwd_inner: 4029.36 | bwd_allreduce: 67.97 | step: 25.54 + 3%|▎ | 265/8720 [43:53<17:04:22, 7.27s/it] {'loss': 1.649, 'grad_norm': 3.995274782180786, 'learning_rate': 9.999996895820283e-06, 'epoch': 0.3} + 3%|▎ | 265/8720 [43:53<17:04:22, 7.27s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1893 +[2025-05-01 22:59:20,130] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 191.30 | bwd_microstep: 275.05 | bwd_inner_microstep: 275.03 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-01 22:59:20,613] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.77 | bwd_microstep: 275.89 | bwd_inner_microstep: 275.88 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.21 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1372 +[2025-05-01 22:59:20,978] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.95 | bwd_microstep: 207.79 | bwd_inner_microstep: 207.77 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-01 22:59:21,458] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.95 | bwd_microstep: 274.51 | bwd_inner_microstep: 274.49 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-01 22:59:21,938] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.13 | bwd_microstep: 273.43 | bwd_inner_microstep: 273.41 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-01 22:59:22,417] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.67 | bwd_microstep: 272.89 | bwd_inner_microstep: 272.87 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 22:59:22,894] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.70 | bwd_microstep: 272.65 | bwd_inner_microstep: 272.63 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 22:59:23,370] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.55 | bwd_microstep: 272.71 | bwd_inner_microstep: 272.69 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 330 +[2025-05-01 22:59:23,579] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 75.63 | bwd_microstep: 119.26 | bwd_inner_microstep: 119.11 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-01 22:59:24,057] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.26 | bwd_microstep: 272.84 | bwd_inner_microstep: 272.82 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 837 +[2025-05-01 22:59:24,290] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 92.49 | bwd_microstep: 126.15 | bwd_inner_microstep: 126.14 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1348 +[2025-05-01 22:59:24,653] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.32 | bwd_microstep: 205.89 | bwd_inner_microstep: 205.83 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 22:59:25,128] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.88 | bwd_microstep: 272.08 | bwd_inner_microstep: 272.06 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.14 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 22:59:25,605] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.57 | bwd_microstep: 271.47 | bwd_inner_microstep: 271.45 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 22:59:26,087] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.89 | bwd_microstep: 272.32 | bwd_inner_microstep: 272.31 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1982 +[2025-05-01 22:59:26,705] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.31 | optimizer_step: 16.87 +[2025-05-01 22:59:26,706] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 197.38 | bwd_microstep: 376.82 | bwd_inner_microstep: 293.21 | bwd_allreduce_microstep: 83.56 | step_microstep: 25.09 +[2025-05-01 22:59:26,707] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2728.13 | bwd: 4041.78 | bwd_inner: 3957.73 | bwd_allreduce: 83.73 | step: 26.46 + 3%|▎ | 266/8720 [44:00<16:55:38, 7.21s/it] {'loss': 1.3766, 'grad_norm': 6.906410217285156, 'learning_rate': 9.999994481458724e-06, 'epoch': 0.31} + 3%|▎ | 266/8720 [44:00<16:55:38, 7.21s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1914 +[2025-05-01 22:59:27,196] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.79 | bwd_microstep: 275.64 | bwd_inner_microstep: 275.62 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-01 22:59:27,676] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.09 | bwd_microstep: 273.71 | bwd_inner_microstep: 273.69 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-01 22:59:28,153] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.82 | bwd_microstep: 273.65 | bwd_inner_microstep: 273.64 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1356 +[2025-05-01 22:59:28,518] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.76 | bwd_microstep: 206.77 | bwd_inner_microstep: 206.56 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-01 22:59:28,997] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.06 | bwd_microstep: 273.30 | bwd_inner_microstep: 273.28 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-01 22:59:29,479] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.15 | bwd_microstep: 273.78 | bwd_inner_microstep: 273.77 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-01 22:59:29,963] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.76 | bwd_microstep: 273.79 | bwd_inner_microstep: 273.77 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-01 22:59:30,444] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.35 | bwd_microstep: 273.28 | bwd_inner_microstep: 273.27 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-01 22:59:30,925] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.83 | bwd_microstep: 273.03 | bwd_inner_microstep: 273.02 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-01 22:59:31,409] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.43 | bwd_microstep: 272.77 | bwd_inner_microstep: 272.75 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 22:59:31,888] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.63 | bwd_microstep: 272.25 | bwd_inner_microstep: 272.23 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 22:59:32,369] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.51 | bwd_microstep: 272.33 | bwd_inner_microstep: 272.32 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 22:59:32,849] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.40 | bwd_microstep: 272.51 | bwd_inner_microstep: 272.49 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.15 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 22:59:33,339] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.27 | bwd_microstep: 271.48 | bwd_inner_microstep: 271.46 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 22:59:33,820] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.91 | bwd_microstep: 271.39 | bwd_inner_microstep: 271.37 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 22:59:34,396] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.25 | optimizer_step: 17.36 +[2025-05-01 22:59:34,396] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.52 | bwd_microstep: 345.61 | bwd_inner_microstep: 271.77 | bwd_allreduce_microstep: 73.80 | step_microstep: 24.69 +[2025-05-01 22:59:34,397] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2977.86 | bwd: 4375.35 | bwd_inner: 4301.00 | bwd_allreduce: 74.00 | step: 25.74 + 3%|▎ | 267/8720 [44:08<17:15:48, 7.35s/it] {'loss': 1.7053, 'grad_norm': 4.1671953201293945, 'learning_rate': 9.99999137728015e-06, 'epoch': 0.31} + 3%|▎ | 267/8720 [44:08<17:15:48, 7.35s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1949 +[2025-05-01 22:59:34,903] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 196.55 | bwd_microstep: 288.88 | bwd_inner_microstep: 288.86 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-01 22:59:35,387] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 191.58 | bwd_microstep: 274.26 | bwd_inner_microstep: 274.24 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 350 +[2025-05-01 22:59:35,604] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 79.05 | bwd_microstep: 122.92 | bwd_inner_microstep: 122.69 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-01 22:59:36,081] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.92 | bwd_microstep: 273.35 | bwd_inner_microstep: 273.33 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-01 22:59:36,562] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.03 | bwd_microstep: 274.01 | bwd_inner_microstep: 273.99 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.14 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-01 22:59:37,044] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.42 | bwd_microstep: 273.71 | bwd_inner_microstep: 273.69 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 22:59:37,524] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.24 | bwd_microstep: 272.32 | bwd_inner_microstep: 272.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 838 +[2025-05-01 22:59:37,763] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.99 | bwd_microstep: 126.12 | bwd_inner_microstep: 126.10 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 335 +[2025-05-01 22:59:37,991] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 84.70 | bwd_microstep: 126.24 | bwd_inner_microstep: 125.93 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-01 22:59:38,470] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.29 | bwd_microstep: 272.79 | bwd_inner_microstep: 272.77 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.14 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 22:59:38,952] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.62 | bwd_microstep: 272.65 | bwd_inner_microstep: 272.63 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 22:59:39,431] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.53 | bwd_microstep: 272.42 | bwd_inner_microstep: 272.40 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 22:59:39,910] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.13 | bwd_microstep: 271.46 | bwd_inner_microstep: 271.44 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-01 22:59:40,389] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.78 | bwd_microstep: 271.06 | bwd_inner_microstep: 271.04 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 315 +[2025-05-01 22:59:40,641] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 92.95 | bwd_microstep: 142.11 | bwd_inner_microstep: 141.91 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.10 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 872 +[2025-05-01 22:59:41,004] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.07 | optimizer_gradients: 2.42 | optimizer_step: 17.00 +[2025-05-01 22:59:41,005] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 101.32 | bwd_microstep: 219.58 | bwd_inner_microstep: 140.72 | bwd_allreduce_microstep: 78.70 | step_microstep: 25.31 +[2025-05-01 22:59:41,007] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2540.71 | bwd: 3753.97 | bwd_inner: 3674.31 | bwd_allreduce: 78.98 | step: 26.85 + 3%|▎ | 268/8720 [44:14<16:44:23, 7.13s/it] {'loss': 1.854, 'grad_norm': 5.549082279205322, 'learning_rate': 9.999987583284985e-06, 'epoch': 0.31} + 3%|▎ | 268/8720 [44:14<16:44:23, 7.13s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1892 +[2025-05-01 22:59:41,495] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.73 | bwd_microstep: 274.32 | bwd_inner_microstep: 274.31 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-01 22:59:41,978] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.62 | bwd_microstep: 273.25 | bwd_inner_microstep: 273.23 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-01 22:59:42,461] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.82 | bwd_microstep: 273.58 | bwd_inner_microstep: 273.56 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-01 22:59:42,944] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.75 | bwd_microstep: 273.72 | bwd_inner_microstep: 273.70 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 22:59:43,424] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.52 | bwd_microstep: 272.51 | bwd_inner_microstep: 272.49 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 22:59:43,904] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.39 | bwd_microstep: 272.27 | bwd_inner_microstep: 272.26 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 837 +[2025-05-01 22:59:44,152] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 96.80 | bwd_microstep: 132.05 | bwd_inner_microstep: 131.84 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-01 22:59:44,631] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.35 | bwd_microstep: 272.77 | bwd_inner_microstep: 272.75 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-01 22:59:45,110] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.14 | bwd_microstep: 272.88 | bwd_inner_microstep: 272.86 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 22:59:45,590] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.24 | bwd_microstep: 273.06 | bwd_inner_microstep: 273.04 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 22:59:46,067] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.88 | bwd_microstep: 271.46 | bwd_inner_microstep: 271.44 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 22:59:46,546] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.93 | bwd_microstep: 271.31 | bwd_inner_microstep: 271.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 22:59:47,024] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.98 | bwd_microstep: 271.62 | bwd_inner_microstep: 271.60 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 828 +[2025-05-01 22:59:47,267] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 96.27 | bwd_microstep: 129.61 | bwd_inner_microstep: 129.43 | bwd_allreduce_microstep: 0.09 | step_microstep: 0.10 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 315 +[2025-05-01 22:59:47,489] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 80.38 | bwd_microstep: 124.70 | bwd_inner_microstep: 124.57 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1995 +[2025-05-01 22:59:48,090] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.33 | optimizer_step: 17.00 +[2025-05-01 22:59:48,090] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 198.99 | bwd_microstep: 362.45 | bwd_inner_microstep: 294.98 | bwd_allreduce_microstep: 67.43 | step_microstep: 24.45 +[2025-05-01 22:59:48,092] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2736.46 | bwd: 4021.63 | bwd_inner: 3953.40 | bwd_allreduce: 67.71 | step: 25.69 + 3%|▎ | 269/8720 [44:21<16:42:17, 7.12s/it] {'loss': 1.5661, 'grad_norm': 4.850590705871582, 'learning_rate': 9.999983099473756e-06, 'epoch': 0.31} + 3%|▎ | 269/8720 [44:21<16:42:17, 7.12s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 634 +[2025-05-01 22:59:48,316] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 78.01 | bwd_microstep: 127.06 | bwd_inner_microstep: 126.92 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 388 +[2025-05-01 22:59:48,525] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 73.70 | bwd_microstep: 121.08 | bwd_inner_microstep: 120.84 | bwd_allreduce_microstep: 0.10 | step_microstep: 0.09 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 359 +[2025-05-01 22:59:48,741] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 81.12 | bwd_microstep: 121.80 | bwd_inner_microstep: 121.46 | bwd_allreduce_microstep: 0.14 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1892 +[2025-05-01 22:59:49,224] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.36 | bwd_microstep: 274.89 | bwd_inner_microstep: 274.88 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1886 +[2025-05-01 22:59:49,706] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.43 | bwd_microstep: 274.40 | bwd_inner_microstep: 274.39 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-01 22:59:50,185] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.50 | bwd_microstep: 273.00 | bwd_inner_microstep: 272.98 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 22:59:50,664] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.14 | bwd_microstep: 272.49 | bwd_inner_microstep: 272.47 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-01 22:59:51,147] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.34 | bwd_microstep: 273.21 | bwd_inner_microstep: 273.20 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 22:59:51,626] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.37 | bwd_microstep: 272.73 | bwd_inner_microstep: 272.71 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-01 22:59:52,105] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.66 | bwd_microstep: 272.83 | bwd_inner_microstep: 272.81 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1094 +[2025-05-01 22:59:52,401] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 115.16 | bwd_microstep: 161.50 | bwd_inner_microstep: 161.31 | bwd_allreduce_microstep: 0.10 | step_microstep: 0.10 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 328 +[2025-05-01 22:59:52,636] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 85.77 | bwd_microstep: 132.95 | bwd_inner_microstep: 132.67 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 22:59:53,116] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.15 | bwd_microstep: 272.84 | bwd_inner_microstep: 272.82 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 22:59:53,596] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.11 | bwd_microstep: 272.40 | bwd_inner_microstep: 272.39 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 22:59:54,074] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.02 | bwd_microstep: 271.56 | bwd_inner_microstep: 271.54 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 22:59:54,645] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.47 | optimizer_step: 17.15 +[2025-05-01 22:59:54,646] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.72 | bwd_microstep: 340.98 | bwd_inner_microstep: 272.10 | bwd_allreduce_microstep: 68.84 | step_microstep: 24.63 +[2025-05-01 22:59:54,647] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2510.23 | bwd: 3735.83 | bwd_inner: 3665.70 | bwd_allreduce: 69.37 | step: 25.72 + 3%|▎ | 270/8720 [44:28<16:18:27, 6.95s/it] {'loss': 1.3585, 'grad_norm': 5.508727550506592, 'learning_rate': 9.999977925847079e-06, 'epoch': 0.31} + 3%|▎ | 270/8720 [44:28<16:18:27, 6.95s/it]dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1109 +[2025-05-01 22:59:54,943] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 115.50 | bwd_microstep: 162.13 | bwd_inner_microstep: 162.10 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-01 22:59:55,424] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.42 | bwd_microstep: 274.98 | bwd_inner_microstep: 274.97 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 22:59:55,902] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.53 | bwd_microstep: 273.05 | bwd_inner_microstep: 273.03 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-01 22:59:56,380] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.09 | bwd_microstep: 273.40 | bwd_inner_microstep: 273.39 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 22:59:56,858] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.79 | bwd_microstep: 273.12 | bwd_inner_microstep: 273.10 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 838 +[2025-05-01 22:59:57,108] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 105.61 | bwd_microstep: 126.37 | bwd_inner_microstep: 126.36 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 834 +[2025-05-01 22:59:57,339] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 90.97 | bwd_microstep: 126.08 | bwd_inner_microstep: 126.06 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 22:59:57,817] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.79 | bwd_microstep: 272.96 | bwd_inner_microstep: 272.94 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 22:59:58,298] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.73 | bwd_microstep: 273.88 | bwd_inner_microstep: 273.86 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 22:59:58,784] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.50 | bwd_microstep: 271.98 | bwd_inner_microstep: 271.97 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 22:59:59,260] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.10 | bwd_microstep: 271.82 | bwd_inner_microstep: 271.80 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 830 +[2025-05-01 22:59:59,498] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 92.68 | bwd_microstep: 130.59 | bwd_inner_microstep: 130.40 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-01 22:59:59,974] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.99 | bwd_microstep: 271.77 | bwd_inner_microstep: 271.76 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 23:00:00,452] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.56 | bwd_microstep: 271.96 | bwd_inner_microstep: 271.94 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 23:00:00,928] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.21 | bwd_microstep: 271.99 | bwd_inner_microstep: 271.98 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 392 +[2025-05-01 23:00:01,263] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.34 | optimizer_step: 17.59 +[2025-05-01 23:00:01,263] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 79.70 | bwd_microstep: 213.85 | bwd_inner_microstep: 146.00 | bwd_allreduce_microstep: 67.72 | step_microstep: 25.09 +[2025-05-01 23:00:01,264] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2564.90 | bwd: 3759.99 | bwd_inner: 3691.76 | bwd_allreduce: 67.85 | step: 26.07 + 3%|▎ | 271/8720 [44:35<16:04:25, 6.85s/it] {'loss': 1.2317, 'grad_norm': 6.502427101135254, 'learning_rate': 9.99997206240567e-06, 'epoch': 0.31} + 3%|▎ | 271/8720 [44:35<16:04:25, 6.85s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1911 +[2025-05-01 23:00:01,753] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.94 | bwd_microstep: 276.47 | bwd_inner_microstep: 276.45 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.21 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1896 +[2025-05-01 23:00:02,237] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.98 | bwd_microstep: 276.01 | bwd_inner_microstep: 275.99 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1941 +[2025-05-01 23:00:02,738] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 196.50 | bwd_microstep: 288.88 | bwd_inner_microstep: 288.85 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 360 +[2025-05-01 23:00:02,959] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 78.85 | bwd_microstep: 128.23 | bwd_inner_microstep: 127.90 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1895 +[2025-05-01 23:00:03,441] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.79 | bwd_microstep: 275.20 | bwd_inner_microstep: 275.18 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-01 23:00:03,922] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.53 | bwd_microstep: 273.66 | bwd_inner_microstep: 273.65 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 857 +[2025-05-01 23:00:04,172] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 99.48 | bwd_microstep: 132.85 | bwd_inner_microstep: 132.61 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-01 23:00:04,657] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.04 | bwd_microstep: 273.35 | bwd_inner_microstep: 273.34 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-01 23:00:05,141] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.35 | bwd_microstep: 273.71 | bwd_inner_microstep: 273.70 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-01 23:00:05,620] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.47 | bwd_microstep: 273.13 | bwd_inner_microstep: 273.11 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-01 23:00:06,097] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.25 | bwd_microstep: 272.85 | bwd_inner_microstep: 272.83 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1357 +[2025-05-01 23:00:06,460] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.07 | bwd_microstep: 206.47 | bwd_inner_microstep: 206.31 | bwd_allreduce_microstep: 0.09 | step_microstep: 0.09 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 839 +[2025-05-01 23:00:06,694] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 91.44 | bwd_microstep: 126.47 | bwd_inner_microstep: 126.32 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-01 23:00:07,171] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.95 | bwd_microstep: 272.97 | bwd_inner_microstep: 272.95 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1345 +[2025-05-01 23:00:07,536] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.63 | bwd_microstep: 205.99 | bwd_inner_microstep: 205.95 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 23:00:08,120] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.51 | optimizer_step: 17.14 +[2025-05-01 23:00:08,120] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.93 | bwd_microstep: 352.02 | bwd_inner_microstep: 272.45 | bwd_allreduce_microstep: 79.52 | step_microstep: 25.36 +[2025-05-01 23:00:08,122] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2640.87 | bwd: 3908.35 | bwd_inner: 3827.70 | bwd_allreduce: 80.03 | step: 26.70 + 3%|▎ | 272/8720 [44:41<16:04:43, 6.85s/it] {'loss': 1.5658, 'grad_norm': 3.43697190284729, 'learning_rate': 9.999965509150336e-06, 'epoch': 0.31} + 3%|▎ | 272/8720 [44:41<16:04:43, 6.85s/it]dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1435 +[2025-05-01 23:00:08,505] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 146.83 | bwd_microstep: 214.24 | bwd_inner_microstep: 214.04 | bwd_allreduce_microstep: 0.09 | step_microstep: 0.10 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 941 +[2025-05-01 23:00:08,771] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 101.66 | bwd_microstep: 147.69 | bwd_inner_microstep: 147.57 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1911 +[2025-05-01 23:00:09,256] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.45 | bwd_microstep: 276.80 | bwd_inner_microstep: 276.78 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 877 +[2025-05-01 23:00:09,509] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 98.47 | bwd_microstep: 135.49 | bwd_inner_microstep: 135.39 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1895 +[2025-05-01 23:00:09,992] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.00 | bwd_microstep: 275.30 | bwd_inner_microstep: 275.28 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1888 +[2025-05-01 23:00:10,477] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.15 | bwd_microstep: 274.66 | bwd_inner_microstep: 274.64 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 331 +[2025-05-01 23:00:10,695] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 82.16 | bwd_microstep: 118.84 | bwd_inner_microstep: 118.54 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 333 +[2025-05-01 23:00:10,918] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 80.13 | bwd_microstep: 127.11 | bwd_inner_microstep: 126.96 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-01 23:00:11,396] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.84 | bwd_microstep: 273.43 | bwd_inner_microstep: 273.41 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-01 23:00:11,875] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.82 | bwd_microstep: 272.64 | bwd_inner_microstep: 272.63 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 23:00:12,355] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.80 | bwd_microstep: 272.92 | bwd_inner_microstep: 272.90 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 23:00:12,834] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.22 | bwd_microstep: 271.54 | bwd_inner_microstep: 271.52 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 23:00:13,311] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.77 | bwd_microstep: 271.39 | bwd_inner_microstep: 271.38 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 23:00:13,789] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.95 | bwd_microstep: 271.39 | bwd_inner_microstep: 271.37 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 23:00:14,267] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.29 | bwd_microstep: 271.43 | bwd_inner_microstep: 271.42 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1897 +[2025-05-01 23:00:14,860] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.30 | optimizer_step: 16.83 +[2025-05-01 23:00:14,860] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.60 | bwd_microstep: 360.20 | bwd_inner_microstep: 276.12 | bwd_allreduce_microstep: 84.02 | step_microstep: 25.88 +[2025-05-01 23:00:14,862] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2590.76 | bwd: 3835.20 | bwd_inner: 3750.04 | bwd_allreduce: 84.53 | step: 26.91 + 3%|▎ | 273/8720 [44:48<16:00:04, 6.82s/it] {'loss': 1.7054, 'grad_norm': 3.390023708343506, 'learning_rate': 9.999958266081981e-06, 'epoch': 0.31} + 3%|▎ | 273/8720 [44:48<16:00:04, 6.82s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1913 +[2025-05-01 23:00:15,358] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.95 | bwd_microstep: 275.62 | bwd_inner_microstep: 275.60 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.17 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 344 +[2025-05-01 23:00:15,563] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 73.65 | bwd_microstep: 118.12 | bwd_inner_microstep: 117.79 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1886 +[2025-05-01 23:00:16,042] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.68 | bwd_microstep: 274.61 | bwd_inner_microstep: 274.59 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-01 23:00:16,521] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.63 | bwd_microstep: 273.80 | bwd_inner_microstep: 273.78 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-01 23:00:16,999] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.00 | bwd_microstep: 274.38 | bwd_inner_microstep: 274.36 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-01 23:00:17,479] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.91 | bwd_microstep: 274.50 | bwd_inner_microstep: 274.48 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-01 23:00:17,956] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.34 | bwd_microstep: 273.45 | bwd_inner_microstep: 273.44 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-01 23:00:18,434] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.87 | bwd_microstep: 273.39 | bwd_inner_microstep: 273.37 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-01 23:00:18,919] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.43 | bwd_microstep: 273.18 | bwd_inner_microstep: 273.16 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-01 23:00:19,396] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.20 | bwd_microstep: 272.97 | bwd_inner_microstep: 272.96 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-01 23:00:19,873] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.61 | bwd_microstep: 273.12 | bwd_inner_microstep: 273.10 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 836 +[2025-05-01 23:00:20,108] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.26 | bwd_microstep: 126.16 | bwd_inner_microstep: 126.09 | bwd_allreduce_microstep: 0.03 | step_microstep: 0.09 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 324 +[2025-05-01 23:00:20,308] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 71.37 | bwd_microstep: 114.70 | bwd_inner_microstep: 114.54 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 23:00:20,786] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.96 | bwd_microstep: 272.52 | bwd_inner_microstep: 272.50 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 23:00:21,262] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.77 | bwd_microstep: 271.43 | bwd_inner_microstep: 271.41 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 888 +[2025-05-01 23:00:21,600] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.33 | optimizer_step: 16.80 +[2025-05-01 23:00:21,600] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.71 | bwd_microstep: 203.14 | bwd_inner_microstep: 136.68 | bwd_allreduce_microstep: 66.30 | step_microstep: 24.31 +[2025-05-01 23:00:21,601] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2601.06 | bwd: 3845.13 | bwd_inner: 3778.03 | bwd_allreduce: 66.56 | step: 25.30 + 3%|▎ | 274/8720 [44:55<15:56:19, 6.79s/it] {'loss': 1.0724, 'grad_norm': 2.6498944759368896, 'learning_rate': 9.999950333201608e-06, 'epoch': 0.31} + 3%|▎ | 274/8720 [44:55<15:56:19, 6.79s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1911 +[2025-05-01 23:00:22,088] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.57 | bwd_microstep: 276.01 | bwd_inner_microstep: 275.99 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-01 23:00:22,568] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.94 | bwd_microstep: 274.78 | bwd_inner_microstep: 274.76 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-01 23:00:23,049] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.93 | bwd_microstep: 274.04 | bwd_inner_microstep: 274.02 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-01 23:00:23,531] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.72 | bwd_microstep: 273.30 | bwd_inner_microstep: 273.28 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.20 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 847 +[2025-05-01 23:00:23,805] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 117.76 | bwd_microstep: 131.86 | bwd_inner_microstep: 131.84 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.12 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 838 +[2025-05-01 23:00:24,055] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 101.65 | bwd_microstep: 125.96 | bwd_inner_microstep: 125.78 | bwd_allreduce_microstep: 0.09 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-01 23:00:24,534] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.56 | bwd_microstep: 272.88 | bwd_inner_microstep: 272.86 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 23:00:25,014] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.40 | bwd_microstep: 272.55 | bwd_inner_microstep: 272.53 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1358 +[2025-05-01 23:00:25,382] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.08 | bwd_microstep: 206.89 | bwd_inner_microstep: 206.73 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:00:25,869] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.56 | bwd_microstep: 272.94 | bwd_inner_microstep: 272.92 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 23:00:26,351] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.80 | bwd_microstep: 272.67 | bwd_inner_microstep: 272.66 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 23:00:26,832] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.90 | bwd_microstep: 272.24 | bwd_inner_microstep: 272.22 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1346 +[2025-05-01 23:00:27,198] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.66 | bwd_microstep: 205.81 | bwd_inner_microstep: 205.70 | bwd_allreduce_microstep: 0.03 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 23:00:27,680] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.43 | bwd_microstep: 271.64 | bwd_inner_microstep: 271.62 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 23:00:28,163] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.14 | bwd_microstep: 271.71 | bwd_inner_microstep: 271.69 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 23:00:28,749] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.46 | optimizer_step: 16.55 +[2025-05-01 23:00:28,749] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.67 | bwd_microstep: 349.74 | bwd_inner_microstep: 272.27 | bwd_allreduce_microstep: 77.40 | step_microstep: 24.99 +[2025-05-01 23:00:28,751] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2771.34 | bwd: 4025.12 | bwd_inner: 3946.88 | bwd_allreduce: 77.73 | step: 26.54 + 3%|▎ | 275/8720 [45:02<16:11:18, 6.90s/it] {'loss': 1.3034, 'grad_norm': 3.875713586807251, 'learning_rate': 9.999941710510307e-06, 'epoch': 0.32} + 3%|▎ | 275/8720 [45:02<16:11:18, 6.90s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1921 +[2025-05-01 23:00:29,256] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.15 | bwd_microstep: 286.71 | bwd_inner_microstep: 286.70 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1889 +[2025-05-01 23:00:29,737] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.05 | bwd_microstep: 274.88 | bwd_inner_microstep: 274.87 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-01 23:00:30,218] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.91 | bwd_microstep: 273.67 | bwd_inner_microstep: 273.65 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-01 23:00:30,700] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.95 | bwd_microstep: 273.86 | bwd_inner_microstep: 273.84 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 23:00:31,189] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.78 | bwd_microstep: 272.63 | bwd_inner_microstep: 272.62 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 23:00:31,668] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.92 | bwd_microstep: 272.37 | bwd_inner_microstep: 272.36 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-01 23:00:32,150] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.96 | bwd_microstep: 273.13 | bwd_inner_microstep: 273.11 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:00:32,633] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.47 | bwd_microstep: 272.81 | bwd_inner_microstep: 272.79 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 324 +[2025-05-01 23:00:32,878] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 99.05 | bwd_microstep: 123.68 | bwd_inner_microstep: 123.36 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-01 23:00:33,358] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.71 | bwd_microstep: 272.99 | bwd_inner_microstep: 272.98 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 23:00:33,840] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.12 | bwd_microstep: 273.09 | bwd_inner_microstep: 273.07 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 23:00:34,321] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.14 | bwd_microstep: 272.55 | bwd_inner_microstep: 272.53 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 320 +[2025-05-01 23:00:34,544] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 89.60 | bwd_microstep: 117.27 | bwd_inner_microstep: 116.95 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 23:00:35,026] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.64 | bwd_microstep: 272.34 | bwd_inner_microstep: 272.32 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 23:00:35,503] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.69 | bwd_microstep: 271.31 | bwd_inner_microstep: 271.29 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-01 23:00:36,073] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.22 | optimizer_step: 16.69 +[2025-05-01 23:00:36,074] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.31 | bwd_microstep: 340.33 | bwd_inner_microstep: 273.82 | bwd_allreduce_microstep: 66.46 | step_microstep: 23.72 +[2025-05-01 23:00:36,075] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2839.05 | bwd: 4143.71 | bwd_inner: 4076.40 | bwd_allreduce: 66.78 | step: 24.77 + 3%|▎ | 276/8720 [45:09<16:28:58, 7.03s/it] {'loss': 1.7436, 'grad_norm': 5.2862420082092285, 'learning_rate': 9.99993239800927e-06, 'epoch': 0.32} + 3%|▎ | 276/8720 [45:09<16:28:58, 7.03s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2244 +[2025-05-01 23:00:36,626] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 209.09 | bwd_microstep: 322.51 | bwd_inner_microstep: 322.49 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1897 +[2025-05-01 23:00:37,107] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.19 | bwd_microstep: 275.61 | bwd_inner_microstep: 275.59 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1888 +[2025-05-01 23:00:37,588] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.92 | bwd_microstep: 274.81 | bwd_inner_microstep: 274.79 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-01 23:00:38,067] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.89 | bwd_microstep: 273.18 | bwd_inner_microstep: 273.16 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-01 23:00:38,549] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.58 | bwd_microstep: 274.35 | bwd_inner_microstep: 274.33 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 23:00:39,026] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.49 | bwd_microstep: 272.60 | bwd_inner_microstep: 272.58 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-01 23:00:39,503] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.93 | bwd_microstep: 272.94 | bwd_inner_microstep: 272.92 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 842 +[2025-05-01 23:00:39,746] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.74 | bwd_microstep: 132.46 | bwd_inner_microstep: 132.44 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 840 +[2025-05-01 23:00:39,979] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 92.30 | bwd_microstep: 126.75 | bwd_inner_microstep: 126.61 | bwd_allreduce_microstep: 0.09 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 23:00:40,455] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.44 | bwd_microstep: 272.53 | bwd_inner_microstep: 272.51 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 23:00:40,931] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.86 | bwd_microstep: 272.72 | bwd_inner_microstep: 272.70 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-01 23:00:41,407] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.35 | bwd_microstep: 272.86 | bwd_inner_microstep: 272.84 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 831 +[2025-05-01 23:00:41,651] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 97.79 | bwd_microstep: 130.14 | bwd_inner_microstep: 129.88 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 23:00:42,127] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.36 | bwd_microstep: 271.30 | bwd_inner_microstep: 271.29 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 23:00:42,605] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.72 | bwd_microstep: 271.05 | bwd_inner_microstep: 271.03 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-01 23:00:43,188] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.21 | optimizer_step: 16.52 +[2025-05-01 23:00:43,189] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.81 | bwd_microstep: 351.78 | bwd_inner_microstep: 274.96 | bwd_allreduce_microstep: 76.76 | step_microstep: 24.46 +[2025-05-01 23:00:43,190] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2759.16 | bwd: 4067.65 | bwd_inner: 3990.16 | bwd_allreduce: 77.03 | step: 25.45 + 3%|▎ | 277/8720 [45:16<16:32:40, 7.05s/it] {'loss': 1.2601, 'grad_norm': 4.287728309631348, 'learning_rate': 9.999922395699782e-06, 'epoch': 0.32} + 3%|▎ | 277/8720 [45:16<16:32:40, 7.05s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1928 +[2025-05-01 23:00:43,696] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.48 | bwd_microstep: 287.47 | bwd_inner_microstep: 287.46 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 346 +[2025-05-01 23:00:43,917] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 83.54 | bwd_microstep: 120.63 | bwd_inner_microstep: 120.31 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-01 23:00:44,397] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.32 | bwd_microstep: 274.46 | bwd_inner_microstep: 274.44 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 329 +[2025-05-01 23:00:44,639] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 90.96 | bwd_microstep: 132.38 | bwd_inner_microstep: 132.21 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-01 23:00:45,119] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.37 | bwd_microstep: 273.06 | bwd_inner_microstep: 273.04 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 841 +[2025-05-01 23:00:45,371] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 101.52 | bwd_microstep: 131.81 | bwd_inner_microstep: 131.77 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-01 23:00:45,850] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.00 | bwd_microstep: 273.21 | bwd_inner_microstep: 273.20 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.07 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-01 23:00:46,331] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.56 | bwd_microstep: 272.81 | bwd_inner_microstep: 272.79 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 23:00:46,810] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.43 | bwd_microstep: 272.32 | bwd_inner_microstep: 272.31 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 23:00:47,288] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.92 | bwd_microstep: 271.33 | bwd_inner_microstep: 271.31 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 23:00:47,765] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.96 | bwd_microstep: 271.36 | bwd_inner_microstep: 271.34 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 23:00:48,244] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.02 | bwd_microstep: 271.71 | bwd_inner_microstep: 271.70 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 23:00:48,723] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.81 | bwd_microstep: 271.34 | bwd_inner_microstep: 271.32 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 23:00:49,200] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.41 | bwd_microstep: 271.16 | bwd_inner_microstep: 271.15 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 314 +[2025-05-01 23:00:49,413] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 80.54 | bwd_microstep: 116.85 | bwd_inner_microstep: 116.70 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1895 +[2025-05-01 23:00:49,997] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.50 | optimizer_step: 17.05 +[2025-05-01 23:00:49,998] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.59 | bwd_microstep: 352.29 | bwd_inner_microstep: 275.74 | bwd_allreduce_microstep: 76.50 | step_microstep: 25.01 +[2025-05-01 23:00:49,999] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2625.05 | bwd: 3864.27 | bwd_inner: 3786.90 | bwd_allreduce: 76.82 | step: 25.99 + 3%|▎ | 278/8720 [45:23<16:22:09, 6.98s/it] {'loss': 1.108, 'grad_norm': 3.7578816413879395, 'learning_rate': 9.99991170358322e-06, 'epoch': 0.32} + 3%|▎ | 278/8720 [45:23<16:22:09, 6.98s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1893 +[2025-05-01 23:00:50,485] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.47 | bwd_microstep: 274.31 | bwd_inner_microstep: 274.29 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1888 +[2025-05-01 23:00:50,966] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.06 | bwd_microstep: 274.55 | bwd_inner_microstep: 274.53 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1887 +[2025-05-01 23:00:51,446] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.67 | bwd_microstep: 274.61 | bwd_inner_microstep: 274.59 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.14 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-01 23:00:51,923] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.94 | bwd_microstep: 273.11 | bwd_inner_microstep: 273.09 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-01 23:00:52,403] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.70 | bwd_microstep: 272.62 | bwd_inner_microstep: 272.60 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 333 +[2025-05-01 23:00:52,644] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.62 | bwd_microstep: 126.30 | bwd_inner_microstep: 126.00 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.11 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 839 +[2025-05-01 23:00:52,885] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 97.11 | bwd_microstep: 126.47 | bwd_inner_microstep: 126.40 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-01 23:00:53,364] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.42 | bwd_microstep: 272.71 | bwd_inner_microstep: 272.70 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:00:53,845] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.19 | bwd_microstep: 272.48 | bwd_inner_microstep: 272.46 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 23:00:54,325] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.73 | bwd_microstep: 272.60 | bwd_inner_microstep: 272.58 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 23:00:54,804] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.75 | bwd_microstep: 272.25 | bwd_inner_microstep: 272.24 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.16 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 23:00:55,282] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.90 | bwd_microstep: 272.09 | bwd_inner_microstep: 272.07 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 23:00:55,762] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.93 | bwd_microstep: 271.21 | bwd_inner_microstep: 271.19 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 23:00:56,246] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.95 | bwd_microstep: 271.47 | bwd_inner_microstep: 271.45 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 23:00:56,724] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.92 | bwd_microstep: 271.22 | bwd_inner_microstep: 271.20 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-01 23:00:57,307] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.18 | optimizer_step: 16.47 +[2025-05-01 23:00:57,308] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.80 | bwd_microstep: 352.37 | bwd_inner_microstep: 271.57 | bwd_allreduce_microstep: 80.75 | step_microstep: 24.12 +[2025-05-01 23:00:57,309] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2829.78 | bwd: 4150.43 | bwd_inner: 4069.03 | bwd_allreduce: 80.99 | step: 25.52 + 3%|▎ | 279/8720 [45:31<16:35:57, 7.08s/it] {'loss': 1.0849, 'grad_norm': 3.5207252502441406, 'learning_rate': 9.999900321661062e-06, 'epoch': 0.32} + 3%|▎ | 279/8720 [45:31<16:35:57, 7.08s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2054 +[2025-05-01 23:00:57,837] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 204.05 | bwd_microstep: 301.29 | bwd_inner_microstep: 301.27 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1898 +[2025-05-01 23:00:58,321] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.49 | bwd_microstep: 275.66 | bwd_inner_microstep: 275.65 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1902 +[2025-05-01 23:00:58,806] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.45 | bwd_microstep: 275.70 | bwd_inner_microstep: 275.68 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 367 +[2025-05-01 23:00:59,055] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.82 | bwd_microstep: 124.99 | bwd_inner_microstep: 124.69 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-01 23:00:59,534] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.44 | bwd_microstep: 274.34 | bwd_inner_microstep: 274.32 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-01 23:01:00,014] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.40 | bwd_microstep: 273.92 | bwd_inner_microstep: 273.90 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 23:01:00,495] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.03 | bwd_microstep: 272.88 | bwd_inner_microstep: 272.86 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-01 23:01:00,976] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.56 | bwd_microstep: 273.60 | bwd_inner_microstep: 273.59 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-01 23:01:01,456] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.40 | bwd_microstep: 273.16 | bwd_inner_microstep: 273.14 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 23:01:01,938] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.92 | bwd_microstep: 272.86 | bwd_inner_microstep: 272.85 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 23:01:02,418] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.87 | bwd_microstep: 272.85 | bwd_inner_microstep: 272.83 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 23:01:02,898] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.75 | bwd_microstep: 272.42 | bwd_inner_microstep: 272.40 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 23:01:03,376] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.52 | bwd_microstep: 271.41 | bwd_inner_microstep: 271.40 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 23:01:03,857] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.45 | bwd_microstep: 271.52 | bwd_inner_microstep: 271.50 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.14 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 321 +[2025-05-01 23:01:04,100] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 100.35 | bwd_microstep: 123.39 | bwd_inner_microstep: 123.15 | bwd_allreduce_microstep: 0.09 | step_microstep: 0.12 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 315 +[2025-05-01 23:01:04,466] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.28 | optimizer_step: 16.63 +[2025-05-01 23:01:04,467] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 89.60 | bwd_microstep: 232.37 | bwd_inner_microstep: 155.15 | bwd_allreduce_microstep: 77.10 | step_microstep: 24.81 +[2025-05-01 23:01:04,468] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2757.73 | bwd: 4062.46 | bwd_inner: 3984.54 | bwd_allreduce: 77.38 | step: 25.84 + 3%|▎ | 280/8720 [45:38<16:39:14, 7.10s/it] {'loss': 1.0811, 'grad_norm': 4.196808338165283, 'learning_rate': 9.999888249934879e-06, 'epoch': 0.32} + 3%|▎ | 280/8720 [45:38<16:39:14, 7.10s/it]dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1144 +[2025-05-01 23:01:04,774] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 118.10 | bwd_microstep: 164.52 | bwd_inner_microstep: 164.50 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1890 +[2025-05-01 23:01:05,256] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.79 | bwd_microstep: 274.80 | bwd_inner_microstep: 274.78 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-01 23:01:05,735] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.94 | bwd_microstep: 273.31 | bwd_inner_microstep: 273.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-01 23:01:06,215] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.46 | bwd_microstep: 273.58 | bwd_inner_microstep: 273.56 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-01 23:01:06,695] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.75 | bwd_microstep: 273.09 | bwd_inner_microstep: 273.07 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-01 23:01:07,175] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.13 | bwd_microstep: 273.12 | bwd_inner_microstep: 273.11 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-01 23:01:07,655] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.14 | bwd_microstep: 273.06 | bwd_inner_microstep: 273.04 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 23:01:08,135] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.95 | bwd_microstep: 272.50 | bwd_inner_microstep: 272.48 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 23:01:08,615] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.32 | bwd_microstep: 272.60 | bwd_inner_microstep: 272.58 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 837 +[2025-05-01 23:01:08,866] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 106.46 | bwd_microstep: 125.62 | bwd_inner_microstep: 125.33 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 23:01:09,350] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.96 | bwd_microstep: 272.62 | bwd_inner_microstep: 272.60 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:01:09,834] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.60 | bwd_microstep: 272.72 | bwd_inner_microstep: 272.70 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 23:01:10,314] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.43 | bwd_microstep: 272.49 | bwd_inner_microstep: 272.47 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 323 +[2025-05-01 23:01:10,555] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 97.23 | bwd_microstep: 125.81 | bwd_inner_microstep: 125.66 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 23:01:11,034] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.09 | bwd_microstep: 272.51 | bwd_inner_microstep: 272.49 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.17 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 833 +[2025-05-01 23:01:11,395] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.29 | optimizer_step: 17.43 +[2025-05-01 23:01:11,396] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 96.22 | bwd_microstep: 222.32 | bwd_inner_microstep: 144.96 | bwd_allreduce_microstep: 77.25 | step_microstep: 25.51 +[2025-05-01 23:01:11,397] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2687.18 | bwd: 3914.72 | bwd_inner: 3836.72 | bwd_allreduce: 77.51 | step: 26.64 + 3%|▎ | 281/8720 [45:45<16:31:44, 7.05s/it] {'loss': 1.2659, 'grad_norm': 5.278073787689209, 'learning_rate': 9.999875488406333e-06, 'epoch': 0.32} + 3%|▎ | 281/8720 [45:45<16:31:44, 7.05s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1939 +[2025-05-01 23:01:11,904] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.17 | bwd_microstep: 288.19 | bwd_inner_microstep: 288.17 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1896 +[2025-05-01 23:01:12,384] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.21 | bwd_microstep: 275.11 | bwd_inner_microstep: 275.09 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1887 +[2025-05-01 23:01:12,863] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.99 | bwd_microstep: 274.60 | bwd_inner_microstep: 274.58 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-01 23:01:13,340] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.46 | bwd_microstep: 273.41 | bwd_inner_microstep: 273.40 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-01 23:01:13,818] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.33 | bwd_microstep: 273.18 | bwd_inner_microstep: 273.16 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-01 23:01:14,295] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.42 | bwd_microstep: 273.46 | bwd_inner_microstep: 273.44 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 23:01:14,773] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.41 | bwd_microstep: 272.65 | bwd_inner_microstep: 272.63 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 325 +[2025-05-01 23:01:15,006] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 91.56 | bwd_microstep: 122.69 | bwd_inner_microstep: 122.49 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:01:15,485] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.68 | bwd_microstep: 272.68 | bwd_inner_microstep: 272.67 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 23:01:15,964] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.63 | bwd_microstep: 272.53 | bwd_inner_microstep: 272.51 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 23:01:16,442] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.82 | bwd_microstep: 272.38 | bwd_inner_microstep: 272.36 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 23:01:16,918] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.96 | bwd_microstep: 271.32 | bwd_inner_microstep: 271.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-01 23:01:17,394] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.13 | bwd_microstep: 271.01 | bwd_inner_microstep: 270.99 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.12 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 396 +[2025-05-01 23:01:17,664] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 125.00 | bwd_microstep: 118.49 | bwd_inner_microstep: 118.30 | bwd_allreduce_microstep: 0.08 | step_microstep: 0.11 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 345 +[2025-05-01 23:01:17,896] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 98.85 | bwd_microstep: 116.81 | bwd_inner_microstep: 116.64 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 23:01:18,499] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.39 | optimizer_step: 16.62 +[2025-05-01 23:01:18,499] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.87 | bwd_microstep: 370.43 | bwd_inner_microstep: 271.79 | bwd_allreduce_microstep: 98.58 | step_microstep: 26.44 +[2025-05-01 23:01:18,501] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2773.18 | bwd: 4019.01 | bwd_inner: 3919.67 | bwd_allreduce: 98.87 | step: 27.84 + 3%|▎ | 282/8720 [45:52<16:33:50, 7.07s/it] {'loss': 1.4465, 'grad_norm': 4.142888069152832, 'learning_rate': 9.999862037077187e-06, 'epoch': 0.32} + 3%|▎ | 282/8720 [45:52<16:33:50, 7.07s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2293 +[2025-05-01 23:01:19,066] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 214.49 | bwd_microstep: 326.09 | bwd_inner_microstep: 326.08 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1902 +[2025-05-01 23:01:19,548] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.04 | bwd_microstep: 275.78 | bwd_inner_microstep: 275.76 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1904 +[2025-05-01 23:01:20,031] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.91 | bwd_microstep: 276.18 | bwd_inner_microstep: 276.13 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.21 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-01 23:01:20,512] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.85 | bwd_microstep: 273.34 | bwd_inner_microstep: 273.32 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:01:20,991] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.17 | bwd_microstep: 272.74 | bwd_inner_microstep: 272.72 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-01 23:01:21,477] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.97 | bwd_microstep: 273.06 | bwd_inner_microstep: 273.04 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.16 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 23:01:21,956] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.11 | bwd_microstep: 272.38 | bwd_inner_microstep: 272.36 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1351 +[2025-05-01 23:01:22,323] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.71 | bwd_microstep: 206.34 | bwd_inner_microstep: 206.21 | bwd_allreduce_microstep: 0.04 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-01 23:01:22,803] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.48 | bwd_microstep: 273.30 | bwd_inner_microstep: 273.28 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-01 23:01:23,286] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.27 | bwd_microstep: 273.16 | bwd_inner_microstep: 273.14 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-01 23:01:23,766] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.48 | bwd_microstep: 272.88 | bwd_inner_microstep: 272.86 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 23:01:24,250] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.45 | bwd_microstep: 271.38 | bwd_inner_microstep: 271.37 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:01:24,730] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.06 | bwd_microstep: 272.75 | bwd_inner_microstep: 272.73 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 23:01:25,206] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.83 | bwd_microstep: 271.70 | bwd_inner_microstep: 271.68 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 23:01:25,682] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.85 | bwd_microstep: 271.31 | bwd_inner_microstep: 271.29 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 23:01:26,269] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 3.03 | optimizer_step: 17.78 +[2025-05-01 23:01:26,270] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.11 | bwd_microstep: 356.91 | bwd_inner_microstep: 271.79 | bwd_allreduce_microstep: 85.07 | step_microstep: 27.12 +[2025-05-01 23:01:26,271] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 3002.42 | bwd: 4439.36 | bwd_inner: 4353.77 | bwd_allreduce: 85.22 | step: 28.41 + 3%|▎ | 283/8720 [46:00<17:03:18, 7.28s/it] {'loss': 1.4973, 'grad_norm': 5.018159866333008, 'learning_rate': 9.999847895949297e-06, 'epoch': 0.32} + 3%|▎ | 283/8720 [46:00<17:03:18, 7.28s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2024 +[2025-05-01 23:01:26,788] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 200.70 | bwd_microstep: 296.31 | bwd_inner_microstep: 296.29 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1952 +[2025-05-01 23:01:27,292] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 197.13 | bwd_microstep: 289.95 | bwd_inner_microstep: 289.88 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.16 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1947 +[2025-05-01 23:01:27,796] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 196.18 | bwd_microstep: 289.59 | bwd_inner_microstep: 289.57 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-01 23:01:28,277] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.40 | bwd_microstep: 274.16 | bwd_inner_microstep: 274.14 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 329 +[2025-05-01 23:01:28,500] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 89.48 | bwd_microstep: 116.78 | bwd_inner_microstep: 116.46 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.19 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 334 +[2025-05-01 23:01:28,759] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 87.19 | bwd_microstep: 153.84 | bwd_inner_microstep: 153.68 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 844 +[2025-05-01 23:01:29,004] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.38 | bwd_microstep: 133.85 | bwd_inner_microstep: 133.54 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 839 +[2025-05-01 23:01:29,252] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 98.97 | bwd_microstep: 132.23 | bwd_inner_microstep: 132.12 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 23:01:29,731] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.36 | bwd_microstep: 272.42 | bwd_inner_microstep: 272.41 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:01:30,211] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.77 | bwd_microstep: 272.62 | bwd_inner_microstep: 272.60 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 23:01:30,690] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.56 | bwd_microstep: 272.57 | bwd_inner_microstep: 272.55 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 23:01:31,170] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.90 | bwd_microstep: 272.66 | bwd_inner_microstep: 272.65 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 23:01:31,652] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.46 | bwd_microstep: 271.31 | bwd_inner_microstep: 271.29 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 827 +[2025-05-01 23:01:31,892] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.16 | bwd_microstep: 129.52 | bwd_inner_microstep: 129.50 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1850 +[2025-05-01 23:01:32,368] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.63 | bwd_microstep: 270.96 | bwd_inner_microstep: 270.94 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1966 +[2025-05-01 23:01:32,976] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.42 | optimizer_step: 16.98 +[2025-05-01 23:01:32,976] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 197.33 | bwd_microstep: 368.57 | bwd_inner_microstep: 291.63 | bwd_allreduce_microstep: 76.88 | step_microstep: 24.91 +[2025-05-01 23:01:32,978] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2576.24 | bwd: 3817.46 | bwd_inner: 3739.41 | bwd_allreduce: 77.35 | step: 26.19 + 3%|▎ | 284/8720 [46:06<16:39:10, 7.11s/it] {'loss': 1.2529, 'grad_norm': 3.2469711303710938, 'learning_rate': 9.999833065024613e-06, 'epoch': 0.33} + 3%|▎ | 284/8720 [46:06<16:39:10, 7.11s/it]dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 987 +[2025-05-01 23:01:33,252] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 102.47 | bwd_microstep: 150.55 | bwd_inner_microstep: 150.32 | bwd_allreduce_microstep: 0.10 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1895 +[2025-05-01 23:01:33,732] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.44 | bwd_microstep: 275.25 | bwd_inner_microstep: 275.23 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-01 23:01:34,210] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.45 | bwd_microstep: 273.65 | bwd_inner_microstep: 273.63 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-01 23:01:34,690] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.50 | bwd_microstep: 274.60 | bwd_inner_microstep: 274.58 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-01 23:01:35,168] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.67 | bwd_microstep: 273.70 | bwd_inner_microstep: 273.68 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 855 +[2025-05-01 23:01:35,413] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 97.35 | bwd_microstep: 133.63 | bwd_inner_microstep: 133.37 | bwd_allreduce_microstep: 0.14 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-01 23:01:35,890] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.60 | bwd_microstep: 273.32 | bwd_inner_microstep: 273.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-01 23:01:36,369] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.60 | bwd_microstep: 273.65 | bwd_inner_microstep: 273.64 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:01:36,847] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.49 | bwd_microstep: 272.52 | bwd_inner_microstep: 272.50 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1093 +[2025-05-01 23:01:37,138] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 115.31 | bwd_microstep: 161.07 | bwd_inner_microstep: 161.03 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 23:01:37,615] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.09 | bwd_microstep: 272.45 | bwd_inner_microstep: 272.43 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 23:01:38,089] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.73 | bwd_microstep: 271.38 | bwd_inner_microstep: 271.36 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 317 +[2025-05-01 23:01:38,307] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 81.73 | bwd_microstep: 122.03 | bwd_inner_microstep: 121.89 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-01 23:01:38,783] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.34 | bwd_microstep: 271.20 | bwd_inner_microstep: 271.18 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-01 23:01:39,263] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.25 | bwd_microstep: 271.29 | bwd_inner_microstep: 271.27 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-01 23:01:39,846] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.32 | optimizer_step: 16.49 +[2025-05-01 23:01:39,847] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.09 | bwd_microstep: 353.13 | bwd_inner_microstep: 271.82 | bwd_allreduce_microstep: 81.26 | step_microstep: 24.31 +[2025-05-01 23:01:39,848] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2664.81 | bwd: 3923.48 | bwd_inner: 3841.30 | bwd_allreduce: 81.64 | step: 25.18 + 3%|▎ | 285/8720 [46:13<16:29:05, 7.04s/it] {'loss': 1.2692, 'grad_norm': 4.362312316894531, 'learning_rate': 9.999817544305181e-06, 'epoch': 0.33} + 3%|▎ | 285/8720 [46:13<16:29:05, 7.04s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1925 +[2025-05-01 23:01:40,353] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.34 | bwd_microstep: 287.17 | bwd_inner_microstep: 287.15 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1362 +[2025-05-01 23:01:40,718] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.76 | bwd_microstep: 207.39 | bwd_inner_microstep: 207.24 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.10 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1368 +[2025-05-01 23:01:41,085] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 142.01 | bwd_microstep: 207.79 | bwd_inner_microstep: 207.66 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.10 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1366 +[2025-05-01 23:01:41,456] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 142.43 | bwd_microstep: 207.75 | bwd_inner_microstep: 207.73 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-01 23:01:41,937] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.17 | bwd_microstep: 273.60 | bwd_inner_microstep: 273.58 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-01 23:01:42,420] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.12 | bwd_microstep: 273.63 | bwd_inner_microstep: 273.61 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 23:01:42,906] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.40 | bwd_microstep: 273.13 | bwd_inner_microstep: 273.11 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 23:01:43,390] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.04 | bwd_microstep: 272.98 | bwd_inner_microstep: 272.96 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 23:01:43,870] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.82 | bwd_microstep: 273.39 | bwd_inner_microstep: 273.37 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 23:01:44,353] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.99 | bwd_microstep: 273.35 | bwd_inner_microstep: 273.34 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:01:44,833] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.16 | bwd_microstep: 273.19 | bwd_inner_microstep: 273.17 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 23:01:45,315] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.32 | bwd_microstep: 273.14 | bwd_inner_microstep: 273.13 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 835 +[2025-05-01 23:01:45,553] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.18 | bwd_microstep: 126.52 | bwd_inner_microstep: 126.47 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 23:01:46,032] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.02 | bwd_microstep: 272.97 | bwd_inner_microstep: 272.95 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 23:01:46,508] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.56 | bwd_microstep: 272.80 | bwd_inner_microstep: 272.79 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1928 +[2025-05-01 23:01:47,098] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.25 | optimizer_step: 16.43 +[2025-05-01 23:01:47,099] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.77 | bwd_microstep: 355.87 | bwd_inner_microstep: 288.89 | bwd_allreduce_microstep: 66.93 | step_microstep: 23.62 +[2025-05-01 23:01:47,100] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2803.71 | bwd: 4124.74 | bwd_inner: 4057.15 | bwd_allreduce: 67.19 | step: 24.79 + 3%|▎ | 286/8720 [46:20<16:38:01, 7.10s/it] {'loss': 1.5771, 'grad_norm': 4.114975452423096, 'learning_rate': 9.999801333793145e-06, 'epoch': 0.33} + 3%|▎ | 286/8720 [46:20<16:38:01, 7.10s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1949 +[2025-05-01 23:01:47,605] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 196.41 | bwd_microstep: 288.65 | bwd_inner_microstep: 288.63 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1893 +[2025-05-01 23:01:48,086] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.65 | bwd_microstep: 274.97 | bwd_inner_microstep: 274.96 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1888 +[2025-05-01 23:01:48,565] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.46 | bwd_microstep: 274.48 | bwd_inner_microstep: 274.46 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-01 23:01:49,044] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.20 | bwd_microstep: 273.77 | bwd_inner_microstep: 273.75 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-01 23:01:49,521] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.41 | bwd_microstep: 273.02 | bwd_inner_microstep: 273.00 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-01 23:01:49,999] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.51 | bwd_microstep: 272.98 | bwd_inner_microstep: 272.96 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 841 +[2025-05-01 23:01:50,240] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.43 | bwd_microstep: 132.17 | bwd_inner_microstep: 132.15 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-01 23:01:50,717] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.94 | bwd_microstep: 272.89 | bwd_inner_microstep: 272.87 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-01 23:01:51,194] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.04 | bwd_microstep: 272.83 | bwd_inner_microstep: 272.81 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 23:01:51,670] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.40 | bwd_microstep: 272.19 | bwd_inner_microstep: 272.17 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:01:52,150] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.50 | bwd_microstep: 272.44 | bwd_inner_microstep: 272.42 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 23:01:52,628] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.86 | bwd_microstep: 272.64 | bwd_inner_microstep: 272.62 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 325 +[2025-05-01 23:01:52,842] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 79.75 | bwd_microstep: 118.48 | bwd_inner_microstep: 118.16 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:01:53,323] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.32 | bwd_microstep: 272.79 | bwd_inner_microstep: 272.77 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.16 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 23:01:53,802] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.47 | bwd_microstep: 271.27 | bwd_inner_microstep: 271.25 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-01 23:01:54,391] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.45 | optimizer_step: 16.73 +[2025-05-01 23:01:54,392] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.04 | bwd_microstep: 356.12 | bwd_inner_microstep: 271.57 | bwd_allreduce_microstep: 84.49 | step_microstep: 24.77 +[2025-05-01 23:01:54,393] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2826.09 | bwd: 4171.72 | bwd_inner: 4086.62 | bwd_allreduce: 84.70 | step: 25.80 + 3%|▎ | 287/8720 [46:28<16:46:08, 7.16s/it] {'loss': 1.7548, 'grad_norm': 5.356560230255127, 'learning_rate': 9.999784433490737e-06, 'epoch': 0.33} + 3%|▎ | 287/8720 [46:28<16:46:08, 7.16s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1979 +[2025-05-01 23:01:54,908] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 199.78 | bwd_microstep: 291.67 | bwd_inner_microstep: 291.65 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1920 +[2025-05-01 23:01:55,396] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 191.85 | bwd_microstep: 276.75 | bwd_inner_microstep: 276.73 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1888 +[2025-05-01 23:01:55,883] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.10 | bwd_microstep: 274.32 | bwd_inner_microstep: 274.30 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 357 +[2025-05-01 23:01:56,127] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 107.20 | bwd_microstep: 116.02 | bwd_inner_microstep: 115.68 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 346 +[2025-05-01 23:01:56,356] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 88.35 | bwd_microstep: 124.81 | bwd_inner_microstep: 124.64 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-01 23:01:56,836] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.63 | bwd_microstep: 273.62 | bwd_inner_microstep: 273.60 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-01 23:01:57,320] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.91 | bwd_microstep: 273.28 | bwd_inner_microstep: 273.26 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-01 23:01:57,802] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.51 | bwd_microstep: 273.22 | bwd_inner_microstep: 273.20 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.23 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 23:01:58,282] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.79 | bwd_microstep: 272.60 | bwd_inner_microstep: 272.58 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 23:01:58,763] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.41 | bwd_microstep: 272.33 | bwd_inner_microstep: 272.31 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.13 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-01 23:01:59,246] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.50 | bwd_microstep: 272.71 | bwd_inner_microstep: 272.69 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 23:01:59,728] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.32 | bwd_microstep: 272.80 | bwd_inner_microstep: 272.78 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 325 +[2025-05-01 23:01:59,946] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 85.06 | bwd_microstep: 116.24 | bwd_inner_microstep: 115.94 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2000 +[2025-05-01 23:02:00,457] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 198.67 | bwd_microstep: 294.79 | bwd_inner_microstep: 294.77 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1899 +[2025-05-01 23:02:00,941] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.53 | bwd_microstep: 276.48 | bwd_inner_microstep: 276.46 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-01 23:02:01,542] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.32 | optimizer_step: 16.43 +[2025-05-01 23:02:01,543] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.89 | bwd_microstep: 367.56 | bwd_inner_microstep: 273.59 | bwd_allreduce_microstep: 93.90 | step_microstep: 25.67 +[2025-05-01 23:02:01,544] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2763.09 | bwd: 4049.26 | bwd_inner: 3954.35 | bwd_allreduce: 94.29 | step: 26.94 + 3%|▎ | 288/8720 [46:35<16:45:40, 7.16s/it] {'loss': 1.3722, 'grad_norm': 3.0252933502197266, 'learning_rate': 9.999766843400291e-06, 'epoch': 0.33} + 3%|▎ | 288/8720 [46:35<16:45:40, 7.16s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1889 +[2025-05-01 23:02:02,029] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.22 | bwd_microstep: 273.98 | bwd_inner_microstep: 273.96 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-01 23:02:02,507] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.02 | bwd_microstep: 274.00 | bwd_inner_microstep: 273.98 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-01 23:02:02,989] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.03 | bwd_microstep: 273.58 | bwd_inner_microstep: 273.57 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-01 23:02:03,471] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.13 | bwd_microstep: 273.53 | bwd_inner_microstep: 273.52 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 848 +[2025-05-01 23:02:03,712] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.90 | bwd_microstep: 132.81 | bwd_inner_microstep: 132.79 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1097 +[2025-05-01 23:02:04,005] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 117.13 | bwd_microstep: 161.39 | bwd_inner_microstep: 161.23 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.18 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 324 +[2025-05-01 23:02:04,228] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 77.27 | bwd_microstep: 129.76 | bwd_inner_microstep: 129.44 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-01 23:02:04,705] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.12 | bwd_microstep: 272.90 | bwd_inner_microstep: 272.88 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-01 23:02:05,183] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.32 | bwd_microstep: 272.78 | bwd_inner_microstep: 272.76 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:02:05,662] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.00 | bwd_microstep: 272.85 | bwd_inner_microstep: 272.83 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.11 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1344 +[2025-05-01 23:02:06,024] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.23 | bwd_microstep: 204.94 | bwd_inner_microstep: 204.73 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 23:02:06,504] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.08 | bwd_microstep: 272.18 | bwd_inner_microstep: 272.16 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-01 23:02:06,982] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.35 | bwd_microstep: 271.62 | bwd_inner_microstep: 271.60 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 23:02:07,460] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.87 | bwd_microstep: 271.24 | bwd_inner_microstep: 271.23 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 23:02:07,937] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.97 | bwd_microstep: 271.18 | bwd_inner_microstep: 271.16 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 23:02:08,518] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 3.04 | optimizer_step: 16.54 +[2025-05-01 23:02:08,519] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.64 | bwd_microstep: 349.19 | bwd_inner_microstep: 271.95 | bwd_allreduce_microstep: 77.19 | step_microstep: 25.53 +[2025-05-01 23:02:08,520] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2688.94 | bwd: 3978.05 | bwd_inner: 3899.87 | bwd_allreduce: 77.62 | step: 26.67 + 3%|▎ | 289/8720 [46:42<16:37:58, 7.10s/it] {'loss': 0.8796, 'grad_norm': 3.500181198120117, 'learning_rate': 9.999748563524235e-06, 'epoch': 0.33} + 3%|▎ | 289/8720 [46:42<16:37:58, 7.10s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1897 +[2025-05-01 23:02:09,009] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.44 | bwd_microstep: 275.44 | bwd_inner_microstep: 275.30 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1892 +[2025-05-01 23:02:09,497] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.78 | bwd_microstep: 275.65 | bwd_inner_microstep: 275.63 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1125 +[2025-05-01 23:02:09,795] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 119.03 | bwd_microstep: 163.65 | bwd_inner_microstep: 163.53 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-01 23:02:10,275] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.37 | bwd_microstep: 274.13 | bwd_inner_microstep: 274.11 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.21 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-01 23:02:10,755] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.04 | bwd_microstep: 273.57 | bwd_inner_microstep: 273.55 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 339 +[2025-05-01 23:02:10,979] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 87.85 | bwd_microstep: 118.38 | bwd_inner_microstep: 118.07 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 852 +[2025-05-01 23:02:11,226] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 96.88 | bwd_microstep: 132.78 | bwd_inner_microstep: 132.70 | bwd_allreduce_microstep: 0.03 | step_microstep: 0.10 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 844 +[2025-05-01 23:02:11,470] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.93 | bwd_microstep: 132.76 | bwd_inner_microstep: 132.59 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.11 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 335 +[2025-05-01 23:02:11,710] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 83.51 | bwd_microstep: 139.74 | bwd_inner_microstep: 139.42 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.18 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1096 +[2025-05-01 23:02:12,006] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 115.55 | bwd_microstep: 161.86 | bwd_inner_microstep: 161.58 | bwd_allreduce_microstep: 0.15 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 23:02:12,488] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.67 | bwd_microstep: 272.48 | bwd_inner_microstep: 272.46 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 325 +[2025-05-01 23:02:12,722] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 99.03 | bwd_microstep: 117.29 | bwd_inner_microstep: 117.13 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 23:02:13,200] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.74 | bwd_microstep: 271.33 | bwd_inner_microstep: 271.31 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 23:02:13,680] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.15 | bwd_microstep: 272.24 | bwd_inner_microstep: 272.22 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 23:02:14,161] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.38 | bwd_microstep: 272.83 | bwd_inner_microstep: 272.81 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 23:02:14,746] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.29 | optimizer_step: 16.56 +[2025-05-01 23:02:14,747] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.39 | bwd_microstep: 351.06 | bwd_inner_microstep: 273.99 | bwd_allreduce_microstep: 77.02 | step_microstep: 24.91 +[2025-05-01 23:02:14,748] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2395.37 | bwd: 3505.42 | bwd_inner: 3426.64 | bwd_allreduce: 77.77 | step: 26.63 + 3%|▎ | 290/8720 [46:48<16:01:00, 6.84s/it] {'loss': 1.1639, 'grad_norm': 2.9278314113616943, 'learning_rate': 9.999729593865089e-06, 'epoch': 0.33} + 3%|▎ | 290/8720 [46:48<16:01:00, 6.84s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1922 +[2025-05-01 23:02:15,254] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 196.06 | bwd_microstep: 286.64 | bwd_inner_microstep: 286.62 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1918 +[2025-05-01 23:02:15,742] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 192.65 | bwd_microstep: 276.63 | bwd_inner_microstep: 276.61 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1386 +[2025-05-01 23:02:16,108] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.64 | bwd_microstep: 209.17 | bwd_inner_microstep: 209.13 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-01 23:02:16,587] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.66 | bwd_microstep: 274.08 | bwd_inner_microstep: 274.06 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1104 +[2025-05-01 23:02:16,881] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 117.81 | bwd_microstep: 161.95 | bwd_inner_microstep: 161.73 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-01 23:02:17,360] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.64 | bwd_microstep: 273.38 | bwd_inner_microstep: 273.36 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1347 +[2025-05-01 23:02:17,721] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.21 | bwd_microstep: 205.84 | bwd_inner_microstep: 205.78 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-01 23:02:18,198] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.97 | bwd_microstep: 272.77 | bwd_inner_microstep: 272.75 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 323 +[2025-05-01 23:02:18,420] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 89.56 | bwd_microstep: 116.35 | bwd_inner_microstep: 116.19 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 23:02:18,896] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.68 | bwd_microstep: 272.72 | bwd_inner_microstep: 272.70 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 23:02:19,373] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.80 | bwd_microstep: 272.29 | bwd_inner_microstep: 272.27 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-01 23:02:19,851] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.37 | bwd_microstep: 273.08 | bwd_inner_microstep: 273.07 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 23:02:20,327] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.07 | bwd_microstep: 271.57 | bwd_inner_microstep: 271.55 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 23:02:20,804] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.56 | bwd_microstep: 271.64 | bwd_inner_microstep: 271.62 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 830 +[2025-05-01 23:02:21,044] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.58 | bwd_microstep: 130.18 | bwd_inner_microstep: 129.93 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 23:02:21,615] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.39 | optimizer_step: 16.82 +[2025-05-01 23:02:21,615] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.92 | bwd_microstep: 342.97 | bwd_inner_microstep: 273.73 | bwd_allreduce_microstep: 69.14 | step_microstep: 24.66 +[2025-05-01 23:02:21,616] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2667.89 | bwd: 3911.34 | bwd_inner: 3841.20 | bwd_allreduce: 69.54 | step: 25.67 + 3%|▎ | 291/8720 [46:55<16:02:05, 6.85s/it] {'loss': 1.8274, 'grad_norm': 5.700450420379639, 'learning_rate': 9.99970993442547e-06, 'epoch': 0.33} + 3%|▎ | 291/8720 [46:55<16:02:05, 6.85s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1897 +[2025-05-01 23:02:22,103] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.30 | bwd_microstep: 274.93 | bwd_inner_microstep: 274.91 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 354 +[2025-05-01 23:02:22,334] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 76.88 | bwd_microstep: 138.76 | bwd_inner_microstep: 138.44 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1891 +[2025-05-01 23:02:22,815] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.22 | bwd_microstep: 274.93 | bwd_inner_microstep: 274.91 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1887 +[2025-05-01 23:02:23,296] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.87 | bwd_microstep: 274.76 | bwd_inner_microstep: 274.74 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-01 23:02:23,774] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.08 | bwd_microstep: 273.56 | bwd_inner_microstep: 273.54 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-01 23:02:24,253] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.47 | bwd_microstep: 272.95 | bwd_inner_microstep: 272.93 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 837 +[2025-05-01 23:02:24,487] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.02 | bwd_microstep: 126.22 | bwd_inner_microstep: 126.19 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-01 23:02:24,967] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.19 | bwd_microstep: 273.83 | bwd_inner_microstep: 273.81 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-01 23:02:25,447] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.42 | bwd_microstep: 273.25 | bwd_inner_microstep: 273.23 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 845 +[2025-05-01 23:02:25,692] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.64 | bwd_microstep: 132.86 | bwd_inner_microstep: 132.60 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 23:02:26,170] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.55 | bwd_microstep: 272.40 | bwd_inner_microstep: 272.38 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 23:02:26,650] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.34 | bwd_microstep: 272.48 | bwd_inner_microstep: 272.46 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 23:02:27,129] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.63 | bwd_microstep: 271.29 | bwd_inner_microstep: 271.27 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 23:02:27,608] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.18 | bwd_microstep: 271.64 | bwd_inner_microstep: 271.62 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 830 +[2025-05-01 23:02:27,854] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 96.83 | bwd_microstep: 130.52 | bwd_inner_microstep: 130.22 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 315 +[2025-05-01 23:02:28,204] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.38 | optimizer_step: 16.85 +[2025-05-01 23:02:28,205] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 84.55 | bwd_microstep: 224.76 | bwd_inner_microstep: 147.10 | bwd_allreduce_microstep: 77.56 | step_microstep: 25.15 +[2025-05-01 23:02:28,206] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2527.87 | bwd: 3759.22 | bwd_inner: 3680.52 | bwd_allreduce: 77.98 | step: 26.49 + 3%|▎ | 292/8720 [47:01<15:51:06, 6.77s/it] {'loss': 1.6604, 'grad_norm': 4.064864635467529, 'learning_rate': 9.999689585208092e-06, 'epoch': 0.33} + 3%|▎ | 292/8720 [47:01<15:51:06, 6.77s/it]dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 866 +[2025-05-01 23:02:28,459] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.68 | bwd_microstep: 134.51 | bwd_inner_microstep: 134.26 | bwd_allreduce_microstep: 0.10 | step_microstep: 0.09 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1371 +[2025-05-01 23:02:28,823] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.69 | bwd_microstep: 207.83 | bwd_inner_microstep: 207.77 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-01 23:02:29,302] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.78 | bwd_microstep: 274.08 | bwd_inner_microstep: 274.06 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-01 23:02:29,780] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.80 | bwd_microstep: 273.46 | bwd_inner_microstep: 273.44 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-01 23:02:30,259] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.45 | bwd_microstep: 273.30 | bwd_inner_microstep: 273.29 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-01 23:02:30,739] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.89 | bwd_microstep: 273.97 | bwd_inner_microstep: 273.95 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-01 23:02:31,220] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.76 | bwd_microstep: 273.41 | bwd_inner_microstep: 273.40 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-01 23:02:31,703] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.22 | bwd_microstep: 273.15 | bwd_inner_microstep: 273.14 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 23:02:32,186] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.81 | bwd_microstep: 272.67 | bwd_inner_microstep: 272.66 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 23:02:32,667] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.73 | bwd_microstep: 272.91 | bwd_inner_microstep: 272.89 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 23:02:33,149] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.10 | bwd_microstep: 272.72 | bwd_inner_microstep: 272.70 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 23:02:33,628] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.39 | bwd_microstep: 271.57 | bwd_inner_microstep: 271.56 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 23:02:34,111] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.50 | bwd_microstep: 272.29 | bwd_inner_microstep: 272.27 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.22 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1343 +[2025-05-01 23:02:34,475] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.48 | bwd_microstep: 204.88 | bwd_inner_microstep: 204.71 | bwd_allreduce_microstep: 0.09 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 23:02:34,958] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.56 | bwd_microstep: 271.65 | bwd_inner_microstep: 271.63 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 23:02:35,544] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 3.05 | optimizer_step: 16.89 +[2025-05-01 23:02:35,544] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.53 | bwd_microstep: 348.30 | bwd_inner_microstep: 271.92 | bwd_allreduce_microstep: 76.34 | step_microstep: 25.67 +[2025-05-01 23:02:35,546] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2829.98 | bwd: 4170.74 | bwd_inner: 4093.69 | bwd_allreduce: 76.65 | step: 27.00 + 3%|▎ | 293/8720 [47:09<16:14:54, 6.94s/it] {'loss': 1.3621, 'grad_norm': 3.4771735668182373, 'learning_rate': 9.999668546215762e-06, 'epoch': 0.34} + 3%|▎ | 293/8720 [47:09<16:14:54, 6.94s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1988 +[2025-05-01 23:02:36,060] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 197.59 | bwd_microstep: 293.32 | bwd_inner_microstep: 293.30 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 451 +[2025-05-01 23:02:36,295] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 78.87 | bwd_microstep: 139.79 | bwd_inner_microstep: 139.50 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1958 +[2025-05-01 23:02:36,801] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 197.82 | bwd_microstep: 290.47 | bwd_inner_microstep: 290.46 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 404 +[2025-05-01 23:02:37,024] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 89.49 | bwd_microstep: 116.11 | bwd_inner_microstep: 115.96 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1935 +[2025-05-01 23:02:37,527] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.90 | bwd_microstep: 288.55 | bwd_inner_microstep: 288.54 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1922 +[2025-05-01 23:02:38,030] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.41 | bwd_microstep: 287.20 | bwd_inner_microstep: 287.18 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1920 +[2025-05-01 23:02:38,517] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.91 | bwd_microstep: 276.64 | bwd_inner_microstep: 276.62 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-01 23:02:39,000] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.92 | bwd_microstep: 273.03 | bwd_inner_microstep: 273.02 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-01 23:02:39,481] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.37 | bwd_microstep: 273.49 | bwd_inner_microstep: 273.47 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-01 23:02:39,962] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.24 | bwd_microstep: 272.96 | bwd_inner_microstep: 272.95 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-01 23:02:40,443] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.33 | bwd_microstep: 272.82 | bwd_inner_microstep: 272.80 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-01 23:02:40,922] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.12 | bwd_microstep: 272.78 | bwd_inner_microstep: 272.76 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 23:02:41,401] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.67 | bwd_microstep: 272.63 | bwd_inner_microstep: 272.61 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 23:02:41,879] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.69 | bwd_microstep: 272.68 | bwd_inner_microstep: 272.66 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 23:02:42,354] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.66 | bwd_microstep: 271.15 | bwd_inner_microstep: 271.13 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1896 +[2025-05-01 23:02:42,928] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.43 | optimizer_step: 17.01 +[2025-05-01 23:02:42,929] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.05 | bwd_microstep: 344.74 | bwd_inner_microstep: 276.01 | bwd_allreduce_microstep: 68.66 | step_microstep: 24.72 +[2025-05-01 23:02:42,930] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2845.71 | bwd: 4218.42 | bwd_inner: 4149.06 | bwd_allreduce: 68.89 | step: 25.65 + 3%|▎ | 294/8720 [47:16<16:33:24, 7.07s/it] {'loss': 1.261, 'grad_norm': 2.2922236919403076, 'learning_rate': 9.999646817451381e-06, 'epoch': 0.34} + 3%|▎ | 294/8720 [47:16<16:33:24, 7.07s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 362 +[2025-05-01 23:02:43,149] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 72.16 | bwd_microstep: 128.18 | bwd_inner_microstep: 127.90 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-01 23:02:43,627] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.67 | bwd_microstep: 273.06 | bwd_inner_microstep: 273.04 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 836 +[2025-05-01 23:02:43,862] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 92.60 | bwd_microstep: 126.23 | bwd_inner_microstep: 125.98 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:02:44,340] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.19 | bwd_microstep: 272.83 | bwd_inner_microstep: 272.81 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 837 +[2025-05-01 23:02:44,574] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 92.37 | bwd_microstep: 126.55 | bwd_inner_microstep: 126.29 | bwd_allreduce_microstep: 0.14 | step_microstep: 0.09 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1092 +[2025-05-01 23:02:44,867] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 115.20 | bwd_microstep: 161.16 | bwd_inner_microstep: 161.14 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 326 +[2025-05-01 23:02:45,090] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 80.09 | bwd_microstep: 127.66 | bwd_inner_microstep: 127.51 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-01 23:02:45,567] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.11 | bwd_microstep: 273.10 | bwd_inner_microstep: 273.08 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:02:46,045] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.97 | bwd_microstep: 272.79 | bwd_inner_microstep: 272.78 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.14 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 23:02:46,520] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.72 | bwd_microstep: 271.26 | bwd_inner_microstep: 271.24 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 23:02:46,996] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.88 | bwd_microstep: 271.51 | bwd_inner_microstep: 271.49 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 23:02:47,473] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.14 | bwd_microstep: 271.33 | bwd_inner_microstep: 271.31 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 829 +[2025-05-01 23:02:47,718] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.24 | bwd_microstep: 129.87 | bwd_inner_microstep: 129.71 | bwd_allreduce_microstep: 0.08 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 23:02:48,195] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.24 | bwd_microstep: 271.28 | bwd_inner_microstep: 271.27 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 23:02:48,675] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.00 | bwd_microstep: 271.30 | bwd_inner_microstep: 271.28 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 23:02:49,258] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.70 | optimizer_step: 17.66 +[2025-05-01 23:02:49,259] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.30 | bwd_microstep: 351.65 | bwd_inner_microstep: 271.80 | bwd_allreduce_microstep: 79.80 | step_microstep: 26.16 +[2025-05-01 23:02:49,260] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2432.56 | bwd: 3599.85 | bwd_inner: 3518.79 | bwd_allreduce: 80.31 | step: 27.25 + 3%|▎ | 295/8720 [47:23<16:02:01, 6.85s/it] {'loss': 1.2101, 'grad_norm': 5.801593780517578, 'learning_rate': 9.999624398917946e-06, 'epoch': 0.34} + 3%|▎ | 295/8720 [47:23<16:02:01, 6.85s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1917 +[2025-05-01 23:02:49,750] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.48 | bwd_microstep: 275.86 | bwd_inner_microstep: 275.84 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 358 +[2025-05-01 23:02:49,998] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 97.48 | bwd_microstep: 133.36 | bwd_inner_microstep: 133.04 | bwd_allreduce_microstep: 0.14 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-01 23:02:50,479] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.25 | bwd_microstep: 273.94 | bwd_inner_microstep: 273.92 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-01 23:02:50,960] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.87 | bwd_microstep: 273.85 | bwd_inner_microstep: 273.84 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-01 23:02:51,444] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.77 | bwd_microstep: 273.03 | bwd_inner_microstep: 273.02 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-01 23:02:51,926] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.12 | bwd_microstep: 273.23 | bwd_inner_microstep: 273.21 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-01 23:02:52,407] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.26 | bwd_microstep: 272.96 | bwd_inner_microstep: 272.94 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 332 +[2025-05-01 23:02:52,634] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 81.06 | bwd_microstep: 129.56 | bwd_inner_microstep: 129.22 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 23:02:53,113] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.49 | bwd_microstep: 272.45 | bwd_inner_microstep: 272.43 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-01 23:02:53,595] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.77 | bwd_microstep: 273.00 | bwd_inner_microstep: 272.98 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 23:02:54,073] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.61 | bwd_microstep: 271.61 | bwd_inner_microstep: 271.59 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 834 +[2025-05-01 23:02:54,311] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.09 | bwd_microstep: 126.20 | bwd_inner_microstep: 126.19 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 23:02:54,788] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.08 | bwd_microstep: 271.38 | bwd_inner_microstep: 271.36 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 23:02:55,265] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.87 | bwd_microstep: 271.36 | bwd_inner_microstep: 271.35 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 23:02:55,742] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.44 | bwd_microstep: 271.27 | bwd_inner_microstep: 271.25 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.15 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 827 +[2025-05-01 23:02:56,097] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.20 | optimizer_step: 16.27 +[2025-05-01 23:02:56,097] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 106.81 | bwd_microstep: 205.95 | bwd_inner_microstep: 130.20 | bwd_allreduce_microstep: 75.64 | step_microstep: 23.85 +[2025-05-01 23:02:56,098] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2646.09 | bwd: 3869.08 | bwd_inner: 3792.54 | bwd_allreduce: 75.97 | step: 24.98 + 3%|▎ | 296/8720 [47:29<16:01:20, 6.85s/it] {'loss': 1.2203, 'grad_norm': 5.25362491607666, 'learning_rate': 9.999601290618555e-06, 'epoch': 0.34} + 3%|▎ | 296/8720 [47:29<16:01:20, 6.85s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1903 +[2025-05-01 23:02:56,587] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.31 | bwd_microstep: 275.60 | bwd_inner_microstep: 275.58 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1892 +[2025-05-01 23:02:57,069] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.17 | bwd_microstep: 275.27 | bwd_inner_microstep: 275.25 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1890 +[2025-05-01 23:02:57,548] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.99 | bwd_microstep: 274.80 | bwd_inner_microstep: 274.79 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-01 23:02:58,028] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.12 | bwd_microstep: 274.24 | bwd_inner_microstep: 274.22 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-01 23:02:58,510] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.89 | bwd_microstep: 273.66 | bwd_inner_microstep: 273.65 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1887 +[2025-05-01 23:02:58,994] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.60 | bwd_microstep: 274.92 | bwd_inner_microstep: 274.90 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-01 23:02:59,474] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.00 | bwd_microstep: 273.58 | bwd_inner_microstep: 273.56 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.14 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 23:02:59,953] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.85 | bwd_microstep: 271.62 | bwd_inner_microstep: 271.60 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 330 +[2025-05-01 23:03:00,177] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 88.88 | bwd_microstep: 118.12 | bwd_inner_microstep: 117.96 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:03:00,657] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.03 | bwd_microstep: 272.92 | bwd_inner_microstep: 272.90 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 23:03:01,138] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.02 | bwd_microstep: 272.87 | bwd_inner_microstep: 272.85 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 23:03:01,619] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.95 | bwd_microstep: 272.73 | bwd_inner_microstep: 272.71 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.15 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 23:03:02,099] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.96 | bwd_microstep: 271.38 | bwd_inner_microstep: 271.37 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-01 23:03:02,580] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.43 | bwd_microstep: 271.35 | bwd_inner_microstep: 271.33 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1850 +[2025-05-01 23:03:03,058] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.88 | bwd_microstep: 271.04 | bwd_inner_microstep: 271.03 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 345 +[2025-05-01 23:03:03,386] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.04 | optimizer_gradients: 2.23 | optimizer_step: 16.14 +[2025-05-01 23:03:03,387] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 80.10 | bwd_microstep: 210.09 | bwd_inner_microstep: 132.23 | bwd_allreduce_microstep: 77.69 | step_microstep: 23.49 +[2025-05-01 23:03:03,388] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2817.83 | bwd: 4154.22 | bwd_inner: 4076.03 | bwd_allreduce: 77.80 | step: 24.70 + 3%|▎ | 297/8720 [47:37<16:19:47, 6.98s/it] {'loss': 1.3706, 'grad_norm': 5.319169044494629, 'learning_rate': 9.999577492556391e-06, 'epoch': 0.34} + 3%|▎ | 297/8720 [47:37<16:19:47, 6.98s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1910 +[2025-05-01 23:03:03,874] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.85 | bwd_microstep: 276.01 | bwd_inner_microstep: 275.99 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1911 +[2025-05-01 23:03:04,358] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.75 | bwd_microstep: 277.23 | bwd_inner_microstep: 277.21 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1897 +[2025-05-01 23:03:04,839] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.39 | bwd_microstep: 275.60 | bwd_inner_microstep: 275.59 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1895 +[2025-05-01 23:03:05,321] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.22 | bwd_microstep: 276.11 | bwd_inner_microstep: 276.09 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1887 +[2025-05-01 23:03:05,802] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.17 | bwd_microstep: 275.06 | bwd_inner_microstep: 275.04 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-01 23:03:06,283] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.35 | bwd_microstep: 274.55 | bwd_inner_microstep: 274.54 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 856 +[2025-05-01 23:03:06,526] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.44 | bwd_microstep: 133.42 | bwd_inner_microstep: 133.26 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-01 23:03:07,004] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.40 | bwd_microstep: 274.38 | bwd_inner_microstep: 274.36 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-01 23:03:07,481] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.98 | bwd_microstep: 273.18 | bwd_inner_microstep: 273.16 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 23:03:07,959] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.16 | bwd_microstep: 272.77 | bwd_inner_microstep: 272.75 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:03:08,437] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.40 | bwd_microstep: 272.82 | bwd_inner_microstep: 272.80 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 327 +[2025-05-01 23:03:08,654] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 82.46 | bwd_microstep: 120.55 | bwd_inner_microstep: 120.41 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.10 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 838 +[2025-05-01 23:03:08,888] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 91.68 | bwd_microstep: 126.62 | bwd_inner_microstep: 126.52 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 23:03:09,366] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.40 | bwd_microstep: 272.69 | bwd_inner_microstep: 272.67 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 23:03:09,841] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.10 | bwd_microstep: 271.11 | bwd_inner_microstep: 271.09 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2053 +[2025-05-01 23:03:10,467] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.21 | optimizer_step: 16.18 +[2025-05-01 23:03:10,468] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 203.24 | bwd_microstep: 379.72 | bwd_inner_microstep: 302.36 | bwd_allreduce_microstep: 77.30 | step_microstep: 24.15 +[2025-05-01 23:03:10,469] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2744.70 | bwd: 4051.86 | bwd_inner: 3973.91 | bwd_allreduce: 77.54 | step: 25.18 + 3%|▎ | 298/8720 [47:44<16:24:02, 7.01s/it] {'loss': 1.4019, 'grad_norm': 3.1769375801086426, 'learning_rate': 9.999553004734741e-06, 'epoch': 0.34} + 3%|▎ | 298/8720 [47:44<16:24:02, 7.01s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 434 +[2025-05-01 23:03:10,703] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 84.45 | bwd_microstep: 127.69 | bwd_inner_microstep: 127.43 | bwd_allreduce_microstep: 0.10 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-01 23:03:11,185] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.75 | bwd_microstep: 273.77 | bwd_inner_microstep: 273.76 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1363 +[2025-05-01 23:03:11,551] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 142.75 | bwd_microstep: 207.41 | bwd_inner_microstep: 207.39 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-01 23:03:12,028] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.00 | bwd_microstep: 273.22 | bwd_inner_microstep: 273.20 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-01 23:03:12,505] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.53 | bwd_microstep: 272.88 | bwd_inner_microstep: 272.86 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-01 23:03:12,982] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.61 | bwd_microstep: 273.32 | bwd_inner_microstep: 273.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-01 23:03:13,459] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.88 | bwd_microstep: 272.90 | bwd_inner_microstep: 272.88 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:03:13,937] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.30 | bwd_microstep: 272.86 | bwd_inner_microstep: 272.84 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.17 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 23:03:14,415] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.80 | bwd_microstep: 271.47 | bwd_inner_microstep: 271.45 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 23:03:14,894] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.41 | bwd_microstep: 271.54 | bwd_inner_microstep: 271.52 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 23:03:15,374] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.13 | bwd_microstep: 271.52 | bwd_inner_microstep: 271.51 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 23:03:15,855] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.97 | bwd_microstep: 271.39 | bwd_inner_microstep: 271.37 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 316 +[2025-05-01 23:03:16,088] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 96.90 | bwd_microstep: 116.66 | bwd_inner_microstep: 116.48 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.11 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 451 +[2025-05-01 23:03:16,325] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.46 | bwd_microstep: 122.84 | bwd_inner_microstep: 122.63 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 23:03:16,807] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.71 | bwd_microstep: 272.70 | bwd_inner_microstep: 272.68 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1849 +[2025-05-01 23:03:17,387] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.16 | optimizer_step: 16.19 +[2025-05-01 23:03:17,387] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.66 | bwd_microstep: 348.47 | bwd_inner_microstep: 271.63 | bwd_allreduce_microstep: 76.78 | step_microstep: 24.07 +[2025-05-01 23:03:17,389] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2684.94 | bwd: 3920.70 | bwd_inner: 3843.10 | bwd_allreduce: 77.09 | step: 25.14 + 3%|▎ | 299/8720 [47:51<16:20:05, 6.98s/it] {'loss': 1.4185, 'grad_norm': 5.306668281555176, 'learning_rate': 9.99952782715698e-06, 'epoch': 0.34} + 3%|▎ | 299/8720 [47:51<16:20:05, 6.98s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-01 23:03:17,876] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.13 | bwd_microstep: 274.11 | bwd_inner_microstep: 274.09 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-01 23:03:18,359] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.65 | bwd_microstep: 274.89 | bwd_inner_microstep: 274.87 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-01 23:03:18,839] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.84 | bwd_microstep: 273.73 | bwd_inner_microstep: 273.71 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-01 23:03:19,318] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.27 | bwd_microstep: 273.72 | bwd_inner_microstep: 273.70 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 23:03:19,796] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.88 | bwd_microstep: 273.15 | bwd_inner_microstep: 273.13 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 23:03:20,274] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.88 | bwd_microstep: 273.24 | bwd_inner_microstep: 273.22 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-01 23:03:20,753] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.34 | bwd_microstep: 273.69 | bwd_inner_microstep: 273.67 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 23:03:21,232] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.06 | bwd_microstep: 273.38 | bwd_inner_microstep: 273.37 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 23:03:21,710] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.96 | bwd_microstep: 273.38 | bwd_inner_microstep: 273.36 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 333 +[2025-05-01 23:03:21,914] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 71.49 | bwd_microstep: 118.88 | bwd_inner_microstep: 118.60 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 23:03:22,392] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.17 | bwd_microstep: 273.27 | bwd_inner_microstep: 273.26 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 23:03:22,869] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.31 | bwd_microstep: 272.09 | bwd_inner_microstep: 272.08 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 318 +[2025-05-01 23:03:23,080] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 82.11 | bwd_microstep: 115.35 | bwd_inner_microstep: 115.17 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.13 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-01 23:03:23,554] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.70 | bwd_microstep: 271.76 | bwd_inner_microstep: 271.74 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 23:03:24,032] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.26 | bwd_microstep: 271.85 | bwd_inner_microstep: 271.83 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2084 +[2025-05-01 23:03:24,648] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.14 | optimizer_step: 17.10 +[2025-05-01 23:03:24,648] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 205.19 | bwd_microstep: 371.40 | bwd_inner_microstep: 305.19 | bwd_allreduce_microstep: 66.17 | step_microstep: 24.34 +[2025-05-01 23:03:24,649] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2822.97 | bwd: 4157.92 | bwd_inner: 4091.08 | bwd_allreduce: 66.40 | step: 25.10 + 3%|▎ | 300/8720 [47:58<16:31:35, 7.07s/it] {'loss': 1.4273, 'grad_norm': 4.152856826782227, 'learning_rate': 9.999501959826584e-06, 'epoch': 0.34} + 3%|▎ | 300/8720 [47:58<16:31:35, 7.07s/it][INFO|trainer.py:3503] 2025-05-01 23:03:27,183 >> Saving model checkpoint to work_dirs/internvl_chat_v2_5/ak/checkpoint-300 +[INFO|configuration_utils.py:472] 2025-05-01 23:03:27,186 >> Configuration saved in work_dirs/internvl_chat_v2_5/ak/checkpoint-300/config.json +[INFO|configuration_utils.py:807] 2025-05-01 23:03:27,186 >> Configuration saved in work_dirs/internvl_chat_v2_5/ak/checkpoint-300/generation_config.json +[INFO|modeling_utils.py:2755] 2025-05-01 23:03:32,541 >> Model weights saved in work_dirs/internvl_chat_v2_5/ak/checkpoint-300/model.safetensors +[INFO|tokenization_utils_base.py:2702] 2025-05-01 23:03:32,543 >> tokenizer config file saved in work_dirs/internvl_chat_v2_5/ak/checkpoint-300/tokenizer_config.json +[INFO|tokenization_utils_base.py:2711] 2025-05-01 23:03:32,543 >> Special tokens file saved in work_dirs/internvl_chat_v2_5/ak/checkpoint-300/special_tokens_map.json +[INFO|tokenization_utils_base.py:2762] 2025-05-01 23:03:32,543 >> added tokens file saved in work_dirs/internvl_chat_v2_5/ak/checkpoint-300/added_tokens.json +[2025-05-01 23:03:32,720] [INFO] [logging.py:96:log_dist] [Rank 0] [Torch] Checkpoint global_step300 is about to be saved! +[2025-05-01 23:03:32,737] [INFO] [logging.py:96:log_dist] [Rank 0] Saving model checkpoint: work_dirs/internvl_chat_v2_5/ak/checkpoint-300/global_step300/mp_rank_00_model_states.pt +[2025-05-01 23:03:32,737] [INFO] [torch_checkpoint_engine.py:21:save] [Torch] Saving work_dirs/internvl_chat_v2_5/ak/checkpoint-300/global_step300/mp_rank_00_model_states.pt... +[2025-05-01 23:03:37,293] [INFO] [torch_checkpoint_engine.py:23:save] [Torch] Saved work_dirs/internvl_chat_v2_5/ak/checkpoint-300/global_step300/mp_rank_00_model_states.pt. +[2025-05-01 23:03:37,294] [INFO] [torch_checkpoint_engine.py:21:save] [Torch] Saving work_dirs/internvl_chat_v2_5/ak/checkpoint-300/global_step300/bf16_zero_pp_rank_0_mp_rank_00_optim_states.pt... +[2025-05-01 23:03:37,500] [INFO] [torch_checkpoint_engine.py:23:save] [Torch] Saved work_dirs/internvl_chat_v2_5/ak/checkpoint-300/global_step300/bf16_zero_pp_rank_0_mp_rank_00_optim_states.pt. +[2025-05-01 23:03:37,500] [INFO] [engine.py:3536:_save_zero_checkpoint] zero checkpoint saved work_dirs/internvl_chat_v2_5/ak/checkpoint-300/global_step300/bf16_zero_pp_rank_0_mp_rank_00_optim_states.pt +[2025-05-01 23:03:37,500] [INFO] [torch_checkpoint_engine.py:33:commit] [Torch] Checkpoint global_step300 is ready now! +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1911 +[2025-05-01 23:03:37,981] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.26 | bwd_microstep: 274.12 | bwd_inner_microstep: 274.10 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-01 23:03:38,463] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.63 | bwd_microstep: 271.69 | bwd_inner_microstep: 271.67 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-01 23:03:38,937] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.92 | bwd_microstep: 271.37 | bwd_inner_microstep: 271.35 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 846 +[2025-05-01 23:03:39,174] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 92.53 | bwd_microstep: 131.51 | bwd_inner_microstep: 131.43 | bwd_allreduce_microstep: 0.04 | step_microstep: 0.09 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 334 +[2025-05-01 23:03:39,382] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 75.69 | bwd_microstep: 118.15 | bwd_inner_microstep: 117.89 | bwd_allreduce_microstep: 0.10 | step_microstep: 0.09 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 334 +[2025-05-01 23:03:39,591] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 77.32 | bwd_microstep: 117.01 | bwd_inner_microstep: 116.87 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-01 23:03:40,065] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.25 | bwd_microstep: 271.95 | bwd_inner_microstep: 271.93 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 23:03:40,541] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.38 | bwd_microstep: 271.63 | bwd_inner_microstep: 271.61 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 23:03:41,017] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.89 | bwd_microstep: 271.67 | bwd_inner_microstep: 271.65 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 834 +[2025-05-01 23:03:41,250] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 91.81 | bwd_microstep: 125.53 | bwd_inner_microstep: 125.25 | bwd_allreduce_microstep: 0.14 | step_microstep: 0.19 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 323 +[2025-05-01 23:03:41,458] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 70.42 | bwd_microstep: 124.34 | bwd_inner_microstep: 124.04 | bwd_allreduce_microstep: 0.14 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 23:03:41,930] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.20 | bwd_microstep: 269.99 | bwd_inner_microstep: 269.97 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 23:03:42,404] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.08 | bwd_microstep: 270.38 | bwd_inner_microstep: 270.37 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 23:03:42,879] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.92 | bwd_microstep: 270.57 | bwd_inner_microstep: 270.55 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 23:03:43,352] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.81 | bwd_microstep: 270.38 | bwd_inner_microstep: 270.37 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.21 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-01 23:03:43,918] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.39 | optimizer_step: 16.68 +[2025-05-01 23:03:43,918] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.31 | bwd_microstep: 338.04 | bwd_inner_microstep: 270.72 | bwd_allreduce_microstep: 67.27 | step_microstep: 24.29 +[2025-05-01 23:03:43,920] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2469.15 | bwd: 3668.42 | bwd_inner: 3599.94 | bwd_allreduce: 67.79 | step: 25.76 + 3%|▎ | 301/8720 [48:17<25:05:13, 10.73s/it] {'loss': 1.4094, 'grad_norm': 5.100588321685791, 'learning_rate': 9.99947540274712e-06, 'epoch': 0.35} + 3%|▎ | 301/8720 [48:17<25:05:13, 10.73s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2141 +[2025-05-01 23:03:44,457] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 204.25 | bwd_microstep: 312.15 | bwd_inner_microstep: 312.13 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1904 +[2025-05-01 23:03:44,934] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.39 | bwd_microstep: 274.11 | bwd_inner_microstep: 274.10 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1896 +[2025-05-01 23:03:45,410] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.99 | bwd_microstep: 273.32 | bwd_inner_microstep: 273.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1894 +[2025-05-01 23:03:45,888] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.81 | bwd_microstep: 273.27 | bwd_inner_microstep: 273.25 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1899 +[2025-05-01 23:03:46,367] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.09 | bwd_microstep: 273.98 | bwd_inner_microstep: 273.96 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1883 +[2025-05-01 23:03:46,844] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.04 | bwd_microstep: 272.98 | bwd_inner_microstep: 272.96 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-01 23:03:47,326] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.60 | bwd_microstep: 272.07 | bwd_inner_microstep: 272.05 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 23:03:47,804] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.15 | bwd_microstep: 271.06 | bwd_inner_microstep: 271.04 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.17 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 23:03:48,282] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.13 | bwd_microstep: 270.96 | bwd_inner_microstep: 270.94 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-01 23:03:48,760] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.09 | bwd_microstep: 271.41 | bwd_inner_microstep: 271.39 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 23:03:49,239] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.73 | bwd_microstep: 270.86 | bwd_inner_microstep: 270.85 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 23:03:49,718] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.08 | bwd_microstep: 271.14 | bwd_inner_microstep: 271.12 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-01 23:03:50,194] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.95 | bwd_microstep: 269.92 | bwd_inner_microstep: 269.90 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 23:03:50,669] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.10 | bwd_microstep: 269.70 | bwd_inner_microstep: 269.68 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 23:03:51,142] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 185.86 | bwd_microstep: 269.62 | bwd_inner_microstep: 269.60 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 375 +[2025-05-01 23:03:51,493] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.39 | optimizer_step: 16.58 +[2025-05-01 23:03:51,493] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 86.61 | bwd_microstep: 223.47 | bwd_inner_microstep: 146.42 | bwd_allreduce_microstep: 76.89 | step_microstep: 24.72 +[2025-05-01 23:03:51,495] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2912.50 | bwd: 4340.03 | bwd_inner: 4262.76 | bwd_allreduce: 76.94 | step: 26.04 + 3%|▎ | 302/8720 [48:25<22:52:26, 9.78s/it] {'loss': 1.2665, 'grad_norm': 5.085047245025635, 'learning_rate': 9.999448155922253e-06, 'epoch': 0.35} + 3%|▎ | 302/8720 [48:25<22:52:26, 9.78s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1893 +[2025-05-01 23:03:51,982] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.94 | bwd_microstep: 273.79 | bwd_inner_microstep: 273.77 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1892 +[2025-05-01 23:03:52,463] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.68 | bwd_microstep: 274.28 | bwd_inner_microstep: 274.27 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-01 23:03:52,943] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.08 | bwd_microstep: 273.81 | bwd_inner_microstep: 273.79 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-01 23:03:53,422] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.74 | bwd_microstep: 272.54 | bwd_inner_microstep: 272.53 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-01 23:03:53,901] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.73 | bwd_microstep: 272.91 | bwd_inner_microstep: 272.89 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-01 23:03:54,386] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.28 | bwd_microstep: 272.64 | bwd_inner_microstep: 272.62 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 329 +[2025-05-01 23:03:54,603] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 80.40 | bwd_microstep: 119.74 | bwd_inner_microstep: 119.41 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.18 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 840 +[2025-05-01 23:03:54,845] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 99.23 | bwd_microstep: 126.01 | bwd_inner_microstep: 125.85 | bwd_allreduce_microstep: 0.09 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 23:03:55,323] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.25 | bwd_microstep: 271.81 | bwd_inner_microstep: 271.79 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 23:03:55,801] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.43 | bwd_microstep: 271.77 | bwd_inner_microstep: 271.76 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 23:03:56,281] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.54 | bwd_microstep: 271.67 | bwd_inner_microstep: 271.65 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 23:03:56,759] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.73 | bwd_microstep: 272.17 | bwd_inner_microstep: 272.16 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 23:03:57,239] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.72 | bwd_microstep: 271.56 | bwd_inner_microstep: 271.55 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 23:03:57,719] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.22 | bwd_microstep: 270.86 | bwd_inner_microstep: 270.84 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1940 +[2025-05-01 23:03:58,219] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.91 | bwd_microstep: 287.37 | bwd_inner_microstep: 287.35 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1893 +[2025-05-01 23:03:58,800] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.41 | optimizer_step: 16.79 +[2025-05-01 23:03:58,801] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.95 | bwd_microstep: 352.26 | bwd_inner_microstep: 274.57 | bwd_allreduce_microstep: 77.64 | step_microstep: 24.76 +[2025-05-01 23:03:58,802] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2829.45 | bwd: 4155.26 | bwd_inner: 4076.86 | bwd_allreduce: 77.91 | step: 25.84 + 3%|▎ | 303/8720 [48:32<21:08:04, 9.04s/it] {'loss': 1.5525, 'grad_norm': 4.557758808135986, 'learning_rate': 9.999420219355744e-06, 'epoch': 0.35} + 3%|▎ | 303/8720 [48:32<21:08:04, 9.04s/it]dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 1092 +[2025-05-01 23:03:59,088] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 106.03 | bwd_microstep: 159.93 | bwd_inner_microstep: 159.74 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.09 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1443 +[2025-05-01 23:03:59,461] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 142.85 | bwd_microstep: 214.71 | bwd_inner_microstep: 214.58 | bwd_allreduce_microstep: 0.09 | step_microstep: 0.10 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1358 +[2025-05-01 23:03:59,824] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.84 | bwd_microstep: 205.81 | bwd_inner_microstep: 205.77 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-01 23:04:00,302] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.99 | bwd_microstep: 272.37 | bwd_inner_microstep: 272.35 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-01 23:04:00,780] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.54 | bwd_microstep: 272.41 | bwd_inner_microstep: 272.40 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-01 23:04:01,258] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.32 | bwd_microstep: 272.46 | bwd_inner_microstep: 272.45 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-01 23:04:01,739] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.93 | bwd_microstep: 273.07 | bwd_inner_microstep: 273.05 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-01 23:04:02,220] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.65 | bwd_microstep: 272.75 | bwd_inner_microstep: 272.73 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 23:04:02,701] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.74 | bwd_microstep: 271.59 | bwd_inner_microstep: 271.57 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 321 +[2025-05-01 23:04:02,930] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 84.83 | bwd_microstep: 126.61 | bwd_inner_microstep: 126.35 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-01 23:04:03,409] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.87 | bwd_microstep: 272.78 | bwd_inner_microstep: 272.77 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 23:04:03,887] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.94 | bwd_microstep: 271.81 | bwd_inner_microstep: 271.79 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-01 23:04:04,367] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.94 | bwd_microstep: 272.27 | bwd_inner_microstep: 272.25 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 23:04:04,851] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.51 | bwd_microstep: 271.60 | bwd_inner_microstep: 271.58 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 831 +[2025-05-01 23:04:05,094] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 97.09 | bwd_microstep: 129.55 | bwd_inner_microstep: 129.44 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.13 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1911 +[2025-05-01 23:04:05,681] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.07 | optimizer_gradients: 2.43 | optimizer_step: 17.60 +[2025-05-01 23:04:05,681] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.77 | bwd_microstep: 354.26 | bwd_inner_microstep: 276.72 | bwd_allreduce_microstep: 77.48 | step_microstep: 25.97 +[2025-05-01 23:04:05,683] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2643.47 | bwd: 3914.09 | bwd_inner: 3835.67 | bwd_allreduce: 77.86 | step: 27.25 + 3%|▎ | 304/8720 [48:39<19:37:06, 8.39s/it] {'loss': 1.3916, 'grad_norm': 4.01069450378418, 'learning_rate': 9.999391593051443e-06, 'epoch': 0.35} + 3%|▎ | 304/8720 [48:39<19:37:06, 8.39s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1899 +[2025-05-01 23:04:06,169] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.98 | bwd_microstep: 274.17 | bwd_inner_microstep: 274.15 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.13 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 864 +[2025-05-01 23:04:06,415] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.81 | bwd_microstep: 133.35 | bwd_inner_microstep: 133.06 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-01 23:04:06,894] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.64 | bwd_microstep: 272.47 | bwd_inner_microstep: 272.45 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1116 +[2025-05-01 23:04:07,186] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 115.53 | bwd_microstep: 162.42 | bwd_inner_microstep: 162.20 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-01 23:04:07,664] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.75 | bwd_microstep: 273.01 | bwd_inner_microstep: 272.85 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-01 23:04:08,141] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.44 | bwd_microstep: 272.27 | bwd_inner_microstep: 272.25 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-01 23:04:08,617] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.63 | bwd_microstep: 272.65 | bwd_inner_microstep: 272.64 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 837 +[2025-05-01 23:04:08,855] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.21 | bwd_microstep: 126.09 | bwd_inner_microstep: 125.82 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.22 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:04:09,335] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.89 | bwd_microstep: 272.10 | bwd_inner_microstep: 272.09 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-01 23:04:09,816] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.23 | bwd_microstep: 273.05 | bwd_inner_microstep: 273.03 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 23:04:10,297] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.82 | bwd_microstep: 272.36 | bwd_inner_microstep: 272.34 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 23:04:10,775] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.79 | bwd_microstep: 271.68 | bwd_inner_microstep: 271.66 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1342 +[2025-05-01 23:04:11,138] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.00 | bwd_microstep: 204.06 | bwd_inner_microstep: 203.96 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 23:04:11,614] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.88 | bwd_microstep: 270.94 | bwd_inner_microstep: 270.92 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 23:04:12,088] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.23 | bwd_microstep: 270.77 | bwd_inner_microstep: 270.75 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 23:04:12,656] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.26 | optimizer_step: 21.06 +[2025-05-01 23:04:12,657] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.71 | bwd_microstep: 337.51 | bwd_inner_microstep: 271.11 | bwd_allreduce_microstep: 66.36 | step_microstep: 28.38 +[2025-05-01 23:04:12,658] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2708.21 | bwd: 3959.04 | bwd_inner: 3891.37 | bwd_allreduce: 66.91 | step: 29.84 + 3%|▎ | 305/8720 [48:46<18:37:17, 7.97s/it] {'loss': 1.8322, 'grad_norm': 5.0215654373168945, 'learning_rate': 9.999362277013303e-06, 'epoch': 0.35} + 3%|▎ | 305/8720 [48:46<18:37:17, 7.97s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2141 +[2025-05-01 23:04:13,195] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 204.14 | bwd_microstep: 313.11 | bwd_inner_microstep: 313.09 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1982 +[2025-05-01 23:04:13,699] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 196.60 | bwd_microstep: 291.19 | bwd_inner_microstep: 291.17 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1914 +[2025-05-01 23:04:14,180] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.64 | bwd_microstep: 275.68 | bwd_inner_microstep: 275.66 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 867 +[2025-05-01 23:04:14,422] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.73 | bwd_microstep: 133.95 | bwd_inner_microstep: 133.82 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-01 23:04:14,899] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.29 | bwd_microstep: 273.53 | bwd_inner_microstep: 273.51 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1368 +[2025-05-01 23:04:15,268] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.52 | bwd_microstep: 206.67 | bwd_inner_microstep: 206.54 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1370 +[2025-05-01 23:04:15,632] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.60 | bwd_microstep: 206.65 | bwd_inner_microstep: 206.55 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-01 23:04:16,112] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.83 | bwd_microstep: 274.49 | bwd_inner_microstep: 274.47 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-01 23:04:16,590] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.63 | bwd_microstep: 274.19 | bwd_inner_microstep: 274.17 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1892 +[2025-05-01 23:04:17,070] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.16 | bwd_microstep: 274.44 | bwd_inner_microstep: 274.42 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-01 23:04:17,547] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.25 | bwd_microstep: 272.82 | bwd_inner_microstep: 272.80 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 23:04:18,022] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.57 | bwd_microstep: 271.92 | bwd_inner_microstep: 271.91 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-01 23:04:18,498] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.66 | bwd_microstep: 272.36 | bwd_inner_microstep: 272.34 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 324 +[2025-05-01 23:04:18,712] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 81.03 | bwd_microstep: 118.30 | bwd_inner_microstep: 118.13 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:04:19,188] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.10 | bwd_microstep: 272.59 | bwd_inner_microstep: 272.57 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-01 23:04:19,759] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.36 | optimizer_step: 21.59 +[2025-05-01 23:04:19,760] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.25 | bwd_microstep: 339.90 | bwd_inner_microstep: 273.42 | bwd_allreduce_microstep: 66.43 | step_microstep: 28.71 +[2025-05-01 23:04:19,761] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2741.72 | bwd: 4071.82 | bwd_inner: 4004.63 | bwd_allreduce: 66.77 | step: 29.57 + 4%|▎ | 306/8720 [48:53<18:00:49, 7.71s/it] {'loss': 1.4109, 'grad_norm': 2.286613941192627, 'learning_rate': 9.999332271245366e-06, 'epoch': 0.35} + 4%|▎ | 306/8720 [48:53<18:00:49, 7.71s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1994 +[2025-05-01 23:04:20,271] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 196.93 | bwd_microstep: 293.31 | bwd_inner_microstep: 293.29 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 458 +[2025-05-01 23:04:20,484] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 75.66 | bwd_microstep: 123.99 | bwd_inner_microstep: 123.68 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.22 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1894 +[2025-05-01 23:04:20,964] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.36 | bwd_microstep: 274.87 | bwd_inner_microstep: 274.85 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1886 +[2025-05-01 23:04:21,444] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.66 | bwd_microstep: 274.34 | bwd_inner_microstep: 274.32 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1886 +[2025-05-01 23:04:21,928] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.23 | bwd_microstep: 274.44 | bwd_inner_microstep: 274.43 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-01 23:04:22,410] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.88 | bwd_microstep: 272.90 | bwd_inner_microstep: 272.89 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-01 23:04:22,889] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.14 | bwd_microstep: 272.97 | bwd_inner_microstep: 272.96 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-01 23:04:23,372] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.85 | bwd_microstep: 273.45 | bwd_inner_microstep: 273.44 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-01 23:04:23,856] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.85 | bwd_microstep: 274.12 | bwd_inner_microstep: 274.11 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-01 23:04:24,338] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.11 | bwd_microstep: 272.36 | bwd_inner_microstep: 272.34 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.13 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-01 23:04:24,817] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.10 | bwd_microstep: 272.95 | bwd_inner_microstep: 272.94 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-01 23:04:25,298] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.69 | bwd_microstep: 272.72 | bwd_inner_microstep: 272.70 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-01 23:04:25,781] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.29 | bwd_microstep: 272.51 | bwd_inner_microstep: 272.49 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 23:04:26,261] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.25 | bwd_microstep: 272.55 | bwd_inner_microstep: 272.54 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 317 +[2025-05-01 23:04:26,499] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.23 | bwd_microstep: 122.61 | bwd_inner_microstep: 122.44 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 23:04:27,100] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.37 | optimizer_step: 26.66 +[2025-05-01 23:04:27,100] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.11 | bwd_microstep: 361.66 | bwd_inner_microstep: 271.44 | bwd_allreduce_microstep: 90.17 | step_microstep: 34.48 +[2025-05-01 23:04:27,102] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2818.94 | bwd: 4181.84 | bwd_inner: 4090.94 | bwd_allreduce: 90.44 | step: 35.85 + 4%|▎ | 307/8720 [49:00<17:45:21, 7.60s/it] {'loss': 1.6049, 'grad_norm': 4.000810146331787, 'learning_rate': 9.999301575751773e-06, 'epoch': 0.35} + 4%|▎ | 307/8720 [49:00<17:45:21, 7.60s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-01 23:04:27,587] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.99 | bwd_microstep: 273.49 | bwd_inner_microstep: 273.47 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1887 +[2025-05-01 23:04:28,069] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.47 | bwd_microstep: 274.66 | bwd_inner_microstep: 274.65 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1370 +[2025-05-01 23:04:28,436] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 142.32 | bwd_microstep: 207.63 | bwd_inner_microstep: 207.53 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-01 23:04:28,916] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.13 | bwd_microstep: 272.86 | bwd_inner_microstep: 272.85 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-01 23:04:29,397] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.01 | bwd_microstep: 273.23 | bwd_inner_microstep: 273.21 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-01 23:04:29,877] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.10 | bwd_microstep: 272.68 | bwd_inner_microstep: 272.66 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-01 23:04:30,356] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.50 | bwd_microstep: 273.24 | bwd_inner_microstep: 273.22 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-01 23:04:30,837] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.39 | bwd_microstep: 272.80 | bwd_inner_microstep: 272.79 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.14 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-01 23:04:31,317] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.25 | bwd_microstep: 272.71 | bwd_inner_microstep: 272.69 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1353 +[2025-05-01 23:04:31,680] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.25 | bwd_microstep: 206.30 | bwd_inner_microstep: 206.29 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.12 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 835 +[2025-05-01 23:04:31,918] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.41 | bwd_microstep: 126.14 | bwd_inner_microstep: 126.02 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 23:04:32,396] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.91 | bwd_microstep: 272.11 | bwd_inner_microstep: 272.09 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.08 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 322 +[2025-05-01 23:04:32,631] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 90.82 | bwd_microstep: 126.15 | bwd_inner_microstep: 125.89 | bwd_allreduce_microstep: 0.09 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 23:04:33,111] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.28 | bwd_microstep: 272.39 | bwd_inner_microstep: 272.37 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1085 +[2025-05-01 23:04:33,405] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 117.69 | bwd_microstep: 159.52 | bwd_inner_microstep: 159.39 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1850 +[2025-05-01 23:04:33,981] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.04 | optimizer_gradients: 2.31 | optimizer_step: 16.44 +[2025-05-01 23:04:33,981] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.82 | bwd_microstep: 347.53 | bwd_inner_microstep: 271.49 | bwd_allreduce_microstep: 75.98 | step_microstep: 23.52 +[2025-05-01 23:04:33,982] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2660.99 | bwd: 3903.50 | bwd_inner: 3826.71 | bwd_allreduce: 76.30 | step: 24.82 + 4%|▎ | 308/8720 [49:07<17:14:59, 7.38s/it] {'loss': 1.5238, 'grad_norm': 4.532593727111816, 'learning_rate': 9.999270190536759e-06, 'epoch': 0.35} + 4%|▎ | 308/8720 [49:07<17:14:59, 7.38s/it]dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1448 +[2025-05-01 23:04:34,363] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 146.72 | bwd_microstep: 215.20 | bwd_inner_microstep: 214.98 | bwd_allreduce_microstep: 0.14 | step_microstep: 0.09 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1389 +[2025-05-01 23:04:34,729] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.64 | bwd_microstep: 208.62 | bwd_inner_microstep: 208.53 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.20 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 350 +[2025-05-01 23:04:34,940] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 77.62 | bwd_microstep: 118.63 | bwd_inner_microstep: 118.51 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 859 +[2025-05-01 23:04:35,181] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 92.87 | bwd_microstep: 134.07 | bwd_inner_microstep: 133.83 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:04:35,656] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.63 | bwd_microstep: 272.35 | bwd_inner_microstep: 272.33 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 23:04:36,131] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.00 | bwd_microstep: 272.21 | bwd_inner_microstep: 272.19 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 23:04:36,608] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.90 | bwd_microstep: 272.45 | bwd_inner_microstep: 272.43 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-01 23:04:37,085] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.20 | bwd_microstep: 273.02 | bwd_inner_microstep: 273.00 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 23:04:37,565] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.38 | bwd_microstep: 272.75 | bwd_inner_microstep: 272.74 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 23:04:38,042] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.55 | bwd_microstep: 272.64 | bwd_inner_microstep: 272.62 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 23:04:38,517] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.14 | bwd_microstep: 272.42 | bwd_inner_microstep: 272.40 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 23:04:38,991] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.53 | bwd_microstep: 271.36 | bwd_inner_microstep: 271.34 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 318 +[2025-05-01 23:04:39,222] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 97.19 | bwd_microstep: 116.37 | bwd_inner_microstep: 116.25 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-01 23:04:39,698] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.59 | bwd_microstep: 271.14 | bwd_inner_microstep: 271.12 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 23:04:40,171] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.47 | bwd_microstep: 271.02 | bwd_inner_microstep: 271.00 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1909 +[2025-05-01 23:04:40,741] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.04 | optimizer_gradients: 2.32 | optimizer_step: 16.39 +[2025-05-01 23:04:40,742] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.18 | bwd_microstep: 342.32 | bwd_inner_microstep: 276.90 | bwd_allreduce_microstep: 65.37 | step_microstep: 23.52 +[2025-05-01 23:04:40,743] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2628.33 | bwd: 3856.70 | bwd_inner: 3790.22 | bwd_allreduce: 65.84 | step: 24.48 + 4%|▎ | 309/8720 [49:14<16:48:43, 7.20s/it] {'loss': 1.3238, 'grad_norm': 4.1664934158325195, 'learning_rate': 9.999238115604652e-06, 'epoch': 0.35} + 4%|▎ | 309/8720 [49:14<16:48:43, 7.20s/it]dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 1010 +[2025-05-01 23:04:41,026] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 112.11 | bwd_microstep: 152.19 | bwd_inner_microstep: 151.87 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1892 +[2025-05-01 23:04:41,511] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.51 | bwd_microstep: 275.45 | bwd_inner_microstep: 275.44 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 367 +[2025-05-01 23:04:41,726] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 84.54 | bwd_microstep: 115.52 | bwd_inner_microstep: 115.36 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1897 +[2025-05-01 23:04:42,210] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.04 | bwd_microstep: 276.04 | bwd_inner_microstep: 276.03 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.14 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1370 +[2025-05-01 23:04:42,583] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.57 | bwd_microstep: 208.04 | bwd_inner_microstep: 207.92 | bwd_allreduce_microstep: 0.03 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-01 23:04:43,065] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.70 | bwd_microstep: 274.55 | bwd_inner_microstep: 274.48 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.12 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1350 +[2025-05-01 23:04:43,432] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.67 | bwd_microstep: 206.48 | bwd_inner_microstep: 206.35 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-01 23:04:43,913] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.72 | bwd_microstep: 273.40 | bwd_inner_microstep: 273.38 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 839 +[2025-05-01 23:04:44,160] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 100.38 | bwd_microstep: 126.15 | bwd_inner_microstep: 126.13 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-01 23:04:44,646] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.56 | bwd_microstep: 273.56 | bwd_inner_microstep: 273.54 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 325 +[2025-05-01 23:04:44,880] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 97.00 | bwd_microstep: 116.05 | bwd_inner_microstep: 115.86 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.11 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1346 +[2025-05-01 23:04:45,252] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 142.79 | bwd_microstep: 205.80 | bwd_inner_microstep: 205.74 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 23:04:45,729] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.32 | bwd_microstep: 271.73 | bwd_inner_microstep: 271.71 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 829 +[2025-05-01 23:04:45,973] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 98.32 | bwd_microstep: 129.44 | bwd_inner_microstep: 129.40 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 827 +[2025-05-01 23:04:46,218] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 97.63 | bwd_microstep: 129.74 | bwd_inner_microstep: 129.46 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.18 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 360 +[2025-05-01 23:04:46,556] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.07 | optimizer_gradients: 2.37 | optimizer_step: 16.43 +[2025-05-01 23:04:46,557] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 91.71 | bwd_microstep: 206.04 | bwd_inner_microstep: 129.25 | bwd_allreduce_microstep: 76.68 | step_microstep: 24.63 +[2025-05-01 23:04:46,558] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2243.14 | bwd: 3240.42 | bwd_inner: 3162.09 | bwd_allreduce: 77.31 | step: 26.26 + 4%|▎ | 310/8720 [49:20<15:50:38, 6.78s/it] {'loss': 1.4837, 'grad_norm': 3.8759546279907227, 'learning_rate': 9.99920535095988e-06, 'epoch': 0.36} + 4%|▎ | 310/8720 [49:20<15:50:38, 6.78s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2005 +[2025-05-01 23:04:47,076] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 200.32 | bwd_microstep: 293.78 | bwd_inner_microstep: 293.76 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1889 +[2025-05-01 23:04:47,557] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.57 | bwd_microstep: 274.36 | bwd_inner_microstep: 274.34 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-01 23:04:48,039] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.66 | bwd_microstep: 273.36 | bwd_inner_microstep: 273.35 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-01 23:04:48,522] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.31 | bwd_microstep: 273.15 | bwd_inner_microstep: 273.13 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 326 +[2025-05-01 23:04:48,745] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 88.76 | bwd_microstep: 116.16 | bwd_inner_microstep: 115.85 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 23:04:49,226] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.70 | bwd_microstep: 272.28 | bwd_inner_microstep: 272.26 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 328 +[2025-05-01 23:04:49,445] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 81.19 | bwd_microstep: 122.00 | bwd_inner_microstep: 121.71 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.10 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 839 +[2025-05-01 23:04:49,685] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 96.00 | bwd_microstep: 126.71 | bwd_inner_microstep: 126.64 | bwd_allreduce_microstep: 0.03 | step_microstep: 0.10 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 842 +[2025-05-01 23:04:49,927] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.33 | bwd_microstep: 131.90 | bwd_inner_microstep: 131.78 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 23:04:50,405] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.22 | bwd_microstep: 272.67 | bwd_inner_microstep: 272.65 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-01 23:04:50,884] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.10 | bwd_microstep: 272.70 | bwd_inner_microstep: 272.68 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 23:04:51,365] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.21 | bwd_microstep: 272.45 | bwd_inner_microstep: 272.43 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 23:04:51,843] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.62 | bwd_microstep: 271.35 | bwd_inner_microstep: 271.34 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 23:04:52,322] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.28 | bwd_microstep: 272.54 | bwd_inner_microstep: 272.52 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 829 +[2025-05-01 23:04:52,567] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.58 | bwd_microstep: 129.97 | bwd_inner_microstep: 129.69 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 23:04:53,146] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.34 | optimizer_step: 16.39 +[2025-05-01 23:04:53,147] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.16 | bwd_microstep: 349.02 | bwd_inner_microstep: 271.91 | bwd_allreduce_microstep: 77.05 | step_microstep: 24.28 +[2025-05-01 23:04:53,148] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2542.63 | bwd: 3724.51 | bwd_inner: 3646.19 | bwd_allreduce: 77.58 | step: 25.38 + 4%|▎ | 311/8720 [49:26<15:42:26, 6.72s/it] {'loss': 1.2069, 'grad_norm': 4.540750980377197, 'learning_rate': 9.999171896606963e-06, 'epoch': 0.36} + 4%|▎ | 311/8720 [49:26<15:42:26, 6.72s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 517 +[2025-05-01 23:04:53,372] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 84.89 | bwd_microstep: 118.09 | bwd_inner_microstep: 117.90 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-01 23:04:53,852] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.52 | bwd_microstep: 274.07 | bwd_inner_microstep: 274.06 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-01 23:04:54,333] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.65 | bwd_microstep: 273.65 | bwd_inner_microstep: 273.63 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-01 23:04:54,814] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.79 | bwd_microstep: 273.66 | bwd_inner_microstep: 273.64 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:04:55,292] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.14 | bwd_microstep: 272.42 | bwd_inner_microstep: 272.40 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:04:55,770] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.16 | bwd_microstep: 272.39 | bwd_inner_microstep: 272.38 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 23:04:56,251] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.06 | bwd_microstep: 272.23 | bwd_inner_microstep: 272.22 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 23:04:56,733] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.01 | bwd_microstep: 272.56 | bwd_inner_microstep: 272.54 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1343 +[2025-05-01 23:04:57,096] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.60 | bwd_microstep: 204.63 | bwd_inner_microstep: 204.49 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 23:04:57,576] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.20 | bwd_microstep: 272.30 | bwd_inner_microstep: 272.28 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 23:04:58,055] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.64 | bwd_microstep: 272.43 | bwd_inner_microstep: 272.42 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 23:04:58,535] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.58 | bwd_microstep: 271.35 | bwd_inner_microstep: 271.33 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 23:04:59,018] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.03 | bwd_microstep: 272.76 | bwd_inner_microstep: 272.75 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 318 +[2025-05-01 23:04:59,237] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 86.20 | bwd_microstep: 116.55 | bwd_inner_microstep: 116.40 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 23:04:59,713] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.84 | bwd_microstep: 271.28 | bwd_inner_microstep: 271.27 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-01 23:05:00,301] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.40 | optimizer_step: 16.66 +[2025-05-01 23:05:00,301] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.26 | bwd_microstep: 352.39 | bwd_inner_microstep: 274.44 | bwd_allreduce_microstep: 77.90 | step_microstep: 24.86 +[2025-05-01 23:05:00,303] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2761.18 | bwd: 4062.86 | bwd_inner: 3984.22 | bwd_allreduce: 78.17 | step: 25.85 + 4%|▎ | 312/8720 [49:34<16:00:25, 6.85s/it] {'loss': 0.9877, 'grad_norm': 5.275179862976074, 'learning_rate': 9.999137752550513e-06, 'epoch': 0.36} + 4%|▎ | 312/8720 [49:34<16:00:25, 6.85s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1925 +[2025-05-01 23:05:00,808] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 194.58 | bwd_microstep: 286.64 | bwd_inner_microstep: 286.62 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1899 +[2025-05-01 23:05:01,289] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.31 | bwd_microstep: 275.51 | bwd_inner_microstep: 275.49 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1367 +[2025-05-01 23:05:01,656] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.99 | bwd_microstep: 207.67 | bwd_inner_microstep: 207.64 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1887 +[2025-05-01 23:05:02,142] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.08 | bwd_microstep: 274.76 | bwd_inner_microstep: 274.75 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-01 23:05:02,623] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.50 | bwd_microstep: 273.35 | bwd_inner_microstep: 273.34 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-01 23:05:03,107] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.95 | bwd_microstep: 274.16 | bwd_inner_microstep: 274.15 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.05 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 851 +[2025-05-01 23:05:03,355] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.57 | bwd_microstep: 132.84 | bwd_inner_microstep: 132.53 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.13 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-01 23:05:03,835] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.49 | bwd_microstep: 273.31 | bwd_inner_microstep: 273.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 837 +[2025-05-01 23:05:04,082] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 100.64 | bwd_microstep: 126.10 | bwd_inner_microstep: 125.89 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 850 +[2025-05-01 23:05:04,329] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 96.17 | bwd_microstep: 133.15 | bwd_inner_microstep: 132.86 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:05:04,808] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.87 | bwd_microstep: 272.51 | bwd_inner_microstep: 272.49 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-01 23:05:05,290] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.38 | bwd_microstep: 272.99 | bwd_inner_microstep: 272.97 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 325 +[2025-05-01 23:05:05,523] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 87.40 | bwd_microstep: 129.37 | bwd_inner_microstep: 129.09 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 23:05:06,002] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.01 | bwd_microstep: 272.53 | bwd_inner_microstep: 272.51 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.07 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 23:05:06,481] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.38 | bwd_microstep: 271.31 | bwd_inner_microstep: 271.29 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 23:05:07,050] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.43 | optimizer_step: 16.53 +[2025-05-01 23:05:07,051] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.68 | bwd_microstep: 338.94 | bwd_inner_microstep: 271.95 | bwd_allreduce_microstep: 66.95 | step_microstep: 24.07 +[2025-05-01 23:05:07,052] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2604.65 | bwd: 3815.25 | bwd_inner: 3747.04 | bwd_allreduce: 67.44 | step: 25.43 + 4%|▎ | 313/8720 [49:40<15:55:51, 6.82s/it] {'loss': 0.9977, 'grad_norm': 3.6978187561035156, 'learning_rate': 9.999102918795247e-06, 'epoch': 0.36} + 4%|▎ | 313/8720 [49:40<15:55:51, 6.82s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2244 +[2025-05-01 23:05:07,605] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 209.35 | bwd_microstep: 322.18 | bwd_inner_microstep: 322.16 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-01 23:05:08,085] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.05 | bwd_microstep: 274.48 | bwd_inner_microstep: 274.46 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-01 23:05:08,564] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.02 | bwd_microstep: 274.02 | bwd_inner_microstep: 274.00 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-01 23:05:09,047] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.82 | bwd_microstep: 273.66 | bwd_inner_microstep: 273.64 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 835 +[2025-05-01 23:05:09,288] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 97.47 | bwd_microstep: 125.79 | bwd_inner_microstep: 125.76 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:05:09,769] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.24 | bwd_microstep: 273.59 | bwd_inner_microstep: 273.38 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:05:10,248] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.05 | bwd_microstep: 272.72 | bwd_inner_microstep: 272.71 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:05:10,727] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.23 | bwd_microstep: 272.67 | bwd_inner_microstep: 272.65 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:05:11,205] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.79 | bwd_microstep: 272.48 | bwd_inner_microstep: 272.46 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 323 +[2025-05-01 23:05:11,432] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 84.32 | bwd_microstep: 126.73 | bwd_inner_microstep: 126.58 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:05:11,912] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.22 | bwd_microstep: 272.69 | bwd_inner_microstep: 272.68 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 23:05:12,391] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.70 | bwd_microstep: 272.38 | bwd_inner_microstep: 272.36 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 23:05:12,869] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.14 | bwd_microstep: 271.58 | bwd_inner_microstep: 271.56 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 23:05:13,349] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.39 | bwd_microstep: 271.63 | bwd_inner_microstep: 271.61 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 23:05:13,830] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.48 | bwd_microstep: 271.37 | bwd_inner_microstep: 271.35 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 504 +[2025-05-01 23:05:14,179] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.45 | optimizer_step: 16.57 +[2025-05-01 23:05:14,179] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.02 | bwd_microstep: 214.80 | bwd_inner_microstep: 138.16 | bwd_allreduce_microstep: 76.54 | step_microstep: 24.40 +[2025-05-01 23:05:14,181] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2744.95 | bwd: 4062.84 | bwd_inner: 3985.60 | bwd_allreduce: 76.79 | step: 25.29 + 4%|▎ | 314/8720 [49:47<16:08:39, 6.91s/it] {'loss': 0.9703, 'grad_norm': 2.6856963634490967, 'learning_rate': 9.999067395345966e-06, 'epoch': 0.36} + 4%|▎ | 314/8720 [49:47<16:08:39, 6.91s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2016 +[2025-05-01 23:05:14,698] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 199.27 | bwd_microstep: 295.29 | bwd_inner_microstep: 295.27 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 388 +[2025-05-01 23:05:14,912] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 81.39 | bwd_microstep: 117.16 | bwd_inner_microstep: 116.91 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-01 23:05:15,393] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.98 | bwd_microstep: 274.26 | bwd_inner_microstep: 274.24 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.12 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 347 +[2025-05-01 23:05:15,612] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 80.26 | bwd_microstep: 122.75 | bwd_inner_microstep: 122.44 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.11 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 852 +[2025-05-01 23:05:15,857] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.30 | bwd_microstep: 133.28 | bwd_inner_microstep: 133.27 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:05:16,336] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.04 | bwd_microstep: 272.74 | bwd_inner_microstep: 272.72 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-01 23:05:16,818] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.69 | bwd_microstep: 272.81 | bwd_inner_microstep: 272.79 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-01 23:05:17,298] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.84 | bwd_microstep: 273.15 | bwd_inner_microstep: 273.13 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 23:05:17,781] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.31 | bwd_microstep: 272.23 | bwd_inner_microstep: 272.21 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 321 +[2025-05-01 23:05:17,999] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 82.16 | bwd_microstep: 119.80 | bwd_inner_microstep: 119.61 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 23:05:18,478] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.09 | bwd_microstep: 272.25 | bwd_inner_microstep: 272.24 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 23:05:18,958] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.46 | bwd_microstep: 271.22 | bwd_inner_microstep: 271.21 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 23:05:19,437] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.55 | bwd_microstep: 271.22 | bwd_inner_microstep: 271.21 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 23:05:19,918] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.47 | bwd_microstep: 271.26 | bwd_inner_microstep: 271.25 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1340 +[2025-05-01 23:05:20,288] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 142.69 | bwd_microstep: 204.70 | bwd_inner_microstep: 204.54 | bwd_allreduce_microstep: 0.08 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 23:05:20,882] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.40 | optimizer_step: 16.62 +[2025-05-01 23:05:20,882] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.60 | bwd_microstep: 359.10 | bwd_inner_microstep: 271.82 | bwd_allreduce_microstep: 87.22 | step_microstep: 24.81 +[2025-05-01 23:05:20,884] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2567.72 | bwd: 3803.30 | bwd_inner: 3715.02 | bwd_allreduce: 87.68 | step: 25.99 + 4%|▎ | 315/8720 [49:54<15:59:42, 6.85s/it] {'loss': 1.1928, 'grad_norm': 5.109849452972412, 'learning_rate': 9.99903118220757e-06, 'epoch': 0.36} + 4%|▎ | 315/8720 [49:54<15:59:42, 6.85s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1961 +[2025-05-01 23:05:21,396] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 198.55 | bwd_microstep: 289.40 | bwd_inner_microstep: 289.38 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1939 +[2025-05-01 23:05:21,900] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.92 | bwd_microstep: 288.55 | bwd_inner_microstep: 288.54 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1922 +[2025-05-01 23:05:22,405] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 194.69 | bwd_microstep: 287.33 | bwd_inner_microstep: 287.31 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.21 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1908 +[2025-05-01 23:05:22,892] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.77 | bwd_microstep: 276.07 | bwd_inner_microstep: 276.05 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-01 23:05:23,376] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.40 | bwd_microstep: 274.16 | bwd_inner_microstep: 274.15 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-01 23:05:23,856] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.13 | bwd_microstep: 272.91 | bwd_inner_microstep: 272.89 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-01 23:05:24,337] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.58 | bwd_microstep: 272.73 | bwd_inner_microstep: 272.71 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1362 +[2025-05-01 23:05:24,703] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.88 | bwd_microstep: 206.91 | bwd_inner_microstep: 206.75 | bwd_allreduce_microstep: 0.09 | step_microstep: 0.10 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1356 +[2025-05-01 23:05:25,068] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.62 | bwd_microstep: 206.17 | bwd_inner_microstep: 206.15 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-01 23:05:25,549] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.52 | bwd_microstep: 273.13 | bwd_inner_microstep: 273.11 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-01 23:05:26,032] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.35 | bwd_microstep: 273.07 | bwd_inner_microstep: 273.05 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 23:05:26,511] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.16 | bwd_microstep: 272.49 | bwd_inner_microstep: 272.47 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 23:05:26,990] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.82 | bwd_microstep: 272.28 | bwd_inner_microstep: 272.25 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 23:05:27,468] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.51 | bwd_microstep: 272.48 | bwd_inner_microstep: 272.46 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 23:05:27,946] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.59 | bwd_microstep: 271.23 | bwd_inner_microstep: 271.21 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-01 23:05:28,533] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.39 | optimizer_step: 17.04 +[2025-05-01 23:05:28,533] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.97 | bwd_microstep: 354.76 | bwd_inner_microstep: 271.39 | bwd_allreduce_microstep: 83.31 | step_microstep: 25.18 +[2025-05-01 23:05:28,535] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2947.11 | bwd: 4363.71 | bwd_inner: 4279.89 | bwd_allreduce: 83.52 | step: 26.39 + 4%|▎ | 316/8720 [50:02<16:33:11, 7.09s/it] {'loss': 1.6025, 'grad_norm': 4.959075927734375, 'learning_rate': 9.998994279385058e-06, 'epoch': 0.36} + 4%|▎ | 316/8720 [50:02<16:33:11, 7.09s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1896 +[2025-05-01 23:05:29,021] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.34 | bwd_microstep: 274.43 | bwd_inner_microstep: 274.41 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1891 +[2025-05-01 23:05:29,504] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.35 | bwd_microstep: 274.77 | bwd_inner_microstep: 274.75 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-01 23:05:29,984] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.35 | bwd_microstep: 274.17 | bwd_inner_microstep: 274.15 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.17 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-01 23:05:30,465] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.16 | bwd_microstep: 273.81 | bwd_inner_microstep: 273.79 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.21 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 322 +[2025-05-01 23:05:30,700] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 98.55 | bwd_microstep: 117.29 | bwd_inner_microstep: 117.00 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.10 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 835 +[2025-05-01 23:05:30,937] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.71 | bwd_microstep: 126.33 | bwd_inner_microstep: 126.26 | bwd_allreduce_microstep: 0.03 | step_microstep: 0.10 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 318 +[2025-05-01 23:05:31,154] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 84.87 | bwd_microstep: 116.87 | bwd_inner_microstep: 116.72 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 23:05:31,632] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.87 | bwd_microstep: 271.40 | bwd_inner_microstep: 271.38 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 23:05:32,111] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.34 | bwd_microstep: 271.33 | bwd_inner_microstep: 271.31 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:05:32,592] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.73 | bwd_microstep: 272.70 | bwd_inner_microstep: 272.68 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 23:05:33,070] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.27 | bwd_microstep: 271.27 | bwd_inner_microstep: 271.25 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 23:05:33,549] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.27 | bwd_microstep: 271.40 | bwd_inner_microstep: 271.38 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 23:05:34,029] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.87 | bwd_microstep: 271.59 | bwd_inner_microstep: 271.57 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 314 +[2025-05-01 23:05:34,241] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 79.74 | bwd_microstep: 117.09 | bwd_inner_microstep: 116.82 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1928 +[2025-05-01 23:05:34,741] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 194.96 | bwd_microstep: 287.84 | bwd_inner_microstep: 287.83 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1892 +[2025-05-01 23:05:35,323] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.31 | optimizer_step: 16.28 +[2025-05-01 23:05:35,324] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.64 | bwd_microstep: 346.77 | bwd_inner_microstep: 275.58 | bwd_allreduce_microstep: 71.15 | step_microstep: 23.39 +[2025-05-01 23:05:35,325] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2632.69 | bwd: 3839.14 | bwd_inner: 3767.06 | bwd_allreduce: 71.52 | step: 24.87 + 4%|▎ | 317/8720 [50:09<16:20:22, 7.00s/it] {'loss': 1.0259, 'grad_norm': 3.6362717151641846, 'learning_rate': 9.998956686883522e-06, 'epoch': 0.36} + 4%|▎ | 317/8720 [50:09<16:20:22, 7.00s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1972 +[2025-05-01 23:05:35,836] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 199.77 | bwd_microstep: 290.85 | bwd_inner_microstep: 290.83 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1903 +[2025-05-01 23:05:36,318] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.97 | bwd_microstep: 275.77 | bwd_inner_microstep: 275.76 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1889 +[2025-05-01 23:05:36,798] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.96 | bwd_microstep: 274.62 | bwd_inner_microstep: 274.60 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1886 +[2025-05-01 23:05:37,277] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.06 | bwd_microstep: 274.40 | bwd_inner_microstep: 274.38 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-01 23:05:37,758] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.83 | bwd_microstep: 273.47 | bwd_inner_microstep: 273.45 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1358 +[2025-05-01 23:05:38,120] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.84 | bwd_microstep: 206.62 | bwd_inner_microstep: 206.50 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-01 23:05:38,600] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.13 | bwd_microstep: 272.71 | bwd_inner_microstep: 272.70 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-01 23:05:39,084] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.13 | bwd_microstep: 274.15 | bwd_inner_microstep: 274.13 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 329 +[2025-05-01 23:05:39,332] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 91.05 | bwd_microstep: 138.74 | bwd_inner_microstep: 138.52 | bwd_allreduce_microstep: 0.08 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-01 23:05:39,812] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.88 | bwd_microstep: 273.11 | bwd_inner_microstep: 273.09 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-01 23:05:40,293] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.69 | bwd_microstep: 272.71 | bwd_inner_microstep: 272.69 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-01 23:05:40,772] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.00 | bwd_microstep: 272.77 | bwd_inner_microstep: 272.75 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 839 +[2025-05-01 23:05:41,020] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 102.29 | bwd_microstep: 126.73 | bwd_inner_microstep: 126.45 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-01 23:05:41,499] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.70 | bwd_microstep: 273.01 | bwd_inner_microstep: 272.99 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 23:05:41,978] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.23 | bwd_microstep: 272.93 | bwd_inner_microstep: 272.91 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 23:05:42,559] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.34 | optimizer_step: 16.34 +[2025-05-01 23:05:42,559] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.10 | bwd_microstep: 351.29 | bwd_inner_microstep: 272.95 | bwd_allreduce_microstep: 78.29 | step_microstep: 24.19 +[2025-05-01 23:05:42,561] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2799.28 | bwd: 4123.93 | bwd_inner: 4044.82 | bwd_allreduce: 78.63 | step: 25.17 + 4%|▎ | 318/8720 [50:16<16:30:13, 7.07s/it] {'loss': 1.5019, 'grad_norm': 3.650247097015381, 'learning_rate': 9.998918404708144e-06, 'epoch': 0.36} + 4%|▎ | 318/8720 [50:16<16:30:13, 7.07s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1895 +[2025-05-01 23:05:43,049] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.78 | bwd_microstep: 274.63 | bwd_inner_microstep: 274.61 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-01 23:05:43,531] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.36 | bwd_microstep: 273.90 | bwd_inner_microstep: 273.88 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-01 23:05:44,013] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.18 | bwd_microstep: 274.48 | bwd_inner_microstep: 274.46 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 343 +[2025-05-01 23:05:44,244] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 91.75 | bwd_microstep: 121.78 | bwd_inner_microstep: 121.48 | bwd_allreduce_microstep: 0.15 | step_microstep: 0.10 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1366 +[2025-05-01 23:05:44,611] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 142.13 | bwd_microstep: 207.33 | bwd_inner_microstep: 207.31 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 845 +[2025-05-01 23:05:44,855] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.35 | bwd_microstep: 132.73 | bwd_inner_microstep: 132.51 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-01 23:05:45,336] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.65 | bwd_microstep: 273.85 | bwd_inner_microstep: 273.83 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 339 +[2025-05-01 23:05:45,565] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 91.13 | bwd_microstep: 120.43 | bwd_inner_microstep: 120.16 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 23:05:46,049] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.63 | bwd_microstep: 272.68 | bwd_inner_microstep: 272.66 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1095 +[2025-05-01 23:05:46,345] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 118.27 | bwd_microstep: 161.21 | bwd_inner_microstep: 161.01 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-01 23:05:46,825] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.43 | bwd_microstep: 272.96 | bwd_inner_microstep: 272.95 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 23:05:47,308] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.45 | bwd_microstep: 272.33 | bwd_inner_microstep: 272.31 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 23:05:47,789] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.90 | bwd_microstep: 272.43 | bwd_inner_microstep: 272.41 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 23:05:48,267] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.78 | bwd_microstep: 271.80 | bwd_inner_microstep: 271.78 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2341 +[2025-05-01 23:05:48,842] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 217.83 | bwd_microstep: 339.30 | bwd_inner_microstep: 339.28 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1889 +[2025-05-01 23:05:49,426] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.42 | optimizer_step: 16.36 +[2025-05-01 23:05:49,427] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.76 | bwd_microstep: 352.31 | bwd_inner_microstep: 275.91 | bwd_allreduce_microstep: 76.34 | step_microstep: 24.19 +[2025-05-01 23:05:49,428] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2649.98 | bwd: 3894.26 | bwd_inner: 3816.70 | bwd_allreduce: 76.88 | step: 25.36 + 4%|▎ | 319/8720 [50:23<16:21:32, 7.01s/it] {'loss': 1.4308, 'grad_norm': 3.8182551860809326, 'learning_rate': 9.99887943286421e-06, 'epoch': 0.37} + 4%|▎ | 319/8720 [50:23<16:21:32, 7.01s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1910 +[2025-05-01 23:05:49,917] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.18 | bwd_microstep: 276.30 | bwd_inner_microstep: 276.28 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1390 +[2025-05-01 23:05:50,284] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 142.48 | bwd_microstep: 209.62 | bwd_inner_microstep: 209.49 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1889 +[2025-05-01 23:05:50,766] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.27 | bwd_microstep: 275.51 | bwd_inner_microstep: 275.50 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-01 23:05:51,247] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 191.03 | bwd_microstep: 274.90 | bwd_inner_microstep: 274.88 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1883 +[2025-05-01 23:05:51,728] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.76 | bwd_microstep: 275.06 | bwd_inner_microstep: 275.05 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 340 +[2025-05-01 23:05:51,942] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 78.08 | bwd_microstep: 123.01 | bwd_inner_microstep: 122.73 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:05:52,420] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.06 | bwd_microstep: 273.43 | bwd_inner_microstep: 273.42 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:05:52,898] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.14 | bwd_microstep: 273.34 | bwd_inner_microstep: 273.32 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 834 +[2025-05-01 23:05:53,138] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 97.79 | bwd_microstep: 126.27 | bwd_inner_microstep: 126.16 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 23:05:53,618] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.32 | bwd_microstep: 273.33 | bwd_inner_microstep: 273.31 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 23:05:54,100] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.55 | bwd_microstep: 273.08 | bwd_inner_microstep: 273.06 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 23:05:54,582] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.92 | bwd_microstep: 273.02 | bwd_inner_microstep: 273.00 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.10 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1344 +[2025-05-01 23:05:54,946] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.94 | bwd_microstep: 204.86 | bwd_inner_microstep: 204.84 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.13 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 829 +[2025-05-01 23:05:55,191] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 98.36 | bwd_microstep: 129.83 | bwd_inner_microstep: 129.60 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 23:05:55,672] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.79 | bwd_microstep: 271.21 | bwd_inner_microstep: 271.20 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 895 +[2025-05-01 23:05:56,031] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.39 | optimizer_step: 16.43 +[2025-05-01 23:05:56,031] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 101.92 | bwd_microstep: 213.28 | bwd_inner_microstep: 136.52 | bwd_allreduce_microstep: 76.60 | step_microstep: 24.25 +[2025-05-01 23:05:56,033] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2557.25 | bwd: 3746.13 | bwd_inner: 3668.56 | bwd_allreduce: 76.96 | step: 25.32 + 4%|▎ | 320/8720 [50:29<16:04:23, 6.89s/it] {'loss': 1.3161, 'grad_norm': 3.634303092956543, 'learning_rate': 9.998839771357094e-06, 'epoch': 0.37} + 4%|▎ | 320/8720 [50:29<16:04:23, 6.89s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1988 +[2025-05-01 23:05:56,547] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 198.44 | bwd_microstep: 293.44 | bwd_inner_microstep: 293.42 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1234 +[2025-05-01 23:05:56,866] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 124.40 | bwd_microstep: 177.72 | bwd_inner_microstep: 177.55 | bwd_allreduce_microstep: 0.08 | step_microstep: 0.21 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1892 +[2025-05-01 23:05:57,348] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.47 | bwd_microstep: 274.79 | bwd_inner_microstep: 274.78 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-01 23:05:57,826] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.85 | bwd_microstep: 273.55 | bwd_inner_microstep: 273.53 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.13 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 847 +[2025-05-01 23:05:58,068] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.42 | bwd_microstep: 132.94 | bwd_inner_microstep: 132.66 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-01 23:05:58,545] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.13 | bwd_microstep: 272.75 | bwd_inner_microstep: 272.74 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1356 +[2025-05-01 23:05:58,908] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.31 | bwd_microstep: 206.38 | bwd_inner_microstep: 206.23 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-01 23:05:59,385] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.60 | bwd_microstep: 272.93 | bwd_inner_microstep: 272.91 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1095 +[2025-05-01 23:05:59,676] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 115.55 | bwd_microstep: 161.40 | bwd_inner_microstep: 161.25 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-01 23:06:00,154] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.55 | bwd_microstep: 273.14 | bwd_inner_microstep: 273.12 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-01 23:06:00,633] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.89 | bwd_microstep: 272.75 | bwd_inner_microstep: 272.73 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:06:01,114] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.64 | bwd_microstep: 272.73 | bwd_inner_microstep: 272.71 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 833 +[2025-05-01 23:06:01,351] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.51 | bwd_microstep: 126.02 | bwd_inner_microstep: 125.91 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 23:06:01,828] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.97 | bwd_microstep: 271.21 | bwd_inner_microstep: 271.19 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 316 +[2025-05-01 23:06:02,051] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 87.23 | bwd_microstep: 118.61 | bwd_inner_microstep: 118.42 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 23:06:02,633] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.39 | optimizer_step: 16.44 +[2025-05-01 23:06:02,633] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.81 | bwd_microstep: 352.73 | bwd_inner_microstep: 271.51 | bwd_allreduce_microstep: 81.18 | step_microstep: 24.27 +[2025-05-01 23:06:02,635] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2552.45 | bwd: 3753.20 | bwd_inner: 3670.74 | bwd_allreduce: 81.80 | step: 25.60 + 4%|▎ | 321/8720 [50:36<15:52:14, 6.80s/it] {'loss': 1.5549, 'grad_norm': 4.654592990875244, 'learning_rate': 9.99879942019227e-06, 'epoch': 0.37} + 4%|▎ | 321/8720 [50:36<15:52:14, 6.80s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1893 +[2025-05-01 23:06:03,124] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 191.12 | bwd_microstep: 275.14 | bwd_inner_microstep: 275.12 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-01 23:06:03,609] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.47 | bwd_microstep: 275.07 | bwd_inner_microstep: 275.05 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-01 23:06:04,089] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.37 | bwd_microstep: 273.77 | bwd_inner_microstep: 273.76 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-01 23:06:04,573] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.53 | bwd_microstep: 275.31 | bwd_inner_microstep: 275.29 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-01 23:06:05,054] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.06 | bwd_microstep: 273.34 | bwd_inner_microstep: 273.32 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-01 23:06:05,537] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.94 | bwd_microstep: 274.45 | bwd_inner_microstep: 274.43 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-01 23:06:06,020] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.10 | bwd_microstep: 274.01 | bwd_inner_microstep: 273.99 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-01 23:06:06,503] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.07 | bwd_microstep: 273.58 | bwd_inner_microstep: 273.56 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-01 23:06:06,987] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.05 | bwd_microstep: 273.48 | bwd_inner_microstep: 273.46 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-01 23:06:07,467] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.16 | bwd_microstep: 273.37 | bwd_inner_microstep: 273.35 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.14 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:06:07,949] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.87 | bwd_microstep: 273.10 | bwd_inner_microstep: 273.08 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1355 +[2025-05-01 23:06:08,317] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.66 | bwd_microstep: 206.36 | bwd_inner_microstep: 206.35 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 23:06:08,801] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.98 | bwd_microstep: 272.48 | bwd_inner_microstep: 272.46 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.15 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 828 +[2025-05-01 23:06:09,049] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 97.15 | bwd_microstep: 129.91 | bwd_inner_microstep: 129.61 | bwd_allreduce_microstep: 0.14 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-01 23:06:09,526] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.68 | bwd_microstep: 271.14 | bwd_inner_microstep: 271.12 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 23:06:10,105] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.29 | optimizer_step: 16.49 +[2025-05-01 23:06:10,106] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.87 | bwd_microstep: 348.23 | bwd_inner_microstep: 271.75 | bwd_allreduce_microstep: 76.42 | step_microstep: 24.31 +[2025-05-01 23:06:10,107] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2888.70 | bwd: 4242.78 | bwd_inner: 4165.75 | bwd_allreduce: 76.64 | step: 25.82 + 4%|▎ | 322/8720 [50:43<16:20:15, 7.00s/it] {'loss': 1.6348, 'grad_norm': 4.935256481170654, 'learning_rate': 9.998758379375301e-06, 'epoch': 0.37} + 4%|▎ | 322/8720 [50:43<16:20:15, 7.00s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1911 +[2025-05-01 23:06:10,597] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.51 | bwd_microstep: 276.48 | bwd_inner_microstep: 276.46 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 361 +[2025-05-01 23:06:10,818] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 86.67 | bwd_microstep: 119.14 | bwd_inner_microstep: 118.81 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1888 +[2025-05-01 23:06:11,298] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.63 | bwd_microstep: 274.72 | bwd_inner_microstep: 274.70 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-01 23:06:11,777] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.77 | bwd_microstep: 273.74 | bwd_inner_microstep: 273.72 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-01 23:06:12,255] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.73 | bwd_microstep: 273.81 | bwd_inner_microstep: 273.79 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-01 23:06:12,733] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.41 | bwd_microstep: 273.56 | bwd_inner_microstep: 273.54 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-01 23:06:13,211] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.43 | bwd_microstep: 273.32 | bwd_inner_microstep: 273.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-01 23:06:13,689] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.64 | bwd_microstep: 272.93 | bwd_inner_microstep: 272.91 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-01 23:06:14,167] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.66 | bwd_microstep: 273.38 | bwd_inner_microstep: 273.36 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.15 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 23:06:14,642] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.30 | bwd_microstep: 272.40 | bwd_inner_microstep: 272.39 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 329 +[2025-05-01 23:06:14,853] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 76.72 | bwd_microstep: 119.14 | bwd_inner_microstep: 118.82 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:06:15,331] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.37 | bwd_microstep: 272.87 | bwd_inner_microstep: 272.85 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-01 23:06:15,812] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.84 | bwd_microstep: 273.19 | bwd_inner_microstep: 273.17 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 23:06:16,293] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.90 | bwd_microstep: 272.66 | bwd_inner_microstep: 272.64 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 23:06:16,770] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.64 | bwd_microstep: 271.41 | bwd_inner_microstep: 271.39 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 827 +[2025-05-01 23:06:17,109] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.04 | optimizer_gradients: 2.32 | optimizer_step: 16.39 +[2025-05-01 23:06:17,110] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.84 | bwd_microstep: 203.98 | bwd_inner_microstep: 130.02 | bwd_allreduce_microstep: 73.86 | step_microstep: 23.48 +[2025-05-01 23:06:17,111] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2716.78 | bwd: 3996.75 | bwd_inner: 3922.03 | bwd_allreduce: 74.17 | step: 24.67 + 4%|▎ | 323/8720 [50:50<16:20:05, 7.00s/it] {'loss': 1.2678, 'grad_norm': 2.6046416759490967, 'learning_rate': 9.998716648911856e-06, 'epoch': 0.37} + 4%|▎ | 323/8720 [50:50<16:20:05, 7.00s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2001 +[2025-05-01 23:06:17,625] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 200.28 | bwd_microstep: 294.08 | bwd_inner_microstep: 294.06 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1995 +[2025-05-01 23:06:18,133] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 198.17 | bwd_microstep: 294.36 | bwd_inner_microstep: 294.35 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1982 +[2025-05-01 23:06:18,638] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 197.26 | bwd_microstep: 292.35 | bwd_inner_microstep: 292.33 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1430 +[2025-05-01 23:06:19,014] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 146.72 | bwd_microstep: 214.52 | bwd_inner_microstep: 214.39 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1931 +[2025-05-01 23:06:19,517] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 197.74 | bwd_microstep: 288.03 | bwd_inner_microstep: 288.01 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1894 +[2025-05-01 23:06:19,997] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.59 | bwd_microstep: 275.28 | bwd_inner_microstep: 275.27 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1889 +[2025-05-01 23:06:20,478] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.04 | bwd_microstep: 275.51 | bwd_inner_microstep: 275.49 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 344 +[2025-05-01 23:06:20,688] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 77.03 | bwd_microstep: 119.79 | bwd_inner_microstep: 119.47 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1109 +[2025-05-01 23:06:20,980] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 114.57 | bwd_microstep: 162.36 | bwd_inner_microstep: 162.20 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 23:06:21,457] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.77 | bwd_microstep: 272.84 | bwd_inner_microstep: 272.82 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 23:06:21,935] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.30 | bwd_microstep: 272.68 | bwd_inner_microstep: 272.66 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-01 23:06:22,421] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.43 | bwd_microstep: 272.74 | bwd_inner_microstep: 272.72 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 23:06:22,898] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.72 | bwd_microstep: 272.55 | bwd_inner_microstep: 272.53 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 23:06:23,376] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.60 | bwd_microstep: 271.54 | bwd_inner_microstep: 271.53 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 23:06:23,853] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.95 | bwd_microstep: 271.51 | bwd_inner_microstep: 271.50 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-01 23:06:24,426] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.41 | optimizer_step: 16.65 +[2025-05-01 23:06:24,427] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.82 | bwd_microstep: 343.11 | bwd_inner_microstep: 272.02 | bwd_allreduce_microstep: 71.04 | step_microstep: 24.42 +[2025-05-01 23:06:24,428] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2833.71 | bwd: 4193.35 | bwd_inner: 4121.44 | bwd_allreduce: 71.43 | step: 25.51 + 4%|▎ | 324/8720 [50:58<16:33:09, 7.10s/it] {'loss': 1.4088, 'grad_norm': 3.520768880844116, 'learning_rate': 9.998674228807685e-06, 'epoch': 0.37} + 4%|▎ | 324/8720 [50:58<16:33:09, 7.10s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-01 23:06:24,912] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.42 | bwd_microstep: 273.43 | bwd_inner_microstep: 273.41 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1894 +[2025-05-01 23:06:25,394] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.35 | bwd_microstep: 275.13 | bwd_inner_microstep: 275.11 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-01 23:06:25,875] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.69 | bwd_microstep: 274.14 | bwd_inner_microstep: 274.12 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-01 23:06:26,357] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.66 | bwd_microstep: 273.40 | bwd_inner_microstep: 273.38 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 848 +[2025-05-01 23:06:26,601] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.44 | bwd_microstep: 132.89 | bwd_inner_microstep: 132.79 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-01 23:06:27,078] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.66 | bwd_microstep: 273.03 | bwd_inner_microstep: 273.01 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-01 23:06:27,557] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.83 | bwd_microstep: 273.35 | bwd_inner_microstep: 273.33 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-01 23:06:28,036] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.93 | bwd_microstep: 273.02 | bwd_inner_microstep: 273.01 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-01 23:06:28,514] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.16 | bwd_microstep: 272.92 | bwd_inner_microstep: 272.90 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 321 +[2025-05-01 23:06:28,740] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 74.47 | bwd_microstep: 129.53 | bwd_inner_microstep: 129.22 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 23:06:29,217] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.00 | bwd_microstep: 272.75 | bwd_inner_microstep: 272.73 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-01 23:06:29,696] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.16 | bwd_microstep: 272.92 | bwd_inner_microstep: 272.90 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 23:06:30,173] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.08 | bwd_microstep: 272.38 | bwd_inner_microstep: 272.36 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1086 +[2025-05-01 23:06:30,468] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 118.70 | bwd_microstep: 160.10 | bwd_inner_microstep: 159.86 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 23:06:30,944] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.70 | bwd_microstep: 271.34 | bwd_inner_microstep: 271.33 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1417 +[2025-05-01 23:06:31,415] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.32 | optimizer_step: 16.71 +[2025-05-01 23:06:31,416] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 145.96 | bwd_microstep: 285.00 | bwd_inner_microstep: 213.99 | bwd_allreduce_microstep: 70.92 | step_microstep: 24.44 +[2025-05-01 23:06:31,417] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2702.92 | bwd: 3985.39 | bwd_inner: 3913.57 | bwd_allreduce: 71.28 | step: 25.53 + 4%|▎ | 325/8720 [51:05<16:28:30, 7.06s/it] {'loss': 1.5413, 'grad_norm': 4.100381374359131, 'learning_rate': 9.998631119068647e-06, 'epoch': 0.37} + 4%|▎ | 325/8720 [51:05<16:28:30, 7.06s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 396 +[2025-05-01 23:06:31,635] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 72.73 | bwd_microstep: 126.07 | bwd_inner_microstep: 125.92 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 348 +[2025-05-01 23:06:31,857] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 76.70 | bwd_microstep: 130.40 | bwd_inner_microstep: 130.26 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-01 23:06:32,338] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.38 | bwd_microstep: 274.52 | bwd_inner_microstep: 274.50 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.21 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-01 23:06:32,819] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.37 | bwd_microstep: 273.99 | bwd_inner_microstep: 273.97 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-01 23:06:33,298] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.69 | bwd_microstep: 273.16 | bwd_inner_microstep: 273.14 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 850 +[2025-05-01 23:06:33,541] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.97 | bwd_microstep: 133.40 | bwd_inner_microstep: 133.21 | bwd_allreduce_microstep: 0.08 | step_microstep: 0.09 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 333 +[2025-05-01 23:06:33,766] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 80.15 | bwd_microstep: 129.77 | bwd_inner_microstep: 129.45 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 23:06:34,246] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.86 | bwd_microstep: 273.25 | bwd_inner_microstep: 273.23 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-01 23:06:34,728] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.90 | bwd_microstep: 273.69 | bwd_inner_microstep: 273.67 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-01 23:06:35,214] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.01 | bwd_microstep: 273.41 | bwd_inner_microstep: 273.39 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 23:06:35,693] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.87 | bwd_microstep: 271.92 | bwd_inner_microstep: 271.90 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 23:06:36,173] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.91 | bwd_microstep: 271.94 | bwd_inner_microstep: 271.92 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 23:06:36,656] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.16 | bwd_microstep: 273.05 | bwd_inner_microstep: 273.03 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 23:06:37,135] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.74 | bwd_microstep: 271.72 | bwd_inner_microstep: 271.71 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1926 +[2025-05-01 23:06:37,637] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 196.00 | bwd_microstep: 287.46 | bwd_inner_microstep: 287.44 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1896 +[2025-05-01 23:06:38,250] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.36 | optimizer_step: 16.86 +[2025-05-01 23:06:38,251] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.32 | bwd_microstep: 381.63 | bwd_inner_microstep: 275.74 | bwd_allreduce_microstep: 105.84 | step_microstep: 24.53 +[2025-05-01 23:06:38,252] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2600.41 | bwd: 3919.45 | bwd_inner: 3812.65 | bwd_allreduce: 106.19 | step: 25.85 + 4%|▎ | 326/8720 [51:11<16:18:43, 7.00s/it] {'loss': 1.0122, 'grad_norm': 2.6580495834350586, 'learning_rate': 9.998587319700684e-06, 'epoch': 0.37} + 4%|▎ | 326/8720 [51:12<16:18:43, 7.00s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1928 +[2025-05-01 23:06:38,754] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.08 | bwd_microstep: 286.79 | bwd_inner_microstep: 286.78 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.07 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1898 +[2025-05-01 23:06:39,236] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.70 | bwd_microstep: 275.27 | bwd_inner_microstep: 275.25 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1900 +[2025-05-01 23:06:39,719] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 191.73 | bwd_microstep: 275.23 | bwd_inner_microstep: 275.21 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1358 +[2025-05-01 23:06:40,081] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.24 | bwd_microstep: 206.62 | bwd_inner_microstep: 206.50 | bwd_allreduce_microstep: 0.03 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-01 23:06:40,559] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.09 | bwd_microstep: 273.00 | bwd_inner_microstep: 272.98 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1352 +[2025-05-01 23:06:40,922] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.50 | bwd_microstep: 206.39 | bwd_inner_microstep: 206.29 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 23:06:41,397] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.94 | bwd_microstep: 272.46 | bwd_inner_microstep: 272.44 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 23:06:41,875] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.15 | bwd_microstep: 272.59 | bwd_inner_microstep: 272.57 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.16 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:06:42,354] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.33 | bwd_microstep: 272.63 | bwd_inner_microstep: 272.61 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.21 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:06:42,832] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.03 | bwd_microstep: 272.70 | bwd_inner_microstep: 272.68 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 23:06:43,309] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.83 | bwd_microstep: 272.57 | bwd_inner_microstep: 272.56 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 23:06:43,786] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.90 | bwd_microstep: 271.50 | bwd_inner_microstep: 271.48 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 23:06:44,265] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.97 | bwd_microstep: 271.47 | bwd_inner_microstep: 271.45 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 23:06:44,743] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.90 | bwd_microstep: 271.52 | bwd_inner_microstep: 271.50 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 23:06:45,221] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.61 | bwd_microstep: 271.28 | bwd_inner_microstep: 271.26 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.07 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1435 +[2025-05-01 23:06:45,703] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.35 | optimizer_step: 16.75 +[2025-05-01 23:06:45,704] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 144.85 | bwd_microstep: 293.86 | bwd_inner_microstep: 215.16 | bwd_allreduce_microstep: 78.59 | step_microstep: 25.06 +[2025-05-01 23:06:45,705] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2887.55 | bwd: 4265.94 | bwd_inner: 4186.78 | bwd_allreduce: 78.76 | step: 26.33 + 4%|▍ | 327/8720 [51:19<16:37:53, 7.13s/it] {'loss': 1.5976, 'grad_norm': 4.659840106964111, 'learning_rate': 9.99854283070984e-06, 'epoch': 0.37} + 4%|▍ | 327/8720 [51:19<16:37:53, 7.13s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1991 +[2025-05-01 23:06:46,223] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 199.73 | bwd_microstep: 293.52 | bwd_inner_microstep: 293.50 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 898 +[2025-05-01 23:06:46,489] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 104.65 | bwd_microstep: 144.73 | bwd_inner_microstep: 144.42 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1371 +[2025-05-01 23:06:46,854] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 142.06 | bwd_microstep: 207.91 | bwd_inner_microstep: 207.73 | bwd_allreduce_microstep: 0.09 | step_microstep: 0.21 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-01 23:06:47,334] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.80 | bwd_microstep: 274.25 | bwd_inner_microstep: 274.23 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-01 23:06:47,813] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.72 | bwd_microstep: 273.35 | bwd_inner_microstep: 273.33 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-01 23:06:48,293] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.88 | bwd_microstep: 273.86 | bwd_inner_microstep: 273.84 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-01 23:06:48,770] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.49 | bwd_microstep: 272.86 | bwd_inner_microstep: 272.84 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-01 23:06:49,249] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.21 | bwd_microstep: 272.95 | bwd_inner_microstep: 272.93 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1349 +[2025-05-01 23:06:49,612] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.65 | bwd_microstep: 206.02 | bwd_inner_microstep: 206.00 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1094 +[2025-05-01 23:06:49,907] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 115.59 | bwd_microstep: 161.25 | bwd_inner_microstep: 161.23 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 23:06:50,387] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.27 | bwd_microstep: 273.55 | bwd_inner_microstep: 273.53 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 23:06:50,867] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.13 | bwd_microstep: 272.91 | bwd_inner_microstep: 272.89 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 23:06:51,350] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.89 | bwd_microstep: 272.60 | bwd_inner_microstep: 272.59 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 23:06:51,832] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.46 | bwd_microstep: 272.24 | bwd_inner_microstep: 272.22 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 318 +[2025-05-01 23:06:52,102] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 133.24 | bwd_microstep: 116.70 | bwd_inner_microstep: 116.56 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 23:06:52,670] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.55 | optimizer_step: 17.63 +[2025-05-01 23:06:52,670] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.65 | bwd_microstep: 339.42 | bwd_inner_microstep: 271.77 | bwd_allreduce_microstep: 67.60 | step_microstep: 26.17 +[2025-05-01 23:06:52,672] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2724.10 | bwd: 3928.20 | bwd_inner: 3859.72 | bwd_allreduce: 67.96 | step: 27.51 + 4%|▍ | 328/8720 [51:26<16:30:44, 7.08s/it] {'loss': 1.2382, 'grad_norm': 4.232193946838379, 'learning_rate': 9.998497652102254e-06, 'epoch': 0.38} + 4%|▍ | 328/8720 [51:26<16:30:44, 7.08s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 462 +[2025-05-01 23:06:52,914] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 86.40 | bwd_microstep: 133.82 | bwd_inner_microstep: 133.65 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 932 +[2025-05-01 23:06:53,182] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 104.31 | bwd_microstep: 147.37 | bwd_inner_microstep: 147.02 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.17 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1929 +[2025-05-01 23:06:53,684] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 196.84 | bwd_microstep: 288.36 | bwd_inner_microstep: 288.34 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1886 +[2025-05-01 23:06:54,165] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.05 | bwd_microstep: 274.86 | bwd_inner_microstep: 274.84 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-01 23:06:54,644] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.71 | bwd_microstep: 273.36 | bwd_inner_microstep: 273.34 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-01 23:06:55,125] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.49 | bwd_microstep: 273.26 | bwd_inner_microstep: 273.25 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-01 23:06:55,604] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.45 | bwd_microstep: 273.17 | bwd_inner_microstep: 273.15 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:06:56,082] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.49 | bwd_microstep: 273.04 | bwd_inner_microstep: 273.02 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 840 +[2025-05-01 23:06:56,315] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 91.73 | bwd_microstep: 126.89 | bwd_inner_microstep: 126.83 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-01 23:06:56,794] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.45 | bwd_microstep: 273.28 | bwd_inner_microstep: 273.26 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:06:57,272] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.16 | bwd_microstep: 272.73 | bwd_inner_microstep: 272.71 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 837 +[2025-05-01 23:06:57,505] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 90.59 | bwd_microstep: 126.47 | bwd_inner_microstep: 126.18 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.15 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-01 23:06:57,981] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.77 | bwd_microstep: 271.51 | bwd_inner_microstep: 271.49 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-01 23:06:58,457] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.67 | bwd_microstep: 271.27 | bwd_inner_microstep: 271.25 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 23:06:58,934] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.32 | bwd_microstep: 271.50 | bwd_inner_microstep: 271.48 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 448 +[2025-05-01 23:06:59,283] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.30 | optimizer_step: 16.50 +[2025-05-01 23:06:59,283] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.80 | bwd_microstep: 209.69 | bwd_inner_microstep: 133.17 | bwd_allreduce_microstep: 76.39 | step_microstep: 24.33 +[2025-05-01 23:06:59,285] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2555.93 | bwd: 3760.68 | bwd_inner: 3683.15 | bwd_allreduce: 76.82 | step: 25.38 + 4%|▍ | 329/8720 [51:33<16:10:51, 6.94s/it] {'loss': 1.109, 'grad_norm': 3.562629461288452, 'learning_rate': 9.998451783884163e-06, 'epoch': 0.38} + 4%|▍ | 329/8720 [51:33<16:10:51, 6.94s/it]dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1493 +[2025-05-01 23:06:59,687] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 149.29 | bwd_microstep: 231.33 | bwd_inner_microstep: 231.25 | bwd_allreduce_microstep: 0.04 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1911 +[2025-05-01 23:07:00,172] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.50 | bwd_microstep: 276.56 | bwd_inner_microstep: 276.54 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.17 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1902 +[2025-05-01 23:07:00,656] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.72 | bwd_microstep: 275.76 | bwd_inner_microstep: 275.74 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1375 +[2025-05-01 23:07:01,026] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 144.16 | bwd_microstep: 208.25 | bwd_inner_microstep: 208.23 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1890 +[2025-05-01 23:07:01,508] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.49 | bwd_microstep: 275.39 | bwd_inner_microstep: 275.38 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1899 +[2025-05-01 23:07:01,990] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.69 | bwd_microstep: 276.33 | bwd_inner_microstep: 276.31 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1365 +[2025-05-01 23:07:02,356] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 143.53 | bwd_microstep: 207.52 | bwd_inner_microstep: 207.48 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-01 23:07:02,834] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.87 | bwd_microstep: 274.07 | bwd_inner_microstep: 274.06 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1347 +[2025-05-01 23:07:03,195] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.51 | bwd_microstep: 205.91 | bwd_inner_microstep: 205.89 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 23:07:03,672] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.07 | bwd_microstep: 272.45 | bwd_inner_microstep: 272.44 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.31 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 23:07:04,149] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.17 | bwd_microstep: 272.63 | bwd_inner_microstep: 272.61 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 23:07:04,625] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.48 | bwd_microstep: 272.33 | bwd_inner_microstep: 272.32 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 23:07:05,100] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.85 | bwd_microstep: 271.49 | bwd_inner_microstep: 271.47 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 23:07:05,576] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.78 | bwd_microstep: 271.51 | bwd_inner_microstep: 271.49 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 23:07:06,050] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.98 | bwd_microstep: 271.46 | bwd_inner_microstep: 271.44 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-01 23:07:06,617] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.04 | optimizer_gradients: 2.25 | optimizer_step: 16.37 +[2025-05-01 23:07:06,617] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.71 | bwd_microstep: 340.17 | bwd_inner_microstep: 274.15 | bwd_allreduce_microstep: 65.97 | step_microstep: 23.34 +[2025-05-01 23:07:06,618] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2846.55 | bwd: 4203.21 | bwd_inner: 4136.82 | bwd_allreduce: 66.10 | step: 24.63 + 4%|▍ | 330/8720 [51:40<16:27:05, 7.06s/it] {'loss': 0.8761, 'grad_norm': 2.5226356983184814, 'learning_rate': 9.998405226061887e-06, 'epoch': 0.38} + 4%|▍ | 330/8720 [51:40<16:27:05, 7.06s/it]dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1759 +[2025-05-01 23:07:07,056] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 162.47 | bwd_microstep: 255.94 | bwd_inner_microstep: 255.67 | bwd_allreduce_microstep: 0.08 | step_microstep: 0.25 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1912 +[2025-05-01 23:07:07,542] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.32 | bwd_microstep: 276.69 | bwd_inner_microstep: 276.67 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1892 +[2025-05-01 23:07:08,023] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.97 | bwd_microstep: 275.46 | bwd_inner_microstep: 275.44 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-01 23:07:08,504] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.62 | bwd_microstep: 273.70 | bwd_inner_microstep: 273.68 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-01 23:07:08,990] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.11 | bwd_microstep: 273.97 | bwd_inner_microstep: 273.95 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 337 +[2025-05-01 23:07:09,199] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 78.14 | bwd_microstep: 117.54 | bwd_inner_microstep: 117.22 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-01 23:07:09,676] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.60 | bwd_microstep: 273.99 | bwd_inner_microstep: 273.97 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1371 +[2025-05-01 23:07:10,039] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.39 | bwd_microstep: 207.64 | bwd_inner_microstep: 207.62 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 23:07:10,516] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.96 | bwd_microstep: 272.53 | bwd_inner_microstep: 272.51 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1097 +[2025-05-01 23:07:10,807] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 115.36 | bwd_microstep: 161.49 | bwd_inner_microstep: 161.35 | bwd_allreduce_microstep: 0.10 | step_microstep: 0.09 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 327 +[2025-05-01 23:07:11,007] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 68.11 | bwd_microstep: 118.53 | bwd_inner_microstep: 118.21 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.16 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 23:07:11,483] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.90 | bwd_microstep: 272.65 | bwd_inner_microstep: 272.63 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 836 +[2025-05-01 23:07:11,715] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 91.53 | bwd_microstep: 126.33 | bwd_inner_microstep: 126.25 | bwd_allreduce_microstep: 0.04 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-01 23:07:12,192] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.74 | bwd_microstep: 273.43 | bwd_inner_microstep: 273.41 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 326 +[2025-05-01 23:07:12,398] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 72.81 | bwd_microstep: 118.77 | bwd_inner_microstep: 118.47 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 320 +[2025-05-01 23:07:12,716] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.27 | optimizer_step: 16.27 +[2025-05-01 23:07:12,716] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 77.98 | bwd_microstep: 202.45 | bwd_inner_microstep: 135.03 | bwd_allreduce_microstep: 67.26 | step_microstep: 23.57 +[2025-05-01 23:07:12,717] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2323.75 | bwd: 3501.30 | bwd_inner: 3432.36 | bwd_allreduce: 67.91 | step: 24.76 + 4%|▍ | 331/8720 [51:46<15:46:42, 6.77s/it] {'loss': 1.3848, 'grad_norm': 3.568255662918091, 'learning_rate': 9.998357978641853e-06, 'epoch': 0.38} + 4%|▍ | 331/8720 [51:46<15:46:42, 6.77s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2113 +[2025-05-01 23:07:13,255] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 204.58 | bwd_microstep: 312.80 | bwd_inner_microstep: 312.78 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1933 +[2025-05-01 23:07:13,755] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.61 | bwd_microstep: 288.63 | bwd_inner_microstep: 288.61 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1903 +[2025-05-01 23:07:14,236] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.88 | bwd_microstep: 276.04 | bwd_inner_microstep: 276.02 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-01 23:07:14,715] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.41 | bwd_microstep: 274.07 | bwd_inner_microstep: 274.06 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 861 +[2025-05-01 23:07:14,959] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.53 | bwd_microstep: 133.39 | bwd_inner_microstep: 133.38 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1886 +[2025-05-01 23:07:15,439] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.81 | bwd_microstep: 274.82 | bwd_inner_microstep: 274.81 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-01 23:07:15,921] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.17 | bwd_microstep: 274.43 | bwd_inner_microstep: 274.42 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-01 23:07:16,402] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.30 | bwd_microstep: 273.64 | bwd_inner_microstep: 273.63 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-01 23:07:16,882] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.99 | bwd_microstep: 273.53 | bwd_inner_microstep: 273.51 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-01 23:07:17,365] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.75 | bwd_microstep: 273.29 | bwd_inner_microstep: 273.27 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.17 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-01 23:07:17,846] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.69 | bwd_microstep: 272.88 | bwd_inner_microstep: 272.86 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-01 23:07:18,329] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.53 | bwd_microstep: 272.86 | bwd_inner_microstep: 272.84 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1348 +[2025-05-01 23:07:18,693] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.18 | bwd_microstep: 205.92 | bwd_inner_microstep: 205.90 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 23:07:19,175] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.91 | bwd_microstep: 272.80 | bwd_inner_microstep: 272.78 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.21 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 23:07:19,653] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.97 | bwd_microstep: 271.64 | bwd_inner_microstep: 271.62 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.23 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-01 23:07:20,221] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.20 | optimizer_step: 16.15 +[2025-05-01 23:07:20,222] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.55 | bwd_microstep: 338.62 | bwd_inner_microstep: 271.84 | bwd_allreduce_microstep: 66.74 | step_microstep: 23.15 +[2025-05-01 23:07:20,223] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2905.55 | bwd: 4289.42 | bwd_inner: 4222.33 | bwd_allreduce: 66.81 | step: 24.53 + 4%|▍ | 332/8720 [51:53<16:17:24, 6.99s/it] {'loss': 1.1878, 'grad_norm': 3.19231915473938, 'learning_rate': 9.998310041630581e-06, 'epoch': 0.38} + 4%|▍ | 332/8720 [51:53<16:17:24, 6.99s/it]dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1144 +[2025-05-01 23:07:20,523] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 116.23 | bwd_microstep: 164.77 | bwd_inner_microstep: 164.51 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1892 +[2025-05-01 23:07:21,004] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.49 | bwd_microstep: 274.87 | bwd_inner_microstep: 274.86 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1888 +[2025-05-01 23:07:21,483] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.20 | bwd_microstep: 274.75 | bwd_inner_microstep: 274.73 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-01 23:07:21,961] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.08 | bwd_microstep: 273.25 | bwd_inner_microstep: 273.23 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-01 23:07:22,441] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.64 | bwd_microstep: 274.55 | bwd_inner_microstep: 274.53 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-01 23:07:22,920] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.66 | bwd_microstep: 274.56 | bwd_inner_microstep: 274.54 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-01 23:07:23,398] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.44 | bwd_microstep: 273.36 | bwd_inner_microstep: 273.34 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-01 23:07:23,877] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.94 | bwd_microstep: 273.41 | bwd_inner_microstep: 273.39 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-01 23:07:24,357] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.79 | bwd_microstep: 273.79 | bwd_inner_microstep: 273.78 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 23:07:24,833] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.29 | bwd_microstep: 272.54 | bwd_inner_microstep: 272.53 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-01 23:07:25,310] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.18 | bwd_microstep: 273.05 | bwd_inner_microstep: 273.04 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 842 +[2025-05-01 23:07:25,552] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.91 | bwd_microstep: 132.78 | bwd_inner_microstep: 132.49 | bwd_allreduce_microstep: 0.14 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 23:07:26,029] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.55 | bwd_microstep: 272.68 | bwd_inner_microstep: 272.66 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-01 23:07:26,510] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.33 | bwd_microstep: 273.29 | bwd_inner_microstep: 273.27 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 932 +[2025-05-01 23:07:26,772] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 101.50 | bwd_microstep: 146.69 | bwd_inner_microstep: 146.56 | bwd_allreduce_microstep: 0.09 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1893 +[2025-05-01 23:07:27,342] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.04 | optimizer_gradients: 2.18 | optimizer_step: 16.14 +[2025-05-01 23:07:27,342] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.67 | bwd_microstep: 341.33 | bwd_inner_microstep: 275.72 | bwd_allreduce_microstep: 65.57 | step_microstep: 23.12 +[2025-05-01 23:07:27,344] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2773.61 | bwd: 4069.78 | bwd_inner: 4003.20 | bwd_allreduce: 65.97 | step: 24.18 + 4%|▍ | 333/8720 [52:01<16:22:41, 7.03s/it] {'loss': 1.601, 'grad_norm': 5.202573299407959, 'learning_rate': 9.998261415034683e-06, 'epoch': 0.38} + 4%|▍ | 333/8720 [52:01<16:22:41, 7.03s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2436 +[2025-05-01 23:07:27,937] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 222.13 | bwd_microstep: 351.92 | bwd_inner_microstep: 351.90 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2053 +[2025-05-01 23:07:28,458] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 202.47 | bwd_microstep: 302.29 | bwd_inner_microstep: 302.27 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 867 +[2025-05-01 23:07:28,702] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.12 | bwd_microstep: 134.57 | bwd_inner_microstep: 134.35 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1889 +[2025-05-01 23:07:29,181] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.69 | bwd_microstep: 274.82 | bwd_inner_microstep: 274.80 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-01 23:07:29,662] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.36 | bwd_microstep: 275.14 | bwd_inner_microstep: 275.12 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-01 23:07:30,141] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.08 | bwd_microstep: 274.54 | bwd_inner_microstep: 274.53 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-01 23:07:30,619] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.20 | bwd_microstep: 273.31 | bwd_inner_microstep: 273.29 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-01 23:07:31,097] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.47 | bwd_microstep: 273.45 | bwd_inner_microstep: 273.44 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1358 +[2025-05-01 23:07:31,459] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.38 | bwd_microstep: 206.72 | bwd_inner_microstep: 206.59 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.10 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 845 +[2025-05-01 23:07:31,699] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.41 | bwd_microstep: 132.83 | bwd_inner_microstep: 132.55 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-01 23:07:32,178] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.03 | bwd_microstep: 273.42 | bwd_inner_microstep: 273.40 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-01 23:07:32,657] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.09 | bwd_microstep: 273.35 | bwd_inner_microstep: 273.33 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 328 +[2025-05-01 23:07:32,864] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 74.83 | bwd_microstep: 118.49 | bwd_inner_microstep: 118.19 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 23:07:33,340] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.47 | bwd_microstep: 272.56 | bwd_inner_microstep: 272.54 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 23:07:33,815] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.51 | bwd_microstep: 271.25 | bwd_inner_microstep: 271.24 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.17 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 23:07:34,380] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.04 | optimizer_gradients: 2.21 | optimizer_step: 15.95 +[2025-05-01 23:07:34,380] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.31 | bwd_microstep: 338.27 | bwd_inner_microstep: 271.89 | bwd_allreduce_microstep: 66.34 | step_microstep: 22.83 +[2025-05-01 23:07:34,382] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2719.26 | bwd: 4047.01 | bwd_inner: 3979.54 | bwd_allreduce: 66.80 | step: 23.93 + 4%|▍ | 334/8720 [52:08<16:22:54, 7.03s/it] {'loss': 1.611, 'grad_norm': 4.491777420043945, 'learning_rate': 9.998212098860867e-06, 'epoch': 0.38} + 4%|▍ | 334/8720 [52:08<16:22:54, 7.03s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1966 +[2025-05-01 23:07:34,888] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 197.03 | bwd_microstep: 290.26 | bwd_inner_microstep: 290.24 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 361 +[2025-05-01 23:07:35,099] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 74.18 | bwd_microstep: 122.81 | bwd_inner_microstep: 122.57 | bwd_allreduce_microstep: 0.09 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1883 +[2025-05-01 23:07:35,577] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.77 | bwd_microstep: 274.37 | bwd_inner_microstep: 274.36 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-01 23:07:36,057] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.13 | bwd_microstep: 273.72 | bwd_inner_microstep: 273.70 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-01 23:07:36,536] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.11 | bwd_microstep: 273.51 | bwd_inner_microstep: 273.50 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-01 23:07:37,016] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.72 | bwd_microstep: 274.28 | bwd_inner_microstep: 274.26 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-01 23:07:37,495] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.19 | bwd_microstep: 273.34 | bwd_inner_microstep: 273.32 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 23:07:37,975] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.74 | bwd_microstep: 272.58 | bwd_inner_microstep: 272.56 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 23:07:38,459] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.53 | bwd_microstep: 272.63 | bwd_inner_microstep: 272.61 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.13 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 833 +[2025-05-01 23:07:38,693] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 91.20 | bwd_microstep: 126.36 | bwd_inner_microstep: 126.22 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:07:39,172] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.67 | bwd_microstep: 272.79 | bwd_inner_microstep: 272.77 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 23:07:39,649] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.27 | bwd_microstep: 272.70 | bwd_inner_microstep: 272.68 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 23:07:40,127] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.21 | bwd_microstep: 272.78 | bwd_inner_microstep: 272.77 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 23:07:40,602] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.24 | bwd_microstep: 271.53 | bwd_inner_microstep: 271.52 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 23:07:41,077] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.98 | bwd_microstep: 271.10 | bwd_inner_microstep: 271.08 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1443 +[2025-05-01 23:07:41,541] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.04 | optimizer_gradients: 2.22 | optimizer_step: 16.18 +[2025-05-01 23:07:41,542] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 145.08 | bwd_microstep: 282.35 | bwd_inner_microstep: 216.07 | bwd_allreduce_microstep: 66.13 | step_microstep: 23.23 +[2025-05-01 23:07:41,543] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2774.77 | bwd: 4097.15 | bwd_inner: 4030.36 | bwd_allreduce: 66.28 | step: 24.40 + 4%|▍ | 335/8720 [52:15<16:28:12, 7.07s/it] {'loss': 1.3236, 'grad_norm': 5.213300704956055, 'learning_rate': 9.99816209311594e-06, 'epoch': 0.38} + 4%|▍ | 335/8720 [52:15<16:28:12, 7.07s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-01 23:07:42,026] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.12 | bwd_microstep: 273.88 | bwd_inner_microstep: 273.86 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1358 +[2025-05-01 23:07:42,389] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.29 | bwd_microstep: 206.56 | bwd_inner_microstep: 206.54 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-01 23:07:42,868] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.13 | bwd_microstep: 273.96 | bwd_inner_microstep: 273.94 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-01 23:07:43,346] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.18 | bwd_microstep: 273.02 | bwd_inner_microstep: 273.00 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-01 23:07:43,826] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.17 | bwd_microstep: 273.65 | bwd_inner_microstep: 273.63 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-01 23:07:44,303] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.69 | bwd_microstep: 272.88 | bwd_inner_microstep: 272.87 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 23:07:44,781] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.17 | bwd_microstep: 272.56 | bwd_inner_microstep: 272.54 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 23:07:45,259] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.05 | bwd_microstep: 272.58 | bwd_inner_microstep: 272.57 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-01 23:07:45,739] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.55 | bwd_microstep: 273.26 | bwd_inner_microstep: 273.24 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 23:07:46,229] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.44 | bwd_microstep: 272.59 | bwd_inner_microstep: 272.58 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 23:07:46,710] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.26 | bwd_microstep: 273.18 | bwd_inner_microstep: 273.16 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 23:07:47,191] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.82 | bwd_microstep: 272.30 | bwd_inner_microstep: 272.28 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 23:07:47,671] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.12 | bwd_microstep: 271.58 | bwd_inner_microstep: 271.57 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 23:07:48,149] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.31 | bwd_microstep: 271.42 | bwd_inner_microstep: 271.40 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1849 +[2025-05-01 23:07:48,629] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.68 | bwd_microstep: 271.02 | bwd_inner_microstep: 271.00 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1999 +[2025-05-01 23:07:49,246] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.54 | optimizer_step: 17.02 +[2025-05-01 23:07:49,247] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 200.23 | bwd_microstep: 372.42 | bwd_inner_microstep: 295.28 | bwd_allreduce_microstep: 77.08 | step_microstep: 25.30 +[2025-05-01 23:07:49,248] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2983.87 | bwd: 4396.90 | bwd_inner: 4319.48 | bwd_allreduce: 77.17 | step: 26.59 + 4%|▍ | 336/8720 [52:22<16:54:45, 7.26s/it] {'loss': 1.2361, 'grad_norm': 4.548589706420898, 'learning_rate': 9.998111397806796e-06, 'epoch': 0.39} + 4%|▍ | 336/8720 [52:22<16:54:45, 7.26s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1999 +[2025-05-01 23:07:49,764] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 197.53 | bwd_microstep: 294.37 | bwd_inner_microstep: 294.35 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1892 +[2025-05-01 23:07:50,250] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.15 | bwd_microstep: 275.13 | bwd_inner_microstep: 275.11 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-01 23:07:50,732] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.40 | bwd_microstep: 273.46 | bwd_inner_microstep: 273.44 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-01 23:07:51,213] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.99 | bwd_microstep: 273.56 | bwd_inner_microstep: 273.55 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-01 23:07:51,693] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.34 | bwd_microstep: 272.78 | bwd_inner_microstep: 272.76 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 23:07:52,173] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.07 | bwd_microstep: 272.44 | bwd_inner_microstep: 272.42 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 23:07:52,652] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.58 | bwd_microstep: 272.42 | bwd_inner_microstep: 272.40 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 23:07:53,131] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.58 | bwd_microstep: 272.77 | bwd_inner_microstep: 272.76 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.20 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 321 +[2025-05-01 23:07:53,342] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 70.26 | bwd_microstep: 126.93 | bwd_inner_microstep: 126.78 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 23:07:53,818] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.61 | bwd_microstep: 272.40 | bwd_inner_microstep: 272.38 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1342 +[2025-05-01 23:07:54,178] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.09 | bwd_microstep: 204.79 | bwd_inner_microstep: 204.71 | bwd_allreduce_microstep: 0.04 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 23:07:54,652] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.22 | bwd_microstep: 271.19 | bwd_inner_microstep: 271.18 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 23:07:55,130] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.94 | bwd_microstep: 271.33 | bwd_inner_microstep: 271.31 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 23:07:55,608] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.77 | bwd_microstep: 271.34 | bwd_inner_microstep: 271.32 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 23:07:56,088] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.40 | bwd_microstep: 271.16 | bwd_inner_microstep: 271.14 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-01 23:07:56,683] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.08 | optimizer_gradients: 2.31 | optimizer_step: 17.31 +[2025-05-01 23:07:56,684] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.49 | bwd_microstep: 360.07 | bwd_inner_microstep: 273.65 | bwd_allreduce_microstep: 86.37 | step_microstep: 26.88 +[2025-05-01 23:07:56,685] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2859.09 | bwd: 4256.18 | bwd_inner: 4169.30 | bwd_allreduce: 86.55 | step: 27.88 + 4%|▍ | 337/8720 [52:30<17:01:59, 7.31s/it] {'loss': 1.3009, 'grad_norm': 4.200974464416504, 'learning_rate': 9.998060012940433e-06, 'epoch': 0.39} + 4%|▍ | 337/8720 [52:30<17:01:59, 7.31s/it]dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1416 +[2025-05-01 23:07:57,068] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 146.36 | bwd_microstep: 212.44 | bwd_inner_microstep: 212.42 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1893 +[2025-05-01 23:07:57,552] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.82 | bwd_microstep: 275.07 | bwd_inner_microstep: 275.05 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 346 +[2025-05-01 23:07:57,801] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 91.62 | bwd_microstep: 139.81 | bwd_inner_microstep: 139.65 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-01 23:07:58,284] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.17 | bwd_microstep: 275.00 | bwd_inner_microstep: 274.98 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-01 23:07:58,767] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.85 | bwd_microstep: 273.35 | bwd_inner_microstep: 273.33 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 841 +[2025-05-01 23:07:59,010] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.29 | bwd_microstep: 131.86 | bwd_inner_microstep: 131.77 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-01 23:07:59,490] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.33 | bwd_microstep: 272.89 | bwd_inner_microstep: 272.87 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 23:07:59,969] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.15 | bwd_microstep: 272.35 | bwd_inner_microstep: 272.33 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:08:00,450] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.52 | bwd_microstep: 272.60 | bwd_inner_microstep: 272.59 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 833 +[2025-05-01 23:08:00,692] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.41 | bwd_microstep: 130.86 | bwd_inner_microstep: 130.71 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:08:01,168] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.29 | bwd_microstep: 272.87 | bwd_inner_microstep: 272.86 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:08:01,645] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.29 | bwd_microstep: 272.76 | bwd_inner_microstep: 272.74 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.15 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-01 23:08:02,124] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.32 | bwd_microstep: 272.94 | bwd_inner_microstep: 272.92 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 23:08:02,602] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.30 | bwd_microstep: 272.48 | bwd_inner_microstep: 272.46 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 23:08:03,079] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.90 | bwd_microstep: 272.50 | bwd_inner_microstep: 272.49 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 23:08:03,646] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.31 | optimizer_step: 16.39 +[2025-05-01 23:08:03,647] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.31 | bwd_microstep: 339.33 | bwd_inner_microstep: 272.12 | bwd_allreduce_microstep: 67.17 | step_microstep: 23.83 +[2025-05-01 23:08:03,648] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2693.58 | bwd: 3959.19 | bwd_inner: 3891.34 | bwd_allreduce: 67.42 | step: 25.05 + 4%|▍ | 338/8720 [52:37<16:47:00, 7.21s/it] {'loss': 1.0625, 'grad_norm': 3.6937317848205566, 'learning_rate': 9.99800793852394e-06, 'epoch': 0.39} + 4%|▍ | 338/8720 [52:37<16:47:00, 7.21s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 366 +[2025-05-01 23:08:03,875] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 75.60 | bwd_microstep: 132.60 | bwd_inner_microstep: 132.40 | bwd_allreduce_microstep: 0.08 | step_microstep: 0.14 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1898 +[2025-05-01 23:08:04,355] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.96 | bwd_microstep: 275.40 | bwd_inner_microstep: 275.38 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-01 23:08:04,833] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.65 | bwd_microstep: 273.50 | bwd_inner_microstep: 273.48 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1887 +[2025-05-01 23:08:05,313] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.94 | bwd_microstep: 274.89 | bwd_inner_microstep: 274.87 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-01 23:08:05,796] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.61 | bwd_microstep: 273.72 | bwd_inner_microstep: 273.70 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-01 23:08:06,275] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.79 | bwd_microstep: 273.34 | bwd_inner_microstep: 273.32 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-01 23:08:06,752] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.62 | bwd_microstep: 273.13 | bwd_inner_microstep: 273.11 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-01 23:08:07,229] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.18 | bwd_microstep: 272.76 | bwd_inner_microstep: 272.74 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 23:08:07,707] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.35 | bwd_microstep: 272.69 | bwd_inner_microstep: 272.67 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-01 23:08:08,185] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.49 | bwd_microstep: 273.05 | bwd_inner_microstep: 273.03 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-01 23:08:08,662] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.59 | bwd_microstep: 272.90 | bwd_inner_microstep: 272.89 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-01 23:08:09,142] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.98 | bwd_microstep: 272.90 | bwd_inner_microstep: 272.88 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1090 +[2025-05-01 23:08:09,434] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 115.96 | bwd_microstep: 161.18 | bwd_inner_microstep: 161.16 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 23:08:09,909] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.14 | bwd_microstep: 271.80 | bwd_inner_microstep: 271.78 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 829 +[2025-05-01 23:08:10,150] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.28 | bwd_microstep: 130.29 | bwd_inner_microstep: 130.02 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1888 +[2025-05-01 23:08:10,732] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.28 | optimizer_step: 16.55 +[2025-05-01 23:08:10,732] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.74 | bwd_microstep: 352.38 | bwd_inner_microstep: 275.76 | bwd_allreduce_microstep: 76.58 | step_microstep: 23.74 +[2025-05-01 23:08:10,733] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2739.60 | bwd: 4056.55 | bwd_inner: 3979.28 | bwd_allreduce: 76.84 | step: 24.70 + 4%|▍ | 339/8720 [52:44<16:41:43, 7.17s/it] {'loss': 1.4698, 'grad_norm': 4.679149627685547, 'learning_rate': 9.997955174564498e-06, 'epoch': 0.39} + 4%|▍ | 339/8720 [52:44<16:41:43, 7.17s/it]dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 924 +[2025-05-01 23:08:11,001] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 103.42 | bwd_microstep: 145.88 | bwd_inner_microstep: 145.84 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.09 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1405 +[2025-05-01 23:08:11,371] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 144.99 | bwd_microstep: 210.80 | bwd_inner_microstep: 210.75 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 366 +[2025-05-01 23:08:11,585] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 78.02 | bwd_microstep: 120.49 | bwd_inner_microstep: 120.34 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1893 +[2025-05-01 23:08:12,066] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.26 | bwd_microstep: 275.69 | bwd_inner_microstep: 275.68 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-01 23:08:12,546] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.71 | bwd_microstep: 274.95 | bwd_inner_microstep: 274.93 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-01 23:08:13,028] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.12 | bwd_microstep: 274.95 | bwd_inner_microstep: 274.93 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-01 23:08:13,510] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.21 | bwd_microstep: 273.80 | bwd_inner_microstep: 273.78 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-01 23:08:13,992] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.50 | bwd_microstep: 273.77 | bwd_inner_microstep: 273.75 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-01 23:08:14,479] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.91 | bwd_microstep: 274.09 | bwd_inner_microstep: 274.07 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-01 23:08:14,963] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.69 | bwd_microstep: 273.89 | bwd_inner_microstep: 273.88 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 23:08:15,444] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.48 | bwd_microstep: 273.02 | bwd_inner_microstep: 273.00 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 23:08:15,925] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.42 | bwd_microstep: 272.92 | bwd_inner_microstep: 272.91 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-01 23:08:16,407] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.33 | bwd_microstep: 273.33 | bwd_inner_microstep: 273.32 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 23:08:16,886] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.93 | bwd_microstep: 273.01 | bwd_inner_microstep: 272.99 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 23:08:17,364] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.37 | bwd_microstep: 271.60 | bwd_inner_microstep: 271.58 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1430 +[2025-05-01 23:08:17,841] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.22 | optimizer_step: 16.38 +[2025-05-01 23:08:17,842] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 145.11 | bwd_microstep: 291.77 | bwd_inner_microstep: 215.20 | bwd_allreduce_microstep: 76.47 | step_microstep: 24.07 +[2025-05-01 23:08:17,843] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2746.12 | bwd: 4054.02 | bwd_inner: 3977.01 | bwd_allreduce: 76.62 | step: 24.98 + 4%|▍ | 340/8720 [52:51<16:39:05, 7.15s/it] {'loss': 1.46, 'grad_norm': 2.8100905418395996, 'learning_rate': 9.997901721069391e-06, 'epoch': 0.39} + 4%|▍ | 340/8720 [52:51<16:39:05, 7.15s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1908 +[2025-05-01 23:08:18,332] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.48 | bwd_microstep: 276.10 | bwd_inner_microstep: 276.08 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-01 23:08:18,811] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.30 | bwd_microstep: 274.00 | bwd_inner_microstep: 273.99 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-01 23:08:19,289] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.40 | bwd_microstep: 274.01 | bwd_inner_microstep: 273.99 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 837 +[2025-05-01 23:08:19,522] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 91.39 | bwd_microstep: 126.57 | bwd_inner_microstep: 126.41 | bwd_allreduce_microstep: 0.08 | step_microstep: 0.15 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-01 23:08:20,002] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.09 | bwd_microstep: 273.46 | bwd_inner_microstep: 273.44 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-01 23:08:20,481] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.81 | bwd_microstep: 273.24 | bwd_inner_microstep: 273.22 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:08:20,960] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.52 | bwd_microstep: 273.30 | bwd_inner_microstep: 273.28 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 23:08:21,438] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.91 | bwd_microstep: 273.31 | bwd_inner_microstep: 273.29 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 23:08:21,916] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.69 | bwd_microstep: 272.13 | bwd_inner_microstep: 272.11 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 23:08:22,392] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.34 | bwd_microstep: 271.91 | bwd_inner_microstep: 271.89 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 23:08:22,869] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.80 | bwd_microstep: 272.02 | bwd_inner_microstep: 272.00 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 23:08:23,344] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.02 | bwd_microstep: 271.71 | bwd_inner_microstep: 271.69 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.16 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 23:08:23,822] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.63 | bwd_microstep: 271.63 | bwd_inner_microstep: 271.62 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 23:08:24,300] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.95 | bwd_microstep: 271.80 | bwd_inner_microstep: 271.78 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 23:08:24,779] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.41 | bwd_microstep: 271.72 | bwd_inner_microstep: 271.70 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1891 +[2025-05-01 23:08:25,368] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.24 | optimizer_step: 16.27 +[2025-05-01 23:08:25,368] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.66 | bwd_microstep: 355.72 | bwd_inner_microstep: 275.90 | bwd_allreduce_microstep: 79.77 | step_microstep: 24.01 +[2025-05-01 23:08:25,370] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2933.09 | bwd: 4302.66 | bwd_inner: 4222.40 | bwd_allreduce: 79.95 | step: 24.98 + 4%|▍ | 341/8720 [52:59<16:54:37, 7.27s/it] {'loss': 1.1754, 'grad_norm': 5.342874050140381, 'learning_rate': 9.997847578045991e-06, 'epoch': 0.39} + 4%|▍ | 341/8720 [52:59<16:54:37, 7.27s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1948 +[2025-05-01 23:08:25,880] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 198.48 | bwd_microstep: 288.60 | bwd_inner_microstep: 288.58 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1916 +[2025-05-01 23:08:26,369] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 193.87 | bwd_microstep: 276.55 | bwd_inner_microstep: 276.53 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1906 +[2025-05-01 23:08:26,853] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.04 | bwd_microstep: 276.91 | bwd_inner_microstep: 276.89 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 875 +[2025-05-01 23:08:27,105] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 98.90 | bwd_microstep: 134.95 | bwd_inner_microstep: 134.89 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.10 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 345 +[2025-05-01 23:08:27,334] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 85.18 | bwd_microstep: 128.16 | bwd_inner_microstep: 127.86 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-01 23:08:27,815] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.51 | bwd_microstep: 273.92 | bwd_inner_microstep: 273.90 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-01 23:08:28,297] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.92 | bwd_microstep: 274.00 | bwd_inner_microstep: 273.98 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-01 23:08:28,779] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.07 | bwd_microstep: 272.83 | bwd_inner_microstep: 272.81 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-01 23:08:29,259] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.88 | bwd_microstep: 273.03 | bwd_inner_microstep: 273.01 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 23:08:29,738] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.71 | bwd_microstep: 272.60 | bwd_inner_microstep: 272.58 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 23:08:30,217] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.21 | bwd_microstep: 272.43 | bwd_inner_microstep: 272.41 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 23:08:30,699] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.09 | bwd_microstep: 272.49 | bwd_inner_microstep: 272.47 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 23:08:31,177] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.69 | bwd_microstep: 271.21 | bwd_inner_microstep: 271.19 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 23:08:31,657] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.36 | bwd_microstep: 271.60 | bwd_inner_microstep: 271.58 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-01 23:08:32,136] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.39 | bwd_microstep: 271.14 | bwd_inner_microstep: 271.12 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2067 +[2025-05-01 23:08:32,763] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.28 | optimizer_step: 16.30 +[2025-05-01 23:08:32,764] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 204.54 | bwd_microstep: 381.25 | bwd_inner_microstep: 304.04 | bwd_allreduce_microstep: 77.14 | step_microstep: 24.15 +[2025-05-01 23:08:32,765] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2860.48 | bwd: 4211.71 | bwd_inner: 4133.93 | bwd_allreduce: 77.38 | step: 25.13 + 4%|▍ | 342/8720 [53:06<16:59:56, 7.30s/it] {'loss': 1.1717, 'grad_norm': 3.2896199226379395, 'learning_rate': 9.997792745501768e-06, 'epoch': 0.39} + 4%|▍ | 342/8720 [53:06<16:59:56, 7.30s/it]dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 907 +[2025-05-01 23:08:33,035] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 103.87 | bwd_microstep: 144.63 | bwd_inner_microstep: 144.51 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.08 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 388 +[2025-05-01 23:08:33,243] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 72.60 | bwd_microstep: 120.91 | bwd_inner_microstep: 120.78 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1910 +[2025-05-01 23:08:33,723] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.25 | bwd_microstep: 276.34 | bwd_inner_microstep: 276.32 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.16 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-01 23:08:34,203] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.73 | bwd_microstep: 274.39 | bwd_inner_microstep: 274.37 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-01 23:08:34,681] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.70 | bwd_microstep: 273.88 | bwd_inner_microstep: 273.87 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1883 +[2025-05-01 23:08:35,160] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.36 | bwd_microstep: 274.23 | bwd_inner_microstep: 274.21 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-01 23:08:35,639] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.10 | bwd_microstep: 273.58 | bwd_inner_microstep: 273.56 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.13 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-01 23:08:36,120] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.84 | bwd_microstep: 273.06 | bwd_inner_microstep: 273.04 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1351 +[2025-05-01 23:08:36,483] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.52 | bwd_microstep: 206.52 | bwd_inner_microstep: 206.50 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 838 +[2025-05-01 23:08:36,720] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.26 | bwd_microstep: 126.82 | bwd_inner_microstep: 126.71 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 23:08:37,199] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.00 | bwd_microstep: 272.97 | bwd_inner_microstep: 272.95 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1093 +[2025-05-01 23:08:37,495] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 115.54 | bwd_microstep: 161.84 | bwd_inner_microstep: 161.62 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.17 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 23:08:37,975] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.08 | bwd_microstep: 272.84 | bwd_inner_microstep: 272.82 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 23:08:38,454] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.30 | bwd_microstep: 272.02 | bwd_inner_microstep: 272.00 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 23:08:38,932] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.09 | bwd_microstep: 271.72 | bwd_inner_microstep: 271.70 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 23:08:39,514] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.31 | optimizer_step: 16.30 +[2025-05-01 23:08:39,515] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.33 | bwd_microstep: 348.78 | bwd_inner_microstep: 272.37 | bwd_allreduce_microstep: 76.35 | step_microstep: 24.10 +[2025-05-01 23:08:39,516] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2605.25 | bwd: 3844.61 | bwd_inner: 3767.40 | bwd_allreduce: 76.72 | step: 25.36 + 4%|▍ | 343/8720 [53:13<16:36:38, 7.14s/it] {'loss': 1.4354, 'grad_norm': 4.432437896728516, 'learning_rate': 9.997737223444288e-06, 'epoch': 0.39} + 4%|▍ | 343/8720 [53:13<16:36:38, 7.14s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2067 +[2025-05-01 23:08:40,043] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 201.83 | bwd_microstep: 302.39 | bwd_inner_microstep: 302.37 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 434 +[2025-05-01 23:08:40,266] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 89.65 | bwd_microstep: 116.23 | bwd_inner_microstep: 116.10 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1905 +[2025-05-01 23:08:40,746] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.11 | bwd_microstep: 276.30 | bwd_inner_microstep: 276.29 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-01 23:08:41,227] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.15 | bwd_microstep: 275.01 | bwd_inner_microstep: 275.00 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1372 +[2025-05-01 23:08:41,595] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.88 | bwd_microstep: 207.76 | bwd_inner_microstep: 207.66 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 857 +[2025-05-01 23:08:41,843] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 96.06 | bwd_microstep: 132.86 | bwd_inner_microstep: 132.84 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-01 23:08:42,324] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.28 | bwd_microstep: 273.69 | bwd_inner_microstep: 273.67 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-01 23:08:42,805] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.62 | bwd_microstep: 272.83 | bwd_inner_microstep: 272.81 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-01 23:08:43,285] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.93 | bwd_microstep: 273.26 | bwd_inner_microstep: 273.24 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.21 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-01 23:08:43,766] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.74 | bwd_microstep: 272.80 | bwd_inner_microstep: 272.78 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 23:08:44,245] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.98 | bwd_microstep: 272.41 | bwd_inner_microstep: 272.39 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-01 23:08:44,727] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.99 | bwd_microstep: 272.77 | bwd_inner_microstep: 272.75 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 23:08:45,208] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.01 | bwd_microstep: 272.73 | bwd_inner_microstep: 272.71 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 23:08:45,687] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.58 | bwd_microstep: 271.33 | bwd_inner_microstep: 271.31 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 23:08:46,169] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.29 | bwd_microstep: 271.06 | bwd_inner_microstep: 271.04 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 23:08:46,750] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.28 | optimizer_step: 16.33 +[2025-05-01 23:08:46,750] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.67 | bwd_microstep: 349.07 | bwd_inner_microstep: 271.67 | bwd_allreduce_microstep: 77.34 | step_microstep: 24.12 +[2025-05-01 23:08:46,752] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2794.39 | bwd: 4112.57 | bwd_inner: 4034.68 | bwd_allreduce: 77.51 | step: 25.51 + 4%|▍ | 344/8720 [53:20<16:40:35, 7.17s/it] {'loss': 1.0352, 'grad_norm': 2.6252777576446533, 'learning_rate': 9.99768101188121e-06, 'epoch': 0.39} + 4%|▍ | 344/8720 [53:20<16:40:35, 7.17s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1946 +[2025-05-01 23:08:47,261] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 197.32 | bwd_microstep: 288.74 | bwd_inner_microstep: 288.72 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1923 +[2025-05-01 23:08:47,761] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 196.58 | bwd_microstep: 287.51 | bwd_inner_microstep: 287.50 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1896 +[2025-05-01 23:08:48,242] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.21 | bwd_microstep: 275.15 | bwd_inner_microstep: 275.14 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1888 +[2025-05-01 23:08:48,724] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.98 | bwd_microstep: 274.97 | bwd_inner_microstep: 274.95 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1367 +[2025-05-01 23:08:49,087] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.09 | bwd_microstep: 207.64 | bwd_inner_microstep: 207.62 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-01 23:08:49,567] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.11 | bwd_microstep: 273.68 | bwd_inner_microstep: 273.66 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-01 23:08:50,045] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.22 | bwd_microstep: 273.02 | bwd_inner_microstep: 273.01 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.14 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:08:50,522] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.48 | bwd_microstep: 272.68 | bwd_inner_microstep: 272.66 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-01 23:08:51,000] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.54 | bwd_microstep: 273.24 | bwd_inner_microstep: 273.22 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 23:08:51,478] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.08 | bwd_microstep: 272.62 | bwd_inner_microstep: 272.60 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 23:08:51,953] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.21 | bwd_microstep: 272.23 | bwd_inner_microstep: 272.22 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 23:08:52,429] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.51 | bwd_microstep: 271.58 | bwd_inner_microstep: 271.56 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 23:08:52,905] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.60 | bwd_microstep: 271.65 | bwd_inner_microstep: 271.63 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 23:08:53,381] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.66 | bwd_microstep: 272.50 | bwd_inner_microstep: 272.48 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1094 +[2025-05-01 23:08:53,671] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 114.85 | bwd_microstep: 161.47 | bwd_inner_microstep: 161.27 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.09 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 828 +[2025-05-01 23:08:53,997] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.27 | optimizer_step: 16.31 +[2025-05-01 23:08:53,998] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 92.27 | bwd_microstep: 196.40 | bwd_inner_microstep: 130.34 | bwd_allreduce_microstep: 65.90 | step_microstep: 24.08 +[2025-05-01 23:08:53,999] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2818.42 | bwd: 4145.09 | bwd_inner: 4078.64 | bwd_allreduce: 66.11 | step: 24.97 + 4%|▍ | 345/8720 [53:27<16:43:54, 7.19s/it] {'loss': 1.2127, 'grad_norm': 4.7909111976623535, 'learning_rate': 9.997624110820288e-06, 'epoch': 0.4} + 4%|▍ | 345/8720 [53:27<16:43:54, 7.19s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1961 +[2025-05-01 23:08:54,511] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 197.32 | bwd_microstep: 289.69 | bwd_inner_microstep: 289.68 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1935 +[2025-05-01 23:08:55,011] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.95 | bwd_microstep: 288.47 | bwd_inner_microstep: 288.45 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 899 +[2025-05-01 23:08:55,274] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 103.36 | bwd_microstep: 143.96 | bwd_inner_microstep: 143.76 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1922 +[2025-05-01 23:08:55,771] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 194.94 | bwd_microstep: 287.17 | bwd_inner_microstep: 287.15 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1890 +[2025-05-01 23:08:56,252] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.01 | bwd_microstep: 274.69 | bwd_inner_microstep: 274.67 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-01 23:08:56,730] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.95 | bwd_microstep: 273.64 | bwd_inner_microstep: 273.62 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-01 23:08:57,209] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.49 | bwd_microstep: 273.20 | bwd_inner_microstep: 273.18 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-01 23:08:57,688] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.71 | bwd_microstep: 273.60 | bwd_inner_microstep: 273.58 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 327 +[2025-05-01 23:08:57,886] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 67.95 | bwd_microstep: 116.14 | bwd_inner_microstep: 116.00 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 837 +[2025-05-01 23:08:58,119] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 91.27 | bwd_microstep: 126.90 | bwd_inner_microstep: 126.88 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:08:58,594] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.90 | bwd_microstep: 272.46 | bwd_inner_microstep: 272.44 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:08:59,071] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.53 | bwd_microstep: 272.61 | bwd_inner_microstep: 272.59 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 23:08:59,548] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.14 | bwd_microstep: 272.44 | bwd_inner_microstep: 272.42 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 23:09:00,023] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.98 | bwd_microstep: 271.56 | bwd_inner_microstep: 271.54 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 23:09:00,498] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.30 | bwd_microstep: 271.28 | bwd_inner_microstep: 271.26 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1904 +[2025-05-01 23:09:01,070] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.04 | optimizer_gradients: 2.65 | optimizer_step: 17.14 +[2025-05-01 23:09:01,071] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.30 | bwd_microstep: 344.08 | bwd_inner_microstep: 276.68 | bwd_allreduce_microstep: 67.30 | step_microstep: 24.65 +[2025-05-01 23:09:01,072] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2740.84 | bwd: 4051.91 | bwd_inner: 3983.95 | bwd_allreduce: 67.48 | step: 25.44 + 4%|▍ | 346/8720 [53:34<16:38:37, 7.16s/it] {'loss': 0.9841, 'grad_norm': 2.854503631591797, 'learning_rate': 9.997566520269375e-06, 'epoch': 0.4} + 4%|▍ | 346/8720 [53:34<16:38:37, 7.16s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1897 +[2025-05-01 23:09:01,556] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.03 | bwd_microstep: 274.72 | bwd_inner_microstep: 274.71 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-01 23:09:02,034] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.80 | bwd_microstep: 274.10 | bwd_inner_microstep: 274.08 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 850 +[2025-05-01 23:09:02,276] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.55 | bwd_microstep: 133.14 | bwd_inner_microstep: 132.94 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-01 23:09:02,754] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.96 | bwd_microstep: 274.04 | bwd_inner_microstep: 274.03 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.21 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-01 23:09:03,235] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.69 | bwd_microstep: 273.38 | bwd_inner_microstep: 273.36 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-01 23:09:03,716] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.52 | bwd_microstep: 273.24 | bwd_inner_microstep: 273.22 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.15 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-01 23:09:04,197] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.78 | bwd_microstep: 273.08 | bwd_inner_microstep: 273.06 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 333 +[2025-05-01 23:09:04,432] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 92.67 | bwd_microstep: 124.52 | bwd_inner_microstep: 124.34 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-01 23:09:04,911] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.60 | bwd_microstep: 272.53 | bwd_inner_microstep: 272.51 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 844 +[2025-05-01 23:09:05,165] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 101.95 | bwd_microstep: 131.48 | bwd_inner_microstep: 131.36 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.11 +dynamic ViT batch size: 6, images per sample: 6.0, dynamic token length: 1603 +[2025-05-01 23:09:05,594] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 163.11 | bwd_microstep: 243.39 | bwd_inner_microstep: 243.38 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 23:09:06,071] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.52 | bwd_microstep: 271.37 | bwd_inner_microstep: 271.36 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.13 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 23:09:06,550] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.49 | bwd_microstep: 270.97 | bwd_inner_microstep: 270.95 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 23:09:07,030] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.56 | bwd_microstep: 270.98 | bwd_inner_microstep: 270.96 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 827 +[2025-05-01 23:09:07,295] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 108.84 | bwd_microstep: 129.35 | bwd_inner_microstep: 129.10 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1939 +[2025-05-01 23:09:07,902] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.66 | optimizer_step: 17.70 +[2025-05-01 23:09:07,903] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.29 | bwd_microstep: 368.03 | bwd_inner_microstep: 289.54 | bwd_allreduce_microstep: 78.44 | step_microstep: 26.44 +[2025-05-01 23:09:07,904] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2636.97 | bwd: 3858.43 | bwd_inner: 3778.94 | bwd_allreduce: 78.90 | step: 27.96 + 4%|▍ | 347/8720 [53:41<16:25:04, 7.06s/it] {'loss': 1.322, 'grad_norm': 4.077744960784912, 'learning_rate': 9.997508240236415e-06, 'epoch': 0.4} + 4%|▍ | 347/8720 [53:41<16:25:04, 7.06s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2001 +[2025-05-01 23:09:08,420] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 197.49 | bwd_microstep: 294.41 | bwd_inner_microstep: 294.39 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.21 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-01 23:09:08,900] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.26 | bwd_microstep: 273.37 | bwd_inner_microstep: 273.35 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-01 23:09:09,380] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.55 | bwd_microstep: 273.17 | bwd_inner_microstep: 273.15 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 6, images per sample: 6.0, dynamic token length: 1618 +[2025-05-01 23:09:09,814] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 166.60 | bwd_microstep: 246.31 | bwd_inner_microstep: 246.29 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 23:09:10,298] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.71 | bwd_microstep: 272.66 | bwd_inner_microstep: 272.65 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-01 23:09:10,779] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.21 | bwd_microstep: 273.05 | bwd_inner_microstep: 273.03 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 23:09:11,260] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.07 | bwd_microstep: 272.58 | bwd_inner_microstep: 272.56 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-01 23:09:11,742] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.25 | bwd_microstep: 273.05 | bwd_inner_microstep: 273.04 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 23:09:12,225] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.60 | bwd_microstep: 272.38 | bwd_inner_microstep: 272.36 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 23:09:12,706] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.82 | bwd_microstep: 272.80 | bwd_inner_microstep: 272.78 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 23:09:13,187] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.15 | bwd_microstep: 272.21 | bwd_inner_microstep: 272.20 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 23:09:13,667] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.87 | bwd_microstep: 272.25 | bwd_inner_microstep: 272.24 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 23:09:14,144] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.93 | bwd_microstep: 271.40 | bwd_inner_microstep: 271.38 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-01 23:09:14,623] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.55 | bwd_microstep: 271.17 | bwd_inner_microstep: 271.16 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 23:09:15,101] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.16 | bwd_microstep: 271.51 | bwd_inner_microstep: 271.50 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 23:09:15,683] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.45 | optimizer_step: 17.28 +[2025-05-01 23:09:15,684] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.71 | bwd_microstep: 349.01 | bwd_inner_microstep: 271.71 | bwd_allreduce_microstep: 77.26 | step_microstep: 25.65 +[2025-05-01 23:09:15,685] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 3008.53 | bwd: 4431.37 | bwd_inner: 4353.79 | bwd_allreduce: 77.34 | step: 26.66 + 4%|▍ | 348/8720 [53:49<16:55:13, 7.28s/it] {'loss': 1.3066, 'grad_norm': 4.7347636222839355, 'learning_rate': 9.997449270729449e-06, 'epoch': 0.4} + 4%|▍ | 348/8720 [53:49<16:55:13, 7.28s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1988 +[2025-05-01 23:09:16,201] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 197.71 | bwd_microstep: 293.07 | bwd_inner_microstep: 293.05 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1931 +[2025-05-01 23:09:16,704] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 196.08 | bwd_microstep: 288.27 | bwd_inner_microstep: 288.25 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1897 +[2025-05-01 23:09:17,186] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.05 | bwd_microstep: 276.05 | bwd_inner_microstep: 276.04 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1895 +[2025-05-01 23:09:17,668] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.61 | bwd_microstep: 275.29 | bwd_inner_microstep: 275.27 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.15 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 337 +[2025-05-01 23:09:17,873] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 67.99 | bwd_microstep: 124.36 | bwd_inner_microstep: 124.21 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1886 +[2025-05-01 23:09:18,351] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.66 | bwd_microstep: 274.42 | bwd_inner_microstep: 274.40 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-01 23:09:18,832] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.88 | bwd_microstep: 274.14 | bwd_inner_microstep: 274.12 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-01 23:09:19,308] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.52 | bwd_microstep: 272.54 | bwd_inner_microstep: 272.52 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 324 +[2025-05-01 23:09:19,510] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 74.23 | bwd_microstep: 114.55 | bwd_inner_microstep: 114.21 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 23:09:19,985] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.08 | bwd_microstep: 272.25 | bwd_inner_microstep: 272.23 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 23:09:20,462] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.00 | bwd_microstep: 272.47 | bwd_inner_microstep: 272.45 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 23:09:20,936] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.99 | bwd_microstep: 271.58 | bwd_inner_microstep: 271.56 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 23:09:21,413] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.77 | bwd_microstep: 271.51 | bwd_inner_microstep: 271.49 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 23:09:21,887] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.85 | bwd_microstep: 271.44 | bwd_inner_microstep: 271.43 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 23:09:22,362] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.61 | bwd_microstep: 271.23 | bwd_inner_microstep: 271.22 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1941 +[2025-05-01 23:09:22,954] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.43 | optimizer_step: 16.77 +[2025-05-01 23:09:22,955] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 196.00 | bwd_microstep: 356.52 | bwd_inner_microstep: 289.41 | bwd_allreduce_microstep: 67.07 | step_microstep: 24.27 +[2025-05-01 23:09:22,956] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2805.76 | bwd: 4179.72 | bwd_inner: 4111.96 | bwd_allreduce: 67.33 | step: 25.30 + 4%|▍ | 349/8720 [53:56<16:54:47, 7.27s/it] {'loss': 1.0408, 'grad_norm': 3.2775096893310547, 'learning_rate': 9.997389611756612e-06, 'epoch': 0.4} + 4%|▍ | 349/8720 [53:56<16:54:47, 7.27s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1930 +[2025-05-01 23:09:23,462] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 197.55 | bwd_microstep: 287.28 | bwd_inner_microstep: 287.26 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1405 +[2025-05-01 23:09:23,832] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 143.18 | bwd_microstep: 210.90 | bwd_inner_microstep: 210.71 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.10 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 362 +[2025-05-01 23:09:24,042] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 71.84 | bwd_microstep: 124.23 | bwd_inner_microstep: 123.99 | bwd_allreduce_microstep: 0.09 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-01 23:09:24,522] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.29 | bwd_microstep: 273.47 | bwd_inner_microstep: 273.45 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1892 +[2025-05-01 23:09:25,005] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.21 | bwd_microstep: 274.83 | bwd_inner_microstep: 274.81 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-01 23:09:25,483] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.74 | bwd_microstep: 273.46 | bwd_inner_microstep: 273.44 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-01 23:09:25,961] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.72 | bwd_microstep: 272.95 | bwd_inner_microstep: 272.93 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 842 +[2025-05-01 23:09:26,208] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 98.30 | bwd_microstep: 131.91 | bwd_inner_microstep: 131.65 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-01 23:09:26,687] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.12 | bwd_microstep: 272.89 | bwd_inner_microstep: 272.87 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 23:09:27,167] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.21 | bwd_microstep: 272.46 | bwd_inner_microstep: 272.44 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.14 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 23:09:27,646] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.29 | bwd_microstep: 272.57 | bwd_inner_microstep: 272.55 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:09:28,124] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.22 | bwd_microstep: 272.55 | bwd_inner_microstep: 272.53 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 23:09:28,612] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.14 | bwd_microstep: 272.54 | bwd_inner_microstep: 272.52 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 23:09:29,096] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.49 | bwd_microstep: 272.86 | bwd_inner_microstep: 272.84 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 835 +[2025-05-01 23:09:29,343] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 96.35 | bwd_microstep: 131.77 | bwd_inner_microstep: 131.71 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 23:09:29,922] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.64 | optimizer_step: 17.08 +[2025-05-01 23:09:29,923] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.00 | bwd_microstep: 348.78 | bwd_inner_microstep: 271.62 | bwd_allreduce_microstep: 77.10 | step_microstep: 25.33 +[2025-05-01 23:09:29,924] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2683.31 | bwd: 3965.51 | bwd_inner: 3887.46 | bwd_allreduce: 77.45 | step: 26.42 + 4%|▍ | 350/8720 [54:03<16:41:54, 7.18s/it] {'loss': 0.9931, 'grad_norm': 6.0516357421875, 'learning_rate': 9.997329263326134e-06, 'epoch': 0.4} + 4%|▍ | 350/8720 [54:03<16:41:54, 7.18s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 383 +[2025-05-01 23:09:30,151] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 85.72 | bwd_microstep: 120.13 | bwd_inner_microstep: 119.97 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1124 +[2025-05-01 23:09:30,449] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 118.58 | bwd_microstep: 163.65 | bwd_inner_microstep: 163.45 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1889 +[2025-05-01 23:09:30,929] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.94 | bwd_microstep: 274.76 | bwd_inner_microstep: 274.74 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-01 23:09:31,408] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.74 | bwd_microstep: 274.04 | bwd_inner_microstep: 274.02 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-01 23:09:31,885] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.46 | bwd_microstep: 273.35 | bwd_inner_microstep: 273.33 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1356 +[2025-05-01 23:09:32,247] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.70 | bwd_microstep: 206.62 | bwd_inner_microstep: 206.47 | bwd_allreduce_microstep: 0.04 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-01 23:09:32,727] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.79 | bwd_microstep: 273.75 | bwd_inner_microstep: 273.73 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-01 23:09:33,209] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.76 | bwd_microstep: 272.93 | bwd_inner_microstep: 272.92 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-01 23:09:33,690] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.17 | bwd_microstep: 273.10 | bwd_inner_microstep: 273.08 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 23:09:34,172] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.34 | bwd_microstep: 272.58 | bwd_inner_microstep: 272.56 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-01 23:09:34,653] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.47 | bwd_microstep: 272.82 | bwd_inner_microstep: 272.80 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-01 23:09:35,136] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.61 | bwd_microstep: 272.87 | bwd_inner_microstep: 272.85 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.13 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-01 23:09:35,620] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.72 | bwd_microstep: 272.74 | bwd_inner_microstep: 272.72 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 23:09:36,108] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.53 | bwd_microstep: 272.73 | bwd_inner_microstep: 272.72 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 23:09:36,586] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.93 | bwd_microstep: 273.10 | bwd_inner_microstep: 273.09 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 23:09:37,157] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.04 | optimizer_gradients: 2.40 | optimizer_step: 16.58 +[2025-05-01 23:09:37,158] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.19 | bwd_microstep: 342.58 | bwd_inner_microstep: 271.77 | bwd_allreduce_microstep: 70.76 | step_microstep: 23.71 +[2025-05-01 23:09:37,159] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2799.31 | bwd: 4111.78 | bwd_inner: 4040.26 | bwd_allreduce: 71.10 | step: 24.81 + 4%|▍ | 351/8720 [54:10<16:43:55, 7.20s/it] {'loss': 2.0396, 'grad_norm': 5.236227512359619, 'learning_rate': 9.997268225446344e-06, 'epoch': 0.4} + 4%|▍ | 351/8720 [54:10<16:43:55, 7.20s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1910 +[2025-05-01 23:09:37,643] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.58 | bwd_microstep: 275.66 | bwd_inner_microstep: 275.64 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1941 +[2025-05-01 23:09:38,143] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.50 | bwd_microstep: 289.17 | bwd_inner_microstep: 289.15 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1892 +[2025-05-01 23:09:38,623] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.14 | bwd_microstep: 275.16 | bwd_inner_microstep: 275.14 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-01 23:09:39,102] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.12 | bwd_microstep: 273.87 | bwd_inner_microstep: 273.85 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1887 +[2025-05-01 23:09:39,583] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.00 | bwd_microstep: 275.33 | bwd_inner_microstep: 275.32 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-01 23:09:40,060] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.56 | bwd_microstep: 273.12 | bwd_inner_microstep: 273.10 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-01 23:09:40,538] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.35 | bwd_microstep: 273.52 | bwd_inner_microstep: 273.51 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 333 +[2025-05-01 23:09:40,736] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 67.30 | bwd_microstep: 116.74 | bwd_inner_microstep: 116.60 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 839 +[2025-05-01 23:09:40,968] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 91.18 | bwd_microstep: 127.00 | bwd_inner_microstep: 126.84 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 23:09:41,445] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.62 | bwd_microstep: 272.45 | bwd_inner_microstep: 272.44 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 23:09:41,921] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.21 | bwd_microstep: 272.34 | bwd_inner_microstep: 272.32 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 23:09:42,401] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.11 | bwd_microstep: 272.36 | bwd_inner_microstep: 272.34 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 23:09:42,875] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.39 | bwd_microstep: 271.42 | bwd_inner_microstep: 271.40 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-01 23:09:43,350] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.94 | bwd_microstep: 271.18 | bwd_inner_microstep: 271.17 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 23:09:43,826] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.80 | bwd_microstep: 271.33 | bwd_inner_microstep: 271.31 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1894 +[2025-05-01 23:09:44,399] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.61 | optimizer_step: 16.92 +[2025-05-01 23:09:44,400] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.83 | bwd_microstep: 343.04 | bwd_inner_microstep: 275.81 | bwd_allreduce_microstep: 67.19 | step_microstep: 24.50 +[2025-05-01 23:09:44,401] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2809.37 | bwd: 4153.73 | bwd_inner: 4085.97 | bwd_allreduce: 67.43 | step: 25.32 + 4%|▍ | 352/8720 [54:18<16:45:39, 7.21s/it] {'loss': 1.2329, 'grad_norm': 3.32660174369812, 'learning_rate': 9.99720649812566e-06, 'epoch': 0.4} + 4%|▍ | 352/8720 [54:18<16:45:39, 7.21s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1893 +[2025-05-01 23:09:44,884] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.83 | bwd_microstep: 274.46 | bwd_inner_microstep: 274.44 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1894 +[2025-05-01 23:09:45,364] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.21 | bwd_microstep: 275.21 | bwd_inner_microstep: 275.19 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-01 23:09:45,842] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.85 | bwd_microstep: 273.98 | bwd_inner_microstep: 273.96 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-01 23:09:46,319] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.62 | bwd_microstep: 273.55 | bwd_inner_microstep: 273.54 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-01 23:09:46,798] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.53 | bwd_microstep: 272.92 | bwd_inner_microstep: 272.90 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.17 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 23:09:47,279] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.01 | bwd_microstep: 272.64 | bwd_inner_microstep: 272.62 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 23:09:47,757] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.42 | bwd_microstep: 272.50 | bwd_inner_microstep: 272.49 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-01 23:09:48,236] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.78 | bwd_microstep: 272.71 | bwd_inner_microstep: 272.70 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 23:09:48,716] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.83 | bwd_microstep: 272.67 | bwd_inner_microstep: 272.65 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.12 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 324 +[2025-05-01 23:09:48,942] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 90.15 | bwd_microstep: 117.58 | bwd_inner_microstep: 117.27 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 23:09:49,419] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.77 | bwd_microstep: 271.40 | bwd_inner_microstep: 271.39 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 23:09:49,897] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.34 | bwd_microstep: 272.28 | bwd_inner_microstep: 272.26 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 23:09:50,375] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.92 | bwd_microstep: 271.28 | bwd_inner_microstep: 271.26 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 23:09:50,854] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.31 | bwd_microstep: 271.38 | bwd_inner_microstep: 271.36 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 316 +[2025-05-01 23:09:51,075] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 86.79 | bwd_microstep: 116.73 | bwd_inner_microstep: 116.57 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-01 23:09:51,657] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.45 | optimizer_step: 16.79 +[2025-05-01 23:09:51,657] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.77 | bwd_microstep: 351.90 | bwd_inner_microstep: 271.59 | bwd_allreduce_microstep: 80.26 | step_microstep: 25.17 +[2025-05-01 23:09:51,659] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2814.78 | bwd: 4133.27 | bwd_inner: 4052.30 | bwd_allreduce: 80.51 | step: 26.35 + 4%|▍ | 353/8720 [54:25<16:47:40, 7.23s/it] {'loss': 1.0982, 'grad_norm': 4.602618217468262, 'learning_rate': 9.997144081372597e-06, 'epoch': 0.4} + 4%|▍ | 353/8720 [54:25<16:47:40, 7.23s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1971 +[2025-05-01 23:09:52,177] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 200.27 | bwd_microstep: 290.92 | bwd_inner_microstep: 290.91 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1926 +[2025-05-01 23:09:52,679] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 194.90 | bwd_microstep: 287.66 | bwd_inner_microstep: 287.64 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-01 23:09:53,161] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.11 | bwd_microstep: 273.84 | bwd_inner_microstep: 273.82 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-01 23:09:53,646] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.50 | bwd_microstep: 273.60 | bwd_inner_microstep: 273.58 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-01 23:09:54,131] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.27 | bwd_microstep: 272.76 | bwd_inner_microstep: 272.75 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-01 23:09:54,612] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.80 | bwd_microstep: 273.34 | bwd_inner_microstep: 273.32 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.21 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-01 23:09:55,093] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.44 | bwd_microstep: 273.11 | bwd_inner_microstep: 273.09 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-01 23:09:55,575] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.95 | bwd_microstep: 273.23 | bwd_inner_microstep: 273.21 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-01 23:09:56,054] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.52 | bwd_microstep: 272.91 | bwd_inner_microstep: 272.89 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-01 23:09:56,534] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.38 | bwd_microstep: 272.83 | bwd_inner_microstep: 272.81 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 23:09:57,018] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.48 | bwd_microstep: 272.70 | bwd_inner_microstep: 272.68 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 23:09:57,498] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.52 | bwd_microstep: 272.40 | bwd_inner_microstep: 272.39 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 23:09:57,983] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.86 | bwd_microstep: 272.47 | bwd_inner_microstep: 272.46 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 322 +[2025-05-01 23:09:58,214] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.41 | bwd_microstep: 120.57 | bwd_inner_microstep: 120.33 | bwd_allreduce_microstep: 0.08 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 23:09:58,695] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.81 | bwd_microstep: 271.34 | bwd_inner_microstep: 271.32 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 23:09:59,274] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.46 | optimizer_step: 16.65 +[2025-05-01 23:09:59,274] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.74 | bwd_microstep: 348.41 | bwd_inner_microstep: 271.50 | bwd_allreduce_microstep: 76.85 | step_microstep: 24.59 +[2025-05-01 23:09:59,276] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2943.53 | bwd: 4322.10 | bwd_inner: 4244.74 | bwd_allreduce: 77.01 | step: 25.60 + 4%|▍ | 354/8720 [54:33<17:03:49, 7.34s/it] {'loss': 1.6809, 'grad_norm': 4.998233318328857, 'learning_rate': 9.99708097519577e-06, 'epoch': 0.41} + 4%|▍ | 354/8720 [54:33<17:03:49, 7.34s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2116 +[2025-05-01 23:09:59,816] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 205.47 | bwd_microstep: 312.17 | bwd_inner_microstep: 312.15 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1923 +[2025-05-01 23:10:00,314] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.29 | bwd_microstep: 287.43 | bwd_inner_microstep: 287.42 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 891 +[2025-05-01 23:10:00,562] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 97.74 | bwd_microstep: 135.95 | bwd_inner_microstep: 135.79 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1888 +[2025-05-01 23:10:01,042] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.03 | bwd_microstep: 274.73 | bwd_inner_microstep: 274.71 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1893 +[2025-05-01 23:10:01,524] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.87 | bwd_microstep: 275.18 | bwd_inner_microstep: 275.17 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1370 +[2025-05-01 23:10:01,890] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 142.60 | bwd_microstep: 207.60 | bwd_inner_microstep: 207.58 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-01 23:10:02,371] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.21 | bwd_microstep: 273.80 | bwd_inner_microstep: 273.78 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.14 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-01 23:10:02,857] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.76 | bwd_microstep: 272.90 | bwd_inner_microstep: 272.89 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1352 +[2025-05-01 23:10:03,225] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.36 | bwd_microstep: 206.10 | bwd_inner_microstep: 206.07 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.11 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1354 +[2025-05-01 23:10:03,595] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.56 | bwd_microstep: 206.33 | bwd_inner_microstep: 206.21 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 23:10:04,077] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.17 | bwd_microstep: 272.70 | bwd_inner_microstep: 272.68 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1343 +[2025-05-01 23:10:04,439] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 139.93 | bwd_microstep: 204.95 | bwd_inner_microstep: 204.94 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 23:10:04,917] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.77 | bwd_microstep: 271.80 | bwd_inner_microstep: 271.79 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1988 +[2025-05-01 23:10:05,430] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 198.50 | bwd_microstep: 293.49 | bwd_inner_microstep: 293.48 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1974 +[2025-05-01 23:10:05,940] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 198.84 | bwd_microstep: 291.61 | bwd_inner_microstep: 291.59 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 23:10:06,521] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.41 | optimizer_step: 16.67 +[2025-05-01 23:10:06,522] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.57 | bwd_microstep: 349.72 | bwd_inner_microstep: 271.83 | bwd_allreduce_microstep: 77.83 | step_microstep: 24.53 +[2025-05-01 23:10:06,523] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2783.29 | bwd: 4136.55 | bwd_inner: 4058.12 | bwd_allreduce: 78.04 | step: 25.74 + 4%|▍ | 355/8720 [54:40<16:59:43, 7.31s/it] {'loss': 1.261, 'grad_norm': 2.4444918632507324, 'learning_rate': 9.997017179603883e-06, 'epoch': 0.41} + 4%|▍ | 355/8720 [54:40<16:59:43, 7.31s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1921 +[2025-05-01 23:10:07,027] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 194.85 | bwd_microstep: 286.53 | bwd_inner_microstep: 286.52 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1929 +[2025-05-01 23:10:07,530] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 196.55 | bwd_microstep: 287.97 | bwd_inner_microstep: 287.95 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1894 +[2025-05-01 23:10:08,012] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.84 | bwd_microstep: 275.00 | bwd_inner_microstep: 274.98 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-01 23:10:08,494] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.88 | bwd_microstep: 273.60 | bwd_inner_microstep: 273.58 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 837 +[2025-05-01 23:10:08,741] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 99.84 | bwd_microstep: 126.34 | bwd_inner_microstep: 126.13 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 23:10:09,226] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.08 | bwd_microstep: 272.71 | bwd_inner_microstep: 272.70 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-01 23:10:09,707] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.47 | bwd_microstep: 272.61 | bwd_inner_microstep: 272.59 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 23:10:10,189] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.00 | bwd_microstep: 272.54 | bwd_inner_microstep: 272.53 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 23:10:10,669] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.35 | bwd_microstep: 272.43 | bwd_inner_microstep: 272.41 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.16 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 835 +[2025-05-01 23:10:10,916] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.94 | bwd_microstep: 135.39 | bwd_inner_microstep: 135.17 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.20 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 319 +[2025-05-01 23:10:11,145] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 92.14 | bwd_microstep: 119.57 | bwd_inner_microstep: 119.41 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-01 23:10:11,622] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.08 | bwd_microstep: 271.33 | bwd_inner_microstep: 271.32 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 23:10:12,105] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.48 | bwd_microstep: 272.39 | bwd_inner_microstep: 272.37 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 23:10:12,583] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.79 | bwd_microstep: 271.57 | bwd_inner_microstep: 271.55 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1130 +[2025-05-01 23:10:12,884] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 119.86 | bwd_microstep: 163.77 | bwd_inner_microstep: 163.59 | bwd_allreduce_microstep: 0.09 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1883 +[2025-05-01 23:10:13,456] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.37 | optimizer_step: 16.83 +[2025-05-01 23:10:13,457] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.79 | bwd_microstep: 341.67 | bwd_inner_microstep: 274.97 | bwd_allreduce_microstep: 66.66 | step_microstep: 23.92 +[2025-05-01 23:10:13,458] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2688.57 | bwd: 3915.54 | bwd_inner: 3847.79 | bwd_allreduce: 67.15 | step: 25.31 + 4%|▍ | 356/8720 [54:47<16:43:38, 7.20s/it] {'loss': 1.441, 'grad_norm': 4.983752250671387, 'learning_rate': 9.996952694605738e-06, 'epoch': 0.41} + 4%|▍ | 356/8720 [54:47<16:43:38, 7.20s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1905 +[2025-05-01 23:10:13,943] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.26 | bwd_microstep: 275.51 | bwd_inner_microstep: 275.49 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1896 +[2025-05-01 23:10:14,425] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.55 | bwd_microstep: 275.56 | bwd_inner_microstep: 275.54 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.16 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-01 23:10:14,906] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.68 | bwd_microstep: 273.78 | bwd_inner_microstep: 273.76 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 345 +[2025-05-01 23:10:15,109] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 72.25 | bwd_microstep: 116.24 | bwd_inner_microstep: 116.06 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-01 23:10:15,586] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.52 | bwd_microstep: 273.32 | bwd_inner_microstep: 273.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-01 23:10:16,065] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.45 | bwd_microstep: 273.83 | bwd_inner_microstep: 273.81 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-01 23:10:16,542] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.98 | bwd_microstep: 272.94 | bwd_inner_microstep: 272.92 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-01 23:10:17,020] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.48 | bwd_microstep: 273.09 | bwd_inner_microstep: 273.07 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 839 +[2025-05-01 23:10:17,252] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 91.49 | bwd_microstep: 126.60 | bwd_inner_microstep: 126.40 | bwd_allreduce_microstep: 0.09 | step_microstep: 0.08 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1348 +[2025-05-01 23:10:17,613] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 139.95 | bwd_microstep: 205.77 | bwd_inner_microstep: 205.75 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1352 +[2025-05-01 23:10:17,977] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.66 | bwd_microstep: 205.99 | bwd_inner_microstep: 205.93 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 23:10:18,457] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.65 | bwd_microstep: 272.81 | bwd_inner_microstep: 272.79 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 23:10:18,936] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.79 | bwd_microstep: 271.51 | bwd_inner_microstep: 271.49 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 23:10:19,412] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.95 | bwd_microstep: 271.23 | bwd_inner_microstep: 271.22 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 23:10:19,886] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.66 | bwd_microstep: 271.26 | bwd_inner_microstep: 271.24 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 433 +[2025-05-01 23:10:20,216] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.04 | optimizer_gradients: 2.42 | optimizer_step: 16.79 +[2025-05-01 23:10:20,217] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 86.24 | bwd_microstep: 207.25 | bwd_inner_microstep: 130.93 | bwd_allreduce_microstep: 76.16 | step_microstep: 23.95 +[2025-05-01 23:10:20,218] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2611.28 | bwd: 3866.78 | bwd_inner: 3789.88 | bwd_allreduce: 76.34 | step: 25.02 + 4%|▍ | 357/8720 [54:53<16:25:08, 7.07s/it] {'loss': 1.5784, 'grad_norm': 5.002701282501221, 'learning_rate': 9.996887520210231e-06, 'epoch': 0.41} + 4%|▍ | 357/8720 [54:53<16:25:08, 7.07s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 451 +[2025-05-01 23:10:20,418] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 70.96 | bwd_microstep: 110.66 | bwd_inner_microstep: 110.35 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1904 +[2025-05-01 23:10:20,900] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.51 | bwd_microstep: 276.19 | bwd_inner_microstep: 276.17 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 357 +[2025-05-01 23:10:21,122] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 90.26 | bwd_microstep: 114.60 | bwd_inner_microstep: 114.45 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.09 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 854 +[2025-05-01 23:10:21,369] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 97.22 | bwd_microstep: 133.50 | bwd_inner_microstep: 133.48 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 845 +[2025-05-01 23:10:21,612] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.93 | bwd_microstep: 132.28 | bwd_inner_microstep: 132.13 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-01 23:10:22,093] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.36 | bwd_microstep: 273.02 | bwd_inner_microstep: 273.00 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-01 23:10:22,573] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.72 | bwd_microstep: 273.14 | bwd_inner_microstep: 273.12 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-01 23:10:23,055] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.16 | bwd_microstep: 273.00 | bwd_inner_microstep: 272.98 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1349 +[2025-05-01 23:10:23,421] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.22 | bwd_microstep: 206.06 | bwd_inner_microstep: 205.97 | bwd_allreduce_microstep: 0.04 | step_microstep: 0.12 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 836 +[2025-05-01 23:10:23,665] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 100.50 | bwd_microstep: 125.80 | bwd_inner_microstep: 125.57 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-01 23:10:24,149] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.35 | bwd_microstep: 272.80 | bwd_inner_microstep: 272.78 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1089 +[2025-05-01 23:10:24,443] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 114.84 | bwd_microstep: 161.05 | bwd_inner_microstep: 161.03 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 23:10:24,924] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.42 | bwd_microstep: 272.39 | bwd_inner_microstep: 272.37 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:10:25,408] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.75 | bwd_microstep: 272.60 | bwd_inner_microstep: 272.59 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 23:10:25,889] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.45 | bwd_microstep: 272.80 | bwd_inner_microstep: 272.79 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 23:10:26,463] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.45 | optimizer_step: 17.08 +[2025-05-01 23:10:26,463] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.24 | bwd_microstep: 341.32 | bwd_inner_microstep: 271.98 | bwd_allreduce_microstep: 69.29 | step_microstep: 24.93 +[2025-05-01 23:10:26,465] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2406.51 | bwd: 3511.31 | bwd_inner: 3440.88 | bwd_allreduce: 69.75 | step: 26.19 + 4%|▍ | 358/8720 [55:00<15:50:44, 6.82s/it] {'loss': 1.4295, 'grad_norm': 5.841538429260254, 'learning_rate': 9.996821656426356e-06, 'epoch': 0.41} + 4%|▍ | 358/8720 [55:00<15:50:44, 6.82s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1919 +[2025-05-01 23:10:26,953] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.77 | bwd_microstep: 276.26 | bwd_inner_microstep: 276.06 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.29 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 895 +[2025-05-01 23:10:27,201] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 96.06 | bwd_microstep: 136.42 | bwd_inner_microstep: 136.18 | bwd_allreduce_microstep: 0.09 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1904 +[2025-05-01 23:10:27,683] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.03 | bwd_microstep: 275.90 | bwd_inner_microstep: 275.88 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 881 +[2025-05-01 23:10:27,932] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 98.68 | bwd_microstep: 135.05 | bwd_inner_microstep: 134.98 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-01 23:10:28,412] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.61 | bwd_microstep: 274.59 | bwd_inner_microstep: 274.57 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-01 23:10:28,891] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.67 | bwd_microstep: 273.79 | bwd_inner_microstep: 273.77 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-01 23:10:29,368] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.12 | bwd_microstep: 272.56 | bwd_inner_microstep: 272.55 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-01 23:10:29,846] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.17 | bwd_microstep: 272.59 | bwd_inner_microstep: 272.57 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 23:10:30,323] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.93 | bwd_microstep: 272.12 | bwd_inner_microstep: 272.11 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 23:10:30,800] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.43 | bwd_microstep: 272.28 | bwd_inner_microstep: 272.27 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 23:10:31,278] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.11 | bwd_microstep: 272.79 | bwd_inner_microstep: 272.77 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1345 +[2025-05-01 23:10:31,641] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.63 | bwd_microstep: 205.56 | bwd_inner_microstep: 205.38 | bwd_allreduce_microstep: 0.10 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 23:10:32,117] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.21 | bwd_microstep: 271.48 | bwd_inner_microstep: 271.47 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-01 23:10:32,593] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.89 | bwd_microstep: 271.27 | bwd_inner_microstep: 271.25 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 23:10:33,069] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.10 | bwd_microstep: 271.59 | bwd_inner_microstep: 271.57 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-01 23:10:33,638] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.42 | optimizer_step: 16.98 +[2025-05-01 23:10:33,638] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.92 | bwd_microstep: 339.65 | bwd_inner_microstep: 271.78 | bwd_allreduce_microstep: 67.82 | step_microstep: 24.83 +[2025-05-01 23:10:33,640] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2788.06 | bwd: 4094.03 | bwd_inner: 4025.23 | bwd_allreduce: 68.22 | step: 25.97 + 4%|▍ | 359/8720 [55:07<16:05:23, 6.93s/it] {'loss': 1.2528, 'grad_norm': 4.477386951446533, 'learning_rate': 9.996755103263199e-06, 'epoch': 0.41} + 4%|▍ | 359/8720 [55:07<16:05:23, 6.93s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1895 +[2025-05-01 23:10:34,125] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.09 | bwd_microstep: 274.44 | bwd_inner_microstep: 274.42 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-01 23:10:34,606] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.86 | bwd_microstep: 273.71 | bwd_inner_microstep: 273.69 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-01 23:10:35,087] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.92 | bwd_microstep: 273.22 | bwd_inner_microstep: 273.20 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-01 23:10:35,573] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.29 | bwd_microstep: 273.87 | bwd_inner_microstep: 273.86 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-01 23:10:36,056] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.77 | bwd_microstep: 273.70 | bwd_inner_microstep: 273.68 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-01 23:10:36,537] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.88 | bwd_microstep: 273.06 | bwd_inner_microstep: 273.04 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-01 23:10:37,019] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.62 | bwd_microstep: 273.09 | bwd_inner_microstep: 273.08 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 23:10:37,500] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.84 | bwd_microstep: 272.34 | bwd_inner_microstep: 272.32 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 23:10:37,979] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.08 | bwd_microstep: 272.47 | bwd_inner_microstep: 272.45 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 23:10:38,459] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.70 | bwd_microstep: 272.45 | bwd_inner_microstep: 272.43 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.15 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 23:10:38,952] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 201.45 | bwd_microstep: 272.43 | bwd_inner_microstep: 272.42 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 23:10:39,429] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.84 | bwd_microstep: 271.45 | bwd_inner_microstep: 271.43 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1341 +[2025-05-01 23:10:39,792] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 142.59 | bwd_microstep: 204.45 | bwd_inner_microstep: 204.43 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-01 23:10:40,270] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.42 | bwd_microstep: 271.33 | bwd_inner_microstep: 271.31 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 23:10:40,749] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.45 | bwd_microstep: 271.35 | bwd_inner_microstep: 271.33 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1923 +[2025-05-01 23:10:41,351] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.54 | optimizer_step: 17.42 +[2025-05-01 23:10:41,351] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.21 | bwd_microstep: 364.43 | bwd_inner_microstep: 288.09 | bwd_allreduce_microstep: 76.29 | step_microstep: 24.91 +[2025-05-01 23:10:41,352] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2996.63 | bwd: 4387.80 | bwd_inner: 4311.20 | bwd_allreduce: 76.37 | step: 26.00 + 4%|▍ | 360/8720 [55:15<16:38:02, 7.16s/it] {'loss': 1.352, 'grad_norm': 4.811659336090088, 'learning_rate': 9.996687860729939e-06, 'epoch': 0.41} + 4%|▍ | 360/8720 [55:15<16:38:02, 7.16s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1942 +[2025-05-01 23:10:41,858] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 197.18 | bwd_microstep: 288.21 | bwd_inner_microstep: 288.19 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1936 +[2025-05-01 23:10:42,360] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 198.19 | bwd_microstep: 288.66 | bwd_inner_microstep: 288.64 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 396 +[2025-05-01 23:10:42,577] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 73.48 | bwd_microstep: 128.65 | bwd_inner_microstep: 128.49 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1888 +[2025-05-01 23:10:43,057] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.22 | bwd_microstep: 274.95 | bwd_inner_microstep: 274.94 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1894 +[2025-05-01 23:10:43,539] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.49 | bwd_microstep: 275.15 | bwd_inner_microstep: 275.13 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-01 23:10:44,018] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.85 | bwd_microstep: 273.32 | bwd_inner_microstep: 273.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 23:10:44,497] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.89 | bwd_microstep: 272.68 | bwd_inner_microstep: 272.66 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 333 +[2025-05-01 23:10:44,709] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 71.73 | bwd_microstep: 126.37 | bwd_inner_microstep: 126.10 | bwd_allreduce_microstep: 0.10 | step_microstep: 0.09 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 330 +[2025-05-01 23:10:44,927] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 72.00 | bwd_microstep: 131.15 | bwd_inner_microstep: 131.01 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.09 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1352 +[2025-05-01 23:10:45,289] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.74 | bwd_microstep: 206.23 | bwd_inner_microstep: 206.21 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:10:45,767] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.40 | bwd_microstep: 272.91 | bwd_inner_microstep: 272.90 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1345 +[2025-05-01 23:10:46,129] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.69 | bwd_microstep: 205.67 | bwd_inner_microstep: 205.66 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 23:10:46,605] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.20 | bwd_microstep: 271.40 | bwd_inner_microstep: 271.38 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 23:10:47,081] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.88 | bwd_microstep: 271.46 | bwd_inner_microstep: 271.44 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 23:10:47,558] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.79 | bwd_microstep: 271.27 | bwd_inner_microstep: 271.25 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1892 +[2025-05-01 23:10:48,139] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.44 | optimizer_step: 17.02 +[2025-05-01 23:10:48,140] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.27 | bwd_microstep: 349.34 | bwd_inner_microstep: 275.09 | bwd_allreduce_microstep: 74.21 | step_microstep: 24.40 +[2025-05-01 23:10:48,141] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2592.70 | bwd: 3907.49 | bwd_inner: 3832.55 | bwd_allreduce: 74.46 | step: 25.22 + 4%|▍ | 361/8720 [55:21<16:22:15, 7.05s/it] {'loss': 1.3433, 'grad_norm': 3.893782377243042, 'learning_rate': 9.996619928835856e-06, 'epoch': 0.41} + 4%|▍ | 361/8720 [55:21<16:22:15, 7.05s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1949 +[2025-05-01 23:10:48,646] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.85 | bwd_microstep: 288.89 | bwd_inner_microstep: 288.87 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.16 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1899 +[2025-05-01 23:10:49,128] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.30 | bwd_microstep: 275.67 | bwd_inner_microstep: 275.65 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.15 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-01 23:10:49,609] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.44 | bwd_microstep: 273.85 | bwd_inner_microstep: 273.83 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 345 +[2025-05-01 23:10:49,865] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 89.32 | bwd_microstep: 149.57 | bwd_inner_microstep: 149.33 | bwd_allreduce_microstep: 0.09 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-01 23:10:50,344] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.51 | bwd_microstep: 273.40 | bwd_inner_microstep: 273.39 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-01 23:10:50,825] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.62 | bwd_microstep: 272.88 | bwd_inner_microstep: 272.86 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:10:51,307] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.19 | bwd_microstep: 272.76 | bwd_inner_microstep: 272.74 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-01 23:10:51,790] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.11 | bwd_microstep: 272.95 | bwd_inner_microstep: 272.93 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:10:52,282] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.45 | bwd_microstep: 282.76 | bwd_inner_microstep: 281.23 | bwd_allreduce_microstep: 0.60 | step_microstep: 0.70 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 23:10:52,769] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.40 | bwd_microstep: 272.93 | bwd_inner_microstep: 272.91 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 23:10:53,250] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.05 | bwd_microstep: 271.53 | bwd_inner_microstep: 271.51 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.17 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 23:10:53,732] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.68 | bwd_microstep: 271.24 | bwd_inner_microstep: 271.22 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 23:10:54,216] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.34 | bwd_microstep: 272.43 | bwd_inner_microstep: 272.41 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 23:10:54,694] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.88 | bwd_microstep: 271.36 | bwd_inner_microstep: 271.34 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-01 23:10:55,174] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.99 | bwd_microstep: 271.25 | bwd_inner_microstep: 271.24 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 23:10:55,760] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.41 | optimizer_step: 16.75 +[2025-05-01 23:10:55,761] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.32 | bwd_microstep: 350.88 | bwd_inner_microstep: 272.94 | bwd_allreduce_microstep: 77.85 | step_microstep: 25.11 +[2025-05-01 23:10:55,762] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2928.05 | bwd: 4344.45 | bwd_inner: 4264.82 | bwd_allreduce: 78.60 | step: 27.01 + 4%|▍ | 362/8720 [55:29<16:46:05, 7.22s/it] {'loss': 1.054, 'grad_norm': 5.424323558807373, 'learning_rate': 9.996551307590319e-06, 'epoch': 0.42} + 4%|▍ | 362/8720 [55:29<16:46:05, 7.22s/it]dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 895 +[2025-05-01 23:10:56,017] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 96.18 | bwd_microstep: 136.97 | bwd_inner_microstep: 136.68 | bwd_allreduce_microstep: 0.14 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1893 +[2025-05-01 23:10:56,500] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.99 | bwd_microstep: 275.07 | bwd_inner_microstep: 275.05 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-01 23:10:56,981] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.96 | bwd_microstep: 273.82 | bwd_inner_microstep: 273.81 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-01 23:10:57,462] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.16 | bwd_microstep: 274.12 | bwd_inner_microstep: 274.10 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-01 23:10:57,942] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.83 | bwd_microstep: 273.51 | bwd_inner_microstep: 273.49 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-01 23:10:58,423] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.05 | bwd_microstep: 273.65 | bwd_inner_microstep: 273.63 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 23:10:58,904] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.15 | bwd_microstep: 272.62 | bwd_inner_microstep: 272.60 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-01 23:10:59,388] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.60 | bwd_microstep: 273.05 | bwd_inner_microstep: 273.03 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 6, images per sample: 6.0, dynamic token length: 1607 +[2025-05-01 23:10:59,816] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 166.87 | bwd_microstep: 244.43 | bwd_inner_microstep: 244.41 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-01 23:11:00,296] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.59 | bwd_microstep: 273.15 | bwd_inner_microstep: 273.14 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 23:11:00,776] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.27 | bwd_microstep: 271.77 | bwd_inner_microstep: 271.76 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 317 +[2025-05-01 23:11:01,041] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 92.93 | bwd_microstep: 152.08 | bwd_inner_microstep: 151.92 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-01 23:11:01,518] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.95 | bwd_microstep: 271.68 | bwd_inner_microstep: 271.66 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1850 +[2025-05-01 23:11:01,995] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.21 | bwd_microstep: 271.43 | bwd_inner_microstep: 271.41 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1413 +[2025-05-01 23:11:02,373] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 145.83 | bwd_microstep: 213.22 | bwd_inner_microstep: 213.20 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1895 +[2025-05-01 23:11:02,953] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.29 | optimizer_step: 17.03 +[2025-05-01 23:11:02,954] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.01 | bwd_microstep: 348.96 | bwd_inner_microstep: 276.02 | bwd_allreduce_microstep: 72.90 | step_microstep: 24.35 +[2025-05-01 23:11:02,955] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2768.19 | bwd: 4099.58 | bwd_inner: 4026.02 | bwd_allreduce: 73.15 | step: 25.41 + 4%|▍ | 363/8720 [55:36<16:44:38, 7.21s/it] {'loss': 1.3395, 'grad_norm': 3.4484548568725586, 'learning_rate': 9.9964819970028e-06, 'epoch': 0.42} + 4%|▍ | 363/8720 [55:36<16:44:38, 7.21s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 435 +[2025-05-01 23:11:03,163] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 71.15 | bwd_microstep: 118.96 | bwd_inner_microstep: 118.84 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1921 +[2025-05-01 23:11:03,660] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 194.89 | bwd_microstep: 287.24 | bwd_inner_microstep: 287.22 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1898 +[2025-05-01 23:11:04,143] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.47 | bwd_microstep: 275.50 | bwd_inner_microstep: 275.48 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-01 23:11:04,622] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.87 | bwd_microstep: 273.34 | bwd_inner_microstep: 273.32 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 23:11:05,100] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.40 | bwd_microstep: 272.68 | bwd_inner_microstep: 272.66 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 323 +[2025-05-01 23:11:05,318] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 84.86 | bwd_microstep: 118.88 | bwd_inner_microstep: 118.67 | bwd_allreduce_microstep: 0.08 | step_microstep: 0.13 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 23:11:05,802] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.81 | bwd_microstep: 272.71 | bwd_inner_microstep: 272.69 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 322 +[2025-05-01 23:11:06,016] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 81.33 | bwd_microstep: 118.60 | bwd_inner_microstep: 118.46 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:11:06,492] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.10 | bwd_microstep: 272.45 | bwd_inner_microstep: 272.43 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 23:11:06,970] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.61 | bwd_microstep: 272.37 | bwd_inner_microstep: 272.35 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 23:11:07,447] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.91 | bwd_microstep: 271.48 | bwd_inner_microstep: 271.46 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 23:11:07,924] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.01 | bwd_microstep: 271.33 | bwd_inner_microstep: 271.32 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.21 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 23:11:08,401] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.19 | bwd_microstep: 271.62 | bwd_inner_microstep: 271.60 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 23:11:08,878] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.51 | bwd_microstep: 271.39 | bwd_inner_microstep: 271.37 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 23:11:09,353] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.90 | bwd_microstep: 271.12 | bwd_inner_microstep: 271.10 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1919 +[2025-05-01 23:11:09,944] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.39 | optimizer_step: 16.78 +[2025-05-01 23:11:09,945] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.31 | bwd_microstep: 361.53 | bwd_inner_microstep: 277.21 | bwd_allreduce_microstep: 84.27 | step_microstep: 25.44 +[2025-05-01 23:11:09,946] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2698.01 | bwd: 4001.27 | bwd_inner: 3916.28 | bwd_allreduce: 84.53 | step: 26.51 + 4%|▍ | 364/8720 [55:43<16:35:15, 7.15s/it] {'loss': 0.8099, 'grad_norm': 3.4843316078186035, 'learning_rate': 9.996411997082858e-06, 'epoch': 0.42} + 4%|▍ | 364/8720 [55:43<16:35:15, 7.15s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1948 +[2025-05-01 23:11:10,451] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.97 | bwd_microstep: 288.68 | bwd_inner_microstep: 288.66 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 916 +[2025-05-01 23:11:10,717] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 104.98 | bwd_microstep: 145.39 | bwd_inner_microstep: 145.11 | bwd_allreduce_microstep: 0.14 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1910 +[2025-05-01 23:11:11,199] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.81 | bwd_microstep: 276.32 | bwd_inner_microstep: 276.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1898 +[2025-05-01 23:11:11,682] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.87 | bwd_microstep: 275.55 | bwd_inner_microstep: 275.53 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-01 23:11:12,160] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.18 | bwd_microstep: 273.52 | bwd_inner_microstep: 273.50 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-01 23:11:12,639] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.64 | bwd_microstep: 274.30 | bwd_inner_microstep: 274.28 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-01 23:11:13,121] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.52 | bwd_microstep: 274.17 | bwd_inner_microstep: 274.15 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-01 23:11:13,599] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.96 | bwd_microstep: 273.14 | bwd_inner_microstep: 273.12 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 838 +[2025-05-01 23:11:13,837] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 98.10 | bwd_microstep: 125.83 | bwd_inner_microstep: 125.82 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-01 23:11:14,313] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.03 | bwd_microstep: 272.82 | bwd_inner_microstep: 272.80 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-01 23:11:14,790] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.17 | bwd_microstep: 272.79 | bwd_inner_microstep: 272.78 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-01 23:11:15,267] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.51 | bwd_microstep: 272.67 | bwd_inner_microstep: 272.65 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 23:11:15,746] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.12 | bwd_microstep: 272.62 | bwd_inner_microstep: 272.60 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 23:11:16,223] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.77 | bwd_microstep: 272.55 | bwd_inner_microstep: 272.53 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 325 +[2025-05-01 23:11:16,439] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 86.30 | bwd_microstep: 116.62 | bwd_inner_microstep: 116.30 | bwd_allreduce_microstep: 0.14 | step_microstep: 0.09 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1093 +[2025-05-01 23:11:16,863] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.07 | optimizer_gradients: 2.45 | optimizer_step: 16.75 +[2025-05-01 23:11:16,864] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 114.97 | bwd_microstep: 267.93 | bwd_inner_microstep: 161.97 | bwd_allreduce_microstep: 105.84 | step_microstep: 27.56 +[2025-05-01 23:11:16,865] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2679.58 | bwd: 3954.97 | bwd_inner: 3848.21 | bwd_allreduce: 106.18 | step: 28.74 + 4%|▍ | 365/8720 [55:50<16:25:37, 7.08s/it] {'loss': 1.2266, 'grad_norm': 3.8911893367767334, 'learning_rate': 9.996341307840152e-06, 'epoch': 0.42} + 4%|▍ | 365/8720 [55:50<16:25:37, 7.08s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1887 +[2025-05-01 23:11:17,349] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.58 | bwd_microstep: 274.35 | bwd_inner_microstep: 274.33 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1362 +[2025-05-01 23:11:17,713] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.93 | bwd_microstep: 206.99 | bwd_inner_microstep: 206.83 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.10 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 842 +[2025-05-01 23:11:17,960] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 99.89 | bwd_microstep: 131.81 | bwd_inner_microstep: 131.69 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.09 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1347 +[2025-05-01 23:11:18,321] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.75 | bwd_microstep: 205.71 | bwd_inner_microstep: 205.62 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.09 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 328 +[2025-05-01 23:11:18,542] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 82.01 | bwd_microstep: 125.61 | bwd_inner_microstep: 125.46 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-01 23:11:19,020] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.74 | bwd_microstep: 273.26 | bwd_inner_microstep: 273.24 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 23:11:19,499] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.11 | bwd_microstep: 272.65 | bwd_inner_microstep: 272.63 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 837 +[2025-05-01 23:11:19,733] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 92.21 | bwd_microstep: 126.40 | bwd_inner_microstep: 126.38 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 23:11:20,210] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.31 | bwd_microstep: 272.62 | bwd_inner_microstep: 272.60 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 23:11:20,690] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.32 | bwd_microstep: 272.74 | bwd_inner_microstep: 272.72 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 23:11:21,168] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.25 | bwd_microstep: 272.46 | bwd_inner_microstep: 272.44 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 23:11:21,649] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.00 | bwd_microstep: 272.07 | bwd_inner_microstep: 272.05 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 831 +[2025-05-01 23:11:21,890] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.93 | bwd_microstep: 129.83 | bwd_inner_microstep: 129.81 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 23:11:22,366] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.57 | bwd_microstep: 271.15 | bwd_inner_microstep: 271.14 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-01 23:11:22,845] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.26 | bwd_microstep: 271.09 | bwd_inner_microstep: 271.07 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 879 +[2025-05-01 23:11:23,200] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.37 | optimizer_step: 16.52 +[2025-05-01 23:11:23,200] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 98.89 | bwd_microstep: 213.88 | bwd_inner_microstep: 137.43 | bwd_allreduce_microstep: 76.30 | step_microstep: 24.33 +[2025-05-01 23:11:23,202] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2447.39 | bwd: 3592.71 | bwd_inner: 3515.54 | bwd_allreduce: 76.62 | step: 25.68 + 4%|▍ | 366/8720 [55:56<15:54:36, 6.86s/it] {'loss': 0.7507, 'grad_norm': 5.912772178649902, 'learning_rate': 9.996269929284432e-06, 'epoch': 0.42} + 4%|▍ | 366/8720 [55:56<15:54:36, 6.86s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1892 +[2025-05-01 23:11:23,688] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.27 | bwd_microstep: 274.07 | bwd_inner_microstep: 274.05 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1886 +[2025-05-01 23:11:24,167] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.40 | bwd_microstep: 274.66 | bwd_inner_microstep: 274.65 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1112 +[2025-05-01 23:11:24,462] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 118.32 | bwd_microstep: 162.76 | bwd_inner_microstep: 162.56 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-01 23:11:24,941] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.08 | bwd_microstep: 274.33 | bwd_inner_microstep: 274.31 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 852 +[2025-05-01 23:11:25,184] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.28 | bwd_microstep: 133.51 | bwd_inner_microstep: 133.25 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-01 23:11:25,663] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.73 | bwd_microstep: 273.69 | bwd_inner_microstep: 273.67 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-01 23:11:26,142] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.26 | bwd_microstep: 274.34 | bwd_inner_microstep: 274.33 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 23:11:26,621] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.35 | bwd_microstep: 273.09 | bwd_inner_microstep: 273.07 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-01 23:11:27,101] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.72 | bwd_microstep: 273.72 | bwd_inner_microstep: 273.70 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 835 +[2025-05-01 23:11:27,333] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 91.97 | bwd_microstep: 126.38 | bwd_inner_microstep: 126.21 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 23:11:27,811] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.86 | bwd_microstep: 273.10 | bwd_inner_microstep: 273.08 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-01 23:11:28,289] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.59 | bwd_microstep: 273.49 | bwd_inner_microstep: 273.48 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 23:11:28,767] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.58 | bwd_microstep: 273.15 | bwd_inner_microstep: 273.13 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 23:11:29,244] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.07 | bwd_microstep: 271.88 | bwd_inner_microstep: 271.86 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 23:11:29,723] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.73 | bwd_microstep: 271.99 | bwd_inner_microstep: 271.97 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 23:11:30,310] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.37 | optimizer_step: 21.38 +[2025-05-01 23:11:30,310] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.40 | bwd_microstep: 349.10 | bwd_inner_microstep: 272.28 | bwd_allreduce_microstep: 76.78 | step_microstep: 29.28 +[2025-05-01 23:11:30,312] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2765.33 | bwd: 4053.32 | bwd_inner: 3975.66 | bwd_allreduce: 77.13 | step: 30.33 + 4%|▍ | 367/8720 [56:04<16:05:05, 6.93s/it] {'loss': 1.318, 'grad_norm': 3.7871620655059814, 'learning_rate': 9.996197861425548e-06, 'epoch': 0.42} + 4%|▍ | 367/8720 [56:04<16:05:05, 6.93s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 462 +[2025-05-01 23:11:30,530] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 80.01 | bwd_microstep: 116.96 | bwd_inner_microstep: 116.80 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1973 +[2025-05-01 23:11:31,034] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 197.23 | bwd_microstep: 291.91 | bwd_inner_microstep: 291.90 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1889 +[2025-05-01 23:11:31,513] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.27 | bwd_microstep: 274.77 | bwd_inner_microstep: 274.75 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1887 +[2025-05-01 23:11:31,992] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.07 | bwd_microstep: 274.58 | bwd_inner_microstep: 274.56 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 874 +[2025-05-01 23:11:32,238] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 97.38 | bwd_microstep: 134.43 | bwd_inner_microstep: 134.32 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1887 +[2025-05-01 23:11:32,718] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.53 | bwd_microstep: 275.17 | bwd_inner_microstep: 275.15 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 345 +[2025-05-01 23:11:32,939] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 84.45 | bwd_microstep: 120.04 | bwd_inner_microstep: 119.70 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-01 23:11:33,419] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.77 | bwd_microstep: 273.79 | bwd_inner_microstep: 273.77 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1351 +[2025-05-01 23:11:33,784] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.72 | bwd_microstep: 206.10 | bwd_inner_microstep: 206.08 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-01 23:11:34,264] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.46 | bwd_microstep: 272.85 | bwd_inner_microstep: 272.83 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 23:11:34,744] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.87 | bwd_microstep: 272.42 | bwd_inner_microstep: 272.40 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 23:11:35,221] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.02 | bwd_microstep: 271.72 | bwd_inner_microstep: 271.70 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-01 23:11:35,698] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.18 | bwd_microstep: 271.14 | bwd_inner_microstep: 271.12 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 23:11:36,176] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.13 | bwd_microstep: 271.35 | bwd_inner_microstep: 271.33 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 23:11:36,656] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.00 | bwd_microstep: 271.11 | bwd_inner_microstep: 271.09 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1931 +[2025-05-01 23:11:37,270] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.90 | optimizer_step: 21.69 +[2025-05-01 23:11:37,270] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 196.54 | bwd_microstep: 365.94 | bwd_inner_microstep: 288.84 | bwd_allreduce_microstep: 77.04 | step_microstep: 30.35 +[2025-05-01 23:11:37,272] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2684.30 | bwd: 3964.36 | bwd_inner: 3886.44 | bwd_allreduce: 77.38 | step: 31.41 + 4%|▍ | 368/8720 [56:11<16:06:08, 6.94s/it] {'loss': 1.322, 'grad_norm': 3.501166343688965, 'learning_rate': 9.996125104273441e-06, 'epoch': 0.42} + 4%|▍ | 368/8720 [56:11<16:06:08, 6.94s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 362 +[2025-05-01 23:11:37,495] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 75.26 | bwd_microstep: 126.16 | bwd_inner_microstep: 126.02 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.13 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-01 23:11:37,974] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.09 | bwd_microstep: 274.47 | bwd_inner_microstep: 274.46 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-01 23:11:38,453] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.51 | bwd_microstep: 273.50 | bwd_inner_microstep: 273.49 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 841 +[2025-05-01 23:11:38,695] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.38 | bwd_microstep: 132.00 | bwd_inner_microstep: 131.81 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.18 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 850 +[2025-05-01 23:11:38,936] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.40 | bwd_microstep: 132.43 | bwd_inner_microstep: 132.40 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-01 23:11:39,414] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.90 | bwd_microstep: 272.81 | bwd_inner_microstep: 272.79 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-01 23:11:39,894] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.36 | bwd_microstep: 273.11 | bwd_inner_microstep: 273.09 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 842 +[2025-05-01 23:11:40,141] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.64 | bwd_microstep: 133.61 | bwd_inner_microstep: 133.35 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-01 23:11:40,621] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.09 | bwd_microstep: 272.93 | bwd_inner_microstep: 272.92 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 23:11:41,099] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.50 | bwd_microstep: 272.52 | bwd_inner_microstep: 272.51 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 23:11:41,579] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.46 | bwd_microstep: 271.29 | bwd_inner_microstep: 271.27 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 23:11:42,061] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.98 | bwd_microstep: 271.08 | bwd_inner_microstep: 271.06 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 317 +[2025-05-01 23:11:42,296] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 90.77 | bwd_microstep: 124.92 | bwd_inner_microstep: 124.59 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 23:11:42,773] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.98 | bwd_microstep: 271.30 | bwd_inner_microstep: 271.28 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1961 +[2025-05-01 23:11:43,282] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 197.01 | bwd_microstep: 290.67 | bwd_inner_microstep: 290.65 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1940 +[2025-05-01 23:11:43,909] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.49 | optimizer_step: 30.97 +[2025-05-01 23:11:43,910] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.73 | bwd_microstep: 368.79 | bwd_inner_microstep: 289.51 | bwd_allreduce_microstep: 79.23 | step_microstep: 39.28 +[2025-05-01 23:11:43,911] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2542.71 | bwd: 3761.70 | bwd_inner: 3681.36 | bwd_allreduce: 79.67 | step: 40.43 + 4%|▍ | 369/8720 [56:17<15:53:28, 6.85s/it] {'loss': 1.5434, 'grad_norm': 4.2298078536987305, 'learning_rate': 9.996051657838152e-06, 'epoch': 0.42} + 4%|▍ | 369/8720 [56:17<15:53:28, 6.85s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1891 +[2025-05-01 23:11:44,399] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.65 | bwd_microstep: 274.23 | bwd_inner_microstep: 274.21 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 348 +[2025-05-01 23:11:44,633] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 83.12 | bwd_microstep: 134.31 | bwd_inner_microstep: 134.15 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-01 23:11:45,114] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.77 | bwd_microstep: 273.26 | bwd_inner_microstep: 273.23 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 23:11:45,595] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.14 | bwd_microstep: 272.84 | bwd_inner_microstep: 272.82 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 23:11:46,075] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.36 | bwd_microstep: 272.41 | bwd_inner_microstep: 272.39 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-01 23:11:46,557] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.15 | bwd_microstep: 272.67 | bwd_inner_microstep: 272.66 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 23:11:47,038] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.83 | bwd_microstep: 272.77 | bwd_inner_microstep: 272.75 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 23:11:47,519] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.43 | bwd_microstep: 272.41 | bwd_inner_microstep: 272.40 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 23:11:47,999] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.79 | bwd_microstep: 271.24 | bwd_inner_microstep: 271.22 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 832 +[2025-05-01 23:11:48,252] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 101.73 | bwd_microstep: 130.84 | bwd_inner_microstep: 130.71 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-01 23:11:48,730] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.44 | bwd_microstep: 271.53 | bwd_inner_microstep: 271.51 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 23:11:49,209] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.69 | bwd_microstep: 271.57 | bwd_inner_microstep: 271.55 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 23:11:49,687] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.76 | bwd_microstep: 271.46 | bwd_inner_microstep: 271.44 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-01 23:11:50,165] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.52 | bwd_microstep: 271.32 | bwd_inner_microstep: 271.31 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1340 +[2025-05-01 23:11:50,528] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.65 | bwd_microstep: 204.40 | bwd_inner_microstep: 204.36 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.13 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-01 23:11:51,114] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.07 | optimizer_gradients: 3.52 | optimizer_step: 16.74 +[2025-05-01 23:11:51,115] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.39 | bwd_microstep: 351.92 | bwd_inner_microstep: 274.27 | bwd_allreduce_microstep: 77.59 | step_microstep: 26.16 +[2025-05-01 23:11:51,116] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2781.03 | bwd: 4089.28 | bwd_inner: 4011.04 | bwd_allreduce: 77.79 | step: 27.37 + 4%|▍ | 370/8720 [56:24<16:08:10, 6.96s/it] {'loss': 1.0801, 'grad_norm': 5.142766952514648, 'learning_rate': 9.995977522129812e-06, 'epoch': 0.42} + 4%|▍ | 370/8720 [56:24<16:08:10, 6.96s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1962 +[2025-05-01 23:11:51,629] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 197.84 | bwd_microstep: 289.96 | bwd_inner_microstep: 289.95 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-01 23:11:52,108] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.15 | bwd_microstep: 274.46 | bwd_inner_microstep: 274.44 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1890 +[2025-05-01 23:11:52,589] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.67 | bwd_microstep: 274.82 | bwd_inner_microstep: 274.80 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-01 23:11:53,068] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.50 | bwd_microstep: 273.84 | bwd_inner_microstep: 273.82 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 334 +[2025-05-01 23:11:53,296] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 80.66 | bwd_microstep: 130.76 | bwd_inner_microstep: 130.45 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.21 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 845 +[2025-05-01 23:11:53,541] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 96.14 | bwd_microstep: 132.83 | bwd_inner_microstep: 132.52 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-01 23:11:54,021] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.25 | bwd_microstep: 273.01 | bwd_inner_microstep: 272.99 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:11:54,501] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.05 | bwd_microstep: 272.61 | bwd_inner_microstep: 272.59 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 23:11:54,980] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.45 | bwd_microstep: 272.33 | bwd_inner_microstep: 272.32 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.38 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 23:11:55,459] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.85 | bwd_microstep: 271.17 | bwd_inner_microstep: 271.15 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 23:11:55,936] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.61 | bwd_microstep: 271.16 | bwd_inner_microstep: 271.14 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 315 +[2025-05-01 23:11:56,169] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 83.56 | bwd_microstep: 133.82 | bwd_inner_microstep: 133.57 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1849 +[2025-05-01 23:11:56,648] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.72 | bwd_microstep: 271.18 | bwd_inner_microstep: 271.16 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1946 +[2025-05-01 23:11:57,152] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 197.03 | bwd_microstep: 288.99 | bwd_inner_microstep: 288.97 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 344 +[2025-05-01 23:11:57,395] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 84.00 | bwd_microstep: 142.10 | bwd_inner_microstep: 141.95 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 23:11:57,978] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.28 | optimizer_step: 21.42 +[2025-05-01 23:11:57,978] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.63 | bwd_microstep: 348.53 | bwd_inner_microstep: 271.90 | bwd_allreduce_microstep: 76.57 | step_microstep: 29.28 +[2025-05-01 23:11:57,980] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2623.78 | bwd: 3921.69 | bwd_inner: 3843.94 | bwd_allreduce: 77.00 | step: 30.96 + 4%|▍ | 371/8720 [56:31<16:04:07, 6.93s/it] {'loss': 1.2833, 'grad_norm': 3.3850817680358887, 'learning_rate': 9.995902697158647e-06, 'epoch': 0.43} + 4%|▍ | 371/8720 [56:31<16:04:07, 6.93s/it]dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 928 +[2025-05-01 23:11:58,252] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 104.16 | bwd_microstep: 146.32 | bwd_inner_microstep: 146.01 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1934 +[2025-05-01 23:11:58,757] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 197.84 | bwd_microstep: 288.54 | bwd_inner_microstep: 288.53 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 337 +[2025-05-01 23:11:58,981] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 79.32 | bwd_microstep: 129.67 | bwd_inner_microstep: 129.51 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 843 +[2025-05-01 23:11:59,227] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.31 | bwd_microstep: 132.85 | bwd_inner_microstep: 132.56 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-01 23:11:59,707] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.02 | bwd_microstep: 272.89 | bwd_inner_microstep: 272.87 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1347 +[2025-05-01 23:12:00,073] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.73 | bwd_microstep: 205.73 | bwd_inner_microstep: 205.59 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.11 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 844 +[2025-05-01 23:12:00,315] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.63 | bwd_microstep: 132.43 | bwd_inner_microstep: 132.41 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1351 +[2025-05-01 23:12:00,680] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.01 | bwd_microstep: 206.39 | bwd_inner_microstep: 206.20 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.11 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 335 +[2025-05-01 23:12:00,897] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 81.08 | bwd_microstep: 120.24 | bwd_inner_microstep: 119.99 | bwd_allreduce_microstep: 0.10 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-01 23:12:01,375] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.65 | bwd_microstep: 272.84 | bwd_inner_microstep: 272.83 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 23:12:01,852] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.83 | bwd_microstep: 273.21 | bwd_inner_microstep: 273.19 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-01 23:12:02,330] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.07 | bwd_microstep: 272.89 | bwd_inner_microstep: 272.88 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.19 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 835 +[2025-05-01 23:12:02,562] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 91.32 | bwd_microstep: 126.41 | bwd_inner_microstep: 126.12 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 23:12:03,037] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.44 | bwd_microstep: 271.09 | bwd_inner_microstep: 271.07 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 23:12:03,511] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.51 | bwd_microstep: 271.26 | bwd_inner_microstep: 271.24 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-01 23:12:04,087] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.46 | optimizer_step: 21.93 +[2025-05-01 23:12:04,088] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.83 | bwd_microstep: 341.49 | bwd_inner_microstep: 274.10 | bwd_allreduce_microstep: 67.35 | step_microstep: 29.49 +[2025-05-01 23:12:04,089] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2344.43 | bwd: 3464.43 | bwd_inner: 3395.32 | bwd_allreduce: 68.14 | step: 30.97 + 4%|▍ | 372/8720 [56:37<15:29:44, 6.68s/it] {'loss': 1.9329, 'grad_norm': 6.238389492034912, 'learning_rate': 9.995827182934984e-06, 'epoch': 0.43} + 4%|▍ | 372/8720 [56:37<15:29:44, 6.68s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2436 +[2025-05-01 23:12:04,684] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 221.62 | bwd_microstep: 352.44 | bwd_inner_microstep: 352.42 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2053 +[2025-05-01 23:12:05,204] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 202.42 | bwd_microstep: 301.95 | bwd_inner_microstep: 301.93 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 435 +[2025-05-01 23:12:05,414] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 70.96 | bwd_microstep: 125.02 | bwd_inner_microstep: 124.88 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1955 +[2025-05-01 23:12:05,918] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 197.63 | bwd_microstep: 290.31 | bwd_inner_microstep: 290.29 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1934 +[2025-05-01 23:12:06,418] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.06 | bwd_microstep: 288.45 | bwd_inner_microstep: 288.43 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1894 +[2025-05-01 23:12:06,900] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.14 | bwd_microstep: 274.99 | bwd_inner_microstep: 274.97 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 340 +[2025-05-01 23:12:07,136] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 92.31 | bwd_microstep: 126.72 | bwd_inner_microstep: 126.46 | bwd_allreduce_microstep: 0.10 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-01 23:12:07,617] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.56 | bwd_microstep: 273.78 | bwd_inner_microstep: 273.76 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-01 23:12:08,096] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.21 | bwd_microstep: 272.78 | bwd_inner_microstep: 272.77 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:12:08,575] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.21 | bwd_microstep: 272.63 | bwd_inner_microstep: 272.61 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 23:12:09,056] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.95 | bwd_microstep: 272.96 | bwd_inner_microstep: 272.94 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 23:12:09,536] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.23 | bwd_microstep: 271.43 | bwd_inner_microstep: 271.41 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 23:12:10,017] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.23 | bwd_microstep: 271.50 | bwd_inner_microstep: 271.48 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 23:12:10,494] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.91 | bwd_microstep: 271.24 | bwd_inner_microstep: 271.22 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.17 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-01 23:12:10,970] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.43 | bwd_microstep: 271.04 | bwd_inner_microstep: 271.02 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2052 +[2025-05-01 23:12:11,595] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.49 | optimizer_step: 16.76 +[2025-05-01 23:12:11,595] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 204.08 | bwd_microstep: 379.06 | bwd_inner_microstep: 302.26 | bwd_allreduce_microstep: 76.75 | step_microstep: 24.80 +[2025-05-01 23:12:11,597] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2878.62 | bwd: 4316.34 | bwd_inner: 4238.96 | bwd_allreduce: 76.96 | step: 26.03 + 4%|▍ | 373/8720 [56:45<16:04:08, 6.93s/it] {'loss': 1.2682, 'grad_norm': 3.7187936305999756, 'learning_rate': 9.995750979469237e-06, 'epoch': 0.43} + 4%|▍ | 373/8720 [56:45<16:04:08, 6.93s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 464 +[2025-05-01 23:12:11,828] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 78.84 | bwd_microstep: 131.13 | bwd_inner_microstep: 130.90 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1939 +[2025-05-01 23:12:12,328] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.49 | bwd_microstep: 288.70 | bwd_inner_microstep: 288.69 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1896 +[2025-05-01 23:12:12,809] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.06 | bwd_microstep: 275.30 | bwd_inner_microstep: 275.28 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-01 23:12:13,287] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.79 | bwd_microstep: 273.52 | bwd_inner_microstep: 273.50 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-01 23:12:13,767] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.98 | bwd_microstep: 273.44 | bwd_inner_microstep: 273.42 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-01 23:12:14,245] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.59 | bwd_microstep: 273.41 | bwd_inner_microstep: 273.39 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 836 +[2025-05-01 23:12:14,480] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.00 | bwd_microstep: 126.31 | bwd_inner_microstep: 126.22 | bwd_allreduce_microstep: 0.04 | step_microstep: 0.09 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 333 +[2025-05-01 23:12:14,686] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 72.58 | bwd_microstep: 118.98 | bwd_inner_microstep: 118.85 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 23:12:15,163] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.53 | bwd_microstep: 272.70 | bwd_inner_microstep: 272.68 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 23:12:15,641] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.26 | bwd_microstep: 272.35 | bwd_inner_microstep: 272.33 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1344 +[2025-05-01 23:12:16,003] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.07 | bwd_microstep: 204.71 | bwd_inner_microstep: 204.44 | bwd_allreduce_microstep: 0.10 | step_microstep: 0.12 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 833 +[2025-05-01 23:12:16,240] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.02 | bwd_microstep: 126.13 | bwd_inner_microstep: 125.98 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 23:12:16,717] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.99 | bwd_microstep: 271.19 | bwd_inner_microstep: 271.17 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 23:12:17,194] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.99 | bwd_microstep: 271.17 | bwd_inner_microstep: 271.15 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1849 +[2025-05-01 23:12:17,670] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.85 | bwd_microstep: 270.84 | bwd_inner_microstep: 270.82 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1893 +[2025-05-01 23:12:18,269] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.15 | optimizer_gradients: 2.35 | optimizer_step: 31.22 +[2025-05-01 23:12:18,271] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.44 | bwd_microstep: 350.29 | bwd_inner_microstep: 275.45 | bwd_allreduce_microstep: 74.79 | step_microstep: 41.17 +[2025-05-01 23:12:18,272] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2565.16 | bwd: 3800.23 | bwd_inner: 3724.43 | bwd_allreduce: 75.16 | step: 42.29 + 4%|▍ | 374/8720 [56:52<15:53:29, 6.85s/it] {'loss': 1.3412, 'grad_norm': 5.446808815002441, 'learning_rate': 9.995674086771922e-06, 'epoch': 0.43} + 4%|▍ | 374/8720 [56:52<15:53:29, 6.85s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1896 +[2025-05-01 23:12:18,765] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.75 | bwd_microstep: 274.53 | bwd_inner_microstep: 274.51 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1364 +[2025-05-01 23:12:19,137] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 144.60 | bwd_microstep: 207.32 | bwd_inner_microstep: 207.14 | bwd_allreduce_microstep: 0.09 | step_microstep: 0.21 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 340 +[2025-05-01 23:12:19,359] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 84.49 | bwd_microstep: 119.58 | bwd_inner_microstep: 119.24 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.23 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 23:12:19,840] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.55 | bwd_microstep: 272.63 | bwd_inner_microstep: 272.61 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-01 23:12:20,324] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.39 | bwd_microstep: 272.93 | bwd_inner_microstep: 272.87 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.21 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 23:12:20,806] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.10 | bwd_microstep: 272.64 | bwd_inner_microstep: 272.62 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:12:21,289] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.55 | bwd_microstep: 272.63 | bwd_inner_microstep: 272.61 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.21 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-01 23:12:21,771] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.52 | bwd_microstep: 272.82 | bwd_inner_microstep: 272.80 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.12 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1355 +[2025-05-01 23:12:22,143] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 142.28 | bwd_microstep: 206.49 | bwd_inner_microstep: 206.39 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.14 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 23:12:22,625] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.36 | bwd_microstep: 272.33 | bwd_inner_microstep: 272.31 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 23:12:23,105] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.87 | bwd_microstep: 272.32 | bwd_inner_microstep: 272.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 23:12:23,587] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.22 | bwd_microstep: 272.62 | bwd_inner_microstep: 272.60 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 23:12:24,068] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.67 | bwd_microstep: 271.27 | bwd_inner_microstep: 271.25 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.15 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 827 +[2025-05-01 23:12:24,330] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 109.31 | bwd_microstep: 129.65 | bwd_inner_microstep: 129.43 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-01 23:12:24,808] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.51 | bwd_microstep: 270.97 | bwd_inner_microstep: 270.96 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1356 +[2025-05-01 23:12:25,280] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.07 | optimizer_gradients: 2.47 | optimizer_step: 16.57 +[2025-05-01 23:12:25,281] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.63 | bwd_microstep: 288.35 | bwd_inner_microstep: 207.38 | bwd_allreduce_microstep: 80.86 | step_microstep: 25.35 +[2025-05-01 23:12:25,283] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2697.43 | bwd: 3949.22 | bwd_inner: 3867.18 | bwd_allreduce: 81.31 | step: 27.18 + 4%|▍ | 375/8720 [56:59<15:59:48, 6.90s/it] {'loss': 1.1181, 'grad_norm': 4.55204963684082, 'learning_rate': 9.995596504853648e-06, 'epoch': 0.43} + 4%|▍ | 375/8720 [56:59<15:59:48, 6.90s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1918 +[2025-05-01 23:12:25,773] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.03 | bwd_microstep: 275.96 | bwd_inner_microstep: 275.94 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.13 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 371 +[2025-05-01 23:12:26,008] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.42 | bwd_microstep: 123.05 | bwd_inner_microstep: 122.83 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.13 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 350 +[2025-05-01 23:12:26,232] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 84.66 | bwd_microstep: 120.75 | bwd_inner_microstep: 120.55 | bwd_allreduce_microstep: 0.08 | step_microstep: 0.13 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-01 23:12:26,714] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.48 | bwd_microstep: 273.45 | bwd_inner_microstep: 273.44 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.26 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 23:12:27,197] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.87 | bwd_microstep: 272.76 | bwd_inner_microstep: 272.75 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-01 23:12:27,681] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.22 | bwd_microstep: 273.17 | bwd_inner_microstep: 273.15 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 327 +[2025-05-01 23:12:27,936] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.94 | bwd_microstep: 137.12 | bwd_inner_microstep: 136.95 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.13 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 840 +[2025-05-01 23:12:28,174] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 92.96 | bwd_microstep: 127.04 | bwd_inner_microstep: 126.80 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.13 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-01 23:12:28,656] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.84 | bwd_microstep: 272.98 | bwd_inner_microstep: 272.96 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.23 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 23:12:29,140] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.23 | bwd_microstep: 272.79 | bwd_inner_microstep: 272.72 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 23:12:29,626] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.80 | bwd_microstep: 272.57 | bwd_inner_microstep: 272.56 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.15 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 23:12:30,110] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.39 | bwd_microstep: 272.47 | bwd_inner_microstep: 272.46 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 23:12:30,591] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.17 | bwd_microstep: 273.26 | bwd_inner_microstep: 273.04 | bwd_allreduce_microstep: 0.08 | step_microstep: 0.16 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 23:12:31,070] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.98 | bwd_microstep: 271.42 | bwd_inner_microstep: 271.36 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.14 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1961 +[2025-05-01 23:12:31,577] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 196.29 | bwd_microstep: 290.70 | bwd_inner_microstep: 290.68 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.21 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-01 23:12:32,164] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.50 | optimizer_step: 16.59 +[2025-05-01 23:12:32,165] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.58 | bwd_microstep: 351.84 | bwd_inner_microstep: 273.44 | bwd_allreduce_microstep: 78.27 | step_microstep: 25.07 +[2025-05-01 23:12:32,166] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2639.45 | bwd: 3881.59 | bwd_inner: 3801.94 | bwd_allreduce: 78.71 | step: 27.33 + 4%|▍ | 376/8720 [57:05<15:58:58, 6.90s/it] {'loss': 1.192, 'grad_norm': 4.823653697967529, 'learning_rate': 9.995518233725118e-06, 'epoch': 0.43} + 4%|▍ | 376/8720 [57:05<15:58:58, 6.90s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2114 +[2025-05-01 23:12:32,714] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 208.85 | bwd_microstep: 312.51 | bwd_inner_microstep: 312.43 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.43 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-01 23:12:33,196] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.87 | bwd_microstep: 273.98 | bwd_inner_microstep: 273.96 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-01 23:12:33,682] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.54 | bwd_microstep: 273.47 | bwd_inner_microstep: 273.46 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-01 23:12:34,165] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.76 | bwd_microstep: 273.59 | bwd_inner_microstep: 273.33 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.20 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 852 +[2025-05-01 23:12:34,421] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 105.77 | bwd_microstep: 132.30 | bwd_inner_microstep: 131.99 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.12 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 326 +[2025-05-01 23:12:34,673] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 98.32 | bwd_microstep: 137.20 | bwd_inner_microstep: 136.82 | bwd_allreduce_microstep: 0.16 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-01 23:12:35,154] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.54 | bwd_microstep: 273.35 | bwd_inner_microstep: 273.34 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.17 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-01 23:12:35,634] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.21 | bwd_microstep: 273.04 | bwd_inner_microstep: 273.02 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.22 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 326 +[2025-05-01 23:12:35,859] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 83.39 | bwd_microstep: 125.71 | bwd_inner_microstep: 125.45 | bwd_allreduce_microstep: 0.10 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 23:12:36,336] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.81 | bwd_microstep: 272.81 | bwd_inner_microstep: 272.71 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.22 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 23:12:36,814] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.33 | bwd_microstep: 272.65 | bwd_inner_microstep: 272.63 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 23:12:37,293] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.84 | bwd_microstep: 272.60 | bwd_inner_microstep: 272.58 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 23:12:37,772] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.37 | bwd_microstep: 272.81 | bwd_inner_microstep: 272.79 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 23:12:38,250] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.40 | bwd_microstep: 271.40 | bwd_inner_microstep: 271.37 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.27 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 23:12:38,731] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.61 | bwd_microstep: 271.35 | bwd_inner_microstep: 271.33 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 1010 +[2025-05-01 23:12:39,124] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.10 | optimizer_gradients: 2.43 | optimizer_step: 31.32 +[2025-05-01 23:12:39,125] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 104.33 | bwd_microstep: 230.43 | bwd_inner_microstep: 152.43 | bwd_allreduce_microstep: 77.84 | step_microstep: 40.02 +[2025-05-01 23:12:39,126] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2681.56 | bwd: 3939.41 | bwd_inner: 3859.98 | bwd_allreduce: 78.36 | step: 42.25 + 4%|▍ | 377/8720 [57:12<16:01:29, 6.91s/it] {'loss': 1.3317, 'grad_norm': 5.980020523071289, 'learning_rate': 9.995439273397129e-06, 'epoch': 0.43} + 4%|▍ | 377/8720 [57:12<16:01:29, 6.91s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1899 +[2025-05-01 23:12:39,617] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 191.03 | bwd_microstep: 275.55 | bwd_inner_microstep: 275.53 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1891 +[2025-05-01 23:12:40,102] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 191.18 | bwd_microstep: 275.46 | bwd_inner_microstep: 275.44 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-01 23:12:40,583] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.73 | bwd_microstep: 273.39 | bwd_inner_microstep: 273.38 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-01 23:12:41,065] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.55 | bwd_microstep: 274.00 | bwd_inner_microstep: 273.98 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 344 +[2025-05-01 23:12:41,298] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 85.92 | bwd_microstep: 130.11 | bwd_inner_microstep: 129.78 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1104 +[2025-05-01 23:12:41,593] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 115.90 | bwd_microstep: 162.29 | bwd_inner_microstep: 162.16 | bwd_allreduce_microstep: 0.04 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-01 23:12:42,075] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.72 | bwd_microstep: 274.20 | bwd_inner_microstep: 274.18 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-01 23:12:42,557] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.62 | bwd_microstep: 273.71 | bwd_inner_microstep: 273.69 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 23:12:43,040] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.70 | bwd_microstep: 273.76 | bwd_inner_microstep: 273.41 | bwd_allreduce_microstep: 0.09 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 23:12:43,520] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.35 | bwd_microstep: 273.03 | bwd_inner_microstep: 273.01 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-01 23:12:44,001] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.00 | bwd_microstep: 273.45 | bwd_inner_microstep: 273.43 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-01 23:12:44,480] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.13 | bwd_microstep: 273.46 | bwd_inner_microstep: 273.45 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1354 +[2025-05-01 23:12:44,846] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.80 | bwd_microstep: 207.05 | bwd_inner_microstep: 206.97 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:12:45,325] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.35 | bwd_microstep: 273.05 | bwd_inner_microstep: 273.03 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.21 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 23:12:45,801] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.16 | bwd_microstep: 271.60 | bwd_inner_microstep: 271.58 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 829 +[2025-05-01 23:12:46,155] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.08 | optimizer_gradients: 2.35 | optimizer_step: 30.55 +[2025-05-01 23:12:46,156] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.81 | bwd_microstep: 204.92 | bwd_inner_microstep: 131.60 | bwd_allreduce_microstep: 73.22 | step_microstep: 38.01 +[2025-05-01 23:12:46,157] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2714.61 | bwd: 3989.13 | bwd_inner: 3914.89 | bwd_allreduce: 73.61 | step: 39.73 + 4%|▍ | 378/8720 [57:19<16:06:07, 6.95s/it] {'loss': 1.1753, 'grad_norm': 4.984204292297363, 'learning_rate': 9.995359623880574e-06, 'epoch': 0.43} + 4%|▍ | 378/8720 [57:19<16:06:07, 6.95s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1934 +[2025-05-01 23:12:46,661] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 196.10 | bwd_microstep: 287.90 | bwd_inner_microstep: 287.89 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1904 +[2025-05-01 23:12:47,143] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.48 | bwd_microstep: 275.77 | bwd_inner_microstep: 275.76 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 872 +[2025-05-01 23:12:47,398] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 97.09 | bwd_microstep: 134.11 | bwd_inner_microstep: 134.10 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-01 23:12:47,882] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.37 | bwd_microstep: 273.29 | bwd_inner_microstep: 273.27 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 343 +[2025-05-01 23:12:48,098] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 81.38 | bwd_microstep: 118.26 | bwd_inner_microstep: 118.11 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-01 23:12:48,578] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.89 | bwd_microstep: 273.46 | bwd_inner_microstep: 273.44 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-01 23:12:49,059] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.56 | bwd_microstep: 273.19 | bwd_inner_microstep: 273.17 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-01 23:12:49,540] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.23 | bwd_microstep: 273.75 | bwd_inner_microstep: 273.73 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 6, images per sample: 6.0, dynamic token length: 1618 +[2025-05-01 23:12:49,967] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 163.79 | bwd_microstep: 246.18 | bwd_inner_microstep: 246.11 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.13 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-01 23:12:50,452] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.22 | bwd_microstep: 273.25 | bwd_inner_microstep: 273.23 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-01 23:12:50,935] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.58 | bwd_microstep: 272.91 | bwd_inner_microstep: 272.89 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 23:12:51,419] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.39 | bwd_microstep: 272.31 | bwd_inner_microstep: 272.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 23:12:51,902] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.15 | bwd_microstep: 272.45 | bwd_inner_microstep: 272.43 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 23:12:52,384] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.36 | bwd_microstep: 271.37 | bwd_inner_microstep: 271.35 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 23:12:52,863] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.98 | bwd_microstep: 271.11 | bwd_inner_microstep: 271.10 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 23:12:53,454] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.37 | optimizer_step: 30.31 +[2025-05-01 23:12:53,454] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.03 | bwd_microstep: 348.32 | bwd_inner_microstep: 271.58 | bwd_allreduce_microstep: 76.69 | step_microstep: 37.91 +[2025-05-01 23:12:53,455] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2804.18 | bwd: 4137.69 | bwd_inner: 4060.49 | bwd_allreduce: 76.86 | step: 39.07 + 4%|▍ | 379/8720 [57:27<16:20:35, 7.05s/it] {'loss': 1.2546, 'grad_norm': 3.4058103561401367, 'learning_rate': 9.995279285186445e-06, 'epoch': 0.43} + 4%|▍ | 379/8720 [57:27<16:20:35, 7.05s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1915 +[2025-05-01 23:12:53,941] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.06 | bwd_microstep: 275.79 | bwd_inner_microstep: 275.78 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1893 +[2025-05-01 23:12:54,420] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.07 | bwd_microstep: 274.85 | bwd_inner_microstep: 274.84 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1888 +[2025-05-01 23:12:54,899] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.14 | bwd_microstep: 274.64 | bwd_inner_microstep: 274.62 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-01 23:12:55,379] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.24 | bwd_microstep: 274.37 | bwd_inner_microstep: 274.35 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1356 +[2025-05-01 23:12:55,743] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.36 | bwd_microstep: 206.87 | bwd_inner_microstep: 206.58 | bwd_allreduce_microstep: 0.08 | step_microstep: 0.14 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:12:56,224] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.51 | bwd_microstep: 272.63 | bwd_inner_microstep: 272.61 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-01 23:12:56,703] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.85 | bwd_microstep: 272.87 | bwd_inner_microstep: 272.85 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 326 +[2025-05-01 23:12:56,932] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 91.73 | bwd_microstep: 121.08 | bwd_inner_microstep: 120.77 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:12:57,412] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.55 | bwd_microstep: 272.75 | bwd_inner_microstep: 272.74 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 23:12:57,893] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.43 | bwd_microstep: 272.43 | bwd_inner_microstep: 272.41 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 23:12:58,377] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.21 | bwd_microstep: 272.25 | bwd_inner_microstep: 272.23 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 834 +[2025-05-01 23:12:58,616] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.33 | bwd_microstep: 126.18 | bwd_inner_microstep: 125.93 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 23:12:59,093] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.11 | bwd_microstep: 271.10 | bwd_inner_microstep: 271.08 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1344 +[2025-05-01 23:12:59,456] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.40 | bwd_microstep: 204.69 | bwd_inner_microstep: 204.66 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 832 +[2025-05-01 23:12:59,697] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.37 | bwd_microstep: 130.08 | bwd_inner_microstep: 129.86 | bwd_allreduce_microstep: 0.10 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 23:13:00,275] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.38 | optimizer_step: 16.48 +[2025-05-01 23:13:00,275] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.99 | bwd_microstep: 348.93 | bwd_inner_microstep: 271.96 | bwd_allreduce_microstep: 76.92 | step_microstep: 24.35 +[2025-05-01 23:13:00,277] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2640.99 | bwd: 3871.62 | bwd_inner: 3793.44 | bwd_allreduce: 77.40 | step: 25.47 + 4%|▍ | 380/8720 [57:34<16:10:51, 6.98s/it] {'loss': 1.4766, 'grad_norm': 4.514821529388428, 'learning_rate': 9.995198257325824e-06, 'epoch': 0.44} + 4%|▍ | 380/8720 [57:34<16:10:51, 6.98s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 350 +[2025-05-01 23:13:00,507] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 79.60 | bwd_microstep: 129.19 | bwd_inner_microstep: 129.04 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-01 23:13:00,986] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.12 | bwd_microstep: 273.76 | bwd_inner_microstep: 273.74 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-01 23:13:01,466] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.08 | bwd_microstep: 273.65 | bwd_inner_microstep: 273.63 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-01 23:13:01,944] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.07 | bwd_microstep: 274.20 | bwd_inner_microstep: 274.18 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1887 +[2025-05-01 23:13:02,423] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.48 | bwd_microstep: 274.55 | bwd_inner_microstep: 274.53 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1099 +[2025-05-01 23:13:02,718] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 117.74 | bwd_microstep: 161.49 | bwd_inner_microstep: 161.32 | bwd_allreduce_microstep: 0.08 | step_microstep: 0.18 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 328 +[2025-05-01 23:13:02,938] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 69.68 | bwd_microstep: 136.44 | bwd_inner_microstep: 136.15 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 23:13:03,413] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.65 | bwd_microstep: 272.66 | bwd_inner_microstep: 272.64 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 325 +[2025-05-01 23:13:03,628] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 75.90 | bwd_microstep: 124.59 | bwd_inner_microstep: 124.34 | bwd_allreduce_microstep: 0.10 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 23:13:04,104] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.43 | bwd_microstep: 272.50 | bwd_inner_microstep: 272.48 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 23:13:04,579] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.36 | bwd_microstep: 272.20 | bwd_inner_microstep: 272.18 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 322 +[2025-05-01 23:13:04,801] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 87.07 | bwd_microstep: 118.30 | bwd_inner_microstep: 118.14 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 23:13:05,277] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.41 | bwd_microstep: 271.24 | bwd_inner_microstep: 271.22 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 23:13:05,753] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.87 | bwd_microstep: 271.36 | bwd_inner_microstep: 271.34 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 318 +[2025-05-01 23:13:05,993] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.90 | bwd_microstep: 125.51 | bwd_inner_microstep: 125.26 | bwd_allreduce_microstep: 0.10 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 23:13:06,573] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.64 | optimizer_step: 16.81 +[2025-05-01 23:13:06,573] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.79 | bwd_microstep: 349.50 | bwd_inner_microstep: 271.96 | bwd_allreduce_microstep: 77.48 | step_microstep: 25.20 +[2025-05-01 23:13:06,575] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2409.84 | bwd: 3601.24 | bwd_inner: 3522.39 | bwd_allreduce: 78.05 | step: 26.28 + 4%|▍ | 381/8720 [57:40<15:42:08, 6.78s/it] {'loss': 1.5454, 'grad_norm': 5.335489273071289, 'learning_rate': 9.99511654030989e-06, 'epoch': 0.44} + 4%|▍ | 381/8720 [57:40<15:42:08, 6.78s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 339 +[2025-05-01 23:13:06,814] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 82.50 | bwd_microstep: 134.76 | bwd_inner_microstep: 134.52 | bwd_allreduce_microstep: 0.09 | step_microstep: 0.10 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1370 +[2025-05-01 23:13:07,181] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.25 | bwd_microstep: 207.85 | bwd_inner_microstep: 207.84 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-01 23:13:07,663] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.29 | bwd_microstep: 274.38 | bwd_inner_microstep: 274.37 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-01 23:13:08,148] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.44 | bwd_microstep: 274.37 | bwd_inner_microstep: 274.36 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:13:08,631] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.91 | bwd_microstep: 273.03 | bwd_inner_microstep: 273.02 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 323 +[2025-05-01 23:13:08,879] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 98.04 | bwd_microstep: 129.40 | bwd_inner_microstep: 129.14 | bwd_allreduce_microstep: 0.08 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-01 23:13:09,359] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.99 | bwd_microstep: 273.47 | bwd_inner_microstep: 273.46 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-01 23:13:09,843] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.35 | bwd_microstep: 273.40 | bwd_inner_microstep: 273.38 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-01 23:13:10,328] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.48 | bwd_microstep: 273.46 | bwd_inner_microstep: 273.44 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 23:13:10,814] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.98 | bwd_microstep: 273.07 | bwd_inner_microstep: 273.05 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 23:13:11,298] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.52 | bwd_microstep: 271.85 | bwd_inner_microstep: 271.84 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.14 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-01 23:13:11,784] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.38 | bwd_microstep: 271.68 | bwd_inner_microstep: 271.66 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 23:13:12,264] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.47 | bwd_microstep: 271.96 | bwd_inner_microstep: 271.94 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-01 23:13:12,744] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.43 | bwd_microstep: 271.72 | bwd_inner_microstep: 271.71 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1850 +[2025-05-01 23:13:13,225] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.27 | bwd_microstep: 271.53 | bwd_inner_microstep: 271.51 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-01 23:13:13,816] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.42 | optimizer_step: 16.61 +[2025-05-01 23:13:13,816] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.42 | bwd_microstep: 354.32 | bwd_inner_microstep: 275.76 | bwd_allreduce_microstep: 78.50 | step_microstep: 24.90 +[2025-05-01 23:13:13,818] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2785.27 | bwd: 4100.30 | bwd_inner: 4021.13 | bwd_allreduce: 78.70 | step: 26.07 + 4%|▍ | 382/8720 [57:47<16:01:22, 6.92s/it] {'loss': 0.8664, 'grad_norm': 4.049262046813965, 'learning_rate': 9.995034134149918e-06, 'epoch': 0.44} + 4%|▍ | 382/8720 [57:47<16:01:22, 6.92s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2101 +[2025-05-01 23:13:14,353] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 205.89 | bwd_microstep: 305.09 | bwd_inner_microstep: 305.07 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1893 +[2025-05-01 23:13:14,833] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.33 | bwd_microstep: 274.63 | bwd_inner_microstep: 274.61 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1902 +[2025-05-01 23:13:15,321] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.33 | bwd_microstep: 275.61 | bwd_inner_microstep: 275.59 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1363 +[2025-05-01 23:13:15,684] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.85 | bwd_microstep: 206.88 | bwd_inner_microstep: 206.87 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-01 23:13:16,163] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.06 | bwd_microstep: 273.06 | bwd_inner_microstep: 273.04 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1357 +[2025-05-01 23:13:16,529] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.99 | bwd_microstep: 206.80 | bwd_inner_microstep: 206.64 | bwd_allreduce_microstep: 0.08 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-01 23:13:17,009] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.70 | bwd_microstep: 273.28 | bwd_inner_microstep: 273.26 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-01 23:13:17,489] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.96 | bwd_microstep: 272.82 | bwd_inner_microstep: 272.80 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 23:13:17,966] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.28 | bwd_microstep: 272.52 | bwd_inner_microstep: 272.50 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 23:13:18,447] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.33 | bwd_microstep: 273.21 | bwd_inner_microstep: 273.20 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 844 +[2025-05-01 23:13:18,695] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 99.71 | bwd_microstep: 132.07 | bwd_inner_microstep: 131.86 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:13:19,173] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.79 | bwd_microstep: 272.53 | bwd_inner_microstep: 272.51 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 23:13:19,650] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.09 | bwd_microstep: 272.11 | bwd_inner_microstep: 272.10 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 23:13:20,129] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.55 | bwd_microstep: 272.28 | bwd_inner_microstep: 272.26 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 23:13:20,610] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.63 | bwd_microstep: 272.58 | bwd_inner_microstep: 272.56 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.12 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 314 +[2025-05-01 23:13:20,954] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.54 | optimizer_step: 16.25 +[2025-05-01 23:13:20,955] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 82.53 | bwd_microstep: 221.85 | bwd_inner_microstep: 144.38 | bwd_allreduce_microstep: 77.29 | step_microstep: 24.45 +[2025-05-01 23:13:20,956] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2746.69 | bwd: 4077.35 | bwd_inner: 3999.31 | bwd_allreduce: 77.56 | step: 25.49 + 4%|▍ | 383/8720 [57:54<16:10:26, 6.98s/it] {'loss': 1.0912, 'grad_norm': 3.6542696952819824, 'learning_rate': 9.994951038857275e-06, 'epoch': 0.44} + 4%|▍ | 383/8720 [57:54<16:10:26, 6.98s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1893 +[2025-05-01 23:13:21,444] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.44 | bwd_microstep: 274.42 | bwd_inner_microstep: 274.40 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1894 +[2025-05-01 23:13:21,927] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.25 | bwd_microstep: 275.18 | bwd_inner_microstep: 275.16 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1370 +[2025-05-01 23:13:22,292] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 142.59 | bwd_microstep: 208.08 | bwd_inner_microstep: 208.00 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 342 +[2025-05-01 23:13:22,504] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 68.16 | bwd_microstep: 130.28 | bwd_inner_microstep: 129.96 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-01 23:13:22,984] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.91 | bwd_microstep: 273.78 | bwd_inner_microstep: 273.76 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-01 23:13:23,466] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.57 | bwd_microstep: 273.74 | bwd_inner_microstep: 273.73 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-01 23:13:23,952] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.19 | bwd_microstep: 273.67 | bwd_inner_microstep: 273.65 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-01 23:13:24,432] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.01 | bwd_microstep: 273.68 | bwd_inner_microstep: 273.67 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:13:24,914] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.91 | bwd_microstep: 273.21 | bwd_inner_microstep: 273.20 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 23:13:25,393] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.76 | bwd_microstep: 271.90 | bwd_inner_microstep: 271.89 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 23:13:25,877] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.89 | bwd_microstep: 271.91 | bwd_inner_microstep: 271.89 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-01 23:13:26,353] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.65 | bwd_microstep: 271.74 | bwd_inner_microstep: 271.73 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 23:13:26,830] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.31 | bwd_microstep: 271.89 | bwd_inner_microstep: 271.88 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 23:13:27,307] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.63 | bwd_microstep: 271.78 | bwd_inner_microstep: 271.76 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2113 +[2025-05-01 23:13:27,842] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 204.60 | bwd_microstep: 313.27 | bwd_inner_microstep: 313.25 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 868 +[2025-05-01 23:13:28,200] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.43 | optimizer_step: 16.50 +[2025-05-01 23:13:28,201] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 104.56 | bwd_microstep: 212.42 | bwd_inner_microstep: 135.56 | bwd_allreduce_microstep: 76.76 | step_microstep: 24.65 +[2025-05-01 23:13:28,202] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2793.11 | bwd: 4141.03 | bwd_inner: 4063.58 | bwd_allreduce: 76.96 | step: 25.70 + 4%|▍ | 384/8720 [58:01<16:21:14, 7.06s/it] {'loss': 1.3969, 'grad_norm': 3.2769904136657715, 'learning_rate': 9.994867254443427e-06, 'epoch': 0.44} + 4%|▍ | 384/8720 [58:01<16:21:14, 7.06s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1983 +[2025-05-01 23:13:28,716] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 198.83 | bwd_microstep: 292.13 | bwd_inner_microstep: 292.11 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.05 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 873 +[2025-05-01 23:13:28,982] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 105.11 | bwd_microstep: 134.39 | bwd_inner_microstep: 134.08 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-01 23:13:29,462] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.52 | bwd_microstep: 274.28 | bwd_inner_microstep: 274.26 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1883 +[2025-05-01 23:13:29,941] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.01 | bwd_microstep: 274.38 | bwd_inner_microstep: 274.36 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-01 23:13:30,420] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.78 | bwd_microstep: 273.98 | bwd_inner_microstep: 273.97 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.18 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 848 +[2025-05-01 23:13:30,664] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.38 | bwd_microstep: 132.87 | bwd_inner_microstep: 132.85 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-01 23:13:31,143] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.33 | bwd_microstep: 273.79 | bwd_inner_microstep: 273.77 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-01 23:13:31,622] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.55 | bwd_microstep: 273.69 | bwd_inner_microstep: 273.67 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 852 +[2025-05-01 23:13:31,868] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 97.12 | bwd_microstep: 133.31 | bwd_inner_microstep: 133.12 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-01 23:13:32,347] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.39 | bwd_microstep: 272.98 | bwd_inner_microstep: 272.97 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1353 +[2025-05-01 23:13:32,711] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.81 | bwd_microstep: 206.17 | bwd_inner_microstep: 206.15 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:13:33,189] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.24 | bwd_microstep: 272.76 | bwd_inner_microstep: 272.74 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 23:13:33,671] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.77 | bwd_microstep: 272.75 | bwd_inner_microstep: 272.74 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1092 +[2025-05-01 23:13:33,968] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 115.53 | bwd_microstep: 161.21 | bwd_inner_microstep: 160.98 | bwd_allreduce_microstep: 0.14 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 23:13:34,446] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.08 | bwd_microstep: 272.47 | bwd_inner_microstep: 272.46 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1130 +[2025-05-01 23:13:34,846] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.48 | optimizer_step: 16.40 +[2025-05-01 23:13:34,846] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 116.22 | bwd_microstep: 242.61 | bwd_inner_microstep: 164.42 | bwd_allreduce_microstep: 78.09 | step_microstep: 24.49 +[2025-05-01 23:13:34,848] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2570.32 | bwd: 3763.88 | bwd_inner: 3684.79 | bwd_allreduce: 78.47 | step: 25.75 + 4%|▍ | 385/8720 [58:08<16:03:43, 6.94s/it] {'loss': 1.2859, 'grad_norm': 5.854839324951172, 'learning_rate': 9.994782780919932e-06, 'epoch': 0.44} + 4%|▍ | 385/8720 [58:08<16:03:43, 6.94s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1945 +[2025-05-01 23:13:35,357] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 197.78 | bwd_microstep: 288.81 | bwd_inner_microstep: 288.79 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 383 +[2025-05-01 23:13:35,569] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 74.69 | bwd_microstep: 122.23 | bwd_inner_microstep: 121.99 | bwd_allreduce_microstep: 0.10 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1922 +[2025-05-01 23:13:36,065] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 193.71 | bwd_microstep: 287.33 | bwd_inner_microstep: 287.31 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 357 +[2025-05-01 23:13:36,270] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 68.17 | bwd_microstep: 123.55 | bwd_inner_microstep: 123.23 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1893 +[2025-05-01 23:13:36,749] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.71 | bwd_microstep: 274.88 | bwd_inner_microstep: 274.86 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1883 +[2025-05-01 23:13:37,230] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.12 | bwd_microstep: 274.39 | bwd_inner_microstep: 274.38 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-01 23:13:37,709] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.04 | bwd_microstep: 273.74 | bwd_inner_microstep: 273.72 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1886 +[2025-05-01 23:13:38,192] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.48 | bwd_microstep: 274.61 | bwd_inner_microstep: 274.59 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-01 23:13:38,672] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.77 | bwd_microstep: 273.22 | bwd_inner_microstep: 273.20 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:13:39,153] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.73 | bwd_microstep: 272.68 | bwd_inner_microstep: 272.66 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.15 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:13:39,638] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.67 | bwd_microstep: 272.87 | bwd_inner_microstep: 272.85 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 320 +[2025-05-01 23:13:39,873] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 90.09 | bwd_microstep: 126.93 | bwd_inner_microstep: 126.62 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 23:13:40,351] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.33 | bwd_microstep: 271.46 | bwd_inner_microstep: 271.44 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 23:13:40,831] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.44 | bwd_microstep: 271.60 | bwd_inner_microstep: 271.54 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.31 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 23:13:41,312] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.62 | bwd_microstep: 271.64 | bwd_inner_microstep: 271.62 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 23:13:41,926] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.09 | optimizer_gradients: 2.40 | optimizer_step: 31.38 +[2025-05-01 23:13:41,927] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.18 | bwd_microstep: 366.46 | bwd_inner_microstep: 271.78 | bwd_allreduce_microstep: 94.60 | step_microstep: 41.73 +[2025-05-01 23:13:41,929] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2701.16 | bwd: 4046.53 | bwd_inner: 3950.75 | bwd_allreduce: 95.00 | step: 43.22 + 4%|▍ | 386/8720 [58:15<16:09:36, 6.98s/it] {'loss': 1.4513, 'grad_norm': 5.1230621337890625, 'learning_rate': 9.994697618298443e-06, 'epoch': 0.44} + 4%|▍ | 386/8720 [58:15<16:09:36, 6.98s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1931 +[2025-05-01 23:13:42,436] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 196.59 | bwd_microstep: 287.73 | bwd_inner_microstep: 287.71 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-01 23:13:42,915] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.62 | bwd_microstep: 274.26 | bwd_inner_microstep: 274.24 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-01 23:13:43,394] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.62 | bwd_microstep: 273.96 | bwd_inner_microstep: 273.94 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-01 23:13:43,871] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.10 | bwd_microstep: 273.45 | bwd_inner_microstep: 273.43 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-01 23:13:44,348] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.68 | bwd_microstep: 272.91 | bwd_inner_microstep: 272.90 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 23:13:44,823] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.07 | bwd_microstep: 272.37 | bwd_inner_microstep: 272.36 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 23:13:45,301] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.95 | bwd_microstep: 272.80 | bwd_inner_microstep: 272.78 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.22 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 23:13:45,780] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.88 | bwd_microstep: 272.61 | bwd_inner_microstep: 272.60 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 23:13:46,261] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.61 | bwd_microstep: 275.14 | bwd_inner_microstep: 275.12 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 23:13:46,738] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.58 | bwd_microstep: 271.20 | bwd_inner_microstep: 271.18 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 23:13:47,218] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.53 | bwd_microstep: 271.42 | bwd_inner_microstep: 271.40 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 23:13:47,696] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.93 | bwd_microstep: 271.40 | bwd_inner_microstep: 271.39 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 23:13:48,177] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.92 | bwd_microstep: 271.39 | bwd_inner_microstep: 271.37 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 23:13:48,658] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.54 | bwd_microstep: 271.17 | bwd_inner_microstep: 271.15 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 23:13:49,138] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.26 | bwd_microstep: 271.09 | bwd_inner_microstep: 271.07 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 23:13:49,734] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.37 | optimizer_step: 31.27 +[2025-05-01 23:13:49,735] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.25 | bwd_microstep: 347.73 | bwd_inner_microstep: 271.54 | bwd_allreduce_microstep: 76.14 | step_microstep: 39.22 +[2025-05-01 23:13:49,736] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 3027.78 | bwd: 4450.64 | bwd_inner: 4374.18 | bwd_allreduce: 76.22 | step: 40.37 + 4%|▍ | 387/8720 [58:23<16:43:55, 7.23s/it] {'loss': 1.2333, 'grad_norm': 5.114424228668213, 'learning_rate': 9.994611766590714e-06, 'epoch': 0.44} + 4%|▍ | 387/8720 [58:23<16:43:55, 7.23s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 448 +[2025-05-01 23:13:49,976] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 79.42 | bwd_microstep: 138.08 | bwd_inner_microstep: 137.93 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 378 +[2025-05-01 23:13:50,229] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 87.72 | bwd_microstep: 150.12 | bwd_inner_microstep: 149.97 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1899 +[2025-05-01 23:13:50,711] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.65 | bwd_microstep: 275.57 | bwd_inner_microstep: 275.56 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-01 23:13:51,189] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.08 | bwd_microstep: 274.40 | bwd_inner_microstep: 274.38 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-01 23:13:51,665] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.14 | bwd_microstep: 272.67 | bwd_inner_microstep: 272.65 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-01 23:13:52,142] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.45 | bwd_microstep: 273.37 | bwd_inner_microstep: 273.35 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 23:13:52,618] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.91 | bwd_microstep: 272.65 | bwd_inner_microstep: 272.64 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-01 23:13:53,095] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.40 | bwd_microstep: 272.91 | bwd_inner_microstep: 272.89 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 331 +[2025-05-01 23:13:53,290] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 66.22 | bwd_microstep: 115.61 | bwd_inner_microstep: 115.48 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 23:13:53,766] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.99 | bwd_microstep: 272.76 | bwd_inner_microstep: 272.74 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 23:13:54,241] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.96 | bwd_microstep: 272.41 | bwd_inner_microstep: 272.39 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 23:13:54,717] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.03 | bwd_microstep: 272.41 | bwd_inner_microstep: 272.39 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 23:13:55,193] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.46 | bwd_microstep: 272.35 | bwd_inner_microstep: 272.34 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 830 +[2025-05-01 23:13:55,430] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.26 | bwd_microstep: 129.94 | bwd_inner_microstep: 129.92 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 23:13:55,904] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.59 | bwd_microstep: 271.43 | bwd_inner_microstep: 271.41 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-01 23:13:56,466] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.04 | optimizer_gradients: 2.37 | optimizer_step: 16.72 +[2025-05-01 23:13:56,467] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.44 | bwd_microstep: 336.76 | bwd_inner_microstep: 271.54 | bwd_allreduce_microstep: 65.18 | step_microstep: 23.83 +[2025-05-01 23:13:56,468] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2589.47 | bwd: 3873.48 | bwd_inner: 3807.66 | bwd_allreduce: 65.41 | step: 24.62 + 4%|▍ | 388/8720 [58:30<16:23:01, 7.08s/it] {'loss': 1.2758, 'grad_norm': 3.6650454998016357, 'learning_rate': 9.994525225808585e-06, 'epoch': 0.44} + 4%|▍ | 388/8720 [58:30<16:23:01, 7.08s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1886 +[2025-05-01 23:13:56,952] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.53 | bwd_microstep: 274.37 | bwd_inner_microstep: 274.36 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1371 +[2025-05-01 23:13:57,317] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 142.54 | bwd_microstep: 207.97 | bwd_inner_microstep: 207.95 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 860 +[2025-05-01 23:13:57,559] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.22 | bwd_microstep: 134.01 | bwd_inner_microstep: 133.99 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-01 23:13:58,038] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.63 | bwd_microstep: 274.35 | bwd_inner_microstep: 274.34 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-01 23:13:58,516] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.51 | bwd_microstep: 273.49 | bwd_inner_microstep: 273.47 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-01 23:13:58,995] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.27 | bwd_microstep: 274.25 | bwd_inner_microstep: 274.24 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-01 23:13:59,474] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.12 | bwd_microstep: 273.72 | bwd_inner_microstep: 273.70 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 23:13:59,953] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.22 | bwd_microstep: 273.44 | bwd_inner_microstep: 273.42 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 837 +[2025-05-01 23:14:00,185] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 91.93 | bwd_microstep: 126.55 | bwd_inner_microstep: 126.54 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1349 +[2025-05-01 23:14:00,546] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.47 | bwd_microstep: 206.46 | bwd_inner_microstep: 206.45 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 23:14:01,021] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.83 | bwd_microstep: 271.86 | bwd_inner_microstep: 271.84 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 318 +[2025-05-01 23:14:01,217] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 66.22 | bwd_microstep: 116.78 | bwd_inner_microstep: 116.64 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 23:14:01,693] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.67 | bwd_microstep: 272.49 | bwd_inner_microstep: 272.47 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 23:14:02,170] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.98 | bwd_microstep: 271.93 | bwd_inner_microstep: 271.91 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 23:14:02,647] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.17 | bwd_microstep: 272.30 | bwd_inner_microstep: 272.29 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 23:14:03,214] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.41 | optimizer_step: 16.50 +[2025-05-01 23:14:03,215] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.68 | bwd_microstep: 339.90 | bwd_inner_microstep: 272.38 | bwd_allreduce_microstep: 67.48 | step_microstep: 24.13 +[2025-05-01 23:14:03,216] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2619.75 | bwd: 3863.92 | bwd_inner: 3796.02 | bwd_allreduce: 67.61 | step: 24.81 + 4%|▍ | 389/8720 [58:36<16:09:07, 6.98s/it] {'loss': 0.9506, 'grad_norm': 4.363682746887207, 'learning_rate': 9.994437995963994e-06, 'epoch': 0.45} + 4%|▍ | 389/8720 [58:36<16:09:07, 6.98s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1967 +[2025-05-01 23:14:03,726] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 198.08 | bwd_microstep: 291.23 | bwd_inner_microstep: 291.22 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1921 +[2025-05-01 23:14:04,225] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.08 | bwd_microstep: 287.57 | bwd_inner_microstep: 287.55 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1933 +[2025-05-01 23:14:04,727] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.77 | bwd_microstep: 288.79 | bwd_inner_microstep: 288.78 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 347 +[2025-05-01 23:14:04,957] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 96.32 | bwd_microstep: 116.02 | bwd_inner_microstep: 115.68 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.19 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1356 +[2025-05-01 23:14:05,322] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.66 | bwd_microstep: 206.90 | bwd_inner_microstep: 206.69 | bwd_allreduce_microstep: 0.14 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-01 23:14:05,802] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.56 | bwd_microstep: 273.63 | bwd_inner_microstep: 273.61 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-01 23:14:06,284] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.14 | bwd_microstep: 273.95 | bwd_inner_microstep: 273.94 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-01 23:14:06,766] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.91 | bwd_microstep: 273.15 | bwd_inner_microstep: 273.13 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-01 23:14:07,246] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.12 | bwd_microstep: 272.95 | bwd_inner_microstep: 272.93 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 837 +[2025-05-01 23:14:07,483] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.04 | bwd_microstep: 126.30 | bwd_inner_microstep: 126.28 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 23:14:07,961] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.14 | bwd_microstep: 271.64 | bwd_inner_microstep: 271.62 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.21 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1351 +[2025-05-01 23:14:08,330] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.60 | bwd_microstep: 206.37 | bwd_inner_microstep: 206.31 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.13 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 321 +[2025-05-01 23:14:08,554] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 89.99 | bwd_microstep: 115.07 | bwd_inner_microstep: 114.75 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 23:14:09,032] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.88 | bwd_microstep: 271.46 | bwd_inner_microstep: 271.44 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 23:14:09,512] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.65 | bwd_microstep: 271.47 | bwd_inner_microstep: 271.45 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.27 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 23:14:10,094] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.42 | optimizer_step: 16.67 +[2025-05-01 23:14:10,094] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.56 | bwd_microstep: 349.10 | bwd_inner_microstep: 271.90 | bwd_allreduce_microstep: 77.14 | step_microstep: 24.87 +[2025-05-01 23:14:10,095] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2661.17 | bwd: 3895.73 | bwd_inner: 3817.41 | bwd_allreduce: 77.56 | step: 26.64 + 4%|▍ | 390/8720 [58:43<16:04:55, 6.95s/it] {'loss': 1.3666, 'grad_norm': 6.4577155113220215, 'learning_rate': 9.994350077068982e-06, 'epoch': 0.45} + 4%|▍ | 390/8720 [58:43<16:04:55, 6.95s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 360 +[2025-05-01 23:14:10,317] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 79.87 | bwd_microstep: 120.79 | bwd_inner_microstep: 120.63 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 839 +[2025-05-01 23:14:10,554] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.19 | bwd_microstep: 126.85 | bwd_inner_microstep: 126.77 | bwd_allreduce_microstep: 0.03 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-01 23:14:11,035] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.04 | bwd_microstep: 273.96 | bwd_inner_microstep: 273.94 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:14:11,516] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.35 | bwd_microstep: 272.76 | bwd_inner_microstep: 272.74 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 23:14:11,997] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.61 | bwd_microstep: 272.65 | bwd_inner_microstep: 272.63 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 850 +[2025-05-01 23:14:12,243] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 96.65 | bwd_microstep: 132.84 | bwd_inner_microstep: 132.54 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 23:14:12,722] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.18 | bwd_microstep: 272.71 | bwd_inner_microstep: 272.69 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-01 23:14:13,204] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.13 | bwd_microstep: 273.32 | bwd_inner_microstep: 273.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1345 +[2025-05-01 23:14:13,571] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.74 | bwd_microstep: 206.10 | bwd_inner_microstep: 206.05 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-01 23:14:14,055] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.68 | bwd_microstep: 273.21 | bwd_inner_microstep: 273.19 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 23:14:14,536] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.10 | bwd_microstep: 273.16 | bwd_inner_microstep: 273.14 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 23:14:15,017] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.04 | bwd_microstep: 272.25 | bwd_inner_microstep: 272.23 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 23:14:15,492] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.12 | bwd_microstep: 271.73 | bwd_inner_microstep: 271.71 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 23:14:15,969] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.19 | bwd_microstep: 272.35 | bwd_inner_microstep: 272.33 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 23:14:16,446] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.95 | bwd_microstep: 271.75 | bwd_inner_microstep: 271.74 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1997 +[2025-05-01 23:14:17,048] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.46 | optimizer_step: 16.65 +[2025-05-01 23:14:17,048] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 202.34 | bwd_microstep: 361.27 | bwd_inner_microstep: 294.87 | bwd_allreduce_microstep: 66.35 | step_microstep: 23.94 +[2025-05-01 23:14:17,049] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2690.82 | bwd: 3947.76 | bwd_inner: 3880.63 | bwd_allreduce: 66.66 | step: 24.96 + 4%|▍ | 391/8720 [58:50<16:04:52, 6.95s/it] {'loss': 0.7514, 'grad_norm': 3.5212326049804688, 'learning_rate': 9.994261469135674e-06, 'epoch': 0.45} + 4%|▍ | 391/8720 [58:50<16:04:52, 6.95s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1974 +[2025-05-01 23:14:17,557] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 196.67 | bwd_microstep: 290.83 | bwd_inner_microstep: 290.81 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1926 +[2025-05-01 23:14:18,054] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 194.73 | bwd_microstep: 287.71 | bwd_inner_microstep: 287.69 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1928 +[2025-05-01 23:14:18,552] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 194.92 | bwd_microstep: 287.74 | bwd_inner_microstep: 287.72 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.15 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-01 23:14:19,030] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.76 | bwd_microstep: 273.28 | bwd_inner_microstep: 273.26 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-01 23:14:19,508] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.19 | bwd_microstep: 273.10 | bwd_inner_microstep: 273.08 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 850 +[2025-05-01 23:14:19,749] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.36 | bwd_microstep: 133.04 | bwd_inner_microstep: 133.01 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-01 23:14:20,227] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.90 | bwd_microstep: 273.36 | bwd_inner_microstep: 273.35 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-01 23:14:20,704] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.00 | bwd_microstep: 272.64 | bwd_inner_microstep: 272.62 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1347 +[2025-05-01 23:14:21,066] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.98 | bwd_microstep: 205.78 | bwd_inner_microstep: 205.66 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 23:14:21,543] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.07 | bwd_microstep: 272.79 | bwd_inner_microstep: 272.77 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 23:14:22,021] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.01 | bwd_microstep: 272.63 | bwd_inner_microstep: 272.61 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 23:14:22,498] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.58 | bwd_microstep: 272.70 | bwd_inner_microstep: 272.69 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 320 +[2025-05-01 23:14:22,699] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 72.77 | bwd_microstep: 114.78 | bwd_inner_microstep: 114.47 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 23:14:23,175] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.85 | bwd_microstep: 271.50 | bwd_inner_microstep: 271.49 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 319 +[2025-05-01 23:14:23,375] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 71.75 | bwd_microstep: 114.94 | bwd_inner_microstep: 114.73 | bwd_allreduce_microstep: 0.08 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 23:14:23,939] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.04 | optimizer_gradients: 2.48 | optimizer_step: 16.67 +[2025-05-01 23:14:23,939] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.10 | bwd_microstep: 338.43 | bwd_inner_microstep: 271.81 | bwd_allreduce_microstep: 66.57 | step_microstep: 24.04 +[2025-05-01 23:14:23,940] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2663.41 | bwd: 3955.30 | bwd_inner: 3887.86 | bwd_allreduce: 66.90 | step: 25.02 + 4%|▍ | 392/8720 [58:57<16:02:17, 6.93s/it] {'loss': 1.1212, 'grad_norm': 4.6518330574035645, 'learning_rate': 9.994172172176296e-06, 'epoch': 0.45} + 4%|▍ | 392/8720 [58:57<16:02:17, 6.93s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 375 +[2025-05-01 23:14:24,145] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 67.86 | bwd_microstep: 118.45 | bwd_inner_microstep: 118.29 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 880 +[2025-05-01 23:14:24,393] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 97.90 | bwd_microstep: 135.87 | bwd_inner_microstep: 135.60 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-01 23:14:24,871] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.43 | bwd_microstep: 273.77 | bwd_inner_microstep: 273.75 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 329 +[2025-05-01 23:14:25,095] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 78.19 | bwd_microstep: 128.83 | bwd_inner_microstep: 128.50 | bwd_allreduce_microstep: 0.14 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-01 23:14:25,574] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.34 | bwd_microstep: 273.13 | bwd_inner_microstep: 273.12 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 834 +[2025-05-01 23:14:25,805] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 90.40 | bwd_microstep: 125.95 | bwd_inner_microstep: 125.72 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-01 23:14:26,284] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.37 | bwd_microstep: 273.24 | bwd_inner_microstep: 273.22 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 332 +[2025-05-01 23:14:26,517] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 89.52 | bwd_microstep: 127.57 | bwd_inner_microstep: 127.33 | bwd_allreduce_microstep: 0.08 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:14:26,997] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.21 | bwd_microstep: 272.92 | bwd_inner_microstep: 272.90 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 23:14:27,475] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.33 | bwd_microstep: 272.73 | bwd_inner_microstep: 272.71 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 23:14:27,951] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.85 | bwd_microstep: 272.16 | bwd_inner_microstep: 272.14 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 23:14:28,429] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.16 | bwd_microstep: 272.58 | bwd_inner_microstep: 272.56 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.33 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 23:14:28,927] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.61 | bwd_microstep: 271.49 | bwd_inner_microstep: 271.47 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 833 +[2025-05-01 23:14:29,162] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 92.31 | bwd_microstep: 126.14 | bwd_inner_microstep: 125.84 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2067 +[2025-05-01 23:14:29,685] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 202.53 | bwd_microstep: 303.28 | bwd_inner_microstep: 303.26 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1942 +[2025-05-01 23:14:30,278] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.56 | optimizer_step: 16.79 +[2025-05-01 23:14:30,278] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 196.47 | bwd_microstep: 356.58 | bwd_inner_microstep: 289.52 | bwd_allreduce_microstep: 67.01 | step_microstep: 24.67 +[2025-05-01 23:14:30,280] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2421.20 | bwd: 3604.80 | bwd_inner: 3536.23 | bwd_allreduce: 67.68 | step: 26.41 + 5%|▍ | 393/8720 [59:04<15:37:28, 6.75s/it] {'loss': 1.4232, 'grad_norm': 4.340027809143066, 'learning_rate': 9.994082186203167e-06, 'epoch': 0.45} + 5%|▍ | 393/8720 [59:04<15:37:28, 6.75s/it]dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1551 +[2025-05-01 23:14:30,692] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 152.64 | bwd_microstep: 238.37 | bwd_inner_microstep: 238.16 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1920 +[2025-05-01 23:14:31,174] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.50 | bwd_microstep: 276.55 | bwd_inner_microstep: 276.53 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 369 +[2025-05-01 23:14:31,398] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 76.50 | bwd_microstep: 132.90 | bwd_inner_microstep: 132.77 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.11 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 358 +[2025-05-01 23:14:31,611] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 71.38 | bwd_microstep: 127.38 | bwd_inner_microstep: 127.24 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.11 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 326 +[2025-05-01 23:14:31,824] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 70.85 | bwd_microstep: 127.55 | bwd_inner_microstep: 127.40 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:14:32,302] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.33 | bwd_microstep: 272.88 | bwd_inner_microstep: 272.86 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-01 23:14:32,781] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.96 | bwd_microstep: 273.20 | bwd_inner_microstep: 273.19 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 330 +[2025-05-01 23:14:32,995] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 71.96 | bwd_microstep: 127.60 | bwd_inner_microstep: 127.37 | bwd_allreduce_microstep: 0.09 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:14:33,472] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.05 | bwd_microstep: 272.81 | bwd_inner_microstep: 272.80 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.09 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1345 +[2025-05-01 23:14:33,835] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.34 | bwd_microstep: 205.91 | bwd_inner_microstep: 205.75 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.21 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1345 +[2025-05-01 23:14:34,198] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.53 | bwd_microstep: 205.76 | bwd_inner_microstep: 205.65 | bwd_allreduce_microstep: 0.03 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 23:14:34,674] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.15 | bwd_microstep: 272.13 | bwd_inner_microstep: 272.12 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 23:14:35,151] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.32 | bwd_microstep: 272.36 | bwd_inner_microstep: 272.34 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 23:14:35,626] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.50 | bwd_microstep: 271.12 | bwd_inner_microstep: 271.11 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1085 +[2025-05-01 23:14:35,918] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 115.21 | bwd_microstep: 159.89 | bwd_inner_microstep: 159.87 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 23:14:36,484] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.42 | optimizer_step: 16.59 +[2025-05-01 23:14:36,485] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.80 | bwd_microstep: 338.45 | bwd_inner_microstep: 271.88 | bwd_allreduce_microstep: 66.52 | step_microstep: 24.13 +[2025-05-01 23:14:36,486] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2347.73 | bwd: 3575.02 | bwd_inner: 3507.18 | bwd_allreduce: 67.11 | step: 25.54 + 5%|▍ | 394/8720 [59:10<15:14:30, 6.59s/it] {'loss': 1.1194, 'grad_norm': 3.228370428085327, 'learning_rate': 9.993991511228702e-06, 'epoch': 0.45} + 5%|▍ | 394/8720 [59:10<15:14:30, 6.59s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1917 +[2025-05-01 23:14:36,973] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.95 | bwd_microstep: 275.90 | bwd_inner_microstep: 275.88 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 872 +[2025-05-01 23:14:37,216] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.52 | bwd_microstep: 134.82 | bwd_inner_microstep: 134.81 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1892 +[2025-05-01 23:14:37,697] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.28 | bwd_microstep: 275.08 | bwd_inner_microstep: 275.06 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-01 23:14:38,177] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.49 | bwd_microstep: 273.30 | bwd_inner_microstep: 273.29 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-01 23:14:38,656] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.13 | bwd_microstep: 273.04 | bwd_inner_microstep: 273.03 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 844 +[2025-05-01 23:14:38,899] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.88 | bwd_microstep: 132.59 | bwd_inner_microstep: 132.52 | bwd_allreduce_microstep: 0.03 | step_microstep: 0.08 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 857 +[2025-05-01 23:14:39,141] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.19 | bwd_microstep: 133.29 | bwd_inner_microstep: 133.01 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 23:14:39,620] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.91 | bwd_microstep: 273.42 | bwd_inner_microstep: 273.40 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.20 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1350 +[2025-05-01 23:14:39,984] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.92 | bwd_microstep: 206.08 | bwd_inner_microstep: 206.06 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 23:14:40,462] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.40 | bwd_microstep: 272.65 | bwd_inner_microstep: 272.63 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 23:14:40,942] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.90 | bwd_microstep: 272.23 | bwd_inner_microstep: 272.22 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 23:14:41,423] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.53 | bwd_microstep: 271.39 | bwd_inner_microstep: 271.37 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 23:14:41,901] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.31 | bwd_microstep: 271.31 | bwd_inner_microstep: 271.29 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 23:14:42,379] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.03 | bwd_microstep: 271.36 | bwd_inner_microstep: 271.34 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 23:14:42,860] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.70 | bwd_microstep: 271.15 | bwd_inner_microstep: 271.13 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 23:14:43,442] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.39 | optimizer_step: 16.82 +[2025-05-01 23:14:43,442] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.57 | bwd_microstep: 348.65 | bwd_inner_microstep: 271.69 | bwd_allreduce_microstep: 76.91 | step_microstep: 24.84 +[2025-05-01 23:14:43,444] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2692.32 | bwd: 3956.32 | bwd_inner: 3878.75 | bwd_allreduce: 77.15 | step: 26.23 + 5%|▍ | 395/8720 [59:17<15:29:45, 6.70s/it] {'loss': 1.5359, 'grad_norm': 5.991851329803467, 'learning_rate': 9.993900147265412e-06, 'epoch': 0.45} + 5%|▍ | 395/8720 [59:17<15:29:45, 6.70s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1935 +[2025-05-01 23:14:43,950] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.29 | bwd_microstep: 287.98 | bwd_inner_microstep: 287.96 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1905 +[2025-05-01 23:14:44,436] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.88 | bwd_microstep: 276.29 | bwd_inner_microstep: 276.27 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-01 23:14:44,918] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.17 | bwd_microstep: 274.05 | bwd_inner_microstep: 274.03 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1886 +[2025-05-01 23:14:45,403] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.80 | bwd_microstep: 274.71 | bwd_inner_microstep: 274.70 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.15 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-01 23:14:45,885] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.33 | bwd_microstep: 274.18 | bwd_inner_microstep: 274.16 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-01 23:14:46,369] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.95 | bwd_microstep: 273.96 | bwd_inner_microstep: 273.94 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-01 23:14:46,854] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.08 | bwd_microstep: 273.82 | bwd_inner_microstep: 273.80 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-01 23:14:47,337] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.47 | bwd_microstep: 273.18 | bwd_inner_microstep: 273.16 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:14:47,818] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.52 | bwd_microstep: 272.80 | bwd_inner_microstep: 272.79 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.15 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-01 23:14:48,298] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.20 | bwd_microstep: 273.11 | bwd_inner_microstep: 273.10 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 841 +[2025-05-01 23:14:48,548] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 97.85 | bwd_microstep: 131.77 | bwd_inner_microstep: 131.52 | bwd_allreduce_microstep: 0.10 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-01 23:14:49,027] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.32 | bwd_microstep: 273.00 | bwd_inner_microstep: 272.98 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 321 +[2025-05-01 23:14:49,254] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 87.14 | bwd_microstep: 122.72 | bwd_inner_microstep: 122.55 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-01 23:14:49,734] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.26 | bwd_microstep: 272.95 | bwd_inner_microstep: 272.93 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.14 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 23:14:50,213] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.99 | bwd_microstep: 271.65 | bwd_inner_microstep: 271.63 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 23:14:50,814] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.50 | optimizer_step: 32.72 +[2025-05-01 23:14:50,815] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.96 | bwd_microstep: 351.72 | bwd_inner_microstep: 271.94 | bwd_allreduce_microstep: 79.73 | step_microstep: 41.07 +[2025-05-01 23:14:50,816] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2840.82 | bwd: 4177.94 | bwd_inner: 4097.58 | bwd_allreduce: 79.95 | step: 42.33 + 5%|▍ | 396/8720 [59:24<15:57:35, 6.90s/it] {'loss': 1.6659, 'grad_norm': 5.07169246673584, 'learning_rate': 9.9938080943259e-06, 'epoch': 0.45} + 5%|▍ | 396/8720 [59:24<15:57:35, 6.90s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 517 +[2025-05-01 23:14:51,035] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 81.95 | bwd_microstep: 115.34 | bwd_inner_microstep: 114.98 | bwd_allreduce_microstep: 0.14 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2005 +[2025-05-01 23:14:51,546] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 198.01 | bwd_microstep: 295.16 | bwd_inner_microstep: 295.14 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1883 +[2025-05-01 23:14:52,028] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.13 | bwd_microstep: 274.35 | bwd_inner_microstep: 274.33 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.14 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1888 +[2025-05-01 23:14:52,511] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.44 | bwd_microstep: 274.88 | bwd_inner_microstep: 274.86 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-01 23:14:52,993] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.59 | bwd_microstep: 273.39 | bwd_inner_microstep: 273.37 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 845 +[2025-05-01 23:14:53,242] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 96.25 | bwd_microstep: 132.87 | bwd_inner_microstep: 132.62 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-01 23:14:53,721] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.20 | bwd_microstep: 272.82 | bwd_inner_microstep: 272.81 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-01 23:14:54,201] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.43 | bwd_microstep: 272.71 | bwd_inner_microstep: 272.69 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:14:54,681] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.33 | bwd_microstep: 272.80 | bwd_inner_microstep: 272.79 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 23:14:55,163] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.49 | bwd_microstep: 272.61 | bwd_inner_microstep: 272.59 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 23:14:55,646] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.05 | bwd_microstep: 271.68 | bwd_inner_microstep: 271.59 | bwd_allreduce_microstep: 0.04 | step_microstep: 0.15 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 23:14:56,125] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.38 | bwd_microstep: 271.50 | bwd_inner_microstep: 271.48 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-01 23:14:56,603] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.06 | bwd_microstep: 271.25 | bwd_inner_microstep: 271.24 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 23:14:57,081] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.72 | bwd_microstep: 271.34 | bwd_inner_microstep: 271.32 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2062 +[2025-05-01 23:14:57,606] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 203.53 | bwd_microstep: 303.17 | bwd_inner_microstep: 303.16 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.14 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1981 +[2025-05-01 23:14:58,218] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.65 | optimizer_step: 17.43 +[2025-05-01 23:14:58,218] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 198.31 | bwd_microstep: 369.90 | bwd_inner_microstep: 292.90 | bwd_allreduce_microstep: 76.95 | step_microstep: 25.56 +[2025-05-01 23:14:58,220] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2852.49 | bwd: 4215.87 | bwd_inner: 4137.95 | bwd_allreduce: 77.34 | step: 26.82 + 5%|▍ | 397/8720 [59:31<16:18:19, 7.05s/it] {'loss': 0.9272, 'grad_norm': 3.3440258502960205, 'learning_rate': 9.993715352422865e-06, 'epoch': 0.46} + 5%|▍ | 397/8720 [59:31<16:18:19, 7.05s/it]dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1759 +[2025-05-01 23:14:58,660] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 161.89 | bwd_microstep: 255.88 | bwd_inner_microstep: 255.59 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1944 +[2025-05-01 23:14:59,165] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 197.82 | bwd_microstep: 289.31 | bwd_inner_microstep: 289.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1888 +[2025-05-01 23:14:59,649] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.45 | bwd_microstep: 274.86 | bwd_inner_microstep: 274.84 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-01 23:15:00,130] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.70 | bwd_microstep: 273.73 | bwd_inner_microstep: 273.71 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-01 23:15:00,612] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.53 | bwd_microstep: 273.57 | bwd_inner_microstep: 273.55 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-01 23:15:01,094] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.88 | bwd_microstep: 273.80 | bwd_inner_microstep: 273.78 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 334 +[2025-05-01 23:15:01,332] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 98.12 | bwd_microstep: 117.24 | bwd_inner_microstep: 117.04 | bwd_allreduce_microstep: 0.08 | step_microstep: 0.13 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1350 +[2025-05-01 23:15:01,704] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.77 | bwd_microstep: 206.58 | bwd_inner_microstep: 206.35 | bwd_allreduce_microstep: 0.14 | step_microstep: 0.19 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 329 +[2025-05-01 23:15:01,941] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 98.49 | bwd_microstep: 116.99 | bwd_inner_microstep: 116.63 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.45 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 23:15:02,425] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.55 | bwd_microstep: 272.47 | bwd_inner_microstep: 272.45 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-01 23:15:02,904] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.96 | bwd_microstep: 273.01 | bwd_inner_microstep: 272.99 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 23:15:03,384] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.64 | bwd_microstep: 272.62 | bwd_inner_microstep: 272.60 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 23:15:03,863] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.40 | bwd_microstep: 272.62 | bwd_inner_microstep: 272.60 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.21 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 23:15:04,342] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.22 | bwd_microstep: 271.55 | bwd_inner_microstep: 271.53 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 23:15:04,821] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.14 | bwd_microstep: 271.63 | bwd_inner_microstep: 271.61 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 23:15:05,418] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.43 | optimizer_step: 32.11 +[2025-05-01 23:15:05,419] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.80 | bwd_microstep: 349.93 | bwd_inner_microstep: 271.95 | bwd_allreduce_microstep: 77.78 | step_microstep: 40.57 +[2025-05-01 23:15:05,420] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2773.94 | bwd: 4065.92 | bwd_inner: 3986.73 | bwd_allreduce: 78.31 | step: 42.19 + 5%|▍ | 398/8720 [59:39<16:24:21, 7.10s/it] {'loss': 1.2682, 'grad_norm': 5.204123020172119, 'learning_rate': 9.993621921569108e-06, 'epoch': 0.46} + 5%|▍ | 398/8720 [59:39<16:24:21, 7.10s/it]dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1385 +[2025-05-01 23:15:05,795] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 143.97 | bwd_microstep: 208.34 | bwd_inner_microstep: 208.31 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1891 +[2025-05-01 23:15:06,275] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.14 | bwd_microstep: 275.12 | bwd_inner_microstep: 275.10 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-01 23:15:06,755] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.53 | bwd_microstep: 273.00 | bwd_inner_microstep: 272.98 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-01 23:15:07,234] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.10 | bwd_microstep: 272.97 | bwd_inner_microstep: 272.95 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-01 23:15:07,714] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.27 | bwd_microstep: 272.94 | bwd_inner_microstep: 272.92 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-01 23:15:08,193] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.62 | bwd_microstep: 273.06 | bwd_inner_microstep: 273.04 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:15:08,675] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.46 | bwd_microstep: 272.68 | bwd_inner_microstep: 272.67 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 23:15:09,155] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.55 | bwd_microstep: 272.32 | bwd_inner_microstep: 272.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-01 23:15:09,635] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.87 | bwd_microstep: 272.91 | bwd_inner_microstep: 272.90 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 23:15:10,118] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.64 | bwd_microstep: 272.76 | bwd_inner_microstep: 272.74 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 23:15:10,594] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.62 | bwd_microstep: 271.36 | bwd_inner_microstep: 271.35 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 23:15:11,073] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.99 | bwd_microstep: 271.51 | bwd_inner_microstep: 271.49 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 317 +[2025-05-01 23:15:11,306] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 98.84 | bwd_microstep: 116.24 | bwd_inner_microstep: 116.01 | bwd_allreduce_microstep: 0.08 | step_microstep: 0.10 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 315 +[2025-05-01 23:15:11,540] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 86.39 | bwd_microstep: 130.81 | bwd_inner_microstep: 130.50 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2128 +[2025-05-01 23:15:12,077] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 205.62 | bwd_microstep: 313.76 | bwd_inner_microstep: 313.74 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1353 +[2025-05-01 23:15:12,544] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.46 | optimizer_step: 16.77 +[2025-05-01 23:15:12,545] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.59 | bwd_microstep: 284.16 | bwd_inner_microstep: 206.96 | bwd_allreduce_microstep: 77.04 | step_microstep: 24.86 +[2025-05-01 23:15:12,546] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2754.85 | bwd: 4054.01 | bwd_inner: 3976.14 | bwd_allreduce: 77.27 | step: 26.04 + 5%|▍ | 399/8720 [59:46<16:25:26, 7.11s/it] {'loss': 0.9324, 'grad_norm': 4.795811653137207, 'learning_rate': 9.993527801777512e-06, 'epoch': 0.46} + 5%|▍ | 399/8720 [59:46<16:25:26, 7.11s/it]dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1393 +[2025-05-01 23:15:12,922] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 144.62 | bwd_microstep: 209.22 | bwd_inner_microstep: 209.06 | bwd_allreduce_microstep: 0.09 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1926 +[2025-05-01 23:15:13,423] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.18 | bwd_microstep: 287.95 | bwd_inner_microstep: 287.93 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-01 23:15:13,907] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.56 | bwd_microstep: 274.64 | bwd_inner_microstep: 274.63 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 856 +[2025-05-01 23:15:14,154] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.65 | bwd_microstep: 133.81 | bwd_inner_microstep: 133.54 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-01 23:15:14,635] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.19 | bwd_microstep: 274.40 | bwd_inner_microstep: 274.38 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 845 +[2025-05-01 23:15:14,878] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.26 | bwd_microstep: 132.90 | bwd_inner_microstep: 132.60 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-01 23:15:15,360] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.55 | bwd_microstep: 273.07 | bwd_inner_microstep: 273.05 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.15 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-01 23:15:15,844] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.95 | bwd_microstep: 272.98 | bwd_inner_microstep: 272.96 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-01 23:15:16,325] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.46 | bwd_microstep: 273.60 | bwd_inner_microstep: 273.59 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 23:15:16,804] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.15 | bwd_microstep: 272.80 | bwd_inner_microstep: 272.78 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 23:15:17,286] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.34 | bwd_microstep: 272.61 | bwd_inner_microstep: 272.59 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 322 +[2025-05-01 23:15:17,527] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 92.05 | bwd_microstep: 129.57 | bwd_inner_microstep: 129.43 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 23:15:18,006] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.06 | bwd_microstep: 271.42 | bwd_inner_microstep: 271.41 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 23:15:18,486] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.48 | bwd_microstep: 272.15 | bwd_inner_microstep: 272.14 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 23:15:18,964] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.19 | bwd_microstep: 271.40 | bwd_inner_microstep: 271.38 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1944 +[2025-05-01 23:15:19,577] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.46 | optimizer_step: 16.51 +[2025-05-01 23:15:19,577] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 197.08 | bwd_microstep: 371.47 | bwd_inner_microstep: 289.77 | bwd_allreduce_microstep: 81.65 | step_microstep: 24.42 +[2025-05-01 23:15:19,579] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2710.39 | bwd: 3994.09 | bwd_inner: 3911.32 | bwd_allreduce: 82.08 | step: 25.60 + 5%|▍ | 400/8720 [59:53<16:22:16, 7.08s/it] {'loss': 0.8676, 'grad_norm': 4.526340007781982, 'learning_rate': 9.993432993061066e-06, 'epoch': 0.46} + 5%|▍ | 400/8720 [59:53<16:22:16, 7.08s/it][INFO|trainer.py:3503] 2025-05-01 23:15:22,202 >> Saving model checkpoint to work_dirs/internvl_chat_v2_5/ak/checkpoint-400 +[INFO|configuration_utils.py:472] 2025-05-01 23:15:22,205 >> Configuration saved in work_dirs/internvl_chat_v2_5/ak/checkpoint-400/config.json +[INFO|configuration_utils.py:807] 2025-05-01 23:15:22,206 >> Configuration saved in work_dirs/internvl_chat_v2_5/ak/checkpoint-400/generation_config.json +[INFO|modeling_utils.py:2755] 2025-05-01 23:15:27,568 >> Model weights saved in work_dirs/internvl_chat_v2_5/ak/checkpoint-400/model.safetensors +[INFO|tokenization_utils_base.py:2702] 2025-05-01 23:15:27,570 >> tokenizer config file saved in work_dirs/internvl_chat_v2_5/ak/checkpoint-400/tokenizer_config.json +[INFO|tokenization_utils_base.py:2711] 2025-05-01 23:15:27,570 >> Special tokens file saved in work_dirs/internvl_chat_v2_5/ak/checkpoint-400/special_tokens_map.json +[INFO|tokenization_utils_base.py:2762] 2025-05-01 23:15:27,570 >> added tokens file saved in work_dirs/internvl_chat_v2_5/ak/checkpoint-400/added_tokens.json +[2025-05-01 23:15:27,784] [INFO] [logging.py:96:log_dist] [Rank 0] [Torch] Checkpoint global_step400 is about to be saved! +[2025-05-01 23:15:27,800] [INFO] [logging.py:96:log_dist] [Rank 0] Saving model checkpoint: work_dirs/internvl_chat_v2_5/ak/checkpoint-400/global_step400/mp_rank_00_model_states.pt +[2025-05-01 23:15:27,800] [INFO] [torch_checkpoint_engine.py:21:save] [Torch] Saving work_dirs/internvl_chat_v2_5/ak/checkpoint-400/global_step400/mp_rank_00_model_states.pt... +[2025-05-01 23:15:32,799] [INFO] [torch_checkpoint_engine.py:23:save] [Torch] Saved work_dirs/internvl_chat_v2_5/ak/checkpoint-400/global_step400/mp_rank_00_model_states.pt. +[2025-05-01 23:15:32,801] [INFO] [torch_checkpoint_engine.py:21:save] [Torch] Saving work_dirs/internvl_chat_v2_5/ak/checkpoint-400/global_step400/bf16_zero_pp_rank_0_mp_rank_00_optim_states.pt... +[2025-05-01 23:15:33,005] [INFO] [torch_checkpoint_engine.py:23:save] [Torch] Saved work_dirs/internvl_chat_v2_5/ak/checkpoint-400/global_step400/bf16_zero_pp_rank_0_mp_rank_00_optim_states.pt. +[2025-05-01 23:15:33,005] [INFO] [engine.py:3536:_save_zero_checkpoint] zero checkpoint saved work_dirs/internvl_chat_v2_5/ak/checkpoint-400/global_step400/bf16_zero_pp_rank_0_mp_rank_00_optim_states.pt +[2025-05-01 23:15:33,005] [INFO] [torch_checkpoint_engine.py:33:commit] [Torch] Checkpoint global_step400 is ready now! +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 458 +[2025-05-01 23:15:33,237] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.69 | bwd_microstep: 114.49 | bwd_inner_microstep: 114.36 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1926 +[2025-05-01 23:15:33,729] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 192.75 | bwd_microstep: 284.58 | bwd_inner_microstep: 284.57 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1910 +[2025-05-01 23:15:34,206] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.36 | bwd_microstep: 273.89 | bwd_inner_microstep: 273.87 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1896 +[2025-05-01 23:15:34,682] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.50 | bwd_microstep: 272.66 | bwd_inner_microstep: 272.64 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-01 23:15:35,160] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.05 | bwd_microstep: 271.31 | bwd_inner_microstep: 271.29 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-01 23:15:35,633] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.23 | bwd_microstep: 271.02 | bwd_inner_microstep: 271.00 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-01 23:15:36,106] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 185.96 | bwd_microstep: 271.00 | bwd_inner_microstep: 270.99 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-01 23:15:36,581] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.23 | bwd_microstep: 271.57 | bwd_inner_microstep: 271.56 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 23:15:37,057] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.61 | bwd_microstep: 271.07 | bwd_inner_microstep: 271.05 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-01 23:15:37,532] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.86 | bwd_microstep: 271.23 | bwd_inner_microstep: 271.22 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:15:38,009] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.71 | bwd_microstep: 270.88 | bwd_inner_microstep: 270.86 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 321 +[2025-05-01 23:15:38,226] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 83.08 | bwd_microstep: 117.80 | bwd_inner_microstep: 117.49 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:15:38,703] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.35 | bwd_microstep: 271.63 | bwd_inner_microstep: 271.61 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 23:15:39,181] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.04 | bwd_microstep: 271.44 | bwd_inner_microstep: 271.42 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 23:15:39,657] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.81 | bwd_microstep: 270.63 | bwd_inner_microstep: 270.61 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 23:15:40,234] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.44 | optimizer_step: 16.58 +[2025-05-01 23:15:40,235] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.32 | bwd_microstep: 348.37 | bwd_inner_microstep: 270.94 | bwd_allreduce_microstep: 77.38 | step_microstep: 24.64 +[2025-05-01 23:15:40,236] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2805.24 | bwd: 4123.62 | bwd_inner: 4045.56 | bwd_allreduce: 77.65 | step: 25.44 + 5%|▍ | 401/8720 [1:00:13<25:46:45, 11.16s/it] {'loss': 1.121, 'grad_norm': 3.6467747688293457, 'learning_rate': 9.993337495432848e-06, 'epoch': 0.46} + 5%|▍ | 401/8720 [1:00:13<25:46:45, 11.16s/it]dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1450 +[2025-05-01 23:15:40,619] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 146.93 | bwd_microstep: 214.18 | bwd_inner_microstep: 214.16 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 419 +[2025-05-01 23:15:40,833] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 77.91 | bwd_microstep: 121.69 | bwd_inner_microstep: 121.38 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1909 +[2025-05-01 23:15:41,314] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.21 | bwd_microstep: 275.58 | bwd_inner_microstep: 275.57 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 856 +[2025-05-01 23:15:41,559] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.76 | bwd_microstep: 132.66 | bwd_inner_microstep: 132.39 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-01 23:15:42,038] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.38 | bwd_microstep: 273.31 | bwd_inner_microstep: 273.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-01 23:15:42,519] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.99 | bwd_microstep: 272.45 | bwd_inner_microstep: 272.43 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1362 +[2025-05-01 23:15:42,888] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.16 | bwd_microstep: 205.84 | bwd_inner_microstep: 205.83 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.11 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 335 +[2025-05-01 23:15:43,113] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 87.68 | bwd_microstep: 117.81 | bwd_inner_microstep: 117.64 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-01 23:15:43,588] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.87 | bwd_microstep: 271.82 | bwd_inner_microstep: 271.80 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 23:15:44,069] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.53 | bwd_microstep: 272.23 | bwd_inner_microstep: 272.21 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 23:15:44,550] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.48 | bwd_microstep: 271.69 | bwd_inner_microstep: 271.67 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.14 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 23:15:45,029] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.53 | bwd_microstep: 271.68 | bwd_inner_microstep: 271.66 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:15:45,509] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.64 | bwd_microstep: 271.83 | bwd_inner_microstep: 271.81 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-01 23:15:45,990] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.45 | bwd_microstep: 270.25 | bwd_inner_microstep: 270.24 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-01 23:15:46,473] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.51 | bwd_microstep: 272.02 | bwd_inner_microstep: 272.00 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1850 +[2025-05-01 23:15:47,055] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.08 | optimizer_gradients: 2.33 | optimizer_step: 16.80 +[2025-05-01 23:15:47,056] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.91 | bwd_microstep: 348.53 | bwd_inner_microstep: 270.62 | bwd_allreduce_microstep: 77.86 | step_microstep: 25.27 +[2025-05-01 23:15:47,057] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2614.50 | bwd: 3863.67 | bwd_inner: 3784.82 | bwd_allreduce: 78.21 | step: 26.66 + 5%|▍ | 402/8720 [1:00:20<22:46:19, 9.86s/it] {'loss': 1.2459, 'grad_norm': 4.091970920562744, 'learning_rate': 9.993241308906036e-06, 'epoch': 0.46} + 5%|▍ | 402/8720 [1:00:20<22:46:19, 9.86s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1946 +[2025-05-01 23:15:47,564] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 194.99 | bwd_microstep: 286.74 | bwd_inner_microstep: 286.65 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.25 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1930 +[2025-05-01 23:15:48,077] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.09 | bwd_microstep: 286.49 | bwd_inner_microstep: 286.47 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1891 +[2025-05-01 23:15:48,560] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.59 | bwd_microstep: 273.75 | bwd_inner_microstep: 273.73 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1887 +[2025-05-01 23:15:49,043] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.15 | bwd_microstep: 273.13 | bwd_inner_microstep: 273.12 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-01 23:15:49,525] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.38 | bwd_microstep: 272.71 | bwd_inner_microstep: 272.69 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-01 23:15:50,004] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.20 | bwd_microstep: 271.80 | bwd_inner_microstep: 271.78 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-01 23:15:50,482] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.08 | bwd_microstep: 271.87 | bwd_inner_microstep: 271.86 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-01 23:15:50,962] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.01 | bwd_microstep: 271.74 | bwd_inner_microstep: 271.72 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-01 23:15:51,443] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.46 | bwd_microstep: 272.67 | bwd_inner_microstep: 272.65 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-01 23:15:51,924] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.20 | bwd_microstep: 271.64 | bwd_inner_microstep: 271.62 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:15:52,403] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.06 | bwd_microstep: 271.36 | bwd_inner_microstep: 271.34 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.21 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 23:15:52,884] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.08 | bwd_microstep: 271.00 | bwd_inner_microstep: 270.98 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 23:15:53,360] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.76 | bwd_microstep: 271.04 | bwd_inner_microstep: 271.02 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-01 23:15:53,836] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.93 | bwd_microstep: 269.91 | bwd_inner_microstep: 269.90 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 316 +[2025-05-01 23:15:54,188] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 82.36 | bwd_microstep: 253.19 | bwd_inner_microstep: 253.04 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2103 +[2025-05-01 23:15:54,816] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.34 | optimizer_step: 16.63 +[2025-05-01 23:15:54,817] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 203.58 | bwd_microstep: 383.21 | bwd_inner_microstep: 309.10 | bwd_allreduce_microstep: 74.07 | step_microstep: 24.16 +[2025-05-01 23:15:54,818] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2923.49 | bwd: 4472.34 | bwd_inner: 4397.71 | bwd_allreduce: 74.22 | step: 25.49 + 5%|▍ | 403/8720 [1:00:28<21:18:58, 9.23s/it] {'loss': 1.2365, 'grad_norm': 2.8885409832000732, 'learning_rate': 9.993144433493898e-06, 'epoch': 0.46} + 5%|▍ | 403/8720 [1:00:28<21:18:58, 9.23s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2105 +[2025-05-01 23:15:55,352] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 204.07 | bwd_microstep: 308.96 | bwd_inner_microstep: 308.94 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-01 23:15:55,828] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.41 | bwd_microstep: 272.78 | bwd_inner_microstep: 272.76 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-01 23:15:56,304] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.89 | bwd_microstep: 272.35 | bwd_inner_microstep: 272.33 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-01 23:15:56,778] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.64 | bwd_microstep: 271.52 | bwd_inner_microstep: 271.50 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-01 23:15:57,256] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.40 | bwd_microstep: 271.78 | bwd_inner_microstep: 271.76 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-01 23:15:57,731] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.08 | bwd_microstep: 271.73 | bwd_inner_microstep: 271.71 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.06 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1353 +[2025-05-01 23:15:58,091] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 139.67 | bwd_microstep: 205.06 | bwd_inner_microstep: 205.04 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-01 23:15:58,565] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.88 | bwd_microstep: 271.68 | bwd_inner_microstep: 271.66 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-01 23:15:59,040] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.69 | bwd_microstep: 271.61 | bwd_inner_microstep: 271.60 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:15:59,515] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.89 | bwd_microstep: 271.28 | bwd_inner_microstep: 271.26 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 23:15:59,992] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.54 | bwd_microstep: 271.07 | bwd_inner_microstep: 271.06 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 23:16:00,468] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.60 | bwd_microstep: 270.19 | bwd_inner_microstep: 270.17 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1343 +[2025-05-01 23:16:00,830] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 139.71 | bwd_microstep: 203.75 | bwd_inner_microstep: 203.73 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 23:16:01,306] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.61 | bwd_microstep: 270.32 | bwd_inner_microstep: 270.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 23:16:01,784] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.10 | bwd_microstep: 270.62 | bwd_inner_microstep: 270.59 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.22 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1971 +[2025-05-01 23:16:02,395] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.41 | optimizer_step: 20.98 +[2025-05-01 23:16:02,396] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 196.25 | bwd_microstep: 368.68 | bwd_inner_microstep: 291.08 | bwd_allreduce_microstep: 77.54 | step_microstep: 29.14 +[2025-05-01 23:16:02,397] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2926.10 | bwd: 4343.43 | bwd_inner: 4265.51 | bwd_allreduce: 77.59 | step: 30.23 + 5%|▍ | 404/8720 [1:00:36<20:10:16, 8.73s/it] {'loss': 1.2421, 'grad_norm': 5.077705383300781, 'learning_rate': 9.993046869209801e-06, 'epoch': 0.46} + 5%|▍ | 404/8720 [1:00:36<20:10:16, 8.73s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2323 +[2025-05-01 23:16:02,970] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 216.88 | bwd_microstep: 336.22 | bwd_inner_microstep: 336.20 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 398 +[2025-05-01 23:16:03,182] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 72.75 | bwd_microstep: 125.51 | bwd_inner_microstep: 125.37 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 405 +[2025-05-01 23:16:03,394] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 75.77 | bwd_microstep: 121.60 | bwd_inner_microstep: 121.43 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.12 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1117 +[2025-05-01 23:16:03,690] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 117.81 | bwd_microstep: 162.05 | bwd_inner_microstep: 161.94 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-01 23:16:04,166] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.36 | bwd_microstep: 273.04 | bwd_inner_microstep: 273.02 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-01 23:16:04,641] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.46 | bwd_microstep: 272.09 | bwd_inner_microstep: 272.08 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-01 23:16:05,115] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.76 | bwd_microstep: 271.65 | bwd_inner_microstep: 271.64 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-01 23:16:05,593] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.22 | bwd_microstep: 273.34 | bwd_inner_microstep: 273.32 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1352 +[2025-05-01 23:16:05,956] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.88 | bwd_microstep: 205.53 | bwd_inner_microstep: 205.34 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 23:16:06,432] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.71 | bwd_microstep: 271.85 | bwd_inner_microstep: 271.83 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 23:16:06,909] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.18 | bwd_microstep: 271.65 | bwd_inner_microstep: 271.64 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1353 +[2025-05-01 23:16:07,272] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.64 | bwd_microstep: 205.74 | bwd_inner_microstep: 205.72 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 23:16:07,747] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.64 | bwd_microstep: 270.58 | bwd_inner_microstep: 270.56 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 23:16:08,221] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.27 | bwd_microstep: 271.38 | bwd_inner_microstep: 271.37 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 23:16:08,694] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.68 | bwd_microstep: 270.45 | bwd_inner_microstep: 270.44 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 23:16:09,267] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.51 | optimizer_step: 23.36 +[2025-05-01 23:16:09,268] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.62 | bwd_microstep: 338.58 | bwd_inner_microstep: 270.98 | bwd_allreduce_microstep: 67.54 | step_microstep: 31.27 +[2025-05-01 23:16:09,269] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2639.34 | bwd: 3941.33 | bwd_inner: 3872.93 | bwd_allreduce: 67.92 | step: 32.47 + 5%|▍ | 405/8720 [1:00:43<18:52:49, 8.17s/it] {'loss': 1.0043, 'grad_norm': 4.740421295166016, 'learning_rate': 9.992948616067202e-06, 'epoch': 0.46} + 5%|▍ | 405/8720 [1:00:43<18:52:49, 8.17s/it]dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1286 +[2025-05-01 23:16:09,623] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 135.07 | bwd_microstep: 198.61 | bwd_inner_microstep: 198.51 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1922 +[2025-05-01 23:16:10,119] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 193.42 | bwd_microstep: 286.26 | bwd_inner_microstep: 286.24 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1897 +[2025-05-01 23:16:10,599] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.68 | bwd_microstep: 274.70 | bwd_inner_microstep: 274.69 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1888 +[2025-05-01 23:16:11,078] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.29 | bwd_microstep: 273.56 | bwd_inner_microstep: 273.55 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1887 +[2025-05-01 23:16:11,558] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.14 | bwd_microstep: 273.84 | bwd_inner_microstep: 273.83 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1892 +[2025-05-01 23:16:12,041] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.50 | bwd_microstep: 274.38 | bwd_inner_microstep: 274.36 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-01 23:16:12,517] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.64 | bwd_microstep: 272.91 | bwd_inner_microstep: 272.90 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1358 +[2025-05-01 23:16:12,881] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.27 | bwd_microstep: 206.01 | bwd_inner_microstep: 205.99 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 23:16:13,358] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.75 | bwd_microstep: 271.57 | bwd_inner_microstep: 271.55 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-01 23:16:13,840] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.00 | bwd_microstep: 271.77 | bwd_inner_microstep: 271.75 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 23:16:14,317] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.41 | bwd_microstep: 271.49 | bwd_inner_microstep: 271.48 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 23:16:14,798] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.10 | bwd_microstep: 272.50 | bwd_inner_microstep: 272.48 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 23:16:15,276] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.93 | bwd_microstep: 272.18 | bwd_inner_microstep: 272.16 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.15 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 23:16:15,759] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.95 | bwd_microstep: 272.09 | bwd_inner_microstep: 272.07 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.15 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 831 +[2025-05-01 23:16:15,999] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.02 | bwd_microstep: 130.05 | bwd_inner_microstep: 129.81 | bwd_allreduce_microstep: 0.09 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-01 23:16:16,574] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.40 | optimizer_step: 16.60 +[2025-05-01 23:16:16,575] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.10 | bwd_microstep: 349.10 | bwd_inner_microstep: 271.47 | bwd_allreduce_microstep: 77.58 | step_microstep: 24.26 +[2025-05-01 23:16:16,576] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2817.93 | bwd: 4171.06 | bwd_inner: 4092.89 | bwd_allreduce: 77.79 | step: 25.52 + 5%|▍ | 406/8720 [1:00:50<18:16:35, 7.91s/it] {'loss': 1.5069, 'grad_norm': 3.3316190242767334, 'learning_rate': 9.992849674079659e-06, 'epoch': 0.47} + 5%|▍ | 406/8720 [1:00:50<18:16:35, 7.91s/it]dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 922 +[2025-05-01 23:16:16,843] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 102.68 | bwd_microstep: 145.85 | bwd_inner_microstep: 145.53 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1921 +[2025-05-01 23:16:17,346] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.66 | bwd_microstep: 286.69 | bwd_inner_microstep: 286.68 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 912 +[2025-05-01 23:16:17,611] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 104.21 | bwd_microstep: 145.12 | bwd_inner_microstep: 145.11 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1897 +[2025-05-01 23:16:18,092] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.00 | bwd_microstep: 275.35 | bwd_inner_microstep: 275.33 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 866 +[2025-05-01 23:16:18,336] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.03 | bwd_microstep: 134.04 | bwd_inner_microstep: 133.79 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.20 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 350 +[2025-05-01 23:16:18,571] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 98.51 | bwd_microstep: 117.99 | bwd_inner_microstep: 117.68 | bwd_allreduce_microstep: 0.14 | step_microstep: 0.09 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 842 +[2025-05-01 23:16:18,812] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.14 | bwd_microstep: 132.66 | bwd_inner_microstep: 132.49 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.12 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 845 +[2025-05-01 23:16:19,053] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.84 | bwd_microstep: 132.20 | bwd_inner_microstep: 132.15 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 23:16:19,530] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.03 | bwd_microstep: 272.49 | bwd_inner_microstep: 272.47 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.16 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-01 23:16:20,008] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.40 | bwd_microstep: 272.95 | bwd_inner_microstep: 272.94 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 23:16:20,484] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.51 | bwd_microstep: 271.37 | bwd_inner_microstep: 271.35 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 23:16:20,961] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.47 | bwd_microstep: 272.65 | bwd_inner_microstep: 272.49 | bwd_allreduce_microstep: 0.08 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 23:16:21,451] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.48 | bwd_microstep: 272.01 | bwd_inner_microstep: 271.99 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 23:16:21,930] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.06 | bwd_microstep: 271.36 | bwd_inner_microstep: 271.34 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 23:16:22,406] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.36 | bwd_microstep: 271.48 | bwd_inner_microstep: 271.47 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.08 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 462 +[2025-05-01 23:16:22,711] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.44 | optimizer_step: 16.68 +[2025-05-01 23:16:22,712] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 69.89 | bwd_microstep: 198.33 | bwd_inner_microstep: 131.21 | bwd_allreduce_microstep: 66.95 | step_microstep: 24.40 +[2025-05-01 23:16:22,713] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2363.98 | bwd: 3472.71 | bwd_inner: 3404.24 | bwd_allreduce: 67.54 | step: 26.14 + 5%|▍ | 407/8720 [1:00:56<17:02:37, 7.38s/it] {'loss': 1.3175, 'grad_norm': 4.6203227043151855, 'learning_rate': 9.992750043260824e-06, 'epoch': 0.47} + 5%|▍ | 407/8720 [1:00:56<17:02:37, 7.38s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1927 +[2025-05-01 23:16:23,217] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 196.23 | bwd_microstep: 286.81 | bwd_inner_microstep: 286.71 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1915 +[2025-05-01 23:16:23,703] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 191.05 | bwd_microstep: 276.14 | bwd_inner_microstep: 276.12 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-01 23:16:24,181] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.21 | bwd_microstep: 272.56 | bwd_inner_microstep: 272.54 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-01 23:16:24,660] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.28 | bwd_microstep: 273.59 | bwd_inner_microstep: 273.57 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-01 23:16:25,140] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.27 | bwd_microstep: 273.39 | bwd_inner_microstep: 273.37 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.13 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 334 +[2025-05-01 23:16:25,390] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 86.59 | bwd_microstep: 145.21 | bwd_inner_microstep: 144.86 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.12 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 334 +[2025-05-01 23:16:25,631] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 83.26 | bwd_microstep: 140.46 | bwd_inner_microstep: 140.10 | bwd_allreduce_microstep: 0.14 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-01 23:16:26,111] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.39 | bwd_microstep: 273.35 | bwd_inner_microstep: 273.33 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-01 23:16:26,592] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.21 | bwd_microstep: 272.64 | bwd_inner_microstep: 272.62 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-01 23:16:27,077] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.20 | bwd_microstep: 273.04 | bwd_inner_microstep: 273.02 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-01 23:16:27,560] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.44 | bwd_microstep: 272.98 | bwd_inner_microstep: 272.96 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 834 +[2025-05-01 23:16:27,807] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 102.98 | bwd_microstep: 125.55 | bwd_inner_microstep: 125.49 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 23:16:28,288] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.25 | bwd_microstep: 271.17 | bwd_inner_microstep: 271.16 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 23:16:28,766] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.15 | bwd_microstep: 271.68 | bwd_inner_microstep: 271.67 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 23:16:29,245] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.47 | bwd_microstep: 271.42 | bwd_inner_microstep: 271.40 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 23:16:29,838] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.47 | optimizer_step: 16.79 +[2025-05-01 23:16:29,839] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.47 | bwd_microstep: 360.05 | bwd_inner_microstep: 271.69 | bwd_allreduce_microstep: 88.30 | step_microstep: 25.07 +[2025-05-01 23:16:29,840] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2731.05 | bwd: 4060.16 | bwd_inner: 3970.77 | bwd_allreduce: 88.70 | step: 26.56 + 5%|▍ | 408/8720 [1:01:03<16:52:00, 7.31s/it] {'loss': 1.8556, 'grad_norm': 4.927193641662598, 'learning_rate': 9.992649723624439e-06, 'epoch': 0.47} + 5%|▍ | 408/8720 [1:01:03<16:52:00, 7.31s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1921 +[2025-05-01 23:16:30,344] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.12 | bwd_microstep: 286.08 | bwd_inner_microstep: 286.07 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1896 +[2025-05-01 23:16:30,827] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.95 | bwd_microstep: 275.14 | bwd_inner_microstep: 275.12 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1888 +[2025-05-01 23:16:31,310] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.03 | bwd_microstep: 274.43 | bwd_inner_microstep: 274.41 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-01 23:16:31,792] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.69 | bwd_microstep: 273.49 | bwd_inner_microstep: 273.47 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-01 23:16:32,271] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.26 | bwd_microstep: 272.79 | bwd_inner_microstep: 272.77 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1096 +[2025-05-01 23:16:32,567] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 115.10 | bwd_microstep: 161.37 | bwd_inner_microstep: 161.24 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.10 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 333 +[2025-05-01 23:16:32,804] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 91.98 | bwd_microstep: 127.65 | bwd_inner_microstep: 127.46 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-01 23:16:33,284] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.42 | bwd_microstep: 272.68 | bwd_inner_microstep: 272.67 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 23:16:33,765] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.88 | bwd_microstep: 272.41 | bwd_inner_microstep: 272.40 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 323 +[2025-05-01 23:16:34,007] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 92.38 | bwd_microstep: 130.45 | bwd_inner_microstep: 130.20 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 23:16:34,485] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.44 | bwd_microstep: 271.04 | bwd_inner_microstep: 271.03 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 23:16:34,964] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.05 | bwd_microstep: 271.07 | bwd_inner_microstep: 271.05 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 318 +[2025-05-01 23:16:35,202] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 102.58 | bwd_microstep: 114.68 | bwd_inner_microstep: 114.46 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 23:16:35,679] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.57 | bwd_microstep: 271.19 | bwd_inner_microstep: 271.18 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 23:16:36,156] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.04 | bwd_microstep: 271.25 | bwd_inner_microstep: 271.23 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 23:16:36,724] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.44 | optimizer_step: 16.75 +[2025-05-01 23:16:36,724] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.54 | bwd_microstep: 338.82 | bwd_inner_microstep: 271.72 | bwd_allreduce_microstep: 67.06 | step_microstep: 24.48 +[2025-05-01 23:16:36,725] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2671.66 | bwd: 3884.62 | bwd_inner: 3816.65 | bwd_allreduce: 67.40 | step: 25.63 + 5%|▍ | 409/8720 [1:01:10<16:34:22, 7.18s/it] {'loss': 1.0439, 'grad_norm': 5.647623538970947, 'learning_rate': 9.992548715184345e-06, 'epoch': 0.47} + 5%|▍ | 409/8720 [1:01:10<16:34:22, 7.18s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2005 +[2025-05-01 23:16:37,237] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 197.53 | bwd_microstep: 294.32 | bwd_inner_microstep: 294.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1966 +[2025-05-01 23:16:37,740] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 196.46 | bwd_microstep: 290.92 | bwd_inner_microstep: 290.91 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1894 +[2025-05-01 23:16:38,220] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.44 | bwd_microstep: 275.33 | bwd_inner_microstep: 275.32 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1894 +[2025-05-01 23:16:38,700] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.36 | bwd_microstep: 275.39 | bwd_inner_microstep: 275.37 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-01 23:16:39,178] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.35 | bwd_microstep: 274.30 | bwd_inner_microstep: 274.28 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 845 +[2025-05-01 23:16:39,418] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.94 | bwd_microstep: 132.27 | bwd_inner_microstep: 132.04 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-01 23:16:39,895] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.93 | bwd_microstep: 272.74 | bwd_inner_microstep: 272.72 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-01 23:16:40,371] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.36 | bwd_microstep: 273.21 | bwd_inner_microstep: 273.20 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 23:16:40,846] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.66 | bwd_microstep: 272.21 | bwd_inner_microstep: 272.19 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 330 +[2025-05-01 23:16:41,050] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 67.64 | bwd_microstep: 122.61 | bwd_inner_microstep: 122.28 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.18 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 837 +[2025-05-01 23:16:41,283] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 90.84 | bwd_microstep: 128.73 | bwd_inner_microstep: 128.72 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 23:16:41,761] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.33 | bwd_microstep: 272.49 | bwd_inner_microstep: 272.47 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 23:16:42,237] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.70 | bwd_microstep: 272.33 | bwd_inner_microstep: 272.31 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1086 +[2025-05-01 23:16:42,525] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 114.67 | bwd_microstep: 159.65 | bwd_inner_microstep: 159.52 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1086 +[2025-05-01 23:16:42,815] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 114.51 | bwd_microstep: 160.08 | bwd_inner_microstep: 159.74 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.19 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 916 +[2025-05-01 23:16:43,165] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.49 | optimizer_step: 16.72 +[2025-05-01 23:16:43,166] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 100.05 | bwd_microstep: 212.64 | bwd_inner_microstep: 145.79 | bwd_allreduce_microstep: 66.69 | step_microstep: 24.47 +[2025-05-01 23:16:43,167] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2485.54 | bwd: 3689.33 | bwd_inner: 3621.34 | bwd_allreduce: 67.15 | step: 25.54 + 5%|▍ | 410/8720 [1:01:16<16:03:37, 6.96s/it] {'loss': 1.1988, 'grad_norm': 5.38405704498291, 'learning_rate': 9.992447017954479e-06, 'epoch': 0.47} + 5%|▍ | 410/8720 [1:01:16<16:03:37, 6.96s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 411 +[2025-05-01 23:16:43,396] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 70.68 | bwd_microstep: 140.49 | bwd_inner_microstep: 140.36 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1896 +[2025-05-01 23:16:43,875] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.68 | bwd_microstep: 275.04 | bwd_inner_microstep: 275.03 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1893 +[2025-05-01 23:16:44,355] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.99 | bwd_microstep: 275.63 | bwd_inner_microstep: 275.52 | bwd_allreduce_microstep: 0.03 | step_microstep: 0.15 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-01 23:16:44,845] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.18 | bwd_microstep: 273.25 | bwd_inner_microstep: 273.23 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-01 23:16:45,323] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.43 | bwd_microstep: 273.56 | bwd_inner_microstep: 273.55 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 329 +[2025-05-01 23:16:45,531] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 76.05 | bwd_microstep: 117.12 | bwd_inner_microstep: 116.99 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1347 +[2025-05-01 23:16:45,891] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 139.74 | bwd_microstep: 205.97 | bwd_inner_microstep: 205.81 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-01 23:16:46,368] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.97 | bwd_microstep: 272.81 | bwd_inner_microstep: 272.80 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:16:46,844] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.78 | bwd_microstep: 272.76 | bwd_inner_microstep: 272.75 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-01 23:16:47,322] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.08 | bwd_microstep: 272.88 | bwd_inner_microstep: 272.86 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 837 +[2025-05-01 23:16:47,556] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 92.25 | bwd_microstep: 126.44 | bwd_inner_microstep: 126.21 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.21 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 23:16:48,033] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.42 | bwd_microstep: 272.27 | bwd_inner_microstep: 272.26 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1349 +[2025-05-01 23:16:48,395] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.17 | bwd_microstep: 205.93 | bwd_inner_microstep: 205.91 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.13 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 23:16:48,872] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.99 | bwd_microstep: 271.33 | bwd_inner_microstep: 271.31 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 23:16:49,351] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.17 | bwd_microstep: 271.08 | bwd_inner_microstep: 271.06 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1974 +[2025-05-01 23:16:49,965] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.42 | optimizer_step: 16.70 +[2025-05-01 23:16:49,965] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 196.94 | bwd_microstep: 372.32 | bwd_inner_microstep: 291.94 | bwd_allreduce_microstep: 80.32 | step_microstep: 24.89 +[2025-05-01 23:16:49,967] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2601.23 | bwd: 3899.01 | bwd_inner: 3817.63 | bwd_allreduce: 80.74 | step: 26.07 + 5%|▍ | 411/8720 [1:01:23<15:57:01, 6.91s/it] {'loss': 1.7948, 'grad_norm': 5.5978875160217285, 'learning_rate': 9.99234463194887e-06, 'epoch': 0.47} + 5%|▍ | 411/8720 [1:01:23<15:57:01, 6.91s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1950 +[2025-05-01 23:16:50,476] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 197.69 | bwd_microstep: 288.48 | bwd_inner_microstep: 288.46 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1936 +[2025-05-01 23:16:50,978] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 196.17 | bwd_microstep: 288.24 | bwd_inner_microstep: 288.22 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1893 +[2025-05-01 23:16:51,462] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.86 | bwd_microstep: 275.10 | bwd_inner_microstep: 275.08 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1921 +[2025-05-01 23:16:51,962] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.28 | bwd_microstep: 286.76 | bwd_inner_microstep: 286.74 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 346 +[2025-05-01 23:16:52,188] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 84.86 | bwd_microstep: 124.75 | bwd_inner_microstep: 124.59 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1371 +[2025-05-01 23:16:52,554] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.19 | bwd_microstep: 207.85 | bwd_inner_microstep: 207.83 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1358 +[2025-05-01 23:16:52,918] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.81 | bwd_microstep: 206.30 | bwd_inner_microstep: 206.28 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 23:16:53,395] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.67 | bwd_microstep: 272.45 | bwd_inner_microstep: 272.44 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 23:16:53,871] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.36 | bwd_microstep: 272.55 | bwd_inner_microstep: 272.53 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 23:16:54,347] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.08 | bwd_microstep: 272.53 | bwd_inner_microstep: 272.51 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-01 23:16:54,823] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.78 | bwd_microstep: 272.56 | bwd_inner_microstep: 272.54 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 318 +[2025-05-01 23:16:55,021] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 67.47 | bwd_microstep: 117.48 | bwd_inner_microstep: 117.34 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.10 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 831 +[2025-05-01 23:16:55,263] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.88 | bwd_microstep: 130.68 | bwd_inner_microstep: 130.54 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 23:16:55,737] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.51 | bwd_microstep: 271.50 | bwd_inner_microstep: 271.48 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 23:16:56,212] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.64 | bwd_microstep: 271.58 | bwd_inner_microstep: 271.56 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 23:16:56,780] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.46 | optimizer_step: 16.84 +[2025-05-01 23:16:56,780] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.23 | bwd_microstep: 339.59 | bwd_inner_microstep: 272.83 | bwd_allreduce_microstep: 66.72 | step_microstep: 24.48 +[2025-05-01 23:16:56,781] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2626.20 | bwd: 3898.44 | bwd_inner: 3831.06 | bwd_allreduce: 66.96 | step: 25.40 + 5%|▍ | 412/8720 [1:01:30<15:52:50, 6.88s/it] {'loss': 1.5182, 'grad_norm': 4.907742500305176, 'learning_rate': 9.992241557181645e-06, 'epoch': 0.47} + 5%|▍ | 412/8720 [1:01:30<15:52:50, 6.88s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1894 +[2025-05-01 23:16:57,265] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.94 | bwd_microstep: 274.23 | bwd_inner_microstep: 274.21 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1886 +[2025-05-01 23:16:57,746] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.83 | bwd_microstep: 274.29 | bwd_inner_microstep: 274.27 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-01 23:16:58,226] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.48 | bwd_microstep: 273.50 | bwd_inner_microstep: 273.47 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-01 23:16:58,704] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.61 | bwd_microstep: 273.84 | bwd_inner_microstep: 273.82 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 23:16:59,183] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.15 | bwd_microstep: 272.14 | bwd_inner_microstep: 272.12 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 845 +[2025-05-01 23:16:59,431] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.81 | bwd_microstep: 132.41 | bwd_inner_microstep: 132.11 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 23:16:59,910] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.16 | bwd_microstep: 272.48 | bwd_inner_microstep: 272.46 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-01 23:17:00,392] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.31 | bwd_microstep: 273.46 | bwd_inner_microstep: 273.44 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 23:17:00,877] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.09 | bwd_microstep: 272.59 | bwd_inner_microstep: 272.57 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 23:17:01,363] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.15 | bwd_microstep: 272.21 | bwd_inner_microstep: 272.19 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:17:01,850] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.58 | bwd_microstep: 272.87 | bwd_inner_microstep: 272.85 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 23:17:02,333] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.78 | bwd_microstep: 271.51 | bwd_inner_microstep: 271.49 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 23:17:02,812] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.03 | bwd_microstep: 271.21 | bwd_inner_microstep: 271.20 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 23:17:03,294] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.75 | bwd_microstep: 271.50 | bwd_inner_microstep: 271.48 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-01 23:17:03,776] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.96 | bwd_microstep: 274.52 | bwd_inner_microstep: 274.50 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-01 23:17:04,364] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.46 | optimizer_step: 16.72 +[2025-05-01 23:17:04,365] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.43 | bwd_microstep: 353.87 | bwd_inner_microstep: 274.77 | bwd_allreduce_microstep: 79.05 | step_microstep: 25.11 +[2025-05-01 23:17:04,366] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2927.64 | bwd: 4306.71 | bwd_inner: 4227.00 | bwd_allreduce: 79.25 | step: 26.49 + 5%|▍ | 413/8720 [1:01:38<16:22:00, 7.09s/it] {'loss': 1.0719, 'grad_norm': 3.681628465652466, 'learning_rate': 9.992137793667026e-06, 'epoch': 0.47} + 5%|▍ | 413/8720 [1:01:38<16:22:00, 7.09s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1972 +[2025-05-01 23:17:04,876] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 196.84 | bwd_microstep: 290.42 | bwd_inner_microstep: 290.39 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1903 +[2025-05-01 23:17:05,361] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.14 | bwd_microstep: 275.81 | bwd_inner_microstep: 275.79 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1906 +[2025-05-01 23:17:05,848] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.16 | bwd_microstep: 276.04 | bwd_inner_microstep: 276.02 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1893 +[2025-05-01 23:17:06,336] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.86 | bwd_microstep: 275.47 | bwd_inner_microstep: 275.46 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1361 +[2025-05-01 23:17:06,709] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 142.43 | bwd_microstep: 207.33 | bwd_inner_microstep: 207.26 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-01 23:17:07,188] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.93 | bwd_microstep: 273.20 | bwd_inner_microstep: 273.18 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 329 +[2025-05-01 23:17:07,507] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 88.50 | bwd_microstep: 212.84 | bwd_inner_microstep: 212.65 | bwd_allreduce_microstep: 0.08 | step_microstep: 0.14 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-01 23:17:07,999] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.83 | bwd_microstep: 273.03 | bwd_inner_microstep: 273.01 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 23:17:08,476] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.67 | bwd_microstep: 272.63 | bwd_inner_microstep: 272.62 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-01 23:17:08,955] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.73 | bwd_microstep: 273.34 | bwd_inner_microstep: 273.32 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 23:17:09,434] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.14 | bwd_microstep: 272.64 | bwd_inner_microstep: 272.62 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 23:17:09,910] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.25 | bwd_microstep: 271.76 | bwd_inner_microstep: 271.75 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 828 +[2025-05-01 23:17:10,149] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.72 | bwd_microstep: 130.51 | bwd_inner_microstep: 130.47 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 23:17:10,624] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.96 | bwd_microstep: 271.47 | bwd_inner_microstep: 271.45 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 23:17:11,101] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.02 | bwd_microstep: 271.35 | bwd_inner_microstep: 271.34 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 23:17:11,682] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.45 | optimizer_step: 16.83 +[2025-05-01 23:17:11,683] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.88 | bwd_microstep: 350.70 | bwd_inner_microstep: 271.90 | bwd_allreduce_microstep: 78.74 | step_microstep: 25.19 +[2025-05-01 23:17:11,684] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2790.71 | bwd: 4198.64 | bwd_inner: 4119.30 | bwd_allreduce: 78.94 | step: 26.17 + 5%|▍ | 414/8720 [1:01:45<16:31:17, 7.16s/it] {'loss': 1.2297, 'grad_norm': 3.4534096717834473, 'learning_rate': 9.992033341419322e-06, 'epoch': 0.47} + 5%|▍ | 414/8720 [1:01:45<16:31:17, 7.16s/it]dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1234 +[2025-05-01 23:17:12,008] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 122.39 | bwd_microstep: 178.03 | bwd_inner_microstep: 177.78 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1935 +[2025-05-01 23:17:12,509] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.52 | bwd_microstep: 288.15 | bwd_inner_microstep: 288.13 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1903 +[2025-05-01 23:17:12,992] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.95 | bwd_microstep: 275.76 | bwd_inner_microstep: 275.74 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-01 23:17:13,470] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.99 | bwd_microstep: 273.09 | bwd_inner_microstep: 273.08 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-01 23:17:13,950] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.11 | bwd_microstep: 273.51 | bwd_inner_microstep: 273.50 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 326 +[2025-05-01 23:17:14,188] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 77.48 | bwd_microstep: 145.90 | bwd_inner_microstep: 145.60 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-01 23:17:14,667] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.54 | bwd_microstep: 272.84 | bwd_inner_microstep: 272.82 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-01 23:17:15,145] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.48 | bwd_microstep: 272.90 | bwd_inner_microstep: 272.88 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.18 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1346 +[2025-05-01 23:17:15,508] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.39 | bwd_microstep: 205.20 | bwd_inner_microstep: 205.06 | bwd_allreduce_microstep: 0.04 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-01 23:17:15,985] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.17 | bwd_microstep: 272.42 | bwd_inner_microstep: 272.40 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 23:17:16,467] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.59 | bwd_microstep: 271.94 | bwd_inner_microstep: 271.92 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.14 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 23:17:16,948] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.40 | bwd_microstep: 272.15 | bwd_inner_microstep: 272.14 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 23:17:17,429] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.22 | bwd_microstep: 271.36 | bwd_inner_microstep: 271.34 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 23:17:17,909] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.88 | bwd_microstep: 270.92 | bwd_inner_microstep: 270.91 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 23:17:18,387] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.51 | bwd_microstep: 271.27 | bwd_inner_microstep: 271.26 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 420 +[2025-05-01 23:17:18,735] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.34 | optimizer_step: 16.92 +[2025-05-01 23:17:18,735] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 86.38 | bwd_microstep: 221.29 | bwd_inner_microstep: 143.62 | bwd_allreduce_microstep: 77.57 | step_microstep: 24.59 +[2025-05-01 23:17:18,736] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2696.64 | bwd: 4036.91 | bwd_inner: 3958.26 | bwd_allreduce: 77.96 | step: 26.23 + 5%|▍ | 415/8720 [1:01:52<16:26:34, 7.13s/it] {'loss': 0.9783, 'grad_norm': 5.006059646606445, 'learning_rate': 9.991928200452952e-06, 'epoch': 0.48} + 5%|▍ | 415/8720 [1:01:52<16:26:34, 7.13s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1892 +[2025-05-01 23:17:19,221] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.94 | bwd_microstep: 274.01 | bwd_inner_microstep: 273.99 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1886 +[2025-05-01 23:17:19,700] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.72 | bwd_microstep: 274.72 | bwd_inner_microstep: 274.70 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-01 23:17:20,186] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.67 | bwd_microstep: 273.83 | bwd_inner_microstep: 273.81 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-01 23:17:20,664] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.02 | bwd_microstep: 272.93 | bwd_inner_microstep: 272.91 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-01 23:17:21,141] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.91 | bwd_microstep: 273.26 | bwd_inner_microstep: 273.24 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.14 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-01 23:17:21,617] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.14 | bwd_microstep: 272.60 | bwd_inner_microstep: 272.58 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 842 +[2025-05-01 23:17:21,858] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.40 | bwd_microstep: 132.32 | bwd_inner_microstep: 132.24 | bwd_allreduce_microstep: 0.04 | step_microstep: 0.09 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 321 +[2025-05-01 23:17:22,077] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 78.56 | bwd_microstep: 125.11 | bwd_inner_microstep: 124.78 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 23:17:22,552] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.54 | bwd_microstep: 272.90 | bwd_inner_microstep: 272.88 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 23:17:23,031] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.01 | bwd_microstep: 272.82 | bwd_inner_microstep: 272.80 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 23:17:23,507] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.08 | bwd_microstep: 272.61 | bwd_inner_microstep: 272.59 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 23:17:23,985] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.77 | bwd_microstep: 272.57 | bwd_inner_microstep: 272.56 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 23:17:24,464] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.74 | bwd_microstep: 271.72 | bwd_inner_microstep: 271.70 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 23:17:24,944] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.99 | bwd_microstep: 272.47 | bwd_inner_microstep: 272.45 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 23:17:25,423] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.68 | bwd_microstep: 271.10 | bwd_inner_microstep: 271.09 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1920 +[2025-05-01 23:17:26,014] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.41 | optimizer_step: 16.91 +[2025-05-01 23:17:26,014] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 191.63 | bwd_microstep: 354.02 | bwd_inner_microstep: 277.19 | bwd_allreduce_microstep: 76.77 | step_microstep: 25.08 +[2025-05-01 23:17:26,016] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2818.50 | bwd: 4159.01 | bwd_inner: 4081.60 | bwd_allreduce: 77.02 | step: 26.24 + 5%|▍ | 416/8720 [1:01:59<16:32:48, 7.17s/it] {'loss': 0.7482, 'grad_norm': 3.216062545776367, 'learning_rate': 9.991822370782416e-06, 'epoch': 0.48} + 5%|▍ | 416/8720 [1:01:59<16:32:48, 7.17s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1930 +[2025-05-01 23:17:26,521] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 194.83 | bwd_microstep: 287.74 | bwd_inner_microstep: 287.69 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1922 +[2025-05-01 23:17:27,020] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 194.77 | bwd_microstep: 287.44 | bwd_inner_microstep: 287.42 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1888 +[2025-05-01 23:17:27,499] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.80 | bwd_microstep: 274.83 | bwd_inner_microstep: 274.82 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1889 +[2025-05-01 23:17:27,979] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.92 | bwd_microstep: 275.45 | bwd_inner_microstep: 275.43 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1883 +[2025-05-01 23:17:28,459] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.64 | bwd_microstep: 275.04 | bwd_inner_microstep: 275.02 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 344 +[2025-05-01 23:17:28,670] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 70.62 | bwd_microstep: 126.09 | bwd_inner_microstep: 125.94 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-01 23:17:29,150] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.53 | bwd_microstep: 274.01 | bwd_inner_microstep: 273.99 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 23:17:29,630] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.64 | bwd_microstep: 273.43 | bwd_inner_microstep: 273.41 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-01 23:17:30,109] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.98 | bwd_microstep: 273.52 | bwd_inner_microstep: 273.51 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-01 23:17:30,592] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.37 | bwd_microstep: 273.39 | bwd_inner_microstep: 273.37 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 842 +[2025-05-01 23:17:30,833] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.17 | bwd_microstep: 131.81 | bwd_inner_microstep: 131.68 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 23:17:31,310] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.04 | bwd_microstep: 272.23 | bwd_inner_microstep: 272.21 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 23:17:31,788] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.82 | bwd_microstep: 272.62 | bwd_inner_microstep: 272.60 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 23:17:32,265] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.78 | bwd_microstep: 271.86 | bwd_inner_microstep: 271.84 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 23:17:32,744] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.45 | bwd_microstep: 272.44 | bwd_inner_microstep: 272.42 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1342 +[2025-05-01 23:17:33,210] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.38 | optimizer_step: 29.74 +[2025-05-01 23:17:33,210] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.30 | bwd_microstep: 272.54 | bwd_inner_microstep: 205.21 | bwd_allreduce_microstep: 67.16 | step_microstep: 37.51 +[2025-05-01 23:17:33,212] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2771.39 | bwd: 4114.51 | bwd_inner: 4046.68 | bwd_allreduce: 67.32 | step: 38.38 + 5%|▍ | 417/8720 [1:02:06<16:33:35, 7.18s/it] {'loss': 0.8168, 'grad_norm': 3.0976808071136475, 'learning_rate': 9.991715852422317e-06, 'epoch': 0.48} + 5%|▍ | 417/8720 [1:02:06<16:33:35, 7.18s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1908 +[2025-05-01 23:17:33,699] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.52 | bwd_microstep: 276.31 | bwd_inner_microstep: 276.29 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 361 +[2025-05-01 23:17:33,914] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 74.16 | bwd_microstep: 126.91 | bwd_inner_microstep: 126.77 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1911 +[2025-05-01 23:17:34,397] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.89 | bwd_microstep: 277.05 | bwd_inner_microstep: 277.04 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-01 23:17:34,876] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.79 | bwd_microstep: 273.90 | bwd_inner_microstep: 273.88 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-01 23:17:35,354] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.45 | bwd_microstep: 273.75 | bwd_inner_microstep: 273.73 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 852 +[2025-05-01 23:17:35,596] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.45 | bwd_microstep: 132.96 | bwd_inner_microstep: 132.84 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-01 23:17:36,074] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.23 | bwd_microstep: 273.86 | bwd_inner_microstep: 273.84 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-01 23:17:36,552] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.18 | bwd_microstep: 273.53 | bwd_inner_microstep: 273.52 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-01 23:17:37,031] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.23 | bwd_microstep: 273.31 | bwd_inner_microstep: 273.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-01 23:17:37,510] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.95 | bwd_microstep: 273.69 | bwd_inner_microstep: 273.67 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 836 +[2025-05-01 23:17:37,751] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 97.72 | bwd_microstep: 125.96 | bwd_inner_microstep: 125.77 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 23:17:38,231] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.43 | bwd_microstep: 272.78 | bwd_inner_microstep: 272.77 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 23:17:38,710] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.86 | bwd_microstep: 271.23 | bwd_inner_microstep: 271.21 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 23:17:39,187] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.24 | bwd_microstep: 271.34 | bwd_inner_microstep: 271.33 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1084 +[2025-05-01 23:17:39,480] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 118.22 | bwd_microstep: 159.85 | bwd_inner_microstep: 159.73 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.16 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 828 +[2025-05-01 23:17:39,810] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.56 | optimizer_step: 17.00 +[2025-05-01 23:17:39,810] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 92.53 | bwd_microstep: 197.50 | bwd_inner_microstep: 130.45 | bwd_allreduce_microstep: 66.96 | step_microstep: 24.80 +[2025-05-01 23:17:39,811] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2550.56 | bwd: 3754.02 | bwd_inner: 3686.24 | bwd_allreduce: 67.27 | step: 25.81 + 5%|▍ | 418/8720 [1:02:13<16:09:21, 7.01s/it] {'loss': 1.3401, 'grad_norm': 2.6865246295928955, 'learning_rate': 9.99160864538735e-06, 'epoch': 0.48} + 5%|▍ | 418/8720 [1:02:13<16:09:21, 7.01s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2113 +[2025-05-01 23:17:40,347] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 203.65 | bwd_microstep: 311.96 | bwd_inner_microstep: 311.95 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 383 +[2025-05-01 23:17:40,548] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 69.02 | bwd_microstep: 117.97 | bwd_inner_microstep: 117.67 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1912 +[2025-05-01 23:17:41,031] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.63 | bwd_microstep: 277.19 | bwd_inner_microstep: 277.17 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.41 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1905 +[2025-05-01 23:17:41,513] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.64 | bwd_microstep: 276.37 | bwd_inner_microstep: 276.36 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.17 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1896 +[2025-05-01 23:17:41,995] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.87 | bwd_microstep: 275.77 | bwd_inner_microstep: 275.75 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 835 +[2025-05-01 23:17:42,231] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.55 | bwd_microstep: 126.41 | bwd_inner_microstep: 126.38 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 23:17:42,710] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.00 | bwd_microstep: 272.79 | bwd_inner_microstep: 272.78 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-01 23:17:43,189] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.32 | bwd_microstep: 273.08 | bwd_inner_microstep: 273.06 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 23:17:43,670] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.19 | bwd_microstep: 272.84 | bwd_inner_microstep: 272.82 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 23:17:44,150] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.20 | bwd_microstep: 272.56 | bwd_inner_microstep: 272.54 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 23:17:44,629] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.33 | bwd_microstep: 272.98 | bwd_inner_microstep: 272.96 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 320 +[2025-05-01 23:17:44,865] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 99.90 | bwd_microstep: 120.03 | bwd_inner_microstep: 119.70 | bwd_allreduce_microstep: 0.14 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 23:17:45,345] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.85 | bwd_microstep: 272.29 | bwd_inner_microstep: 272.27 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 317 +[2025-05-01 23:17:45,590] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 110.34 | bwd_microstep: 117.44 | bwd_inner_microstep: 117.24 | bwd_allreduce_microstep: 0.08 | step_microstep: 0.14 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 23:17:46,072] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.42 | bwd_microstep: 272.05 | bwd_inner_microstep: 272.00 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.14 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-01 23:17:46,693] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.07 | optimizer_gradients: 2.47 | optimizer_step: 30.52 +[2025-05-01 23:17:46,694] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.08 | bwd_microstep: 374.10 | bwd_inner_microstep: 274.34 | bwd_allreduce_microstep: 99.70 | step_microstep: 39.66 +[2025-05-01 23:17:46,695] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2652.63 | bwd: 3905.93 | bwd_inner: 3805.15 | bwd_allreduce: 100.12 | step: 41.30 + 5%|▍ | 419/8720 [1:02:20<16:04:09, 6.97s/it] {'loss': 1.337, 'grad_norm': 5.7907328605651855, 'learning_rate': 9.991500749692305e-06, 'epoch': 0.48} + 5%|▍ | 419/8720 [1:02:20<16:04:09, 6.97s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1909 +[2025-05-01 23:17:47,183] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.82 | bwd_microstep: 276.39 | bwd_inner_microstep: 276.38 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1918 +[2025-05-01 23:17:47,666] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.77 | bwd_microstep: 277.33 | bwd_inner_microstep: 277.31 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1898 +[2025-05-01 23:17:48,147] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.55 | bwd_microstep: 275.36 | bwd_inner_microstep: 275.34 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-01 23:17:48,626] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.49 | bwd_microstep: 273.27 | bwd_inner_microstep: 273.25 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.23 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 347 +[2025-05-01 23:17:48,855] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 92.11 | bwd_microstep: 122.71 | bwd_inner_microstep: 122.52 | bwd_allreduce_microstep: 0.08 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-01 23:17:49,334] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.61 | bwd_microstep: 274.49 | bwd_inner_microstep: 274.47 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-01 23:17:49,814] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.87 | bwd_microstep: 274.46 | bwd_inner_microstep: 274.44 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-01 23:17:50,292] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.12 | bwd_microstep: 273.86 | bwd_inner_microstep: 273.84 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-01 23:17:50,772] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.58 | bwd_microstep: 273.31 | bwd_inner_microstep: 273.29 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-01 23:17:51,258] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.91 | bwd_microstep: 273.49 | bwd_inner_microstep: 273.47 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 836 +[2025-05-01 23:17:51,491] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 92.53 | bwd_microstep: 126.28 | bwd_inner_microstep: 126.20 | bwd_allreduce_microstep: 0.04 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 23:17:51,968] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.77 | bwd_microstep: 271.32 | bwd_inner_microstep: 271.30 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1345 +[2025-05-01 23:17:52,331] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.35 | bwd_microstep: 205.73 | bwd_inner_microstep: 205.68 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 23:17:52,807] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.57 | bwd_microstep: 272.00 | bwd_inner_microstep: 271.98 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-01 23:17:53,283] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.13 | bwd_microstep: 271.96 | bwd_inner_microstep: 271.94 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 378 +[2025-05-01 23:17:53,661] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.37 | optimizer_step: 17.32 +[2025-05-01 23:17:53,662] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.86 | bwd_microstep: 244.67 | bwd_inner_microstep: 158.53 | bwd_allreduce_microstep: 85.97 | step_microstep: 26.28 +[2025-05-01 23:17:53,663] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2687.73 | bwd: 3986.67 | bwd_inner: 3900.06 | bwd_allreduce: 86.15 | step: 27.39 + 5%|▍ | 420/8720 [1:02:27<16:04:01, 6.97s/it] {'loss': 1.2701, 'grad_norm': 3.5174598693847656, 'learning_rate': 9.991392165352068e-06, 'epoch': 0.48} + 5%|▍ | 420/8720 [1:02:27<16:04:01, 6.97s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1991 +[2025-05-01 23:17:54,175] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 197.52 | bwd_microstep: 293.92 | bwd_inner_microstep: 293.90 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1920 +[2025-05-01 23:17:54,661] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.53 | bwd_microstep: 277.54 | bwd_inner_microstep: 277.53 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.13 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-01 23:17:55,142] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.18 | bwd_microstep: 274.81 | bwd_inner_microstep: 274.79 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.21 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-01 23:17:55,624] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.24 | bwd_microstep: 275.12 | bwd_inner_microstep: 275.10 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-01 23:17:56,104] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.50 | bwd_microstep: 273.95 | bwd_inner_microstep: 273.93 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 840 +[2025-05-01 23:17:56,344] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 98.49 | bwd_microstep: 126.48 | bwd_inner_microstep: 126.27 | bwd_allreduce_microstep: 0.09 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-01 23:17:56,822] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.24 | bwd_microstep: 273.23 | bwd_inner_microstep: 273.22 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-01 23:17:57,301] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.88 | bwd_microstep: 272.67 | bwd_inner_microstep: 272.66 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 23:17:57,779] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.98 | bwd_microstep: 273.33 | bwd_inner_microstep: 273.32 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:17:58,258] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.73 | bwd_microstep: 273.46 | bwd_inner_microstep: 273.44 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 23:17:58,736] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.56 | bwd_microstep: 273.16 | bwd_inner_microstep: 273.14 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 23:17:59,213] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.21 | bwd_microstep: 271.97 | bwd_inner_microstep: 271.95 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 835 +[2025-05-01 23:17:59,452] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 98.81 | bwd_microstep: 126.23 | bwd_inner_microstep: 125.96 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.21 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 23:17:59,928] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.34 | bwd_microstep: 272.12 | bwd_inner_microstep: 272.10 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 23:18:00,404] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.96 | bwd_microstep: 271.93 | bwd_inner_microstep: 271.91 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1887 +[2025-05-01 23:18:00,996] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.42 | optimizer_step: 16.54 +[2025-05-01 23:18:00,997] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.97 | bwd_microstep: 361.23 | bwd_inner_microstep: 275.65 | bwd_allreduce_microstep: 85.53 | step_microstep: 25.03 +[2025-05-01 23:18:00,998] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2857.83 | bwd: 4191.22 | bwd_inner: 4104.90 | bwd_allreduce: 85.79 | step: 26.51 + 5%|▍ | 421/8720 [1:02:34<16:19:04, 7.08s/it] {'loss': 0.7041, 'grad_norm': 2.138834238052368, 'learning_rate': 9.991282892381622e-06, 'epoch': 0.48} + 5%|▍ | 421/8720 [1:02:34<16:19:04, 7.08s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-01 23:18:01,482] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.14 | bwd_microstep: 273.85 | bwd_inner_microstep: 273.83 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-01 23:18:01,962] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.39 | bwd_microstep: 274.21 | bwd_inner_microstep: 274.19 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-01 23:18:02,442] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.18 | bwd_microstep: 273.93 | bwd_inner_microstep: 273.91 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-01 23:18:02,922] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.21 | bwd_microstep: 273.96 | bwd_inner_microstep: 273.95 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1098 +[2025-05-01 23:18:03,218] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 119.12 | bwd_microstep: 162.11 | bwd_inner_microstep: 161.84 | bwd_allreduce_microstep: 0.14 | step_microstep: 0.13 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 327 +[2025-05-01 23:18:03,452] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 89.99 | bwd_microstep: 129.53 | bwd_inner_microstep: 129.20 | bwd_allreduce_microstep: 0.14 | step_microstep: 0.11 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 836 +[2025-05-01 23:18:03,690] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 97.35 | bwd_microstep: 126.50 | bwd_inner_microstep: 126.24 | bwd_allreduce_microstep: 0.14 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-01 23:18:04,168] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.35 | bwd_microstep: 273.68 | bwd_inner_microstep: 273.66 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:18:04,647] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.16 | bwd_microstep: 273.82 | bwd_inner_microstep: 273.80 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 23:18:05,126] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.04 | bwd_microstep: 273.48 | bwd_inner_microstep: 273.46 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 23:18:05,601] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.59 | bwd_microstep: 271.65 | bwd_inner_microstep: 271.63 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 23:18:06,079] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.11 | bwd_microstep: 273.52 | bwd_inner_microstep: 273.51 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 23:18:06,559] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.81 | bwd_microstep: 272.46 | bwd_inner_microstep: 272.44 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.21 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 23:18:07,040] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.86 | bwd_microstep: 271.71 | bwd_inner_microstep: 271.69 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 23:18:07,520] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.31 | bwd_microstep: 272.00 | bwd_inner_microstep: 271.98 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 23:18:08,118] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.68 | optimizer_step: 17.54 +[2025-05-01 23:18:08,118] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.67 | bwd_microstep: 364.54 | bwd_inner_microstep: 272.84 | bwd_allreduce_microstep: 91.65 | step_microstep: 26.84 +[2025-05-01 23:18:08,119] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2771.95 | bwd: 4061.03 | bwd_inner: 3968.24 | bwd_allreduce: 92.15 | step: 28.20 + 5%|▍ | 422/8720 [1:02:41<16:20:45, 7.09s/it] {'loss': 0.9424, 'grad_norm': 3.5079288482666016, 'learning_rate': 9.991172930796037e-06, 'epoch': 0.48} + 5%|▍ | 422/8720 [1:02:41<16:20:45, 7.09s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1909 +[2025-05-01 23:18:08,607] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.12 | bwd_microstep: 276.56 | bwd_inner_microstep: 276.54 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-01 23:18:09,087] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.40 | bwd_microstep: 275.07 | bwd_inner_microstep: 275.05 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1366 +[2025-05-01 23:18:09,451] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.52 | bwd_microstep: 207.37 | bwd_inner_microstep: 207.20 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.23 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-01 23:18:09,931] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.38 | bwd_microstep: 274.08 | bwd_inner_microstep: 274.05 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-01 23:18:10,411] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.75 | bwd_microstep: 273.87 | bwd_inner_microstep: 273.85 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 23:18:10,889] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.39 | bwd_microstep: 273.17 | bwd_inner_microstep: 273.15 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 23:18:11,365] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.25 | bwd_microstep: 272.08 | bwd_inner_microstep: 272.06 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 23:18:11,841] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.98 | bwd_microstep: 273.05 | bwd_inner_microstep: 273.03 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.15 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:18:12,320] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.00 | bwd_microstep: 273.41 | bwd_inner_microstep: 273.39 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.21 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 23:18:12,798] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.58 | bwd_microstep: 271.97 | bwd_inner_microstep: 271.96 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 23:18:13,284] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.61 | bwd_microstep: 273.25 | bwd_inner_microstep: 273.23 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 23:18:13,765] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.00 | bwd_microstep: 273.16 | bwd_inner_microstep: 273.14 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.22 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 23:18:14,246] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.87 | bwd_microstep: 273.50 | bwd_inner_microstep: 273.49 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 23:18:14,726] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.73 | bwd_microstep: 272.06 | bwd_inner_microstep: 271.96 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.21 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-01 23:18:15,204] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.88 | bwd_microstep: 271.94 | bwd_inner_microstep: 271.92 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 327 +[2025-05-01 23:18:15,602] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.37 | optimizer_step: 30.51 +[2025-05-01 23:18:15,603] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 115.14 | bwd_microstep: 223.85 | bwd_inner_microstep: 138.78 | bwd_allreduce_microstep: 84.97 | step_microstep: 39.07 +[2025-05-01 23:18:15,604] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2903.28 | bwd: 4258.48 | bwd_inner: 4172.84 | bwd_allreduce: 85.19 | step: 41.04 + 5%|▍ | 423/8720 [1:02:49<16:36:56, 7.21s/it] {'loss': 1.1957, 'grad_norm': 3.7029576301574707, 'learning_rate': 9.991062280610492e-06, 'epoch': 0.49} + 5%|▍ | 423/8720 [1:02:49<16:36:56, 7.21s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 634 +[2025-05-01 23:18:15,828] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 89.22 | bwd_microstep: 116.38 | bwd_inner_microstep: 116.10 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1972 +[2025-05-01 23:18:16,331] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 196.56 | bwd_microstep: 291.63 | bwd_inner_microstep: 291.62 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1895 +[2025-05-01 23:18:16,812] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.50 | bwd_microstep: 275.56 | bwd_inner_microstep: 275.54 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1894 +[2025-05-01 23:18:17,293] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.51 | bwd_microstep: 275.53 | bwd_inner_microstep: 275.51 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1883 +[2025-05-01 23:18:17,772] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.74 | bwd_microstep: 274.71 | bwd_inner_microstep: 274.70 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1368 +[2025-05-01 23:18:18,141] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 142.50 | bwd_microstep: 207.30 | bwd_inner_microstep: 207.28 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-01 23:18:18,618] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.15 | bwd_microstep: 273.14 | bwd_inner_microstep: 273.13 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-01 23:18:19,096] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.05 | bwd_microstep: 273.50 | bwd_inner_microstep: 273.48 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 23:18:19,574] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.32 | bwd_microstep: 273.02 | bwd_inner_microstep: 273.00 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 845 +[2025-05-01 23:18:19,821] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 100.36 | bwd_microstep: 131.87 | bwd_inner_microstep: 131.78 | bwd_allreduce_microstep: 0.04 | step_microstep: 0.10 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1351 +[2025-05-01 23:18:20,184] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.53 | bwd_microstep: 206.54 | bwd_inner_microstep: 206.36 | bwd_allreduce_microstep: 0.14 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 23:18:20,661] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.96 | bwd_microstep: 272.15 | bwd_inner_microstep: 272.13 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 23:18:21,139] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.20 | bwd_microstep: 272.08 | bwd_inner_microstep: 272.07 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.11 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 829 +[2025-05-01 23:18:21,386] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 101.04 | bwd_microstep: 129.74 | bwd_inner_microstep: 129.34 | bwd_allreduce_microstep: 0.14 | step_microstep: 0.10 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 338 +[2025-05-01 23:18:21,625] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 88.73 | bwd_microstep: 135.80 | bwd_inner_microstep: 134.62 | bwd_allreduce_microstep: 0.08 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-01 23:18:22,208] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.47 | optimizer_step: 16.72 +[2025-05-01 23:18:22,209] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.17 | bwd_microstep: 353.08 | bwd_inner_microstep: 274.14 | bwd_allreduce_microstep: 78.84 | step_microstep: 25.04 +[2025-05-01 23:18:22,210] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2561.23 | bwd: 3762.11 | bwd_inner: 3681.97 | bwd_allreduce: 79.34 | step: 26.17 + 5%|▍ | 424/8720 [1:02:55<16:11:48, 7.03s/it] {'loss': 1.4213, 'grad_norm': 3.9393668174743652, 'learning_rate': 9.990950941840245e-06, 'epoch': 0.49} + 5%|▍ | 424/8720 [1:02:55<16:11:48, 7.03s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2084 +[2025-05-01 23:18:22,738] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 202.96 | bwd_microstep: 304.51 | bwd_inner_microstep: 304.49 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1886 +[2025-05-01 23:18:23,219] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.01 | bwd_microstep: 275.12 | bwd_inner_microstep: 275.10 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-01 23:18:23,699] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.53 | bwd_microstep: 273.72 | bwd_inner_microstep: 273.71 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-01 23:18:24,177] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.77 | bwd_microstep: 273.78 | bwd_inner_microstep: 273.76 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-01 23:18:24,659] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.98 | bwd_microstep: 274.10 | bwd_inner_microstep: 274.08 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 838 +[2025-05-01 23:18:24,902] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 98.22 | bwd_microstep: 125.99 | bwd_inner_microstep: 125.83 | bwd_allreduce_microstep: 0.08 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-01 23:18:25,388] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.24 | bwd_microstep: 273.81 | bwd_inner_microstep: 273.79 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-01 23:18:25,874] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.63 | bwd_microstep: 274.29 | bwd_inner_microstep: 274.27 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 23:18:26,353] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.23 | bwd_microstep: 272.74 | bwd_inner_microstep: 272.72 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 23:18:26,831] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.97 | bwd_microstep: 271.81 | bwd_inner_microstep: 271.79 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 23:18:27,311] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.58 | bwd_microstep: 272.11 | bwd_inner_microstep: 272.09 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 23:18:27,789] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.11 | bwd_microstep: 272.05 | bwd_inner_microstep: 272.04 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 23:18:28,267] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.35 | bwd_microstep: 271.64 | bwd_inner_microstep: 271.63 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 23:18:28,750] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.94 | bwd_microstep: 271.89 | bwd_inner_microstep: 271.87 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 23:18:29,228] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.05 | bwd_microstep: 272.00 | bwd_inner_microstep: 271.98 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 23:18:29,822] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.44 | optimizer_step: 30.27 +[2025-05-01 23:18:29,822] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.35 | bwd_microstep: 349.56 | bwd_inner_microstep: 272.64 | bwd_allreduce_microstep: 76.86 | step_microstep: 38.33 +[2025-05-01 23:18:29,824] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2947.51 | bwd: 4329.14 | bwd_inner: 4251.79 | bwd_allreduce: 77.02 | step: 39.20 + 5%|▍ | 425/8720 [1:03:03<16:36:00, 7.20s/it] {'loss': 1.0701, 'grad_norm': 3.8982503414154053, 'learning_rate': 9.990838914500661e-06, 'epoch': 0.49} + 5%|▍ | 425/8720 [1:03:03<16:36:00, 7.20s/it]dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 922 +[2025-05-01 23:18:30,093] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 101.40 | bwd_microstep: 145.98 | bwd_inner_microstep: 145.79 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1917 +[2025-05-01 23:18:30,575] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.55 | bwd_microstep: 277.10 | bwd_inner_microstep: 277.08 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1906 +[2025-05-01 23:18:31,056] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.80 | bwd_microstep: 276.85 | bwd_inner_microstep: 276.83 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1890 +[2025-05-01 23:18:31,538] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.36 | bwd_microstep: 275.59 | bwd_inner_microstep: 275.57 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-01 23:18:32,015] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.61 | bwd_microstep: 274.19 | bwd_inner_microstep: 274.17 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-01 23:18:32,497] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.26 | bwd_microstep: 274.88 | bwd_inner_microstep: 274.86 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-01 23:18:32,980] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.20 | bwd_microstep: 274.34 | bwd_inner_microstep: 274.32 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 841 +[2025-05-01 23:18:33,233] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 102.74 | bwd_microstep: 132.25 | bwd_inner_microstep: 132.13 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:18:33,712] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.25 | bwd_microstep: 273.02 | bwd_inner_microstep: 273.00 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 842 +[2025-05-01 23:18:33,962] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 100.09 | bwd_microstep: 131.89 | bwd_inner_microstep: 131.73 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.09 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 840 +[2025-05-01 23:18:34,204] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.49 | bwd_microstep: 132.04 | bwd_inner_microstep: 131.80 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-01 23:18:34,684] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.24 | bwd_microstep: 273.66 | bwd_inner_microstep: 273.64 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 23:18:35,163] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.94 | bwd_microstep: 273.32 | bwd_inner_microstep: 273.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 23:18:35,642] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.81 | bwd_microstep: 272.25 | bwd_inner_microstep: 272.23 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 23:18:36,117] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.33 | bwd_microstep: 272.63 | bwd_inner_microstep: 272.61 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 23:18:36,682] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.04 | optimizer_gradients: 2.36 | optimizer_step: 16.59 +[2025-05-01 23:18:36,683] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.71 | bwd_microstep: 338.61 | bwd_inner_microstep: 272.28 | bwd_allreduce_microstep: 66.28 | step_microstep: 23.91 +[2025-05-01 23:18:36,684] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2665.47 | bwd: 3898.65 | bwd_inner: 3831.43 | bwd_allreduce: 66.65 | step: 24.83 + 5%|▍ | 426/8720 [1:03:10<16:21:32, 7.10s/it] {'loss': 1.2823, 'grad_norm': 4.692329406738281, 'learning_rate': 9.990726198607195e-06, 'epoch': 0.49} + 5%|▍ | 426/8720 [1:03:10<16:21:32, 7.10s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 350 +[2025-05-01 23:18:36,888] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 68.12 | bwd_microstep: 118.53 | bwd_inner_microstep: 118.40 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-01 23:18:37,369] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.13 | bwd_microstep: 275.52 | bwd_inner_microstep: 275.51 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 859 +[2025-05-01 23:18:37,613] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 96.09 | bwd_microstep: 134.01 | bwd_inner_microstep: 133.80 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-01 23:18:38,093] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.09 | bwd_microstep: 274.25 | bwd_inner_microstep: 274.23 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1093 +[2025-05-01 23:18:38,386] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 116.54 | bwd_microstep: 161.65 | bwd_inner_microstep: 161.50 | bwd_allreduce_microstep: 0.10 | step_microstep: 0.10 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 328 +[2025-05-01 23:18:38,617] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 97.22 | bwd_microstep: 115.85 | bwd_inner_microstep: 115.64 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-01 23:18:39,098] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.11 | bwd_microstep: 274.15 | bwd_inner_microstep: 274.13 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-01 23:18:39,579] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.53 | bwd_microstep: 274.41 | bwd_inner_microstep: 274.39 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 23:18:40,063] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.77 | bwd_microstep: 273.99 | bwd_inner_microstep: 273.97 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 23:18:40,547] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.39 | bwd_microstep: 273.89 | bwd_inner_microstep: 273.88 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.21 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 23:18:41,030] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.37 | bwd_microstep: 273.55 | bwd_inner_microstep: 273.54 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 23:18:41,511] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.47 | bwd_microstep: 271.81 | bwd_inner_microstep: 271.79 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-01 23:18:41,990] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.54 | bwd_microstep: 272.33 | bwd_inner_microstep: 272.32 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 828 +[2025-05-01 23:18:42,242] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 100.33 | bwd_microstep: 129.89 | bwd_inner_microstep: 129.79 | bwd_allreduce_microstep: 0.04 | step_microstep: 0.12 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 827 +[2025-05-01 23:18:42,495] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 100.90 | bwd_microstep: 129.74 | bwd_inner_microstep: 129.53 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1889 +[2025-05-01 23:18:43,085] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.30 | optimizer_step: 16.57 +[2025-05-01 23:18:43,086] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.35 | bwd_microstep: 353.07 | bwd_inner_microstep: 276.00 | bwd_allreduce_microstep: 77.01 | step_microstep: 24.44 +[2025-05-01 23:18:43,087] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2473.51 | bwd: 3606.76 | bwd_inner: 3528.51 | bwd_allreduce: 77.54 | step: 25.73 + 5%|▍ | 427/8720 [1:03:16<15:52:35, 6.89s/it] {'loss': 1.223, 'grad_norm': 3.9159932136535645, 'learning_rate': 9.990612794175396e-06, 'epoch': 0.49} + 5%|▍ | 427/8720 [1:03:16<15:52:35, 6.89s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1911 +[2025-05-01 23:18:43,577] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.10 | bwd_microstep: 276.24 | bwd_inner_microstep: 276.23 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-01 23:18:44,060] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.14 | bwd_microstep: 274.27 | bwd_inner_microstep: 274.25 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-01 23:18:44,540] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.62 | bwd_microstep: 273.75 | bwd_inner_microstep: 273.73 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 23:18:45,023] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.42 | bwd_microstep: 273.23 | bwd_inner_microstep: 273.21 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 330 +[2025-05-01 23:18:45,259] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 96.46 | bwd_microstep: 118.71 | bwd_inner_microstep: 118.56 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-01 23:18:45,739] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.64 | bwd_microstep: 273.67 | bwd_inner_microstep: 273.65 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-01 23:18:46,222] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.71 | bwd_microstep: 273.55 | bwd_inner_microstep: 273.53 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 23:18:46,703] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.70 | bwd_microstep: 273.66 | bwd_inner_microstep: 273.64 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 325 +[2025-05-01 23:18:46,968] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 87.09 | bwd_microstep: 160.78 | bwd_inner_microstep: 160.62 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 23:18:47,446] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.26 | bwd_microstep: 272.52 | bwd_inner_microstep: 272.51 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 320 +[2025-05-01 23:18:47,679] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 87.96 | bwd_microstep: 127.96 | bwd_inner_microstep: 127.76 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 23:18:48,156] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.13 | bwd_microstep: 271.55 | bwd_inner_microstep: 271.53 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 23:18:48,634] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.41 | bwd_microstep: 271.53 | bwd_inner_microstep: 271.52 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 23:18:49,111] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.88 | bwd_microstep: 271.75 | bwd_inner_microstep: 271.73 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-01 23:18:49,587] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.78 | bwd_microstep: 271.60 | bwd_inner_microstep: 271.58 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 23:18:50,166] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.34 | optimizer_step: 16.69 +[2025-05-01 23:18:50,167] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.06 | bwd_microstep: 348.33 | bwd_inner_microstep: 271.87 | bwd_allreduce_microstep: 76.40 | step_microstep: 24.65 +[2025-05-01 23:18:50,168] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2726.01 | bwd: 4033.16 | bwd_inner: 3956.04 | bwd_allreduce: 76.66 | step: 25.69 + 5%|▍ | 428/8720 [1:03:23<16:00:18, 6.95s/it] {'loss': 1.0727, 'grad_norm': 5.411410808563232, 'learning_rate': 9.990498701220911e-06, 'epoch': 0.49} + 5%|▍ | 428/8720 [1:03:23<16:00:18, 6.95s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1892 +[2025-05-01 23:18:50,656] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.37 | bwd_microstep: 275.54 | bwd_inner_microstep: 275.52 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 860 +[2025-05-01 23:18:50,901] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.95 | bwd_microstep: 133.79 | bwd_inner_microstep: 133.76 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-01 23:18:51,380] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.19 | bwd_microstep: 274.83 | bwd_inner_microstep: 274.81 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-01 23:18:51,860] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.76 | bwd_microstep: 274.65 | bwd_inner_microstep: 274.64 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.20 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 858 +[2025-05-01 23:18:52,107] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 98.20 | bwd_microstep: 133.61 | bwd_inner_microstep: 133.40 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1883 +[2025-05-01 23:18:52,588] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.62 | bwd_microstep: 275.17 | bwd_inner_microstep: 275.15 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 852 +[2025-05-01 23:18:52,837] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 96.10 | bwd_microstep: 133.56 | bwd_inner_microstep: 133.28 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.11 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1362 +[2025-05-01 23:18:53,204] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 143.33 | bwd_microstep: 206.77 | bwd_inner_microstep: 206.75 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1355 +[2025-05-01 23:18:53,569] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.08 | bwd_microstep: 206.53 | bwd_inner_microstep: 206.40 | bwd_allreduce_microstep: 0.03 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 23:18:54,047] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.44 | bwd_microstep: 272.88 | bwd_inner_microstep: 272.87 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 23:18:54,525] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.77 | bwd_microstep: 272.28 | bwd_inner_microstep: 272.26 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 23:18:55,004] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.68 | bwd_microstep: 272.51 | bwd_inner_microstep: 272.49 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:18:55,483] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.94 | bwd_microstep: 272.94 | bwd_inner_microstep: 272.92 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:18:55,962] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.09 | bwd_microstep: 273.15 | bwd_inner_microstep: 273.14 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 23:18:56,442] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.29 | bwd_microstep: 273.08 | bwd_inner_microstep: 273.06 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 23:18:57,011] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.04 | optimizer_gradients: 2.35 | optimizer_step: 16.61 +[2025-05-01 23:18:57,011] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.95 | bwd_microstep: 339.30 | bwd_inner_microstep: 273.55 | bwd_allreduce_microstep: 65.70 | step_microstep: 23.71 +[2025-05-01 23:18:57,012] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2651.45 | bwd: 3890.67 | bwd_inner: 3824.05 | bwd_allreduce: 66.06 | step: 24.82 + 5%|▍ | 429/8720 [1:03:30<15:55:46, 6.92s/it] {'loss': 0.9557, 'grad_norm': 3.1373291015625, 'learning_rate': 9.990383919759481e-06, 'epoch': 0.49} + 5%|▍ | 429/8720 [1:03:30<15:55:46, 6.92s/it]dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 898 +[2025-05-01 23:18:57,275] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 100.27 | bwd_microstep: 143.89 | bwd_inner_microstep: 143.80 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1917 +[2025-05-01 23:18:57,757] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.02 | bwd_microstep: 277.83 | bwd_inner_microstep: 277.82 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1904 +[2025-05-01 23:18:58,241] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.82 | bwd_microstep: 276.91 | bwd_inner_microstep: 276.89 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 371 +[2025-05-01 23:18:58,442] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 69.62 | bwd_microstep: 117.75 | bwd_inner_microstep: 117.44 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1892 +[2025-05-01 23:18:58,924] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.68 | bwd_microstep: 275.70 | bwd_inner_microstep: 275.68 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1887 +[2025-05-01 23:18:59,406] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.20 | bwd_microstep: 275.55 | bwd_inner_microstep: 275.54 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1361 +[2025-05-01 23:18:59,774] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.96 | bwd_microstep: 207.11 | bwd_inner_microstep: 206.96 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-01 23:19:00,259] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.93 | bwd_microstep: 273.88 | bwd_inner_microstep: 273.86 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-01 23:19:00,748] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.55 | bwd_microstep: 273.58 | bwd_inner_microstep: 273.56 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-01 23:19:01,231] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.87 | bwd_microstep: 273.70 | bwd_inner_microstep: 273.68 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-01 23:19:01,712] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.97 | bwd_microstep: 273.93 | bwd_inner_microstep: 273.91 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:19:02,197] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.11 | bwd_microstep: 273.06 | bwd_inner_microstep: 273.04 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1343 +[2025-05-01 23:19:02,560] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.45 | bwd_microstep: 204.65 | bwd_inner_microstep: 204.64 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 23:19:03,035] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.56 | bwd_microstep: 271.98 | bwd_inner_microstep: 271.96 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 23:19:03,512] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.55 | bwd_microstep: 271.46 | bwd_inner_microstep: 271.44 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2056 +[2025-05-01 23:19:04,125] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.38 | optimizer_step: 16.64 +[2025-05-01 23:19:04,126] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 203.72 | bwd_microstep: 370.70 | bwd_inner_microstep: 302.89 | bwd_allreduce_microstep: 67.77 | step_microstep: 23.94 +[2025-05-01 23:19:04,127] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2737.92 | bwd: 4061.76 | bwd_inner: 3993.18 | bwd_allreduce: 68.11 | step: 24.83 + 5%|▍ | 430/8720 [1:03:37<16:03:52, 6.98s/it] {'loss': 1.7441, 'grad_norm': 4.069449424743652, 'learning_rate': 9.99026844980694e-06, 'epoch': 0.49} + 5%|▍ | 430/8720 [1:03:37<16:03:52, 6.98s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1954 +[2025-05-01 23:19:04,634] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 197.51 | bwd_microstep: 289.57 | bwd_inner_microstep: 289.55 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1933 +[2025-05-01 23:19:05,140] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 197.35 | bwd_microstep: 288.86 | bwd_inner_microstep: 288.84 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-01 23:19:05,620] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.00 | bwd_microstep: 273.92 | bwd_inner_microstep: 273.90 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1368 +[2025-05-01 23:19:05,987] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 142.07 | bwd_microstep: 207.87 | bwd_inner_microstep: 207.81 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-01 23:19:06,469] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.07 | bwd_microstep: 275.28 | bwd_inner_microstep: 275.26 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-01 23:19:06,952] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.63 | bwd_microstep: 274.86 | bwd_inner_microstep: 274.84 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-01 23:19:07,434] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.98 | bwd_microstep: 274.30 | bwd_inner_microstep: 274.28 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.14 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-01 23:19:07,918] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.62 | bwd_microstep: 274.17 | bwd_inner_microstep: 274.16 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-01 23:19:08,402] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.20 | bwd_microstep: 274.98 | bwd_inner_microstep: 274.97 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-01 23:19:08,883] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.36 | bwd_microstep: 273.92 | bwd_inner_microstep: 273.90 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 23:19:09,364] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.10 | bwd_microstep: 274.45 | bwd_inner_microstep: 273.99 | bwd_allreduce_microstep: 0.42 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-01 23:19:09,848] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.37 | bwd_microstep: 274.45 | bwd_inner_microstep: 274.44 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.17 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-01 23:19:10,329] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.70 | bwd_microstep: 274.29 | bwd_inner_microstep: 274.27 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 23:19:10,810] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.54 | bwd_microstep: 273.16 | bwd_inner_microstep: 273.15 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1086 +[2025-05-01 23:19:11,106] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 116.27 | bwd_microstep: 160.51 | bwd_inner_microstep: 160.43 | bwd_allreduce_microstep: 0.03 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 23:19:11,692] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.39 | optimizer_step: 16.64 +[2025-05-01 23:19:11,693] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.53 | bwd_microstep: 355.00 | bwd_inner_microstep: 273.20 | bwd_allreduce_microstep: 81.75 | step_microstep: 24.54 +[2025-05-01 23:19:11,694] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2927.93 | bwd: 4319.69 | bwd_inner: 4236.99 | bwd_allreduce: 81.95 | step: 25.78 + 5%|▍ | 431/8720 [1:03:45<16:28:19, 7.15s/it] {'loss': 1.0741, 'grad_norm': 2.672320604324341, 'learning_rate': 9.99015229137922e-06, 'epoch': 0.49} + 5%|▍ | 431/8720 [1:03:45<16:28:19, 7.15s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1921 +[2025-05-01 23:19:12,199] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.24 | bwd_microstep: 286.95 | bwd_inner_microstep: 286.94 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 360 +[2025-05-01 23:19:12,433] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 96.70 | bwd_microstep: 118.67 | bwd_inner_microstep: 118.38 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-01 23:19:12,914] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.32 | bwd_microstep: 274.52 | bwd_inner_microstep: 274.50 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-01 23:19:13,396] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.54 | bwd_microstep: 274.45 | bwd_inner_microstep: 274.43 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-01 23:19:13,877] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.86 | bwd_microstep: 273.73 | bwd_inner_microstep: 273.72 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-01 23:19:14,361] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.91 | bwd_microstep: 273.65 | bwd_inner_microstep: 273.64 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 23:19:14,840] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.70 | bwd_microstep: 273.49 | bwd_inner_microstep: 273.47 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-01 23:19:15,322] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.58 | bwd_microstep: 274.01 | bwd_inner_microstep: 273.99 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 23:19:15,802] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.53 | bwd_microstep: 273.38 | bwd_inner_microstep: 273.37 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 322 +[2025-05-01 23:19:16,021] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 83.68 | bwd_microstep: 119.17 | bwd_inner_microstep: 118.85 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-01 23:19:16,501] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.01 | bwd_microstep: 273.70 | bwd_inner_microstep: 273.68 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 318 +[2025-05-01 23:19:16,727] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 88.23 | bwd_microstep: 120.46 | bwd_inner_microstep: 120.26 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 319 +[2025-05-01 23:19:16,954] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 85.98 | bwd_microstep: 124.34 | bwd_inner_microstep: 124.12 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 23:19:17,433] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.67 | bwd_microstep: 272.22 | bwd_inner_microstep: 272.20 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 23:19:17,912] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.95 | bwd_microstep: 271.98 | bwd_inner_microstep: 271.96 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 23:19:18,507] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.39 | optimizer_step: 16.58 +[2025-05-01 23:19:18,508] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.31 | bwd_microstep: 362.57 | bwd_inner_microstep: 272.51 | bwd_allreduce_microstep: 90.00 | step_microstep: 24.81 +[2025-05-01 23:19:18,509] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2627.85 | bwd: 3867.37 | bwd_inner: 3776.29 | bwd_allreduce: 90.43 | step: 26.02 + 5%|▍ | 432/8720 [1:03:52<16:14:09, 7.05s/it] {'loss': 1.0877, 'grad_norm': 5.653922080993652, 'learning_rate': 9.990035444492347e-06, 'epoch': 0.5} + 5%|▍ | 432/8720 [1:03:52<16:14:09, 7.05s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 368 +[2025-05-01 23:19:18,742] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 83.88 | bwd_microstep: 127.71 | bwd_inner_microstep: 127.56 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 362 +[2025-05-01 23:19:18,957] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 80.83 | bwd_microstep: 119.22 | bwd_inner_microstep: 118.89 | bwd_allreduce_microstep: 0.14 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1893 +[2025-05-01 23:19:19,440] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.25 | bwd_microstep: 275.66 | bwd_inner_microstep: 275.65 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-01 23:19:19,980] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 208.54 | bwd_microstep: 310.56 | bwd_inner_microstep: 310.55 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-01 23:19:20,503] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 215.42 | bwd_microstep: 284.66 | bwd_inner_microstep: 284.58 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-01 23:19:21,003] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 194.99 | bwd_microstep: 285.46 | bwd_inner_microstep: 285.39 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-01 23:19:21,501] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 194.42 | bwd_microstep: 282.38 | bwd_inner_microstep: 282.30 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 23:19:22,053] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.63 | bwd_microstep: 341.57 | bwd_inner_microstep: 341.55 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 23:19:22,654] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 291.23 | bwd_microstep: 287.36 | bwd_inner_microstep: 287.34 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1347 +[2025-05-01 23:19:23,282] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 241.64 | bwd_microstep: 368.64 | bwd_inner_microstep: 368.54 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:19:24,150] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 402.29 | bwd_microstep: 443.21 | bwd_inner_microstep: 443.19 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.16 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 23:19:24,974] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 357.83 | bwd_microstep: 448.74 | bwd_inner_microstep: 448.73 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 23:19:25,793] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 322.80 | bwd_microstep: 465.81 | bwd_inner_microstep: 465.80 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.51 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 23:19:26,655] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 332.81 | bwd_microstep: 495.31 | bwd_inner_microstep: 495.29 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.28 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-01 23:19:27,432] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 296.05 | bwd_microstep: 449.05 | bwd_inner_microstep: 449.03 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 23:19:28,718] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.39 | optimizer_step: 19.15 +[2025-05-01 23:19:28,720] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 404.40 | bwd_microstep: 823.22 | bwd_inner_microstep: 392.47 | bwd_allreduce_microstep: 430.74 | step_microstep: 28.65 +[2025-05-01 23:19:28,721] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4005.72 | bwd: 5808.64 | bwd_inner: 5376.97 | bwd_allreduce: 431.12 | step: 39.06 + 5%|▍ | 433/8720 [1:04:02<18:25:01, 8.00s/it] {'loss': 0.9867, 'grad_norm': 5.472483158111572, 'learning_rate': 9.989917909162442e-06, 'epoch': 0.5} + 5%|▍ | 433/8720 [1:04:02<18:25:01, 8.00s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1959 +[2025-05-01 23:19:29,547] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 345.11 | bwd_microstep: 438.68 | bwd_inner_microstep: 438.67 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.30 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1386 +[2025-05-01 23:19:30,233] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 204.39 | bwd_microstep: 450.30 | bwd_inner_microstep: 450.29 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.33 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1895 +[2025-05-01 23:19:31,028] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 228.58 | bwd_microstep: 534.05 | bwd_inner_microstep: 534.03 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 348 +[2025-05-01 23:19:31,263] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 75.80 | bwd_microstep: 142.66 | bwd_inner_microstep: 142.64 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1379 +[2025-05-01 23:19:31,968] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 318.59 | bwd_microstep: 360.34 | bwd_inner_microstep: 360.00 | bwd_allreduce_microstep: 0.32 | step_microstep: 0.21 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-01 23:19:32,773] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 328.41 | bwd_microstep: 456.23 | bwd_inner_microstep: 456.21 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-01 23:19:33,657] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 364.66 | bwd_microstep: 485.92 | bwd_inner_microstep: 485.90 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.51 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-01 23:19:34,500] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 334.72 | bwd_microstep: 477.01 | bwd_inner_microstep: 476.99 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.48 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 326 +[2025-05-01 23:19:34,754] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 80.82 | bwd_microstep: 140.66 | bwd_inner_microstep: 140.64 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 23:19:35,522] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 423.21 | bwd_microstep: 314.71 | bwd_inner_microstep: 314.69 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 23:19:35,999] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.81 | bwd_microstep: 273.44 | bwd_inner_microstep: 273.42 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 830 +[2025-05-01 23:19:36,238] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.11 | bwd_microstep: 130.36 | bwd_inner_microstep: 130.08 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 23:19:36,718] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.13 | bwd_microstep: 275.83 | bwd_inner_microstep: 275.81 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 23:19:37,198] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.36 | bwd_microstep: 272.14 | bwd_inner_microstep: 272.12 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 827 +[2025-05-01 23:19:37,439] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.08 | bwd_microstep: 129.92 | bwd_inner_microstep: 129.84 | bwd_allreduce_microstep: 0.04 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 23:19:38,021] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.35 | optimizer_step: 16.64 +[2025-05-01 23:19:38,022] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.70 | bwd_microstep: 352.09 | bwd_inner_microstep: 274.02 | bwd_allreduce_microstep: 78.02 | step_microstep: 24.53 +[2025-05-01 23:19:38,023] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 3646.31 | bwd: 5234.40 | bwd_inner: 5155.36 | bwd_allreduce: 78.59 | step: 41.97 + 5%|▍ | 434/8720 [1:04:11<19:18:44, 8.39s/it] {'loss': 1.1211, 'grad_norm': 5.081465721130371, 'learning_rate': 9.98979968540572e-06, 'epoch': 0.5} + 5%|▍ | 434/8720 [1:04:11<19:18:44, 8.39s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1904 +[2025-05-01 23:19:38,512] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.44 | bwd_microstep: 275.97 | bwd_inner_microstep: 275.95 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-01 23:19:38,995] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.27 | bwd_microstep: 274.97 | bwd_inner_microstep: 274.96 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1364 +[2025-05-01 23:19:39,365] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.71 | bwd_microstep: 207.39 | bwd_inner_microstep: 207.27 | bwd_allreduce_microstep: 0.03 | step_microstep: 0.10 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 842 +[2025-05-01 23:19:39,608] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.39 | bwd_microstep: 132.57 | bwd_inner_microstep: 132.40 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-01 23:19:40,089] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.00 | bwd_microstep: 273.57 | bwd_inner_microstep: 273.56 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-01 23:19:40,569] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.44 | bwd_microstep: 273.88 | bwd_inner_microstep: 273.87 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-01 23:19:41,052] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.24 | bwd_microstep: 273.93 | bwd_inner_microstep: 273.91 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-01 23:19:41,535] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.75 | bwd_microstep: 273.72 | bwd_inner_microstep: 273.71 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-01 23:19:42,022] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.21 | bwd_microstep: 274.05 | bwd_inner_microstep: 274.03 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:19:42,503] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.38 | bwd_microstep: 273.50 | bwd_inner_microstep: 273.48 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 23:19:42,983] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.18 | bwd_microstep: 273.48 | bwd_inner_microstep: 273.46 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 23:19:43,463] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.55 | bwd_microstep: 273.00 | bwd_inner_microstep: 272.98 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 23:19:43,945] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.33 | bwd_microstep: 272.20 | bwd_inner_microstep: 272.18 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 828 +[2025-05-01 23:19:44,194] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 98.00 | bwd_microstep: 130.06 | bwd_inner_microstep: 129.91 | bwd_allreduce_microstep: 0.08 | step_microstep: 0.13 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 23:19:44,683] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.62 | bwd_microstep: 272.28 | bwd_inner_microstep: 272.26 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1850 +[2025-05-01 23:19:45,268] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.36 | optimizer_step: 16.45 +[2025-05-01 23:19:45,268] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.40 | bwd_microstep: 352.05 | bwd_inner_microstep: 272.15 | bwd_allreduce_microstep: 79.85 | step_microstep: 24.32 +[2025-05-01 23:19:45,270] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2794.53 | bwd: 4106.71 | bwd_inner: 4026.08 | bwd_allreduce: 80.13 | step: 25.34 + 5%|▍ | 435/8720 [1:04:19<18:31:12, 8.05s/it] {'loss': 1.0887, 'grad_norm': 3.921065330505371, 'learning_rate': 9.989680773238489e-06, 'epoch': 0.5} + 5%|▍ | 435/8720 [1:04:19<18:31:12, 8.05s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1927 +[2025-05-01 23:19:45,776] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.97 | bwd_microstep: 287.87 | bwd_inner_microstep: 287.85 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1913 +[2025-05-01 23:19:46,264] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 192.22 | bwd_microstep: 277.13 | bwd_inner_microstep: 277.11 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1896 +[2025-05-01 23:19:46,750] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.68 | bwd_microstep: 276.02 | bwd_inner_microstep: 276.00 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 347 +[2025-05-01 23:19:46,979] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 90.76 | bwd_microstep: 121.21 | bwd_inner_microstep: 120.90 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-01 23:19:47,460] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.08 | bwd_microstep: 274.31 | bwd_inner_microstep: 274.29 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-01 23:19:47,943] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.94 | bwd_microstep: 275.31 | bwd_inner_microstep: 275.29 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-01 23:19:48,427] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.21 | bwd_microstep: 274.20 | bwd_inner_microstep: 274.18 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-01 23:19:48,908] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.81 | bwd_microstep: 273.29 | bwd_inner_microstep: 273.27 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.14 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-01 23:19:49,389] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.98 | bwd_microstep: 273.43 | bwd_inner_microstep: 273.42 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 23:19:49,869] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.86 | bwd_microstep: 272.16 | bwd_inner_microstep: 272.14 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 23:19:50,347] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.17 | bwd_microstep: 271.87 | bwd_inner_microstep: 271.85 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 23:19:50,828] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.44 | bwd_microstep: 271.97 | bwd_inner_microstep: 271.95 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 23:19:51,307] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.46 | bwd_microstep: 271.87 | bwd_inner_microstep: 271.85 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1342 +[2025-05-01 23:19:51,670] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.58 | bwd_microstep: 204.82 | bwd_inner_microstep: 204.60 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-01 23:19:52,146] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.42 | bwd_microstep: 271.45 | bwd_inner_microstep: 271.43 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 23:19:52,718] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.31 | optimizer_step: 16.43 +[2025-05-01 23:19:52,719] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.76 | bwd_microstep: 343.34 | bwd_inner_microstep: 272.37 | bwd_allreduce_microstep: 70.93 | step_microstep: 23.68 +[2025-05-01 23:19:52,720] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2887.95 | bwd: 4240.32 | bwd_inner: 4168.57 | bwd_allreduce: 71.24 | step: 25.15 + 5%|▌ | 436/8720 [1:04:26<18:06:15, 7.87s/it] {'loss': 0.9958, 'grad_norm': 3.8364830017089844, 'learning_rate': 9.989561172677158e-06, 'epoch': 0.5} + 5%|▌ | 436/8720 [1:04:26<18:06:15, 7.87s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 433 +[2025-05-01 23:19:52,921] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 67.66 | bwd_microstep: 115.69 | bwd_inner_microstep: 115.56 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1900 +[2025-05-01 23:19:53,402] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.82 | bwd_microstep: 276.43 | bwd_inner_microstep: 276.41 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1914 +[2025-05-01 23:19:53,889] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 193.09 | bwd_microstep: 277.13 | bwd_inner_microstep: 277.11 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1883 +[2025-05-01 23:19:54,369] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.33 | bwd_microstep: 275.01 | bwd_inner_microstep: 274.99 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 843 +[2025-05-01 23:19:54,613] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.45 | bwd_microstep: 132.08 | bwd_inner_microstep: 132.01 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 23:19:55,093] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.34 | bwd_microstep: 273.95 | bwd_inner_microstep: 273.93 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 332 +[2025-05-01 23:19:55,331] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 101.87 | bwd_microstep: 117.27 | bwd_inner_microstep: 116.96 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 23:19:55,814] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.58 | bwd_microstep: 273.00 | bwd_inner_microstep: 272.98 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 23:19:56,296] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.06 | bwd_microstep: 273.47 | bwd_inner_microstep: 273.45 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 23:19:56,778] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.19 | bwd_microstep: 273.14 | bwd_inner_microstep: 273.13 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 325 +[2025-05-01 23:19:57,020] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.16 | bwd_microstep: 130.63 | bwd_inner_microstep: 130.40 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 23:19:57,500] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.25 | bwd_microstep: 272.93 | bwd_inner_microstep: 272.91 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 23:19:57,984] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.63 | bwd_microstep: 273.25 | bwd_inner_microstep: 273.23 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 23:19:58,464] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.13 | bwd_microstep: 273.16 | bwd_inner_microstep: 273.14 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 23:19:58,947] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.20 | bwd_microstep: 275.36 | bwd_inner_microstep: 275.34 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 23:19:59,599] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.34 | optimizer_step: 19.09 +[2025-05-01 23:19:59,599] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 210.91 | bwd_microstep: 392.81 | bwd_inner_microstep: 310.32 | bwd_allreduce_microstep: 82.41 | step_microstep: 27.96 +[2025-05-01 23:19:59,601] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2652.28 | bwd: 3905.38 | bwd_inner: 3822.02 | bwd_allreduce: 82.75 | step: 28.96 + 5%|▌ | 437/8720 [1:04:33<17:25:20, 7.57s/it] {'loss': 1.2284, 'grad_norm': 5.919919967651367, 'learning_rate': 9.989440883738226e-06, 'epoch': 0.5} + 5%|▌ | 437/8720 [1:04:33<17:25:20, 7.57s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-01 23:20:00,102] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 194.43 | bwd_microstep: 283.35 | bwd_inner_microstep: 283.30 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.13 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-01 23:20:00,600] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 194.81 | bwd_microstep: 283.85 | bwd_inner_microstep: 283.81 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1360 +[2025-05-01 23:20:00,975] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 147.96 | bwd_microstep: 208.74 | bwd_inner_microstep: 208.70 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-01 23:20:01,476] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 191.02 | bwd_microstep: 292.94 | bwd_inner_microstep: 292.92 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-01 23:20:02,478] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 409.33 | bwd_microstep: 568.85 | bwd_inner_microstep: 568.83 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.49 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1357 +[2025-05-01 23:20:02,916] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 194.36 | bwd_microstep: 210.75 | bwd_inner_microstep: 210.73 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:20:03,744] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.07 | bwd_microstep: 620.30 | bwd_inner_microstep: 620.28 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:20:04,424] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 342.44 | bwd_microstep: 304.62 | bwd_inner_microstep: 304.60 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.49 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 23:20:05,448] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 421.82 | bwd_microstep: 572.35 | bwd_inner_microstep: 572.33 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 23:20:06,186] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.78 | bwd_microstep: 529.41 | bwd_inner_microstep: 529.39 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.44 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 317 +[2025-05-01 23:20:06,446] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.12 | bwd_microstep: 134.31 | bwd_inner_microstep: 134.29 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 23:20:07,168] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 260.79 | bwd_microstep: 429.27 | bwd_inner_microstep: 429.25 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 23:20:07,955] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 436.78 | bwd_microstep: 320.95 | bwd_inner_microstep: 320.93 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.11 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 315 +[2025-05-01 23:20:08,178] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 77.58 | bwd_microstep: 129.86 | bwd_inner_microstep: 129.84 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-01 23:20:09,077] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 421.65 | bwd_microstep: 447.32 | bwd_inner_microstep: 447.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1918 +[2025-05-01 23:20:10,215] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.37 | optimizer_step: 16.41 +[2025-05-01 23:20:10,215] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 243.71 | bwd_microstep: 854.80 | bwd_inner_microstep: 637.13 | bwd_allreduce_microstep: 217.63 | step_microstep: 23.72 +[2025-05-01 23:20:10,216] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4011.48 | bwd: 6191.63 | bwd_inner: 5973.62 | bwd_allreduce: 217.71 | step: 41.30 + 5%|▌ | 438/8720 [1:04:43<19:31:10, 8.48s/it] {'loss': 1.2754, 'grad_norm': 4.899748802185059, 'learning_rate': 9.989319906438288e-06, 'epoch': 0.5} + 5%|▌ | 438/8720 [1:04:43<19:31:10, 8.48s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1911 +[2025-05-01 23:20:11,107] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 237.25 | bwd_microstep: 631.24 | bwd_inner_microstep: 631.22 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.48 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1370 +[2025-05-01 23:20:11,649] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 301.06 | bwd_microstep: 211.43 | bwd_inner_microstep: 211.41 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-01 23:20:12,647] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 361.22 | bwd_microstep: 620.25 | bwd_inner_microstep: 620.23 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-01 23:20:13,326] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 196.27 | bwd_microstep: 463.09 | bwd_inner_microstep: 463.07 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.47 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-01 23:20:14,131] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 436.15 | bwd_microstep: 339.61 | bwd_inner_microstep: 339.59 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-01 23:20:15,114] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 338.06 | bwd_microstep: 625.31 | bwd_inner_microstep: 625.29 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-01 23:20:15,789] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 202.07 | bwd_microstep: 443.81 | bwd_inner_microstep: 443.79 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-01 23:20:16,681] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 428.11 | bwd_microstep: 434.45 | bwd_inner_microstep: 434.43 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:20:17,559] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 233.68 | bwd_microstep: 626.54 | bwd_inner_microstep: 626.52 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 845 +[2025-05-01 23:20:17,919] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 194.82 | bwd_microstep: 134.92 | bwd_inner_microstep: 134.70 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-01 23:20:18,764] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 288.34 | bwd_microstep: 541.86 | bwd_inner_microstep: 541.85 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 840 +[2025-05-01 23:20:19,008] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.72 | bwd_microstep: 133.63 | bwd_inner_microstep: 133.61 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-01 23:20:19,974] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 392.17 | bwd_microstep: 555.79 | bwd_inner_microstep: 555.77 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 23:20:20,662] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.50 | bwd_microstep: 475.59 | bwd_inner_microstep: 475.58 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.48 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-01 23:20:21,373] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 401.73 | bwd_microstep: 275.55 | bwd_inner_microstep: 275.54 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1890 +[2025-05-01 23:20:22,512] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.29 | optimizer_step: 16.52 +[2025-05-01 23:20:22,512] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 426.65 | bwd_microstep: 661.55 | bwd_inner_microstep: 551.34 | bwd_allreduce_microstep: 110.16 | step_microstep: 23.78 +[2025-05-01 23:20:22,514] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4723.65 | bwd: 7174.66 | bwd_inner: 7063.98 | bwd_allreduce: 110.33 | step: 38.93 + 5%|▌ | 439/8720 [1:04:56<22:08:57, 9.63s/it] {'loss': 1.1753, 'grad_norm': 3.0791051387786865, 'learning_rate': 9.989198240794035e-06, 'epoch': 0.5} + 5%|▌ | 439/8720 [1:04:56<22:08:57, 9.63s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1898 +[2025-05-01 23:20:23,436] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 275.65 | bwd_microstep: 623.68 | bwd_inner_microstep: 623.66 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1899 +[2025-05-01 23:20:24,122] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 197.58 | bwd_microstep: 465.14 | bwd_inner_microstep: 465.12 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1368 +[2025-05-01 23:20:24,872] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 315.20 | bwd_microstep: 407.02 | bwd_inner_microstep: 407.00 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-01 23:20:25,648] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.75 | bwd_microstep: 564.87 | bwd_inner_microstep: 564.85 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.46 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-01 23:20:26,353] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 394.60 | bwd_microstep: 278.45 | bwd_inner_microstep: 278.43 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-01 23:20:27,409] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 411.46 | bwd_microstep: 626.49 | bwd_inner_microstep: 626.47 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-01 23:20:28,056] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 199.65 | bwd_microstep: 424.35 | bwd_inner_microstep: 424.34 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.30 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1355 +[2025-05-01 23:20:28,617] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 316.65 | bwd_microstep: 216.28 | bwd_inner_microstep: 216.15 | bwd_allreduce_microstep: 0.04 | step_microstep: 0.09 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 840 +[2025-05-01 23:20:29,020] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 91.91 | bwd_microstep: 294.65 | bwd_inner_microstep: 294.63 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-01 23:20:29,844] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 441.77 | bwd_microstep: 348.68 | bwd_inner_microstep: 348.66 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 839 +[2025-05-01 23:20:30,252] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.03 | bwd_microstep: 298.06 | bwd_inner_microstep: 298.04 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 323 +[2025-05-01 23:20:30,523] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 100.77 | bwd_microstep: 138.51 | bwd_inner_microstep: 138.49 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 23:20:31,230] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 332.11 | bwd_microstep: 342.30 | bwd_inner_microstep: 342.28 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 23:20:32,154] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 422.90 | bwd_microstep: 471.07 | bwd_inner_microstep: 471.05 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1849 +[2025-05-01 23:20:32,917] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.38 | bwd_microstep: 555.74 | bwd_inner_microstep: 555.72 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2201 +[2025-05-01 23:20:34,414] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 3.75 | optimizer_step: 15.83 +[2025-05-01 23:20:34,415] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 478.78 | bwd_microstep: 964.23 | bwd_inner_microstep: 361.10 | bwd_allreduce_microstep: 603.09 | step_microstep: 24.81 +[2025-05-01 23:20:34,416] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4452.09 | bwd: 7019.52 | bwd_inner: 6415.99 | bwd_allreduce: 603.25 | step: 48.65 + 5%|▌ | 440/8720 [1:05:08<23:42:51, 10.31s/it] {'loss': 1.2705, 'grad_norm': 3.4759738445281982, 'learning_rate': 9.989075886822254e-06, 'epoch': 0.5} + 5%|▌ | 440/8720 [1:05:08<23:42:51, 10.31s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1903 +[2025-05-01 23:20:35,310] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 242.91 | bwd_microstep: 628.82 | bwd_inner_microstep: 628.81 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.45 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1909 +[2025-05-01 23:20:36,013] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 234.54 | bwd_microstep: 435.67 | bwd_inner_microstep: 435.65 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.46 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-01 23:20:36,851] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 424.70 | bwd_microstep: 381.41 | bwd_inner_microstep: 381.40 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-01 23:20:37,752] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 261.95 | bwd_microstep: 621.73 | bwd_inner_microstep: 621.71 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.49 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 330 +[2025-05-01 23:20:38,011] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 101.14 | bwd_microstep: 129.79 | bwd_inner_microstep: 129.77 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.27 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-01 23:20:38,722] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 192.68 | bwd_microstep: 497.76 | bwd_inner_microstep: 497.74 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-01 23:20:39,438] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 405.78 | bwd_microstep: 277.09 | bwd_inner_microstep: 277.07 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-01 23:20:40,508] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 416.20 | bwd_microstep: 630.89 | bwd_inner_microstep: 630.87 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.20 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1092 +[2025-05-01 23:20:40,809] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 122.72 | bwd_microstep: 162.69 | bwd_inner_microstep: 162.67 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 23:20:41,821] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 372.45 | bwd_microstep: 622.62 | bwd_inner_microstep: 622.60 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 23:20:42,553] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 216.18 | bwd_microstep: 481.19 | bwd_inner_microstep: 481.17 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 23:20:43,267] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 371.44 | bwd_microstep: 308.00 | bwd_inner_microstep: 307.98 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 23:20:44,123] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 423.79 | bwd_microstep: 402.06 | bwd_inner_microstep: 402.04 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 23:20:45,050] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 287.36 | bwd_microstep: 622.42 | bwd_inner_microstep: 622.40 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 23:20:45,740] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 239.02 | bwd_microstep: 416.65 | bwd_inner_microstep: 416.63 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-01 23:20:46,674] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.10 | optimizer_step: 16.24 +[2025-05-01 23:20:46,675] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 422.98 | bwd_microstep: 458.87 | bwd_inner_microstep: 390.78 | bwd_allreduce_microstep: 68.04 | step_microstep: 23.52 +[2025-05-01 23:20:46,676] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4735.74 | bwd: 7077.67 | bwd_inner: 7009.32 | bwd_allreduce: 68.11 | step: 45.68 + 5%|▌ | 441/8720 [1:05:20<25:03:23, 10.90s/it] {'loss': 1.258, 'grad_norm': 3.728241205215454, 'learning_rate': 9.988952844539825e-06, 'epoch': 0.51} + 5%|▌ | 441/8720 [1:05:20<25:03:23, 10.90s/it]dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 854 +[2025-05-01 23:20:47,019] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.97 | bwd_microstep: 227.39 | bwd_inner_microstep: 227.37 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-01 23:20:47,916] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 427.63 | bwd_microstep: 437.37 | bwd_inner_microstep: 437.35 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-01 23:20:48,801] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 241.57 | bwd_microstep: 625.88 | bwd_inner_microstep: 625.86 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 843 +[2025-05-01 23:20:49,153] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.48 | bwd_microstep: 134.80 | bwd_inner_microstep: 134.75 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-01 23:20:49,992] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 194.73 | bwd_microstep: 626.86 | bwd_inner_microstep: 626.84 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-01 23:20:50,724] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 390.61 | bwd_microstep: 307.46 | bwd_inner_microstep: 307.44 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:20:51,636] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 422.83 | bwd_microstep: 458.48 | bwd_inner_microstep: 458.47 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.15 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:20:52,502] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 229.39 | bwd_microstep: 618.27 | bwd_inner_microstep: 618.26 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.47 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-01 23:20:53,207] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 251.10 | bwd_microstep: 418.90 | bwd_inner_microstep: 418.88 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:20:54,052] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 422.48 | bwd_microstep: 390.68 | bwd_inner_microstep: 390.66 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 23:20:54,983] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 288.37 | bwd_microstep: 625.24 | bwd_inner_microstep: 625.22 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 23:20:55,649] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 237.19 | bwd_microstep: 393.81 | bwd_inner_microstep: 393.80 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.30 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 23:20:56,589] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 427.54 | bwd_microstep: 480.86 | bwd_inner_microstep: 480.84 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 23:20:57,423] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 199.77 | bwd_microstep: 615.53 | bwd_inner_microstep: 615.51 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.53 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 23:20:58,145] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 226.98 | bwd_microstep: 460.56 | bwd_inner_microstep: 460.54 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1849 +[2025-05-01 23:20:59,040] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 3.94 | optimizer_step: 19.91 +[2025-05-01 23:20:59,040] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 434.21 | bwd_microstep: 408.18 | bwd_inner_microstep: 340.38 | bwd_allreduce_microstep: 67.75 | step_microstep: 29.04 +[2025-05-01 23:20:59,042] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4676.74 | bwd: 7230.30 | bwd_inner: 7162.19 | bwd_allreduce: 67.85 | step: 53.17 + 5%|▌ | 442/8720 [1:05:32<26:04:03, 11.34s/it] {'loss': 0.8957, 'grad_norm': 4.713553428649902, 'learning_rate': 9.98882911396372e-06, 'epoch': 0.51} + 5%|▌ | 442/8720 [1:05:32<26:04:03, 11.34s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2067 +[2025-05-01 23:21:00,164] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 432.82 | bwd_microstep: 669.13 | bwd_inner_microstep: 669.11 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 419 +[2025-05-01 23:21:00,366] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 71.66 | bwd_microstep: 117.14 | bwd_inner_microstep: 116.89 | bwd_allreduce_microstep: 0.10 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1922 +[2025-05-01 23:21:01,349] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 333.08 | bwd_microstep: 633.19 | bwd_inner_microstep: 633.18 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1359 +[2025-05-01 23:21:01,805] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 145.00 | bwd_microstep: 291.37 | bwd_inner_microstep: 291.35 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-01 23:21:02,712] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 427.93 | bwd_microstep: 445.48 | bwd_inner_microstep: 445.46 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 23:21:03,594] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 239.34 | bwd_microstep: 623.00 | bwd_inner_microstep: 622.98 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 6, images per sample: 6.0, dynamic token length: 1607 +[2025-05-01 23:21:04,153] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 261.56 | bwd_microstep: 263.82 | bwd_inner_microstep: 263.80 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-01 23:21:05,085] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 430.20 | bwd_microstep: 471.01 | bwd_inner_microstep: 470.99 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 23:21:05,924] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.04 | bwd_microstep: 624.37 | bwd_inner_microstep: 624.36 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.49 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 318 +[2025-05-01 23:21:06,172] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 98.43 | bwd_microstep: 122.28 | bwd_inner_microstep: 121.96 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 23:21:06,920] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.70 | bwd_microstep: 538.40 | bwd_inner_microstep: 538.38 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 23:21:07,651] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 424.11 | bwd_microstep: 276.33 | bwd_inner_microstep: 276.31 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 23:21:08,692] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 403.37 | bwd_microstep: 620.18 | bwd_inner_microstep: 620.16 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1978 +[2025-05-01 23:21:09,437] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 211.45 | bwd_microstep: 508.54 | bwd_inner_microstep: 508.53 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 23:21:10,272] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 439.38 | bwd_microstep: 362.59 | bwd_inner_microstep: 362.57 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-01 23:21:11,516] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.11 | optimizer_step: 15.72 +[2025-05-01 23:21:11,517] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 269.72 | bwd_microstep: 936.84 | bwd_inner_microstep: 618.50 | bwd_allreduce_microstep: 318.30 | step_microstep: 22.90 +[2025-05-01 23:21:11,518] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4567.63 | bwd: 7503.70 | bwd_inner: 7184.66 | bwd_allreduce: 318.57 | step: 39.94 + 5%|▌ | 443/8720 [1:05:45<26:51:01, 11.68s/it] {'loss': 0.8645, 'grad_norm': 3.5912790298461914, 'learning_rate': 9.988704695111014e-06, 'epoch': 0.51} + 5%|▌ | 443/8720 [1:05:45<26:51:01, 11.68s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1889 +[2025-05-01 23:21:12,421] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 276.07 | bwd_microstep: 606.25 | bwd_inner_microstep: 606.23 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.07 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-01 23:21:13,090] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 193.05 | bwd_microstep: 457.50 | bwd_inner_microstep: 457.48 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1356 +[2025-05-01 23:21:13,847] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 315.60 | bwd_microstep: 412.66 | bwd_inner_microstep: 412.64 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.13 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-01 23:21:14,568] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.93 | bwd_microstep: 509.84 | bwd_inner_microstep: 509.82 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.44 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-01 23:21:15,391] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 443.45 | bwd_microstep: 344.82 | bwd_inner_microstep: 344.80 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-01 23:21:16,296] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 257.90 | bwd_microstep: 627.89 | bwd_inner_microstep: 627.87 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.31 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 842 +[2025-05-01 23:21:16,696] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 222.60 | bwd_microstep: 148.50 | bwd_inner_microstep: 148.22 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 333 +[2025-05-01 23:21:16,899] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 70.24 | bwd_microstep: 118.92 | bwd_inner_microstep: 118.60 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:21:17,863] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 413.16 | bwd_microstep: 534.28 | bwd_inner_microstep: 534.27 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 23:21:18,634] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.01 | bwd_microstep: 562.99 | bwd_inner_microstep: 562.97 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 23:21:19,402] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 442.37 | bwd_microstep: 293.76 | bwd_inner_microstep: 293.74 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 23:21:20,367] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 362.26 | bwd_microstep: 586.89 | bwd_inner_microstep: 586.87 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 23:21:21,070] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.71 | bwd_microstep: 495.17 | bwd_inner_microstep: 495.16 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 23:21:21,904] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 443.03 | bwd_microstep: 364.55 | bwd_inner_microstep: 364.53 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 23:21:22,844] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 303.25 | bwd_microstep: 618.90 | bwd_inner_microstep: 618.89 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.48 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-01 23:21:24,112] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.09 | optimizer_step: 15.80 +[2025-05-01 23:21:24,112] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 290.86 | bwd_microstep: 921.35 | bwd_inner_microstep: 387.92 | bwd_allreduce_microstep: 533.38 | step_microstep: 23.13 +[2025-05-01 23:21:24,114] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4602.33 | bwd: 7604.34 | bwd_inner: 7070.12 | bwd_allreduce: 533.69 | step: 36.93 + 5%|▌ | 444/8720 [1:05:57<27:28:47, 11.95s/it] {'loss': 1.1308, 'grad_norm': 4.386841297149658, 'learning_rate': 9.98857958799887e-06, 'epoch': 0.51} + 5%|▌ | 444/8720 [1:05:57<27:28:47, 11.95s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1905 +[2025-05-01 23:21:25,011] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 245.45 | bwd_microstep: 630.15 | bwd_inner_microstep: 630.13 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.50 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1396 +[2025-05-01 23:21:25,484] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 224.54 | bwd_microstep: 211.84 | bwd_inner_microstep: 211.65 | bwd_allreduce_microstep: 0.08 | step_microstep: 0.12 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1377 +[2025-05-01 23:21:26,248] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 271.33 | bwd_microstep: 474.47 | bwd_inner_microstep: 474.45 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1889 +[2025-05-01 23:21:26,951] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 343.19 | bwd_microstep: 324.18 | bwd_inner_microstep: 324.16 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-01 23:21:27,902] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 424.29 | bwd_microstep: 494.06 | bwd_inner_microstep: 494.04 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-01 23:21:28,729] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.68 | bwd_microstep: 617.92 | bwd_inner_microstep: 617.90 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 835 +[2025-05-01 23:21:29,128] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 214.40 | bwd_microstep: 152.39 | bwd_inner_microstep: 152.11 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:21:29,936] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.41 | bwd_microstep: 598.46 | bwd_inner_microstep: 598.44 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.50 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-01 23:21:30,665] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 419.28 | bwd_microstep: 278.45 | bwd_inner_microstep: 278.43 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 839 +[2025-05-01 23:21:31,154] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.43 | bwd_microstep: 283.53 | bwd_inner_microstep: 283.51 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-01 23:21:31,949] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 442.79 | bwd_microstep: 321.47 | bwd_inner_microstep: 321.45 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:21:32,932] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 343.46 | bwd_microstep: 622.48 | bwd_inner_microstep: 622.46 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.50 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-01 23:21:33,621] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 246.09 | bwd_microstep: 410.50 | bwd_inner_microstep: 410.48 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 23:21:34,477] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 423.43 | bwd_microstep: 402.24 | bwd_inner_microstep: 402.22 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 23:21:35,365] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 257.00 | bwd_microstep: 613.68 | bwd_inner_microstep: 613.66 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 23:21:36,555] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.07 | optimizer_step: 15.83 +[2025-05-01 23:21:36,556] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 274.80 | bwd_microstep: 862.78 | bwd_inner_microstep: 354.89 | bwd_allreduce_microstep: 507.83 | step_microstep: 23.09 +[2025-05-01 23:21:36,557] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4698.45 | bwd: 7298.60 | bwd_inner: 6790.08 | bwd_allreduce: 508.06 | step: 45.17 + 5%|▌ | 445/8720 [1:06:10<27:48:52, 12.10s/it] {'loss': 1.6015, 'grad_norm': 5.202878952026367, 'learning_rate': 9.988453792644546e-06, 'epoch': 0.51} + 5%|▌ | 445/8720 [1:06:10<27:48:52, 12.10s/it]dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 922 +[2025-05-01 23:21:36,952] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 100.96 | bwd_microstep: 273.26 | bwd_inner_microstep: 273.24 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1907 +[2025-05-01 23:21:37,717] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 440.78 | bwd_microstep: 293.57 | bwd_inner_microstep: 293.55 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 876 +[2025-05-01 23:21:38,218] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 184.91 | bwd_microstep: 300.11 | bwd_inner_microstep: 300.10 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1377 +[2025-05-01 23:21:38,898] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 330.62 | bwd_microstep: 321.78 | bwd_inner_microstep: 321.76 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-01 23:21:39,746] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 203.03 | bwd_microstep: 625.80 | bwd_inner_microstep: 625.78 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.52 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1888 +[2025-05-01 23:21:40,463] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 319.75 | bwd_microstep: 362.52 | bwd_inner_microstep: 362.50 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-01 23:21:41,373] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 424.45 | bwd_microstep: 453.46 | bwd_inner_microstep: 453.44 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-01 23:21:42,252] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 242.14 | bwd_microstep: 619.76 | bwd_inner_microstep: 619.74 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.30 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-01 23:21:42,932] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 286.77 | bwd_microstep: 359.23 | bwd_inner_microstep: 359.21 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.33 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-01 23:21:43,840] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 423.03 | bwd_microstep: 455.32 | bwd_inner_microstep: 455.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 23:21:44,721] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 243.07 | bwd_microstep: 619.13 | bwd_inner_microstep: 619.11 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.47 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 23:21:45,380] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 283.15 | bwd_microstep: 341.52 | bwd_inner_microstep: 341.51 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.31 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 320 +[2025-05-01 23:21:45,630] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 98.25 | bwd_microstep: 121.95 | bwd_inner_microstep: 119.60 | bwd_allreduce_microstep: 2.34 | step_microstep: 2.52 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 23:21:46,451] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 439.86 | bwd_microstep: 351.06 | bwd_inner_microstep: 351.04 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 23:21:47,406] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 319.37 | bwd_microstep: 617.75 | bwd_inner_microstep: 617.73 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.51 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1850 +[2025-05-01 23:21:48,665] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.14 | optimizer_step: 15.68 +[2025-05-01 23:21:48,665] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 208.90 | bwd_microstep: 992.80 | bwd_inner_microstep: 433.81 | bwd_allreduce_microstep: 558.95 | step_microstep: 22.98 +[2025-05-01 23:21:48,666] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4548.93 | bwd: 7109.02 | bwd_inner: 6547.43 | bwd_allreduce: 559.03 | step: 47.19 + 5%|▌ | 446/8720 [1:06:22<27:49:00, 12.10s/it] {'loss': 1.6279, 'grad_norm': 3.8550047874450684, 'learning_rate': 9.9883273090654e-06, 'epoch': 0.51} + 5%|▌ | 446/8720 [1:06:22<27:49:00, 12.10s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1901 +[2025-05-01 23:21:49,555] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 237.59 | bwd_microstep: 628.89 | bwd_inner_microstep: 628.87 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1893 +[2025-05-01 23:21:50,248] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 348.59 | bwd_microstep: 312.02 | bwd_inner_microstep: 312.00 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 358 +[2025-05-01 23:21:50,540] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 109.21 | bwd_microstep: 152.94 | bwd_inner_microstep: 152.93 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.36 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 340 +[2025-05-01 23:21:50,813] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 104.24 | bwd_microstep: 142.12 | bwd_inner_microstep: 142.10 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.46 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1883 +[2025-05-01 23:21:51,513] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 345.82 | bwd_microstep: 321.43 | bwd_inner_microstep: 321.41 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-01 23:21:52,361] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 425.98 | bwd_microstep: 390.41 | bwd_inner_microstep: 390.39 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 848 +[2025-05-01 23:21:52,747] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.77 | bwd_microstep: 274.41 | bwd_inner_microstep: 274.39 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.47 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-01 23:21:53,659] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 424.89 | bwd_microstep: 454.86 | bwd_inner_microstep: 454.84 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-01 23:21:54,502] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 197.53 | bwd_microstep: 627.93 | bwd_inner_microstep: 627.91 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.28 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 23:21:55,197] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 386.31 | bwd_microstep: 276.44 | bwd_inner_microstep: 276.42 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 23:21:56,259] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 413.86 | bwd_microstep: 632.72 | bwd_inner_microstep: 632.70 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 23:21:56,904] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.76 | bwd_microstep: 428.72 | bwd_inner_microstep: 428.70 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 23:21:57,801] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 423.69 | bwd_microstep: 441.84 | bwd_inner_microstep: 441.82 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 23:21:58,585] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.59 | bwd_microstep: 577.16 | bwd_inner_microstep: 577.14 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 23:21:59,280] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 331.60 | bwd_microstep: 330.12 | bwd_inner_microstep: 330.10 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-01 23:22:00,309] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.15 | optimizer_step: 15.84 +[2025-05-01 23:22:00,309] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 417.67 | bwd_microstep: 558.15 | bwd_inner_microstep: 482.65 | bwd_allreduce_microstep: 75.46 | step_microstep: 23.74 +[2025-05-01 23:22:00,310] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4647.01 | bwd: 6550.17 | bwd_inner: 6474.39 | bwd_allreduce: 75.55 | step: 45.78 + 5%|▌ | 447/8720 [1:06:34<27:29:51, 11.97s/it] {'loss': 1.223, 'grad_norm': 4.396090507507324, 'learning_rate': 9.988200137278883e-06, 'epoch': 0.51} + 5%|▌ | 447/8720 [1:06:34<27:29:51, 11.97s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1931 +[2025-05-01 23:22:01,337] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 347.18 | bwd_microstep: 656.20 | bwd_inner_microstep: 656.18 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.53 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 882 +[2025-05-01 23:22:01,604] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 103.79 | bwd_microstep: 136.94 | bwd_inner_microstep: 136.65 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1900 +[2025-05-01 23:22:02,623] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 375.05 | bwd_microstep: 620.68 | bwd_inner_microstep: 620.66 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.26 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-01 23:22:03,290] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 194.18 | bwd_microstep: 452.69 | bwd_inner_microstep: 452.67 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-01 23:22:04,172] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 427.78 | bwd_microstep: 422.82 | bwd_inner_microstep: 422.80 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-01 23:22:05,078] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 262.39 | bwd_microstep: 626.47 | bwd_inner_microstep: 626.45 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-01 23:22:05,764] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 262.05 | bwd_microstep: 389.20 | bwd_inner_microstep: 389.19 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-01 23:22:06,646] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 429.06 | bwd_microstep: 421.24 | bwd_inner_microstep: 421.22 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 23:22:07,534] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 247.40 | bwd_microstep: 623.19 | bwd_inner_microstep: 623.17 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.46 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 23:22:08,226] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 233.29 | bwd_microstep: 426.80 | bwd_inner_microstep: 426.78 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:22:09,019] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 441.17 | bwd_microstep: 319.33 | bwd_inner_microstep: 319.31 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 837 +[2025-05-01 23:22:09,441] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 105.42 | bwd_microstep: 300.70 | bwd_inner_microstep: 300.68 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 23:22:10,312] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 427.09 | bwd_microstep: 412.36 | bwd_inner_microstep: 412.35 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.16 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 23:22:11,201] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 248.85 | bwd_microstep: 622.10 | bwd_inner_microstep: 622.08 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 23:22:11,896] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 274.24 | bwd_microstep: 385.02 | bwd_inner_microstep: 385.00 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1906 +[2025-05-01 23:22:12,877] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.86 | optimizer_step: 16.54 +[2025-05-01 23:22:12,878] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 428.92 | bwd_microstep: 497.93 | bwd_inner_microstep: 430.78 | bwd_allreduce_microstep: 67.12 | step_microstep: 24.52 +[2025-05-01 23:22:12,879] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4807.74 | bwd: 7313.71 | bwd_inner: 7246.04 | bwd_allreduce: 67.32 | step: 47.64 + 5%|▌ | 448/8720 [1:06:46<27:54:34, 12.15s/it] {'loss': 1.3831, 'grad_norm': 3.7262165546417236, 'learning_rate': 9.988072277302536e-06, 'epoch': 0.51} + 5%|▌ | 448/8720 [1:06:46<27:54:34, 12.15s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2201 +[2025-05-01 23:22:13,966] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 414.55 | bwd_microstep: 652.29 | bwd_inner_microstep: 652.27 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2124 +[2025-05-01 23:22:14,849] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 207.67 | bwd_microstep: 655.49 | bwd_inner_microstep: 655.47 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.53 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1894 +[2025-05-01 23:22:15,563] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 401.33 | bwd_microstep: 280.21 | bwd_inner_microstep: 280.19 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1905 +[2025-05-01 23:22:16,578] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 428.64 | bwd_microstep: 570.55 | bwd_inner_microstep: 570.54 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1894 +[2025-05-01 23:22:17,306] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 191.90 | bwd_microstep: 515.91 | bwd_inner_microstep: 515.89 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 351 +[2025-05-01 23:22:17,587] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 106.63 | bwd_microstep: 143.90 | bwd_inner_microstep: 143.88 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-01 23:22:18,319] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 318.96 | bwd_microstep: 379.49 | bwd_inner_microstep: 379.47 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 23:22:19,154] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 419.44 | bwd_microstep: 382.25 | bwd_inner_microstep: 382.20 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 23:22:20,090] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 293.02 | bwd_microstep: 625.32 | bwd_inner_microstep: 625.31 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.33 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:22:20,775] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 298.17 | bwd_microstep: 353.25 | bwd_inner_microstep: 353.23 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:22:21,686] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 421.86 | bwd_microstep: 457.34 | bwd_inner_microstep: 457.32 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-01 23:22:22,540] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 216.90 | bwd_microstep: 619.88 | bwd_inner_microstep: 619.86 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.43 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 23:22:23,213] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 210.48 | bwd_microstep: 430.22 | bwd_inner_microstep: 430.20 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.31 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 317 +[2025-05-01 23:22:23,470] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.93 | bwd_microstep: 131.52 | bwd_inner_microstep: 131.50 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 23:22:24,193] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 416.69 | bwd_microstep: 275.50 | bwd_inner_microstep: 275.48 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 23:22:25,363] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.24 | optimizer_step: 16.11 +[2025-05-01 23:22:25,363] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 400.08 | bwd_microstep: 730.02 | bwd_inner_microstep: 592.75 | bwd_allreduce_microstep: 137.21 | step_microstep: 23.29 +[2025-05-01 23:22:25,365] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4842.16 | bwd: 7203.14 | bwd_inner: 7065.58 | bwd_allreduce: 137.30 | step: 45.01 + 5%|▌ | 449/8720 [1:06:59<28:08:23, 12.25s/it] {'loss': 1.0341, 'grad_norm': 3.38020396232605, 'learning_rate': 9.987943729154004e-06, 'epoch': 0.51} + 5%|▌ | 449/8720 [1:06:59<28:08:23, 12.25s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1899 +[2025-05-01 23:22:26,274] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 255.46 | bwd_microstep: 632.11 | bwd_inner_microstep: 632.09 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.46 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 852 +[2025-05-01 23:22:26,674] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 221.65 | bwd_microstep: 149.43 | bwd_inner_microstep: 149.37 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-01 23:22:27,517] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 396.43 | bwd_microstep: 427.92 | bwd_inner_microstep: 427.90 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 842 +[2025-05-01 23:22:28,029] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 211.30 | bwd_microstep: 273.82 | bwd_inner_microstep: 273.60 | bwd_allreduce_microstep: 0.09 | step_microstep: 0.09 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 845 +[2025-05-01 23:22:28,401] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.25 | bwd_microstep: 262.55 | bwd_inner_microstep: 262.36 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.35 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 332 +[2025-05-01 23:22:28,667] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 99.03 | bwd_microstep: 138.41 | bwd_inner_microstep: 138.39 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.31 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 23:22:29,518] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 203.28 | bwd_microstep: 618.56 | bwd_inner_microstep: 618.54 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.33 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 321 +[2025-05-01 23:22:29,748] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 76.00 | bwd_microstep: 124.18 | bwd_inner_microstep: 124.02 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 23:22:30,580] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 410.35 | bwd_microstep: 402.85 | bwd_inner_microstep: 402.83 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 23:22:31,443] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 418.30 | bwd_microstep: 413.10 | bwd_inner_microstep: 413.09 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 23:22:32,317] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 423.70 | bwd_microstep: 420.83 | bwd_inner_microstep: 420.81 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 23:22:33,163] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 313.39 | bwd_microstep: 503.74 | bwd_inner_microstep: 503.72 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.31 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 23:22:34,016] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 225.88 | bwd_microstep: 594.23 | bwd_inner_microstep: 594.22 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-01 23:22:34,838] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 232.00 | bwd_microstep: 557.87 | bwd_inner_microstep: 557.85 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1850 +[2025-05-01 23:22:35,678] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 222.55 | bwd_microstep: 597.85 | bwd_inner_microstep: 597.84 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 827 +[2025-05-01 23:22:36,345] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 4.68 | optimizer_step: 19.85 +[2025-05-01 23:22:36,347] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.11 | bwd_microstep: 529.76 | bwd_inner_microstep: 253.09 | bwd_allreduce_microstep: 276.63 | step_microstep: 29.86 +[2025-05-01 23:22:36,349] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 3897.59 | bwd: 6647.26 | bwd_inner: 6369.79 | bwd_allreduce: 277.04 | step: 51.68 + 5%|▌ | 450/8720 [1:07:10<27:16:03, 11.87s/it] {'loss': 1.0229, 'grad_norm': 6.104565143585205, 'learning_rate': 9.987814492851017e-06, 'epoch': 0.52} + 5%|▌ | 450/8720 [1:07:10<27:16:03, 11.87s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1911 +[2025-05-01 23:22:37,266] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 379.78 | bwd_microstep: 495.54 | bwd_inner_microstep: 495.52 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 872 +[2025-05-01 23:22:37,613] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 147.07 | bwd_microstep: 169.02 | bwd_inner_microstep: 169.00 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 362 +[2025-05-01 23:22:37,889] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 109.90 | bwd_microstep: 135.87 | bwd_inner_microstep: 135.85 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.33 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-01 23:22:38,776] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 344.72 | bwd_microstep: 510.31 | bwd_inner_microstep: 510.29 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-01 23:22:39,604] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 274.62 | bwd_microstep: 521.51 | bwd_inner_microstep: 521.49 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.37 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-01 23:22:40,393] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 271.40 | bwd_microstep: 487.57 | bwd_inner_microstep: 487.55 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.22 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 23:22:41,225] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 350.39 | bwd_microstep: 467.08 | bwd_inner_microstep: 467.07 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 23:22:42,107] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 370.14 | bwd_microstep: 497.20 | bwd_inner_microstep: 497.18 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 23:22:42,991] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 343.92 | bwd_microstep: 522.57 | bwd_inner_microstep: 522.55 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.13 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 321 +[2025-05-01 23:22:43,226] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 79.85 | bwd_microstep: 137.83 | bwd_inner_microstep: 137.81 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 23:22:44,075] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 414.28 | bwd_microstep: 402.83 | bwd_inner_microstep: 402.81 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 23:22:44,939] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 331.70 | bwd_microstep: 500.42 | bwd_inner_microstep: 500.40 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.48 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 23:22:45,812] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 239.39 | bwd_microstep: 603.23 | bwd_inner_microstep: 603.22 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.75 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2293 +[2025-05-01 23:22:46,685] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 290.14 | bwd_microstep: 558.55 | bwd_inner_microstep: 558.53 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1934 +[2025-05-01 23:22:47,620] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 439.94 | bwd_microstep: 467.18 | bwd_inner_microstep: 467.16 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 23:22:48,768] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.51 | optimizer_step: 16.07 +[2025-05-01 23:22:48,769] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 414.47 | bwd_microstep: 680.66 | bwd_inner_microstep: 411.87 | bwd_allreduce_microstep: 268.77 | step_microstep: 23.65 +[2025-05-01 23:22:48,770] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4801.62 | bwd: 7157.34 | bwd_inner: 6888.30 | bwd_allreduce: 268.83 | step: 46.31 + 5%|▌ | 451/8720 [1:07:22<27:38:31, 12.03s/it] {'loss': 0.9043, 'grad_norm': 3.6693811416625977, 'learning_rate': 9.98768456841141e-06, 'epoch': 0.52} + 5%|▌ | 451/8720 [1:07:22<27:38:31, 12.03s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 351 +[2025-05-01 23:22:49,036] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 106.56 | bwd_microstep: 121.94 | bwd_inner_microstep: 121.92 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1889 +[2025-05-01 23:22:49,920] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 313.48 | bwd_microstep: 538.51 | bwd_inner_microstep: 538.49 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-01 23:22:50,793] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 292.69 | bwd_microstep: 548.49 | bwd_inner_microstep: 548.47 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.50 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-01 23:22:51,649] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 236.85 | bwd_microstep: 586.37 | bwd_inner_microstep: 586.35 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.53 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-01 23:22:52,532] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 242.16 | bwd_microstep: 608.17 | bwd_inner_microstep: 608.16 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.50 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-01 23:22:53,400] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 223.32 | bwd_microstep: 614.52 | bwd_inner_microstep: 614.50 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.64 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1358 +[2025-05-01 23:22:53,993] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 146.27 | bwd_microstep: 427.32 | bwd_inner_microstep: 427.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.51 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-01 23:22:54,853] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 327.10 | bwd_microstep: 496.40 | bwd_inner_microstep: 496.38 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-01 23:22:55,706] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 331.62 | bwd_microstep: 489.06 | bwd_inner_microstep: 489.04 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:22:56,583] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 339.41 | bwd_microstep: 505.45 | bwd_inner_microstep: 505.43 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 321 +[2025-05-01 23:22:56,819] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 99.48 | bwd_microstep: 108.65 | bwd_inner_microstep: 108.51 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 23:22:57,653] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 316.54 | bwd_microstep: 501.32 | bwd_inner_microstep: 501.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-01 23:22:58,484] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 335.14 | bwd_microstep: 480.61 | bwd_inner_microstep: 480.59 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 827 +[2025-05-01 23:22:58,941] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 147.06 | bwd_microstep: 293.44 | bwd_inner_microstep: 293.43 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 23:22:59,808] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 334.88 | bwd_microstep: 499.31 | bwd_inner_microstep: 499.29 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.46 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-01 23:23:00,852] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.13 | optimizer_step: 16.03 +[2025-05-01 23:23:00,852] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 238.48 | bwd_microstep: 750.55 | bwd_inner_microstep: 611.63 | bwd_allreduce_microstep: 138.87 | step_microstep: 23.34 +[2025-05-01 23:23:00,853] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4030.97 | bwd: 7570.15 | bwd_inner: 7430.86 | bwd_allreduce: 139.00 | step: 50.73 + 5%|▌ | 452/8720 [1:07:34<27:40:22, 12.05s/it] {'loss': 1.1003, 'grad_norm': 4.087332248687744, 'learning_rate': 9.987553955853103e-06, 'epoch': 0.52} + 5%|▌ | 452/8720 [1:07:34<27:40:22, 12.05s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1928 +[2025-05-01 23:23:01,761] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 424.88 | bwd_microstep: 459.96 | bwd_inner_microstep: 459.93 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1893 +[2025-05-01 23:23:02,658] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 424.01 | bwd_microstep: 438.68 | bwd_inner_microstep: 438.66 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 343 +[2025-05-01 23:23:02,930] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 104.29 | bwd_microstep: 139.61 | bwd_inner_microstep: 139.59 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-01 23:23:03,792] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 220.97 | bwd_microstep: 610.37 | bwd_inner_microstep: 610.35 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.47 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-01 23:23:04,626] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 251.00 | bwd_microstep: 566.25 | bwd_inner_microstep: 566.23 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 847 +[2025-05-01 23:23:05,059] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 125.53 | bwd_microstep: 290.08 | bwd_inner_microstep: 290.06 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 335 +[2025-05-01 23:23:05,309] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 84.33 | bwd_microstep: 146.68 | bwd_inner_microstep: 146.66 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.53 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 23:23:06,183] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 422.10 | bwd_microstep: 414.59 | bwd_inner_microstep: 414.57 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-01 23:23:07,065] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 422.17 | bwd_microstep: 425.93 | bwd_inner_microstep: 425.91 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 23:23:07,928] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 415.18 | bwd_microstep: 416.24 | bwd_inner_microstep: 416.22 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 23:23:08,778] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 314.41 | bwd_microstep: 502.84 | bwd_inner_microstep: 502.80 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.52 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 23:23:09,639] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 325.72 | bwd_microstep: 503.09 | bwd_inner_microstep: 503.07 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.33 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 23:23:10,511] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 226.41 | bwd_microstep: 613.85 | bwd_inner_microstep: 613.82 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 23:23:11,330] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 242.22 | bwd_microstep: 547.24 | bwd_inner_microstep: 547.22 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 317 +[2025-05-01 23:23:11,562] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 74.82 | bwd_microstep: 140.58 | bwd_inner_microstep: 140.57 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.51 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1849 +[2025-05-01 23:23:12,648] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.15 | optimizer_step: 16.00 +[2025-05-01 23:23:12,649] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 343.74 | bwd_microstep: 690.96 | bwd_inner_microstep: 525.62 | bwd_allreduce_microstep: 165.30 | step_microstep: 23.19 +[2025-05-01 23:23:12,650] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4421.71 | bwd: 6906.96 | bwd_inner: 6741.30 | bwd_allreduce: 165.38 | step: 51.26 + 5%|▌ | 453/8720 [1:07:46<27:29:43, 11.97s/it] {'loss': 1.2215, 'grad_norm': 4.656979560852051, 'learning_rate': 9.98742265519412e-06, 'epoch': 0.52} + 5%|▌ | 453/8720 [1:07:46<27:29:43, 11.97s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1958 +[2025-05-01 23:23:13,555] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 397.21 | bwd_microstep: 488.28 | bwd_inner_microstep: 488.26 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1920 +[2025-05-01 23:23:14,438] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 378.16 | bwd_microstep: 489.45 | bwd_inner_microstep: 489.43 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-01 23:23:15,320] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 369.49 | bwd_microstep: 495.68 | bwd_inner_microstep: 495.66 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-01 23:23:16,199] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 345.87 | bwd_microstep: 518.23 | bwd_inner_microstep: 518.22 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-01 23:23:16,994] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 372.87 | bwd_microstep: 400.90 | bwd_inner_microstep: 400.89 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.51 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-01 23:23:17,848] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 427.10 | bwd_microstep: 393.12 | bwd_inner_microstep: 393.10 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-01 23:23:18,710] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 422.27 | bwd_microstep: 411.54 | bwd_inner_microstep: 411.52 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-01 23:23:19,587] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 422.96 | bwd_microstep: 424.97 | bwd_inner_microstep: 424.95 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-01 23:23:20,457] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 423.74 | bwd_microstep: 414.32 | bwd_inner_microstep: 414.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.48 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 23:23:21,304] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 288.55 | bwd_microstep: 525.90 | bwd_inner_microstep: 525.88 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 23:23:22,188] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 270.55 | bwd_microstep: 595.89 | bwd_inner_microstep: 595.87 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 23:23:23,025] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 254.46 | bwd_microstep: 564.28 | bwd_inner_microstep: 564.27 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 23:23:23,858] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 296.06 | bwd_microstep: 519.35 | bwd_inner_microstep: 519.33 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 23:23:24,698] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 324.68 | bwd_microstep: 496.59 | bwd_inner_microstep: 496.57 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 23:23:25,579] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 355.32 | bwd_microstep: 510.38 | bwd_inner_microstep: 510.36 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1850 +[2025-05-01 23:23:26,775] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.18 | optimizer_step: 15.95 +[2025-05-01 23:23:26,775] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 367.62 | bwd_microstep: 788.12 | bwd_inner_microstep: 433.58 | bwd_allreduce_microstep: 354.49 | step_microstep: 23.18 +[2025-05-01 23:23:26,776] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 5716.72 | bwd: 8037.01 | bwd_inner: 7682.20 | bwd_allreduce: 354.58 | step: 31.20 + 5%|▌ | 454/8720 [1:08:00<28:58:36, 12.62s/it] {'loss': 1.1849, 'grad_norm': 5.334934711456299, 'learning_rate': 9.987290666452573e-06, 'epoch': 0.52} + 5%|▌ | 454/8720 [1:08:00<28:58:36, 12.62s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 360 +[2025-05-01 23:23:27,039] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 87.69 | bwd_microstep: 152.19 | bwd_inner_microstep: 152.17 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1894 +[2025-05-01 23:23:27,903] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 422.58 | bwd_microstep: 410.40 | bwd_inner_microstep: 410.38 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.28 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1889 +[2025-05-01 23:23:28,765] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 266.57 | bwd_microstep: 561.15 | bwd_inner_microstep: 561.14 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 342 +[2025-05-01 23:23:29,001] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 99.39 | bwd_microstep: 107.75 | bwd_inner_microstep: 107.61 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1362 +[2025-05-01 23:23:29,615] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 228.62 | bwd_microstep: 368.95 | bwd_inner_microstep: 368.80 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.09 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 329 +[2025-05-01 23:23:29,839] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 72.50 | bwd_microstep: 135.66 | bwd_inner_microstep: 135.65 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-01 23:23:30,690] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 422.15 | bwd_microstep: 394.21 | bwd_inner_microstep: 394.19 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 23:23:31,565] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 421.68 | bwd_microstep: 416.80 | bwd_inner_microstep: 416.78 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 840 +[2025-05-01 23:23:32,039] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 198.91 | bwd_microstep: 245.15 | bwd_inner_microstep: 244.87 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:23:32,825] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 308.33 | bwd_microstep: 461.12 | bwd_inner_microstep: 461.10 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 839 +[2025-05-01 23:23:33,328] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 203.33 | bwd_microstep: 279.70 | bwd_inner_microstep: 279.68 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 23:23:34,185] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 231.51 | bwd_microstep: 589.12 | bwd_inner_microstep: 589.10 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.42 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 23:23:35,066] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 232.97 | bwd_microstep: 614.60 | bwd_inner_microstep: 614.58 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.20 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1344 +[2025-05-01 23:23:35,666] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 146.59 | bwd_microstep: 432.53 | bwd_inner_microstep: 432.52 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 23:23:36,522] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 321.82 | bwd_microstep: 498.80 | bwd_inner_microstep: 498.79 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1850 +[2025-05-01 23:23:37,587] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.20 | optimizer_step: 16.10 +[2025-05-01 23:23:37,588] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 325.97 | bwd_microstep: 684.06 | bwd_inner_microstep: 498.18 | bwd_allreduce_microstep: 185.83 | step_microstep: 24.21 +[2025-05-01 23:23:37,589] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 3990.51 | bwd: 6352.25 | bwd_inner: 6165.60 | bwd_allreduce: 186.18 | step: 48.21 + 5%|▌ | 455/8720 [1:08:11<27:43:41, 12.08s/it] {'loss': 0.8841, 'grad_norm': 4.863905906677246, 'learning_rate': 9.987157989646672e-06, 'epoch': 0.52} + 5%|▌ | 455/8720 [1:08:11<27:43:41, 12.08s/it]dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 941 +[2025-05-01 23:23:38,160] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 213.81 | bwd_microstep: 333.71 | bwd_inner_microstep: 333.69 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 900 +[2025-05-01 23:23:38,557] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 163.54 | bwd_microstep: 203.35 | bwd_inner_microstep: 203.33 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1920 +[2025-05-01 23:23:39,441] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 419.88 | bwd_microstep: 434.12 | bwd_inner_microstep: 434.10 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1890 +[2025-05-01 23:23:40,302] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 382.29 | bwd_microstep: 450.45 | bwd_inner_microstep: 450.42 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-01 23:23:41,189] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 380.21 | bwd_microstep: 471.77 | bwd_inner_microstep: 471.75 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-01 23:23:42,051] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 254.73 | bwd_microstep: 575.90 | bwd_inner_microstep: 575.88 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-01 23:23:42,866] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 240.21 | bwd_microstep: 557.54 | bwd_inner_microstep: 557.52 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 330 +[2025-05-01 23:23:43,090] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 79.54 | bwd_microstep: 126.30 | bwd_inner_microstep: 126.28 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 23:23:43,945] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 423.62 | bwd_microstep: 399.44 | bwd_inner_microstep: 399.42 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-01 23:23:44,834] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 423.01 | bwd_microstep: 431.83 | bwd_inner_microstep: 431.81 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 23:23:45,696] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 417.85 | bwd_microstep: 409.81 | bwd_inner_microstep: 409.79 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 23:23:46,570] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 421.97 | bwd_microstep: 419.27 | bwd_inner_microstep: 419.25 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:23:47,441] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 409.24 | bwd_microstep: 431.41 | bwd_inner_microstep: 431.40 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 23:23:48,316] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 403.80 | bwd_microstep: 443.17 | bwd_inner_microstep: 443.15 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.32 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 23:23:49,194] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 336.04 | bwd_microstep: 509.28 | bwd_inner_microstep: 509.27 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.31 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1914 +[2025-05-01 23:23:50,325] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.15 | optimizer_step: 16.45 +[2025-05-01 23:23:50,326] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 269.07 | bwd_microstep: 808.36 | bwd_inner_microstep: 585.41 | bwd_allreduce_microstep: 222.90 | step_microstep: 24.41 +[2025-05-01 23:23:50,327] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 5238.74 | bwd: 7005.71 | bwd_inner: 6782.47 | bwd_allreduce: 222.99 | step: 50.65 + 5%|▌ | 456/8720 [1:08:24<28:10:44, 12.28s/it] {'loss': 1.1227, 'grad_norm': 3.978020429611206, 'learning_rate': 9.987024624794723e-06, 'epoch': 0.52} + 5%|▌ | 456/8720 [1:08:24<28:10:44, 12.28s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 433 +[2025-05-01 23:23:50,617] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 109.83 | bwd_microstep: 158.73 | bwd_inner_microstep: 158.71 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1917 +[2025-05-01 23:23:51,490] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 302.94 | bwd_microstep: 537.46 | bwd_inner_microstep: 537.44 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1899 +[2025-05-01 23:23:52,332] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 229.79 | bwd_microstep: 584.18 | bwd_inner_microstep: 584.17 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 870 +[2025-05-01 23:23:52,732] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 99.48 | bwd_microstep: 286.14 | bwd_inner_microstep: 286.12 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1366 +[2025-05-01 23:23:53,369] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 328.72 | bwd_microstep: 280.68 | bwd_inner_microstep: 280.66 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-01 23:23:54,233] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 427.94 | bwd_microstep: 403.95 | bwd_inner_microstep: 403.93 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 23:23:55,093] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 425.27 | bwd_microstep: 401.75 | bwd_inner_microstep: 401.73 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.48 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 325 +[2025-05-01 23:23:55,361] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 99.82 | bwd_microstep: 138.60 | bwd_inner_microstep: 138.59 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 324 +[2025-05-01 23:23:55,590] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 86.47 | bwd_microstep: 114.75 | bwd_inner_microstep: 114.59 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-01 23:23:56,469] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 381.15 | bwd_microstep: 481.58 | bwd_inner_microstep: 481.56 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:23:57,348] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 348.57 | bwd_microstep: 514.65 | bwd_inner_microstep: 514.63 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 23:23:58,180] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 338.25 | bwd_microstep: 476.61 | bwd_inner_microstep: 476.59 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 319 +[2025-05-01 23:23:58,406] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 76.97 | bwd_microstep: 133.21 | bwd_inner_microstep: 133.19 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 23:23:59,275] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 422.11 | bwd_microstep: 415.39 | bwd_inner_microstep: 415.37 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 23:24:00,148] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 397.99 | bwd_microstep: 448.63 | bwd_inner_microstep: 448.61 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 23:24:01,281] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 3.68 | optimizer_step: 19.78 +[2025-05-01 23:24:01,281] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 336.62 | bwd_microstep: 740.25 | bwd_inner_microstep: 495.81 | bwd_allreduce_microstep: 244.36 | step_microstep: 28.88 +[2025-05-01 23:24:01,282] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4411.82 | bwd: 6116.58 | bwd_inner: 5871.74 | bwd_allreduce: 244.51 | step: 50.59 + 5%|▌ | 457/8720 [1:08:35<27:16:08, 11.88s/it] {'loss': 1.1936, 'grad_norm': 2.809380292892456, 'learning_rate': 9.986890571915125e-06, 'epoch': 0.52} + 5%|▌ | 457/8720 [1:08:35<27:16:08, 11.88s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1927 +[2025-05-01 23:24:02,219] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 437.24 | bwd_microstep: 457.53 | bwd_inner_microstep: 457.51 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 368 +[2025-05-01 23:24:02,507] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 109.23 | bwd_microstep: 152.74 | bwd_inner_microstep: 152.73 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1902 +[2025-05-01 23:24:03,280] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 216.38 | bwd_microstep: 527.24 | bwd_inner_microstep: 527.22 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 853 +[2025-05-01 23:24:03,670] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 98.26 | bwd_microstep: 274.14 | bwd_inner_microstep: 274.12 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 342 +[2025-05-01 23:24:03,945] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 100.43 | bwd_microstep: 144.40 | bwd_inner_microstep: 144.38 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 859 +[2025-05-01 23:24:04,266] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 136.04 | bwd_microstep: 154.84 | bwd_inner_microstep: 154.82 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-01 23:24:05,148] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 423.26 | bwd_microstep: 427.13 | bwd_inner_microstep: 427.12 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-01 23:24:06,020] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 425.39 | bwd_microstep: 414.81 | bwd_inner_microstep: 414.79 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 844 +[2025-05-01 23:24:06,542] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 210.68 | bwd_microstep: 282.73 | bwd_inner_microstep: 282.52 | bwd_allreduce_microstep: 0.10 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-01 23:24:07,418] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 287.88 | bwd_microstep: 572.15 | bwd_inner_microstep: 572.14 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-01 23:24:08,298] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 319.68 | bwd_microstep: 542.11 | bwd_inner_microstep: 542.10 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-01 23:24:09,175] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 342.24 | bwd_microstep: 516.48 | bwd_inner_microstep: 516.46 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.22 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-01 23:24:10,050] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 359.45 | bwd_microstep: 497.48 | bwd_inner_microstep: 497.46 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 23:24:10,922] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 390.94 | bwd_microstep: 464.25 | bwd_inner_microstep: 464.23 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 23:24:11,806] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 413.75 | bwd_microstep: 452.46 | bwd_inner_microstep: 452.44 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.50 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2033 +[2025-05-01 23:24:13,212] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.96 | optimizer_step: 15.96 +[2025-05-01 23:24:13,212] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 457.82 | bwd_microstep: 892.69 | bwd_inner_microstep: 510.26 | bwd_allreduce_microstep: 382.38 | step_microstep: 24.04 +[2025-05-01 23:24:13,213] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4728.53 | bwd: 6773.22 | bwd_inner: 6390.34 | bwd_allreduce: 382.54 | step: 41.42 + 5%|▌ | 458/8720 [1:08:46<27:17:50, 11.89s/it] {'loss': 1.3115, 'grad_norm': 3.5199944972991943, 'learning_rate': 9.986755831026368e-06, 'epoch': 0.53} + 5%|▌ | 458/8720 [1:08:46<27:17:50, 11.89s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1895 +[2025-05-01 23:24:14,142] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 427.04 | bwd_microstep: 461.25 | bwd_inner_microstep: 461.23 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-01 23:24:15,060] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 421.48 | bwd_microstep: 464.58 | bwd_inner_microstep: 464.56 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-01 23:24:15,981] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 425.39 | bwd_microstep: 464.46 | bwd_inner_microstep: 464.44 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.48 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-01 23:24:16,895] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 357.12 | bwd_microstep: 522.31 | bwd_inner_microstep: 522.29 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-01 23:24:17,809] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 302.47 | bwd_microstep: 578.53 | bwd_inner_microstep: 578.51 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1358 +[2025-05-01 23:24:18,450] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 197.60 | bwd_microstep: 413.27 | bwd_inner_microstep: 413.25 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.48 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-01 23:24:19,363] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 336.18 | bwd_microstep: 545.33 | bwd_inner_microstep: 545.31 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-01 23:24:20,267] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 278.69 | bwd_microstep: 592.85 | bwd_inner_microstep: 592.83 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.53 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-01 23:24:21,177] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 249.39 | bwd_microstep: 627.89 | bwd_inner_microstep: 627.87 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1351 +[2025-05-01 23:24:21,815] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 151.02 | bwd_microstep: 465.26 | bwd_inner_microstep: 465.24 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 322 +[2025-05-01 23:24:22,055] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 102.62 | bwd_microstep: 108.85 | bwd_inner_microstep: 108.72 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 23:24:22,929] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 324.22 | bwd_microstep: 534.08 | bwd_inner_microstep: 534.06 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.15 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 830 +[2025-05-01 23:24:23,373] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 130.83 | bwd_microstep: 295.68 | bwd_inner_microstep: 295.66 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 23:24:24,282] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 340.88 | bwd_microstep: 531.04 | bwd_inner_microstep: 531.02 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.51 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 23:24:25,193] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 286.41 | bwd_microstep: 589.00 | bwd_inner_microstep: 588.99 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 23:24:26,279] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.20 | optimizer_step: 16.44 +[2025-05-01 23:24:26,280] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 249.42 | bwd_microstep: 782.08 | bwd_inner_microstep: 618.62 | bwd_allreduce_microstep: 163.42 | step_microstep: 23.91 +[2025-05-01 23:24:26,282] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4580.71 | bwd: 7976.49 | bwd_inner: 7812.66 | bwd_allreduce: 163.55 | step: 55.27 + 5%|▌ | 459/8720 [1:09:00<28:06:15, 12.25s/it] {'loss': 1.3973, 'grad_norm': 5.411953926086426, 'learning_rate': 9.986620402147049e-06, 'epoch': 0.53} + 5%|▌ | 459/8720 [1:09:00<28:06:15, 12.25s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 428 +[2025-05-01 23:24:26,608] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 127.70 | bwd_microstep: 157.85 | bwd_inner_microstep: 157.83 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-01 23:24:27,520] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 327.95 | bwd_microstep: 552.34 | bwd_inner_microstep: 552.32 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.30 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-01 23:24:28,425] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 272.75 | bwd_microstep: 599.97 | bwd_inner_microstep: 599.95 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.28 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-01 23:24:29,330] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 252.94 | bwd_microstep: 620.83 | bwd_inner_microstep: 620.81 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 23:24:30,219] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 257.14 | bwd_microstep: 609.43 | bwd_inner_microstep: 609.41 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.99 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 839 +[2025-05-01 23:24:30,593] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.07 | bwd_microstep: 259.46 | bwd_inner_microstep: 259.44 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.32 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:24:31,500] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 418.50 | bwd_microstep: 463.27 | bwd_inner_microstep: 463.25 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.49 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:24:32,407] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 359.98 | bwd_microstep: 514.44 | bwd_inner_microstep: 514.43 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 23:24:33,310] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 306.38 | bwd_microstep: 564.21 | bwd_inner_microstep: 564.20 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.48 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 834 +[2025-05-01 23:24:33,670] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 155.29 | bwd_microstep: 174.54 | bwd_inner_microstep: 174.52 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 23:24:34,578] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 422.96 | bwd_microstep: 453.25 | bwd_inner_microstep: 453.23 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-01 23:24:35,480] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 417.23 | bwd_microstep: 452.40 | bwd_inner_microstep: 452.39 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.85 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 23:24:36,384] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 399.46 | bwd_microstep: 475.91 | bwd_inner_microstep: 475.89 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.52 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 315 +[2025-05-01 23:24:36,642] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.95 | bwd_microstep: 131.77 | bwd_inner_microstep: 131.75 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.52 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-01 23:24:37,526] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 258.77 | bwd_microstep: 607.14 | bwd_inner_microstep: 607.13 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-01 23:24:38,556] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.25 | optimizer_step: 16.70 +[2025-05-01 23:24:38,557] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 275.68 | bwd_microstep: 712.13 | bwd_inner_microstep: 585.34 | bwd_allreduce_microstep: 126.78 | step_microstep: 26.06 +[2025-05-01 23:24:38,558] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4442.68 | bwd: 7348.94 | bwd_inner: 7221.90 | bwd_allreduce: 126.84 | step: 57.60 + 5%|▌ | 460/8720 [1:09:12<28:07:16, 12.26s/it] {'loss': 0.958, 'grad_norm': 4.362586975097656, 'learning_rate': 9.986484285295848e-06, 'epoch': 0.53} + 5%|▌ | 460/8720 [1:09:12<28:07:16, 12.26s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1946 +[2025-05-01 23:24:39,531] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 435.41 | bwd_microstep: 496.82 | bwd_inner_microstep: 496.80 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.32 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1935 +[2025-05-01 23:24:40,488] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 404.84 | bwd_microstep: 522.15 | bwd_inner_microstep: 522.13 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1914 +[2025-05-01 23:24:41,413] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 314.40 | bwd_microstep: 575.71 | bwd_inner_microstep: 575.69 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 889 +[2025-05-01 23:24:41,806] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 156.70 | bwd_microstep: 206.25 | bwd_inner_microstep: 206.23 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1897 +[2025-05-01 23:24:42,731] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 423.72 | bwd_microstep: 471.26 | bwd_inner_microstep: 471.25 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1888 +[2025-05-01 23:24:43,640] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 419.14 | bwd_microstep: 463.10 | bwd_inner_microstep: 463.08 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.50 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-01 23:24:44,550] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 360.77 | bwd_microstep: 518.05 | bwd_inner_microstep: 518.03 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.48 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-01 23:24:45,459] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 303.41 | bwd_microstep: 570.71 | bwd_inner_microstep: 570.69 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-01 23:24:46,365] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 247.03 | bwd_microstep: 624.26 | bwd_inner_microstep: 624.25 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:24:47,261] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 256.63 | bwd_microstep: 608.86 | bwd_inner_microstep: 608.84 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 23:24:48,137] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 267.46 | bwd_microstep: 588.09 | bwd_inner_microstep: 588.07 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 23:24:49,018] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 296.42 | bwd_microstep: 561.38 | bwd_inner_microstep: 561.36 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 23:24:49,903] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 334.24 | bwd_microstep: 524.51 | bwd_inner_microstep: 524.49 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.23 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 23:24:50,785] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 346.04 | bwd_microstep: 513.85 | bwd_inner_microstep: 513.83 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1911 +[2025-05-01 23:24:51,676] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 389.89 | bwd_microstep: 477.83 | bwd_inner_microstep: 477.81 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 23:24:53,061] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.54 | optimizer_step: 17.84 +[2025-05-01 23:24:53,062] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 421.03 | bwd_microstep: 919.66 | bwd_inner_microstep: 456.23 | bwd_allreduce_microstep: 463.38 | step_microstep: 26.14 +[2025-05-01 23:24:53,063] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 5376.98 | bwd: 8642.52 | bwd_inner: 8178.81 | bwd_allreduce: 463.47 | step: 49.27 + 5%|▌ | 461/8720 [1:09:26<29:39:46, 12.93s/it] {'loss': 1.2428, 'grad_norm': 3.108809471130371, 'learning_rate': 9.986347480491543e-06, 'epoch': 0.53} + 5%|▌ | 461/8720 [1:09:26<29:39:46, 12.93s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 360 +[2025-05-01 23:24:53,344] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 108.49 | bwd_microstep: 135.00 | bwd_inner_microstep: 134.98 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.33 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-01 23:24:54,263] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 371.73 | bwd_microstep: 514.99 | bwd_inner_microstep: 514.97 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.28 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-01 23:24:55,177] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 316.51 | bwd_microstep: 564.41 | bwd_inner_microstep: 564.39 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.43 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-01 23:24:56,084] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 257.92 | bwd_microstep: 616.53 | bwd_inner_microstep: 616.51 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:24:56,979] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 249.11 | bwd_microstep: 613.80 | bwd_inner_microstep: 613.78 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.79 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 23:24:57,864] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 257.85 | bwd_microstep: 609.42 | bwd_inner_microstep: 609.40 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 23:24:58,744] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 281.30 | bwd_microstep: 580.74 | bwd_inner_microstep: 580.70 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 23:24:59,627] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 310.05 | bwd_microstep: 554.35 | bwd_inner_microstep: 554.34 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:25:00,514] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 339.21 | bwd_microstep: 523.47 | bwd_inner_microstep: 523.45 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 23:25:01,398] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 364.23 | bwd_microstep: 496.61 | bwd_inner_microstep: 496.58 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.23 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:25:02,275] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 394.08 | bwd_microstep: 463.54 | bwd_inner_microstep: 463.52 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 23:25:03,167] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 420.61 | bwd_microstep: 452.36 | bwd_inner_microstep: 452.34 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 23:25:04,081] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 422.42 | bwd_microstep: 454.89 | bwd_inner_microstep: 454.87 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 23:25:04,981] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 416.85 | bwd_microstep: 448.26 | bwd_inner_microstep: 448.24 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-01 23:25:05,873] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 417.49 | bwd_microstep: 452.70 | bwd_inner_microstep: 452.68 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.28 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 23:25:07,082] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.17 | optimizer_gradients: 2.24 | optimizer_step: 16.17 +[2025-05-01 23:25:07,083] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 367.58 | bwd_microstep: 787.24 | bwd_inner_microstep: 502.15 | bwd_allreduce_microstep: 285.04 | step_microstep: 24.73 +[2025-05-01 23:25:07,084] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 5295.29 | bwd: 8268.44 | bwd_inner: 7982.93 | bwd_allreduce: 285.13 | step: 44.86 + 5%|▌ | 462/8720 [1:09:40<30:24:46, 13.26s/it] {'loss': 0.815, 'grad_norm': 3.4591827392578125, 'learning_rate': 9.986209987753012e-06, 'epoch': 0.53} + 5%|▌ | 462/8720 [1:09:40<30:24:46, 13.26s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1940 +[2025-05-01 23:25:08,069] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 451.07 | bwd_microstep: 491.82 | bwd_inner_microstep: 491.80 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1905 +[2025-05-01 23:25:08,983] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 425.84 | bwd_microstep: 454.30 | bwd_inner_microstep: 454.28 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-01 23:25:09,904] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 392.55 | bwd_microstep: 495.46 | bwd_inner_microstep: 495.45 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.44 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-01 23:25:10,823] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 334.26 | bwd_microstep: 553.04 | bwd_inner_microstep: 553.03 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 322 +[2025-05-01 23:25:11,055] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 99.95 | bwd_microstep: 104.41 | bwd_inner_microstep: 104.22 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 23:25:11,932] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 340.43 | bwd_microstep: 517.18 | bwd_inner_microstep: 517.17 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:25:12,811] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 366.47 | bwd_microstep: 492.70 | bwd_inner_microstep: 492.65 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:25:13,688] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 401.05 | bwd_microstep: 458.58 | bwd_inner_microstep: 458.56 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 834 +[2025-05-01 23:25:14,217] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 217.96 | bwd_microstep: 282.06 | bwd_inner_microstep: 282.04 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 23:25:15,123] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 250.92 | bwd_microstep: 622.49 | bwd_inner_microstep: 622.47 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-01 23:25:16,020] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 259.07 | bwd_microstep: 610.20 | bwd_inner_microstep: 610.18 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 23:25:16,898] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 269.34 | bwd_microstep: 591.05 | bwd_inner_microstep: 590.95 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.24 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 23:25:17,776] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 292.81 | bwd_microstep: 567.80 | bwd_inner_microstep: 567.78 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 316 +[2025-05-01 23:25:18,008] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 83.40 | bwd_microstep: 129.34 | bwd_inner_microstep: 129.32 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-01 23:25:18,912] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 417.10 | bwd_microstep: 450.11 | bwd_inner_microstep: 450.10 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 23:25:20,160] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.20 | optimizer_step: 15.89 +[2025-05-01 23:25:20,160] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 417.35 | bwd_microstep: 783.84 | bwd_inner_microstep: 460.00 | bwd_allreduce_microstep: 323.79 | step_microstep: 23.16 +[2025-05-01 23:25:20,161] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 5019.45 | bwd: 7604.47 | bwd_inner: 7280.11 | bwd_allreduce: 323.96 | step: 43.69 + 5%|▌ | 463/8720 [1:09:53<30:16:56, 13.20s/it] {'loss': 0.8291, 'grad_norm': 4.304379463195801, 'learning_rate': 9.98607180709922e-06, 'epoch': 0.53} + 5%|▌ | 463/8720 [1:09:53<30:16:56, 13.20s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 391 +[2025-05-01 23:25:20,471] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 119.20 | bwd_microstep: 153.22 | bwd_inner_microstep: 153.20 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-01 23:25:21,384] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 347.08 | bwd_microstep: 533.64 | bwd_inner_microstep: 533.62 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-01 23:25:22,300] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 291.26 | bwd_microstep: 591.93 | bwd_inner_microstep: 591.91 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-01 23:25:23,200] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 247.00 | bwd_microstep: 621.18 | bwd_inner_microstep: 621.17 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-01 23:25:24,089] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 256.30 | bwd_microstep: 608.99 | bwd_inner_microstep: 608.97 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.21 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 23:25:24,966] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 270.61 | bwd_microstep: 589.03 | bwd_inner_microstep: 589.01 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 23:25:25,842] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 293.48 | bwd_microstep: 564.25 | bwd_inner_microstep: 564.23 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 23:25:26,719] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 320.40 | bwd_microstep: 538.19 | bwd_inner_microstep: 538.18 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 23:25:27,596] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 343.46 | bwd_microstep: 515.63 | bwd_inner_microstep: 515.61 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 318 +[2025-05-01 23:25:27,840] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 89.40 | bwd_microstep: 134.12 | bwd_inner_microstep: 134.11 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.32 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 23:25:28,756] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 426.11 | bwd_microstep: 453.69 | bwd_inner_microstep: 453.67 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.42 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 23:25:29,667] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 365.80 | bwd_microstep: 511.50 | bwd_inner_microstep: 511.48 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 830 +[2025-05-01 23:25:30,042] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 210.74 | bwd_microstep: 135.80 | bwd_inner_microstep: 135.51 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.20 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 319 +[2025-05-01 23:25:30,291] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 98.46 | bwd_microstep: 134.89 | bwd_inner_microstep: 134.88 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.08 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1450 +[2025-05-01 23:25:30,979] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 337.95 | bwd_microstep: 322.79 | bwd_inner_microstep: 322.77 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1930 +[2025-05-01 23:25:32,293] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.18 | optimizer_step: 16.02 +[2025-05-01 23:25:32,293] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 436.14 | bwd_microstep: 825.15 | bwd_inner_microstep: 473.35 | bwd_allreduce_microstep: 351.74 | step_microstep: 23.21 +[2025-05-01 23:25:32,294] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4453.26 | bwd: 7234.05 | bwd_inner: 6881.72 | bwd_allreduce: 351.94 | step: 44.70 + 5%|▌ | 464/8720 [1:10:06<29:32:32, 12.88s/it] {'loss': 0.9, 'grad_norm': 4.375000476837158, 'learning_rate': 9.985932938549232e-06, 'epoch': 0.53} + 5%|▌ | 464/8720 [1:10:06<29:32:32, 12.88s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1994 +[2025-05-01 23:25:33,289] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 452.57 | bwd_microstep: 502.89 | bwd_inner_microstep: 502.87 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1957 +[2025-05-01 23:25:34,243] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 437.44 | bwd_microstep: 484.29 | bwd_inner_microstep: 484.27 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1933 +[2025-05-01 23:25:35,200] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 370.50 | bwd_microstep: 553.26 | bwd_inner_microstep: 553.24 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.51 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 371 +[2025-05-01 23:25:35,442] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 108.38 | bwd_microstep: 106.35 | bwd_inner_microstep: 106.21 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1890 +[2025-05-01 23:25:36,321] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 342.84 | bwd_microstep: 519.14 | bwd_inner_microstep: 519.12 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.22 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1889 +[2025-05-01 23:25:37,197] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 360.32 | bwd_microstep: 498.61 | bwd_inner_microstep: 498.59 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-01 23:25:38,070] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 391.47 | bwd_microstep: 465.77 | bwd_inner_microstep: 465.76 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-01 23:25:38,971] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 426.22 | bwd_microstep: 456.38 | bwd_inner_microstep: 456.37 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.49 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 23:25:39,887] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 424.67 | bwd_microstep: 459.17 | bwd_inner_microstep: 459.15 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 23:25:40,801] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 422.65 | bwd_microstep: 458.45 | bwd_inner_microstep: 458.43 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.32 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 23:25:41,708] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 399.09 | bwd_microstep: 478.03 | bwd_inner_microstep: 478.01 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.43 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 23:25:42,612] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 342.00 | bwd_microstep: 529.43 | bwd_inner_microstep: 529.41 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1341 +[2025-05-01 23:25:43,251] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 244.38 | bwd_microstep: 364.19 | bwd_inner_microstep: 364.17 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 23:25:44,158] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 389.09 | bwd_microstep: 485.86 | bwd_inner_microstep: 485.85 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 23:25:45,067] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 334.92 | bwd_microstep: 542.83 | bwd_inner_microstep: 542.81 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.33 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1911 +[2025-05-01 23:25:46,206] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.21 | optimizer_step: 17.69 +[2025-05-01 23:25:46,208] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 283.01 | bwd_microstep: 802.80 | bwd_inner_microstep: 601.16 | bwd_allreduce_microstep: 201.60 | step_microstep: 25.26 +[2025-05-01 23:25:46,209] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 5729.49 | bwd: 7707.48 | bwd_inner: 7505.46 | bwd_allreduce: 201.73 | step: 51.81 + 5%|▌ | 465/8720 [1:10:19<30:15:05, 13.19s/it] {'loss': 1.2852, 'grad_norm': 3.5306081771850586, 'learning_rate': 9.985793382122208e-06, 'epoch': 0.53} + 5%|▌ | 465/8720 [1:10:19<30:15:05, 13.19s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1931 +[2025-05-01 23:25:47,182] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 441.62 | bwd_microstep: 489.15 | bwd_inner_microstep: 489.13 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 346 +[2025-05-01 23:25:47,452] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 97.61 | bwd_microstep: 142.92 | bwd_inner_microstep: 142.90 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-01 23:25:48,352] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 268.97 | bwd_microstep: 598.19 | bwd_inner_microstep: 598.17 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-01 23:25:49,261] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 251.65 | bwd_microstep: 625.04 | bwd_inner_microstep: 625.02 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.53 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-01 23:25:50,143] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 258.02 | bwd_microstep: 605.63 | bwd_inner_microstep: 605.61 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.01 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 846 +[2025-05-01 23:25:50,532] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 97.69 | bwd_microstep: 274.09 | bwd_inner_microstep: 274.07 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-01 23:25:51,442] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 402.27 | bwd_microstep: 475.84 | bwd_inner_microstep: 475.82 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 23:25:52,350] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 348.57 | bwd_microstep: 527.26 | bwd_inner_microstep: 527.24 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 23:25:53,257] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 293.98 | bwd_microstep: 580.62 | bwd_inner_microstep: 580.60 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.28 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1343 +[2025-05-01 23:25:53,892] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.25 | bwd_microstep: 409.93 | bwd_inner_microstep: 409.91 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 23:25:54,797] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 340.81 | bwd_microstep: 531.60 | bwd_inner_microstep: 531.58 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 23:25:55,615] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 305.10 | bwd_microstep: 480.42 | bwd_inner_microstep: 480.40 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 23:25:56,495] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 361.34 | bwd_microstep: 488.93 | bwd_inner_microstep: 488.91 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 23:25:57,348] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 350.73 | bwd_microstep: 483.83 | bwd_inner_microstep: 483.81 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1850 +[2025-05-01 23:25:58,158] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 298.31 | bwd_microstep: 481.54 | bwd_inner_microstep: 481.52 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.23 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1849 +[2025-05-01 23:25:59,297] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.27 | optimizer_step: 16.68 +[2025-05-01 23:25:59,298] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 301.36 | bwd_microstep: 782.56 | bwd_inner_microstep: 486.24 | bwd_allreduce_microstep: 296.30 | step_microstep: 26.09 +[2025-05-01 23:25:59,299] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4613.23 | bwd: 7977.54 | bwd_inner: 7680.96 | bwd_allreduce: 296.37 | step: 55.63 + 5%|▌ | 466/8720 [1:10:33<30:10:39, 13.16s/it] {'loss': 0.7186, 'grad_norm': 3.829745054244995, 'learning_rate': 9.985653137837402e-06, 'epoch': 0.53} + 5%|▌ | 466/8720 [1:10:33<30:10:39, 13.16s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2113 +[2025-05-01 23:26:00,271] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 338.92 | bwd_microstep: 591.67 | bwd_inner_microstep: 591.65 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1893 +[2025-05-01 23:26:01,108] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 301.92 | bwd_microstep: 505.04 | bwd_inner_microstep: 505.02 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1883 +[2025-05-01 23:26:01,982] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 347.97 | bwd_microstep: 494.53 | bwd_inner_microstep: 494.51 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 339 +[2025-05-01 23:26:02,211] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 86.14 | bwd_microstep: 126.65 | bwd_inner_microstep: 126.63 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.50 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-01 23:26:03,035] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 312.55 | bwd_microstep: 480.13 | bwd_inner_microstep: 480.11 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-01 23:26:03,888] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 329.80 | bwd_microstep: 491.02 | bwd_inner_microstep: 491.00 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1095 +[2025-05-01 23:26:04,392] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 209.41 | bwd_microstep: 279.39 | bwd_inner_microstep: 279.38 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-01 23:26:05,286] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 390.52 | bwd_microstep: 485.05 | bwd_inner_microstep: 485.04 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.53 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:26:06,090] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 291.77 | bwd_microstep: 492.58 | bwd_inner_microstep: 492.56 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 23:26:06,915] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 295.12 | bwd_microstep: 498.50 | bwd_inner_microstep: 498.49 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.49 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 23:26:07,767] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 330.28 | bwd_microstep: 489.99 | bwd_inner_microstep: 489.98 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 330 +[2025-05-01 23:26:07,990] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 80.60 | bwd_microstep: 125.88 | bwd_inner_microstep: 125.86 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 317 +[2025-05-01 23:26:08,225] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.36 | bwd_microstep: 111.14 | bwd_inner_microstep: 111.01 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 23:26:09,126] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 392.08 | bwd_microstep: 491.33 | bwd_inner_microstep: 491.31 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.14 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-01 23:26:09,920] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 287.30 | bwd_microstep: 486.22 | bwd_inner_microstep: 486.21 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1360 +[2025-05-01 23:26:10,722] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.86 | optimizer_step: 18.19 +[2025-05-01 23:26:10,724] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 224.64 | bwd_microstep: 521.41 | bwd_inner_microstep: 420.21 | bwd_allreduce_microstep: 101.08 | step_microstep: 28.43 +[2025-05-01 23:26:10,725] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4313.29 | bwd: 6670.55 | bwd_inner: 6569.06 | bwd_allreduce: 101.16 | step: 50.59 + 5%|▌ | 467/8720 [1:10:44<28:58:47, 12.64s/it] {'loss': 1.1617, 'grad_norm': 6.240654468536377, 'learning_rate': 9.985512205714161e-06, 'epoch': 0.54} + 5%|▌ | 467/8720 [1:10:44<28:58:47, 12.64s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1981 +[2025-05-01 23:26:11,631] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 340.45 | bwd_microstep: 532.76 | bwd_inner_microstep: 532.74 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1922 +[2025-05-01 23:26:12,503] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 338.12 | bwd_microstep: 504.86 | bwd_inner_microstep: 504.84 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-01 23:26:13,414] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 398.65 | bwd_microstep: 496.48 | bwd_inner_microstep: 496.46 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.91 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-01 23:26:14,231] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 310.22 | bwd_microstep: 487.65 | bwd_inner_microstep: 487.63 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-01 23:26:15,041] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 292.30 | bwd_microstep: 483.16 | bwd_inner_microstep: 483.14 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-01 23:26:15,892] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 331.38 | bwd_microstep: 490.34 | bwd_inner_microstep: 490.32 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:26:16,786] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 373.39 | bwd_microstep: 501.89 | bwd_inner_microstep: 501.87 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.33 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 325 +[2025-05-01 23:26:17,010] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 76.60 | bwd_microstep: 128.56 | bwd_inner_microstep: 128.54 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1351 +[2025-05-01 23:26:17,694] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 260.73 | bwd_microstep: 396.70 | bwd_inner_microstep: 396.68 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.33 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:26:18,510] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 292.36 | bwd_microstep: 501.72 | bwd_inner_microstep: 501.70 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.28 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 322 +[2025-05-01 23:26:18,748] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 97.84 | bwd_microstep: 110.03 | bwd_inner_microstep: 109.70 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 23:26:19,650] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 394.23 | bwd_microstep: 489.60 | bwd_inner_microstep: 489.58 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 23:26:20,498] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 349.94 | bwd_microstep: 478.73 | bwd_inner_microstep: 478.71 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 316 +[2025-05-01 23:26:20,740] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 79.42 | bwd_microstep: 132.43 | bwd_inner_microstep: 132.41 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.32 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 23:26:21,580] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 318.72 | bwd_microstep: 490.97 | bwd_inner_microstep: 490.95 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2136 +[2025-05-01 23:26:22,845] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.30 | optimizer_step: 26.39 +[2025-05-01 23:26:22,845] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 417.29 | bwd_microstep: 797.42 | bwd_inner_microstep: 529.25 | bwd_allreduce_microstep: 268.12 | step_microstep: 33.97 +[2025-05-01 23:26:22,846] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4671.55 | bwd: 7023.32 | bwd_inner: 6754.60 | bwd_allreduce: 268.33 | step: 56.25 + 5%|▌ | 468/8720 [1:10:56<28:36:59, 12.48s/it] {'loss': 0.9341, 'grad_norm': 3.0024025440216064, 'learning_rate': 9.98537058577193e-06, 'epoch': 0.54} + 5%|▌ | 468/8720 [1:10:56<28:36:59, 12.48s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 388 +[2025-05-01 23:26:23,110] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 91.61 | bwd_microstep: 151.82 | bwd_inner_microstep: 151.80 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.33 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 870 +[2025-05-01 23:26:23,528] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 149.31 | bwd_microstep: 238.48 | bwd_inner_microstep: 238.46 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.33 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-01 23:26:24,335] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 288.10 | bwd_microstep: 486.99 | bwd_inner_microstep: 486.97 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1927 +[2025-05-01 23:26:25,219] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 347.89 | bwd_microstep: 504.36 | bwd_inner_microstep: 504.35 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-01 23:26:26,120] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 394.74 | bwd_microstep: 489.13 | bwd_inner_microstep: 489.11 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.74 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-01 23:26:26,923] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 296.61 | bwd_microstep: 487.85 | bwd_inner_microstep: 487.83 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-01 23:26:27,754] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 313.46 | bwd_microstep: 482.76 | bwd_inner_microstep: 482.74 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-01 23:26:28,605] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 328.99 | bwd_microstep: 492.66 | bwd_inner_microstep: 492.65 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-01 23:26:29,487] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 379.24 | bwd_microstep: 484.53 | bwd_inner_microstep: 484.52 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-01 23:26:30,304] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 307.78 | bwd_microstep: 484.29 | bwd_inner_microstep: 484.27 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:26:31,125] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 286.55 | bwd_microstep: 500.99 | bwd_inner_microstep: 500.97 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 836 +[2025-05-01 23:26:31,539] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 196.38 | bwd_microstep: 185.45 | bwd_inner_microstep: 185.44 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.28 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 23:26:32,349] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 307.05 | bwd_microstep: 479.60 | bwd_inner_microstep: 479.58 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 23:26:33,194] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 325.52 | bwd_microstep: 490.47 | bwd_inner_microstep: 490.45 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 342 +[2025-05-01 23:26:33,430] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.99 | bwd_microstep: 124.41 | bwd_inner_microstep: 124.39 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.33 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 832 +[2025-05-01 23:26:34,065] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.18 | optimizer_step: 17.91 +[2025-05-01 23:26:34,067] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 152.42 | bwd_microstep: 431.86 | bwd_inner_microstep: 226.55 | bwd_allreduce_microstep: 205.26 | step_microstep: 25.54 +[2025-05-01 23:26:34,068] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4260.57 | bwd: 6515.66 | bwd_inner: 6310.09 | bwd_allreduce: 205.34 | step: 52.10 + 5%|▌ | 469/8720 [1:11:07<27:44:49, 12.11s/it] {'loss': 1.4613, 'grad_norm': 4.35919713973999, 'learning_rate': 9.985228278030244e-06, 'epoch': 0.54} + 5%|▌ | 469/8720 [1:11:07<27:44:49, 12.11s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 437 +[2025-05-01 23:26:34,383] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 119.11 | bwd_microstep: 158.36 | bwd_inner_microstep: 158.20 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1895 +[2025-05-01 23:26:35,233] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 335.53 | bwd_microstep: 495.25 | bwd_inner_microstep: 495.23 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.48 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1889 +[2025-05-01 23:26:36,052] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 299.73 | bwd_microstep: 489.64 | bwd_inner_microstep: 489.62 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.82 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-01 23:26:36,865] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 296.96 | bwd_microstep: 488.90 | bwd_inner_microstep: 488.88 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1883 +[2025-05-01 23:26:37,766] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 378.54 | bwd_microstep: 496.69 | bwd_inner_microstep: 496.67 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 853 +[2025-05-01 23:26:38,207] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 146.76 | bwd_microstep: 279.86 | bwd_inner_microstep: 279.85 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.60 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1354 +[2025-05-01 23:26:38,788] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 197.54 | bwd_microstep: 366.78 | bwd_inner_microstep: 366.77 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-01 23:26:39,684] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 374.41 | bwd_microstep: 504.83 | bwd_inner_microstep: 504.81 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 23:26:40,501] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 289.64 | bwd_microstep: 511.25 | bwd_inner_microstep: 511.23 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-01 23:26:41,320] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 330.87 | bwd_microstep: 470.06 | bwd_inner_microstep: 470.04 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:26:42,192] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 368.25 | bwd_microstep: 486.04 | bwd_inner_microstep: 486.02 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 23:26:43,019] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 305.70 | bwd_microstep: 489.37 | bwd_inner_microstep: 489.35 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.31 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 23:26:43,842] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 294.60 | bwd_microstep: 488.27 | bwd_inner_microstep: 488.25 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.51 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 318 +[2025-05-01 23:26:44,088] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 88.73 | bwd_microstep: 129.42 | bwd_inner_microstep: 129.19 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.38 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 319 +[2025-05-01 23:26:44,297] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 67.23 | bwd_microstep: 125.26 | bwd_inner_microstep: 125.24 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 867 +[2025-05-01 23:26:44,997] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 3.68 | optimizer_step: 16.71 +[2025-05-01 23:26:44,998] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 218.12 | bwd_microstep: 432.46 | bwd_inner_microstep: 187.29 | bwd_allreduce_microstep: 245.12 | step_microstep: 25.73 +[2025-05-01 23:26:44,999] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4111.63 | bwd: 6412.46 | bwd_inner: 6166.68 | bwd_allreduce: 245.48 | step: 40.89 + 5%|▌ | 470/8720 [1:11:18<26:56:07, 11.75s/it] {'loss': 1.4586, 'grad_norm': 3.687530279159546, 'learning_rate': 9.985085282508742e-06, 'epoch': 0.54} + 5%|▌ | 470/8720 [1:11:18<26:56:07, 11.75s/it]dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1130 +[2025-05-01 23:26:45,544] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 252.86 | bwd_microstep: 252.43 | bwd_inner_microstep: 252.41 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.32 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1896 +[2025-05-01 23:26:46,378] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 315.43 | bwd_microstep: 494.84 | bwd_inner_microstep: 494.77 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-01 23:26:47,287] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 402.68 | bwd_microstep: 487.71 | bwd_inner_microstep: 487.69 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.92 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 338 +[2025-05-01 23:26:47,503] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 69.65 | bwd_microstep: 131.07 | bwd_inner_microstep: 131.05 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.48 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 847 +[2025-05-01 23:26:47,923] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 197.78 | bwd_microstep: 196.00 | bwd_inner_microstep: 195.98 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 23:26:48,769] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 306.27 | bwd_microstep: 505.39 | bwd_inner_microstep: 505.37 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-01 23:26:49,581] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 294.84 | bwd_microstep: 488.83 | bwd_inner_microstep: 488.82 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 23:26:50,473] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 364.65 | bwd_microstep: 492.73 | bwd_inner_microstep: 492.71 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 23:26:51,328] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 347.90 | bwd_microstep: 487.87 | bwd_inner_microstep: 487.85 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 23:26:52,168] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 301.16 | bwd_microstep: 509.17 | bwd_inner_microstep: 509.16 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 23:26:52,982] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 292.84 | bwd_microstep: 502.04 | bwd_inner_microstep: 502.02 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 23:26:53,801] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 309.68 | bwd_microstep: 477.36 | bwd_inner_microstep: 477.34 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.28 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 23:26:54,665] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 319.78 | bwd_microstep: 508.84 | bwd_inner_microstep: 508.82 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 316 +[2025-05-01 23:26:54,889] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.53 | bwd_microstep: 106.72 | bwd_inner_microstep: 106.35 | bwd_allreduce_microstep: 0.25 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 23:26:55,765] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 365.19 | bwd_microstep: 479.10 | bwd_inner_microstep: 479.08 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1351 +[2025-05-01 23:26:56,553] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.26 | optimizer_step: 16.84 +[2025-05-01 23:26:56,554] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 214.36 | bwd_microstep: 525.12 | bwd_inner_microstep: 398.03 | bwd_allreduce_microstep: 126.95 | step_microstep: 25.05 +[2025-05-01 23:26:56,555] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4448.56 | bwd: 6645.21 | bwd_inner: 6517.58 | bwd_allreduce: 127.24 | step: 44.33 + 5%|▌ | 471/8720 [1:11:30<26:47:47, 11.69s/it] {'loss': 1.0457, 'grad_norm': 5.499013423919678, 'learning_rate': 9.984941599227147e-06, 'epoch': 0.54} + 5%|▌ | 471/8720 [1:11:30<26:47:47, 11.69s/it]dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 881 +[2025-05-01 23:26:56,906] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 156.36 | bwd_microstep: 154.15 | bwd_inner_microstep: 154.13 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1908 +[2025-05-01 23:26:57,770] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 423.37 | bwd_microstep: 408.96 | bwd_inner_microstep: 408.94 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-01 23:26:58,623] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 423.52 | bwd_microstep: 395.02 | bwd_inner_microstep: 395.00 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-01 23:26:59,484] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 427.28 | bwd_microstep: 402.00 | bwd_inner_microstep: 401.98 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.32 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-01 23:27:00,341] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 424.00 | bwd_microstep: 400.02 | bwd_inner_microstep: 400.00 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.49 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 23:27:01,189] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 424.05 | bwd_microstep: 392.14 | bwd_inner_microstep: 392.12 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 330 +[2025-05-01 23:27:01,447] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 103.36 | bwd_microstep: 124.00 | bwd_inner_microstep: 123.99 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-01 23:27:02,310] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 355.35 | bwd_microstep: 475.56 | bwd_inner_microstep: 475.54 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1094 +[2025-05-01 23:27:02,775] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 261.24 | bwd_microstep: 176.13 | bwd_inner_microstep: 176.05 | bwd_allreduce_microstep: 0.04 | step_microstep: 0.09 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1089 +[2025-05-01 23:27:03,408] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 251.12 | bwd_microstep: 365.16 | bwd_inner_microstep: 365.14 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.33 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 23:27:04,248] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 207.03 | bwd_microstep: 602.91 | bwd_inner_microstep: 602.90 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 23:27:05,080] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 214.44 | bwd_microstep: 585.19 | bwd_inner_microstep: 585.18 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.46 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 23:27:05,912] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 231.07 | bwd_microstep: 569.44 | bwd_inner_microstep: 569.42 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 23:27:06,751] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 246.81 | bwd_microstep: 557.65 | bwd_inner_microstep: 557.63 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.49 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2001 +[2025-05-01 23:27:07,695] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 271.90 | bwd_microstep: 638.93 | bwd_inner_microstep: 638.91 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1910 +[2025-05-01 23:27:08,762] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.21 | optimizer_step: 16.45 +[2025-05-01 23:27:08,763] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 234.47 | bwd_microstep: 780.83 | bwd_inner_microstep: 634.12 | bwd_allreduce_microstep: 146.65 | step_microstep: 23.86 +[2025-05-01 23:27:08,764] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4655.32 | bwd: 7028.11 | bwd_inner: 6881.08 | bwd_allreduce: 146.78 | step: 57.16 + 5%|▌ | 472/8720 [1:11:42<27:08:40, 11.85s/it] {'loss': 0.8541, 'grad_norm': 3.46059513092041, 'learning_rate': 9.984797228205284e-06, 'epoch': 0.54} + 5%|▌ | 472/8720 [1:11:42<27:08:40, 11.85s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2053 +[2025-05-01 23:27:09,682] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 408.26 | bwd_microstep: 490.59 | bwd_inner_microstep: 490.57 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 328 +[2025-05-01 23:27:09,935] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 97.27 | bwd_microstep: 138.96 | bwd_inner_microstep: 138.94 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-01 23:27:10,798] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 404.03 | bwd_microstep: 428.94 | bwd_inner_microstep: 428.92 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-01 23:27:11,653] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 399.88 | bwd_microstep: 428.24 | bwd_inner_microstep: 428.23 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1092 +[2025-05-01 23:27:12,164] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 265.05 | bwd_microstep: 221.97 | bwd_inner_microstep: 221.75 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 23:27:13,034] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 347.49 | bwd_microstep: 507.57 | bwd_inner_microstep: 507.55 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 23:27:13,909] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 330.27 | bwd_microstep: 529.05 | bwd_inner_microstep: 529.03 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 23:27:14,782] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 309.55 | bwd_microstep: 545.98 | bwd_inner_microstep: 545.96 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 23:27:15,655] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 280.41 | bwd_microstep: 575.55 | bwd_inner_microstep: 575.53 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 23:27:16,531] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 252.65 | bwd_microstep: 605.16 | bwd_inner_microstep: 605.14 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 23:27:17,387] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 219.74 | bwd_microstep: 616.28 | bwd_inner_microstep: 616.26 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.53 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 318 +[2025-05-01 23:27:17,626] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 84.46 | bwd_microstep: 131.86 | bwd_inner_microstep: 131.84 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.33 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 831 +[2025-05-01 23:27:18,170] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 206.27 | bwd_microstep: 302.48 | bwd_inner_microstep: 302.46 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-01 23:27:19,014] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 199.49 | bwd_microstep: 614.70 | bwd_inner_microstep: 614.68 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 23:27:19,848] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 202.96 | bwd_microstep: 598.69 | bwd_inner_microstep: 598.67 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 23:27:20,914] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.25 | optimizer_step: 16.18 +[2025-05-01 23:27:20,914] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 214.66 | bwd_microstep: 793.90 | bwd_inner_microstep: 588.52 | bwd_allreduce_microstep: 205.33 | step_microstep: 23.41 +[2025-05-01 23:27:20,915] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4222.31 | bwd: 7529.92 | bwd_inner: 7324.06 | bwd_allreduce: 205.53 | step: 39.68 + 5%|▌ | 473/8720 [1:11:54<27:21:03, 11.94s/it] {'loss': 1.0684, 'grad_norm': 5.599592685699463, 'learning_rate': 9.984652169463071e-06, 'epoch': 0.54} + 5%|▌ | 473/8720 [1:11:54<27:21:03, 11.94s/it]dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 993 +[2025-05-01 23:27:21,476] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 201.84 | bwd_microstep: 336.02 | bwd_inner_microstep: 336.00 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1910 +[2025-05-01 23:27:22,359] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 256.25 | bwd_microstep: 594.98 | bwd_inner_microstep: 594.96 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1914 +[2025-05-01 23:27:23,257] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 234.23 | bwd_microstep: 630.11 | bwd_inner_microstep: 630.09 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1886 +[2025-05-01 23:27:24,140] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 226.66 | bwd_microstep: 626.07 | bwd_inner_microstep: 626.05 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.53 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-01 23:27:24,985] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 200.28 | bwd_microstep: 620.67 | bwd_inner_microstep: 620.65 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-01 23:27:25,844] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 202.21 | bwd_microstep: 622.68 | bwd_inner_microstep: 622.67 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-01 23:27:26,701] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 200.58 | bwd_microstep: 623.55 | bwd_inner_microstep: 623.53 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-01 23:27:27,592] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 228.79 | bwd_microstep: 627.47 | bwd_inner_microstep: 627.45 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.15 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:27:28,462] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 229.57 | bwd_microstep: 621.21 | bwd_inner_microstep: 621.19 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.20 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 318 +[2025-05-01 23:27:28,707] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 96.28 | bwd_microstep: 126.58 | bwd_inner_microstep: 126.57 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 23:27:29,562] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 423.35 | bwd_microstep: 395.71 | bwd_inner_microstep: 395.69 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 23:27:30,415] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 422.35 | bwd_microstep: 396.09 | bwd_inner_microstep: 396.08 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 23:27:31,265] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 423.20 | bwd_microstep: 394.38 | bwd_inner_microstep: 394.36 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1991 +[2025-05-01 23:27:32,199] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 453.37 | bwd_microstep: 446.27 | bwd_inner_microstep: 446.25 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1967 +[2025-05-01 23:27:33,122] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 446.70 | bwd_microstep: 442.26 | bwd_inner_microstep: 442.24 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1901 +[2025-05-01 23:27:34,363] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.26 | optimizer_step: 16.34 +[2025-05-01 23:27:34,364] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 415.39 | bwd_microstep: 779.19 | bwd_inner_microstep: 429.47 | bwd_allreduce_microstep: 349.66 | step_microstep: 24.04 +[2025-05-01 23:27:34,366] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4661.03 | bwd: 8283.24 | bwd_inner: 7933.27 | bwd_allreduce: 349.75 | step: 57.09 + 5%|▌ | 474/8720 [1:12:08<28:23:12, 12.39s/it] {'loss': 1.0356, 'grad_norm': 3.1269497871398926, 'learning_rate': 9.984506423020523e-06, 'epoch': 0.54} + 5%|▌ | 474/8720 [1:12:08<28:23:12, 12.39s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1974 +[2025-05-01 23:27:35,270] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 412.55 | bwd_microstep: 469.17 | bwd_inner_microstep: 469.15 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1930 +[2025-05-01 23:27:36,161] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 417.90 | bwd_microstep: 458.22 | bwd_inner_microstep: 458.20 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 359 +[2025-05-01 23:27:36,433] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 104.72 | bwd_microstep: 152.77 | bwd_inner_microstep: 152.75 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.34 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 360 +[2025-05-01 23:27:36,716] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 105.56 | bwd_microstep: 150.66 | bwd_inner_microstep: 150.64 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1894 +[2025-05-01 23:27:37,566] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 208.33 | bwd_microstep: 608.09 | bwd_inner_microstep: 608.07 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1377 +[2025-05-01 23:27:38,158] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 170.14 | bwd_microstep: 389.17 | bwd_inner_microstep: 389.15 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.51 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1886 +[2025-05-01 23:27:39,022] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 364.55 | bwd_microstep: 465.30 | bwd_inner_microstep: 465.28 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-01 23:27:39,887] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 360.55 | bwd_microstep: 471.89 | bwd_inner_microstep: 471.87 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-01 23:27:40,743] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 352.65 | bwd_microstep: 469.53 | bwd_inner_microstep: 469.52 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 846 +[2025-05-01 23:27:41,164] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 222.23 | bwd_microstep: 168.25 | bwd_inner_microstep: 167.96 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 23:27:42,036] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 361.42 | bwd_microstep: 495.55 | bwd_inner_microstep: 495.54 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.22 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:27:42,913] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 366.80 | bwd_microstep: 493.25 | bwd_inner_microstep: 493.24 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 23:27:43,791] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 372.40 | bwd_microstep: 486.95 | bwd_inner_microstep: 486.90 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 23:27:44,675] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 342.53 | bwd_microstep: 512.73 | bwd_inner_microstep: 512.71 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 23:27:45,557] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 319.86 | bwd_microstep: 534.08 | bwd_inner_microstep: 534.07 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.21 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 23:27:46,585] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.33 | optimizer_step: 17.04 +[2025-05-01 23:27:46,587] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 289.02 | bwd_microstep: 695.50 | bwd_inner_microstep: 571.31 | bwd_allreduce_microstep: 124.14 | step_microstep: 27.71 +[2025-05-01 23:27:46,589] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4770.97 | bwd: 7021.15 | bwd_inner: 6896.44 | bwd_allreduce: 124.35 | step: 43.28 + 5%|▌ | 475/8720 [1:12:20<28:16:01, 12.34s/it] {'loss': 1.1387, 'grad_norm': 3.255617380142212, 'learning_rate': 9.984359988897742e-06, 'epoch': 0.54} + 5%|▌ | 475/8720 [1:12:20<28:16:01, 12.34s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1921 +[2025-05-01 23:27:47,522] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 441.51 | bwd_microstep: 449.69 | bwd_inner_microstep: 449.67 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1897 +[2025-05-01 23:27:48,407] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 422.48 | bwd_microstep: 428.81 | bwd_inner_microstep: 428.79 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-01 23:27:49,270] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 424.14 | bwd_microstep: 403.87 | bwd_inner_microstep: 403.86 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 337 +[2025-05-01 23:27:49,548] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 104.02 | bwd_microstep: 142.71 | bwd_inner_microstep: 142.69 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 346 +[2025-05-01 23:27:49,794] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 97.01 | bwd_microstep: 118.45 | bwd_inner_microstep: 118.14 | bwd_allreduce_microstep: 0.08 | step_microstep: 0.13 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1360 +[2025-05-01 23:27:50,546] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 289.49 | bwd_microstep: 445.27 | bwd_inner_microstep: 445.15 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-01 23:27:51,426] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 257.26 | bwd_microstep: 604.83 | bwd_inner_microstep: 604.81 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-01 23:27:52,289] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 229.27 | bwd_microstep: 616.25 | bwd_inner_microstep: 616.23 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 847 +[2025-05-01 23:27:52,616] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 115.06 | bwd_microstep: 192.47 | bwd_inner_microstep: 192.46 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.31 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 23:27:53,404] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 422.43 | bwd_microstep: 332.99 | bwd_inner_microstep: 332.98 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.14 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 23:27:54,263] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 435.01 | bwd_microstep: 381.97 | bwd_inner_microstep: 381.96 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 23:27:54,737] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.39 | bwd_microstep: 271.08 | bwd_inner_microstep: 271.07 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 23:27:55,439] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 191.42 | bwd_microstep: 493.16 | bwd_inner_microstep: 493.11 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 317 +[2025-05-01 23:27:55,695] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 99.47 | bwd_microstep: 126.71 | bwd_inner_microstep: 126.69 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.41 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-01 23:27:56,537] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 204.73 | bwd_microstep: 616.67 | bwd_inner_microstep: 616.65 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 23:27:57,586] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.24 | optimizer_step: 16.36 +[2025-05-01 23:27:57,586] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 198.83 | bwd_microstep: 797.10 | bwd_inner_microstep: 614.49 | bwd_allreduce_microstep: 182.56 | step_microstep: 23.72 +[2025-05-01 23:27:57,588] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4119.41 | bwd: 6422.10 | bwd_inner: 6238.84 | bwd_allreduce: 182.80 | step: 41.34 + 5%|▌ | 476/8720 [1:12:31<27:20:26, 11.94s/it] {'loss': 1.1121, 'grad_norm': 4.116827011108398, 'learning_rate': 9.984212867114938e-06, 'epoch': 0.55} + 5%|▌ | 476/8720 [1:12:31<27:20:26, 11.94s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1913 +[2025-05-01 23:27:58,472] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 395.28 | bwd_microstep: 465.82 | bwd_inner_microstep: 465.80 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-01 23:27:59,345] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 368.50 | bwd_microstep: 490.08 | bwd_inner_microstep: 490.06 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1359 +[2025-05-01 23:28:00,065] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 237.58 | bwd_microstep: 464.71 | bwd_inner_microstep: 464.69 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 337 +[2025-05-01 23:28:00,318] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 100.85 | bwd_microstep: 123.12 | bwd_inner_microstep: 123.10 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.33 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-01 23:28:01,173] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 424.63 | bwd_microstep: 394.44 | bwd_inner_microstep: 394.42 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-01 23:28:02,026] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 428.48 | bwd_microstep: 388.78 | bwd_inner_microstep: 388.76 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.32 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 23:28:02,880] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 422.45 | bwd_microstep: 394.88 | bwd_inner_microstep: 394.86 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.49 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 23:28:03,761] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 421.21 | bwd_microstep: 428.71 | bwd_inner_microstep: 428.69 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-01 23:28:04,561] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 300.80 | bwd_microstep: 468.33 | bwd_inner_microstep: 468.31 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 23:28:05,361] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 333.96 | bwd_microstep: 446.77 | bwd_inner_microstep: 446.75 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 23:28:06,257] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 322.60 | bwd_microstep: 541.17 | bwd_inner_microstep: 541.15 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 23:28:07,050] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 258.89 | bwd_microstep: 513.24 | bwd_inner_microstep: 513.22 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-01 23:28:07,925] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 328.29 | bwd_microstep: 528.43 | bwd_inner_microstep: 528.42 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 23:28:08,802] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 303.77 | bwd_microstep: 553.88 | bwd_inner_microstep: 553.87 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 351 +[2025-05-01 23:28:09,073] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 114.35 | bwd_microstep: 135.47 | bwd_inner_microstep: 135.46 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.48 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 23:28:10,374] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.25 | optimizer_step: 16.50 +[2025-05-01 23:28:10,375] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 421.72 | bwd_microstep: 820.23 | bwd_inner_microstep: 400.36 | bwd_allreduce_microstep: 419.81 | step_microstep: 25.27 +[2025-05-01 23:28:10,376] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 5183.20 | bwd: 7158.07 | bwd_inner: 6737.93 | bwd_allreduce: 419.89 | step: 46.95 + 5%|▌ | 477/8720 [1:12:44<27:55:16, 12.19s/it] {'loss': 0.9405, 'grad_norm': 3.9584288597106934, 'learning_rate': 9.9840650576924e-06, 'epoch': 0.55} + 5%|▌ | 477/8720 [1:12:44<27:55:16, 12.19s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1889 +[2025-05-01 23:28:11,258] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 397.21 | bwd_microstep: 461.07 | bwd_inner_microstep: 461.05 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-01 23:28:12,136] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 374.18 | bwd_microstep: 485.85 | bwd_inner_microstep: 485.83 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 334 +[2025-05-01 23:28:12,375] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 97.79 | bwd_microstep: 124.60 | bwd_inner_microstep: 124.58 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.33 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:28:13,097] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 244.64 | bwd_microstep: 444.43 | bwd_inner_microstep: 444.41 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-01 23:28:13,944] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 375.96 | bwd_microstep: 451.83 | bwd_inner_microstep: 451.81 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-01 23:28:14,804] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 372.71 | bwd_microstep: 455.01 | bwd_inner_microstep: 454.99 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.28 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-01 23:28:15,664] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 369.56 | bwd_microstep: 458.82 | bwd_inner_microstep: 458.80 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 23:28:16,514] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 362.48 | bwd_microstep: 455.05 | bwd_inner_microstep: 455.03 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 328 +[2025-05-01 23:28:16,786] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 101.85 | bwd_microstep: 138.68 | bwd_inner_microstep: 138.67 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:28:17,629] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 199.84 | bwd_microstep: 617.96 | bwd_inner_microstep: 617.94 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.33 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 23:28:18,475] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 205.27 | bwd_microstep: 606.50 | bwd_inner_microstep: 606.48 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 23:28:19,321] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 211.49 | bwd_microstep: 600.30 | bwd_inner_microstep: 600.28 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 23:28:20,161] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 221.62 | bwd_microstep: 586.76 | bwd_inner_microstep: 586.74 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.29 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 23:28:21,008] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 231.21 | bwd_microstep: 583.64 | bwd_inner_microstep: 583.62 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 23:28:21,834] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 238.05 | bwd_microstep: 555.07 | bwd_inner_microstep: 555.06 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 23:28:22,879] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.25 | optimizer_step: 16.14 +[2025-05-01 23:28:22,880] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 201.12 | bwd_microstep: 793.64 | bwd_inner_microstep: 612.28 | bwd_allreduce_microstep: 181.31 | step_microstep: 23.41 +[2025-05-01 23:28:22,882] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4204.91 | bwd: 7819.23 | bwd_inner: 7637.61 | bwd_allreduce: 181.39 | step: 51.56 + 5%|▌ | 478/8720 [1:12:56<28:07:50, 12.29s/it] {'loss': 1.4369, 'grad_norm': 5.4681830406188965, 'learning_rate': 9.983916560650528e-06, 'epoch': 0.55} + 5%|▌ | 478/8720 [1:12:56<28:07:50, 12.29s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2092 +[2025-05-01 23:28:23,806] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 424.75 | bwd_microstep: 477.63 | bwd_inner_microstep: 477.61 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1988 +[2025-05-01 23:28:24,727] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 446.22 | bwd_microstep: 445.40 | bwd_inner_microstep: 445.39 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.46 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1909 +[2025-05-01 23:28:25,598] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 426.44 | bwd_microstep: 412.05 | bwd_inner_microstep: 412.03 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.53 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1908 +[2025-05-01 23:28:26,466] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 432.70 | bwd_microstep: 403.00 | bwd_inner_microstep: 402.99 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.32 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1903 +[2025-05-01 23:28:27,323] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 427.59 | bwd_microstep: 397.69 | bwd_inner_microstep: 397.67 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1886 +[2025-05-01 23:28:28,178] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 425.40 | bwd_microstep: 397.85 | bwd_inner_microstep: 397.83 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-01 23:28:29,030] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 424.56 | bwd_microstep: 394.60 | bwd_inner_microstep: 394.59 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 334 +[2025-05-01 23:28:29,286] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 104.53 | bwd_microstep: 121.47 | bwd_inner_microstep: 121.45 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-01 23:28:30,135] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 338.08 | bwd_microstep: 479.76 | bwd_inner_microstep: 479.75 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 332 +[2025-05-01 23:28:30,399] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 100.16 | bwd_microstep: 133.37 | bwd_inner_microstep: 133.09 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.23 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 23:28:31,239] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 198.55 | bwd_microstep: 622.87 | bwd_inner_microstep: 622.85 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:28:32,090] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 202.60 | bwd_microstep: 616.77 | bwd_inner_microstep: 616.75 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 23:28:32,934] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 205.89 | bwd_microstep: 605.55 | bwd_inner_microstep: 605.53 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.54 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 23:28:33,784] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 211.92 | bwd_microstep: 604.01 | bwd_inner_microstep: 604.00 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.33 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 23:28:34,648] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 220.09 | bwd_microstep: 614.34 | bwd_inner_microstep: 614.32 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 314 +[2025-05-01 23:28:35,385] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.07 | optimizer_gradients: 2.30 | optimizer_step: 16.27 +[2025-05-01 23:28:35,386] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 75.84 | bwd_microstep: 609.56 | bwd_inner_microstep: 140.30 | bwd_allreduce_microstep: 469.22 | step_microstep: 24.68 +[2025-05-01 23:28:35,387] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4665.31 | bwd: 7335.94 | bwd_inner: 6866.14 | bwd_allreduce: 469.30 | step: 55.94 + 5%|▌ | 479/8720 [1:13:09<28:16:32, 12.35s/it] {'loss': 0.9319, 'grad_norm': 2.2405121326446533, 'learning_rate': 9.983767376009806e-06, 'epoch': 0.55} + 5%|▌ | 479/8720 [1:13:09<28:16:32, 12.35s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-01 23:28:36,262] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 400.87 | bwd_microstep: 454.56 | bwd_inner_microstep: 454.54 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-01 23:28:37,140] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 376.80 | bwd_microstep: 482.30 | bwd_inner_microstep: 482.28 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-01 23:28:38,015] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 349.57 | bwd_microstep: 510.67 | bwd_inner_microstep: 510.65 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1889 +[2025-05-01 23:28:38,892] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 334.18 | bwd_microstep: 526.41 | bwd_inner_microstep: 526.39 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.17 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-01 23:28:39,770] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 310.36 | bwd_microstep: 548.62 | bwd_inner_microstep: 548.60 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1371 +[2025-05-01 23:28:40,420] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 161.00 | bwd_microstep: 470.83 | bwd_inner_microstep: 470.81 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-01 23:28:41,263] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 256.59 | bwd_microstep: 549.57 | bwd_inner_microstep: 549.55 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.32 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1349 +[2025-05-01 23:28:41,868] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 225.31 | bwd_microstep: 349.83 | bwd_inner_microstep: 349.81 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.48 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 23:28:42,728] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 400.59 | bwd_microstep: 429.81 | bwd_inner_microstep: 429.79 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-01 23:28:43,585] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 390.68 | bwd_microstep: 432.24 | bwd_inner_microstep: 432.22 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 23:28:44,455] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 385.92 | bwd_microstep: 451.43 | bwd_inner_microstep: 451.41 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.28 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 23:28:45,330] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 367.06 | bwd_microstep: 475.72 | bwd_inner_microstep: 475.71 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.33 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 23:28:46,206] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 341.73 | bwd_microstep: 502.49 | bwd_inner_microstep: 502.47 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.46 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 23:28:47,060] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 312.86 | bwd_microstep: 506.87 | bwd_inner_microstep: 506.85 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 23:28:47,909] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 312.69 | bwd_microstep: 504.34 | bwd_inner_microstep: 504.33 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-01 23:28:49,067] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 4.35 | optimizer_step: 19.58 +[2025-05-01 23:28:49,067] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 312.63 | bwd_microstep: 785.97 | bwd_inner_microstep: 505.62 | bwd_allreduce_microstep: 280.30 | step_microstep: 29.48 +[2025-05-01 23:28:49,069] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 5238.73 | bwd: 7981.66 | bwd_inner: 7701.05 | bwd_allreduce: 280.38 | step: 51.31 + 6%|▌ | 480/8720 [1:13:22<29:11:07, 12.75s/it] {'loss': 0.7614, 'grad_norm': 3.5643997192382812, 'learning_rate': 9.983617503790816e-06, 'epoch': 0.55} + 6%|▌ | 480/8720 [1:13:22<29:11:07, 12.75s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-01 23:28:49,962] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 421.60 | bwd_microstep: 432.43 | bwd_inner_microstep: 432.41 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-01 23:28:50,859] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 315.57 | bwd_microstep: 546.25 | bwd_inner_microstep: 546.23 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-01 23:28:51,710] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 202.17 | bwd_microstep: 625.24 | bwd_inner_microstep: 625.22 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-01 23:28:52,557] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 199.21 | bwd_microstep: 617.11 | bwd_inner_microstep: 617.09 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.46 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 23:28:53,401] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 203.73 | bwd_microstep: 606.53 | bwd_inner_microstep: 606.51 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-01 23:28:54,246] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 214.46 | bwd_microstep: 595.96 | bwd_inner_microstep: 595.95 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 23:28:55,098] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 220.90 | bwd_microstep: 597.36 | bwd_inner_microstep: 597.34 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.54 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 23:28:55,950] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 220.96 | bwd_microstep: 596.15 | bwd_inner_microstep: 596.14 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.45 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 23:28:56,797] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 223.60 | bwd_microstep: 589.34 | bwd_inner_microstep: 589.32 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 23:28:57,639] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 233.92 | bwd_microstep: 576.34 | bwd_inner_microstep: 576.32 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 23:28:58,485] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 241.64 | bwd_microstep: 570.02 | bwd_inner_microstep: 569.98 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 23:28:59,325] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 246.10 | bwd_microstep: 559.88 | bwd_inner_microstep: 559.86 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.33 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 23:29:00,169] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 256.61 | bwd_microstep: 553.02 | bwd_inner_microstep: 553.01 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 23:29:01,009] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 262.61 | bwd_microstep: 542.87 | bwd_inner_microstep: 542.86 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.48 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1849 +[2025-05-01 23:29:01,854] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 274.40 | bwd_microstep: 536.74 | bwd_inner_microstep: 536.73 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.33 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1944 +[2025-05-01 23:29:03,007] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.07 | optimizer_gradients: 2.28 | optimizer_step: 16.62 +[2025-05-01 23:29:03,008] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 288.10 | bwd_microstep: 808.97 | bwd_inner_microstep: 586.44 | bwd_allreduce_microstep: 222.48 | step_microstep: 24.93 +[2025-05-01 23:29:03,009] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4025.58 | bwd: 9354.22 | bwd_inner: 9131.40 | bwd_allreduce: 222.56 | step: 60.61 + 6%|▌ | 481/8720 [1:13:36<29:59:57, 13.11s/it] {'loss': 1.0181, 'grad_norm': 5.62826681137085, 'learning_rate': 9.983466944014234e-06, 'epoch': 0.55} + 6%|▌ | 481/8720 [1:13:36<29:59:57, 13.11s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1883 +[2025-05-01 23:29:03,892] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 403.07 | bwd_microstep: 458.12 | bwd_inner_microstep: 458.10 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 350 +[2025-05-01 23:29:04,136] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 82.95 | bwd_microstep: 142.96 | bwd_inner_microstep: 142.94 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1364 +[2025-05-01 23:29:04,754] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 329.26 | bwd_microstep: 260.71 | bwd_inner_microstep: 260.55 | bwd_allreduce_microstep: 0.09 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-01 23:29:05,619] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 424.22 | bwd_microstep: 424.87 | bwd_inner_microstep: 424.86 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-01 23:29:06,494] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 412.49 | bwd_microstep: 446.38 | bwd_inner_microstep: 446.37 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-01 23:29:07,373] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 395.76 | bwd_microstep: 466.09 | bwd_inner_microstep: 466.07 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 23:29:08,247] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 372.05 | bwd_microstep: 484.72 | bwd_inner_microstep: 484.70 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-01 23:29:09,122] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 357.64 | bwd_microstep: 501.31 | bwd_inner_microstep: 501.29 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 23:29:09,996] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 340.75 | bwd_microstep: 517.46 | bwd_inner_microstep: 517.44 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:29:10,879] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 313.85 | bwd_microstep: 548.22 | bwd_inner_microstep: 548.20 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 835 +[2025-05-01 23:29:11,250] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 92.44 | bwd_microstep: 261.07 | bwd_inner_microstep: 261.05 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 23:29:12,134] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 403.17 | bwd_microstep: 446.32 | bwd_inner_microstep: 446.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.50 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 23:29:13,020] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 372.09 | bwd_microstep: 479.14 | bwd_inner_microstep: 479.12 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.52 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 828 +[2025-05-01 23:29:13,425] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 217.65 | bwd_microstep: 158.02 | bwd_inner_microstep: 157.72 | bwd_allreduce_microstep: 0.14 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 23:29:14,254] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 409.54 | bwd_microstep: 401.64 | bwd_inner_microstep: 401.62 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.32 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-01 23:29:15,563] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.32 | optimizer_step: 16.56 +[2025-05-01 23:29:15,563] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 418.26 | bwd_microstep: 832.64 | bwd_inner_microstep: 400.37 | bwd_allreduce_microstep: 432.21 | step_microstep: 24.10 +[2025-05-01 23:29:15,564] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 5345.02 | bwd: 6829.69 | bwd_inner: 6396.75 | bwd_allreduce: 432.50 | step: 36.85 + 6%|▌ | 482/8720 [1:13:49<29:36:58, 12.94s/it] {'loss': 1.0368, 'grad_norm': 5.138814449310303, 'learning_rate': 9.983315696700832e-06, 'epoch': 0.55} + 6%|▌ | 482/8720 [1:13:49<29:36:58, 12.94s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-01 23:29:16,446] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 386.80 | bwd_microstep: 472.50 | bwd_inner_microstep: 472.48 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.11 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1362 +[2025-05-01 23:29:17,199] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 291.46 | bwd_microstep: 446.11 | bwd_inner_microstep: 446.09 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-01 23:29:18,078] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 273.79 | bwd_microstep: 586.39 | bwd_inner_microstep: 586.37 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-01 23:29:18,955] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 270.56 | bwd_microstep: 588.80 | bwd_inner_microstep: 588.78 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1356 +[2025-05-01 23:29:19,569] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 142.62 | bwd_microstep: 450.43 | bwd_inner_microstep: 450.41 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1349 +[2025-05-01 23:29:20,172] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 248.16 | bwd_microstep: 320.49 | bwd_inner_microstep: 320.48 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-01 23:29:21,116] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 421.24 | bwd_microstep: 489.14 | bwd_inner_microstep: 489.12 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.06 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1089 +[2025-05-01 23:29:21,623] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 180.55 | bwd_microstep: 306.10 | bwd_inner_microstep: 306.03 | bwd_allreduce_microstep: 0.03 | step_microstep: 0.13 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-01 23:29:22,533] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 390.53 | bwd_microstep: 492.50 | bwd_inner_microstep: 492.48 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 23:29:23,435] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 371.12 | bwd_microstep: 507.23 | bwd_inner_microstep: 507.21 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.90 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 23:29:24,313] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 340.49 | bwd_microstep: 512.45 | bwd_inner_microstep: 512.43 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 23:29:25,173] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 321.90 | bwd_microstep: 514.64 | bwd_inner_microstep: 514.62 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 23:29:26,031] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 315.99 | bwd_microstep: 508.16 | bwd_inner_microstep: 508.14 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 23:29:26,893] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 311.21 | bwd_microstep: 516.88 | bwd_inner_microstep: 516.86 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 23:29:27,740] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 308.96 | bwd_microstep: 503.65 | bwd_inner_microstep: 503.63 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1908 +[2025-05-01 23:29:29,038] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.07 | optimizer_gradients: 2.20 | optimizer_step: 22.37 +[2025-05-01 23:29:29,038] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 334.68 | bwd_microstep: 902.10 | bwd_inner_microstep: 515.94 | bwd_allreduce_microstep: 386.15 | step_microstep: 31.39 +[2025-05-01 23:29:29,039] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4909.88 | bwd: 8117.59 | bwd_inner: 7731.09 | bwd_allreduce: 386.26 | step: 50.25 + 6%|▌ | 483/8720 [1:14:02<29:58:38, 13.10s/it] {'loss': 1.1829, 'grad_norm': 4.400724411010742, 'learning_rate': 9.983163761871479e-06, 'epoch': 0.55} + 6%|▌ | 483/8720 [1:14:02<29:58:38, 13.10s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1963 +[2025-05-01 23:29:29,950] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 394.58 | bwd_microstep: 493.09 | bwd_inner_microstep: 493.07 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.20 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 350 +[2025-05-01 23:29:30,209] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 102.19 | bwd_microstep: 129.09 | bwd_inner_microstep: 128.90 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-01 23:29:31,076] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 315.98 | bwd_microstep: 529.38 | bwd_inner_microstep: 529.36 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.42 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1366 +[2025-05-01 23:29:31,705] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 227.06 | bwd_microstep: 367.96 | bwd_inner_microstep: 367.94 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.29 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-01 23:29:32,580] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 351.50 | bwd_microstep: 486.93 | bwd_inner_microstep: 486.91 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.31 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-01 23:29:33,459] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 364.29 | bwd_microstep: 484.94 | bwd_inner_microstep: 484.93 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-01 23:29:34,352] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 385.03 | bwd_microstep: 486.91 | bwd_inner_microstep: 486.89 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-01 23:29:35,217] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 393.44 | bwd_microstep: 454.13 | bwd_inner_microstep: 454.12 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 23:29:36,083] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 323.90 | bwd_microstep: 509.70 | bwd_inner_microstep: 509.68 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.28 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 842 +[2025-05-01 23:29:36,526] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 162.73 | bwd_microstep: 250.80 | bwd_inner_microstep: 250.78 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.43 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1354 +[2025-05-01 23:29:37,168] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 241.37 | bwd_microstep: 369.72 | bwd_inner_microstep: 369.52 | bwd_allreduce_microstep: 0.18 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-01 23:29:38,043] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 334.01 | bwd_microstep: 513.58 | bwd_inner_microstep: 513.56 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.21 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 323 +[2025-05-01 23:29:38,277] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 99.86 | bwd_microstep: 107.15 | bwd_inner_microstep: 106.90 | bwd_allreduce_microstep: 0.10 | step_microstep: 0.09 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 832 +[2025-05-01 23:29:38,719] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 170.62 | bwd_microstep: 256.23 | bwd_inner_microstep: 256.09 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 23:29:39,619] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 378.02 | bwd_microstep: 503.03 | bwd_inner_microstep: 503.01 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.96 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1911 +[2025-05-01 23:29:40,831] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.17 | optimizer_step: 18.70 +[2025-05-01 23:29:40,831] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 350.13 | bwd_microstep: 817.31 | bwd_inner_microstep: 530.35 | bwd_allreduce_microstep: 286.95 | step_microstep: 26.36 +[2025-05-01 23:29:40,832] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4594.59 | bwd: 6760.00 | bwd_inner: 6472.11 | bwd_allreduce: 287.34 | step: 42.31 + 6%|▌ | 484/8720 [1:14:14<29:04:32, 12.71s/it] {'loss': 1.5206, 'grad_norm': 6.28127384185791, 'learning_rate': 9.983011139547134e-06, 'epoch': 0.56} + 6%|▌ | 484/8720 [1:14:14<29:04:32, 12.71s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 419 +[2025-05-01 23:29:41,098] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 86.75 | bwd_microstep: 157.60 | bwd_inner_microstep: 157.58 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1915 +[2025-05-01 23:29:41,976] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 327.86 | bwd_microstep: 518.92 | bwd_inner_microstep: 518.90 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1929 +[2025-05-01 23:29:42,837] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 314.43 | bwd_microstep: 514.50 | bwd_inner_microstep: 514.48 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.33 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-01 23:29:43,712] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 344.34 | bwd_microstep: 496.26 | bwd_inner_microstep: 496.25 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.33 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-01 23:29:44,604] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 352.90 | bwd_microstep: 507.56 | bwd_inner_microstep: 507.54 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-01 23:29:45,234] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 315.87 | bwd_microstep: 281.69 | bwd_inner_microstep: 281.67 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 326 +[2025-05-01 23:29:45,444] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 81.00 | bwd_microstep: 115.75 | bwd_inner_microstep: 115.56 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:29:45,937] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 192.77 | bwd_microstep: 285.60 | bwd_inner_microstep: 285.59 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-01 23:29:46,764] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 302.95 | bwd_microstep: 505.16 | bwd_inner_microstep: 505.14 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-01 23:29:47,655] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 329.25 | bwd_microstep: 529.62 | bwd_inner_microstep: 529.60 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.57 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-01 23:29:48,470] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 306.01 | bwd_microstep: 490.56 | bwd_inner_microstep: 490.52 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.28 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-01 23:29:49,344] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 355.98 | bwd_microstep: 485.83 | bwd_inner_microstep: 485.82 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.22 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-01 23:29:50,243] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 397.63 | bwd_microstep: 484.50 | bwd_inner_microstep: 484.48 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 321 +[2025-05-01 23:29:50,470] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 89.49 | bwd_microstep: 122.63 | bwd_inner_microstep: 122.61 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.32 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-01 23:29:51,341] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 326.43 | bwd_microstep: 514.25 | bwd_inner_microstep: 514.24 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 827 +[2025-05-01 23:29:52,099] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.30 | optimizer_step: 25.57 +[2025-05-01 23:29:52,099] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 152.23 | bwd_microstep: 558.25 | bwd_inner_microstep: 272.71 | bwd_allreduce_microstep: 285.50 | step_microstep: 33.10 +[2025-05-01 23:29:52,100] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4275.80 | bwd: 6568.71 | bwd_inner: 6282.78 | bwd_allreduce: 285.63 | step: 52.81 + 6%|▌ | 485/8720 [1:14:25<28:04:58, 12.28s/it] {'loss': 1.1876, 'grad_norm': 3.54793643951416, 'learning_rate': 9.982857829748855e-06, 'epoch': 0.56} + 6%|▌ | 485/8720 [1:14:25<28:04:58, 12.28s/it]dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1286 +[2025-05-01 23:29:52,757] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 259.26 | bwd_microstep: 377.45 | bwd_inner_microstep: 377.43 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.20 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 380 +[2025-05-01 23:29:52,987] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 74.44 | bwd_microstep: 140.43 | bwd_inner_microstep: 140.05 | bwd_allreduce_microstep: 0.18 | step_microstep: 0.18 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1372 +[2025-05-01 23:29:53,669] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 241.53 | bwd_microstep: 415.81 | bwd_inner_microstep: 415.79 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-01 23:29:54,571] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 371.97 | bwd_microstep: 512.01 | bwd_inner_microstep: 511.99 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.91 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-01 23:29:55,452] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 341.37 | bwd_microstep: 520.12 | bwd_inner_microstep: 520.11 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1101 +[2025-05-01 23:29:55,965] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 177.88 | bwd_microstep: 315.74 | bwd_inner_microstep: 315.53 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:29:56,868] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 379.30 | bwd_microstep: 505.53 | bwd_inner_microstep: 505.51 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-01 23:29:57,753] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 350.13 | bwd_microstep: 518.35 | bwd_inner_microstep: 518.33 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:29:58,617] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 327.37 | bwd_microstep: 517.23 | bwd_inner_microstep: 517.21 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.43 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-01 23:29:59,498] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 323.89 | bwd_microstep: 526.02 | bwd_inner_microstep: 526.00 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.50 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:30:00,351] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 301.25 | bwd_microstep: 518.48 | bwd_inner_microstep: 518.47 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 23:30:01,195] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 302.21 | bwd_microstep: 505.68 | bwd_inner_microstep: 505.66 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.28 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 23:30:02,060] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 331.16 | bwd_microstep: 499.64 | bwd_inner_microstep: 499.62 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 23:30:02,922] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 326.55 | bwd_microstep: 505.49 | bwd_inner_microstep: 505.48 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-01 23:30:03,794] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 330.73 | bwd_microstep: 513.55 | bwd_inner_microstep: 513.53 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.28 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 435 +[2025-05-01 23:30:04,431] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.25 | optimizer_step: 17.37 +[2025-05-01 23:30:04,432] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 117.34 | bwd_microstep: 468.97 | bwd_inner_microstep: 122.40 | bwd_allreduce_microstep: 346.48 | step_microstep: 27.08 +[2025-05-01 23:30:04,433] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4556.28 | bwd: 7360.52 | bwd_inner: 7013.37 | bwd_allreduce: 346.81 | step: 45.46 + 6%|▌ | 486/8720 [1:14:38<28:07:12, 12.29s/it] {'loss': 1.0178, 'grad_norm': 3.270024538040161, 'learning_rate': 9.982703832497792e-06, 'epoch': 0.56} + 6%|▌ | 486/8720 [1:14:38<28:07:12, 12.29s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1936 +[2025-05-01 23:30:05,360] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 339.13 | bwd_microstep: 545.89 | bwd_inner_microstep: 545.87 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.31 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1896 +[2025-05-01 23:30:06,223] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 318.72 | bwd_microstep: 512.11 | bwd_inner_microstep: 512.09 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.51 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-01 23:30:07,057] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 315.64 | bwd_microstep: 485.98 | bwd_inner_microstep: 485.94 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-01 23:30:07,958] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 396.47 | bwd_microstep: 487.41 | bwd_inner_microstep: 487.40 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1883 +[2025-05-01 23:30:08,860] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 372.49 | bwd_microstep: 509.16 | bwd_inner_microstep: 509.14 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.93 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-01 23:30:09,743] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 343.54 | bwd_microstep: 518.95 | bwd_inner_microstep: 518.93 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-01 23:30:10,603] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 319.35 | bwd_microstep: 516.60 | bwd_inner_microstep: 516.59 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.49 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-01 23:30:11,473] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 315.25 | bwd_microstep: 519.88 | bwd_inner_microstep: 519.86 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:30:12,320] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 316.94 | bwd_microstep: 497.71 | bwd_inner_microstep: 497.69 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 23:30:13,149] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 340.89 | bwd_microstep: 470.25 | bwd_inner_microstep: 470.23 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.32 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-01 23:30:14,033] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 329.51 | bwd_microstep: 519.57 | bwd_inner_microstep: 519.55 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 23:30:14,915] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 346.41 | bwd_microstep: 507.08 | bwd_inner_microstep: 507.06 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-01 23:30:15,787] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 325.63 | bwd_microstep: 525.19 | bwd_inner_microstep: 525.17 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-01 23:30:16,632] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 332.82 | bwd_microstep: 490.99 | bwd_inner_microstep: 490.98 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 23:30:17,486] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 325.13 | bwd_microstep: 507.02 | bwd_inner_microstep: 507.00 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.32 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 527 +[2025-05-01 23:30:18,093] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.29 | optimizer_step: 18.07 +[2025-05-01 23:30:18,095] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 121.39 | bwd_microstep: 431.76 | bwd_inner_microstep: 139.12 | bwd_allreduce_microstep: 292.60 | step_microstep: 26.46 +[2025-05-01 23:30:18,096] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 5159.21 | bwd: 8045.58 | bwd_inner: 7752.62 | bwd_allreduce: 292.69 | step: 47.18 + 6%|▌ | 487/8720 [1:14:51<29:03:21, 12.71s/it] {'loss': 1.5113, 'grad_norm': 3.490595579147339, 'learning_rate': 9.982549147815192e-06, 'epoch': 0.56} + 6%|▌ | 487/8720 [1:14:51<29:03:21, 12.71s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1896 +[2025-05-01 23:30:18,999] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 333.17 | bwd_microstep: 527.48 | bwd_inner_microstep: 527.46 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1890 +[2025-05-01 23:30:19,855] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 337.73 | bwd_microstep: 487.04 | bwd_inner_microstep: 487.02 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.31 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1890 +[2025-05-01 23:30:20,717] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 343.31 | bwd_microstep: 488.24 | bwd_inner_microstep: 488.22 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.51 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-01 23:30:21,576] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 340.33 | bwd_microstep: 490.57 | bwd_inner_microstep: 490.56 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.51 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1883 +[2025-05-01 23:30:22,444] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 332.50 | bwd_microstep: 503.01 | bwd_inner_microstep: 502.99 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.61 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-01 23:30:23,284] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 309.59 | bwd_microstep: 512.99 | bwd_inner_microstep: 512.97 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-01 23:30:24,158] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 320.02 | bwd_microstep: 528.13 | bwd_inner_microstep: 528.11 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.29 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-01 23:30:25,026] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 340.25 | bwd_microstep: 493.50 | bwd_inner_microstep: 493.49 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:30:25,889] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 335.53 | bwd_microstep: 498.22 | bwd_inner_microstep: 498.20 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.20 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 321 +[2025-05-01 23:30:26,120] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 89.65 | bwd_microstep: 124.22 | bwd_inner_microstep: 124.20 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 23:30:26,940] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 332.65 | bwd_microstep: 455.27 | bwd_inner_microstep: 455.26 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.32 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 23:30:27,772] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 330.36 | bwd_microstep: 470.29 | bwd_inner_microstep: 470.27 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 321 +[2025-05-01 23:30:28,016] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 97.44 | bwd_microstep: 130.44 | bwd_inner_microstep: 129.95 | bwd_allreduce_microstep: 0.47 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 23:30:28,835] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 326.95 | bwd_microstep: 472.29 | bwd_inner_microstep: 472.27 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 23:30:29,717] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 340.22 | bwd_microstep: 512.49 | bwd_inner_microstep: 512.47 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.43 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-01 23:30:30,961] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.27 | optimizer_step: 24.15 +[2025-05-01 23:30:30,961] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 335.89 | bwd_microstep: 848.40 | bwd_inner_microstep: 444.15 | bwd_allreduce_microstep: 404.20 | step_microstep: 33.62 +[2025-05-01 23:30:30,963] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4845.21 | bwd: 7542.60 | bwd_inner: 7137.61 | bwd_allreduce: 404.71 | step: 58.54 + 6%|▌ | 488/8720 [1:15:04<29:09:43, 12.75s/it] {'loss': 1.0901, 'grad_norm': 5.309833526611328, 'learning_rate': 9.982393775722392e-06, 'epoch': 0.56} + 6%|▌ | 488/8720 [1:15:04<29:09:43, 12.75s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1941 +[2025-05-01 23:30:31,852] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 324.75 | bwd_microstep: 523.03 | bwd_inner_microstep: 523.01 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1899 +[2025-05-01 23:30:32,687] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 305.24 | bwd_microstep: 497.85 | bwd_inner_microstep: 497.83 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1883 +[2025-05-01 23:30:33,553] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 331.21 | bwd_microstep: 504.71 | bwd_inner_microstep: 504.69 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.87 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-01 23:30:34,394] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 328.02 | bwd_microstep: 493.75 | bwd_inner_microstep: 493.74 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.28 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1883 +[2025-05-01 23:30:35,133] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 316.53 | bwd_microstep: 393.92 | bwd_inner_microstep: 393.90 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-01 23:30:35,916] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 240.84 | bwd_microstep: 524.61 | bwd_inner_microstep: 524.60 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.38 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-01 23:30:36,765] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 333.10 | bwd_microstep: 488.70 | bwd_inner_microstep: 488.68 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-01 23:30:37,616] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 340.96 | bwd_microstep: 477.90 | bwd_inner_microstep: 477.88 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 23:30:38,463] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 344.06 | bwd_microstep: 472.37 | bwd_inner_microstep: 472.35 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.32 +dynamic ViT batch size: 6, images per sample: 6.0, dynamic token length: 1607 +[2025-05-01 23:30:39,218] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 290.62 | bwd_microstep: 434.20 | bwd_inner_microstep: 434.19 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 23:30:40,096] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 349.55 | bwd_microstep: 504.26 | bwd_inner_microstep: 504.24 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.86 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 23:30:40,867] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 327.05 | bwd_microstep: 423.48 | bwd_inner_microstep: 423.46 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.49 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 23:30:41,708] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 310.73 | bwd_microstep: 495.89 | bwd_inner_microstep: 495.87 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.50 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 23:30:42,564] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 346.15 | bwd_microstep: 477.95 | bwd_inner_microstep: 477.93 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1918 +[2025-05-01 23:30:43,427] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 344.80 | bwd_microstep: 489.50 | bwd_inner_microstep: 489.48 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1103 +[2025-05-01 23:30:44,096] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.20 | optimizer_step: 17.73 +[2025-05-01 23:30:44,097] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 222.17 | bwd_microstep: 397.16 | bwd_inner_microstep: 269.02 | bwd_allreduce_microstep: 128.10 | step_microstep: 26.12 +[2025-05-01 23:30:44,098] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 5055.72 | bwd: 7599.31 | bwd_inner: 7470.89 | bwd_allreduce: 128.18 | step: 47.49 + 6%|▌ | 489/8720 [1:15:17<29:25:18, 12.87s/it] {'loss': 1.003, 'grad_norm': 3.336683511734009, 'learning_rate': 9.982237716240835e-06, 'epoch': 0.56} + 6%|▌ | 489/8720 [1:15:17<29:25:18, 12.87s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1912 +[2025-05-01 23:30:44,915] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 296.51 | bwd_microstep: 482.82 | bwd_inner_microstep: 482.80 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-01 23:30:45,773] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 317.07 | bwd_microstep: 509.06 | bwd_inner_microstep: 509.04 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-01 23:30:46,636] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 316.25 | bwd_microstep: 517.81 | bwd_inner_microstep: 517.79 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.28 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:30:47,423] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 307.19 | bwd_microstep: 446.18 | bwd_inner_microstep: 446.17 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 844 +[2025-05-01 23:30:47,897] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 207.38 | bwd_microstep: 234.11 | bwd_inner_microstep: 234.09 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 843 +[2025-05-01 23:30:48,298] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 150.82 | bwd_microstep: 230.17 | bwd_inner_microstep: 230.15 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-01 23:30:49,185] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 327.55 | bwd_microstep: 527.19 | bwd_inner_microstep: 527.17 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 23:30:50,037] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 328.99 | bwd_microstep: 499.10 | bwd_inner_microstep: 499.09 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-01 23:30:50,860] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 313.71 | bwd_microstep: 490.17 | bwd_inner_microstep: 490.15 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 837 +[2025-05-01 23:30:51,230] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 146.39 | bwd_microstep: 198.88 | bwd_inner_microstep: 198.86 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 23:30:52,123] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 343.62 | bwd_microstep: 517.21 | bwd_inner_microstep: 517.19 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.28 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 23:30:52,956] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 333.22 | bwd_microstep: 479.23 | bwd_inner_microstep: 479.21 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-01 23:30:53,871] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 401.54 | bwd_microstep: 489.37 | bwd_inner_microstep: 489.36 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.22 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 23:30:54,654] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 335.78 | bwd_microstep: 427.71 | bwd_inner_microstep: 427.64 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 23:30:55,523] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 343.92 | bwd_microstep: 505.52 | bwd_inner_microstep: 505.50 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 850 +[2025-05-01 23:30:56,261] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.24 | optimizer_step: 16.66 +[2025-05-01 23:30:56,262] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 143.37 | bwd_microstep: 540.99 | bwd_inner_microstep: 282.08 | bwd_allreduce_microstep: 258.89 | step_microstep: 26.47 +[2025-05-01 23:30:56,263] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4613.23 | bwd: 7095.54 | bwd_inner: 6836.32 | bwd_allreduce: 258.98 | step: 50.20 + 6%|▌ | 490/8720 [1:15:30<28:56:08, 12.66s/it] {'loss': 1.0233, 'grad_norm': 4.950743675231934, 'learning_rate': 9.982080969392045e-06, 'epoch': 0.56} + 6%|▌ | 490/8720 [1:15:30<28:56:08, 12.66s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1909 +[2025-05-01 23:30:57,141] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 339.36 | bwd_microstep: 498.68 | bwd_inner_microstep: 498.67 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.11 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1386 +[2025-05-01 23:30:57,822] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 279.19 | bwd_microstep: 383.02 | bwd_inner_microstep: 383.00 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1904 +[2025-05-01 23:30:58,709] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 328.96 | bwd_microstep: 526.30 | bwd_inner_microstep: 526.28 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.32 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-01 23:30:59,573] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 325.15 | bwd_microstep: 508.19 | bwd_inner_microstep: 508.17 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-01 23:31:00,411] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 305.39 | bwd_microstep: 515.65 | bwd_inner_microstep: 515.63 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-01 23:31:01,285] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 331.15 | bwd_microstep: 513.02 | bwd_inner_microstep: 513.00 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-01 23:31:02,178] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 361.10 | bwd_microstep: 505.75 | bwd_inner_microstep: 505.74 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 23:31:03,062] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 347.47 | bwd_microstep: 515.76 | bwd_inner_microstep: 515.74 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.52 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-01 23:31:03,887] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 323.44 | bwd_microstep: 469.56 | bwd_inner_microstep: 469.55 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:31:04,750] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 329.36 | bwd_microstep: 501.46 | bwd_inner_microstep: 501.44 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.49 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 325 +[2025-05-01 23:31:05,013] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.87 | bwd_microstep: 137.33 | bwd_inner_microstep: 137.32 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.31 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 23:31:05,840] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 314.75 | bwd_microstep: 489.29 | bwd_inner_microstep: 489.27 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 832 +[2025-05-01 23:31:06,291] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 168.95 | bwd_microstep: 266.83 | bwd_inner_microstep: 266.75 | bwd_allreduce_microstep: 0.04 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 23:31:07,113] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 360.30 | bwd_microstep: 440.67 | bwd_inner_microstep: 440.65 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.28 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 23:31:07,987] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 365.54 | bwd_microstep: 476.64 | bwd_inner_microstep: 476.62 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 23:31:09,130] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.21 | optimizer_step: 16.63 +[2025-05-01 23:31:09,131] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 327.01 | bwd_microstep: 760.65 | bwd_inner_microstep: 510.24 | bwd_allreduce_microstep: 250.39 | step_microstep: 26.23 +[2025-05-01 23:31:09,132] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4902.89 | bwd: 7508.82 | bwd_inner: 7258.08 | bwd_allreduce: 250.51 | step: 48.06 + 6%|▌ | 491/8720 [1:15:42<29:04:38, 12.72s/it] {'loss': 1.2996, 'grad_norm': 4.7636823654174805, 'learning_rate': 9.98192353519765e-06, 'epoch': 0.56} + 6%|▌ | 491/8720 [1:15:42<29:04:38, 12.72s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2140 +[2025-05-01 23:31:10,125] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 366.77 | bwd_microstep: 594.87 | bwd_inner_microstep: 594.85 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1888 +[2025-05-01 23:31:10,990] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 321.29 | bwd_microstep: 514.00 | bwd_inner_microstep: 513.98 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1118 +[2025-05-01 23:31:11,499] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 222.14 | bwd_microstep: 260.60 | bwd_inner_microstep: 260.59 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-01 23:31:12,390] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 335.96 | bwd_microstep: 523.33 | bwd_inner_microstep: 523.31 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.36 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 334 +[2025-05-01 23:31:12,614] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 71.43 | bwd_microstep: 128.06 | bwd_inner_microstep: 128.05 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-01 23:31:13,453] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 338.72 | bwd_microstep: 471.19 | bwd_inner_microstep: 471.17 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.48 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 847 +[2025-05-01 23:31:13,922] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 214.89 | bwd_microstep: 229.34 | bwd_inner_microstep: 229.32 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 843 +[2025-05-01 23:31:14,368] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 133.95 | bwd_microstep: 291.14 | bwd_inner_microstep: 291.12 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 326 +[2025-05-01 23:31:14,593] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 71.01 | bwd_microstep: 133.38 | bwd_inner_microstep: 133.36 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.48 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-01 23:31:15,461] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 329.47 | bwd_microstep: 509.17 | bwd_inner_microstep: 509.15 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.31 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 23:31:16,334] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 329.85 | bwd_microstep: 513.25 | bwd_inner_microstep: 513.23 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 23:31:17,202] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 329.08 | bwd_microstep: 506.69 | bwd_inner_microstep: 506.67 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 23:31:18,077] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 354.74 | bwd_microstep: 490.77 | bwd_inner_microstep: 490.70 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 318 +[2025-05-01 23:31:18,296] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 88.10 | bwd_microstep: 115.46 | bwd_inner_microstep: 115.44 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.33 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 23:31:19,147] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 324.71 | bwd_microstep: 496.71 | bwd_inner_microstep: 496.69 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1092 +[2025-05-01 23:31:19,970] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.17 | optimizer_step: 16.77 +[2025-05-01 23:31:19,971] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 220.02 | bwd_microstep: 551.67 | bwd_inner_microstep: 305.30 | bwd_allreduce_microstep: 246.35 | step_microstep: 26.21 +[2025-05-01 23:31:19,973] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4052.09 | bwd: 6329.65 | bwd_inner: 6082.97 | bwd_allreduce: 246.44 | step: 54.00 + 6%|▌ | 492/8720 [1:15:53<27:47:09, 12.16s/it] {'loss': 1.2274, 'grad_norm': 5.9927077293396, 'learning_rate': 9.98176541367937e-06, 'epoch': 0.56} + 6%|▌ | 492/8720 [1:15:53<27:47:09, 12.16s/it]dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 876 +[2025-05-01 23:31:20,433] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 134.33 | bwd_microstep: 283.70 | bwd_inner_microstep: 283.68 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.31 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1889 +[2025-05-01 23:31:21,293] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 314.39 | bwd_microstep: 514.07 | bwd_inner_microstep: 514.05 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.28 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-01 23:31:22,167] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 319.72 | bwd_microstep: 522.80 | bwd_inner_microstep: 522.79 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-01 23:31:23,024] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 328.39 | bwd_microstep: 498.38 | bwd_inner_microstep: 498.36 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-01 23:31:23,850] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 350.97 | bwd_microstep: 458.23 | bwd_inner_microstep: 458.21 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 840 +[2025-05-01 23:31:24,298] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 174.77 | bwd_microstep: 258.78 | bwd_inner_microstep: 258.66 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-01 23:31:25,203] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 365.25 | bwd_microstep: 521.03 | bwd_inner_microstep: 521.01 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-01 23:31:26,060] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 318.48 | bwd_microstep: 519.36 | bwd_inner_microstep: 519.35 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:31:26,877] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 314.31 | bwd_microstep: 468.55 | bwd_inner_microstep: 468.54 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 23:31:27,753] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 354.34 | bwd_microstep: 491.76 | bwd_inner_microstep: 491.74 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:31:28,664] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 403.30 | bwd_microstep: 492.14 | bwd_inner_microstep: 492.12 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-01 23:31:29,563] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 375.96 | bwd_microstep: 505.26 | bwd_inner_microstep: 505.24 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 23:31:30,411] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 331.29 | bwd_microstep: 497.87 | bwd_inner_microstep: 497.85 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.51 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 827 +[2025-05-01 23:31:30,835] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 117.25 | bwd_microstep: 288.86 | bwd_inner_microstep: 288.85 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.33 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 23:31:31,639] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 321.01 | bwd_microstep: 454.56 | bwd_inner_microstep: 454.55 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.33 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 315 +[2025-05-01 23:31:32,252] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.23 | optimizer_step: 26.64 +[2025-05-01 23:31:32,253] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 88.93 | bwd_microstep: 461.20 | bwd_inner_microstep: 133.28 | bwd_allreduce_microstep: 327.86 | step_microstep: 35.57 +[2025-05-01 23:31:32,254] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4612.61 | bwd: 7236.58 | bwd_inner: 6908.29 | bwd_allreduce: 328.00 | step: 55.01 + 6%|▌ | 493/8720 [1:16:06<27:51:53, 12.19s/it] {'loss': 1.1043, 'grad_norm': 3.833282232284546, 'learning_rate': 9.98160660485902e-06, 'epoch': 0.57} + 6%|▌ | 493/8720 [1:16:06<27:51:53, 12.19s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 439 +[2025-05-01 23:31:32,549] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 116.57 | bwd_microstep: 157.11 | bwd_inner_microstep: 157.09 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.49 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1913 +[2025-05-01 23:31:33,420] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 317.73 | bwd_microstep: 519.59 | bwd_inner_microstep: 519.57 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.28 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1130 +[2025-05-01 23:31:33,901] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 182.18 | bwd_microstep: 268.70 | bwd_inner_microstep: 268.68 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-01 23:31:34,784] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 361.63 | bwd_microstep: 491.30 | bwd_inner_microstep: 491.28 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-01 23:31:35,695] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 398.09 | bwd_microstep: 496.59 | bwd_inner_microstep: 496.57 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-01 23:31:36,587] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 355.95 | bwd_microstep: 516.02 | bwd_inner_microstep: 516.00 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.33 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-01 23:31:37,446] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 314.88 | bwd_microstep: 519.87 | bwd_inner_microstep: 519.85 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-01 23:31:38,310] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 313.54 | bwd_microstep: 515.99 | bwd_inner_microstep: 515.97 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.48 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-01 23:31:39,190] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 335.05 | bwd_microstep: 512.32 | bwd_inner_microstep: 512.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.91 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:31:40,048] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 329.19 | bwd_microstep: 509.93 | bwd_inner_microstep: 509.91 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 23:31:40,909] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 312.07 | bwd_microstep: 514.74 | bwd_inner_microstep: 514.72 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.28 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 23:31:41,777] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 318.21 | bwd_microstep: 516.31 | bwd_inner_microstep: 516.29 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 23:31:42,640] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 321.14 | bwd_microstep: 509.96 | bwd_inner_microstep: 509.94 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 23:31:43,510] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 329.88 | bwd_microstep: 511.28 | bwd_inner_microstep: 511.26 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 23:31:44,380] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 331.16 | bwd_microstep: 509.09 | bwd_inner_microstep: 509.07 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 23:31:45,649] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.33 | optimizer_step: 18.65 +[2025-05-01 23:31:45,651] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 330.14 | bwd_microstep: 882.89 | bwd_inner_microstep: 508.77 | bwd_allreduce_microstep: 374.11 | step_microstep: 28.20 +[2025-05-01 23:31:45,653] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4967.32 | bwd: 7951.67 | bwd_inner: 7577.29 | bwd_allreduce: 374.17 | step: 55.32 + 6%|▌ | 494/8720 [1:16:19<28:41:22, 12.56s/it] {'loss': 1.1711, 'grad_norm': 3.1507182121276855, 'learning_rate': 9.981447108758511e-06, 'epoch': 0.57} + 6%|▌ | 494/8720 [1:16:19<28:41:22, 12.56s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2323 +[2025-05-01 23:31:46,711] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 375.07 | bwd_microstep: 643.30 | bwd_inner_microstep: 643.28 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1902 +[2025-05-01 23:31:47,617] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 357.42 | bwd_microstep: 529.28 | bwd_inner_microstep: 529.26 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.50 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-01 23:31:48,436] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 278.75 | bwd_microstep: 519.08 | bwd_inner_microstep: 519.06 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-01 23:31:49,318] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 331.56 | bwd_microstep: 516.64 | bwd_inner_microstep: 516.62 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.52 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-01 23:31:50,213] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 322.06 | bwd_microstep: 538.81 | bwd_inner_microstep: 538.79 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-01 23:31:51,091] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 233.60 | bwd_microstep: 609.66 | bwd_inner_microstep: 609.64 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.49 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1092 +[2025-05-01 23:31:51,560] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 147.34 | bwd_microstep: 290.30 | bwd_inner_microstep: 290.28 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 836 +[2025-05-01 23:31:52,038] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 213.87 | bwd_microstep: 237.33 | bwd_inner_microstep: 237.11 | bwd_allreduce_microstep: 0.08 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 23:31:52,924] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 285.86 | bwd_microstep: 581.14 | bwd_inner_microstep: 581.12 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 23:31:53,801] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 250.58 | bwd_microstep: 606.89 | bwd_inner_microstep: 606.87 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 23:31:54,661] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 214.49 | bwd_microstep: 624.42 | bwd_inner_microstep: 624.33 | bwd_allreduce_microstep: 0.03 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 23:31:55,540] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 231.98 | bwd_microstep: 620.57 | bwd_inner_microstep: 620.56 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.52 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 833 +[2025-05-01 23:31:55,840] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 103.00 | bwd_microstep: 178.81 | bwd_inner_microstep: 178.79 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 23:31:56,705] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 424.22 | bwd_microstep: 408.60 | bwd_inner_microstep: 408.58 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 23:31:57,563] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 422.32 | bwd_microstep: 404.17 | bwd_inner_microstep: 404.15 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1888 +[2025-05-01 23:31:58,847] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.08 | optimizer_gradients: 2.30 | optimizer_step: 16.65 +[2025-05-01 23:31:58,847] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 434.09 | bwd_microstep: 791.56 | bwd_inner_microstep: 416.23 | bwd_allreduce_microstep: 375.29 | step_microstep: 27.17 +[2025-05-01 23:31:58,849] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4626.13 | bwd: 8100.62 | bwd_inner: 7724.73 | bwd_allreduce: 375.46 | step: 55.09 + 6%|▌ | 495/8720 [1:16:32<29:07:27, 12.75s/it] {'loss': 1.0056, 'grad_norm': 4.567164421081543, 'learning_rate': 9.981286925399845e-06, 'epoch': 0.57} + 6%|▌ | 495/8720 [1:16:32<29:07:27, 12.75s/it]dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1181 +[2025-05-01 23:31:59,515] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 253.41 | bwd_microstep: 389.93 | bwd_inner_microstep: 389.91 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-01 23:32:00,364] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 201.44 | bwd_microstep: 615.10 | bwd_inner_microstep: 615.08 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 340 +[2025-05-01 23:32:00,600] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 87.93 | bwd_microstep: 117.78 | bwd_inner_microstep: 117.51 | bwd_allreduce_microstep: 0.10 | step_microstep: 0.10 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 348 +[2025-05-01 23:32:00,858] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 102.31 | bwd_microstep: 140.77 | bwd_inner_microstep: 140.27 | bwd_allreduce_microstep: 0.15 | step_microstep: 0.18 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 862 +[2025-05-01 23:32:01,324] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 225.32 | bwd_microstep: 211.51 | bwd_inner_microstep: 211.25 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.10 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 333 +[2025-05-01 23:32:01,566] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 90.68 | bwd_microstep: 132.40 | bwd_inner_microstep: 132.38 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.49 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-01 23:32:02,418] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 428.39 | bwd_microstep: 391.50 | bwd_inner_microstep: 391.48 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 23:32:03,268] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 423.40 | bwd_microstep: 392.33 | bwd_inner_microstep: 392.31 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 841 +[2025-05-01 23:32:03,809] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 209.46 | bwd_microstep: 304.14 | bwd_inner_microstep: 303.51 | bwd_allreduce_microstep: 0.62 | step_microstep: 0.29 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 836 +[2025-05-01 23:32:04,122] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 99.62 | bwd_microstep: 195.38 | bwd_inner_microstep: 195.36 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:32:04,981] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 418.36 | bwd_microstep: 408.63 | bwd_inner_microstep: 408.61 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 23:32:05,855] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 426.02 | bwd_microstep: 415.21 | bwd_inner_microstep: 415.19 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 23:32:06,722] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 406.55 | bwd_microstep: 428.95 | bwd_inner_microstep: 428.93 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 23:32:07,585] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 399.18 | bwd_microstep: 431.20 | bwd_inner_microstep: 431.18 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 23:32:08,435] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 392.57 | bwd_microstep: 428.40 | bwd_inner_microstep: 428.38 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.25 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-01 23:32:09,683] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.26 | optimizer_step: 20.06 +[2025-05-01 23:32:09,684] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 396.18 | bwd_microstep: 793.29 | bwd_inner_microstep: 431.02 | bwd_allreduce_microstep: 362.22 | step_microstep: 28.94 +[2025-05-01 23:32:09,685] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4560.77 | bwd: 5796.55 | bwd_inner: 5432.58 | bwd_allreduce: 363.18 | step: 51.35 + 6%|▌ | 496/8720 [1:16:43<27:48:36, 12.17s/it] {'loss': 1.0413, 'grad_norm': 4.076443195343018, 'learning_rate': 9.981126054805122e-06, 'epoch': 0.57} + 6%|▌ | 496/8720 [1:16:43<27:48:36, 12.17s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1900 +[2025-05-01 23:32:10,519] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 398.36 | bwd_microstep: 414.76 | bwd_inner_microstep: 414.74 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1887 +[2025-05-01 23:32:11,393] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 428.36 | bwd_microstep: 426.44 | bwd_inner_microstep: 426.42 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-01 23:32:12,274] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 411.40 | bwd_microstep: 455.05 | bwd_inner_microstep: 455.03 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 853 +[2025-05-01 23:32:12,779] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.58 | bwd_microstep: 299.02 | bwd_inner_microstep: 299.00 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-01 23:32:13,672] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 284.02 | bwd_microstep: 572.71 | bwd_inner_microstep: 572.70 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.33 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-01 23:32:14,537] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 208.04 | bwd_microstep: 626.16 | bwd_inner_microstep: 626.14 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-01 23:32:15,389] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 203.37 | bwd_microstep: 617.38 | bwd_inner_microstep: 617.36 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-01 23:32:16,246] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 207.92 | bwd_microstep: 614.42 | bwd_inner_microstep: 614.40 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.31 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 839 +[2025-05-01 23:32:16,571] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 124.27 | bwd_microstep: 168.64 | bwd_inner_microstep: 168.62 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.52 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 23:32:17,444] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 430.20 | bwd_microstep: 410.63 | bwd_inner_microstep: 410.61 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 23:32:18,298] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 425.60 | bwd_microstep: 396.46 | bwd_inner_microstep: 396.44 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:32:19,153] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 423.67 | bwd_microstep: 397.71 | bwd_inner_microstep: 397.69 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:32:20,025] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 429.65 | bwd_microstep: 407.71 | bwd_inner_microstep: 407.69 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 23:32:20,882] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 424.68 | bwd_microstep: 398.84 | bwd_inner_microstep: 398.82 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-01 23:32:21,735] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 423.61 | bwd_microstep: 395.03 | bwd_inner_microstep: 395.01 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 827 +[2025-05-01 23:32:22,461] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.19 | optimizer_step: 17.24 +[2025-05-01 23:32:22,462] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 206.37 | bwd_microstep: 464.14 | bwd_inner_microstep: 306.79 | bwd_allreduce_microstep: 157.30 | step_microstep: 25.97 +[2025-05-01 23:32:22,463] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 5218.05 | bwd: 7065.12 | bwd_inner: 6907.49 | bwd_allreduce: 157.38 | step: 54.43 + 6%|▌ | 497/8720 [1:16:56<28:13:13, 12.35s/it] {'loss': 0.8317, 'grad_norm': 2.7546021938323975, 'learning_rate': 9.980964496996537e-06, 'epoch': 0.57} + 6%|▌ | 497/8720 [1:16:56<28:13:13, 12.35s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1892 +[2025-05-01 23:32:23,439] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 429.40 | bwd_microstep: 404.28 | bwd_inner_microstep: 404.26 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-01 23:32:24,322] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 427.12 | bwd_microstep: 421.55 | bwd_inner_microstep: 421.53 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-01 23:32:25,204] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 394.58 | bwd_microstep: 459.30 | bwd_inner_microstep: 459.28 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-01 23:32:26,076] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 313.25 | bwd_microstep: 524.69 | bwd_inner_microstep: 524.68 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 848 +[2025-05-01 23:32:26,445] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 204.59 | bwd_microstep: 134.48 | bwd_inner_microstep: 134.46 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 23:32:27,319] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 386.13 | bwd_microstep: 472.48 | bwd_inner_microstep: 472.47 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-01 23:32:28,143] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 374.96 | bwd_microstep: 432.67 | bwd_inner_microstep: 432.65 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 23:32:28,984] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 421.01 | bwd_microstep: 401.28 | bwd_inner_microstep: 401.27 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.50 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 326 +[2025-05-01 23:32:29,247] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 107.70 | bwd_microstep: 125.77 | bwd_inner_microstep: 125.75 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.44 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 23:32:30,099] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 358.84 | bwd_microstep: 461.11 | bwd_inner_microstep: 461.09 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 23:32:30,953] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 363.37 | bwd_microstep: 457.75 | bwd_inner_microstep: 457.73 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.48 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 23:32:31,826] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 364.71 | bwd_microstep: 474.19 | bwd_inner_microstep: 474.17 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 23:32:32,687] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 351.50 | bwd_microstep: 477.39 | bwd_inner_microstep: 477.37 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 23:32:33,536] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 349.28 | bwd_microstep: 465.66 | bwd_inner_microstep: 465.64 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 23:32:34,393] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 355.61 | bwd_microstep: 467.18 | bwd_inner_microstep: 467.16 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1850 +[2025-05-01 23:32:35,595] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.19 | optimizer_step: 16.12 +[2025-05-01 23:32:35,596] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 356.01 | bwd_microstep: 792.02 | bwd_inner_microstep: 464.47 | bwd_allreduce_microstep: 327.50 | step_microstep: 24.88 +[2025-05-01 23:32:35,597] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 5558.00 | bwd: 6971.82 | bwd_inner: 6643.98 | bwd_allreduce: 327.58 | step: 53.67 + 6%|▌ | 498/8720 [1:17:09<28:45:03, 12.59s/it] {'loss': 0.9698, 'grad_norm': 5.275992393493652, 'learning_rate': 9.980802251996383e-06, 'epoch': 0.57} + 6%|▌ | 498/8720 [1:17:09<28:45:03, 12.59s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1922 +[2025-05-01 23:32:36,504] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 417.79 | bwd_microstep: 468.43 | bwd_inner_microstep: 468.41 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 360 +[2025-05-01 23:32:36,765] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 90.85 | bwd_microstep: 155.27 | bwd_inner_microstep: 155.25 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.28 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1890 +[2025-05-01 23:32:37,662] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 426.10 | bwd_microstep: 442.75 | bwd_inner_microstep: 442.73 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-01 23:32:38,523] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 390.38 | bwd_microstep: 436.37 | bwd_inner_microstep: 436.35 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 23:32:39,389] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 391.32 | bwd_microstep: 440.61 | bwd_inner_microstep: 440.59 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:32:40,245] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 384.57 | bwd_microstep: 437.47 | bwd_inner_microstep: 437.45 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:32:41,098] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 386.83 | bwd_microstep: 432.07 | bwd_inner_microstep: 432.05 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1345 +[2025-05-01 23:32:41,732] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 327.36 | bwd_microstep: 274.21 | bwd_inner_microstep: 274.19 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.52 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 23:32:42,597] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 418.59 | bwd_microstep: 412.64 | bwd_inner_microstep: 412.62 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-01 23:32:43,455] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 426.74 | bwd_microstep: 396.72 | bwd_inner_microstep: 396.71 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 23:32:44,326] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 421.88 | bwd_microstep: 415.11 | bwd_inner_microstep: 415.09 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 23:32:45,196] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 422.41 | bwd_microstep: 414.10 | bwd_inner_microstep: 414.08 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 23:32:46,071] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 423.38 | bwd_microstep: 419.03 | bwd_inner_microstep: 419.01 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 832 +[2025-05-01 23:32:46,487] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 216.61 | bwd_microstep: 170.22 | bwd_inner_microstep: 169.89 | bwd_allreduce_microstep: 0.14 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 23:32:47,363] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 367.53 | bwd_microstep: 492.84 | bwd_inner_microstep: 492.82 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 23:32:48,383] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.31 | optimizer_step: 33.31 +[2025-05-01 23:32:48,385] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 344.13 | bwd_microstep: 620.59 | bwd_inner_microstep: 518.87 | bwd_allreduce_microstep: 101.67 | step_microstep: 41.94 +[2025-05-01 23:32:48,387] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 5856.40 | bwd: 6428.46 | bwd_inner: 6326.22 | bwd_allreduce: 101.87 | step: 70.38 + 6%|▌ | 499/8720 [1:17:22<28:53:13, 12.65s/it] {'loss': 1.1887, 'grad_norm': 4.34716796875, 'learning_rate': 9.980639319827036e-06, 'epoch': 0.57} + 6%|▌ | 499/8720 [1:17:22<28:53:13, 12.65s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 405 +[2025-05-01 23:32:48,700] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 119.18 | bwd_microstep: 154.05 | bwd_inner_microstep: 154.03 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1913 +[2025-05-01 23:32:49,588] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 313.97 | bwd_microstep: 541.94 | bwd_inner_microstep: 541.92 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.48 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1907 +[2025-05-01 23:32:50,474] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 291.03 | bwd_microstep: 560.79 | bwd_inner_microstep: 560.77 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 371 +[2025-05-01 23:32:50,712] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 108.29 | bwd_microstep: 102.20 | bwd_inner_microstep: 101.86 | bwd_allreduce_microstep: 0.17 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-01 23:32:51,596] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 312.42 | bwd_microstep: 554.10 | bwd_inner_microstep: 554.08 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-01 23:32:52,488] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 287.82 | bwd_microstep: 584.87 | bwd_inner_microstep: 584.85 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-01 23:32:53,359] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 229.70 | bwd_microstep: 621.86 | bwd_inner_microstep: 621.85 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1356 +[2025-05-01 23:32:53,956] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 147.09 | bwd_microstep: 427.93 | bwd_inner_microstep: 427.92 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.48 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-01 23:32:54,839] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 322.06 | bwd_microstep: 522.02 | bwd_inner_microstep: 522.01 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 23:32:55,711] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 300.69 | bwd_microstep: 534.69 | bwd_inner_microstep: 534.67 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.32 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:32:56,565] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 237.76 | bwd_microstep: 582.45 | bwd_inner_microstep: 582.43 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 23:32:57,417] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 237.18 | bwd_microstep: 580.07 | bwd_inner_microstep: 580.06 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 326 +[2025-05-01 23:32:57,674] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 98.54 | bwd_microstep: 128.98 | bwd_inner_microstep: 128.83 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 23:32:58,553] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 390.85 | bwd_microstep: 471.78 | bwd_inner_microstep: 471.76 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 23:32:59,432] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 390.28 | bwd_microstep: 472.57 | bwd_inner_microstep: 472.55 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 23:33:00,570] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.38 | optimizer_step: 18.61 +[2025-05-01 23:33:00,572] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 367.24 | bwd_microstep: 728.84 | bwd_inner_microstep: 492.51 | bwd_allreduce_microstep: 236.32 | step_microstep: 28.14 +[2025-05-01 23:33:00,574] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4153.96 | bwd: 7569.17 | bwd_inner: 7332.19 | bwd_allreduce: 236.56 | step: 47.80 + 6%|▌ | 500/8720 [1:17:34<28:33:59, 12.51s/it] {'loss': 1.7738, 'grad_norm': 5.906229496002197, 'learning_rate': 9.980475700510981e-06, 'epoch': 0.57} + 6%|▌ | 500/8720 [1:17:34<28:33:59, 12.51s/it][INFO|trainer.py:3503] 2025-05-01 23:33:04,228 >> Saving model checkpoint to work_dirs/internvl_chat_v2_5/ak/checkpoint-500 +[INFO|configuration_utils.py:472] 2025-05-01 23:33:04,231 >> Configuration saved in work_dirs/internvl_chat_v2_5/ak/checkpoint-500/config.json +[INFO|configuration_utils.py:807] 2025-05-01 23:33:04,232 >> Configuration saved in work_dirs/internvl_chat_v2_5/ak/checkpoint-500/generation_config.json +[INFO|modeling_utils.py:2755] 2025-05-01 23:33:09,494 >> Model weights saved in work_dirs/internvl_chat_v2_5/ak/checkpoint-500/model.safetensors +[INFO|tokenization_utils_base.py:2702] 2025-05-01 23:33:09,496 >> tokenizer config file saved in work_dirs/internvl_chat_v2_5/ak/checkpoint-500/tokenizer_config.json +[INFO|tokenization_utils_base.py:2711] 2025-05-01 23:33:09,497 >> Special tokens file saved in work_dirs/internvl_chat_v2_5/ak/checkpoint-500/special_tokens_map.json +[INFO|tokenization_utils_base.py:2762] 2025-05-01 23:33:09,497 >> added tokens file saved in work_dirs/internvl_chat_v2_5/ak/checkpoint-500/added_tokens.json +[2025-05-01 23:33:09,625] [INFO] [logging.py:96:log_dist] [Rank 0] [Torch] Checkpoint global_step500 is about to be saved! +[2025-05-01 23:33:09,648] [INFO] [logging.py:96:log_dist] [Rank 0] Saving model checkpoint: work_dirs/internvl_chat_v2_5/ak/checkpoint-500/global_step500/mp_rank_00_model_states.pt +[2025-05-01 23:33:09,648] [INFO] [torch_checkpoint_engine.py:21:save] [Torch] Saving work_dirs/internvl_chat_v2_5/ak/checkpoint-500/global_step500/mp_rank_00_model_states.pt... +[2025-05-01 23:33:14,572] [INFO] [torch_checkpoint_engine.py:23:save] [Torch] Saved work_dirs/internvl_chat_v2_5/ak/checkpoint-500/global_step500/mp_rank_00_model_states.pt. +[2025-05-01 23:33:14,574] [INFO] [torch_checkpoint_engine.py:21:save] [Torch] Saving work_dirs/internvl_chat_v2_5/ak/checkpoint-500/global_step500/bf16_zero_pp_rank_0_mp_rank_00_optim_states.pt... +[2025-05-01 23:33:14,851] [INFO] [torch_checkpoint_engine.py:23:save] [Torch] Saved work_dirs/internvl_chat_v2_5/ak/checkpoint-500/global_step500/bf16_zero_pp_rank_0_mp_rank_00_optim_states.pt. +[2025-05-01 23:33:14,851] [INFO] [engine.py:3536:_save_zero_checkpoint] zero checkpoint saved work_dirs/internvl_chat_v2_5/ak/checkpoint-500/global_step500/bf16_zero_pp_rank_0_mp_rank_00_optim_states.pt +[2025-05-01 23:33:14,851] [INFO] [torch_checkpoint_engine.py:33:commit] [Torch] Checkpoint global_step500 is ready now! +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-01 23:33:15,742] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 327.68 | bwd_microstep: 536.35 | bwd_inner_microstep: 536.31 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.24 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1360 +[2025-05-01 23:33:16,431] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 202.61 | bwd_microstep: 466.61 | bwd_inner_microstep: 466.59 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.33 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-01 23:33:17,289] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 226.10 | bwd_microstep: 597.66 | bwd_inner_microstep: 597.64 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-01 23:33:18,159] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 225.44 | bwd_microstep: 609.97 | bwd_inner_microstep: 609.95 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.48 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-01 23:33:19,032] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 215.13 | bwd_microstep: 624.26 | bwd_inner_microstep: 624.24 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-01 23:33:19,889] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 221.99 | bwd_microstep: 603.23 | bwd_inner_microstep: 603.21 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1356 +[2025-05-01 23:33:20,499] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 143.79 | bwd_microstep: 447.66 | bwd_inner_microstep: 447.64 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:33:21,355] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 307.39 | bwd_microstep: 516.16 | bwd_inner_microstep: 516.14 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.33 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 23:33:22,226] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 304.67 | bwd_microstep: 532.21 | bwd_inner_microstep: 532.20 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 23:33:23,082] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 295.80 | bwd_microstep: 527.61 | bwd_inner_microstep: 527.59 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 320 +[2025-05-01 23:33:23,316] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.98 | bwd_microstep: 107.82 | bwd_inner_microstep: 107.55 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 23:33:24,198] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 251.31 | bwd_microstep: 610.48 | bwd_inner_microstep: 610.46 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 23:33:25,064] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 229.18 | bwd_microstep: 619.14 | bwd_inner_microstep: 619.13 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 23:33:25,904] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 199.89 | bwd_microstep: 616.94 | bwd_inner_microstep: 616.92 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1935 +[2025-05-01 23:33:26,795] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 210.00 | bwd_microstep: 647.29 | bwd_inner_microstep: 647.27 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1888 +[2025-05-01 23:33:27,806] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.07 | optimizer_gradients: 4.60 | optimizer_step: 24.16 +[2025-05-01 23:33:27,806] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 236.62 | bwd_microstep: 709.92 | bwd_inner_microstep: 584.05 | bwd_allreduce_microstep: 125.82 | step_microstep: 35.89 +[2025-05-01 23:33:27,808] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 3693.50 | bwd: 8773.39 | bwd_inner: 8646.98 | bwd_allreduce: 126.00 | step: 61.16 + 6%|▌ | 501/8720 [1:18:01<38:38:43, 16.93s/it] {'loss': 1.0409, 'grad_norm': 3.0923686027526855, 'learning_rate': 9.980311394070788e-06, 'epoch': 0.57} + 6%|▌ | 501/8720 [1:18:01<38:38:43, 16.93s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-01 23:33:28,687] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 421.80 | bwd_microstep: 417.21 | bwd_inner_microstep: 417.19 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.48 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 347 +[2025-05-01 23:33:28,952] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 106.15 | bwd_microstep: 127.01 | bwd_inner_microstep: 126.99 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-01 23:33:29,850] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 357.91 | bwd_microstep: 507.89 | bwd_inner_microstep: 507.87 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 852 +[2025-05-01 23:33:30,221] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 169.96 | bwd_microstep: 171.77 | bwd_inner_microstep: 171.75 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.50 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-01 23:33:31,100] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 416.27 | bwd_microstep: 430.70 | bwd_inner_microstep: 430.68 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 23:33:31,962] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 393.57 | bwd_microstep: 435.91 | bwd_inner_microstep: 435.89 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 838 +[2025-05-01 23:33:32,411] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 214.36 | bwd_microstep: 204.67 | bwd_inner_microstep: 204.45 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-01 23:33:33,293] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 314.28 | bwd_microstep: 549.47 | bwd_inner_microstep: 549.45 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 23:33:34,176] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 285.69 | bwd_microstep: 579.10 | bwd_inner_microstep: 579.08 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:33:35,052] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 253.46 | bwd_microstep: 603.74 | bwd_inner_microstep: 603.72 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.31 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 23:33:35,927] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 243.86 | bwd_microstep: 609.45 | bwd_inner_microstep: 609.43 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.17 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 23:33:36,783] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 215.64 | bwd_microstep: 619.89 | bwd_inner_microstep: 619.88 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 23:33:37,637] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 215.44 | bwd_microstep: 612.67 | bwd_inner_microstep: 612.65 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 827 +[2025-05-01 23:33:37,978] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 130.99 | bwd_microstep: 180.38 | bwd_inner_microstep: 180.36 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.32 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 314 +[2025-05-01 23:33:38,228] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 105.46 | bwd_microstep: 114.32 | bwd_inner_microstep: 114.30 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-01 23:33:39,489] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.07 | optimizer_gradients: 2.40 | optimizer_step: 27.38 +[2025-05-01 23:33:39,489] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 366.96 | bwd_microstep: 828.28 | bwd_inner_microstep: 477.01 | bwd_allreduce_microstep: 351.22 | step_microstep: 36.93 +[2025-05-01 23:33:39,491] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4211.69 | bwd: 6992.49 | bwd_inner: 6640.73 | bwd_allreduce: 351.43 | step: 62.30 + 6%|▌ | 502/8720 [1:18:13<35:02:56, 15.35s/it] {'loss': 0.662, 'grad_norm': 2.634125232696533, 'learning_rate': 9.980146400529126e-06, 'epoch': 0.58} + 6%|▌ | 502/8720 [1:18:13<35:02:56, 15.35s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1894 +[2025-05-01 23:33:40,404] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 407.89 | bwd_microstep: 485.48 | bwd_inner_microstep: 485.47 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-01 23:33:41,315] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 370.88 | bwd_microstep: 524.14 | bwd_inner_microstep: 524.13 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-01 23:33:42,230] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 340.78 | bwd_microstep: 554.81 | bwd_inner_microstep: 554.80 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-01 23:33:43,146] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 302.59 | bwd_microstep: 593.30 | bwd_inner_microstep: 593.28 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 849 +[2025-05-01 23:33:43,535] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 106.57 | bwd_microstep: 264.61 | bwd_inner_microstep: 264.57 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-01 23:33:44,428] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 434.27 | bwd_microstep: 424.15 | bwd_inner_microstep: 424.13 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.45 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-01 23:33:45,316] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 433.47 | bwd_microstep: 421.34 | bwd_inner_microstep: 421.32 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 838 +[2025-05-01 23:33:45,818] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 212.92 | bwd_microstep: 261.55 | bwd_inner_microstep: 261.43 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 23:33:46,717] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 261.82 | bwd_microstep: 618.63 | bwd_inner_microstep: 618.62 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.20 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 840 +[2025-05-01 23:33:47,043] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 104.63 | bwd_microstep: 203.30 | bwd_inner_microstep: 203.29 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 23:33:47,919] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 419.14 | bwd_microstep: 422.13 | bwd_inner_microstep: 422.11 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 23:33:48,788] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 418.76 | bwd_microstep: 417.70 | bwd_inner_microstep: 417.68 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.52 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 325 +[2025-05-01 23:33:49,046] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 103.69 | bwd_microstep: 124.10 | bwd_inner_microstep: 124.08 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.50 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-01 23:33:49,751] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 371.45 | bwd_microstep: 301.85 | bwd_inner_microstep: 301.81 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 23:33:50,626] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 423.95 | bwd_microstep: 418.44 | bwd_inner_microstep: 418.42 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.33 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 23:33:52,053] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 3.84 | optimizer_step: 20.81 +[2025-05-01 23:33:52,054] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 418.95 | bwd_microstep: 947.62 | bwd_inner_microstep: 424.19 | bwd_allreduce_microstep: 523.38 | step_microstep: 31.69 +[2025-05-01 23:33:52,055] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 5131.63 | bwd: 6983.18 | bwd_inner: 6459.33 | bwd_allreduce: 523.52 | step: 53.90 + 6%|▌ | 503/8720 [1:18:25<33:08:11, 14.52s/it] {'loss': 1.0382, 'grad_norm': 4.5639824867248535, 'learning_rate': 9.979980719908762e-06, 'epoch': 0.58} + 6%|▌ | 503/8720 [1:18:25<33:08:11, 14.52s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 419 +[2025-05-01 23:33:52,351] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 99.48 | bwd_microstep: 173.54 | bwd_inner_microstep: 173.52 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1929 +[2025-05-01 23:33:53,271] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 435.38 | bwd_microstep: 452.45 | bwd_inner_microstep: 452.43 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.25 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-01 23:33:54,163] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 421.15 | bwd_microstep: 441.79 | bwd_inner_microstep: 441.78 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-01 23:33:55,046] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 423.46 | bwd_microstep: 430.19 | bwd_inner_microstep: 430.18 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-01 23:33:55,937] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 424.32 | bwd_microstep: 432.89 | bwd_inner_microstep: 432.87 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-01 23:33:56,822] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 422.86 | bwd_microstep: 429.14 | bwd_inner_microstep: 429.12 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 338 +[2025-05-01 23:33:57,098] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 101.21 | bwd_microstep: 142.82 | bwd_inner_microstep: 142.80 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-01 23:33:57,968] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 246.27 | bwd_microstep: 591.70 | bwd_inner_microstep: 591.68 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.48 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-01 23:33:58,831] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 265.64 | bwd_microstep: 565.76 | bwd_inner_microstep: 565.74 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-01 23:33:59,702] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 291.72 | bwd_microstep: 547.31 | bwd_inner_microstep: 547.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1352 +[2025-05-01 23:34:00,320] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 262.82 | bwd_microstep: 324.80 | bwd_inner_microstep: 324.78 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-01 23:34:01,189] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 421.24 | bwd_microstep: 415.71 | bwd_inner_microstep: 415.69 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.30 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 23:34:02,058] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 423.19 | bwd_microstep: 413.72 | bwd_inner_microstep: 413.70 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 23:34:02,926] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 420.43 | bwd_microstep: 414.73 | bwd_inner_microstep: 414.71 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.48 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-01 23:34:03,795] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 425.93 | bwd_microstep: 409.32 | bwd_inner_microstep: 409.31 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 314 +[2025-05-01 23:34:04,432] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.07 | optimizer_gradients: 4.61 | optimizer_step: 24.99 +[2025-05-01 23:34:04,433] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 102.55 | bwd_microstep: 469.69 | bwd_inner_microstep: 131.95 | bwd_allreduce_microstep: 337.69 | step_microstep: 37.25 +[2025-05-01 23:34:04,434] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 5187.63 | bwd: 6655.60 | bwd_inner: 6317.58 | bwd_allreduce: 337.78 | step: 68.43 + 6%|▌ | 504/8720 [1:18:38<31:40:14, 13.88s/it] {'loss': 1.5086, 'grad_norm': 5.700324535369873, 'learning_rate': 9.979814352232548e-06, 'epoch': 0.58} + 6%|▌ | 504/8720 [1:18:38<31:40:14, 13.88s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1903 +[2025-05-01 23:34:05,330] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 422.19 | bwd_microstep: 429.41 | bwd_inner_microstep: 429.39 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 347 +[2025-05-01 23:34:05,591] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 103.63 | bwd_microstep: 133.37 | bwd_inner_microstep: 133.17 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1887 +[2025-05-01 23:34:06,479] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 420.91 | bwd_microstep: 436.03 | bwd_inner_microstep: 436.02 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.33 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-01 23:34:07,362] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 422.07 | bwd_microstep: 430.82 | bwd_inner_microstep: 430.80 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-01 23:34:08,250] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 424.19 | bwd_microstep: 430.05 | bwd_inner_microstep: 430.03 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.46 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-01 23:34:09,138] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 428.95 | bwd_microstep: 426.15 | bwd_inner_microstep: 426.14 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 838 +[2025-05-01 23:34:09,629] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 212.84 | bwd_microstep: 258.60 | bwd_inner_microstep: 258.38 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.08 +dynamic ViT batch size: 6, images per sample: 6.0, dynamic token length: 1613 +[2025-05-01 23:34:10,419] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 214.90 | bwd_microstep: 556.12 | bwd_inner_microstep: 556.10 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-01 23:34:11,289] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 226.43 | bwd_microstep: 611.77 | bwd_inner_microstep: 611.75 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 23:34:12,155] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 241.16 | bwd_microstep: 590.49 | bwd_inner_microstep: 590.48 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.50 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 23:34:13,021] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 264.79 | bwd_microstep: 569.15 | bwd_inner_microstep: 569.13 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 23:34:13,886] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 286.67 | bwd_microstep: 546.26 | bwd_inner_microstep: 546.24 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 23:34:14,752] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 305.80 | bwd_microstep: 527.56 | bwd_inner_microstep: 527.54 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 318 +[2025-05-01 23:34:15,001] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.44 | bwd_microstep: 125.46 | bwd_inner_microstep: 124.87 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.40 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 23:34:15,855] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 218.41 | bwd_microstep: 615.40 | bwd_inner_microstep: 615.38 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 23:34:16,952] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.28 | optimizer_step: 18.23 +[2025-05-01 23:34:16,953] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 210.76 | bwd_microstep: 828.87 | bwd_inner_microstep: 614.12 | bwd_allreduce_microstep: 214.69 | step_microstep: 26.39 +[2025-05-01 23:34:16,954] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4499.12 | bwd: 7515.71 | bwd_inner: 7300.14 | bwd_allreduce: 214.85 | step: 53.15 + 6%|▌ | 505/8720 [1:18:50<30:44:02, 13.47s/it] {'loss': 0.7508, 'grad_norm': 3.7804114818573, 'learning_rate': 9.979647297523438e-06, 'epoch': 0.58} + 6%|▌ | 505/8720 [1:18:50<30:44:02, 13.47s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 418 +[2025-05-01 23:34:17,255] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 113.82 | bwd_microstep: 168.25 | bwd_inner_microstep: 168.02 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.28 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1915 +[2025-05-01 23:34:18,148] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 420.00 | bwd_microstep: 443.19 | bwd_inner_microstep: 443.17 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 860 +[2025-05-01 23:34:18,632] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 217.85 | bwd_microstep: 239.71 | bwd_inner_microstep: 239.54 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-01 23:34:19,546] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 302.99 | bwd_microstep: 592.13 | bwd_inner_microstep: 592.11 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-01 23:34:20,445] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 255.85 | bwd_microstep: 621.69 | bwd_inner_microstep: 621.67 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.53 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-01 23:34:21,309] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 219.43 | bwd_microstep: 620.85 | bwd_inner_microstep: 620.84 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.30 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1357 +[2025-05-01 23:34:21,921] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 164.06 | bwd_microstep: 413.62 | bwd_inner_microstep: 413.60 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.48 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 840 +[2025-05-01 23:34:22,354] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 218.42 | bwd_microstep: 182.23 | bwd_inner_microstep: 182.13 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.11 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 852 +[2025-05-01 23:34:22,817] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 143.67 | bwd_microstep: 299.15 | bwd_inner_microstep: 299.13 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.51 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 23:34:23,695] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 367.32 | bwd_microstep: 474.23 | bwd_inner_microstep: 474.22 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 23:34:24,570] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 382.95 | bwd_microstep: 458.27 | bwd_inner_microstep: 458.25 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.53 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 838 +[2025-05-01 23:34:25,030] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 213.85 | bwd_microstep: 215.52 | bwd_inner_microstep: 215.35 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 23:34:25,942] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 310.81 | bwd_microstep: 581.15 | bwd_inner_microstep: 581.13 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 23:34:26,844] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 271.35 | bwd_microstep: 610.79 | bwd_inner_microstep: 610.78 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-01 23:34:27,708] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 223.85 | bwd_microstep: 617.20 | bwd_inner_microstep: 617.18 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.52 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 23:34:28,817] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.37 | optimizer_step: 17.70 +[2025-05-01 23:34:28,818] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 214.88 | bwd_microstep: 833.61 | bwd_inner_microstep: 615.50 | bwd_allreduce_microstep: 218.06 | step_microstep: 27.39 +[2025-05-01 23:34:28,819] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4040.97 | bwd: 7371.68 | bwd_inner: 7152.69 | bwd_allreduce: 218.34 | step: 45.65 + 6%|▌ | 506/8720 [1:19:02<29:37:56, 12.99s/it] {'loss': 1.1365, 'grad_norm': 4.773699760437012, 'learning_rate': 9.979479555804483e-06, 'epoch': 0.58} + 6%|▌ | 506/8720 [1:19:02<29:37:56, 12.99s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1979 +[2025-05-01 23:34:29,770] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 448.93 | bwd_microstep: 459.86 | bwd_inner_microstep: 459.84 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1954 +[2025-05-01 23:34:30,700] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 443.63 | bwd_microstep: 452.08 | bwd_inner_microstep: 452.07 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1903 +[2025-05-01 23:34:31,588] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 427.46 | bwd_microstep: 426.25 | bwd_inner_microstep: 426.23 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1901 +[2025-05-01 23:34:32,468] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 427.12 | bwd_microstep: 419.24 | bwd_inner_microstep: 419.22 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1893 +[2025-05-01 23:34:33,348] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 423.40 | bwd_microstep: 423.80 | bwd_inner_microstep: 423.78 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-01 23:34:34,244] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 427.96 | bwd_microstep: 436.15 | bwd_inner_microstep: 436.13 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-01 23:34:35,153] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 421.74 | bwd_microstep: 471.39 | bwd_inner_microstep: 471.38 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-01 23:34:36,065] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 390.19 | bwd_microstep: 503.64 | bwd_inner_microstep: 503.62 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1364 +[2025-05-01 23:34:36,805] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 250.80 | bwd_microstep: 468.94 | bwd_inner_microstep: 468.92 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.53 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-01 23:34:37,673] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 212.20 | bwd_microstep: 621.37 | bwd_inner_microstep: 621.35 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-01 23:34:38,539] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 235.31 | bwd_microstep: 596.30 | bwd_inner_microstep: 596.28 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-01 23:34:39,406] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 255.73 | bwd_microstep: 577.44 | bwd_inner_microstep: 577.42 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-01 23:34:40,275] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 278.03 | bwd_microstep: 556.76 | bwd_inner_microstep: 556.74 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.32 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 23:34:41,136] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 302.17 | bwd_microstep: 526.44 | bwd_inner_microstep: 526.42 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 23:34:42,009] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 325.39 | bwd_microstep: 513.40 | bwd_inner_microstep: 513.38 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 23:34:43,242] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 4.67 | optimizer_step: 23.52 +[2025-05-01 23:34:43,243] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 337.18 | bwd_microstep: 829.88 | bwd_inner_microstep: 494.73 | bwd_allreduce_microstep: 335.09 | step_microstep: 35.27 +[2025-05-01 23:34:43,244] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 5607.18 | bwd: 8282.96 | bwd_inner: 7947.54 | bwd_allreduce: 335.18 | step: 61.58 + 6%|▌ | 507/8720 [1:19:16<30:36:47, 13.42s/it] {'loss': 1.0442, 'grad_norm': 4.085476398468018, 'learning_rate': 9.979311127098823e-06, 'epoch': 0.58} + 6%|▌ | 507/8720 [1:19:16<30:36:47, 13.42s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1954 +[2025-05-01 23:34:44,184] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 428.58 | bwd_microstep: 490.14 | bwd_inner_microstep: 490.12 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.13 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-01 23:34:45,095] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 395.66 | bwd_microstep: 498.41 | bwd_inner_microstep: 498.28 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.29 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1355 +[2025-05-01 23:34:45,838] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 256.87 | bwd_microstep: 466.85 | bwd_inner_microstep: 466.83 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-01 23:34:46,709] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 214.12 | bwd_microstep: 623.03 | bwd_inner_microstep: 623.01 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-01 23:34:47,578] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 223.90 | bwd_microstep: 611.10 | bwd_inner_microstep: 611.08 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.53 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-01 23:34:48,444] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 244.65 | bwd_microstep: 586.95 | bwd_inner_microstep: 586.93 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 23:34:49,303] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 269.59 | bwd_microstep: 556.78 | bwd_inner_microstep: 556.76 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.49 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 23:34:50,171] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 299.63 | bwd_microstep: 536.73 | bwd_inner_microstep: 536.71 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 23:34:51,044] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 320.35 | bwd_microstep: 520.20 | bwd_inner_microstep: 520.18 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 834 +[2025-05-01 23:34:51,441] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 213.37 | bwd_microstep: 156.04 | bwd_inner_microstep: 155.88 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.22 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-01 23:34:52,358] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 361.49 | bwd_microstep: 538.21 | bwd_inner_microstep: 538.19 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 23:34:53,278] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 339.45 | bwd_microstep: 561.32 | bwd_inner_microstep: 561.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 321 +[2025-05-01 23:34:53,502] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 75.55 | bwd_microstep: 131.19 | bwd_inner_microstep: 131.17 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 23:34:54,365] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 417.28 | bwd_microstep: 413.09 | bwd_inner_microstep: 413.08 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 23:34:55,227] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 421.47 | bwd_microstep: 408.34 | bwd_inner_microstep: 408.32 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 23:34:56,660] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.29 | optimizer_step: 23.05 +[2025-05-01 23:34:56,661] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 418.29 | bwd_microstep: 949.64 | bwd_inner_microstep: 423.17 | bwd_allreduce_microstep: 526.42 | step_microstep: 32.00 +[2025-05-01 23:34:56,662] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4900.10 | bwd: 8048.11 | bwd_inner: 7521.06 | bwd_allreduce: 526.62 | step: 56.56 + 6%|▌ | 508/8720 [1:19:30<30:36:31, 13.42s/it] {'loss': 1.6267, 'grad_norm': 7.347454071044922, 'learning_rate': 9.979142011429694e-06, 'epoch': 0.58} + 6%|▌ | 508/8720 [1:19:30<30:36:31, 13.42s/it]dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1150 +[2025-05-01 23:34:57,307] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 251.70 | bwd_microstep: 371.57 | bwd_inner_microstep: 371.56 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.46 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1893 +[2025-05-01 23:34:58,186] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 242.93 | bwd_microstep: 604.38 | bwd_inner_microstep: 604.36 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 860 +[2025-05-01 23:34:58,537] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 161.80 | bwd_microstep: 159.33 | bwd_inner_microstep: 159.31 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1886 +[2025-05-01 23:34:59,417] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 422.07 | bwd_microstep: 425.45 | bwd_inner_microstep: 425.43 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1366 +[2025-05-01 23:35:00,180] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 313.26 | bwd_microstep: 422.00 | bwd_inner_microstep: 421.98 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-01 23:35:01,097] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 295.84 | bwd_microstep: 603.05 | bwd_inner_microstep: 603.04 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-01 23:35:01,999] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 252.47 | bwd_microstep: 627.77 | bwd_inner_microstep: 627.75 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 23:35:02,873] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 223.46 | bwd_microstep: 623.92 | bwd_inner_microstep: 623.90 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 328 +[2025-05-01 23:35:03,138] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 101.36 | bwd_microstep: 129.72 | bwd_inner_microstep: 129.70 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.33 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 837 +[2025-05-01 23:35:03,672] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 202.21 | bwd_microstep: 297.85 | bwd_inner_microstep: 297.83 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.48 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 23:35:04,537] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 230.73 | bwd_microstep: 597.83 | bwd_inner_microstep: 597.81 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 23:35:05,297] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 251.84 | bwd_microstep: 471.19 | bwd_inner_microstep: 471.17 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.53 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 23:35:06,171] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 390.01 | bwd_microstep: 451.92 | bwd_inner_microstep: 451.90 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 321 +[2025-05-01 23:35:06,440] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 101.73 | bwd_microstep: 137.64 | bwd_inner_microstep: 137.62 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 23:35:07,300] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 228.53 | bwd_microstep: 599.46 | bwd_inner_microstep: 599.44 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 23:35:08,457] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.07 | optimizer_gradients: 4.03 | optimizer_step: 22.27 +[2025-05-01 23:35:08,458] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 254.33 | bwd_microstep: 838.60 | bwd_inner_microstep: 574.86 | bwd_allreduce_microstep: 263.68 | step_microstep: 34.67 +[2025-05-01 23:35:08,459] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 3924.19 | bwd: 7361.71 | bwd_inner: 7097.69 | bwd_allreduce: 263.77 | step: 65.66 + 6%|▌ | 509/8720 [1:19:42<29:29:44, 12.93s/it] {'loss': 1.3642, 'grad_norm': 6.044901371002197, 'learning_rate': 9.97897220882043e-06, 'epoch': 0.58} + 6%|▌ | 509/8720 [1:19:42<29:29:44, 12.93s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2136 +[2025-05-01 23:35:09,467] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 456.57 | bwd_microstep: 512.88 | bwd_inner_microstep: 512.86 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.44 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1893 +[2025-05-01 23:35:10,348] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 421.23 | bwd_microstep: 426.77 | bwd_inner_microstep: 426.75 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1927 +[2025-05-01 23:35:11,276] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 444.00 | bwd_microstep: 452.28 | bwd_inner_microstep: 452.26 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-01 23:35:12,155] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 423.40 | bwd_microstep: 423.46 | bwd_inner_microstep: 423.44 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.30 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-01 23:35:13,036] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 426.42 | bwd_microstep: 422.40 | bwd_inner_microstep: 422.38 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-01 23:35:13,916] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 423.08 | bwd_microstep: 424.06 | bwd_inner_microstep: 424.04 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.49 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-01 23:35:14,787] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 419.94 | bwd_microstep: 417.85 | bwd_inner_microstep: 417.83 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-01 23:35:15,663] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 421.61 | bwd_microstep: 421.11 | bwd_inner_microstep: 421.09 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.20 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 326 +[2025-05-01 23:35:15,964] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 113.87 | bwd_microstep: 155.95 | bwd_inner_microstep: 155.93 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.52 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-01 23:35:16,840] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 365.20 | bwd_microstep: 475.04 | bwd_inner_microstep: 475.02 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.31 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 23:35:17,712] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 383.01 | bwd_microstep: 457.00 | bwd_inner_microstep: 456.98 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.49 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-01 23:35:18,583] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 399.97 | bwd_microstep: 440.73 | bwd_inner_microstep: 440.71 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1089 +[2025-05-01 23:35:19,118] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 264.11 | bwd_microstep: 244.37 | bwd_inner_microstep: 244.18 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 23:35:20,027] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 354.41 | bwd_microstep: 538.64 | bwd_inner_microstep: 538.62 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 23:35:20,940] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 324.89 | bwd_microstep: 569.38 | bwd_inner_microstep: 569.37 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1850 +[2025-05-01 23:35:22,026] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.07 | optimizer_gradients: 3.49 | optimizer_step: 16.62 +[2025-05-01 23:35:22,028] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 280.08 | bwd_microstep: 760.77 | bwd_inner_microstep: 604.08 | bwd_allreduce_microstep: 156.64 | step_microstep: 27.89 +[2025-05-01 23:35:22,029] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 5921.69 | bwd: 7142.71 | bwd_inner: 6985.61 | bwd_allreduce: 156.79 | step: 52.45 + 6%|▌ | 510/8720 [1:19:55<29:55:49, 13.12s/it] {'loss': 1.361, 'grad_norm': 5.063836574554443, 'learning_rate': 9.978801719294456e-06, 'epoch': 0.58} + 6%|▌ | 510/8720 [1:19:55<29:55:49, 13.12s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1953 +[2025-05-01 23:35:22,966] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 444.86 | bwd_microstep: 449.92 | bwd_inner_microstep: 449.90 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1931 +[2025-05-01 23:35:23,900] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 446.61 | bwd_microstep: 452.71 | bwd_inner_microstep: 452.69 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.51 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 368 +[2025-05-01 23:35:24,174] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 108.65 | bwd_microstep: 135.33 | bwd_inner_microstep: 135.31 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.31 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-01 23:35:25,054] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 358.49 | bwd_microstep: 485.79 | bwd_inner_microstep: 485.77 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.32 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-01 23:35:25,934] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 369.17 | bwd_microstep: 474.79 | bwd_inner_microstep: 474.76 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1358 +[2025-05-01 23:35:26,559] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 325.48 | bwd_microstep: 268.64 | bwd_inner_microstep: 268.62 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 23:35:27,433] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 423.57 | bwd_microstep: 418.18 | bwd_inner_microstep: 418.15 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-01 23:35:28,304] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 423.01 | bwd_microstep: 416.35 | bwd_inner_microstep: 416.33 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-01 23:35:29,180] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 421.95 | bwd_microstep: 423.96 | bwd_inner_microstep: 423.94 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 839 +[2025-05-01 23:35:29,689] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 212.15 | bwd_microstep: 279.12 | bwd_inner_microstep: 279.10 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.32 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:35:30,558] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 291.02 | bwd_microstep: 546.00 | bwd_inner_microstep: 545.98 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.30 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 23:35:31,430] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 313.26 | bwd_microstep: 526.78 | bwd_inner_microstep: 526.76 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.30 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 23:35:32,290] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 329.18 | bwd_microstep: 499.14 | bwd_inner_microstep: 499.12 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 23:35:33,157] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 352.75 | bwd_microstep: 482.22 | bwd_inner_microstep: 482.20 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 23:35:34,020] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 374.80 | bwd_microstep: 455.90 | bwd_inner_microstep: 455.88 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 23:35:35,290] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.31 | optimizer_step: 16.82 +[2025-05-01 23:35:35,291] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 396.85 | bwd_microstep: 817.77 | bwd_inner_microstep: 441.71 | bwd_allreduce_microstep: 376.01 | step_microstep: 24.30 +[2025-05-01 23:35:35,292] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 5591.78 | bwd: 7132.59 | bwd_inner: 6756.26 | bwd_allreduce: 376.10 | step: 57.18 + 6%|▌ | 511/8720 [1:20:09<30:01:10, 13.16s/it] {'loss': 0.739, 'grad_norm': 4.027556896209717, 'learning_rate': 9.978630542875293e-06, 'epoch': 0.59} + 6%|▌ | 511/8720 [1:20:09<30:01:10, 13.16s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2067 +[2025-05-01 23:35:36,252] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 406.65 | bwd_microstep: 533.60 | bwd_inner_microstep: 533.58 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 347 +[2025-05-01 23:35:36,497] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 85.10 | bwd_microstep: 143.70 | bwd_inner_microstep: 143.68 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.28 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-01 23:35:37,375] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 422.14 | bwd_microstep: 423.85 | bwd_inner_microstep: 423.83 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-01 23:35:38,307] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 427.24 | bwd_microstep: 472.85 | bwd_inner_microstep: 472.83 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-01 23:35:39,157] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 328.82 | bwd_microstep: 501.66 | bwd_inner_microstep: 501.64 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-01 23:35:39,959] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 326.66 | bwd_microstep: 443.27 | bwd_inner_microstep: 443.25 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.30 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1356 +[2025-05-01 23:35:40,593] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 243.17 | bwd_microstep: 361.06 | bwd_inner_microstep: 361.04 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.48 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-01 23:35:41,451] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 328.98 | bwd_microstep: 498.39 | bwd_inner_microstep: 498.37 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 321 +[2025-05-01 23:35:41,676] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 80.74 | bwd_microstep: 126.57 | bwd_inner_microstep: 126.56 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 23:35:42,491] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 331.50 | bwd_microstep: 454.71 | bwd_inner_microstep: 454.69 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1346 +[2025-05-01 23:35:43,126] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 246.34 | bwd_microstep: 367.27 | bwd_inner_microstep: 367.08 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 23:35:43,953] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 329.14 | bwd_microstep: 471.82 | bwd_inner_microstep: 471.81 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 23:35:44,811] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 327.36 | bwd_microstep: 510.59 | bwd_inner_microstep: 510.57 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 23:35:45,619] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 326.17 | bwd_microstep: 448.43 | bwd_inner_microstep: 448.41 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.51 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 23:35:46,466] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 321.07 | bwd_microstep: 498.07 | bwd_inner_microstep: 498.05 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1923 +[2025-05-01 23:35:47,565] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.32 | optimizer_step: 25.00 +[2025-05-01 23:35:47,566] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 334.77 | bwd_microstep: 712.73 | bwd_inner_microstep: 518.46 | bwd_allreduce_microstep: 194.26 | step_microstep: 34.49 +[2025-05-01 23:35:47,568] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4865.75 | bwd: 6968.57 | bwd_inner: 6773.87 | bwd_allreduce: 194.50 | step: 56.18 + 6%|▌ | 512/8720 [1:20:21<29:24:33, 12.90s/it] {'loss': 1.4814, 'grad_norm': 6.168867111206055, 'learning_rate': 9.97845867958656e-06, 'epoch': 0.59} + 6%|▌ | 512/8720 [1:20:21<29:24:33, 12.90s/it]dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1427 +[2025-05-01 23:35:48,219] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 236.54 | bwd_microstep: 391.19 | bwd_inner_microstep: 391.00 | bwd_allreduce_microstep: 0.18 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1905 +[2025-05-01 23:35:49,030] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 333.57 | bwd_microstep: 458.55 | bwd_inner_microstep: 458.53 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 362 +[2025-05-01 23:35:49,285] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 100.29 | bwd_microstep: 122.56 | bwd_inner_microstep: 122.54 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.50 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-01 23:35:50,131] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 325.94 | bwd_microstep: 498.33 | bwd_inner_microstep: 498.32 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1110 +[2025-05-01 23:35:50,640] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 214.00 | bwd_microstep: 277.90 | bwd_inner_microstep: 277.88 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.33 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 23:35:51,439] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 327.22 | bwd_microstep: 442.22 | bwd_inner_microstep: 442.20 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.22 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 325 +[2025-05-01 23:35:51,675] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 99.26 | bwd_microstep: 109.56 | bwd_inner_microstep: 109.33 | bwd_allreduce_microstep: 0.09 | step_microstep: 0.09 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 321 +[2025-05-01 23:35:51,898] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 84.38 | bwd_microstep: 121.59 | bwd_inner_microstep: 121.57 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1351 +[2025-05-01 23:35:52,522] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 219.13 | bwd_microstep: 374.33 | bwd_inner_microstep: 374.31 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.33 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-01 23:35:53,347] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 333.41 | bwd_microstep: 455.52 | bwd_inner_microstep: 455.50 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.49 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 23:35:54,183] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 326.33 | bwd_microstep: 474.71 | bwd_inner_microstep: 474.69 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 23:35:55,029] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 329.46 | bwd_microstep: 496.95 | bwd_inner_microstep: 496.93 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 23:35:55,833] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 327.59 | bwd_microstep: 441.74 | bwd_inner_microstep: 441.72 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.52 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 23:35:56,691] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 328.55 | bwd_microstep: 497.46 | bwd_inner_microstep: 497.44 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.87 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 23:35:57,500] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 326.79 | bwd_microstep: 465.51 | bwd_inner_microstep: 465.49 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 23:35:58,572] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 4.44 | optimizer_step: 24.57 +[2025-05-01 23:35:58,573] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 326.38 | bwd_microstep: 686.04 | bwd_inner_microstep: 471.46 | bwd_allreduce_microstep: 214.54 | step_microstep: 34.34 +[2025-05-01 23:35:58,574] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4238.75 | bwd: 6314.20 | bwd_inner: 6098.99 | bwd_allreduce: 214.87 | step: 55.25 + 6%|▌ | 513/8720 [1:20:32<28:06:44, 12.33s/it] {'loss': 0.8753, 'grad_norm': 2.934136390686035, 'learning_rate': 9.978286129451965e-06, 'epoch': 0.59} + 6%|▌ | 513/8720 [1:20:32<28:06:44, 12.33s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1934 +[2025-05-01 23:35:59,439] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 345.14 | bwd_microstep: 491.37 | bwd_inner_microstep: 491.35 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1935 +[2025-05-01 23:36:00,338] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 353.86 | bwd_microstep: 528.91 | bwd_inner_microstep: 528.89 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1883 +[2025-05-01 23:36:01,152] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 330.24 | bwd_microstep: 465.21 | bwd_inner_microstep: 465.19 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.30 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-01 23:36:01,988] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 334.79 | bwd_microstep: 472.45 | bwd_inner_microstep: 472.43 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-01 23:36:02,860] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 338.03 | bwd_microstep: 514.53 | bwd_inner_microstep: 514.52 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-01 23:36:03,664] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 326.50 | bwd_microstep: 454.80 | bwd_inner_microstep: 454.79 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.32 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-01 23:36:04,515] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 325.90 | bwd_microstep: 499.09 | bwd_inner_microstep: 499.07 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:36:05,354] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 328.08 | bwd_microstep: 493.39 | bwd_inner_microstep: 493.38 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 23:36:06,173] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 331.53 | bwd_microstep: 452.86 | bwd_inner_microstep: 452.84 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.51 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 23:36:07,030] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 327.81 | bwd_microstep: 498.17 | bwd_inner_microstep: 498.15 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 23:36:07,854] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 327.92 | bwd_microstep: 472.96 | bwd_inner_microstep: 472.94 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.28 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-01 23:36:08,670] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 329.82 | bwd_microstep: 454.71 | bwd_inner_microstep: 454.69 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 23:36:09,539] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 332.88 | bwd_microstep: 507.33 | bwd_inner_microstep: 507.32 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.70 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 23:36:10,344] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 328.25 | bwd_microstep: 457.78 | bwd_inner_microstep: 457.76 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 907 +[2025-05-01 23:36:10,815] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 163.42 | bwd_microstep: 279.80 | bwd_inner_microstep: 279.62 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1921 +[2025-05-01 23:36:11,945] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.27 | optimizer_step: 16.60 +[2025-05-01 23:36:11,945] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 335.66 | bwd_microstep: 752.13 | bwd_inner_microstep: 527.93 | bwd_allreduce_microstep: 224.19 | step_microstep: 24.27 +[2025-05-01 23:36:11,946] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 5159.77 | bwd: 7795.52 | bwd_inner: 7570.88 | bwd_allreduce: 224.34 | step: 42.83 + 6%|▌ | 514/8720 [1:20:45<28:49:05, 12.64s/it] {'loss': 1.1403, 'grad_norm': 5.264055252075195, 'learning_rate': 9.978112892495313e-06, 'epoch': 0.59} + 6%|▌ | 514/8720 [1:20:45<28:49:05, 12.64s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1988 +[2025-05-01 23:36:12,831] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 337.66 | bwd_microstep: 523.85 | bwd_inner_microstep: 523.83 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1934 +[2025-05-01 23:36:13,693] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 349.19 | bwd_microstep: 482.93 | bwd_inner_microstep: 482.91 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.21 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1899 +[2025-05-01 23:36:14,527] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 336.46 | bwd_microstep: 471.46 | bwd_inner_microstep: 471.44 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1888 +[2025-05-01 23:36:15,405] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 334.52 | bwd_microstep: 521.88 | bwd_inner_microstep: 521.86 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 849 +[2025-05-01 23:36:15,793] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 136.96 | bwd_microstep: 232.13 | bwd_inner_microstep: 231.89 | bwd_allreduce_microstep: 0.22 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-01 23:36:16,650] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 326.31 | bwd_microstep: 510.89 | bwd_inner_microstep: 510.87 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-01 23:36:17,465] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 327.14 | bwd_microstep: 456.50 | bwd_inner_microstep: 456.48 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 836 +[2025-05-01 23:36:17,908] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 166.69 | bwd_microstep: 247.72 | bwd_inner_microstep: 247.70 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 23:36:18,717] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 327.30 | bwd_microstep: 459.28 | bwd_inner_microstep: 459.26 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1343 +[2025-05-01 23:36:19,343] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 239.42 | bwd_microstep: 356.78 | bwd_inner_microstep: 356.77 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 23:36:20,228] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 366.52 | bwd_microstep: 483.79 | bwd_inner_microstep: 483.77 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 23:36:21,180] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 444.15 | bwd_microstep: 484.23 | bwd_inner_microstep: 484.21 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1086 +[2025-05-01 23:36:21,714] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 245.85 | bwd_microstep: 262.86 | bwd_inner_microstep: 262.66 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.18 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 315 +[2025-05-01 23:36:21,955] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.76 | bwd_microstep: 121.56 | bwd_inner_microstep: 121.54 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.41 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 23:36:22,760] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 295.34 | bwd_microstep: 491.69 | bwd_inner_microstep: 491.67 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.50 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 23:36:24,277] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 3.46 | optimizer_step: 17.70 +[2025-05-01 23:36:24,279] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 360.97 | bwd_microstep: 1101.67 | bwd_inner_microstep: 482.72 | bwd_allreduce_microstep: 618.94 | step_microstep: 28.37 +[2025-05-01 23:36:24,280] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4689.19 | bwd: 7209.21 | bwd_inner: 6589.61 | bwd_allreduce: 619.21 | step: 50.78 + 6%|▌ | 515/8720 [1:20:58<28:36:19, 12.55s/it] {'loss': 1.3526, 'grad_norm': 5.664745330810547, 'learning_rate': 9.977938968740505e-06, 'epoch': 0.59} + 6%|▌ | 515/8720 [1:20:58<28:36:19, 12.55s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2001 +[2025-05-01 23:36:25,192] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 327.05 | bwd_microstep: 542.48 | bwd_inner_microstep: 542.46 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1892 +[2025-05-01 23:36:26,120] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 358.71 | bwd_microstep: 538.53 | bwd_inner_microstep: 538.51 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 351 +[2025-05-01 23:36:26,366] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 86.71 | bwd_microstep: 142.52 | bwd_inner_microstep: 142.50 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-01 23:36:27,263] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 325.34 | bwd_microstep: 543.55 | bwd_inner_microstep: 543.54 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-01 23:36:28,160] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 383.95 | bwd_microstep: 492.43 | bwd_inner_microstep: 492.41 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.49 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-01 23:36:29,002] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 302.97 | bwd_microstep: 508.99 | bwd_inner_microstep: 508.98 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.22 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-01 23:36:29,920] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 411.17 | bwd_microstep: 489.41 | bwd_inner_microstep: 489.39 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:36:30,737] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 304.88 | bwd_microstep: 482.03 | bwd_inner_microstep: 482.02 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 333 +[2025-05-01 23:36:30,980] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 82.40 | bwd_microstep: 143.06 | bwd_inner_microstep: 143.04 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.30 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 23:36:31,947] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 427.47 | bwd_microstep: 506.62 | bwd_inner_microstep: 506.60 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-01 23:36:32,897] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 403.24 | bwd_microstep: 515.00 | bwd_inner_microstep: 514.98 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 840 +[2025-05-01 23:36:33,289] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 100.82 | bwd_microstep: 270.22 | bwd_inner_microstep: 270.20 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-01 23:36:34,134] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 303.44 | bwd_microstep: 511.88 | bwd_inner_microstep: 511.86 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 23:36:35,056] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 411.64 | bwd_microstep: 492.06 | bwd_inner_microstep: 492.04 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 322 +[2025-05-01 23:36:35,301] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 89.03 | bwd_microstep: 124.54 | bwd_inner_microstep: 124.52 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.33 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 23:36:36,426] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.25 | optimizer_step: 16.79 +[2025-05-01 23:36:36,427] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 390.47 | bwd_microstep: 678.68 | bwd_inner_microstep: 524.19 | bwd_allreduce_microstep: 154.47 | step_microstep: 26.19 +[2025-05-01 23:36:36,428] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4708.97 | bwd: 6982.01 | bwd_inner: 6827.27 | bwd_allreduce: 154.53 | step: 50.28 + 6%|▌ | 516/8720 [1:21:10<28:19:35, 12.43s/it] {'loss': 1.304, 'grad_norm': 6.480757236480713, 'learning_rate': 9.977764358211537e-06, 'epoch': 0.59} + 6%|▌ | 516/8720 [1:21:10<28:19:35, 12.43s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1930 +[2025-05-01 23:36:37,364] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 351.62 | bwd_microstep: 551.67 | bwd_inner_microstep: 551.65 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1897 +[2025-05-01 23:36:38,275] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 388.59 | bwd_microstep: 497.98 | bwd_inner_microstep: 497.96 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.32 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-01 23:36:39,115] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 304.42 | bwd_microstep: 505.77 | bwd_inner_microstep: 505.76 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-01 23:36:40,057] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 422.14 | bwd_microstep: 500.75 | bwd_inner_microstep: 500.73 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-01 23:36:40,940] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 222.13 | bwd_microstep: 628.43 | bwd_inner_microstep: 628.41 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.54 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1361 +[2025-05-01 23:36:41,632] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 330.98 | bwd_microstep: 330.30 | bwd_inner_microstep: 330.28 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:36:42,517] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 315.82 | bwd_microstep: 539.64 | bwd_inner_microstep: 539.62 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-01 23:36:43,414] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 382.65 | bwd_microstep: 493.00 | bwd_inner_microstep: 492.99 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 837 +[2025-05-01 23:36:43,827] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 170.70 | bwd_microstep: 210.24 | bwd_inner_microstep: 210.22 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-01 23:36:44,693] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 341.86 | bwd_microstep: 501.55 | bwd_inner_microstep: 501.53 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:36:45,657] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 443.66 | bwd_microstep: 487.77 | bwd_inner_microstep: 487.75 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.33 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:36:46,515] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 310.76 | bwd_microstep: 518.10 | bwd_inner_microstep: 518.08 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 23:36:47,424] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 399.19 | bwd_microstep: 492.04 | bwd_inner_microstep: 492.02 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 23:36:48,244] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 299.55 | bwd_microstep: 489.77 | bwd_inner_microstep: 489.75 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 23:36:49,123] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 419.96 | bwd_microstep: 430.74 | bwd_inner_microstep: 430.72 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-01 23:36:50,425] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 2.33 | optimizer_gradients: 2.17 | optimizer_step: 16.74 +[2025-05-01 23:36:50,427] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 424.36 | bwd_microstep: 821.80 | bwd_inner_microstep: 498.09 | bwd_allreduce_microstep: 323.69 | step_microstep: 28.53 +[2025-05-01 23:36:50,428] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 5528.33 | bwd: 7999.55 | bwd_inner: 7675.59 | bwd_allreduce: 323.76 | step: 52.51 + 6%|▌ | 517/8720 [1:21:24<29:23:47, 12.90s/it] {'loss': 0.8846, 'grad_norm': 4.809855937957764, 'learning_rate': 9.9775890609325e-06, 'epoch': 0.59} + 6%|▌ | 517/8720 [1:21:24<29:23:47, 12.90s/it]dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 915 +[2025-05-01 23:36:50,903] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 222.79 | bwd_microstep: 211.54 | bwd_inner_microstep: 211.52 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-01 23:36:51,853] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 402.58 | bwd_microstep: 515.48 | bwd_inner_microstep: 515.47 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 23:36:52,679] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 301.49 | bwd_microstep: 501.98 | bwd_inner_microstep: 501.97 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 329 +[2025-05-01 23:36:52,945] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 96.22 | bwd_microstep: 140.47 | bwd_inner_microstep: 140.45 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 23:36:53,808] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 221.25 | bwd_microstep: 619.31 | bwd_inner_microstep: 619.29 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-01 23:36:54,750] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 374.93 | bwd_microstep: 535.78 | bwd_inner_microstep: 535.76 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.94 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:36:55,578] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 306.05 | bwd_microstep: 502.18 | bwd_inner_microstep: 502.16 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 23:36:56,444] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 342.17 | bwd_microstep: 498.53 | bwd_inner_microstep: 498.51 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.28 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 23:36:57,403] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 444.66 | bwd_microstep: 482.22 | bwd_inner_microstep: 482.21 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 23:36:58,261] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 305.46 | bwd_microstep: 523.28 | bwd_inner_microstep: 523.27 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 23:36:59,168] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 398.89 | bwd_microstep: 490.90 | bwd_inner_microstep: 490.88 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 23:36:59,991] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 300.03 | bwd_microstep: 492.62 | bwd_inner_microstep: 492.61 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 23:37:00,941] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 417.88 | bwd_microstep: 502.58 | bwd_inner_microstep: 502.56 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.49 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 23:37:01,712] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 301.98 | bwd_microstep: 438.32 | bwd_inner_microstep: 438.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-01 23:37:02,774] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 415.24 | bwd_microstep: 628.82 | bwd_inner_microstep: 628.80 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.08 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 316 +[2025-05-01 23:37:03,316] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.30 | optimizer_step: 16.67 +[2025-05-01 23:37:03,317] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 79.85 | bwd_microstep: 422.89 | bwd_inner_microstep: 138.53 | bwd_allreduce_microstep: 284.31 | step_microstep: 24.84 +[2025-05-01 23:37:03,318] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4931.41 | bwd: 7506.93 | bwd_inner: 7222.30 | bwd_allreduce: 284.39 | step: 48.66 + 6%|▌ | 518/8720 [1:21:37<29:23:00, 12.90s/it] {'loss': 0.8572, 'grad_norm': 5.86330509185791, 'learning_rate': 9.977413076927577e-06, 'epoch': 0.59} + 6%|▌ | 518/8720 [1:21:37<29:23:00, 12.90s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1930 +[2025-05-01 23:37:04,409] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 415.93 | bwd_microstep: 651.94 | bwd_inner_microstep: 651.92 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.52 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1925 +[2025-05-01 23:37:05,276] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 310.34 | bwd_microstep: 535.80 | bwd_inner_microstep: 535.78 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1894 +[2025-05-01 23:37:06,182] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 341.56 | bwd_microstep: 541.34 | bwd_inner_microstep: 541.32 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.21 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1886 +[2025-05-01 23:37:07,061] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 360.90 | bwd_microstep: 497.78 | bwd_inner_microstep: 497.76 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.33 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-01 23:37:07,924] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 304.49 | bwd_microstep: 526.64 | bwd_inner_microstep: 526.62 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.15 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-01 23:37:08,837] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 401.47 | bwd_microstep: 493.42 | bwd_inner_microstep: 493.40 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-01 23:37:09,660] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 301.09 | bwd_microstep: 491.74 | bwd_inner_microstep: 491.72 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-01 23:37:10,677] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 369.09 | bwd_microstep: 630.10 | bwd_inner_microstep: 630.08 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 344 +[2025-05-01 23:37:10,933] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 86.31 | bwd_microstep: 136.05 | bwd_inner_microstep: 136.04 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-01 23:37:11,866] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 367.24 | bwd_microstep: 532.34 | bwd_inner_microstep: 532.32 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.96 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-01 23:37:12,752] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 238.70 | bwd_microstep: 628.59 | bwd_inner_microstep: 628.57 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.32 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-01 23:37:13,674] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 350.36 | bwd_microstep: 540.61 | bwd_inner_microstep: 540.59 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 23:37:14,528] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 331.47 | bwd_microstep: 505.72 | bwd_inner_microstep: 505.70 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 23:37:15,417] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 321.33 | bwd_microstep: 540.17 | bwd_inner_microstep: 540.15 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 23:37:16,290] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 368.80 | bwd_microstep: 484.22 | bwd_inner_microstep: 484.20 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.53 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 23:37:17,512] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 4.74 | optimizer_step: 20.38 +[2025-05-01 23:37:17,513] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 302.55 | bwd_microstep: 859.44 | bwd_inner_microstep: 524.50 | bwd_allreduce_microstep: 334.89 | step_microstep: 30.47 +[2025-05-01 23:37:17,514] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 5171.49 | bwd: 8595.90 | bwd_inner: 8260.69 | bwd_allreduce: 334.97 | step: 51.22 + 6%|▌ | 519/8720 [1:21:51<30:16:03, 13.29s/it] {'loss': 1.3736, 'grad_norm': 5.808008193969727, 'learning_rate': 9.977236406221049e-06, 'epoch': 0.6} + 6%|▌ | 519/8720 [1:21:51<30:16:03, 13.29s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1974 +[2025-05-01 23:37:18,554] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 356.22 | bwd_microstep: 660.84 | bwd_inner_microstep: 660.82 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1898 +[2025-05-01 23:37:19,384] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 298.91 | bwd_microstep: 496.51 | bwd_inner_microstep: 496.49 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1894 +[2025-05-01 23:37:20,335] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 385.92 | bwd_microstep: 533.18 | bwd_inner_microstep: 533.16 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.95 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1895 +[2025-05-01 23:37:21,212] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 230.85 | bwd_microstep: 626.20 | bwd_inner_microstep: 626.18 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 866 +[2025-05-01 23:37:21,645] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 223.07 | bwd_microstep: 178.43 | bwd_inner_microstep: 178.16 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-01 23:37:22,656] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 362.65 | bwd_microstep: 626.83 | bwd_inner_microstep: 626.81 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.53 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 341 +[2025-05-01 23:37:22,900] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 91.53 | bwd_microstep: 125.10 | bwd_inner_microstep: 124.79 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.18 +dynamic ViT batch size: 6, images per sample: 6.0, dynamic token length: 1615 +[2025-05-01 23:37:23,835] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 356.80 | bwd_microstep: 560.47 | bwd_inner_microstep: 560.45 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-01 23:37:24,660] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 299.41 | bwd_microstep: 493.04 | bwd_inner_microstep: 493.02 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-01 23:37:25,608] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 402.89 | bwd_microstep: 510.94 | bwd_inner_microstep: 510.92 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-01 23:37:26,435] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 301.61 | bwd_microstep: 502.44 | bwd_inner_microstep: 502.42 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:37:27,356] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 349.46 | bwd_microstep: 539.46 | bwd_inner_microstep: 539.45 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-01 23:37:28,281] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 279.46 | bwd_microstep: 625.20 | bwd_inner_microstep: 625.18 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 325 +[2025-05-01 23:37:28,532] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 102.13 | bwd_microstep: 116.68 | bwd_inner_microstep: 116.39 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.11 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 831 +[2025-05-01 23:37:28,951] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 115.43 | bwd_microstep: 287.06 | bwd_inner_microstep: 287.04 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-01 23:37:30,130] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.20 | optimizer_step: 16.61 +[2025-05-01 23:37:30,131] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 300.99 | bwd_microstep: 822.40 | bwd_inner_microstep: 492.07 | bwd_allreduce_microstep: 330.28 | step_microstep: 24.31 +[2025-05-01 23:37:30,132] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4457.24 | bwd: 7704.85 | bwd_inner: 7373.53 | bwd_allreduce: 330.72 | step: 49.33 + 6%|▌ | 520/8720 [1:22:03<29:48:25, 13.09s/it] {'loss': 1.3544, 'grad_norm': 3.8188154697418213, 'learning_rate': 9.977059048837288e-06, 'epoch': 0.6} + 6%|▌ | 520/8720 [1:22:03<29:48:25, 13.09s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2033 +[2025-05-01 23:37:31,245] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 420.59 | bwd_microstep: 670.46 | bwd_inner_microstep: 670.44 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.27 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1890 +[2025-05-01 23:37:32,112] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 220.35 | bwd_microstep: 626.54 | bwd_inner_microstep: 626.53 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.44 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 860 +[2025-05-01 23:37:32,555] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 225.15 | bwd_microstep: 189.95 | bwd_inner_microstep: 189.77 | bwd_allreduce_microstep: 0.09 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-01 23:37:33,546] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 339.23 | bwd_microstep: 629.73 | bwd_inner_microstep: 629.71 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.45 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1370 +[2025-05-01 23:37:34,155] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 206.93 | bwd_microstep: 371.11 | bwd_inner_microstep: 371.09 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 23:37:35,055] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 427.13 | bwd_microstep: 443.18 | bwd_inner_microstep: 443.16 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1349 +[2025-05-01 23:37:35,452] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.92 | bwd_microstep: 239.30 | bwd_inner_microstep: 239.28 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.53 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 23:37:36,473] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 422.22 | bwd_microstep: 568.30 | bwd_inner_microstep: 568.29 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 23:37:37,291] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 371.49 | bwd_microstep: 425.80 | bwd_inner_microstep: 425.78 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.31 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:37:38,284] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 428.00 | bwd_microstep: 535.07 | bwd_inner_microstep: 535.05 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 23:37:39,193] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 396.42 | bwd_microstep: 493.11 | bwd_inner_microstep: 493.09 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.33 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 23:37:40,017] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 304.66 | bwd_microstep: 490.05 | bwd_inner_microstep: 490.04 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 23:37:41,037] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 367.76 | bwd_microstep: 633.88 | bwd_inner_microstep: 633.86 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 23:37:41,893] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 216.59 | bwd_microstep: 605.64 | bwd_inner_microstep: 605.63 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.43 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 23:37:42,768] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 417.87 | bwd_microstep: 424.85 | bwd_inner_microstep: 424.84 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 23:37:44,065] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.20 | optimizer_step: 18.85 +[2025-05-01 23:37:44,067] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 425.03 | bwd_microstep: 816.07 | bwd_inner_microstep: 497.50 | bwd_allreduce_microstep: 318.55 | step_microstep: 28.15 +[2025-05-01 23:37:44,068] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 5330.21 | bwd: 8163.11 | bwd_inner: 7844.09 | bwd_allreduce: 318.73 | step: 51.43 + 6%|▌ | 521/8720 [1:22:17<30:23:10, 13.34s/it] {'loss': 0.716, 'grad_norm': 3.3727025985717773, 'learning_rate': 9.976881004800763e-06, 'epoch': 0.6} + 6%|▌ | 521/8720 [1:22:17<30:23:10, 13.34s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1894 +[2025-05-01 23:37:45,017] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 365.43 | bwd_microstep: 542.97 | bwd_inner_microstep: 542.95 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1890 +[2025-05-01 23:37:45,869] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 319.13 | bwd_microstep: 513.39 | bwd_inner_microstep: 513.37 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1889 +[2025-05-01 23:37:46,756] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 322.53 | bwd_microstep: 536.64 | bwd_inner_microstep: 536.62 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-01 23:37:47,648] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 374.94 | bwd_microstep: 496.21 | bwd_inner_microstep: 496.19 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 848 +[2025-05-01 23:37:48,083] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 182.50 | bwd_microstep: 223.29 | bwd_inner_microstep: 223.27 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1365 +[2025-05-01 23:37:48,785] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 276.09 | bwd_microstep: 394.22 | bwd_inner_microstep: 394.20 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 844 +[2025-05-01 23:37:49,197] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 136.03 | bwd_microstep: 246.60 | bwd_inner_microstep: 246.58 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.33 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-01 23:37:50,072] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 309.94 | bwd_microstep: 533.36 | bwd_inner_microstep: 533.34 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 839 +[2025-05-01 23:37:50,550] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 181.60 | bwd_microstep: 279.39 | bwd_inner_microstep: 279.37 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.54 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 23:37:51,377] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 300.37 | bwd_microstep: 506.58 | bwd_inner_microstep: 506.56 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:37:52,257] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 347.19 | bwd_microstep: 501.71 | bwd_inner_microstep: 501.69 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 23:37:53,215] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 443.94 | bwd_microstep: 483.86 | bwd_inner_microstep: 483.84 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:37:54,095] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 297.23 | bwd_microstep: 551.10 | bwd_inner_microstep: 551.08 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 23:37:55,053] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 441.54 | bwd_microstep: 481.35 | bwd_inner_microstep: 481.33 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 23:37:55,876] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 300.08 | bwd_microstep: 489.35 | bwd_inner_microstep: 489.33 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 23:37:57,004] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.24 | optimizer_step: 18.73 +[2025-05-01 23:37:57,006] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 401.96 | bwd_microstep: 668.00 | bwd_inner_microstep: 507.16 | bwd_allreduce_microstep: 160.82 | step_microstep: 28.49 +[2025-05-01 23:37:57,008] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 5000.42 | bwd: 7448.00 | bwd_inner: 7286.90 | bwd_allreduce: 160.88 | step: 54.63 + 6%|▌ | 522/8720 [1:22:30<30:06:27, 13.22s/it] {'loss': 0.9003, 'grad_norm': 3.3618528842926025, 'learning_rate': 9.976702274136038e-06, 'epoch': 0.6} + 6%|▌ | 522/8720 [1:22:30<30:06:27, 13.22s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2008 +[2025-05-01 23:37:57,957] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 353.23 | bwd_microstep: 556.19 | bwd_inner_microstep: 556.17 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 457 +[2025-05-01 23:37:58,284] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 121.29 | bwd_microstep: 176.74 | bwd_inner_microstep: 176.72 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1968 +[2025-05-01 23:37:59,157] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 309.57 | bwd_microstep: 532.63 | bwd_inner_microstep: 532.62 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1949 +[2025-05-01 23:38:00,159] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 433.36 | bwd_microstep: 541.73 | bwd_inner_microstep: 541.71 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.21 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1900 +[2025-05-01 23:38:01,001] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 300.86 | bwd_microstep: 523.87 | bwd_inner_microstep: 523.85 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.19 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1122 +[2025-05-01 23:38:01,566] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 210.58 | bwd_microstep: 324.46 | bwd_inner_microstep: 324.44 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-01 23:38:02,449] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 324.13 | bwd_microstep: 527.51 | bwd_inner_microstep: 527.49 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 326 +[2025-05-01 23:38:02,682] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 77.48 | bwd_microstep: 126.14 | bwd_inner_microstep: 126.12 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 842 +[2025-05-01 23:38:03,133] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 199.58 | bwd_microstep: 219.42 | bwd_inner_microstep: 219.40 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-01 23:38:04,003] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 329.82 | bwd_microstep: 511.06 | bwd_inner_microstep: 511.04 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.23 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 836 +[2025-05-01 23:38:04,428] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.03 | bwd_microstep: 208.98 | bwd_inner_microstep: 206.62 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:38:05,300] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 331.95 | bwd_microstep: 509.78 | bwd_inner_microstep: 509.76 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 23:38:06,157] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 333.81 | bwd_microstep: 494.70 | bwd_inner_microstep: 494.68 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 23:38:07,060] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 389.64 | bwd_microstep: 496.20 | bwd_inner_microstep: 496.19 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 23:38:07,949] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 354.10 | bwd_microstep: 517.08 | bwd_inner_microstep: 517.06 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 23:38:09,087] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.26 | optimizer_step: 16.68 +[2025-05-01 23:38:09,088] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 304.50 | bwd_microstep: 791.48 | bwd_inner_microstep: 485.33 | bwd_allreduce_microstep: 306.14 | step_microstep: 26.09 +[2025-05-01 23:38:09,089] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4559.85 | bwd: 7057.98 | bwd_inner: 6749.23 | bwd_allreduce: 308.54 | step: 43.63 + 6%|▌ | 523/8720 [1:22:42<29:19:30, 12.88s/it] {'loss': 1.1558, 'grad_norm': 6.322717666625977, 'learning_rate': 9.976522856867773e-06, 'epoch': 0.6} + 6%|▌ | 523/8720 [1:22:42<29:19:30, 12.88s/it]dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 865 +[2025-05-01 23:38:09,546] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 213.99 | bwd_microstep: 213.05 | bwd_inner_microstep: 212.84 | bwd_allreduce_microstep: 0.19 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1891 +[2025-05-01 23:38:10,423] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 333.93 | bwd_microstep: 512.98 | bwd_inner_microstep: 512.97 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-01 23:38:11,304] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 338.00 | bwd_microstep: 517.34 | bwd_inner_microstep: 517.32 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1117 +[2025-05-01 23:38:11,812] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 215.43 | bwd_microstep: 266.75 | bwd_inner_microstep: 266.73 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.32 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-01 23:38:12,708] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 336.22 | bwd_microstep: 526.49 | bwd_inner_microstep: 526.48 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.51 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-01 23:38:13,587] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 334.78 | bwd_microstep: 516.50 | bwd_inner_microstep: 516.48 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 23:38:14,453] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 334.65 | bwd_microstep: 500.94 | bwd_inner_microstep: 500.92 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 332 +[2025-05-01 23:38:14,678] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 83.28 | bwd_microstep: 125.76 | bwd_inner_microstep: 125.74 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.32 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 330 +[2025-05-01 23:38:14,919] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 98.85 | bwd_microstep: 111.74 | bwd_inner_microstep: 111.72 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.49 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 23:38:15,786] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 346.11 | bwd_microstep: 489.28 | bwd_inner_microstep: 489.26 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.28 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 23:38:16,661] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 355.80 | bwd_microstep: 484.89 | bwd_inner_microstep: 484.87 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1090 +[2025-05-01 23:38:17,224] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 262.65 | bwd_microstep: 276.94 | bwd_inner_microstep: 276.71 | bwd_allreduce_microstep: 0.22 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 23:38:18,082] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 335.31 | bwd_microstep: 495.59 | bwd_inner_microstep: 495.57 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 23:38:18,983] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 385.78 | bwd_microstep: 496.75 | bwd_inner_microstep: 496.74 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1286 +[2025-05-01 23:38:19,588] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 220.86 | bwd_microstep: 366.16 | bwd_inner_microstep: 366.15 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1972 +[2025-05-01 23:38:20,857] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.28 | optimizer_step: 18.79 +[2025-05-01 23:38:20,860] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 354.15 | bwd_microstep: 859.98 | bwd_inner_microstep: 553.00 | bwd_allreduce_microstep: 306.97 | step_microstep: 28.53 +[2025-05-01 23:38:20,861] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4549.76 | bwd: 6761.15 | bwd_inner: 6453.50 | bwd_allreduce: 307.44 | step: 48.20 + 6%|▌ | 524/8720 [1:22:54<28:33:55, 12.55s/it] {'loss': 1.2643, 'grad_norm': 4.946002006530762, 'learning_rate': 9.97634275302072e-06, 'epoch': 0.6} + 6%|▌ | 524/8720 [1:22:54<28:33:55, 12.55s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2092 +[2025-05-01 23:38:21,791] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 305.65 | bwd_microstep: 582.70 | bwd_inner_microstep: 582.68 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1919 +[2025-05-01 23:38:22,693] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 348.33 | bwd_microstep: 520.39 | bwd_inner_microstep: 520.37 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.33 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1905 +[2025-05-01 23:38:23,526] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 304.11 | bwd_microstep: 512.71 | bwd_inner_microstep: 512.70 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 337 +[2025-05-01 23:38:23,767] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 99.99 | bwd_microstep: 111.79 | bwd_inner_microstep: 111.44 | bwd_allreduce_microstep: 0.14 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1887 +[2025-05-01 23:38:24,670] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 394.67 | bwd_microstep: 492.16 | bwd_inner_microstep: 492.14 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 841 +[2025-05-01 23:38:25,119] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 171.40 | bwd_microstep: 263.06 | bwd_inner_microstep: 262.81 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.21 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1349 +[2025-05-01 23:38:25,770] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 255.55 | bwd_microstep: 378.06 | bwd_inner_microstep: 377.82 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 23:38:26,646] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 334.84 | bwd_microstep: 510.44 | bwd_inner_microstep: 510.42 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 23:38:27,520] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 334.78 | bwd_microstep: 511.53 | bwd_inner_microstep: 511.51 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 23:38:28,395] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 333.55 | bwd_microstep: 514.47 | bwd_inner_microstep: 514.45 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.23 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 323 +[2025-05-01 23:38:28,630] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 101.40 | bwd_microstep: 104.93 | bwd_inner_microstep: 104.66 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 23:38:29,532] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 388.56 | bwd_microstep: 497.16 | bwd_inner_microstep: 497.14 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 23:38:30,373] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 300.31 | bwd_microstep: 520.65 | bwd_inner_microstep: 520.63 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.32 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-01 23:38:31,258] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 322.06 | bwd_microstep: 530.64 | bwd_inner_microstep: 530.62 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.56 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 23:38:32,127] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 336.40 | bwd_microstep: 514.33 | bwd_inner_microstep: 514.31 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.49 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 23:38:33,274] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.32 | optimizer_step: 18.70 +[2025-05-01 23:38:33,277] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 320.14 | bwd_microstep: 771.98 | bwd_inner_microstep: 526.16 | bwd_allreduce_microstep: 245.80 | step_microstep: 28.33 +[2025-05-01 23:38:33,278] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4651.62 | bwd: 7337.10 | bwd_inner: 7090.00 | bwd_allreduce: 246.45 | step: 38.99 + 6%|▌ | 525/8720 [1:23:07<28:28:23, 12.51s/it] {'loss': 1.2075, 'grad_norm': 4.652669429779053, 'learning_rate': 9.976161962619725e-06, 'epoch': 0.6} + 6%|▌ | 525/8720 [1:23:07<28:28:23, 12.51s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 360 +[2025-05-01 23:38:33,529] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 74.55 | bwd_microstep: 137.20 | bwd_inner_microstep: 137.16 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.78 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-01 23:38:34,411] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 337.13 | bwd_microstep: 517.40 | bwd_inner_microstep: 517.38 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-01 23:38:35,294] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 345.13 | bwd_microstep: 510.44 | bwd_inner_microstep: 510.43 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 327 +[2025-05-01 23:38:35,525] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 99.45 | bwd_microstep: 105.63 | bwd_inner_microstep: 105.48 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 23:38:36,432] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 390.16 | bwd_microstep: 499.27 | bwd_inner_microstep: 499.25 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-01 23:38:37,326] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 360.56 | bwd_microstep: 514.53 | bwd_inner_microstep: 514.51 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.87 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 322 +[2025-05-01 23:38:37,548] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 73.70 | bwd_microstep: 132.74 | bwd_inner_microstep: 132.72 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.18 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 326 +[2025-05-01 23:38:37,786] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 99.46 | bwd_microstep: 113.23 | bwd_inner_microstep: 112.90 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1089 +[2025-05-01 23:38:38,305] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 223.84 | bwd_microstep: 274.47 | bwd_inner_microstep: 274.45 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.49 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 23:38:39,204] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 350.57 | bwd_microstep: 514.75 | bwd_inner_microstep: 514.73 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:38:40,077] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 318.13 | bwd_microstep: 520.99 | bwd_inner_microstep: 520.97 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.49 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 320 +[2025-05-01 23:38:40,328] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 86.74 | bwd_microstep: 131.92 | bwd_inner_microstep: 131.90 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.49 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 23:38:41,210] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 337.00 | bwd_microstep: 514.81 | bwd_inner_microstep: 514.79 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.98 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 827 +[2025-05-01 23:38:41,652] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 151.67 | bwd_microstep: 274.51 | bwd_inner_microstep: 274.49 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.25 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1914 +[2025-05-01 23:38:42,544] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 343.23 | bwd_microstep: 530.56 | bwd_inner_microstep: 530.54 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.58 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1887 +[2025-05-01 23:38:43,693] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.36 | optimizer_step: 17.88 +[2025-05-01 23:38:43,694] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 328.53 | bwd_microstep: 777.49 | bwd_inner_microstep: 522.91 | bwd_allreduce_microstep: 254.52 | step_microstep: 26.91 +[2025-05-01 23:38:43,696] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 3919.74 | bwd: 6069.96 | bwd_inner: 5814.72 | bwd_allreduce: 254.78 | step: 42.94 + 6%|▌ | 526/8720 [1:23:17<27:02:32, 11.88s/it] {'loss': 1.0003, 'grad_norm': 4.906101703643799, 'learning_rate': 9.975980485689733e-06, 'epoch': 0.6} + 6%|▌ | 526/8720 [1:23:17<27:02:32, 11.88s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1897 +[2025-05-01 23:38:44,613] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 359.67 | bwd_microstep: 515.27 | bwd_inner_microstep: 515.25 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1905 +[2025-05-01 23:38:45,492] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 329.85 | bwd_microstep: 525.72 | bwd_inner_microstep: 525.70 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.31 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 358 +[2025-05-01 23:38:45,729] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 72.72 | bwd_microstep: 136.61 | bwd_inner_microstep: 136.60 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.12 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 346 +[2025-05-01 23:38:45,961] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 100.81 | bwd_microstep: 105.79 | bwd_inner_microstep: 105.48 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-01 23:38:46,823] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 385.53 | bwd_microstep: 452.75 | bwd_inner_microstep: 452.73 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.44 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-01 23:38:47,696] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 328.85 | bwd_microstep: 510.14 | bwd_inner_microstep: 510.12 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-01 23:38:48,528] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 317.26 | bwd_microstep: 483.81 | bwd_inner_microstep: 483.80 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 326 +[2025-05-01 23:38:48,770] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 100.53 | bwd_microstep: 122.32 | bwd_inner_microstep: 122.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.50 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 835 +[2025-05-01 23:38:49,194] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 134.15 | bwd_microstep: 256.45 | bwd_inner_microstep: 256.41 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 321 +[2025-05-01 23:38:49,463] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.14 | bwd_microstep: 139.35 | bwd_inner_microstep: 139.33 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 23:38:50,329] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 332.76 | bwd_microstep: 500.34 | bwd_inner_microstep: 500.32 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 23:38:51,191] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 318.13 | bwd_microstep: 517.04 | bwd_inner_microstep: 517.02 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 319 +[2025-05-01 23:38:51,451] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 86.40 | bwd_microstep: 142.29 | bwd_inner_microstep: 142.27 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 23:38:52,326] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 326.45 | bwd_microstep: 515.88 | bwd_inner_microstep: 515.86 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-01 23:38:53,200] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 328.44 | bwd_microstep: 515.19 | bwd_inner_microstep: 515.17 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-01 23:38:54,355] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.26 | optimizer_step: 16.69 +[2025-05-01 23:38:54,356] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 333.79 | bwd_microstep: 770.19 | bwd_inner_microstep: 511.47 | bwd_allreduce_microstep: 258.70 | step_microstep: 26.10 +[2025-05-01 23:38:54,357] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 3950.43 | bwd: 6209.16 | bwd_inner: 5949.89 | bwd_allreduce: 258.88 | step: 53.50 + 6%|▌ | 527/8720 [1:23:28<26:12:23, 11.52s/it] {'loss': 0.9626, 'grad_norm': 4.915237903594971, 'learning_rate': 9.975798322255778e-06, 'epoch': 0.6} + 6%|▌ | 527/8720 [1:23:28<26:12:23, 11.52s/it]dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 993 +[2025-05-01 23:38:54,870] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 216.72 | bwd_microstep: 265.91 | bwd_inner_microstep: 265.89 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.50 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 388 +[2025-05-01 23:38:55,129] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 102.04 | bwd_microstep: 127.84 | bwd_inner_microstep: 127.83 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1889 +[2025-05-01 23:38:56,007] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 323.40 | bwd_microstep: 521.74 | bwd_inner_microstep: 521.72 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-01 23:38:56,899] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 329.82 | bwd_microstep: 532.26 | bwd_inner_microstep: 532.24 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.60 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 852 +[2025-05-01 23:38:57,343] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 132.79 | bwd_microstep: 293.64 | bwd_inner_microstep: 293.62 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.11 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1364 +[2025-05-01 23:38:57,958] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 223.52 | bwd_microstep: 371.83 | bwd_inner_microstep: 371.81 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.33 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-01 23:38:58,832] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 327.81 | bwd_microstep: 511.67 | bwd_inner_microstep: 511.66 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-01 23:38:59,701] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 337.07 | bwd_microstep: 500.50 | bwd_inner_microstep: 500.48 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 23:39:00,576] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 347.93 | bwd_microstep: 495.24 | bwd_inner_microstep: 495.22 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.31 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 23:39:01,423] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 342.81 | bwd_microstep: 471.94 | bwd_inner_microstep: 471.92 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 23:39:02,306] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 333.35 | bwd_microstep: 518.22 | bwd_inner_microstep: 518.20 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 23:39:03,181] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 335.57 | bwd_microstep: 511.94 | bwd_inner_microstep: 511.93 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 23:39:04,035] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 344.58 | bwd_microstep: 482.13 | bwd_inner_microstep: 482.11 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 830 +[2025-05-01 23:39:04,477] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 169.14 | bwd_microstep: 259.23 | bwd_inner_microstep: 259.19 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-01 23:39:05,363] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 359.16 | bwd_microstep: 508.38 | bwd_inner_microstep: 508.36 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1849 +[2025-05-01 23:39:06,482] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 2.35 | optimizer_gradients: 2.26 | optimizer_step: 16.62 +[2025-05-01 23:39:06,484] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 323.83 | bwd_microstep: 752.29 | bwd_inner_microstep: 514.76 | bwd_allreduce_microstep: 237.52 | step_microstep: 28.37 +[2025-05-01 23:39:06,485] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4549.49 | bwd: 7124.79 | bwd_inner: 6886.97 | bwd_allreduce: 237.60 | step: 49.65 + 6%|▌ | 528/8720 [1:23:40<26:37:17, 11.70s/it] {'loss': 0.9233, 'grad_norm': 4.43087911605835, 'learning_rate': 9.975615472342996e-06, 'epoch': 0.61} + 6%|▌ | 528/8720 [1:23:40<26:37:17, 11.70s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1957 +[2025-05-01 23:39:07,407] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 328.78 | bwd_microstep: 551.26 | bwd_inner_microstep: 551.24 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1927 +[2025-05-01 23:39:08,322] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 333.46 | bwd_microstep: 549.71 | bwd_inner_microstep: 549.69 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.51 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 381 +[2025-05-01 23:39:08,562] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 77.48 | bwd_microstep: 140.48 | bwd_inner_microstep: 140.29 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.18 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1358 +[2025-05-01 23:39:09,240] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 241.36 | bwd_microstep: 413.21 | bwd_inner_microstep: 413.15 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-01 23:39:10,091] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 321.26 | bwd_microstep: 508.27 | bwd_inner_microstep: 508.25 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.32 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1883 +[2025-05-01 23:39:10,955] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 328.24 | bwd_microstep: 503.63 | bwd_inner_microstep: 503.61 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 844 +[2025-05-01 23:39:11,358] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.19 | bwd_microstep: 188.63 | bwd_inner_microstep: 188.40 | bwd_allreduce_microstep: 0.14 | step_microstep: 0.09 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1356 +[2025-05-01 23:39:12,034] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 298.41 | bwd_microstep: 360.40 | bwd_inner_microstep: 360.38 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.28 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-01 23:39:12,857] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 310.08 | bwd_microstep: 483.07 | bwd_inner_microstep: 482.99 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-01 23:39:13,760] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 396.29 | bwd_microstep: 488.07 | bwd_inner_microstep: 488.05 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 843 +[2025-05-01 23:39:14,208] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 177.42 | bwd_microstep: 254.27 | bwd_inner_microstep: 254.05 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-01 23:39:15,108] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 381.25 | bwd_microstep: 501.14 | bwd_inner_microstep: 501.13 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.91 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 23:39:15,989] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 344.56 | bwd_microstep: 516.42 | bwd_inner_microstep: 516.41 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-01 23:39:16,802] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 275.16 | bwd_microstep: 517.08 | bwd_inner_microstep: 517.06 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1850 +[2025-05-01 23:39:17,653] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 328.60 | bwd_microstep: 495.73 | bwd_inner_microstep: 495.71 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.23 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-01 23:39:18,889] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.20 | optimizer_step: 16.70 +[2025-05-01 23:39:18,890] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 331.62 | bwd_microstep: 849.35 | bwd_inner_microstep: 508.02 | bwd_allreduce_microstep: 341.32 | step_microstep: 26.00 +[2025-05-01 23:39:18,891] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4660.06 | bwd: 7320.77 | bwd_inner: 6978.47 | bwd_allreduce: 341.65 | step: 42.01 + 6%|▌ | 529/8720 [1:23:52<27:06:02, 11.91s/it] {'loss': 0.9647, 'grad_norm': 5.770899772644043, 'learning_rate': 9.975431935976612e-06, 'epoch': 0.61} + 6%|▌ | 529/8720 [1:23:52<27:06:02, 11.91s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1911 +[2025-05-01 23:39:19,767] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 322.45 | bwd_microstep: 527.36 | bwd_inner_microstep: 527.34 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.50 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1931 +[2025-05-01 23:39:20,690] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 343.54 | bwd_microstep: 547.29 | bwd_inner_microstep: 547.27 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 369 +[2025-05-01 23:39:20,924] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 76.64 | bwd_microstep: 136.13 | bwd_inner_microstep: 136.11 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.42 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1898 +[2025-05-01 23:39:21,808] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 337.17 | bwd_microstep: 519.21 | bwd_inner_microstep: 519.19 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 348 +[2025-05-01 23:39:22,049] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 103.35 | bwd_microstep: 113.58 | bwd_inner_microstep: 113.46 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-01 23:39:22,953] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 392.59 | bwd_microstep: 493.41 | bwd_inner_microstep: 493.40 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-01 23:39:23,859] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 380.07 | bwd_microstep: 505.97 | bwd_inner_microstep: 505.95 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.89 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-01 23:39:24,724] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 329.62 | bwd_microstep: 516.93 | bwd_inner_microstep: 516.91 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.49 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-01 23:39:25,597] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 324.02 | bwd_microstep: 517.82 | bwd_inner_microstep: 517.80 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-01 23:39:26,468] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 315.62 | bwd_microstep: 523.72 | bwd_inner_microstep: 523.70 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 23:39:27,325] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 310.99 | bwd_microstep: 514.22 | bwd_inner_microstep: 514.20 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.32 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 325 +[2025-05-01 23:39:27,562] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 86.89 | bwd_microstep: 122.45 | bwd_inner_microstep: 122.20 | bwd_allreduce_microstep: 0.24 | step_microstep: 0.39 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 321 +[2025-05-01 23:39:27,778] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 76.37 | bwd_microstep: 122.81 | bwd_inner_microstep: 122.79 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.32 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 23:39:28,643] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 325.09 | bwd_microstep: 509.18 | bwd_inner_microstep: 509.16 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.17 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 23:39:29,514] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 329.96 | bwd_microstep: 512.07 | bwd_inner_microstep: 512.05 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1948 +[2025-05-01 23:39:30,709] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 2.50 | optimizer_gradients: 2.22 | optimizer_step: 16.58 +[2025-05-01 23:39:30,712] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 355.52 | bwd_microstep: 787.38 | bwd_inner_microstep: 496.74 | bwd_allreduce_microstep: 290.59 | step_microstep: 26.59 +[2025-05-01 23:39:30,713] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4409.80 | bwd: 6969.54 | bwd_inner: 6678.29 | bwd_allreduce: 290.96 | step: 49.96 + 6%|▌ | 530/8720 [1:24:04<27:02:12, 11.88s/it] {'loss': 1.0822, 'grad_norm': 3.554180860519409, 'learning_rate': 9.975247713181946e-06, 'epoch': 0.61} + 6%|▌ | 530/8720 [1:24:04<27:02:12, 11.88s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1897 +[2025-05-01 23:39:31,568] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 332.58 | bwd_microstep: 482.66 | bwd_inner_microstep: 482.65 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1888 +[2025-05-01 23:39:32,475] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 388.53 | bwd_microstep: 499.83 | bwd_inner_microstep: 499.82 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.09 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 858 +[2025-05-01 23:39:32,916] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 145.15 | bwd_microstep: 280.92 | bwd_inner_microstep: 280.30 | bwd_allreduce_microstep: 0.61 | step_microstep: 0.39 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-01 23:39:33,774] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 322.45 | bwd_microstep: 514.55 | bwd_inner_microstep: 514.53 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.44 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-01 23:39:34,643] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 322.19 | bwd_microstep: 515.63 | bwd_inner_microstep: 515.62 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.28 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 23:39:35,506] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 311.69 | bwd_microstep: 519.40 | bwd_inner_microstep: 519.39 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 842 +[2025-05-01 23:39:35,907] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 153.42 | bwd_microstep: 218.78 | bwd_inner_microstep: 218.76 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.40 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 837 +[2025-05-01 23:39:36,333] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 124.91 | bwd_microstep: 284.39 | bwd_inner_microstep: 284.37 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 23:39:37,196] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 324.00 | bwd_microstep: 515.52 | bwd_inner_microstep: 515.50 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 23:39:38,068] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 319.72 | bwd_microstep: 518.56 | bwd_inner_microstep: 518.55 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 23:39:38,939] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 314.93 | bwd_microstep: 524.29 | bwd_inner_microstep: 524.28 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.87 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 835 +[2025-05-01 23:39:39,355] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 117.61 | bwd_microstep: 279.99 | bwd_inner_microstep: 279.97 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.31 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 23:39:40,218] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 319.64 | bwd_microstep: 516.83 | bwd_inner_microstep: 516.81 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.32 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 832 +[2025-05-01 23:39:40,653] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 113.89 | bwd_microstep: 290.44 | bwd_inner_microstep: 290.42 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 23:39:41,469] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 274.35 | bwd_microstep: 510.43 | bwd_inner_microstep: 510.41 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.47 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1959 +[2025-05-01 23:39:42,668] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.52 | optimizer_step: 18.51 +[2025-05-01 23:39:42,670] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 348.74 | bwd_microstep: 793.35 | bwd_inner_microstep: 545.40 | bwd_allreduce_microstep: 247.93 | step_microstep: 28.34 +[2025-05-01 23:39:42,672] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4233.73 | bwd: 7265.58 | bwd_inner: 7016.77 | bwd_allreduce: 248.61 | step: 53.78 + 6%|▌ | 531/8720 [1:24:16<27:04:56, 11.91s/it] {'loss': 0.8347, 'grad_norm': 4.4074225425720215, 'learning_rate': 9.975062803984417e-06, 'epoch': 0.61} + 6%|▌ | 531/8720 [1:24:16<27:04:56, 11.91s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2134 +[2025-05-01 23:39:43,627] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 352.60 | bwd_microstep: 562.96 | bwd_inner_microstep: 562.94 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.49 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1889 +[2025-05-01 23:39:44,483] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 330.34 | bwd_microstep: 494.54 | bwd_inner_microstep: 494.52 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.33 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1897 +[2025-05-01 23:39:45,365] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 359.96 | bwd_microstep: 489.51 | bwd_inner_microstep: 489.49 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-01 23:39:46,255] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 386.15 | bwd_microstep: 486.41 | bwd_inner_microstep: 486.39 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-01 23:39:47,156] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 390.21 | bwd_microstep: 494.60 | bwd_inner_microstep: 494.58 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-01 23:39:48,053] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 358.72 | bwd_microstep: 519.11 | bwd_inner_microstep: 519.09 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.72 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 848 +[2025-05-01 23:39:48,300] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 97.88 | bwd_microstep: 133.23 | bwd_inner_microstep: 133.15 | bwd_allreduce_microstep: 0.04 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 23:39:48,778] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.69 | bwd_microstep: 272.86 | bwd_inner_microstep: 272.84 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 23:39:49,255] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.68 | bwd_microstep: 272.56 | bwd_inner_microstep: 272.54 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 23:39:49,733] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.58 | bwd_microstep: 273.64 | bwd_inner_microstep: 273.62 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 23:39:50,211] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.51 | bwd_microstep: 272.66 | bwd_inner_microstep: 272.64 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 23:39:50,687] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.04 | bwd_microstep: 271.52 | bwd_inner_microstep: 271.50 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 23:39:51,163] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.03 | bwd_microstep: 271.46 | bwd_inner_microstep: 271.44 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 23:39:51,642] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.13 | bwd_microstep: 273.96 | bwd_inner_microstep: 273.94 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 23:39:52,122] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.51 | bwd_microstep: 272.05 | bwd_inner_microstep: 272.03 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-01 23:39:52,691] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.30 | optimizer_step: 16.35 +[2025-05-01 23:39:52,692] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.79 | bwd_microstep: 340.32 | bwd_inner_microstep: 274.41 | bwd_allreduce_microstep: 65.87 | step_microstep: 23.70 +[2025-05-01 23:39:52,693] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 3975.63 | bwd: 5701.41 | bwd_inner: 5635.15 | bwd_allreduce: 65.99 | step: 30.07 + 6%|▌ | 532/8720 [1:24:26<25:47:34, 11.34s/it] {'loss': 1.0186, 'grad_norm': 4.720156192779541, 'learning_rate': 9.974877208409531e-06, 'epoch': 0.61} + 6%|▌ | 532/8720 [1:24:26<25:47:34, 11.34s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 346 +[2025-05-01 23:39:52,904] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 69.27 | bwd_microstep: 123.51 | bwd_inner_microstep: 123.38 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-01 23:39:53,383] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.53 | bwd_microstep: 274.46 | bwd_inner_microstep: 274.44 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-01 23:39:53,861] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.53 | bwd_microstep: 273.36 | bwd_inner_microstep: 273.35 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-01 23:39:54,339] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.34 | bwd_microstep: 273.43 | bwd_inner_microstep: 273.41 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:39:54,817] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.20 | bwd_microstep: 273.29 | bwd_inner_microstep: 273.27 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-01 23:39:55,294] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.02 | bwd_microstep: 273.05 | bwd_inner_microstep: 273.03 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 23:39:55,771] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.17 | bwd_microstep: 273.02 | bwd_inner_microstep: 273.00 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 327 +[2025-05-01 23:39:55,969] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 67.63 | bwd_microstep: 117.73 | bwd_inner_microstep: 117.58 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 23:39:56,443] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.15 | bwd_microstep: 272.51 | bwd_inner_microstep: 272.49 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 23:39:56,920] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.88 | bwd_microstep: 273.22 | bwd_inner_microstep: 273.20 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:39:57,397] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.24 | bwd_microstep: 272.62 | bwd_inner_microstep: 272.60 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-01 23:39:57,872] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.41 | bwd_microstep: 271.27 | bwd_inner_microstep: 271.25 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 23:39:58,347] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.01 | bwd_microstep: 271.50 | bwd_inner_microstep: 271.48 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 23:39:58,821] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.96 | bwd_microstep: 270.94 | bwd_inner_microstep: 270.92 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1891 +[2025-05-01 23:39:59,303] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.14 | bwd_microstep: 275.89 | bwd_inner_microstep: 275.87 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-01 23:39:59,871] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.28 | optimizer_step: 16.29 +[2025-05-01 23:39:59,871] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.24 | bwd_microstep: 340.38 | bwd_inner_microstep: 274.43 | bwd_allreduce_microstep: 65.90 | step_microstep: 23.74 +[2025-05-01 23:39:59,872] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2780.46 | bwd: 4130.21 | bwd_inner: 4063.78 | bwd_allreduce: 66.08 | step: 24.48 + 6%|▌ | 533/8720 [1:24:33<22:57:03, 10.09s/it] {'loss': 1.1109, 'grad_norm': 5.140010833740234, 'learning_rate': 9.974690926482897e-06, 'epoch': 0.61} + 6%|▌ | 533/8720 [1:24:33<22:57:03, 10.09s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-01 23:40:00,353] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.60 | bwd_microstep: 272.35 | bwd_inner_microstep: 272.33 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 339 +[2025-05-01 23:40:00,552] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 67.94 | bwd_microstep: 117.50 | bwd_inner_microstep: 117.37 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-01 23:40:01,029] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.18 | bwd_microstep: 273.90 | bwd_inner_microstep: 273.89 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 848 +[2025-05-01 23:40:01,271] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.38 | bwd_microstep: 132.35 | bwd_inner_microstep: 132.33 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-01 23:40:01,747] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.87 | bwd_microstep: 273.44 | bwd_inner_microstep: 273.42 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-01 23:40:02,224] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.21 | bwd_microstep: 273.14 | bwd_inner_microstep: 273.12 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 23:40:02,700] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.74 | bwd_microstep: 272.43 | bwd_inner_microstep: 272.42 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1347 +[2025-05-01 23:40:03,062] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.49 | bwd_microstep: 205.82 | bwd_inner_microstep: 205.81 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 23:40:03,539] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.72 | bwd_microstep: 272.40 | bwd_inner_microstep: 272.38 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 23:40:04,016] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.41 | bwd_microstep: 273.05 | bwd_inner_microstep: 273.03 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 23:40:04,494] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.28 | bwd_microstep: 273.14 | bwd_inner_microstep: 273.13 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 23:40:04,971] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.76 | bwd_microstep: 272.36 | bwd_inner_microstep: 272.34 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 829 +[2025-05-01 23:40:05,207] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 92.24 | bwd_microstep: 129.86 | bwd_inner_microstep: 129.84 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 23:40:05,680] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.19 | bwd_microstep: 271.09 | bwd_inner_microstep: 271.08 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 23:40:06,156] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.83 | bwd_microstep: 271.92 | bwd_inner_microstep: 271.90 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1953 +[2025-05-01 23:40:06,748] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.27 | optimizer_step: 16.37 +[2025-05-01 23:40:06,748] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 197.19 | bwd_microstep: 355.94 | bwd_inner_microstep: 290.11 | bwd_allreduce_microstep: 65.78 | step_microstep: 23.74 +[2025-05-01 23:40:06,749] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2667.76 | bwd: 3940.72 | bwd_inner: 3874.52 | bwd_allreduce: 65.91 | step: 24.49 + 6%|▌ | 534/8720 [1:24:40<20:45:18, 9.13s/it] {'loss': 1.1198, 'grad_norm': 5.19149923324585, 'learning_rate': 9.974503958230215e-06, 'epoch': 0.61} + 6%|▌ | 534/8720 [1:24:40<20:45:18, 9.13s/it]dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 907 +[2025-05-01 23:40:07,014] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 100.59 | bwd_microstep: 144.50 | bwd_inner_microstep: 144.48 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1893 +[2025-05-01 23:40:07,493] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.37 | bwd_microstep: 275.68 | bwd_inner_microstep: 275.66 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-01 23:40:07,972] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.28 | bwd_microstep: 273.78 | bwd_inner_microstep: 273.76 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-01 23:40:08,450] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.79 | bwd_microstep: 273.82 | bwd_inner_microstep: 273.80 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-01 23:40:08,928] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.74 | bwd_microstep: 274.00 | bwd_inner_microstep: 273.98 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 337 +[2025-05-01 23:40:09,128] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 70.95 | bwd_microstep: 115.91 | bwd_inner_microstep: 115.79 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 326 +[2025-05-01 23:40:09,327] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 68.00 | bwd_microstep: 118.31 | bwd_inner_microstep: 118.18 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-01 23:40:09,804] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.78 | bwd_microstep: 274.03 | bwd_inner_microstep: 274.02 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 23:40:10,281] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.22 | bwd_microstep: 273.09 | bwd_inner_microstep: 273.08 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-01 23:40:10,758] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.76 | bwd_microstep: 272.97 | bwd_inner_microstep: 272.95 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 23:40:11,235] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.87 | bwd_microstep: 273.44 | bwd_inner_microstep: 273.43 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-01 23:40:11,713] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.42 | bwd_microstep: 272.96 | bwd_inner_microstep: 272.94 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-01 23:40:12,191] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.45 | bwd_microstep: 273.13 | bwd_inner_microstep: 273.11 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 23:40:12,667] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.26 | bwd_microstep: 272.19 | bwd_inner_microstep: 272.17 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 832 +[2025-05-01 23:40:12,903] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 92.32 | bwd_microstep: 130.11 | bwd_inner_microstep: 130.09 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 23:40:13,467] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.38 | optimizer_step: 16.42 +[2025-05-01 23:40:13,468] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.42 | bwd_microstep: 338.05 | bwd_inner_microstep: 271.90 | bwd_allreduce_microstep: 66.11 | step_microstep: 23.94 +[2025-05-01 23:40:13,469] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2595.99 | bwd: 3856.02 | bwd_inner: 3789.41 | bwd_allreduce: 66.28 | step: 24.75 + 6%|▌ | 535/8720 [1:24:47<19:06:36, 8.41s/it] {'loss': 1.2218, 'grad_norm': 3.0876338481903076, 'learning_rate': 9.974316303677279e-06, 'epoch': 0.61} + 6%|▌ | 535/8720 [1:24:47<19:06:36, 8.41s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1919 +[2025-05-01 23:40:13,957] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 191.12 | bwd_microstep: 277.25 | bwd_inner_microstep: 277.24 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 353 +[2025-05-01 23:40:14,165] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 71.81 | bwd_microstep: 122.47 | bwd_inner_microstep: 122.34 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-01 23:40:14,641] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.24 | bwd_microstep: 273.73 | bwd_inner_microstep: 273.72 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1350 +[2025-05-01 23:40:15,002] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.75 | bwd_microstep: 205.67 | bwd_inner_microstep: 205.65 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1105 +[2025-05-01 23:40:15,295] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 117.24 | bwd_microstep: 161.59 | bwd_inner_microstep: 161.57 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-01 23:40:15,772] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.90 | bwd_microstep: 273.46 | bwd_inner_microstep: 273.44 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 323 +[2025-05-01 23:40:15,969] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 69.80 | bwd_microstep: 114.15 | bwd_inner_microstep: 114.03 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 23:40:16,445] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.94 | bwd_microstep: 273.09 | bwd_inner_microstep: 273.07 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-01 23:40:16,921] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.07 | bwd_microstep: 273.10 | bwd_inner_microstep: 273.08 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 23:40:17,397] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.51 | bwd_microstep: 272.44 | bwd_inner_microstep: 272.42 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 23:40:17,872] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.73 | bwd_microstep: 272.02 | bwd_inner_microstep: 272.00 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 23:40:18,348] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.92 | bwd_microstep: 271.89 | bwd_inner_microstep: 271.87 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 23:40:18,823] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.86 | bwd_microstep: 272.09 | bwd_inner_microstep: 272.08 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 23:40:19,298] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.69 | bwd_microstep: 271.54 | bwd_inner_microstep: 271.52 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 23:40:19,773] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.67 | bwd_microstep: 271.16 | bwd_inner_microstep: 271.15 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 371 +[2025-05-01 23:40:20,073] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.21 | optimizer_step: 16.25 +[2025-05-01 23:40:20,074] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 67.79 | bwd_microstep: 197.04 | bwd_inner_microstep: 130.86 | bwd_allreduce_microstep: 66.10 | step_microstep: 23.59 +[2025-05-01 23:40:20,075] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2541.80 | bwd: 3802.73 | bwd_inner: 3736.10 | bwd_allreduce: 66.26 | step: 24.33 + 6%|▌ | 536/8720 [1:24:53<17:52:52, 7.87s/it] {'loss': 1.4394, 'grad_norm': 5.3374342918396, 'learning_rate': 9.97412796284998e-06, 'epoch': 0.61} + 6%|▌ | 536/8720 [1:24:53<17:52:52, 7.87s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2628 +[2025-05-01 23:40:20,696] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 230.57 | bwd_microstep: 369.96 | bwd_inner_microstep: 369.94 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1938 +[2025-05-01 23:40:21,197] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 197.41 | bwd_microstep: 288.38 | bwd_inner_microstep: 288.37 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 350 +[2025-05-01 23:40:21,397] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 68.30 | bwd_microstep: 117.81 | bwd_inner_microstep: 117.69 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-01 23:40:21,874] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.56 | bwd_microstep: 273.25 | bwd_inner_microstep: 273.24 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-01 23:40:22,351] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.22 | bwd_microstep: 273.67 | bwd_inner_microstep: 273.65 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 23:40:22,829] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.28 | bwd_microstep: 273.10 | bwd_inner_microstep: 273.08 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:40:23,306] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.11 | bwd_microstep: 272.95 | bwd_inner_microstep: 272.93 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 23:40:23,783] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.69 | bwd_microstep: 272.49 | bwd_inner_microstep: 272.47 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 23:40:24,258] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.88 | bwd_microstep: 272.76 | bwd_inner_microstep: 272.74 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-01 23:40:24,735] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.53 | bwd_microstep: 272.92 | bwd_inner_microstep: 272.90 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-01 23:40:25,211] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.96 | bwd_microstep: 272.83 | bwd_inner_microstep: 272.81 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:40:25,688] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.12 | bwd_microstep: 272.98 | bwd_inner_microstep: 272.96 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 23:40:26,163] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.49 | bwd_microstep: 271.39 | bwd_inner_microstep: 271.38 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 23:40:26,638] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.98 | bwd_microstep: 272.50 | bwd_inner_microstep: 272.48 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 23:40:27,113] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.18 | bwd_microstep: 271.39 | bwd_inner_microstep: 271.38 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 23:40:27,676] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.18 | optimizer_step: 16.14 +[2025-05-01 23:40:27,677] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.70 | bwd_microstep: 337.32 | bwd_inner_microstep: 271.90 | bwd_allreduce_microstep: 65.38 | step_microstep: 23.27 +[2025-05-01 23:40:27,678] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2948.74 | bwd: 4385.74 | bwd_inner: 4319.95 | bwd_allreduce: 65.50 | step: 23.96 + 6%|▌ | 537/8720 [1:25:01<17:41:57, 7.79s/it] {'loss': 0.95, 'grad_norm': 4.679978370666504, 'learning_rate': 9.973938935774299e-06, 'epoch': 0.62} + 6%|▌ | 537/8720 [1:25:01<17:41:57, 7.79s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1930 +[2025-05-01 23:40:28,180] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.11 | bwd_microstep: 287.34 | bwd_inner_microstep: 287.32 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1889 +[2025-05-01 23:40:28,659] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.84 | bwd_microstep: 275.11 | bwd_inner_microstep: 275.09 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 360 +[2025-05-01 23:40:28,857] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 68.30 | bwd_microstep: 117.11 | bwd_inner_microstep: 116.99 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1379 +[2025-05-01 23:40:29,221] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.01 | bwd_microstep: 208.37 | bwd_inner_microstep: 208.35 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 381 +[2025-05-01 23:40:29,418] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 67.21 | bwd_microstep: 116.47 | bwd_inner_microstep: 116.35 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1098 +[2025-05-01 23:40:29,707] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 114.42 | bwd_microstep: 161.04 | bwd_inner_microstep: 161.03 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-01 23:40:30,183] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.13 | bwd_microstep: 273.44 | bwd_inner_microstep: 273.43 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-01 23:40:30,659] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.98 | bwd_microstep: 272.82 | bwd_inner_microstep: 272.81 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 23:40:31,134] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.69 | bwd_microstep: 272.73 | bwd_inner_microstep: 272.72 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-01 23:40:31,611] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.65 | bwd_microstep: 273.59 | bwd_inner_microstep: 273.57 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1355 +[2025-05-01 23:40:31,973] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.51 | bwd_microstep: 206.65 | bwd_inner_microstep: 206.64 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 23:40:32,450] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.97 | bwd_microstep: 272.57 | bwd_inner_microstep: 272.55 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 23:40:32,926] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.18 | bwd_microstep: 272.11 | bwd_inner_microstep: 272.09 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-01 23:40:33,401] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.01 | bwd_microstep: 271.46 | bwd_inner_microstep: 271.44 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1930 +[2025-05-01 23:40:33,900] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.77 | bwd_microstep: 287.99 | bwd_inner_microstep: 287.98 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1921 +[2025-05-01 23:40:34,485] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.24 | optimizer_step: 16.18 +[2025-05-01 23:40:34,486] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 194.26 | bwd_microstep: 353.04 | bwd_inner_microstep: 287.37 | bwd_allreduce_microstep: 65.62 | step_microstep: 23.37 +[2025-05-01 23:40:34,487] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2625.81 | bwd: 3921.89 | bwd_inner: 3855.76 | bwd_allreduce: 65.80 | step: 24.09 + 6%|▌ | 538/8720 [1:25:08<17:01:49, 7.49s/it] {'loss': 1.3388, 'grad_norm': 6.412501335144043, 'learning_rate': 9.973749222476317e-06, 'epoch': 0.62} + 6%|▌ | 538/8720 [1:25:08<17:01:49, 7.49s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2128 +[2025-05-01 23:40:35,024] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 204.08 | bwd_microstep: 313.52 | bwd_inner_microstep: 313.51 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1940 +[2025-05-01 23:40:35,524] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.79 | bwd_microstep: 289.00 | bwd_inner_microstep: 288.98 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 857 +[2025-05-01 23:40:35,764] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.12 | bwd_microstep: 133.00 | bwd_inner_microstep: 132.98 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-01 23:40:36,243] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.66 | bwd_microstep: 274.91 | bwd_inner_microstep: 274.89 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-01 23:40:36,720] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.63 | bwd_microstep: 273.77 | bwd_inner_microstep: 273.75 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-01 23:40:37,196] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.24 | bwd_microstep: 273.05 | bwd_inner_microstep: 273.03 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-01 23:40:37,672] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.33 | bwd_microstep: 272.81 | bwd_inner_microstep: 272.79 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-01 23:40:38,149] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.04 | bwd_microstep: 272.86 | bwd_inner_microstep: 272.85 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:40:38,626] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.15 | bwd_microstep: 272.88 | bwd_inner_microstep: 272.87 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-01 23:40:39,103] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.18 | bwd_microstep: 272.81 | bwd_inner_microstep: 272.79 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 319 +[2025-05-01 23:40:39,305] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 71.60 | bwd_microstep: 117.42 | bwd_inner_microstep: 117.28 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 23:40:39,779] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.70 | bwd_microstep: 271.17 | bwd_inner_microstep: 271.16 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 23:40:40,252] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.59 | bwd_microstep: 270.94 | bwd_inner_microstep: 270.92 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 827 +[2025-05-01 23:40:40,490] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.70 | bwd_microstep: 130.05 | bwd_inner_microstep: 130.03 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2134 +[2025-05-01 23:40:41,023] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 204.37 | bwd_microstep: 314.54 | bwd_inner_microstep: 314.52 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1990 +[2025-05-01 23:40:41,621] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.18 | optimizer_step: 16.21 +[2025-05-01 23:40:41,621] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 199.32 | bwd_microstep: 360.46 | bwd_inner_microstep: 294.64 | bwd_allreduce_microstep: 65.78 | step_microstep: 23.41 +[2025-05-01 23:40:41,622] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2759.28 | bwd: 4113.22 | bwd_inner: 4047.02 | bwd_allreduce: 65.91 | step: 24.09 + 6%|▌ | 539/8720 [1:25:15<16:47:04, 7.39s/it] {'loss': 1.0321, 'grad_norm': 4.17597770690918, 'learning_rate': 9.973558822982206e-06, 'epoch': 0.62} + 6%|▌ | 539/8720 [1:25:15<16:47:04, 7.39s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1915 +[2025-05-01 23:40:42,109] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 191.07 | bwd_microstep: 276.24 | bwd_inner_microstep: 276.23 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1887 +[2025-05-01 23:40:42,588] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.34 | bwd_microstep: 274.98 | bwd_inner_microstep: 274.96 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 862 +[2025-05-01 23:40:42,830] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.71 | bwd_microstep: 133.75 | bwd_inner_microstep: 133.73 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-01 23:40:43,307] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.61 | bwd_microstep: 273.67 | bwd_inner_microstep: 273.65 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-01 23:40:43,783] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.50 | bwd_microstep: 272.66 | bwd_inner_microstep: 272.64 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-01 23:40:44,260] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.92 | bwd_microstep: 272.76 | bwd_inner_microstep: 272.74 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 845 +[2025-05-01 23:40:44,500] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.77 | bwd_microstep: 132.53 | bwd_inner_microstep: 132.51 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:40:44,974] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.64 | bwd_microstep: 272.10 | bwd_inner_microstep: 272.08 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 23:40:45,449] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.62 | bwd_microstep: 272.66 | bwd_inner_microstep: 272.64 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 23:40:45,924] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.11 | bwd_microstep: 272.26 | bwd_inner_microstep: 272.24 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 23:40:46,400] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.61 | bwd_microstep: 272.29 | bwd_inner_microstep: 272.27 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 23:40:46,875] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.34 | bwd_microstep: 271.96 | bwd_inner_microstep: 271.94 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 23:40:47,348] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.27 | bwd_microstep: 271.06 | bwd_inner_microstep: 271.04 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 23:40:47,823] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.02 | bwd_microstep: 271.33 | bwd_inner_microstep: 271.31 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 23:40:48,296] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.02 | bwd_microstep: 270.75 | bwd_inner_microstep: 270.73 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1377 +[2025-05-01 23:40:48,749] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.21 | optimizer_step: 16.14 +[2025-05-01 23:40:48,749] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.16 | bwd_microstep: 274.54 | bwd_inner_microstep: 208.74 | bwd_allreduce_microstep: 65.76 | step_microstep: 23.16 +[2025-05-01 23:40:48,750] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2779.48 | bwd: 4085.53 | bwd_inner: 4019.45 | bwd_allreduce: 65.84 | step: 23.81 + 6%|▌ | 540/8720 [1:25:22<16:36:23, 7.31s/it] {'loss': 0.7171, 'grad_norm': 4.447988510131836, 'learning_rate': 9.973367737318236e-06, 'epoch': 0.62} + 6%|▌ | 540/8720 [1:25:22<16:36:23, 7.31s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1911 +[2025-05-01 23:40:49,236] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.42 | bwd_microstep: 276.54 | bwd_inner_microstep: 276.52 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1909 +[2025-05-01 23:40:49,717] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.96 | bwd_microstep: 277.02 | bwd_inner_microstep: 277.00 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-01 23:40:50,195] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.59 | bwd_microstep: 273.89 | bwd_inner_microstep: 273.87 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-01 23:40:50,673] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.93 | bwd_microstep: 274.65 | bwd_inner_microstep: 274.63 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-01 23:40:51,150] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.21 | bwd_microstep: 273.86 | bwd_inner_microstep: 273.84 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-01 23:40:51,628] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.94 | bwd_microstep: 273.75 | bwd_inner_microstep: 273.73 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-01 23:40:52,106] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.93 | bwd_microstep: 273.64 | bwd_inner_microstep: 273.62 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1365 +[2025-05-01 23:40:52,469] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.61 | bwd_microstep: 207.41 | bwd_inner_microstep: 207.39 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-01 23:40:52,946] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.81 | bwd_microstep: 273.32 | bwd_inner_microstep: 273.31 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:40:53,424] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.35 | bwd_microstep: 272.91 | bwd_inner_microstep: 272.89 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 23:40:53,901] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.09 | bwd_microstep: 272.74 | bwd_inner_microstep: 272.72 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 23:40:54,377] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.24 | bwd_microstep: 271.77 | bwd_inner_microstep: 271.75 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 23:40:54,853] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.57 | bwd_microstep: 273.57 | bwd_inner_microstep: 273.55 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-01 23:40:55,328] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.39 | bwd_microstep: 271.36 | bwd_inner_microstep: 271.34 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 23:40:55,803] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.49 | bwd_microstep: 271.41 | bwd_inner_microstep: 271.40 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 23:40:56,367] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.21 | optimizer_step: 16.24 +[2025-05-01 23:40:56,367] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.12 | bwd_microstep: 337.14 | bwd_inner_microstep: 271.90 | bwd_allreduce_microstep: 65.20 | step_microstep: 23.31 +[2025-05-01 23:40:56,368] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2975.41 | bwd: 4374.97 | bwd_inner: 4309.46 | bwd_allreduce: 65.28 | step: 23.95 + 6%|▌ | 541/8720 [1:25:30<16:48:55, 7.40s/it] {'loss': 1.1501, 'grad_norm': 3.516685724258423, 'learning_rate': 9.97317596551077e-06, 'epoch': 0.62} + 6%|▌ | 541/8720 [1:25:30<16:48:55, 7.40s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1904 +[2025-05-01 23:40:56,854] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.82 | bwd_microstep: 276.26 | bwd_inner_microstep: 276.24 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 337 +[2025-05-01 23:40:57,051] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 67.39 | bwd_microstep: 117.27 | bwd_inner_microstep: 117.14 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-01 23:40:57,528] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.09 | bwd_microstep: 273.58 | bwd_inner_microstep: 273.56 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-01 23:40:58,005] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.42 | bwd_microstep: 273.47 | bwd_inner_microstep: 273.45 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-01 23:40:58,484] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.40 | bwd_microstep: 274.57 | bwd_inner_microstep: 274.55 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-01 23:40:58,963] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.49 | bwd_microstep: 274.30 | bwd_inner_microstep: 274.28 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-01 23:40:59,441] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.72 | bwd_microstep: 274.09 | bwd_inner_microstep: 274.08 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 839 +[2025-05-01 23:40:59,673] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 92.00 | bwd_microstep: 126.72 | bwd_inner_microstep: 126.70 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-01 23:41:00,150] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.66 | bwd_microstep: 273.15 | bwd_inner_microstep: 273.13 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-01 23:41:00,626] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.94 | bwd_microstep: 272.80 | bwd_inner_microstep: 272.78 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 23:41:01,102] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.74 | bwd_microstep: 272.67 | bwd_inner_microstep: 272.65 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 23:41:01,580] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.54 | bwd_microstep: 273.50 | bwd_inner_microstep: 273.49 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 23:41:02,058] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.98 | bwd_microstep: 273.17 | bwd_inner_microstep: 273.15 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 23:41:02,533] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.09 | bwd_microstep: 271.30 | bwd_inner_microstep: 271.29 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-01 23:41:03,007] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.03 | bwd_microstep: 271.36 | bwd_inner_microstep: 271.34 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 429 +[2025-05-01 23:41:03,315] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.23 | optimizer_step: 16.19 +[2025-05-01 23:41:03,316] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 71.54 | bwd_microstep: 201.02 | bwd_inner_microstep: 135.19 | bwd_allreduce_microstep: 65.75 | step_microstep: 23.19 +[2025-05-01 23:41:03,317] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2688.62 | bwd: 3999.25 | bwd_inner: 3933.07 | bwd_allreduce: 65.87 | step: 23.87 + 6%|▌ | 542/8720 [1:25:37<16:30:17, 7.27s/it] {'loss': 1.0359, 'grad_norm': 4.358692646026611, 'learning_rate': 9.972983507586265e-06, 'epoch': 0.62} + 6%|▌ | 542/8720 [1:25:37<16:30:17, 7.27s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2054 +[2025-05-01 23:41:03,841] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 203.49 | bwd_microstep: 301.45 | bwd_inner_microstep: 301.43 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-01 23:41:04,318] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.78 | bwd_microstep: 273.56 | bwd_inner_microstep: 273.55 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1892 +[2025-05-01 23:41:04,799] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.01 | bwd_microstep: 275.14 | bwd_inner_microstep: 275.12 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1887 +[2025-05-01 23:41:05,278] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.78 | bwd_microstep: 274.41 | bwd_inner_microstep: 274.40 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-01 23:41:05,756] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.33 | bwd_microstep: 273.06 | bwd_inner_microstep: 273.04 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-01 23:41:06,233] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.73 | bwd_microstep: 272.66 | bwd_inner_microstep: 272.64 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 836 +[2025-05-01 23:41:06,464] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 90.94 | bwd_microstep: 126.05 | bwd_inner_microstep: 126.03 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:41:06,939] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.61 | bwd_microstep: 272.27 | bwd_inner_microstep: 272.25 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 23:41:07,417] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.72 | bwd_microstep: 272.06 | bwd_inner_microstep: 272.04 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-01 23:41:07,896] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.63 | bwd_microstep: 272.43 | bwd_inner_microstep: 272.41 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 23:41:08,375] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.62 | bwd_microstep: 272.16 | bwd_inner_microstep: 272.14 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 23:41:08,856] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.12 | bwd_microstep: 272.24 | bwd_inner_microstep: 272.23 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 23:41:09,335] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.46 | bwd_microstep: 272.41 | bwd_inner_microstep: 272.40 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-01 23:41:09,812] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.17 | bwd_microstep: 270.85 | bwd_inner_microstep: 270.84 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-01 23:41:10,288] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.76 | bwd_microstep: 270.82 | bwd_inner_microstep: 270.81 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 23:41:10,868] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.07 | optimizer_gradients: 2.20 | optimizer_step: 16.50 +[2025-05-01 23:41:10,868] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.69 | bwd_microstep: 347.69 | bwd_inner_microstep: 271.27 | bwd_allreduce_microstep: 76.37 | step_microstep: 24.57 +[2025-05-01 23:41:10,870] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2935.54 | bwd: 4319.29 | bwd_inner: 4242.60 | bwd_allreduce: 76.45 | step: 25.29 + 6%|▌ | 543/8720 [1:25:44<16:42:00, 7.35s/it] {'loss': 0.8589, 'grad_norm': 5.005644798278809, 'learning_rate': 9.972790363571272e-06, 'epoch': 0.62} + 6%|▌ | 543/8720 [1:25:44<16:42:00, 7.35s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1934 +[2025-05-01 23:41:11,376] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 196.25 | bwd_microstep: 287.45 | bwd_inner_microstep: 287.43 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1927 +[2025-05-01 23:41:11,879] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.61 | bwd_microstep: 287.49 | bwd_inner_microstep: 287.47 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1902 +[2025-05-01 23:41:12,363] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.87 | bwd_microstep: 275.99 | bwd_inner_microstep: 275.98 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-01 23:41:12,846] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.35 | bwd_microstep: 273.86 | bwd_inner_microstep: 273.84 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 329 +[2025-05-01 23:41:13,069] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 84.16 | bwd_microstep: 120.53 | bwd_inner_microstep: 120.38 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 834 +[2025-05-01 23:41:13,311] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.12 | bwd_microstep: 132.75 | bwd_inner_microstep: 132.49 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 23:41:13,789] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.21 | bwd_microstep: 272.51 | bwd_inner_microstep: 272.49 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 23:41:14,268] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.19 | bwd_microstep: 273.10 | bwd_inner_microstep: 273.08 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 835 +[2025-05-01 23:41:14,499] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 90.83 | bwd_microstep: 126.27 | bwd_inner_microstep: 126.05 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 23:41:14,974] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.37 | bwd_microstep: 271.44 | bwd_inner_microstep: 271.42 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 23:41:15,450] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.74 | bwd_microstep: 271.53 | bwd_inner_microstep: 271.51 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 23:41:15,924] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.98 | bwd_microstep: 271.32 | bwd_inner_microstep: 271.31 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.14 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 23:41:16,401] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.72 | bwd_microstep: 271.57 | bwd_inner_microstep: 271.55 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-01 23:41:16,878] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.59 | bwd_microstep: 270.86 | bwd_inner_microstep: 270.84 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1850 +[2025-05-01 23:41:17,358] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.70 | bwd_microstep: 270.66 | bwd_inner_microstep: 270.64 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-01 23:41:17,924] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.23 | optimizer_step: 16.42 +[2025-05-01 23:41:17,924] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.78 | bwd_microstep: 339.22 | bwd_inner_microstep: 273.37 | bwd_allreduce_microstep: 65.80 | step_microstep: 23.79 +[2025-05-01 23:41:17,926] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2731.12 | bwd: 4016.61 | bwd_inner: 3949.89 | bwd_allreduce: 66.18 | step: 24.89 + 6%|▌ | 544/8720 [1:25:51<16:29:41, 7.26s/it] {'loss': 0.9556, 'grad_norm': 5.110790252685547, 'learning_rate': 9.972596533492439e-06, 'epoch': 0.62} + 6%|▌ | 544/8720 [1:25:51<16:29:41, 7.26s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-01 23:41:18,409] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.49 | bwd_microstep: 273.19 | bwd_inner_microstep: 273.18 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-01 23:41:18,885] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.71 | bwd_microstep: 273.07 | bwd_inner_microstep: 273.05 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 843 +[2025-05-01 23:41:19,125] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.26 | bwd_microstep: 132.14 | bwd_inner_microstep: 132.12 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1888 +[2025-05-01 23:41:19,602] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.28 | bwd_microstep: 274.37 | bwd_inner_microstep: 274.36 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1360 +[2025-05-01 23:41:19,963] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.10 | bwd_microstep: 206.46 | bwd_inner_microstep: 206.44 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-01 23:41:20,439] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.80 | bwd_microstep: 272.88 | bwd_inner_microstep: 272.87 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1357 +[2025-05-01 23:41:20,801] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.66 | bwd_microstep: 206.45 | bwd_inner_microstep: 206.43 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-01 23:41:21,277] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.13 | bwd_microstep: 272.89 | bwd_inner_microstep: 272.87 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 23:41:21,753] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.53 | bwd_microstep: 272.79 | bwd_inner_microstep: 272.78 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 23:41:22,230] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.60 | bwd_microstep: 272.90 | bwd_inner_microstep: 272.88 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 23:41:22,707] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.96 | bwd_microstep: 272.99 | bwd_inner_microstep: 272.97 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 23:41:23,183] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.15 | bwd_microstep: 272.27 | bwd_inner_microstep: 272.25 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 835 +[2025-05-01 23:41:23,413] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 90.58 | bwd_microstep: 126.14 | bwd_inner_microstep: 126.06 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 23:41:23,895] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.35 | bwd_microstep: 271.10 | bwd_inner_microstep: 271.08 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1427 +[2025-05-01 23:41:24,268] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 144.46 | bwd_microstep: 214.35 | bwd_inner_microstep: 214.33 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1921 +[2025-05-01 23:41:24,885] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.21 | optimizer_step: 16.35 +[2025-05-01 23:41:24,885] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.63 | bwd_microstep: 379.60 | bwd_inner_microstep: 287.20 | bwd_allreduce_microstep: 92.35 | step_microstep: 23.85 +[2025-05-01 23:41:24,887] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2688.44 | bwd: 3993.64 | bwd_inner: 3900.86 | bwd_allreduce: 92.41 | step: 24.64 + 6%|▋ | 545/8720 [1:25:58<16:17:13, 7.17s/it] {'loss': 1.4741, 'grad_norm': 5.100629806518555, 'learning_rate': 9.972402017376508e-06, 'epoch': 0.62} + 6%|▋ | 545/8720 [1:25:58<16:17:13, 7.17s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1930 +[2025-05-01 23:41:25,390] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.64 | bwd_microstep: 287.13 | bwd_inner_microstep: 287.09 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1911 +[2025-05-01 23:41:25,873] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.41 | bwd_microstep: 276.64 | bwd_inner_microstep: 276.62 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1130 +[2025-05-01 23:41:26,168] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 116.57 | bwd_microstep: 163.23 | bwd_inner_microstep: 163.15 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1887 +[2025-05-01 23:41:26,652] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.76 | bwd_microstep: 275.15 | bwd_inner_microstep: 275.13 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-01 23:41:27,135] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.17 | bwd_microstep: 273.96 | bwd_inner_microstep: 273.94 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-01 23:41:27,616] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.03 | bwd_microstep: 273.96 | bwd_inner_microstep: 273.94 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-01 23:41:28,097] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.24 | bwd_microstep: 273.00 | bwd_inner_microstep: 272.96 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.13 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 23:41:28,578] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.77 | bwd_microstep: 272.20 | bwd_inner_microstep: 272.19 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 23:41:29,058] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.78 | bwd_microstep: 272.17 | bwd_inner_microstep: 272.15 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 843 +[2025-05-01 23:41:29,306] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 97.41 | bwd_microstep: 131.82 | bwd_inner_microstep: 131.80 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 6, images per sample: 6.0, dynamic token length: 1607 +[2025-05-01 23:41:29,732] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 163.66 | bwd_microstep: 244.25 | bwd_inner_microstep: 244.23 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-01 23:41:30,214] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.27 | bwd_microstep: 274.18 | bwd_inner_microstep: 274.16 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:41:30,693] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.00 | bwd_microstep: 272.89 | bwd_inner_microstep: 272.87 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 320 +[2025-05-01 23:41:30,928] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 89.84 | bwd_microstep: 126.57 | bwd_inner_microstep: 126.23 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 23:41:31,408] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.88 | bwd_microstep: 272.84 | bwd_inner_microstep: 272.82 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1899 +[2025-05-01 23:41:32,001] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.30 | optimizer_step: 16.65 +[2025-05-01 23:41:32,002] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 191.21 | bwd_microstep: 358.14 | bwd_inner_microstep: 276.55 | bwd_allreduce_microstep: 81.54 | step_microstep: 24.78 +[2025-05-01 23:41:32,003] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2743.25 | bwd: 4048.23 | bwd_inner: 3965.94 | bwd_allreduce: 81.77 | step: 26.03 + 6%|▋ | 546/8720 [1:26:05<16:14:53, 7.16s/it] {'loss': 1.0947, 'grad_norm': 5.9554266929626465, 'learning_rate': 9.972206815250313e-06, 'epoch': 0.63} + 6%|▋ | 546/8720 [1:26:05<16:14:53, 7.16s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2014 +[2025-05-01 23:41:32,523] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 200.73 | bwd_microstep: 295.83 | bwd_inner_microstep: 295.81 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1958 +[2025-05-01 23:41:33,029] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 196.66 | bwd_microstep: 290.00 | bwd_inner_microstep: 289.98 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1904 +[2025-05-01 23:41:33,513] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.24 | bwd_microstep: 276.24 | bwd_inner_microstep: 276.22 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-01 23:41:33,995] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.64 | bwd_microstep: 273.32 | bwd_inner_microstep: 273.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 329 +[2025-05-01 23:41:34,225] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 85.08 | bwd_microstep: 127.52 | bwd_inner_microstep: 127.16 | bwd_allreduce_microstep: 0.15 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-01 23:41:34,706] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.14 | bwd_microstep: 273.61 | bwd_inner_microstep: 273.59 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-01 23:41:35,190] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.59 | bwd_microstep: 273.95 | bwd_inner_microstep: 273.93 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 23:41:35,670] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.45 | bwd_microstep: 273.16 | bwd_inner_microstep: 273.14 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 23:41:36,150] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.29 | bwd_microstep: 273.13 | bwd_inner_microstep: 273.11 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-01 23:41:36,630] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.41 | bwd_microstep: 272.77 | bwd_inner_microstep: 272.75 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.14 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 329 +[2025-05-01 23:41:36,847] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 85.02 | bwd_microstep: 116.92 | bwd_inner_microstep: 116.77 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1353 +[2025-05-01 23:41:37,211] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.96 | bwd_microstep: 206.33 | bwd_inner_microstep: 206.23 | bwd_allreduce_microstep: 0.04 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 23:41:37,689] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.34 | bwd_microstep: 272.26 | bwd_inner_microstep: 272.24 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 23:41:38,167] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.94 | bwd_microstep: 272.34 | bwd_inner_microstep: 272.32 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 23:41:38,645] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.04 | bwd_microstep: 271.40 | bwd_inner_microstep: 271.38 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1346 +[2025-05-01 23:41:39,115] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.25 | optimizer_step: 16.68 +[2025-05-01 23:41:39,115] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.40 | bwd_microstep: 282.40 | bwd_inner_microstep: 206.16 | bwd_allreduce_microstep: 76.09 | step_microstep: 24.50 +[2025-05-01 23:41:39,117] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2740.54 | bwd: 4051.24 | bwd_inner: 3974.26 | bwd_allreduce: 76.40 | step: 25.79 + 6%|▋ | 547/8720 [1:26:12<16:13:02, 7.14s/it] {'loss': 1.4356, 'grad_norm': 6.4965715408325195, 'learning_rate': 9.972010927140788e-06, 'epoch': 0.63} + 6%|▋ | 547/8720 [1:26:12<16:13:02, 7.14s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 435 +[2025-05-01 23:41:39,331] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 79.33 | bwd_microstep: 114.04 | bwd_inner_microstep: 113.85 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.13 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1907 +[2025-05-01 23:41:39,814] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.90 | bwd_microstep: 276.28 | bwd_inner_microstep: 276.26 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-01 23:41:40,294] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.56 | bwd_microstep: 273.78 | bwd_inner_microstep: 273.76 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-01 23:41:40,775] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.70 | bwd_microstep: 274.03 | bwd_inner_microstep: 274.01 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-01 23:41:41,257] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.56 | bwd_microstep: 273.78 | bwd_inner_microstep: 273.77 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 842 +[2025-05-01 23:41:41,503] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.61 | bwd_microstep: 132.00 | bwd_inner_microstep: 131.76 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-01 23:41:41,983] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.79 | bwd_microstep: 273.19 | bwd_inner_microstep: 273.17 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-01 23:41:42,463] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.05 | bwd_microstep: 273.26 | bwd_inner_microstep: 273.24 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 23:41:42,940] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.83 | bwd_microstep: 271.22 | bwd_inner_microstep: 271.20 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 23:41:43,417] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.36 | bwd_microstep: 271.34 | bwd_inner_microstep: 271.32 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 23:41:43,896] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.23 | bwd_microstep: 272.40 | bwd_inner_microstep: 272.38 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 23:41:44,375] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.30 | bwd_microstep: 272.88 | bwd_inner_microstep: 272.87 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 23:41:44,854] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.01 | bwd_microstep: 271.19 | bwd_inner_microstep: 271.18 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 23:41:45,333] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.69 | bwd_microstep: 271.71 | bwd_inner_microstep: 271.69 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 23:41:45,814] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.20 | bwd_microstep: 271.90 | bwd_inner_microstep: 271.89 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-01 23:41:46,398] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.29 | optimizer_step: 16.24 +[2025-05-01 23:41:46,399] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.54 | bwd_microstep: 353.10 | bwd_inner_microstep: 273.36 | bwd_allreduce_microstep: 79.69 | step_microstep: 24.10 +[2025-05-01 23:41:46,400] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2814.29 | bwd: 4146.17 | bwd_inner: 4065.74 | bwd_allreduce: 79.96 | step: 25.13 + 6%|▋ | 548/8720 [1:26:20<16:18:38, 7.19s/it] {'loss': 1.0052, 'grad_norm': 4.609399795532227, 'learning_rate': 9.971814353074954e-06, 'epoch': 0.63} + 6%|▋ | 548/8720 [1:26:20<16:18:38, 7.19s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 337 +[2025-05-01 23:41:46,617] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 79.11 | bwd_microstep: 117.20 | bwd_inner_microstep: 117.05 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-01 23:41:47,098] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.17 | bwd_microstep: 274.01 | bwd_inner_microstep: 273.99 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 23:41:47,578] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.64 | bwd_microstep: 272.70 | bwd_inner_microstep: 272.68 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 330 +[2025-05-01 23:41:47,809] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 97.98 | bwd_microstep: 115.56 | bwd_inner_microstep: 115.26 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 23:41:48,286] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.00 | bwd_microstep: 272.47 | bwd_inner_microstep: 272.45 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 23:41:48,767] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.92 | bwd_microstep: 272.52 | bwd_inner_microstep: 272.50 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 23:41:49,245] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.37 | bwd_microstep: 272.74 | bwd_inner_microstep: 272.72 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 23:41:49,724] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.03 | bwd_microstep: 272.51 | bwd_inner_microstep: 272.49 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 23:41:50,200] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.83 | bwd_microstep: 271.80 | bwd_inner_microstep: 271.79 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 23:41:50,677] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.94 | bwd_microstep: 272.43 | bwd_inner_microstep: 272.41 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-01 23:41:51,157] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.61 | bwd_microstep: 273.22 | bwd_inner_microstep: 273.20 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 23:41:51,636] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.56 | bwd_microstep: 273.09 | bwd_inner_microstep: 273.07 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 315 +[2025-05-01 23:41:51,849] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 80.15 | bwd_microstep: 117.28 | bwd_inner_microstep: 117.12 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 23:41:52,325] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.23 | bwd_microstep: 271.46 | bwd_inner_microstep: 271.44 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 23:41:52,803] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.82 | bwd_microstep: 271.81 | bwd_inner_microstep: 271.79 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1946 +[2025-05-01 23:41:53,403] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.21 | optimizer_step: 16.19 +[2025-05-01 23:41:53,404] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 196.61 | bwd_microstep: 364.36 | bwd_inner_microstep: 289.49 | bwd_allreduce_microstep: 74.82 | step_microstep: 23.27 +[2025-05-01 23:41:53,405] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2716.62 | bwd: 3985.22 | bwd_inner: 3909.59 | bwd_allreduce: 75.13 | step: 24.37 + 6%|▋ | 549/8720 [1:26:27<16:11:04, 7.13s/it] {'loss': 0.6712, 'grad_norm': 3.148427724838257, 'learning_rate': 9.971617093079935e-06, 'epoch': 0.63} + 6%|▋ | 549/8720 [1:26:27<16:11:04, 7.13s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1915 +[2025-05-01 23:41:53,891] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.61 | bwd_microstep: 276.81 | bwd_inner_microstep: 276.79 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1924 +[2025-05-01 23:41:54,389] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 196.47 | bwd_microstep: 287.18 | bwd_inner_microstep: 287.17 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-01 23:41:54,868] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.72 | bwd_microstep: 274.12 | bwd_inner_microstep: 274.10 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 856 +[2025-05-01 23:41:55,109] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.17 | bwd_microstep: 133.58 | bwd_inner_microstep: 133.34 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-01 23:41:55,587] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.74 | bwd_microstep: 274.38 | bwd_inner_microstep: 274.36 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-01 23:41:56,064] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.90 | bwd_microstep: 272.86 | bwd_inner_microstep: 272.84 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-01 23:41:56,543] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.30 | bwd_microstep: 273.44 | bwd_inner_microstep: 273.42 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-01 23:41:57,024] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.10 | bwd_microstep: 273.82 | bwd_inner_microstep: 273.80 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 23:41:57,507] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.23 | bwd_microstep: 272.66 | bwd_inner_microstep: 272.64 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1362 +[2025-05-01 23:41:57,878] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.50 | bwd_microstep: 206.70 | bwd_inner_microstep: 206.68 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 23:41:58,357] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.79 | bwd_microstep: 272.38 | bwd_inner_microstep: 272.36 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 23:41:58,839] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.19 | bwd_microstep: 273.09 | bwd_inner_microstep: 273.07 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-01 23:41:59,323] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.26 | bwd_microstep: 272.90 | bwd_inner_microstep: 272.89 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 23:41:59,802] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.29 | bwd_microstep: 271.13 | bwd_inner_microstep: 271.12 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 23:42:00,282] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.33 | bwd_microstep: 271.12 | bwd_inner_microstep: 271.10 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 23:42:00,868] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.23 | optimizer_step: 16.16 +[2025-05-01 23:42:00,869] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.12 | bwd_microstep: 356.46 | bwd_inner_microstep: 271.68 | bwd_allreduce_microstep: 84.73 | step_microstep: 23.83 +[2025-05-01 23:42:00,870] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2886.37 | bwd: 4262.67 | bwd_inner: 4177.42 | bwd_allreduce: 84.89 | step: 24.65 + 6%|▋ | 550/8720 [1:26:34<16:24:41, 7.23s/it] {'loss': 1.0991, 'grad_norm': 4.395330429077148, 'learning_rate': 9.971419147182943e-06, 'epoch': 0.63} + 6%|▋ | 550/8720 [1:26:34<16:24:41, 7.23s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-01 23:42:01,357] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.00 | bwd_microstep: 274.16 | bwd_inner_microstep: 274.15 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.17 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-01 23:42:01,839] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.41 | bwd_microstep: 273.48 | bwd_inner_microstep: 273.47 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1361 +[2025-05-01 23:42:02,205] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 142.18 | bwd_microstep: 206.70 | bwd_inner_microstep: 206.68 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-01 23:42:02,683] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.15 | bwd_microstep: 273.00 | bwd_inner_microstep: 272.99 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-01 23:42:03,163] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.11 | bwd_microstep: 272.74 | bwd_inner_microstep: 272.73 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 23:42:03,644] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.00 | bwd_microstep: 272.74 | bwd_inner_microstep: 272.73 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-01 23:42:04,123] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.68 | bwd_microstep: 272.55 | bwd_inner_microstep: 272.53 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1351 +[2025-05-01 23:42:04,490] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.88 | bwd_microstep: 206.30 | bwd_inner_microstep: 206.19 | bwd_allreduce_microstep: 0.03 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-01 23:42:04,968] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.40 | bwd_microstep: 272.75 | bwd_inner_microstep: 272.73 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:42:05,446] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.71 | bwd_microstep: 272.44 | bwd_inner_microstep: 272.42 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 324 +[2025-05-01 23:42:05,664] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 87.21 | bwd_microstep: 116.30 | bwd_inner_microstep: 116.03 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 23:42:06,140] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.32 | bwd_microstep: 271.23 | bwd_inner_microstep: 271.21 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 317 +[2025-05-01 23:42:06,355] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 81.31 | bwd_microstep: 118.35 | bwd_inner_microstep: 118.11 | bwd_allreduce_microstep: 0.08 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 23:42:06,832] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.09 | bwd_microstep: 271.19 | bwd_inner_microstep: 271.17 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 317 +[2025-05-01 23:42:07,049] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 82.26 | bwd_microstep: 118.45 | bwd_inner_microstep: 118.14 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 23:42:07,625] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.20 | optimizer_step: 16.32 +[2025-05-01 23:42:07,626] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.15 | bwd_microstep: 348.23 | bwd_inner_microstep: 271.58 | bwd_allreduce_microstep: 76.60 | step_microstep: 24.07 +[2025-05-01 23:42:07,627] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2605.49 | bwd: 3840.74 | bwd_inner: 3763.03 | bwd_allreduce: 77.00 | step: 25.30 + 6%|▋ | 551/8720 [1:26:41<16:05:11, 7.09s/it] {'loss': 0.9696, 'grad_norm': 6.086929798126221, 'learning_rate': 9.97122051541129e-06, 'epoch': 0.63} + 6%|▋ | 551/8720 [1:26:41<16:05:11, 7.09s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2101 +[2025-05-01 23:42:08,158] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 204.26 | bwd_microstep: 305.30 | bwd_inner_microstep: 305.28 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1911 +[2025-05-01 23:42:08,641] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.56 | bwd_microstep: 276.92 | bwd_inner_microstep: 276.90 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 375 +[2025-05-01 23:42:08,841] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 68.56 | bwd_microstep: 117.98 | bwd_inner_microstep: 117.84 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1121 +[2025-05-01 23:42:09,136] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 117.49 | bwd_microstep: 163.38 | bwd_inner_microstep: 163.16 | bwd_allreduce_microstep: 0.14 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-01 23:42:09,617] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.77 | bwd_microstep: 274.42 | bwd_inner_microstep: 274.41 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-01 23:42:10,096] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.15 | bwd_microstep: 272.91 | bwd_inner_microstep: 272.89 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-01 23:42:10,573] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.35 | bwd_microstep: 273.15 | bwd_inner_microstep: 273.13 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 23:42:11,049] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.75 | bwd_microstep: 272.41 | bwd_inner_microstep: 272.40 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 841 +[2025-05-01 23:42:11,292] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 96.05 | bwd_microstep: 131.83 | bwd_inner_microstep: 131.79 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 23:42:11,767] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.09 | bwd_microstep: 272.50 | bwd_inner_microstep: 272.48 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 844 +[2025-05-01 23:42:12,009] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.37 | bwd_microstep: 132.25 | bwd_inner_microstep: 132.13 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 23:42:12,483] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.56 | bwd_microstep: 272.13 | bwd_inner_microstep: 272.11 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 23:42:12,958] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.63 | bwd_microstep: 271.13 | bwd_inner_microstep: 271.11 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 23:42:13,432] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.62 | bwd_microstep: 271.07 | bwd_inner_microstep: 271.05 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 828 +[2025-05-01 23:42:13,669] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.76 | bwd_microstep: 129.67 | bwd_inner_microstep: 129.64 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1924 +[2025-05-01 23:42:14,256] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.04 | optimizer_gradients: 2.22 | optimizer_step: 16.09 +[2025-05-01 23:42:14,257] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 194.57 | bwd_microstep: 354.76 | bwd_inner_microstep: 287.90 | bwd_allreduce_microstep: 66.82 | step_microstep: 23.19 +[2025-05-01 23:42:14,258] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2568.26 | bwd: 3791.88 | bwd_inner: 3724.29 | bwd_allreduce: 67.12 | step: 24.12 + 6%|▋ | 552/8720 [1:26:48<15:46:16, 6.95s/it] {'loss': 1.1423, 'grad_norm': 3.037984848022461, 'learning_rate': 9.971021197792379e-06, 'epoch': 0.63} + 6%|▋ | 552/8720 [1:26:48<15:46:16, 6.95s/it]dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1214 +[2025-05-01 23:42:14,574] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 122.74 | bwd_microstep: 175.00 | bwd_inner_microstep: 174.73 | bwd_allreduce_microstep: 0.15 | step_microstep: 0.09 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 391 +[2025-05-01 23:42:14,780] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 74.90 | bwd_microstep: 117.18 | bwd_inner_microstep: 117.05 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1921 +[2025-05-01 23:42:15,277] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 194.26 | bwd_microstep: 286.96 | bwd_inner_microstep: 286.95 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1903 +[2025-05-01 23:42:15,760] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.89 | bwd_microstep: 275.72 | bwd_inner_microstep: 275.70 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 849 +[2025-05-01 23:42:16,006] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.68 | bwd_microstep: 132.60 | bwd_inner_microstep: 132.40 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-01 23:42:16,484] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.81 | bwd_microstep: 273.16 | bwd_inner_microstep: 273.14 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-01 23:42:16,962] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.15 | bwd_microstep: 272.61 | bwd_inner_microstep: 272.59 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 840 +[2025-05-01 23:42:17,204] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 99.09 | bwd_microstep: 126.24 | bwd_inner_microstep: 126.18 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-01 23:42:17,682] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.07 | bwd_microstep: 272.51 | bwd_inner_microstep: 272.50 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 23:42:18,160] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.13 | bwd_microstep: 272.33 | bwd_inner_microstep: 272.31 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:42:18,639] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.29 | bwd_microstep: 272.66 | bwd_inner_microstep: 272.64 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 23:42:19,119] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.13 | bwd_microstep: 272.37 | bwd_inner_microstep: 272.35 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 23:42:19,598] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.95 | bwd_microstep: 272.25 | bwd_inner_microstep: 272.23 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 23:42:20,076] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.02 | bwd_microstep: 272.07 | bwd_inner_microstep: 272.05 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 319 +[2025-05-01 23:42:20,302] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 90.95 | bwd_microstep: 117.88 | bwd_inner_microstep: 117.67 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1850 +[2025-05-01 23:42:20,878] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.29 | optimizer_step: 16.31 +[2025-05-01 23:42:20,879] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.02 | bwd_microstep: 348.26 | bwd_inner_microstep: 271.31 | bwd_allreduce_microstep: 76.89 | step_microstep: 24.16 +[2025-05-01 23:42:20,880] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2558.74 | bwd: 3759.89 | bwd_inner: 3681.92 | bwd_allreduce: 77.32 | step: 25.14 + 6%|▋ | 553/8720 [1:26:54<15:32:48, 6.85s/it] {'loss': 1.023, 'grad_norm': 4.970282554626465, 'learning_rate': 9.970821194353707e-06, 'epoch': 0.63} + 6%|▋ | 553/8720 [1:26:54<15:32:48, 6.85s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-01 23:42:21,365] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.99 | bwd_microstep: 273.21 | bwd_inner_microstep: 273.19 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.15 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-01 23:42:21,845] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.70 | bwd_microstep: 274.73 | bwd_inner_microstep: 274.71 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-01 23:42:22,324] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.91 | bwd_microstep: 273.31 | bwd_inner_microstep: 273.29 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-01 23:42:22,805] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.18 | bwd_microstep: 272.97 | bwd_inner_microstep: 272.95 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-01 23:42:23,284] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.56 | bwd_microstep: 272.67 | bwd_inner_microstep: 272.65 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1096 +[2025-05-01 23:42:23,577] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 115.28 | bwd_microstep: 161.12 | bwd_inner_microstep: 161.10 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:42:24,055] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.32 | bwd_microstep: 272.56 | bwd_inner_microstep: 272.54 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 23:42:24,533] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.10 | bwd_microstep: 272.37 | bwd_inner_microstep: 272.35 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 23:42:25,010] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.85 | bwd_microstep: 272.32 | bwd_inner_microstep: 272.30 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 23:42:25,486] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.78 | bwd_microstep: 272.28 | bwd_inner_microstep: 272.27 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 23:42:25,960] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.74 | bwd_microstep: 271.11 | bwd_inner_microstep: 271.09 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 23:42:26,433] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.08 | bwd_microstep: 270.93 | bwd_inner_microstep: 270.92 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 23:42:26,908] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.87 | bwd_microstep: 271.04 | bwd_inner_microstep: 271.02 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 23:42:27,384] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.46 | bwd_microstep: 271.30 | bwd_inner_microstep: 271.28 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 396 +[2025-05-01 23:42:27,616] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.49 | bwd_microstep: 120.25 | bwd_inner_microstep: 119.94 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1893 +[2025-05-01 23:42:28,199] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.24 | optimizer_step: 16.48 +[2025-05-01 23:42:28,200] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.75 | bwd_microstep: 353.35 | bwd_inner_microstep: 275.31 | bwd_allreduce_microstep: 77.99 | step_microstep: 24.61 +[2025-05-01 23:42:28,201] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2848.75 | bwd: 4175.53 | bwd_inner: 4096.99 | bwd_allreduce: 78.20 | step: 25.54 + 6%|▋ | 554/8720 [1:27:01<15:51:44, 6.99s/it] {'loss': 1.1828, 'grad_norm': 4.692841529846191, 'learning_rate': 9.97062050512287e-06, 'epoch': 0.64} + 6%|▋ | 554/8720 [1:27:01<15:51:44, 6.99s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 435 +[2025-05-01 23:42:28,408] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 73.11 | bwd_microstep: 114.42 | bwd_inner_microstep: 114.16 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.08 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1380 +[2025-05-01 23:42:28,774] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 143.43 | bwd_microstep: 208.30 | bwd_inner_microstep: 208.28 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-01 23:42:29,252] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.73 | bwd_microstep: 274.02 | bwd_inner_microstep: 274.00 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-01 23:42:29,732] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.04 | bwd_microstep: 274.88 | bwd_inner_microstep: 274.86 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-01 23:42:30,210] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.12 | bwd_microstep: 273.01 | bwd_inner_microstep: 272.99 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1096 +[2025-05-01 23:42:30,501] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 115.86 | bwd_microstep: 160.91 | bwd_inner_microstep: 160.80 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-01 23:42:30,978] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.10 | bwd_microstep: 272.92 | bwd_inner_microstep: 272.91 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 835 +[2025-05-01 23:42:31,217] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.84 | bwd_microstep: 125.84 | bwd_inner_microstep: 125.63 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-01 23:42:31,696] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.22 | bwd_microstep: 273.09 | bwd_inner_microstep: 273.07 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 322 +[2025-05-01 23:42:31,916] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 82.81 | bwd_microstep: 120.47 | bwd_inner_microstep: 120.33 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 23:42:32,393] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.68 | bwd_microstep: 272.37 | bwd_inner_microstep: 272.35 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:42:32,870] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.13 | bwd_microstep: 272.43 | bwd_inner_microstep: 272.41 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.15 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 323 +[2025-05-01 23:42:33,095] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 86.93 | bwd_microstep: 121.22 | bwd_inner_microstep: 121.09 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 322 +[2025-05-01 23:42:33,318] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 91.12 | bwd_microstep: 116.93 | bwd_inner_microstep: 116.79 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 23:42:33,794] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.26 | bwd_microstep: 270.97 | bwd_inner_microstep: 270.95 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1850 +[2025-05-01 23:42:34,372] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.07 | optimizer_gradients: 2.36 | optimizer_step: 16.47 +[2025-05-01 23:42:34,372] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.77 | bwd_microstep: 348.23 | bwd_inner_microstep: 271.10 | bwd_allreduce_microstep: 77.08 | step_microstep: 24.61 +[2025-05-01 23:42:34,374] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2382.82 | bwd: 3500.14 | bwd_inner: 3421.85 | bwd_allreduce: 77.60 | step: 25.77 + 6%|▋ | 555/8720 [1:27:08<15:18:12, 6.75s/it] {'loss': 1.1921, 'grad_norm': 4.5353312492370605, 'learning_rate': 9.970419130127553e-06, 'epoch': 0.64} + 6%|▋ | 555/8720 [1:27:08<15:18:12, 6.75s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1952 +[2025-05-01 23:42:34,883] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 197.39 | bwd_microstep: 288.74 | bwd_inner_microstep: 288.72 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1891 +[2025-05-01 23:42:35,363] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.51 | bwd_microstep: 274.97 | bwd_inner_microstep: 274.95 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-01 23:42:35,843] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.64 | bwd_microstep: 273.52 | bwd_inner_microstep: 273.47 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.16 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-01 23:42:36,324] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.15 | bwd_microstep: 273.41 | bwd_inner_microstep: 273.39 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-01 23:42:36,804] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.27 | bwd_microstep: 273.03 | bwd_inner_microstep: 273.02 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-01 23:42:37,284] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.27 | bwd_microstep: 273.30 | bwd_inner_microstep: 273.28 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 323 +[2025-05-01 23:42:37,515] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 92.82 | bwd_microstep: 120.00 | bwd_inner_microstep: 119.70 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 23:42:38,000] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.59 | bwd_microstep: 272.95 | bwd_inner_microstep: 272.94 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 832 +[2025-05-01 23:42:38,242] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.65 | bwd_microstep: 130.31 | bwd_inner_microstep: 130.02 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-01 23:42:38,720] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.99 | bwd_microstep: 272.79 | bwd_inner_microstep: 272.77 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 23:42:39,200] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.48 | bwd_microstep: 272.58 | bwd_inner_microstep: 272.56 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 23:42:39,683] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.81 | bwd_microstep: 272.54 | bwd_inner_microstep: 272.52 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.15 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 23:42:40,166] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.88 | bwd_microstep: 272.28 | bwd_inner_microstep: 272.26 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 23:42:40,649] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.67 | bwd_microstep: 271.01 | bwd_inner_microstep: 270.99 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1345 +[2025-05-01 23:42:41,014] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.12 | bwd_microstep: 205.22 | bwd_inner_microstep: 205.20 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 23:42:41,591] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.29 | optimizer_step: 16.26 +[2025-05-01 23:42:41,592] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.01 | bwd_microstep: 349.27 | bwd_inner_microstep: 271.64 | bwd_allreduce_microstep: 77.58 | step_microstep: 24.26 +[2025-05-01 23:42:41,594] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2788.87 | bwd: 4096.07 | bwd_inner: 4017.52 | bwd_allreduce: 77.90 | step: 25.84 + 6%|▋ | 556/8720 [1:27:15<15:37:22, 6.89s/it] {'loss': 1.1208, 'grad_norm': 5.605320930480957, 'learning_rate': 9.970217069395539e-06, 'epoch': 0.64} + 6%|▋ | 556/8720 [1:27:15<15:37:22, 6.89s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1928 +[2025-05-01 23:42:42,100] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.34 | bwd_microstep: 287.02 | bwd_inner_microstep: 287.00 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-01 23:42:42,581] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.11 | bwd_microstep: 274.80 | bwd_inner_microstep: 274.78 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1894 +[2025-05-01 23:42:43,061] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.59 | bwd_microstep: 275.33 | bwd_inner_microstep: 275.31 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1894 +[2025-05-01 23:42:43,541] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.80 | bwd_microstep: 275.10 | bwd_inner_microstep: 275.08 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-01 23:42:44,019] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.66 | bwd_microstep: 273.19 | bwd_inner_microstep: 273.17 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-01 23:42:44,496] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.65 | bwd_microstep: 272.97 | bwd_inner_microstep: 272.95 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-01 23:42:44,973] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.23 | bwd_microstep: 273.39 | bwd_inner_microstep: 273.37 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-01 23:42:45,450] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.53 | bwd_microstep: 272.83 | bwd_inner_microstep: 272.82 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 837 +[2025-05-01 23:42:45,689] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 97.64 | bwd_microstep: 126.06 | bwd_inner_microstep: 126.02 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 23:42:46,166] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.70 | bwd_microstep: 273.51 | bwd_inner_microstep: 273.49 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 23:42:46,644] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.87 | bwd_microstep: 272.39 | bwd_inner_microstep: 272.37 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 23:42:47,121] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.16 | bwd_microstep: 272.92 | bwd_inner_microstep: 272.91 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-01 23:42:47,598] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.73 | bwd_microstep: 271.46 | bwd_inner_microstep: 271.45 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-01 23:42:48,073] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.94 | bwd_microstep: 271.59 | bwd_inner_microstep: 271.57 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-01 23:42:48,549] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.76 | bwd_microstep: 270.92 | bwd_inner_microstep: 270.91 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.14 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 962 +[2025-05-01 23:42:48,912] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.23 | optimizer_step: 16.32 +[2025-05-01 23:42:48,912] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 105.97 | bwd_microstep: 217.76 | bwd_inner_microstep: 150.36 | bwd_allreduce_microstep: 67.30 | step_microstep: 23.68 +[2025-05-01 23:42:48,913] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2852.41 | bwd: 4181.27 | bwd_inner: 4113.59 | bwd_allreduce: 67.37 | step: 24.50 + 6%|▋ | 557/8720 [1:27:22<15:54:45, 7.02s/it] {'loss': 1.3572, 'grad_norm': 6.643209934234619, 'learning_rate': 9.970014322954706e-06, 'epoch': 0.64} + 6%|▋ | 557/8720 [1:27:22<15:54:45, 7.02s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1914 +[2025-05-01 23:42:49,400] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.73 | bwd_microstep: 276.12 | bwd_inner_microstep: 276.11 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 877 +[2025-05-01 23:42:49,648] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 98.96 | bwd_microstep: 134.72 | bwd_inner_microstep: 134.60 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1900 +[2025-05-01 23:42:50,187] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 206.77 | bwd_microstep: 316.89 | bwd_inner_microstep: 316.87 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 342 +[2025-05-01 23:42:50,403] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 76.49 | bwd_microstep: 125.03 | bwd_inner_microstep: 124.71 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-01 23:42:50,896] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 193.86 | bwd_microstep: 281.98 | bwd_inner_microstep: 281.94 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-01 23:42:51,392] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 194.03 | bwd_microstep: 282.70 | bwd_inner_microstep: 282.67 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-01 23:42:51,882] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 193.81 | bwd_microstep: 275.89 | bwd_inner_microstep: 275.87 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1353 +[2025-05-01 23:42:52,407] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 170.22 | bwd_microstep: 333.10 | bwd_inner_microstep: 333.08 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 23:42:53,015] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 226.83 | bwd_microstep: 340.82 | bwd_inner_microstep: 340.80 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.51 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1092 +[2025-05-01 23:42:53,432] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 224.61 | bwd_microstep: 161.36 | bwd_inner_microstep: 161.21 | bwd_allreduce_microstep: 0.09 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 23:42:54,131] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 362.85 | bwd_microstep: 318.08 | bwd_inner_microstep: 318.06 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 23:42:54,890] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 378.45 | bwd_microstep: 350.36 | bwd_inner_microstep: 350.34 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-01 23:42:55,682] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 290.46 | bwd_microstep: 472.38 | bwd_inner_microstep: 472.36 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.48 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-01 23:42:56,377] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 193.89 | bwd_microstep: 484.00 | bwd_inner_microstep: 483.98 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.13 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 23:42:57,072] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 284.14 | bwd_microstep: 395.78 | bwd_inner_microstep: 395.72 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1905 +[2025-05-01 23:42:58,093] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.21 | optimizer_step: 16.13 +[2025-05-01 23:42:58,093] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 401.27 | bwd_microstep: 579.29 | bwd_inner_microstep: 368.62 | bwd_allreduce_microstep: 210.63 | step_microstep: 23.40 +[2025-05-01 23:42:58,094] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 3686.14 | bwd: 5128.54 | bwd_inner: 4917.01 | bwd_allreduce: 210.96 | step: 31.83 + 6%|▋ | 558/8720 [1:27:31<17:22:55, 7.67s/it] {'loss': 0.9396, 'grad_norm': 3.323320150375366, 'learning_rate': 9.969810890833026e-06, 'epoch': 0.64} + 6%|▋ | 558/8720 [1:27:31<17:22:55, 7.67s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-01 23:42:58,818] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 329.19 | bwd_microstep: 372.32 | bwd_inner_microstep: 372.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.52 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 858 +[2025-05-01 23:42:59,233] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 205.81 | bwd_microstep: 176.83 | bwd_inner_microstep: 176.57 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-01 23:42:59,927] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 298.83 | bwd_microstep: 377.74 | bwd_inner_microstep: 377.72 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1356 +[2025-05-01 23:43:00,497] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 263.92 | bwd_microstep: 289.61 | bwd_inner_microstep: 289.54 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 835 +[2025-05-01 23:43:00,935] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 157.10 | bwd_microstep: 264.15 | bwd_inner_microstep: 264.13 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.66 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 23:43:01,629] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.38 | bwd_microstep: 483.41 | bwd_inner_microstep: 483.39 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-01 23:43:02,334] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 306.26 | bwd_microstep: 379.15 | bwd_inner_microstep: 379.13 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.28 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 23:43:03,147] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 351.32 | bwd_microstep: 425.55 | bwd_inner_microstep: 425.53 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 23:43:03,903] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 215.62 | bwd_microstep: 510.63 | bwd_inner_microstep: 510.61 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 23:43:04,746] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 321.81 | bwd_microstep: 500.03 | bwd_inner_microstep: 500.01 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 23:43:05,594] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 328.47 | bwd_microstep: 499.56 | bwd_inner_microstep: 499.54 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.14 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 23:43:06,383] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 274.44 | bwd_microstep: 496.82 | bwd_inner_microstep: 496.80 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 23:43:07,230] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 335.78 | bwd_microstep: 481.18 | bwd_inner_microstep: 481.15 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 23:43:08,062] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 320.72 | bwd_microstep: 492.11 | bwd_inner_microstep: 492.09 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 23:43:08,908] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 336.10 | bwd_microstep: 480.48 | bwd_inner_microstep: 480.46 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.09 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 369 +[2025-05-01 23:43:09,421] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.20 | optimizer_step: 16.45 +[2025-05-01 23:43:09,421] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 102.24 | bwd_microstep: 373.53 | bwd_inner_microstep: 136.08 | bwd_allreduce_microstep: 237.44 | step_microstep: 23.61 +[2025-05-01 23:43:09,422] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4337.79 | bwd: 6603.16 | bwd_inner: 6365.07 | bwd_allreduce: 237.64 | step: 40.45 + 6%|▋ | 559/8720 [1:27:43<19:52:11, 8.77s/it] {'loss': 1.1011, 'grad_norm': 6.051146030426025, 'learning_rate': 9.969606773058563e-06, 'epoch': 0.64} + 6%|▋ | 559/8720 [1:27:43<19:52:11, 8.77s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1899 +[2025-05-01 23:43:10,305] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 333.36 | bwd_microstep: 526.61 | bwd_inner_microstep: 526.58 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.31 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 337 +[2025-05-01 23:43:10,537] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 72.04 | bwd_microstep: 130.35 | bwd_inner_microstep: 130.33 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-01 23:43:11,395] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 327.65 | bwd_microstep: 499.25 | bwd_inner_microstep: 499.23 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.48 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-01 23:43:12,198] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 330.93 | bwd_microstep: 439.48 | bwd_inner_microstep: 439.46 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.31 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 23:43:12,995] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 322.09 | bwd_microstep: 445.18 | bwd_inner_microstep: 445.16 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.25 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-01 23:43:13,779] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 310.20 | bwd_microstep: 445.89 | bwd_inner_microstep: 445.87 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 323 +[2025-05-01 23:43:14,021] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 90.20 | bwd_microstep: 128.86 | bwd_inner_microstep: 128.67 | bwd_allreduce_microstep: 0.18 | step_microstep: 0.18 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1344 +[2025-05-01 23:43:14,637] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 221.29 | bwd_microstep: 368.79 | bwd_inner_microstep: 368.77 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.33 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 23:43:15,441] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 316.33 | bwd_microstep: 468.37 | bwd_inner_microstep: 468.36 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.84 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 23:43:16,227] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 300.37 | bwd_microstep: 466.40 | bwd_inner_microstep: 466.38 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 23:43:16,999] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 310.65 | bwd_microstep: 439.99 | bwd_inner_microstep: 439.98 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.17 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 321 +[2025-05-01 23:43:17,224] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 81.18 | bwd_microstep: 125.15 | bwd_inner_microstep: 125.01 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 23:43:18,104] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 362.99 | bwd_microstep: 498.70 | bwd_inner_microstep: 498.68 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.53 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 23:43:18,933] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 304.18 | bwd_microstep: 505.13 | bwd_inner_microstep: 505.11 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.29 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-01 23:43:19,768] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 313.48 | bwd_microstep: 488.85 | bwd_inner_microstep: 488.84 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 23:43:20,885] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.21 | optimizer_step: 16.56 +[2025-05-01 23:43:20,887] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 313.81 | bwd_microstep: 747.49 | bwd_inner_microstep: 507.55 | bwd_allreduce_microstep: 239.93 | step_microstep: 28.54 +[2025-05-01 23:43:20,888] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4310.53 | bwd: 6724.52 | bwd_inner: 6484.04 | bwd_allreduce: 240.22 | step: 53.71 + 6%|▋ | 560/8720 [1:27:54<21:42:21, 9.58s/it] {'loss': 0.8307, 'grad_norm': 4.23840856552124, 'learning_rate': 9.96940196965948e-06, 'epoch': 0.64} + 6%|▋ | 560/8720 [1:27:54<21:42:21, 9.58s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1945 +[2025-05-01 23:43:21,812] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 340.59 | bwd_microstep: 549.32 | bwd_inner_microstep: 549.30 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.19 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1403 +[2025-05-01 23:43:22,499] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 241.60 | bwd_microstep: 420.69 | bwd_inner_microstep: 420.55 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1903 +[2025-05-01 23:43:23,392] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 359.32 | bwd_microstep: 513.63 | bwd_inner_microstep: 513.61 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.49 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-01 23:43:24,238] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 315.91 | bwd_microstep: 510.23 | bwd_inner_microstep: 510.22 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.31 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-01 23:43:25,076] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 307.76 | bwd_microstep: 499.31 | bwd_inner_microstep: 499.29 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.61 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-01 23:43:25,725] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 248.09 | bwd_microstep: 384.39 | bwd_inner_microstep: 384.37 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-01 23:43:26,414] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 310.04 | bwd_microstep: 363.67 | bwd_inner_microstep: 363.66 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 329 +[2025-05-01 23:43:26,616] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 67.77 | bwd_microstep: 121.57 | bwd_inner_microstep: 121.25 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-01 23:43:27,338] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 295.76 | bwd_microstep: 409.25 | bwd_inner_microstep: 409.23 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.28 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-01 23:43:27,976] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 223.94 | bwd_microstep: 384.56 | bwd_inner_microstep: 384.54 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 325 +[2025-05-01 23:43:28,176] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 67.99 | bwd_microstep: 118.46 | bwd_inner_microstep: 118.33 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 23:43:28,924] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 366.80 | bwd_microstep: 353.87 | bwd_inner_microstep: 353.85 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 23:43:29,735] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 329.37 | bwd_microstep: 454.32 | bwd_inner_microstep: 454.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 23:43:30,365] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.17 | bwd_microstep: 426.84 | bwd_inner_microstep: 426.82 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.91 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 315 +[2025-05-01 23:43:30,567] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 72.96 | bwd_microstep: 114.19 | bwd_inner_microstep: 114.06 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1379 +[2025-05-01 23:43:31,249] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.20 | optimizer_step: 16.18 +[2025-05-01 23:43:31,250] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.74 | bwd_microstep: 502.84 | bwd_inner_microstep: 414.32 | bwd_allreduce_microstep: 88.37 | step_microstep: 23.28 +[2025-05-01 23:43:31,251] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 3877.67 | bwd: 6127.20 | bwd_inner: 6037.88 | bwd_allreduce: 88.72 | step: 32.79 + 6%|▋ | 561/8720 [1:28:04<22:14:09, 9.81s/it] {'loss': 1.0967, 'grad_norm': 3.2730836868286133, 'learning_rate': 9.969196480664032e-06, 'epoch': 0.64} + 6%|▋ | 561/8720 [1:28:04<22:14:09, 9.81s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1986 +[2025-05-01 23:43:31,979] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 326.48 | bwd_microstep: 382.23 | bwd_inner_microstep: 382.21 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1952 +[2025-05-01 23:43:32,767] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 402.97 | bwd_microstep: 369.71 | bwd_inner_microstep: 369.69 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.19 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 856 +[2025-05-01 23:43:33,135] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 194.48 | bwd_microstep: 146.00 | bwd_inner_microstep: 145.98 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.31 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-01 23:43:33,749] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 250.52 | bwd_microstep: 334.82 | bwd_inner_microstep: 334.80 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.22 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 341 +[2025-05-01 23:43:33,989] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 98.76 | bwd_microstep: 113.42 | bwd_inner_microstep: 113.40 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.49 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-01 23:43:34,886] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 348.45 | bwd_microstep: 515.75 | bwd_inner_microstep: 515.73 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.27 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-01 23:43:35,704] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 325.85 | bwd_microstep: 470.14 | bwd_inner_microstep: 470.12 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-01 23:43:36,594] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 337.09 | bwd_microstep: 519.71 | bwd_inner_microstep: 519.69 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.40 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 23:43:37,467] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 331.05 | bwd_microstep: 517.17 | bwd_inner_microstep: 517.15 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.51 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 23:43:38,347] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 333.23 | bwd_microstep: 517.89 | bwd_inner_microstep: 517.87 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.33 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:43:39,224] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 354.40 | bwd_microstep: 496.90 | bwd_inner_microstep: 496.88 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 23:43:40,053] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 355.10 | bwd_microstep: 456.08 | bwd_inner_microstep: 456.06 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 23:43:40,945] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 338.97 | bwd_microstep: 522.57 | bwd_inner_microstep: 522.56 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.50 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 23:43:41,713] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 255.17 | bwd_microstep: 483.88 | bwd_inner_microstep: 483.86 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 829 +[2025-05-01 23:43:42,142] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 131.91 | bwd_microstep: 282.74 | bwd_inner_microstep: 282.72 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 23:43:43,152] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.07 | optimizer_gradients: 2.19 | optimizer_step: 16.34 +[2025-05-01 23:43:43,153] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 272.27 | bwd_microstep: 697.16 | bwd_inner_microstep: 451.78 | bwd_allreduce_microstep: 245.34 | step_microstep: 24.64 +[2025-05-01 23:43:43,154] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4656.61 | bwd: 6826.18 | bwd_inner: 6580.53 | bwd_allreduce: 245.42 | step: 44.73 + 6%|▋ | 562/8720 [1:28:16<23:39:20, 10.44s/it] {'loss': 1.0344, 'grad_norm': 5.1595001220703125, 'learning_rate': 9.968990306100568e-06, 'epoch': 0.64} + 6%|▋ | 562/8720 [1:28:16<23:39:20, 10.44s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2084 +[2025-05-01 23:43:44,041] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 337.67 | bwd_microstep: 517.65 | bwd_inner_microstep: 517.64 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-01 23:43:44,884] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 339.91 | bwd_microstep: 485.91 | bwd_inner_microstep: 485.89 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-01 23:43:45,694] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 324.25 | bwd_microstep: 466.01 | bwd_inner_microstep: 465.99 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.51 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-01 23:43:46,469] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 279.57 | bwd_microstep: 463.87 | bwd_inner_microstep: 463.85 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 844 +[2025-05-01 23:43:46,836] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 210.51 | bwd_microstep: 134.24 | bwd_inner_microstep: 134.15 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:43:47,669] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 370.66 | bwd_microstep: 435.74 | bwd_inner_microstep: 435.72 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-01 23:43:48,513] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 346.11 | bwd_microstep: 482.05 | bwd_inner_microstep: 482.03 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.91 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 325 +[2025-05-01 23:43:48,734] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 74.37 | bwd_microstep: 130.38 | bwd_inner_microstep: 130.36 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.30 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 23:43:49,496] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 260.56 | bwd_microstep: 473.12 | bwd_inner_microstep: 473.10 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 23:43:50,334] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 389.05 | bwd_microstep: 431.72 | bwd_inner_microstep: 431.70 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 23:43:51,229] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 394.27 | bwd_microstep: 483.19 | bwd_inner_microstep: 483.18 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 23:43:52,118] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 368.55 | bwd_microstep: 500.82 | bwd_inner_microstep: 500.80 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.92 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 23:43:52,933] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 303.72 | bwd_microstep: 492.92 | bwd_inner_microstep: 492.90 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.83 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1962 +[2025-05-01 23:43:53,858] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 376.11 | bwd_microstep: 531.17 | bwd_inner_microstep: 531.15 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.91 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1920 +[2025-05-01 23:43:54,683] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 347.80 | bwd_microstep: 456.51 | bwd_inner_microstep: 456.49 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.47 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1887 +[2025-05-01 23:43:55,772] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.23 | optimizer_step: 18.72 +[2025-05-01 23:43:55,774] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 347.03 | bwd_microstep: 684.31 | bwd_inner_microstep: 512.94 | bwd_allreduce_microstep: 171.36 | step_microstep: 28.32 +[2025-05-01 23:43:55,775] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 5070.01 | bwd: 7169.63 | bwd_inner: 6997.92 | bwd_allreduce: 171.48 | step: 41.89 + 6%|▋ | 563/8720 [1:28:29<25:08:17, 11.09s/it] {'loss': 0.8901, 'grad_norm': 3.0206851959228516, 'learning_rate': 9.968783445997533e-06, 'epoch': 0.65} + 6%|▋ | 563/8720 [1:28:29<25:08:17, 11.09s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2033 +[2025-05-01 23:43:56,710] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 354.38 | bwd_microstep: 550.87 | bwd_inner_microstep: 550.85 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2008 +[2025-05-01 23:43:57,650] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 358.64 | bwd_microstep: 554.89 | bwd_inner_microstep: 554.87 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.17 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-01 23:43:58,452] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 300.57 | bwd_microstep: 484.47 | bwd_inner_microstep: 484.45 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-01 23:43:59,299] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 345.93 | bwd_microstep: 480.64 | bwd_inner_microstep: 480.62 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:44:00,154] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 319.59 | bwd_microstep: 501.80 | bwd_inner_microstep: 501.78 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.30 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 845 +[2025-05-01 23:44:00,509] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 102.99 | bwd_microstep: 222.61 | bwd_inner_microstep: 222.59 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.49 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-01 23:44:01,350] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 310.87 | bwd_microstep: 499.43 | bwd_inner_microstep: 499.42 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.90 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-01 23:44:02,140] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 255.77 | bwd_microstep: 516.85 | bwd_inner_microstep: 516.83 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 23:44:02,947] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 298.14 | bwd_microstep: 492.19 | bwd_inner_microstep: 492.17 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.17 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:44:03,750] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 348.22 | bwd_microstep: 434.46 | bwd_inner_microstep: 434.45 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:44:04,589] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 343.97 | bwd_microstep: 474.59 | bwd_inner_microstep: 474.57 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-01 23:44:05,443] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 321.41 | bwd_microstep: 496.96 | bwd_inner_microstep: 496.94 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 23:44:06,230] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 276.24 | bwd_microstep: 480.39 | bwd_inner_microstep: 480.37 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 23:44:07,073] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 361.89 | bwd_microstep: 462.19 | bwd_inner_microstep: 462.17 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1944 +[2025-05-01 23:44:07,849] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 234.55 | bwd_microstep: 507.62 | bwd_inner_microstep: 507.60 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1902 +[2025-05-01 23:44:08,833] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.07 | optimizer_gradients: 2.20 | optimizer_step: 16.26 +[2025-05-01 23:44:08,833] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.75 | bwd_microstep: 747.98 | bwd_inner_microstep: 501.61 | bwd_allreduce_microstep: 246.30 | step_microstep: 24.45 +[2025-05-01 23:44:08,835] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4722.79 | bwd: 7907.92 | bwd_inner: 7661.29 | bwd_allreduce: 246.38 | step: 40.44 + 6%|▋ | 564/8720 [1:28:42<26:28:08, 11.68s/it] {'loss': 1.3639, 'grad_norm': 5.8081841468811035, 'learning_rate': 9.968575900383466e-06, 'epoch': 0.65} + 6%|▋ | 564/8720 [1:28:42<26:28:08, 11.68s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 353 +[2025-05-01 23:44:09,081] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 101.05 | bwd_microstep: 122.48 | bwd_inner_microstep: 122.46 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1903 +[2025-05-01 23:44:09,950] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 313.94 | bwd_microstep: 521.10 | bwd_inner_microstep: 521.08 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1894 +[2025-05-01 23:44:10,783] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 281.20 | bwd_microstep: 524.90 | bwd_inner_microstep: 524.89 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.32 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 351 +[2025-05-01 23:44:11,021] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 79.24 | bwd_microstep: 129.70 | bwd_inner_microstep: 129.68 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1889 +[2025-05-01 23:44:11,819] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 324.38 | bwd_microstep: 439.87 | bwd_inner_microstep: 439.85 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-01 23:44:12,557] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 281.79 | bwd_microstep: 426.07 | bwd_inner_microstep: 426.05 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1364 +[2025-05-01 23:44:13,225] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 239.01 | bwd_microstep: 401.72 | bwd_inner_microstep: 401.70 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.33 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 332 +[2025-05-01 23:44:13,456] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 72.48 | bwd_microstep: 137.12 | bwd_inner_microstep: 137.10 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.33 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 846 +[2025-05-01 23:44:13,893] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 209.20 | bwd_microstep: 195.86 | bwd_inner_microstep: 195.84 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.32 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1347 +[2025-05-01 23:44:14,559] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 261.72 | bwd_microstep: 376.18 | bwd_inner_microstep: 376.17 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1353 +[2025-05-01 23:44:15,226] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 228.68 | bwd_microstep: 410.08 | bwd_inner_microstep: 409.96 | bwd_allreduce_microstep: 0.09 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-01 23:44:16,122] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 371.40 | bwd_microstep: 503.88 | bwd_inner_microstep: 503.86 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 330 +[2025-05-01 23:44:16,335] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 81.11 | bwd_microstep: 109.88 | bwd_inner_microstep: 109.40 | bwd_allreduce_microstep: 0.47 | step_microstep: 0.23 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 318 +[2025-05-01 23:44:16,550] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 80.18 | bwd_microstep: 117.74 | bwd_inner_microstep: 116.92 | bwd_allreduce_microstep: 0.80 | step_microstep: 2.31 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 23:44:17,411] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 324.82 | bwd_microstep: 504.82 | bwd_inner_microstep: 504.80 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.33 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1899 +[2025-05-01 23:44:18,667] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.22 | optimizer_step: 17.41 +[2025-05-01 23:44:18,668] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 330.94 | bwd_microstep: 867.34 | bwd_inner_microstep: 509.67 | bwd_allreduce_microstep: 357.66 | step_microstep: 25.14 +[2025-05-01 23:44:18,669] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 3581.10 | bwd: 5788.77 | bwd_inner: 5429.45 | bwd_allreduce: 358.62 | step: 53.52 + 6%|▋ | 565/8720 [1:28:52<25:12:41, 11.13s/it] {'loss': 1.1495, 'grad_norm': 3.2402000427246094, 'learning_rate': 9.968367669287002e-06, 'epoch': 0.65} + 6%|▋ | 565/8720 [1:28:52<25:12:41, 11.13s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-01 23:44:19,495] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 288.95 | bwd_microstep: 508.31 | bwd_inner_microstep: 508.28 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.33 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-01 23:44:20,356] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 332.27 | bwd_microstep: 499.69 | bwd_inner_microstep: 499.67 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-01 23:44:21,276] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 402.37 | bwd_microstep: 500.42 | bwd_inner_microstep: 500.40 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-01 23:44:22,131] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 352.09 | bwd_microstep: 483.45 | bwd_inner_microstep: 483.43 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.87 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1350 +[2025-05-01 23:44:22,712] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 202.62 | bwd_microstep: 362.40 | bwd_inner_microstep: 362.18 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 331 +[2025-05-01 23:44:22,968] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 97.70 | bwd_microstep: 128.77 | bwd_inner_microstep: 128.75 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.48 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-01 23:44:23,811] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 322.13 | bwd_microstep: 489.96 | bwd_inner_microstep: 489.95 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 832 +[2025-05-01 23:44:24,230] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 134.07 | bwd_microstep: 255.15 | bwd_inner_microstep: 255.13 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.33 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 23:44:25,048] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 305.32 | bwd_microstep: 484.64 | bwd_inner_microstep: 484.62 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.41 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 23:44:25,845] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 329.77 | bwd_microstep: 449.89 | bwd_inner_microstep: 449.87 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 23:44:26,643] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 347.39 | bwd_microstep: 435.34 | bwd_inner_microstep: 435.32 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 23:44:27,452] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 347.77 | bwd_microstep: 443.01 | bwd_inner_microstep: 442.99 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-01 23:44:28,278] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 305.96 | bwd_microstep: 490.45 | bwd_inner_microstep: 490.43 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.22 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 23:44:29,110] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 314.88 | bwd_microstep: 486.53 | bwd_inner_microstep: 486.51 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 23:44:29,917] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 284.01 | bwd_microstep: 488.54 | bwd_inner_microstep: 488.52 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-01 23:44:30,971] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.13 | optimizer_step: 17.44 +[2025-05-01 23:44:30,973] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 290.99 | bwd_microstep: 711.12 | bwd_inner_microstep: 491.41 | bwd_allreduce_microstep: 219.66 | step_microstep: 24.88 +[2025-05-01 23:44:30,974] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4658.18 | bwd: 7217.67 | bwd_inner: 6997.49 | bwd_allreduce: 219.94 | step: 44.23 + 6%|▋ | 566/8720 [1:29:04<26:00:23, 11.48s/it] {'loss': 0.8855, 'grad_norm': 4.730573654174805, 'learning_rate': 9.968158752736868e-06, 'epoch': 0.65} + 6%|▋ | 566/8720 [1:29:04<26:00:23, 11.48s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 348 +[2025-05-01 23:44:31,257] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 102.95 | bwd_microstep: 139.41 | bwd_inner_microstep: 139.38 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.33 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-01 23:44:32,043] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 278.17 | bwd_microstep: 487.03 | bwd_inner_microstep: 487.01 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.17 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1891 +[2025-05-01 23:44:32,866] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 297.15 | bwd_microstep: 498.68 | bwd_inner_microstep: 498.67 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-01 23:44:33,767] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 402.94 | bwd_microstep: 478.94 | bwd_inner_microstep: 478.93 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.47 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-01 23:44:34,559] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 290.57 | bwd_microstep: 483.02 | bwd_inner_microstep: 483.00 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-01 23:44:35,373] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 291.67 | bwd_microstep: 494.01 | bwd_inner_microstep: 493.99 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 23:44:36,191] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 399.52 | bwd_microstep: 402.30 | bwd_inner_microstep: 402.28 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-01 23:44:37,071] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 391.38 | bwd_microstep: 470.67 | bwd_inner_microstep: 470.65 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.30 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 325 +[2025-05-01 23:44:37,309] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 79.76 | bwd_microstep: 128.85 | bwd_inner_microstep: 128.83 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-01 23:44:38,147] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 317.34 | bwd_microstep: 493.39 | bwd_inner_microstep: 493.37 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 835 +[2025-05-01 23:44:38,595] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 170.01 | bwd_microstep: 264.43 | bwd_inner_microstep: 264.17 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 23:44:39,473] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 349.14 | bwd_microstep: 508.94 | bwd_inner_microstep: 508.92 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 23:44:40,328] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 314.88 | bwd_microstep: 512.22 | bwd_inner_microstep: 512.20 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 23:44:41,139] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 322.36 | bwd_microstep: 470.37 | bwd_inner_microstep: 470.35 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-01 23:44:41,788] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.76 | bwd_microstep: 443.99 | bwd_inner_microstep: 443.97 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.33 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 473 +[2025-05-01 23:44:42,336] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.15 | optimizer_step: 26.30 +[2025-05-01 23:44:42,336] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 81.49 | bwd_microstep: 406.49 | bwd_inner_microstep: 165.49 | bwd_allreduce_microstep: 240.96 | step_microstep: 33.51 +[2025-05-01 23:44:42,337] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4276.96 | bwd: 6682.76 | bwd_inner: 6441.25 | bwd_allreduce: 241.16 | step: 49.42 + 7%|▋ | 567/8720 [1:29:16<25:55:13, 11.45s/it] {'loss': 0.8067, 'grad_norm': 3.8740148544311523, 'learning_rate': 9.967949150761887e-06, 'epoch': 0.65} + 7%|▋ | 567/8720 [1:29:16<25:55:13, 11.45s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1990 +[2025-05-01 23:44:43,257] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 360.57 | bwd_microstep: 538.60 | bwd_inner_microstep: 538.59 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1926 +[2025-05-01 23:44:44,133] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 367.97 | bwd_microstep: 488.61 | bwd_inner_microstep: 488.60 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1896 +[2025-05-01 23:44:44,984] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 334.33 | bwd_microstep: 486.81 | bwd_inner_microstep: 486.79 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-01 23:44:45,848] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 330.91 | bwd_microstep: 514.67 | bwd_inner_microstep: 514.65 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.51 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-01 23:44:46,706] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 318.95 | bwd_microstep: 507.26 | bwd_inner_microstep: 507.24 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-01 23:44:47,570] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 320.09 | bwd_microstep: 515.67 | bwd_inner_microstep: 515.60 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-01 23:44:48,507] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 408.80 | bwd_microstep: 511.89 | bwd_inner_microstep: 511.87 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.54 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 835 +[2025-05-01 23:44:48,905] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 100.35 | bwd_microstep: 279.18 | bwd_inner_microstep: 279.16 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-01 23:44:49,757] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 314.74 | bwd_microstep: 507.59 | bwd_inner_microstep: 507.57 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1360 +[2025-05-01 23:44:50,423] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 248.83 | bwd_microstep: 398.12 | bwd_inner_microstep: 398.10 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.33 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 23:44:51,264] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 313.63 | bwd_microstep: 495.69 | bwd_inner_microstep: 495.67 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.50 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 23:44:52,101] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 314.86 | bwd_microstep: 491.69 | bwd_inner_microstep: 491.67 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 23:44:53,035] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 389.10 | bwd_microstep: 518.47 | bwd_inner_microstep: 518.46 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.94 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 23:44:53,866] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 315.24 | bwd_microstep: 495.05 | bwd_inner_microstep: 495.03 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 23:44:54,703] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 310.07 | bwd_microstep: 494.40 | bwd_inner_microstep: 494.38 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.31 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-01 23:44:55,932] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.15 | optimizer_step: 25.99 +[2025-05-01 23:44:55,932] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 391.03 | bwd_microstep: 775.29 | bwd_inner_microstep: 493.39 | bwd_allreduce_microstep: 281.85 | step_microstep: 33.25 +[2025-05-01 23:44:55,933] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 5139.37 | bwd: 8019.01 | bwd_inner: 7736.78 | bwd_allreduce: 281.95 | step: 54.06 + 7%|▋ | 568/8720 [1:29:29<27:22:41, 12.09s/it] {'loss': 1.0738, 'grad_norm': 5.278524398803711, 'learning_rate': 9.967738863390976e-06, 'epoch': 0.65} + 7%|▋ | 568/8720 [1:29:29<27:22:41, 12.09s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 368 +[2025-05-01 23:44:56,188] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 100.61 | bwd_microstep: 134.19 | bwd_inner_microstep: 134.17 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-01 23:44:57,025] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 316.39 | bwd_microstep: 491.42 | bwd_inner_microstep: 491.40 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-01 23:44:57,888] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 321.58 | bwd_microstep: 510.60 | bwd_inner_microstep: 510.58 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-01 23:44:58,784] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 324.97 | bwd_microstep: 539.57 | bwd_inner_microstep: 539.55 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.59 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-01 23:44:59,643] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 320.99 | bwd_microstep: 518.97 | bwd_inner_microstep: 518.95 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-01 23:45:00,490] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 310.07 | bwd_microstep: 505.22 | bwd_inner_microstep: 505.20 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.39 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 326 +[2025-05-01 23:45:00,733] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 98.83 | bwd_microstep: 114.47 | bwd_inner_microstep: 114.45 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.33 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:45:01,629] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 366.59 | bwd_microstep: 497.71 | bwd_inner_microstep: 497.69 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.31 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-01 23:45:02,456] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 264.04 | bwd_microstep: 532.03 | bwd_inner_microstep: 532.01 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.32 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-01 23:45:03,314] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 330.36 | bwd_microstep: 504.29 | bwd_inner_microstep: 504.27 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-01 23:45:04,253] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 323.21 | bwd_microstep: 585.38 | bwd_inner_microstep: 585.36 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.98 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 23:45:05,068] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 288.03 | bwd_microstep: 509.60 | bwd_inner_microstep: 509.58 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 23:45:05,989] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 420.27 | bwd_microstep: 482.14 | bwd_inner_microstep: 482.12 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.30 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 23:45:06,926] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 329.95 | bwd_microstep: 576.61 | bwd_inner_microstep: 576.59 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.00 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 23:45:07,734] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 289.11 | bwd_microstep: 501.46 | bwd_inner_microstep: 501.44 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 23:45:09,178] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.15 | optimizer_step: 16.82 +[2025-05-01 23:45:09,179] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 421.26 | bwd_microstep: 969.83 | bwd_inner_microstep: 487.17 | bwd_allreduce_microstep: 482.64 | step_microstep: 26.47 +[2025-05-01 23:45:09,180] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4826.25 | bwd: 7973.48 | bwd_inner: 7490.56 | bwd_allreduce: 482.71 | step: 49.69 + 7%|▋ | 569/8720 [1:29:42<28:09:45, 12.44s/it] {'loss': 0.9778, 'grad_norm': 4.254790782928467, 'learning_rate': 9.96752789065315e-06, 'epoch': 0.65} + 7%|▋ | 569/8720 [1:29:42<28:09:45, 12.44s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1966 +[2025-05-01 23:45:10,119] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 317.84 | bwd_microstep: 579.91 | bwd_inner_microstep: 579.89 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.37 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1921 +[2025-05-01 23:45:11,049] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 338.91 | bwd_microstep: 571.12 | bwd_inner_microstep: 571.11 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-01 23:45:11,939] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 381.63 | bwd_microstep: 489.70 | bwd_inner_microstep: 489.68 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 852 +[2025-05-01 23:45:12,401] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 222.28 | bwd_microstep: 209.93 | bwd_inner_microstep: 209.66 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.09 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1371 +[2025-05-01 23:45:13,076] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 293.83 | bwd_microstep: 364.62 | bwd_inner_microstep: 364.48 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 23:45:14,010] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 423.96 | bwd_microstep: 491.07 | bwd_inner_microstep: 491.05 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-01 23:45:14,904] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 347.40 | bwd_microstep: 515.01 | bwd_inner_microstep: 514.99 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.30 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 834 +[2025-05-01 23:45:15,344] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 214.93 | bwd_microstep: 196.31 | bwd_inner_microstep: 196.12 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 835 +[2025-05-01 23:45:15,783] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 176.47 | bwd_microstep: 235.55 | bwd_inner_microstep: 235.53 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.31 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 23:45:16,680] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 341.77 | bwd_microstep: 522.87 | bwd_inner_microstep: 522.85 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.83 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-01 23:45:17,486] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 301.49 | bwd_microstep: 487.80 | bwd_inner_microstep: 487.78 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-01 23:45:18,355] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 319.11 | bwd_microstep: 523.39 | bwd_inner_microstep: 523.37 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.21 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 23:45:19,299] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 413.36 | bwd_microstep: 510.36 | bwd_inner_microstep: 510.34 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 23:45:20,133] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 305.40 | bwd_microstep: 505.42 | bwd_inner_microstep: 505.40 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.47 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 23:45:20,994] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 320.81 | bwd_microstep: 506.20 | bwd_inner_microstep: 506.18 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.32 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 23:45:22,261] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.07 | optimizer_gradients: 2.22 | optimizer_step: 16.22 +[2025-05-01 23:45:22,262] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 383.31 | bwd_microstep: 828.49 | bwd_inner_microstep: 462.49 | bwd_allreduce_microstep: 365.96 | step_microstep: 24.41 +[2025-05-01 23:45:22,263] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 5102.44 | bwd: 7537.78 | bwd_inner: 7171.18 | bwd_allreduce: 366.23 | step: 42.75 + 7%|▋ | 570/8720 [1:29:56<28:35:44, 12.63s/it] {'loss': 1.1969, 'grad_norm': 5.756519317626953, 'learning_rate': 9.967316232577511e-06, 'epoch': 0.65} + 7%|▋ | 570/8720 [1:29:56<28:35:44, 12.63s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1911 +[2025-05-01 23:45:23,175] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 400.93 | bwd_microstep: 489.31 | bwd_inner_microstep: 489.29 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1130 +[2025-05-01 23:45:23,699] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 220.37 | bwd_microstep: 283.78 | bwd_inner_microstep: 283.76 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 381 +[2025-05-01 23:45:23,977] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 106.82 | bwd_microstep: 143.63 | bwd_inner_microstep: 143.16 | bwd_allreduce_microstep: 0.45 | step_microstep: 0.25 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-01 23:45:24,786] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 325.14 | bwd_microstep: 466.92 | bwd_inner_microstep: 466.90 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 346 +[2025-05-01 23:45:25,029] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 100.37 | bwd_microstep: 124.98 | bwd_inner_microstep: 124.97 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.49 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1371 +[2025-05-01 23:45:25,652] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 221.77 | bwd_microstep: 373.75 | bwd_inner_microstep: 373.73 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 845 +[2025-05-01 23:45:26,089] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 201.69 | bwd_microstep: 210.67 | bwd_inner_microstep: 210.46 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-01 23:45:26,982] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 367.20 | bwd_microstep: 497.59 | bwd_inner_microstep: 497.57 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-01 23:45:27,874] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 368.53 | bwd_microstep: 505.50 | bwd_inner_microstep: 505.48 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.87 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-01 23:45:28,701] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 300.74 | bwd_microstep: 506.32 | bwd_inner_microstep: 506.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.30 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1344 +[2025-05-01 23:45:29,348] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 235.24 | bwd_microstep: 384.83 | bwd_inner_microstep: 384.82 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 23:45:30,219] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 353.40 | bwd_microstep: 481.40 | bwd_inner_microstep: 481.39 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-01 23:45:31,057] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 309.18 | bwd_microstep: 500.89 | bwd_inner_microstep: 500.87 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 318 +[2025-05-01 23:45:31,282] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.50 | bwd_microstep: 114.54 | bwd_inner_microstep: 114.20 | bwd_allreduce_microstep: 0.14 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-01 23:45:32,126] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 338.20 | bwd_microstep: 487.26 | bwd_inner_microstep: 487.25 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-01 23:45:33,211] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.09 | optimizer_step: 16.81 +[2025-05-01 23:45:33,212] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 337.63 | bwd_microstep: 694.46 | bwd_inner_microstep: 485.71 | bwd_allreduce_microstep: 208.70 | step_microstep: 24.69 +[2025-05-01 23:45:33,213] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4280.65 | bwd: 6265.88 | bwd_inner: 6055.92 | bwd_allreduce: 209.02 | step: 38.29 + 7%|▋ | 571/8720 [1:30:06<27:27:07, 12.13s/it] {'loss': 1.0662, 'grad_norm': 3.86820387840271, 'learning_rate': 9.967103889193263e-06, 'epoch': 0.65} + 7%|▋ | 571/8720 [1:30:06<27:27:07, 12.13s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1907 +[2025-05-01 23:45:34,091] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 340.26 | bwd_microstep: 496.03 | bwd_inner_microstep: 496.01 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.81 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1900 +[2025-05-01 23:45:34,864] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 279.34 | bwd_microstep: 474.99 | bwd_inner_microstep: 474.97 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.48 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 367 +[2025-05-01 23:45:35,123] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.08 | bwd_microstep: 133.88 | bwd_inner_microstep: 133.86 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.33 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1894 +[2025-05-01 23:45:35,932] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 311.49 | bwd_microstep: 465.03 | bwd_inner_microstep: 465.01 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1892 +[2025-05-01 23:45:36,791] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 377.21 | bwd_microstep: 464.25 | bwd_inner_microstep: 464.23 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-01 23:45:37,582] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 309.47 | bwd_microstep: 461.02 | bwd_inner_microstep: 461.00 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 23:45:38,332] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 278.16 | bwd_microstep: 437.51 | bwd_inner_microstep: 437.49 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.28 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 839 +[2025-05-01 23:45:38,718] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 192.53 | bwd_microstep: 162.71 | bwd_inner_microstep: 162.69 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.50 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-01 23:45:39,509] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 297.93 | bwd_microstep: 460.14 | bwd_inner_microstep: 460.12 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 324 +[2025-05-01 23:45:39,755] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 103.25 | bwd_microstep: 124.06 | bwd_inner_microstep: 124.04 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.31 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 23:45:40,522] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 275.01 | bwd_microstep: 462.47 | bwd_inner_microstep: 462.46 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:45:41,295] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 275.72 | bwd_microstep: 464.98 | bwd_inner_microstep: 464.96 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 23:45:42,105] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 317.58 | bwd_microstep: 460.30 | bwd_inner_microstep: 460.28 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-01 23:45:42,951] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 373.28 | bwd_microstep: 456.20 | bwd_inner_microstep: 456.18 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 23:45:43,771] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 309.80 | bwd_microstep: 492.53 | bwd_inner_microstep: 492.51 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.22 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1917 +[2025-05-01 23:45:44,812] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.12 | optimizer_step: 16.15 +[2025-05-01 23:45:44,813] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 403.77 | bwd_microstep: 596.77 | bwd_inner_microstep: 478.39 | bwd_allreduce_microstep: 118.33 | step_microstep: 24.27 +[2025-05-01 23:45:44,814] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4537.79 | bwd: 6612.86 | bwd_inner: 6494.21 | bwd_allreduce: 118.42 | step: 43.52 + 7%|▋ | 572/8720 [1:30:18<27:05:20, 11.97s/it] {'loss': 1.0787, 'grad_norm': 4.945301055908203, 'learning_rate': 9.966890860529701e-06, 'epoch': 0.66} + 7%|▋ | 572/8720 [1:30:18<27:05:20, 11.97s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1962 +[2025-05-01 23:45:45,742] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 406.95 | bwd_microstep: 498.29 | bwd_inner_microstep: 498.27 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.90 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1935 +[2025-05-01 23:45:46,520] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 273.26 | bwd_microstep: 486.20 | bwd_inner_microstep: 486.18 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.51 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 895 +[2025-05-01 23:45:46,930] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 218.48 | bwd_microstep: 160.51 | bwd_inner_microstep: 160.49 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1899 +[2025-05-01 23:45:47,810] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 352.54 | bwd_microstep: 497.85 | bwd_inner_microstep: 497.83 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1889 +[2025-05-01 23:45:48,584] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 281.68 | bwd_microstep: 473.10 | bwd_inner_microstep: 473.09 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1373 +[2025-05-01 23:45:49,183] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 199.58 | bwd_microstep: 371.60 | bwd_inner_microstep: 371.56 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-01 23:45:50,058] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 401.49 | bwd_microstep: 454.97 | bwd_inner_microstep: 454.95 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-01 23:45:50,778] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 239.09 | bwd_microstep: 453.43 | bwd_inner_microstep: 453.41 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.22 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 842 +[2025-05-01 23:45:51,229] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 199.78 | bwd_microstep: 237.14 | bwd_inner_microstep: 237.12 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 841 +[2025-05-01 23:45:51,655] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 119.86 | bwd_microstep: 289.88 | bwd_inner_microstep: 289.86 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.33 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-01 23:45:52,398] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 280.89 | bwd_microstep: 440.05 | bwd_inner_microstep: 440.04 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.32 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:45:53,259] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 342.38 | bwd_microstep: 488.46 | bwd_inner_microstep: 488.45 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 23:45:54,129] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 381.34 | bwd_microstep: 469.33 | bwd_inner_microstep: 469.31 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.67 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 23:45:54,953] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 306.21 | bwd_microstep: 498.80 | bwd_inner_microstep: 498.78 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 23:45:55,777] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 284.54 | bwd_microstep: 510.45 | bwd_inner_microstep: 510.43 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.33 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1981 +[2025-05-01 23:45:56,999] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.12 | optimizer_step: 17.12 +[2025-05-01 23:45:57,000] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 354.87 | bwd_microstep: 817.46 | bwd_inner_microstep: 545.96 | bwd_allreduce_microstep: 271.46 | step_microstep: 25.41 +[2025-05-01 23:45:57,002] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4642.87 | bwd: 7147.52 | bwd_inner: 6875.74 | bwd_allreduce: 271.54 | step: 46.35 + 7%|▋ | 573/8720 [1:30:30<27:14:03, 12.03s/it] {'loss': 1.248, 'grad_norm': 5.278702259063721, 'learning_rate': 9.966677146616215e-06, 'epoch': 0.66} + 7%|▋ | 573/8720 [1:30:30<27:14:03, 12.03s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1921 +[2025-05-01 23:45:57,711] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 278.96 | bwd_microstep: 408.83 | bwd_inner_microstep: 408.81 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1894 +[2025-05-01 23:45:58,593] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 365.70 | bwd_microstep: 486.71 | bwd_inner_microstep: 486.69 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-01 23:45:59,494] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 396.47 | bwd_microstep: 486.14 | bwd_inner_microstep: 486.12 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 340 +[2025-05-01 23:45:59,727] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.38 | bwd_microstep: 122.76 | bwd_inner_microstep: 122.74 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.32 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-01 23:46:00,602] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 335.19 | bwd_microstep: 503.86 | bwd_inner_microstep: 503.85 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.31 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-01 23:46:01,474] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 324.89 | bwd_microstep: 510.69 | bwd_inner_microstep: 510.67 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.31 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-01 23:46:02,308] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 318.60 | bwd_microstep: 485.00 | bwd_inner_microstep: 484.99 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.24 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 23:46:03,193] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 338.86 | bwd_microstep: 515.14 | bwd_inner_microstep: 515.12 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.05 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1351 +[2025-05-01 23:46:03,836] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 241.17 | bwd_microstep: 382.87 | bwd_inner_microstep: 382.85 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.48 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 23:46:04,657] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 322.61 | bwd_microstep: 466.78 | bwd_inner_microstep: 466.76 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1346 +[2025-05-01 23:46:05,288] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 268.96 | bwd_microstep: 335.67 | bwd_inner_microstep: 335.48 | bwd_allreduce_microstep: 0.17 | step_microstep: 0.33 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 23:46:06,153] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 322.41 | bwd_microstep: 522.44 | bwd_inner_microstep: 522.42 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.31 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1344 +[2025-05-01 23:46:06,768] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 219.12 | bwd_microstep: 367.67 | bwd_inner_microstep: 367.63 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 23:46:07,586] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 398.98 | bwd_microstep: 401.47 | bwd_inner_microstep: 401.46 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 23:46:08,478] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 361.57 | bwd_microstep: 495.79 | bwd_inner_microstep: 495.77 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 23:46:09,601] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.12 | optimizer_step: 16.88 +[2025-05-01 23:46:09,602] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 310.63 | bwd_microstep: 765.25 | bwd_inner_microstep: 513.08 | bwd_allreduce_microstep: 252.16 | step_microstep: 26.45 +[2025-05-01 23:46:09,603] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4897.41 | bwd: 7257.10 | bwd_inner: 7004.47 | bwd_allreduce: 252.40 | step: 47.07 + 7%|▋ | 574/8720 [1:30:43<27:37:03, 12.21s/it] {'loss': 0.8401, 'grad_norm': 6.356505393981934, 'learning_rate': 9.966462747482291e-06, 'epoch': 0.66} + 7%|▋ | 574/8720 [1:30:43<27:37:03, 12.21s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1914 +[2025-05-01 23:46:10,452] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 303.35 | bwd_microstep: 505.43 | bwd_inner_microstep: 505.42 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 371 +[2025-05-01 23:46:10,681] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 77.96 | bwd_microstep: 135.19 | bwd_inner_microstep: 135.17 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.46 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1901 +[2025-05-01 23:46:11,502] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 324.99 | bwd_microstep: 466.45 | bwd_inner_microstep: 466.43 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1889 +[2025-05-01 23:46:12,333] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 323.14 | bwd_microstep: 489.63 | bwd_inner_microstep: 489.61 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-01 23:46:13,137] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 388.15 | bwd_microstep: 400.76 | bwd_inner_microstep: 400.74 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-01 23:46:14,038] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 368.10 | bwd_microstep: 502.75 | bwd_inner_microstep: 502.71 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 23:46:14,897] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 318.93 | bwd_microstep: 509.91 | bwd_inner_microstep: 509.90 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-01 23:46:15,755] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 309.55 | bwd_microstep: 516.34 | bwd_inner_microstep: 516.32 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 323 +[2025-05-01 23:46:16,010] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 92.54 | bwd_microstep: 132.41 | bwd_inner_microstep: 132.39 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.33 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 23:46:16,810] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 347.30 | bwd_microstep: 423.12 | bwd_inner_microstep: 423.09 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 23:46:17,630] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 401.76 | bwd_microstep: 403.17 | bwd_inner_microstep: 403.15 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 23:46:18,457] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 280.01 | bwd_microstep: 528.69 | bwd_inner_microstep: 528.67 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.79 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 23:46:19,293] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 296.83 | bwd_microstep: 519.92 | bwd_inner_microstep: 519.90 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.48 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 23:46:20,125] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 316.66 | bwd_microstep: 484.86 | bwd_inner_microstep: 484.84 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.57 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 23:46:20,949] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 304.81 | bwd_microstep: 501.56 | bwd_inner_microstep: 501.54 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.93 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1883 +[2025-05-01 23:46:22,102] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.20 | optimizer_step: 17.96 +[2025-05-01 23:46:22,103] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 284.37 | bwd_microstep: 826.14 | bwd_inner_microstep: 522.08 | bwd_allreduce_microstep: 304.02 | step_microstep: 25.92 +[2025-05-01 23:46:22,105] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4738.37 | bwd: 7346.36 | bwd_inner: 7041.99 | bwd_allreduce: 304.10 | step: 43.19 + 7%|▋ | 575/8720 [1:30:55<27:48:53, 12.29s/it] {'loss': 1.3859, 'grad_norm': 6.254643440246582, 'learning_rate': 9.966247663157505e-06, 'epoch': 0.66} + 7%|▋ | 575/8720 [1:30:55<27:48:53, 12.29s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1925 +[2025-05-01 23:46:23,009] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 410.00 | bwd_microstep: 472.72 | bwd_inner_microstep: 472.71 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1916 +[2025-05-01 23:46:23,841] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 395.99 | bwd_microstep: 418.36 | bwd_inner_microstep: 418.34 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 866 +[2025-05-01 23:46:24,314] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 206.24 | bwd_microstep: 239.55 | bwd_inner_microstep: 239.54 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.52 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-01 23:46:25,191] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 326.60 | bwd_microstep: 522.66 | bwd_inner_microstep: 522.64 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-01 23:46:26,056] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 313.54 | bwd_microstep: 519.39 | bwd_inner_microstep: 519.37 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-01 23:46:26,916] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 321.68 | bwd_microstep: 504.29 | bwd_inner_microstep: 504.27 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.28 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-01 23:46:27,785] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 333.08 | bwd_microstep: 501.53 | bwd_inner_microstep: 501.51 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 329 +[2025-05-01 23:46:28,026] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 102.20 | bwd_microstep: 110.79 | bwd_inner_microstep: 110.70 | bwd_allreduce_microstep: 0.03 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-01 23:46:28,930] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 395.61 | bwd_microstep: 489.92 | bwd_inner_microstep: 489.90 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.31 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 839 +[2025-05-01 23:46:29,350] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 111.00 | bwd_microstep: 279.05 | bwd_inner_microstep: 279.03 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 23:46:30,219] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 320.35 | bwd_microstep: 517.15 | bwd_inner_microstep: 517.13 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.31 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-01 23:46:31,083] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 315.13 | bwd_microstep: 513.42 | bwd_inner_microstep: 513.41 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.49 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 23:46:31,924] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 307.69 | bwd_microstep: 501.78 | bwd_inner_microstep: 501.76 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 318 +[2025-05-01 23:46:32,160] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.13 | bwd_microstep: 113.72 | bwd_inner_microstep: 113.53 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.14 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 316 +[2025-05-01 23:46:32,396] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 96.43 | bwd_microstep: 120.90 | bwd_inner_microstep: 120.88 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.32 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 23:46:33,566] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.16 | optimizer_step: 19.95 +[2025-05-01 23:46:33,567] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 314.51 | bwd_microstep: 798.72 | bwd_inner_microstep: 517.21 | bwd_allreduce_microstep: 281.46 | step_microstep: 27.43 +[2025-05-01 23:46:33,568] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4364.13 | bwd: 6624.01 | bwd_inner: 6341.98 | bwd_allreduce: 281.67 | step: 52.74 + 7%|▋ | 576/8720 [1:31:07<27:14:47, 12.04s/it] {'loss': 1.0656, 'grad_norm': 4.4704060554504395, 'learning_rate': 9.966031893671536e-06, 'epoch': 0.66} + 7%|▋ | 576/8720 [1:31:07<27:14:47, 12.04s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1908 +[2025-05-01 23:46:34,385] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 336.07 | bwd_microstep: 458.10 | bwd_inner_microstep: 458.08 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1888 +[2025-05-01 23:46:35,199] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 321.11 | bwd_microstep: 465.17 | bwd_inner_microstep: 465.16 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.30 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-01 23:46:35,990] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 326.40 | bwd_microstep: 430.53 | bwd_inner_microstep: 430.51 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.53 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1366 +[2025-05-01 23:46:36,643] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 303.84 | bwd_microstep: 320.07 | bwd_inner_microstep: 319.90 | bwd_allreduce_microstep: 0.08 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-01 23:46:37,453] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 336.07 | bwd_microstep: 456.34 | bwd_inner_microstep: 456.33 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 839 +[2025-05-01 23:46:37,867] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 192.21 | bwd_microstep: 205.40 | bwd_inner_microstep: 205.38 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.32 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:46:38,612] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 220.10 | bwd_microstep: 495.09 | bwd_inner_microstep: 495.07 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.33 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 844 +[2025-05-01 23:46:39,007] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 202.91 | bwd_microstep: 163.71 | bwd_inner_microstep: 163.64 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-01 23:46:39,881] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 369.35 | bwd_microstep: 488.50 | bwd_inner_microstep: 488.48 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 834 +[2025-05-01 23:46:40,275] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 138.75 | bwd_microstep: 238.43 | bwd_inner_microstep: 238.16 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 23:46:41,092] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 323.04 | bwd_microstep: 473.70 | bwd_inner_microstep: 473.68 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 23:46:41,683] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 300.58 | bwd_microstep: 272.79 | bwd_inner_microstep: 272.77 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 23:46:42,364] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.39 | bwd_microstep: 474.88 | bwd_inner_microstep: 474.86 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.96 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2140 +[2025-05-01 23:46:43,175] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 272.73 | bwd_microstep: 518.84 | bwd_inner_microstep: 518.82 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-01 23:46:43,981] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 298.44 | bwd_microstep: 473.74 | bwd_inner_microstep: 473.72 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1368 +[2025-05-01 23:46:44,817] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.12 | optimizer_step: 16.81 +[2025-05-01 23:46:44,818] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 273.56 | bwd_microstep: 508.45 | bwd_inner_microstep: 339.33 | bwd_allreduce_microstep: 169.07 | step_microstep: 26.08 +[2025-05-01 23:46:44,819] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4403.44 | bwd: 6443.85 | bwd_inner: 6273.94 | bwd_allreduce: 169.41 | step: 41.88 + 7%|▋ | 577/8720 [1:31:18<26:42:25, 11.81s/it] {'loss': 0.9501, 'grad_norm': 5.232212066650391, 'learning_rate': 9.965815439054146e-06, 'epoch': 0.66} + 7%|▋ | 577/8720 [1:31:18<26:42:25, 11.81s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-01 23:46:45,620] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 274.35 | bwd_microstep: 498.54 | bwd_inner_microstep: 498.52 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1104 +[2025-05-01 23:46:46,066] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.87 | bwd_microstep: 235.13 | bwd_inner_microstep: 234.93 | bwd_allreduce_microstep: 0.18 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 846 +[2025-05-01 23:46:46,509] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 169.43 | bwd_microstep: 242.91 | bwd_inner_microstep: 242.89 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.40 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 838 +[2025-05-01 23:46:46,910] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 159.47 | bwd_microstep: 209.03 | bwd_inner_microstep: 209.01 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.27 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-01 23:46:47,670] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 302.79 | bwd_microstep: 435.32 | bwd_inner_microstep: 435.31 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.33 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 326 +[2025-05-01 23:46:47,881] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 73.24 | bwd_microstep: 117.35 | bwd_inner_microstep: 114.87 | bwd_allreduce_microstep: 0.12 | step_microstep: 2.32 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-01 23:46:48,648] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 298.14 | bwd_microstep: 447.06 | bwd_inner_microstep: 447.04 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.17 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1346 +[2025-05-01 23:46:49,210] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 219.30 | bwd_microstep: 323.89 | bwd_inner_microstep: 323.87 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:46:50,041] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 306.69 | bwd_microstep: 502.76 | bwd_inner_microstep: 502.74 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.50 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 23:46:50,897] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 317.13 | bwd_microstep: 512.01 | bwd_inner_microstep: 511.99 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 23:46:51,742] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 314.42 | bwd_microstep: 497.20 | bwd_inner_microstep: 497.18 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.32 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 23:46:52,590] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 317.72 | bwd_microstep: 495.68 | bwd_inner_microstep: 495.66 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.31 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 23:46:53,446] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 306.26 | bwd_microstep: 517.22 | bwd_inner_microstep: 517.20 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 23:46:54,293] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 314.82 | bwd_microstep: 508.56 | bwd_inner_microstep: 508.55 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.47 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1850 +[2025-05-01 23:46:55,135] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 309.17 | bwd_microstep: 499.61 | bwd_inner_microstep: 499.59 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.30 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1948 +[2025-05-01 23:46:56,307] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.28 | optimizer_step: 18.72 +[2025-05-01 23:46:56,310] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 340.55 | bwd_microstep: 773.96 | bwd_inner_microstep: 531.12 | bwd_allreduce_microstep: 242.83 | step_microstep: 28.19 +[2025-05-01 23:46:56,311] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4210.35 | bwd: 6816.38 | bwd_inner: 6570.48 | bwd_allreduce: 245.29 | step: 54.62 + 7%|▋ | 578/8720 [1:31:30<26:29:23, 11.71s/it] {'loss': 1.0163, 'grad_norm': 6.628451824188232, 'learning_rate': 9.965598299335204e-06, 'epoch': 0.66} + 7%|▋ | 578/8720 [1:31:30<26:29:23, 11.71s/it]dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 928 +[2025-05-01 23:46:56,783] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 219.72 | bwd_microstep: 216.48 | bwd_inner_microstep: 216.46 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1997 +[2025-05-01 23:46:57,711] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 341.68 | bwd_microstep: 551.96 | bwd_inner_microstep: 551.94 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1917 +[2025-05-01 23:46:58,577] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 312.34 | bwd_microstep: 519.45 | bwd_inner_microstep: 519.43 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.44 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1928 +[2025-05-01 23:46:59,476] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 334.62 | bwd_microstep: 530.65 | bwd_inner_microstep: 530.64 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-01 23:47:00,330] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 323.58 | bwd_microstep: 498.01 | bwd_inner_microstep: 497.99 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-01 23:47:01,212] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 332.12 | bwd_microstep: 517.45 | bwd_inner_microstep: 517.44 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 844 +[2025-05-01 23:47:01,645] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 192.73 | bwd_microstep: 213.82 | bwd_inner_microstep: 211.46 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-01 23:47:02,520] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 335.18 | bwd_microstep: 508.24 | bwd_inner_microstep: 508.22 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.23 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-01 23:47:03,397] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 328.79 | bwd_microstep: 516.41 | bwd_inner_microstep: 516.40 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.22 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-01 23:47:04,255] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 308.94 | bwd_microstep: 521.48 | bwd_inner_microstep: 521.47 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 23:47:05,149] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 364.17 | bwd_microstep: 512.95 | bwd_inner_microstep: 512.93 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.70 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-01 23:47:06,012] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 325.37 | bwd_microstep: 519.22 | bwd_inner_microstep: 519.21 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-01 23:47:06,881] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 324.51 | bwd_microstep: 511.12 | bwd_inner_microstep: 511.10 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 23:47:07,760] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 320.76 | bwd_microstep: 526.38 | bwd_inner_microstep: 526.37 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 319 +[2025-05-01 23:47:08,000] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 89.12 | bwd_microstep: 120.91 | bwd_inner_microstep: 120.89 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1850 +[2025-05-01 23:47:08,991] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.18 | optimizer_step: 30.19 +[2025-05-01 23:47:08,992] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 313.15 | bwd_microstep: 609.99 | bwd_inner_microstep: 466.06 | bwd_allreduce_microstep: 143.91 | step_microstep: 39.49 +[2025-05-01 23:47:08,993] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4766.73 | bwd: 7394.54 | bwd_inner: 7248.01 | bwd_allreduce: 143.98 | step: 62.25 + 7%|▋ | 579/8720 [1:31:42<27:08:39, 12.00s/it] {'loss': 1.3725, 'grad_norm': 4.572105407714844, 'learning_rate': 9.965380474544662e-06, 'epoch': 0.66} + 7%|▋ | 579/8720 [1:31:42<27:08:39, 12.00s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1906 +[2025-05-01 23:47:09,809] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 311.20 | bwd_microstep: 464.18 | bwd_inner_microstep: 464.16 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1897 +[2025-05-01 23:47:10,671] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 331.30 | bwd_microstep: 502.77 | bwd_inner_microstep: 502.76 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.02 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1893 +[2025-05-01 23:47:11,159] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.17 | bwd_microstep: 276.36 | bwd_inner_microstep: 276.34 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 348 +[2025-05-01 23:47:11,373] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 79.74 | bwd_microstep: 119.03 | bwd_inner_microstep: 118.86 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1118 +[2025-05-01 23:47:11,879] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 185.84 | bwd_microstep: 302.69 | bwd_inner_microstep: 302.51 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 23:47:12,492] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 284.12 | bwd_microstep: 307.72 | bwd_inner_microstep: 307.70 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 840 +[2025-05-01 23:47:12,725] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 91.61 | bwd_microstep: 126.87 | bwd_inner_microstep: 126.75 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1094 +[2025-05-01 23:47:13,016] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 115.58 | bwd_microstep: 161.37 | bwd_inner_microstep: 161.35 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:47:13,825] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 314.77 | bwd_microstep: 479.90 | bwd_inner_microstep: 479.88 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 23:47:14,628] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 308.45 | bwd_microstep: 474.86 | bwd_inner_microstep: 474.84 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 23:47:15,386] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 301.85 | bwd_microstep: 426.30 | bwd_inner_microstep: 426.28 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 23:47:15,863] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.50 | bwd_microstep: 272.59 | bwd_inner_microstep: 272.57 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 23:47:16,614] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 255.48 | bwd_microstep: 478.31 | bwd_inner_microstep: 478.29 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 320 +[2025-05-01 23:47:16,858] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.97 | bwd_microstep: 119.05 | bwd_inner_microstep: 119.03 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 23:47:17,656] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 327.92 | bwd_microstep: 450.59 | bwd_inner_microstep: 450.57 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 315 +[2025-05-01 23:47:18,222] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.31 | optimizer_step: 23.90 +[2025-05-01 23:47:18,223] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 99.40 | bwd_microstep: 407.41 | bwd_inner_microstep: 117.97 | bwd_allreduce_microstep: 289.33 | step_microstep: 31.74 +[2025-05-01 23:47:18,224] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 3486.72 | bwd: 5370.03 | bwd_inner: 5079.97 | bwd_allreduce: 289.58 | step: 41.61 + 7%|▋ | 580/8720 [1:31:51<25:15:28, 11.17s/it] {'loss': 0.7806, 'grad_norm': 4.325414657592773, 'learning_rate': 9.965161964712575e-06, 'epoch': 0.67} + 7%|▋ | 580/8720 [1:31:51<25:15:28, 11.17s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 3522 +[2025-05-01 23:47:19,743] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 519.70 | bwd_microstep: 974.27 | bwd_inner_microstep: 974.25 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1949 +[2025-05-01 23:47:20,675] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 362.67 | bwd_microstep: 547.40 | bwd_inner_microstep: 547.38 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.32 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1416 +[2025-05-01 23:47:21,313] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 222.25 | bwd_microstep: 385.98 | bwd_inner_microstep: 385.88 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.09 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 359 +[2025-05-01 23:47:21,563] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 103.23 | bwd_microstep: 130.12 | bwd_inner_microstep: 130.11 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1371 +[2025-05-01 23:47:22,236] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 210.49 | bwd_microstep: 429.88 | bwd_inner_microstep: 429.83 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-01 23:47:23,131] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 357.57 | bwd_microstep: 514.16 | bwd_inner_microstep: 514.15 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-01 23:47:23,978] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 308.01 | bwd_microstep: 507.06 | bwd_inner_microstep: 507.04 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.32 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-01 23:47:24,839] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 317.06 | bwd_microstep: 512.92 | bwd_inner_microstep: 512.90 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.28 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-01 23:47:25,702] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 320.38 | bwd_microstep: 508.65 | bwd_inner_microstep: 508.63 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-01 23:47:26,612] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 360.68 | bwd_microstep: 517.81 | bwd_inner_microstep: 517.80 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:47:27,428] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 312.02 | bwd_microstep: 484.14 | bwd_inner_microstep: 484.12 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 23:47:28,213] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 317.33 | bwd_microstep: 441.35 | bwd_inner_microstep: 441.33 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 23:47:28,996] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 320.13 | bwd_microstep: 434.73 | bwd_inner_microstep: 434.70 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 23:47:29,822] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 326.22 | bwd_microstep: 480.52 | bwd_inner_microstep: 480.50 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.85 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 320 +[2025-05-01 23:47:30,033] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 67.99 | bwd_microstep: 126.00 | bwd_inner_microstep: 125.98 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.32 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1940 +[2025-05-01 23:47:31,038] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.32 | optimizer_step: 18.55 +[2025-05-01 23:47:31,041] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 331.76 | bwd_microstep: 619.06 | bwd_inner_microstep: 452.00 | bwd_allreduce_microstep: 167.04 | step_microstep: 28.07 +[2025-05-01 23:47:31,042] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4757.39 | bwd: 7614.09 | bwd_inner: 7446.60 | bwd_allreduce: 167.18 | step: 48.12 + 7%|▋ | 581/8720 [1:32:04<26:22:27, 11.67s/it] {'loss': 1.328, 'grad_norm': 5.510688781738281, 'learning_rate': 9.964942769869091e-06, 'epoch': 0.67} + 7%|▋ | 581/8720 [1:32:04<26:22:27, 11.67s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1905 +[2025-05-01 23:47:31,844] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 329.24 | bwd_microstep: 431.44 | bwd_inner_microstep: 431.42 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-01 23:47:32,681] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 314.39 | bwd_microstep: 494.89 | bwd_inner_microstep: 494.87 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.13 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-01 23:47:33,489] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 341.87 | bwd_microstep: 444.72 | bwd_inner_microstep: 444.70 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-01 23:47:34,360] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 354.26 | bwd_microstep: 484.28 | bwd_inner_microstep: 484.26 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-01 23:47:35,213] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 324.33 | bwd_microstep: 498.53 | bwd_inner_microstep: 498.51 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.18 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 840 +[2025-05-01 23:47:35,592] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 148.49 | bwd_microstep: 215.94 | bwd_inner_microstep: 215.73 | bwd_allreduce_microstep: 0.20 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 23:47:36,449] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 332.40 | bwd_microstep: 506.01 | bwd_inner_microstep: 505.99 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.28 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 23:47:37,272] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 324.98 | bwd_microstep: 468.14 | bwd_inner_microstep: 468.12 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:47:38,107] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 340.09 | bwd_microstep: 479.24 | bwd_inner_microstep: 479.00 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.88 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 23:47:38,964] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 317.46 | bwd_microstep: 508.00 | bwd_inner_microstep: 507.98 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 23:47:39,730] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 339.15 | bwd_microstep: 409.43 | bwd_inner_microstep: 409.41 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 23:47:40,521] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 324.79 | bwd_microstep: 450.41 | bwd_inner_microstep: 450.40 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-01 23:47:41,292] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 278.74 | bwd_microstep: 465.25 | bwd_inner_microstep: 465.23 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 23:47:42,011] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 306.01 | bwd_microstep: 395.68 | bwd_inner_microstep: 395.66 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2141 +[2025-05-01 23:47:42,891] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 323.67 | bwd_microstep: 540.68 | bwd_inner_microstep: 540.66 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1933 +[2025-05-01 23:47:43,875] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.27 | optimizer_step: 16.39 +[2025-05-01 23:47:43,876] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 313.45 | bwd_microstep: 630.01 | bwd_inner_microstep: 418.86 | bwd_allreduce_microstep: 211.10 | step_microstep: 24.61 +[2025-05-01 23:47:43,877] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 5013.19 | bwd: 7422.67 | bwd_inner: 7210.84 | bwd_allreduce: 211.38 | step: 35.78 + 7%|▋ | 582/8720 [1:32:17<27:09:46, 12.02s/it] {'loss': 0.7713, 'grad_norm': 4.745087623596191, 'learning_rate': 9.964722890044445e-06, 'epoch': 0.67} + 7%|▋ | 582/8720 [1:32:17<27:09:46, 12.02s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2005 +[2025-05-01 23:47:44,728] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 309.00 | bwd_microstep: 504.37 | bwd_inner_microstep: 504.35 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.84 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1891 +[2025-05-01 23:47:45,452] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 303.85 | bwd_microstep: 402.66 | bwd_inner_microstep: 402.64 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1888 +[2025-05-01 23:47:46,313] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 313.93 | bwd_microstep: 529.29 | bwd_inner_microstep: 529.27 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-01 23:47:47,108] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 345.11 | bwd_microstep: 423.95 | bwd_inner_microstep: 423.93 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.19 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1371 +[2025-05-01 23:47:47,787] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 314.60 | bwd_microstep: 334.26 | bwd_inner_microstep: 334.24 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-01 23:47:48,675] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 337.59 | bwd_microstep: 519.54 | bwd_inner_microstep: 519.52 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.89 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 840 +[2025-05-01 23:47:49,020] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 137.71 | bwd_microstep: 190.03 | bwd_inner_microstep: 190.01 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-01 23:47:49,913] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 370.93 | bwd_microstep: 485.52 | bwd_inner_microstep: 485.50 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.42 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 23:47:50,783] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 340.74 | bwd_microstep: 495.22 | bwd_inner_microstep: 495.20 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.46 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-01 23:47:51,616] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 293.19 | bwd_microstep: 507.25 | bwd_inner_microstep: 507.23 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.45 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-01 23:47:52,449] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 305.66 | bwd_microstep: 497.51 | bwd_inner_microstep: 497.49 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 23:47:53,348] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 413.32 | bwd_microstep: 466.91 | bwd_inner_microstep: 466.89 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-01 23:47:54,108] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 318.42 | bwd_microstep: 423.02 | bwd_inner_microstep: 423.01 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 23:47:54,900] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 329.62 | bwd_microstep: 443.09 | bwd_inner_microstep: 443.08 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-01 23:47:55,712] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 304.17 | bwd_microstep: 479.09 | bwd_inner_microstep: 479.07 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1949 +[2025-05-01 23:47:56,766] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.30 | optimizer_step: 20.83 +[2025-05-01 23:47:56,768] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 316.75 | bwd_microstep: 686.64 | bwd_inner_microstep: 473.93 | bwd_allreduce_microstep: 212.70 | step_microstep: 32.71 +[2025-05-01 23:47:56,770] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 5054.50 | bwd: 7388.34 | bwd_inner: 7175.38 | bwd_allreduce: 212.76 | step: 51.69 + 7%|▋ | 583/8720 [1:32:30<27:45:19, 12.28s/it] {'loss': 0.9025, 'grad_norm': 3.05385422706604, 'learning_rate': 9.96450232526898e-06, 'epoch': 0.67} + 7%|▋ | 583/8720 [1:32:30<27:45:19, 12.28s/it]dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1234 +[2025-05-01 23:47:57,375] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 257.91 | bwd_microstep: 314.51 | bwd_inner_microstep: 314.49 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 891 +[2025-05-01 23:47:57,813] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 161.40 | bwd_microstep: 240.04 | bwd_inner_microstep: 240.02 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.30 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-01 23:47:58,648] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 325.99 | bwd_microstep: 483.92 | bwd_inner_microstep: 483.91 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-01 23:47:59,519] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 323.10 | bwd_microstep: 518.42 | bwd_inner_microstep: 518.40 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-01 23:48:00,413] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 358.14 | bwd_microstep: 504.42 | bwd_inner_microstep: 504.40 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-01 23:48:01,275] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 326.82 | bwd_microstep: 511.68 | bwd_inner_microstep: 511.66 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:48:02,193] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 357.66 | bwd_microstep: 527.60 | bwd_inner_microstep: 527.59 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-01 23:48:03,051] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 309.91 | bwd_microstep: 516.56 | bwd_inner_microstep: 516.54 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 23:48:03,913] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 319.05 | bwd_microstep: 510.53 | bwd_inner_microstep: 510.52 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:48:04,786] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 334.77 | bwd_microstep: 512.08 | bwd_inner_microstep: 512.06 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.28 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 23:48:05,650] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 317.49 | bwd_microstep: 512.02 | bwd_inner_microstep: 512.01 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-01 23:48:06,516] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 305.30 | bwd_microstep: 528.43 | bwd_inner_microstep: 528.41 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 321 +[2025-05-01 23:48:06,739] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 71.18 | bwd_microstep: 131.02 | bwd_inner_microstep: 131.01 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.53 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 321 +[2025-05-01 23:48:07,005] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 100.59 | bwd_microstep: 138.51 | bwd_inner_microstep: 138.49 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 23:48:07,830] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 313.28 | bwd_microstep: 490.62 | bwd_inner_microstep: 490.60 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-01 23:48:08,907] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.98 | optimizer_step: 26.66 +[2025-05-01 23:48:08,909] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 340.85 | bwd_microstep: 687.09 | bwd_inner_microstep: 448.18 | bwd_allreduce_microstep: 238.86 | step_microstep: 35.00 +[2025-05-01 23:48:08,911] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4523.43 | bwd: 7127.48 | bwd_inner: 6888.30 | bwd_allreduce: 238.94 | step: 62.61 + 7%|▋ | 584/8720 [1:32:42<27:39:28, 12.24s/it] {'loss': 1.0664, 'grad_norm': 4.014359951019287, 'learning_rate': 9.964281075573118e-06, 'epoch': 0.67} + 7%|▋ | 584/8720 [1:32:42<27:39:28, 12.24s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2103 +[2025-05-01 23:48:09,868] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 357.12 | bwd_microstep: 559.93 | bwd_inner_microstep: 559.91 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1952 +[2025-05-01 23:48:10,807] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 368.04 | bwd_microstep: 551.96 | bwd_inner_microstep: 551.94 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.98 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1893 +[2025-05-01 23:48:11,630] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 293.60 | bwd_microstep: 513.19 | bwd_inner_microstep: 513.17 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 861 +[2025-05-01 23:48:12,049] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 150.82 | bwd_microstep: 253.42 | bwd_inner_microstep: 253.41 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.17 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-01 23:48:12,910] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 322.32 | bwd_microstep: 511.19 | bwd_inner_microstep: 511.18 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-01 23:48:13,761] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 354.25 | bwd_microstep: 470.53 | bwd_inner_microstep: 470.51 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.24 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-01 23:48:14,633] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 350.32 | bwd_microstep: 491.27 | bwd_inner_microstep: 491.25 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.83 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1352 +[2025-05-01 23:48:15,278] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 236.22 | bwd_microstep: 392.28 | bwd_inner_microstep: 392.09 | bwd_allreduce_microstep: 0.18 | step_microstep: 0.17 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-01 23:48:16,144] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 334.40 | bwd_microstep: 506.00 | bwd_inner_microstep: 505.98 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:48:17,005] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 335.74 | bwd_microstep: 503.14 | bwd_inner_microstep: 503.13 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 23:48:17,893] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 362.31 | bwd_microstep: 507.84 | bwd_inner_microstep: 507.82 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.69 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 23:48:18,737] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 312.67 | bwd_microstep: 510.87 | bwd_inner_microstep: 510.85 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.33 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 23:48:19,583] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 318.40 | bwd_microstep: 495.56 | bwd_inner_microstep: 495.54 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 23:48:20,445] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 326.94 | bwd_microstep: 503.94 | bwd_inner_microstep: 503.92 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.48 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 23:48:21,306] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 337.64 | bwd_microstep: 494.33 | bwd_inner_microstep: 494.31 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 366 +[2025-05-01 23:48:21,861] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.45 | optimizer_step: 18.57 +[2025-05-01 23:48:21,863] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 112.83 | bwd_microstep: 400.27 | bwd_inner_microstep: 132.39 | bwd_allreduce_microstep: 267.86 | step_microstep: 28.18 +[2025-05-01 23:48:21,864] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4873.50 | bwd: 7665.72 | bwd_inner: 7397.41 | bwd_allreduce: 268.10 | step: 36.71 + 7%|▋ | 585/8720 [1:32:55<28:08:22, 12.45s/it] {'loss': 1.121, 'grad_norm': 3.991307020187378, 'learning_rate': 9.96405914098739e-06, 'epoch': 0.67} + 7%|▋ | 585/8720 [1:32:55<28:08:22, 12.45s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1904 +[2025-05-01 23:48:22,738] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 312.72 | bwd_microstep: 518.54 | bwd_inner_microstep: 518.52 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1893 +[2025-05-01 23:48:23,594] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 321.70 | bwd_microstep: 502.50 | bwd_inner_microstep: 502.48 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.23 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1894 +[2025-05-01 23:48:24,476] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 331.73 | bwd_microstep: 519.34 | bwd_inner_microstep: 519.32 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-01 23:48:25,347] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 331.23 | bwd_microstep: 515.43 | bwd_inner_microstep: 515.41 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-01 23:48:26,217] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 343.03 | bwd_microstep: 494.95 | bwd_inner_microstep: 494.94 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:48:27,148] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 411.48 | bwd_microstep: 503.57 | bwd_inner_microstep: 503.55 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-01 23:48:28,032] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 341.23 | bwd_microstep: 522.72 | bwd_inner_microstep: 522.70 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.30 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-01 23:48:28,534] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 198.48 | bwd_microstep: 273.63 | bwd_inner_microstep: 273.61 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1344 +[2025-05-01 23:48:28,895] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.63 | bwd_microstep: 204.81 | bwd_inner_microstep: 204.79 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 23:48:29,492] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 308.62 | bwd_microstep: 272.33 | bwd_inner_microstep: 272.32 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 23:48:29,969] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.93 | bwd_microstep: 272.20 | bwd_inner_microstep: 272.18 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.17 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 23:48:30,567] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 309.07 | bwd_microstep: 272.01 | bwd_inner_microstep: 271.99 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 23:48:31,042] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.93 | bwd_microstep: 271.93 | bwd_inner_microstep: 271.91 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-01 23:48:31,638] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 309.66 | bwd_microstep: 272.02 | bwd_inner_microstep: 272.00 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 23:48:32,113] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.36 | bwd_microstep: 271.40 | bwd_inner_microstep: 271.38 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1924 +[2025-05-01 23:48:32,820] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.04 | optimizer_gradients: 2.29 | optimizer_step: 16.32 +[2025-05-01 23:48:32,821] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 258.41 | bwd_microstep: 410.68 | bwd_inner_microstep: 345.06 | bwd_allreduce_microstep: 65.58 | step_microstep: 23.47 +[2025-05-01 23:48:32,822] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4484.04 | bwd: 6098.05 | bwd_inner: 6032.16 | bwd_allreduce: 65.66 | step: 33.64 + 7%|▋ | 586/8720 [1:33:06<27:07:14, 12.00s/it] {'loss': 1.2879, 'grad_norm': 5.5621819496154785, 'learning_rate': 9.963836521542412e-06, 'epoch': 0.67} + 7%|▋ | 586/8720 [1:33:06<27:07:14, 12.00s/it]dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1430 +[2025-05-01 23:48:33,201] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 146.14 | bwd_microstep: 213.87 | bwd_inner_microstep: 213.67 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1896 +[2025-05-01 23:48:33,790] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.93 | bwd_microstep: 384.71 | bwd_inner_microstep: 384.69 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1887 +[2025-05-01 23:48:34,276] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 194.19 | bwd_microstep: 275.14 | bwd_inner_microstep: 275.12 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-01 23:48:34,829] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.33 | bwd_microstep: 343.79 | bwd_inner_microstep: 343.77 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.28 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-01 23:48:35,333] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 199.58 | bwd_microstep: 273.41 | bwd_inner_microstep: 273.39 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-01 23:48:35,874] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.62 | bwd_microstep: 331.49 | bwd_inner_microstep: 331.47 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-01 23:48:36,391] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 211.23 | bwd_microstep: 274.13 | bwd_inner_microstep: 274.11 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-01 23:48:36,909] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.63 | bwd_microstep: 311.51 | bwd_inner_microstep: 311.49 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.21 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 842 +[2025-05-01 23:48:37,207] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 142.59 | bwd_microstep: 132.04 | bwd_inner_microstep: 131.87 | bwd_allreduce_microstep: 0.09 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-01 23:48:37,684] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.79 | bwd_microstep: 273.01 | bwd_inner_microstep: 272.99 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 23:48:38,282] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.50 | bwd_microstep: 392.11 | bwd_inner_microstep: 392.09 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 23:48:38,757] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.68 | bwd_microstep: 272.06 | bwd_inner_microstep: 272.04 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1094 +[2025-05-01 23:48:39,052] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 115.48 | bwd_microstep: 163.90 | bwd_inner_microstep: 161.58 | bwd_allreduce_microstep: 2.30 | step_microstep: 2.30 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 23:48:39,621] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 266.65 | bwd_microstep: 272.26 | bwd_inner_microstep: 272.24 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 23:48:40,095] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.83 | bwd_microstep: 271.36 | bwd_inner_microstep: 271.34 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 377 +[2025-05-01 23:48:40,433] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.04 | optimizer_gradients: 2.26 | optimizer_step: 16.23 +[2025-05-01 23:48:40,433] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.69 | bwd_microstep: 207.62 | bwd_inner_microstep: 140.36 | bwd_allreduce_microstep: 67.15 | step_microstep: 23.28 +[2025-05-01 23:48:40,435] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2879.66 | bwd: 4392.43 | bwd_inner: 4322.27 | bwd_allreduce: 69.71 | step: 33.28 + 7%|▋ | 587/8720 [1:33:14<24:08:29, 10.69s/it] {'loss': 0.9506, 'grad_norm': 4.8860321044921875, 'learning_rate': 9.963613217268895e-06, 'epoch': 0.67} + 7%|▋ | 587/8720 [1:33:14<24:08:29, 10.69s/it]dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1493 +[2025-05-01 23:48:40,833] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 148.67 | bwd_microstep: 230.97 | bwd_inner_microstep: 230.93 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-01 23:48:41,372] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.02 | bwd_microstep: 332.49 | bwd_inner_microstep: 332.47 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-01 23:48:41,886] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 211.40 | bwd_microstep: 273.27 | bwd_inner_microstep: 273.25 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 837 +[2025-05-01 23:48:42,119] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 91.85 | bwd_microstep: 126.54 | bwd_inner_microstep: 126.29 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.21 +dynamic ViT batch size: 6, images per sample: 6.0, dynamic token length: 1613 +[2025-05-01 23:48:42,659] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 163.43 | bwd_microstep: 362.50 | bwd_inner_microstep: 362.49 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 328 +[2025-05-01 23:48:42,861] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 69.11 | bwd_microstep: 119.22 | bwd_inner_microstep: 119.08 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 23:48:43,337] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.84 | bwd_microstep: 273.16 | bwd_inner_microstep: 273.15 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 23:48:43,935] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 306.67 | bwd_microstep: 276.45 | bwd_inner_microstep: 276.43 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 23:48:44,413] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.43 | bwd_microstep: 273.15 | bwd_inner_microstep: 273.13 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.13 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 23:48:45,011] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 258.68 | bwd_microstep: 323.85 | bwd_inner_microstep: 323.83 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 23:48:45,489] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.80 | bwd_microstep: 272.16 | bwd_inner_microstep: 272.14 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 318 +[2025-05-01 23:48:45,723] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 87.88 | bwd_microstep: 127.75 | bwd_inner_microstep: 127.73 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 23:48:46,257] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 231.39 | bwd_microstep: 271.99 | bwd_inner_microstep: 271.97 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-01 23:48:46,764] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.81 | bwd_microstep: 299.13 | bwd_inner_microstep: 299.11 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 23:48:47,307] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 236.19 | bwd_microstep: 271.58 | bwd_inner_microstep: 271.56 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1941 +[2025-05-01 23:48:48,027] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.28 | optimizer_step: 16.20 +[2025-05-01 23:48:48,027] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 196.40 | bwd_microstep: 483.33 | bwd_inner_microstep: 331.50 | bwd_allreduce_microstep: 151.79 | step_microstep: 23.44 +[2025-05-01 23:48:48,028] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2943.35 | bwd: 4317.59 | bwd_inner: 4165.09 | bwd_allreduce: 152.04 | step: 31.37 + 7%|▋ | 588/8720 [1:33:21<22:02:34, 9.76s/it] {'loss': 0.7749, 'grad_norm': 5.433356285095215, 'learning_rate': 9.963389228197652e-06, 'epoch': 0.67} + 7%|▋ | 588/8720 [1:33:21<22:02:34, 9.76s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1971 +[2025-05-01 23:48:48,537] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 198.08 | bwd_microstep: 290.86 | bwd_inner_microstep: 290.85 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1981 +[2025-05-01 23:48:49,159] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 196.41 | bwd_microstep: 411.39 | bwd_inner_microstep: 411.37 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1929 +[2025-05-01 23:48:49,660] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.65 | bwd_microstep: 289.23 | bwd_inner_microstep: 289.21 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1385 +[2025-05-01 23:48:50,132] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 144.32 | bwd_microstep: 308.93 | bwd_inner_microstep: 308.91 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.33 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-01 23:48:50,617] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 192.07 | bwd_microstep: 273.89 | bwd_inner_microstep: 273.87 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-01 23:48:51,156] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.29 | bwd_microstep: 329.09 | bwd_inner_microstep: 329.07 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-01 23:48:51,674] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 209.37 | bwd_microstep: 274.21 | bwd_inner_microstep: 274.19 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:48:52,191] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.23 | bwd_microstep: 312.80 | bwd_inner_microstep: 312.78 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.21 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 840 +[2025-05-01 23:48:52,484] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 138.02 | bwd_microstep: 129.76 | bwd_inner_microstep: 129.51 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 334 +[2025-05-01 23:48:52,697] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 83.11 | bwd_microstep: 115.56 | bwd_inner_microstep: 115.32 | bwd_allreduce_microstep: 0.10 | step_microstep: 0.08 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 837 +[2025-05-01 23:48:52,927] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 89.78 | bwd_microstep: 126.55 | bwd_inner_microstep: 126.40 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 23:48:53,524] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.07 | bwd_microstep: 393.42 | bwd_inner_microstep: 393.40 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1344 +[2025-05-01 23:48:53,884] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.82 | bwd_microstep: 204.60 | bwd_inner_microstep: 204.58 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-01 23:48:54,473] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.31 | bwd_microstep: 383.36 | bwd_inner_microstep: 383.34 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 827 +[2025-05-01 23:48:54,791] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 155.55 | bwd_microstep: 130.38 | bwd_inner_microstep: 130.32 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1926 +[2025-05-01 23:48:55,379] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.04 | optimizer_gradients: 2.27 | optimizer_step: 16.52 +[2025-05-01 23:48:55,379] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 194.94 | bwd_microstep: 354.68 | bwd_inner_microstep: 288.09 | bwd_allreduce_microstep: 66.55 | step_microstep: 23.57 +[2025-05-01 23:48:55,380] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2691.79 | bwd: 4328.74 | bwd_inner: 4261.28 | bwd_allreduce: 66.89 | step: 31.51 + 7%|▋ | 589/8720 [1:33:29<20:24:35, 9.04s/it] {'loss': 0.8901, 'grad_norm': 3.6134705543518066, 'learning_rate': 9.963164554359584e-06, 'epoch': 0.68} + 7%|▋ | 589/8720 [1:33:29<20:24:35, 9.04s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1895 +[2025-05-01 23:48:56,084] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 352.14 | bwd_microstep: 332.03 | bwd_inner_microstep: 332.01 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-01 23:48:56,565] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.15 | bwd_microstep: 274.90 | bwd_inner_microstep: 274.89 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 359 +[2025-05-01 23:48:56,796] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 79.72 | bwd_microstep: 135.30 | bwd_inner_microstep: 135.28 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 855 +[2025-05-01 23:48:57,165] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 206.50 | bwd_microstep: 133.46 | bwd_inner_microstep: 133.26 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1886 +[2025-05-01 23:48:57,646] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.43 | bwd_microstep: 274.73 | bwd_inner_microstep: 274.71 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 23:48:58,344] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.86 | bwd_microstep: 493.10 | bwd_inner_microstep: 493.08 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 844 +[2025-05-01 23:48:58,588] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.35 | bwd_microstep: 132.37 | bwd_inner_microstep: 132.32 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1091 +[2025-05-01 23:48:58,884] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 117.67 | bwd_microstep: 161.02 | bwd_inner_microstep: 160.97 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.09 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 324 +[2025-05-01 23:48:59,125] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 97.83 | bwd_microstep: 123.14 | bwd_inner_microstep: 123.12 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.31 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 23:48:59,782] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 350.36 | bwd_microstep: 273.09 | bwd_inner_microstep: 273.07 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 23:49:00,262] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.55 | bwd_microstep: 272.69 | bwd_inner_microstep: 272.67 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:49:00,963] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 390.59 | bwd_microstep: 289.36 | bwd_inner_microstep: 289.34 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1346 +[2025-05-01 23:49:01,327] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.65 | bwd_microstep: 205.61 | bwd_inner_microstep: 205.57 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 321 +[2025-05-01 23:49:01,559] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 86.11 | bwd_microstep: 127.61 | bwd_inner_microstep: 127.59 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.51 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 23:49:02,211] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 347.77 | bwd_microstep: 271.66 | bwd_inner_microstep: 271.64 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 23:49:02,788] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.23 | optimizer_step: 16.74 +[2025-05-01 23:49:02,789] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.75 | bwd_microstep: 349.31 | bwd_inner_microstep: 271.63 | bwd_allreduce_microstep: 77.67 | step_microstep: 26.11 +[2025-05-01 23:49:02,790] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 3212.16 | bwd: 3849.44 | bwd_inner: 3771.16 | bwd_allreduce: 77.88 | step: 34.17 + 7%|▋ | 590/8720 [1:33:36<19:18:27, 8.55s/it] {'loss': 1.1402, 'grad_norm': 4.869449138641357, 'learning_rate': 9.962939195785683e-06, 'epoch': 0.68} + 7%|▋ | 590/8720 [1:33:36<19:18:27, 8.55s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1948 +[2025-05-01 23:49:03,433] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 319.37 | bwd_microstep: 288.92 | bwd_inner_microstep: 288.90 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.20 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 341 +[2025-05-01 23:49:03,650] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 72.13 | bwd_microstep: 130.31 | bwd_inner_microstep: 130.05 | bwd_allreduce_microstep: 0.09 | step_microstep: 0.14 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1362 +[2025-05-01 23:49:04,175] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.92 | bwd_microstep: 367.99 | bwd_inner_microstep: 367.97 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-01 23:49:04,686] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 207.70 | bwd_microstep: 274.13 | bwd_inner_microstep: 274.11 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-01 23:49:05,263] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.57 | bwd_microstep: 370.14 | bwd_inner_microstep: 370.12 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.28 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1098 +[2025-05-01 23:49:05,652] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 199.74 | bwd_microstep: 161.26 | bwd_inner_microstep: 161.07 | bwd_allreduce_microstep: 0.09 | step_microstep: 0.14 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1352 +[2025-05-01 23:49:06,013] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.47 | bwd_microstep: 206.27 | bwd_inner_microstep: 206.16 | bwd_allreduce_microstep: 0.04 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-01 23:49:06,598] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.90 | bwd_microstep: 379.97 | bwd_inner_microstep: 379.95 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.63 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 23:49:07,080] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 191.14 | bwd_microstep: 272.87 | bwd_inner_microstep: 272.85 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 321 +[2025-05-01 23:49:07,297] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 81.49 | bwd_microstep: 120.32 | bwd_inner_microstep: 119.99 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 23:49:07,996] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 268.75 | bwd_microstep: 412.15 | bwd_inner_microstep: 412.13 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 23:49:08,476] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.95 | bwd_microstep: 272.13 | bwd_inner_microstep: 272.11 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 23:49:09,178] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 198.12 | bwd_microstep: 483.00 | bwd_inner_microstep: 482.99 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 23:49:09,658] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.92 | bwd_microstep: 272.10 | bwd_inner_microstep: 272.08 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 23:49:10,357] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.79 | bwd_microstep: 492.14 | bwd_inner_microstep: 492.12 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 23:49:10,938] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.25 | optimizer_step: 16.18 +[2025-05-01 23:49:10,939] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.78 | bwd_microstep: 349.65 | bwd_inner_microstep: 271.65 | bwd_allreduce_microstep: 77.95 | step_microstep: 23.95 +[2025-05-01 23:49:10,940] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2952.48 | bwd: 4853.42 | bwd_inner: 4774.36 | bwd_allreduce: 78.43 | step: 30.19 + 7%|▋ | 591/8720 [1:33:44<19:02:00, 8.43s/it] {'loss': 0.6598, 'grad_norm': 3.5281434059143066, 'learning_rate': 9.962713152507046e-06, 'epoch': 0.68} + 7%|▋ | 591/8720 [1:33:44<19:02:00, 8.43s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2068 +[2025-05-01 23:49:11,690] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 203.68 | bwd_microstep: 523.19 | bwd_inner_microstep: 523.17 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.08 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 473 +[2025-05-01 23:49:11,913] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 92.58 | bwd_microstep: 112.66 | bwd_inner_microstep: 112.43 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1953 +[2025-05-01 23:49:12,434] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 196.08 | bwd_microstep: 303.18 | bwd_inner_microstep: 303.16 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1897 +[2025-05-01 23:49:13,095] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 350.88 | bwd_microstep: 275.90 | bwd_inner_microstep: 275.89 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-01 23:49:13,572] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.91 | bwd_microstep: 273.44 | bwd_inner_microstep: 273.43 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 845 +[2025-05-01 23:49:14,024] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 177.31 | bwd_microstep: 259.32 | bwd_inner_microstep: 259.31 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1360 +[2025-05-01 23:49:14,611] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 232.25 | bwd_microstep: 337.21 | bwd_inner_microstep: 337.19 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 345 +[2025-05-01 23:49:14,835] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 83.11 | bwd_microstep: 125.41 | bwd_inner_microstep: 125.39 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-01 23:49:15,553] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 297.53 | bwd_microstep: 397.59 | bwd_inner_microstep: 397.58 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-01 23:49:16,347] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 299.49 | bwd_microstep: 467.60 | bwd_inner_microstep: 467.58 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.84 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1351 +[2025-05-01 23:49:16,921] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 211.22 | bwd_microstep: 345.42 | bwd_inner_microstep: 344.64 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.21 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 836 +[2025-05-01 23:49:17,273] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 102.22 | bwd_microstep: 232.32 | bwd_inner_microstep: 232.01 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 23:49:18,022] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 300.50 | bwd_microstep: 428.94 | bwd_inner_microstep: 428.93 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.32 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 23:49:18,769] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 296.72 | bwd_microstep: 418.24 | bwd_inner_microstep: 418.22 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 23:49:19,532] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 296.09 | bwd_microstep: 448.81 | bwd_inner_microstep: 448.79 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 829 +[2025-05-01 23:49:19,995] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.30 | optimizer_step: 16.34 +[2025-05-01 23:49:19,995] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 103.62 | bwd_microstep: 306.93 | bwd_inner_microstep: 239.93 | bwd_allreduce_microstep: 66.86 | step_microstep: 23.81 +[2025-05-01 23:49:19,996] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 3431.98 | bwd: 5256.23 | bwd_inner: 5187.83 | bwd_allreduce: 67.14 | step: 34.96 + 7%|▋ | 592/8720 [1:33:53<19:27:17, 8.62s/it] {'loss': 1.0867, 'grad_norm': 3.7236387729644775, 'learning_rate': 9.962486424554858e-06, 'epoch': 0.68} + 7%|▋ | 592/8720 [1:33:53<19:27:17, 8.62s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1910 +[2025-05-01 23:49:20,614] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.90 | bwd_microstep: 405.67 | bwd_inner_microstep: 405.65 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-01 23:49:21,251] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 229.42 | bwd_microstep: 373.33 | bwd_inner_microstep: 373.31 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.43 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1895 +[2025-05-01 23:49:21,915] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 262.35 | bwd_microstep: 366.67 | bwd_inner_microstep: 366.66 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-01 23:49:22,784] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 332.24 | bwd_microstep: 504.21 | bwd_inner_microstep: 504.20 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-01 23:49:23,659] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 336.42 | bwd_microstep: 509.69 | bwd_inner_microstep: 509.66 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-01 23:49:24,539] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 330.50 | bwd_microstep: 521.26 | bwd_inner_microstep: 521.25 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-01 23:49:25,417] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 336.09 | bwd_microstep: 514.85 | bwd_inner_microstep: 514.83 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 23:49:26,289] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 335.35 | bwd_microstep: 505.99 | bwd_inner_microstep: 505.97 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.51 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-01 23:49:26,954] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 288.08 | bwd_microstep: 350.65 | bwd_inner_microstep: 350.64 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 23:49:27,830] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 331.01 | bwd_microstep: 516.54 | bwd_inner_microstep: 516.53 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.23 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 327 +[2025-05-01 23:49:28,071] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 100.16 | bwd_microstep: 116.51 | bwd_inner_microstep: 116.38 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 23:49:28,970] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 387.36 | bwd_microstep: 492.20 | bwd_inner_microstep: 492.18 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 23:49:29,860] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 363.81 | bwd_microstep: 506.28 | bwd_inner_microstep: 506.27 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.87 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-01 23:49:30,606] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 304.69 | bwd_microstep: 424.97 | bwd_inner_microstep: 424.95 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-01 23:49:31,369] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 278.40 | bwd_microstep: 454.62 | bwd_inner_microstep: 454.60 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1365 +[2025-05-01 23:49:32,222] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.08 | optimizer_gradients: 3.30 | optimizer_step: 16.57 +[2025-05-01 23:49:32,222] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 290.20 | bwd_microstep: 506.76 | bwd_inner_microstep: 323.67 | bwd_allreduce_microstep: 183.04 | step_microstep: 26.70 +[2025-05-01 23:49:32,224] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4695.90 | bwd: 7070.23 | bwd_inner: 6886.77 | bwd_allreduce: 183.16 | step: 42.03 + 7%|▋ | 593/8720 [1:34:05<21:53:52, 9.70s/it] {'loss': 1.1306, 'grad_norm': 7.02325963973999, 'learning_rate': 9.962259011960396e-06, 'epoch': 0.68} + 7%|▋ | 593/8720 [1:34:05<21:53:52, 9.70s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1899 +[2025-05-01 23:49:33,121] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 393.67 | bwd_microstep: 480.75 | bwd_inner_microstep: 480.73 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.88 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-01 23:49:33,879] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 271.53 | bwd_microstep: 466.29 | bwd_inner_microstep: 466.27 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-01 23:49:34,699] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 309.09 | bwd_microstep: 487.15 | bwd_inner_microstep: 487.13 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-01 23:49:35,540] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 364.57 | bwd_microstep: 459.09 | bwd_inner_microstep: 459.07 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.28 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-01 23:49:36,333] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 301.99 | bwd_microstep: 458.71 | bwd_inner_microstep: 458.69 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.42 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-01 23:49:37,088] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 274.08 | bwd_microstep: 449.37 | bwd_inner_microstep: 449.35 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-01 23:49:37,929] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 322.27 | bwd_microstep: 488.45 | bwd_inner_microstep: 488.43 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 23:49:38,737] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 340.39 | bwd_microstep: 450.01 | bwd_inner_microstep: 449.99 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.48 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 326 +[2025-05-01 23:49:38,996] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 92.74 | bwd_microstep: 136.38 | bwd_inner_microstep: 136.36 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.32 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:49:39,890] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 353.41 | bwd_microstep: 508.81 | bwd_inner_microstep: 508.79 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 842 +[2025-05-01 23:49:40,327] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 118.48 | bwd_microstep: 294.94 | bwd_inner_microstep: 294.92 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.52 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 23:49:41,189] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 315.26 | bwd_microstep: 517.32 | bwd_inner_microstep: 517.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.30 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 23:49:42,046] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 314.25 | bwd_microstep: 508.71 | bwd_inner_microstep: 508.69 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.48 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 23:49:42,908] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 321.02 | bwd_microstep: 508.64 | bwd_inner_microstep: 508.62 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.22 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1986 +[2025-05-01 23:49:43,829] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 347.82 | bwd_microstep: 546.33 | bwd_inner_microstep: 546.31 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1935 +[2025-05-01 23:49:44,823] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.30 | optimizer_step: 18.87 +[2025-05-01 23:49:44,826] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 229.10 | bwd_microstep: 723.31 | bwd_inner_microstep: 547.88 | bwd_allreduce_microstep: 175.41 | step_microstep: 28.46 +[2025-05-01 23:49:44,827] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4669.62 | bwd: 7484.24 | bwd_inner: 7308.56 | bwd_allreduce: 175.48 | step: 53.70 + 7%|▋ | 594/8720 [1:34:18<23:51:47, 10.57s/it] {'loss': 1.2167, 'grad_norm': 5.0090227127075195, 'learning_rate': 9.962030914755036e-06, 'epoch': 0.68} + 7%|▋ | 594/8720 [1:34:18<23:51:47, 10.57s/it]dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 876 +[2025-05-01 23:49:45,281] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 203.24 | bwd_microstep: 213.62 | bwd_inner_microstep: 213.42 | bwd_allreduce_microstep: 0.18 | step_microstep: 0.06 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1367 +[2025-05-01 23:49:45,979] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 242.51 | bwd_microstep: 423.99 | bwd_inner_microstep: 423.88 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-01 23:49:46,865] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 349.51 | bwd_microstep: 517.38 | bwd_inner_microstep: 517.37 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-01 23:49:47,732] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 321.84 | bwd_microstep: 518.01 | bwd_inner_microstep: 517.99 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-01 23:49:48,580] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 306.18 | bwd_microstep: 507.21 | bwd_inner_microstep: 507.20 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.32 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 837 +[2025-05-01 23:49:48,993] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 176.87 | bwd_microstep: 208.68 | bwd_inner_microstep: 208.66 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 837 +[2025-05-01 23:49:49,429] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 194.16 | bwd_microstep: 213.43 | bwd_inner_microstep: 213.41 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.40 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:49:50,262] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 327.56 | bwd_microstep: 482.28 | bwd_inner_microstep: 482.26 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.16 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 832 +[2025-05-01 23:49:50,715] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 171.18 | bwd_microstep: 268.49 | bwd_inner_microstep: 268.28 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.10 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1342 +[2025-05-01 23:49:51,355] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 250.31 | bwd_microstep: 371.99 | bwd_inner_microstep: 371.97 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.61 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-01 23:49:52,199] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 342.97 | bwd_microstep: 469.35 | bwd_inner_microstep: 469.33 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 23:49:53,102] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 388.75 | bwd_microstep: 496.73 | bwd_inner_microstep: 496.71 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.94 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 23:49:53,944] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 316.36 | bwd_microstep: 507.25 | bwd_inner_microstep: 507.24 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 23:49:54,791] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 311.46 | bwd_microstep: 503.44 | bwd_inner_microstep: 503.42 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.50 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1972 +[2025-05-01 23:49:55,694] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 332.84 | bwd_microstep: 540.41 | bwd_inner_microstep: 540.39 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1883 +[2025-05-01 23:49:56,843] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.27 | optimizer_step: 22.32 +[2025-05-01 23:49:56,844] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 327.06 | bwd_microstep: 765.78 | bwd_inner_microstep: 506.37 | bwd_allreduce_microstep: 259.37 | step_microstep: 29.67 +[2025-05-01 23:49:56,845] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4562.72 | bwd: 7008.10 | bwd_inner: 6747.92 | bwd_allreduce: 259.61 | step: 46.39 + 7%|▋ | 595/8720 [1:34:30<24:50:12, 11.00s/it] {'loss': 0.8362, 'grad_norm': 3.6348178386688232, 'learning_rate': 9.961802132970248e-06, 'epoch': 0.68} + 7%|▋ | 595/8720 [1:34:30<24:50:12, 11.00s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 362 +[2025-05-01 23:49:57,079] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.50 | bwd_microstep: 105.98 | bwd_inner_microstep: 105.76 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1895 +[2025-05-01 23:49:57,916] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 331.94 | bwd_microstep: 489.94 | bwd_inner_microstep: 489.93 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-01 23:49:58,776] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 318.13 | bwd_microstep: 518.52 | bwd_inner_microstep: 518.51 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.85 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-01 23:49:59,588] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 278.57 | bwd_microstep: 514.26 | bwd_inner_microstep: 514.24 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-01 23:50:00,447] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 347.33 | bwd_microstep: 483.01 | bwd_inner_microstep: 482.99 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 23:50:01,239] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 262.65 | bwd_microstep: 511.41 | bwd_inner_microstep: 511.39 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.30 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:50:02,078] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 316.12 | bwd_microstep: 495.87 | bwd_inner_microstep: 495.85 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.53 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 23:50:02,870] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 273.76 | bwd_microstep: 496.95 | bwd_inner_microstep: 496.93 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 320 +[2025-05-01 23:50:03,113] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 99.46 | bwd_microstep: 110.82 | bwd_inner_microstep: 110.61 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.16 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 23:50:03,889] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 300.08 | bwd_microstep: 456.92 | bwd_inner_microstep: 456.90 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 23:50:04,774] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 360.74 | bwd_microstep: 494.44 | bwd_inner_microstep: 494.42 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 23:50:05,638] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 339.71 | bwd_microstep: 504.84 | bwd_inner_microstep: 504.82 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.32 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 23:50:06,483] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 307.44 | bwd_microstep: 507.49 | bwd_inner_microstep: 507.48 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.32 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 23:50:07,318] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 309.65 | bwd_microstep: 493.15 | bwd_inner_microstep: 493.13 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-01 23:50:08,178] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 323.30 | bwd_microstep: 505.37 | bwd_inner_microstep: 505.35 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.22 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1849 +[2025-05-01 23:50:09,343] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.22 | optimizer_step: 26.38 +[2025-05-01 23:50:09,344] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 342.64 | bwd_microstep: 761.82 | bwd_inner_microstep: 484.02 | bwd_allreduce_microstep: 277.76 | step_microstep: 33.89 +[2025-05-01 23:50:09,345] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4604.96 | bwd: 7450.83 | bwd_inner: 7172.45 | bwd_allreduce: 277.89 | step: 54.22 + 7%|▋ | 596/8720 [1:34:43<25:50:45, 11.45s/it] {'loss': 1.2817, 'grad_norm': 6.2164740562438965, 'learning_rate': 9.961572666637596e-06, 'epoch': 0.68} + 7%|▋ | 596/8720 [1:34:43<25:50:45, 11.45s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1893 +[2025-05-01 23:50:10,246] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 398.74 | bwd_microstep: 480.29 | bwd_inner_microstep: 480.28 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.30 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 860 +[2025-05-01 23:50:10,660] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 144.84 | bwd_microstep: 241.90 | bwd_inner_microstep: 241.88 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.29 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1887 +[2025-05-01 23:50:11,517] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 348.83 | bwd_microstep: 474.08 | bwd_inner_microstep: 474.06 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.30 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-01 23:50:12,372] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 322.35 | bwd_microstep: 502.55 | bwd_inner_microstep: 502.53 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.63 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-01 23:50:13,210] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 312.36 | bwd_microstep: 507.12 | bwd_inner_microstep: 507.10 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.82 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-01 23:50:14,039] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 309.07 | bwd_microstep: 502.69 | bwd_inner_microstep: 502.67 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.85 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 329 +[2025-05-01 23:50:14,257] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 78.18 | bwd_microstep: 122.38 | bwd_inner_microstep: 122.36 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.50 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-01 23:50:15,108] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 318.42 | bwd_microstep: 504.93 | bwd_inner_microstep: 504.91 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.65 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-01 23:50:15,946] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 314.89 | bwd_microstep: 505.70 | bwd_inner_microstep: 505.68 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.65 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 23:50:16,778] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 312.72 | bwd_microstep: 502.55 | bwd_inner_microstep: 502.53 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.84 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 23:50:17,610] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 312.08 | bwd_microstep: 502.06 | bwd_inner_microstep: 502.04 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.86 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 23:50:18,449] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 310.99 | bwd_microstep: 509.27 | bwd_inner_microstep: 509.25 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.85 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 23:50:19,284] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 311.30 | bwd_microstep: 507.63 | bwd_inner_microstep: 507.61 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 23:50:20,121] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 318.57 | bwd_microstep: 499.22 | bwd_inner_microstep: 499.20 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-01 23:50:20,957] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 329.39 | bwd_microstep: 488.75 | bwd_inner_microstep: 488.73 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 23:50:22,008] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.22 | optimizer_step: 16.64 +[2025-05-01 23:50:22,009] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 335.23 | bwd_microstep: 674.78 | bwd_inner_microstep: 481.98 | bwd_allreduce_microstep: 192.78 | step_microstep: 26.38 +[2025-05-01 23:50:22,010] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4777.87 | bwd: 7525.90 | bwd_inner: 7332.84 | bwd_allreduce: 192.85 | step: 42.05 + 7%|▋ | 597/8720 [1:34:55<26:39:55, 11.82s/it] {'loss': 0.831, 'grad_norm': 7.198513031005859, 'learning_rate': 9.961342515788737e-06, 'epoch': 0.68} + 7%|▋ | 597/8720 [1:34:55<26:39:55, 11.82s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1917 +[2025-05-01 23:50:22,873] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 340.80 | bwd_microstep: 480.33 | bwd_inner_microstep: 480.31 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1926 +[2025-05-01 23:50:23,753] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 324.74 | bwd_microstep: 525.89 | bwd_inner_microstep: 525.87 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1898 +[2025-05-01 23:50:24,593] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 323.92 | bwd_microstep: 498.59 | bwd_inner_microstep: 498.57 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1896 +[2025-05-01 23:50:25,432] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 335.92 | bwd_microstep: 488.50 | bwd_inner_microstep: 488.48 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1892 +[2025-05-01 23:50:26,273] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 330.76 | bwd_microstep: 494.40 | bwd_inner_microstep: 494.39 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1098 +[2025-05-01 23:50:26,794] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 229.83 | bwd_microstep: 276.08 | bwd_inner_microstep: 276.06 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-01 23:50:27,634] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 325.81 | bwd_microstep: 496.86 | bwd_inner_microstep: 496.84 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.13 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-01 23:50:28,473] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 318.76 | bwd_microstep: 503.69 | bwd_inner_microstep: 503.67 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 23:50:29,302] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 311.48 | bwd_microstep: 500.41 | bwd_inner_microstep: 500.39 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.65 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 23:50:30,113] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 309.36 | bwd_microstep: 482.84 | bwd_inner_microstep: 482.82 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 23:50:30,929] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 317.21 | bwd_microstep: 476.05 | bwd_inner_microstep: 476.03 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 23:50:31,739] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 317.84 | bwd_microstep: 463.07 | bwd_inner_microstep: 463.05 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 23:50:32,530] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 301.60 | bwd_microstep: 457.64 | bwd_inner_microstep: 457.62 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.48 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 23:50:33,373] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 331.94 | bwd_microstep: 480.72 | bwd_inner_microstep: 480.70 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 987 +[2025-05-01 23:50:33,801] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 105.31 | bwd_microstep: 306.87 | bwd_inner_microstep: 306.85 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.51 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-01 23:50:34,839] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.06 | optimizer_step: 17.59 +[2025-05-01 23:50:34,841] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 288.48 | bwd_microstep: 696.17 | bwd_inner_microstep: 498.05 | bwd_allreduce_microstep: 198.07 | step_microstep: 25.31 +[2025-05-01 23:50:34,842] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4813.63 | bwd: 7628.10 | bwd_inner: 7429.71 | bwd_allreduce: 198.15 | step: 40.74 + 7%|▋ | 598/8720 [1:35:08<27:20:54, 12.12s/it] {'loss': 1.3487, 'grad_norm': 5.161885738372803, 'learning_rate': 9.961111680455423e-06, 'epoch': 0.69} + 7%|▋ | 598/8720 [1:35:08<27:20:54, 12.12s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1903 +[2025-05-01 23:50:35,729] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 347.55 | bwd_microstep: 497.89 | bwd_inner_microstep: 497.87 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.52 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1897 +[2025-05-01 23:50:36,581] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 348.07 | bwd_microstep: 479.36 | bwd_inner_microstep: 479.34 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.97 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-01 23:50:37,463] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 337.16 | bwd_microstep: 516.61 | bwd_inner_microstep: 516.59 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-01 23:50:38,309] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 333.13 | bwd_microstep: 481.81 | bwd_inner_microstep: 481.79 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-01 23:50:39,202] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 338.03 | bwd_microstep: 520.47 | bwd_inner_microstep: 520.46 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1361 +[2025-05-01 23:50:39,901] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 259.68 | bwd_microstep: 416.33 | bwd_inner_microstep: 416.21 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 23:50:40,669] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 301.23 | bwd_microstep: 446.64 | bwd_inner_microstep: 446.63 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.56 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-01 23:50:41,440] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 301.86 | bwd_microstep: 450.31 | bwd_inner_microstep: 450.29 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-01 23:50:42,204] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 306.28 | bwd_microstep: 438.60 | bwd_inner_microstep: 438.58 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.30 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-01 23:50:42,996] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 302.02 | bwd_microstep: 464.01 | bwd_inner_microstep: 463.99 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1354 +[2025-05-01 23:50:43,647] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 222.24 | bwd_microstep: 399.16 | bwd_inner_microstep: 399.15 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 23:50:44,552] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 392.41 | bwd_microstep: 492.79 | bwd_inner_microstep: 492.77 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 23:50:45,447] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 373.06 | bwd_microstep: 501.19 | bwd_inner_microstep: 501.17 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.95 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 23:50:46,255] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 282.65 | bwd_microstep: 507.32 | bwd_inner_microstep: 507.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 321 +[2025-05-01 23:50:46,493] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 99.98 | bwd_microstep: 122.09 | bwd_inner_microstep: 122.07 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.49 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 829 +[2025-05-01 23:50:47,305] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.15 | optimizer_step: 22.37 +[2025-05-01 23:50:47,305] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 148.20 | bwd_microstep: 606.72 | bwd_inner_microstep: 261.46 | bwd_allreduce_microstep: 345.25 | step_microstep: 29.90 +[2025-05-01 23:50:47,306] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4693.44 | bwd: 7341.34 | bwd_inner: 6995.70 | bwd_allreduce: 345.37 | step: 47.33 + 7%|▋ | 599/8720 [1:35:21<27:34:30, 12.22s/it] {'loss': 0.9531, 'grad_norm': 8.168682098388672, 'learning_rate': 9.960880160669502e-06, 'epoch': 0.69} + 7%|▋ | 599/8720 [1:35:21<27:34:30, 12.22s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1890 +[2025-05-01 23:50:48,112] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 312.83 | bwd_microstep: 468.66 | bwd_inner_microstep: 468.64 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1893 +[2025-05-01 23:50:49,016] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 394.02 | bwd_microstep: 491.29 | bwd_inner_microstep: 491.28 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1366 +[2025-05-01 23:50:49,674] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 263.75 | bwd_microstep: 376.23 | bwd_inner_microstep: 373.87 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.32 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-01 23:50:50,552] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 336.54 | bwd_microstep: 510.74 | bwd_inner_microstep: 510.72 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.20 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 328 +[2025-05-01 23:50:50,803] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 100.19 | bwd_microstep: 124.35 | bwd_inner_microstep: 124.33 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.16 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:50:51,578] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 310.21 | bwd_microstep: 448.15 | bwd_inner_microstep: 448.13 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-01 23:50:52,392] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 345.54 | bwd_microstep: 450.69 | bwd_inner_microstep: 450.67 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:50:53,236] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 317.06 | bwd_microstep: 495.09 | bwd_inner_microstep: 495.07 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 23:50:54,077] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 309.91 | bwd_microstep: 500.17 | bwd_inner_microstep: 500.15 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.91 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 23:50:54,875] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 315.89 | bwd_microstep: 464.66 | bwd_inner_microstep: 464.64 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 23:50:55,712] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 311.49 | bwd_microstep: 498.96 | bwd_inner_microstep: 498.94 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.88 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 23:50:56,510] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 331.28 | bwd_microstep: 448.92 | bwd_inner_microstep: 448.90 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 23:50:57,353] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 350.07 | bwd_microstep: 475.37 | bwd_inner_microstep: 475.35 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.65 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 23:50:57,946] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 302.70 | bwd_microstep: 270.83 | bwd_inner_microstep: 270.81 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 23:50:58,635] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 386.01 | bwd_microstep: 284.51 | bwd_inner_microstep: 284.49 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 23:50:59,423] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.17 | optimizer_step: 16.27 +[2025-05-01 23:50:59,424] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 315.41 | bwd_microstep: 431.72 | bwd_inner_microstep: 354.38 | bwd_allreduce_microstep: 77.28 | step_microstep: 24.13 +[2025-05-01 23:50:59,425] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 5002.76 | bwd: 6740.34 | bwd_inner: 6660.40 | bwd_allreduce: 79.70 | step: 34.43 + 7%|▋ | 600/8720 [1:35:33<27:30:01, 12.19s/it] {'loss': 0.8179, 'grad_norm': 6.441941738128662, 'learning_rate': 9.960647956462914e-06, 'epoch': 0.69} + 7%|▋ | 600/8720 [1:35:33<27:30:01, 12.19s/it][INFO|trainer.py:3503] 2025-05-01 23:51:02,180 >> Saving model checkpoint to work_dirs/internvl_chat_v2_5/ak/checkpoint-600 +[INFO|configuration_utils.py:472] 2025-05-01 23:51:02,182 >> Configuration saved in work_dirs/internvl_chat_v2_5/ak/checkpoint-600/config.json +[INFO|configuration_utils.py:807] 2025-05-01 23:51:02,183 >> Configuration saved in work_dirs/internvl_chat_v2_5/ak/checkpoint-600/generation_config.json +[INFO|modeling_utils.py:2755] 2025-05-01 23:51:07,449 >> Model weights saved in work_dirs/internvl_chat_v2_5/ak/checkpoint-600/model.safetensors +[INFO|tokenization_utils_base.py:2702] 2025-05-01 23:51:07,451 >> tokenizer config file saved in work_dirs/internvl_chat_v2_5/ak/checkpoint-600/tokenizer_config.json +[INFO|tokenization_utils_base.py:2711] 2025-05-01 23:51:07,451 >> Special tokens file saved in work_dirs/internvl_chat_v2_5/ak/checkpoint-600/special_tokens_map.json +[INFO|tokenization_utils_base.py:2762] 2025-05-01 23:51:07,451 >> added tokens file saved in work_dirs/internvl_chat_v2_5/ak/checkpoint-600/added_tokens.json +[2025-05-01 23:51:07,578] [INFO] [logging.py:96:log_dist] [Rank 0] [Torch] Checkpoint global_step600 is about to be saved! +[2025-05-01 23:51:07,600] [INFO] [logging.py:96:log_dist] [Rank 0] Saving model checkpoint: work_dirs/internvl_chat_v2_5/ak/checkpoint-600/global_step600/mp_rank_00_model_states.pt +[2025-05-01 23:51:07,600] [INFO] [torch_checkpoint_engine.py:21:save] [Torch] Saving work_dirs/internvl_chat_v2_5/ak/checkpoint-600/global_step600/mp_rank_00_model_states.pt... +[2025-05-01 23:51:12,162] [INFO] [torch_checkpoint_engine.py:23:save] [Torch] Saved work_dirs/internvl_chat_v2_5/ak/checkpoint-600/global_step600/mp_rank_00_model_states.pt. +[2025-05-01 23:51:12,164] [INFO] [torch_checkpoint_engine.py:21:save] [Torch] Saving work_dirs/internvl_chat_v2_5/ak/checkpoint-600/global_step600/bf16_zero_pp_rank_0_mp_rank_00_optim_states.pt... +[2025-05-01 23:51:12,367] [INFO] [torch_checkpoint_engine.py:23:save] [Torch] Saved work_dirs/internvl_chat_v2_5/ak/checkpoint-600/global_step600/bf16_zero_pp_rank_0_mp_rank_00_optim_states.pt. +[2025-05-01 23:51:12,367] [INFO] [engine.py:3536:_save_zero_checkpoint] zero checkpoint saved work_dirs/internvl_chat_v2_5/ak/checkpoint-600/global_step600/bf16_zero_pp_rank_0_mp_rank_00_optim_states.pt +[2025-05-01 23:51:12,367] [INFO] [torch_checkpoint_engine.py:33:commit] [Torch] Checkpoint global_step600 is ready now! +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 504 +[2025-05-01 23:51:12,614] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 83.12 | bwd_microstep: 137.82 | bwd_inner_microstep: 137.80 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1944 +[2025-05-01 23:51:13,494] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 318.83 | bwd_microstep: 527.41 | bwd_inner_microstep: 527.39 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.33 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1904 +[2025-05-01 23:51:14,271] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 311.65 | bwd_microstep: 447.56 | bwd_inner_microstep: 447.54 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.76 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-01 23:51:15,083] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 305.87 | bwd_microstep: 487.07 | bwd_inner_microstep: 487.05 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.49 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-01 23:51:15,860] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 304.46 | bwd_microstep: 440.88 | bwd_inner_microstep: 440.86 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.30 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-01 23:51:16,686] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 289.94 | bwd_microstep: 512.29 | bwd_inner_microstep: 512.28 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 23:51:17,453] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 305.44 | bwd_microstep: 443.26 | bwd_inner_microstep: 443.24 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.70 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:51:18,225] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 310.20 | bwd_microstep: 444.20 | bwd_inner_microstep: 444.19 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 23:51:18,986] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 303.53 | bwd_microstep: 440.28 | bwd_inner_microstep: 440.27 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.75 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-01 23:51:19,748] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 299.54 | bwd_microstep: 443.86 | bwd_inner_microstep: 443.82 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 23:51:20,587] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 344.00 | bwd_microstep: 479.40 | bwd_inner_microstep: 479.38 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.77 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 23:51:21,389] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 277.69 | bwd_microstep: 507.77 | bwd_inner_microstep: 507.75 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-01 23:51:22,250] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 317.16 | bwd_microstep: 517.41 | bwd_inner_microstep: 517.39 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.19 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 829 +[2025-05-01 23:51:22,652] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 126.54 | bwd_microstep: 259.34 | bwd_inner_microstep: 259.05 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 23:51:23,412] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 301.25 | bwd_microstep: 441.22 | bwd_inner_microstep: 441.21 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1849 +[2025-05-01 23:51:24,365] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.11 | optimizer_step: 16.30 +[2025-05-01 23:51:24,365] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 308.90 | bwd_microstep: 601.14 | bwd_inner_microstep: 442.11 | bwd_allreduce_microstep: 159.02 | step_microstep: 23.72 +[2025-05-01 23:51:24,367] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4507.86 | bwd: 7130.92 | bwd_inner: 6971.37 | bwd_allreduce: 159.20 | step: 37.10 + 7%|▋ | 601/8720 [1:35:58<36:07:23, 16.02s/it] {'loss': 1.0135, 'grad_norm': 5.312713623046875, 'learning_rate': 9.960415067867695e-06, 'epoch': 0.69} + 7%|▋ | 601/8720 [1:35:58<36:07:23, 16.02s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1966 +[2025-05-01 23:51:25,165] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 314.94 | bwd_microstep: 461.08 | bwd_inner_microstep: 461.06 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 377 +[2025-05-01 23:51:25,397] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 84.34 | bwd_microstep: 127.10 | bwd_inner_microstep: 126.98 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1893 +[2025-05-01 23:51:26,264] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 371.51 | bwd_microstep: 478.44 | bwd_inner_microstep: 478.42 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1377 +[2025-05-01 23:51:26,925] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 227.58 | bwd_microstep: 404.93 | bwd_inner_microstep: 404.72 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.34 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 342 +[2025-05-01 23:51:27,176] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 86.15 | bwd_microstep: 136.77 | bwd_inner_microstep: 136.75 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-01 23:51:28,066] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 345.96 | bwd_microstep: 517.64 | bwd_inner_microstep: 517.62 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.30 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-01 23:51:28,883] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 268.40 | bwd_microstep: 516.09 | bwd_inner_microstep: 516.07 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1353 +[2025-05-01 23:51:29,508] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 215.30 | bwd_microstep: 387.10 | bwd_inner_microstep: 387.09 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 327 +[2025-05-01 23:51:29,735] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 85.56 | bwd_microstep: 120.95 | bwd_inner_microstep: 120.93 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.31 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-01 23:51:30,538] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 327.34 | bwd_microstep: 451.44 | bwd_inner_microstep: 451.42 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.49 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-01 23:51:31,331] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 326.70 | bwd_microstep: 431.71 | bwd_inner_microstep: 431.69 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 835 +[2025-05-01 23:51:31,732] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 184.91 | bwd_microstep: 198.35 | bwd_inner_microstep: 198.33 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.32 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 316 +[2025-05-01 23:51:31,990] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 96.14 | bwd_microstep: 131.39 | bwd_inner_microstep: 131.38 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 23:51:32,789] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 276.21 | bwd_microstep: 498.71 | bwd_inner_microstep: 498.69 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 23:51:33,678] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 346.53 | bwd_microstep: 511.39 | bwd_inner_microstep: 511.37 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1897 +[2025-05-01 23:51:34,720] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.14 | optimizer_step: 17.30 +[2025-05-01 23:51:34,722] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 323.59 | bwd_microstep: 665.65 | bwd_inner_microstep: 486.63 | bwd_allreduce_microstep: 178.98 | step_microstep: 24.68 +[2025-05-01 23:51:34,723] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 3881.12 | bwd: 6038.76 | bwd_inner: 5859.18 | bwd_allreduce: 179.30 | step: 50.91 + 7%|▋ | 602/8720 [1:36:08<32:17:28, 14.32s/it] {'loss': 0.8886, 'grad_norm': 5.365538120269775, 'learning_rate': 9.960181494915975e-06, 'epoch': 0.69} + 7%|▋ | 602/8720 [1:36:08<32:17:28, 14.32s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1963 +[2025-05-01 23:51:35,661] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 343.70 | bwd_microstep: 551.51 | bwd_inner_microstep: 551.49 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 907 +[2025-05-01 23:51:36,153] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 220.23 | bwd_microstep: 246.44 | bwd_inner_microstep: 246.42 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.58 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 357 +[2025-05-01 23:51:36,387] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 86.33 | bwd_microstep: 131.75 | bwd_inner_microstep: 131.73 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.52 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-01 23:51:37,259] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 334.07 | bwd_microstep: 505.56 | bwd_inner_microstep: 505.55 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.33 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 845 +[2025-05-01 23:51:37,661] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 144.78 | bwd_microstep: 236.28 | bwd_inner_microstep: 236.26 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.52 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-01 23:51:38,500] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 313.12 | bwd_microstep: 496.01 | bwd_inner_microstep: 495.99 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.43 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 23:51:39,332] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 299.77 | bwd_microstep: 499.99 | bwd_inner_microstep: 499.98 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:51:40,166] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 309.53 | bwd_microstep: 494.15 | bwd_inner_microstep: 494.14 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.32 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-01 23:51:41,000] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 367.22 | bwd_microstep: 435.23 | bwd_inner_microstep: 435.21 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.31 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-01 23:51:41,771] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 302.63 | bwd_microstep: 443.43 | bwd_inner_microstep: 443.41 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.31 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-01 23:51:42,530] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 303.79 | bwd_microstep: 433.95 | bwd_inner_microstep: 433.93 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.55 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:51:43,289] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 302.94 | bwd_microstep: 438.34 | bwd_inner_microstep: 438.32 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.76 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1342 +[2025-05-01 23:51:43,914] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 194.72 | bwd_microstep: 413.05 | bwd_inner_microstep: 413.02 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 835 +[2025-05-01 23:51:44,354] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 163.84 | bwd_microstep: 262.39 | bwd_inner_microstep: 262.32 | bwd_allreduce_microstep: 0.03 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 23:51:45,162] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 310.74 | bwd_microstep: 478.86 | bwd_inner_microstep: 478.84 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 439 +[2025-05-01 23:51:45,603] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.07 | optimizer_gradients: 2.09 | optimizer_step: 16.03 +[2025-05-01 23:51:45,603] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 102.09 | bwd_microstep: 301.66 | bwd_inner_microstep: 131.78 | bwd_allreduce_microstep: 169.83 | step_microstep: 23.34 +[2025-05-01 23:51:45,605] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4099.41 | bwd: 6368.65 | bwd_inner: 6198.41 | bwd_allreduce: 169.95 | step: 46.90 + 7%|▋ | 603/8720 [1:36:19<29:57:33, 13.29s/it] {'loss': 0.9564, 'grad_norm': 3.380389451980591, 'learning_rate': 9.95994723763998e-06, 'epoch': 0.69} + 7%|▋ | 603/8720 [1:36:19<29:57:33, 13.29s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1917 +[2025-05-01 23:51:46,498] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 327.27 | bwd_microstep: 527.86 | bwd_inner_microstep: 527.84 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1895 +[2025-05-01 23:51:47,299] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 317.27 | bwd_microstep: 465.25 | bwd_inner_microstep: 465.24 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.30 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1888 +[2025-05-01 23:51:48,153] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 338.81 | bwd_microstep: 485.20 | bwd_inner_microstep: 485.19 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.55 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1888 +[2025-05-01 23:51:48,969] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 305.15 | bwd_microstep: 491.79 | bwd_inner_microstep: 491.77 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-01 23:51:49,806] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 274.98 | bwd_microstep: 531.65 | bwd_inner_microstep: 531.63 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.76 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1883 +[2025-05-01 23:51:50,577] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 302.39 | bwd_microstep: 450.66 | bwd_inner_microstep: 450.65 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-01 23:51:51,358] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 297.71 | bwd_microstep: 466.90 | bwd_inner_microstep: 466.88 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 23:51:52,172] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 343.49 | bwd_microstep: 443.03 | bwd_inner_microstep: 443.01 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.55 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 23:51:52,939] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 303.38 | bwd_microstep: 447.18 | bwd_inner_microstep: 447.16 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-01 23:51:53,765] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 291.25 | bwd_microstep: 515.19 | bwd_inner_microstep: 515.17 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.31 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 23:51:54,559] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 303.46 | bwd_microstep: 471.32 | bwd_inner_microstep: 471.31 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 322 +[2025-05-01 23:51:54,792] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 102.96 | bwd_microstep: 103.97 | bwd_inner_microstep: 103.65 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 23:51:55,689] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 383.38 | bwd_microstep: 496.39 | bwd_inner_microstep: 496.37 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.46 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1343 +[2025-05-01 23:51:56,313] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 194.50 | bwd_microstep: 415.02 | bwd_inner_microstep: 415.00 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 23:51:57,151] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 383.35 | bwd_microstep: 433.89 | bwd_inner_microstep: 433.87 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.31 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1926 +[2025-05-01 23:51:58,112] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.25 | optimizer_step: 16.70 +[2025-05-01 23:51:58,113] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 332.32 | bwd_microstep: 583.37 | bwd_inner_microstep: 475.11 | bwd_allreduce_microstep: 108.25 | step_microstep: 26.05 +[2025-05-01 23:51:58,114] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4801.59 | bwd: 7328.71 | bwd_inner: 7219.92 | bwd_allreduce: 108.43 | step: 40.40 + 7%|▋ | 604/8720 [1:36:31<29:25:54, 13.05s/it] {'loss': 1.1905, 'grad_norm': 5.9537835121154785, 'learning_rate': 9.959712296072029e-06, 'epoch': 0.69} + 7%|▋ | 604/8720 [1:36:31<29:25:54, 13.05s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 378 +[2025-05-01 23:51:58,378] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 111.86 | bwd_microstep: 117.62 | bwd_inner_microstep: 117.47 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 879 +[2025-05-01 23:51:58,830] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 171.56 | bwd_microstep: 267.01 | bwd_inner_microstep: 266.87 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 345 +[2025-05-01 23:51:59,058] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 85.78 | bwd_microstep: 125.89 | bwd_inner_microstep: 125.88 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1356 +[2025-05-01 23:51:59,717] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 253.41 | bwd_microstep: 374.72 | bwd_inner_microstep: 374.70 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.52 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-01 23:52:00,590] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 321.10 | bwd_microstep: 520.38 | bwd_inner_microstep: 520.36 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.31 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-01 23:52:01,466] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 316.47 | bwd_microstep: 526.74 | bwd_inner_microstep: 526.72 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.51 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 23:52:02,289] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 275.76 | bwd_microstep: 513.04 | bwd_inner_microstep: 513.02 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 23:52:03,183] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 349.90 | bwd_microstep: 511.99 | bwd_inner_microstep: 511.97 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 23:52:04,041] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 322.29 | bwd_microstep: 515.40 | bwd_inner_microstep: 515.38 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.48 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 23:52:04,819] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 305.50 | bwd_microstep: 442.00 | bwd_inner_microstep: 441.98 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.58 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 23:52:05,588] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 307.54 | bwd_microstep: 443.79 | bwd_inner_microstep: 443.77 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.78 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 23:52:06,351] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 304.57 | bwd_microstep: 441.30 | bwd_inner_microstep: 441.28 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.55 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 23:52:07,107] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 302.72 | bwd_microstep: 435.18 | bwd_inner_microstep: 435.16 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.76 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 23:52:07,749] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 324.87 | bwd_microstep: 299.80 | bwd_inner_microstep: 299.78 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 23:52:08,602] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 383.47 | bwd_microstep: 451.77 | bwd_inner_microstep: 451.75 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 346 +[2025-05-01 23:52:09,160] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.21 | optimizer_step: 30.61 +[2025-05-01 23:52:09,160] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 82.28 | bwd_microstep: 419.38 | bwd_inner_microstep: 130.49 | bwd_allreduce_microstep: 288.84 | step_microstep: 38.07 +[2025-05-01 23:52:09,161] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4219.01 | bwd: 6406.04 | bwd_inner: 6116.70 | bwd_allreduce: 288.99 | step: 58.86 + 7%|▋ | 605/8720 [1:36:42<28:04:06, 12.45s/it] {'loss': 0.9891, 'grad_norm': 5.345273017883301, 'learning_rate': 9.959476670244533e-06, 'epoch': 0.69} + 7%|▋ | 605/8720 [1:36:42<28:04:06, 12.45s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1915 +[2025-05-01 23:52:09,976] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 302.58 | bwd_microstep: 490.60 | bwd_inner_microstep: 490.59 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1894 +[2025-05-01 23:52:10,798] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 391.73 | bwd_microstep: 411.64 | bwd_inner_microstep: 411.63 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1891 +[2025-05-01 23:52:11,701] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 349.03 | bwd_microstep: 520.33 | bwd_inner_microstep: 520.29 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.30 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 839 +[2025-05-01 23:52:12,077] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 144.71 | bwd_microstep: 211.72 | bwd_inner_microstep: 211.49 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-01 23:52:12,929] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 333.82 | bwd_microstep: 490.55 | bwd_inner_microstep: 490.48 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-01 23:52:13,738] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 291.45 | bwd_microstep: 496.89 | bwd_inner_microstep: 496.87 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-01 23:52:14,596] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 344.96 | bwd_microstep: 482.84 | bwd_inner_microstep: 482.82 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 840 +[2025-05-01 23:52:14,896] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 148.17 | bwd_microstep: 126.41 | bwd_inner_microstep: 126.38 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 328 +[2025-05-01 23:52:15,119] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 73.55 | bwd_microstep: 134.55 | bwd_inner_microstep: 134.53 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 23:52:15,984] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 321.76 | bwd_microstep: 516.72 | bwd_inner_microstep: 516.70 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.50 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1344 +[2025-05-01 23:52:16,604] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 223.56 | bwd_microstep: 362.99 | bwd_inner_microstep: 362.97 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.52 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 833 +[2025-05-01 23:52:17,031] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 197.39 | bwd_microstep: 198.61 | bwd_inner_microstep: 198.59 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.33 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 23:52:17,899] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 331.77 | bwd_microstep: 502.02 | bwd_inner_microstep: 502.00 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 23:52:18,757] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 339.82 | bwd_microstep: 485.74 | bwd_inner_microstep: 485.73 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 23:52:19,524] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 246.00 | bwd_microstep: 504.88 | bwd_inner_microstep: 504.86 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1916 +[2025-05-01 23:52:20,727] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.40 | optimizer_step: 18.49 +[2025-05-01 23:52:20,729] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 340.26 | bwd_microstep: 811.12 | bwd_inner_microstep: 518.53 | bwd_allreduce_microstep: 292.58 | step_microstep: 28.48 +[2025-05-01 23:52:20,731] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4380.49 | bwd: 6747.65 | bwd_inner: 6454.48 | bwd_allreduce: 292.67 | step: 48.42 + 7%|▋ | 606/8720 [1:36:54<27:28:13, 12.19s/it] {'loss': 1.1319, 'grad_norm': 5.646172523498535, 'learning_rate': 9.959240360190002e-06, 'epoch': 0.69} + 7%|▋ | 606/8720 [1:36:54<27:28:13, 12.19s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 411 +[2025-05-01 23:52:20,998] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 90.79 | bwd_microstep: 139.09 | bwd_inner_microstep: 138.94 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1914 +[2025-05-01 23:52:21,842] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 399.42 | bwd_microstep: 425.24 | bwd_inner_microstep: 425.22 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-01 23:52:22,570] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 222.54 | bwd_microstep: 475.13 | bwd_inner_microstep: 475.11 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1366 +[2025-05-01 23:52:23,180] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 257.97 | bwd_microstep: 337.11 | bwd_inner_microstep: 336.89 | bwd_allreduce_microstep: 0.20 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-01 23:52:23,921] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 240.71 | bwd_microstep: 472.84 | bwd_inner_microstep: 472.82 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-01 23:52:24,734] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 376.89 | bwd_microstep: 419.43 | bwd_inner_microstep: 419.42 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.28 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-01 23:52:25,490] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 239.91 | bwd_microstep: 485.43 | bwd_inner_microstep: 485.41 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 324 +[2025-05-01 23:52:25,708] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 80.96 | bwd_microstep: 121.91 | bwd_inner_microstep: 121.89 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.27 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-01 23:52:26,399] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 251.16 | bwd_microstep: 422.91 | bwd_inner_microstep: 422.89 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-01 23:52:27,250] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 388.65 | bwd_microstep: 443.92 | bwd_inner_microstep: 443.90 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.31 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 23:52:27,960] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 247.68 | bwd_microstep: 433.71 | bwd_inner_microstep: 433.69 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:52:28,761] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 397.74 | bwd_microstep: 384.97 | bwd_inner_microstep: 384.95 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 23:52:29,563] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 300.57 | bwd_microstep: 483.29 | bwd_inner_microstep: 483.27 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 23:52:30,295] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 280.14 | bwd_microstep: 430.36 | bwd_inner_microstep: 430.34 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 23:52:31,124] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 315.09 | bwd_microstep: 482.98 | bwd_inner_microstep: 482.96 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1849 +[2025-05-01 23:52:32,242] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.34 | optimizer_step: 17.20 +[2025-05-01 23:52:32,243] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 390.21 | bwd_microstep: 684.94 | bwd_inner_microstep: 499.10 | bwd_allreduce_microstep: 185.82 | step_microstep: 24.78 +[2025-05-01 23:52:32,244] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4480.26 | bwd: 6643.25 | bwd_inner: 6456.85 | bwd_allreduce: 186.14 | step: 34.88 + 7%|▋ | 607/8720 [1:37:05<27:00:30, 11.98s/it] {'loss': 1.2566, 'grad_norm': 4.597816467285156, 'learning_rate': 9.959003365941038e-06, 'epoch': 0.7} + 7%|▋ | 607/8720 [1:37:05<27:00:30, 11.98s/it]dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1759 +[2025-05-01 23:52:32,953] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 271.97 | bwd_microstep: 416.59 | bwd_inner_microstep: 416.57 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.69 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 915 +[2025-05-01 23:52:33,359] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 159.03 | bwd_microstep: 229.90 | bwd_inner_microstep: 229.88 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.31 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1899 +[2025-05-01 23:52:34,181] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 284.00 | bwd_microstep: 517.88 | bwd_inner_microstep: 517.86 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-01 23:52:34,955] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 306.02 | bwd_microstep: 438.39 | bwd_inner_microstep: 438.37 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.27 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-01 23:52:35,723] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 302.68 | bwd_microstep: 443.77 | bwd_inner_microstep: 443.76 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-01 23:52:36,493] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 302.29 | bwd_microstep: 446.33 | bwd_inner_microstep: 446.32 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.62 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-01 23:52:37,259] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 301.34 | bwd_microstep: 447.90 | bwd_inner_microstep: 447.88 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-01 23:52:38,024] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 303.60 | bwd_microstep: 443.86 | bwd_inner_microstep: 443.84 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.60 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-01 23:52:38,813] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 307.20 | bwd_microstep: 462.55 | bwd_inner_microstep: 462.53 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.28 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:52:39,669] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 323.22 | bwd_microstep: 504.90 | bwd_inner_microstep: 504.88 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.33 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 23:52:40,501] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 325.09 | bwd_microstep: 486.05 | bwd_inner_microstep: 486.03 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 23:52:41,334] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 311.65 | bwd_microstep: 489.38 | bwd_inner_microstep: 489.36 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.27 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1850 +[2025-05-01 23:52:42,150] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 316.19 | bwd_microstep: 479.20 | bwd_inner_microstep: 479.18 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.58 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1337 +[2025-05-01 23:52:42,749] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 204.70 | bwd_microstep: 376.38 | bwd_inner_microstep: 376.36 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.32 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1891 +[2025-05-01 23:52:43,629] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 344.00 | bwd_microstep: 504.17 | bwd_inner_microstep: 504.16 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-01 23:52:44,796] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 3.06 | optimizer_step: 16.83 +[2025-05-01 23:52:44,796] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 322.56 | bwd_microstep: 789.56 | bwd_inner_microstep: 489.57 | bwd_allreduce_microstep: 299.97 | step_microstep: 25.36 +[2025-05-01 23:52:44,797] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4685.51 | bwd: 7476.81 | bwd_inner: 7176.56 | bwd_allreduce: 300.04 | step: 48.98 + 7%|▋ | 608/8720 [1:37:18<27:23:23, 12.16s/it] {'loss': 0.9343, 'grad_norm': 2.6018292903900146, 'learning_rate': 9.958765687530336e-06, 'epoch': 0.7} + 7%|▋ | 608/8720 [1:37:18<27:23:23, 12.16s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-01 23:52:45,640] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 351.88 | bwd_microstep: 466.15 | bwd_inner_microstep: 466.13 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.51 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-01 23:52:46,372] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 241.81 | bwd_microstep: 458.33 | bwd_inner_microstep: 458.31 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-01 23:52:47,252] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 342.34 | bwd_microstep: 505.36 | bwd_inner_microstep: 505.34 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 23:52:48,094] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 309.49 | bwd_microstep: 499.94 | bwd_inner_microstep: 499.92 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.43 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1358 +[2025-05-01 23:52:48,755] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 226.23 | bwd_microstep: 407.87 | bwd_inner_microstep: 407.79 | bwd_allreduce_microstep: 0.04 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:52:49,652] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 380.86 | bwd_microstep: 499.16 | bwd_inner_microstep: 499.14 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.91 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-01 23:52:50,511] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 334.27 | bwd_microstep: 505.77 | bwd_inner_microstep: 505.75 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 321 +[2025-05-01 23:52:50,739] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 75.11 | bwd_microstep: 123.56 | bwd_inner_microstep: 123.54 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 23:52:51,583] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 354.40 | bwd_microstep: 457.49 | bwd_inner_microstep: 457.47 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.48 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 23:52:52,398] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 329.87 | bwd_microstep: 461.48 | bwd_inner_microstep: 461.46 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 23:52:53,158] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 236.29 | bwd_microstep: 506.30 | bwd_inner_microstep: 506.28 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.49 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 23:52:54,014] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 333.46 | bwd_microstep: 491.25 | bwd_inner_microstep: 491.23 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 23:52:54,849] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 346.43 | bwd_microstep: 469.26 | bwd_inner_microstep: 469.23 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 23:52:55,701] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 315.05 | bwd_microstep: 502.97 | bwd_inner_microstep: 502.95 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1850 +[2025-05-01 23:52:56,522] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 330.96 | bwd_microstep: 455.42 | bwd_inner_microstep: 455.40 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 321 +[2025-05-01 23:52:57,011] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 3.46 | optimizer_step: 17.67 +[2025-05-01 23:52:57,013] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.39 | bwd_microstep: 342.87 | bwd_inner_microstep: 127.03 | bwd_allreduce_microstep: 215.27 | step_microstep: 27.38 +[2025-05-01 23:52:57,014] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4602.74 | bwd: 7153.19 | bwd_inner: 6937.01 | bwd_allreduce: 215.41 | step: 54.79 + 7%|▋ | 609/8720 [1:37:30<27:25:47, 12.17s/it] {'loss': 0.7069, 'grad_norm': 7.065230369567871, 'learning_rate': 9.958527324990687e-06, 'epoch': 0.7} + 7%|▋ | 609/8720 [1:37:30<27:25:47, 12.17s/it]dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 866 +[2025-05-01 23:52:57,460] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 198.25 | bwd_microstep: 210.39 | bwd_inner_microstep: 210.37 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1914 +[2025-05-01 23:52:58,301] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 332.28 | bwd_microstep: 480.75 | bwd_inner_microstep: 480.74 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1883 +[2025-05-01 23:52:59,166] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 335.26 | bwd_microstep: 502.49 | bwd_inner_microstep: 502.47 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1358 +[2025-05-01 23:52:59,819] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 213.57 | bwd_microstep: 408.74 | bwd_inner_microstep: 406.44 | bwd_allreduce_microstep: 2.29 | step_microstep: 2.33 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-01 23:53:00,658] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 330.85 | bwd_microstep: 487.50 | bwd_inner_microstep: 487.49 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1352 +[2025-05-01 23:53:01,313] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 273.62 | bwd_microstep: 364.38 | bwd_inner_microstep: 364.36 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.32 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-01 23:53:02,188] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 336.31 | bwd_microstep: 508.92 | bwd_inner_microstep: 508.90 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.23 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 332 +[2025-05-01 23:53:02,425] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 99.42 | bwd_microstep: 109.84 | bwd_inner_microstep: 109.67 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:53:03,295] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 351.69 | bwd_microstep: 500.84 | bwd_inner_microstep: 500.82 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 23:53:04,147] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 366.63 | bwd_microstep: 466.59 | bwd_inner_microstep: 466.57 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.60 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1346 +[2025-05-01 23:53:04,770] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 247.13 | bwd_microstep: 360.28 | bwd_inner_microstep: 360.20 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 23:53:05,668] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 386.63 | bwd_microstep: 493.77 | bwd_inner_microstep: 493.75 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.20 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 833 +[2025-05-01 23:53:06,046] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 145.80 | bwd_microstep: 213.97 | bwd_inner_microstep: 213.96 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.31 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 23:53:06,876] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 341.35 | bwd_microstep: 467.17 | bwd_inner_microstep: 467.15 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 23:53:07,773] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 389.74 | bwd_microstep: 489.17 | bwd_inner_microstep: 489.16 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-01 23:53:08,988] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.19 | optimizer_step: 26.33 +[2025-05-01 23:53:08,988] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 362.29 | bwd_microstep: 801.37 | bwd_inner_microstep: 508.96 | bwd_allreduce_microstep: 292.36 | step_microstep: 33.62 +[2025-05-01 23:53:08,989] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4710.69 | bwd: 6866.22 | bwd_inner: 6571.04 | bwd_allreduce: 294.85 | step: 44.77 + 7%|▋ | 610/8720 [1:37:42<27:17:22, 12.11s/it] {'loss': 1.077, 'grad_norm': 4.685674667358398, 'learning_rate': 9.958288278354979e-06, 'epoch': 0.7} + 7%|▋ | 610/8720 [1:37:42<27:17:22, 12.11s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2201 +[2025-05-01 23:53:09,958] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 413.02 | bwd_microstep: 534.55 | bwd_inner_microstep: 534.53 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 911 +[2025-05-01 23:53:10,431] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 213.92 | bwd_microstep: 242.86 | bwd_inner_microstep: 242.84 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1904 +[2025-05-01 23:53:11,308] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 358.75 | bwd_microstep: 488.13 | bwd_inner_microstep: 488.11 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-01 23:53:12,200] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 389.02 | bwd_microstep: 486.03 | bwd_inner_microstep: 486.01 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-01 23:53:13,104] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 393.11 | bwd_microstep: 493.80 | bwd_inner_microstep: 493.78 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-01 23:53:13,988] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 346.99 | bwd_microstep: 515.80 | bwd_inner_microstep: 515.78 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-01 23:53:14,847] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 320.60 | bwd_microstep: 515.73 | bwd_inner_microstep: 515.71 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.32 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-01 23:53:15,693] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 312.23 | bwd_microstep: 499.86 | bwd_inner_microstep: 499.84 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 327 +[2025-05-01 23:53:15,944] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 90.41 | bwd_microstep: 132.74 | bwd_inner_microstep: 132.61 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.08 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1343 +[2025-05-01 23:53:16,566] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 232.32 | bwd_microstep: 370.13 | bwd_inner_microstep: 370.11 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1344 +[2025-05-01 23:53:17,168] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 212.79 | bwd_microstep: 361.55 | bwd_inner_microstep: 361.41 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.09 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 832 +[2025-05-01 23:53:17,609] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 202.75 | bwd_microstep: 212.06 | bwd_inner_microstep: 212.04 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.33 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 23:53:18,477] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 345.19 | bwd_microstep: 493.55 | bwd_inner_microstep: 493.54 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 23:53:19,363] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 349.41 | bwd_microstep: 516.90 | bwd_inner_microstep: 516.89 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.50 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 23:53:20,215] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 321.33 | bwd_microstep: 511.89 | bwd_inner_microstep: 511.87 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.90 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 23:53:21,238] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.18 | optimizer_step: 16.92 +[2025-05-01 23:53:21,239] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 277.21 | bwd_microstep: 703.56 | bwd_inner_microstep: 510.48 | bwd_allreduce_microstep: 193.06 | step_microstep: 26.22 +[2025-05-01 23:53:21,240] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4778.95 | bwd: 7079.17 | bwd_inner: 6885.59 | bwd_allreduce: 193.29 | step: 44.05 + 7%|▋ | 611/8720 [1:37:54<27:22:51, 12.16s/it] {'loss': 0.7669, 'grad_norm': 4.251306533813477, 'learning_rate': 9.958048547656189e-06, 'epoch': 0.7} + 7%|▋ | 611/8720 [1:37:54<27:22:51, 12.16s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 419 +[2025-05-01 23:53:21,516] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 117.31 | bwd_microstep: 124.75 | bwd_inner_microstep: 124.43 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-01 23:53:22,371] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 380.60 | bwd_microstep: 454.56 | bwd_inner_microstep: 454.54 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.30 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-01 23:53:23,178] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 315.92 | bwd_microstep: 456.30 | bwd_inner_microstep: 456.28 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-01 23:53:23,955] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 309.28 | bwd_microstep: 448.79 | bwd_inner_microstep: 448.77 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.61 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-01 23:53:24,718] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 305.24 | bwd_microstep: 441.39 | bwd_inner_microstep: 441.37 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-01 23:53:25,480] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 299.98 | bwd_microstep: 445.07 | bwd_inner_microstep: 445.05 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 326 +[2025-05-01 23:53:25,703] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 77.33 | bwd_microstep: 131.77 | bwd_inner_microstep: 131.76 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 23:53:26,504] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 282.80 | bwd_microstep: 487.54 | bwd_inner_microstep: 487.52 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.24 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:53:27,355] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 346.60 | bwd_microstep: 486.45 | bwd_inner_microstep: 486.43 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:53:28,229] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 351.39 | bwd_microstep: 502.32 | bwd_inner_microstep: 502.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 326 +[2025-05-01 23:53:28,452] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 70.89 | bwd_microstep: 130.14 | bwd_inner_microstep: 130.12 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.33 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 23:53:29,292] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 326.79 | bwd_microstep: 483.48 | bwd_inner_microstep: 483.47 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 834 +[2025-05-01 23:53:29,733] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 177.07 | bwd_microstep: 247.40 | bwd_inner_microstep: 247.10 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 23:53:30,555] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 315.42 | bwd_microstep: 486.54 | bwd_inner_microstep: 486.52 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.31 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 23:53:31,381] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 312.47 | bwd_microstep: 484.00 | bwd_inner_microstep: 483.99 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1890 +[2025-05-01 23:53:32,546] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.24 | optimizer_step: 16.80 +[2025-05-01 23:53:32,546] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 290.33 | bwd_microstep: 821.54 | bwd_inner_microstep: 501.34 | bwd_allreduce_microstep: 320.19 | step_microstep: 26.27 +[2025-05-01 23:53:32,547] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4279.30 | bwd: 6632.13 | bwd_inner: 6311.11 | bwd_allreduce: 320.49 | step: 39.66 + 7%|▋ | 612/8720 [1:38:06<26:48:09, 11.90s/it] {'loss': 1.4581, 'grad_norm': 10.115828514099121, 'learning_rate': 9.957808132927393e-06, 'epoch': 0.7} + 7%|▋ | 612/8720 [1:38:06<26:48:09, 11.90s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1913 +[2025-05-01 23:53:33,377] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 298.69 | bwd_microstep: 506.98 | bwd_inner_microstep: 506.96 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.49 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1935 +[2025-05-01 23:53:34,199] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 321.13 | bwd_microstep: 468.41 | bwd_inner_microstep: 468.40 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1887 +[2025-05-01 23:53:35,047] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 363.61 | bwd_microstep: 450.31 | bwd_inner_microstep: 450.29 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.58 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1883 +[2025-05-01 23:53:35,815] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 302.41 | bwd_microstep: 448.15 | bwd_inner_microstep: 448.13 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-01 23:53:36,614] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 313.07 | bwd_microstep: 460.12 | bwd_inner_microstep: 460.10 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-01 23:53:37,382] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 306.43 | bwd_microstep: 445.22 | bwd_inner_microstep: 445.20 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-01 23:53:38,213] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 323.70 | bwd_microstep: 490.35 | bwd_inner_microstep: 490.34 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 331 +[2025-05-01 23:53:38,447] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 90.28 | bwd_microstep: 127.47 | bwd_inner_microstep: 127.45 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.51 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-01 23:53:39,251] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 326.75 | bwd_microstep: 458.39 | bwd_inner_microstep: 458.37 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.45 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-01 23:53:40,107] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 320.19 | bwd_microstep: 504.91 | bwd_inner_microstep: 504.89 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 23:53:40,898] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 327.00 | bwd_microstep: 429.57 | bwd_inner_microstep: 429.56 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.51 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 23:53:41,774] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 355.22 | bwd_microstep: 487.21 | bwd_inner_microstep: 487.19 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.33 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1346 +[2025-05-01 23:53:42,408] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 224.97 | bwd_microstep: 377.16 | bwd_inner_microstep: 377.14 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 23:53:43,218] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 326.32 | bwd_microstep: 452.24 | bwd_inner_microstep: 452.22 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.32 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 23:53:44,053] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 325.15 | bwd_microstep: 488.03 | bwd_inner_microstep: 488.01 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 314 +[2025-05-01 23:53:44,502] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 3.02 | optimizer_step: 20.17 +[2025-05-01 23:53:44,503] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 76.89 | bwd_microstep: 330.68 | bwd_inner_microstep: 137.89 | bwd_allreduce_microstep: 192.73 | step_microstep: 28.98 +[2025-05-01 23:53:44,505] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4601.71 | bwd: 6925.20 | bwd_inner: 6732.15 | bwd_allreduce: 192.81 | step: 51.73 + 7%|▋ | 613/8720 [1:38:18<26:50:22, 11.92s/it] {'loss': 1.337, 'grad_norm': 6.352406978607178, 'learning_rate': 9.957567034201758e-06, 'epoch': 0.7} + 7%|▋ | 613/8720 [1:38:18<26:50:22, 11.92s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 400 +[2025-05-01 23:53:44,821] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 121.09 | bwd_microstep: 157.93 | bwd_inner_microstep: 157.61 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.40 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 897 +[2025-05-01 23:53:45,246] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 116.03 | bwd_microstep: 292.97 | bwd_inner_microstep: 292.76 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1919 +[2025-05-01 23:53:46,073] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 360.98 | bwd_microstep: 446.23 | bwd_inner_microstep: 446.21 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1899 +[2025-05-01 23:53:46,949] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 366.60 | bwd_microstep: 494.12 | bwd_inner_microstep: 494.10 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1131 +[2025-05-01 23:53:47,464] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 214.05 | bwd_microstep: 283.09 | bwd_inner_microstep: 282.86 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-01 23:53:48,320] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 342.97 | bwd_microstep: 496.83 | bwd_inner_microstep: 496.76 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 23:53:49,146] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 404.31 | bwd_microstep: 405.38 | bwd_inner_microstep: 405.36 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 841 +[2025-05-01 23:53:49,599] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.25 | bwd_microstep: 251.00 | bwd_inner_microstep: 250.77 | bwd_allreduce_microstep: 0.09 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-01 23:53:50,457] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 350.51 | bwd_microstep: 489.67 | bwd_inner_microstep: 489.65 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.15 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 23:53:51,321] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 352.62 | bwd_microstep: 491.93 | bwd_inner_microstep: 491.91 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-01 23:53:52,213] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 364.26 | bwd_microstep: 507.04 | bwd_inner_microstep: 507.02 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.28 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 467 +[2025-05-01 23:53:52,465] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 77.04 | bwd_microstep: 146.61 | bwd_inner_microstep: 146.59 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.27 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 457 +[2025-05-01 23:53:52,726] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 107.15 | bwd_microstep: 122.32 | bwd_inner_microstep: 122.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.33 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1990 +[2025-05-01 23:53:53,685] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 363.33 | bwd_microstep: 560.78 | bwd_inner_microstep: 560.76 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.93 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 23:53:54,493] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 286.31 | bwd_microstep: 502.56 | bwd_inner_microstep: 502.54 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1337 +[2025-05-01 23:53:55,447] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.21 | optimizer_step: 23.78 +[2025-05-01 23:53:55,448] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.73 | bwd_microstep: 706.16 | bwd_inner_microstep: 414.20 | bwd_allreduce_microstep: 291.91 | step_microstep: 32.00 +[2025-05-01 23:53:55,449] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4201.10 | bwd: 6354.67 | bwd_inner: 6061.52 | bwd_allreduce: 292.27 | step: 42.94 + 7%|▋ | 614/8720 [1:38:29<26:10:33, 11.63s/it] {'loss': 1.0263, 'grad_norm': 3.0716216564178467, 'learning_rate': 9.957325251512546e-06, 'epoch': 0.7} + 7%|▋ | 614/8720 [1:38:29<26:10:33, 11.63s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2140 +[2025-05-01 23:53:56,384] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 390.12 | bwd_microstep: 522.09 | bwd_inner_microstep: 522.08 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1994 +[2025-05-01 23:53:57,277] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 334.43 | bwd_microstep: 537.66 | bwd_inner_microstep: 537.64 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.49 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1889 +[2025-05-01 23:53:58,173] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 366.24 | bwd_microstep: 500.35 | bwd_inner_microstep: 500.33 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-01 23:53:59,071] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 378.33 | bwd_microstep: 499.63 | bwd_inner_microstep: 499.61 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-01 23:53:59,897] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 304.09 | bwd_microstep: 498.01 | bwd_inner_microstep: 497.99 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1366 +[2025-05-01 23:54:00,527] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 226.52 | bwd_microstep: 375.96 | bwd_inner_microstep: 375.95 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-01 23:54:01,380] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 308.64 | bwd_microstep: 515.75 | bwd_inner_microstep: 515.73 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.49 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-01 23:54:02,251] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 333.67 | bwd_microstep: 508.56 | bwd_inner_microstep: 508.54 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.51 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 330 +[2025-05-01 23:54:02,516] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 91.70 | bwd_microstep: 141.04 | bwd_inner_microstep: 141.02 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-01 23:54:03,390] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 329.61 | bwd_microstep: 510.93 | bwd_inner_microstep: 510.91 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.32 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:54:04,244] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 307.04 | bwd_microstep: 512.96 | bwd_inner_microstep: 512.94 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.32 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 23:54:05,103] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 314.82 | bwd_microstep: 509.93 | bwd_inner_microstep: 509.92 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-01 23:54:05,960] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 309.88 | bwd_microstep: 513.02 | bwd_inner_microstep: 513.00 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.45 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 23:54:06,816] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 317.34 | bwd_microstep: 505.52 | bwd_inner_microstep: 505.50 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.90 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 23:54:07,673] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 340.04 | bwd_microstep: 498.89 | bwd_inner_microstep: 498.87 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.89 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 842 +[2025-05-01 23:54:08,387] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.24 | optimizer_step: 25.92 +[2025-05-01 23:54:08,388] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 130.29 | bwd_microstep: 537.37 | bwd_inner_microstep: 271.02 | bwd_allreduce_microstep: 266.20 | step_microstep: 33.31 +[2025-05-01 23:54:08,389] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4782.67 | bwd: 7687.69 | bwd_inner: 7421.13 | bwd_allreduce: 266.25 | step: 59.25 + 7%|▋ | 615/8720 [1:38:42<27:03:39, 12.02s/it] {'loss': 0.8382, 'grad_norm': 4.469949245452881, 'learning_rate': 9.957082784893117e-06, 'epoch': 0.71} + 7%|▋ | 615/8720 [1:38:42<27:03:39, 12.02s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1901 +[2025-05-01 23:54:09,248] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 363.87 | bwd_microstep: 472.32 | bwd_inner_microstep: 472.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-01 23:54:10,128] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 363.29 | bwd_microstep: 482.45 | bwd_inner_microstep: 482.43 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.27 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-01 23:54:11,013] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 335.24 | bwd_microstep: 519.16 | bwd_inner_microstep: 519.15 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-01 23:54:11,830] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 286.18 | bwd_microstep: 500.45 | bwd_inner_microstep: 500.43 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 847 +[2025-05-01 23:54:12,275] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 202.24 | bwd_microstep: 218.93 | bwd_inner_microstep: 218.64 | bwd_allreduce_microstep: 0.15 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 23:54:13,191] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 402.75 | bwd_microstep: 496.43 | bwd_inner_microstep: 496.41 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 846 +[2025-05-01 23:54:13,638] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 149.71 | bwd_microstep: 283.61 | bwd_inner_microstep: 283.01 | bwd_allreduce_microstep: 0.59 | step_microstep: 0.40 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-01 23:54:14,487] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 316.06 | bwd_microstep: 513.48 | bwd_inner_microstep: 513.46 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.32 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 23:54:15,340] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 310.98 | bwd_microstep: 510.30 | bwd_inner_microstep: 510.28 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-01 23:54:16,216] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 324.87 | bwd_microstep: 518.62 | bwd_inner_microstep: 518.60 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 23:54:17,091] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 328.32 | bwd_microstep: 518.97 | bwd_inner_microstep: 518.95 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:54:17,973] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 332.22 | bwd_microstep: 516.57 | bwd_inner_microstep: 516.55 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 23:54:18,858] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 360.54 | bwd_microstep: 505.85 | bwd_inner_microstep: 505.83 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 23:54:19,707] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 310.51 | bwd_microstep: 507.90 | bwd_inner_microstep: 507.89 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 23:54:20,568] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 326.31 | bwd_microstep: 506.71 | bwd_inner_microstep: 506.69 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.33 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-01 23:54:21,762] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.04 | optimizer_gradients: 2.19 | optimizer_step: 18.44 +[2025-05-01 23:54:21,762] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 368.64 | bwd_microstep: 769.31 | bwd_inner_microstep: 505.72 | bwd_allreduce_microstep: 263.54 | step_microstep: 26.28 +[2025-05-01 23:54:21,764] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 5081.67 | bwd: 7841.08 | bwd_inner: 7576.38 | bwd_allreduce: 264.33 | step: 45.91 + 7%|▋ | 616/8720 [1:38:55<27:58:21, 12.43s/it] {'loss': 1.3323, 'grad_norm': 5.46063232421875, 'learning_rate': 9.956839634376921e-06, 'epoch': 0.71} + 7%|▋ | 616/8720 [1:38:55<27:58:21, 12.43s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1922 +[2025-05-01 23:54:22,728] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 415.89 | bwd_microstep: 527.35 | bwd_inner_microstep: 527.33 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1883 +[2025-05-01 23:54:23,577] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 309.67 | bwd_microstep: 520.75 | bwd_inner_microstep: 520.73 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-01 23:54:24,447] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 336.14 | bwd_microstep: 506.98 | bwd_inner_microstep: 506.96 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.13 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1116 +[2025-05-01 23:54:24,995] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 255.18 | bwd_microstep: 277.11 | bwd_inner_microstep: 277.10 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-01 23:54:25,934] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 412.00 | bwd_microstep: 510.27 | bwd_inner_microstep: 510.25 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-01 23:54:26,738] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 300.11 | bwd_microstep: 484.72 | bwd_inner_microstep: 484.71 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-01 23:54:27,588] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 310.50 | bwd_microstep: 512.05 | bwd_inner_microstep: 512.03 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-01 23:54:28,503] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 399.50 | bwd_microstep: 498.52 | bwd_inner_microstep: 498.50 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.91 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 23:54:29,342] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 313.85 | bwd_microstep: 506.55 | bwd_inner_microstep: 506.53 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 23:54:30,188] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 320.07 | bwd_microstep: 495.41 | bwd_inner_microstep: 495.39 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 23:54:31,031] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 340.28 | bwd_microstep: 473.93 | bwd_inner_microstep: 473.91 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.40 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 23:54:31,881] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 318.19 | bwd_microstep: 501.86 | bwd_inner_microstep: 501.84 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 23:54:32,760] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 334.21 | bwd_microstep: 516.59 | bwd_inner_microstep: 516.58 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 23:54:33,608] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 313.22 | bwd_microstep: 506.81 | bwd_inner_microstep: 506.80 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.31 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 23:54:34,458] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 318.78 | bwd_microstep: 498.23 | bwd_inner_microstep: 498.21 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 23:54:35,387] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.23 | optimizer_step: 16.02 +[2025-05-01 23:54:35,388] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 353.73 | bwd_microstep: 522.65 | bwd_inner_microstep: 321.92 | bwd_allreduce_microstep: 200.69 | step_microstep: 23.30 +[2025-05-01 23:54:35,389] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 5351.27 | bwd: 7859.79 | bwd_inner: 7658.79 | bwd_allreduce: 200.77 | step: 42.48 + 7%|▋ | 617/8720 [1:39:09<28:46:43, 12.79s/it] {'loss': 0.8054, 'grad_norm': 4.9803147315979, 'learning_rate': 9.956595799997504e-06, 'epoch': 0.71} + 7%|▋ | 617/8720 [1:39:09<28:46:43, 12.79s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1966 +[2025-05-01 23:54:36,121] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 200.80 | bwd_microstep: 511.83 | bwd_inner_microstep: 511.81 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1948 +[2025-05-01 23:54:36,792] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 235.32 | bwd_microstep: 420.78 | bwd_inner_microstep: 420.76 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 888 +[2025-05-01 23:54:37,143] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 98.89 | bwd_microstep: 235.20 | bwd_inner_microstep: 235.19 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1905 +[2025-05-01 23:54:37,802] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 268.44 | bwd_microstep: 356.32 | bwd_inner_microstep: 356.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-01 23:54:38,436] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 300.51 | bwd_microstep: 304.50 | bwd_inner_microstep: 304.48 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 334 +[2025-05-01 23:54:38,695] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 91.62 | bwd_microstep: 137.87 | bwd_inner_microstep: 137.85 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.33 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 23:54:39,290] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.67 | bwd_microstep: 375.71 | bwd_inner_microstep: 375.70 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.32 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:54:39,915] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 271.25 | bwd_microstep: 319.68 | bwd_inner_microstep: 319.66 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.49 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-01 23:54:40,690] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 330.40 | bwd_microstep: 413.11 | bwd_inner_microstep: 413.09 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.30 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:54:41,361] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 233.27 | bwd_microstep: 403.36 | bwd_inner_microstep: 403.34 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.32 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 23:54:41,989] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 246.01 | bwd_microstep: 351.69 | bwd_inner_microstep: 351.67 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 23:54:42,662] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 291.77 | bwd_microstep: 344.30 | bwd_inner_microstep: 344.28 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 23:54:43,420] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 303.40 | bwd_microstep: 423.11 | bwd_inner_microstep: 423.09 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.32 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1346 +[2025-05-01 23:54:43,831] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 172.35 | bwd_microstep: 205.44 | bwd_inner_microstep: 205.43 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 23:54:44,530] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 336.88 | bwd_microstep: 345.36 | bwd_inner_microstep: 345.34 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2141 +[2025-05-01 23:54:45,627] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.19 | optimizer_step: 16.04 +[2025-05-01 23:54:45,627] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 422.37 | bwd_microstep: 632.34 | bwd_inner_microstep: 426.36 | bwd_allreduce_microstep: 205.93 | step_microstep: 23.34 +[2025-05-01 23:54:45,628] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 3998.85 | bwd: 5780.62 | bwd_inner: 5574.37 | bwd_allreduce: 206.01 | step: 45.17 + 7%|▋ | 618/8720 [1:39:19<27:03:22, 12.02s/it] {'loss': 1.0957, 'grad_norm': 5.850666046142578, 'learning_rate': 9.956351281788506e-06, 'epoch': 0.71} + 7%|▋ | 618/8720 [1:39:19<27:03:22, 12.02s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1995 +[2025-05-01 23:54:46,360] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 313.80 | bwd_microstep: 397.83 | bwd_inner_microstep: 397.81 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1962 +[2025-05-01 23:54:47,089] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 312.99 | bwd_microstep: 400.20 | bwd_inner_microstep: 400.19 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1903 +[2025-05-01 23:54:47,801] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 283.05 | bwd_microstep: 411.55 | bwd_inner_microstep: 411.53 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-01 23:54:48,563] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 233.85 | bwd_microstep: 507.89 | bwd_inner_microstep: 507.87 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-01 23:54:49,425] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 319.87 | bwd_microstep: 506.19 | bwd_inner_microstep: 506.18 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.28 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-01 23:54:50,213] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 340.70 | bwd_microstep: 428.93 | bwd_inner_microstep: 428.91 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-01 23:54:51,123] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 383.85 | bwd_microstep: 499.09 | bwd_inner_microstep: 499.07 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 23:54:51,936] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 339.60 | bwd_microstep: 454.22 | bwd_inner_microstep: 454.20 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1091 +[2025-05-01 23:54:52,477] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 203.52 | bwd_microstep: 311.53 | bwd_inner_microstep: 311.34 | bwd_allreduce_microstep: 0.10 | step_microstep: 0.11 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 833 +[2025-05-01 23:54:52,862] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 144.64 | bwd_microstep: 222.22 | bwd_inner_microstep: 222.19 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 23:54:53,716] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 389.63 | bwd_microstep: 444.11 | bwd_inner_microstep: 444.09 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 23:54:54,561] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 339.13 | bwd_microstep: 486.17 | bwd_inner_microstep: 486.14 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 23:54:55,420] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 317.60 | bwd_microstep: 512.22 | bwd_inner_microstep: 512.20 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.87 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 315 +[2025-05-01 23:54:55,640] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 79.95 | bwd_microstep: 122.51 | bwd_inner_microstep: 122.49 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1925 +[2025-05-01 23:54:56,312] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 226.43 | bwd_microstep: 415.68 | bwd_inner_microstep: 415.66 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1883 +[2025-05-01 23:54:57,147] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.13 | optimizer_step: 15.79 +[2025-05-01 23:54:57,147] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 312.77 | bwd_microstep: 483.89 | bwd_inner_microstep: 388.89 | bwd_allreduce_microstep: 94.94 | step_microstep: 23.00 +[2025-05-01 23:54:57,148] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4541.19 | bwd: 6604.27 | bwd_inner: 6508.78 | bwd_allreduce: 95.14 | step: 30.75 + 7%|▋ | 619/8720 [1:39:30<26:42:48, 11.87s/it] {'loss': 0.8616, 'grad_norm': 4.918130397796631, 'learning_rate': 9.956106079783662e-06, 'epoch': 0.71} + 7%|▋ | 619/8720 [1:39:30<26:42:48, 11.87s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2000 +[2025-05-01 23:54:57,909] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 325.49 | bwd_microstep: 415.43 | bwd_inner_microstep: 415.41 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-01 23:54:58,536] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 231.09 | bwd_microstep: 376.82 | bwd_inner_microstep: 376.81 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.28 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1125 +[2025-05-01 23:54:58,955] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 184.32 | bwd_microstep: 206.60 | bwd_inner_microstep: 206.39 | bwd_allreduce_microstep: 0.19 | step_microstep: 0.79 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 854 +[2025-05-01 23:54:59,262] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 138.30 | bwd_microstep: 136.32 | bwd_inner_microstep: 136.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.30 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1892 +[2025-05-01 23:54:59,965] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 270.11 | bwd_microstep: 401.15 | bwd_inner_microstep: 401.13 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 847 +[2025-05-01 23:55:00,326] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 97.64 | bwd_microstep: 249.97 | bwd_inner_microstep: 249.86 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-01 23:55:00,951] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 230.66 | bwd_microstep: 375.29 | bwd_inner_microstep: 375.28 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-01 23:55:01,635] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 255.18 | bwd_microstep: 401.51 | bwd_inner_microstep: 401.50 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-01 23:55:02,282] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 257.61 | bwd_microstep: 371.85 | bwd_inner_microstep: 371.83 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.21 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-01 23:55:02,940] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 235.77 | bwd_microstep: 396.63 | bwd_inner_microstep: 396.62 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 23:55:03,654] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 313.61 | bwd_microstep: 384.46 | bwd_inner_microstep: 384.44 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.66 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 23:55:04,261] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 192.19 | bwd_microstep: 396.96 | bwd_inner_microstep: 396.94 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 23:55:04,993] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.80 | bwd_microstep: 526.31 | bwd_inner_microstep: 526.29 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 23:55:05,671] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 248.94 | bwd_microstep: 411.15 | bwd_inner_microstep: 411.13 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1345 +[2025-05-01 23:55:06,227] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.73 | bwd_microstep: 395.31 | bwd_inner_microstep: 395.16 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 23:55:07,233] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.15 | optimizer_step: 15.94 +[2025-05-01 23:55:07,233] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 361.47 | bwd_microstep: 601.83 | bwd_inner_microstep: 432.36 | bwd_allreduce_microstep: 169.43 | step_microstep: 23.16 +[2025-05-01 23:55:07,235] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 3671.71 | bwd: 6047.65 | bwd_inner: 5877.46 | bwd_allreduce: 169.84 | step: 32.01 + 7%|▋ | 620/8720 [1:39:40<25:30:20, 11.34s/it] {'loss': 1.0444, 'grad_norm': 5.148181915283203, 'learning_rate': 9.955860194016803e-06, 'epoch': 0.71} + 7%|▋ | 620/8720 [1:39:40<25:30:20, 11.34s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1941 +[2025-05-01 23:55:08,175] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 381.44 | bwd_microstep: 536.77 | bwd_inner_microstep: 536.75 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1922 +[2025-05-01 23:55:09,017] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 273.01 | bwd_microstep: 548.12 | bwd_inner_microstep: 548.10 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.68 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1363 +[2025-05-01 23:55:09,609] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 226.61 | bwd_microstep: 346.13 | bwd_inner_microstep: 346.11 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.47 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-01 23:55:10,491] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 353.64 | bwd_microstep: 494.19 | bwd_inner_microstep: 494.17 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-01 23:55:11,404] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 403.29 | bwd_microstep: 491.47 | bwd_inner_microstep: 491.46 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.27 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-01 23:55:12,299] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 354.72 | bwd_microstep: 517.18 | bwd_inner_microstep: 517.16 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:55:13,123] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 321.08 | bwd_microstep: 482.55 | bwd_inner_microstep: 482.53 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:55:14,012] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 358.49 | bwd_microstep: 514.16 | bwd_inner_microstep: 514.14 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 320 +[2025-05-01 23:55:14,230] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 73.06 | bwd_microstep: 126.66 | bwd_inner_microstep: 126.64 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 23:55:15,101] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 315.42 | bwd_microstep: 530.93 | bwd_inner_microstep: 530.92 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.77 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 23:55:15,962] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 330.60 | bwd_microstep: 511.45 | bwd_inner_microstep: 511.43 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.51 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 23:55:16,809] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 303.86 | bwd_microstep: 511.12 | bwd_inner_microstep: 511.11 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.31 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 23:55:17,601] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 308.85 | bwd_microstep: 450.53 | bwd_inner_microstep: 450.51 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 318 +[2025-05-01 23:55:17,857] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 96.12 | bwd_microstep: 130.03 | bwd_inner_microstep: 130.01 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.33 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2066 +[2025-05-01 23:55:18,786] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 335.63 | bwd_microstep: 567.02 | bwd_inner_microstep: 567.00 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.32 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-01 23:55:19,837] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.13 | optimizer_step: 16.80 +[2025-05-01 23:55:19,838] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 299.29 | bwd_microstep: 699.61 | bwd_inner_microstep: 505.14 | bwd_allreduce_microstep: 194.43 | step_microstep: 24.49 +[2025-05-01 23:55:19,839] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4735.06 | bwd: 7457.93 | bwd_inner: 7263.18 | bwd_allreduce: 194.51 | step: 47.78 + 7%|▋ | 621/8720 [1:39:53<26:21:38, 11.72s/it] {'loss': 0.713, 'grad_norm': 3.690194606781006, 'learning_rate': 9.955613624521846e-06, 'epoch': 0.71} + 7%|▋ | 621/8720 [1:39:53<26:21:38, 11.72s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2084 +[2025-05-01 23:55:20,782] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 343.34 | bwd_microstep: 557.31 | bwd_inner_microstep: 557.29 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-01 23:55:21,642] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 336.81 | bwd_microstep: 493.31 | bwd_inner_microstep: 493.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-01 23:55:22,549] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 395.82 | bwd_microstep: 494.18 | bwd_inner_microstep: 494.16 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.87 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-01 23:55:23,377] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 306.25 | bwd_microstep: 502.29 | bwd_inner_microstep: 502.27 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:55:24,220] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 312.36 | bwd_microstep: 499.44 | bwd_inner_microstep: 499.42 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 23:55:25,052] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 307.74 | bwd_microstep: 490.16 | bwd_inner_microstep: 490.15 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 23:55:25,932] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 359.86 | bwd_microstep: 491.14 | bwd_inner_microstep: 491.12 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 23:55:26,819] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 372.97 | bwd_microstep: 496.73 | bwd_inner_microstep: 496.71 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 23:55:27,658] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 309.46 | bwd_microstep: 506.04 | bwd_inner_microstep: 506.02 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.32 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 23:55:28,502] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 305.29 | bwd_microstep: 506.94 | bwd_inner_microstep: 506.92 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 23:55:29,359] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 327.76 | bwd_microstep: 496.79 | bwd_inner_microstep: 496.78 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.48 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 23:55:30,203] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 316.23 | bwd_microstep: 496.21 | bwd_inner_microstep: 496.19 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.40 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 23:55:31,054] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 319.95 | bwd_microstep: 500.69 | bwd_inner_microstep: 500.68 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 23:55:31,933] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 336.31 | bwd_microstep: 512.10 | bwd_inner_microstep: 512.08 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.65 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 23:55:32,738] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 302.43 | bwd_microstep: 484.65 | bwd_inner_microstep: 484.64 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1708 +[2025-05-01 23:55:33,767] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.69 | optimizer_step: 16.38 +[2025-05-01 23:55:33,768] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 321.87 | bwd_microstep: 669.47 | bwd_inner_microstep: 477.80 | bwd_allreduce_microstep: 191.65 | step_microstep: 24.80 +[2025-05-01 23:55:33,769] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 5274.40 | bwd: 8197.46 | bwd_inner: 8005.54 | bwd_allreduce: 191.71 | step: 47.92 + 7%|▋ | 622/8720 [1:40:07<27:51:03, 12.38s/it] {'loss': 1.1018, 'grad_norm': 7.489566802978516, 'learning_rate': 9.955366371332815e-06, 'epoch': 0.71} + 7%|▋ | 622/8720 [1:40:07<27:51:03, 12.38s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2105 +[2025-05-01 23:55:34,707] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 343.52 | bwd_microstep: 554.60 | bwd_inner_microstep: 554.58 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1393 +[2025-05-01 23:55:35,407] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 296.81 | bwd_microstep: 386.38 | bwd_inner_microstep: 386.36 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.33 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-01 23:55:36,264] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 327.21 | bwd_microstep: 501.91 | bwd_inner_microstep: 501.89 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-01 23:55:37,127] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 367.19 | bwd_microstep: 478.90 | bwd_inner_microstep: 478.88 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-01 23:55:38,018] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 384.25 | bwd_microstep: 491.12 | bwd_inner_microstep: 491.10 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 844 +[2025-05-01 23:55:38,419] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 165.20 | bwd_microstep: 221.01 | bwd_inner_microstep: 220.80 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-01 23:55:39,330] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 400.47 | bwd_microstep: 492.34 | bwd_inner_microstep: 492.33 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-01 23:55:40,189] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 353.97 | bwd_microstep: 485.95 | bwd_inner_microstep: 485.94 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:55:41,074] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 332.49 | bwd_microstep: 518.99 | bwd_inner_microstep: 518.98 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 23:55:41,919] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 302.03 | bwd_microstep: 508.81 | bwd_inner_microstep: 508.79 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.32 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 23:55:42,787] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 327.40 | bwd_microstep: 508.41 | bwd_inner_microstep: 508.39 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.50 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 23:55:43,584] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 328.18 | bwd_microstep: 437.05 | bwd_inner_microstep: 437.04 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 23:55:44,423] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 320.13 | bwd_microstep: 489.98 | bwd_inner_microstep: 489.96 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 828 +[2025-05-01 23:55:44,809] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 92.22 | bwd_microstep: 276.40 | bwd_inner_microstep: 276.38 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.33 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1903 +[2025-05-01 23:55:45,552] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 244.61 | bwd_microstep: 468.07 | bwd_inner_microstep: 468.05 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1888 +[2025-05-01 23:55:46,587] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.17 | optimizer_step: 16.34 +[2025-05-01 23:55:46,588] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 397.11 | bwd_microstep: 596.48 | bwd_inner_microstep: 442.79 | bwd_allreduce_microstep: 153.64 | step_microstep: 23.62 +[2025-05-01 23:55:46,589] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4982.67 | bwd: 7416.44 | bwd_inner: 7262.26 | bwd_allreduce: 153.85 | step: 40.61 + 7%|▋ | 623/8720 [1:40:20<28:08:34, 12.51s/it] {'loss': 1.02, 'grad_norm': 4.010837078094482, 'learning_rate': 9.955118434483822e-06, 'epoch': 0.71} + 7%|▋ | 623/8720 [1:40:20<28:08:34, 12.51s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1974 +[2025-05-01 23:55:47,516] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 413.66 | bwd_microstep: 489.13 | bwd_inner_microstep: 489.11 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.33 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1925 +[2025-05-01 23:55:48,263] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 261.72 | bwd_microstep: 461.88 | bwd_inner_microstep: 461.86 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 868 +[2025-05-01 23:55:48,684] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 208.75 | bwd_microstep: 182.13 | bwd_inner_microstep: 181.96 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1898 +[2025-05-01 23:55:49,507] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 372.50 | bwd_microstep: 433.51 | bwd_inner_microstep: 433.49 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1890 +[2025-05-01 23:55:50,274] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 247.02 | bwd_microstep: 487.92 | bwd_inner_microstep: 487.90 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-01 23:55:51,098] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 373.03 | bwd_microstep: 433.46 | bwd_inner_microstep: 433.44 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-01 23:55:51,866] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 244.15 | bwd_microstep: 493.94 | bwd_inner_microstep: 493.93 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-01 23:55:52,680] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 361.99 | bwd_microstep: 434.28 | bwd_inner_microstep: 434.26 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.33 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-01 23:55:53,456] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 252.33 | bwd_microstep: 493.75 | bwd_inner_microstep: 493.73 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1357 +[2025-05-01 23:55:54,032] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 247.43 | bwd_microstep: 313.11 | bwd_inner_microstep: 313.06 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 328 +[2025-05-01 23:55:54,266] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 96.64 | bwd_microstep: 121.94 | bwd_inner_microstep: 121.92 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.32 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 23:55:54,996] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 264.15 | bwd_microstep: 431.43 | bwd_inner_microstep: 431.41 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.48 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:55:55,845] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 322.30 | bwd_microstep: 497.99 | bwd_inner_microstep: 497.98 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 23:55:56,595] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 300.51 | bwd_microstep: 430.56 | bwd_inner_microstep: 430.54 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 23:55:57,321] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 267.98 | bwd_microstep: 426.77 | bwd_inner_microstep: 426.75 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 23:55:58,375] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.16 | optimizer_step: 15.89 +[2025-05-01 23:55:58,375] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 301.27 | bwd_microstep: 698.24 | bwd_inner_microstep: 393.81 | bwd_allreduce_microstep: 304.39 | step_microstep: 23.13 +[2025-05-01 23:55:58,377] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4535.31 | bwd: 6830.10 | bwd_inner: 6525.19 | bwd_allreduce: 304.57 | step: 44.72 + 7%|▋ | 624/8720 [1:40:32<27:38:54, 12.29s/it] {'loss': 1.464, 'grad_norm': 8.53575611114502, 'learning_rate': 9.954869814009068e-06, 'epoch': 0.72} + 7%|▋ | 624/8720 [1:40:32<27:38:54, 12.29s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1893 +[2025-05-01 23:55:59,198] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 377.66 | bwd_microstep: 422.22 | bwd_inner_microstep: 422.21 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-01 23:55:59,987] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 259.90 | bwd_microstep: 498.48 | bwd_inner_microstep: 498.46 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-01 23:56:00,762] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 319.20 | bwd_microstep: 438.13 | bwd_inner_microstep: 438.11 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-01 23:56:01,594] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 305.48 | bwd_microstep: 495.17 | bwd_inner_microstep: 495.16 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-01 23:56:02,311] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 269.13 | bwd_microstep: 428.20 | bwd_inner_microstep: 428.18 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 23:56:03,175] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 358.13 | bwd_microstep: 471.77 | bwd_inner_microstep: 471.75 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-01 23:56:03,943] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 257.51 | bwd_microstep: 487.54 | bwd_inner_microstep: 487.52 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.31 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1099 +[2025-05-01 23:56:04,465] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 144.41 | bwd_microstep: 347.27 | bwd_inner_microstep: 347.25 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.33 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-01 23:56:05,245] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 282.20 | bwd_microstep: 478.18 | bwd_inner_microstep: 478.16 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.23 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:56:06,044] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 292.54 | bwd_microstep: 477.00 | bwd_inner_microstep: 476.99 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1346 +[2025-05-01 23:56:06,707] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 309.90 | bwd_microstep: 326.34 | bwd_inner_microstep: 326.32 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.32 +dynamic ViT batch size: 6, images per sample: 6.0, dynamic token length: 1603 +[2025-05-01 23:56:07,419] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 236.52 | bwd_microstep: 445.49 | bwd_inner_microstep: 445.48 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 23:56:08,300] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 387.61 | bwd_microstep: 474.72 | bwd_inner_microstep: 474.70 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 23:56:09,079] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 279.13 | bwd_microstep: 478.95 | bwd_inner_microstep: 478.93 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 23:56:09,876] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 292.89 | bwd_microstep: 476.03 | bwd_inner_microstep: 476.01 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-01 23:56:10,870] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.14 | optimizer_step: 16.79 +[2025-05-01 23:56:10,871] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 370.35 | bwd_microstep: 572.40 | bwd_inner_microstep: 484.56 | bwd_allreduce_microstep: 87.79 | step_microstep: 24.82 +[2025-05-01 23:56:10,872] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4742.48 | bwd: 7317.91 | bwd_inner: 7229.80 | bwd_allreduce: 87.87 | step: 44.23 + 7%|▋ | 625/8720 [1:40:44<27:46:59, 12.36s/it] {'loss': 1.2111, 'grad_norm': 5.343022346496582, 'learning_rate': 9.954620509942856e-06, 'epoch': 0.72} + 7%|▋ | 625/8720 [1:40:44<27:46:59, 12.36s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-01 23:56:11,722] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 322.49 | bwd_microstep: 487.34 | bwd_inner_microstep: 487.32 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-01 23:56:12,598] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 386.26 | bwd_microstep: 472.40 | bwd_inner_microstep: 472.38 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-01 23:56:13,468] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 325.48 | bwd_microstep: 521.42 | bwd_inner_microstep: 521.40 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 333 +[2025-05-01 23:56:13,684] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 69.59 | bwd_microstep: 127.40 | bwd_inner_microstep: 127.04 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-01 23:56:14,474] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 281.29 | bwd_microstep: 477.71 | bwd_inner_microstep: 477.68 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-01 23:56:15,115] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 352.00 | bwd_microstep: 273.45 | bwd_inner_microstep: 273.43 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-01 23:56:15,592] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.02 | bwd_microstep: 272.99 | bwd_inner_microstep: 272.97 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1355 +[2025-05-01 23:56:15,954] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.56 | bwd_microstep: 206.40 | bwd_inner_microstep: 206.38 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 23:56:16,430] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.55 | bwd_microstep: 273.05 | bwd_inner_microstep: 273.04 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 23:56:17,147] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 311.80 | bwd_microstep: 387.39 | bwd_inner_microstep: 387.37 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 23:56:17,972] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 353.27 | bwd_microstep: 441.86 | bwd_inner_microstep: 441.84 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1345 +[2025-05-01 23:56:18,332] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.22 | bwd_microstep: 205.60 | bwd_inner_microstep: 205.57 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 23:56:18,806] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.49 | bwd_microstep: 271.16 | bwd_inner_microstep: 271.14 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-01 23:56:19,527] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 235.76 | bwd_microstep: 467.22 | bwd_inner_microstep: 467.20 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 23:56:20,181] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 349.40 | bwd_microstep: 272.19 | bwd_inner_microstep: 272.17 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-01 23:56:21,199] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.21 | optimizer_step: 16.50 +[2025-05-01 23:56:21,199] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 268.80 | bwd_microstep: 709.86 | bwd_inner_microstep: 482.44 | bwd_allreduce_microstep: 227.37 | step_microstep: 23.91 +[2025-05-01 23:56:21,201] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4099.82 | bwd: 5867.46 | bwd_inner: 5639.39 | bwd_allreduce: 227.62 | step: 33.97 + 7%|▋ | 626/8720 [1:40:54<26:24:36, 11.75s/it] {'loss': 1.017, 'grad_norm': 4.425351142883301, 'learning_rate': 9.954370522319583e-06, 'epoch': 0.72} + 7%|▋ | 626/8720 [1:40:54<26:24:36, 11.75s/it]dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1386 +[2025-05-01 23:56:21,571] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 142.24 | bwd_microstep: 208.42 | bwd_inner_microstep: 208.18 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.19 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 341 +[2025-05-01 23:56:21,784] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 73.95 | bwd_microstep: 124.34 | bwd_inner_microstep: 124.02 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-01 23:56:22,393] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.40 | bwd_microstep: 402.16 | bwd_inner_microstep: 402.14 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-01 23:56:23,214] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 317.05 | bwd_microstep: 471.87 | bwd_inner_microstep: 471.85 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.51 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-01 23:56:23,785] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 268.34 | bwd_microstep: 273.39 | bwd_inner_microstep: 273.37 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-01 23:56:24,423] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.43 | bwd_microstep: 430.60 | bwd_inner_microstep: 430.58 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.33 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-01 23:56:25,101] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 210.19 | bwd_microstep: 434.53 | bwd_inner_microstep: 434.51 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 843 +[2025-05-01 23:56:25,455] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 116.94 | bwd_microstep: 208.79 | bwd_inner_microstep: 208.78 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 23:56:26,269] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 300.43 | bwd_microstep: 485.90 | bwd_inner_microstep: 485.88 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.92 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 322 +[2025-05-01 23:56:26,477] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 69.03 | bwd_microstep: 122.36 | bwd_inner_microstep: 122.09 | bwd_allreduce_microstep: 0.10 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 23:56:26,955] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.37 | bwd_microstep: 273.28 | bwd_inner_microstep: 273.26 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 23:56:27,796] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 302.69 | bwd_microstep: 518.17 | bwd_inner_microstep: 518.16 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 23:56:28,663] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 318.40 | bwd_microstep: 511.52 | bwd_inner_microstep: 511.50 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 23:56:29,509] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 320.86 | bwd_microstep: 494.31 | bwd_inner_microstep: 494.29 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-01 23:56:30,405] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 367.63 | bwd_microstep: 507.92 | bwd_inner_microstep: 507.90 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.32 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1949 +[2025-05-01 23:56:31,550] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.15 | optimizer_step: 16.78 +[2025-05-01 23:56:31,551] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 336.05 | bwd_microstep: 758.35 | bwd_inner_microstep: 546.20 | bwd_allreduce_microstep: 212.14 | step_microstep: 26.45 +[2025-05-01 23:56:31,552] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 3710.86 | bwd: 6226.00 | bwd_inner: 6012.84 | bwd_allreduce: 212.55 | step: 44.75 + 7%|▋ | 627/8720 [1:41:05<25:28:05, 11.33s/it] {'loss': 0.8702, 'grad_norm': 4.9976677894592285, 'learning_rate': 9.954119851173736e-06, 'epoch': 0.72} + 7%|▋ | 627/8720 [1:41:05<25:28:05, 11.33s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 388 +[2025-05-01 23:56:31,824] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 106.61 | bwd_microstep: 124.77 | bwd_inner_microstep: 124.75 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1892 +[2025-05-01 23:56:32,713] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 338.94 | bwd_microstep: 518.34 | bwd_inner_microstep: 518.32 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.29 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1889 +[2025-05-01 23:56:33,590] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 327.54 | bwd_microstep: 516.11 | bwd_inner_microstep: 516.09 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-01 23:56:34,451] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 314.63 | bwd_microstep: 512.66 | bwd_inner_microstep: 512.65 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-01 23:56:35,315] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 337.50 | bwd_microstep: 496.33 | bwd_inner_microstep: 496.31 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-01 23:56:36,167] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 315.88 | bwd_microstep: 512.80 | bwd_inner_microstep: 512.78 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.32 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-01 23:56:37,045] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 329.44 | bwd_microstep: 521.75 | bwd_inner_microstep: 521.74 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-01 23:56:37,970] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 399.65 | bwd_microstep: 506.74 | bwd_inner_microstep: 506.72 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-01 23:56:38,795] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 306.05 | bwd_microstep: 497.16 | bwd_inner_microstep: 497.14 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-01 23:56:39,672] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 330.96 | bwd_microstep: 513.96 | bwd_inner_microstep: 513.94 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-01 23:56:40,580] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 400.58 | bwd_microstep: 489.41 | bwd_inner_microstep: 489.39 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:56:41,455] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 315.19 | bwd_microstep: 529.25 | bwd_inner_microstep: 529.23 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.87 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:56:42,316] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 339.26 | bwd_microstep: 499.42 | bwd_inner_microstep: 499.40 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 23:56:43,152] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 313.70 | bwd_microstep: 492.64 | bwd_inner_microstep: 492.62 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 830 +[2025-05-01 23:56:43,638] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 200.99 | bwd_microstep: 260.25 | bwd_inner_microstep: 259.95 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 23:56:44,796] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.19 | optimizer_step: 16.76 +[2025-05-01 23:56:44,797] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 360.10 | bwd_microstep: 754.94 | bwd_inner_microstep: 504.97 | bwd_allreduce_microstep: 249.96 | step_microstep: 26.08 +[2025-05-01 23:56:44,799] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 5036.93 | bwd: 7746.55 | bwd_inner: 7496.05 | bwd_allreduce: 250.14 | step: 48.58 + 7%|▋ | 628/8720 [1:41:18<26:45:29, 11.90s/it] {'loss': 0.979, 'grad_norm': 4.916419982910156, 'learning_rate': 9.953868496539898e-06, 'epoch': 0.72} + 7%|▋ | 628/8720 [1:41:18<26:45:29, 11.90s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1924 +[2025-05-01 23:56:45,706] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 320.17 | bwd_microstep: 544.51 | bwd_inner_microstep: 544.49 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.31 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1894 +[2025-05-01 23:56:46,577] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 318.45 | bwd_microstep: 518.58 | bwd_inner_microstep: 518.56 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1900 +[2025-05-01 23:56:47,429] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 322.69 | bwd_microstep: 499.17 | bwd_inner_microstep: 499.15 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-01 23:56:48,333] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 381.95 | bwd_microstep: 506.47 | bwd_inner_microstep: 506.46 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1116 +[2025-05-01 23:56:48,837] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.54 | bwd_microstep: 302.36 | bwd_inner_microstep: 302.17 | bwd_allreduce_microstep: 0.10 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-01 23:56:49,750] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 386.19 | bwd_microstep: 506.42 | bwd_inner_microstep: 506.40 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.94 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-01 23:56:50,607] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 321.05 | bwd_microstep: 516.63 | bwd_inner_microstep: 516.61 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-01 23:56:51,478] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 317.13 | bwd_microstep: 521.96 | bwd_inner_microstep: 521.94 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.31 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 23:56:52,312] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 309.62 | bwd_microstep: 492.51 | bwd_inner_microstep: 492.49 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.28 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:56:53,184] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 313.52 | bwd_microstep: 518.03 | bwd_inner_microstep: 518.01 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.50 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 23:56:54,049] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 333.98 | bwd_microstep: 500.64 | bwd_inner_microstep: 500.62 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 23:56:54,969] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 389.34 | bwd_microstep: 514.38 | bwd_inner_microstep: 514.37 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 831 +[2025-05-01 23:56:55,389] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 112.26 | bwd_microstep: 289.59 | bwd_inner_microstep: 289.57 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.51 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1345 +[2025-05-01 23:56:55,977] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 213.85 | bwd_microstep: 344.20 | bwd_inner_microstep: 344.18 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 23:56:56,844] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 329.76 | bwd_microstep: 511.94 | bwd_inner_microstep: 511.92 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 23:56:58,019] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.18 | optimizer_step: 16.77 +[2025-05-01 23:56:58,020] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 353.73 | bwd_microstep: 769.28 | bwd_inner_microstep: 458.64 | bwd_allreduce_microstep: 310.62 | step_microstep: 26.20 +[2025-05-01 23:56:58,021] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4909.91 | bwd: 7856.69 | bwd_inner: 7545.59 | bwd_allreduce: 310.80 | step: 46.93 + 7%|▋ | 629/8720 [1:41:31<27:38:36, 12.30s/it] {'loss': 1.0723, 'grad_norm': 5.319332122802734, 'learning_rate': 9.953616458452748e-06, 'epoch': 0.72} + 7%|▋ | 629/8720 [1:41:31<27:38:36, 12.30s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1938 +[2025-05-01 23:56:58,923] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 328.45 | bwd_microstep: 533.34 | bwd_inner_microstep: 533.32 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.20 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 879 +[2025-05-01 23:56:59,391] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 171.40 | bwd_microstep: 281.05 | bwd_inner_microstep: 280.77 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1893 +[2025-05-01 23:57:00,230] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 315.66 | bwd_microstep: 506.54 | bwd_inner_microstep: 506.52 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-01 23:57:01,137] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 374.58 | bwd_microstep: 512.31 | bwd_inner_microstep: 512.29 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-01 23:57:01,992] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 315.68 | bwd_microstep: 514.48 | bwd_inner_microstep: 514.46 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1357 +[2025-05-01 23:57:02,645] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 219.21 | bwd_microstep: 405.59 | bwd_inner_microstep: 405.58 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-01 23:57:03,560] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 380.45 | bwd_microstep: 514.37 | bwd_inner_microstep: 514.36 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.52 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 329 +[2025-05-01 23:57:03,777] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 74.30 | bwd_microstep: 127.50 | bwd_inner_microstep: 127.17 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-01 23:57:04,640] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 329.41 | bwd_microstep: 507.47 | bwd_inner_microstep: 507.45 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 23:57:05,484] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 326.55 | bwd_microstep: 483.16 | bwd_inner_microstep: 483.14 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 832 +[2025-05-01 23:57:05,922] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 200.09 | bwd_microstep: 209.39 | bwd_inner_microstep: 209.15 | bwd_allreduce_microstep: 0.23 | step_microstep: 1.30 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 23:57:06,796] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 326.17 | bwd_microstep: 514.89 | bwd_inner_microstep: 514.88 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 23:57:07,661] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 340.52 | bwd_microstep: 496.98 | bwd_inner_microstep: 496.97 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 23:57:08,589] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 403.29 | bwd_microstep: 506.58 | bwd_inner_microstep: 506.56 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 23:57:09,424] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 341.15 | bwd_microstep: 475.82 | bwd_inner_microstep: 475.80 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.28 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 23:57:10,488] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.22 | optimizer_step: 17.88 +[2025-05-01 23:57:10,491] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 308.53 | bwd_microstep: 702.35 | bwd_inner_microstep: 484.33 | bwd_allreduce_microstep: 217.97 | step_microstep: 25.35 +[2025-05-01 23:57:10,492] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4755.35 | bwd: 7291.87 | bwd_inner: 7072.86 | bwd_allreduce: 218.51 | step: 43.77 + 7%|▋ | 630/8720 [1:41:44<27:45:18, 12.35s/it] {'loss': 0.8365, 'grad_norm': 4.32837438583374, 'learning_rate': 9.953363736947059e-06, 'epoch': 0.72} + 7%|▋ | 630/8720 [1:41:44<27:45:18, 12.35s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2000 +[2025-05-01 23:57:11,371] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 334.43 | bwd_microstep: 504.75 | bwd_inner_microstep: 504.74 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 879 +[2025-05-01 23:57:11,826] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 172.30 | bwd_microstep: 267.71 | bwd_inner_microstep: 267.57 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1896 +[2025-05-01 23:57:12,663] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 352.41 | bwd_microstep: 465.94 | bwd_inner_microstep: 465.92 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 340 +[2025-05-01 23:57:12,907] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 77.13 | bwd_microstep: 135.29 | bwd_inner_microstep: 135.27 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.47 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-01 23:57:13,752] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 318.48 | bwd_microstep: 494.61 | bwd_inner_microstep: 494.59 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-01 23:57:14,614] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 347.30 | bwd_microstep: 485.14 | bwd_inner_microstep: 485.12 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-01 23:57:15,499] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 364.95 | bwd_microstep: 500.10 | bwd_inner_microstep: 500.08 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-01 23:57:16,242] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 277.39 | bwd_microstep: 442.90 | bwd_inner_microstep: 442.88 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-01 23:57:17,088] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 329.08 | bwd_microstep: 486.81 | bwd_inner_microstep: 486.79 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-01 23:57:17,855] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 366.22 | bwd_microstep: 385.96 | bwd_inner_microstep: 385.95 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 325 +[2025-05-01 23:57:18,084] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 98.96 | bwd_microstep: 105.83 | bwd_inner_microstep: 105.70 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 23:57:18,971] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 363.74 | bwd_microstep: 505.13 | bwd_inner_microstep: 505.11 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 23:57:19,829] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 320.03 | bwd_microstep: 514.72 | bwd_inner_microstep: 514.70 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.31 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 23:57:20,673] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 309.80 | bwd_microstep: 501.80 | bwd_inner_microstep: 501.79 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.28 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 23:57:21,559] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 335.01 | bwd_microstep: 518.87 | bwd_inner_microstep: 518.85 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1909 +[2025-05-01 23:57:22,732] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.23 | optimizer_step: 16.23 +[2025-05-01 23:57:22,732] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 336.20 | bwd_microstep: 791.97 | bwd_inner_microstep: 517.20 | bwd_allreduce_microstep: 274.75 | step_microstep: 25.34 +[2025-05-01 23:57:22,734] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4703.34 | bwd: 7107.57 | bwd_inner: 6832.33 | bwd_allreduce: 274.92 | step: 46.96 + 7%|▋ | 631/8720 [1:41:56<27:40:35, 12.32s/it] {'loss': 1.2193, 'grad_norm': 4.483588695526123, 'learning_rate': 9.953110332057697e-06, 'epoch': 0.72} + 7%|▋ | 631/8720 [1:41:56<27:40:35, 12.32s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2054 +[2025-05-01 23:57:23,637] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 325.54 | bwd_microstep: 554.48 | bwd_inner_microstep: 554.46 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 473 +[2025-05-01 23:57:23,934] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 106.86 | bwd_microstep: 162.62 | bwd_inner_microstep: 162.14 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.24 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1921 +[2025-05-01 23:57:24,854] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 362.46 | bwd_microstep: 538.14 | bwd_inner_microstep: 538.12 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.49 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-01 23:57:25,683] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 317.26 | bwd_microstep: 493.38 | bwd_inner_microstep: 493.36 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-01 23:57:26,602] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 394.78 | bwd_microstep: 506.70 | bwd_inner_microstep: 506.68 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.90 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 840 +[2025-05-01 23:57:27,026] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 127.17 | bwd_microstep: 279.73 | bwd_inner_microstep: 279.71 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 845 +[2025-05-01 23:57:27,452] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 112.86 | bwd_microstep: 291.42 | bwd_inner_microstep: 291.40 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-01 23:57:28,281] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 304.58 | bwd_microstep: 494.68 | bwd_inner_microstep: 494.66 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.14 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 23:57:29,087] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 322.27 | bwd_microstep: 465.87 | bwd_inner_microstep: 465.85 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 23:57:29,943] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 399.86 | bwd_microstep: 438.09 | bwd_inner_microstep: 438.07 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 23:57:30,801] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 350.11 | bwd_microstep: 482.50 | bwd_inner_microstep: 482.48 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.78 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 23:57:31,675] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 334.20 | bwd_microstep: 515.64 | bwd_inner_microstep: 515.62 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.31 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 23:57:32,540] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 317.44 | bwd_microstep: 516.26 | bwd_inner_microstep: 516.24 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.28 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 23:57:33,400] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 298.42 | bwd_microstep: 526.66 | bwd_inner_microstep: 526.65 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.28 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 23:57:34,217] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 311.21 | bwd_microstep: 487.94 | bwd_inner_microstep: 487.92 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 23:57:35,437] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.19 | optimizer_step: 16.45 +[2025-05-01 23:57:35,438] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 391.37 | bwd_microstep: 789.60 | bwd_inner_microstep: 489.69 | bwd_allreduce_microstep: 299.90 | step_microstep: 24.36 +[2025-05-01 23:57:35,439] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4776.27 | bwd: 7543.70 | bwd_inner: 7243.06 | bwd_allreduce: 299.96 | step: 43.16 + 7%|▋ | 632/8720 [1:42:09<27:56:05, 12.43s/it] {'loss': 0.7176, 'grad_norm': 7.259215354919434, 'learning_rate': 9.95285624381962e-06, 'epoch': 0.72} + 7%|▋ | 632/8720 [1:42:09<27:56:05, 12.43s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2014 +[2025-05-01 23:57:36,387] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 381.71 | bwd_microstep: 544.57 | bwd_inner_microstep: 544.55 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1904 +[2025-05-01 23:57:37,195] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 351.10 | bwd_microstep: 439.56 | bwd_inner_microstep: 439.54 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1888 +[2025-05-01 23:57:38,085] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 377.31 | bwd_microstep: 486.26 | bwd_inner_microstep: 486.19 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-01 23:57:39,000] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 398.28 | bwd_microstep: 500.89 | bwd_inner_microstep: 500.87 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-01 23:57:39,854] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 323.85 | bwd_microstep: 510.59 | bwd_inner_microstep: 510.57 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.32 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-01 23:57:40,661] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 327.35 | bwd_microstep: 450.55 | bwd_inner_microstep: 450.53 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-01 23:57:41,569] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 385.90 | bwd_microstep: 503.58 | bwd_inner_microstep: 503.56 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.71 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-01 23:57:42,379] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 284.42 | bwd_microstep: 506.39 | bwd_inner_microstep: 506.37 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 23:57:43,262] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 332.05 | bwd_microstep: 521.75 | bwd_inner_microstep: 521.73 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.22 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-01 23:57:44,153] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 344.86 | bwd_microstep: 517.15 | bwd_inner_microstep: 517.13 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.92 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-01 23:57:44,968] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 311.15 | bwd_microstep: 486.40 | bwd_inner_microstep: 486.38 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 23:57:45,834] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 326.68 | bwd_microstep: 511.38 | bwd_inner_microstep: 511.36 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1342 +[2025-05-01 23:57:46,472] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 241.13 | bwd_microstep: 366.39 | bwd_inner_microstep: 366.37 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 23:57:47,311] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 356.10 | bwd_microstep: 453.60 | bwd_inner_microstep: 453.58 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 23:57:48,184] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 397.66 | bwd_microstep: 457.36 | bwd_inner_microstep: 457.34 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.23 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-01 23:57:49,272] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 4.73 | optimizer_step: 20.88 +[2025-05-01 23:57:49,274] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 319.56 | bwd_microstep: 723.35 | bwd_inner_microstep: 516.21 | bwd_allreduce_microstep: 207.09 | step_microstep: 30.90 +[2025-05-01 23:57:49,276] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 5459.00 | bwd: 7979.78 | bwd_inner: 7772.31 | bwd_allreduce: 207.19 | step: 42.64 + 7%|▋ | 633/8720 [1:42:23<28:52:42, 12.86s/it] {'loss': 1.2399, 'grad_norm': 6.187389850616455, 'learning_rate': 9.952601472267885e-06, 'epoch': 0.73} + 7%|▋ | 633/8720 [1:42:23<28:52:42, 12.86s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1936 +[2025-05-01 23:57:50,193] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 342.48 | bwd_microstep: 533.24 | bwd_inner_microstep: 533.22 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 391 +[2025-05-01 23:57:50,448] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 98.19 | bwd_microstep: 124.09 | bwd_inner_microstep: 124.08 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.51 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1908 +[2025-05-01 23:57:51,342] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 349.40 | bwd_microstep: 512.56 | bwd_inner_microstep: 512.54 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.88 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-01 23:57:52,144] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 302.92 | bwd_microstep: 478.98 | bwd_inner_microstep: 478.96 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 23:57:53,019] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 319.50 | bwd_microstep: 520.58 | bwd_inner_microstep: 520.56 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-01 23:57:53,897] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 359.61 | bwd_microstep: 484.37 | bwd_inner_microstep: 484.35 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 23:57:54,743] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 309.91 | bwd_microstep: 501.82 | bwd_inner_microstep: 501.80 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.33 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1355 +[2025-05-01 23:57:55,372] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 233.13 | bwd_microstep: 363.08 | bwd_inner_microstep: 363.06 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-01 23:57:56,257] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 334.09 | bwd_microstep: 524.06 | bwd_inner_microstep: 524.04 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 23:57:57,062] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 329.07 | bwd_microstep: 442.37 | bwd_inner_microstep: 442.35 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 23:57:57,776] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 261.68 | bwd_microstep: 432.29 | bwd_inner_microstep: 432.28 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 23:57:58,482] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 290.35 | bwd_microstep: 397.70 | bwd_inner_microstep: 397.68 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 23:57:59,182] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 299.03 | bwd_microstep: 385.74 | bwd_inner_microstep: 385.72 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 319 +[2025-05-01 23:57:59,395] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 85.43 | bwd_microstep: 113.47 | bwd_inner_microstep: 113.45 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.20 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 829 +[2025-05-01 23:57:59,748] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 97.66 | bwd_microstep: 238.42 | bwd_inner_microstep: 238.21 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 23:58:00,575] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 3.09 | optimizer_step: 16.93 +[2025-05-01 23:58:00,576] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 295.46 | bwd_microstep: 484.02 | bwd_inner_microstep: 394.35 | bwd_allreduce_microstep: 89.66 | step_microstep: 27.34 +[2025-05-01 23:58:00,577] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4307.82 | bwd: 6536.82 | bwd_inner: 6446.73 | bwd_allreduce: 89.79 | step: 50.04 + 7%|▋ | 634/8720 [1:42:34<27:49:42, 12.39s/it] {'loss': 0.9042, 'grad_norm': 6.746903896331787, 'learning_rate': 9.952346017437642e-06, 'epoch': 0.73} + 7%|▋ | 634/8720 [1:42:34<27:49:42, 12.39s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1986 +[2025-05-01 23:58:01,348] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 281.71 | bwd_microstep: 447.00 | bwd_inner_microstep: 446.99 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-01 23:58:02,053] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 302.64 | bwd_microstep: 386.20 | bwd_inner_microstep: 386.18 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 849 +[2025-05-01 23:58:02,407] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 166.11 | bwd_microstep: 166.80 | bwd_inner_microstep: 166.59 | bwd_allreduce_microstep: 0.09 | step_microstep: 0.09 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 845 +[2025-05-01 23:58:02,785] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.07 | bwd_microstep: 165.98 | bwd_inner_microstep: 165.96 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-01 23:58:03,433] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 272.63 | bwd_microstep: 345.44 | bwd_inner_microstep: 345.43 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-01 23:58:03,963] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.59 | bwd_microstep: 325.73 | bwd_inner_microstep: 325.71 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-01 23:58:04,619] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 343.11 | bwd_microstep: 284.02 | bwd_inner_microstep: 284.00 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1349 +[2025-05-01 23:58:04,983] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.73 | bwd_microstep: 206.39 | bwd_inner_microstep: 206.37 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-01 23:58:05,690] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 337.29 | bwd_microstep: 343.49 | bwd_inner_microstep: 343.47 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-01 23:58:06,280] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 232.50 | bwd_microstep: 343.17 | bwd_inner_microstep: 343.15 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 834 +[2025-05-01 23:58:06,511] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 90.93 | bwd_microstep: 126.04 | bwd_inner_microstep: 126.02 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 6, images per sample: 6.0, dynamic token length: 1607 +[2025-05-01 23:58:07,063] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 163.88 | bwd_microstep: 373.27 | bwd_inner_microstep: 373.25 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-01 23:58:07,544] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.15 | bwd_microstep: 273.17 | bwd_inner_microstep: 273.16 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 23:58:08,371] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 321.84 | bwd_microstep: 487.40 | bwd_inner_microstep: 487.38 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.50 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2053 +[2025-05-01 23:58:09,283] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 364.68 | bwd_microstep: 518.41 | bwd_inner_microstep: 518.40 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1973 +[2025-05-01 23:58:10,455] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.20 | optimizer_step: 15.89 +[2025-05-01 23:58:10,456] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 345.81 | bwd_microstep: 775.30 | bwd_inner_microstep: 557.42 | bwd_allreduce_microstep: 217.83 | step_microstep: 23.84 +[2025-05-01 23:58:10,457] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 3937.50 | bwd: 5567.84 | bwd_inner: 5349.52 | bwd_allreduce: 217.98 | step: 29.64 + 7%|▋ | 635/8720 [1:42:44<26:07:54, 11.64s/it] {'loss': 1.3197, 'grad_norm': 4.794038772583008, 'learning_rate': 9.952089879364133e-06, 'epoch': 0.73} + 7%|▋ | 635/8720 [1:42:44<26:07:54, 11.64s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1955 +[2025-05-01 23:58:11,397] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 403.89 | bwd_microstep: 514.56 | bwd_inner_microstep: 514.55 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.81 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-01 23:58:12,285] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 352.15 | bwd_microstep: 519.29 | bwd_inner_microstep: 519.28 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-01 23:58:13,152] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 327.93 | bwd_microstep: 520.31 | bwd_inner_microstep: 520.29 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-01 23:58:13,973] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 316.19 | bwd_microstep: 476.03 | bwd_inner_microstep: 476.01 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.28 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 835 +[2025-05-01 23:58:14,401] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 125.25 | bwd_microstep: 281.00 | bwd_inner_microstep: 280.98 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:58:15,173] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 296.27 | bwd_microstep: 453.54 | bwd_inner_microstep: 453.53 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.32 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-01 23:58:15,944] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 296.43 | bwd_microstep: 443.43 | bwd_inner_microstep: 443.41 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 23:58:16,698] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 273.93 | bwd_microstep: 464.12 | bwd_inner_microstep: 464.10 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-01 23:58:17,452] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 291.75 | bwd_microstep: 445.44 | bwd_inner_microstep: 445.42 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 23:58:18,206] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 302.62 | bwd_microstep: 435.83 | bwd_inner_microstep: 435.81 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1353 +[2025-05-01 23:58:18,793] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 233.92 | bwd_microstep: 338.66 | bwd_inner_microstep: 338.65 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:58:19,543] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 348.23 | bwd_microstep: 386.88 | bwd_inner_microstep: 386.86 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 23:58:20,333] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 301.91 | bwd_microstep: 471.16 | bwd_inner_microstep: 471.15 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.98 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 23:58:21,115] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 295.22 | bwd_microstep: 459.21 | bwd_inner_microstep: 459.19 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1849 +[2025-05-01 23:58:21,829] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 266.71 | bwd_microstep: 426.35 | bwd_inner_microstep: 426.33 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 899 +[2025-05-01 23:58:22,302] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.19 | optimizer_step: 15.87 +[2025-05-01 23:58:22,303] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 127.27 | bwd_microstep: 306.63 | bwd_inner_microstep: 230.13 | bwd_allreduce_microstep: 76.35 | step_microstep: 23.56 +[2025-05-01 23:58:22,305] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4559.56 | bwd: 6942.47 | bwd_inner: 6865.75 | bwd_allreduce: 76.40 | step: 39.45 + 7%|▋ | 636/8720 [1:42:56<26:16:18, 11.70s/it] {'loss': 1.3913, 'grad_norm': 8.912388801574707, 'learning_rate': 9.951833058082696e-06, 'epoch': 0.73} + 7%|▋ | 636/8720 [1:42:56<26:16:18, 11.70s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 383 +[2025-05-01 23:58:22,540] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 83.04 | bwd_microstep: 131.62 | bwd_inner_microstep: 131.47 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1124 +[2025-05-01 23:58:23,046] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 180.13 | bwd_microstep: 309.11 | bwd_inner_microstep: 308.99 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1890 +[2025-05-01 23:58:23,761] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 306.15 | bwd_microstep: 389.81 | bwd_inner_microstep: 389.79 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-01 23:58:24,467] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 300.55 | bwd_microstep: 387.67 | bwd_inner_microstep: 387.65 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-01 23:58:25,205] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 295.48 | bwd_microstep: 425.63 | bwd_inner_microstep: 425.61 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-01 23:58:25,846] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 270.44 | bwd_microstep: 344.30 | bwd_inner_microstep: 344.28 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-01 23:58:26,536] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.05 | bwd_microstep: 485.61 | bwd_inner_microstep: 485.59 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-01 23:58:27,130] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 301.36 | bwd_microstep: 275.43 | bwd_inner_microstep: 275.41 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 328 +[2025-05-01 23:58:27,362] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.13 | bwd_microstep: 121.63 | bwd_inner_microstep: 121.61 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-01 23:58:28,097] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 241.07 | bwd_microstep: 461.38 | bwd_inner_microstep: 461.36 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-01 23:58:28,808] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 198.15 | bwd_microstep: 489.63 | bwd_inner_microstep: 489.61 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.00 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1092 +[2025-05-01 23:58:29,229] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 114.89 | bwd_microstep: 287.03 | bwd_inner_microstep: 287.01 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.32 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 23:58:29,988] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 238.63 | bwd_microstep: 491.11 | bwd_inner_microstep: 491.09 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 23:58:30,677] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 231.12 | bwd_microstep: 442.30 | bwd_inner_microstep: 442.28 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 23:58:31,464] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 375.98 | bwd_microstep: 394.01 | bwd_inner_microstep: 393.99 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.31 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 848 +[2025-05-01 23:58:31,890] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 4.19 | optimizer_step: 20.67 +[2025-05-01 23:58:31,892] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 168.74 | bwd_microstep: 200.33 | bwd_inner_microstep: 133.40 | bwd_allreduce_microstep: 66.78 | step_microstep: 31.27 +[2025-05-01 23:58:31,893] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 3589.71 | bwd: 5636.63 | bwd_inner: 5569.24 | bwd_allreduce: 66.97 | step: 42.26 + 7%|▋ | 637/8720 [1:43:05<24:50:51, 11.07s/it] {'loss': 1.2342, 'grad_norm': 4.807147026062012, 'learning_rate': 9.951575553628762e-06, 'epoch': 0.73} + 7%|▋ | 637/8720 [1:43:05<24:50:51, 11.07s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 348 +[2025-05-01 23:58:32,174] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 102.41 | bwd_microstep: 137.86 | bwd_inner_microstep: 137.85 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.31 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-01 23:58:32,872] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 194.88 | bwd_microstep: 485.23 | bwd_inner_microstep: 485.21 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 852 +[2025-05-01 23:58:33,113] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.73 | bwd_microstep: 133.10 | bwd_inner_microstep: 132.83 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-01 23:58:33,909] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 385.52 | bwd_microstep: 391.97 | bwd_inner_microstep: 391.95 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.31 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-01 23:58:34,684] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 261.41 | bwd_microstep: 483.71 | bwd_inner_microstep: 483.69 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 23:58:35,373] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 266.48 | bwd_microstep: 406.32 | bwd_inner_microstep: 406.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 23:58:36,073] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.58 | bwd_microstep: 492.01 | bwd_inner_microstep: 491.99 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 326 +[2025-05-01 23:58:36,307] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 92.05 | bwd_microstep: 123.53 | bwd_inner_microstep: 123.23 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 23:58:37,137] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 361.25 | bwd_microstep: 434.96 | bwd_inner_microstep: 434.94 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 23:58:37,832] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 312.14 | bwd_microstep: 364.32 | bwd_inner_microstep: 364.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 23:58:38,530] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 366.42 | bwd_microstep: 313.58 | bwd_inner_microstep: 313.56 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 23:58:39,342] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 356.63 | bwd_microstep: 437.76 | bwd_inner_microstep: 437.69 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.22 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 23:58:40,120] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 304.84 | bwd_microstep: 447.60 | bwd_inner_microstep: 447.59 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.30 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 23:58:40,890] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 308.40 | bwd_microstep: 440.78 | bwd_inner_microstep: 440.76 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.57 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 23:58:41,654] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 301.78 | bwd_microstep: 445.03 | bwd_inner_microstep: 445.01 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.58 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 23:58:42,675] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.22 | optimizer_step: 16.73 +[2025-05-01 23:58:42,676] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 303.95 | bwd_microstep: 672.69 | bwd_inner_microstep: 351.85 | bwd_allreduce_microstep: 320.83 | step_microstep: 26.03 +[2025-05-01 23:58:42,677] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4201.11 | bwd: 6210.52 | bwd_inner: 5888.90 | bwd_allreduce: 321.10 | step: 35.12 + 7%|▋ | 638/8720 [1:43:16<24:39:14, 10.98s/it] {'loss': 0.8165, 'grad_norm': 5.920230388641357, 'learning_rate': 9.95131736603786e-06, 'epoch': 0.73} + 7%|▋ | 638/8720 [1:43:16<24:39:14, 10.98s/it]dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1403 +[2025-05-01 23:58:43,324] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 231.79 | bwd_microstep: 376.29 | bwd_inner_microstep: 376.27 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 355 +[2025-05-01 23:58:43,579] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 90.77 | bwd_microstep: 134.21 | bwd_inner_microstep: 134.20 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.25 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1890 +[2025-05-01 23:58:44,451] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 327.44 | bwd_microstep: 525.03 | bwd_inner_microstep: 525.02 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 858 +[2025-05-01 23:58:44,898] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 123.89 | bwd_microstep: 294.34 | bwd_inner_microstep: 294.32 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.33 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-01 23:58:45,767] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 327.21 | bwd_microstep: 518.44 | bwd_inner_microstep: 518.42 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 845 +[2025-05-01 23:58:46,217] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 120.87 | bwd_microstep: 296.81 | bwd_inner_microstep: 296.79 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-01 23:58:47,064] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 326.36 | bwd_microstep: 497.61 | bwd_inner_microstep: 497.59 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.50 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 334 +[2025-05-01 23:58:47,306] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 82.27 | bwd_microstep: 127.39 | bwd_inner_microstep: 127.37 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1098 +[2025-05-01 23:58:47,783] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 232.46 | bwd_microstep: 217.45 | bwd_inner_microstep: 217.29 | bwd_allreduce_microstep: 0.10 | step_microstep: 0.09 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 850 +[2025-05-01 23:58:48,247] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 223.74 | bwd_microstep: 213.92 | bwd_inner_microstep: 213.90 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.51 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-01 23:58:49,091] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 329.75 | bwd_microstep: 484.82 | bwd_inner_microstep: 484.80 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1353 +[2025-05-01 23:58:49,771] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 310.13 | bwd_microstep: 342.62 | bwd_inner_microstep: 342.60 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 837 +[2025-05-01 23:58:50,196] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 137.75 | bwd_microstep: 254.77 | bwd_inner_microstep: 254.73 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 23:58:50,973] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 307.44 | bwd_microstep: 439.65 | bwd_inner_microstep: 439.63 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.17 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 23:58:51,741] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 310.74 | bwd_microstep: 440.13 | bwd_inner_microstep: 440.11 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 23:58:52,699] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.25 | optimizer_step: 16.54 +[2025-05-01 23:58:52,699] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 309.70 | bwd_microstep: 607.57 | bwd_inner_microstep: 444.05 | bwd_allreduce_microstep: 163.50 | step_microstep: 24.01 +[2025-05-01 23:58:52,700] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 3792.32 | bwd: 5771.06 | bwd_inner: 5607.11 | bwd_allreduce: 163.64 | step: 48.51 + 7%|▋ | 639/8720 [1:43:26<24:00:13, 10.69s/it] {'loss': 1.2223, 'grad_norm': 5.284739971160889, 'learning_rate': 9.951058495345608e-06, 'epoch': 0.73} + 7%|▋ | 639/8720 [1:43:26<24:00:13, 10.69s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 429 +[2025-05-01 23:58:52,935] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 96.64 | bwd_microstep: 117.43 | bwd_inner_microstep: 117.41 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.33 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 911 +[2025-05-01 23:58:53,357] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 163.33 | bwd_microstep: 238.14 | bwd_inner_microstep: 238.12 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.27 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1928 +[2025-05-01 23:58:54,214] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 314.42 | bwd_microstep: 522.84 | bwd_inner_microstep: 522.82 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1910 +[2025-05-01 23:58:55,039] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 321.27 | bwd_microstep: 479.19 | bwd_inner_microstep: 479.17 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-01 23:58:55,929] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 328.06 | bwd_microstep: 532.93 | bwd_inner_microstep: 532.91 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.79 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1364 +[2025-05-01 23:58:56,548] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 235.75 | bwd_microstep: 365.63 | bwd_inner_microstep: 365.61 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1359 +[2025-05-01 23:58:57,149] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 228.22 | bwd_microstep: 342.43 | bwd_inner_microstep: 342.23 | bwd_allreduce_microstep: 0.18 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-01 23:58:58,012] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 349.07 | bwd_microstep: 488.59 | bwd_inner_microstep: 488.57 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 852 +[2025-05-01 23:58:58,381] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 138.91 | bwd_microstep: 212.87 | bwd_inner_microstep: 212.85 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 843 +[2025-05-01 23:58:58,782] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 191.93 | bwd_microstep: 180.54 | bwd_inner_microstep: 180.52 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.32 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:58:59,607] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 308.44 | bwd_microstep: 487.15 | bwd_inner_microstep: 487.14 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 23:59:00,467] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 379.72 | bwd_microstep: 462.58 | bwd_inner_microstep: 462.56 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 23:59:01,240] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 276.22 | bwd_microstep: 465.47 | bwd_inner_microstep: 465.45 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 23:59:02,058] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 306.14 | bwd_microstep: 485.36 | bwd_inner_microstep: 485.33 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-01 23:59:02,917] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 376.23 | bwd_microstep: 465.44 | bwd_inner_microstep: 465.42 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-01 23:59:03,944] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.29 | optimizer_step: 17.21 +[2025-05-01 23:59:03,944] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 278.41 | bwd_microstep: 694.95 | bwd_inner_microstep: 464.51 | bwd_allreduce_microstep: 230.39 | step_microstep: 24.88 +[2025-05-01 23:59:03,946] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4292.68 | bwd: 6541.54 | bwd_inner: 6310.63 | bwd_allreduce: 230.65 | step: 47.18 + 7%|▋ | 640/8720 [1:43:37<24:22:21, 10.86s/it] {'loss': 0.7997, 'grad_norm': 2.5272390842437744, 'learning_rate': 9.950798941587722e-06, 'epoch': 0.73} + 7%|▋ | 640/8720 [1:43:37<24:22:21, 10.86s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 527 +[2025-05-01 23:59:04,263] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 122.59 | bwd_microstep: 173.95 | bwd_inner_microstep: 173.93 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1234 +[2025-05-01 23:59:04,805] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 132.12 | bwd_microstep: 380.06 | bwd_inner_microstep: 379.25 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.24 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1929 +[2025-05-01 23:59:05,606] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 288.58 | bwd_microstep: 494.36 | bwd_inner_microstep: 494.34 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.28 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1900 +[2025-05-01 23:59:06,402] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 276.20 | bwd_microstep: 487.23 | bwd_inner_microstep: 487.21 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1883 +[2025-05-01 23:59:07,298] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 389.23 | bwd_microstep: 489.09 | bwd_inner_microstep: 489.07 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 345 +[2025-05-01 23:59:07,522] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 78.60 | bwd_microstep: 130.03 | bwd_inner_microstep: 130.01 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-01 23:59:08,325] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 288.48 | bwd_microstep: 485.21 | bwd_inner_microstep: 485.19 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-01 23:59:09,208] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 393.39 | bwd_microstep: 469.51 | bwd_inner_microstep: 469.49 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:59:09,977] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 274.36 | bwd_microstep: 471.26 | bwd_inner_microstep: 471.24 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 840 +[2025-05-01 23:59:10,359] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 203.79 | bwd_microstep: 152.71 | bwd_inner_microstep: 152.70 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:59:11,211] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 337.39 | bwd_microstep: 484.45 | bwd_inner_microstep: 484.43 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:59:12,034] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 340.38 | bwd_microstep: 462.94 | bwd_inner_microstep: 462.92 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 322 +[2025-05-01 23:59:12,289] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 86.20 | bwd_microstep: 136.44 | bwd_inner_microstep: 136.42 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.51 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-01 23:59:13,141] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 336.96 | bwd_microstep: 485.99 | bwd_inner_microstep: 485.97 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 316 +[2025-05-01 23:59:13,361] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 82.52 | bwd_microstep: 121.12 | bwd_inner_microstep: 120.91 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 23:59:14,468] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.25 | optimizer_step: 16.60 +[2025-05-01 23:59:14,468] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 277.31 | bwd_microstep: 773.79 | bwd_inner_microstep: 486.34 | bwd_allreduce_microstep: 287.40 | step_microstep: 24.15 +[2025-05-01 23:59:14,470] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 3907.97 | bwd: 6198.15 | bwd_inner: 5909.44 | bwd_allreduce: 288.28 | step: 45.80 + 7%|▋ | 641/8720 [1:43:48<24:08:36, 10.76s/it] {'loss': 1.0542, 'grad_norm': 3.8752315044403076, 'learning_rate': 9.95053870480001e-06, 'epoch': 0.74} + 7%|▋ | 641/8720 [1:43:48<24:08:36, 10.76s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 384 +[2025-05-01 23:59:14,729] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 100.62 | bwd_microstep: 136.27 | bwd_inner_microstep: 136.25 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.33 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 345 +[2025-05-01 23:59:14,972] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 86.03 | bwd_microstep: 127.30 | bwd_inner_microstep: 127.28 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.47 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-01 23:59:15,831] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 342.33 | bwd_microstep: 485.09 | bwd_inner_microstep: 485.08 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-01 23:59:16,656] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 340.76 | bwd_microstep: 466.73 | bwd_inner_microstep: 466.72 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.31 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-01 23:59:17,474] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 276.64 | bwd_microstep: 507.89 | bwd_inner_microstep: 507.87 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-01 23:59:18,322] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 319.06 | bwd_microstep: 499.62 | bwd_inner_microstep: 499.61 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.46 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-01 23:59:19,172] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 315.77 | bwd_microstep: 500.50 | bwd_inner_microstep: 500.48 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.21 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 844 +[2025-05-01 23:59:19,605] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 205.93 | bwd_microstep: 199.21 | bwd_inner_microstep: 199.20 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 336 +[2025-05-01 23:59:19,852] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 106.07 | bwd_microstep: 113.40 | bwd_inner_microstep: 113.20 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-01 23:59:20,712] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 343.68 | bwd_microstep: 498.26 | bwd_inner_microstep: 498.25 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 23:59:21,530] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 297.22 | bwd_microstep: 501.74 | bwd_inner_microstep: 501.72 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 23:59:22,363] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 303.12 | bwd_microstep: 495.77 | bwd_inner_microstep: 495.75 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.38 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 23:59:23,185] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 309.72 | bwd_microstep: 480.71 | bwd_inner_microstep: 480.69 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-01 23:59:24,018] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 300.64 | bwd_microstep: 500.39 | bwd_inner_microstep: 500.37 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-01 23:59:24,843] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 310.36 | bwd_microstep: 482.10 | bwd_inner_microstep: 482.08 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.52 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2068 +[2025-05-01 23:59:25,915] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.21 | optimizer_step: 16.71 +[2025-05-01 23:59:25,917] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 340.36 | bwd_microstep: 675.21 | bwd_inner_microstep: 563.05 | bwd_allreduce_microstep: 112.15 | step_microstep: 28.43 +[2025-05-01 23:59:25,918] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4298.26 | bwd: 6670.20 | bwd_inner: 6557.66 | bwd_allreduce: 112.08 | step: 55.18 + 7%|▋ | 642/8720 [1:43:59<24:36:26, 10.97s/it] {'loss': 0.9902, 'grad_norm': 4.342890739440918, 'learning_rate': 9.950277785018376e-06, 'epoch': 0.74} + 7%|▋ | 642/8720 [1:43:59<24:36:26, 10.97s/it]dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1422 +[2025-05-01 23:59:26,585] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 243.19 | bwd_microstep: 395.61 | bwd_inner_microstep: 395.59 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1889 +[2025-05-01 23:59:27,414] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 373.47 | bwd_microstep: 438.15 | bwd_inner_microstep: 438.13 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-01 23:59:28,269] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 391.82 | bwd_microstep: 444.62 | bwd_inner_microstep: 444.60 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-01 23:59:29,125] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 372.91 | bwd_microstep: 464.87 | bwd_inner_microstep: 464.85 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-01 23:59:30,002] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 384.55 | bwd_microstep: 476.76 | bwd_inner_microstep: 476.74 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-01 23:59:30,871] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 354.68 | bwd_microstep: 495.90 | bwd_inner_microstep: 495.88 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.95 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-01 23:59:31,709] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 314.17 | bwd_microstep: 504.98 | bwd_inner_microstep: 504.96 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-01 23:59:32,545] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 311.68 | bwd_microstep: 501.57 | bwd_inner_microstep: 501.55 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.51 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 843 +[2025-05-01 23:59:32,962] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 109.86 | bwd_microstep: 279.15 | bwd_inner_microstep: 278.62 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.24 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1109 +[2025-05-01 23:59:33,446] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 165.60 | bwd_microstep: 302.14 | bwd_inner_microstep: 302.12 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-01 23:59:34,296] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 375.14 | bwd_microstep: 459.22 | bwd_inner_microstep: 459.20 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-01 23:59:35,082] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 323.28 | bwd_microstep: 443.10 | bwd_inner_microstep: 443.08 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-01 23:59:35,895] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 306.57 | bwd_microstep: 481.49 | bwd_inner_microstep: 481.47 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.66 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 23:59:36,645] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 312.39 | bwd_microstep: 421.14 | bwd_inner_microstep: 421.12 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-01 23:59:37,457] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 320.14 | bwd_microstep: 469.90 | bwd_inner_microstep: 469.89 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.31 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 23:59:38,413] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 2.34 | optimizer_gradients: 2.20 | optimizer_step: 16.75 +[2025-05-01 23:59:38,416] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 306.86 | bwd_microstep: 593.00 | bwd_inner_microstep: 457.96 | bwd_allreduce_microstep: 135.02 | step_microstep: 28.54 +[2025-05-01 23:59:38,417] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4966.11 | bwd: 7171.60 | bwd_inner: 7035.78 | bwd_allreduce: 135.09 | step: 40.38 + 7%|▋ | 643/8720 [1:44:12<25:38:01, 11.43s/it] {'loss': 0.9768, 'grad_norm': 5.625659465789795, 'learning_rate': 9.950016182278817e-06, 'epoch': 0.74} + 7%|▋ | 643/8720 [1:44:12<25:38:01, 11.43s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 371 +[2025-05-01 23:59:38,635] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 71.19 | bwd_microstep: 124.91 | bwd_inner_microstep: 124.89 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.49 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1904 +[2025-05-01 23:59:39,433] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 305.88 | bwd_microstep: 461.98 | bwd_inner_microstep: 461.97 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1893 +[2025-05-01 23:59:40,231] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 321.69 | bwd_microstep: 458.50 | bwd_inner_microstep: 458.48 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.52 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-01 23:59:41,070] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 301.72 | bwd_microstep: 506.79 | bwd_inner_microstep: 506.77 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-01 23:59:41,900] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 300.57 | bwd_microstep: 497.25 | bwd_inner_microstep: 497.23 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-01 23:59:42,766] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 327.05 | bwd_microstep: 506.89 | bwd_inner_microstep: 506.87 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.45 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-01 23:59:43,639] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 334.59 | bwd_microstep: 506.59 | bwd_inner_microstep: 506.57 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-01 23:59:44,508] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 332.69 | bwd_microstep: 506.13 | bwd_inner_microstep: 506.11 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.23 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 23:59:45,384] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 336.41 | bwd_microstep: 507.04 | bwd_inner_microstep: 507.02 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 23:59:46,257] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 336.65 | bwd_microstep: 511.11 | bwd_inner_microstep: 511.09 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-01 23:59:47,124] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 310.76 | bwd_microstep: 526.29 | bwd_inner_microstep: 526.28 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.50 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-01 23:59:48,003] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 335.64 | bwd_microstep: 514.33 | bwd_inner_microstep: 514.31 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-01 23:59:48,884] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 335.57 | bwd_microstep: 516.53 | bwd_inner_microstep: 516.51 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-01 23:59:49,739] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 337.60 | bwd_microstep: 491.07 | bwd_inner_microstep: 491.06 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-01 23:59:50,574] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 305.13 | bwd_microstep: 492.90 | bwd_inner_microstep: 492.88 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2628 +[2025-05-01 23:59:51,926] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.20 | optimizer_step: 23.19 +[2025-05-01 23:59:51,927] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 395.54 | bwd_microstep: 896.78 | bwd_inner_microstep: 642.01 | bwd_allreduce_microstep: 254.76 | step_microstep: 31.03 +[2025-05-01 23:59:51,928] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4988.65 | bwd: 8025.09 | bwd_inner: 7770.07 | bwd_allreduce: 254.82 | step: 53.47 + 7%|▋ | 644/8720 [1:44:25<27:02:02, 12.05s/it] {'loss': 1.2085, 'grad_norm': 6.035943031311035, 'learning_rate': 9.949753896617425e-06, 'epoch': 0.74} + 7%|▋ | 644/8720 [1:44:25<27:02:02, 12.05s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1962 +[2025-05-01 23:59:52,851] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 373.52 | bwd_microstep: 526.15 | bwd_inner_microstep: 526.14 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.90 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1889 +[2025-05-01 23:59:53,692] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 311.25 | bwd_microstep: 505.39 | bwd_inner_microstep: 505.37 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-01 23:59:54,516] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 302.62 | bwd_microstep: 490.02 | bwd_inner_microstep: 490.00 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-01 23:59:55,357] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 308.91 | bwd_microstep: 497.53 | bwd_inner_microstep: 497.51 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-01 23:59:56,198] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 311.71 | bwd_microstep: 496.32 | bwd_inner_microstep: 496.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.62 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-01 23:59:57,044] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 316.53 | bwd_microstep: 500.40 | bwd_inner_microstep: 500.38 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.30 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-01 23:59:57,902] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 340.00 | bwd_microstep: 486.75 | bwd_inner_microstep: 486.73 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1355 +[2025-05-01 23:59:58,560] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 291.69 | bwd_microstep: 348.46 | bwd_inner_microstep: 348.44 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-01 23:59:59,400] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 316.19 | bwd_microstep: 490.11 | bwd_inner_microstep: 490.09 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.28 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 00:00:00,229] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 303.29 | bwd_microstep: 494.89 | bwd_inner_microstep: 494.87 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.87 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 329 +[2025-05-02 00:00:00,451] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 83.51 | bwd_microstep: 121.47 | bwd_inner_microstep: 120.47 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.28 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 325 +[2025-05-02 00:00:00,701] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 96.78 | bwd_microstep: 119.63 | bwd_inner_microstep: 119.61 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.32 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 00:00:01,535] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 321.96 | bwd_microstep: 481.84 | bwd_inner_microstep: 481.82 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.22 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 00:00:02,370] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 315.75 | bwd_microstep: 486.75 | bwd_inner_microstep: 486.73 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 00:00:03,158] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 308.64 | bwd_microstep: 456.93 | bwd_inner_microstep: 456.89 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.20 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 827 +[2025-05-02 00:00:03,817] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.15 | optimizer_step: 19.76 +[2025-05-02 00:00:03,819] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 144.17 | bwd_microstep: 472.86 | bwd_inner_microstep: 209.69 | bwd_allreduce_microstep: 263.04 | step_microstep: 27.50 +[2025-05-02 00:00:03,820] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4446.40 | bwd: 6975.56 | bwd_inner: 6711.09 | bwd_allreduce: 263.11 | step: 53.38 + 7%|▋ | 645/8720 [1:44:37<26:55:34, 12.00s/it] {'loss': 1.1552, 'grad_norm': 5.616715908050537, 'learning_rate': 9.949490928070386e-06, 'epoch': 0.74} + 7%|▋ | 645/8720 [1:44:37<26:55:34, 12.00s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1935 +[2025-05-02 00:00:04,708] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 326.10 | bwd_microstep: 521.46 | bwd_inner_microstep: 521.44 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.22 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1930 +[2025-05-02 00:00:05,600] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 327.82 | bwd_microstep: 536.50 | bwd_inner_microstep: 536.48 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1919 +[2025-05-02 00:00:06,353] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 265.17 | bwd_microstep: 466.50 | bwd_inner_microstep: 466.48 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 889 +[2025-05-02 00:00:06,746] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 126.64 | bwd_microstep: 236.78 | bwd_inner_microstep: 236.76 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.51 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1904 +[2025-05-02 00:00:07,492] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 265.66 | bwd_microstep: 445.42 | bwd_inner_microstep: 445.40 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1387 +[2025-05-02 00:00:08,095] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 204.96 | bwd_microstep: 369.01 | bwd_inner_microstep: 368.99 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-02 00:00:08,882] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 319.59 | bwd_microstep: 451.83 | bwd_inner_microstep: 451.81 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.65 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-02 00:00:09,526] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 192.44 | bwd_microstep: 433.58 | bwd_inner_microstep: 433.57 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-02 00:00:10,293] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 290.89 | bwd_microstep: 456.91 | bwd_inner_microstep: 456.89 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.33 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 00:00:11,036] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 257.27 | bwd_microstep: 454.30 | bwd_inner_microstep: 454.28 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 317 +[2025-05-02 00:00:11,279] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 87.45 | bwd_microstep: 125.51 | bwd_inner_microstep: 125.28 | bwd_allreduce_microstep: 0.08 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 00:00:12,051] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 309.26 | bwd_microstep: 445.12 | bwd_inner_microstep: 445.10 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 00:00:12,702] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.53 | bwd_microstep: 434.25 | bwd_inner_microstep: 434.24 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 00:00:13,501] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 347.87 | bwd_microstep: 433.78 | bwd_inner_microstep: 433.76 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 00:00:14,294] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 335.94 | bwd_microstep: 440.14 | bwd_inner_microstep: 440.12 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.88 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1936 +[2025-05-02 00:00:15,535] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.28 | optimizer_step: 25.18 +[2025-05-02 00:00:15,536] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 359.21 | bwd_microstep: 832.67 | bwd_inner_microstep: 542.07 | bwd_allreduce_microstep: 290.55 | step_microstep: 32.93 +[2025-05-02 00:00:15,537] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4211.69 | bwd: 7083.81 | bwd_inner: 6792.75 | bwd_allreduce: 290.71 | step: 51.60 + 7%|▋ | 646/8720 [1:44:49<26:43:39, 11.92s/it] {'loss': 1.1389, 'grad_norm': 4.992251396179199, 'learning_rate': 9.949227276673978e-06, 'epoch': 0.74} + 7%|▋ | 646/8720 [1:44:49<26:43:39, 11.92s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1954 +[2025-05-02 00:00:16,472] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 398.58 | bwd_microstep: 511.69 | bwd_inner_microstep: 511.67 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.21 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1883 +[2025-05-02 00:00:17,383] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 384.93 | bwd_microstep: 506.10 | bwd_inner_microstep: 506.09 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1900 +[2025-05-02 00:00:18,277] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 355.51 | bwd_microstep: 519.75 | bwd_inner_microstep: 519.74 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1887 +[2025-05-02 00:00:19,097] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 323.71 | bwd_microstep: 479.04 | bwd_inner_microstep: 479.03 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-02 00:00:19,952] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 326.22 | bwd_microstep: 507.67 | bwd_inner_microstep: 507.65 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 345 +[2025-05-02 00:00:20,230] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 100.00 | bwd_microstep: 146.22 | bwd_inner_microstep: 146.20 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.53 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 00:00:21,047] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 304.53 | bwd_microstep: 493.04 | bwd_inner_microstep: 493.02 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.31 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 00:00:21,940] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 340.95 | bwd_microstep: 521.49 | bwd_inner_microstep: 521.47 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.85 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 00:00:22,830] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 355.54 | bwd_microstep: 515.70 | bwd_inner_microstep: 515.68 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 00:00:23,533] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 313.27 | bwd_microstep: 368.43 | bwd_inner_microstep: 368.41 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 00:00:24,361] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 333.99 | bwd_microstep: 477.74 | bwd_inner_microstep: 477.72 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 00:00:25,236] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 341.30 | bwd_microstep: 516.22 | bwd_inner_microstep: 516.20 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 00:00:26,097] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 345.60 | bwd_microstep: 495.50 | bwd_inner_microstep: 495.48 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 00:00:26,851] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 340.55 | bwd_microstep: 394.60 | bwd_inner_microstep: 394.58 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 00:00:27,635] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 243.51 | bwd_microstep: 523.36 | bwd_inner_microstep: 523.34 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 00:00:28,848] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.16 | optimizer_step: 19.09 +[2025-05-02 00:00:28,850] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 306.63 | bwd_microstep: 860.46 | bwd_inner_microstep: 511.86 | bwd_allreduce_microstep: 348.56 | step_microstep: 26.97 +[2025-05-02 00:00:28,851] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 5114.64 | bwd: 7837.03 | bwd_inner: 7488.16 | bwd_allreduce: 348.64 | step: 40.52 + 7%|▋ | 647/8720 [1:45:02<27:39:58, 12.34s/it] {'loss': 1.3836, 'grad_norm': 4.446049213409424, 'learning_rate': 9.94896294246458e-06, 'epoch': 0.74} + 7%|▋ | 647/8720 [1:45:02<27:39:58, 12.34s/it]dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1417 +[2025-05-02 00:00:29,529] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 234.23 | bwd_microstep: 406.79 | bwd_inner_microstep: 406.56 | bwd_allreduce_microstep: 0.14 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1901 +[2025-05-02 00:00:30,424] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 399.49 | bwd_microstep: 476.62 | bwd_inner_microstep: 476.60 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1887 +[2025-05-02 00:00:31,255] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 327.36 | bwd_microstep: 473.13 | bwd_inner_microstep: 473.11 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 855 +[2025-05-02 00:00:31,696] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 202.53 | bwd_microstep: 222.68 | bwd_inner_microstep: 222.40 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1887 +[2025-05-02 00:00:32,586] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 370.16 | bwd_microstep: 490.35 | bwd_inner_microstep: 490.33 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1365 +[2025-05-02 00:00:33,255] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 255.17 | bwd_microstep: 384.48 | bwd_inner_microstep: 384.46 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 00:00:34,144] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 334.63 | bwd_microstep: 523.94 | bwd_inner_microstep: 523.92 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.31 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1091 +[2025-05-02 00:00:34,685] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 167.77 | bwd_microstep: 344.08 | bwd_inner_microstep: 344.07 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 839 +[2025-05-02 00:00:35,114] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 142.53 | bwd_microstep: 270.78 | bwd_inner_microstep: 270.43 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.21 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 836 +[2025-05-02 00:00:35,538] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 124.95 | bwd_microstep: 280.03 | bwd_inner_microstep: 280.02 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 00:00:36,399] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 331.30 | bwd_microstep: 509.28 | bwd_inner_microstep: 509.26 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.87 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 00:00:37,293] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 355.89 | bwd_microstep: 517.98 | bwd_inner_microstep: 517.96 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 00:00:38,149] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 318.65 | bwd_microstep: 514.94 | bwd_inner_microstep: 514.92 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.32 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 315 +[2025-05-02 00:00:38,393] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 79.66 | bwd_microstep: 133.10 | bwd_inner_microstep: 133.08 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 00:00:39,223] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 353.04 | bwd_microstep: 446.87 | bwd_inner_microstep: 446.86 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1387 +[2025-05-02 00:00:40,234] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.08 | optimizer_gradients: 2.19 | optimizer_step: 16.53 +[2025-05-02 00:00:40,235] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 231.38 | bwd_microstep: 725.60 | bwd_inner_microstep: 424.05 | bwd_allreduce_microstep: 301.38 | step_microstep: 25.53 +[2025-05-02 00:00:40,237] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4228.69 | bwd: 6720.70 | bwd_inner: 6418.16 | bwd_allreduce: 301.66 | step: 48.08 + 7%|▋ | 648/8720 [1:45:13<27:01:20, 12.05s/it] {'loss': 1.1329, 'grad_norm': 4.534087657928467, 'learning_rate': 9.948697925478654e-06, 'epoch': 0.74} + 7%|▋ | 648/8720 [1:45:13<27:01:20, 12.05s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2084 +[2025-05-02 00:00:41,201] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 418.42 | bwd_microstep: 522.10 | bwd_inner_microstep: 522.09 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2005 +[2025-05-02 00:00:42,140] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 409.87 | bwd_microstep: 512.37 | bwd_inner_microstep: 512.32 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-02 00:00:43,057] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 404.49 | bwd_microstep: 496.87 | bwd_inner_microstep: 496.85 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1356 +[2025-05-02 00:00:43,705] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 248.86 | bwd_microstep: 380.51 | bwd_inner_microstep: 380.49 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 837 +[2025-05-02 00:00:44,140] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 200.50 | bwd_microstep: 205.33 | bwd_inner_microstep: 204.92 | bwd_allreduce_microstep: 0.18 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 00:00:45,013] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 329.48 | bwd_microstep: 509.94 | bwd_inner_microstep: 509.92 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.51 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 00:00:45,900] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 336.10 | bwd_microstep: 523.07 | bwd_inner_microstep: 523.06 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.48 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 328 +[2025-05-02 00:00:46,140] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 103.28 | bwd_microstep: 116.45 | bwd_inner_microstep: 116.15 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 00:00:46,944] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 300.38 | bwd_microstep: 486.44 | bwd_inner_microstep: 486.42 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 00:00:47,847] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 398.33 | bwd_microstep: 487.81 | bwd_inner_microstep: 487.79 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 00:00:48,753] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 388.58 | bwd_microstep: 498.62 | bwd_inner_microstep: 498.60 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 00:00:49,644] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 357.41 | bwd_microstep: 515.59 | bwd_inner_microstep: 515.57 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.59 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 00:00:50,461] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 280.73 | bwd_microstep: 516.68 | bwd_inner_microstep: 516.66 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 00:00:51,333] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 352.64 | bwd_microstep: 495.98 | bwd_inner_microstep: 495.97 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 00:00:52,238] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 381.93 | bwd_microstep: 503.03 | bwd_inner_microstep: 503.01 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 337 +[2025-05-02 00:00:52,789] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.12 | optimizer_step: 16.83 +[2025-05-02 00:00:52,790] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 82.11 | bwd_microstep: 430.54 | bwd_inner_microstep: 130.54 | bwd_allreduce_microstep: 299.98 | step_microstep: 26.32 +[2025-05-02 00:00:52,791] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4992.97 | bwd: 7201.35 | bwd_inner: 6900.66 | bwd_allreduce: 300.35 | step: 37.38 + 7%|▋ | 649/8720 [1:45:26<27:21:25, 12.20s/it] {'loss': 0.9299, 'grad_norm': 5.076428413391113, 'learning_rate': 9.948432225752768e-06, 'epoch': 0.74} + 7%|▋ | 649/8720 [1:45:26<27:21:25, 12.20s/it]dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 1010 +[2025-05-02 00:00:53,297] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.77 | bwd_microstep: 325.99 | bwd_inner_microstep: 325.97 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.20 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 898 +[2025-05-02 00:00:53,761] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 139.27 | bwd_microstep: 307.75 | bwd_inner_microstep: 307.73 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.77 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1377 +[2025-05-02 00:00:54,381] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 220.35 | bwd_microstep: 383.98 | bwd_inner_microstep: 383.97 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.54 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-02 00:00:55,251] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 332.14 | bwd_microstep: 518.51 | bwd_inner_microstep: 518.49 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.48 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-02 00:00:56,116] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 319.54 | bwd_microstep: 515.54 | bwd_inner_microstep: 515.52 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.32 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 00:00:56,984] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 316.26 | bwd_microstep: 519.09 | bwd_inner_microstep: 519.07 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 00:00:57,846] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 312.31 | bwd_microstep: 516.05 | bwd_inner_microstep: 516.03 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.32 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 00:00:58,664] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 299.17 | bwd_microstep: 486.41 | bwd_inner_microstep: 486.39 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.13 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 00:00:59,555] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 387.85 | bwd_microstep: 487.24 | bwd_inner_microstep: 487.23 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1354 +[2025-05-02 00:01:00,170] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 207.63 | bwd_microstep: 389.40 | bwd_inner_microstep: 389.25 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 00:01:01,068] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 388.90 | bwd_microstep: 494.02 | bwd_inner_microstep: 494.00 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 00:01:01,961] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 357.05 | bwd_microstep: 518.26 | bwd_inner_microstep: 518.24 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 00:01:02,807] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 319.44 | bwd_microstep: 508.04 | bwd_inner_microstep: 508.02 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 00:01:03,669] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 314.76 | bwd_microstep: 512.15 | bwd_inner_microstep: 512.13 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.51 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 00:01:04,472] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 313.19 | bwd_microstep: 455.99 | bwd_inner_microstep: 455.97 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1961 +[2025-05-02 00:01:05,730] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.20 | optimizer_step: 31.82 +[2025-05-02 00:01:05,731] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 374.71 | bwd_microstep: 813.34 | bwd_inner_microstep: 520.59 | bwd_allreduce_microstep: 292.74 | step_microstep: 41.30 +[2025-05-02 00:01:05,732] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4744.30 | bwd: 7752.51 | bwd_inner: 7458.61 | bwd_allreduce: 292.89 | step: 60.00 + 7%|▋ | 650/8720 [1:45:39<27:51:01, 12.42s/it] {'loss': 1.1559, 'grad_norm': 6.497921466827393, 'learning_rate': 9.948165843323578e-06, 'epoch': 0.75} + 7%|▋ | 650/8720 [1:45:39<27:51:01, 12.42s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1919 +[2025-05-02 00:01:06,620] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 331.10 | bwd_microstep: 516.27 | bwd_inner_microstep: 516.25 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1894 +[2025-05-02 00:01:07,501] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 337.59 | bwd_microstep: 516.80 | bwd_inner_microstep: 516.57 | bwd_allreduce_microstep: 0.21 | step_microstep: 0.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-02 00:01:08,384] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 330.58 | bwd_microstep: 521.36 | bwd_inner_microstep: 521.34 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1890 +[2025-05-02 00:01:09,269] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 339.37 | bwd_microstep: 517.60 | bwd_inner_microstep: 517.59 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 00:01:09,856] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 287.80 | bwd_microstep: 274.04 | bwd_inner_microstep: 274.02 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 00:01:10,560] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 393.96 | bwd_microstep: 291.57 | bwd_inner_microstep: 291.56 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-02 00:01:11,261] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 243.39 | bwd_microstep: 443.57 | bwd_inner_microstep: 443.56 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 327 +[2025-05-02 00:01:11,470] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 79.19 | bwd_microstep: 115.58 | bwd_inner_microstep: 115.45 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 00:01:12,173] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 329.46 | bwd_microstep: 356.93 | bwd_inner_microstep: 356.91 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 00:01:12,876] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.80 | bwd_microstep: 495.77 | bwd_inner_microstep: 495.76 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 320 +[2025-05-02 00:01:13,096] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 88.18 | bwd_microstep: 114.74 | bwd_inner_microstep: 114.42 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 00:01:13,797] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 273.39 | bwd_microstep: 410.61 | bwd_inner_microstep: 410.59 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.14 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 00:01:14,499] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.20 | bwd_microstep: 495.19 | bwd_inner_microstep: 495.17 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 00:01:15,091] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.32 | bwd_microstep: 380.61 | bwd_inner_microstep: 380.59 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.32 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 00:01:15,659] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 262.15 | bwd_microstep: 271.95 | bwd_inner_microstep: 271.93 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1979 +[2025-05-02 00:01:16,494] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.07 | optimizer_gradients: 2.33 | optimizer_step: 30.85 +[2025-05-02 00:01:16,495] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 417.14 | bwd_microstep: 362.53 | bwd_inner_microstep: 295.56 | bwd_allreduce_microstep: 66.92 | step_microstep: 38.95 +[2025-05-02 00:01:16,497] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4279.40 | bwd: 6085.34 | bwd_inner: 6017.36 | bwd_allreduce: 67.37 | step: 42.97 + 7%|▋ | 651/8720 [1:45:50<26:43:46, 11.93s/it] {'loss': 1.1129, 'grad_norm': 4.266901016235352, 'learning_rate': 9.947898778227832e-06, 'epoch': 0.75} + 7%|▋ | 651/8720 [1:45:50<26:43:46, 11.93s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 398 +[2025-05-02 00:01:16,782] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 111.69 | bwd_microstep: 151.91 | bwd_inner_microstep: 151.89 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.42 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1923 +[2025-05-02 00:01:17,382] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 233.27 | bwd_microstep: 335.35 | bwd_inner_microstep: 335.33 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1903 +[2025-05-02 00:01:18,016] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 325.38 | bwd_microstep: 276.67 | bwd_inner_microstep: 276.65 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 339 +[2025-05-02 00:01:18,239] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 81.71 | bwd_microstep: 125.30 | bwd_inner_microstep: 125.28 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.48 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 00:01:18,821] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 274.14 | bwd_microstep: 273.83 | bwd_inner_microstep: 273.81 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 00:01:19,523] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 399.13 | bwd_microstep: 286.53 | bwd_inner_microstep: 286.52 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 00:01:20,224] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 248.62 | bwd_microstep: 436.72 | bwd_inner_microstep: 436.71 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 835 +[2025-05-02 00:01:20,460] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 92.23 | bwd_microstep: 128.64 | bwd_inner_microstep: 128.60 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 00:01:21,159] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 356.87 | bwd_microstep: 327.28 | bwd_inner_microstep: 327.26 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 00:01:21,859] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 199.54 | bwd_microstep: 484.77 | bwd_inner_microstep: 484.75 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1349 +[2025-05-02 00:01:22,278] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.43 | bwd_microstep: 261.82 | bwd_inner_microstep: 261.80 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.33 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 00:01:22,898] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 319.01 | bwd_microstep: 273.03 | bwd_inner_microstep: 273.01 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 00:01:23,598] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 363.55 | bwd_microstep: 321.42 | bwd_inner_microstep: 321.40 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 00:01:24,298] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 207.24 | bwd_microstep: 476.21 | bwd_inner_microstep: 476.20 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 00:01:24,968] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.83 | bwd_microstep: 462.45 | bwd_inner_microstep: 462.43 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.32 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 00:01:25,902] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.26 | optimizer_step: 22.86 +[2025-05-02 00:01:25,904] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 196.58 | bwd_microstep: 680.59 | bwd_inner_microstep: 330.26 | bwd_allreduce_microstep: 350.32 | step_microstep: 32.55 +[2025-05-02 00:01:25,905] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 3738.00 | bwd: 5302.55 | bwd_inner: 4951.92 | bwd_allreduce: 350.40 | step: 45.08 + 7%|▋ | 652/8720 [1:45:59<25:02:07, 11.17s/it] {'loss': 0.8745, 'grad_norm': 6.93304443359375, 'learning_rate': 9.947631030502379e-06, 'epoch': 0.75} + 7%|▋ | 652/8720 [1:45:59<25:02:07, 11.17s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1991 +[2025-05-02 00:01:26,661] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 340.38 | bwd_microstep: 388.94 | bwd_inner_microstep: 388.92 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 898 +[2025-05-02 00:01:27,129] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 216.98 | bwd_microstep: 220.74 | bwd_inner_microstep: 220.72 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-02 00:01:27,989] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 336.79 | bwd_microstep: 492.41 | bwd_inner_microstep: 492.40 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.43 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1886 +[2025-05-02 00:01:28,839] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 317.15 | bwd_microstep: 501.59 | bwd_inner_microstep: 501.57 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.50 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-02 00:01:29,712] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 333.73 | bwd_microstep: 505.10 | bwd_inner_microstep: 505.08 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 00:01:30,581] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 335.31 | bwd_microstep: 500.51 | bwd_inner_microstep: 500.50 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.27 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 00:01:31,370] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 286.20 | bwd_microstep: 474.90 | bwd_inner_microstep: 474.88 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.92 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 00:01:32,062] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.66 | bwd_microstep: 485.39 | bwd_inner_microstep: 485.37 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 00:01:32,918] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 369.02 | bwd_microstep: 460.59 | bwd_inner_microstep: 460.57 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 00:01:33,801] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 371.03 | bwd_microstep: 484.41 | bwd_inner_microstep: 484.40 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 326 +[2025-05-02 00:01:34,027] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 82.04 | bwd_microstep: 126.07 | bwd_inner_microstep: 126.06 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1344 +[2025-05-02 00:01:34,659] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 210.53 | bwd_microstep: 389.82 | bwd_inner_microstep: 389.69 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 00:01:35,555] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 398.52 | bwd_microstep: 481.47 | bwd_inner_microstep: 481.45 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.14 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 830 +[2025-05-02 00:01:35,999] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 170.78 | bwd_microstep: 256.84 | bwd_inner_microstep: 256.55 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 00:01:36,895] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 375.84 | bwd_microstep: 499.58 | bwd_inner_microstep: 499.56 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 00:01:38,047] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.58 | optimizer_step: 18.30 +[2025-05-02 00:01:38,048] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 324.95 | bwd_microstep: 783.84 | bwd_inner_microstep: 511.19 | bwd_allreduce_microstep: 272.63 | step_microstep: 28.37 +[2025-05-02 00:01:38,050] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4657.81 | bwd: 7052.25 | bwd_inner: 6778.97 | bwd_allreduce: 272.89 | step: 46.64 + 7%|▋ | 653/8720 [1:46:11<25:41:13, 11.46s/it] {'loss': 0.7045, 'grad_norm': 4.707345962524414, 'learning_rate': 9.947362600184157e-06, 'epoch': 0.75} + 7%|▋ | 653/8720 [1:46:11<25:41:13, 11.46s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1930 +[2025-05-02 00:01:38,968] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 347.13 | bwd_microstep: 544.38 | bwd_inner_microstep: 544.36 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 882 +[2025-05-02 00:01:39,391] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 107.18 | bwd_microstep: 294.62 | bwd_inner_microstep: 294.60 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 345 +[2025-05-02 00:01:39,627] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 75.23 | bwd_microstep: 130.65 | bwd_inner_microstep: 130.63 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.33 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-02 00:01:40,518] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 335.34 | bwd_microstep: 523.97 | bwd_inner_microstep: 523.96 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.32 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 337 +[2025-05-02 00:01:40,745] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 71.43 | bwd_microstep: 132.06 | bwd_inner_microstep: 132.04 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1105 +[2025-05-02 00:01:41,301] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 212.34 | bwd_microstep: 316.00 | bwd_inner_microstep: 315.98 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.50 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1098 +[2025-05-02 00:01:41,785] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 183.13 | bwd_microstep: 270.90 | bwd_inner_microstep: 270.88 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.31 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-02 00:01:42,650] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 331.02 | bwd_microstep: 499.93 | bwd_inner_microstep: 499.91 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 00:01:43,506] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 324.94 | bwd_microstep: 501.70 | bwd_inner_microstep: 501.68 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 00:01:44,326] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 363.39 | bwd_microstep: 436.28 | bwd_inner_microstep: 436.26 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 00:01:45,199] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 315.38 | bwd_microstep: 522.78 | bwd_inner_microstep: 522.76 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 326 +[2025-05-02 00:01:45,421] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 74.29 | bwd_microstep: 126.70 | bwd_inner_microstep: 126.68 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.33 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 328 +[2025-05-02 00:01:45,673] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 85.34 | bwd_microstep: 137.32 | bwd_inner_microstep: 137.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 00:01:46,463] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 263.80 | bwd_microstep: 505.14 | bwd_inner_microstep: 505.12 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.28 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 322 +[2025-05-02 00:01:46,703] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.29 | bwd_microstep: 117.59 | bwd_inner_microstep: 117.57 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.33 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 00:01:47,635] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 5.99 | optimizer_step: 21.80 +[2025-05-02 00:01:47,635] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 309.56 | bwd_microstep: 559.40 | bwd_inner_microstep: 487.92 | bwd_allreduce_microstep: 71.44 | step_microstep: 33.01 +[2025-05-02 00:01:47,637] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 3492.79 | bwd: 5619.42 | bwd_inner: 5547.67 | bwd_allreduce: 71.52 | step: 61.53 + 8%|▊ | 654/8720 [1:46:21<24:25:14, 10.90s/it] {'loss': 1.6101, 'grad_norm': 7.619023323059082, 'learning_rate': 9.947093487310197e-06, 'epoch': 0.75} + 8%|▊ | 654/8720 [1:46:21<24:25:14, 10.90s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1925 +[2025-05-02 00:01:48,540] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 395.43 | bwd_microstep: 485.50 | bwd_inner_microstep: 485.48 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.60 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 891 +[2025-05-02 00:01:48,969] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 125.46 | bwd_microstep: 286.49 | bwd_inner_microstep: 285.70 | bwd_allreduce_microstep: 0.77 | step_microstep: 0.23 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-02 00:01:49,836] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 335.08 | bwd_microstep: 513.84 | bwd_inner_microstep: 513.82 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.99 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 348 +[2025-05-02 00:01:50,052] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 72.82 | bwd_microstep: 127.14 | bwd_inner_microstep: 127.13 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.35 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 852 +[2025-05-02 00:01:50,384] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 175.35 | bwd_microstep: 132.54 | bwd_inner_microstep: 132.27 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 00:01:50,983] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.87 | bwd_microstep: 391.69 | bwd_inner_microstep: 391.68 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 00:01:51,866] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 319.66 | bwd_microstep: 530.71 | bwd_inner_microstep: 530.69 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 00:01:52,534] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 326.38 | bwd_microstep: 324.82 | bwd_inner_microstep: 324.80 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1098 +[2025-05-02 00:01:53,002] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 117.62 | bwd_microstep: 332.86 | bwd_inner_microstep: 332.85 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.82 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 00:01:53,860] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 331.21 | bwd_microstep: 506.15 | bwd_inner_microstep: 506.13 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 00:01:54,726] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 364.47 | bwd_microstep: 473.58 | bwd_inner_microstep: 473.56 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 328 +[2025-05-02 00:01:54,963] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 96.94 | bwd_microstep: 121.08 | bwd_inner_microstep: 121.07 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 00:01:55,838] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 321.04 | bwd_microstep: 520.48 | bwd_inner_microstep: 520.46 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 00:01:56,693] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 325.56 | bwd_microstep: 509.97 | bwd_inner_microstep: 509.95 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.92 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 00:01:57,553] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 352.42 | bwd_microstep: 479.22 | bwd_inner_microstep: 479.20 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 00:01:58,701] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.31 | optimizer_step: 18.70 +[2025-05-02 00:01:58,704] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 374.24 | bwd_microstep: 729.40 | bwd_inner_microstep: 466.87 | bwd_allreduce_microstep: 262.45 | step_microstep: 28.49 +[2025-05-02 00:01:58,705] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4222.37 | bwd: 6465.50 | bwd_inner: 6201.70 | bwd_allreduce: 263.41 | step: 39.30 + 8%|▊ | 655/8720 [1:46:32<24:31:59, 10.95s/it] {'loss': 1.5829, 'grad_norm': 7.056811332702637, 'learning_rate': 9.94682369191763e-06, 'epoch': 0.75} + 8%|▊ | 655/8720 [1:46:32<24:31:59, 10.95s/it]dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1551 +[2025-05-02 00:01:59,447] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 261.30 | bwd_microstep: 441.68 | bwd_inner_microstep: 441.67 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1921 +[2025-05-02 00:02:00,380] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 343.06 | bwd_microstep: 553.86 | bwd_inner_microstep: 553.84 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1887 +[2025-05-02 00:02:01,265] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 327.73 | bwd_microstep: 522.23 | bwd_inner_microstep: 522.21 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.52 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 00:02:02,138] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 320.11 | bwd_microstep: 517.54 | bwd_inner_microstep: 517.52 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1363 +[2025-05-02 00:02:02,840] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 234.67 | bwd_microstep: 435.96 | bwd_inner_microstep: 435.95 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.90 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 00:02:03,692] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 313.92 | bwd_microstep: 519.52 | bwd_inner_microstep: 519.51 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 835 +[2025-05-02 00:02:04,118] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 118.52 | bwd_microstep: 277.76 | bwd_inner_microstep: 277.74 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 00:02:04,996] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 320.74 | bwd_microstep: 525.72 | bwd_inner_microstep: 525.70 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 00:02:05,858] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 319.00 | bwd_microstep: 518.25 | bwd_inner_microstep: 518.23 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 00:02:06,728] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 313.58 | bwd_microstep: 524.17 | bwd_inner_microstep: 524.15 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.47 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 00:02:07,610] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 331.24 | bwd_microstep: 519.03 | bwd_inner_microstep: 519.02 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.42 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 00:02:08,470] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 317.20 | bwd_microstep: 511.50 | bwd_inner_microstep: 511.48 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 00:02:09,256] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 327.71 | bwd_microstep: 428.45 | bwd_inner_microstep: 428.43 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 00:02:10,140] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 392.43 | bwd_microstep: 460.14 | bwd_inner_microstep: 460.12 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.87 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 634 +[2025-05-02 00:02:10,400] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 97.31 | bwd_microstep: 147.74 | bwd_inner_microstep: 147.49 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.21 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 400 +[2025-05-02 00:02:10,803] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.32 | optimizer_step: 16.46 +[2025-05-02 00:02:10,803] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 81.12 | bwd_microstep: 282.88 | bwd_inner_microstep: 128.02 | bwd_allreduce_microstep: 154.84 | step_microstep: 23.78 +[2025-05-02 00:02:10,804] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4419.61 | bwd: 7186.64 | bwd_inner: 7031.10 | bwd_allreduce: 154.90 | step: 52.10 + 8%|▊ | 656/8720 [1:46:44<25:17:59, 11.29s/it] {'loss': 0.669, 'grad_norm': 3.062558174133301, 'learning_rate': 9.94655321404368e-06, 'epoch': 0.75} + 8%|▊ | 656/8720 [1:46:44<25:17:59, 11.29s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1939 +[2025-05-02 00:02:11,642] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 327.37 | bwd_microstep: 488.41 | bwd_inner_microstep: 488.39 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.86 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1389 +[2025-05-02 00:02:12,250] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 235.87 | bwd_microstep: 355.76 | bwd_inner_microstep: 355.19 | bwd_allreduce_microstep: 0.55 | step_microstep: 0.23 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-02 00:02:13,058] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 312.85 | bwd_microstep: 471.98 | bwd_inner_microstep: 471.96 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.89 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 00:02:13,875] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 322.73 | bwd_microstep: 473.80 | bwd_inner_microstep: 473.78 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.89 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 00:02:14,674] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 320.00 | bwd_microstep: 458.26 | bwd_inner_microstep: 458.25 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.88 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 00:02:15,475] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 318.24 | bwd_microstep: 464.93 | bwd_inner_microstep: 464.92 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 00:02:16,270] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 307.64 | bwd_microstep: 469.98 | bwd_inner_microstep: 469.96 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.90 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 844 +[2025-05-02 00:02:16,665] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 153.29 | bwd_microstep: 222.76 | bwd_inner_microstep: 222.01 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.22 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 00:02:17,469] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 319.33 | bwd_microstep: 464.42 | bwd_inner_microstep: 464.41 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.64 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 00:02:18,271] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 317.36 | bwd_microstep: 466.98 | bwd_inner_microstep: 466.96 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.77 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 00:02:19,073] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 315.54 | bwd_microstep: 469.00 | bwd_inner_microstep: 468.99 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.90 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 00:02:19,882] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 319.65 | bwd_microstep: 470.68 | bwd_inner_microstep: 470.67 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.90 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 00:02:20,687] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 321.43 | bwd_microstep: 466.73 | bwd_inner_microstep: 466.71 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 00:02:21,484] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 315.69 | bwd_microstep: 463.56 | bwd_inner_microstep: 463.54 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.43 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 314 +[2025-05-02 00:02:21,710] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.45 | bwd_microstep: 116.28 | bwd_inner_microstep: 116.26 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.24 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1895 +[2025-05-02 00:02:22,717] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.43 | optimizer_step: 30.61 +[2025-05-02 00:02:22,717] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 315.01 | bwd_microstep: 635.08 | bwd_inner_microstep: 475.85 | bwd_allreduce_microstep: 159.22 | step_microstep: 39.67 +[2025-05-02 00:02:22,718] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4616.45 | bwd: 6958.62 | bwd_inner: 6797.88 | bwd_allreduce: 159.82 | step: 51.65 + 8%|▊ | 657/8720 [1:46:56<25:42:47, 11.48s/it] {'loss': 1.2221, 'grad_norm': 4.244693756103516, 'learning_rate': 9.946282053725657e-06, 'epoch': 0.75} + 8%|▊ | 657/8720 [1:46:56<25:42:47, 11.48s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1935 +[2025-05-02 00:02:23,578] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 333.75 | bwd_microstep: 503.03 | bwd_inner_microstep: 503.01 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.88 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 875 +[2025-05-02 00:02:23,978] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 150.35 | bwd_microstep: 233.73 | bwd_inner_microstep: 233.11 | bwd_allreduce_microstep: 0.60 | step_microstep: 0.23 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-02 00:02:24,804] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 330.56 | bwd_microstep: 478.25 | bwd_inner_microstep: 478.23 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.92 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 00:02:25,638] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 327.22 | bwd_microstep: 484.83 | bwd_inner_microstep: 484.81 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.08 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 335 +[2025-05-02 00:02:25,860] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 85.75 | bwd_microstep: 119.76 | bwd_inner_microstep: 119.74 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.24 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 00:02:26,679] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 314.05 | bwd_microstep: 486.45 | bwd_inner_microstep: 485.53 | bwd_allreduce_microstep: 0.91 | step_microstep: 0.39 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 838 +[2025-05-02 00:02:27,068] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 153.79 | bwd_microstep: 216.64 | bwd_inner_microstep: 216.62 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.61 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 321 +[2025-05-02 00:02:27,292] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 84.24 | bwd_microstep: 118.88 | bwd_inner_microstep: 118.56 | bwd_allreduce_microstep: 0.30 | step_microstep: 0.38 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 00:02:28,111] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 323.78 | bwd_microstep: 475.24 | bwd_inner_microstep: 474.31 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.25 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 321 +[2025-05-02 00:02:28,353] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 104.10 | bwd_microstep: 117.27 | bwd_inner_microstep: 117.06 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.61 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 00:02:29,175] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 326.71 | bwd_microstep: 474.44 | bwd_inner_microstep: 474.42 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.97 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 00:02:29,988] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 328.96 | bwd_microstep: 465.53 | bwd_inner_microstep: 464.57 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.23 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 829 +[2025-05-02 00:02:30,384] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 155.64 | bwd_microstep: 223.25 | bwd_inner_microstep: 223.24 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.23 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 828 +[2025-05-02 00:02:30,780] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 155.60 | bwd_microstep: 224.14 | bwd_inner_microstep: 223.74 | bwd_allreduce_microstep: 0.39 | step_microstep: 0.25 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 829 +[2025-05-02 00:02:31,182] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 156.49 | bwd_microstep: 226.28 | bwd_inner_microstep: 226.26 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.24 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 00:02:32,208] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.62 | optimizer_step: 30.67 +[2025-05-02 00:02:32,209] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 333.07 | bwd_microstep: 634.79 | bwd_inner_microstep: 473.02 | bwd_allreduce_microstep: 160.83 | step_microstep: 40.43 +[2025-05-02 00:02:32,210] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 3664.07 | bwd: 5482.51 | bwd_inner: 5316.26 | bwd_allreduce: 164.56 | step: 47.73 + 8%|▊ | 658/8720 [1:47:05<24:22:26, 10.88s/it] {'loss': 1.2032, 'grad_norm': 6.20365047454834, 'learning_rate': 9.946010211000976e-06, 'epoch': 0.75} + 8%|▊ | 658/8720 [1:47:05<24:22:26, 10.88s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2043 +[2025-05-02 00:02:33,106] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 355.57 | bwd_microstep: 516.83 | bwd_inner_microstep: 516.81 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1893 +[2025-05-02 00:02:33,954] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 333.44 | bwd_microstep: 496.67 | bwd_inner_microstep: 496.65 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.97 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-02 00:02:34,803] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 336.90 | bwd_microstep: 494.79 | bwd_inner_microstep: 494.77 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.96 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 00:02:35,653] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 341.18 | bwd_microstep: 491.67 | bwd_inner_microstep: 491.66 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.92 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1361 +[2025-05-02 00:02:36,282] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 244.91 | bwd_microstep: 365.88 | bwd_inner_microstep: 365.86 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.24 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-02 00:02:37,124] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 334.32 | bwd_microstep: 489.43 | bwd_inner_microstep: 489.41 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.30 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 00:02:37,970] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 334.66 | bwd_microstep: 494.65 | bwd_inner_microstep: 494.64 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.94 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 00:02:38,816] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 332.22 | bwd_microstep: 494.55 | bwd_inner_microstep: 494.53 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 00:02:39,656] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 332.63 | bwd_microstep: 489.93 | bwd_inner_microstep: 489.91 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.92 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 00:02:40,505] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 333.42 | bwd_microstep: 498.16 | bwd_inner_microstep: 498.14 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.97 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 00:02:41,350] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 333.56 | bwd_microstep: 494.05 | bwd_inner_microstep: 494.03 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.94 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 00:02:42,188] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 334.20 | bwd_microstep: 484.19 | bwd_inner_microstep: 484.17 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.93 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 00:02:43,029] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 335.42 | bwd_microstep: 487.55 | bwd_inner_microstep: 487.53 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.00 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 00:02:43,868] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 329.37 | bwd_microstep: 491.28 | bwd_inner_microstep: 491.26 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.13 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 00:02:44,707] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 332.56 | bwd_microstep: 489.12 | bwd_inner_microstep: 489.11 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.99 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 00:02:45,751] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.47 | optimizer_step: 29.99 +[2025-05-02 00:02:45,751] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 332.35 | bwd_microstep: 654.96 | bwd_inner_microstep: 491.06 | bwd_allreduce_microstep: 163.89 | step_microstep: 39.22 +[2025-05-02 00:02:45,753] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 5276.70 | bwd: 7933.71 | bwd_inner: 7769.56 | bwd_allreduce: 163.95 | step: 53.57 + 8%|▊ | 659/8720 [1:47:19<26:09:23, 11.68s/it] {'loss': 1.043, 'grad_norm': 7.177011013031006, 'learning_rate': 9.945737685907138e-06, 'epoch': 0.76} + 8%|▊ | 659/8720 [1:47:19<26:09:23, 11.68s/it]dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 1008 +[2025-05-02 00:02:46,219] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 181.27 | bwd_microstep: 264.82 | bwd_inner_microstep: 264.07 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.22 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1911 +[2025-05-02 00:02:47,079] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 338.99 | bwd_microstep: 502.75 | bwd_inner_microstep: 502.73 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.96 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1893 +[2025-05-02 00:02:47,938] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 338.58 | bwd_microstep: 502.16 | bwd_inner_microstep: 502.14 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.13 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-02 00:02:48,792] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 340.21 | bwd_microstep: 495.86 | bwd_inner_microstep: 495.84 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.93 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 00:02:49,642] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 337.67 | bwd_microstep: 494.22 | bwd_inner_microstep: 494.20 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.14 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 00:02:50,495] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 338.60 | bwd_microstep: 496.64 | bwd_inner_microstep: 496.62 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.01 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 00:02:51,351] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 339.63 | bwd_microstep: 497.12 | bwd_inner_microstep: 497.10 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 00:02:52,190] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 330.52 | bwd_microstep: 491.00 | bwd_inner_microstep: 490.99 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.02 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 00:02:53,026] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 327.42 | bwd_microstep: 490.10 | bwd_inner_microstep: 490.08 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.98 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 00:02:53,871] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 338.29 | bwd_microstep: 489.06 | bwd_inner_microstep: 489.04 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.94 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 00:02:54,713] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 329.88 | bwd_microstep: 493.05 | bwd_inner_microstep: 493.03 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.02 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 00:02:55,565] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 336.92 | bwd_microstep: 496.23 | bwd_inner_microstep: 496.21 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.33 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 00:02:56,412] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 336.17 | bwd_microstep: 490.94 | bwd_inner_microstep: 490.92 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.39 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 831 +[2025-05-02 00:02:56,823] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 160.74 | bwd_microstep: 233.18 | bwd_inner_microstep: 233.16 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.28 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 00:02:57,671] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 338.74 | bwd_microstep: 491.59 | bwd_inner_microstep: 491.57 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.97 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 00:02:58,723] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.43 | optimizer_step: 30.07 +[2025-05-02 00:02:58,724] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 338.81 | bwd_microstep: 658.93 | bwd_inner_microstep: 493.65 | bwd_allreduce_microstep: 165.27 | step_microstep: 37.94 +[2025-05-02 00:02:58,725] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 5052.47 | bwd: 7588.41 | bwd_inner: 7421.36 | bwd_allreduce: 165.33 | step: 50.22 + 8%|▊ | 660/8720 [1:47:32<27:01:14, 12.07s/it] {'loss': 0.9531, 'grad_norm': 4.681777000427246, 'learning_rate': 9.945464478481746e-06, 'epoch': 0.76} + 8%|▊ | 660/8720 [1:47:32<27:01:14, 12.07s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1910 +[2025-05-02 00:02:59,595] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 342.38 | bwd_microstep: 504.39 | bwd_inner_microstep: 504.37 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.95 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1894 +[2025-05-02 00:03:00,460] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 337.51 | bwd_microstep: 508.93 | bwd_inner_microstep: 508.91 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-02 00:03:01,321] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 341.70 | bwd_microstep: 500.43 | bwd_inner_microstep: 500.41 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.99 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 847 +[2025-05-02 00:03:01,740] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 164.09 | bwd_microstep: 239.24 | bwd_inner_microstep: 239.22 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.65 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 00:03:02,601] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 336.12 | bwd_microstep: 506.99 | bwd_inner_microstep: 506.97 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 00:03:03,460] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 338.53 | bwd_microstep: 502.63 | bwd_inner_microstep: 502.61 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.13 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1357 +[2025-05-02 00:03:04,103] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 249.67 | bwd_microstep: 376.38 | bwd_inner_microstep: 376.36 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.87 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 00:03:04,961] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 338.25 | bwd_microstep: 500.57 | bwd_inner_microstep: 500.55 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.17 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 00:03:05,817] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 337.50 | bwd_microstep: 499.59 | bwd_inner_microstep: 499.57 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 00:03:06,676] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 339.38 | bwd_microstep: 501.44 | bwd_inner_microstep: 501.42 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 00:03:07,535] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 341.57 | bwd_microstep: 499.99 | bwd_inner_microstep: 499.97 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.02 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 00:03:08,396] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 342.07 | bwd_microstep: 501.63 | bwd_inner_microstep: 501.61 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.99 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 00:03:09,257] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 339.45 | bwd_microstep: 503.60 | bwd_inner_microstep: 503.58 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.98 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 00:03:10,114] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 339.64 | bwd_microstep: 499.45 | bwd_inner_microstep: 499.43 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.16 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 897 +[2025-05-02 00:03:10,573] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 182.35 | bwd_microstep: 260.61 | bwd_inner_microstep: 260.59 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.84 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1918 +[2025-05-02 00:03:11,654] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.48 | optimizer_step: 30.57 +[2025-05-02 00:03:11,654] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 349.53 | bwd_microstep: 676.32 | bwd_inner_microstep: 508.51 | bwd_allreduce_microstep: 167.79 | step_microstep: 38.43 +[2025-05-02 00:03:11,656] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 5019.73 | bwd: 7582.17 | bwd_inner: 7414.11 | bwd_allreduce: 167.86 | step: 53.34 + 8%|▊ | 661/8720 [1:47:45<27:35:45, 12.33s/it] {'loss': 0.9723, 'grad_norm': 5.929232120513916, 'learning_rate': 9.945190588762488e-06, 'epoch': 0.76} + 8%|▊ | 661/8720 [1:47:45<27:35:45, 12.33s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 398 +[2025-05-02 00:03:11,887] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 82.79 | bwd_microstep: 128.66 | bwd_inner_microstep: 128.64 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.52 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-02 00:03:12,756] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 344.39 | bwd_microstep: 506.78 | bwd_inner_microstep: 506.76 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.17 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 00:03:13,623] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 342.12 | bwd_microstep: 507.13 | bwd_inner_microstep: 507.12 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.99 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 00:03:14,486] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 345.01 | bwd_microstep: 499.51 | bwd_inner_microstep: 499.49 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.07 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 00:03:15,350] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 340.78 | bwd_microstep: 505.66 | bwd_inner_microstep: 505.64 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.76 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 00:03:16,216] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 337.69 | bwd_microstep: 509.45 | bwd_inner_microstep: 509.43 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.05 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 330 +[2025-05-02 00:03:16,426] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 77.30 | bwd_microstep: 117.81 | bwd_inner_microstep: 117.22 | bwd_allreduce_microstep: 0.57 | step_microstep: 0.26 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 00:03:17,295] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 342.12 | bwd_microstep: 508.40 | bwd_inner_microstep: 508.38 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 00:03:18,162] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 344.36 | bwd_microstep: 505.09 | bwd_inner_microstep: 505.07 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 00:03:19,026] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 342.75 | bwd_microstep: 503.88 | bwd_inner_microstep: 503.86 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 00:03:19,891] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 343.58 | bwd_microstep: 502.62 | bwd_inner_microstep: 502.60 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 00:03:20,766] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 347.19 | bwd_microstep: 510.07 | bwd_inner_microstep: 510.05 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 00:03:21,636] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 345.95 | bwd_microstep: 504.02 | bwd_inner_microstep: 504.00 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.52 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 00:03:22,501] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 344.66 | bwd_microstep: 501.36 | bwd_inner_microstep: 501.34 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1931 +[2025-05-02 00:03:23,427] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 358.51 | bwd_microstep: 548.89 | bwd_inner_microstep: 548.88 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.20 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1098 +[2025-05-02 00:03:24,152] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.56 | optimizer_step: 17.06 +[2025-05-02 00:03:24,153] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 212.50 | bwd_microstep: 469.53 | bwd_inner_microstep: 297.80 | bwd_allreduce_microstep: 170.83 | step_microstep: 26.66 +[2025-05-02 00:03:24,154] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4851.67 | bwd: 7328.85 | bwd_inner: 7157.19 | bwd_allreduce: 171.46 | step: 41.99 + 8%|▊ | 662/8720 [1:47:57<27:42:27, 12.38s/it] {'loss': 0.6744, 'grad_norm': 6.209382057189941, 'learning_rate': 9.944916016787154e-06, 'epoch': 0.76} + 8%|▊ | 662/8720 [1:47:57<27:42:27, 12.38s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1955 +[2025-05-02 00:03:25,084] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 359.23 | bwd_microstep: 547.59 | bwd_inner_microstep: 547.57 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1909 +[2025-05-02 00:03:25,975] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 349.58 | bwd_microstep: 522.92 | bwd_inner_microstep: 522.90 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.75 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1905 +[2025-05-02 00:03:26,864] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 350.19 | bwd_microstep: 520.66 | bwd_inner_microstep: 520.64 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-02 00:03:27,741] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 347.16 | bwd_microstep: 512.54 | bwd_inner_microstep: 512.52 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.22 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 00:03:28,619] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 346.18 | bwd_microstep: 513.28 | bwd_inner_microstep: 513.26 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-02 00:03:29,497] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 347.00 | bwd_microstep: 513.20 | bwd_inner_microstep: 513.18 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.16 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 00:03:30,377] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 348.49 | bwd_microstep: 513.43 | bwd_inner_microstep: 513.40 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 00:03:31,252] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 345.91 | bwd_microstep: 511.47 | bwd_inner_microstep: 511.45 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.11 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 839 +[2025-05-02 00:03:31,668] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 165.65 | bwd_microstep: 233.47 | bwd_inner_microstep: 233.45 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.82 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 00:03:32,547] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 349.17 | bwd_microstep: 511.20 | bwd_inner_microstep: 511.18 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.16 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 836 +[2025-05-02 00:03:32,963] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 167.47 | bwd_microstep: 232.37 | bwd_inner_microstep: 232.35 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.26 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 00:03:33,840] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 350.61 | bwd_microstep: 509.13 | bwd_inner_microstep: 509.11 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.22 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 827 +[2025-05-02 00:03:34,263] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 166.45 | bwd_microstep: 239.34 | bwd_inner_microstep: 239.32 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.38 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 00:03:35,133] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 342.35 | bwd_microstep: 509.36 | bwd_inner_microstep: 509.34 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2168 +[2025-05-02 00:03:36,138] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 385.85 | bwd_microstep: 600.16 | bwd_inner_microstep: 600.15 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.12 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 366 +[2025-05-02 00:03:36,569] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.51 | optimizer_step: 17.18 +[2025-05-02 00:03:36,569] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 85.08 | bwd_microstep: 306.08 | bwd_inner_microstep: 132.78 | bwd_allreduce_microstep: 173.28 | step_microstep: 24.90 +[2025-05-02 00:03:36,570] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4806.38 | bwd: 7296.19 | bwd_inner: 7120.82 | bwd_allreduce: 173.35 | step: 39.65 + 8%|▊ | 663/8720 [1:48:10<27:43:45, 12.39s/it] {'loss': 1.1235, 'grad_norm': 4.445651531219482, 'learning_rate': 9.944640762593621e-06, 'epoch': 0.76} + 8%|▊ | 663/8720 [1:48:10<27:43:45, 12.39s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1929 +[2025-05-02 00:03:37,505] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 363.56 | bwd_microstep: 548.29 | bwd_inner_microstep: 548.27 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.02 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1883 +[2025-05-02 00:03:38,392] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 352.82 | bwd_microstep: 516.91 | bwd_inner_microstep: 516.89 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-02 00:03:39,280] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 351.96 | bwd_microstep: 517.84 | bwd_inner_microstep: 517.82 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.88 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 00:03:40,162] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 349.25 | bwd_microstep: 515.21 | bwd_inner_microstep: 515.19 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 00:03:41,048] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 353.93 | bwd_microstep: 514.99 | bwd_inner_microstep: 514.97 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.13 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 342 +[2025-05-02 00:03:41,253] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 73.63 | bwd_microstep: 116.09 | bwd_inner_microstep: 116.07 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.41 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-02 00:03:42,138] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 352.27 | bwd_microstep: 515.39 | bwd_inner_microstep: 515.37 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.26 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 332 +[2025-05-02 00:03:42,343] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 75.93 | bwd_microstep: 113.59 | bwd_inner_microstep: 113.57 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.59 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 00:03:43,222] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 346.16 | bwd_microstep: 515.28 | bwd_inner_microstep: 515.26 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 00:03:44,103] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 349.35 | bwd_microstep: 513.61 | bwd_inner_microstep: 513.59 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.23 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 00:03:44,979] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 348.32 | bwd_microstep: 509.99 | bwd_inner_microstep: 509.98 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.19 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1086 +[2025-05-02 00:03:45,506] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 209.77 | bwd_microstep: 301.12 | bwd_inner_microstep: 301.11 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.98 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 00:03:46,392] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 351.54 | bwd_microstep: 516.24 | bwd_inner_microstep: 516.22 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.25 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 00:03:47,272] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 347.38 | bwd_microstep: 515.77 | bwd_inner_microstep: 515.75 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.14 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 00:03:48,161] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 355.33 | bwd_microstep: 516.17 | bwd_inner_microstep: 516.15 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.28 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1892 +[2025-05-02 00:03:49,260] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.64 | optimizer_step: 16.85 +[2025-05-02 00:03:49,260] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 352.26 | bwd_microstep: 705.12 | bwd_inner_microstep: 527.93 | bwd_allreduce_microstep: 177.17 | step_microstep: 24.73 +[2025-05-02 00:03:49,261] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4933.25 | bwd: 7451.60 | bwd_inner: 7274.17 | bwd_allreduce: 177.24 | step: 40.69 + 8%|▊ | 664/8720 [1:48:23<27:55:40, 12.48s/it] {'loss': 0.8553, 'grad_norm': 4.751760482788086, 'learning_rate': 9.94436482621987e-06, 'epoch': 0.76} + 8%|▊ | 664/8720 [1:48:23<27:55:40, 12.48s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-02 00:03:50,167] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 359.14 | bwd_microstep: 524.06 | bwd_inner_microstep: 524.04 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-02 00:03:51,066] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 354.45 | bwd_microstep: 527.25 | bwd_inner_microstep: 527.23 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.15 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1356 +[2025-05-02 00:03:51,743] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 261.56 | bwd_microstep: 398.09 | bwd_inner_microstep: 398.07 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.02 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 00:03:52,638] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 358.06 | bwd_microstep: 519.73 | bwd_inner_microstep: 519.71 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.25 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1365 +[2025-05-02 00:03:53,318] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 265.81 | bwd_microstep: 397.81 | bwd_inner_microstep: 397.79 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.97 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 837 +[2025-05-02 00:03:53,741] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 169.86 | bwd_microstep: 236.68 | bwd_inner_microstep: 236.66 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.88 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 00:03:54,638] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 357.71 | bwd_microstep: 522.36 | bwd_inner_microstep: 522.34 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.26 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 331 +[2025-05-02 00:03:54,861] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 74.45 | bwd_microstep: 133.54 | bwd_inner_microstep: 133.53 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.56 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 328 +[2025-05-02 00:03:55,093] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 89.00 | bwd_microstep: 120.77 | bwd_inner_microstep: 120.15 | bwd_allreduce_microstep: 0.60 | step_microstep: 0.22 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 00:03:55,992] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 356.03 | bwd_microstep: 523.62 | bwd_inner_microstep: 523.60 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.17 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 00:03:56,879] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 355.77 | bwd_microstep: 513.39 | bwd_inner_microstep: 513.37 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 00:03:57,773] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 354.25 | bwd_microstep: 521.98 | bwd_inner_microstep: 521.96 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.24 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 834 +[2025-05-02 00:03:58,200] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 170.79 | bwd_microstep: 239.53 | bwd_inner_microstep: 239.51 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.87 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 00:03:59,093] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 357.51 | bwd_microstep: 516.62 | bwd_inner_microstep: 516.60 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.29 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-02 00:03:59,743] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 238.47 | bwd_microstep: 392.00 | bwd_inner_microstep: 391.98 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.51 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 00:04:00,754] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.60 | optimizer_step: 16.51 +[2025-05-02 00:04:00,754] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 338.47 | bwd_microstep: 618.87 | bwd_inner_microstep: 462.21 | bwd_allreduce_microstep: 156.64 | step_microstep: 24.50 +[2025-05-02 00:04:00,755] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4461.34 | bwd: 6706.29 | bwd_inner: 6548.79 | bwd_allreduce: 157.31 | step: 41.12 + 8%|▊ | 665/8720 [1:48:34<27:15:45, 12.18s/it] {'loss': 1.0379, 'grad_norm': 5.434371471405029, 'learning_rate': 9.944088207703965e-06, 'epoch': 0.76} + 8%|▊ | 665/8720 [1:48:34<27:15:45, 12.18s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2116 +[2025-05-02 00:04:01,664] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 355.62 | bwd_microstep: 530.77 | bwd_inner_microstep: 530.75 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.86 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 962 +[2025-05-02 00:04:02,101] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 169.79 | bwd_microstep: 251.44 | bwd_inner_microstep: 250.86 | bwd_allreduce_microstep: 0.56 | step_microstep: 0.39 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 396 +[2025-05-02 00:04:02,319] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 81.99 | bwd_microstep: 120.30 | bwd_inner_microstep: 120.28 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.21 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1390 +[2025-05-02 00:04:02,931] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 233.68 | bwd_microstep: 360.93 | bwd_inner_microstep: 360.91 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.80 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 00:04:03,739] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 318.16 | bwd_microstep: 471.27 | bwd_inner_microstep: 471.26 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.90 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 844 +[2025-05-02 00:04:04,134] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 157.14 | bwd_microstep: 221.18 | bwd_inner_microstep: 221.16 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.60 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1350 +[2025-05-02 00:04:04,747] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 242.63 | bwd_microstep: 354.43 | bwd_inner_microstep: 354.41 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.81 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 00:04:05,549] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 317.43 | bwd_microstep: 466.55 | bwd_inner_microstep: 466.54 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.89 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 00:04:06,355] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 319.33 | bwd_microstep: 467.88 | bwd_inner_microstep: 467.86 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.63 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 836 +[2025-05-02 00:04:06,737] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 151.76 | bwd_microstep: 215.35 | bwd_inner_microstep: 214.59 | bwd_allreduce_microstep: 0.74 | step_microstep: 0.24 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 00:04:07,543] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 316.78 | bwd_microstep: 471.85 | bwd_inner_microstep: 471.83 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.89 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 00:04:08,343] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 317.45 | bwd_microstep: 463.64 | bwd_inner_microstep: 463.62 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.89 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 00:04:09,153] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 324.03 | bwd_microstep: 468.97 | bwd_inner_microstep: 468.95 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 00:04:09,960] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 322.59 | bwd_microstep: 466.48 | bwd_inner_microstep: 466.46 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.89 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 00:04:10,767] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 320.78 | bwd_microstep: 468.73 | bwd_inner_microstep: 468.72 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.93 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 00:04:11,753] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.40 | optimizer_step: 16.50 +[2025-05-02 00:04:11,754] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 315.98 | bwd_microstep: 629.59 | bwd_inner_microstep: 471.97 | bwd_allreduce_microstep: 157.61 | step_microstep: 24.06 +[2025-05-02 00:04:11,755] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4265.11 | bwd: 6429.36 | bwd_inner: 6270.18 | bwd_allreduce: 158.97 | step: 36.06 + 8%|▊ | 666/8720 [1:48:45<26:27:49, 11.83s/it] {'loss': 1.039, 'grad_norm': 7.510803699493408, 'learning_rate': 9.943810907084073e-06, 'epoch': 0.76} + 8%|▊ | 666/8720 [1:48:45<26:27:49, 11.83s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1961 +[2025-05-02 00:04:12,626] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 336.68 | bwd_microstep: 512.28 | bwd_inner_microstep: 512.26 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.85 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1921 +[2025-05-02 00:04:13,487] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 331.94 | bwd_microstep: 511.22 | bwd_inner_microstep: 511.20 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1888 +[2025-05-02 00:04:14,312] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 323.47 | bwd_microstep: 483.83 | bwd_inner_microstep: 483.80 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.92 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-02 00:04:15,143] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 331.75 | bwd_microstep: 482.34 | bwd_inner_microstep: 482.32 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.90 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-02 00:04:15,966] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 324.38 | bwd_microstep: 480.13 | bwd_inner_microstep: 480.11 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.95 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1883 +[2025-05-02 00:04:16,791] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 323.20 | bwd_microstep: 484.21 | bwd_inner_microstep: 484.19 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.90 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 00:04:17,615] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 325.09 | bwd_microstep: 480.50 | bwd_inner_microstep: 480.48 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.94 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 00:04:18,432] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 321.52 | bwd_microstep: 477.24 | bwd_inner_microstep: 477.21 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.90 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 00:04:19,254] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 324.04 | bwd_microstep: 478.97 | bwd_inner_microstep: 478.96 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 00:04:20,084] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 328.69 | bwd_microstep: 483.09 | bwd_inner_microstep: 483.07 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 00:04:20,921] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 325.57 | bwd_microstep: 493.29 | bwd_inner_microstep: 493.27 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.92 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 00:04:21,749] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 328.02 | bwd_microstep: 481.71 | bwd_inner_microstep: 481.69 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.97 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 00:04:22,585] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 329.78 | bwd_microstep: 487.56 | bwd_inner_microstep: 487.54 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 00:04:23,413] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 331.43 | bwd_microstep: 478.86 | bwd_inner_microstep: 478.84 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 00:04:24,218] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 322.20 | bwd_microstep: 464.07 | bwd_inner_microstep: 464.05 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.93 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 00:04:25,224] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.61 | optimizer_step: 16.79 +[2025-05-02 00:04:25,225] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 322.18 | bwd_microstep: 642.08 | bwd_inner_microstep: 481.23 | bwd_allreduce_microstep: 160.83 | step_microstep: 24.81 +[2025-05-02 00:04:25,226] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 5229.94 | bwd: 7921.36 | bwd_inner: 7760.27 | bwd_allreduce: 160.89 | step: 39.32 + 8%|▊ | 667/8720 [1:48:58<27:33:46, 12.32s/it] {'loss': 1.004, 'grad_norm': 5.642129421234131, 'learning_rate': 9.943532924398446e-06, 'epoch': 0.76} + 8%|▊ | 667/8720 [1:48:58<27:33:46, 12.32s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 420 +[2025-05-02 00:04:25,456] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 84.68 | bwd_microstep: 124.57 | bwd_inner_microstep: 124.25 | bwd_allreduce_microstep: 0.31 | step_microstep: 0.39 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1899 +[2025-05-02 00:04:26,280] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 327.03 | bwd_microstep: 480.60 | bwd_inner_microstep: 480.58 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.95 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1896 +[2025-05-02 00:04:27,131] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 334.59 | bwd_microstep: 497.56 | bwd_inner_microstep: 497.55 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.97 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 00:04:27,973] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 328.79 | bwd_microstep: 494.56 | bwd_inner_microstep: 494.54 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.94 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 00:04:28,819] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 331.69 | bwd_microstep: 495.99 | bwd_inner_microstep: 495.98 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-02 00:04:29,658] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 329.09 | bwd_microstep: 490.84 | bwd_inner_microstep: 490.82 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.94 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1093 +[2025-05-02 00:04:30,161] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 200.59 | bwd_microstep: 285.72 | bwd_inner_microstep: 284.91 | bwd_allreduce_microstep: 0.80 | step_microstep: 0.25 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 00:04:30,996] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 331.03 | bwd_microstep: 486.18 | bwd_inner_microstep: 486.16 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.95 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 00:04:31,839] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 333.59 | bwd_microstep: 491.13 | bwd_inner_microstep: 491.11 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.07 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 847 +[2025-05-02 00:04:32,246] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 161.30 | bwd_microstep: 229.04 | bwd_inner_microstep: 229.02 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.62 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 00:04:33,089] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 335.96 | bwd_microstep: 489.76 | bwd_inner_microstep: 489.74 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.96 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 00:04:33,929] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 333.27 | bwd_microstep: 488.17 | bwd_inner_microstep: 488.15 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.99 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 00:04:34,778] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 336.29 | bwd_microstep: 493.77 | bwd_inner_microstep: 493.75 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.97 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1343 +[2025-05-02 00:04:35,408] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 245.20 | bwd_microstep: 367.12 | bwd_inner_microstep: 367.10 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.72 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 00:04:36,255] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 332.67 | bwd_microstep: 494.66 | bwd_inner_microstep: 494.64 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.95 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 00:04:37,285] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.57 | optimizer_step: 16.75 +[2025-05-02 00:04:37,286] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 333.72 | bwd_microstep: 654.13 | bwd_inner_microstep: 490.67 | bwd_allreduce_microstep: 163.44 | step_microstep: 26.21 +[2025-05-02 00:04:37,287] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4679.47 | bwd: 7063.80 | bwd_inner: 6899.00 | bwd_allreduce: 164.60 | step: 38.98 + 8%|▊ | 668/8720 [1:49:11<27:23:05, 12.24s/it] {'loss': 1.4319, 'grad_norm': 5.167781352996826, 'learning_rate': 9.943254259685442e-06, 'epoch': 0.77} + 8%|▊ | 668/8720 [1:49:11<27:23:05, 12.24s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 405 +[2025-05-02 00:04:37,528] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 91.36 | bwd_microstep: 127.67 | bwd_inner_microstep: 127.65 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.30 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1916 +[2025-05-02 00:04:38,384] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 338.12 | bwd_microstep: 500.87 | bwd_inner_microstep: 500.85 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.91 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1900 +[2025-05-02 00:04:39,240] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 333.13 | bwd_microstep: 502.13 | bwd_inner_microstep: 502.12 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.01 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-02 00:04:40,070] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 326.47 | bwd_microstep: 485.00 | bwd_inner_microstep: 484.98 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.13 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 347 +[2025-05-02 00:04:40,304] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 87.43 | bwd_microstep: 131.58 | bwd_inner_microstep: 131.56 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.22 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1361 +[2025-05-02 00:04:40,930] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 240.71 | bwd_microstep: 367.77 | bwd_inner_microstep: 367.75 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.71 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 00:04:41,776] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 330.45 | bwd_microstep: 497.20 | bwd_inner_microstep: 497.19 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.38 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 00:04:42,622] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 331.81 | bwd_microstep: 495.91 | bwd_inner_microstep: 495.90 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 00:04:43,477] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 333.78 | bwd_microstep: 496.66 | bwd_inner_microstep: 496.64 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.99 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 00:04:44,333] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 339.74 | bwd_microstep: 496.24 | bwd_inner_microstep: 496.23 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.94 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 331 +[2025-05-02 00:04:44,538] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 75.38 | bwd_microstep: 114.74 | bwd_inner_microstep: 114.21 | bwd_allreduce_microstep: 0.51 | step_microstep: 0.26 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 00:04:45,386] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 335.63 | bwd_microstep: 492.58 | bwd_inner_microstep: 492.56 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.24 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 00:04:46,237] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 337.24 | bwd_microstep: 494.26 | bwd_inner_microstep: 494.24 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 00:04:47,092] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 337.77 | bwd_microstep: 499.74 | bwd_inner_microstep: 499.72 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.97 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 00:04:47,946] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 338.27 | bwd_microstep: 493.32 | bwd_inner_microstep: 493.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.99 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1903 +[2025-05-02 00:04:49,008] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.45 | optimizer_step: 17.31 +[2025-05-02 00:04:49,009] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 340.51 | bwd_microstep: 675.96 | bwd_inner_microstep: 508.89 | bwd_allreduce_microstep: 167.06 | step_microstep: 26.32 +[2025-05-02 00:04:49,010] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4517.81 | bwd: 6871.65 | bwd_inner: 6703.82 | bwd_allreduce: 167.63 | step: 38.47 + 8%|▊ | 669/8720 [1:49:22<27:02:00, 12.09s/it] {'loss': 1.1438, 'grad_norm': 4.796934604644775, 'learning_rate': 9.942974912983505e-06, 'epoch': 0.77} + 8%|▊ | 669/8720 [1:49:22<27:02:00, 12.09s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2114 +[2025-05-02 00:04:49,984] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 371.41 | bwd_microstep: 574.95 | bwd_inner_microstep: 574.93 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.28 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1973 +[2025-05-02 00:04:50,895] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 354.02 | bwd_microstep: 539.12 | bwd_inner_microstep: 539.10 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.97 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1961 +[2025-05-02 00:04:51,807] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 354.82 | bwd_microstep: 539.05 | bwd_inner_microstep: 539.03 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.16 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1181 +[2025-05-02 00:04:52,350] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 213.04 | bwd_microstep: 313.56 | bwd_inner_microstep: 313.54 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.86 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1903 +[2025-05-02 00:04:53,221] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 340.76 | bwd_microstep: 511.88 | bwd_inner_microstep: 511.86 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.07 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-02 00:04:54,081] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 336.81 | bwd_microstep: 505.50 | bwd_inner_microstep: 505.48 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.76 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 00:04:54,939] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 338.70 | bwd_microstep: 501.32 | bwd_inner_microstep: 501.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.08 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1364 +[2025-05-02 00:04:55,590] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 251.23 | bwd_microstep: 381.68 | bwd_inner_microstep: 381.66 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.88 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 00:04:56,452] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 342.42 | bwd_microstep: 502.42 | bwd_inner_microstep: 502.40 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.09 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1353 +[2025-05-02 00:04:57,103] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 252.15 | bwd_microstep: 380.62 | bwd_inner_microstep: 380.61 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.26 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 00:04:57,975] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 346.84 | bwd_microstep: 508.32 | bwd_inner_microstep: 508.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.01 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1346 +[2025-05-02 00:04:58,625] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 253.52 | bwd_microstep: 378.30 | bwd_inner_microstep: 378.28 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.93 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 00:04:59,485] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 338.57 | bwd_microstep: 502.92 | bwd_inner_microstep: 502.90 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 00:05:00,351] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 342.12 | bwd_microstep: 505.38 | bwd_inner_microstep: 505.37 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.10 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 828 +[2025-05-02 00:05:00,765] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 160.48 | bwd_microstep: 237.10 | bwd_inner_microstep: 237.08 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.73 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 316 +[2025-05-02 00:05:01,204] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.67 | optimizer_step: 30.29 +[2025-05-02 00:05:01,205] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 86.25 | bwd_microstep: 297.17 | bwd_inner_microstep: 127.73 | bwd_allreduce_microstep: 169.42 | step_microstep: 39.36 +[2025-05-02 00:05:01,206] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4683.15 | bwd: 7180.14 | bwd_inner: 7009.61 | bwd_allreduce: 169.49 | step: 52.53 + 8%|▊ | 670/8720 [1:49:34<27:06:07, 12.12s/it] {'loss': 1.3918, 'grad_norm': 9.541781425476074, 'learning_rate': 9.942694884331171e-06, 'epoch': 0.77} + 8%|▊ | 670/8720 [1:49:34<27:06:07, 12.12s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1904 +[2025-05-02 00:05:02,088] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 344.33 | bwd_microstep: 510.44 | bwd_inner_microstep: 510.42 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.00 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1901 +[2025-05-02 00:05:02,967] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 343.44 | bwd_microstep: 515.73 | bwd_inner_microstep: 515.71 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1895 +[2025-05-02 00:05:03,836] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 343.85 | bwd_microstep: 506.20 | bwd_inner_microstep: 506.18 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.07 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1889 +[2025-05-02 00:05:04,709] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 342.64 | bwd_microstep: 510.06 | bwd_inner_microstep: 510.05 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 00:05:05,586] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 348.47 | bwd_microstep: 510.50 | bwd_inner_microstep: 510.49 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.23 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-02 00:05:06,462] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 347.69 | bwd_microstep: 509.86 | bwd_inner_microstep: 509.85 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.23 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1361 +[2025-05-02 00:05:07,119] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 255.05 | bwd_microstep: 384.80 | bwd_inner_microstep: 384.78 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.95 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 336 +[2025-05-02 00:05:07,336] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 76.35 | bwd_microstep: 124.27 | bwd_inner_microstep: 123.71 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.39 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 00:05:08,209] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 344.06 | bwd_microstep: 511.28 | bwd_inner_microstep: 511.26 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 00:05:09,080] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 344.17 | bwd_microstep: 509.25 | bwd_inner_microstep: 509.24 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 00:05:09,949] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 343.08 | bwd_microstep: 507.64 | bwd_inner_microstep: 507.63 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 00:05:10,822] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 347.27 | bwd_microstep: 508.59 | bwd_inner_microstep: 508.57 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.02 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 00:05:11,693] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 345.17 | bwd_microstep: 507.20 | bwd_inner_microstep: 507.19 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 00:05:12,567] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 344.41 | bwd_microstep: 511.96 | bwd_inner_microstep: 511.94 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 00:05:13,432] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 343.85 | bwd_microstep: 503.45 | bwd_inner_microstep: 503.44 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.14 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1958 +[2025-05-02 00:05:14,567] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.47 | optimizer_step: 29.59 +[2025-05-02 00:05:14,567] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 359.35 | bwd_microstep: 721.40 | bwd_inner_microstep: 551.13 | bwd_allreduce_microstep: 170.25 | step_microstep: 37.66 +[2025-05-02 00:05:14,569] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 5173.18 | bwd: 7852.66 | bwd_inner: 7682.14 | bwd_allreduce: 170.31 | step: 53.59 + 8%|▊ | 671/8720 [1:49:48<27:55:50, 12.49s/it] {'loss': 0.8351, 'grad_norm': 3.2388458251953125, 'learning_rate': 9.942414173767076e-06, 'epoch': 0.77} + 8%|▊ | 671/8720 [1:49:48<27:55:50, 12.49s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1930 +[2025-05-02 00:05:15,497] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 362.39 | bwd_microstep: 543.70 | bwd_inner_microstep: 543.68 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.01 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1888 +[2025-05-02 00:05:16,379] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 349.62 | bwd_microstep: 514.13 | bwd_inner_microstep: 514.11 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.14 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-02 00:05:17,253] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 345.44 | bwd_microstep: 509.72 | bwd_inner_microstep: 509.70 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 00:05:18,132] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 344.43 | bwd_microstep: 515.91 | bwd_inner_microstep: 515.89 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.21 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 00:05:19,008] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 349.09 | bwd_microstep: 509.25 | bwd_inner_microstep: 509.23 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.17 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 00:05:19,884] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 347.58 | bwd_microstep: 510.80 | bwd_inner_microstep: 510.78 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 00:05:20,756] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 347.58 | bwd_microstep: 506.26 | bwd_inner_microstep: 506.24 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.12 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 836 +[2025-05-02 00:05:21,172] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 167.18 | bwd_microstep: 233.64 | bwd_inner_microstep: 232.67 | bwd_allreduce_microstep: 0.96 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 00:05:22,051] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 348.68 | bwd_microstep: 510.37 | bwd_inner_microstep: 510.35 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.12 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 323 +[2025-05-02 00:05:22,262] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 77.03 | bwd_microstep: 118.08 | bwd_inner_microstep: 118.07 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.38 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1093 +[2025-05-02 00:05:22,790] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 210.61 | bwd_microstep: 301.36 | bwd_inner_microstep: 300.56 | bwd_allreduce_microstep: 0.78 | step_microstep: 0.39 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1346 +[2025-05-02 00:05:23,461] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 260.92 | bwd_microstep: 392.24 | bwd_inner_microstep: 392.22 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.99 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 00:05:24,340] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 349.20 | bwd_microstep: 511.09 | bwd_inner_microstep: 511.08 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.06 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 318 +[2025-05-02 00:05:24,547] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 75.59 | bwd_microstep: 116.07 | bwd_inner_microstep: 116.06 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.27 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 00:05:25,421] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 346.43 | bwd_microstep: 511.31 | bwd_inner_microstep: 511.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.75 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1915 +[2025-05-02 00:05:26,530] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.50 | optimizer_step: 29.55 +[2025-05-02 00:05:26,531] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 353.74 | bwd_microstep: 701.67 | bwd_inner_microstep: 527.19 | bwd_allreduce_microstep: 174.46 | step_microstep: 37.47 +[2025-05-02 00:05:26,532] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4635.51 | bwd: 7005.61 | bwd_inner: 6829.15 | bwd_allreduce: 176.26 | step: 50.50 + 8%|▊ | 672/8720 [1:50:00<27:34:21, 12.33s/it] {'loss': 0.8905, 'grad_norm': 5.0207109451293945, 'learning_rate': 9.94213278132995e-06, 'epoch': 0.77} + 8%|▊ | 672/8720 [1:50:00<27:34:21, 12.33s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1948 +[2025-05-02 00:05:27,468] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 360.14 | bwd_microstep: 552.91 | bwd_inner_microstep: 552.89 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-02 00:05:28,360] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 352.52 | bwd_microstep: 521.94 | bwd_inner_microstep: 521.92 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.07 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-02 00:05:29,248] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 350.52 | bwd_microstep: 519.50 | bwd_inner_microstep: 519.48 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.33 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1891 +[2025-05-02 00:05:30,135] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 347.50 | bwd_microstep: 521.35 | bwd_inner_microstep: 521.33 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.13 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-02 00:05:31,023] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 351.39 | bwd_microstep: 518.72 | bwd_inner_microstep: 518.70 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.27 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 00:05:31,913] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 352.81 | bwd_microstep: 518.69 | bwd_inner_microstep: 518.67 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.04 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 841 +[2025-05-02 00:05:32,344] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 170.87 | bwd_microstep: 243.40 | bwd_inner_microstep: 243.38 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1355 +[2025-05-02 00:05:33,014] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 260.01 | bwd_microstep: 393.40 | bwd_inner_microstep: 393.38 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.98 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 00:05:33,904] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 352.36 | bwd_microstep: 519.84 | bwd_inner_microstep: 519.82 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.13 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 00:05:34,795] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 352.95 | bwd_microstep: 519.77 | bwd_inner_microstep: 519.75 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.05 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 324 +[2025-05-02 00:05:35,000] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 73.28 | bwd_microstep: 117.09 | bwd_inner_microstep: 117.07 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.17 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 00:05:35,883] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 352.73 | bwd_microstep: 511.72 | bwd_inner_microstep: 511.70 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 00:05:36,770] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 349.55 | bwd_microstep: 517.53 | bwd_inner_microstep: 517.51 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.14 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 00:05:37,668] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 356.58 | bwd_microstep: 520.74 | bwd_inner_microstep: 520.73 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.21 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2024 +[2025-05-02 00:05:38,630] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 376.68 | bwd_microstep: 565.02 | bwd_inner_microstep: 565.00 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.24 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1907 +[2025-05-02 00:05:39,737] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.47 | optimizer_step: 16.52 +[2025-05-02 00:05:39,737] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 357.64 | bwd_microstep: 707.64 | bwd_inner_microstep: 530.30 | bwd_allreduce_microstep: 177.33 | step_microstep: 24.76 +[2025-05-02 00:05:39,738] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 5117.52 | bwd: 7769.26 | bwd_inner: 7591.66 | bwd_allreduce: 177.40 | step: 39.92 + 8%|▊ | 673/8720 [1:50:13<28:09:15, 12.60s/it] {'loss': 1.1948, 'grad_norm': 4.546990871429443, 'learning_rate': 9.941850707058612e-06, 'epoch': 0.77} + 8%|▊ | 673/8720 [1:50:13<28:09:15, 12.60s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1952 +[2025-05-02 00:05:40,679] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 363.98 | bwd_microstep: 553.37 | bwd_inner_microstep: 553.35 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.45 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1941 +[2025-05-02 00:05:41,617] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 367.68 | bwd_microstep: 551.38 | bwd_inner_microstep: 551.36 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.25 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1935 +[2025-05-02 00:05:42,557] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 366.50 | bwd_microstep: 555.47 | bwd_inner_microstep: 555.45 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.21 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1923 +[2025-05-02 00:05:43,492] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 368.89 | bwd_microstep: 547.15 | bwd_inner_microstep: 547.13 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.25 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1889 +[2025-05-02 00:05:44,393] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 357.68 | bwd_microstep: 525.63 | bwd_inner_microstep: 525.61 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-02 00:05:45,294] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 356.47 | bwd_microstep: 526.09 | bwd_inner_microstep: 526.07 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 00:05:46,194] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 360.13 | bwd_microstep: 521.44 | bwd_inner_microstep: 521.42 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.24 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 00:05:47,095] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 357.07 | bwd_microstep: 525.78 | bwd_inner_microstep: 525.76 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 00:05:47,991] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 355.19 | bwd_microstep: 521.38 | bwd_inner_microstep: 521.36 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.30 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 838 +[2025-05-02 00:05:48,416] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 167.97 | bwd_microstep: 240.56 | bwd_inner_microstep: 240.54 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.99 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 00:05:49,319] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 360.48 | bwd_microstep: 523.39 | bwd_inner_microstep: 523.37 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.40 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 325 +[2025-05-02 00:05:49,529] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 78.66 | bwd_microstep: 115.81 | bwd_inner_microstep: 115.67 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 00:05:50,223] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 227.41 | bwd_microstep: 450.33 | bwd_inner_microstep: 450.31 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 00:05:51,094] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 403.25 | bwd_microstep: 449.45 | bwd_inner_microstep: 449.43 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.50 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 00:05:51,899] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 317.52 | bwd_microstep: 456.16 | bwd_inner_microstep: 456.14 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.88 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 00:05:52,886] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.50 | optimizer_step: 17.07 +[2025-05-02 00:05:52,887] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 319.24 | bwd_microstep: 626.31 | bwd_inner_microstep: 469.16 | bwd_allreduce_microstep: 157.13 | step_microstep: 25.07 +[2025-05-02 00:05:52,888] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 5128.10 | bwd: 7689.71 | bwd_inner: 7532.19 | bwd_allreduce: 157.25 | step: 41.98 + 8%|▊ | 674/8720 [1:50:26<28:31:21, 12.76s/it] {'loss': 1.0218, 'grad_norm': 3.94084095954895, 'learning_rate': 9.941567950991977e-06, 'epoch': 0.77} + 8%|▊ | 674/8720 [1:50:26<28:31:21, 12.76s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2068 +[2025-05-02 00:05:53,770] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 343.71 | bwd_microstep: 515.44 | bwd_inner_microstep: 515.43 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.73 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1983 +[2025-05-02 00:05:54,629] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 339.48 | bwd_microstep: 501.84 | bwd_inner_microstep: 501.82 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.30 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 389 +[2025-05-02 00:05:54,847] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 87.15 | bwd_microstep: 115.83 | bwd_inner_microstep: 115.82 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.22 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1897 +[2025-05-02 00:05:55,652] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 316.21 | bwd_microstep: 471.39 | bwd_inner_microstep: 471.37 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.07 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 350 +[2025-05-02 00:05:55,875] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 79.18 | bwd_microstep: 129.03 | bwd_inner_microstep: 129.02 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.37 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1896 +[2025-05-02 00:05:56,686] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 321.00 | bwd_microstep: 472.14 | bwd_inner_microstep: 472.12 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.42 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1883 +[2025-05-02 00:05:57,500] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 324.58 | bwd_microstep: 472.14 | bwd_inner_microstep: 472.12 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.90 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1892 +[2025-05-02 00:05:58,303] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 316.23 | bwd_microstep: 468.55 | bwd_inner_microstep: 468.54 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.88 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 338 +[2025-05-02 00:05:58,515] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 74.66 | bwd_microstep: 122.20 | bwd_inner_microstep: 121.72 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.21 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 00:05:59,320] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 323.54 | bwd_microstep: 465.22 | bwd_inner_microstep: 465.20 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 00:06:00,139] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 329.06 | bwd_microstep: 471.94 | bwd_inner_microstep: 471.92 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.89 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 321 +[2025-05-02 00:06:00,353] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 78.73 | bwd_microstep: 117.16 | bwd_inner_microstep: 117.14 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.22 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 00:06:01,155] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 315.17 | bwd_microstep: 468.66 | bwd_inner_microstep: 468.65 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.90 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 00:06:01,953] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 321.51 | bwd_microstep: 457.81 | bwd_inner_microstep: 457.79 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.89 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 00:06:02,769] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 322.34 | bwd_microstep: 475.41 | bwd_inner_microstep: 475.39 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.72 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1373 +[2025-05-02 00:06:03,565] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.42 | optimizer_step: 16.72 +[2025-05-02 00:06:03,565] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 236.05 | bwd_microstep: 520.67 | bwd_inner_microstep: 363.40 | bwd_allreduce_microstep: 157.26 | step_microstep: 24.47 +[2025-05-02 00:06:03,567] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4128.60 | bwd: 6245.43 | bwd_inner: 6087.45 | bwd_allreduce: 157.32 | step: 36.25 + 8%|▊ | 675/8720 [1:50:37<27:07:20, 12.14s/it] {'loss': 0.9586, 'grad_norm': 3.3983469009399414, 'learning_rate': 9.941284513169059e-06, 'epoch': 0.77} + 8%|▊ | 675/8720 [1:50:37<27:07:20, 12.14s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 435 +[2025-05-02 00:06:03,796] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 82.84 | bwd_microstep: 126.86 | bwd_inner_microstep: 126.48 | bwd_allreduce_microstep: 0.37 | step_microstep: 0.22 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1953 +[2025-05-02 00:06:04,663] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 336.03 | bwd_microstep: 513.21 | bwd_inner_microstep: 513.19 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.91 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 400 +[2025-05-02 00:06:04,877] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 79.41 | bwd_microstep: 119.07 | bwd_inner_microstep: 119.05 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.22 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1918 +[2025-05-02 00:06:05,700] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 322.77 | bwd_microstep: 481.79 | bwd_inner_microstep: 481.77 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.92 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1883 +[2025-05-02 00:06:06,525] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 328.17 | bwd_microstep: 478.17 | bwd_inner_microstep: 478.15 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.89 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-02 00:06:07,333] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 325.95 | bwd_microstep: 464.24 | bwd_inner_microstep: 464.22 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.94 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 00:06:08,155] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 327.31 | bwd_microstep: 476.58 | bwd_inner_microstep: 476.56 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.07 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 00:06:08,962] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 317.81 | bwd_microstep: 471.15 | bwd_inner_microstep: 471.14 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.95 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 00:06:09,781] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 326.16 | bwd_microstep: 474.44 | bwd_inner_microstep: 474.42 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.90 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 00:06:10,601] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 324.81 | bwd_microstep: 476.65 | bwd_inner_microstep: 476.63 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.00 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 00:06:11,418] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 327.07 | bwd_microstep: 472.18 | bwd_inner_microstep: 472.16 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 00:06:12,250] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 328.02 | bwd_microstep: 485.89 | bwd_inner_microstep: 485.87 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.92 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 834 +[2025-05-02 00:06:12,639] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 152.09 | bwd_microstep: 220.51 | bwd_inner_microstep: 219.74 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.24 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 00:06:13,466] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 328.70 | bwd_microstep: 480.86 | bwd_inner_microstep: 480.84 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.93 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 00:06:14,296] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 331.14 | bwd_microstep: 480.92 | bwd_inner_microstep: 480.90 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.30 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 00:06:15,325] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.39 | optimizer_step: 16.76 +[2025-05-02 00:06:15,326] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 329.89 | bwd_microstep: 657.84 | bwd_inner_microstep: 498.28 | bwd_allreduce_microstep: 159.54 | step_microstep: 24.47 +[2025-05-02 00:06:15,327] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4568.19 | bwd: 6880.35 | bwd_inner: 6719.43 | bwd_allreduce: 159.97 | step: 36.93 + 8%|▊ | 676/8720 [1:50:49<26:52:00, 12.02s/it] {'loss': 1.203, 'grad_norm': 4.807995319366455, 'learning_rate': 9.941000393628957e-06, 'epoch': 0.78} + 8%|▊ | 676/8720 [1:50:49<26:52:00, 12.02s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1926 +[2025-05-02 00:06:16,216] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 343.36 | bwd_microstep: 523.11 | bwd_inner_microstep: 523.09 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.90 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-02 00:06:17,055] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 329.37 | bwd_microstep: 492.84 | bwd_inner_microstep: 492.82 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.92 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 00:06:17,893] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 332.68 | bwd_microstep: 486.68 | bwd_inner_microstep: 486.66 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.94 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 00:06:18,731] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 331.71 | bwd_microstep: 488.16 | bwd_inner_microstep: 488.15 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.66 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 337 +[2025-05-02 00:06:18,941] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 75.33 | bwd_microstep: 119.60 | bwd_inner_microstep: 119.58 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.21 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 00:06:19,784] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 332.96 | bwd_microstep: 491.96 | bwd_inner_microstep: 491.94 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.94 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 00:06:20,619] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 333.14 | bwd_microstep: 484.46 | bwd_inner_microstep: 484.44 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.93 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 00:06:21,456] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 332.54 | bwd_microstep: 486.86 | bwd_inner_microstep: 486.84 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.93 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 00:06:22,297] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 331.67 | bwd_microstep: 492.06 | bwd_inner_microstep: 492.05 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.96 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 00:06:23,145] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 333.02 | bwd_microstep: 496.98 | bwd_inner_microstep: 496.96 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.99 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 322 +[2025-05-02 00:06:23,350] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 71.92 | bwd_microstep: 117.32 | bwd_inner_microstep: 117.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.69 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 00:06:24,191] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 333.62 | bwd_microstep: 490.36 | bwd_inner_microstep: 490.34 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.00 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 00:06:25,033] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 330.08 | bwd_microstep: 494.15 | bwd_inner_microstep: 494.14 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.95 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 00:06:25,876] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 331.96 | bwd_microstep: 493.23 | bwd_inner_microstep: 493.21 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.94 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 00:06:26,723] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 335.67 | bwd_microstep: 492.91 | bwd_inner_microstep: 492.89 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 00:06:27,748] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.40 | optimizer_step: 16.46 +[2025-05-02 00:06:27,748] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 334.70 | bwd_microstep: 649.77 | bwd_inner_microstep: 485.71 | bwd_allreduce_microstep: 164.05 | step_microstep: 23.97 +[2025-05-02 00:06:27,749] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4813.73 | bwd: 7300.83 | bwd_inner: 7136.13 | bwd_allreduce: 164.11 | step: 36.55 + 8%|▊ | 677/8720 [1:51:01<27:07:49, 12.14s/it] {'loss': 0.9432, 'grad_norm': 4.850130081176758, 'learning_rate': 9.940715592410875e-06, 'epoch': 0.78} + 8%|▊ | 677/8720 [1:51:01<27:07:49, 12.14s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1913 +[2025-05-02 00:06:28,613] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 340.14 | bwd_microstep: 501.58 | bwd_inner_microstep: 501.56 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.92 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1909 +[2025-05-02 00:06:29,476] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 338.69 | bwd_microstep: 506.28 | bwd_inner_microstep: 506.26 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.11 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 356 +[2025-05-02 00:06:29,699] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 76.69 | bwd_microstep: 130.78 | bwd_inner_microstep: 130.77 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-02 00:06:30,550] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 337.79 | bwd_microstep: 496.44 | bwd_inner_microstep: 496.42 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.95 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-02 00:06:31,406] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 333.21 | bwd_microstep: 504.39 | bwd_inner_microstep: 504.37 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.59 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 00:06:32,260] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 335.29 | bwd_microstep: 499.52 | bwd_inner_microstep: 499.50 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.96 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 00:06:33,109] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 336.06 | bwd_microstep: 495.28 | bwd_inner_microstep: 495.26 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.13 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 331 +[2025-05-02 00:06:33,323] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 78.90 | bwd_microstep: 119.41 | bwd_inner_microstep: 118.88 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.25 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 00:06:34,170] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 333.51 | bwd_microstep: 496.51 | bwd_inner_microstep: 496.49 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.95 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1357 +[2025-05-02 00:06:34,815] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 249.24 | bwd_microstep: 378.07 | bwd_inner_microstep: 378.05 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.89 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 00:06:35,660] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 340.30 | bwd_microstep: 487.11 | bwd_inner_microstep: 487.10 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.00 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 00:06:36,509] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 337.09 | bwd_microstep: 492.98 | bwd_inner_microstep: 492.96 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 00:06:37,359] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 337.13 | bwd_microstep: 492.97 | bwd_inner_microstep: 492.95 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.98 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 00:06:38,208] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 335.34 | bwd_microstep: 495.48 | bwd_inner_microstep: 495.46 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.48 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 828 +[2025-05-02 00:06:38,619] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 160.22 | bwd_microstep: 234.85 | bwd_inner_microstep: 234.83 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.78 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1849 +[2025-05-02 00:06:39,658] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.39 | optimizer_step: 16.58 +[2025-05-02 00:06:39,658] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 337.46 | bwd_microstep: 660.07 | bwd_inner_microstep: 493.81 | bwd_allreduce_microstep: 166.24 | step_microstep: 24.63 +[2025-05-02 00:06:39,659] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4607.08 | bwd: 6991.73 | bwd_inner: 6824.71 | bwd_allreduce: 166.31 | step: 38.02 + 8%|▊ | 678/8720 [1:51:13<26:58:14, 12.07s/it] {'loss': 0.9768, 'grad_norm': 3.857652187347412, 'learning_rate': 9.9404301095541e-06, 'epoch': 0.78} + 8%|▊ | 678/8720 [1:51:13<26:58:14, 12.07s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1950 +[2025-05-02 00:06:40,573] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 357.43 | bwd_microstep: 533.66 | bwd_inner_microstep: 533.64 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.97 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1888 +[2025-05-02 00:06:41,437] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 337.51 | bwd_microstep: 508.06 | bwd_inner_microstep: 508.05 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.97 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 333 +[2025-05-02 00:06:41,646] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 71.74 | bwd_microstep: 121.91 | bwd_inner_microstep: 121.89 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.38 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1360 +[2025-05-02 00:06:42,297] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 253.73 | bwd_microstep: 379.47 | bwd_inner_microstep: 379.45 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.75 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 00:06:43,151] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 338.63 | bwd_microstep: 497.52 | bwd_inner_microstep: 497.50 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.16 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 00:06:44,006] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 336.36 | bwd_microstep: 500.59 | bwd_inner_microstep: 500.57 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 00:06:44,862] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 339.31 | bwd_microstep: 499.39 | bwd_inner_microstep: 499.37 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 00:06:45,727] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 342.47 | bwd_microstep: 504.47 | bwd_inner_microstep: 504.46 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.01 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 00:06:46,584] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 339.50 | bwd_microstep: 500.70 | bwd_inner_microstep: 500.68 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.07 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 00:06:47,445] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 342.10 | bwd_microstep: 501.17 | bwd_inner_microstep: 501.15 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.00 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 00:06:48,305] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 341.36 | bwd_microstep: 500.22 | bwd_inner_microstep: 500.20 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 00:06:49,150] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 330.14 | bwd_microstep: 497.59 | bwd_inner_microstep: 497.57 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.02 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 323 +[2025-05-02 00:06:49,368] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 83.77 | bwd_microstep: 117.75 | bwd_inner_microstep: 117.73 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.22 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 00:06:50,238] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 342.93 | bwd_microstep: 507.55 | bwd_inner_microstep: 507.53 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 00:06:51,096] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 341.28 | bwd_microstep: 499.57 | bwd_inner_microstep: 499.55 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.17 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 00:06:52,151] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.46 | optimizer_step: 16.56 +[2025-05-02 00:06:52,151] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 340.44 | bwd_microstep: 671.82 | bwd_inner_microstep: 502.90 | bwd_allreduce_microstep: 168.90 | step_microstep: 24.67 +[2025-05-02 00:06:52,153] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4838.69 | bwd: 7341.43 | bwd_inner: 7172.26 | bwd_allreduce: 168.97 | step: 37.84 + 8%|▊ | 679/8720 [1:51:25<27:14:55, 12.20s/it] {'loss': 1.0196, 'grad_norm': 5.497163772583008, 'learning_rate': 9.940143945098022e-06, 'epoch': 0.78} + 8%|▊ | 679/8720 [1:51:25<27:14:55, 12.20s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 378 +[2025-05-02 00:06:52,368] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 74.58 | bwd_microstep: 120.63 | bwd_inner_microstep: 120.61 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.38 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1928 +[2025-05-02 00:06:53,272] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 351.37 | bwd_microstep: 534.40 | bwd_inner_microstep: 534.38 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.98 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 353 +[2025-05-02 00:06:53,486] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 82.05 | bwd_microstep: 116.01 | bwd_inner_microstep: 116.00 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.37 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1893 +[2025-05-02 00:06:54,360] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 345.20 | bwd_microstep: 509.42 | bwd_inner_microstep: 509.40 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.22 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-02 00:06:55,228] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 343.31 | bwd_microstep: 507.74 | bwd_inner_microstep: 507.72 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.06 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 349 +[2025-05-02 00:06:55,443] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 82.56 | bwd_microstep: 117.76 | bwd_inner_microstep: 117.74 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 00:06:56,307] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 343.87 | bwd_microstep: 502.43 | bwd_inner_microstep: 502.41 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-02 00:06:57,175] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 341.51 | bwd_microstep: 508.89 | bwd_inner_microstep: 508.87 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-02 00:06:58,050] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 346.74 | bwd_microstep: 511.12 | bwd_inner_microstep: 511.10 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.95 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 00:06:58,915] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 342.80 | bwd_microstep: 504.52 | bwd_inner_microstep: 504.51 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 00:06:59,773] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 338.69 | bwd_microstep: 501.51 | bwd_inner_microstep: 501.49 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 844 +[2025-05-02 00:07:00,201] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 168.70 | bwd_microstep: 243.00 | bwd_inner_microstep: 242.98 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.74 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 00:07:01,072] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 346.26 | bwd_microstep: 506.94 | bwd_inner_microstep: 506.93 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 00:07:01,939] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 344.51 | bwd_microstep: 504.71 | bwd_inner_microstep: 504.69 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.08 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 316 +[2025-05-02 00:07:02,143] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 73.50 | bwd_microstep: 115.91 | bwd_inner_microstep: 115.89 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.25 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1994 +[2025-05-02 00:07:03,277] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.38 | optimizer_gradients: 2.39 | optimizer_step: 29.74 +[2025-05-02 00:07:03,278] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 362.50 | bwd_microstep: 718.46 | bwd_inner_microstep: 549.09 | bwd_allreduce_microstep: 169.36 | step_microstep: 37.49 +[2025-05-02 00:07:03,279] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4288.13 | bwd: 6524.29 | bwd_inner: 6353.83 | bwd_allreduce: 169.42 | step: 49.91 + 8%|▊ | 680/8720 [1:51:37<26:31:34, 11.88s/it] {'loss': 1.087, 'grad_norm': 3.8850913047790527, 'learning_rate': 9.93985709908212e-06, 'epoch': 0.78} + 8%|▊ | 680/8720 [1:51:37<26:31:34, 11.88s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1982 +[2025-05-02 00:07:04,217] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 362.48 | bwd_microstep: 553.20 | bwd_inner_microstep: 553.18 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.00 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1896 +[2025-05-02 00:07:05,097] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 344.19 | bwd_microstep: 517.61 | bwd_inner_microstep: 517.59 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1889 +[2025-05-02 00:07:05,975] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 343.98 | bwd_microstep: 516.16 | bwd_inner_microstep: 516.14 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 00:07:06,855] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 349.75 | bwd_microstep: 512.18 | bwd_inner_microstep: 512.16 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 00:07:07,730] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 343.89 | bwd_microstep: 512.38 | bwd_inner_microstep: 512.36 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 00:07:08,608] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 346.52 | bwd_microstep: 513.62 | bwd_inner_microstep: 513.61 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 00:07:09,484] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 347.93 | bwd_microstep: 511.03 | bwd_inner_microstep: 511.01 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.22 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 00:07:10,364] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 350.61 | bwd_microstep: 510.96 | bwd_inner_microstep: 510.94 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.54 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 00:07:11,240] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 351.31 | bwd_microstep: 506.35 | bwd_inner_microstep: 506.33 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 00:07:12,120] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 348.13 | bwd_microstep: 513.88 | bwd_inner_microstep: 513.86 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.15 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 00:07:12,995] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 350.21 | bwd_microstep: 506.66 | bwd_inner_microstep: 506.65 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 00:07:13,871] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 347.43 | bwd_microstep: 510.06 | bwd_inner_microstep: 510.04 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 00:07:14,747] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 350.31 | bwd_microstep: 506.42 | bwd_inner_microstep: 506.40 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.26 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 00:07:15,625] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 347.26 | bwd_microstep: 511.79 | bwd_inner_microstep: 511.78 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 00:07:16,507] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 349.62 | bwd_microstep: 515.21 | bwd_inner_microstep: 515.19 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 00:07:17,587] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.40 | optimizer_step: 16.59 +[2025-05-02 00:07:17,587] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 347.49 | bwd_microstep: 690.55 | bwd_inner_microstep: 518.87 | bwd_allreduce_microstep: 171.67 | step_microstep: 24.36 +[2025-05-02 00:07:17,588] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 5581.11 | bwd: 8408.07 | bwd_inner: 8236.14 | bwd_allreduce: 171.73 | step: 42.11 + 8%|▊ | 681/8720 [1:51:51<28:09:08, 12.61s/it] {'loss': 1.0075, 'grad_norm': 6.171899318695068, 'learning_rate': 9.939569571545966e-06, 'epoch': 0.78} + 8%|▊ | 681/8720 [1:51:51<28:09:08, 12.61s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1897 +[2025-05-02 00:07:18,486] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 350.60 | bwd_microstep: 523.73 | bwd_inner_microstep: 523.71 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.07 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-02 00:07:19,377] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 352.60 | bwd_microstep: 520.23 | bwd_inner_microstep: 520.21 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.13 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1890 +[2025-05-02 00:07:20,270] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 352.66 | bwd_microstep: 521.27 | bwd_inner_microstep: 521.25 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 00:07:21,159] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 349.18 | bwd_microstep: 519.35 | bwd_inner_microstep: 519.33 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.24 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 00:07:22,052] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 351.91 | bwd_microstep: 519.71 | bwd_inner_microstep: 519.70 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 00:07:22,940] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 349.61 | bwd_microstep: 519.73 | bwd_inner_microstep: 519.71 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.13 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 00:07:23,828] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 349.56 | bwd_microstep: 519.99 | bwd_inner_microstep: 519.97 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.27 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 840 +[2025-05-02 00:07:24,248] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 167.97 | bwd_microstep: 235.80 | bwd_inner_microstep: 235.78 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.75 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 00:07:25,132] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 352.09 | bwd_microstep: 514.29 | bwd_inner_microstep: 514.27 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.13 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 00:07:26,015] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 348.08 | bwd_microstep: 516.28 | bwd_inner_microstep: 516.26 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 00:07:26,909] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 350.76 | bwd_microstep: 524.52 | bwd_inner_microstep: 524.50 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.35 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 320 +[2025-05-02 00:07:27,116] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 75.10 | bwd_microstep: 116.43 | bwd_inner_microstep: 116.41 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 00:07:28,005] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 351.80 | bwd_microstep: 519.27 | bwd_inner_microstep: 519.25 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 00:07:28,886] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 349.27 | bwd_microstep: 512.73 | bwd_inner_microstep: 512.71 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.14 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 00:07:29,775] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 353.40 | bwd_microstep: 517.60 | bwd_inner_microstep: 517.58 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.28 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 00:07:31,146] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.45 | optimizer_step: 16.64 +[2025-05-02 00:07:31,146] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 352.83 | bwd_microstep: 976.84 | bwd_inner_microstep: 519.05 | bwd_allreduce_microstep: 457.78 | step_microstep: 24.56 +[2025-05-02 00:07:31,148] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 5157.21 | bwd: 8077.77 | bwd_inner: 7619.73 | bwd_allreduce: 457.84 | step: 40.93 + 8%|▊ | 682/8720 [1:52:04<28:47:11, 12.89s/it] {'loss': 1.0237, 'grad_norm': 5.66080379486084, 'learning_rate': 9.939281362529232e-06, 'epoch': 0.78} + 8%|▊ | 682/8720 [1:52:04<28:47:11, 12.89s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 383 +[2025-05-02 00:07:31,372] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 79.56 | bwd_microstep: 123.66 | bwd_inner_microstep: 123.15 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.42 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-02 00:07:32,274] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 359.29 | bwd_microstep: 524.50 | bwd_inner_microstep: 524.48 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.14 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 840 +[2025-05-02 00:07:32,698] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 169.24 | bwd_microstep: 237.81 | bwd_inner_microstep: 237.79 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.86 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 00:07:33,602] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 358.59 | bwd_microstep: 524.38 | bwd_inner_microstep: 524.36 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.15 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 00:07:34,496] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 355.39 | bwd_microstep: 520.47 | bwd_inner_microstep: 520.45 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.26 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 00:07:35,395] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 359.19 | bwd_microstep: 521.86 | bwd_inner_microstep: 521.85 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.32 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 00:07:36,289] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 353.88 | bwd_microstep: 521.92 | bwd_inner_microstep: 521.90 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.24 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 00:07:37,193] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 361.16 | bwd_microstep: 522.70 | bwd_inner_microstep: 522.68 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 00:07:38,083] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 356.63 | bwd_microstep: 515.20 | bwd_inner_microstep: 515.19 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 00:07:38,985] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 356.63 | bwd_microstep: 527.27 | bwd_inner_microstep: 527.25 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.24 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 00:07:39,883] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 357.28 | bwd_microstep: 521.89 | bwd_inner_microstep: 521.87 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.27 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 00:07:40,642] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 354.54 | bwd_microstep: 387.18 | bwd_inner_microstep: 387.16 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 00:07:41,356] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 254.77 | bwd_microstep: 442.07 | bwd_inner_microstep: 442.05 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 00:07:42,232] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 382.59 | bwd_microstep: 459.75 | bwd_inner_microstep: 459.74 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.90 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1988 +[2025-05-02 00:07:43,095] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 335.32 | bwd_microstep: 510.29 | bwd_inner_microstep: 510.27 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.90 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-02 00:07:44,085] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.41 | optimizer_step: 20.81 +[2025-05-02 00:07:44,086] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 319.73 | bwd_microstep: 625.45 | bwd_inner_microstep: 468.81 | bwd_allreduce_microstep: 156.62 | step_microstep: 28.59 +[2025-05-02 00:07:44,087] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 5113.77 | bwd: 7486.40 | bwd_inner: 7329.52 | bwd_allreduce: 156.68 | step: 45.07 + 8%|▊ | 683/8720 [1:52:17<28:48:50, 12.91s/it] {'loss': 0.9767, 'grad_norm': 5.860901355743408, 'learning_rate': 9.938992472071677e-06, 'epoch': 0.78} + 8%|▊ | 683/8720 [1:52:17<28:48:50, 12.91s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2001 +[2025-05-02 00:07:44,956] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 336.61 | bwd_microstep: 509.90 | bwd_inner_microstep: 509.88 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.07 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1962 +[2025-05-02 00:07:45,810] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 332.77 | bwd_microstep: 503.90 | bwd_inner_microstep: 503.88 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1928 +[2025-05-02 00:07:46,668] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 335.36 | bwd_microstep: 505.24 | bwd_inner_microstep: 505.22 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1890 +[2025-05-02 00:07:47,477] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 321.91 | bwd_microstep: 466.00 | bwd_inner_microstep: 465.98 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.89 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-02 00:07:48,296] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 322.81 | bwd_microstep: 479.07 | bwd_inner_microstep: 479.05 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.93 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-02 00:07:49,100] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 320.58 | bwd_microstep: 465.02 | bwd_inner_microstep: 465.01 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.41 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 00:07:49,910] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 316.68 | bwd_microstep: 476.49 | bwd_inner_microstep: 476.47 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.91 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 330 +[2025-05-02 00:07:50,128] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 85.67 | bwd_microstep: 114.07 | bwd_inner_microstep: 114.06 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.29 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 00:07:50,940] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 322.80 | bwd_microstep: 473.04 | bwd_inner_microstep: 473.02 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.92 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 00:07:51,754] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 327.30 | bwd_microstep: 469.32 | bwd_inner_microstep: 469.30 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.90 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 00:07:52,572] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 326.13 | bwd_microstep: 474.32 | bwd_inner_microstep: 474.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.91 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 321 +[2025-05-02 00:07:52,803] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 97.04 | bwd_microstep: 115.80 | bwd_inner_microstep: 115.78 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.47 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 321 +[2025-05-02 00:07:53,007] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 74.83 | bwd_microstep: 114.65 | bwd_inner_microstep: 114.63 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.45 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 00:07:53,823] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 326.90 | bwd_microstep: 471.94 | bwd_inner_microstep: 471.92 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.91 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 00:07:54,638] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 326.05 | bwd_microstep: 471.93 | bwd_inner_microstep: 471.91 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.90 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 00:07:55,656] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.44 | optimizer_step: 21.00 +[2025-05-02 00:07:55,657] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 329.75 | bwd_microstep: 639.38 | bwd_inner_microstep: 480.61 | bwd_allreduce_microstep: 158.75 | step_microstep: 28.89 +[2025-05-02 00:07:55,658] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4503.20 | bwd: 6750.08 | bwd_inner: 6591.06 | bwd_allreduce: 158.82 | step: 41.93 + 8%|▊ | 684/8720 [1:52:29<27:54:56, 12.51s/it] {'loss': 0.7797, 'grad_norm': 3.584592580795288, 'learning_rate': 9.938702900213161e-06, 'epoch': 0.78} + 8%|▊ | 684/8720 [1:52:29<27:54:56, 12.51s/it]dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 867 +[2025-05-02 00:07:56,072] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 160.48 | bwd_microstep: 233.54 | bwd_inner_microstep: 233.52 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.55 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-02 00:07:56,903] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 329.00 | bwd_microstep: 484.48 | bwd_inner_microstep: 484.46 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.90 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 341 +[2025-05-02 00:07:57,110] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 79.68 | bwd_microstep: 113.31 | bwd_inner_microstep: 113.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.31 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-02 00:07:57,939] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 330.04 | bwd_microstep: 479.02 | bwd_inner_microstep: 479.00 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 00:07:58,775] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 333.10 | bwd_microstep: 485.13 | bwd_inner_microstep: 485.11 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.10 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1093 +[2025-05-02 00:07:59,273] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.31 | bwd_microstep: 286.93 | bwd_inner_microstep: 286.91 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.67 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 00:08:00,112] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 329.06 | bwd_microstep: 492.13 | bwd_inner_microstep: 492.11 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 00:08:00,929] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 331.13 | bwd_microstep: 464.73 | bwd_inner_microstep: 464.72 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.93 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 00:08:01,761] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 329.80 | bwd_microstep: 485.37 | bwd_inner_microstep: 485.35 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.92 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 00:08:02,606] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 333.18 | bwd_microstep: 493.54 | bwd_inner_microstep: 493.52 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.29 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1355 +[2025-05-02 00:08:03,239] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 246.57 | bwd_microstep: 370.19 | bwd_inner_microstep: 370.17 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.81 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 325 +[2025-05-02 00:08:03,447] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 76.36 | bwd_microstep: 113.61 | bwd_inner_microstep: 113.59 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.30 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 00:08:04,280] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 330.22 | bwd_microstep: 486.25 | bwd_inner_microstep: 486.24 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.96 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 00:08:05,113] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 330.25 | bwd_microstep: 485.12 | bwd_inner_microstep: 485.10 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.96 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1850 +[2025-05-02 00:08:05,942] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 329.65 | bwd_microstep: 482.75 | bwd_inner_microstep: 482.73 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.94 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1850 +[2025-05-02 00:08:06,964] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.41 | optimizer_step: 16.82 +[2025-05-02 00:08:06,964] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 332.86 | bwd_microstep: 644.49 | bwd_inner_microstep: 485.39 | bwd_allreduce_microstep: 159.09 | step_microstep: 23.95 +[2025-05-02 00:08:06,965] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4396.69 | bwd: 6600.59 | bwd_inner: 6441.23 | bwd_allreduce: 159.15 | step: 36.77 + 8%|▊ | 685/8720 [1:52:40<27:06:36, 12.15s/it] {'loss': 1.1498, 'grad_norm': 5.429064750671387, 'learning_rate': 9.938412646993632e-06, 'epoch': 0.79} + 8%|▊ | 685/8720 [1:52:40<27:06:36, 12.15s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1894 +[2025-05-02 00:08:07,821] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 339.24 | bwd_microstep: 493.99 | bwd_inner_microstep: 493.97 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.91 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1888 +[2025-05-02 00:08:08,673] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 338.47 | bwd_microstep: 495.81 | bwd_inner_microstep: 495.79 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.94 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1886 +[2025-05-02 00:08:09,521] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 333.85 | bwd_microstep: 497.59 | bwd_inner_microstep: 497.57 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.92 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-02 00:08:10,365] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 332.43 | bwd_microstep: 490.12 | bwd_inner_microstep: 490.11 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.96 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 337 +[2025-05-02 00:08:10,568] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 72.53 | bwd_microstep: 116.32 | bwd_inner_microstep: 116.30 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.31 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 00:08:11,419] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 334.02 | bwd_microstep: 498.12 | bwd_inner_microstep: 498.10 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.95 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 00:08:12,264] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 333.79 | bwd_microstep: 492.54 | bwd_inner_microstep: 492.52 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.94 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 00:08:13,117] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 335.18 | bwd_microstep: 496.63 | bwd_inner_microstep: 496.61 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 00:08:13,962] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 331.82 | bwd_microstep: 495.67 | bwd_inner_microstep: 495.65 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.92 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 834 +[2025-05-02 00:08:14,361] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 159.09 | bwd_microstep: 224.83 | bwd_inner_microstep: 224.81 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.78 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 00:08:15,214] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 335.70 | bwd_microstep: 499.42 | bwd_inner_microstep: 499.40 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.94 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 00:08:16,063] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 334.93 | bwd_microstep: 492.93 | bwd_inner_microstep: 492.92 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.13 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1345 +[2025-05-02 00:08:16,702] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 246.08 | bwd_microstep: 376.16 | bwd_inner_microstep: 376.14 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.68 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 00:08:17,544] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 334.97 | bwd_microstep: 489.81 | bwd_inner_microstep: 489.79 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.98 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 00:08:18,387] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 335.53 | bwd_microstep: 490.71 | bwd_inner_microstep: 490.69 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1849 +[2025-05-02 00:08:19,428] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.34 | optimizer_step: 16.54 +[2025-05-02 00:08:19,429] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 336.21 | bwd_microstep: 659.50 | bwd_inner_microstep: 495.93 | bwd_allreduce_microstep: 163.56 | step_microstep: 25.39 +[2025-05-02 00:08:19,430] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4833.61 | bwd: 7310.15 | bwd_inner: 7146.33 | bwd_allreduce: 163.62 | step: 38.91 + 8%|▊ | 686/8720 [1:52:53<27:19:12, 12.24s/it] {'loss': 1.3075, 'grad_norm': 7.645816326141357, 'learning_rate': 9.938121712453134e-06, 'epoch': 0.79} + 8%|▊ | 686/8720 [1:52:53<27:19:12, 12.24s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-02 00:08:20,286] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 337.29 | bwd_microstep: 496.47 | bwd_inner_microstep: 496.45 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.92 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 00:08:21,138] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 335.84 | bwd_microstep: 498.81 | bwd_inner_microstep: 498.80 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.02 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 840 +[2025-05-02 00:08:21,538] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 159.76 | bwd_microstep: 224.54 | bwd_inner_microstep: 224.52 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.67 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 00:08:22,393] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 336.50 | bwd_microstep: 497.54 | bwd_inner_microstep: 497.52 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.98 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1109 +[2025-05-02 00:08:22,840] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 200.28 | bwd_microstep: 230.19 | bwd_inner_microstep: 230.17 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 325 +[2025-05-02 00:08:23,039] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 67.80 | bwd_microstep: 117.62 | bwd_inner_microstep: 117.50 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 00:08:23,515] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.03 | bwd_microstep: 273.45 | bwd_inner_microstep: 273.43 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 00:08:23,997] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.30 | bwd_microstep: 273.53 | bwd_inner_microstep: 273.51 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1346 +[2025-05-02 00:08:24,363] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 143.20 | bwd_microstep: 206.65 | bwd_inner_microstep: 206.63 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 319 +[2025-05-02 00:08:24,563] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 68.46 | bwd_microstep: 118.42 | bwd_inner_microstep: 118.28 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 00:08:25,039] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.48 | bwd_microstep: 273.28 | bwd_inner_microstep: 273.27 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 00:08:25,514] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.60 | bwd_microstep: 271.41 | bwd_inner_microstep: 271.39 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 00:08:25,989] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.58 | bwd_microstep: 271.39 | bwd_inner_microstep: 271.38 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 00:08:26,464] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.28 | bwd_microstep: 272.02 | bwd_inner_microstep: 272.00 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 00:08:26,937] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.50 | bwd_microstep: 270.96 | bwd_inner_microstep: 270.94 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 00:08:27,502] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.36 | optimizer_step: 16.26 +[2025-05-02 00:08:27,502] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.35 | bwd_microstep: 338.31 | bwd_inner_microstep: 271.61 | bwd_allreduce_microstep: 66.66 | step_microstep: 23.63 +[2025-05-02 00:08:27,503] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 3156.08 | bwd: 4634.65 | bwd_inner: 4567.48 | bwd_allreduce: 66.83 | step: 27.77 + 8%|▊ | 687/8720 [1:53:01<24:31:32, 10.99s/it] {'loss': 0.894, 'grad_norm': 6.115693092346191, 'learning_rate': 9.937830096631806e-06, 'epoch': 0.79} + 8%|▊ | 687/8720 [1:53:01<24:31:32, 10.99s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1952 +[2025-05-02 00:08:28,008] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.89 | bwd_microstep: 289.01 | bwd_inner_microstep: 288.99 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 380 +[2025-05-02 00:08:28,211] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 72.12 | bwd_microstep: 118.17 | bwd_inner_microstep: 118.04 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-02 00:08:28,689] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.59 | bwd_microstep: 274.54 | bwd_inner_microstep: 274.52 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 00:08:29,166] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.29 | bwd_microstep: 273.19 | bwd_inner_microstep: 273.17 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 00:08:29,642] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.42 | bwd_microstep: 273.31 | bwd_inner_microstep: 273.29 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 843 +[2025-05-02 00:08:29,881] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.30 | bwd_microstep: 132.04 | bwd_inner_microstep: 132.02 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 00:08:30,356] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.83 | bwd_microstep: 272.48 | bwd_inner_microstep: 272.47 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 00:08:30,833] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.54 | bwd_microstep: 273.27 | bwd_inner_microstep: 273.25 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 00:08:31,310] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.07 | bwd_microstep: 273.53 | bwd_inner_microstep: 273.51 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 00:08:31,787] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.13 | bwd_microstep: 272.93 | bwd_inner_microstep: 272.91 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 323 +[2025-05-02 00:08:31,985] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 67.61 | bwd_microstep: 117.32 | bwd_inner_microstep: 117.19 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 00:08:32,459] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.53 | bwd_microstep: 271.98 | bwd_inner_microstep: 271.96 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 317 +[2025-05-02 00:08:32,657] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 69.61 | bwd_microstep: 114.52 | bwd_inner_microstep: 114.40 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 00:08:33,130] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.39 | bwd_microstep: 271.20 | bwd_inner_microstep: 271.18 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 00:08:33,604] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.73 | bwd_microstep: 271.25 | bwd_inner_microstep: 271.23 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 00:08:34,173] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.41 | optimizer_step: 20.96 +[2025-05-02 00:08:34,174] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.84 | bwd_microstep: 338.05 | bwd_inner_microstep: 272.04 | bwd_allreduce_microstep: 65.97 | step_microstep: 28.45 +[2025-05-02 00:08:34,175] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2570.64 | bwd: 3836.83 | bwd_inner: 3770.26 | bwd_allreduce: 66.18 | step: 29.23 + 8%|▊ | 688/8720 [1:53:07<21:37:53, 9.70s/it] {'loss': 0.737, 'grad_norm': 4.192381381988525, 'learning_rate': 9.93753779956988e-06, 'epoch': 0.79} + 8%|▊ | 688/8720 [1:53:07<21:37:53, 9.70s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1934 +[2025-05-02 00:08:34,679] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 196.49 | bwd_microstep: 287.40 | bwd_inner_microstep: 287.39 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1899 +[2025-05-02 00:08:35,159] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.69 | bwd_microstep: 275.67 | bwd_inner_microstep: 275.66 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1890 +[2025-05-02 00:08:35,637] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.71 | bwd_microstep: 274.59 | bwd_inner_microstep: 274.57 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-02 00:08:36,115] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.29 | bwd_microstep: 274.20 | bwd_inner_microstep: 274.18 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-02 00:08:36,593] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.51 | bwd_microstep: 274.48 | bwd_inner_microstep: 274.46 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 337 +[2025-05-02 00:08:36,798] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 69.31 | bwd_microstep: 121.62 | bwd_inner_microstep: 121.50 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-02 00:08:37,274] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.72 | bwd_microstep: 273.77 | bwd_inner_microstep: 273.76 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-02 00:08:37,752] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.51 | bwd_microstep: 274.12 | bwd_inner_microstep: 274.10 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 00:08:38,229] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.97 | bwd_microstep: 272.94 | bwd_inner_microstep: 272.92 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 00:08:38,707] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.37 | bwd_microstep: 273.54 | bwd_inner_microstep: 273.53 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 332 +[2025-05-02 00:08:38,909] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 71.11 | bwd_microstep: 117.36 | bwd_inner_microstep: 117.23 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 00:08:39,386] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.49 | bwd_microstep: 272.97 | bwd_inner_microstep: 272.95 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 833 +[2025-05-02 00:08:39,618] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 92.01 | bwd_microstep: 126.03 | bwd_inner_microstep: 126.02 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 829 +[2025-05-02 00:08:39,854] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 91.96 | bwd_microstep: 130.32 | bwd_inner_microstep: 130.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 00:08:40,328] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.64 | bwd_microstep: 271.32 | bwd_inner_microstep: 271.31 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 00:08:40,898] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.47 | optimizer_step: 21.02 +[2025-05-02 00:08:40,899] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.63 | bwd_microstep: 338.08 | bwd_inner_microstep: 271.68 | bwd_allreduce_microstep: 66.35 | step_microstep: 28.60 +[2025-05-02 00:08:40,900] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2594.17 | bwd: 3858.46 | bwd_inner: 3791.59 | bwd_allreduce: 66.52 | step: 29.43 + 8%|▊ | 689/8720 [1:53:14<19:38:26, 8.80s/it] {'loss': 1.062, 'grad_norm': 4.791027545928955, 'learning_rate': 9.937244821307685e-06, 'epoch': 0.79} + 8%|▊ | 689/8720 [1:53:14<19:38:26, 8.80s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1924 +[2025-05-02 00:08:41,401] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 194.93 | bwd_microstep: 286.76 | bwd_inner_microstep: 286.75 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 358 +[2025-05-02 00:08:41,616] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 79.17 | bwd_microstep: 122.12 | bwd_inner_microstep: 121.99 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-02 00:08:42,093] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.75 | bwd_microstep: 273.66 | bwd_inner_microstep: 273.64 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 339 +[2025-05-02 00:08:42,296] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 69.29 | bwd_microstep: 120.30 | bwd_inner_microstep: 120.18 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-02 00:08:42,773] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.99 | bwd_microstep: 274.26 | bwd_inner_microstep: 274.25 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-02 00:08:43,251] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.02 | bwd_microstep: 273.93 | bwd_inner_microstep: 273.92 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 00:08:43,728] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.74 | bwd_microstep: 272.32 | bwd_inner_microstep: 272.30 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 00:08:44,205] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.22 | bwd_microstep: 273.30 | bwd_inner_microstep: 273.28 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 00:08:44,682] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.98 | bwd_microstep: 272.74 | bwd_inner_microstep: 272.72 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 837 +[2025-05-02 00:08:44,914] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 91.28 | bwd_microstep: 126.32 | bwd_inner_microstep: 126.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1093 +[2025-05-02 00:08:45,204] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 115.03 | bwd_microstep: 161.19 | bwd_inner_microstep: 161.17 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1351 +[2025-05-02 00:08:45,565] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.75 | bwd_microstep: 205.96 | bwd_inner_microstep: 205.94 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 00:08:46,042] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.81 | bwd_microstep: 272.34 | bwd_inner_microstep: 272.32 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 00:08:46,517] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.18 | bwd_microstep: 271.25 | bwd_inner_microstep: 271.24 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 828 +[2025-05-02 00:08:46,753] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 92.06 | bwd_microstep: 130.48 | bwd_inner_microstep: 130.46 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 00:08:47,317] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.43 | optimizer_step: 16.33 +[2025-05-02 00:08:47,317] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.43 | bwd_microstep: 337.86 | bwd_inner_microstep: 271.75 | bwd_allreduce_microstep: 66.06 | step_microstep: 23.82 +[2025-05-02 00:08:47,319] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2478.34 | bwd: 3674.83 | bwd_inner: 3608.24 | bwd_allreduce: 66.24 | step: 24.60 + 8%|▊ | 690/8720 [1:53:21<18:02:31, 8.09s/it] {'loss': 1.1934, 'grad_norm': 5.767274379730225, 'learning_rate': 9.936951161885637e-06, 'epoch': 0.79} + 8%|▊ | 690/8720 [1:53:21<18:02:31, 8.09s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 504 +[2025-05-02 00:08:47,523] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 71.99 | bwd_microstep: 114.44 | bwd_inner_microstep: 114.29 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1997 +[2025-05-02 00:08:48,030] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 197.24 | bwd_microstep: 294.47 | bwd_inner_microstep: 294.45 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1944 +[2025-05-02 00:08:48,530] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.92 | bwd_microstep: 288.68 | bwd_inner_microstep: 288.66 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1902 +[2025-05-02 00:08:49,012] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 191.73 | bwd_microstep: 275.86 | bwd_inner_microstep: 275.84 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 864 +[2025-05-02 00:08:49,256] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 96.27 | bwd_microstep: 133.64 | bwd_inner_microstep: 133.51 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1887 +[2025-05-02 00:08:49,737] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.37 | bwd_microstep: 275.39 | bwd_inner_microstep: 275.37 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-02 00:08:50,219] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.28 | bwd_microstep: 274.13 | bwd_inner_microstep: 274.11 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 00:08:50,701] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.53 | bwd_microstep: 272.78 | bwd_inner_microstep: 272.76 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 00:08:51,185] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.79 | bwd_microstep: 273.25 | bwd_inner_microstep: 273.23 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 842 +[2025-05-02 00:08:51,433] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 98.17 | bwd_microstep: 132.54 | bwd_inner_microstep: 132.31 | bwd_allreduce_microstep: 0.09 | step_microstep: 0.23 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 00:08:51,913] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.10 | bwd_microstep: 273.44 | bwd_inner_microstep: 273.42 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 00:08:52,395] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.38 | bwd_microstep: 272.91 | bwd_inner_microstep: 272.89 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 00:08:52,878] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.97 | bwd_microstep: 272.58 | bwd_inner_microstep: 272.56 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.14 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 318 +[2025-05-02 00:08:53,120] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.48 | bwd_microstep: 127.19 | bwd_inner_microstep: 127.04 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 317 +[2025-05-02 00:08:53,341] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 87.18 | bwd_microstep: 118.03 | bwd_inner_microstep: 117.73 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1942 +[2025-05-02 00:08:53,947] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.07 | optimizer_gradients: 2.45 | optimizer_step: 16.55 +[2025-05-02 00:08:53,947] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 197.73 | bwd_microstep: 366.18 | bwd_inner_microstep: 289.55 | bwd_allreduce_microstep: 76.57 | step_microstep: 24.71 +[2025-05-02 00:08:53,949] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2553.73 | bwd: 3765.59 | bwd_inner: 3687.92 | bwd_allreduce: 77.04 | step: 25.90 + 8%|▊ | 691/8720 [1:53:27<17:03:54, 7.65s/it] {'loss': 1.2032, 'grad_norm': 5.992283344268799, 'learning_rate': 9.936656821344255e-06, 'epoch': 0.79} + 8%|▊ | 691/8720 [1:53:27<17:03:54, 7.65s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1887 +[2025-05-02 00:08:54,435] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.63 | bwd_microstep: 274.07 | bwd_inner_microstep: 274.04 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.13 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1379 +[2025-05-02 00:08:54,805] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 143.76 | bwd_microstep: 208.30 | bwd_inner_microstep: 208.26 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 344 +[2025-05-02 00:08:55,058] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 92.48 | bwd_microstep: 143.74 | bwd_inner_microstep: 143.43 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.15 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1883 +[2025-05-02 00:08:55,539] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.07 | bwd_microstep: 274.37 | bwd_inner_microstep: 274.36 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 00:08:56,023] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.67 | bwd_microstep: 274.09 | bwd_inner_microstep: 274.07 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 00:08:56,505] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.47 | bwd_microstep: 273.38 | bwd_inner_microstep: 273.36 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 00:08:56,985] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.83 | bwd_microstep: 273.77 | bwd_inner_microstep: 273.76 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-02 00:08:57,466] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.44 | bwd_microstep: 274.40 | bwd_inner_microstep: 274.38 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 842 +[2025-05-02 00:08:57,713] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.63 | bwd_microstep: 132.21 | bwd_inner_microstep: 131.91 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 00:08:58,191] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.61 | bwd_microstep: 272.52 | bwd_inner_microstep: 272.50 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 00:08:58,670] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.27 | bwd_microstep: 272.62 | bwd_inner_microstep: 272.60 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 00:08:59,150] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.06 | bwd_microstep: 272.22 | bwd_inner_microstep: 272.20 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 00:08:59,630] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.99 | bwd_microstep: 272.46 | bwd_inner_microstep: 272.44 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 00:09:00,109] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.25 | bwd_microstep: 272.76 | bwd_inner_microstep: 272.74 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 319 +[2025-05-02 00:09:00,323] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 81.10 | bwd_microstep: 117.46 | bwd_inner_microstep: 117.32 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 00:09:00,924] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.56 | optimizer_step: 16.75 +[2025-05-02 00:09:00,924] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.92 | bwd_microstep: 371.80 | bwd_inner_microstep: 271.67 | bwd_allreduce_microstep: 100.06 | step_microstep: 26.41 +[2025-05-02 00:09:00,925] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2675.84 | bwd: 3980.26 | bwd_inner: 3879.19 | bwd_allreduce: 100.45 | step: 27.58 + 8%|▊ | 692/8720 [1:53:34<16:36:38, 7.45s/it] {'loss': 0.7345, 'grad_norm': 5.314786434173584, 'learning_rate': 9.936361799724141e-06, 'epoch': 0.79} + 8%|▊ | 692/8720 [1:53:34<16:36:38, 7.45s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1968 +[2025-05-02 00:09:01,435] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 198.04 | bwd_microstep: 290.51 | bwd_inner_microstep: 290.49 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1925 +[2025-05-02 00:09:01,934] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.23 | bwd_microstep: 287.68 | bwd_inner_microstep: 287.67 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 381 +[2025-05-02 00:09:02,169] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.67 | bwd_microstep: 125.21 | bwd_inner_microstep: 124.88 | bwd_allreduce_microstep: 0.14 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1903 +[2025-05-02 00:09:02,649] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.94 | bwd_microstep: 276.07 | bwd_inner_microstep: 276.05 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1887 +[2025-05-02 00:09:03,129] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.22 | bwd_microstep: 274.50 | bwd_inner_microstep: 274.48 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-02 00:09:03,607] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.47 | bwd_microstep: 274.74 | bwd_inner_microstep: 274.72 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-02 00:09:04,086] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.92 | bwd_microstep: 274.39 | bwd_inner_microstep: 274.37 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.05 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 838 +[2025-05-02 00:09:04,330] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 102.72 | bwd_microstep: 125.62 | bwd_inner_microstep: 125.60 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 00:09:04,806] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.29 | bwd_microstep: 272.77 | bwd_inner_microstep: 272.75 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1091 +[2025-05-02 00:09:05,097] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 115.80 | bwd_microstep: 160.89 | bwd_inner_microstep: 160.71 | bwd_allreduce_microstep: 0.10 | step_microstep: 0.10 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 329 +[2025-05-02 00:09:05,316] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 82.58 | bwd_microstep: 119.31 | bwd_inner_microstep: 118.97 | bwd_allreduce_microstep: 0.14 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 00:09:05,794] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.43 | bwd_microstep: 273.30 | bwd_inner_microstep: 273.28 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 00:09:06,272] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.72 | bwd_microstep: 272.63 | bwd_inner_microstep: 272.61 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 00:09:06,747] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.89 | bwd_microstep: 271.94 | bwd_inner_microstep: 271.93 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 00:09:07,222] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.66 | bwd_microstep: 271.06 | bwd_inner_microstep: 271.04 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1911 +[2025-05-02 00:09:07,810] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.40 | optimizer_step: 31.02 +[2025-05-02 00:09:07,810] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.19 | bwd_microstep: 343.94 | bwd_inner_microstep: 277.10 | bwd_allreduce_microstep: 66.79 | step_microstep: 38.45 +[2025-05-02 00:09:07,812] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2675.45 | bwd: 3914.63 | bwd_inner: 3846.80 | bwd_allreduce: 67.22 | step: 39.66 + 8%|▊ | 693/8720 [1:53:41<16:13:54, 7.28s/it] {'loss': 0.8664, 'grad_norm': 4.283771514892578, 'learning_rate': 9.936066097066003e-06, 'epoch': 0.79} + 8%|▊ | 693/8720 [1:53:41<16:13:54, 7.28s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1958 +[2025-05-02 00:09:08,317] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 196.01 | bwd_microstep: 289.93 | bwd_inner_microstep: 289.91 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1904 +[2025-05-02 00:09:08,799] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.36 | bwd_microstep: 276.49 | bwd_inner_microstep: 276.47 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-02 00:09:09,279] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.01 | bwd_microstep: 274.82 | bwd_inner_microstep: 274.80 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-02 00:09:09,758] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.84 | bwd_microstep: 273.82 | bwd_inner_microstep: 273.80 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-02 00:09:10,238] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.96 | bwd_microstep: 273.79 | bwd_inner_microstep: 273.77 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 00:09:10,715] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.41 | bwd_microstep: 272.93 | bwd_inner_microstep: 272.91 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 00:09:11,192] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.66 | bwd_microstep: 272.83 | bwd_inner_microstep: 272.81 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 00:09:11,670] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.61 | bwd_microstep: 273.15 | bwd_inner_microstep: 273.13 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 00:09:12,147] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.81 | bwd_microstep: 273.35 | bwd_inner_microstep: 273.33 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 329 +[2025-05-02 00:09:12,352] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 74.64 | bwd_microstep: 116.84 | bwd_inner_microstep: 116.71 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 00:09:12,828] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.02 | bwd_microstep: 273.21 | bwd_inner_microstep: 273.19 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 00:09:13,304] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.00 | bwd_microstep: 272.57 | bwd_inner_microstep: 272.56 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 00:09:13,781] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.88 | bwd_microstep: 272.77 | bwd_inner_microstep: 272.76 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 00:09:14,258] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.70 | bwd_microstep: 271.33 | bwd_inner_microstep: 271.32 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 00:09:14,735] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.11 | bwd_microstep: 272.51 | bwd_inner_microstep: 272.49 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 00:09:15,306] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.38 | optimizer_step: 16.59 +[2025-05-02 00:09:15,306] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.55 | bwd_microstep: 341.60 | bwd_inner_microstep: 274.47 | bwd_allreduce_microstep: 67.08 | step_microstep: 23.98 +[2025-05-02 00:09:15,307] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2918.28 | bwd: 4301.96 | bwd_inner: 4234.46 | bwd_allreduce: 67.22 | step: 25.02 + 8%|▊ | 694/8720 [1:53:49<16:22:27, 7.34s/it] {'loss': 1.2242, 'grad_norm': 5.231097221374512, 'learning_rate': 9.935769713410636e-06, 'epoch': 0.8} + 8%|▊ | 694/8720 [1:53:49<16:22:27, 7.34s/it]dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1360 +[2025-05-02 00:09:15,675] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 142.07 | bwd_microstep: 206.21 | bwd_inner_microstep: 206.19 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-02 00:09:16,154] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.49 | bwd_microstep: 273.73 | bwd_inner_microstep: 273.72 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 00:09:16,634] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.07 | bwd_microstep: 274.30 | bwd_inner_microstep: 274.28 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-02 00:09:17,112] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.82 | bwd_microstep: 273.70 | bwd_inner_microstep: 273.69 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-02 00:09:17,596] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.56 | bwd_microstep: 275.13 | bwd_inner_microstep: 275.12 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 00:09:18,078] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.34 | bwd_microstep: 274.50 | bwd_inner_microstep: 274.48 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 00:09:18,558] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.10 | bwd_microstep: 272.89 | bwd_inner_microstep: 272.88 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 00:09:19,036] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.10 | bwd_microstep: 272.37 | bwd_inner_microstep: 272.35 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 00:09:19,513] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.43 | bwd_microstep: 272.77 | bwd_inner_microstep: 272.75 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 839 +[2025-05-02 00:09:19,762] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 107.09 | bwd_microstep: 125.64 | bwd_inner_microstep: 125.51 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 00:09:20,240] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.76 | bwd_microstep: 272.17 | bwd_inner_microstep: 272.15 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 00:09:20,719] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.31 | bwd_microstep: 272.53 | bwd_inner_microstep: 272.51 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 00:09:21,196] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.43 | bwd_microstep: 270.96 | bwd_inner_microstep: 270.95 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 00:09:21,673] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.88 | bwd_microstep: 270.97 | bwd_inner_microstep: 270.95 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 00:09:22,152] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.64 | bwd_microstep: 270.91 | bwd_inner_microstep: 270.89 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 00:09:22,751] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.37 | optimizer_step: 16.54 +[2025-05-02 00:09:22,751] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.92 | bwd_microstep: 368.18 | bwd_inner_microstep: 272.01 | bwd_allreduce_microstep: 96.13 | step_microstep: 25.22 +[2025-05-02 00:09:22,753] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2898.68 | bwd: 4247.00 | bwd_inner: 4150.42 | bwd_allreduce: 96.27 | step: 26.11 + 8%|▊ | 695/8720 [1:53:56<16:26:22, 7.37s/it] {'loss': 1.2911, 'grad_norm': 8.880066871643066, 'learning_rate': 9.935472648798928e-06, 'epoch': 0.8} + 8%|▊ | 695/8720 [1:53:56<16:26:22, 7.37s/it]dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1708 +[2025-05-02 00:09:23,189] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 160.92 | bwd_microstep: 256.04 | bwd_inner_microstep: 256.00 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1946 +[2025-05-02 00:09:23,692] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 197.71 | bwd_microstep: 289.39 | bwd_inner_microstep: 289.38 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1906 +[2025-05-02 00:09:24,176] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.96 | bwd_microstep: 276.56 | bwd_inner_microstep: 276.54 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1903 +[2025-05-02 00:09:24,659] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.87 | bwd_microstep: 275.95 | bwd_inner_microstep: 275.93 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 357 +[2025-05-02 00:09:24,871] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 82.67 | bwd_microstep: 116.26 | bwd_inner_microstep: 116.01 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.09 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 856 +[2025-05-02 00:09:25,118] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 99.83 | bwd_microstep: 133.35 | bwd_inner_microstep: 133.12 | bwd_allreduce_microstep: 0.14 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 00:09:25,595] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.71 | bwd_microstep: 272.80 | bwd_inner_microstep: 272.78 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 00:09:26,074] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.45 | bwd_microstep: 273.43 | bwd_inner_microstep: 273.41 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1356 +[2025-05-02 00:09:26,437] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 142.18 | bwd_microstep: 206.33 | bwd_inner_microstep: 206.32 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 00:09:26,915] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.70 | bwd_microstep: 272.79 | bwd_inner_microstep: 272.76 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 00:09:27,393] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.39 | bwd_microstep: 272.59 | bwd_inner_microstep: 272.57 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 00:09:27,870] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.52 | bwd_microstep: 272.86 | bwd_inner_microstep: 272.84 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 00:09:28,345] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.59 | bwd_microstep: 271.25 | bwd_inner_microstep: 271.23 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 00:09:28,821] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.37 | bwd_microstep: 272.31 | bwd_inner_microstep: 272.29 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 00:09:29,295] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.98 | bwd_microstep: 271.11 | bwd_inner_microstep: 271.09 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 00:09:29,882] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.40 | optimizer_step: 16.51 +[2025-05-02 00:09:29,882] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.21 | bwd_microstep: 357.90 | bwd_inner_microstep: 272.65 | bwd_allreduce_microstep: 85.20 | step_microstep: 25.35 +[2025-05-02 00:09:29,883] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2763.75 | bwd: 4090.96 | bwd_inner: 4004.99 | bwd_allreduce: 85.47 | step: 26.39 + 8%|▊ | 696/8720 [1:54:03<16:16:28, 7.30s/it] {'loss': 1.3743, 'grad_norm': 7.176342964172363, 'learning_rate': 9.935174903271864e-06, 'epoch': 0.8} + 8%|▊ | 696/8720 [1:54:03<16:16:28, 7.30s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1948 +[2025-05-02 00:09:30,389] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 196.09 | bwd_microstep: 289.39 | bwd_inner_microstep: 289.34 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1910 +[2025-05-02 00:09:30,877] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 192.10 | bwd_microstep: 279.12 | bwd_inner_microstep: 279.07 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1893 +[2025-05-02 00:09:31,362] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.85 | bwd_microstep: 277.27 | bwd_inner_microstep: 277.23 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 00:09:31,844] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.23 | bwd_microstep: 274.07 | bwd_inner_microstep: 274.05 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 00:09:32,322] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.85 | bwd_microstep: 273.08 | bwd_inner_microstep: 273.07 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 00:09:32,802] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.24 | bwd_microstep: 273.08 | bwd_inner_microstep: 273.07 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.21 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 00:09:33,282] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.78 | bwd_microstep: 273.52 | bwd_inner_microstep: 273.50 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 00:09:33,763] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.96 | bwd_microstep: 272.95 | bwd_inner_microstep: 272.93 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 331 +[2025-05-02 00:09:34,007] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 112.73 | bwd_microstep: 113.86 | bwd_inner_microstep: 113.64 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 00:09:34,486] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.19 | bwd_microstep: 272.80 | bwd_inner_microstep: 272.79 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.20 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1353 +[2025-05-02 00:09:34,855] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 142.11 | bwd_microstep: 206.17 | bwd_inner_microstep: 206.08 | bwd_allreduce_microstep: 0.04 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 00:09:35,337] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.13 | bwd_microstep: 272.11 | bwd_inner_microstep: 272.09 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 00:09:35,815] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.62 | bwd_microstep: 272.33 | bwd_inner_microstep: 272.31 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 322 +[2025-05-02 00:09:36,057] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.47 | bwd_microstep: 130.28 | bwd_inner_microstep: 130.13 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 835 +[2025-05-02 00:09:36,296] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 98.46 | bwd_microstep: 125.85 | bwd_inner_microstep: 125.77 | bwd_allreduce_microstep: 0.03 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 00:09:36,882] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.36 | optimizer_step: 16.70 +[2025-05-02 00:09:36,882] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.50 | bwd_microstep: 356.95 | bwd_inner_microstep: 272.50 | bwd_allreduce_microstep: 84.40 | step_microstep: 25.44 +[2025-05-02 00:09:36,884] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2726.94 | bwd: 3962.91 | bwd_inner: 3877.68 | bwd_allreduce: 84.72 | step: 26.93 + 8%|▊ | 697/8720 [1:54:10<16:04:15, 7.21s/it] {'loss': 0.7437, 'grad_norm': 8.861610412597656, 'learning_rate': 9.934876476870525e-06, 'epoch': 0.8} + 8%|▊ | 697/8720 [1:54:10<16:04:15, 7.21s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1921 +[2025-05-02 00:09:37,386] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.64 | bwd_microstep: 286.20 | bwd_inner_microstep: 286.18 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.20 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 360 +[2025-05-02 00:09:37,610] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 91.93 | bwd_microstep: 118.07 | bwd_inner_microstep: 117.69 | bwd_allreduce_microstep: 0.15 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1891 +[2025-05-02 00:09:38,091] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.57 | bwd_microstep: 275.41 | bwd_inner_microstep: 275.39 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-02 00:09:38,571] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.40 | bwd_microstep: 275.10 | bwd_inner_microstep: 275.08 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-02 00:09:39,054] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.42 | bwd_microstep: 274.41 | bwd_inner_microstep: 274.39 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-02 00:09:39,533] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.57 | bwd_microstep: 274.38 | bwd_inner_microstep: 274.37 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.22 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 00:09:40,012] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.17 | bwd_microstep: 272.82 | bwd_inner_microstep: 272.80 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 00:09:40,493] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.44 | bwd_microstep: 273.28 | bwd_inner_microstep: 273.26 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 853 +[2025-05-02 00:09:40,757] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 114.11 | bwd_microstep: 131.95 | bwd_inner_microstep: 131.93 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 00:09:41,237] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.54 | bwd_microstep: 273.00 | bwd_inner_microstep: 272.98 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.20 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 323 +[2025-05-02 00:09:41,482] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 109.80 | bwd_microstep: 117.24 | bwd_inner_microstep: 117.08 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 00:09:41,962] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.67 | bwd_microstep: 272.56 | bwd_inner_microstep: 272.54 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 318 +[2025-05-02 00:09:42,192] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 100.07 | bwd_microstep: 113.76 | bwd_inner_microstep: 113.56 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 00:09:42,669] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.14 | bwd_microstep: 271.29 | bwd_inner_microstep: 271.27 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 00:09:43,149] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.96 | bwd_microstep: 271.10 | bwd_inner_microstep: 271.09 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 422 +[2025-05-02 00:09:43,536] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.07 | optimizer_gradients: 2.43 | optimizer_step: 16.08 +[2025-05-02 00:09:43,537] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 112.61 | bwd_microstep: 230.73 | bwd_inner_microstep: 130.39 | bwd_allreduce_microstep: 100.19 | step_microstep: 26.38 +[2025-05-02 00:09:43,539] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2616.67 | bwd: 3731.42 | bwd_inner: 3630.23 | bwd_allreduce: 100.54 | step: 28.00 + 8%|▊ | 698/8720 [1:54:17<15:41:54, 7.04s/it] {'loss': 1.4135, 'grad_norm': 7.01162052154541, 'learning_rate': 9.934577369636078e-06, 'epoch': 0.8} + 8%|▊ | 698/8720 [1:54:17<15:41:54, 7.04s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2116 +[2025-05-02 00:09:44,079] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 204.80 | bwd_microstep: 312.43 | bwd_inner_microstep: 312.41 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.07 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 853 +[2025-05-02 00:09:44,344] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 113.90 | bwd_microstep: 131.89 | bwd_inner_microstep: 131.71 | bwd_allreduce_microstep: 0.08 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 00:09:44,829] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.52 | bwd_microstep: 272.70 | bwd_inner_microstep: 272.66 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.21 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1349 +[2025-05-02 00:09:45,195] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.44 | bwd_microstep: 205.97 | bwd_inner_microstep: 205.80 | bwd_allreduce_microstep: 0.09 | step_microstep: 0.13 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 841 +[2025-05-02 00:09:45,460] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 114.38 | bwd_microstep: 131.24 | bwd_inner_microstep: 130.91 | bwd_allreduce_microstep: 0.15 | step_microstep: 0.15 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 325 +[2025-05-02 00:09:45,708] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 111.84 | bwd_microstep: 115.08 | bwd_inner_microstep: 114.90 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 00:09:46,191] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.70 | bwd_microstep: 272.50 | bwd_inner_microstep: 272.49 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 00:09:46,670] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.75 | bwd_microstep: 272.40 | bwd_inner_microstep: 272.38 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 00:09:47,153] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.92 | bwd_microstep: 272.34 | bwd_inner_microstep: 272.32 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 00:09:47,631] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.24 | bwd_microstep: 272.42 | bwd_inner_microstep: 272.40 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 00:09:48,112] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.00 | bwd_microstep: 272.21 | bwd_inner_microstep: 272.20 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 00:09:48,595] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.77 | bwd_microstep: 272.30 | bwd_inner_microstep: 272.28 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 00:09:49,081] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.88 | bwd_microstep: 272.32 | bwd_inner_microstep: 272.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 00:09:49,564] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.00 | bwd_microstep: 272.57 | bwd_inner_microstep: 272.55 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.11 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1345 +[2025-05-02 00:09:49,935] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.76 | bwd_microstep: 205.61 | bwd_inner_microstep: 205.57 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 00:09:50,541] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.18 | optimizer_step: 16.09 +[2025-05-02 00:09:50,542] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.53 | bwd_microstep: 372.98 | bwd_inner_microstep: 271.51 | bwd_allreduce_microstep: 101.41 | step_microstep: 25.59 +[2025-05-02 00:09:50,543] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2707.93 | bwd: 3927.13 | bwd_inner: 3824.47 | bwd_allreduce: 101.90 | step: 27.02 + 8%|▊ | 699/8720 [1:54:24<15:40:10, 7.03s/it] {'loss': 0.9923, 'grad_norm': 8.139345169067383, 'learning_rate': 9.93427758160979e-06, 'epoch': 0.8} + 8%|▊ | 699/8720 [1:54:24<15:40:10, 7.03s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2062 +[2025-05-02 00:09:51,072] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 203.18 | bwd_microstep: 302.11 | bwd_inner_microstep: 302.10 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 356 +[2025-05-02 00:09:51,291] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 85.35 | bwd_microstep: 119.48 | bwd_inner_microstep: 119.34 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1893 +[2025-05-02 00:09:51,770] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.15 | bwd_microstep: 274.71 | bwd_inner_microstep: 274.69 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 00:09:52,248] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.17 | bwd_microstep: 272.96 | bwd_inner_microstep: 272.94 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-02 00:09:52,727] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.08 | bwd_microstep: 273.28 | bwd_inner_microstep: 273.26 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 00:09:53,207] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.36 | bwd_microstep: 273.16 | bwd_inner_microstep: 273.14 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 00:09:53,686] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.64 | bwd_microstep: 272.58 | bwd_inner_microstep: 272.56 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.09 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 852 +[2025-05-02 00:09:53,932] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.54 | bwd_microstep: 133.30 | bwd_inner_microstep: 133.05 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 00:09:54,411] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.06 | bwd_microstep: 272.43 | bwd_inner_microstep: 272.41 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 00:09:54,893] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.47 | bwd_microstep: 272.40 | bwd_inner_microstep: 272.38 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 00:09:55,372] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.36 | bwd_microstep: 272.79 | bwd_inner_microstep: 272.77 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 00:09:55,853] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.22 | bwd_microstep: 272.83 | bwd_inner_microstep: 272.82 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 319 +[2025-05-02 00:09:56,083] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 90.41 | bwd_microstep: 122.65 | bwd_inner_microstep: 122.50 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 00:09:56,561] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.94 | bwd_microstep: 271.15 | bwd_inner_microstep: 271.13 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 488 +[2025-05-02 00:09:56,790] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 86.84 | bwd_microstep: 125.89 | bwd_inner_microstep: 125.73 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2014 +[2025-05-02 00:09:57,402] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.19 | optimizer_step: 16.07 +[2025-05-02 00:09:57,403] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 197.10 | bwd_microstep: 373.98 | bwd_inner_microstep: 296.21 | bwd_allreduce_microstep: 77.71 | step_microstep: 24.06 +[2025-05-02 00:09:57,404] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2644.48 | bwd: 3905.77 | bwd_inner: 3827.15 | bwd_allreduce: 78.08 | step: 25.23 + 8%|▊ | 700/8720 [1:54:31<15:33:09, 6.98s/it] {'loss': 0.9989, 'grad_norm': 3.821842908859253, 'learning_rate': 9.933977112833024e-06, 'epoch': 0.8} + 8%|▊ | 700/8720 [1:54:31<15:33:09, 6.98s/it][INFO|trainer.py:3503] 2025-05-02 00:09:59,885 >> Saving model checkpoint to work_dirs/internvl_chat_v2_5/ak/checkpoint-700 +[INFO|configuration_utils.py:472] 2025-05-02 00:09:59,888 >> Configuration saved in work_dirs/internvl_chat_v2_5/ak/checkpoint-700/config.json +[INFO|configuration_utils.py:807] 2025-05-02 00:09:59,888 >> Configuration saved in work_dirs/internvl_chat_v2_5/ak/checkpoint-700/generation_config.json +[INFO|modeling_utils.py:2755] 2025-05-02 00:10:05,503 >> Model weights saved in work_dirs/internvl_chat_v2_5/ak/checkpoint-700/model.safetensors +[INFO|tokenization_utils_base.py:2702] 2025-05-02 00:10:05,505 >> tokenizer config file saved in work_dirs/internvl_chat_v2_5/ak/checkpoint-700/tokenizer_config.json +[INFO|tokenization_utils_base.py:2711] 2025-05-02 00:10:05,505 >> Special tokens file saved in work_dirs/internvl_chat_v2_5/ak/checkpoint-700/special_tokens_map.json +[INFO|tokenization_utils_base.py:2762] 2025-05-02 00:10:05,505 >> added tokens file saved in work_dirs/internvl_chat_v2_5/ak/checkpoint-700/added_tokens.json +[2025-05-02 00:10:05,635] [INFO] [logging.py:96:log_dist] [Rank 0] [Torch] Checkpoint global_step700 is about to be saved! +[2025-05-02 00:10:05,655] [INFO] [logging.py:96:log_dist] [Rank 0] Saving model checkpoint: work_dirs/internvl_chat_v2_5/ak/checkpoint-700/global_step700/mp_rank_00_model_states.pt +[2025-05-02 00:10:05,655] [INFO] [torch_checkpoint_engine.py:21:save] [Torch] Saving work_dirs/internvl_chat_v2_5/ak/checkpoint-700/global_step700/mp_rank_00_model_states.pt... +[2025-05-02 00:10:10,121] [INFO] [torch_checkpoint_engine.py:23:save] [Torch] Saved work_dirs/internvl_chat_v2_5/ak/checkpoint-700/global_step700/mp_rank_00_model_states.pt. +[2025-05-02 00:10:10,123] [INFO] [torch_checkpoint_engine.py:21:save] [Torch] Saving work_dirs/internvl_chat_v2_5/ak/checkpoint-700/global_step700/bf16_zero_pp_rank_0_mp_rank_00_optim_states.pt... +[2025-05-02 00:10:10,397] [INFO] [torch_checkpoint_engine.py:23:save] [Torch] Saved work_dirs/internvl_chat_v2_5/ak/checkpoint-700/global_step700/bf16_zero_pp_rank_0_mp_rank_00_optim_states.pt. +[2025-05-02 00:10:10,397] [INFO] [engine.py:3536:_save_zero_checkpoint] zero checkpoint saved work_dirs/internvl_chat_v2_5/ak/checkpoint-700/global_step700/bf16_zero_pp_rank_0_mp_rank_00_optim_states.pt +[2025-05-02 00:10:10,398] [INFO] [torch_checkpoint_engine.py:33:commit] [Torch] Checkpoint global_step700 is ready now! +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1997 +[2025-05-02 00:10:10,911] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 196.50 | bwd_microstep: 291.21 | bwd_inner_microstep: 291.19 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1899 +[2025-05-02 00:10:11,388] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.80 | bwd_microstep: 273.17 | bwd_inner_microstep: 273.10 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.20 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1128 +[2025-05-02 00:10:11,686] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 117.63 | bwd_microstep: 162.23 | bwd_inner_microstep: 162.06 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1886 +[2025-05-02 00:10:12,162] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.61 | bwd_microstep: 272.21 | bwd_inner_microstep: 272.19 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-02 00:10:12,638] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.49 | bwd_microstep: 272.33 | bwd_inner_microstep: 272.29 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.14 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 00:10:13,116] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.93 | bwd_microstep: 271.71 | bwd_inner_microstep: 271.66 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.14 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 833 +[2025-05-02 00:10:13,374] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 113.38 | bwd_microstep: 124.29 | bwd_inner_microstep: 123.91 | bwd_allreduce_microstep: 0.18 | step_microstep: 0.15 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 00:10:13,857] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.34 | bwd_microstep: 270.77 | bwd_inner_microstep: 270.75 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 333 +[2025-05-02 00:10:14,104] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 82.09 | bwd_microstep: 150.50 | bwd_inner_microstep: 150.35 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 00:10:14,578] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.64 | bwd_microstep: 271.65 | bwd_inner_microstep: 271.64 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 00:10:15,054] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.39 | bwd_microstep: 271.38 | bwd_inner_microstep: 271.36 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 00:10:15,527] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.81 | bwd_microstep: 270.49 | bwd_inner_microstep: 270.48 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 00:10:16,003] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.07 | bwd_microstep: 272.47 | bwd_inner_microstep: 272.46 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 00:10:16,479] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.69 | bwd_microstep: 270.90 | bwd_inner_microstep: 270.88 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 00:10:16,956] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.05 | bwd_microstep: 270.84 | bwd_inner_microstep: 270.82 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 00:10:17,548] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.07 | optimizer_gradients: 2.23 | optimizer_step: 28.16 +[2025-05-02 00:10:17,548] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.44 | bwd_microstep: 349.09 | bwd_inner_microstep: 270.36 | bwd_allreduce_microstep: 78.56 | step_microstep: 35.87 +[2025-05-02 00:10:17,550] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2764.54 | bwd: 4065.37 | bwd_inner: 3985.74 | bwd_allreduce: 78.89 | step: 37.40 + 8%|▊ | 701/8720 [1:54:51<24:20:48, 10.93s/it] {'loss': 0.9943, 'grad_norm': 4.679582118988037, 'learning_rate': 9.933675963347233e-06, 'epoch': 0.8} + 8%|▊ | 701/8720 [1:54:51<24:20:48, 10.93s/it]dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 898 +[2025-05-02 00:10:17,813] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 100.31 | bwd_microstep: 143.32 | bwd_inner_microstep: 143.17 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1904 +[2025-05-02 00:10:18,292] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.31 | bwd_microstep: 274.84 | bwd_inner_microstep: 274.82 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 00:10:18,768] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.65 | bwd_microstep: 271.86 | bwd_inner_microstep: 271.84 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 00:10:19,246] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.87 | bwd_microstep: 273.00 | bwd_inner_microstep: 272.99 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 00:10:19,724] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.61 | bwd_microstep: 271.87 | bwd_inner_microstep: 271.85 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-02 00:10:20,208] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.55 | bwd_microstep: 273.10 | bwd_inner_microstep: 273.09 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-02 00:10:20,692] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.57 | bwd_microstep: 273.02 | bwd_inner_microstep: 273.00 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 333 +[2025-05-02 00:10:20,916] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 85.97 | bwd_microstep: 120.43 | bwd_inner_microstep: 120.27 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 00:10:21,394] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.09 | bwd_microstep: 272.04 | bwd_inner_microstep: 272.02 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 00:10:21,874] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.45 | bwd_microstep: 271.99 | bwd_inner_microstep: 271.97 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.13 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 00:10:22,359] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.67 | bwd_microstep: 271.87 | bwd_inner_microstep: 271.81 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.56 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 00:10:22,839] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.92 | bwd_microstep: 272.04 | bwd_inner_microstep: 272.02 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 00:10:23,317] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.95 | bwd_microstep: 271.83 | bwd_inner_microstep: 271.82 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 00:10:23,795] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.75 | bwd_microstep: 271.73 | bwd_inner_microstep: 271.71 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 00:10:24,273] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.84 | bwd_microstep: 270.68 | bwd_inner_microstep: 270.66 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 00:10:24,867] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.32 | optimizer_step: 22.98 +[2025-05-02 00:10:24,867] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.47 | bwd_microstep: 354.43 | bwd_inner_microstep: 271.44 | bwd_allreduce_microstep: 82.87 | step_microstep: 31.27 +[2025-05-02 00:10:24,869] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2819.59 | bwd: 4158.15 | bwd_inner: 4074.57 | bwd_allreduce: 83.04 | step: 32.84 + 8%|▊ | 702/8720 [1:54:58<21:55:54, 9.85s/it] {'loss': 1.15, 'grad_norm': 10.71335220336914, 'learning_rate': 9.933374133193962e-06, 'epoch': 0.8} + 8%|▊ | 702/8720 [1:54:58<21:55:54, 9.85s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1921 +[2025-05-02 00:10:25,372] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.00 | bwd_microstep: 284.78 | bwd_inner_microstep: 284.76 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.13 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1892 +[2025-05-02 00:10:25,855] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.11 | bwd_microstep: 273.63 | bwd_inner_microstep: 273.62 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-02 00:10:26,334] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.13 | bwd_microstep: 272.68 | bwd_inner_microstep: 272.66 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1355 +[2025-05-02 00:10:26,700] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.92 | bwd_microstep: 205.78 | bwd_inner_microstep: 205.58 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 00:10:27,180] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.41 | bwd_microstep: 272.56 | bwd_inner_microstep: 272.55 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 00:10:27,659] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.46 | bwd_microstep: 271.69 | bwd_inner_microstep: 271.67 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 00:10:28,139] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.11 | bwd_microstep: 271.26 | bwd_inner_microstep: 271.24 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 00:10:28,617] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.07 | bwd_microstep: 271.46 | bwd_inner_microstep: 271.44 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 00:10:29,097] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.07 | bwd_microstep: 271.49 | bwd_inner_microstep: 271.47 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 00:10:29,575] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.76 | bwd_microstep: 271.60 | bwd_inner_microstep: 271.53 | bwd_allreduce_microstep: 0.03 | step_microstep: 0.13 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 00:10:30,055] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.94 | bwd_microstep: 270.36 | bwd_inner_microstep: 270.34 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 00:10:30,535] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.38 | bwd_microstep: 271.39 | bwd_inner_microstep: 271.23 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.30 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 00:10:31,013] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.07 | bwd_microstep: 270.34 | bwd_inner_microstep: 270.33 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 00:10:31,489] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.77 | bwd_microstep: 270.70 | bwd_inner_microstep: 270.68 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 00:10:31,964] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.69 | bwd_microstep: 270.24 | bwd_inner_microstep: 270.22 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 00:10:32,553] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.07 | optimizer_gradients: 4.13 | optimizer_step: 22.87 +[2025-05-02 00:10:32,554] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.00 | bwd_microstep: 351.69 | bwd_inner_microstep: 270.70 | bwd_allreduce_microstep: 80.93 | step_microstep: 33.58 +[2025-05-02 00:10:32,555] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2960.50 | bwd: 4371.75 | bwd_inner: 4290.02 | bwd_allreduce: 81.22 | step: 35.33 + 8%|▊ | 703/8720 [1:55:06<20:29:09, 9.20s/it] {'loss': 0.782, 'grad_norm': 4.782496452331543, 'learning_rate': 9.933071622414853e-06, 'epoch': 0.81} + 8%|▊ | 703/8720 [1:55:06<20:29:09, 9.20s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2041 +[2025-05-02 00:10:33,077] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 200.74 | bwd_microstep: 296.67 | bwd_inner_microstep: 296.65 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 391 +[2025-05-02 00:10:33,334] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 87.69 | bwd_microstep: 151.98 | bwd_inner_microstep: 151.47 | bwd_allreduce_microstep: 0.20 | step_microstep: 0.28 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1921 +[2025-05-02 00:10:33,832] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 194.25 | bwd_microstep: 285.79 | bwd_inner_microstep: 285.77 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1894 +[2025-05-02 00:10:34,314] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.82 | bwd_microstep: 274.36 | bwd_inner_microstep: 274.34 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 00:10:34,795] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.69 | bwd_microstep: 272.28 | bwd_inner_microstep: 272.27 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.11 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 846 +[2025-05-02 00:10:35,055] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 98.93 | bwd_microstep: 141.86 | bwd_inner_microstep: 141.68 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 00:10:35,538] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.85 | bwd_microstep: 271.47 | bwd_inner_microstep: 271.45 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 838 +[2025-05-02 00:10:35,822] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 98.14 | bwd_microstep: 165.14 | bwd_inner_microstep: 165.02 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 00:10:36,300] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.75 | bwd_microstep: 272.39 | bwd_inner_microstep: 272.37 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.11 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1358 +[2025-05-02 00:10:36,668] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.05 | bwd_microstep: 206.33 | bwd_inner_microstep: 206.08 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 00:10:37,152] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.70 | bwd_microstep: 272.99 | bwd_inner_microstep: 272.97 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 00:10:37,631] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.96 | bwd_microstep: 271.83 | bwd_inner_microstep: 271.82 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 00:10:38,107] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.35 | bwd_microstep: 270.92 | bwd_inner_microstep: 270.90 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 00:10:38,587] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.28 | bwd_microstep: 270.81 | bwd_inner_microstep: 270.79 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 00:10:39,067] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.47 | bwd_microstep: 270.66 | bwd_inner_microstep: 270.64 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 00:10:39,684] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.07 | optimizer_gradients: 2.32 | optimizer_step: 28.94 +[2025-05-02 00:10:39,685] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.32 | bwd_microstep: 374.46 | bwd_inner_microstep: 271.32 | bwd_allreduce_microstep: 103.09 | step_microstep: 37.33 +[2025-05-02 00:10:39,687] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2704.57 | bwd: 4070.11 | bwd_inner: 3965.68 | bwd_allreduce: 103.61 | step: 38.72 + 8%|▊ | 704/8720 [1:55:13<19:06:13, 8.58s/it] {'loss': 0.9805, 'grad_norm': 6.608046054840088, 'learning_rate': 9.932768431051645e-06, 'epoch': 0.81} + 8%|▊ | 704/8720 [1:55:13<19:06:13, 8.58s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1953 +[2025-05-02 00:10:40,197] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.78 | bwd_microstep: 288.04 | bwd_inner_microstep: 287.92 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1923 +[2025-05-02 00:10:40,694] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 193.27 | bwd_microstep: 286.38 | bwd_inner_microstep: 286.36 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1896 +[2025-05-02 00:10:41,176] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.46 | bwd_microstep: 274.55 | bwd_inner_microstep: 274.39 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.21 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-02 00:10:41,655] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.97 | bwd_microstep: 272.80 | bwd_inner_microstep: 272.78 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 00:10:42,136] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.40 | bwd_microstep: 272.82 | bwd_inner_microstep: 272.80 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-02 00:10:42,625] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.01 | bwd_microstep: 273.54 | bwd_inner_microstep: 273.51 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-02 00:10:43,105] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.34 | bwd_microstep: 273.40 | bwd_inner_microstep: 273.39 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.20 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 852 +[2025-05-02 00:10:43,412] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.35 | bwd_microstep: 194.40 | bwd_inner_microstep: 194.22 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.12 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1365 +[2025-05-02 00:10:43,780] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.32 | bwd_microstep: 206.60 | bwd_inner_microstep: 206.58 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1109 +[2025-05-02 00:10:44,072] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 115.21 | bwd_microstep: 161.71 | bwd_inner_microstep: 161.63 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 322 +[2025-05-02 00:10:44,294] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 74.13 | bwd_microstep: 134.05 | bwd_inner_microstep: 133.88 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 00:10:44,775] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.75 | bwd_microstep: 272.30 | bwd_inner_microstep: 272.29 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 00:10:45,251] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.16 | bwd_microstep: 271.94 | bwd_inner_microstep: 271.93 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 00:10:45,725] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.36 | bwd_microstep: 270.88 | bwd_inner_microstep: 270.86 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 00:10:46,201] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.36 | bwd_microstep: 272.07 | bwd_inner_microstep: 272.06 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 00:10:46,776] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.08 | optimizer_step: 17.35 +[2025-05-02 00:10:46,776] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.92 | bwd_microstep: 345.91 | bwd_inner_microstep: 273.26 | bwd_allreduce_microstep: 72.54 | step_microstep: 24.70 +[2025-05-02 00:10:46,778] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2696.48 | bwd: 4071.59 | bwd_inner: 3997.95 | bwd_allreduce: 72.94 | step: 26.55 + 8%|▊ | 705/8720 [1:55:20<18:06:14, 8.13s/it] {'loss': 1.236, 'grad_norm': 5.813797950744629, 'learning_rate': 9.932464559146162e-06, 'epoch': 0.81} + 8%|▊ | 705/8720 [1:55:20<18:06:14, 8.13s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2056 +[2025-05-02 00:10:47,301] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 202.69 | bwd_microstep: 300.47 | bwd_inner_microstep: 300.45 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-02 00:10:47,779] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.92 | bwd_microstep: 274.36 | bwd_inner_microstep: 274.34 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-02 00:10:48,256] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.79 | bwd_microstep: 272.66 | bwd_inner_microstep: 272.65 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-02 00:10:48,733] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.53 | bwd_microstep: 273.36 | bwd_inner_microstep: 273.34 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 334 +[2025-05-02 00:10:48,939] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 74.46 | bwd_microstep: 117.26 | bwd_inner_microstep: 116.95 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 00:10:49,418] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.10 | bwd_microstep: 273.04 | bwd_inner_microstep: 273.03 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 00:10:49,896] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.12 | bwd_microstep: 272.30 | bwd_inner_microstep: 272.28 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 00:10:50,377] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.34 | bwd_microstep: 273.10 | bwd_inner_microstep: 273.08 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 00:10:50,855] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.20 | bwd_microstep: 272.57 | bwd_inner_microstep: 272.55 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 00:10:51,333] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.89 | bwd_microstep: 271.91 | bwd_inner_microstep: 271.89 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 00:10:51,815] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.22 | bwd_microstep: 272.77 | bwd_inner_microstep: 272.75 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 00:10:52,291] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.50 | bwd_microstep: 271.42 | bwd_inner_microstep: 271.40 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 00:10:52,770] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.55 | bwd_microstep: 270.64 | bwd_inner_microstep: 270.63 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 830 +[2025-05-02 00:10:53,019] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 100.55 | bwd_microstep: 129.87 | bwd_inner_microstep: 129.68 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1974 +[2025-05-02 00:10:53,524] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 196.48 | bwd_microstep: 290.50 | bwd_inner_microstep: 290.48 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1907 +[2025-05-02 00:10:54,116] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.06 | optimizer_step: 16.61 +[2025-05-02 00:10:54,117] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.14 | bwd_microstep: 359.79 | bwd_inner_microstep: 275.75 | bwd_allreduce_microstep: 83.98 | step_microstep: 24.23 +[2025-05-02 00:10:54,118] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2831.16 | bwd: 4196.08 | bwd_inner: 4111.32 | bwd_allreduce: 84.31 | step: 25.33 + 8%|▊ | 706/8720 [1:55:27<17:34:28, 7.89s/it] {'loss': 1.0966, 'grad_norm': 7.084877967834473, 'learning_rate': 9.932160006740333e-06, 'epoch': 0.81} + 8%|▊ | 706/8720 [1:55:27<17:34:28, 7.89s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1888 +[2025-05-02 00:10:54,605] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.21 | bwd_microstep: 273.63 | bwd_inner_microstep: 273.62 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1886 +[2025-05-02 00:10:55,087] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.21 | bwd_microstep: 274.73 | bwd_inner_microstep: 274.71 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-02 00:10:55,568] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.77 | bwd_microstep: 274.04 | bwd_inner_microstep: 274.02 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 00:10:56,047] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.53 | bwd_microstep: 272.15 | bwd_inner_microstep: 272.13 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-02 00:10:56,529] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.52 | bwd_microstep: 273.88 | bwd_inner_microstep: 273.86 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1351 +[2025-05-02 00:10:56,896] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.32 | bwd_microstep: 205.41 | bwd_inner_microstep: 205.35 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.11 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 333 +[2025-05-02 00:10:57,138] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.10 | bwd_microstep: 126.34 | bwd_inner_microstep: 126.19 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 00:10:57,617] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.28 | bwd_microstep: 273.15 | bwd_inner_microstep: 273.13 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 00:10:58,095] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.36 | bwd_microstep: 272.55 | bwd_inner_microstep: 272.53 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 00:10:58,573] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.08 | bwd_microstep: 272.21 | bwd_inner_microstep: 272.19 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1349 +[2025-05-02 00:10:58,937] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.37 | bwd_microstep: 205.86 | bwd_inner_microstep: 205.85 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 00:10:59,414] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.73 | bwd_microstep: 271.38 | bwd_inner_microstep: 271.36 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 00:10:59,893] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.25 | bwd_microstep: 271.95 | bwd_inner_microstep: 271.93 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 00:11:00,372] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.87 | bwd_microstep: 271.14 | bwd_inner_microstep: 271.12 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 00:11:00,851] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.90 | bwd_microstep: 271.17 | bwd_inner_microstep: 271.15 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 00:11:01,435] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.06 | optimizer_step: 16.61 +[2025-05-02 00:11:01,435] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.43 | bwd_microstep: 350.56 | bwd_inner_microstep: 273.71 | bwd_allreduce_microstep: 76.79 | step_microstep: 24.44 +[2025-05-02 00:11:01,436] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2829.55 | bwd: 4160.17 | bwd_inner: 4082.88 | bwd_allreduce: 76.95 | step: 25.45 + 8%|▊ | 707/8720 [1:55:35<17:11:15, 7.72s/it] {'loss': 1.2825, 'grad_norm': 8.068401336669922, 'learning_rate': 9.93185477387617e-06, 'epoch': 0.81} + 8%|▊ | 707/8720 [1:55:35<17:11:15, 7.72s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1902 +[2025-05-02 00:11:01,925] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.54 | bwd_microstep: 275.24 | bwd_inner_microstep: 275.22 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-02 00:11:02,407] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.06 | bwd_microstep: 274.06 | bwd_inner_microstep: 274.04 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-02 00:11:02,888] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.75 | bwd_microstep: 273.14 | bwd_inner_microstep: 273.12 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1370 +[2025-05-02 00:11:03,255] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 143.48 | bwd_microstep: 206.92 | bwd_inner_microstep: 206.90 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 00:11:03,736] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.35 | bwd_microstep: 272.90 | bwd_inner_microstep: 272.88 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-02 00:11:04,220] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.16 | bwd_microstep: 273.69 | bwd_inner_microstep: 273.67 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 00:11:04,700] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.36 | bwd_microstep: 272.48 | bwd_inner_microstep: 272.46 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 00:11:05,180] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.85 | bwd_microstep: 272.88 | bwd_inner_microstep: 272.86 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 00:11:05,659] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.53 | bwd_microstep: 272.58 | bwd_inner_microstep: 272.57 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 00:11:06,139] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.90 | bwd_microstep: 272.26 | bwd_inner_microstep: 272.25 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 00:11:06,621] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.59 | bwd_microstep: 272.49 | bwd_inner_microstep: 272.48 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.16 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1342 +[2025-05-02 00:11:06,986] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.20 | bwd_microstep: 204.46 | bwd_inner_microstep: 204.44 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 00:11:07,466] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.53 | bwd_microstep: 271.29 | bwd_inner_microstep: 271.28 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 00:11:07,944] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.81 | bwd_microstep: 271.51 | bwd_inner_microstep: 271.49 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 00:11:08,424] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.92 | bwd_microstep: 270.78 | bwd_inner_microstep: 270.76 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 00:11:09,024] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.07 | optimizer_step: 16.66 +[2025-05-02 00:11:09,025] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.52 | bwd_microstep: 369.03 | bwd_inner_microstep: 271.51 | bwd_allreduce_microstep: 97.47 | step_microstep: 24.49 +[2025-05-02 00:11:09,026] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2923.16 | bwd: 4325.74 | bwd_inner: 4227.94 | bwd_allreduce: 97.56 | step: 25.65 + 8%|▊ | 708/8720 [1:55:42<17:05:49, 7.68s/it] {'loss': 0.958, 'grad_norm': 4.991962909698486, 'learning_rate': 9.931548860595787e-06, 'epoch': 0.81} + 8%|▊ | 708/8720 [1:55:42<17:05:49, 7.68s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 400 +[2025-05-02 00:11:09,246] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 79.82 | bwd_microstep: 118.76 | bwd_inner_microstep: 118.52 | bwd_allreduce_microstep: 0.09 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-02 00:11:09,725] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.42 | bwd_microstep: 273.99 | bwd_inner_microstep: 273.97 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 00:11:10,207] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.67 | bwd_microstep: 273.61 | bwd_inner_microstep: 273.60 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 00:11:10,689] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.71 | bwd_microstep: 273.79 | bwd_inner_microstep: 273.77 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-02 00:11:11,170] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.39 | bwd_microstep: 273.50 | bwd_inner_microstep: 273.48 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 338 +[2025-05-02 00:11:11,388] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 81.92 | bwd_microstep: 119.96 | bwd_inner_microstep: 119.81 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 00:11:11,866] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.58 | bwd_microstep: 272.67 | bwd_inner_microstep: 272.65 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-02 00:11:12,347] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.76 | bwd_microstep: 273.38 | bwd_inner_microstep: 273.36 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 00:11:12,829] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.30 | bwd_microstep: 273.07 | bwd_inner_microstep: 273.05 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 00:11:13,308] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.97 | bwd_microstep: 272.34 | bwd_inner_microstep: 272.32 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 00:11:13,786] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.75 | bwd_microstep: 272.25 | bwd_inner_microstep: 272.24 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 00:11:14,264] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.09 | bwd_microstep: 272.30 | bwd_inner_microstep: 272.28 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 00:11:14,742] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.97 | bwd_microstep: 272.14 | bwd_inner_microstep: 272.12 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1086 +[2025-05-02 00:11:15,034] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 115.45 | bwd_microstep: 159.90 | bwd_inner_microstep: 159.89 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 00:11:15,511] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.91 | bwd_microstep: 271.47 | bwd_inner_microstep: 271.45 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 00:11:16,097] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.06 | optimizer_step: 16.42 +[2025-05-02 00:11:16,098] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.11 | bwd_microstep: 354.98 | bwd_inner_microstep: 271.80 | bwd_allreduce_microstep: 83.12 | step_microstep: 24.00 +[2025-05-02 00:11:16,099] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2724.45 | bwd: 4028.17 | bwd_inner: 3944.42 | bwd_allreduce: 83.32 | step: 24.91 + 8%|▊ | 709/8720 [1:55:49<16:41:17, 7.50s/it] {'loss': 1.3058, 'grad_norm': 6.311586856842041, 'learning_rate': 9.931242266941387e-06, 'epoch': 0.81} + 8%|▊ | 709/8720 [1:55:49<16:41:17, 7.50s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1927 +[2025-05-02 00:11:16,606] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 197.15 | bwd_microstep: 286.93 | bwd_inner_microstep: 286.91 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1366 +[2025-05-02 00:11:16,972] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.73 | bwd_microstep: 207.39 | bwd_inner_microstep: 207.23 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.19 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1118 +[2025-05-02 00:11:17,271] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 117.89 | bwd_microstep: 163.06 | bwd_inner_microstep: 162.85 | bwd_allreduce_microstep: 0.10 | step_microstep: 0.10 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 341 +[2025-05-02 00:11:17,494] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 83.88 | bwd_microstep: 122.32 | bwd_inner_microstep: 122.13 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-02 00:11:17,975] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.57 | bwd_microstep: 274.32 | bwd_inner_microstep: 274.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 00:11:18,455] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.64 | bwd_microstep: 273.11 | bwd_inner_microstep: 273.09 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 00:11:18,937] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.42 | bwd_microstep: 273.35 | bwd_inner_microstep: 273.34 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 00:11:19,418] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.26 | bwd_microstep: 273.56 | bwd_inner_microstep: 273.54 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-02 00:11:19,902] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.23 | bwd_microstep: 273.19 | bwd_inner_microstep: 273.17 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 00:11:20,381] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.75 | bwd_microstep: 272.24 | bwd_inner_microstep: 272.22 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.39 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 00:11:20,861] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.87 | bwd_microstep: 272.72 | bwd_inner_microstep: 272.70 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 00:11:21,341] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.88 | bwd_microstep: 272.62 | bwd_inner_microstep: 272.48 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.13 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 00:11:21,824] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.75 | bwd_microstep: 272.85 | bwd_inner_microstep: 272.83 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 828 +[2025-05-02 00:11:22,085] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 107.62 | bwd_microstep: 129.79 | bwd_inner_microstep: 129.56 | bwd_allreduce_microstep: 0.08 | step_microstep: 0.17 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1850 +[2025-05-02 00:11:22,563] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.74 | bwd_microstep: 270.94 | bwd_inner_microstep: 270.93 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 418 +[2025-05-02 00:11:22,977] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.09 | optimizer_gradients: 11.55 | optimizer_step: 29.17 +[2025-05-02 00:11:22,977] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 97.82 | bwd_microstep: 251.11 | bwd_inner_microstep: 171.74 | bwd_allreduce_microstep: 79.22 | step_microstep: 47.04 +[2025-05-02 00:11:22,979] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2631.81 | bwd: 3889.64 | bwd_inner: 3809.21 | bwd_allreduce: 79.72 | step: 48.58 + 8%|▊ | 710/8720 [1:55:56<16:16:23, 7.31s/it] {'loss': 1.0845, 'grad_norm': 4.4648756980896, 'learning_rate': 9.930934992955272e-06, 'epoch': 0.81} + 8%|▊ | 710/8720 [1:55:56<16:16:23, 7.31s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 00:11:23,466] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.49 | bwd_microstep: 272.61 | bwd_inner_microstep: 272.59 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.24 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1358 +[2025-05-02 00:11:23,838] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 142.42 | bwd_microstep: 206.88 | bwd_inner_microstep: 206.86 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.12 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1363 +[2025-05-02 00:11:24,205] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.54 | bwd_microstep: 207.03 | bwd_inner_microstep: 207.01 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.13 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 00:11:24,685] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.08 | bwd_microstep: 272.42 | bwd_inner_microstep: 272.40 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-02 00:11:25,168] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.49 | bwd_microstep: 273.68 | bwd_inner_microstep: 273.49 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.21 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 00:11:25,656] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.91 | bwd_microstep: 273.05 | bwd_inner_microstep: 272.86 | bwd_allreduce_microstep: 0.09 | step_microstep: 0.16 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 00:11:26,140] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.53 | bwd_microstep: 272.19 | bwd_inner_microstep: 272.17 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 00:11:26,625] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.68 | bwd_microstep: 272.80 | bwd_inner_microstep: 272.78 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 00:11:27,110] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.47 | bwd_microstep: 272.65 | bwd_inner_microstep: 272.63 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 00:11:27,594] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.99 | bwd_microstep: 273.27 | bwd_inner_microstep: 273.25 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.22 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 00:11:28,079] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.41 | bwd_microstep: 272.06 | bwd_inner_microstep: 272.04 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.22 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 00:11:28,562] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.92 | bwd_microstep: 271.95 | bwd_inner_microstep: 271.94 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 00:11:29,045] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.93 | bwd_microstep: 271.92 | bwd_inner_microstep: 271.90 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 00:11:29,526] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.83 | bwd_microstep: 271.08 | bwd_inner_microstep: 271.06 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 00:11:30,005] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.06 | bwd_microstep: 271.32 | bwd_inner_microstep: 271.18 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.22 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 00:11:30,604] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.12 | optimizer_gradients: 2.25 | optimizer_step: 27.10 +[2025-05-02 00:11:30,605] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.84 | bwd_microstep: 352.38 | bwd_inner_microstep: 271.61 | bwd_allreduce_microstep: 80.72 | step_microstep: 39.14 +[2025-05-02 00:11:30,607] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2920.18 | bwd: 4307.44 | bwd_inner: 4225.79 | bwd_allreduce: 81.09 | step: 41.09 + 8%|▊ | 711/8720 [1:56:04<16:28:56, 7.41s/it] {'loss': 0.7805, 'grad_norm': 6.509702205657959, 'learning_rate': 9.930627038679832e-06, 'epoch': 0.82} + 8%|▊ | 711/8720 [1:56:04<16:28:56, 7.41s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2134 +[2025-05-02 00:11:31,155] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 207.03 | bwd_microstep: 313.70 | bwd_inner_microstep: 313.69 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.14 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1915 +[2025-05-02 00:11:31,643] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.43 | bwd_microstep: 276.50 | bwd_inner_microstep: 276.49 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-02 00:11:32,131] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.36 | bwd_microstep: 273.87 | bwd_inner_microstep: 273.85 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.15 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 00:11:32,620] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.70 | bwd_microstep: 273.03 | bwd_inner_microstep: 273.01 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-02 00:11:33,104] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.72 | bwd_microstep: 273.55 | bwd_inner_microstep: 273.53 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 00:11:33,591] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.21 | bwd_microstep: 272.83 | bwd_inner_microstep: 272.81 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.14 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 00:11:34,073] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.87 | bwd_microstep: 273.05 | bwd_inner_microstep: 273.04 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.15 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 00:11:34,555] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.91 | bwd_microstep: 272.59 | bwd_inner_microstep: 272.57 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.15 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 00:11:35,039] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.23 | bwd_microstep: 272.94 | bwd_inner_microstep: 272.92 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 00:11:35,523] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.76 | bwd_microstep: 273.26 | bwd_inner_microstep: 273.23 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 00:11:36,011] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.79 | bwd_microstep: 273.33 | bwd_inner_microstep: 273.31 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.14 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 00:11:36,495] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.49 | bwd_microstep: 272.89 | bwd_inner_microstep: 272.88 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.17 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 00:11:36,977] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.51 | bwd_microstep: 272.35 | bwd_inner_microstep: 272.33 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 00:11:37,455] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.06 | bwd_microstep: 271.08 | bwd_inner_microstep: 271.07 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 828 +[2025-05-02 00:11:37,702] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.44 | bwd_microstep: 134.85 | bwd_inner_microstep: 134.54 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1948 +[2025-05-02 00:11:38,311] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.07 | optimizer_gradients: 2.29 | optimizer_step: 17.98 +[2025-05-02 00:11:38,312] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.25 | bwd_microstep: 370.48 | bwd_inner_microstep: 290.29 | bwd_allreduce_microstep: 80.13 | step_microstep: 26.47 +[2025-05-02 00:11:38,314] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2954.39 | bwd: 4370.36 | bwd_inner: 4289.61 | bwd_allreduce: 80.33 | step: 28.22 + 8%|▊ | 712/8720 [1:56:12<16:40:38, 7.50s/it] {'loss': 1.1308, 'grad_norm': 6.325161457061768, 'learning_rate': 9.930318404157552e-06, 'epoch': 0.82} + 8%|▊ | 712/8720 [1:56:12<16:40:38, 7.50s/it]dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1387 +[2025-05-02 00:11:38,688] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.81 | bwd_microstep: 208.94 | bwd_inner_microstep: 208.76 | bwd_allreduce_microstep: 0.09 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1926 +[2025-05-02 00:11:39,191] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.16 | bwd_microstep: 287.34 | bwd_inner_microstep: 287.33 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1886 +[2025-05-02 00:11:39,675] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.19 | bwd_microstep: 274.60 | bwd_inner_microstep: 274.59 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.23 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1366 +[2025-05-02 00:11:40,044] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.39 | bwd_microstep: 207.61 | bwd_inner_microstep: 207.48 | bwd_allreduce_microstep: 0.08 | step_microstep: 0.11 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 842 +[2025-05-02 00:11:40,313] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 113.03 | bwd_microstep: 134.25 | bwd_inner_microstep: 134.23 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 00:11:40,793] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.46 | bwd_microstep: 273.57 | bwd_inner_microstep: 273.55 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 00:11:41,289] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.42 | bwd_microstep: 287.51 | bwd_inner_microstep: 287.40 | bwd_allreduce_microstep: 0.04 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 00:11:41,771] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.67 | bwd_microstep: 274.29 | bwd_inner_microstep: 274.27 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 00:11:42,254] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.92 | bwd_microstep: 274.58 | bwd_inner_microstep: 274.56 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.24 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 00:11:42,739] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.96 | bwd_microstep: 275.56 | bwd_inner_microstep: 275.50 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 322 +[2025-05-02 00:11:42,986] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 103.78 | bwd_microstep: 121.52 | bwd_inner_microstep: 121.17 | bwd_allreduce_microstep: 0.15 | step_microstep: 0.21 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 00:11:43,535] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 215.81 | bwd_microstep: 313.67 | bwd_inner_microstep: 313.64 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 00:11:44,023] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 193.93 | bwd_microstep: 273.88 | bwd_inner_microstep: 273.85 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 833 +[2025-05-02 00:11:44,267] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 96.84 | bwd_microstep: 127.38 | bwd_inner_microstep: 127.37 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 00:11:44,802] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 191.72 | bwd_microstep: 322.27 | bwd_inner_microstep: 322.23 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 313 +[2025-05-02 00:11:45,470] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.15 | optimizer_step: 17.39 +[2025-05-02 00:11:45,471] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 86.38 | bwd_microstep: 531.10 | bwd_inner_microstep: 212.35 | bwd_allreduce_microstep: 318.64 | step_microstep: 25.58 +[2025-05-02 00:11:45,472] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2616.11 | bwd: 4188.20 | bwd_inner: 3868.36 | bwd_allreduce: 319.11 | step: 29.33 + 8%|▊ | 713/8720 [1:56:19<16:26:52, 7.40s/it] {'loss': 0.9532, 'grad_norm': 4.646678447723389, 'learning_rate': 9.930009089431017e-06, 'epoch': 0.82} + 8%|▊ | 713/8720 [1:56:19<16:26:52, 7.40s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 341 +[2025-05-02 00:11:45,941] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 210.83 | bwd_microstep: 239.56 | bwd_inner_microstep: 239.23 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 00:11:47,457] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 521.12 | bwd_microstep: 929.74 | bwd_inner_microstep: 929.72 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 00:11:49,981] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1014.36 | bwd_microstep: 1446.75 | bwd_inner_microstep: 1446.67 | bwd_allreduce_microstep: 0.03 | step_microstep: 0.14 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 843 +[2025-05-02 00:11:51,543] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 242.24 | bwd_microstep: 1070.53 | bwd_inner_microstep: 1070.36 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.22 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1360 +[2025-05-02 00:11:53,376] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 580.25 | bwd_microstep: 1237.14 | bwd_inner_microstep: 1237.04 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 00:11:55,907] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1113.09 | bwd_microstep: 1400.11 | bwd_inner_microstep: 1399.71 | bwd_allreduce_microstep: 0.21 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 00:11:58,434] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1108.62 | bwd_microstep: 1351.76 | bwd_inner_microstep: 1351.74 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 00:12:00,956] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1058.77 | bwd_microstep: 1398.54 | bwd_inner_microstep: 1398.52 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 00:12:03,488] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1114.22 | bwd_microstep: 1400.51 | bwd_inner_microstep: 1400.48 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 00:12:06,018] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1112.43 | bwd_microstep: 1400.27 | bwd_inner_microstep: 1400.18 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.21 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 00:12:08,541] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1110.38 | bwd_microstep: 1350.17 | bwd_inner_microstep: 1350.15 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 832 +[2025-05-02 00:12:09,807] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 434.95 | bwd_microstep: 574.25 | bwd_inner_microstep: 574.07 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 00:12:12,639] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 921.81 | bwd_microstep: 1598.68 | bwd_inner_microstep: 1598.66 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 316 +[2025-05-02 00:12:13,185] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 347.72 | bwd_microstep: 183.11 | bwd_inner_microstep: 181.99 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 00:12:15,707] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1015.02 | bwd_microstep: 1301.78 | bwd_inner_microstep: 1301.77 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.58 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-02 00:12:18,982] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.07 | optimizer_gradients: 2.15 | optimizer_step: 28.64 +[2025-05-02 00:12:18,982] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1068.63 | bwd_microstep: 2017.45 | bwd_inner_microstep: 1507.92 | bwd_allreduce_microstep: 509.49 | step_microstep: 36.51 +[2025-05-02 00:12:18,983] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 12974.35 | bwd: 18900.51 | bwd_inner: 18389.48 | bwd_allreduce: 510.14 | step: 38.83 + 8%|▊ | 714/8720 [1:56:52<33:52:10, 15.23s/it] {'loss': 0.9643, 'grad_norm': 5.30964994430542, 'learning_rate': 9.929699094542897e-06, 'epoch': 0.82} + 8%|▊ | 714/8720 [1:56:52<33:52:10, 15.23s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1988 +[2025-05-02 00:12:21,845] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 933.59 | bwd_microstep: 1618.50 | bwd_inner_microstep: 1618.48 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1931 +[2025-05-02 00:12:24,382] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1014.55 | bwd_microstep: 1461.08 | bwd_inner_microstep: 1461.06 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1893 +[2025-05-02 00:12:27,018] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1121.74 | bwd_microstep: 1405.67 | bwd_inner_microstep: 1405.61 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 360 +[2025-05-02 00:12:27,802] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 399.37 | bwd_microstep: 368.73 | bwd_inner_microstep: 368.60 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1130 +[2025-05-02 00:12:29,469] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 609.53 | bwd_microstep: 995.73 | bwd_inner_microstep: 995.71 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 00:12:32,049] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1120.76 | bwd_microstep: 1400.35 | bwd_inner_microstep: 1400.33 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 00:12:34,585] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1117.75 | bwd_microstep: 1400.71 | bwd_inner_microstep: 1400.70 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 00:12:37,115] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1119.60 | bwd_microstep: 1393.00 | bwd_inner_microstep: 1392.99 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-02 00:12:39,650] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1119.93 | bwd_microstep: 1397.56 | bwd_inner_microstep: 1397.54 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 00:12:42,177] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1206.53 | bwd_microstep: 1302.47 | bwd_inner_microstep: 1302.45 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 00:12:44,694] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1103.25 | bwd_microstep: 1302.16 | bwd_inner_microstep: 1302.14 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.17 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 00:12:47,528] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1021.21 | bwd_microstep: 1599.43 | bwd_inner_microstep: 1599.41 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 00:12:50,112] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 868.18 | bwd_microstep: 1648.63 | bwd_inner_microstep: 1648.61 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 00:12:52,642] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 872.68 | bwd_microstep: 1638.91 | bwd_inner_microstep: 1638.71 | bwd_allreduce_microstep: 0.10 | step_microstep: 0.24 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 00:12:55,168] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1110.11 | bwd_microstep: 1397.02 | bwd_inner_microstep: 1397.01 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 00:12:58,369] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.14 | optimizer_step: 17.27 +[2025-05-02 00:12:58,370] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1104.71 | bwd_microstep: 2055.87 | bwd_inner_microstep: 1396.76 | bwd_allreduce_microstep: 659.06 | step_microstep: 25.03 +[2025-05-02 00:12:58,371] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 15843.31 | bwd: 22385.87 | bwd_inner: 21726.13 | bwd_allreduce: 659.33 | step: 26.22 + 8%|▊ | 715/8720 [1:57:32<49:58:49, 22.48s/it] {'loss': 0.9958, 'grad_norm': 7.280932903289795, 'learning_rate': 9.929388419535962e-06, 'epoch': 0.82} + 8%|▊ | 715/8720 [1:57:32<49:58:49, 22.48s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1911 +[2025-05-02 00:13:00,901] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1062.98 | bwd_microstep: 1446.76 | bwd_inner_microstep: 1446.74 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 358 +[2025-05-02 00:13:01,792] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 306.75 | bwd_microstep: 519.50 | bwd_inner_microstep: 519.19 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1886 +[2025-05-02 00:13:04,318] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 922.70 | bwd_microstep: 1587.43 | bwd_inner_microstep: 1587.41 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-02 00:13:06,848] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1066.60 | bwd_microstep: 1445.78 | bwd_inner_microstep: 1445.76 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-02 00:13:09,367] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 813.74 | bwd_microstep: 1447.56 | bwd_inner_microstep: 1447.55 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 00:13:12,202] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 924.96 | bwd_microstep: 1598.48 | bwd_inner_microstep: 1598.46 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 00:13:14,736] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 923.41 | bwd_microstep: 1591.16 | bwd_inner_microstep: 1590.93 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.56 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 00:13:17,264] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 920.30 | bwd_microstep: 1589.69 | bwd_inner_microstep: 1589.65 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 00:13:19,782] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1055.79 | bwd_microstep: 1396.06 | bwd_inner_microstep: 1396.04 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 00:13:22,303] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1012.63 | bwd_microstep: 1445.64 | bwd_inner_microstep: 1445.62 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 00:13:24,826] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 965.50 | bwd_microstep: 1446.17 | bwd_inner_microstep: 1446.10 | bwd_allreduce_microstep: 0.03 | step_microstep: 0.15 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 00:13:27,349] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 869.52 | bwd_microstep: 1588.37 | bwd_inner_microstep: 1588.12 | bwd_allreduce_microstep: 0.10 | step_microstep: 0.37 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 00:13:27,921] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 284.99 | bwd_microstep: 267.88 | bwd_inner_microstep: 267.87 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 00:13:28,391] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.17 | bwd_microstep: 268.88 | bwd_inner_microstep: 268.86 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1889 +[2025-05-02 00:13:28,867] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.94 | bwd_microstep: 272.32 | bwd_inner_microstep: 272.31 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 849 +[2025-05-02 00:13:29,248] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.07 | optimizer_gradients: 2.09 | optimizer_step: 27.17 +[2025-05-02 00:13:29,249] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.26 | bwd_microstep: 238.74 | bwd_inner_microstep: 131.89 | bwd_allreduce_microstep: 106.68 | step_microstep: 35.10 +[2025-05-02 00:13:29,250] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 11596.08 | bwd: 18150.56 | bwd_inner: 18042.63 | bwd_allreduce: 107.22 | step: 37.11 + 8%|▊ | 716/8720 [1:58:02<55:34:47, 25.00s/it] {'loss': 0.8747, 'grad_norm': 3.9628260135650635, 'learning_rate': 9.929077064453071e-06, 'epoch': 0.82} + 8%|▊ | 716/8720 [1:58:03<55:34:47, 25.00s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2098 +[2025-05-02 00:13:29,775] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 201.96 | bwd_microstep: 299.32 | bwd_inner_microstep: 299.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 459 +[2025-05-02 00:13:29,997] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 85.84 | bwd_microstep: 119.31 | bwd_inner_microstep: 119.15 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 932 +[2025-05-02 00:13:30,264] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 103.05 | bwd_microstep: 145.06 | bwd_inner_microstep: 144.78 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1899 +[2025-05-02 00:13:30,740] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.31 | bwd_microstep: 272.09 | bwd_inner_microstep: 272.07 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1894 +[2025-05-02 00:13:31,218] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.93 | bwd_microstep: 272.12 | bwd_inner_microstep: 272.10 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1883 +[2025-05-02 00:13:31,695] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.02 | bwd_microstep: 271.03 | bwd_inner_microstep: 271.02 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.15 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 00:13:32,171] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.76 | bwd_microstep: 270.16 | bwd_inner_microstep: 270.14 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.13 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 850 +[2025-05-02 00:13:32,418] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 99.83 | bwd_microstep: 131.07 | bwd_inner_microstep: 130.85 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 00:13:32,891] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 185.83 | bwd_microstep: 269.62 | bwd_inner_microstep: 269.60 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 00:13:33,365] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.70 | bwd_microstep: 270.35 | bwd_inner_microstep: 270.34 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 00:13:33,838] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.07 | bwd_microstep: 268.98 | bwd_inner_microstep: 268.97 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 00:13:34,313] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.24 | bwd_microstep: 269.88 | bwd_inner_microstep: 269.86 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 00:13:34,788] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.71 | bwd_microstep: 268.44 | bwd_inner_microstep: 268.42 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 00:13:35,260] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 185.84 | bwd_microstep: 268.05 | bwd_inner_microstep: 268.03 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 00:13:35,731] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 185.88 | bwd_microstep: 267.93 | bwd_inner_microstep: 267.91 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1917 +[2025-05-02 00:13:36,330] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.06 | optimizer_step: 27.48 +[2025-05-02 00:13:36,330] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.68 | bwd_microstep: 355.93 | bwd_inner_microstep: 274.03 | bwd_allreduce_microstep: 81.84 | step_microstep: 35.27 +[2025-05-02 00:13:36,332] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2729.28 | bwd: 4019.41 | bwd_inner: 3936.66 | bwd_allreduce: 82.19 | step: 36.73 + 8%|▊ | 717/8720 [1:58:10<43:37:24, 19.62s/it] {'loss': 0.8224, 'grad_norm': 2.9875400066375732, 'learning_rate': 9.928765029337184e-06, 'epoch': 0.82} + 8%|▊ | 717/8720 [1:58:10<43:37:24, 19.62s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 388 +[2025-05-02 00:13:36,549] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 82.38 | bwd_microstep: 113.44 | bwd_inner_microstep: 113.11 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.18 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 347 +[2025-05-02 00:13:36,763] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 79.28 | bwd_microstep: 119.49 | bwd_inner_microstep: 119.17 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1891 +[2025-05-02 00:13:37,239] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.58 | bwd_microstep: 271.55 | bwd_inner_microstep: 271.53 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 00:13:37,714] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.74 | bwd_microstep: 270.58 | bwd_inner_microstep: 270.56 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1350 +[2025-05-02 00:13:38,076] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 139.84 | bwd_microstep: 203.37 | bwd_inner_microstep: 203.36 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 333 +[2025-05-02 00:13:38,296] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 88.61 | bwd_microstep: 116.37 | bwd_inner_microstep: 116.06 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.17 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 00:13:38,772] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.51 | bwd_microstep: 270.33 | bwd_inner_microstep: 270.32 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 00:13:39,250] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.34 | bwd_microstep: 269.24 | bwd_inner_microstep: 269.22 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 00:13:39,725] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.19 | bwd_microstep: 270.40 | bwd_inner_microstep: 270.39 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 323 +[2025-05-02 00:13:39,940] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 80.37 | bwd_microstep: 118.46 | bwd_inner_microstep: 118.13 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 00:13:40,415] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.23 | bwd_microstep: 269.65 | bwd_inner_microstep: 269.63 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 00:13:40,891] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.97 | bwd_microstep: 269.84 | bwd_inner_microstep: 269.82 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 00:13:41,365] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.22 | bwd_microstep: 269.78 | bwd_inner_microstep: 269.76 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 00:13:41,840] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.92 | bwd_microstep: 270.44 | bwd_inner_microstep: 270.42 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 00:13:42,313] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 185.52 | bwd_microstep: 268.49 | bwd_inner_microstep: 268.47 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 00:13:42,886] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.03 | optimizer_step: 16.81 +[2025-05-02 00:13:42,887] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.25 | bwd_microstep: 345.66 | bwd_inner_microstep: 269.17 | bwd_allreduce_microstep: 76.44 | step_microstep: 23.78 +[2025-05-02 00:13:42,888] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2524.61 | bwd: 3717.23 | bwd_inner: 3639.39 | bwd_allreduce: 76.99 | step: 25.13 + 8%|▊ | 718/8720 [1:58:16<34:54:11, 15.70s/it] {'loss': 0.7178, 'grad_norm': 5.7621235847473145, 'learning_rate': 9.92845231423135e-06, 'epoch': 0.82} + 8%|▊ | 718/8720 [1:58:16<34:54:11, 15.70s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1896 +[2025-05-02 00:13:43,367] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.38 | bwd_microstep: 271.21 | bwd_inner_microstep: 271.19 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1890 +[2025-05-02 00:13:43,842] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.33 | bwd_microstep: 271.50 | bwd_inner_microstep: 271.48 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-02 00:13:44,318] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 185.96 | bwd_microstep: 270.79 | bwd_inner_microstep: 270.78 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1887 +[2025-05-02 00:13:44,793] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 185.87 | bwd_microstep: 271.69 | bwd_inner_microstep: 271.67 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 00:13:45,270] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 185.90 | bwd_microstep: 269.77 | bwd_inner_microstep: 269.75 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 338 +[2025-05-02 00:13:45,506] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 98.58 | bwd_microstep: 116.96 | bwd_inner_microstep: 116.63 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.21 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 00:13:45,988] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.95 | bwd_microstep: 272.07 | bwd_inner_microstep: 272.06 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 334 +[2025-05-02 00:13:46,211] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 87.65 | bwd_microstep: 118.31 | bwd_inner_microstep: 118.03 | bwd_allreduce_microstep: 0.14 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 00:13:46,687] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.58 | bwd_microstep: 271.05 | bwd_inner_microstep: 271.03 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.17 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 00:13:47,164] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.61 | bwd_microstep: 271.03 | bwd_inner_microstep: 271.01 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 00:13:47,642] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.80 | bwd_microstep: 270.57 | bwd_inner_microstep: 270.55 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 00:13:48,121] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.36 | bwd_microstep: 271.11 | bwd_inner_microstep: 271.05 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1346 +[2025-05-02 00:13:48,484] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 139.60 | bwd_microstep: 204.08 | bwd_inner_microstep: 203.82 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 00:13:48,959] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.83 | bwd_microstep: 270.96 | bwd_inner_microstep: 270.94 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 00:13:49,434] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.48 | bwd_microstep: 269.73 | bwd_inner_microstep: 269.72 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 00:13:50,011] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.11 | optimizer_step: 16.81 +[2025-05-02 00:13:50,012] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 185.92 | bwd_microstep: 346.85 | bwd_inner_microstep: 269.58 | bwd_allreduce_microstep: 77.22 | step_microstep: 24.65 +[2025-05-02 00:13:50,013] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2755.40 | bwd: 4037.77 | bwd_inner: 3959.44 | bwd_allreduce: 77.64 | step: 26.11 + 8%|▊ | 719/8720 [1:58:23<29:10:53, 13.13s/it] {'loss': 1.1958, 'grad_norm': 6.430479049682617, 'learning_rate': 9.928138919178707e-06, 'epoch': 0.82} + 8%|▊ | 719/8720 [1:58:23<29:10:53, 13.13s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2103 +[2025-05-02 00:13:50,546] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 203.02 | bwd_microstep: 306.19 | bwd_inner_microstep: 306.17 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1929 +[2025-05-02 00:13:51,041] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 193.10 | bwd_microstep: 284.51 | bwd_inner_microstep: 284.49 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1891 +[2025-05-02 00:13:51,519] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.95 | bwd_microstep: 272.04 | bwd_inner_microstep: 272.03 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1896 +[2025-05-02 00:13:51,999] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.71 | bwd_microstep: 272.41 | bwd_inner_microstep: 272.39 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1349 +[2025-05-02 00:13:52,359] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 138.43 | bwd_microstep: 204.52 | bwd_inner_microstep: 204.37 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.21 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 00:13:52,835] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 185.40 | bwd_microstep: 269.92 | bwd_inner_microstep: 269.91 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 00:13:53,307] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 184.90 | bwd_microstep: 269.65 | bwd_inner_microstep: 269.63 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 00:13:53,780] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 185.78 | bwd_microstep: 268.61 | bwd_inner_microstep: 268.59 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 322 +[2025-05-02 00:13:53,997] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 84.95 | bwd_microstep: 115.55 | bwd_inner_microstep: 115.29 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 00:13:54,470] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.13 | bwd_microstep: 270.14 | bwd_inner_microstep: 270.12 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 00:13:54,948] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.85 | bwd_microstep: 271.34 | bwd_inner_microstep: 271.32 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 00:13:55,424] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.79 | bwd_microstep: 270.22 | bwd_inner_microstep: 270.20 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 00:13:55,899] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.84 | bwd_microstep: 269.93 | bwd_inner_microstep: 269.91 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 00:13:56,373] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.65 | bwd_microstep: 269.91 | bwd_inner_microstep: 269.89 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.18 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 317 +[2025-05-02 00:13:56,592] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 80.08 | bwd_microstep: 123.19 | bwd_inner_microstep: 122.89 | bwd_allreduce_microstep: 0.14 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1939 +[2025-05-02 00:13:57,199] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.11 | optimizer_step: 16.66 +[2025-05-02 00:13:57,199] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 194.33 | bwd_microstep: 370.62 | bwd_inner_microstep: 287.30 | bwd_allreduce_microstep: 83.27 | step_microstep: 24.34 +[2025-05-02 00:13:57,201] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2758.56 | bwd: 4108.83 | bwd_inner: 4024.62 | bwd_allreduce: 83.64 | step: 25.58 + 8%|▊ | 720/8720 [1:58:30<25:12:57, 11.35s/it] {'loss': 1.2434, 'grad_norm': 8.344841003417969, 'learning_rate': 9.927824844222498e-06, 'epoch': 0.83} + 8%|▊ | 720/8720 [1:58:30<25:12:57, 11.35s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 377 +[2025-05-02 00:13:57,417] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 79.39 | bwd_microstep: 115.93 | bwd_inner_microstep: 115.62 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.18 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1371 +[2025-05-02 00:13:57,784] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 142.29 | bwd_microstep: 206.69 | bwd_inner_microstep: 206.51 | bwd_allreduce_microstep: 0.09 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 00:13:58,262] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.35 | bwd_microstep: 271.92 | bwd_inner_microstep: 271.91 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 847 +[2025-05-02 00:13:58,506] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.51 | bwd_microstep: 131.57 | bwd_inner_microstep: 131.44 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1096 +[2025-05-02 00:13:58,800] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 117.28 | bwd_microstep: 159.82 | bwd_inner_microstep: 159.68 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.18 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 845 +[2025-05-02 00:13:59,045] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 96.72 | bwd_microstep: 131.61 | bwd_inner_microstep: 131.58 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 00:13:59,528] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.21 | bwd_microstep: 271.72 | bwd_inner_microstep: 271.70 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 00:14:00,005] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.98 | bwd_microstep: 271.35 | bwd_inner_microstep: 271.33 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.24 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 00:14:00,483] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.30 | bwd_microstep: 271.10 | bwd_inner_microstep: 271.08 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 00:14:00,961] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.42 | bwd_microstep: 270.88 | bwd_inner_microstep: 270.86 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 00:14:01,439] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.88 | bwd_microstep: 270.52 | bwd_inner_microstep: 270.50 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.13 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1344 +[2025-05-02 00:14:01,803] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.57 | bwd_microstep: 203.31 | bwd_inner_microstep: 203.29 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 00:14:02,279] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.71 | bwd_microstep: 271.05 | bwd_inner_microstep: 270.91 | bwd_allreduce_microstep: 0.04 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 319 +[2025-05-02 00:14:02,513] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 82.41 | bwd_microstep: 136.55 | bwd_inner_microstep: 136.31 | bwd_allreduce_microstep: 0.09 | step_microstep: 0.10 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 830 +[2025-05-02 00:14:02,754] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 92.88 | bwd_microstep: 129.65 | bwd_inner_microstep: 129.34 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1911 +[2025-05-02 00:14:03,336] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.06 | optimizer_step: 16.67 +[2025-05-02 00:14:03,337] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.76 | bwd_microstep: 352.95 | bwd_inner_microstep: 275.47 | bwd_allreduce_microstep: 77.43 | step_microstep: 24.24 +[2025-05-02 00:14:03,338] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2352.31 | bwd: 3466.81 | bwd_inner: 3387.74 | bwd_allreduce: 78.12 | step: 25.86 + 8%|▊ | 721/8720 [1:58:37<21:44:24, 9.78s/it] {'loss': 1.1237, 'grad_norm': 6.8194427490234375, 'learning_rate': 9.927510089406052e-06, 'epoch': 0.83} + 8%|▊ | 721/8720 [1:58:37<21:44:24, 9.78s/it]dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1448 +[2025-05-02 00:14:03,721] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 147.08 | bwd_microstep: 214.07 | bwd_inner_microstep: 213.98 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 867 +[2025-05-02 00:14:03,961] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.51 | bwd_microstep: 132.72 | bwd_inner_microstep: 132.48 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-02 00:14:04,435] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.33 | bwd_microstep: 271.75 | bwd_inner_microstep: 271.73 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1890 +[2025-05-02 00:14:04,908] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.40 | bwd_microstep: 272.43 | bwd_inner_microstep: 272.41 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 860 +[2025-05-02 00:14:05,151] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 96.11 | bwd_microstep: 132.28 | bwd_inner_microstep: 132.18 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 00:14:05,622] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 185.93 | bwd_microstep: 270.02 | bwd_inner_microstep: 270.00 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 837 +[2025-05-02 00:14:05,851] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 90.15 | bwd_microstep: 125.40 | bwd_inner_microstep: 125.25 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 00:14:06,323] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.20 | bwd_microstep: 270.42 | bwd_inner_microstep: 270.40 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 00:14:06,795] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.94 | bwd_microstep: 270.29 | bwd_inner_microstep: 270.28 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 840 +[2025-05-02 00:14:07,034] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 90.74 | bwd_microstep: 130.66 | bwd_inner_microstep: 130.64 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 00:14:07,508] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.55 | bwd_microstep: 270.95 | bwd_inner_microstep: 270.93 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 00:14:07,981] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.92 | bwd_microstep: 271.31 | bwd_inner_microstep: 271.29 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 00:14:08,455] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.13 | bwd_microstep: 270.77 | bwd_inner_microstep: 270.76 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 00:14:08,927] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 185.58 | bwd_microstep: 269.45 | bwd_inner_microstep: 269.43 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.17 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 00:14:09,402] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.09 | bwd_microstep: 270.59 | bwd_inner_microstep: 270.58 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 00:14:09,969] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.10 | optimizer_step: 16.81 +[2025-05-02 00:14:09,970] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.74 | bwd_microstep: 338.88 | bwd_inner_microstep: 271.76 | bwd_allreduce_microstep: 67.08 | step_microstep: 24.00 +[2025-05-02 00:14:09,971] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2570.14 | bwd: 3782.06 | bwd_inner: 3714.16 | bwd_allreduce: 67.43 | step: 25.03 + 8%|▊ | 722/8720 [1:58:43<19:38:08, 8.84s/it] {'loss': 1.0029, 'grad_norm': 4.950373649597168, 'learning_rate': 9.927194654772791e-06, 'epoch': 0.83} + 8%|▊ | 722/8720 [1:58:43<19:38:08, 8.84s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 345 +[2025-05-02 00:14:10,179] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 68.64 | bwd_microstep: 121.15 | bwd_inner_microstep: 121.02 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1887 +[2025-05-02 00:14:10,656] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.02 | bwd_microstep: 273.66 | bwd_inner_microstep: 273.64 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 00:14:11,132] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.03 | bwd_microstep: 272.05 | bwd_inner_microstep: 272.03 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 335 +[2025-05-02 00:14:11,339] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 68.19 | bwd_microstep: 125.76 | bwd_inner_microstep: 125.43 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 340 +[2025-05-02 00:14:11,548] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 74.40 | bwd_microstep: 117.97 | bwd_inner_microstep: 117.84 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 00:14:12,022] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.20 | bwd_microstep: 271.85 | bwd_inner_microstep: 271.84 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.11 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1091 +[2025-05-02 00:14:12,314] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 115.66 | bwd_microstep: 160.15 | bwd_inner_microstep: 159.93 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 00:14:12,789] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.91 | bwd_microstep: 271.96 | bwd_inner_microstep: 271.94 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 00:14:13,264] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.66 | bwd_microstep: 271.81 | bwd_inner_microstep: 271.79 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 00:14:13,740] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.35 | bwd_microstep: 272.50 | bwd_inner_microstep: 272.47 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 00:14:14,216] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.77 | bwd_microstep: 272.02 | bwd_inner_microstep: 272.00 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 00:14:14,690] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.09 | bwd_microstep: 271.49 | bwd_inner_microstep: 271.47 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 00:14:15,165] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.19 | bwd_microstep: 272.24 | bwd_inner_microstep: 272.23 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 320 +[2025-05-02 00:14:15,388] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 88.37 | bwd_microstep: 118.82 | bwd_inner_microstep: 118.52 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 00:14:15,863] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.87 | bwd_microstep: 271.17 | bwd_inner_microstep: 271.16 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 316 +[2025-05-02 00:14:16,211] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.14 | optimizer_step: 17.07 +[2025-05-02 00:14:16,212] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 90.74 | bwd_microstep: 214.56 | bwd_inner_microstep: 137.49 | bwd_allreduce_microstep: 76.91 | step_microstep: 24.94 +[2025-05-02 00:14:16,213] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2379.81 | bwd: 3579.29 | bwd_inner: 3501.05 | bwd_allreduce: 77.42 | step: 26.33 + 8%|▊ | 723/8720 [1:58:49<17:54:15, 8.06s/it] {'loss': 1.2145, 'grad_norm': 6.151959419250488, 'learning_rate': 9.926878540366239e-06, 'epoch': 0.83} + 8%|▊ | 723/8720 [1:58:49<17:54:15, 8.06s/it]dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 1105 +[2025-05-02 00:14:16,504] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 107.51 | bwd_microstep: 161.35 | bwd_inner_microstep: 161.13 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1923 +[2025-05-02 00:14:17,002] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 193.96 | bwd_microstep: 285.73 | bwd_inner_microstep: 285.72 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 00:14:17,482] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.48 | bwd_microstep: 272.04 | bwd_inner_microstep: 272.03 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 00:14:17,961] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.87 | bwd_microstep: 271.09 | bwd_inner_microstep: 271.08 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 00:14:18,438] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.64 | bwd_microstep: 272.02 | bwd_inner_microstep: 272.00 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1354 +[2025-05-02 00:14:18,802] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.07 | bwd_microstep: 205.32 | bwd_inner_microstep: 205.19 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.13 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 841 +[2025-05-02 00:14:19,053] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.10 | bwd_microstep: 131.85 | bwd_inner_microstep: 131.61 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 00:14:19,535] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.74 | bwd_microstep: 271.65 | bwd_inner_microstep: 271.63 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 00:14:20,009] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.65 | bwd_microstep: 271.57 | bwd_inner_microstep: 271.52 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 00:14:20,488] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.82 | bwd_microstep: 271.16 | bwd_inner_microstep: 271.14 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 00:14:20,963] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.37 | bwd_microstep: 271.31 | bwd_inner_microstep: 271.29 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 00:14:21,436] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.80 | bwd_microstep: 270.37 | bwd_inner_microstep: 270.35 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 00:14:21,910] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.94 | bwd_microstep: 270.26 | bwd_inner_microstep: 270.21 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 00:14:22,381] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 185.71 | bwd_microstep: 269.97 | bwd_inner_microstep: 269.95 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1934 +[2025-05-02 00:14:22,879] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 194.84 | bwd_microstep: 286.97 | bwd_inner_microstep: 286.95 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1893 +[2025-05-02 00:14:23,450] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.24 | optimizer_step: 16.78 +[2025-05-02 00:14:23,451] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.73 | bwd_microstep: 341.48 | bwd_inner_microstep: 275.39 | bwd_allreduce_microstep: 66.04 | step_microstep: 26.67 +[2025-05-02 00:14:23,453] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2788.94 | bwd: 4124.18 | bwd_inner: 4057.22 | bwd_allreduce: 66.39 | step: 27.81 + 8%|▊ | 724/8720 [1:58:57<17:21:24, 7.81s/it] {'loss': 1.1484, 'grad_norm': 5.097113609313965, 'learning_rate': 9.926561746230003e-06, 'epoch': 0.83} + 8%|▊ | 724/8720 [1:58:57<17:21:24, 7.81s/it]dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1759 +[2025-05-02 00:14:23,896] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 162.19 | bwd_microstep: 255.33 | bwd_inner_microstep: 255.16 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.13 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1915 +[2025-05-02 00:14:24,382] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.74 | bwd_microstep: 276.17 | bwd_inner_microstep: 276.15 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1897 +[2025-05-02 00:14:24,865] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.10 | bwd_microstep: 274.66 | bwd_inner_microstep: 274.65 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1894 +[2025-05-02 00:14:25,345] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.89 | bwd_microstep: 274.78 | bwd_inner_microstep: 274.76 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 381 +[2025-05-02 00:14:25,568] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 83.71 | bwd_microstep: 124.17 | bwd_inner_microstep: 124.01 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-02 00:14:26,048] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.25 | bwd_microstep: 272.85 | bwd_inner_microstep: 272.83 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 843 +[2025-05-02 00:14:26,294] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.71 | bwd_microstep: 131.71 | bwd_inner_microstep: 131.60 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 00:14:26,774] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.17 | bwd_microstep: 272.49 | bwd_inner_microstep: 272.47 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 00:14:27,254] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.48 | bwd_microstep: 272.68 | bwd_inner_microstep: 272.66 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 00:14:27,734] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.68 | bwd_microstep: 272.85 | bwd_inner_microstep: 272.83 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 00:14:28,213] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.23 | bwd_microstep: 271.72 | bwd_inner_microstep: 271.71 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 833 +[2025-05-02 00:14:28,458] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 100.15 | bwd_microstep: 125.56 | bwd_inner_microstep: 125.31 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 00:14:28,940] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.69 | bwd_microstep: 270.73 | bwd_inner_microstep: 270.71 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 00:14:29,420] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.44 | bwd_microstep: 271.12 | bwd_inner_microstep: 271.11 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 00:14:29,897] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.12 | bwd_microstep: 270.74 | bwd_inner_microstep: 270.72 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 00:14:30,465] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.38 | optimizer_step: 18.16 +[2025-05-02 00:14:30,465] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.19 | bwd_microstep: 338.98 | bwd_inner_microstep: 271.43 | bwd_allreduce_microstep: 67.44 | step_microstep: 25.94 +[2025-05-02 00:14:30,466] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2703.39 | bwd: 3976.61 | bwd_inner: 3908.20 | bwd_allreduce: 67.85 | step: 27.21 + 8%|▊ | 725/8720 [1:59:04<16:49:07, 7.57s/it] {'loss': 0.7527, 'grad_norm': 5.041042804718018, 'learning_rate': 9.926244272407792e-06, 'epoch': 0.83} + 8%|▊ | 725/8720 [1:59:04<16:49:07, 7.57s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2168 +[2025-05-02 00:14:31,007] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 205.13 | bwd_microstep: 315.12 | bwd_inner_microstep: 315.10 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 900 +[2025-05-02 00:14:31,268] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 102.52 | bwd_microstep: 143.35 | bwd_inner_microstep: 143.29 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-02 00:14:31,744] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.99 | bwd_microstep: 273.58 | bwd_inner_microstep: 273.56 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-02 00:14:32,220] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.12 | bwd_microstep: 273.37 | bwd_inner_microstep: 273.36 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 00:14:32,696] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.96 | bwd_microstep: 272.25 | bwd_inner_microstep: 272.23 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1353 +[2025-05-02 00:14:33,058] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.96 | bwd_microstep: 205.80 | bwd_inner_microstep: 205.69 | bwd_allreduce_microstep: 0.03 | step_microstep: 0.09 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 848 +[2025-05-02 00:14:33,300] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.11 | bwd_microstep: 132.67 | bwd_inner_microstep: 132.48 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 00:14:33,776] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.01 | bwd_microstep: 272.25 | bwd_inner_microstep: 272.23 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-02 00:14:34,256] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.44 | bwd_microstep: 272.85 | bwd_inner_microstep: 272.83 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 00:14:34,736] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.39 | bwd_microstep: 272.54 | bwd_inner_microstep: 272.52 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 00:14:35,218] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.15 | bwd_microstep: 272.15 | bwd_inner_microstep: 272.13 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 00:14:35,698] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.51 | bwd_microstep: 271.55 | bwd_inner_microstep: 271.53 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.29 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 00:14:36,176] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.85 | bwd_microstep: 270.40 | bwd_inner_microstep: 270.38 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 00:14:36,652] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.80 | bwd_microstep: 270.45 | bwd_inner_microstep: 270.43 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 00:14:37,130] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.67 | bwd_microstep: 270.25 | bwd_inner_microstep: 270.24 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2001 +[2025-05-02 00:14:37,750] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.48 | optimizer_step: 18.74 +[2025-05-02 00:14:37,750] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 197.54 | bwd_microstep: 373.64 | bwd_inner_microstep: 294.37 | bwd_allreduce_microstep: 79.20 | step_microstep: 27.28 +[2025-05-02 00:14:37,752] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2802.81 | bwd: 4162.28 | bwd_inner: 4082.42 | bwd_allreduce: 79.43 | step: 28.53 + 8%|▊ | 726/8720 [1:59:11<16:37:34, 7.49s/it] {'loss': 1.4318, 'grad_norm': 7.347090244293213, 'learning_rate': 9.925926118943406e-06, 'epoch': 0.83} + 8%|▊ | 726/8720 [1:59:11<16:37:34, 7.49s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1936 +[2025-05-02 00:14:38,257] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.38 | bwd_microstep: 286.56 | bwd_inner_microstep: 286.54 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1921 +[2025-05-02 00:14:38,755] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 194.22 | bwd_microstep: 286.33 | bwd_inner_microstep: 286.31 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1903 +[2025-05-02 00:14:39,236] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.50 | bwd_microstep: 275.36 | bwd_inner_microstep: 275.34 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-02 00:14:39,715] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.64 | bwd_microstep: 273.21 | bwd_inner_microstep: 273.20 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.15 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-02 00:14:40,195] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.40 | bwd_microstep: 272.96 | bwd_inner_microstep: 272.94 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 328 +[2025-05-02 00:14:40,415] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 84.03 | bwd_microstep: 120.29 | bwd_inner_microstep: 120.04 | bwd_allreduce_microstep: 0.10 | step_microstep: 0.13 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 00:14:40,896] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.62 | bwd_microstep: 273.14 | bwd_inner_microstep: 273.12 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-02 00:14:41,377] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.30 | bwd_microstep: 273.09 | bwd_inner_microstep: 273.07 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 00:14:41,858] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.58 | bwd_microstep: 272.73 | bwd_inner_microstep: 272.71 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 842 +[2025-05-02 00:14:42,103] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.43 | bwd_microstep: 131.74 | bwd_inner_microstep: 131.68 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 00:14:42,580] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.24 | bwd_microstep: 272.32 | bwd_inner_microstep: 272.31 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 834 +[2025-05-02 00:14:42,818] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.31 | bwd_microstep: 126.37 | bwd_inner_microstep: 126.10 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 00:14:43,295] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.06 | bwd_microstep: 271.54 | bwd_inner_microstep: 271.52 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 315 +[2025-05-02 00:14:43,528] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 84.40 | bwd_microstep: 130.44 | bwd_inner_microstep: 130.22 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1982 +[2025-05-02 00:14:44,036] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 197.90 | bwd_microstep: 291.60 | bwd_inner_microstep: 291.58 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1405 +[2025-05-02 00:14:44,516] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.45 | optimizer_step: 18.45 +[2025-05-02 00:14:44,517] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 144.12 | bwd_microstep: 290.93 | bwd_inner_microstep: 210.51 | bwd_allreduce_microstep: 80.27 | step_microstep: 26.67 +[2025-05-02 00:14:44,518] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2598.78 | bwd: 3848.68 | bwd_inner: 3767.37 | bwd_allreduce: 80.63 | step: 27.88 + 8%|▊ | 727/8720 [1:59:18<16:08:36, 7.27s/it] {'loss': 0.869, 'grad_norm': 5.513124942779541, 'learning_rate': 9.925607285880736e-06, 'epoch': 0.83} + 8%|▊ | 727/8720 [1:59:18<16:08:36, 7.27s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1990 +[2025-05-02 00:14:45,032] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 197.49 | bwd_microstep: 293.39 | bwd_inner_microstep: 293.34 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1915 +[2025-05-02 00:14:45,517] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.93 | bwd_microstep: 276.08 | bwd_inner_microstep: 276.06 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1912 +[2025-05-02 00:14:46,002] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 191.42 | bwd_microstep: 275.85 | bwd_inner_microstep: 275.83 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 347 +[2025-05-02 00:14:46,233] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.68 | bwd_microstep: 119.11 | bwd_inner_microstep: 118.80 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1894 +[2025-05-02 00:14:46,717] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.19 | bwd_microstep: 275.11 | bwd_inner_microstep: 275.02 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-02 00:14:47,198] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.69 | bwd_microstep: 274.06 | bwd_inner_microstep: 274.04 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 00:14:47,678] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.88 | bwd_microstep: 273.63 | bwd_inner_microstep: 273.62 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1366 +[2025-05-02 00:14:48,044] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.81 | bwd_microstep: 207.40 | bwd_inner_microstep: 207.37 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-02 00:14:48,527] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.70 | bwd_microstep: 274.18 | bwd_inner_microstep: 274.17 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 00:14:49,009] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.97 | bwd_microstep: 272.35 | bwd_inner_microstep: 272.33 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 833 +[2025-05-02 00:14:49,255] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 102.35 | bwd_microstep: 125.29 | bwd_inner_microstep: 125.02 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 00:14:49,737] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.23 | bwd_microstep: 271.04 | bwd_inner_microstep: 271.02 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.17 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 00:14:50,214] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.55 | bwd_microstep: 271.05 | bwd_inner_microstep: 271.03 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 00:14:50,691] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.96 | bwd_microstep: 271.40 | bwd_inner_microstep: 271.38 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 00:14:51,174] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.72 | bwd_microstep: 271.06 | bwd_inner_microstep: 271.04 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.17 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 00:14:51,743] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.23 | optimizer_step: 17.59 +[2025-05-02 00:14:51,743] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.26 | bwd_microstep: 340.80 | bwd_inner_microstep: 272.22 | bwd_allreduce_microstep: 68.54 | step_microstep: 25.07 +[2025-05-02 00:14:51,744] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2798.48 | bwd: 4091.85 | bwd_inner: 4022.39 | bwd_allreduce: 68.87 | step: 26.53 + 8%|▊ | 728/8720 [1:59:25<16:06:38, 7.26s/it] {'loss': 1.0191, 'grad_norm': 6.269610404968262, 'learning_rate': 9.92528777326377e-06, 'epoch': 0.83} + 8%|▊ | 728/8720 [1:59:25<16:06:38, 7.26s/it]dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1390 +[2025-05-02 00:14:52,115] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 142.32 | bwd_microstep: 208.44 | bwd_inner_microstep: 208.23 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 00:14:52,592] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.44 | bwd_microstep: 273.47 | bwd_inner_microstep: 273.46 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1347 +[2025-05-02 00:14:52,955] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 143.03 | bwd_microstep: 205.58 | bwd_inner_microstep: 205.56 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1351 +[2025-05-02 00:14:53,317] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.33 | bwd_microstep: 205.81 | bwd_inner_microstep: 205.80 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 332 +[2025-05-02 00:14:53,535] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 83.46 | bwd_microstep: 120.61 | bwd_inner_microstep: 120.31 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.10 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 329 +[2025-05-02 00:14:53,758] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 91.28 | bwd_microstep: 115.24 | bwd_inner_microstep: 115.08 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 00:14:54,236] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.85 | bwd_microstep: 272.17 | bwd_inner_microstep: 272.15 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 00:14:54,714] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.65 | bwd_microstep: 272.28 | bwd_inner_microstep: 272.27 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 00:14:55,193] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.46 | bwd_microstep: 272.59 | bwd_inner_microstep: 272.58 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 00:14:55,673] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.21 | bwd_microstep: 272.60 | bwd_inner_microstep: 272.58 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 00:14:56,150] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.87 | bwd_microstep: 271.38 | bwd_inner_microstep: 271.36 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 00:14:56,629] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.11 | bwd_microstep: 272.13 | bwd_inner_microstep: 272.11 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 318 +[2025-05-02 00:14:56,868] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.38 | bwd_microstep: 127.44 | bwd_inner_microstep: 127.30 | bwd_allreduce_microstep: 0.03 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 00:14:57,347] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.41 | bwd_microstep: 271.22 | bwd_inner_microstep: 271.20 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.17 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 315 +[2025-05-02 00:14:57,575] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 89.57 | bwd_microstep: 119.39 | bwd_inner_microstep: 119.23 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1933 +[2025-05-02 00:14:58,180] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.27 | optimizer_step: 18.34 +[2025-05-02 00:14:58,181] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 196.42 | bwd_microstep: 365.51 | bwd_inner_microstep: 288.71 | bwd_allreduce_microstep: 76.74 | step_microstep: 26.11 +[2025-05-02 00:14:58,182] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2485.44 | bwd: 3645.98 | bwd_inner: 3568.11 | bwd_allreduce: 77.20 | step: 27.25 + 8%|▊ | 729/8720 [1:59:31<15:33:51, 7.01s/it] {'loss': 0.597, 'grad_norm': 4.998619079589844, 'learning_rate': 9.924967581136592e-06, 'epoch': 0.84} + 8%|▊ | 729/8720 [1:59:31<15:33:51, 7.01s/it]dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 879 +[2025-05-02 00:14:58,435] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.35 | bwd_microstep: 135.60 | bwd_inner_microstep: 135.45 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1905 +[2025-05-02 00:14:58,918] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.38 | bwd_microstep: 275.67 | bwd_inner_microstep: 275.65 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 341 +[2025-05-02 00:14:59,117] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 68.69 | bwd_microstep: 117.54 | bwd_inner_microstep: 117.40 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.09 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 341 +[2025-05-02 00:14:59,323] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 71.54 | bwd_microstep: 120.85 | bwd_inner_microstep: 120.72 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1888 +[2025-05-02 00:14:59,801] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.85 | bwd_microstep: 274.55 | bwd_inner_microstep: 274.53 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-02 00:15:00,281] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.00 | bwd_microstep: 274.65 | bwd_inner_microstep: 274.62 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-02 00:15:00,760] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.81 | bwd_microstep: 274.49 | bwd_inner_microstep: 274.47 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1356 +[2025-05-02 00:15:01,122] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.67 | bwd_microstep: 206.26 | bwd_inner_microstep: 206.14 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.12 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1364 +[2025-05-02 00:15:01,494] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.54 | bwd_microstep: 207.09 | bwd_inner_microstep: 206.97 | bwd_allreduce_microstep: 0.03 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 00:15:01,972] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.33 | bwd_microstep: 272.64 | bwd_inner_microstep: 272.63 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 00:15:02,451] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.44 | bwd_microstep: 272.11 | bwd_inner_microstep: 272.10 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 00:15:02,930] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.67 | bwd_microstep: 271.69 | bwd_inner_microstep: 271.62 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 00:15:03,413] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.01 | bwd_microstep: 271.93 | bwd_inner_microstep: 271.91 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 00:15:03,892] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.94 | bwd_microstep: 271.45 | bwd_inner_microstep: 271.43 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 00:15:04,372] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.25 | bwd_microstep: 270.21 | bwd_inner_microstep: 270.20 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 00:15:04,953] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.24 | optimizer_step: 17.77 +[2025-05-02 00:15:04,954] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.61 | bwd_microstep: 348.22 | bwd_inner_microstep: 270.66 | bwd_allreduce_microstep: 77.50 | step_microstep: 25.61 +[2025-05-02 00:15:04,955] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2584.72 | bwd: 3865.08 | bwd_inner: 3786.59 | bwd_allreduce: 77.91 | step: 26.75 + 8%|▊ | 730/8720 [1:59:38<15:24:11, 6.94s/it] {'loss': 1.2439, 'grad_norm': 5.52574348449707, 'learning_rate': 9.924646709543373e-06, 'epoch': 0.84} + 8%|▊ | 730/8720 [1:59:38<15:24:11, 6.94s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1887 +[2025-05-02 00:15:05,440] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.64 | bwd_microstep: 273.27 | bwd_inner_microstep: 273.25 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-02 00:15:05,920] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.48 | bwd_microstep: 273.19 | bwd_inner_microstep: 273.17 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 00:15:06,396] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.68 | bwd_microstep: 273.06 | bwd_inner_microstep: 273.04 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 00:15:06,874] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.20 | bwd_microstep: 272.25 | bwd_inner_microstep: 272.23 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 00:15:07,351] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.47 | bwd_microstep: 272.46 | bwd_inner_microstep: 272.44 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-02 00:15:07,830] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.91 | bwd_microstep: 272.89 | bwd_inner_microstep: 272.88 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 00:15:08,307] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.22 | bwd_microstep: 271.41 | bwd_inner_microstep: 271.39 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 00:15:08,788] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.93 | bwd_microstep: 272.45 | bwd_inner_microstep: 272.43 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 326 +[2025-05-02 00:15:09,019] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.95 | bwd_microstep: 116.70 | bwd_inner_microstep: 116.37 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.11 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 842 +[2025-05-02 00:15:09,274] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 99.30 | bwd_microstep: 136.44 | bwd_inner_microstep: 136.38 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 00:15:09,752] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.08 | bwd_microstep: 272.20 | bwd_inner_microstep: 272.19 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 00:15:10,231] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.75 | bwd_microstep: 271.63 | bwd_inner_microstep: 271.61 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 00:15:10,711] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.88 | bwd_microstep: 271.65 | bwd_inner_microstep: 271.60 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.17 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 00:15:11,196] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.70 | bwd_microstep: 271.16 | bwd_inner_microstep: 271.14 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 00:15:11,675] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.89 | bwd_microstep: 271.09 | bwd_inner_microstep: 271.07 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1850 +[2025-05-02 00:15:12,264] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.25 | optimizer_step: 17.67 +[2025-05-02 00:15:12,264] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.09 | bwd_microstep: 350.15 | bwd_inner_microstep: 271.30 | bwd_allreduce_microstep: 78.81 | step_microstep: 25.51 +[2025-05-02 00:15:12,266] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2828.81 | bwd: 4142.09 | bwd_inner: 4062.57 | bwd_allreduce: 79.03 | step: 26.69 + 8%|▊ | 731/8720 [1:59:46<15:38:52, 7.05s/it] {'loss': 0.7257, 'grad_norm': 4.657297134399414, 'learning_rate': 9.924325158528385e-06, 'epoch': 0.84} + 8%|▊ | 731/8720 [1:59:46<15:38:52, 7.05s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1888 +[2025-05-02 00:15:12,754] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.33 | bwd_microstep: 273.99 | bwd_inner_microstep: 273.98 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1889 +[2025-05-02 00:15:13,238] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.18 | bwd_microstep: 275.22 | bwd_inner_microstep: 275.21 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 00:15:13,719] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.70 | bwd_microstep: 273.46 | bwd_inner_microstep: 273.44 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-02 00:15:14,199] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.26 | bwd_microstep: 273.42 | bwd_inner_microstep: 273.40 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-02 00:15:14,678] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.80 | bwd_microstep: 273.59 | bwd_inner_microstep: 273.57 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 00:15:15,159] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.16 | bwd_microstep: 273.11 | bwd_inner_microstep: 273.09 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 00:15:15,642] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.96 | bwd_microstep: 273.43 | bwd_inner_microstep: 273.39 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 00:15:16,127] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.00 | bwd_microstep: 273.35 | bwd_inner_microstep: 273.33 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 00:15:16,611] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.13 | bwd_microstep: 273.17 | bwd_inner_microstep: 273.15 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 00:15:17,090] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.24 | bwd_microstep: 273.20 | bwd_inner_microstep: 273.08 | bwd_allreduce_microstep: 0.03 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 00:15:17,572] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.32 | bwd_microstep: 272.76 | bwd_inner_microstep: 272.74 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 00:15:18,049] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.79 | bwd_microstep: 271.25 | bwd_inner_microstep: 271.23 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 00:15:18,530] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.34 | bwd_microstep: 271.51 | bwd_inner_microstep: 271.48 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 320 +[2025-05-02 00:15:18,769] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.37 | bwd_microstep: 126.53 | bwd_inner_microstep: 126.31 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 00:15:19,245] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.42 | bwd_microstep: 270.87 | bwd_inner_microstep: 270.86 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1917 +[2025-05-02 00:15:19,833] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.22 | optimizer_step: 18.16 +[2025-05-02 00:15:19,833] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.79 | bwd_microstep: 354.14 | bwd_inner_microstep: 277.57 | bwd_allreduce_microstep: 76.51 | step_microstep: 25.99 +[2025-05-02 00:15:19,835] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2924.42 | bwd: 4303.03 | bwd_inner: 4225.91 | bwd_allreduce: 76.70 | step: 26.95 + 8%|▊ | 732/8720 [1:59:53<15:59:25, 7.21s/it] {'loss': 1.0354, 'grad_norm': 5.930012226104736, 'learning_rate': 9.924002928135987e-06, 'epoch': 0.84} + 8%|▊ | 732/8720 [1:59:53<15:59:25, 7.21s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1970 +[2025-05-02 00:15:20,346] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 199.18 | bwd_microstep: 289.71 | bwd_inner_microstep: 289.70 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 880 +[2025-05-02 00:15:20,596] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 98.26 | bwd_microstep: 135.33 | bwd_inner_microstep: 135.22 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1917 +[2025-05-02 00:15:21,078] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.62 | bwd_microstep: 276.47 | bwd_inner_microstep: 276.45 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1915 +[2025-05-02 00:15:21,559] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.49 | bwd_microstep: 276.29 | bwd_inner_microstep: 276.27 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-02 00:15:22,037] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.12 | bwd_microstep: 273.65 | bwd_inner_microstep: 273.64 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1367 +[2025-05-02 00:15:22,402] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 143.06 | bwd_microstep: 207.31 | bwd_inner_microstep: 207.18 | bwd_allreduce_microstep: 0.08 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 00:15:22,881] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.23 | bwd_microstep: 274.11 | bwd_inner_microstep: 274.09 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 836 +[2025-05-02 00:15:23,116] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.01 | bwd_microstep: 126.31 | bwd_inner_microstep: 126.22 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 837 +[2025-05-02 00:15:23,348] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 91.24 | bwd_microstep: 126.40 | bwd_inner_microstep: 126.32 | bwd_allreduce_microstep: 0.03 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 00:15:23,824] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.99 | bwd_microstep: 271.91 | bwd_inner_microstep: 271.89 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 00:15:24,303] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.46 | bwd_microstep: 271.43 | bwd_inner_microstep: 271.41 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 830 +[2025-05-02 00:15:24,550] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 98.54 | bwd_microstep: 130.22 | bwd_inner_microstep: 130.00 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.12 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 829 +[2025-05-02 00:15:24,793] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.37 | bwd_microstep: 130.23 | bwd_inner_microstep: 129.99 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 00:15:25,269] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.78 | bwd_microstep: 271.34 | bwd_inner_microstep: 271.32 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 00:15:25,745] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.72 | bwd_microstep: 270.98 | bwd_inner_microstep: 270.96 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1385 +[2025-05-02 00:15:26,227] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.24 | optimizer_step: 17.78 +[2025-05-02 00:15:26,227] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 143.68 | bwd_microstep: 293.71 | bwd_inner_microstep: 208.79 | bwd_allreduce_microstep: 84.81 | step_microstep: 25.51 +[2025-05-02 00:15:26,228] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2471.45 | bwd: 3625.51 | bwd_inner: 3539.49 | bwd_allreduce: 85.33 | step: 26.61 + 8%|▊ | 733/8720 [1:59:59<15:26:51, 6.96s/it] {'loss': 0.7753, 'grad_norm': 6.242107391357422, 'learning_rate': 9.92368001841064e-06, 'epoch': 0.84} + 8%|▊ | 733/8720 [1:59:59<15:26:51, 6.96s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1974 +[2025-05-02 00:15:26,738] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 196.86 | bwd_microstep: 290.50 | bwd_inner_microstep: 290.48 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1903 +[2025-05-02 00:15:27,221] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.91 | bwd_microstep: 275.81 | bwd_inner_microstep: 275.79 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1366 +[2025-05-02 00:15:27,589] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.37 | bwd_microstep: 206.97 | bwd_inner_microstep: 206.96 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1883 +[2025-05-02 00:15:28,070] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.30 | bwd_microstep: 274.52 | bwd_inner_microstep: 274.51 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1359 +[2025-05-02 00:15:28,436] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.94 | bwd_microstep: 207.10 | bwd_inner_microstep: 206.95 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 00:15:28,917] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.92 | bwd_microstep: 273.42 | bwd_inner_microstep: 273.40 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 841 +[2025-05-02 00:15:29,161] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.36 | bwd_microstep: 132.43 | bwd_inner_microstep: 132.35 | bwd_allreduce_microstep: 0.04 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 00:15:29,640] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.84 | bwd_microstep: 272.65 | bwd_inner_microstep: 272.63 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 00:15:30,119] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.98 | bwd_microstep: 272.87 | bwd_inner_microstep: 272.85 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 844 +[2025-05-02 00:15:30,373] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 103.15 | bwd_microstep: 132.06 | bwd_inner_microstep: 131.91 | bwd_allreduce_microstep: 0.08 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 00:15:30,851] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.34 | bwd_microstep: 272.16 | bwd_inner_microstep: 272.15 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 00:15:31,331] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.31 | bwd_microstep: 271.94 | bwd_inner_microstep: 271.92 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 00:15:31,809] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.83 | bwd_microstep: 270.99 | bwd_inner_microstep: 270.98 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 00:15:32,288] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.96 | bwd_microstep: 271.40 | bwd_inner_microstep: 271.38 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 00:15:32,768] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.53 | bwd_microstep: 271.09 | bwd_inner_microstep: 271.07 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 00:15:33,354] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.25 | optimizer_step: 18.04 +[2025-05-02 00:15:33,354] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.98 | bwd_microstep: 351.71 | bwd_inner_microstep: 271.59 | bwd_allreduce_microstep: 80.07 | step_microstep: 26.44 +[2025-05-02 00:15:33,356] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2749.23 | bwd: 4047.70 | bwd_inner: 3966.93 | bwd_allreduce: 80.37 | step: 27.46 + 8%|▊ | 734/8720 [2:00:07<15:33:18, 7.01s/it] {'loss': 0.9077, 'grad_norm': 4.205868721008301, 'learning_rate': 9.923356429396888e-06, 'epoch': 0.84} + 8%|▊ | 734/8720 [2:00:07<15:33:18, 7.01s/it]dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 899 +[2025-05-02 00:15:33,623] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 100.35 | bwd_microstep: 144.00 | bwd_inner_microstep: 143.71 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-02 00:15:34,104] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.83 | bwd_microstep: 274.26 | bwd_inner_microstep: 274.24 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1130 +[2025-05-02 00:15:34,401] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 116.33 | bwd_microstep: 164.16 | bwd_inner_microstep: 164.06 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 00:15:34,882] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.67 | bwd_microstep: 274.29 | bwd_inner_microstep: 274.27 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 00:15:35,365] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.08 | bwd_microstep: 274.53 | bwd_inner_microstep: 274.51 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 00:15:35,846] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.45 | bwd_microstep: 273.38 | bwd_inner_microstep: 273.36 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 00:15:36,330] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.38 | bwd_microstep: 274.52 | bwd_inner_microstep: 274.50 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 00:15:36,815] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.82 | bwd_microstep: 273.62 | bwd_inner_microstep: 273.60 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 00:15:37,299] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.40 | bwd_microstep: 273.99 | bwd_inner_microstep: 273.97 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 00:15:37,782] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.74 | bwd_microstep: 273.80 | bwd_inner_microstep: 273.69 | bwd_allreduce_microstep: 0.04 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 00:15:38,266] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.14 | bwd_microstep: 273.51 | bwd_inner_microstep: 273.44 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 00:15:38,747] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.61 | bwd_microstep: 272.58 | bwd_inner_microstep: 272.57 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.20 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1344 +[2025-05-02 00:15:39,109] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.31 | bwd_microstep: 204.28 | bwd_inner_microstep: 204.26 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 00:15:39,588] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.74 | bwd_microstep: 272.23 | bwd_inner_microstep: 272.21 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 00:15:40,071] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.04 | bwd_microstep: 271.34 | bwd_inner_microstep: 271.33 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 00:15:40,657] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.26 | optimizer_step: 17.55 +[2025-05-02 00:15:40,658] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.48 | bwd_microstep: 354.55 | bwd_inner_microstep: 271.84 | bwd_allreduce_microstep: 82.66 | step_microstep: 25.63 +[2025-05-02 00:15:40,659] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2813.01 | bwd: 4149.13 | bwd_inner: 4065.61 | bwd_allreduce: 82.97 | step: 26.84 + 8%|▊ | 735/8720 [2:00:14<15:44:50, 7.10s/it] {'loss': 0.813, 'grad_norm': 4.176086902618408, 'learning_rate': 9.923032161139376e-06, 'epoch': 0.84} + 8%|▊ | 735/8720 [2:00:14<15:44:50, 7.10s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2113 +[2025-05-02 00:15:41,199] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 205.10 | bwd_microstep: 311.42 | bwd_inner_microstep: 311.40 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1570 +[2025-05-02 00:15:41,609] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 151.88 | bwd_microstep: 239.12 | bwd_inner_microstep: 239.11 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1931 +[2025-05-02 00:15:42,110] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.18 | bwd_microstep: 287.67 | bwd_inner_microstep: 287.65 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1904 +[2025-05-02 00:15:42,596] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.29 | bwd_microstep: 275.87 | bwd_inner_microstep: 275.85 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1116 +[2025-05-02 00:15:42,894] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 116.09 | bwd_microstep: 162.22 | bwd_inner_microstep: 162.04 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.10 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 860 +[2025-05-02 00:15:43,141] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.86 | bwd_microstep: 133.83 | bwd_inner_microstep: 133.54 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-02 00:15:43,621] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.45 | bwd_microstep: 273.16 | bwd_inner_microstep: 273.14 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-02 00:15:44,102] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.40 | bwd_microstep: 273.70 | bwd_inner_microstep: 273.69 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 00:15:44,582] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.38 | bwd_microstep: 272.36 | bwd_inner_microstep: 272.34 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.21 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 00:15:45,062] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.61 | bwd_microstep: 272.11 | bwd_inner_microstep: 272.09 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.17 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 00:15:45,544] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.54 | bwd_microstep: 272.55 | bwd_inner_microstep: 272.54 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 00:15:46,025] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.19 | bwd_microstep: 272.46 | bwd_inner_microstep: 272.44 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 00:15:46,508] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.71 | bwd_microstep: 272.35 | bwd_inner_microstep: 272.33 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 00:15:46,988] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.00 | bwd_microstep: 272.02 | bwd_inner_microstep: 272.01 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 00:15:47,467] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.43 | bwd_microstep: 271.05 | bwd_inner_microstep: 271.03 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 00:15:48,043] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 3.19 | optimizer_step: 17.70 +[2025-05-02 00:15:48,044] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.87 | bwd_microstep: 338.58 | bwd_inner_microstep: 271.61 | bwd_allreduce_microstep: 66.92 | step_microstep: 26.06 +[2025-05-02 00:15:48,045] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2837.60 | bwd: 4200.58 | bwd_inner: 4132.86 | bwd_allreduce: 67.20 | step: 27.40 + 8%|▊ | 736/8720 [2:00:21<15:56:03, 7.18s/it] {'loss': 0.951, 'grad_norm': 5.945047855377197, 'learning_rate': 9.922707213682845e-06, 'epoch': 0.84} + 8%|▊ | 736/8720 [2:00:21<15:56:03, 7.18s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-02 00:15:48,527] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.92 | bwd_microstep: 273.30 | bwd_inner_microstep: 273.29 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 00:15:49,005] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.44 | bwd_microstep: 273.17 | bwd_inner_microstep: 273.15 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 00:15:49,484] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.47 | bwd_microstep: 273.28 | bwd_inner_microstep: 273.26 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1355 +[2025-05-02 00:15:49,847] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 142.19 | bwd_microstep: 206.31 | bwd_inner_microstep: 206.29 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1353 +[2025-05-02 00:15:50,210] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.87 | bwd_microstep: 206.22 | bwd_inner_microstep: 206.12 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.18 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 846 +[2025-05-02 00:15:50,452] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.13 | bwd_microstep: 132.30 | bwd_inner_microstep: 132.03 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 00:15:50,928] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.37 | bwd_microstep: 272.89 | bwd_inner_microstep: 272.88 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 00:15:51,410] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.70 | bwd_microstep: 272.53 | bwd_inner_microstep: 272.51 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 00:15:51,888] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.88 | bwd_microstep: 272.81 | bwd_inner_microstep: 272.79 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 00:15:52,364] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.34 | bwd_microstep: 272.64 | bwd_inner_microstep: 272.62 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 00:15:52,840] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.77 | bwd_microstep: 272.20 | bwd_inner_microstep: 272.18 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 318 +[2025-05-02 00:15:53,066] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 87.15 | bwd_microstep: 121.74 | bwd_inner_microstep: 121.52 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 00:15:53,544] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.27 | bwd_microstep: 272.24 | bwd_inner_microstep: 272.22 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 00:15:54,027] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.97 | bwd_microstep: 271.18 | bwd_inner_microstep: 271.16 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 00:15:54,508] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.44 | bwd_microstep: 271.26 | bwd_inner_microstep: 271.24 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1850 +[2025-05-02 00:15:55,089] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.31 | optimizer_step: 17.68 +[2025-05-02 00:15:55,089] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.09 | bwd_microstep: 348.53 | bwd_inner_microstep: 271.50 | bwd_allreduce_microstep: 76.98 | step_microstep: 25.21 +[2025-05-02 00:15:55,090] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2727.67 | bwd: 4012.66 | bwd_inner: 3934.84 | bwd_allreduce: 77.29 | step: 26.23 + 8%|▊ | 737/8720 [2:00:28<15:50:22, 7.14s/it] {'loss': 0.6693, 'grad_norm': 7.128800392150879, 'learning_rate': 9.922381587072123e-06, 'epoch': 0.85} + 8%|▊ | 737/8720 [2:00:28<15:50:22, 7.14s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1898 +[2025-05-02 00:15:55,575] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.73 | bwd_microstep: 275.22 | bwd_inner_microstep: 275.20 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1892 +[2025-05-02 00:15:56,056] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.39 | bwd_microstep: 275.15 | bwd_inner_microstep: 275.13 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-02 00:15:56,536] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.67 | bwd_microstep: 274.17 | bwd_inner_microstep: 274.16 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 00:15:57,017] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.12 | bwd_microstep: 273.42 | bwd_inner_microstep: 273.39 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 00:15:57,498] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.99 | bwd_microstep: 272.86 | bwd_inner_microstep: 272.84 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 00:15:57,977] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.30 | bwd_microstep: 272.69 | bwd_inner_microstep: 272.67 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 00:15:58,456] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.24 | bwd_microstep: 273.00 | bwd_inner_microstep: 272.98 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 842 +[2025-05-02 00:15:58,712] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 104.16 | bwd_microstep: 131.44 | bwd_inner_microstep: 131.38 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 00:15:59,193] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.52 | bwd_microstep: 272.88 | bwd_inner_microstep: 272.86 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 00:15:59,674] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.04 | bwd_microstep: 272.75 | bwd_inner_microstep: 272.73 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 00:16:00,153] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.27 | bwd_microstep: 272.36 | bwd_inner_microstep: 272.34 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 00:16:00,631] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.46 | bwd_microstep: 271.37 | bwd_inner_microstep: 271.35 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 00:16:01,111] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.93 | bwd_microstep: 273.05 | bwd_inner_microstep: 273.04 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 316 +[2025-05-02 00:16:01,337] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 86.72 | bwd_microstep: 122.70 | bwd_inner_microstep: 122.43 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.10 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1342 +[2025-05-02 00:16:01,699] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.59 | bwd_microstep: 204.67 | bwd_inner_microstep: 204.65 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2016 +[2025-05-02 00:16:02,321] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.23 | optimizer_step: 17.06 +[2025-05-02 00:16:02,322] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 200.09 | bwd_microstep: 379.08 | bwd_inner_microstep: 296.26 | bwd_allreduce_microstep: 82.77 | step_microstep: 24.93 +[2025-05-02 00:16:02,323] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2794.87 | bwd: 4116.86 | bwd_inner: 4033.48 | bwd_allreduce: 82.96 | step: 26.05 + 8%|▊ | 738/8720 [2:00:36<15:53:54, 7.17s/it] {'loss': 0.7364, 'grad_norm': 5.339770317077637, 'learning_rate': 9.922055281352134e-06, 'epoch': 0.85} + 8%|▊ | 738/8720 [2:00:36<15:53:54, 7.17s/it]dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 907 +[2025-05-02 00:16:02,594] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 103.89 | bwd_microstep: 144.77 | bwd_inner_microstep: 144.46 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1887 +[2025-05-02 00:16:03,075] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.85 | bwd_microstep: 275.02 | bwd_inner_microstep: 275.00 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1889 +[2025-05-02 00:16:03,561] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.78 | bwd_microstep: 275.46 | bwd_inner_microstep: 275.41 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 327 +[2025-05-02 00:16:03,794] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.55 | bwd_microstep: 118.85 | bwd_inner_microstep: 118.68 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 00:16:04,273] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.33 | bwd_microstep: 273.40 | bwd_inner_microstep: 273.38 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 839 +[2025-05-02 00:16:04,518] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 101.11 | bwd_microstep: 126.10 | bwd_inner_microstep: 126.08 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 00:16:04,998] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.59 | bwd_microstep: 273.02 | bwd_inner_microstep: 273.01 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 842 +[2025-05-02 00:16:05,241] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.31 | bwd_microstep: 132.02 | bwd_inner_microstep: 131.92 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 00:16:05,720] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.46 | bwd_microstep: 272.73 | bwd_inner_microstep: 272.71 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 00:16:06,199] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.37 | bwd_microstep: 273.02 | bwd_inner_microstep: 273.01 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 00:16:06,678] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.29 | bwd_microstep: 273.11 | bwd_inner_microstep: 273.10 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 00:16:07,162] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.18 | bwd_microstep: 273.09 | bwd_inner_microstep: 273.07 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 00:16:07,644] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.93 | bwd_microstep: 271.51 | bwd_inner_microstep: 271.49 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1340 +[2025-05-02 00:16:08,011] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 143.07 | bwd_microstep: 204.35 | bwd_inner_microstep: 204.34 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1084 +[2025-05-02 00:16:08,305] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 117.56 | bwd_microstep: 159.65 | bwd_inner_microstep: 159.54 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.09 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 317 +[2025-05-02 00:16:08,645] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 3.78 | optimizer_step: 20.53 +[2025-05-02 00:16:08,646] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 79.80 | bwd_microstep: 214.61 | bwd_inner_microstep: 136.54 | bwd_allreduce_microstep: 77.91 | step_microstep: 30.81 +[2025-05-02 00:16:08,647] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2431.71 | bwd: 3560.80 | bwd_inner: 3481.90 | bwd_allreduce: 78.27 | step: 32.02 + 8%|▊ | 739/8720 [2:00:42<15:20:00, 6.92s/it] {'loss': 0.9493, 'grad_norm': 5.970356464385986, 'learning_rate': 9.921728296567897e-06, 'epoch': 0.85} + 8%|▊ | 739/8720 [2:00:42<15:20:00, 6.92s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1957 +[2025-05-02 00:16:09,157] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 197.66 | bwd_microstep: 289.63 | bwd_inner_microstep: 289.62 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 435 +[2025-05-02 00:16:09,365] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 76.83 | bwd_microstep: 117.17 | bwd_inner_microstep: 116.84 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1890 +[2025-05-02 00:16:09,845] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.49 | bwd_microstep: 275.06 | bwd_inner_microstep: 275.04 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 00:16:10,323] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.94 | bwd_microstep: 273.60 | bwd_inner_microstep: 273.58 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.15 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-02 00:16:10,805] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.79 | bwd_microstep: 274.65 | bwd_inner_microstep: 274.63 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 00:16:11,284] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.34 | bwd_microstep: 273.65 | bwd_inner_microstep: 273.63 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 00:16:11,762] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.36 | bwd_microstep: 273.59 | bwd_inner_microstep: 273.57 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 00:16:12,240] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.12 | bwd_microstep: 272.94 | bwd_inner_microstep: 272.92 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 00:16:12,719] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.92 | bwd_microstep: 273.88 | bwd_inner_microstep: 273.86 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 00:16:13,198] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.87 | bwd_microstep: 273.32 | bwd_inner_microstep: 273.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 00:16:13,678] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.66 | bwd_microstep: 272.93 | bwd_inner_microstep: 272.91 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 00:16:14,158] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.74 | bwd_microstep: 272.71 | bwd_inner_microstep: 272.69 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1345 +[2025-05-02 00:16:14,522] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.63 | bwd_microstep: 205.63 | bwd_inner_microstep: 205.50 | bwd_allreduce_microstep: 0.03 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 00:16:15,001] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.59 | bwd_microstep: 271.54 | bwd_inner_microstep: 271.53 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 00:16:15,483] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.73 | bwd_microstep: 271.95 | bwd_inner_microstep: 271.94 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 00:16:16,078] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 3.04 | optimizer_step: 17.33 +[2025-05-02 00:16:16,078] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.68 | bwd_microstep: 358.80 | bwd_inner_microstep: 272.09 | bwd_allreduce_microstep: 86.66 | step_microstep: 26.01 +[2025-05-02 00:16:16,079] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2873.00 | bwd: 4251.11 | bwd_inner: 4163.71 | bwd_allreduce: 86.95 | step: 27.05 + 8%|▊ | 740/8720 [2:00:49<15:40:28, 7.07s/it] {'loss': 0.9782, 'grad_norm': 5.329863548278809, 'learning_rate': 9.921400632764523e-06, 'epoch': 0.85} + 8%|▊ | 740/8720 [2:00:49<15:40:28, 7.07s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-02 00:16:16,566] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.60 | bwd_microstep: 273.89 | bwd_inner_microstep: 273.88 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-02 00:16:17,046] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.72 | bwd_microstep: 273.39 | bwd_inner_microstep: 273.38 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 00:16:17,528] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.36 | bwd_microstep: 273.61 | bwd_inner_microstep: 273.60 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 340 +[2025-05-02 00:16:17,749] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 81.94 | bwd_microstep: 123.08 | bwd_inner_microstep: 122.93 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 00:16:18,229] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.64 | bwd_microstep: 273.94 | bwd_inner_microstep: 273.92 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 331 +[2025-05-02 00:16:18,456] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 89.62 | bwd_microstep: 119.04 | bwd_inner_microstep: 118.89 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 00:16:18,935] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.56 | bwd_microstep: 273.58 | bwd_inner_microstep: 273.56 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-02 00:16:19,417] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.43 | bwd_microstep: 274.39 | bwd_inner_microstep: 274.37 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 00:16:19,895] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.62 | bwd_microstep: 273.72 | bwd_inner_microstep: 273.70 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 00:16:20,371] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.11 | bwd_microstep: 273.16 | bwd_inner_microstep: 273.15 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 00:16:20,845] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.01 | bwd_microstep: 271.49 | bwd_inner_microstep: 271.47 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 00:16:21,321] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.83 | bwd_microstep: 271.60 | bwd_inner_microstep: 271.58 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 00:16:21,797] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.16 | bwd_microstep: 272.62 | bwd_inner_microstep: 272.60 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 00:16:22,272] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.75 | bwd_microstep: 271.75 | bwd_inner_microstep: 271.73 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 00:16:22,746] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.54 | bwd_microstep: 271.51 | bwd_inner_microstep: 271.49 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 00:16:23,310] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.20 | optimizer_step: 17.07 +[2025-05-02 00:16:23,311] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.64 | bwd_microstep: 336.80 | bwd_inner_microstep: 271.55 | bwd_allreduce_microstep: 65.21 | step_microstep: 24.87 +[2025-05-02 00:16:23,313] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2813.24 | bwd: 4127.60 | bwd_inner: 4061.84 | bwd_allreduce: 65.40 | step: 25.71 + 8%|▊ | 741/8720 [2:00:57<15:46:49, 7.12s/it] {'loss': 0.9652, 'grad_norm': 6.777255535125732, 'learning_rate': 9.921072289987219e-06, 'epoch': 0.85} + 8%|▊ | 741/8720 [2:00:57<15:46:49, 7.12s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1953 +[2025-05-02 00:16:23,820] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 196.38 | bwd_microstep: 289.10 | bwd_inner_microstep: 289.08 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 879 +[2025-05-02 00:16:24,064] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.31 | bwd_microstep: 135.33 | bwd_inner_microstep: 135.31 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1893 +[2025-05-02 00:16:24,544] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.26 | bwd_microstep: 275.24 | bwd_inner_microstep: 275.22 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 00:16:25,022] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.12 | bwd_microstep: 273.49 | bwd_inner_microstep: 273.48 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 00:16:25,500] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.19 | bwd_microstep: 273.57 | bwd_inner_microstep: 273.55 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-02 00:16:25,978] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.52 | bwd_microstep: 273.30 | bwd_inner_microstep: 273.28 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 00:16:26,454] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.80 | bwd_microstep: 273.19 | bwd_inner_microstep: 273.17 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 00:16:26,931] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.68 | bwd_microstep: 273.44 | bwd_inner_microstep: 273.42 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 00:16:27,407] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.97 | bwd_microstep: 273.05 | bwd_inner_microstep: 273.03 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 00:16:27,884] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.84 | bwd_microstep: 273.06 | bwd_inner_microstep: 273.04 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 00:16:28,361] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.52 | bwd_microstep: 273.15 | bwd_inner_microstep: 273.14 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 00:16:28,837] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.93 | bwd_microstep: 272.06 | bwd_inner_microstep: 272.04 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 00:16:29,312] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.58 | bwd_microstep: 272.31 | bwd_inner_microstep: 272.29 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 00:16:29,787] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.72 | bwd_microstep: 271.77 | bwd_inner_microstep: 271.76 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 00:16:30,263] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.55 | bwd_microstep: 272.08 | bwd_inner_microstep: 272.06 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 320 +[2025-05-02 00:16:30,564] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.15 | optimizer_step: 17.58 +[2025-05-02 00:16:30,564] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 66.82 | bwd_microstep: 196.74 | bwd_inner_microstep: 130.48 | bwd_allreduce_microstep: 66.17 | step_microstep: 24.89 +[2025-05-02 00:16:30,565] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2811.95 | bwd: 4170.88 | bwd_inner: 4104.38 | bwd_allreduce: 66.24 | step: 25.52 + 9%|▊ | 742/8720 [2:01:04<15:51:55, 7.16s/it] {'loss': 0.9457, 'grad_norm': 5.066812515258789, 'learning_rate': 9.920743268281285e-06, 'epoch': 0.85} + 9%|▊ | 742/8720 [2:01:04<15:51:55, 7.16s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1991 +[2025-05-02 00:16:31,076] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 197.24 | bwd_microstep: 293.94 | bwd_inner_microstep: 293.92 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1894 +[2025-05-02 00:16:31,558] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.15 | bwd_microstep: 276.04 | bwd_inner_microstep: 276.02 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-02 00:16:32,037] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.77 | bwd_microstep: 275.05 | bwd_inner_microstep: 275.03 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-02 00:16:32,517] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.88 | bwd_microstep: 274.52 | bwd_inner_microstep: 274.50 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-02 00:16:32,997] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.79 | bwd_microstep: 274.32 | bwd_inner_microstep: 274.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 00:16:33,474] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.04 | bwd_microstep: 273.12 | bwd_inner_microstep: 273.10 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 00:16:33,951] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.78 | bwd_microstep: 273.49 | bwd_inner_microstep: 273.47 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 837 +[2025-05-02 00:16:34,181] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 90.74 | bwd_microstep: 126.24 | bwd_inner_microstep: 126.22 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 00:16:34,658] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.91 | bwd_microstep: 273.01 | bwd_inner_microstep: 272.99 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 00:16:35,136] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.39 | bwd_microstep: 273.38 | bwd_inner_microstep: 273.36 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 00:16:35,613] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.81 | bwd_microstep: 273.13 | bwd_inner_microstep: 273.11 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 831 +[2025-05-02 00:16:35,850] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 92.78 | bwd_microstep: 130.24 | bwd_inner_microstep: 130.22 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 00:16:36,324] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.68 | bwd_microstep: 271.53 | bwd_inner_microstep: 271.51 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 00:16:36,799] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.26 | bwd_microstep: 271.47 | bwd_inner_microstep: 271.45 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 00:16:37,273] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.67 | bwd_microstep: 271.24 | bwd_inner_microstep: 271.21 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1849 +[2025-05-02 00:16:37,837] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.04 | optimizer_gradients: 2.20 | optimizer_step: 17.11 +[2025-05-02 00:16:37,837] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.18 | bwd_microstep: 336.79 | bwd_inner_microstep: 271.54 | bwd_allreduce_microstep: 65.21 | step_microstep: 24.14 +[2025-05-02 00:16:37,838] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2837.82 | bwd: 4167.49 | bwd_inner: 4101.96 | bwd_allreduce: 65.28 | step: 24.80 + 9%|▊ | 743/8720 [2:01:11<15:56:20, 7.19s/it] {'loss': 1.0253, 'grad_norm': 6.323126792907715, 'learning_rate': 9.920413567692113e-06, 'epoch': 0.85} + 9%|▊ | 743/8720 [2:01:11<15:56:20, 7.19s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1974 +[2025-05-02 00:16:38,346] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 196.46 | bwd_microstep: 291.15 | bwd_inner_microstep: 291.13 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1387 +[2025-05-02 00:16:38,710] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.24 | bwd_microstep: 208.96 | bwd_inner_microstep: 208.94 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1893 +[2025-05-02 00:16:39,190] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.05 | bwd_microstep: 275.51 | bwd_inner_microstep: 275.50 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 340 +[2025-05-02 00:16:39,386] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 67.10 | bwd_microstep: 115.86 | bwd_inner_microstep: 115.73 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 00:16:39,862] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.40 | bwd_microstep: 274.08 | bwd_inner_microstep: 274.07 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-02 00:16:40,340] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.87 | bwd_microstep: 273.89 | bwd_inner_microstep: 273.87 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 00:16:40,817] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.95 | bwd_microstep: 273.23 | bwd_inner_microstep: 273.22 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 00:16:41,296] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.55 | bwd_microstep: 273.68 | bwd_inner_microstep: 273.66 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 331 +[2025-05-02 00:16:41,493] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 67.36 | bwd_microstep: 116.37 | bwd_inner_microstep: 116.25 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 00:16:41,969] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.39 | bwd_microstep: 273.02 | bwd_inner_microstep: 273.00 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 00:16:42,446] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.25 | bwd_microstep: 273.08 | bwd_inner_microstep: 273.06 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 00:16:42,922] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.18 | bwd_microstep: 272.83 | bwd_inner_microstep: 272.81 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 00:16:43,397] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.20 | bwd_microstep: 272.01 | bwd_inner_microstep: 272.00 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 00:16:43,873] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.39 | bwd_microstep: 271.85 | bwd_inner_microstep: 271.84 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1933 +[2025-05-02 00:16:44,372] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 196.30 | bwd_microstep: 287.90 | bwd_inner_microstep: 287.88 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 00:16:44,937] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.13 | optimizer_step: 17.52 +[2025-05-02 00:16:44,938] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.19 | bwd_microstep: 337.86 | bwd_inner_microstep: 272.12 | bwd_allreduce_microstep: 65.70 | step_microstep: 24.79 +[2025-05-02 00:16:44,939] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2741.63 | bwd: 4091.33 | bwd_inner: 4025.12 | bwd_allreduce: 65.87 | step: 25.51 + 9%|▊ | 744/8720 [2:01:18<15:52:31, 7.17s/it] {'loss': 1.1526, 'grad_norm': 4.20751953125, 'learning_rate': 9.92008318826519e-06, 'epoch': 0.85} + 9%|▊ | 744/8720 [2:01:18<15:52:31, 7.17s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1941 +[2025-05-02 00:16:45,442] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.32 | bwd_microstep: 288.27 | bwd_inner_microstep: 288.25 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1386 +[2025-05-02 00:16:45,807] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.58 | bwd_microstep: 208.87 | bwd_inner_microstep: 208.85 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 00:16:46,285] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.02 | bwd_microstep: 273.99 | bwd_inner_microstep: 273.97 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-02 00:16:46,763] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.59 | bwd_microstep: 274.37 | bwd_inner_microstep: 274.35 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-02 00:16:47,240] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.02 | bwd_microstep: 274.00 | bwd_inner_microstep: 273.98 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 00:16:47,718] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.93 | bwd_microstep: 273.47 | bwd_inner_microstep: 273.46 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-02 00:16:48,195] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.94 | bwd_microstep: 273.97 | bwd_inner_microstep: 273.95 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-02 00:16:48,675] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.36 | bwd_microstep: 274.86 | bwd_inner_microstep: 274.77 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.23 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1089 +[2025-05-02 00:16:48,979] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 116.89 | bwd_microstep: 161.96 | bwd_inner_microstep: 161.94 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 00:16:49,465] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 197.06 | bwd_microstep: 273.33 | bwd_inner_microstep: 273.31 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 00:16:49,940] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.62 | bwd_microstep: 272.49 | bwd_inner_microstep: 272.48 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 00:16:50,418] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.44 | bwd_microstep: 273.45 | bwd_inner_microstep: 273.43 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 00:16:50,910] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.63 | bwd_microstep: 275.16 | bwd_inner_microstep: 275.10 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 00:16:51,456] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 215.06 | bwd_microstep: 310.38 | bwd_inner_microstep: 310.36 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 00:16:51,947] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 199.60 | bwd_microstep: 271.70 | bwd_inner_microstep: 271.69 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.15 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 00:16:52,550] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.21 | optimizer_gradients: 2.29 | optimizer_step: 18.49 +[2025-05-02 00:16:52,551] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.75 | bwd_microstep: 357.40 | bwd_inner_microstep: 273.66 | bwd_allreduce_microstep: 83.69 | step_microstep: 28.36 +[2025-05-02 00:16:52,553] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2954.57 | bwd: 4337.69 | bwd_inner: 4253.56 | bwd_allreduce: 83.83 | step: 29.47 + 9%|▊ | 745/8720 [2:01:26<16:10:30, 7.30s/it] {'loss': 1.5763, 'grad_norm': 7.707737922668457, 'learning_rate': 9.919752130046096e-06, 'epoch': 0.85} + 9%|▊ | 745/8720 [2:01:26<16:10:30, 7.30s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1899 +[2025-05-02 00:16:53,859] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 256.78 | bwd_microstep: 1020.79 | bwd_inner_microstep: 1020.77 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.13 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1370 +[2025-05-02 00:16:55,228] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 481.42 | bwd_microstep: 868.28 | bwd_inner_microstep: 868.23 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.13 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-02 00:16:57,476] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1069.66 | bwd_microstep: 1158.71 | bwd_inner_microstep: 1158.69 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-02 00:17:00,296] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1159.48 | bwd_microstep: 1598.58 | bwd_inner_microstep: 1598.56 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 00:17:02,196] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 926.57 | bwd_microstep: 953.95 | bwd_inner_microstep: 953.93 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 00:17:02,671] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.88 | bwd_microstep: 271.63 | bwd_inner_microstep: 271.62 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 327 +[2025-05-02 00:17:02,895] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 76.88 | bwd_microstep: 129.55 | bwd_inner_microstep: 129.14 | bwd_allreduce_microstep: 0.16 | step_microstep: 0.25 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 324 +[2025-05-02 00:17:03,106] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 68.29 | bwd_microstep: 126.95 | bwd_inner_microstep: 126.80 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 00:17:03,585] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.25 | bwd_microstep: 271.93 | bwd_inner_microstep: 271.86 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.22 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 00:17:04,062] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.18 | bwd_microstep: 270.79 | bwd_inner_microstep: 270.77 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1345 +[2025-05-02 00:17:04,424] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 139.84 | bwd_microstep: 204.99 | bwd_inner_microstep: 204.89 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 00:17:04,901] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.70 | bwd_microstep: 271.76 | bwd_inner_microstep: 271.75 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 00:17:05,376] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.94 | bwd_microstep: 270.45 | bwd_inner_microstep: 270.43 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 00:17:05,851] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.57 | bwd_microstep: 270.37 | bwd_inner_microstep: 270.35 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 00:17:06,327] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.22 | bwd_microstep: 270.76 | bwd_inner_microstep: 270.75 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1901 +[2025-05-02 00:17:06,915] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.29 | optimizer_step: 17.36 +[2025-05-02 00:17:06,916] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.92 | bwd_microstep: 354.18 | bwd_inner_microstep: 275.71 | bwd_allreduce_microstep: 78.37 | step_microstep: 25.63 +[2025-05-02 00:17:06,917] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 5682.29 | bwd: 8313.85 | bwd_inner: 8234.36 | bwd_allreduce: 78.74 | step: 27.28 + 9%|▊ | 746/8720 [2:01:40<20:52:01, 9.42s/it] {'loss': 0.79, 'grad_norm': 6.76314640045166, 'learning_rate': 9.919420393080505e-06, 'epoch': 0.86} + 9%|▊ | 746/8720 [2:01:40<20:52:01, 9.42s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1897 +[2025-05-02 00:17:07,409] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.47 | bwd_microstep: 273.86 | bwd_inner_microstep: 273.84 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1897 +[2025-05-02 00:17:07,892] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.62 | bwd_microstep: 274.93 | bwd_inner_microstep: 274.91 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1893 +[2025-05-02 00:17:08,373] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.24 | bwd_microstep: 274.28 | bwd_inner_microstep: 274.26 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1883 +[2025-05-02 00:17:08,853] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.20 | bwd_microstep: 273.30 | bwd_inner_microstep: 273.28 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 00:17:09,330] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.38 | bwd_microstep: 272.23 | bwd_inner_microstep: 272.22 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-02 00:17:09,809] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.81 | bwd_microstep: 272.58 | bwd_inner_microstep: 272.56 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 00:17:10,288] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.73 | bwd_microstep: 271.69 | bwd_inner_microstep: 271.67 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.14 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 00:17:10,769] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.33 | bwd_microstep: 271.60 | bwd_inner_microstep: 271.58 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 00:17:11,253] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.86 | bwd_microstep: 271.54 | bwd_inner_microstep: 271.52 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 00:17:11,738] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.87 | bwd_microstep: 271.37 | bwd_inner_microstep: 271.35 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 00:17:12,223] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.88 | bwd_microstep: 271.71 | bwd_inner_microstep: 271.69 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 00:17:12,708] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.34 | bwd_microstep: 270.09 | bwd_inner_microstep: 270.07 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 00:17:13,185] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.85 | bwd_microstep: 270.90 | bwd_inner_microstep: 270.88 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 00:17:13,663] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.59 | bwd_microstep: 270.89 | bwd_inner_microstep: 270.83 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.07 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 00:17:14,145] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.69 | bwd_microstep: 270.85 | bwd_inner_microstep: 270.83 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-02 00:17:14,741] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.07 | optimizer_gradients: 4.20 | optimizer_step: 20.78 +[2025-05-02 00:17:14,741] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.12 | bwd_microstep: 351.66 | bwd_inner_microstep: 273.71 | bwd_allreduce_microstep: 77.88 | step_microstep: 32.03 +[2025-05-02 00:17:14,743] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 3006.55 | bwd: 4433.49 | bwd_inner: 4355.22 | bwd_allreduce: 77.99 | step: 33.31 + 9%|▊ | 747/8720 [2:01:48<19:48:09, 8.94s/it] {'loss': 1.0164, 'grad_norm': 4.908529281616211, 'learning_rate': 9.919087977414183e-06, 'epoch': 0.86} + 9%|▊ | 747/8720 [2:01:48<19:48:09, 8.94s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1899 +[2025-05-02 00:17:15,231] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.83 | bwd_microstep: 274.36 | bwd_inner_microstep: 274.34 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1887 +[2025-05-02 00:17:15,716] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.21 | bwd_microstep: 274.77 | bwd_inner_microstep: 274.75 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.14 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-02 00:17:16,201] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.43 | bwd_microstep: 273.37 | bwd_inner_microstep: 273.35 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 00:17:16,682] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.65 | bwd_microstep: 272.37 | bwd_inner_microstep: 272.36 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 00:17:17,164] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.33 | bwd_microstep: 272.61 | bwd_inner_microstep: 272.59 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 00:17:17,644] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.30 | bwd_microstep: 272.58 | bwd_inner_microstep: 272.56 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 00:17:18,127] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.83 | bwd_microstep: 272.93 | bwd_inner_microstep: 272.91 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 00:17:18,605] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.39 | bwd_microstep: 271.80 | bwd_inner_microstep: 271.78 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1346 +[2025-05-02 00:17:18,969] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.68 | bwd_microstep: 205.01 | bwd_inner_microstep: 204.85 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 00:17:19,448] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.33 | bwd_microstep: 270.77 | bwd_inner_microstep: 270.76 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 00:17:19,926] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.68 | bwd_microstep: 271.09 | bwd_inner_microstep: 271.08 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 00:17:20,403] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.89 | bwd_microstep: 270.96 | bwd_inner_microstep: 270.94 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1988 +[2025-05-02 00:17:20,912] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 198.44 | bwd_microstep: 293.63 | bwd_inner_microstep: 293.61 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1915 +[2025-05-02 00:17:21,399] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.12 | bwd_microstep: 276.55 | bwd_inner_microstep: 276.54 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1908 +[2025-05-02 00:17:21,883] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.25 | bwd_microstep: 276.23 | bwd_inner_microstep: 276.21 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 00:17:22,475] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.25 | optimizer_step: 18.00 +[2025-05-02 00:17:22,476] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.28 | bwd_microstep: 358.74 | bwd_inner_microstep: 273.25 | bwd_allreduce_microstep: 85.43 | step_microstep: 26.87 +[2025-05-02 00:17:22,477] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2986.24 | bwd: 4407.80 | bwd_inner: 4321.88 | bwd_allreduce: 85.60 | step: 27.93 + 9%|▊ | 748/8720 [2:01:56<18:59:47, 8.58s/it] {'loss': 1.3595, 'grad_norm': 10.319784164428711, 'learning_rate': 9.918754883092995e-06, 'epoch': 0.86} + 9%|▊ | 748/8720 [2:01:56<18:59:47, 8.58s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 383 +[2025-05-02 00:17:22,697] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 83.06 | bwd_microstep: 117.37 | bwd_inner_microstep: 117.08 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1893 +[2025-05-02 00:17:23,178] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.02 | bwd_microstep: 275.50 | bwd_inner_microstep: 275.48 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-02 00:17:23,658] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.66 | bwd_microstep: 273.76 | bwd_inner_microstep: 273.74 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 329 +[2025-05-02 00:17:23,880] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 92.93 | bwd_microstep: 115.81 | bwd_inner_microstep: 115.66 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.09 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 844 +[2025-05-02 00:17:24,128] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 101.00 | bwd_microstep: 131.97 | bwd_inner_microstep: 131.78 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 00:17:24,606] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.84 | bwd_microstep: 272.63 | bwd_inner_microstep: 272.57 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 00:17:25,085] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.16 | bwd_microstep: 273.37 | bwd_inner_microstep: 273.35 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.20 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 842 +[2025-05-02 00:17:25,338] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 106.42 | bwd_microstep: 131.55 | bwd_inner_microstep: 131.25 | bwd_allreduce_microstep: 0.14 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 00:17:25,819] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.42 | bwd_microstep: 273.57 | bwd_inner_microstep: 273.55 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.21 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 00:17:26,301] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.28 | bwd_microstep: 273.15 | bwd_inner_microstep: 273.13 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.17 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 836 +[2025-05-02 00:17:26,558] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 113.13 | bwd_microstep: 125.58 | bwd_inner_microstep: 125.29 | bwd_allreduce_microstep: 0.15 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 00:17:27,040] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.56 | bwd_microstep: 271.91 | bwd_inner_microstep: 271.90 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 317 +[2025-05-02 00:17:27,284] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 109.80 | bwd_microstep: 117.70 | bwd_inner_microstep: 117.46 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 00:17:27,764] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.23 | bwd_microstep: 271.49 | bwd_inner_microstep: 271.47 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 00:17:28,245] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.88 | bwd_microstep: 271.24 | bwd_inner_microstep: 271.22 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 354 +[2025-05-02 00:17:28,645] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.24 | optimizer_step: 17.29 +[2025-05-02 00:17:28,645] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 118.36 | bwd_microstep: 236.81 | bwd_inner_microstep: 136.88 | bwd_allreduce_microstep: 99.82 | step_microstep: 27.00 +[2025-05-02 00:17:28,647] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2428.36 | bwd: 3433.54 | bwd_inner: 3332.12 | bwd_allreduce: 100.45 | step: 28.52 + 9%|▊ | 749/8720 [2:02:02<17:23:42, 7.86s/it] {'loss': 1.2407, 'grad_norm': 10.4559965133667, 'learning_rate': 9.918421110162893e-06, 'epoch': 0.86} + 9%|▊ | 749/8720 [2:02:02<17:23:42, 7.86s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1949 +[2025-05-02 00:17:29,155] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 196.03 | bwd_microstep: 288.32 | bwd_inner_microstep: 288.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1905 +[2025-05-02 00:17:29,638] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.00 | bwd_microstep: 275.77 | bwd_inner_microstep: 275.75 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1902 +[2025-05-02 00:17:30,122] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.10 | bwd_microstep: 275.67 | bwd_inner_microstep: 275.65 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-02 00:17:30,600] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.96 | bwd_microstep: 274.04 | bwd_inner_microstep: 274.03 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-02 00:17:31,079] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.52 | bwd_microstep: 273.71 | bwd_inner_microstep: 273.69 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.23 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 00:17:31,556] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.27 | bwd_microstep: 272.72 | bwd_inner_microstep: 272.71 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 00:17:32,033] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.62 | bwd_microstep: 272.67 | bwd_inner_microstep: 272.65 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 00:17:32,509] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.23 | bwd_microstep: 272.49 | bwd_inner_microstep: 272.47 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 842 +[2025-05-02 00:17:32,754] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 97.99 | bwd_microstep: 131.60 | bwd_inner_microstep: 131.57 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 324 +[2025-05-02 00:17:32,984] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 98.51 | bwd_microstep: 117.54 | bwd_inner_microstep: 117.38 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 00:17:33,463] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.56 | bwd_microstep: 272.57 | bwd_inner_microstep: 272.56 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 00:17:33,943] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.19 | bwd_microstep: 272.45 | bwd_inner_microstep: 272.44 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.20 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 325 +[2025-05-02 00:17:34,187] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 104.71 | bwd_microstep: 121.87 | bwd_inner_microstep: 121.71 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 00:17:34,666] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.97 | bwd_microstep: 272.08 | bwd_inner_microstep: 272.07 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 00:17:35,144] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.09 | bwd_microstep: 271.18 | bwd_inner_microstep: 271.16 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 00:17:35,749] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.24 | optimizer_step: 17.20 +[2025-05-02 00:17:35,749] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.16 | bwd_microstep: 370.99 | bwd_inner_microstep: 271.59 | bwd_allreduce_microstep: 99.35 | step_microstep: 26.85 +[2025-05-02 00:17:35,751] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2762.54 | bwd: 4035.75 | bwd_inner: 3935.78 | bwd_allreduce: 99.56 | step: 28.13 + 9%|▊ | 750/8720 [2:02:09<16:53:34, 7.63s/it] {'loss': 0.7348, 'grad_norm': 7.877056121826172, 'learning_rate': 9.918086658669926e-06, 'epoch': 0.86} + 9%|▊ | 750/8720 [2:02:09<16:53:34, 7.63s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1911 +[2025-05-02 00:17:36,241] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 191.30 | bwd_microstep: 275.87 | bwd_inner_microstep: 275.86 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-02 00:17:36,722] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.91 | bwd_microstep: 273.78 | bwd_inner_microstep: 273.76 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.16 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-02 00:17:37,202] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.60 | bwd_microstep: 274.48 | bwd_inner_microstep: 274.47 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 344 +[2025-05-02 00:17:37,440] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 104.36 | bwd_microstep: 117.91 | bwd_inner_microstep: 117.65 | bwd_allreduce_microstep: 0.09 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-02 00:17:37,924] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.41 | bwd_microstep: 273.75 | bwd_inner_microstep: 273.73 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 00:17:38,403] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.57 | bwd_microstep: 272.41 | bwd_inner_microstep: 272.40 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 00:17:38,884] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.73 | bwd_microstep: 272.80 | bwd_inner_microstep: 272.78 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-02 00:17:39,365] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.02 | bwd_microstep: 273.12 | bwd_inner_microstep: 273.10 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 00:17:39,848] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.37 | bwd_microstep: 272.65 | bwd_inner_microstep: 272.63 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 00:17:40,330] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.24 | bwd_microstep: 272.97 | bwd_inner_microstep: 272.95 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 00:17:40,814] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.32 | bwd_microstep: 272.53 | bwd_inner_microstep: 272.51 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 00:17:41,296] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.86 | bwd_microstep: 272.84 | bwd_inner_microstep: 272.82 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 00:17:41,779] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.61 | bwd_microstep: 272.86 | bwd_inner_microstep: 272.84 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 829 +[2025-05-02 00:17:42,036] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 108.27 | bwd_microstep: 129.92 | bwd_inner_microstep: 129.58 | bwd_allreduce_microstep: 0.14 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 00:17:42,514] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.65 | bwd_microstep: 271.32 | bwd_inner_microstep: 271.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1967 +[2025-05-02 00:17:43,150] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.26 | optimizer_step: 17.33 +[2025-05-02 00:17:43,150] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 199.96 | bwd_microstep: 390.26 | bwd_inner_microstep: 291.49 | bwd_allreduce_microstep: 98.70 | step_microstep: 26.92 +[2025-05-02 00:17:43,152] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2872.73 | bwd: 4189.54 | bwd_inner: 4090.02 | bwd_allreduce: 98.99 | step: 28.02 + 9%|▊ | 751/8720 [2:02:16<16:44:18, 7.56s/it] {'loss': 1.2295, 'grad_norm': 13.216157913208008, 'learning_rate': 9.917751528660236e-06, 'epoch': 0.86} + 9%|▊ | 751/8720 [2:02:16<16:44:18, 7.56s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1898 +[2025-05-02 00:17:43,641] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.73 | bwd_microstep: 274.92 | bwd_inner_microstep: 274.91 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1925 +[2025-05-02 00:17:44,141] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.49 | bwd_microstep: 287.66 | bwd_inner_microstep: 287.64 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1891 +[2025-05-02 00:17:44,623] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.58 | bwd_microstep: 274.90 | bwd_inner_microstep: 274.88 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 00:17:45,104] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.71 | bwd_microstep: 272.78 | bwd_inner_microstep: 272.76 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 00:17:45,584] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.79 | bwd_microstep: 272.82 | bwd_inner_microstep: 272.80 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 00:17:46,066] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.95 | bwd_microstep: 273.24 | bwd_inner_microstep: 273.22 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 00:17:46,546] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.74 | bwd_microstep: 272.88 | bwd_inner_microstep: 272.86 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 00:17:47,023] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.06 | bwd_microstep: 271.47 | bwd_inner_microstep: 271.46 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 00:17:47,499] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.88 | bwd_microstep: 271.39 | bwd_inner_microstep: 271.37 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 00:17:47,979] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.36 | bwd_microstep: 272.36 | bwd_inner_microstep: 272.34 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 00:17:48,461] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.33 | bwd_microstep: 272.24 | bwd_inner_microstep: 272.23 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 00:17:48,944] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.28 | bwd_microstep: 271.54 | bwd_inner_microstep: 271.52 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 00:17:49,421] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.78 | bwd_microstep: 271.32 | bwd_inner_microstep: 271.31 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.14 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 00:17:49,901] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.96 | bwd_microstep: 271.22 | bwd_inner_microstep: 271.21 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1493 +[2025-05-02 00:17:50,304] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 150.23 | bwd_microstep: 231.63 | bwd_inner_microstep: 231.52 | bwd_allreduce_microstep: 0.03 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1903 +[2025-05-02 00:17:50,905] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.12 | optimizer_step: 17.31 +[2025-05-02 00:17:50,906] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.25 | bwd_microstep: 362.42 | bwd_inner_microstep: 276.55 | bwd_allreduce_microstep: 85.82 | step_microstep: 25.85 +[2025-05-02 00:17:50,907] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2988.68 | bwd: 4424.83 | bwd_inner: 4338.57 | bwd_allreduce: 85.97 | step: 26.85 + 9%|▊ | 752/8720 [2:02:24<16:51:53, 7.62s/it] {'loss': 1.0774, 'grad_norm': 8.10831356048584, 'learning_rate': 9.91741572018006e-06, 'epoch': 0.86} + 9%|▊ | 752/8720 [2:02:24<16:51:53, 7.62s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1926 +[2025-05-02 00:17:51,412] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.56 | bwd_microstep: 287.12 | bwd_inner_microstep: 287.11 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1883 +[2025-05-02 00:17:51,896] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.30 | bwd_microstep: 274.45 | bwd_inner_microstep: 274.43 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-02 00:17:52,378] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.78 | bwd_microstep: 274.21 | bwd_inner_microstep: 274.19 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 00:17:52,857] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.90 | bwd_microstep: 272.86 | bwd_inner_microstep: 272.84 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-02 00:17:53,335] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.53 | bwd_microstep: 273.63 | bwd_inner_microstep: 273.61 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 00:17:53,812] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.62 | bwd_microstep: 273.03 | bwd_inner_microstep: 273.01 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 00:17:54,291] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.61 | bwd_microstep: 273.25 | bwd_inner_microstep: 273.24 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 00:17:54,770] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.29 | bwd_microstep: 272.97 | bwd_inner_microstep: 272.95 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.16 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 00:17:55,248] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.91 | bwd_microstep: 272.71 | bwd_inner_microstep: 272.69 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 00:17:55,728] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.19 | bwd_microstep: 272.97 | bwd_inner_microstep: 272.96 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 00:17:56,206] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.93 | bwd_microstep: 272.78 | bwd_inner_microstep: 272.76 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 00:17:56,682] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.33 | bwd_microstep: 272.57 | bwd_inner_microstep: 272.55 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 00:17:57,157] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.37 | bwd_microstep: 271.22 | bwd_inner_microstep: 271.20 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 00:17:57,632] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.45 | bwd_microstep: 271.47 | bwd_inner_microstep: 271.45 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.14 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 00:17:58,107] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.80 | bwd_microstep: 271.24 | bwd_inner_microstep: 271.22 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2054 +[2025-05-02 00:17:58,716] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.04 | optimizer_gradients: 2.59 | optimizer_step: 17.08 +[2025-05-02 00:17:58,717] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 201.31 | bwd_microstep: 369.11 | bwd_inner_microstep: 302.77 | bwd_allreduce_microstep: 66.30 | step_microstep: 24.51 +[2025-05-02 00:17:58,718] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 3042.59 | bwd: 4475.60 | bwd_inner: 4408.99 | bwd_allreduce: 66.38 | step: 25.48 + 9%|▊ | 753/8720 [2:02:32<16:59:18, 7.68s/it] {'loss': 0.7838, 'grad_norm': 5.821498870849609, 'learning_rate': 9.917079233275726e-06, 'epoch': 0.86} + 9%|▊ | 753/8720 [2:02:32<16:59:18, 7.68s/it]dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1124 +[2025-05-02 00:17:59,015] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 115.16 | bwd_microstep: 163.19 | bwd_inner_microstep: 162.97 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1893 +[2025-05-02 00:17:59,495] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.18 | bwd_microstep: 275.14 | bwd_inner_microstep: 275.12 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.13 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-02 00:17:59,975] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.33 | bwd_microstep: 274.15 | bwd_inner_microstep: 274.14 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1883 +[2025-05-02 00:18:00,457] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.73 | bwd_microstep: 274.37 | bwd_inner_microstep: 274.35 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.13 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 00:18:00,939] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.49 | bwd_microstep: 273.13 | bwd_inner_microstep: 273.12 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 838 +[2025-05-02 00:18:01,186] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 100.63 | bwd_microstep: 126.36 | bwd_inner_microstep: 126.21 | bwd_allreduce_microstep: 0.10 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 00:18:01,671] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.31 | bwd_microstep: 273.03 | bwd_inner_microstep: 273.02 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 00:18:02,152] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.27 | bwd_microstep: 272.67 | bwd_inner_microstep: 272.65 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 00:18:02,636] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.47 | bwd_microstep: 272.75 | bwd_inner_microstep: 272.73 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 00:18:03,114] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.25 | bwd_microstep: 271.45 | bwd_inner_microstep: 271.43 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 00:18:03,594] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.91 | bwd_microstep: 271.02 | bwd_inner_microstep: 271.00 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 00:18:04,075] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.79 | bwd_microstep: 271.10 | bwd_inner_microstep: 271.08 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2053 +[2025-05-02 00:18:04,596] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 200.98 | bwd_microstep: 302.12 | bwd_inner_microstep: 302.10 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1930 +[2025-05-02 00:18:05,099] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 194.62 | bwd_microstep: 288.20 | bwd_inner_microstep: 288.18 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1416 +[2025-05-02 00:18:05,476] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 145.23 | bwd_microstep: 213.21 | bwd_inner_microstep: 213.02 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 00:18:06,063] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.20 | optimizer_step: 17.34 +[2025-05-02 00:18:06,063] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.13 | bwd_microstep: 354.14 | bwd_inner_microstep: 273.77 | bwd_allreduce_microstep: 80.32 | step_microstep: 25.14 +[2025-05-02 00:18:06,065] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2832.05 | bwd: 4176.12 | bwd_inner: 4094.91 | bwd_allreduce: 80.72 | step: 26.67 + 9%|▊ | 754/8720 [2:02:39<16:46:07, 7.58s/it] {'loss': 1.1249, 'grad_norm': 7.068643569946289, 'learning_rate': 9.916742067993658e-06, 'epoch': 0.86} + 9%|▊ | 754/8720 [2:02:39<16:46:07, 7.58s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1888 +[2025-05-02 00:18:06,552] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.14 | bwd_microstep: 274.04 | bwd_inner_microstep: 274.03 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-02 00:18:07,032] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.56 | bwd_microstep: 273.65 | bwd_inner_microstep: 273.63 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 00:18:07,514] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.43 | bwd_microstep: 273.14 | bwd_inner_microstep: 273.12 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 00:18:07,995] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.33 | bwd_microstep: 272.64 | bwd_inner_microstep: 272.60 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 00:18:08,478] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.67 | bwd_microstep: 273.32 | bwd_inner_microstep: 273.31 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 00:18:08,960] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.45 | bwd_microstep: 272.84 | bwd_inner_microstep: 272.82 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 847 +[2025-05-02 00:18:09,207] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 96.72 | bwd_microstep: 132.53 | bwd_inner_microstep: 132.29 | bwd_allreduce_microstep: 0.14 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 00:18:09,686] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.61 | bwd_microstep: 272.68 | bwd_inner_microstep: 272.67 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 00:18:10,166] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.92 | bwd_microstep: 272.59 | bwd_inner_microstep: 272.58 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.13 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 00:18:10,645] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.33 | bwd_microstep: 272.41 | bwd_inner_microstep: 272.39 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 00:18:11,125] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.32 | bwd_microstep: 272.42 | bwd_inner_microstep: 272.40 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.15 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 00:18:11,605] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.87 | bwd_microstep: 271.58 | bwd_inner_microstep: 271.56 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 00:18:12,083] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.97 | bwd_microstep: 271.57 | bwd_inner_microstep: 271.55 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 00:18:12,561] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.74 | bwd_microstep: 271.68 | bwd_inner_microstep: 271.66 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 00:18:13,040] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.53 | bwd_microstep: 271.46 | bwd_inner_microstep: 271.44 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 00:18:13,624] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.18 | optimizer_step: 17.01 +[2025-05-02 00:18:13,624] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.51 | bwd_microstep: 352.97 | bwd_inner_microstep: 272.13 | bwd_allreduce_microstep: 80.78 | step_microstep: 24.98 +[2025-05-02 00:18:13,626] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2930.71 | bwd: 4301.55 | bwd_inner: 4220.19 | bwd_allreduce: 80.99 | step: 26.13 + 9%|▊ | 755/8720 [2:02:47<16:45:20, 7.57s/it] {'loss': 0.9451, 'grad_norm': 5.667577266693115, 'learning_rate': 9.916404224380371e-06, 'epoch': 0.87} + 9%|▊ | 755/8720 [2:02:47<16:45:20, 7.57s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 362 +[2025-05-02 00:18:13,859] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 86.09 | bwd_microstep: 125.72 | bwd_inner_microstep: 125.45 | bwd_allreduce_microstep: 0.09 | step_microstep: 0.10 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 340 +[2025-05-02 00:18:14,093] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 81.76 | bwd_microstep: 135.56 | bwd_inner_microstep: 135.25 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1883 +[2025-05-02 00:18:14,573] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.22 | bwd_microstep: 274.23 | bwd_inner_microstep: 274.21 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1886 +[2025-05-02 00:18:15,056] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.80 | bwd_microstep: 274.37 | bwd_inner_microstep: 274.35 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 855 +[2025-05-02 00:18:15,309] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 100.70 | bwd_microstep: 132.80 | bwd_inner_microstep: 132.73 | bwd_allreduce_microstep: 0.03 | step_microstep: 0.10 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 334 +[2025-05-02 00:18:15,531] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 85.88 | bwd_microstep: 119.45 | bwd_inner_microstep: 119.28 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 00:18:16,013] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.05 | bwd_microstep: 272.96 | bwd_inner_microstep: 272.94 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 00:18:16,499] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.90 | bwd_microstep: 272.93 | bwd_inner_microstep: 272.92 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 00:18:16,983] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.29 | bwd_microstep: 272.80 | bwd_inner_microstep: 272.78 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 00:18:17,463] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.52 | bwd_microstep: 272.75 | bwd_inner_microstep: 272.73 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 00:18:17,943] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.04 | bwd_microstep: 272.54 | bwd_inner_microstep: 272.52 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 00:18:18,422] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.06 | bwd_microstep: 271.56 | bwd_inner_microstep: 271.54 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 00:18:18,901] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.97 | bwd_microstep: 271.54 | bwd_inner_microstep: 271.53 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 00:18:19,380] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.84 | bwd_microstep: 271.48 | bwd_inner_microstep: 271.47 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1340 +[2025-05-02 00:18:19,744] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.20 | bwd_microstep: 204.52 | bwd_inner_microstep: 204.35 | bwd_allreduce_microstep: 0.08 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1895 +[2025-05-02 00:18:20,332] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.18 | optimizer_step: 17.20 +[2025-05-02 00:18:20,332] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.35 | bwd_microstep: 354.30 | bwd_inner_microstep: 276.30 | bwd_allreduce_microstep: 77.95 | step_microstep: 25.17 +[2025-05-02 00:18:20,334] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2574.25 | bwd: 3799.62 | bwd_inner: 3720.53 | bwd_allreduce: 78.44 | step: 26.31 + 9%|▊ | 756/8720 [2:02:54<16:10:44, 7.31s/it] {'loss': 1.1558, 'grad_norm': 5.433504104614258, 'learning_rate': 9.916065702482476e-06, 'epoch': 0.87} + 9%|▊ | 756/8720 [2:02:54<16:10:44, 7.31s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1935 +[2025-05-02 00:18:20,841] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 196.07 | bwd_microstep: 288.50 | bwd_inner_microstep: 288.48 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1905 +[2025-05-02 00:18:21,329] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 191.02 | bwd_microstep: 276.81 | bwd_inner_microstep: 276.80 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1384 +[2025-05-02 00:18:21,700] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 144.38 | bwd_microstep: 209.08 | bwd_inner_microstep: 209.06 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 865 +[2025-05-02 00:18:21,948] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 97.65 | bwd_microstep: 134.04 | bwd_inner_microstep: 133.85 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1894 +[2025-05-02 00:18:22,432] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.78 | bwd_microstep: 275.65 | bwd_inner_microstep: 275.63 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.14 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 346 +[2025-05-02 00:18:22,676] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 103.01 | bwd_microstep: 123.00 | bwd_inner_microstep: 122.85 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1373 +[2025-05-02 00:18:23,043] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.74 | bwd_microstep: 208.04 | bwd_inner_microstep: 207.88 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-02 00:18:23,524] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.51 | bwd_microstep: 273.90 | bwd_inner_microstep: 273.88 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.15 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 00:18:24,006] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.61 | bwd_microstep: 273.01 | bwd_inner_microstep: 272.99 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.15 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 00:18:24,487] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.42 | bwd_microstep: 273.30 | bwd_inner_microstep: 273.28 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 847 +[2025-05-02 00:18:24,736] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 97.60 | bwd_microstep: 132.52 | bwd_inner_microstep: 132.32 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 840 +[2025-05-02 00:18:24,974] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.36 | bwd_microstep: 126.31 | bwd_inner_microstep: 126.23 | bwd_allreduce_microstep: 0.04 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 00:18:25,453] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.52 | bwd_microstep: 272.57 | bwd_inner_microstep: 272.55 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 00:18:25,935] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.21 | bwd_microstep: 271.27 | bwd_inner_microstep: 271.26 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 828 +[2025-05-02 00:18:26,183] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 98.10 | bwd_microstep: 129.89 | bwd_inner_microstep: 129.67 | bwd_allreduce_microstep: 0.10 | step_microstep: 0.17 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 00:18:26,763] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.18 | optimizer_step: 17.11 +[2025-05-02 00:18:26,763] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.16 | bwd_microstep: 348.90 | bwd_inner_microstep: 271.84 | bwd_allreduce_microstep: 77.01 | step_microstep: 24.80 +[2025-05-02 00:18:26,765] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2486.77 | bwd: 3616.91 | bwd_inner: 3538.63 | bwd_allreduce: 77.57 | step: 26.53 + 9%|▊ | 757/8720 [2:03:00<15:35:28, 7.05s/it] {'loss': 1.0835, 'grad_norm': 3.6541361808776855, 'learning_rate': 9.915726502346677e-06, 'epoch': 0.87} + 9%|▊ | 757/8720 [2:03:00<15:35:28, 7.05s/it]dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1234 +[2025-05-02 00:18:27,085] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 121.29 | bwd_microstep: 177.11 | bwd_inner_microstep: 176.86 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1911 +[2025-05-02 00:18:27,570] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.73 | bwd_microstep: 276.57 | bwd_inner_microstep: 276.55 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1907 +[2025-05-02 00:18:28,054] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.71 | bwd_microstep: 276.25 | bwd_inner_microstep: 276.24 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1892 +[2025-05-02 00:18:28,536] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.34 | bwd_microstep: 275.09 | bwd_inner_microstep: 275.07 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-02 00:18:29,018] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.47 | bwd_microstep: 274.71 | bwd_inner_microstep: 274.67 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-02 00:18:29,503] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.63 | bwd_microstep: 274.37 | bwd_inner_microstep: 274.35 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-02 00:18:29,987] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 191.44 | bwd_microstep: 274.07 | bwd_inner_microstep: 274.05 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 00:18:30,467] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.99 | bwd_microstep: 273.06 | bwd_inner_microstep: 273.04 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 341 +[2025-05-02 00:18:30,694] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 86.18 | bwd_microstep: 123.97 | bwd_inner_microstep: 123.81 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-02 00:18:31,174] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.84 | bwd_microstep: 273.32 | bwd_inner_microstep: 273.31 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1361 +[2025-05-02 00:18:31,541] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.42 | bwd_microstep: 206.90 | bwd_inner_microstep: 206.77 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 00:18:32,024] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.00 | bwd_microstep: 272.99 | bwd_inner_microstep: 272.97 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 836 +[2025-05-02 00:18:32,263] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.49 | bwd_microstep: 128.43 | bwd_inner_microstep: 128.22 | bwd_allreduce_microstep: 0.09 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 00:18:32,743] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.06 | bwd_microstep: 272.70 | bwd_inner_microstep: 272.69 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 827 +[2025-05-02 00:18:32,982] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.55 | bwd_microstep: 130.26 | bwd_inner_microstep: 130.19 | bwd_allreduce_microstep: 0.03 | step_microstep: 0.12 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1337 +[2025-05-02 00:18:33,449] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.23 | optimizer_step: 17.25 +[2025-05-02 00:18:33,450] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 142.40 | bwd_microstep: 283.54 | bwd_inner_microstep: 204.60 | bwd_allreduce_microstep: 78.79 | step_microstep: 25.20 +[2025-05-02 00:18:33,451] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2575.16 | bwd: 3793.45 | bwd_inner: 3713.52 | bwd_allreduce: 79.20 | step: 26.43 + 9%|▊ | 758/8720 [2:03:07<15:20:57, 6.94s/it] {'loss': 1.1035, 'grad_norm': 5.639096736907959, 'learning_rate': 9.915386624019772e-06, 'epoch': 0.87} + 9%|▊ | 758/8720 [2:03:07<15:20:57, 6.94s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2628 +[2025-05-02 00:18:34,075] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 230.35 | bwd_microstep: 370.34 | bwd_inner_microstep: 370.32 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1944 +[2025-05-02 00:18:34,579] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 196.36 | bwd_microstep: 289.62 | bwd_inner_microstep: 289.60 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-02 00:18:35,059] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.98 | bwd_microstep: 274.01 | bwd_inner_microstep: 274.00 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-02 00:18:35,540] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.21 | bwd_microstep: 274.36 | bwd_inner_microstep: 274.34 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 00:18:36,019] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.86 | bwd_microstep: 273.82 | bwd_inner_microstep: 273.81 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 00:18:36,499] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.74 | bwd_microstep: 273.72 | bwd_inner_microstep: 273.71 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 00:18:36,978] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.70 | bwd_microstep: 273.32 | bwd_inner_microstep: 273.30 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 00:18:37,457] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.54 | bwd_microstep: 272.99 | bwd_inner_microstep: 272.97 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 334 +[2025-05-02 00:18:37,667] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 68.98 | bwd_microstep: 127.07 | bwd_inner_microstep: 126.94 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 00:18:38,143] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.72 | bwd_microstep: 273.04 | bwd_inner_microstep: 273.03 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.20 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 836 +[2025-05-02 00:18:38,378] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 92.05 | bwd_microstep: 126.14 | bwd_inner_microstep: 126.03 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 316 +[2025-05-02 00:18:38,598] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 82.71 | bwd_microstep: 123.18 | bwd_inner_microstep: 122.99 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1341 +[2025-05-02 00:18:38,964] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 142.97 | bwd_microstep: 204.70 | bwd_inner_microstep: 204.69 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 00:18:39,440] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.74 | bwd_microstep: 271.11 | bwd_inner_microstep: 271.10 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 00:18:39,919] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.69 | bwd_microstep: 271.17 | bwd_inner_microstep: 271.15 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1931 +[2025-05-02 00:18:40,519] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.28 | optimizer_step: 17.37 +[2025-05-02 00:18:40,519] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 194.97 | bwd_microstep: 355.42 | bwd_inner_microstep: 288.91 | bwd_allreduce_microstep: 66.46 | step_microstep: 24.74 +[2025-05-02 00:18:40,521] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2711.26 | bwd: 4054.07 | bwd_inner: 3986.96 | bwd_allreduce: 66.70 | step: 25.95 + 9%|▊ | 759/8720 [2:03:14<15:25:54, 6.98s/it] {'loss': 0.7716, 'grad_norm': 5.385800361633301, 'learning_rate': 9.915046067548648e-06, 'epoch': 0.87} + 9%|▊ | 759/8720 [2:03:14<15:25:54, 6.98s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 375 +[2025-05-02 00:18:40,736] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 75.47 | bwd_microstep: 121.70 | bwd_inner_microstep: 121.42 | bwd_allreduce_microstep: 0.14 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-02 00:18:41,214] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.15 | bwd_microstep: 273.63 | bwd_inner_microstep: 273.61 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 349 +[2025-05-02 00:18:41,427] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 78.81 | bwd_microstep: 118.28 | bwd_inner_microstep: 118.14 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 00:18:41,903] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.94 | bwd_microstep: 272.76 | bwd_inner_microstep: 272.74 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 00:18:42,381] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.54 | bwd_microstep: 272.88 | bwd_inner_microstep: 272.86 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 00:18:42,858] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.92 | bwd_microstep: 272.64 | bwd_inner_microstep: 272.62 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 841 +[2025-05-02 00:18:43,099] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.90 | bwd_microstep: 132.60 | bwd_inner_microstep: 132.33 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 00:18:43,576] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.75 | bwd_microstep: 272.67 | bwd_inner_microstep: 272.66 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 328 +[2025-05-02 00:18:43,786] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 76.04 | bwd_microstep: 118.81 | bwd_inner_microstep: 118.59 | bwd_allreduce_microstep: 0.08 | step_microstep: 0.13 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 00:18:44,265] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.89 | bwd_microstep: 272.83 | bwd_inner_microstep: 272.81 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1356 +[2025-05-02 00:18:44,630] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.63 | bwd_microstep: 206.72 | bwd_inner_microstep: 206.62 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 00:18:45,110] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.36 | bwd_microstep: 272.58 | bwd_inner_microstep: 272.57 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1343 +[2025-05-02 00:18:45,473] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.09 | bwd_microstep: 204.88 | bwd_inner_microstep: 204.76 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 00:18:45,952] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.78 | bwd_microstep: 271.32 | bwd_inner_microstep: 271.31 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 00:18:46,430] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.41 | bwd_microstep: 271.63 | bwd_inner_microstep: 271.61 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1925 +[2025-05-02 00:18:47,034] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.15 | optimizer_step: 17.28 +[2025-05-02 00:18:47,035] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.36 | bwd_microstep: 366.60 | bwd_inner_microstep: 288.28 | bwd_allreduce_microstep: 78.27 | step_microstep: 25.02 +[2025-05-02 00:18:47,036] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2498.73 | bwd: 3722.62 | bwd_inner: 3643.08 | bwd_allreduce: 78.84 | step: 26.35 + 9%|▊ | 760/8720 [2:03:20<15:07:26, 6.84s/it] {'loss': 1.0865, 'grad_norm': 7.699448108673096, 'learning_rate': 9.914704832980296e-06, 'epoch': 0.87} + 9%|▊ | 760/8720 [2:03:20<15:07:26, 6.84s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 359 +[2025-05-02 00:18:47,269] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 83.74 | bwd_microstep: 127.96 | bwd_inner_microstep: 127.66 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1897 +[2025-05-02 00:18:47,752] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.18 | bwd_microstep: 275.98 | bwd_inner_microstep: 275.96 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1889 +[2025-05-02 00:18:48,238] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 191.21 | bwd_microstep: 275.46 | bwd_inner_microstep: 275.44 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1105 +[2025-05-02 00:18:48,534] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 116.42 | bwd_microstep: 161.96 | bwd_inner_microstep: 161.94 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 847 +[2025-05-02 00:18:48,780] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.06 | bwd_microstep: 133.51 | bwd_inner_microstep: 133.24 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.18 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1356 +[2025-05-02 00:18:49,145] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.05 | bwd_microstep: 206.34 | bwd_inner_microstep: 206.32 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 00:18:49,623] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.78 | bwd_microstep: 272.19 | bwd_inner_microstep: 272.17 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 333 +[2025-05-02 00:18:49,855] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 90.68 | bwd_microstep: 122.52 | bwd_inner_microstep: 122.21 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 00:18:50,334] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.44 | bwd_microstep: 272.92 | bwd_inner_microstep: 272.90 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 00:18:50,814] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.98 | bwd_microstep: 272.82 | bwd_inner_microstep: 272.80 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 00:18:51,293] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.32 | bwd_microstep: 272.79 | bwd_inner_microstep: 272.77 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 00:18:51,773] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.65 | bwd_microstep: 272.50 | bwd_inner_microstep: 272.48 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 00:18:52,255] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.43 | bwd_microstep: 273.25 | bwd_inner_microstep: 273.23 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 00:18:52,737] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.18 | bwd_microstep: 272.34 | bwd_inner_microstep: 272.32 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 00:18:53,215] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.82 | bwd_microstep: 271.25 | bwd_inner_microstep: 271.24 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 00:18:53,796] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.13 | optimizer_step: 17.04 +[2025-05-02 00:18:53,797] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.79 | bwd_microstep: 349.31 | bwd_inner_microstep: 271.86 | bwd_allreduce_microstep: 77.40 | step_microstep: 24.65 +[2025-05-02 00:18:53,798] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2608.34 | bwd: 3833.20 | bwd_inner: 3754.69 | bwd_allreduce: 77.85 | step: 25.85 + 9%|▊ | 761/8720 [2:03:27<15:04:13, 6.82s/it] {'loss': 1.2171, 'grad_norm': 8.220170021057129, 'learning_rate': 9.914362920361786e-06, 'epoch': 0.87} + 9%|▊ | 761/8720 [2:03:27<15:04:13, 6.82s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1928 +[2025-05-02 00:18:54,304] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.21 | bwd_microstep: 287.32 | bwd_inner_microstep: 287.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 866 +[2025-05-02 00:18:54,554] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 100.23 | bwd_microstep: 134.41 | bwd_inner_microstep: 134.32 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.08 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 344 +[2025-05-02 00:18:54,756] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 67.76 | bwd_microstep: 119.58 | bwd_inner_microstep: 119.44 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.11 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 855 +[2025-05-02 00:18:54,998] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.05 | bwd_microstep: 133.79 | bwd_inner_microstep: 133.77 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 00:18:55,474] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.90 | bwd_microstep: 272.90 | bwd_inner_microstep: 272.88 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 00:18:55,954] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.50 | bwd_microstep: 273.15 | bwd_inner_microstep: 273.14 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 324 +[2025-05-02 00:18:56,174] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 88.46 | bwd_microstep: 115.11 | bwd_inner_microstep: 114.95 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 00:18:56,652] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.12 | bwd_microstep: 273.06 | bwd_inner_microstep: 273.04 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 00:18:57,128] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.95 | bwd_microstep: 272.78 | bwd_inner_microstep: 272.76 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 00:18:57,605] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.65 | bwd_microstep: 272.88 | bwd_inner_microstep: 272.86 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 322 +[2025-05-02 00:18:57,820] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 81.99 | bwd_microstep: 117.25 | bwd_inner_microstep: 117.00 | bwd_allreduce_microstep: 0.08 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 00:18:58,296] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.77 | bwd_microstep: 272.82 | bwd_inner_microstep: 272.80 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 00:18:58,774] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.39 | bwd_microstep: 271.20 | bwd_inner_microstep: 271.18 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.17 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 827 +[2025-05-02 00:18:59,017] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 96.79 | bwd_microstep: 130.02 | bwd_inner_microstep: 129.93 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 00:18:59,493] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.05 | bwd_microstep: 271.18 | bwd_inner_microstep: 271.16 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 383 +[2025-05-02 00:18:59,825] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.14 | optimizer_step: 16.92 +[2025-05-02 00:18:59,825] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 81.51 | bwd_microstep: 210.63 | bwd_inner_microstep: 133.38 | bwd_allreduce_microstep: 77.09 | step_microstep: 24.79 +[2025-05-02 00:18:59,827] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2315.02 | bwd: 3428.17 | bwd_inner: 3350.12 | bwd_allreduce: 77.40 | step: 25.88 + 9%|▊ | 762/8720 [2:03:33<14:32:44, 6.58s/it] {'loss': 0.876, 'grad_norm': 4.965578556060791, 'learning_rate': 9.914020329740296e-06, 'epoch': 0.87} + 9%|▊ | 762/8720 [2:03:33<14:32:44, 6.58s/it]dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 870 +[2025-05-02 00:19:00,082] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 99.14 | bwd_microstep: 134.26 | bwd_inner_microstep: 134.12 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.09 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 344 +[2025-05-02 00:19:00,310] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 86.81 | bwd_microstep: 125.76 | bwd_inner_microstep: 125.50 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-02 00:19:00,792] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.90 | bwd_microstep: 274.00 | bwd_inner_microstep: 273.98 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-02 00:19:01,275] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.31 | bwd_microstep: 273.60 | bwd_inner_microstep: 273.59 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.07 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 00:19:01,760] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.62 | bwd_microstep: 273.04 | bwd_inner_microstep: 273.02 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 00:19:02,245] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.91 | bwd_microstep: 272.94 | bwd_inner_microstep: 272.92 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 333 +[2025-05-02 00:19:02,475] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 91.72 | bwd_microstep: 122.95 | bwd_inner_microstep: 122.79 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 00:19:02,954] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.64 | bwd_microstep: 272.78 | bwd_inner_microstep: 272.76 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 00:19:03,436] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.21 | bwd_microstep: 273.00 | bwd_inner_microstep: 272.99 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1351 +[2025-05-02 00:19:03,805] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.74 | bwd_microstep: 206.48 | bwd_inner_microstep: 206.27 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 00:19:04,282] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.06 | bwd_microstep: 271.58 | bwd_inner_microstep: 271.56 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 00:19:04,760] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.49 | bwd_microstep: 273.01 | bwd_inner_microstep: 273.00 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 00:19:05,239] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.32 | bwd_microstep: 271.58 | bwd_inner_microstep: 271.56 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 00:19:05,717] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.45 | bwd_microstep: 271.12 | bwd_inner_microstep: 271.10 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 00:19:06,194] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.96 | bwd_microstep: 271.29 | bwd_inner_microstep: 271.10 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 00:19:06,777] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.38 | optimizer_step: 17.00 +[2025-05-02 00:19:06,778] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.89 | bwd_microstep: 349.61 | bwd_inner_microstep: 271.58 | bwd_allreduce_microstep: 77.98 | step_microstep: 24.93 +[2025-05-02 00:19:06,779] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2680.74 | bwd: 3937.10 | bwd_inner: 3857.94 | bwd_allreduce: 78.54 | step: 26.04 + 9%|▉ | 763/8720 [2:03:40<14:47:26, 6.69s/it] {'loss': 0.5677, 'grad_norm': 3.8551435470581055, 'learning_rate': 9.913677061163089e-06, 'epoch': 0.87} + 9%|▉ | 763/8720 [2:03:40<14:47:26, 6.69s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1905 +[2025-05-02 00:19:07,268] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.34 | bwd_microstep: 275.59 | bwd_inner_microstep: 275.57 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1903 +[2025-05-02 00:19:07,752] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.96 | bwd_microstep: 275.92 | bwd_inner_microstep: 275.90 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-02 00:19:08,233] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.62 | bwd_microstep: 273.71 | bwd_inner_microstep: 273.70 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 00:19:08,713] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.28 | bwd_microstep: 272.85 | bwd_inner_microstep: 272.83 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 00:19:09,194] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.96 | bwd_microstep: 272.69 | bwd_inner_microstep: 272.67 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 00:19:09,676] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.54 | bwd_microstep: 272.79 | bwd_inner_microstep: 272.78 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 327 +[2025-05-02 00:19:09,912] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 100.11 | bwd_microstep: 116.68 | bwd_inner_microstep: 116.51 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 00:19:10,391] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.30 | bwd_microstep: 273.00 | bwd_inner_microstep: 272.98 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 00:19:10,871] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.26 | bwd_microstep: 272.65 | bwd_inner_microstep: 272.64 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 00:19:11,350] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.57 | bwd_microstep: 271.46 | bwd_inner_microstep: 271.45 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 00:19:11,832] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.36 | bwd_microstep: 272.98 | bwd_inner_microstep: 272.96 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 00:19:12,316] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.36 | bwd_microstep: 272.31 | bwd_inner_microstep: 272.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 00:19:12,796] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.20 | bwd_microstep: 272.48 | bwd_inner_microstep: 272.45 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 00:19:13,275] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.35 | bwd_microstep: 271.33 | bwd_inner_microstep: 271.31 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.16 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 00:19:13,751] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.04 | bwd_microstep: 271.26 | bwd_inner_microstep: 271.24 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 434 +[2025-05-02 00:19:14,125] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.09 | optimizer_step: 17.03 +[2025-05-02 00:19:14,125] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 104.82 | bwd_microstep: 224.57 | bwd_inner_microstep: 133.45 | bwd_allreduce_microstep: 90.93 | step_microstep: 24.87 +[2025-05-02 00:19:14,126] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2850.66 | bwd: 4162.31 | bwd_inner: 4070.85 | bwd_allreduce: 91.04 | step: 25.84 + 9%|▉ | 764/8720 [2:03:47<15:13:25, 6.89s/it] {'loss': 0.9528, 'grad_norm': 7.412578582763672, 'learning_rate': 9.913333114677521e-06, 'epoch': 0.88} + 9%|▉ | 764/8720 [2:03:47<15:13:25, 6.89s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1896 +[2025-05-02 00:19:14,613] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.48 | bwd_microstep: 274.61 | bwd_inner_microstep: 274.59 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 00:19:15,095] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.77 | bwd_microstep: 273.38 | bwd_inner_microstep: 273.37 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1360 +[2025-05-02 00:19:15,460] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.79 | bwd_microstep: 206.86 | bwd_inner_microstep: 206.83 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 00:19:15,940] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.65 | bwd_microstep: 273.60 | bwd_inner_microstep: 273.58 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 00:19:16,420] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.10 | bwd_microstep: 273.60 | bwd_inner_microstep: 273.59 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 00:19:16,904] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.30 | bwd_microstep: 272.90 | bwd_inner_microstep: 272.89 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1351 +[2025-05-02 00:19:17,272] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.92 | bwd_microstep: 206.08 | bwd_inner_microstep: 206.06 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 00:19:17,756] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.55 | bwd_microstep: 272.82 | bwd_inner_microstep: 272.80 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 00:19:18,235] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.44 | bwd_microstep: 273.06 | bwd_inner_microstep: 273.04 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 00:19:18,717] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.52 | bwd_microstep: 272.51 | bwd_inner_microstep: 272.49 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.13 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 00:19:19,199] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.83 | bwd_microstep: 273.15 | bwd_inner_microstep: 273.13 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 00:19:19,680] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.09 | bwd_microstep: 272.72 | bwd_inner_microstep: 272.71 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.11 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 836 +[2025-05-02 00:19:19,925] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 97.49 | bwd_microstep: 126.24 | bwd_inner_microstep: 125.96 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 00:19:20,404] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.08 | bwd_microstep: 271.46 | bwd_inner_microstep: 271.44 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 00:19:20,881] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.74 | bwd_microstep: 271.31 | bwd_inner_microstep: 271.29 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 00:19:21,463] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.13 | optimizer_step: 17.13 +[2025-05-02 00:19:21,463] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.67 | bwd_microstep: 351.75 | bwd_inner_microstep: 271.73 | bwd_allreduce_microstep: 79.97 | step_microstep: 24.78 +[2025-05-02 00:19:21,465] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2835.04 | bwd: 4166.13 | bwd_inner: 4085.52 | bwd_allreduce: 80.19 | step: 26.06 + 9%|▉ | 765/8720 [2:03:55<15:31:10, 7.02s/it] {'loss': 0.9286, 'grad_norm': 5.792952060699463, 'learning_rate': 9.912988490331048e-06, 'epoch': 0.88} + 9%|▉ | 765/8720 [2:03:55<15:31:10, 7.02s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1988 +[2025-05-02 00:19:21,978] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 197.59 | bwd_microstep: 293.04 | bwd_inner_microstep: 293.02 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1894 +[2025-05-02 00:19:22,462] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.68 | bwd_microstep: 274.97 | bwd_inner_microstep: 274.96 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-02 00:19:22,943] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.80 | bwd_microstep: 274.12 | bwd_inner_microstep: 274.10 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.13 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-02 00:19:23,427] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.77 | bwd_microstep: 273.63 | bwd_inner_microstep: 273.61 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 00:19:23,911] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.29 | bwd_microstep: 272.60 | bwd_inner_microstep: 272.59 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 00:19:24,394] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.42 | bwd_microstep: 272.91 | bwd_inner_microstep: 272.90 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 326 +[2025-05-02 00:19:24,611] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 82.16 | bwd_microstep: 118.51 | bwd_inner_microstep: 118.32 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 00:19:25,089] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.60 | bwd_microstep: 272.87 | bwd_inner_microstep: 272.86 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 00:19:25,569] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.07 | bwd_microstep: 273.11 | bwd_inner_microstep: 273.10 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.13 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 00:19:26,048] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.75 | bwd_microstep: 272.23 | bwd_inner_microstep: 272.21 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 00:19:26,528] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.56 | bwd_microstep: 272.63 | bwd_inner_microstep: 272.62 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 00:19:27,005] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.70 | bwd_microstep: 271.45 | bwd_inner_microstep: 271.43 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 00:19:27,483] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.95 | bwd_microstep: 271.32 | bwd_inner_microstep: 271.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 00:19:27,964] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.43 | bwd_microstep: 271.31 | bwd_inner_microstep: 271.29 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 00:19:28,442] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.91 | bwd_microstep: 271.43 | bwd_inner_microstep: 271.42 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 898 +[2025-05-02 00:19:28,806] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.38 | optimizer_step: 17.05 +[2025-05-02 00:19:28,807] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 101.39 | bwd_microstep: 222.61 | bwd_inner_microstep: 144.16 | bwd_allreduce_microstep: 78.30 | step_microstep: 24.91 +[2025-05-02 00:19:28,808] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2836.70 | bwd: 4178.79 | bwd_inner: 4100.01 | bwd_allreduce: 78.41 | step: 26.19 + 9%|▉ | 766/8720 [2:04:02<15:43:48, 7.12s/it] {'loss': 1.0434, 'grad_norm': 6.739953994750977, 'learning_rate': 9.912643188171213e-06, 'epoch': 0.88} + 9%|▉ | 766/8720 [2:04:02<15:43:48, 7.12s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1896 +[2025-05-02 00:19:29,296] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.20 | bwd_microstep: 275.13 | bwd_inner_microstep: 275.11 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 00:19:29,776] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.11 | bwd_microstep: 273.65 | bwd_inner_microstep: 273.64 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 00:19:30,255] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.09 | bwd_microstep: 273.65 | bwd_inner_microstep: 273.63 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.13 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1362 +[2025-05-02 00:19:30,623] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 143.40 | bwd_microstep: 206.87 | bwd_inner_microstep: 206.75 | bwd_allreduce_microstep: 0.03 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-02 00:19:31,101] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.41 | bwd_microstep: 273.71 | bwd_inner_microstep: 273.69 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-02 00:19:31,579] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.34 | bwd_microstep: 273.34 | bwd_inner_microstep: 273.32 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-02 00:19:32,058] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.85 | bwd_microstep: 274.02 | bwd_inner_microstep: 274.01 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 844 +[2025-05-02 00:19:32,301] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 96.89 | bwd_microstep: 132.16 | bwd_inner_microstep: 132.14 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1091 +[2025-05-02 00:19:32,593] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 115.06 | bwd_microstep: 161.46 | bwd_inner_microstep: 161.20 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 00:19:33,070] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.85 | bwd_microstep: 272.86 | bwd_inner_microstep: 272.85 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.13 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 00:19:33,548] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.77 | bwd_microstep: 272.49 | bwd_inner_microstep: 272.47 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 00:19:34,024] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.76 | bwd_microstep: 272.59 | bwd_inner_microstep: 272.57 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.15 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 00:19:34,500] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.88 | bwd_microstep: 271.52 | bwd_inner_microstep: 271.51 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 00:19:34,977] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.18 | bwd_microstep: 271.57 | bwd_inner_microstep: 271.55 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 316 +[2025-05-02 00:19:35,179] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 68.88 | bwd_microstep: 119.88 | bwd_inner_microstep: 119.67 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 00:19:35,745] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.04 | optimizer_gradients: 2.17 | optimizer_step: 17.11 +[2025-05-02 00:19:35,745] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.93 | bwd_microstep: 338.37 | bwd_inner_microstep: 271.71 | bwd_allreduce_microstep: 66.61 | step_microstep: 24.09 +[2025-05-02 00:19:35,746] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2691.34 | bwd: 3963.37 | bwd_inner: 3895.88 | bwd_allreduce: 66.96 | step: 25.74 + 9%|▉ | 767/8720 [2:04:09<15:36:23, 7.06s/it] {'loss': 0.9985, 'grad_norm': 6.95710563659668, 'learning_rate': 9.912297208245656e-06, 'epoch': 0.88} + 9%|▉ | 767/8720 [2:04:09<15:36:23, 7.06s/it]dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 967 +[2025-05-02 00:19:36,019] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 104.27 | bwd_microstep: 150.34 | bwd_inner_microstep: 150.22 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1974 +[2025-05-02 00:19:36,524] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 197.07 | bwd_microstep: 291.55 | bwd_inner_microstep: 291.54 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 391 +[2025-05-02 00:19:36,733] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 74.61 | bwd_microstep: 120.18 | bwd_inner_microstep: 119.88 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.19 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 881 +[2025-05-02 00:19:36,982] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 98.39 | bwd_microstep: 135.77 | bwd_inner_microstep: 135.60 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1910 +[2025-05-02 00:19:37,465] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.54 | bwd_microstep: 277.28 | bwd_inner_microstep: 277.26 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.15 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1894 +[2025-05-02 00:19:37,948] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.46 | bwd_microstep: 274.91 | bwd_inner_microstep: 274.89 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-02 00:19:38,430] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.81 | bwd_microstep: 273.69 | bwd_inner_microstep: 273.67 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 00:19:38,915] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.33 | bwd_microstep: 273.81 | bwd_inner_microstep: 273.79 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-02 00:19:39,399] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.91 | bwd_microstep: 273.58 | bwd_inner_microstep: 273.57 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 00:19:39,881] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.69 | bwd_microstep: 272.99 | bwd_inner_microstep: 272.97 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1354 +[2025-05-02 00:19:40,247] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.54 | bwd_microstep: 206.53 | bwd_inner_microstep: 206.43 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 00:19:40,728] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.98 | bwd_microstep: 272.56 | bwd_inner_microstep: 272.55 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 834 +[2025-05-02 00:19:40,966] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.74 | bwd_microstep: 126.08 | bwd_inner_microstep: 125.80 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 00:19:41,443] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.77 | bwd_microstep: 271.43 | bwd_inner_microstep: 271.42 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 00:19:41,923] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.85 | bwd_microstep: 271.43 | bwd_inner_microstep: 271.41 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 00:19:42,510] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.19 | optimizer_step: 17.02 +[2025-05-02 00:19:42,511] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.37 | bwd_microstep: 353.65 | bwd_inner_microstep: 273.18 | bwd_allreduce_microstep: 80.42 | step_microstep: 24.96 +[2025-05-02 00:19:42,512] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2599.93 | bwd: 3845.91 | bwd_inner: 3764.26 | bwd_allreduce: 80.91 | step: 26.42 + 9%|▉ | 768/8720 [2:04:16<15:24:29, 6.98s/it] {'loss': 1.4932, 'grad_norm': 7.6144185066223145, 'learning_rate': 9.91195055060211e-06, 'epoch': 0.88} + 9%|▉ | 768/8720 [2:04:16<15:24:29, 6.98s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1935 +[2025-05-02 00:19:43,020] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 196.82 | bwd_microstep: 287.45 | bwd_inner_microstep: 287.43 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1889 +[2025-05-02 00:19:43,504] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.63 | bwd_microstep: 274.48 | bwd_inner_microstep: 274.47 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1893 +[2025-05-02 00:19:43,985] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.31 | bwd_microstep: 274.80 | bwd_inner_microstep: 274.78 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1366 +[2025-05-02 00:19:44,353] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.06 | bwd_microstep: 207.38 | bwd_inner_microstep: 207.27 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.11 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 847 +[2025-05-02 00:19:44,599] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.21 | bwd_microstep: 132.86 | bwd_inner_microstep: 132.69 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-02 00:19:45,080] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.04 | bwd_microstep: 273.34 | bwd_inner_microstep: 273.33 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 00:19:45,561] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.82 | bwd_microstep: 272.98 | bwd_inner_microstep: 272.97 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 00:19:46,040] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.30 | bwd_microstep: 272.26 | bwd_inner_microstep: 272.24 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 00:19:46,519] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.88 | bwd_microstep: 272.89 | bwd_inner_microstep: 272.86 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 00:19:47,001] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.12 | bwd_microstep: 272.27 | bwd_inner_microstep: 272.25 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 00:19:47,482] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.23 | bwd_microstep: 272.52 | bwd_inner_microstep: 272.50 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 00:19:47,960] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.33 | bwd_microstep: 272.44 | bwd_inner_microstep: 272.42 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 00:19:48,441] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.25 | bwd_microstep: 272.39 | bwd_inner_microstep: 272.37 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 321 +[2025-05-02 00:19:48,683] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.12 | bwd_microstep: 126.54 | bwd_inner_microstep: 126.29 | bwd_allreduce_microstep: 0.08 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 00:19:49,160] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.73 | bwd_microstep: 270.99 | bwd_inner_microstep: 270.97 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 315 +[2025-05-02 00:19:49,494] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.20 | optimizer_step: 16.88 +[2025-05-02 00:19:49,494] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 84.29 | bwd_microstep: 209.39 | bwd_inner_microstep: 131.88 | bwd_allreduce_microstep: 77.35 | step_microstep: 24.52 +[2025-05-02 00:19:49,496] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2686.76 | bwd: 3965.03 | bwd_inner: 3886.89 | bwd_allreduce: 77.56 | step: 25.74 + 9%|▉ | 769/8720 [2:04:23<15:24:40, 6.98s/it] {'loss': 0.8419, 'grad_norm': 9.753809928894043, 'learning_rate': 9.911603215288399e-06, 'epoch': 0.88} + 9%|▉ | 769/8720 [2:04:23<15:24:40, 6.98s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 429 +[2025-05-02 00:19:49,721] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 80.74 | bwd_microstep: 123.31 | bwd_inner_microstep: 122.99 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1901 +[2025-05-02 00:19:50,204] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.29 | bwd_microstep: 275.86 | bwd_inner_microstep: 275.84 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1888 +[2025-05-02 00:19:50,685] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.74 | bwd_microstep: 274.69 | bwd_inner_microstep: 274.67 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 337 +[2025-05-02 00:19:50,904] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 81.06 | bwd_microstep: 122.18 | bwd_inner_microstep: 121.87 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 00:19:51,383] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.77 | bwd_microstep: 273.24 | bwd_inner_microstep: 273.22 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 00:19:51,862] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.50 | bwd_microstep: 272.75 | bwd_inner_microstep: 272.73 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-02 00:19:52,344] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.77 | bwd_microstep: 273.36 | bwd_inner_microstep: 273.34 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-02 00:19:52,827] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.87 | bwd_microstep: 273.46 | bwd_inner_microstep: 273.44 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 843 +[2025-05-02 00:19:53,074] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.49 | bwd_microstep: 132.78 | bwd_inner_microstep: 132.55 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 00:19:53,553] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.50 | bwd_microstep: 272.86 | bwd_inner_microstep: 272.84 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 00:19:54,034] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.70 | bwd_microstep: 273.11 | bwd_inner_microstep: 273.10 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 834 +[2025-05-02 00:19:54,276] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 96.53 | bwd_microstep: 126.02 | bwd_inner_microstep: 125.74 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.10 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1346 +[2025-05-02 00:19:54,641] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.09 | bwd_microstep: 206.13 | bwd_inner_microstep: 205.96 | bwd_allreduce_microstep: 0.09 | step_microstep: 0.18 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 834 +[2025-05-02 00:19:54,878] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.26 | bwd_microstep: 125.86 | bwd_inner_microstep: 125.75 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 00:19:55,357] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.77 | bwd_microstep: 272.42 | bwd_inner_microstep: 272.41 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 00:19:55,943] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.19 | optimizer_step: 16.95 +[2025-05-02 00:19:55,944] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.27 | bwd_microstep: 353.69 | bwd_inner_microstep: 271.88 | bwd_allreduce_microstep: 81.75 | step_microstep: 24.86 +[2025-05-02 00:19:55,945] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2476.98 | bwd: 3651.83 | bwd_inner: 3568.45 | bwd_allreduce: 82.50 | step: 25.99 + 9%|▉ | 770/8720 [2:04:29<15:03:34, 6.82s/it] {'loss': 0.9918, 'grad_norm': 6.8882527351379395, 'learning_rate': 9.911255202352446e-06, 'epoch': 0.88} + 9%|▉ | 770/8720 [2:04:29<15:03:34, 6.82s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-02 00:19:56,432] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.69 | bwd_microstep: 273.07 | bwd_inner_microstep: 273.05 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-02 00:19:56,915] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.78 | bwd_microstep: 273.88 | bwd_inner_microstep: 273.86 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 00:19:57,396] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.47 | bwd_microstep: 274.11 | bwd_inner_microstep: 274.10 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-02 00:19:57,879] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.22 | bwd_microstep: 273.65 | bwd_inner_microstep: 273.63 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.22 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 00:19:58,364] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.52 | bwd_microstep: 273.00 | bwd_inner_microstep: 272.98 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.17 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 00:19:58,848] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.73 | bwd_microstep: 273.23 | bwd_inner_microstep: 273.21 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 00:19:59,327] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.65 | bwd_microstep: 272.84 | bwd_inner_microstep: 272.82 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 00:19:59,807] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.01 | bwd_microstep: 273.32 | bwd_inner_microstep: 273.30 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 00:20:00,286] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.82 | bwd_microstep: 272.70 | bwd_inner_microstep: 272.68 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 00:20:00,764] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.68 | bwd_microstep: 272.42 | bwd_inner_microstep: 272.40 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 00:20:01,240] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.15 | bwd_microstep: 271.43 | bwd_inner_microstep: 271.42 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 00:20:01,715] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.69 | bwd_microstep: 271.40 | bwd_inner_microstep: 271.38 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 00:20:02,194] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.06 | bwd_microstep: 272.49 | bwd_inner_microstep: 272.47 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 00:20:02,672] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.43 | bwd_microstep: 272.26 | bwd_inner_microstep: 272.25 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 830 +[2025-05-02 00:20:02,919] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 92.24 | bwd_microstep: 130.54 | bwd_inner_microstep: 130.34 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2041 +[2025-05-02 00:20:03,528] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.27 | optimizer_step: 17.55 +[2025-05-02 00:20:03,528] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 198.74 | bwd_microstep: 369.21 | bwd_inner_microstep: 299.44 | bwd_allreduce_microstep: 69.73 | step_microstep: 24.98 +[2025-05-02 00:20:03,530] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2934.54 | bwd: 4319.58 | bwd_inner: 4249.40 | bwd_allreduce: 69.86 | step: 26.53 + 9%|▉ | 771/8720 [2:04:37<15:33:47, 7.05s/it] {'loss': 0.6778, 'grad_norm': 7.036398410797119, 'learning_rate': 9.910906511842262e-06, 'epoch': 0.88} + 9%|▉ | 771/8720 [2:04:37<15:33:47, 7.05s/it]dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 967 +[2025-05-02 00:20:03,813] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 110.33 | bwd_microstep: 150.13 | bwd_inner_microstep: 149.83 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-02 00:20:04,292] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.42 | bwd_microstep: 273.81 | bwd_inner_microstep: 273.79 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-02 00:20:04,771] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.88 | bwd_microstep: 273.55 | bwd_inner_microstep: 273.53 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-02 00:20:05,250] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.90 | bwd_microstep: 274.02 | bwd_inner_microstep: 274.00 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.13 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 323 +[2025-05-02 00:20:05,485] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 96.97 | bwd_microstep: 120.47 | bwd_inner_microstep: 120.16 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 00:20:05,961] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.21 | bwd_microstep: 272.67 | bwd_inner_microstep: 272.65 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 00:20:06,438] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.33 | bwd_microstep: 272.96 | bwd_inner_microstep: 272.95 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 00:20:06,917] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.26 | bwd_microstep: 272.76 | bwd_inner_microstep: 272.74 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 00:20:07,397] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.76 | bwd_microstep: 272.59 | bwd_inner_microstep: 272.58 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 00:20:07,874] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.24 | bwd_microstep: 272.83 | bwd_inner_microstep: 272.81 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.16 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 00:20:08,352] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.81 | bwd_microstep: 272.36 | bwd_inner_microstep: 272.34 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 00:20:08,831] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.06 | bwd_microstep: 272.43 | bwd_inner_microstep: 272.41 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 00:20:09,311] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.64 | bwd_microstep: 272.66 | bwd_inner_microstep: 272.65 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 00:20:09,789] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.25 | bwd_microstep: 271.57 | bwd_inner_microstep: 271.55 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 00:20:10,268] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.43 | bwd_microstep: 271.55 | bwd_inner_microstep: 271.53 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1966 +[2025-05-02 00:20:10,886] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.19 | optimizer_step: 17.08 +[2025-05-02 00:20:10,887] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 199.87 | bwd_microstep: 376.32 | bwd_inner_microstep: 291.64 | bwd_allreduce_microstep: 84.62 | step_microstep: 25.64 +[2025-05-02 00:20:10,888] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2865.04 | bwd: 4192.72 | bwd_inner: 4107.28 | bwd_allreduce: 84.95 | step: 26.86 + 9%|▉ | 772/8720 [2:04:44<15:45:59, 7.14s/it] {'loss': 0.8545, 'grad_norm': 5.2651519775390625, 'learning_rate': 9.910557143805954e-06, 'epoch': 0.89} + 9%|▉ | 772/8720 [2:04:44<15:45:59, 7.14s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1905 +[2025-05-02 00:20:11,374] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.57 | bwd_microstep: 275.54 | bwd_inner_microstep: 275.53 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1890 +[2025-05-02 00:20:11,854] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.09 | bwd_microstep: 274.82 | bwd_inner_microstep: 274.81 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1890 +[2025-05-02 00:20:12,335] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.49 | bwd_microstep: 274.85 | bwd_inner_microstep: 274.84 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1091 +[2025-05-02 00:20:12,627] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 115.96 | bwd_microstep: 161.02 | bwd_inner_microstep: 160.79 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 00:20:13,105] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.39 | bwd_microstep: 272.85 | bwd_inner_microstep: 272.84 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 324 +[2025-05-02 00:20:13,323] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 82.68 | bwd_microstep: 121.34 | bwd_inner_microstep: 121.11 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.09 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 844 +[2025-05-02 00:20:13,566] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 96.41 | bwd_microstep: 132.64 | bwd_inner_microstep: 132.44 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 00:20:14,044] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.01 | bwd_microstep: 272.59 | bwd_inner_microstep: 272.58 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 00:20:14,521] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.08 | bwd_microstep: 272.81 | bwd_inner_microstep: 272.79 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 00:20:14,998] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.71 | bwd_microstep: 272.93 | bwd_inner_microstep: 272.92 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 00:20:15,474] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.43 | bwd_microstep: 272.62 | bwd_inner_microstep: 272.60 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 00:20:15,950] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.65 | bwd_microstep: 271.41 | bwd_inner_microstep: 271.39 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 00:20:16,426] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.17 | bwd_microstep: 271.44 | bwd_inner_microstep: 271.42 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.21 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 00:20:16,902] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.07 | bwd_microstep: 271.21 | bwd_inner_microstep: 271.19 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 00:20:17,379] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.50 | bwd_microstep: 271.35 | bwd_inner_microstep: 271.33 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1911 +[2025-05-02 00:20:17,973] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.17 | optimizer_step: 16.90 +[2025-05-02 00:20:17,973] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.87 | bwd_microstep: 363.30 | bwd_inner_microstep: 277.23 | bwd_allreduce_microstep: 86.02 | step_microstep: 25.38 +[2025-05-02 00:20:17,975] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2755.77 | bwd: 4052.79 | bwd_inner: 3965.93 | bwd_allreduce: 86.29 | step: 26.45 + 9%|▉ | 773/8720 [2:04:51<15:43:42, 7.12s/it] {'loss': 0.9693, 'grad_norm': 8.044286727905273, 'learning_rate': 9.910207098291722e-06, 'epoch': 0.89} + 9%|▉ | 773/8720 [2:04:51<15:43:42, 7.12s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1931 +[2025-05-02 00:20:18,477] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 194.84 | bwd_microstep: 287.84 | bwd_inner_microstep: 287.82 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-02 00:20:18,955] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.76 | bwd_microstep: 273.43 | bwd_inner_microstep: 273.42 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-02 00:20:19,434] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.68 | bwd_microstep: 274.17 | bwd_inner_microstep: 274.15 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-02 00:20:19,913] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.58 | bwd_microstep: 274.46 | bwd_inner_microstep: 274.44 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.22 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 00:20:20,391] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.64 | bwd_microstep: 272.69 | bwd_inner_microstep: 272.67 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 00:20:20,871] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.63 | bwd_microstep: 273.39 | bwd_inner_microstep: 273.38 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 00:20:21,351] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.94 | bwd_microstep: 272.52 | bwd_inner_microstep: 272.50 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.12 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 836 +[2025-05-02 00:20:21,603] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 110.15 | bwd_microstep: 125.49 | bwd_inner_microstep: 125.46 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.11 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 832 +[2025-05-02 00:20:21,856] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 106.15 | bwd_microstep: 129.90 | bwd_inner_microstep: 129.77 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.11 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 325 +[2025-05-02 00:20:22,124] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 107.03 | bwd_microstep: 144.81 | bwd_inner_microstep: 144.46 | bwd_allreduce_microstep: 0.14 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 00:20:22,604] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.27 | bwd_microstep: 272.84 | bwd_inner_microstep: 272.82 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 00:20:23,086] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.69 | bwd_microstep: 273.14 | bwd_inner_microstep: 273.12 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 00:20:23,566] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.53 | bwd_microstep: 271.44 | bwd_inner_microstep: 271.42 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 00:20:24,047] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.77 | bwd_microstep: 272.37 | bwd_inner_microstep: 272.35 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 00:20:24,524] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.53 | bwd_microstep: 271.27 | bwd_inner_microstep: 271.24 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 00:20:25,105] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.17 | optimizer_step: 16.82 +[2025-05-02 00:20:25,105] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.62 | bwd_microstep: 349.36 | bwd_inner_microstep: 273.48 | bwd_allreduce_microstep: 75.83 | step_microstep: 24.45 +[2025-05-02 00:20:25,107] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2788.46 | bwd: 4039.19 | bwd_inner: 3962.59 | bwd_allreduce: 76.12 | step: 25.83 + 9%|▉ | 774/8720 [2:04:58<15:43:54, 7.13s/it] {'loss': 0.988, 'grad_norm': 7.124157905578613, 'learning_rate': 9.909856375347859e-06, 'epoch': 0.89} + 9%|▉ | 774/8720 [2:04:58<15:43:54, 7.13s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 460 +[2025-05-02 00:20:25,339] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 82.80 | bwd_microstep: 128.93 | bwd_inner_microstep: 128.72 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1922 +[2025-05-02 00:20:25,839] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 197.13 | bwd_microstep: 287.48 | bwd_inner_microstep: 287.46 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1905 +[2025-05-02 00:20:26,322] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.01 | bwd_microstep: 276.15 | bwd_inner_microstep: 276.13 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-02 00:20:26,800] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.53 | bwd_microstep: 274.00 | bwd_inner_microstep: 273.98 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 00:20:27,278] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.22 | bwd_microstep: 273.46 | bwd_inner_microstep: 273.44 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-02 00:20:27,755] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.73 | bwd_microstep: 273.30 | bwd_inner_microstep: 273.28 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 328 +[2025-05-02 00:20:27,966] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 67.10 | bwd_microstep: 130.74 | bwd_inner_microstep: 130.57 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.08 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 325 +[2025-05-02 00:20:28,174] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 69.91 | bwd_microstep: 124.52 | bwd_inner_microstep: 124.22 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 00:20:28,650] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.71 | bwd_microstep: 272.79 | bwd_inner_microstep: 272.77 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 00:20:29,128] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.98 | bwd_microstep: 272.88 | bwd_inner_microstep: 272.86 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 00:20:29,605] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.20 | bwd_microstep: 272.62 | bwd_inner_microstep: 272.60 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.15 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 00:20:30,084] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.33 | bwd_microstep: 272.42 | bwd_inner_microstep: 272.40 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 00:20:30,563] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.56 | bwd_microstep: 271.31 | bwd_inner_microstep: 271.29 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 00:20:31,041] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.25 | bwd_microstep: 271.30 | bwd_inner_microstep: 271.29 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 828 +[2025-05-02 00:20:31,287] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.12 | bwd_microstep: 134.39 | bwd_inner_microstep: 134.33 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1927 +[2025-05-02 00:20:31,890] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.41 | optimizer_step: 16.92 +[2025-05-02 00:20:31,890] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 194.98 | bwd_microstep: 365.59 | bwd_inner_microstep: 288.25 | bwd_allreduce_microstep: 77.28 | step_microstep: 25.16 +[2025-05-02 00:20:31,892] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2597.26 | bwd: 3901.94 | bwd_inner: 3823.77 | bwd_allreduce: 77.60 | step: 26.33 + 9%|▉ | 775/8720 [2:05:05<15:30:12, 7.02s/it] {'loss': 0.9957, 'grad_norm': 6.559855937957764, 'learning_rate': 9.909504975022753e-06, 'epoch': 0.89} + 9%|▉ | 775/8720 [2:05:05<15:30:12, 7.02s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1953 +[2025-05-02 00:20:32,400] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 196.75 | bwd_microstep: 288.95 | bwd_inner_microstep: 288.94 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1905 +[2025-05-02 00:20:32,884] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.54 | bwd_microstep: 275.86 | bwd_inner_microstep: 275.85 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-02 00:20:33,363] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.53 | bwd_microstep: 273.82 | bwd_inner_microstep: 273.80 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 00:20:33,841] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.20 | bwd_microstep: 272.76 | bwd_inner_microstep: 272.75 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 00:20:34,321] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.09 | bwd_microstep: 272.75 | bwd_inner_microstep: 272.74 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 330 +[2025-05-02 00:20:34,533] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 67.60 | bwd_microstep: 130.57 | bwd_inner_microstep: 130.26 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.18 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 331 +[2025-05-02 00:20:34,747] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 79.33 | bwd_microstep: 119.79 | bwd_inner_microstep: 119.58 | bwd_allreduce_microstep: 0.08 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 00:20:35,224] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.08 | bwd_microstep: 272.80 | bwd_inner_microstep: 272.78 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 00:20:35,702] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.34 | bwd_microstep: 272.66 | bwd_inner_microstep: 272.64 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 00:20:36,180] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.06 | bwd_microstep: 272.57 | bwd_inner_microstep: 272.55 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 00:20:36,658] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.22 | bwd_microstep: 272.64 | bwd_inner_microstep: 272.62 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 836 +[2025-05-02 00:20:36,891] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 92.01 | bwd_microstep: 126.32 | bwd_inner_microstep: 126.17 | bwd_allreduce_microstep: 0.10 | step_microstep: 0.09 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1344 +[2025-05-02 00:20:37,252] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.03 | bwd_microstep: 204.85 | bwd_inner_microstep: 204.73 | bwd_allreduce_microstep: 0.03 | step_microstep: 0.18 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 832 +[2025-05-02 00:20:37,497] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 99.02 | bwd_microstep: 130.16 | bwd_inner_microstep: 129.93 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1892 +[2025-05-02 00:20:37,980] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.08 | bwd_microstep: 275.01 | bwd_inner_microstep: 274.99 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 00:20:38,569] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.66 | optimizer_step: 17.79 +[2025-05-02 00:20:38,569] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.15 | bwd_microstep: 353.40 | bwd_inner_microstep: 272.02 | bwd_allreduce_microstep: 81.33 | step_microstep: 26.15 +[2025-05-02 00:20:38,571] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2567.69 | bwd: 3815.07 | bwd_inner: 3732.45 | bwd_allreduce: 81.91 | step: 27.59 + 9%|▉ | 776/8720 [2:05:12<15:16:22, 6.92s/it] {'loss': 1.1174, 'grad_norm': 8.418855667114258, 'learning_rate': 9.909152897364884e-06, 'epoch': 0.89} + 9%|▉ | 776/8720 [2:05:12<15:16:22, 6.92s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1971 +[2025-05-02 00:20:39,085] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 199.23 | bwd_microstep: 290.92 | bwd_inner_microstep: 290.91 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1962 +[2025-05-02 00:20:39,590] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 196.59 | bwd_microstep: 290.65 | bwd_inner_microstep: 290.63 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1934 +[2025-05-02 00:20:40,094] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.23 | bwd_microstep: 288.56 | bwd_inner_microstep: 288.54 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1367 +[2025-05-02 00:20:40,460] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.35 | bwd_microstep: 207.36 | bwd_inner_microstep: 207.34 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-02 00:20:40,941] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.43 | bwd_microstep: 273.76 | bwd_inner_microstep: 273.74 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-02 00:20:41,423] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.08 | bwd_microstep: 274.51 | bwd_inner_microstep: 274.49 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 845 +[2025-05-02 00:20:41,674] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 100.51 | bwd_microstep: 132.90 | bwd_inner_microstep: 132.75 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 00:20:42,153] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.74 | bwd_microstep: 273.03 | bwd_inner_microstep: 273.01 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 00:20:42,632] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.77 | bwd_microstep: 272.73 | bwd_inner_microstep: 272.71 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 00:20:43,113] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.55 | bwd_microstep: 272.72 | bwd_inner_microstep: 272.70 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 00:20:43,593] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.95 | bwd_microstep: 273.50 | bwd_inner_microstep: 273.48 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 320 +[2025-05-02 00:20:43,812] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 81.63 | bwd_microstep: 120.05 | bwd_inner_microstep: 119.85 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 322 +[2025-05-02 00:20:44,028] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 85.70 | bwd_microstep: 114.43 | bwd_inner_microstep: 114.13 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 00:20:44,507] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.80 | bwd_microstep: 271.20 | bwd_inner_microstep: 271.18 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 00:20:44,983] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.81 | bwd_microstep: 271.16 | bwd_inner_microstep: 271.14 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 428 +[2025-05-02 00:20:45,319] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.21 | optimizer_step: 17.04 +[2025-05-02 00:20:45,320] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 84.18 | bwd_microstep: 211.38 | bwd_inner_microstep: 134.15 | bwd_allreduce_microstep: 77.07 | step_microstep: 25.22 +[2025-05-02 00:20:45,321] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2594.16 | bwd: 3838.94 | bwd_inner: 3760.94 | bwd_allreduce: 77.39 | step: 26.25 + 9%|▉ | 777/8720 [2:05:19<15:09:26, 6.87s/it] {'loss': 0.8049, 'grad_norm': 4.291380405426025, 'learning_rate': 9.908800142422826e-06, 'epoch': 0.89} + 9%|▉ | 777/8720 [2:05:19<15:09:26, 6.87s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1906 +[2025-05-02 00:20:45,809] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.30 | bwd_microstep: 275.39 | bwd_inner_microstep: 275.37 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1903 +[2025-05-02 00:20:46,291] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.52 | bwd_microstep: 275.96 | bwd_inner_microstep: 275.95 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 882 +[2025-05-02 00:20:46,543] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 96.54 | bwd_microstep: 135.75 | bwd_inner_microstep: 135.55 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 00:20:47,022] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.97 | bwd_microstep: 272.71 | bwd_inner_microstep: 272.70 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 00:20:47,502] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.20 | bwd_microstep: 272.88 | bwd_inner_microstep: 272.87 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1105 +[2025-05-02 00:20:47,798] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 115.67 | bwd_microstep: 161.94 | bwd_inner_microstep: 161.89 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.12 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 839 +[2025-05-02 00:20:48,042] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.66 | bwd_microstep: 126.50 | bwd_inner_microstep: 126.28 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 00:20:48,521] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.87 | bwd_microstep: 272.91 | bwd_inner_microstep: 272.90 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 00:20:49,000] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.67 | bwd_microstep: 272.71 | bwd_inner_microstep: 272.69 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 00:20:49,480] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.35 | bwd_microstep: 272.66 | bwd_inner_microstep: 272.65 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 00:20:49,962] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.94 | bwd_microstep: 272.16 | bwd_inner_microstep: 272.14 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.14 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 00:20:50,441] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.01 | bwd_microstep: 271.30 | bwd_inner_microstep: 271.29 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 318 +[2025-05-02 00:20:50,663] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 78.60 | bwd_microstep: 128.64 | bwd_inner_microstep: 128.48 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 00:20:51,140] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.17 | bwd_microstep: 271.48 | bwd_inner_microstep: 271.43 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 00:20:51,618] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.49 | bwd_microstep: 271.37 | bwd_inner_microstep: 271.35 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2018 +[2025-05-02 00:20:52,236] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.11 | optimizer_step: 17.11 +[2025-05-02 00:20:52,237] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 200.86 | bwd_microstep: 373.52 | bwd_inner_microstep: 296.97 | bwd_allreduce_microstep: 76.49 | step_microstep: 24.78 +[2025-05-02 00:20:52,238] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2661.44 | bwd: 3927.99 | bwd_inner: 3850.54 | bwd_allreduce: 76.86 | step: 26.04 + 9%|▉ | 778/8720 [2:05:25<15:11:12, 6.88s/it] {'loss': 1.077, 'grad_norm': 7.665526866912842, 'learning_rate': 9.908446710245247e-06, 'epoch': 0.89} + 9%|▉ | 778/8720 [2:05:25<15:11:12, 6.88s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1909 +[2025-05-02 00:20:52,727] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.60 | bwd_microstep: 275.82 | bwd_inner_microstep: 275.80 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1902 +[2025-05-02 00:20:53,211] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.72 | bwd_microstep: 275.86 | bwd_inner_microstep: 275.85 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1896 +[2025-05-02 00:20:53,692] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.79 | bwd_microstep: 275.44 | bwd_inner_microstep: 275.42 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 864 +[2025-05-02 00:20:53,938] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.01 | bwd_microstep: 134.42 | bwd_inner_microstep: 134.12 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-02 00:20:54,420] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.02 | bwd_microstep: 274.42 | bwd_inner_microstep: 274.41 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 00:20:54,899] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.90 | bwd_microstep: 273.08 | bwd_inner_microstep: 273.07 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 00:20:55,378] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.43 | bwd_microstep: 272.90 | bwd_inner_microstep: 272.88 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 00:20:55,858] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.08 | bwd_microstep: 273.32 | bwd_inner_microstep: 273.31 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 00:20:56,339] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.82 | bwd_microstep: 272.91 | bwd_inner_microstep: 272.89 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 00:20:56,823] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.54 | bwd_microstep: 273.02 | bwd_inner_microstep: 273.00 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 00:20:57,307] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.32 | bwd_microstep: 272.41 | bwd_inner_microstep: 272.39 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 00:20:57,785] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.15 | bwd_microstep: 271.81 | bwd_inner_microstep: 271.79 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 00:20:58,266] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.18 | bwd_microstep: 272.62 | bwd_inner_microstep: 272.59 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.12 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 315 +[2025-05-02 00:20:58,506] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.37 | bwd_microstep: 127.12 | bwd_inner_microstep: 126.88 | bwd_allreduce_microstep: 0.10 | step_microstep: 0.12 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 828 +[2025-05-02 00:20:58,749] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.73 | bwd_microstep: 130.63 | bwd_inner_microstep: 130.38 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.18 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 316 +[2025-05-02 00:20:59,089] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.17 | optimizer_step: 17.20 +[2025-05-02 00:20:59,089] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 83.51 | bwd_microstep: 215.38 | bwd_inner_microstep: 136.94 | bwd_allreduce_microstep: 78.28 | step_microstep: 25.19 +[2025-05-02 00:20:59,091] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2632.81 | bwd: 3891.29 | bwd_inner: 3811.89 | bwd_allreduce: 78.64 | step: 26.67 + 9%|▉ | 779/8720 [2:05:32<15:09:51, 6.87s/it] {'loss': 1.0109, 'grad_norm': 7.599294662475586, 'learning_rate': 9.908092600880906e-06, 'epoch': 0.89} + 9%|▉ | 779/8720 [2:05:32<15:09:51, 6.87s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2053 +[2025-05-02 00:20:59,617] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 201.23 | bwd_microstep: 301.48 | bwd_inner_microstep: 301.46 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1886 +[2025-05-02 00:21:00,099] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.36 | bwd_microstep: 274.55 | bwd_inner_microstep: 274.54 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-02 00:21:00,580] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.67 | bwd_microstep: 273.67 | bwd_inner_microstep: 273.66 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 334 +[2025-05-02 00:21:00,794] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 75.03 | bwd_microstep: 122.44 | bwd_inner_microstep: 122.13 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 00:21:01,272] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.75 | bwd_microstep: 273.08 | bwd_inner_microstep: 273.07 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 00:21:01,753] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.46 | bwd_microstep: 273.38 | bwd_inner_microstep: 273.36 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 00:21:02,235] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.45 | bwd_microstep: 272.63 | bwd_inner_microstep: 272.61 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 00:21:02,717] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.54 | bwd_microstep: 272.65 | bwd_inner_microstep: 272.63 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 00:21:03,197] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.66 | bwd_microstep: 272.87 | bwd_inner_microstep: 272.86 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 00:21:03,677] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.66 | bwd_microstep: 272.76 | bwd_inner_microstep: 272.75 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 00:21:04,158] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.05 | bwd_microstep: 273.03 | bwd_inner_microstep: 273.01 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 840 +[2025-05-02 00:21:04,401] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 98.41 | bwd_microstep: 126.29 | bwd_inner_microstep: 126.02 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.24 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 00:21:04,887] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.40 | bwd_microstep: 273.32 | bwd_inner_microstep: 273.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 00:21:05,371] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.62 | bwd_microstep: 272.78 | bwd_inner_microstep: 272.75 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 00:21:05,851] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.71 | bwd_microstep: 271.42 | bwd_inner_microstep: 271.41 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 00:21:06,432] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.16 | optimizer_step: 17.19 +[2025-05-02 00:21:06,433] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.83 | bwd_microstep: 349.30 | bwd_inner_microstep: 272.01 | bwd_allreduce_microstep: 77.23 | step_microstep: 25.15 +[2025-05-02 00:21:06,434] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2830.46 | bwd: 4175.76 | bwd_inner: 4097.63 | bwd_allreduce: 77.55 | step: 26.65 + 9%|▉ | 780/8720 [2:05:40<15:28:20, 7.02s/it] {'loss': 0.5357, 'grad_norm': 4.261849880218506, 'learning_rate': 9.907737814378658e-06, 'epoch': 0.89} + 9%|▉ | 780/8720 [2:05:40<15:28:20, 7.02s/it]dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 915 +[2025-05-02 00:21:06,705] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 103.41 | bwd_microstep: 145.24 | bwd_inner_microstep: 145.08 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1910 +[2025-05-02 00:21:07,189] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.54 | bwd_microstep: 276.57 | bwd_inner_microstep: 276.55 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-02 00:21:07,669] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.38 | bwd_microstep: 273.24 | bwd_inner_microstep: 273.23 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.16 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 00:21:08,148] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.14 | bwd_microstep: 272.70 | bwd_inner_microstep: 272.68 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.16 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 00:21:08,628] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.13 | bwd_microstep: 273.30 | bwd_inner_microstep: 273.28 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 00:21:09,109] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.47 | bwd_microstep: 273.14 | bwd_inner_microstep: 273.13 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1349 +[2025-05-02 00:21:09,474] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.97 | bwd_microstep: 206.07 | bwd_inner_microstep: 205.97 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.18 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 845 +[2025-05-02 00:21:09,720] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 96.11 | bwd_microstep: 132.10 | bwd_inner_microstep: 132.06 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 00:21:10,198] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.94 | bwd_microstep: 272.48 | bwd_inner_microstep: 272.46 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 00:21:10,680] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.09 | bwd_microstep: 272.78 | bwd_inner_microstep: 272.77 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 00:21:11,159] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.41 | bwd_microstep: 272.85 | bwd_inner_microstep: 272.84 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 00:21:11,637] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.00 | bwd_microstep: 272.44 | bwd_inner_microstep: 272.42 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 00:21:12,115] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.82 | bwd_microstep: 271.52 | bwd_inner_microstep: 271.51 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 00:21:12,597] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.93 | bwd_microstep: 272.42 | bwd_inner_microstep: 272.40 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 00:21:13,074] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.86 | bwd_microstep: 271.11 | bwd_inner_microstep: 271.09 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 00:21:13,658] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 3.40 | optimizer_step: 19.08 +[2025-05-02 00:21:13,658] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.14 | bwd_microstep: 350.14 | bwd_inner_microstep: 271.78 | bwd_allreduce_microstep: 78.31 | step_microstep: 28.51 +[2025-05-02 00:21:13,660] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2792.01 | bwd: 4108.17 | bwd_inner: 4029.25 | bwd_allreduce: 78.49 | step: 29.98 + 9%|▉ | 781/8720 [2:05:47<15:36:35, 7.08s/it] {'loss': 1.4663, 'grad_norm': 7.193757057189941, 'learning_rate': 9.90738235078745e-06, 'epoch': 0.9} + 9%|▉ | 781/8720 [2:05:47<15:36:35, 7.08s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 378 +[2025-05-02 00:21:13,882] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 80.55 | bwd_microstep: 120.07 | bwd_inner_microstep: 119.75 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.23 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1924 +[2025-05-02 00:21:14,383] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 194.77 | bwd_microstep: 287.46 | bwd_inner_microstep: 287.44 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 381 +[2025-05-02 00:21:14,620] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.12 | bwd_microstep: 124.30 | bwd_inner_microstep: 124.00 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1134 +[2025-05-02 00:21:14,920] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 118.39 | bwd_microstep: 164.22 | bwd_inner_microstep: 164.17 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1902 +[2025-05-02 00:21:15,404] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.36 | bwd_microstep: 275.74 | bwd_inner_microstep: 275.72 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.16 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1892 +[2025-05-02 00:21:15,892] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.97 | bwd_microstep: 274.87 | bwd_inner_microstep: 274.86 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 346 +[2025-05-02 00:21:16,134] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 79.12 | bwd_microstep: 142.64 | bwd_inner_microstep: 142.51 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-02 00:21:16,614] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.30 | bwd_microstep: 274.42 | bwd_inner_microstep: 274.40 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 343 +[2025-05-02 00:21:16,829] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 73.78 | bwd_microstep: 127.80 | bwd_inner_microstep: 127.64 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-02 00:21:17,308] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.84 | bwd_microstep: 274.39 | bwd_inner_microstep: 274.36 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 00:21:17,786] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.15 | bwd_microstep: 272.84 | bwd_inner_microstep: 272.82 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 00:21:18,267] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.70 | bwd_microstep: 272.84 | bwd_inner_microstep: 272.82 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1345 +[2025-05-02 00:21:18,636] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 142.17 | bwd_microstep: 205.89 | bwd_inner_microstep: 205.67 | bwd_allreduce_microstep: 0.10 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 00:21:19,114] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.38 | bwd_microstep: 272.18 | bwd_inner_microstep: 272.16 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.15 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 00:21:19,596] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.27 | bwd_microstep: 271.21 | bwd_inner_microstep: 271.19 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 313 +[2025-05-02 00:21:19,955] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.22 | optimizer_step: 17.02 +[2025-05-02 00:21:19,956] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 91.69 | bwd_microstep: 226.00 | bwd_inner_microstep: 148.93 | bwd_allreduce_microstep: 76.91 | step_microstep: 25.03 +[2025-05-02 00:21:19,957] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2384.20 | bwd: 3586.99 | bwd_inner: 3508.70 | bwd_allreduce: 77.46 | step: 26.62 + 9%|▉ | 782/8720 [2:05:53<15:05:27, 6.84s/it] {'loss': 0.8544, 'grad_norm': 5.5421528816223145, 'learning_rate': 9.907026210156324e-06, 'epoch': 0.9} + 9%|▉ | 782/8720 [2:05:53<15:05:27, 6.84s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 383 +[2025-05-02 00:21:20,177] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 81.21 | bwd_microstep: 117.41 | bwd_inner_microstep: 117.25 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1910 +[2025-05-02 00:21:20,660] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.24 | bwd_microstep: 276.24 | bwd_inner_microstep: 276.23 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 866 +[2025-05-02 00:21:20,933] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 118.64 | bwd_microstep: 132.97 | bwd_inner_microstep: 132.96 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1887 +[2025-05-02 00:21:21,412] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.13 | bwd_microstep: 274.59 | bwd_inner_microstep: 274.57 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-02 00:21:21,891] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.38 | bwd_microstep: 273.73 | bwd_inner_microstep: 273.72 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 839 +[2025-05-02 00:21:22,126] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 92.63 | bwd_microstep: 126.42 | bwd_inner_microstep: 126.17 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.23 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 329 +[2025-05-02 00:21:22,378] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 96.76 | bwd_microstep: 138.38 | bwd_inner_microstep: 138.18 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 838 +[2025-05-02 00:21:22,610] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 91.27 | bwd_microstep: 126.69 | bwd_inner_microstep: 126.35 | bwd_allreduce_microstep: 0.17 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 00:21:23,095] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.67 | bwd_microstep: 272.74 | bwd_inner_microstep: 272.73 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 00:21:23,574] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.69 | bwd_microstep: 272.81 | bwd_inner_microstep: 272.79 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 333 +[2025-05-02 00:21:23,823] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 111.52 | bwd_microstep: 117.69 | bwd_inner_microstep: 117.39 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 00:21:24,301] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.23 | bwd_microstep: 272.88 | bwd_inner_microstep: 272.86 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 330 +[2025-05-02 00:21:24,520] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 85.39 | bwd_microstep: 117.70 | bwd_inner_microstep: 117.41 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 00:21:25,000] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.74 | bwd_microstep: 272.80 | bwd_inner_microstep: 272.79 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 00:21:25,483] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.73 | bwd_microstep: 271.55 | bwd_inner_microstep: 271.53 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 00:21:26,064] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.29 | optimizer_step: 17.24 +[2025-05-02 00:21:26,065] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.03 | bwd_microstep: 348.91 | bwd_inner_microstep: 271.79 | bwd_allreduce_microstep: 77.07 | step_microstep: 25.73 +[2025-05-02 00:21:26,067] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2377.91 | bwd: 3413.67 | bwd_inner: 3334.97 | bwd_allreduce: 77.73 | step: 26.94 + 9%|▉ | 783/8720 [2:05:59<14:36:11, 6.62s/it] {'loss': 0.9381, 'grad_norm': 4.4584550857543945, 'learning_rate': 9.906669392534415e-06, 'epoch': 0.9} + 9%|▉ | 783/8720 [2:05:59<14:36:11, 6.62s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1896 +[2025-05-02 00:21:26,552] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.16 | bwd_microstep: 274.57 | bwd_inner_microstep: 274.55 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-02 00:21:27,032] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.66 | bwd_microstep: 274.10 | bwd_inner_microstep: 274.08 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-02 00:21:27,511] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.23 | bwd_microstep: 274.16 | bwd_inner_microstep: 274.14 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 859 +[2025-05-02 00:21:27,761] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 99.14 | bwd_microstep: 133.41 | bwd_inner_microstep: 133.26 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-02 00:21:28,243] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.32 | bwd_microstep: 273.98 | bwd_inner_microstep: 273.96 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 845 +[2025-05-02 00:21:28,499] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 104.02 | bwd_microstep: 132.43 | bwd_inner_microstep: 132.19 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 00:21:28,979] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.32 | bwd_microstep: 273.06 | bwd_inner_microstep: 273.04 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 00:21:29,462] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.46 | bwd_microstep: 273.30 | bwd_inner_microstep: 273.28 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 00:21:29,944] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.27 | bwd_microstep: 272.71 | bwd_inner_microstep: 272.69 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 00:21:30,425] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.14 | bwd_microstep: 272.82 | bwd_inner_microstep: 272.80 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 00:21:30,905] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.68 | bwd_microstep: 273.04 | bwd_inner_microstep: 273.02 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 00:21:31,385] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.64 | bwd_microstep: 271.36 | bwd_inner_microstep: 271.34 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.14 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 00:21:31,865] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.54 | bwd_microstep: 271.28 | bwd_inner_microstep: 271.26 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 00:21:32,347] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.87 | bwd_microstep: 271.00 | bwd_inner_microstep: 270.98 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 362 +[2025-05-02 00:21:32,554] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 71.30 | bwd_microstep: 120.27 | bwd_inner_microstep: 119.95 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 00:21:33,132] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.18 | optimizer_step: 17.17 +[2025-05-02 00:21:33,133] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.45 | bwd_microstep: 350.45 | bwd_inner_microstep: 273.34 | bwd_allreduce_microstep: 77.06 | step_microstep: 24.86 +[2025-05-02 00:21:33,134] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2728.81 | bwd: 4012.02 | bwd_inner: 3933.99 | bwd_allreduce: 77.44 | step: 26.14 + 9%|▉ | 784/8720 [2:06:06<14:53:43, 6.76s/it] {'loss': 0.9786, 'grad_norm': 4.906748294830322, 'learning_rate': 9.90631189797095e-06, 'epoch': 0.9} + 9%|▉ | 784/8720 [2:06:06<14:53:43, 6.76s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2293 +[2025-05-02 00:21:33,695] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 212.39 | bwd_microstep: 326.42 | bwd_inner_microstep: 326.40 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1570 +[2025-05-02 00:21:34,101] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 150.18 | bwd_microstep: 239.90 | bwd_inner_microstep: 239.77 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1892 +[2025-05-02 00:21:34,582] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.89 | bwd_microstep: 274.98 | bwd_inner_microstep: 274.96 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-02 00:21:35,064] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.88 | bwd_microstep: 273.35 | bwd_inner_microstep: 273.34 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-02 00:21:35,547] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.22 | bwd_microstep: 273.76 | bwd_inner_microstep: 273.74 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-02 00:21:36,029] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.38 | bwd_microstep: 273.44 | bwd_inner_microstep: 273.42 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-02 00:21:36,506] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.69 | bwd_microstep: 273.45 | bwd_inner_microstep: 273.43 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 00:21:36,984] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.07 | bwd_microstep: 273.19 | bwd_inner_microstep: 273.18 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 328 +[2025-05-02 00:21:37,200] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 76.14 | bwd_microstep: 125.70 | bwd_inner_microstep: 125.50 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 00:21:37,681] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.27 | bwd_microstep: 272.61 | bwd_inner_microstep: 272.59 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 00:21:38,158] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.37 | bwd_microstep: 272.79 | bwd_inner_microstep: 272.78 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 00:21:38,636] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.74 | bwd_microstep: 272.83 | bwd_inner_microstep: 272.82 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.15 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 00:21:39,111] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.21 | bwd_microstep: 272.28 | bwd_inner_microstep: 272.26 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 832 +[2025-05-02 00:21:39,367] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 108.65 | bwd_microstep: 129.54 | bwd_inner_microstep: 129.51 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 00:21:39,843] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.29 | bwd_microstep: 272.64 | bwd_inner_microstep: 272.63 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1953 +[2025-05-02 00:21:40,441] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.12 | optimizer_step: 17.08 +[2025-05-02 00:21:40,442] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 196.69 | bwd_microstep: 360.73 | bwd_inner_microstep: 290.53 | bwd_allreduce_microstep: 70.16 | step_microstep: 24.21 +[2025-05-02 00:21:40,443] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2824.73 | bwd: 4187.67 | bwd_inner: 4116.91 | bwd_allreduce: 70.39 | step: 25.43 + 9%|▉ | 785/8720 [2:06:14<15:15:24, 6.92s/it] {'loss': 1.4752, 'grad_norm': 8.925286293029785, 'learning_rate': 9.905953726515249e-06, 'epoch': 0.9} + 9%|▉ | 785/8720 [2:06:14<15:15:24, 6.92s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 517 +[2025-05-02 00:21:40,654] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 73.14 | bwd_microstep: 120.29 | bwd_inner_microstep: 120.14 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1448 +[2025-05-02 00:21:41,034] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 146.19 | bwd_microstep: 215.86 | bwd_inner_microstep: 215.71 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-02 00:21:41,512] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.57 | bwd_microstep: 274.22 | bwd_inner_microstep: 274.20 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1893 +[2025-05-02 00:21:41,992] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.13 | bwd_microstep: 275.02 | bwd_inner_microstep: 275.01 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 00:21:42,468] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.16 | bwd_microstep: 272.41 | bwd_inner_microstep: 272.39 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 00:21:42,945] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.14 | bwd_microstep: 272.69 | bwd_inner_microstep: 272.68 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 00:21:43,424] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.50 | bwd_microstep: 272.50 | bwd_inner_microstep: 272.48 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 00:21:43,903] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.65 | bwd_microstep: 272.91 | bwd_inner_microstep: 272.90 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 00:21:44,383] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.05 | bwd_microstep: 272.52 | bwd_inner_microstep: 272.50 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 00:21:44,863] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.26 | bwd_microstep: 271.28 | bwd_inner_microstep: 271.26 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 00:21:45,340] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.10 | bwd_microstep: 271.26 | bwd_inner_microstep: 271.24 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 322 +[2025-05-02 00:21:45,561] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 88.50 | bwd_microstep: 115.47 | bwd_inner_microstep: 115.15 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 00:21:46,038] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.49 | bwd_microstep: 271.39 | bwd_inner_microstep: 271.37 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 00:21:46,517] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.85 | bwd_microstep: 271.32 | bwd_inner_microstep: 271.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 00:21:46,998] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.02 | bwd_microstep: 271.26 | bwd_inner_microstep: 271.24 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 898 +[2025-05-02 00:21:47,363] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.14 | optimizer_step: 17.17 +[2025-05-02 00:21:47,363] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 101.72 | bwd_microstep: 220.83 | bwd_inner_microstep: 144.53 | bwd_allreduce_microstep: 76.19 | step_microstep: 24.97 +[2025-05-02 00:21:47,365] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2673.13 | bwd: 3941.31 | bwd_inner: 3864.23 | bwd_allreduce: 76.52 | step: 25.93 + 9%|▉ | 786/8720 [2:06:21<15:15:21, 6.92s/it] {'loss': 0.903, 'grad_norm': 8.487229347229004, 'learning_rate': 9.905594878216729e-06, 'epoch': 0.9} + 9%|▉ | 786/8720 [2:06:21<15:15:21, 6.92s/it]dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 987 +[2025-05-02 00:21:47,640] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 104.22 | bwd_microstep: 150.18 | bwd_inner_microstep: 150.01 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1926 +[2025-05-02 00:21:48,141] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.74 | bwd_microstep: 287.53 | bwd_inner_microstep: 287.52 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1920 +[2025-05-02 00:21:48,626] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 192.42 | bwd_microstep: 276.40 | bwd_inner_microstep: 276.38 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1893 +[2025-05-02 00:21:49,105] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.05 | bwd_microstep: 274.73 | bwd_inner_microstep: 274.71 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 844 +[2025-05-02 00:21:49,346] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.17 | bwd_microstep: 132.33 | bwd_inner_microstep: 132.17 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.08 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1351 +[2025-05-02 00:21:49,709] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.99 | bwd_microstep: 206.23 | bwd_inner_microstep: 206.21 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 00:21:50,184] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.42 | bwd_microstep: 272.08 | bwd_inner_microstep: 272.06 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 00:21:50,661] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.74 | bwd_microstep: 272.66 | bwd_inner_microstep: 272.64 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 00:21:51,137] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.85 | bwd_microstep: 272.56 | bwd_inner_microstep: 272.54 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.16 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 00:21:51,613] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.25 | bwd_microstep: 271.49 | bwd_inner_microstep: 271.47 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 00:21:52,088] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.99 | bwd_microstep: 272.14 | bwd_inner_microstep: 272.12 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 00:21:52,562] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.32 | bwd_microstep: 271.27 | bwd_inner_microstep: 271.26 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 00:21:53,037] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.86 | bwd_microstep: 271.01 | bwd_inner_microstep: 271.00 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 00:21:53,511] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.28 | bwd_microstep: 270.99 | bwd_inner_microstep: 270.97 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 826 +[2025-05-02 00:21:53,749] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.43 | bwd_microstep: 129.48 | bwd_inner_microstep: 129.46 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2105 +[2025-05-02 00:21:54,371] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.05 | optimizer_step: 16.91 +[2025-05-02 00:21:54,371] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 203.78 | bwd_microstep: 379.51 | bwd_inner_microstep: 312.66 | bwd_allreduce_microstep: 66.80 | step_microstep: 23.89 +[2025-05-02 00:21:54,372] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2720.26 | bwd: 4010.62 | bwd_inner: 3943.23 | bwd_allreduce: 67.00 | step: 24.96 + 9%|▉ | 787/8720 [2:06:28<15:18:33, 6.95s/it] {'loss': 1.0836, 'grad_norm': 7.06987190246582, 'learning_rate': 9.905235353124897e-06, 'epoch': 0.9} + 9%|▉ | 787/8720 [2:06:28<15:18:33, 6.95s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1920 +[2025-05-02 00:21:54,859] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.70 | bwd_microstep: 275.99 | bwd_inner_microstep: 275.98 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.14 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1381 +[2025-05-02 00:21:55,227] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 143.93 | bwd_microstep: 208.88 | bwd_inner_microstep: 208.73 | bwd_allreduce_microstep: 0.04 | step_microstep: 0.09 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 350 +[2025-05-02 00:21:55,445] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 78.47 | bwd_microstep: 124.53 | bwd_inner_microstep: 124.39 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1894 +[2025-05-02 00:21:55,924] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.79 | bwd_microstep: 274.93 | bwd_inner_microstep: 274.91 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-02 00:21:56,402] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.01 | bwd_microstep: 273.60 | bwd_inner_microstep: 273.58 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 00:21:56,879] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.68 | bwd_microstep: 272.89 | bwd_inner_microstep: 272.87 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 00:21:57,356] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.37 | bwd_microstep: 272.75 | bwd_inner_microstep: 272.73 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 00:21:57,833] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.57 | bwd_microstep: 273.01 | bwd_inner_microstep: 273.00 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 00:21:58,314] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.47 | bwd_microstep: 272.99 | bwd_inner_microstep: 272.97 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 00:21:58,796] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.18 | bwd_microstep: 273.56 | bwd_inner_microstep: 273.54 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 321 +[2025-05-02 00:21:59,026] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 91.54 | bwd_microstep: 118.84 | bwd_inner_microstep: 118.66 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 00:21:59,503] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.75 | bwd_microstep: 272.22 | bwd_inner_microstep: 272.21 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 00:21:59,984] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.17 | bwd_microstep: 272.29 | bwd_inner_microstep: 272.27 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.16 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 00:22:00,464] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.14 | bwd_microstep: 271.30 | bwd_inner_microstep: 271.28 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 00:22:00,945] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.10 | bwd_microstep: 271.10 | bwd_inner_microstep: 271.08 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 00:22:01,537] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.13 | optimizer_step: 16.77 +[2025-05-02 00:22:01,538] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.65 | bwd_microstep: 358.54 | bwd_inner_microstep: 273.59 | bwd_allreduce_microstep: 84.90 | step_microstep: 24.52 +[2025-05-02 00:22:01,539] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2769.14 | bwd: 4087.48 | bwd_inner: 4001.89 | bwd_allreduce: 85.19 | step: 25.73 + 9%|▉ | 788/8720 [2:06:35<15:27:13, 7.01s/it] {'loss': 0.9214, 'grad_norm': 4.804137229919434, 'learning_rate': 9.904875151289353e-06, 'epoch': 0.9} + 9%|▉ | 788/8720 [2:06:35<15:27:13, 7.01s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1924 +[2025-05-02 00:22:02,044] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 194.78 | bwd_microstep: 286.87 | bwd_inner_microstep: 286.85 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1904 +[2025-05-02 00:22:02,527] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.73 | bwd_microstep: 275.88 | bwd_inner_microstep: 275.86 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1889 +[2025-05-02 00:22:03,011] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.59 | bwd_microstep: 274.87 | bwd_inner_microstep: 274.85 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.13 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1887 +[2025-05-02 00:22:03,495] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.23 | bwd_microstep: 274.74 | bwd_inner_microstep: 274.72 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-02 00:22:03,977] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.70 | bwd_microstep: 274.36 | bwd_inner_microstep: 274.34 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 00:22:04,459] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.28 | bwd_microstep: 273.42 | bwd_inner_microstep: 273.41 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1361 +[2025-05-02 00:22:04,827] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.89 | bwd_microstep: 206.88 | bwd_inner_microstep: 206.87 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 00:22:05,312] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.20 | bwd_microstep: 273.08 | bwd_inner_microstep: 273.06 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 00:22:05,794] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.70 | bwd_microstep: 272.89 | bwd_inner_microstep: 272.87 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 327 +[2025-05-02 00:22:06,009] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 80.68 | bwd_microstep: 119.04 | bwd_inner_microstep: 118.84 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 00:22:06,488] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.65 | bwd_microstep: 272.83 | bwd_inner_microstep: 272.81 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 00:22:06,968] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.02 | bwd_microstep: 272.40 | bwd_inner_microstep: 272.38 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 00:22:07,449] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.76 | bwd_microstep: 271.46 | bwd_inner_microstep: 271.44 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 00:22:07,926] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.72 | bwd_microstep: 271.46 | bwd_inner_microstep: 271.44 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 00:22:08,407] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.52 | bwd_microstep: 271.31 | bwd_inner_microstep: 271.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 00:22:08,987] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.15 | optimizer_step: 17.53 +[2025-05-02 00:22:08,988] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.26 | bwd_microstep: 347.98 | bwd_inner_microstep: 272.01 | bwd_allreduce_microstep: 75.92 | step_microstep: 26.01 +[2025-05-02 00:22:08,989] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2875.32 | bwd: 4239.49 | bwd_inner: 4163.10 | bwd_allreduce: 76.07 | step: 27.00 + 9%|▉ | 789/8720 [2:06:42<15:44:24, 7.14s/it] {'loss': 0.9985, 'grad_norm': 8.966215133666992, 'learning_rate': 9.904514272759794e-06, 'epoch': 0.9} + 9%|▉ | 789/8720 [2:06:42<15:44:24, 7.14s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1888 +[2025-05-02 00:22:09,476] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.39 | bwd_microstep: 274.14 | bwd_inner_microstep: 274.12 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-02 00:22:09,958] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.79 | bwd_microstep: 273.80 | bwd_inner_microstep: 273.78 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 00:22:10,440] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.73 | bwd_microstep: 273.47 | bwd_inner_microstep: 273.45 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1359 +[2025-05-02 00:22:10,807] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.02 | bwd_microstep: 206.84 | bwd_inner_microstep: 206.71 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 00:22:11,293] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.01 | bwd_microstep: 273.25 | bwd_inner_microstep: 273.23 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 00:22:11,776] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.73 | bwd_microstep: 272.61 | bwd_inner_microstep: 272.60 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 00:22:12,259] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.52 | bwd_microstep: 272.94 | bwd_inner_microstep: 272.92 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1358 +[2025-05-02 00:22:12,635] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 142.15 | bwd_microstep: 206.32 | bwd_inner_microstep: 206.28 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.12 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 325 +[2025-05-02 00:22:12,877] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.38 | bwd_microstep: 123.46 | bwd_inner_microstep: 123.27 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 00:22:13,354] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.11 | bwd_microstep: 272.38 | bwd_inner_microstep: 272.36 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.14 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 835 +[2025-05-02 00:22:13,591] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.61 | bwd_microstep: 126.14 | bwd_inner_microstep: 125.88 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 00:22:14,071] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.27 | bwd_microstep: 272.65 | bwd_inner_microstep: 272.64 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1344 +[2025-05-02 00:22:14,434] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.21 | bwd_microstep: 204.64 | bwd_inner_microstep: 204.58 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 00:22:14,910] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.04 | bwd_microstep: 271.32 | bwd_inner_microstep: 271.31 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 00:22:15,387] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.48 | bwd_microstep: 271.30 | bwd_inner_microstep: 271.28 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 00:22:15,955] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.04 | optimizer_gradients: 2.10 | optimizer_step: 16.90 +[2025-05-02 00:22:15,956] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.65 | bwd_microstep: 339.18 | bwd_inner_microstep: 271.91 | bwd_allreduce_microstep: 67.23 | step_microstep: 23.80 +[2025-05-02 00:22:15,957] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2687.67 | bwd: 3934.56 | bwd_inner: 3866.45 | bwd_allreduce: 67.55 | step: 25.25 + 9%|▉ | 790/8720 [2:06:49<15:37:11, 7.09s/it] {'loss': 1.2035, 'grad_norm': 8.24381160736084, 'learning_rate': 9.904152717586006e-06, 'epoch': 0.91} + 9%|▉ | 790/8720 [2:06:49<15:37:11, 7.09s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2053 +[2025-05-02 00:22:16,478] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 200.68 | bwd_microstep: 301.25 | bwd_inner_microstep: 301.24 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1898 +[2025-05-02 00:22:16,961] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.49 | bwd_microstep: 275.34 | bwd_inner_microstep: 275.32 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 343 +[2025-05-02 00:22:17,183] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 81.54 | bwd_microstep: 125.39 | bwd_inner_microstep: 125.10 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-02 00:22:17,661] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.41 | bwd_microstep: 273.81 | bwd_inner_microstep: 273.79 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1358 +[2025-05-02 00:22:18,024] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.81 | bwd_microstep: 206.75 | bwd_inner_microstep: 206.73 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-02 00:22:18,500] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.16 | bwd_microstep: 273.33 | bwd_inner_microstep: 273.31 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-02 00:22:18,980] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.48 | bwd_microstep: 273.34 | bwd_inner_microstep: 273.32 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 00:22:19,460] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.44 | bwd_microstep: 273.05 | bwd_inner_microstep: 273.04 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 00:22:19,942] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.33 | bwd_microstep: 272.63 | bwd_inner_microstep: 272.60 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 844 +[2025-05-02 00:22:20,195] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 99.65 | bwd_microstep: 131.93 | bwd_inner_microstep: 131.85 | bwd_allreduce_microstep: 0.03 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 00:22:20,674] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.72 | bwd_microstep: 272.16 | bwd_inner_microstep: 272.15 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 00:22:21,153] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.54 | bwd_microstep: 272.61 | bwd_inner_microstep: 272.59 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 00:22:21,631] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.27 | bwd_microstep: 271.48 | bwd_inner_microstep: 271.46 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 00:22:22,112] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.87 | bwd_microstep: 271.32 | bwd_inner_microstep: 271.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2013 +[2025-05-02 00:22:22,629] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 199.71 | bwd_microstep: 296.16 | bwd_inner_microstep: 296.14 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 00:22:23,213] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.25 | optimizer_step: 16.97 +[2025-05-02 00:22:23,214] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.30 | bwd_microstep: 351.25 | bwd_inner_microstep: 273.56 | bwd_allreduce_microstep: 77.64 | step_microstep: 25.02 +[2025-05-02 00:22:23,215] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2795.05 | bwd: 4141.83 | bwd_inner: 4063.56 | bwd_allreduce: 77.88 | step: 26.10 + 9%|▉ | 791/8720 [2:06:56<15:43:47, 7.14s/it] {'loss': 1.0388, 'grad_norm': 5.390271186828613, 'learning_rate': 9.903790485817872e-06, 'epoch': 0.91} + 9%|▉ | 791/8720 [2:06:56<15:43:47, 7.14s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1921 +[2025-05-02 00:22:23,720] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 194.87 | bwd_microstep: 286.59 | bwd_inner_microstep: 286.58 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-02 00:22:24,202] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.42 | bwd_microstep: 274.60 | bwd_inner_microstep: 274.58 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-02 00:22:24,681] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.02 | bwd_microstep: 273.85 | bwd_inner_microstep: 273.83 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-02 00:22:25,160] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.61 | bwd_microstep: 273.69 | bwd_inner_microstep: 273.67 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-02 00:22:25,639] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.47 | bwd_microstep: 273.47 | bwd_inner_microstep: 273.46 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 00:22:26,120] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.67 | bwd_microstep: 273.39 | bwd_inner_microstep: 273.37 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 00:22:26,600] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.12 | bwd_microstep: 272.89 | bwd_inner_microstep: 272.88 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 00:22:27,081] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.70 | bwd_microstep: 272.71 | bwd_inner_microstep: 272.69 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 00:22:27,560] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.33 | bwd_microstep: 272.49 | bwd_inner_microstep: 272.48 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 835 +[2025-05-02 00:22:27,804] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 97.27 | bwd_microstep: 126.92 | bwd_inner_microstep: 126.62 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 00:22:28,283] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.06 | bwd_microstep: 272.78 | bwd_inner_microstep: 272.76 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 00:22:28,766] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.83 | bwd_microstep: 272.43 | bwd_inner_microstep: 272.42 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 00:22:29,247] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.62 | bwd_microstep: 271.21 | bwd_inner_microstep: 271.19 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 00:22:29,729] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.84 | bwd_microstep: 271.23 | bwd_inner_microstep: 271.21 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 00:22:30,208] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.12 | bwd_microstep: 271.20 | bwd_inner_microstep: 271.18 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 389 +[2025-05-02 00:22:30,564] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.21 | optimizer_step: 17.15 +[2025-05-02 00:22:30,564] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.25 | bwd_microstep: 218.29 | bwd_inner_microstep: 141.17 | bwd_allreduce_microstep: 76.95 | step_microstep: 25.10 +[2025-05-02 00:22:30,566] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2836.81 | bwd: 4177.79 | bwd_inner: 4100.21 | bwd_allreduce: 77.13 | step: 26.17 + 9%|▉ | 792/8720 [2:07:04<15:51:56, 7.20s/it] {'loss': 0.9585, 'grad_norm': 5.0358123779296875, 'learning_rate': 9.903427577505367e-06, 'epoch': 0.91} + 9%|▉ | 792/8720 [2:07:04<15:51:56, 7.20s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 388 +[2025-05-02 00:22:30,785] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 82.45 | bwd_microstep: 115.15 | bwd_inner_microstep: 115.00 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1886 +[2025-05-02 00:22:31,267] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.42 | bwd_microstep: 274.55 | bwd_inner_microstep: 274.53 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1883 +[2025-05-02 00:22:31,748] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.42 | bwd_microstep: 274.33 | bwd_inner_microstep: 274.31 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 00:22:32,227] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.00 | bwd_microstep: 272.62 | bwd_inner_microstep: 272.60 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 00:22:32,709] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.09 | bwd_microstep: 273.37 | bwd_inner_microstep: 273.35 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-02 00:22:33,191] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.65 | bwd_microstep: 273.16 | bwd_inner_microstep: 273.14 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 00:22:33,672] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.21 | bwd_microstep: 272.50 | bwd_inner_microstep: 272.48 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 00:22:34,152] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.08 | bwd_microstep: 272.58 | bwd_inner_microstep: 272.57 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 00:22:34,633] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.31 | bwd_microstep: 272.95 | bwd_inner_microstep: 272.93 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 832 +[2025-05-02 00:22:34,873] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.08 | bwd_microstep: 130.28 | bwd_inner_microstep: 129.97 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 00:22:35,351] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.63 | bwd_microstep: 272.30 | bwd_inner_microstep: 272.28 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 00:22:35,828] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.93 | bwd_microstep: 271.19 | bwd_inner_microstep: 271.18 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 00:22:36,306] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.13 | bwd_microstep: 271.19 | bwd_inner_microstep: 271.17 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 00:22:36,784] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.00 | bwd_microstep: 270.95 | bwd_inner_microstep: 270.93 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1903 +[2025-05-02 00:22:37,267] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.27 | bwd_microstep: 275.92 | bwd_inner_microstep: 275.90 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1367 +[2025-05-02 00:22:37,736] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.18 | optimizer_step: 17.14 +[2025-05-02 00:22:37,737] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.37 | bwd_microstep: 285.80 | bwd_inner_microstep: 207.84 | bwd_allreduce_microstep: 77.80 | step_microstep: 25.10 +[2025-05-02 00:22:37,738] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2768.69 | bwd: 4078.88 | bwd_inner: 4000.35 | bwd_allreduce: 78.02 | step: 26.14 + 9%|▉ | 793/8720 [2:07:11<15:50:33, 7.19s/it] {'loss': 1.2055, 'grad_norm': 7.7769293785095215, 'learning_rate': 9.903063992698559e-06, 'epoch': 0.91} + 9%|▉ | 793/8720 [2:07:11<15:50:33, 7.19s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2089 +[2025-05-02 00:22:38,271] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 204.03 | bwd_microstep: 305.07 | bwd_inner_microstep: 305.05 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 900 +[2025-05-02 00:22:38,530] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 100.08 | bwd_microstep: 143.99 | bwd_inner_microstep: 143.81 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1910 +[2025-05-02 00:22:39,011] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.55 | bwd_microstep: 276.27 | bwd_inner_microstep: 276.25 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1896 +[2025-05-02 00:22:39,492] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.87 | bwd_microstep: 274.97 | bwd_inner_microstep: 274.96 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1379 +[2025-05-02 00:22:39,861] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.40 | bwd_microstep: 208.37 | bwd_inner_microstep: 208.23 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 00:22:40,346] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.94 | bwd_microstep: 273.16 | bwd_inner_microstep: 273.15 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 00:22:40,828] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.44 | bwd_microstep: 272.66 | bwd_inner_microstep: 272.64 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 834 +[2025-05-02 00:22:41,068] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.87 | bwd_microstep: 125.88 | bwd_inner_microstep: 125.83 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 00:22:41,547] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.26 | bwd_microstep: 272.40 | bwd_inner_microstep: 272.38 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 834 +[2025-05-02 00:22:41,794] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 102.84 | bwd_microstep: 125.14 | bwd_inner_microstep: 125.03 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 00:22:42,277] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.88 | bwd_microstep: 272.73 | bwd_inner_microstep: 272.71 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 00:22:42,755] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.52 | bwd_microstep: 271.23 | bwd_inner_microstep: 271.21 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1342 +[2025-05-02 00:22:43,118] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.38 | bwd_microstep: 204.61 | bwd_inner_microstep: 204.47 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 00:22:43,595] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.20 | bwd_microstep: 271.36 | bwd_inner_microstep: 271.35 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 00:22:44,073] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.01 | bwd_microstep: 271.36 | bwd_inner_microstep: 271.34 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 00:22:44,652] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.26 | optimizer_step: 17.43 +[2025-05-02 00:22:44,652] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.72 | bwd_microstep: 349.45 | bwd_inner_microstep: 271.52 | bwd_allreduce_microstep: 77.87 | step_microstep: 25.57 +[2025-05-02 00:22:44,654] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2669.62 | bwd: 3918.79 | bwd_inner: 3840.00 | bwd_allreduce: 78.25 | step: 26.69 + 9%|▉ | 794/8720 [2:07:18<15:39:22, 7.11s/it] {'loss': 0.8403, 'grad_norm': 6.703042984008789, 'learning_rate': 9.902699731447607e-06, 'epoch': 0.91} + 9%|▉ | 794/8720 [2:07:18<15:39:22, 7.11s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1961 +[2025-05-02 00:22:45,163] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 196.72 | bwd_microstep: 289.53 | bwd_inner_microstep: 289.51 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1888 +[2025-05-02 00:22:45,644] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.00 | bwd_microstep: 274.78 | bwd_inner_microstep: 274.75 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 867 +[2025-05-02 00:22:45,891] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.22 | bwd_microstep: 135.10 | bwd_inner_microstep: 134.94 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-02 00:22:46,371] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.20 | bwd_microstep: 273.11 | bwd_inner_microstep: 273.09 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1100 +[2025-05-02 00:22:46,671] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 118.22 | bwd_microstep: 161.61 | bwd_inner_microstep: 161.39 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-02 00:22:47,157] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.09 | bwd_microstep: 273.70 | bwd_inner_microstep: 273.68 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1089 +[2025-05-02 00:22:47,454] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 115.54 | bwd_microstep: 160.47 | bwd_inner_microstep: 160.36 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 00:22:47,936] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.30 | bwd_microstep: 272.40 | bwd_inner_microstep: 272.39 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 832 +[2025-05-02 00:22:48,176] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.35 | bwd_microstep: 130.15 | bwd_inner_microstep: 129.88 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 00:22:48,656] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.45 | bwd_microstep: 272.29 | bwd_inner_microstep: 272.27 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 00:22:49,134] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.69 | bwd_microstep: 271.33 | bwd_inner_microstep: 271.31 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 00:22:49,613] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.46 | bwd_microstep: 271.27 | bwd_inner_microstep: 271.25 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 00:22:50,097] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.77 | bwd_microstep: 271.27 | bwd_inner_microstep: 271.25 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 00:22:50,578] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.49 | bwd_microstep: 271.17 | bwd_inner_microstep: 271.16 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1850 +[2025-05-02 00:22:51,056] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.92 | bwd_microstep: 271.04 | bwd_inner_microstep: 271.02 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2005 +[2025-05-02 00:22:51,674] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.07 | optimizer_gradients: 2.15 | optimizer_step: 17.09 +[2025-05-02 00:22:51,674] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 200.31 | bwd_microstep: 372.90 | bwd_inner_microstep: 295.60 | bwd_allreduce_microstep: 77.25 | step_microstep: 24.97 +[2025-05-02 00:22:51,676] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2706.32 | bwd: 3972.23 | bwd_inner: 3893.90 | bwd_allreduce: 77.73 | step: 26.19 + 9%|▉ | 795/8720 [2:07:25<15:35:42, 7.08s/it] {'loss': 0.8479, 'grad_norm': 5.464700698852539, 'learning_rate': 9.902334793802767e-06, 'epoch': 0.91} + 9%|▉ | 795/8720 [2:07:25<15:35:42, 7.08s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 428 +[2025-05-02 00:22:51,891] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 79.00 | bwd_microstep: 115.53 | bwd_inner_microstep: 115.32 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1962 +[2025-05-02 00:22:52,395] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 196.14 | bwd_microstep: 290.63 | bwd_inner_microstep: 290.61 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1899 +[2025-05-02 00:22:52,877] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.46 | bwd_microstep: 275.52 | bwd_inner_microstep: 275.51 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-02 00:22:53,357] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.03 | bwd_microstep: 274.47 | bwd_inner_microstep: 274.45 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-02 00:22:53,837] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.99 | bwd_microstep: 273.65 | bwd_inner_microstep: 273.63 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 00:22:54,318] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.34 | bwd_microstep: 273.41 | bwd_inner_microstep: 273.39 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 833 +[2025-05-02 00:22:54,554] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.93 | bwd_microstep: 125.90 | bwd_inner_microstep: 125.72 | bwd_allreduce_microstep: 0.10 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 00:22:55,033] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.16 | bwd_microstep: 272.74 | bwd_inner_microstep: 272.72 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 00:22:55,512] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.70 | bwd_microstep: 272.55 | bwd_inner_microstep: 272.53 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 00:22:55,993] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.89 | bwd_microstep: 272.69 | bwd_inner_microstep: 272.67 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 00:22:56,473] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.84 | bwd_microstep: 272.84 | bwd_inner_microstep: 272.82 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 00:22:56,952] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.20 | bwd_microstep: 272.93 | bwd_inner_microstep: 272.92 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 00:22:57,429] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.17 | bwd_microstep: 271.45 | bwd_inner_microstep: 271.44 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.05 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1346 +[2025-05-02 00:22:57,794] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.47 | bwd_microstep: 205.70 | bwd_inner_microstep: 205.53 | bwd_allreduce_microstep: 0.08 | step_microstep: 0.18 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 320 +[2025-05-02 00:22:58,012] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 83.33 | bwd_microstep: 119.11 | bwd_inner_microstep: 118.94 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 00:22:58,590] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.13 | optimizer_step: 17.03 +[2025-05-02 00:22:58,590] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.10 | bwd_microstep: 348.05 | bwd_inner_microstep: 271.80 | bwd_allreduce_microstep: 76.20 | step_microstep: 24.63 +[2025-05-02 00:22:58,592] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2673.40 | bwd: 3937.28 | bwd_inner: 3860.11 | bwd_allreduce: 76.62 | step: 25.63 + 9%|▉ | 796/8720 [2:07:32<15:28:54, 7.03s/it] {'loss': 0.7786, 'grad_norm': 4.84187126159668, 'learning_rate': 9.90196917981439e-06, 'epoch': 0.91} + 9%|▉ | 796/8720 [2:07:32<15:28:54, 7.03s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2098 +[2025-05-02 00:22:59,122] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 202.43 | bwd_microstep: 304.78 | bwd_inner_microstep: 304.76 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1952 +[2025-05-02 00:22:59,623] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 196.00 | bwd_microstep: 289.78 | bwd_inner_microstep: 289.77 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1436 +[2025-05-02 00:22:59,998] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 145.80 | bwd_microstep: 214.60 | bwd_inner_microstep: 214.59 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 355 +[2025-05-02 00:23:00,208] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 76.85 | bwd_microstep: 120.68 | bwd_inner_microstep: 120.55 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1887 +[2025-05-02 00:23:00,686] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.43 | bwd_microstep: 274.57 | bwd_inner_microstep: 274.55 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1370 +[2025-05-02 00:23:01,050] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.10 | bwd_microstep: 207.50 | bwd_inner_microstep: 207.48 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-02 00:23:01,527] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.45 | bwd_microstep: 274.20 | bwd_inner_microstep: 274.18 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-02 00:23:02,005] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.79 | bwd_microstep: 273.46 | bwd_inner_microstep: 273.44 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 00:23:02,482] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.40 | bwd_microstep: 272.92 | bwd_inner_microstep: 272.90 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 00:23:02,958] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.76 | bwd_microstep: 272.93 | bwd_inner_microstep: 272.91 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 00:23:03,437] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.69 | bwd_microstep: 272.42 | bwd_inner_microstep: 272.41 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1345 +[2025-05-02 00:23:03,800] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.43 | bwd_microstep: 205.67 | bwd_inner_microstep: 205.56 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 833 +[2025-05-02 00:23:04,034] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 91.89 | bwd_microstep: 125.90 | bwd_inner_microstep: 125.69 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 00:23:04,509] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.55 | bwd_microstep: 271.53 | bwd_inner_microstep: 271.51 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 00:23:04,982] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.63 | bwd_microstep: 271.28 | bwd_inner_microstep: 271.26 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 00:23:05,546] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.10 | optimizer_step: 17.22 +[2025-05-02 00:23:05,547] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.63 | bwd_microstep: 337.32 | bwd_inner_microstep: 271.67 | bwd_allreduce_microstep: 65.61 | step_microstep: 24.18 +[2025-05-02 00:23:05,548] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2690.58 | bwd: 3989.59 | bwd_inner: 3923.26 | bwd_allreduce: 65.88 | step: 25.05 + 9%|▉ | 797/8720 [2:07:39<15:25:39, 7.01s/it] {'loss': 1.1152, 'grad_norm': 4.275616645812988, 'learning_rate': 9.901602889532912e-06, 'epoch': 0.91} + 9%|▉ | 797/8720 [2:07:39<15:25:39, 7.01s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1934 +[2025-05-02 00:23:06,051] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.96 | bwd_microstep: 287.62 | bwd_inner_microstep: 287.60 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-02 00:23:06,530] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.50 | bwd_microstep: 273.93 | bwd_inner_microstep: 273.91 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-02 00:23:07,007] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.51 | bwd_microstep: 274.24 | bwd_inner_microstep: 274.22 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 337 +[2025-05-02 00:23:07,205] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 66.61 | bwd_microstep: 117.61 | bwd_inner_microstep: 117.41 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 00:23:07,681] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.93 | bwd_microstep: 272.63 | bwd_inner_microstep: 272.61 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 00:23:08,159] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.95 | bwd_microstep: 272.46 | bwd_inner_microstep: 272.44 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1092 +[2025-05-02 00:23:08,456] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 119.25 | bwd_microstep: 160.95 | bwd_inner_microstep: 160.79 | bwd_allreduce_microstep: 0.08 | step_microstep: 0.11 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 841 +[2025-05-02 00:23:08,700] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.29 | bwd_microstep: 132.25 | bwd_inner_microstep: 132.13 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.10 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1093 +[2025-05-02 00:23:08,993] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 114.61 | bwd_microstep: 161.15 | bwd_inner_microstep: 161.01 | bwd_allreduce_microstep: 0.04 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 00:23:09,470] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.62 | bwd_microstep: 271.52 | bwd_inner_microstep: 271.50 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 00:23:09,950] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.24 | bwd_microstep: 272.72 | bwd_inner_microstep: 272.70 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 321 +[2025-05-02 00:23:10,146] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 66.11 | bwd_microstep: 116.68 | bwd_inner_microstep: 116.54 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 00:23:10,620] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.34 | bwd_microstep: 271.20 | bwd_inner_microstep: 271.18 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 00:23:11,094] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.14 | bwd_microstep: 271.25 | bwd_inner_microstep: 271.24 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 00:23:11,569] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.76 | bwd_microstep: 271.30 | bwd_inner_microstep: 271.28 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 866 +[2025-05-02 00:23:11,900] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.04 | optimizer_gradients: 2.12 | optimizer_step: 17.03 +[2025-05-02 00:23:11,901] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.79 | bwd_microstep: 200.25 | bwd_inner_microstep: 134.24 | bwd_allreduce_microstep: 65.86 | step_microstep: 23.92 +[2025-05-02 00:23:11,902] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2447.30 | bwd: 3627.88 | bwd_inner: 3560.94 | bwd_allreduce: 66.26 | step: 25.03 + 9%|▉ | 798/8720 [2:07:45<14:59:34, 6.81s/it] {'loss': 0.9732, 'grad_norm': 8.646736145019531, 'learning_rate': 9.901235923008874e-06, 'epoch': 0.92} + 9%|▉ | 798/8720 [2:07:45<14:59:34, 6.81s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1917 +[2025-05-02 00:23:12,387] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.49 | bwd_microstep: 275.87 | bwd_inner_microstep: 275.86 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1893 +[2025-05-02 00:23:12,867] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.31 | bwd_microstep: 275.13 | bwd_inner_microstep: 275.12 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 00:23:13,344] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.48 | bwd_microstep: 273.40 | bwd_inner_microstep: 273.39 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-02 00:23:13,822] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.53 | bwd_microstep: 273.30 | bwd_inner_microstep: 273.28 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 00:23:14,303] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.70 | bwd_microstep: 273.20 | bwd_inner_microstep: 273.18 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 00:23:14,787] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.12 | bwd_microstep: 273.61 | bwd_inner_microstep: 273.60 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 00:23:15,267] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.27 | bwd_microstep: 273.04 | bwd_inner_microstep: 273.03 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 00:23:15,746] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.77 | bwd_microstep: 273.09 | bwd_inner_microstep: 273.07 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 00:23:16,224] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.25 | bwd_microstep: 272.53 | bwd_inner_microstep: 272.51 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 836 +[2025-05-02 00:23:16,455] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 91.74 | bwd_microstep: 126.24 | bwd_inner_microstep: 126.06 | bwd_allreduce_microstep: 0.09 | step_microstep: 0.18 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 332 +[2025-05-02 00:23:16,662] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 75.36 | bwd_microstep: 118.50 | bwd_inner_microstep: 118.22 | bwd_allreduce_microstep: 0.15 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 00:23:17,138] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.52 | bwd_microstep: 272.26 | bwd_inner_microstep: 272.24 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 00:23:17,614] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.52 | bwd_microstep: 272.29 | bwd_inner_microstep: 272.27 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.13 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 00:23:18,092] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.86 | bwd_microstep: 270.96 | bwd_inner_microstep: 270.94 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 907 +[2025-05-02 00:23:18,354] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 101.45 | bwd_microstep: 144.48 | bwd_inner_microstep: 144.39 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 00:23:18,933] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.13 | optimizer_step: 17.10 +[2025-05-02 00:23:18,934] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.42 | bwd_microstep: 348.89 | bwd_inner_microstep: 273.12 | bwd_allreduce_microstep: 75.72 | step_microstep: 24.64 +[2025-05-02 00:23:18,935] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2720.47 | bwd: 4016.87 | bwd_inner: 3940.32 | bwd_allreduce: 76.09 | step: 25.67 + 9%|▉ | 799/8720 [2:07:52<15:08:14, 6.88s/it] {'loss': 0.8754, 'grad_norm': 3.61706805229187, 'learning_rate': 9.900868280292899e-06, 'epoch': 0.92} + 9%|▉ | 799/8720 [2:07:52<15:08:14, 6.88s/it]dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1214 +[2025-05-02 00:23:19,255] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 122.91 | bwd_microstep: 175.65 | bwd_inner_microstep: 175.48 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.10 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1413 +[2025-05-02 00:23:19,631] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 145.47 | bwd_microstep: 212.97 | bwd_inner_microstep: 212.89 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1905 +[2025-05-02 00:23:20,114] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.54 | bwd_microstep: 276.06 | bwd_inner_microstep: 276.04 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1890 +[2025-05-02 00:23:20,596] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.37 | bwd_microstep: 274.56 | bwd_inner_microstep: 274.54 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-02 00:23:21,075] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.22 | bwd_microstep: 273.48 | bwd_inner_microstep: 273.46 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1883 +[2025-05-02 00:23:21,555] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.13 | bwd_microstep: 274.25 | bwd_inner_microstep: 274.24 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 342 +[2025-05-02 00:23:21,758] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 71.20 | bwd_microstep: 118.96 | bwd_inner_microstep: 118.65 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-02 00:23:22,234] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.66 | bwd_microstep: 273.29 | bwd_inner_microstep: 273.27 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 00:23:22,710] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.49 | bwd_microstep: 272.47 | bwd_inner_microstep: 272.45 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 841 +[2025-05-02 00:23:22,951] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.53 | bwd_microstep: 131.95 | bwd_inner_microstep: 131.74 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 00:23:23,427] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.77 | bwd_microstep: 272.87 | bwd_inner_microstep: 272.86 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 00:23:23,905] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.02 | bwd_microstep: 272.94 | bwd_inner_microstep: 272.93 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 00:23:24,382] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.81 | bwd_microstep: 272.32 | bwd_inner_microstep: 272.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 00:23:24,858] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.02 | bwd_microstep: 271.37 | bwd_inner_microstep: 271.35 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 00:23:25,332] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.23 | bwd_microstep: 271.06 | bwd_inner_microstep: 271.04 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1911 +[2025-05-02 00:23:25,904] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.12 | optimizer_step: 17.04 +[2025-05-02 00:23:25,904] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.63 | bwd_microstep: 343.30 | bwd_inner_microstep: 277.12 | bwd_allreduce_microstep: 66.14 | step_microstep: 23.97 +[2025-05-02 00:23:25,905] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2699.72 | bwd: 3987.59 | bwd_inner: 3920.43 | bwd_allreduce: 66.53 | step: 24.83 + 9%|▉ | 800/8720 [2:07:59<15:11:38, 6.91s/it] {'loss': 0.891, 'grad_norm': 4.900758266448975, 'learning_rate': 9.90049996143571e-06, 'epoch': 0.92} + 9%|▉ | 800/8720 [2:07:59<15:11:38, 6.91s/it][INFO|trainer.py:3503] 2025-05-02 00:23:28,350 >> Saving model checkpoint to work_dirs/internvl_chat_v2_5/ak/checkpoint-800 +[INFO|configuration_utils.py:472] 2025-05-02 00:23:28,353 >> Configuration saved in work_dirs/internvl_chat_v2_5/ak/checkpoint-800/config.json +[INFO|configuration_utils.py:807] 2025-05-02 00:23:28,353 >> Configuration saved in work_dirs/internvl_chat_v2_5/ak/checkpoint-800/generation_config.json +[INFO|modeling_utils.py:2755] 2025-05-02 00:23:33,442 >> Model weights saved in work_dirs/internvl_chat_v2_5/ak/checkpoint-800/model.safetensors +[INFO|tokenization_utils_base.py:2702] 2025-05-02 00:23:33,443 >> tokenizer config file saved in work_dirs/internvl_chat_v2_5/ak/checkpoint-800/tokenizer_config.json +[INFO|tokenization_utils_base.py:2711] 2025-05-02 00:23:33,444 >> Special tokens file saved in work_dirs/internvl_chat_v2_5/ak/checkpoint-800/special_tokens_map.json +[INFO|tokenization_utils_base.py:2762] 2025-05-02 00:23:33,444 >> added tokens file saved in work_dirs/internvl_chat_v2_5/ak/checkpoint-800/added_tokens.json +[2025-05-02 00:23:33,586] [INFO] [logging.py:96:log_dist] [Rank 0] [Torch] Checkpoint global_step800 is about to be saved! +[2025-05-02 00:23:33,603] [INFO] [logging.py:96:log_dist] [Rank 0] Saving model checkpoint: work_dirs/internvl_chat_v2_5/ak/checkpoint-800/global_step800/mp_rank_00_model_states.pt +[2025-05-02 00:23:33,603] [INFO] [torch_checkpoint_engine.py:21:save] [Torch] Saving work_dirs/internvl_chat_v2_5/ak/checkpoint-800/global_step800/mp_rank_00_model_states.pt... +[2025-05-02 00:23:38,008] [INFO] [torch_checkpoint_engine.py:23:save] [Torch] Saved work_dirs/internvl_chat_v2_5/ak/checkpoint-800/global_step800/mp_rank_00_model_states.pt. +[2025-05-02 00:23:38,010] [INFO] [torch_checkpoint_engine.py:21:save] [Torch] Saving work_dirs/internvl_chat_v2_5/ak/checkpoint-800/global_step800/bf16_zero_pp_rank_0_mp_rank_00_optim_states.pt... +[2025-05-02 00:23:38,208] [INFO] [torch_checkpoint_engine.py:23:save] [Torch] Saved work_dirs/internvl_chat_v2_5/ak/checkpoint-800/global_step800/bf16_zero_pp_rank_0_mp_rank_00_optim_states.pt. +[2025-05-02 00:23:38,208] [INFO] [engine.py:3536:_save_zero_checkpoint] zero checkpoint saved work_dirs/internvl_chat_v2_5/ak/checkpoint-800/global_step800/bf16_zero_pp_rank_0_mp_rank_00_optim_states.pt +[2025-05-02 00:23:38,208] [INFO] [torch_checkpoint_engine.py:33:commit] [Torch] Checkpoint global_step800 is ready now! +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1890 +[2025-05-02 00:23:38,701] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.42 | bwd_microstep: 271.89 | bwd_inner_microstep: 271.87 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 00:23:39,175] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.68 | bwd_microstep: 270.32 | bwd_inner_microstep: 270.31 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 00:23:39,647] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.02 | bwd_microstep: 270.23 | bwd_inner_microstep: 270.21 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 00:23:40,119] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.43 | bwd_microstep: 270.41 | bwd_inner_microstep: 270.39 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 00:23:40,590] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.20 | bwd_microstep: 270.44 | bwd_inner_microstep: 270.42 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 00:23:41,065] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.41 | bwd_microstep: 270.89 | bwd_inner_microstep: 270.87 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.40 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 00:23:41,538] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.96 | bwd_microstep: 270.47 | bwd_inner_microstep: 270.46 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 323 +[2025-05-02 00:23:41,757] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 80.57 | bwd_microstep: 121.23 | bwd_inner_microstep: 120.90 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 00:23:42,231] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.70 | bwd_microstep: 270.60 | bwd_inner_microstep: 270.58 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 00:23:42,709] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.03 | bwd_microstep: 271.32 | bwd_inner_microstep: 271.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 830 +[2025-05-02 00:23:42,952] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 97.24 | bwd_microstep: 129.05 | bwd_inner_microstep: 129.01 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 00:23:43,427] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.43 | bwd_microstep: 270.19 | bwd_inner_microstep: 270.18 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 318 +[2025-05-02 00:23:43,664] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 91.78 | bwd_microstep: 127.78 | bwd_inner_microstep: 127.46 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 00:23:44,139] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.82 | bwd_microstep: 270.72 | bwd_inner_microstep: 270.63 | bwd_allreduce_microstep: 0.04 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 00:23:44,615] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.54 | bwd_microstep: 270.05 | bwd_inner_microstep: 270.03 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1850 +[2025-05-02 00:23:45,216] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.08 | optimizer_gradients: 2.85 | optimizer_step: 31.48 +[2025-05-02 00:23:45,217] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.49 | bwd_microstep: 352.82 | bwd_inner_microstep: 270.46 | bwd_allreduce_microstep: 82.31 | step_microstep: 40.35 +[2025-05-02 00:23:45,218] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2699.38 | bwd: 3978.50 | bwd_inner: 3895.20 | bwd_allreduce: 82.70 | step: 42.00 + 9%|▉ | 801/8720 [2:08:18<23:22:51, 10.63s/it] {'loss': 0.6407, 'grad_norm': 6.392548561096191, 'learning_rate': 9.900130966488122e-06, 'epoch': 0.92} + 9%|▉ | 801/8720 [2:08:18<23:22:51, 10.63s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1901 +[2025-05-02 00:23:45,706] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.77 | bwd_microstep: 273.99 | bwd_inner_microstep: 273.98 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1883 +[2025-05-02 00:23:46,185] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.82 | bwd_microstep: 273.47 | bwd_inner_microstep: 273.46 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-02 00:23:46,664] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.47 | bwd_microstep: 272.96 | bwd_inner_microstep: 272.94 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 838 +[2025-05-02 00:23:46,907] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.85 | bwd_microstep: 128.65 | bwd_inner_microstep: 128.40 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.20 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 333 +[2025-05-02 00:23:47,126] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 83.60 | bwd_microstep: 119.08 | bwd_inner_microstep: 118.94 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 00:23:47,603] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.42 | bwd_microstep: 271.86 | bwd_inner_microstep: 271.85 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 331 +[2025-05-02 00:23:47,829] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 83.11 | bwd_microstep: 126.17 | bwd_inner_microstep: 125.85 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 00:23:48,305] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.06 | bwd_microstep: 271.59 | bwd_inner_microstep: 271.58 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 00:23:48,786] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.90 | bwd_microstep: 272.45 | bwd_inner_microstep: 272.44 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 328 +[2025-05-02 00:23:49,000] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 82.32 | bwd_microstep: 115.70 | bwd_inner_microstep: 115.42 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 333 +[2025-05-02 00:23:49,217] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 76.15 | bwd_microstep: 125.49 | bwd_inner_microstep: 125.36 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 00:23:49,692] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.54 | bwd_microstep: 272.10 | bwd_inner_microstep: 272.08 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 00:23:50,167] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.56 | bwd_microstep: 271.92 | bwd_inner_microstep: 271.90 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 00:23:50,641] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.20 | bwd_microstep: 271.52 | bwd_inner_microstep: 271.51 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 00:23:51,115] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.66 | bwd_microstep: 270.43 | bwd_inner_microstep: 270.41 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 00:23:51,677] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.12 | optimizer_step: 16.92 +[2025-05-02 00:23:51,678] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.59 | bwd_microstep: 337.35 | bwd_inner_microstep: 270.69 | bwd_allreduce_microstep: 66.61 | step_microstep: 24.24 +[2025-05-02 00:23:51,679] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2484.71 | bwd: 3674.86 | bwd_inner: 3606.96 | bwd_allreduce: 67.14 | step: 25.58 + 9%|▉ | 802/8720 [2:08:25<20:37:34, 9.38s/it] {'loss': 1.0594, 'grad_norm': 4.716929912567139, 'learning_rate': 9.899761295501043e-06, 'epoch': 0.92} + 9%|▉ | 802/8720 [2:08:25<20:37:34, 9.38s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1905 +[2025-05-02 00:23:52,164] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.36 | bwd_microstep: 274.61 | bwd_inner_microstep: 274.59 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1890 +[2025-05-02 00:23:52,642] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.84 | bwd_microstep: 273.98 | bwd_inner_microstep: 273.96 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 873 +[2025-05-02 00:23:52,888] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 98.06 | bwd_microstep: 133.76 | bwd_inner_microstep: 133.74 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 00:23:53,362] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.32 | bwd_microstep: 272.29 | bwd_inner_microstep: 272.27 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 841 +[2025-05-02 00:23:53,601] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.75 | bwd_microstep: 131.32 | bwd_inner_microstep: 131.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 00:23:54,076] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.23 | bwd_microstep: 272.53 | bwd_inner_microstep: 272.51 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 326 +[2025-05-02 00:23:54,273] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 67.42 | bwd_microstep: 115.82 | bwd_inner_microstep: 115.70 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1347 +[2025-05-02 00:23:54,632] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 139.40 | bwd_microstep: 204.89 | bwd_inner_microstep: 204.87 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 00:23:55,105] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.59 | bwd_microstep: 271.29 | bwd_inner_microstep: 271.28 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 00:23:55,578] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.26 | bwd_microstep: 271.63 | bwd_inner_microstep: 271.62 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 00:23:56,053] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.92 | bwd_microstep: 271.37 | bwd_inner_microstep: 271.35 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 00:23:56,526] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.06 | bwd_microstep: 271.38 | bwd_inner_microstep: 271.37 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 00:23:57,001] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.36 | bwd_microstep: 272.12 | bwd_inner_microstep: 272.10 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 00:23:57,474] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.55 | bwd_microstep: 270.26 | bwd_inner_microstep: 270.24 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 00:23:57,947] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.99 | bwd_microstep: 271.21 | bwd_inner_microstep: 271.19 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1889 +[2025-05-02 00:23:58,512] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.04 | optimizer_gradients: 2.12 | optimizer_step: 16.68 +[2025-05-02 00:23:58,513] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.51 | bwd_microstep: 339.59 | bwd_inner_microstep: 274.17 | bwd_allreduce_microstep: 65.37 | step_microstep: 23.64 +[2025-05-02 00:23:58,514] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2650.38 | bwd: 3918.09 | bwd_inner: 3852.29 | bwd_allreduce: 65.50 | step: 24.32 + 9%|▉ | 803/8720 [2:08:32<18:56:44, 8.61s/it] {'loss': 0.9874, 'grad_norm': 5.488677978515625, 'learning_rate': 9.899390948525473e-06, 'epoch': 0.92} + 9%|▉ | 803/8720 [2:08:32<18:56:44, 8.61s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1911 +[2025-05-02 00:23:58,999] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.04 | bwd_microstep: 275.24 | bwd_inner_microstep: 275.22 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1896 +[2025-05-02 00:23:59,479] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.74 | bwd_microstep: 274.51 | bwd_inner_microstep: 274.49 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 867 +[2025-05-02 00:23:59,722] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.72 | bwd_microstep: 133.97 | bwd_inner_microstep: 133.95 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 874 +[2025-05-02 00:23:59,967] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 96.67 | bwd_microstep: 134.37 | bwd_inner_microstep: 134.35 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-02 00:24:00,442] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.65 | bwd_microstep: 272.53 | bwd_inner_microstep: 272.52 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-02 00:24:00,919] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.49 | bwd_microstep: 273.10 | bwd_inner_microstep: 273.09 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-02 00:24:01,397] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.94 | bwd_microstep: 273.63 | bwd_inner_microstep: 273.61 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-02 00:24:01,875] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.99 | bwd_microstep: 273.70 | bwd_inner_microstep: 273.69 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1354 +[2025-05-02 00:24:02,237] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.42 | bwd_microstep: 205.37 | bwd_inner_microstep: 205.36 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 00:24:02,711] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.71 | bwd_microstep: 271.68 | bwd_inner_microstep: 271.66 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 00:24:03,185] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.01 | bwd_microstep: 271.20 | bwd_inner_microstep: 271.18 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 00:24:03,658] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.48 | bwd_microstep: 271.54 | bwd_inner_microstep: 271.52 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 00:24:04,132] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.27 | bwd_microstep: 271.15 | bwd_inner_microstep: 271.13 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 00:24:04,604] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.69 | bwd_microstep: 269.91 | bwd_inner_microstep: 269.89 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1850 +[2025-05-02 00:24:05,075] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.50 | bwd_microstep: 269.60 | bwd_inner_microstep: 269.58 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2089 +[2025-05-02 00:24:05,693] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.21 | optimizer_step: 23.09 +[2025-05-02 00:24:05,693] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 201.77 | bwd_microstep: 371.38 | bwd_inner_microstep: 304.43 | bwd_allreduce_microstep: 66.90 | step_microstep: 30.54 +[2025-05-02 00:24:05,694] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2789.86 | bwd: 4112.89 | bwd_inner: 4045.67 | bwd_allreduce: 66.98 | step: 31.20 + 9%|▉ | 804/8720 [2:08:39<17:59:49, 8.18s/it] {'loss': 1.102, 'grad_norm': 6.166934013366699, 'learning_rate': 9.899019925612507e-06, 'epoch': 0.92} + 9%|▉ | 804/8720 [2:08:39<17:59:49, 8.18s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2067 +[2025-05-02 00:24:06,219] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 202.87 | bwd_microstep: 301.20 | bwd_inner_microstep: 301.18 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1988 +[2025-05-02 00:24:06,723] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 196.48 | bwd_microstep: 292.47 | bwd_inner_microstep: 292.45 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1912 +[2025-05-02 00:24:07,202] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.69 | bwd_microstep: 275.46 | bwd_inner_microstep: 275.44 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-02 00:24:07,678] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.84 | bwd_microstep: 273.23 | bwd_inner_microstep: 273.21 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 00:24:08,154] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.07 | bwd_microstep: 272.41 | bwd_inner_microstep: 272.39 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 326 +[2025-05-02 00:24:08,352] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 67.42 | bwd_microstep: 117.20 | bwd_inner_microstep: 117.07 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 00:24:08,827] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.81 | bwd_microstep: 272.15 | bwd_inner_microstep: 272.13 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 00:24:09,306] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.30 | bwd_microstep: 272.34 | bwd_inner_microstep: 272.32 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 00:24:09,789] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.43 | bwd_microstep: 272.62 | bwd_inner_microstep: 272.60 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 00:24:10,268] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.54 | bwd_microstep: 271.95 | bwd_inner_microstep: 271.94 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 00:24:10,751] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.97 | bwd_microstep: 272.67 | bwd_inner_microstep: 272.66 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 00:24:11,230] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.88 | bwd_microstep: 272.28 | bwd_inner_microstep: 272.26 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 00:24:11,711] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.29 | bwd_microstep: 272.11 | bwd_inner_microstep: 272.09 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.15 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 00:24:12,193] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.97 | bwd_microstep: 271.97 | bwd_inner_microstep: 271.95 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 00:24:12,671] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.94 | bwd_microstep: 270.86 | bwd_inner_microstep: 270.84 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 00:24:13,268] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.09 | optimizer_step: 24.29 +[2025-05-02 00:24:13,269] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.44 | bwd_microstep: 358.20 | bwd_inner_microstep: 271.44 | bwd_allreduce_microstep: 86.71 | step_microstep: 31.96 +[2025-05-02 00:24:13,270] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2917.61 | bwd: 4339.14 | bwd_inner: 4252.01 | bwd_allreduce: 86.84 | step: 32.86 + 9%|▉ | 805/8720 [2:08:47<17:35:38, 8.00s/it] {'loss': 0.9082, 'grad_norm': 6.132362365722656, 'learning_rate': 9.898648226813333e-06, 'epoch': 0.92} + 9%|▉ | 805/8720 [2:08:47<17:35:38, 8.00s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1919 +[2025-05-02 00:24:13,761] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 192.09 | bwd_microstep: 275.97 | bwd_inner_microstep: 275.95 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 362 +[2025-05-02 00:24:13,980] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 81.31 | bwd_microstep: 121.48 | bwd_inner_microstep: 121.23 | bwd_allreduce_microstep: 0.09 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-02 00:24:14,458] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.11 | bwd_microstep: 273.06 | bwd_inner_microstep: 273.04 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 337 +[2025-05-02 00:24:14,675] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 80.63 | bwd_microstep: 119.95 | bwd_inner_microstep: 119.73 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 00:24:15,153] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.79 | bwd_microstep: 272.58 | bwd_inner_microstep: 272.56 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 00:24:15,634] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.86 | bwd_microstep: 272.27 | bwd_inner_microstep: 272.25 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-02 00:24:16,118] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.35 | bwd_microstep: 272.41 | bwd_inner_microstep: 272.39 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 00:24:16,600] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.33 | bwd_microstep: 272.54 | bwd_inner_microstep: 272.53 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 00:24:17,082] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.57 | bwd_microstep: 272.74 | bwd_inner_microstep: 272.73 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 328 +[2025-05-02 00:24:17,314] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 90.45 | bwd_microstep: 123.16 | bwd_inner_microstep: 123.00 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 00:24:17,792] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.60 | bwd_microstep: 272.40 | bwd_inner_microstep: 272.39 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 00:24:18,270] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.55 | bwd_microstep: 271.26 | bwd_inner_microstep: 271.24 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 00:24:18,748] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.92 | bwd_microstep: 271.53 | bwd_inner_microstep: 271.51 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 00:24:19,228] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.31 | bwd_microstep: 271.26 | bwd_inner_microstep: 271.24 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 00:24:19,705] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.70 | bwd_microstep: 271.49 | bwd_inner_microstep: 271.47 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 00:24:20,290] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.07 | optimizer_gradients: 2.09 | optimizer_step: 16.70 +[2025-05-02 00:24:20,291] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.02 | bwd_microstep: 353.20 | bwd_inner_microstep: 271.77 | bwd_allreduce_microstep: 81.38 | step_microstep: 24.46 +[2025-05-02 00:24:20,292] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2708.22 | bwd: 3987.36 | bwd_inner: 3905.22 | bwd_allreduce: 81.65 | step: 25.40 + 9%|▉ | 806/8720 [2:08:54<16:56:43, 7.71s/it] {'loss': 1.2124, 'grad_norm': 9.28641414642334, 'learning_rate': 9.898275852179231e-06, 'epoch': 0.92} + 9%|▉ | 806/8720 [2:08:54<16:56:43, 7.71s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1886 +[2025-05-02 00:24:20,778] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.90 | bwd_microstep: 273.80 | bwd_inner_microstep: 273.78 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1360 +[2025-05-02 00:24:21,143] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.75 | bwd_microstep: 205.87 | bwd_inner_microstep: 205.85 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 00:24:21,621] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.14 | bwd_microstep: 272.40 | bwd_inner_microstep: 272.38 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 00:24:22,100] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.90 | bwd_microstep: 272.33 | bwd_inner_microstep: 272.31 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 844 +[2025-05-02 00:24:22,341] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.03 | bwd_microstep: 132.02 | bwd_inner_microstep: 131.82 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 00:24:22,815] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.26 | bwd_microstep: 272.06 | bwd_inner_microstep: 272.04 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1351 +[2025-05-02 00:24:23,176] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.80 | bwd_microstep: 205.79 | bwd_inner_microstep: 205.65 | bwd_allreduce_microstep: 0.03 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 00:24:23,650] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.57 | bwd_microstep: 272.13 | bwd_inner_microstep: 272.12 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 00:24:24,126] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.50 | bwd_microstep: 272.17 | bwd_inner_microstep: 272.15 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 00:24:24,600] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.70 | bwd_microstep: 270.72 | bwd_inner_microstep: 270.71 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 00:24:25,073] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.25 | bwd_microstep: 270.64 | bwd_inner_microstep: 270.62 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 00:24:25,546] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.64 | bwd_microstep: 270.84 | bwd_inner_microstep: 270.83 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 00:24:26,019] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.62 | bwd_microstep: 270.66 | bwd_inner_microstep: 270.65 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 00:24:26,492] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.05 | bwd_microstep: 270.66 | bwd_inner_microstep: 270.65 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2103 +[2025-05-02 00:24:27,020] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 202.96 | bwd_microstep: 310.46 | bwd_inner_microstep: 310.45 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1914 +[2025-05-02 00:24:27,594] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.04 | optimizer_gradients: 2.07 | optimizer_step: 16.66 +[2025-05-02 00:24:27,594] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 191.39 | bwd_microstep: 342.82 | bwd_inner_microstep: 276.67 | bwd_allreduce_microstep: 66.12 | step_microstep: 23.64 +[2025-05-02 00:24:27,595] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2834.19 | bwd: 4185.41 | bwd_inner: 4118.75 | bwd_allreduce: 66.31 | step: 24.48 + 9%|▉ | 807/8720 [2:09:01<16:40:29, 7.59s/it] {'loss': 1.1507, 'grad_norm': 6.643326759338379, 'learning_rate': 9.897902801761577e-06, 'epoch': 0.93} + 9%|▉ | 807/8720 [2:09:01<16:40:29, 7.59s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1931 +[2025-05-02 00:24:28,097] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 194.91 | bwd_microstep: 287.26 | bwd_inner_microstep: 287.24 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1919 +[2025-05-02 00:24:28,579] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.44 | bwd_microstep: 276.61 | bwd_inner_microstep: 276.59 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 00:24:29,056] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.56 | bwd_microstep: 273.12 | bwd_inner_microstep: 273.11 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 00:24:29,531] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.49 | bwd_microstep: 272.53 | bwd_inner_microstep: 272.51 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 00:24:30,008] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.61 | bwd_microstep: 272.80 | bwd_inner_microstep: 272.79 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 00:24:30,484] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.98 | bwd_microstep: 272.79 | bwd_inner_microstep: 272.77 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 00:24:30,960] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.18 | bwd_microstep: 272.62 | bwd_inner_microstep: 272.60 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 00:24:31,436] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.11 | bwd_microstep: 272.96 | bwd_inner_microstep: 272.95 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 00:24:31,912] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.14 | bwd_microstep: 272.53 | bwd_inner_microstep: 272.51 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 00:24:32,389] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.31 | bwd_microstep: 272.25 | bwd_inner_microstep: 272.23 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 00:24:32,865] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.82 | bwd_microstep: 272.91 | bwd_inner_microstep: 272.89 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 00:24:33,342] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.49 | bwd_microstep: 271.26 | bwd_inner_microstep: 271.24 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.16 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 00:24:33,817] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.79 | bwd_microstep: 271.08 | bwd_inner_microstep: 271.07 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 830 +[2025-05-02 00:24:34,056] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.52 | bwd_microstep: 129.86 | bwd_inner_microstep: 129.84 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 318 +[2025-05-02 00:24:34,278] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 82.01 | bwd_microstep: 124.21 | bwd_inner_microstep: 124.06 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 00:24:34,863] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.05 | optimizer_step: 19.82 +[2025-05-02 00:24:34,863] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.75 | bwd_microstep: 351.78 | bwd_inner_microstep: 271.36 | bwd_allreduce_microstep: 80.37 | step_microstep: 27.65 +[2025-05-02 00:24:34,865] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2818.80 | bwd: 4166.62 | bwd_inner: 4085.79 | bwd_allreduce: 80.51 | step: 28.58 + 9%|▉ | 808/8720 [2:09:08<16:27:54, 7.49s/it] {'loss': 0.947, 'grad_norm': 7.234145641326904, 'learning_rate': 9.897529075611835e-06, 'epoch': 0.93} + 9%|▉ | 808/8720 [2:09:08<16:27:54, 7.49s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1896 +[2025-05-02 00:24:35,351] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.15 | bwd_microstep: 274.25 | bwd_inner_microstep: 274.23 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1896 +[2025-05-02 00:24:35,833] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.76 | bwd_microstep: 275.35 | bwd_inner_microstep: 275.34 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1901 +[2025-05-02 00:24:36,317] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.36 | bwd_microstep: 276.07 | bwd_inner_microstep: 276.05 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1890 +[2025-05-02 00:24:36,798] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.25 | bwd_microstep: 274.62 | bwd_inner_microstep: 274.61 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.07 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-02 00:24:37,279] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.09 | bwd_microstep: 274.60 | bwd_inner_microstep: 274.59 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 837 +[2025-05-02 00:24:37,517] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 96.03 | bwd_microstep: 126.13 | bwd_inner_microstep: 126.11 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 00:24:37,995] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.26 | bwd_microstep: 272.88 | bwd_inner_microstep: 272.86 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 00:24:38,470] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.83 | bwd_microstep: 272.31 | bwd_inner_microstep: 272.29 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 00:24:38,947] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.68 | bwd_microstep: 273.64 | bwd_inner_microstep: 273.62 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 00:24:39,425] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.02 | bwd_microstep: 272.86 | bwd_inner_microstep: 272.85 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 00:24:39,902] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.63 | bwd_microstep: 272.33 | bwd_inner_microstep: 272.32 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 00:24:40,378] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.74 | bwd_microstep: 272.43 | bwd_inner_microstep: 272.42 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 00:24:40,853] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.78 | bwd_microstep: 271.76 | bwd_inner_microstep: 271.74 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 321 +[2025-05-02 00:24:41,067] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 79.49 | bwd_microstep: 120.48 | bwd_inner_microstep: 120.24 | bwd_allreduce_microstep: 0.09 | step_microstep: 0.09 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 830 +[2025-05-02 00:24:41,304] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 92.93 | bwd_microstep: 130.55 | bwd_inner_microstep: 130.43 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 00:24:41,874] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.04 | optimizer_step: 19.78 +[2025-05-02 00:24:41,874] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.14 | bwd_microstep: 340.23 | bwd_inner_microstep: 271.64 | bwd_allreduce_microstep: 68.55 | step_microstep: 26.80 +[2025-05-02 00:24:41,875] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2721.85 | bwd: 4000.55 | bwd_inner: 3931.41 | bwd_allreduce: 68.75 | step: 27.75 + 9%|▉ | 809/8720 [2:09:15<16:08:41, 7.35s/it] {'loss': 0.8904, 'grad_norm': 6.472304821014404, 'learning_rate': 9.897154673781568e-06, 'epoch': 0.93} + 9%|▉ | 809/8720 [2:09:15<16:08:41, 7.35s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2341 +[2025-05-02 00:24:42,452] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 218.01 | bwd_microstep: 338.16 | bwd_inner_microstep: 338.14 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1384 +[2025-05-02 00:24:42,817] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.31 | bwd_microstep: 208.72 | bwd_inner_microstep: 208.71 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1883 +[2025-05-02 00:24:43,295] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.48 | bwd_microstep: 274.60 | bwd_inner_microstep: 274.59 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.11 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1368 +[2025-05-02 00:24:43,660] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 142.84 | bwd_microstep: 207.20 | bwd_inner_microstep: 207.05 | bwd_allreduce_microstep: 0.10 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-02 00:24:44,137] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.42 | bwd_microstep: 273.22 | bwd_inner_microstep: 273.20 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 00:24:44,613] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.22 | bwd_microstep: 273.14 | bwd_inner_microstep: 273.12 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 00:24:45,091] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.36 | bwd_microstep: 272.76 | bwd_inner_microstep: 272.74 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 00:24:45,569] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.90 | bwd_microstep: 273.05 | bwd_inner_microstep: 273.03 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 00:24:46,045] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.31 | bwd_microstep: 273.03 | bwd_inner_microstep: 273.01 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 00:24:46,520] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.80 | bwd_microstep: 271.64 | bwd_inner_microstep: 271.62 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 00:24:46,997] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.08 | bwd_microstep: 272.30 | bwd_inner_microstep: 272.28 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 00:24:47,472] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.55 | bwd_microstep: 271.81 | bwd_inner_microstep: 271.79 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 00:24:47,945] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.33 | bwd_microstep: 270.87 | bwd_inner_microstep: 270.86 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 00:24:48,419] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.28 | bwd_microstep: 271.37 | bwd_inner_microstep: 271.35 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 00:24:48,895] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.63 | bwd_microstep: 271.25 | bwd_inner_microstep: 271.23 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 00:24:49,458] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.06 | optimizer_step: 16.64 +[2025-05-02 00:24:49,458] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.84 | bwd_microstep: 337.53 | bwd_inner_microstep: 271.44 | bwd_allreduce_microstep: 66.05 | step_microstep: 23.66 +[2025-05-02 00:24:49,459] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2950.12 | bwd: 4360.68 | bwd_inner: 4294.17 | bwd_allreduce: 66.20 | step: 24.57 + 9%|▉ | 810/8720 [2:09:23<16:17:56, 7.42s/it] {'loss': 0.7328, 'grad_norm': 5.75784158706665, 'learning_rate': 9.89677959632243e-06, 'epoch': 0.93} + 9%|▉ | 810/8720 [2:09:23<16:17:56, 7.42s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 448 +[2025-05-02 00:24:49,668] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 71.27 | bwd_microstep: 118.84 | bwd_inner_microstep: 118.65 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1927 +[2025-05-02 00:24:50,165] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 194.53 | bwd_microstep: 287.56 | bwd_inner_microstep: 287.54 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-02 00:24:50,646] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.11 | bwd_microstep: 273.89 | bwd_inner_microstep: 273.87 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-02 00:24:51,125] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.04 | bwd_microstep: 273.08 | bwd_inner_microstep: 273.06 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 00:24:51,605] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.01 | bwd_microstep: 273.24 | bwd_inner_microstep: 273.22 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 332 +[2025-05-02 00:24:51,819] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 81.39 | bwd_microstep: 117.64 | bwd_inner_microstep: 117.32 | bwd_allreduce_microstep: 0.14 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 00:24:52,300] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.00 | bwd_microstep: 273.40 | bwd_inner_microstep: 273.38 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 00:24:52,781] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.32 | bwd_microstep: 272.40 | bwd_inner_microstep: 272.38 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 00:24:53,262] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.60 | bwd_microstep: 272.78 | bwd_inner_microstep: 272.76 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 00:24:53,745] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.03 | bwd_microstep: 272.59 | bwd_inner_microstep: 272.57 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 00:24:54,226] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.52 | bwd_microstep: 272.83 | bwd_inner_microstep: 272.81 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 323 +[2025-05-02 00:24:54,457] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 88.65 | bwd_microstep: 124.83 | bwd_inner_microstep: 124.49 | bwd_allreduce_microstep: 0.15 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 00:24:54,934] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.11 | bwd_microstep: 271.16 | bwd_inner_microstep: 271.14 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 00:24:55,411] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.37 | bwd_microstep: 271.37 | bwd_inner_microstep: 271.35 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 00:24:55,889] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.26 | bwd_microstep: 271.33 | bwd_inner_microstep: 271.31 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 00:24:56,471] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.05 | optimizer_step: 24.11 +[2025-05-02 00:24:56,472] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.78 | bwd_microstep: 346.31 | bwd_inner_microstep: 271.52 | bwd_allreduce_microstep: 74.74 | step_microstep: 31.21 +[2025-05-02 00:24:56,473] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2700.65 | bwd: 3993.31 | bwd_inner: 3917.58 | bwd_allreduce: 75.16 | step: 32.31 + 9%|▉ | 811/8720 [2:09:30<16:01:48, 7.30s/it] {'loss': 0.9653, 'grad_norm': 4.395528793334961, 'learning_rate': 9.896403843286169e-06, 'epoch': 0.93} + 9%|▉ | 811/8720 [2:09:30<16:01:48, 7.30s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-02 00:24:56,956] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.19 | bwd_microstep: 273.86 | bwd_inner_microstep: 273.84 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-02 00:24:57,433] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.84 | bwd_microstep: 273.55 | bwd_inner_microstep: 273.54 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-02 00:24:57,911] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.31 | bwd_microstep: 273.47 | bwd_inner_microstep: 273.45 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 00:24:58,387] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.45 | bwd_microstep: 273.18 | bwd_inner_microstep: 273.16 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 00:24:58,864] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.99 | bwd_microstep: 273.26 | bwd_inner_microstep: 273.24 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 00:24:59,343] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.70 | bwd_microstep: 272.65 | bwd_inner_microstep: 272.63 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 00:24:59,821] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.76 | bwd_microstep: 272.39 | bwd_inner_microstep: 272.37 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 00:25:00,302] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.92 | bwd_microstep: 272.70 | bwd_inner_microstep: 272.68 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 00:25:00,781] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.38 | bwd_microstep: 272.52 | bwd_inner_microstep: 272.50 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 00:25:01,260] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.85 | bwd_microstep: 272.61 | bwd_inner_microstep: 272.59 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 321 +[2025-05-02 00:25:01,482] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 84.46 | bwd_microstep: 121.06 | bwd_inner_microstep: 120.76 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 00:25:01,959] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.66 | bwd_microstep: 272.29 | bwd_inner_microstep: 272.28 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 00:25:02,437] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.46 | bwd_microstep: 271.53 | bwd_inner_microstep: 271.51 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 00:25:02,917] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.95 | bwd_microstep: 272.46 | bwd_inner_microstep: 272.44 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.20 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 831 +[2025-05-02 00:25:03,160] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.14 | bwd_microstep: 130.45 | bwd_inner_microstep: 130.38 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 00:25:03,739] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.13 | optimizer_step: 16.84 +[2025-05-02 00:25:03,739] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.00 | bwd_microstep: 349.35 | bwd_inner_microstep: 272.12 | bwd_allreduce_microstep: 77.13 | step_microstep: 24.70 +[2025-05-02 00:25:03,741] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2817.74 | bwd: 4147.37 | bwd_inner: 4069.59 | bwd_allreduce: 77.35 | step: 25.78 + 9%|▉ | 812/8720 [2:09:37<16:00:38, 7.29s/it] {'loss': 0.7684, 'grad_norm': 6.172597408294678, 'learning_rate': 9.896027414724621e-06, 'epoch': 0.93} + 9%|▉ | 812/8720 [2:09:37<16:00:38, 7.29s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1892 +[2025-05-02 00:25:04,227] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.81 | bwd_microstep: 274.50 | bwd_inner_microstep: 274.48 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1891 +[2025-05-02 00:25:04,707] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.82 | bwd_microstep: 275.15 | bwd_inner_microstep: 275.13 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 353 +[2025-05-02 00:25:04,916] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 74.56 | bwd_microstep: 120.95 | bwd_inner_microstep: 120.65 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-02 00:25:05,394] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.82 | bwd_microstep: 273.95 | bwd_inner_microstep: 273.93 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 845 +[2025-05-02 00:25:05,638] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.88 | bwd_microstep: 133.08 | bwd_inner_microstep: 132.88 | bwd_allreduce_microstep: 0.08 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 00:25:06,118] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.59 | bwd_microstep: 273.55 | bwd_inner_microstep: 273.53 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1096 +[2025-05-02 00:25:06,409] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 115.90 | bwd_microstep: 161.34 | bwd_inner_microstep: 161.25 | bwd_allreduce_microstep: 0.04 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 00:25:06,887] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.85 | bwd_microstep: 272.88 | bwd_inner_microstep: 272.86 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 00:25:07,364] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.10 | bwd_microstep: 273.04 | bwd_inner_microstep: 273.02 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 328 +[2025-05-02 00:25:07,581] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 83.49 | bwd_microstep: 117.35 | bwd_inner_microstep: 117.03 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 00:25:08,058] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.68 | bwd_microstep: 272.50 | bwd_inner_microstep: 272.48 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 00:25:08,536] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.54 | bwd_microstep: 272.69 | bwd_inner_microstep: 272.67 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 00:25:09,012] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.10 | bwd_microstep: 272.32 | bwd_inner_microstep: 272.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 00:25:09,489] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.54 | bwd_microstep: 272.31 | bwd_inner_microstep: 272.29 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 00:25:09,966] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.21 | bwd_microstep: 272.17 | bwd_inner_microstep: 272.15 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 00:25:10,540] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.10 | optimizer_step: 23.81 +[2025-05-02 00:25:10,540] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.64 | bwd_microstep: 338.71 | bwd_inner_microstep: 271.67 | bwd_allreduce_microstep: 66.99 | step_microstep: 31.11 +[2025-05-02 00:25:10,542] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2629.22 | bwd: 3876.54 | bwd_inner: 3808.48 | bwd_allreduce: 67.44 | step: 32.10 + 9%|▉ | 813/8720 [2:09:44<15:41:10, 7.14s/it] {'loss': 0.9964, 'grad_norm': 5.0957770347595215, 'learning_rate': 9.895650310689724e-06, 'epoch': 0.93} + 9%|▉ | 813/8720 [2:09:44<15:41:10, 7.14s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 435 +[2025-05-02 00:25:10,747] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 72.30 | bwd_microstep: 113.89 | bwd_inner_microstep: 113.58 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1929 +[2025-05-02 00:25:11,244] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 194.17 | bwd_microstep: 287.61 | bwd_inner_microstep: 287.59 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 879 +[2025-05-02 00:25:11,489] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 96.05 | bwd_microstep: 135.00 | bwd_inner_microstep: 134.80 | bwd_allreduce_microstep: 0.10 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1895 +[2025-05-02 00:25:11,970] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.09 | bwd_microstep: 275.01 | bwd_inner_microstep: 274.99 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1890 +[2025-05-02 00:25:12,450] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.16 | bwd_microstep: 274.70 | bwd_inner_microstep: 274.68 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 00:25:12,928] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.53 | bwd_microstep: 273.01 | bwd_inner_microstep: 272.99 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-02 00:25:13,405] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.22 | bwd_microstep: 273.59 | bwd_inner_microstep: 273.57 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.14 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 00:25:13,883] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.08 | bwd_microstep: 273.17 | bwd_inner_microstep: 273.15 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 00:25:14,360] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.87 | bwd_microstep: 272.49 | bwd_inner_microstep: 272.47 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 843 +[2025-05-02 00:25:14,601] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.17 | bwd_microstep: 132.33 | bwd_inner_microstep: 132.16 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 00:25:15,076] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.34 | bwd_microstep: 272.73 | bwd_inner_microstep: 272.71 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 835 +[2025-05-02 00:25:15,310] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.16 | bwd_microstep: 126.08 | bwd_inner_microstep: 125.94 | bwd_allreduce_microstep: 0.09 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 00:25:15,785] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.25 | bwd_microstep: 271.99 | bwd_inner_microstep: 271.97 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 00:25:16,260] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.85 | bwd_microstep: 271.45 | bwd_inner_microstep: 271.43 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 00:25:16,735] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.80 | bwd_microstep: 271.44 | bwd_inner_microstep: 271.42 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 00:25:17,303] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.81 | optimizer_step: 16.98 +[2025-05-02 00:25:17,304] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.14 | bwd_microstep: 339.94 | bwd_inner_microstep: 273.16 | bwd_allreduce_microstep: 66.73 | step_microstep: 24.81 +[2025-05-02 00:25:17,305] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2621.91 | bwd: 3864.50 | bwd_inner: 3796.71 | bwd_allreduce: 67.22 | step: 25.76 + 9%|▉ | 814/8720 [2:09:51<15:26:04, 7.03s/it] {'loss': 0.9338, 'grad_norm': 5.011132717132568, 'learning_rate': 9.895272531233501e-06, 'epoch': 0.93} + 9%|▉ | 814/8720 [2:09:51<15:26:04, 7.03s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2068 +[2025-05-02 00:25:17,829] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 201.58 | bwd_microstep: 302.25 | bwd_inner_microstep: 302.23 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1954 +[2025-05-02 00:25:18,332] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 198.13 | bwd_microstep: 289.99 | bwd_inner_microstep: 289.97 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 366 +[2025-05-02 00:25:18,555] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 91.10 | bwd_microstep: 118.55 | bwd_inner_microstep: 118.42 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1908 +[2025-05-02 00:25:19,036] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.55 | bwd_microstep: 276.51 | bwd_inner_microstep: 276.49 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 865 +[2025-05-02 00:25:19,281] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.26 | bwd_microstep: 134.47 | bwd_inner_microstep: 134.20 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1887 +[2025-05-02 00:25:19,761] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.65 | bwd_microstep: 275.05 | bwd_inner_microstep: 275.03 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 00:25:20,240] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.55 | bwd_microstep: 273.41 | bwd_inner_microstep: 273.39 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-02 00:25:20,721] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.55 | bwd_microstep: 273.26 | bwd_inner_microstep: 273.24 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 00:25:21,204] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.65 | bwd_microstep: 272.90 | bwd_inner_microstep: 272.88 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 00:25:21,687] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.99 | bwd_microstep: 273.21 | bwd_inner_microstep: 273.19 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 00:25:22,166] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.11 | bwd_microstep: 272.35 | bwd_inner_microstep: 272.33 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 324 +[2025-05-02 00:25:22,398] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 97.74 | bwd_microstep: 116.61 | bwd_inner_microstep: 116.44 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 00:25:22,877] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.59 | bwd_microstep: 272.43 | bwd_inner_microstep: 272.41 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 00:25:23,357] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.41 | bwd_microstep: 272.07 | bwd_inner_microstep: 272.05 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 00:25:23,839] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.24 | bwd_microstep: 273.30 | bwd_inner_microstep: 273.28 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 00:25:24,415] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.09 | optimizer_step: 16.85 +[2025-05-02 00:25:24,415] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.60 | bwd_microstep: 347.21 | bwd_inner_microstep: 271.76 | bwd_allreduce_microstep: 75.41 | step_microstep: 24.04 +[2025-05-02 00:25:24,416] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2757.36 | bwd: 4043.62 | bwd_inner: 3967.39 | bwd_allreduce: 75.73 | step: 25.01 + 9%|▉ | 815/8720 [2:09:58<15:29:15, 7.05s/it] {'loss': 1.1211, 'grad_norm': 5.771512031555176, 'learning_rate': 9.894894076408075e-06, 'epoch': 0.93} + 9%|▉ | 815/8720 [2:09:58<15:29:15, 7.05s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1981 +[2025-05-02 00:25:24,927] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 198.15 | bwd_microstep: 291.72 | bwd_inner_microstep: 291.70 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1915 +[2025-05-02 00:25:25,408] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.58 | bwd_microstep: 276.71 | bwd_inner_microstep: 276.70 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 375 +[2025-05-02 00:25:25,621] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 78.33 | bwd_microstep: 120.21 | bwd_inner_microstep: 119.97 | bwd_allreduce_microstep: 0.10 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-02 00:25:26,101] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.38 | bwd_microstep: 274.04 | bwd_inner_microstep: 274.02 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1109 +[2025-05-02 00:25:26,393] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 115.40 | bwd_microstep: 162.55 | bwd_inner_microstep: 162.34 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 00:25:26,873] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.12 | bwd_microstep: 272.91 | bwd_inner_microstep: 272.89 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 00:25:27,353] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.54 | bwd_microstep: 273.21 | bwd_inner_microstep: 273.19 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 00:25:27,833] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.10 | bwd_microstep: 273.09 | bwd_inner_microstep: 273.07 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 842 +[2025-05-02 00:25:28,074] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.31 | bwd_microstep: 132.38 | bwd_inner_microstep: 132.25 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 00:25:28,552] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.95 | bwd_microstep: 272.90 | bwd_inner_microstep: 272.88 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 00:25:29,030] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.26 | bwd_microstep: 273.20 | bwd_inner_microstep: 273.18 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 00:25:29,508] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.36 | bwd_microstep: 273.01 | bwd_inner_microstep: 273.00 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 00:25:29,985] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.05 | bwd_microstep: 272.62 | bwd_inner_microstep: 272.60 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 833 +[2025-05-02 00:25:30,219] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 92.35 | bwd_microstep: 126.74 | bwd_inner_microstep: 126.63 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 00:25:30,694] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.85 | bwd_microstep: 272.30 | bwd_inner_microstep: 272.28 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 00:25:31,261] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.15 | optimizer_step: 16.96 +[2025-05-02 00:25:31,261] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.26 | bwd_microstep: 338.58 | bwd_inner_microstep: 271.84 | bwd_allreduce_microstep: 66.70 | step_microstep: 24.17 +[2025-05-02 00:25:31,262] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2656.71 | bwd: 3906.25 | bwd_inner: 3838.62 | bwd_allreduce: 67.07 | step: 25.15 + 9%|▉ | 816/8720 [2:10:05<15:20:57, 6.99s/it] {'loss': 1.1056, 'grad_norm': 5.405725002288818, 'learning_rate': 9.894514946265659e-06, 'epoch': 0.94} + 9%|▉ | 816/8720 [2:10:05<15:20:57, 6.99s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2092 +[2025-05-02 00:25:31,791] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 204.29 | bwd_microstep: 304.19 | bwd_inner_microstep: 304.17 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 895 +[2025-05-02 00:25:32,041] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 98.95 | bwd_microstep: 136.00 | bwd_inner_microstep: 135.98 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1891 +[2025-05-02 00:25:32,520] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.35 | bwd_microstep: 275.13 | bwd_inner_microstep: 275.12 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1891 +[2025-05-02 00:25:32,999] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.69 | bwd_microstep: 275.18 | bwd_inner_microstep: 275.16 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 345 +[2025-05-02 00:25:33,202] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 71.38 | bwd_microstep: 117.63 | bwd_inner_microstep: 117.39 | bwd_allreduce_microstep: 0.09 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 00:25:33,680] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.29 | bwd_microstep: 273.66 | bwd_inner_microstep: 273.64 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 00:25:34,158] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.10 | bwd_microstep: 273.40 | bwd_inner_microstep: 273.38 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1352 +[2025-05-02 00:25:34,522] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 142.64 | bwd_microstep: 206.14 | bwd_inner_microstep: 206.09 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.11 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 333 +[2025-05-02 00:25:34,736] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 80.37 | bwd_microstep: 117.21 | bwd_inner_microstep: 117.06 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 00:25:35,215] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.00 | bwd_microstep: 273.66 | bwd_inner_microstep: 273.64 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 00:25:35,695] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.15 | bwd_microstep: 272.84 | bwd_inner_microstep: 272.82 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 00:25:36,175] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.03 | bwd_microstep: 272.73 | bwd_inner_microstep: 272.70 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 00:25:36,654] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.15 | bwd_microstep: 272.11 | bwd_inner_microstep: 272.10 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 00:25:37,130] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.85 | bwd_microstep: 271.26 | bwd_inner_microstep: 271.25 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1991 +[2025-05-02 00:25:37,641] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 198.54 | bwd_microstep: 293.80 | bwd_inner_microstep: 293.78 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 922 +[2025-05-02 00:25:38,009] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.06 | optimizer_step: 16.72 +[2025-05-02 00:25:38,010] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 104.09 | bwd_microstep: 222.84 | bwd_inner_microstep: 146.48 | bwd_allreduce_microstep: 76.26 | step_microstep: 24.27 +[2025-05-02 00:25:38,011] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2593.56 | bwd: 3857.85 | bwd_inner: 3780.88 | bwd_allreduce: 76.43 | step: 25.31 + 9%|▉ | 817/8720 [2:10:11<15:11:18, 6.92s/it] {'loss': 0.879, 'grad_norm': 5.888737678527832, 'learning_rate': 9.894135140858555e-06, 'epoch': 0.94} + 9%|▉ | 817/8720 [2:10:11<15:11:18, 6.92s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1942 +[2025-05-02 00:25:38,517] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.31 | bwd_microstep: 288.46 | bwd_inner_microstep: 288.45 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1921 +[2025-05-02 00:25:39,018] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.29 | bwd_microstep: 287.35 | bwd_inner_microstep: 287.34 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 00:25:39,498] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.50 | bwd_microstep: 273.79 | bwd_inner_microstep: 273.77 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 00:25:39,980] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.88 | bwd_microstep: 273.60 | bwd_inner_microstep: 273.59 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 855 +[2025-05-02 00:25:40,228] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.87 | bwd_microstep: 133.66 | bwd_inner_microstep: 133.43 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.18 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1360 +[2025-05-02 00:25:40,594] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.47 | bwd_microstep: 206.98 | bwd_inner_microstep: 206.83 | bwd_allreduce_microstep: 0.04 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 00:25:41,074] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.09 | bwd_microstep: 273.29 | bwd_inner_microstep: 273.27 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1109 +[2025-05-02 00:25:41,368] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 115.26 | bwd_microstep: 162.36 | bwd_inner_microstep: 162.34 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 00:25:41,848] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.95 | bwd_microstep: 273.22 | bwd_inner_microstep: 273.20 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 00:25:42,330] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.51 | bwd_microstep: 273.16 | bwd_inner_microstep: 273.14 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 00:25:42,811] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.55 | bwd_microstep: 273.16 | bwd_inner_microstep: 273.14 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1351 +[2025-05-02 00:25:43,178] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.72 | bwd_microstep: 206.35 | bwd_inner_microstep: 206.22 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 00:25:43,664] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.95 | bwd_microstep: 273.29 | bwd_inner_microstep: 273.27 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 00:25:44,144] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.58 | bwd_microstep: 272.34 | bwd_inner_microstep: 272.32 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 00:25:44,625] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.29 | bwd_microstep: 272.26 | bwd_inner_microstep: 272.24 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 835 +[2025-05-02 00:25:44,965] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.05 | optimizer_step: 17.36 +[2025-05-02 00:25:44,965] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 96.69 | bwd_microstep: 202.99 | bwd_inner_microstep: 126.65 | bwd_allreduce_microstep: 76.24 | step_microstep: 24.85 +[2025-05-02 00:25:44,967] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2679.50 | bwd: 3946.35 | bwd_inner: 3869.24 | bwd_allreduce: 76.55 | step: 25.92 + 9%|▉ | 818/8720 [2:10:18<15:12:39, 6.93s/it] {'loss': 1.3592, 'grad_norm': 8.544722557067871, 'learning_rate': 9.893754660239166e-06, 'epoch': 0.94} + 9%|▉ | 818/8720 [2:10:18<15:12:39, 6.93s/it]dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1435 +[2025-05-02 00:25:45,349] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 145.99 | bwd_microstep: 213.93 | bwd_inner_microstep: 213.91 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1926 +[2025-05-02 00:25:45,849] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.31 | bwd_microstep: 287.51 | bwd_inner_microstep: 287.49 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1908 +[2025-05-02 00:25:46,333] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.30 | bwd_microstep: 276.82 | bwd_inner_microstep: 276.80 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1934 +[2025-05-02 00:25:46,836] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.28 | bwd_microstep: 288.25 | bwd_inner_microstep: 288.23 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-02 00:25:47,316] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.78 | bwd_microstep: 274.60 | bwd_inner_microstep: 274.58 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1883 +[2025-05-02 00:25:47,797] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.80 | bwd_microstep: 274.85 | bwd_inner_microstep: 274.83 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-02 00:25:48,276] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.67 | bwd_microstep: 274.00 | bwd_inner_microstep: 273.98 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 00:25:48,753] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.19 | bwd_microstep: 273.49 | bwd_inner_microstep: 273.47 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 834 +[2025-05-02 00:25:48,983] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 90.61 | bwd_microstep: 125.93 | bwd_inner_microstep: 125.77 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.09 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 327 +[2025-05-02 00:25:49,183] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 68.67 | bwd_microstep: 117.82 | bwd_inner_microstep: 117.58 | bwd_allreduce_microstep: 0.09 | step_microstep: 0.08 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1351 +[2025-05-02 00:25:49,547] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.67 | bwd_microstep: 206.32 | bwd_inner_microstep: 206.19 | bwd_allreduce_microstep: 0.03 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 00:25:50,028] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.36 | bwd_microstep: 273.23 | bwd_inner_microstep: 273.21 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 00:25:50,506] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.63 | bwd_microstep: 272.53 | bwd_inner_microstep: 272.51 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 00:25:50,984] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.84 | bwd_microstep: 272.02 | bwd_inner_microstep: 272.00 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 00:25:51,463] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.48 | bwd_microstep: 271.93 | bwd_inner_microstep: 271.91 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 00:25:52,040] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.04 | optimizer_gradients: 2.03 | optimizer_step: 16.71 +[2025-05-02 00:25:52,041] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.25 | bwd_microstep: 348.21 | bwd_inner_microstep: 272.29 | bwd_allreduce_microstep: 75.88 | step_microstep: 23.50 +[2025-05-02 00:25:52,042] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2725.48 | bwd: 4051.49 | bwd_inner: 3974.87 | bwd_allreduce: 76.12 | step: 24.34 + 9%|▉ | 819/8720 [2:10:25<15:18:12, 6.97s/it] {'loss': 0.9589, 'grad_norm': 5.050429821014404, 'learning_rate': 9.893373504459983e-06, 'epoch': 0.94} + 9%|▉ | 819/8720 [2:10:25<15:18:12, 6.97s/it]dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 867 +[2025-05-02 00:25:52,289] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.21 | bwd_microstep: 134.22 | bwd_inner_microstep: 133.95 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 00:25:52,767] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.87 | bwd_microstep: 274.04 | bwd_inner_microstep: 274.02 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1888 +[2025-05-02 00:25:53,247] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.27 | bwd_microstep: 274.65 | bwd_inner_microstep: 274.63 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-02 00:25:53,727] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.23 | bwd_microstep: 274.68 | bwd_inner_microstep: 274.66 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-02 00:25:54,207] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.80 | bwd_microstep: 273.41 | bwd_inner_microstep: 273.39 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 326 +[2025-05-02 00:25:54,429] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 88.08 | bwd_microstep: 116.94 | bwd_inner_microstep: 116.61 | bwd_allreduce_microstep: 0.14 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 00:25:54,907] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.78 | bwd_microstep: 273.41 | bwd_inner_microstep: 273.39 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 327 +[2025-05-02 00:25:55,126] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 85.01 | bwd_microstep: 117.23 | bwd_inner_microstep: 117.08 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 00:25:55,605] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.13 | bwd_microstep: 273.09 | bwd_inner_microstep: 273.07 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1349 +[2025-05-02 00:25:55,968] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.32 | bwd_microstep: 205.77 | bwd_inner_microstep: 205.75 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 00:25:56,446] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.95 | bwd_microstep: 272.31 | bwd_inner_microstep: 272.29 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 00:25:56,924] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.58 | bwd_microstep: 272.70 | bwd_inner_microstep: 272.68 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 00:25:57,403] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.29 | bwd_microstep: 272.57 | bwd_inner_microstep: 272.56 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 00:25:57,883] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.47 | bwd_microstep: 271.16 | bwd_inner_microstep: 271.14 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 00:25:58,363] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.52 | bwd_microstep: 271.17 | bwd_inner_microstep: 271.15 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2436 +[2025-05-02 00:25:59,058] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.05 | optimizer_step: 16.68 +[2025-05-02 00:25:59,058] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 223.51 | bwd_microstep: 430.36 | bwd_inner_microstep: 353.23 | bwd_allreduce_microstep: 77.08 | step_microstep: 24.33 +[2025-05-02 00:25:59,060] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2705.63 | bwd: 4007.79 | bwd_inner: 3929.77 | bwd_allreduce: 77.46 | step: 25.51 + 9%|▉ | 820/8720 [2:10:32<15:19:56, 6.99s/it] {'loss': 0.7875, 'grad_norm': 5.761865615844727, 'learning_rate': 9.89299167357359e-06, 'epoch': 0.94} + 9%|▉ | 820/8720 [2:10:32<15:19:56, 6.99s/it]dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1385 +[2025-05-02 00:25:59,432] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 142.18 | bwd_microstep: 207.93 | bwd_inner_microstep: 207.91 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-02 00:25:59,909] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.25 | bwd_microstep: 274.06 | bwd_inner_microstep: 274.04 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-02 00:26:00,394] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.42 | bwd_microstep: 273.93 | bwd_inner_microstep: 273.92 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-02 00:26:00,872] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.64 | bwd_microstep: 274.27 | bwd_inner_microstep: 274.25 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 347 +[2025-05-02 00:26:01,081] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 78.20 | bwd_microstep: 117.32 | bwd_inner_microstep: 117.00 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-02 00:26:01,558] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.79 | bwd_microstep: 273.72 | bwd_inner_microstep: 273.70 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-02 00:26:02,039] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.92 | bwd_microstep: 274.50 | bwd_inner_microstep: 274.48 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 846 +[2025-05-02 00:26:02,285] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.77 | bwd_microstep: 132.70 | bwd_inner_microstep: 132.53 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 00:26:02,763] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.59 | bwd_microstep: 273.05 | bwd_inner_microstep: 273.04 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 00:26:03,242] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.73 | bwd_microstep: 272.67 | bwd_inner_microstep: 272.65 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 836 +[2025-05-02 00:26:03,485] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 98.11 | bwd_microstep: 125.77 | bwd_inner_microstep: 125.57 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 00:26:03,966] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.10 | bwd_microstep: 272.32 | bwd_inner_microstep: 272.31 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 00:26:04,448] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.34 | bwd_microstep: 273.39 | bwd_inner_microstep: 273.37 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 00:26:04,929] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.74 | bwd_microstep: 272.47 | bwd_inner_microstep: 272.45 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 00:26:05,407] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.95 | bwd_microstep: 271.28 | bwd_inner_microstep: 271.26 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 00:26:05,983] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.04 | optimizer_gradients: 2.02 | optimizer_step: 16.68 +[2025-05-02 00:26:05,983] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.67 | bwd_microstep: 348.09 | bwd_inner_microstep: 271.68 | bwd_allreduce_microstep: 76.36 | step_microstep: 23.50 +[2025-05-02 00:26:05,984] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2676.07 | bwd: 3937.56 | bwd_inner: 3860.25 | bwd_allreduce: 76.73 | step: 24.44 + 9%|▉ | 821/8720 [2:10:39<15:17:19, 6.97s/it] {'loss': 0.8029, 'grad_norm': 10.597471237182617, 'learning_rate': 9.892609167632672e-06, 'epoch': 0.94} + 9%|▉ | 821/8720 [2:10:39<15:17:19, 6.97s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1908 +[2025-05-02 00:26:06,471] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.43 | bwd_microstep: 275.73 | bwd_inner_microstep: 275.71 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1892 +[2025-05-02 00:26:06,951] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.31 | bwd_microstep: 275.51 | bwd_inner_microstep: 275.49 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-02 00:26:07,430] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.92 | bwd_microstep: 274.21 | bwd_inner_microstep: 274.19 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-02 00:26:07,909] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.97 | bwd_microstep: 274.54 | bwd_inner_microstep: 274.53 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 00:26:08,386] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.17 | bwd_microstep: 272.55 | bwd_inner_microstep: 272.53 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 00:26:08,864] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.39 | bwd_microstep: 272.73 | bwd_inner_microstep: 272.72 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 00:26:09,342] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.34 | bwd_microstep: 272.61 | bwd_inner_microstep: 272.59 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 00:26:09,821] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.57 | bwd_microstep: 272.79 | bwd_inner_microstep: 272.77 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 00:26:10,298] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.41 | bwd_microstep: 272.65 | bwd_inner_microstep: 272.64 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 833 +[2025-05-02 00:26:10,533] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 92.73 | bwd_microstep: 126.22 | bwd_inner_microstep: 125.92 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 00:26:11,009] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.47 | bwd_microstep: 272.37 | bwd_inner_microstep: 272.35 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 00:26:11,487] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.10 | bwd_microstep: 272.42 | bwd_inner_microstep: 272.40 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 00:26:11,961] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.54 | bwd_microstep: 271.11 | bwd_inner_microstep: 271.09 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 00:26:12,435] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.07 | bwd_microstep: 271.26 | bwd_inner_microstep: 271.25 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.14 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1904 +[2025-05-02 00:26:12,918] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.80 | bwd_microstep: 275.95 | bwd_inner_microstep: 275.93 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.14 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-02 00:26:13,486] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.00 | optimizer_step: 16.74 +[2025-05-02 00:26:13,486] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.30 | bwd_microstep: 339.85 | bwd_inner_microstep: 274.14 | bwd_allreduce_microstep: 65.66 | step_microstep: 23.65 +[2025-05-02 00:26:13,487] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2924.22 | bwd: 4292.52 | bwd_inner: 4226.30 | bwd_allreduce: 65.85 | step: 24.79 + 9%|▉ | 822/8720 [2:10:47<15:38:18, 7.13s/it] {'loss': 0.9702, 'grad_norm': 5.824907302856445, 'learning_rate': 9.892225986689995e-06, 'epoch': 0.94} + 9%|▉ | 822/8720 [2:10:47<15:38:18, 7.13s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1944 +[2025-05-02 00:26:13,991] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.76 | bwd_microstep: 288.52 | bwd_inner_microstep: 288.50 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.15 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1910 +[2025-05-02 00:26:14,476] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.31 | bwd_microstep: 277.07 | bwd_inner_microstep: 277.05 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-02 00:26:14,954] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.43 | bwd_microstep: 273.59 | bwd_inner_microstep: 273.58 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 862 +[2025-05-02 00:26:15,200] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 97.77 | bwd_microstep: 133.83 | bwd_inner_microstep: 133.80 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 00:26:15,677] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.12 | bwd_microstep: 273.52 | bwd_inner_microstep: 273.50 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 00:26:16,155] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.22 | bwd_microstep: 273.60 | bwd_inner_microstep: 273.58 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 00:26:16,633] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.74 | bwd_microstep: 273.20 | bwd_inner_microstep: 273.18 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 00:26:17,111] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.37 | bwd_microstep: 273.27 | bwd_inner_microstep: 273.25 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 329 +[2025-05-02 00:26:17,318] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 79.58 | bwd_microstep: 113.34 | bwd_inner_microstep: 113.04 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 00:26:17,795] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.36 | bwd_microstep: 272.80 | bwd_inner_microstep: 272.78 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 00:26:18,271] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.69 | bwd_microstep: 272.38 | bwd_inner_microstep: 272.36 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 00:26:18,748] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.95 | bwd_microstep: 272.77 | bwd_inner_microstep: 272.75 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 00:26:19,225] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.42 | bwd_microstep: 272.62 | bwd_inner_microstep: 272.60 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 00:26:19,701] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.29 | bwd_microstep: 273.22 | bwd_inner_microstep: 273.20 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 00:26:20,177] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.39 | bwd_microstep: 272.73 | bwd_inner_microstep: 272.71 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 00:26:20,746] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.04 | optimizer_step: 16.68 +[2025-05-02 00:26:20,746] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.19 | bwd_microstep: 340.90 | bwd_inner_microstep: 272.88 | bwd_allreduce_microstep: 67.96 | step_microstep: 23.58 +[2025-05-02 00:26:20,747] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2829.35 | bwd: 4157.40 | bwd_inner: 4088.83 | bwd_allreduce: 68.17 | step: 24.62 + 9%|▉ | 823/8720 [2:10:54<15:43:24, 7.17s/it] {'loss': 0.9679, 'grad_norm': 6.271563529968262, 'learning_rate': 9.891842130798423e-06, 'epoch': 0.94} + 9%|▉ | 823/8720 [2:10:54<15:43:24, 7.17s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1959 +[2025-05-02 00:26:21,254] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 198.15 | bwd_microstep: 289.13 | bwd_inner_microstep: 289.11 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 418 +[2025-05-02 00:26:21,456] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 67.96 | bwd_microstep: 120.14 | bwd_inner_microstep: 119.82 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1910 +[2025-05-02 00:26:21,937] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.48 | bwd_microstep: 276.94 | bwd_inner_microstep: 276.92 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1889 +[2025-05-02 00:26:22,417] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.44 | bwd_microstep: 274.79 | bwd_inner_microstep: 274.77 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.13 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 00:26:22,895] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.55 | bwd_microstep: 273.35 | bwd_inner_microstep: 273.34 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 00:26:23,372] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.83 | bwd_microstep: 273.42 | bwd_inner_microstep: 273.40 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 00:26:23,849] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.18 | bwd_microstep: 272.69 | bwd_inner_microstep: 272.68 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 839 +[2025-05-02 00:26:24,081] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 91.47 | bwd_microstep: 126.66 | bwd_inner_microstep: 126.46 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.18 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1094 +[2025-05-02 00:26:24,374] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 117.04 | bwd_microstep: 161.40 | bwd_inner_microstep: 161.16 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 00:26:24,852] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.82 | bwd_microstep: 272.48 | bwd_inner_microstep: 272.47 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 00:26:25,329] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.77 | bwd_microstep: 272.67 | bwd_inner_microstep: 272.66 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 00:26:25,807] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.28 | bwd_microstep: 272.90 | bwd_inner_microstep: 272.88 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.11 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 323 +[2025-05-02 00:26:26,020] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 82.28 | bwd_microstep: 115.50 | bwd_inner_microstep: 115.30 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 00:26:26,493] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.25 | bwd_microstep: 271.22 | bwd_inner_microstep: 271.20 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 00:26:26,968] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.63 | bwd_microstep: 271.14 | bwd_inner_microstep: 271.12 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1888 +[2025-05-02 00:26:27,538] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.09 | optimizer_step: 16.89 +[2025-05-02 00:26:27,538] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.62 | bwd_microstep: 341.35 | bwd_inner_microstep: 275.15 | bwd_allreduce_microstep: 66.15 | step_microstep: 24.06 +[2025-05-02 00:26:27,540] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2635.51 | bwd: 3885.90 | bwd_inner: 3818.57 | bwd_allreduce: 66.64 | step: 25.30 + 9%|▉ | 824/8720 [2:11:01<15:28:27, 7.06s/it] {'loss': 1.0914, 'grad_norm': 7.084454536437988, 'learning_rate': 9.89145760001092e-06, 'epoch': 0.94} + 9%|▉ | 824/8720 [2:11:01<15:28:27, 7.06s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1967 +[2025-05-02 00:26:28,046] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.72 | bwd_microstep: 290.37 | bwd_inner_microstep: 290.35 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1919 +[2025-05-02 00:26:28,528] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.70 | bwd_microstep: 276.63 | bwd_inner_microstep: 276.61 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1897 +[2025-05-02 00:26:29,008] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.64 | bwd_microstep: 275.66 | bwd_inner_microstep: 275.65 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1891 +[2025-05-02 00:26:29,488] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.49 | bwd_microstep: 274.50 | bwd_inner_microstep: 274.48 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-02 00:26:29,967] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.26 | bwd_microstep: 274.38 | bwd_inner_microstep: 274.36 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 343 +[2025-05-02 00:26:30,168] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 68.24 | bwd_microstep: 119.54 | bwd_inner_microstep: 119.42 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1358 +[2025-05-02 00:26:30,529] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.76 | bwd_microstep: 206.50 | bwd_inner_microstep: 206.48 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-02 00:26:31,008] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.22 | bwd_microstep: 273.82 | bwd_inner_microstep: 273.80 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-02 00:26:31,486] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.15 | bwd_microstep: 273.76 | bwd_inner_microstep: 273.74 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 00:26:31,963] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.85 | bwd_microstep: 272.46 | bwd_inner_microstep: 272.44 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 00:26:32,442] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.73 | bwd_microstep: 272.77 | bwd_inner_microstep: 272.75 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 00:26:32,924] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.93 | bwd_microstep: 272.32 | bwd_inner_microstep: 272.31 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 00:26:33,407] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.54 | bwd_microstep: 271.37 | bwd_inner_microstep: 271.35 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 00:26:33,888] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.83 | bwd_microstep: 272.08 | bwd_inner_microstep: 272.06 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 00:26:34,368] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.76 | bwd_microstep: 271.82 | bwd_inner_microstep: 271.80 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 00:26:34,951] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.12 | optimizer_step: 16.68 +[2025-05-02 00:26:34,952] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.59 | bwd_microstep: 349.62 | bwd_inner_microstep: 272.47 | bwd_allreduce_microstep: 77.09 | step_microstep: 24.53 +[2025-05-02 00:26:34,953] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2862.09 | bwd: 4247.61 | bwd_inner: 4170.10 | bwd_allreduce: 77.23 | step: 25.26 + 9%|▉ | 825/8720 [2:11:08<15:42:34, 7.16s/it] {'loss': 1.1118, 'grad_norm': 6.89068603515625, 'learning_rate': 9.891072394380532e-06, 'epoch': 0.95} + 9%|▉ | 825/8720 [2:11:08<15:42:34, 7.16s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2005 +[2025-05-02 00:26:35,469] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 197.58 | bwd_microstep: 294.54 | bwd_inner_microstep: 294.52 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 967 +[2025-05-02 00:26:35,740] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 104.01 | bwd_microstep: 150.63 | bwd_inner_microstep: 150.40 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1912 +[2025-05-02 00:26:36,222] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.24 | bwd_microstep: 276.99 | bwd_inner_microstep: 276.97 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 00:26:36,700] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.80 | bwd_microstep: 273.57 | bwd_inner_microstep: 273.56 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 00:26:37,180] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.59 | bwd_microstep: 274.15 | bwd_inner_microstep: 274.13 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 00:26:37,660] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.85 | bwd_microstep: 274.07 | bwd_inner_microstep: 274.05 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 00:26:38,142] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.98 | bwd_microstep: 273.12 | bwd_inner_microstep: 273.11 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 00:26:38,621] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.98 | bwd_microstep: 272.89 | bwd_inner_microstep: 272.87 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1099 +[2025-05-02 00:26:38,918] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 118.08 | bwd_microstep: 161.74 | bwd_inner_microstep: 161.48 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 843 +[2025-05-02 00:26:39,160] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.14 | bwd_microstep: 132.17 | bwd_inner_microstep: 132.08 | bwd_allreduce_microstep: 0.04 | step_microstep: 0.11 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 322 +[2025-05-02 00:26:39,396] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 85.25 | bwd_microstep: 129.75 | bwd_inner_microstep: 129.62 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 00:26:39,870] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.09 | bwd_microstep: 272.17 | bwd_inner_microstep: 272.15 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 00:26:40,347] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.79 | bwd_microstep: 273.17 | bwd_inner_microstep: 273.16 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 00:26:40,822] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.47 | bwd_microstep: 271.40 | bwd_inner_microstep: 271.38 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 00:26:41,298] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.11 | bwd_microstep: 271.40 | bwd_inner_microstep: 271.39 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 317 +[2025-05-02 00:26:41,603] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.15 | optimizer_step: 16.79 +[2025-05-02 00:26:41,603] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 67.98 | bwd_microstep: 199.72 | bwd_inner_microstep: 132.94 | bwd_allreduce_microstep: 66.69 | step_microstep: 24.07 +[2025-05-02 00:26:41,604] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2551.62 | bwd: 3801.57 | bwd_inner: 3733.88 | bwd_allreduce: 67.09 | step: 24.95 + 9%|▉ | 826/8720 [2:11:15<15:22:09, 7.01s/it] {'loss': 1.2172, 'grad_norm': 10.830012321472168, 'learning_rate': 9.890686513960407e-06, 'epoch': 0.95} + 9%|▉ | 826/8720 [2:11:15<15:22:09, 7.01s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1928 +[2025-05-02 00:26:42,107] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.45 | bwd_microstep: 287.11 | bwd_inner_microstep: 287.09 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1902 +[2025-05-02 00:26:42,588] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.32 | bwd_microstep: 275.72 | bwd_inner_microstep: 275.71 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1896 +[2025-05-02 00:26:43,069] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.96 | bwd_microstep: 275.42 | bwd_inner_microstep: 275.40 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-02 00:26:43,549] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.16 | bwd_microstep: 274.13 | bwd_inner_microstep: 274.11 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 342 +[2025-05-02 00:26:43,783] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 98.35 | bwd_microstep: 117.71 | bwd_inner_microstep: 117.55 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 00:26:44,263] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.91 | bwd_microstep: 273.12 | bwd_inner_microstep: 273.10 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-02 00:26:44,744] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.58 | bwd_microstep: 273.70 | bwd_inner_microstep: 273.69 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-02 00:26:45,226] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.94 | bwd_microstep: 274.30 | bwd_inner_microstep: 274.29 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 00:26:45,704] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.21 | bwd_microstep: 272.69 | bwd_inner_microstep: 272.67 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 00:26:46,185] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.01 | bwd_microstep: 272.96 | bwd_inner_microstep: 272.94 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 00:26:46,665] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.03 | bwd_microstep: 273.05 | bwd_inner_microstep: 273.03 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 00:26:47,145] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.06 | bwd_microstep: 272.45 | bwd_inner_microstep: 272.43 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 00:26:47,627] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.11 | bwd_microstep: 272.69 | bwd_inner_microstep: 272.67 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 834 +[2025-05-02 00:26:47,875] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 98.27 | bwd_microstep: 130.37 | bwd_inner_microstep: 130.28 | bwd_allreduce_microstep: 0.04 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1958 +[2025-05-02 00:26:48,379] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.99 | bwd_microstep: 290.38 | bwd_inner_microstep: 290.36 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1952 +[2025-05-02 00:26:48,987] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.11 | optimizer_step: 16.63 +[2025-05-02 00:26:48,987] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 196.64 | bwd_microstep: 367.90 | bwd_inner_microstep: 289.85 | bwd_allreduce_microstep: 78.00 | step_microstep: 24.48 +[2025-05-02 00:26:48,989] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2868.63 | bwd: 4203.75 | bwd_inner: 4125.22 | bwd_allreduce: 78.18 | step: 25.36 + 9%|▉ | 827/8720 [2:11:22<15:36:55, 7.12s/it] {'loss': 1.1539, 'grad_norm': 6.541538238525391, 'learning_rate': 9.89029995880378e-06, 'epoch': 0.95} + 9%|▉ | 827/8720 [2:11:22<15:36:55, 7.12s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1916 +[2025-05-02 00:26:49,480] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 191.76 | bwd_microstep: 276.26 | bwd_inner_microstep: 276.25 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-02 00:26:49,963] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.91 | bwd_microstep: 275.19 | bwd_inner_microstep: 275.17 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.15 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 860 +[2025-05-02 00:26:50,211] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 96.58 | bwd_microstep: 133.32 | bwd_inner_microstep: 133.21 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.10 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 329 +[2025-05-02 00:26:50,436] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 83.12 | bwd_microstep: 126.91 | bwd_inner_microstep: 126.66 | bwd_allreduce_microstep: 0.10 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 00:26:50,917] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.61 | bwd_microstep: 274.38 | bwd_inner_microstep: 274.36 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-02 00:26:51,400] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.42 | bwd_microstep: 273.23 | bwd_inner_microstep: 273.21 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-02 00:26:51,881] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.57 | bwd_microstep: 273.85 | bwd_inner_microstep: 273.83 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 00:26:52,363] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.61 | bwd_microstep: 273.26 | bwd_inner_microstep: 273.24 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 00:26:52,846] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.76 | bwd_microstep: 272.97 | bwd_inner_microstep: 272.95 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 00:26:53,325] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.80 | bwd_microstep: 272.48 | bwd_inner_microstep: 272.46 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 00:26:53,804] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.99 | bwd_microstep: 272.59 | bwd_inner_microstep: 272.58 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 00:26:54,285] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.26 | bwd_microstep: 272.53 | bwd_inner_microstep: 272.51 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 00:26:54,767] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.84 | bwd_microstep: 272.12 | bwd_inner_microstep: 272.11 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 00:26:55,245] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.42 | bwd_microstep: 271.65 | bwd_inner_microstep: 271.64 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 00:26:55,723] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.56 | bwd_microstep: 271.02 | bwd_inner_microstep: 271.00 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1899 +[2025-05-02 00:26:56,311] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.22 | optimizer_step: 16.75 +[2025-05-02 00:26:56,311] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.31 | bwd_microstep: 353.43 | bwd_inner_microstep: 276.84 | bwd_allreduce_microstep: 76.54 | step_microstep: 24.75 +[2025-05-02 00:26:56,313] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2829.15 | bwd: 4165.24 | bwd_inner: 4088.08 | bwd_allreduce: 76.75 | step: 25.76 + 9%|▉ | 828/8720 [2:11:30<15:44:45, 7.18s/it] {'loss': 1.4351, 'grad_norm': 13.846487045288086, 'learning_rate': 9.889912728963982e-06, 'epoch': 0.95} + 9%|▉ | 828/8720 [2:11:30<15:44:45, 7.18s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2005 +[2025-05-02 00:26:56,828] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 198.57 | bwd_microstep: 294.42 | bwd_inner_microstep: 294.40 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 880 +[2025-05-02 00:26:57,074] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 96.84 | bwd_microstep: 134.72 | bwd_inner_microstep: 134.70 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1893 +[2025-05-02 00:26:57,552] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.55 | bwd_microstep: 275.22 | bwd_inner_microstep: 275.20 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1889 +[2025-05-02 00:26:58,030] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.80 | bwd_microstep: 274.66 | bwd_inner_microstep: 274.64 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 00:26:58,507] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.11 | bwd_microstep: 273.41 | bwd_inner_microstep: 273.39 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 845 +[2025-05-02 00:26:58,747] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.50 | bwd_microstep: 132.61 | bwd_inner_microstep: 132.39 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 00:26:59,224] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.79 | bwd_microstep: 273.65 | bwd_inner_microstep: 273.63 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 00:26:59,704] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.60 | bwd_microstep: 273.71 | bwd_inner_microstep: 273.69 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 834 +[2025-05-02 00:26:59,935] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 91.59 | bwd_microstep: 125.84 | bwd_inner_microstep: 125.76 | bwd_allreduce_microstep: 0.04 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 00:27:00,412] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.82 | bwd_microstep: 272.49 | bwd_inner_microstep: 272.48 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 834 +[2025-05-02 00:27:00,647] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.29 | bwd_microstep: 125.82 | bwd_inner_microstep: 125.77 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 00:27:01,124] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.81 | bwd_microstep: 271.04 | bwd_inner_microstep: 271.02 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 00:27:01,604] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.66 | bwd_microstep: 271.05 | bwd_inner_microstep: 271.04 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 00:27:02,083] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.75 | bwd_microstep: 272.10 | bwd_inner_microstep: 272.08 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 00:27:02,560] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.05 | bwd_microstep: 271.14 | bwd_inner_microstep: 271.12 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 00:27:03,152] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.07 | optimizer_gradients: 2.12 | optimizer_step: 16.62 +[2025-05-02 00:27:03,152] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.02 | bwd_microstep: 359.14 | bwd_inner_microstep: 271.69 | bwd_allreduce_microstep: 87.37 | step_microstep: 24.64 +[2025-05-02 00:27:03,154] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2645.39 | bwd: 3901.07 | bwd_inner: 3813.00 | bwd_allreduce: 87.59 | step: 25.60 + 10%|▉ | 829/8720 [2:11:36<15:31:10, 7.08s/it] {'loss': 1.1088, 'grad_norm': 8.93311882019043, 'learning_rate': 9.889524824494437e-06, 'epoch': 0.95} + 10%|▉ | 829/8720 [2:11:36<15:31:10, 7.08s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1901 +[2025-05-02 00:27:03,643] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.39 | bwd_microstep: 275.92 | bwd_inner_microstep: 275.90 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1371 +[2025-05-02 00:27:04,010] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.97 | bwd_microstep: 207.54 | bwd_inner_microstep: 207.50 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 345 +[2025-05-02 00:27:04,227] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 82.44 | bwd_microstep: 118.85 | bwd_inner_microstep: 118.54 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 00:27:04,706] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.46 | bwd_microstep: 273.77 | bwd_inner_microstep: 273.75 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 00:27:05,184] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.97 | bwd_microstep: 272.73 | bwd_inner_microstep: 272.71 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 333 +[2025-05-02 00:27:05,401] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 82.06 | bwd_microstep: 119.25 | bwd_inner_microstep: 119.11 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 843 +[2025-05-02 00:27:05,646] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.50 | bwd_microstep: 132.89 | bwd_inner_microstep: 132.64 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 00:27:06,125] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.17 | bwd_microstep: 272.82 | bwd_inner_microstep: 272.80 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 00:27:06,603] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.33 | bwd_microstep: 272.73 | bwd_inner_microstep: 272.71 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 00:27:07,082] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.87 | bwd_microstep: 272.81 | bwd_inner_microstep: 272.79 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 00:27:07,558] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.88 | bwd_microstep: 272.32 | bwd_inner_microstep: 272.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 00:27:08,033] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.55 | bwd_microstep: 271.25 | bwd_inner_microstep: 271.24 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 316 +[2025-05-02 00:27:08,233] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 67.18 | bwd_microstep: 119.29 | bwd_inner_microstep: 119.15 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 315 +[2025-05-02 00:27:08,433] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 67.29 | bwd_microstep: 119.47 | bwd_inner_microstep: 119.14 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 00:27:08,906] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.26 | bwd_microstep: 271.03 | bwd_inner_microstep: 271.01 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1949 +[2025-05-02 00:27:09,498] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.04 | optimizer_gradients: 2.92 | optimizer_step: 16.46 +[2025-05-02 00:27:09,498] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.84 | bwd_microstep: 356.42 | bwd_inner_microstep: 289.85 | bwd_allreduce_microstep: 66.53 | step_microstep: 24.17 +[2025-05-02 00:27:09,499] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2426.87 | bwd: 3629.22 | bwd_inner: 3561.34 | bwd_allreduce: 67.06 | step: 25.34 + 10%|▉ | 830/8720 [2:11:43<15:01:59, 6.86s/it] {'loss': 1.0916, 'grad_norm': 5.595932483673096, 'learning_rate': 9.889136245448662e-06, 'epoch': 0.95} + 10%|▉ | 830/8720 [2:11:43<15:01:59, 6.86s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1908 +[2025-05-02 00:27:09,984] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.08 | bwd_microstep: 275.61 | bwd_inner_microstep: 275.60 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1929 +[2025-05-02 00:27:10,481] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.28 | bwd_microstep: 287.72 | bwd_inner_microstep: 287.70 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 899 +[2025-05-02 00:27:10,741] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 101.10 | bwd_microstep: 144.37 | bwd_inner_microstep: 144.32 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1891 +[2025-05-02 00:27:11,221] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.73 | bwd_microstep: 275.10 | bwd_inner_microstep: 275.08 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 329 +[2025-05-02 00:27:11,445] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 88.30 | bwd_microstep: 119.14 | bwd_inner_microstep: 118.99 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 00:27:11,937] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 201.01 | bwd_microstep: 273.50 | bwd_inner_microstep: 273.47 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 00:27:12,420] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.72 | bwd_microstep: 274.10 | bwd_inner_microstep: 274.08 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-02 00:27:12,903] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.82 | bwd_microstep: 275.01 | bwd_inner_microstep: 274.99 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1352 +[2025-05-02 00:27:13,270] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.39 | bwd_microstep: 208.34 | bwd_inner_microstep: 208.29 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 329 +[2025-05-02 00:27:13,489] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 84.95 | bwd_microstep: 117.76 | bwd_inner_microstep: 117.45 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.21 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 834 +[2025-05-02 00:27:13,752] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 102.23 | bwd_microstep: 142.39 | bwd_inner_microstep: 142.11 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 00:27:14,243] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 200.04 | bwd_microstep: 272.64 | bwd_inner_microstep: 272.62 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 00:27:14,727] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.87 | bwd_microstep: 276.87 | bwd_inner_microstep: 276.85 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 00:27:15,738] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 260.10 | bwd_microstep: 730.41 | bwd_inner_microstep: 730.39 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1966 +[2025-05-02 00:27:16,936] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 773.62 | bwd_microstep: 358.20 | bwd_inner_microstep: 358.18 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 00:27:19,338] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.06 | optimizer_step: 16.64 +[2025-05-02 00:27:19,338] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 722.89 | bwd_microstep: 1638.07 | bwd_inner_microstep: 919.60 | bwd_allreduce_microstep: 718.43 | step_microstep: 24.15 +[2025-05-02 00:27:19,340] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 3816.81 | bwd: 5669.32 | bwd_inner: 4949.82 | bwd_allreduce: 718.69 | step: 25.38 + 10%|▉ | 831/8720 [2:11:53<16:59:27, 7.75s/it] {'loss': 1.2082, 'grad_norm': 5.225240707397461, 'learning_rate': 9.888746991880265e-06, 'epoch': 0.95} + 10%|▉ | 831/8720 [2:11:53<16:59:27, 7.75s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 467 +[2025-05-02 00:27:20,662] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 588.43 | bwd_microstep: 667.06 | bwd_inner_microstep: 666.90 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.08 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1234 +[2025-05-02 00:27:23,194] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 863.55 | bwd_microstep: 1554.36 | bwd_inner_microstep: 1554.19 | bwd_allreduce_microstep: 0.08 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1939 +[2025-05-02 00:27:27,510] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1802.22 | bwd_microstep: 2495.65 | bwd_inner_microstep: 2495.63 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 345 +[2025-05-02 00:27:28,494] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 248.12 | bwd_microstep: 720.44 | bwd_inner_microstep: 720.17 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.10 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1360 +[2025-05-02 00:27:31,461] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1318.11 | bwd_microstep: 1633.58 | bwd_inner_microstep: 1633.52 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 00:27:35,374] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1321.78 | bwd_microstep: 2284.05 | bwd_inner_microstep: 2284.03 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1350 +[2025-05-02 00:27:38,774] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1406.28 | bwd_microstep: 1879.63 | bwd_inner_microstep: 1830.36 | bwd_allreduce_microstep: 49.26 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 00:27:42,283] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1023.55 | bwd_microstep: 2277.99 | bwd_inner_microstep: 2277.97 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 00:27:46,144] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1456.70 | bwd_microstep: 2289.62 | bwd_inner_microstep: 2289.61 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.06 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1347 +[2025-05-02 00:27:49,745] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1612.41 | bwd_microstep: 1634.32 | bwd_inner_microstep: 1634.13 | bwd_allreduce_microstep: 0.10 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 00:27:53,665] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1614.51 | bwd_microstep: 2288.04 | bwd_inner_microstep: 2288.03 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 00:27:57,610] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1264.67 | bwd_microstep: 2281.20 | bwd_inner_microstep: 2281.18 | bwd_allreduce_microstep: 0.01 | step_microstep: 98.89 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 00:28:01,995] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1746.23 | bwd_microstep: 2288.68 | bwd_inner_microstep: 2288.66 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.14 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 00:28:06,308] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 2006.01 | bwd_microstep: 2288.94 | bwd_inner_microstep: 2288.93 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.11 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1341 +[2025-05-02 00:28:09,123] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1024.95 | bwd_microstep: 1725.17 | bwd_inner_microstep: 1725.15 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 00:28:14,148] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.10 | optimizer_step: 16.66 +[2025-05-02 00:28:14,148] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1597.33 | bwd_microstep: 3105.16 | bwd_inner_microstep: 2385.56 | bwd_allreduce_microstep: 719.55 | step_microstep: 24.26 +[2025-05-02 00:28:14,150] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 20894.69 | bwd: 31414.03 | bwd_inner: 30594.87 | bwd_allreduce: 769.26 | step: 125.73 + 10%|▉ | 832/8720 [2:12:47<47:59:06, 21.90s/it] {'loss': 1.0611, 'grad_norm': 8.733611106872559, 'learning_rate': 9.888357063842953e-06, 'epoch': 0.95} + 10%|▉ | 832/8720 [2:12:48<47:59:06, 21.90s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1938 +[2025-05-02 00:28:18,652] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1224.98 | bwd_microstep: 2779.80 | bwd_inner_microstep: 2779.70 | bwd_allreduce_microstep: 0.04 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1883 +[2025-05-02 00:28:22,516] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1556.16 | bwd_microstep: 2289.19 | bwd_inner_microstep: 2289.17 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1362 +[2025-05-02 00:28:25,534] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1370.55 | bwd_microstep: 1630.85 | bwd_inner_microstep: 1630.70 | bwd_allreduce_microstep: 0.08 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-02 00:28:29,395] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1458.45 | bwd_microstep: 2289.29 | bwd_inner_microstep: 2289.27 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.32 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 337 +[2025-05-02 00:28:31,358] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 798.46 | bwd_microstep: 959.06 | bwd_inner_microstep: 958.90 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-02 00:28:34,661] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1209.65 | bwd_microstep: 2078.16 | bwd_inner_microstep: 2078.14 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 00:28:38,520] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1264.03 | bwd_microstep: 2288.59 | bwd_inner_microstep: 2288.57 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1362 +[2025-05-02 00:28:42,170] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1658.02 | bwd_microstep: 1638.38 | bwd_inner_microstep: 1638.23 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 00:28:46,081] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1603.57 | bwd_microstep: 2289.13 | bwd_inner_microstep: 2289.04 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 00:28:49,942] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1556.96 | bwd_microstep: 2286.17 | bwd_inner_microstep: 2286.15 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 00:28:54,249] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 2001.61 | bwd_microstep: 2287.71 | bwd_inner_microstep: 2287.70 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 00:28:58,168] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1614.82 | bwd_microstep: 2286.36 | bwd_inner_microstep: 2286.33 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 00:28:59,323] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 871.30 | bwd_microstep: 266.57 | bwd_inner_microstep: 266.55 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 00:28:59,789] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 184.49 | bwd_microstep: 266.67 | bwd_inner_microstep: 266.65 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 828 +[2025-05-02 00:29:00,022] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 90.40 | bwd_microstep: 127.92 | bwd_inner_microstep: 127.68 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 00:29:00,581] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.10 | optimizer_step: 16.53 +[2025-05-02 00:29:00,581] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 184.54 | bwd_microstep: 336.32 | bwd_inner_microstep: 269.89 | bwd_allreduce_microstep: 66.38 | step_microstep: 23.53 +[2025-05-02 00:29:00,582] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 18647.80 | bwd: 26100.27 | bwd_inner: 26032.73 | bwd_allreduce: 66.89 | step: 25.17 + 10%|▉ | 833/8720 [2:13:34<64:02:19, 29.23s/it] {'loss': 1.1703, 'grad_norm': 5.622715950012207, 'learning_rate': 9.887966461390516e-06, 'epoch': 0.96} + 10%|▉ | 833/8720 [2:13:34<64:02:19, 29.23s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1933 +[2025-05-02 00:29:01,078] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 193.31 | bwd_microstep: 282.67 | bwd_inner_microstep: 282.66 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1903 +[2025-05-02 00:29:01,552] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.18 | bwd_microstep: 271.83 | bwd_inner_microstep: 271.81 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1883 +[2025-05-02 00:29:02,023] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 185.76 | bwd_microstep: 269.79 | bwd_inner_microstep: 269.77 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 00:29:02,494] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 185.53 | bwd_microstep: 269.58 | bwd_inner_microstep: 269.57 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 845 +[2025-05-02 00:29:02,730] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 91.40 | bwd_microstep: 130.32 | bwd_inner_microstep: 130.17 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 00:29:03,198] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 184.51 | bwd_microstep: 268.97 | bwd_inner_microstep: 268.95 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 00:29:03,668] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 185.18 | bwd_microstep: 268.83 | bwd_inner_microstep: 268.81 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 00:29:04,138] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 185.22 | bwd_microstep: 269.34 | bwd_inner_microstep: 269.33 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1349 +[2025-05-02 00:29:04,494] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 138.06 | bwd_microstep: 203.43 | bwd_inner_microstep: 203.36 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1345 +[2025-05-02 00:29:04,850] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 137.80 | bwd_microstep: 202.92 | bwd_inner_microstep: 202.77 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 00:29:05,318] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 184.46 | bwd_microstep: 268.87 | bwd_inner_microstep: 268.85 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 00:29:05,787] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 185.15 | bwd_microstep: 267.80 | bwd_inner_microstep: 267.78 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 00:29:06,256] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 184.80 | bwd_microstep: 268.03 | bwd_inner_microstep: 268.02 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 00:29:06,730] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 185.73 | bwd_microstep: 268.04 | bwd_inner_microstep: 268.02 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.17 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 00:29:07,202] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 184.97 | bwd_microstep: 267.99 | bwd_inner_microstep: 267.97 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1897 +[2025-05-02 00:29:07,783] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.09 | optimizer_step: 16.49 +[2025-05-02 00:29:07,784] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.43 | bwd_microstep: 351.15 | bwd_inner_microstep: 273.01 | bwd_allreduce_microstep: 78.09 | step_microstep: 24.19 +[2025-05-02 00:29:07,785] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2784.19 | bwd: 4129.62 | bwd_inner: 4050.89 | bwd_allreduce: 78.35 | step: 25.10 + 10%|▉ | 834/8720 [2:13:41<49:33:21, 22.62s/it] {'loss': 0.8161, 'grad_norm': 6.224848747253418, 'learning_rate': 9.887575184576848e-06, 'epoch': 0.96} + 10%|▉ | 834/8720 [2:13:41<49:33:21, 22.62s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1901 +[2025-05-02 00:29:08,267] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.58 | bwd_microstep: 271.87 | bwd_inner_microstep: 271.85 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 358 +[2025-05-02 00:29:08,476] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 76.13 | bwd_microstep: 118.02 | bwd_inner_microstep: 117.69 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-02 00:29:08,951] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.96 | bwd_microstep: 271.93 | bwd_inner_microstep: 271.91 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-02 00:29:09,426] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.89 | bwd_microstep: 271.89 | bwd_inner_microstep: 271.87 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1361 +[2025-05-02 00:29:09,786] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.17 | bwd_microstep: 205.22 | bwd_inner_microstep: 205.06 | bwd_allreduce_microstep: 0.08 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-02 00:29:10,262] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.46 | bwd_microstep: 272.54 | bwd_inner_microstep: 272.53 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1359 +[2025-05-02 00:29:10,621] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.57 | bwd_microstep: 204.61 | bwd_inner_microstep: 204.56 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 00:29:11,093] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.27 | bwd_microstep: 270.49 | bwd_inner_microstep: 270.47 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 838 +[2025-05-02 00:29:11,322] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 89.63 | bwd_microstep: 125.08 | bwd_inner_microstep: 124.94 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.12 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 332 +[2025-05-02 00:29:11,523] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 71.40 | bwd_microstep: 116.06 | bwd_inner_microstep: 115.93 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 00:29:11,997] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.58 | bwd_microstep: 271.19 | bwd_inner_microstep: 271.18 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 00:29:12,473] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.23 | bwd_microstep: 271.59 | bwd_inner_microstep: 271.58 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 832 +[2025-05-02 00:29:12,713] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.84 | bwd_microstep: 129.70 | bwd_inner_microstep: 129.40 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1086 +[2025-05-02 00:29:13,001] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 113.38 | bwd_microstep: 158.69 | bwd_inner_microstep: 158.58 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1893 +[2025-05-02 00:29:13,479] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.12 | bwd_microstep: 272.74 | bwd_inner_microstep: 272.73 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-02 00:29:14,062] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.15 | optimizer_step: 16.69 +[2025-05-02 00:29:14,063] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.54 | bwd_microstep: 353.88 | bwd_inner_microstep: 272.07 | bwd_allreduce_microstep: 81.74 | step_microstep: 24.64 +[2025-05-02 00:29:14,064] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2412.44 | bwd: 3585.61 | bwd_inner: 3502.51 | bwd_allreduce: 82.34 | step: 25.67 + 10%|▉ | 835/8720 [2:13:47<38:48:39, 17.72s/it] {'loss': 1.4562, 'grad_norm': 6.397011756896973, 'learning_rate': 9.887183233455927e-06, 'epoch': 0.96} + 10%|▉ | 835/8720 [2:13:47<38:48:39, 17.72s/it]dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 928 +[2025-05-02 00:29:14,335] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 103.17 | bwd_microstep: 144.61 | bwd_inner_microstep: 144.46 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 388 +[2025-05-02 00:29:14,550] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 84.77 | bwd_microstep: 115.06 | bwd_inner_microstep: 114.80 | bwd_allreduce_microstep: 0.08 | step_microstep: 0.10 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 899 +[2025-05-02 00:29:14,812] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 100.88 | bwd_microstep: 143.20 | bwd_inner_microstep: 143.17 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1893 +[2025-05-02 00:29:15,293] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.17 | bwd_microstep: 273.49 | bwd_inner_microstep: 273.47 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1893 +[2025-05-02 00:29:15,773] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.69 | bwd_microstep: 273.72 | bwd_inner_microstep: 273.70 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1105 +[2025-05-02 00:29:16,065] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 114.81 | bwd_microstep: 160.85 | bwd_inner_microstep: 160.77 | bwd_allreduce_microstep: 0.03 | step_microstep: 0.09 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1356 +[2025-05-02 00:29:16,424] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 139.39 | bwd_microstep: 205.09 | bwd_inner_microstep: 205.07 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 00:29:16,899] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.33 | bwd_microstep: 271.73 | bwd_inner_microstep: 271.71 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 00:29:17,374] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.41 | bwd_microstep: 270.01 | bwd_inner_microstep: 270.00 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 00:29:17,847] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.92 | bwd_microstep: 270.50 | bwd_inner_microstep: 270.48 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1094 +[2025-05-02 00:29:18,134] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 113.11 | bwd_microstep: 159.44 | bwd_inner_microstep: 159.42 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 326 +[2025-05-02 00:29:18,340] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 71.69 | bwd_microstep: 120.04 | bwd_inner_microstep: 119.90 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.09 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1343 +[2025-05-02 00:29:18,699] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 139.34 | bwd_microstep: 203.62 | bwd_inner_microstep: 203.45 | bwd_allreduce_microstep: 0.10 | step_microstep: 0.09 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 319 +[2025-05-02 00:29:18,915] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 81.94 | bwd_microstep: 120.11 | bwd_inner_microstep: 119.81 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 00:29:19,389] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.32 | bwd_microstep: 269.91 | bwd_inner_microstep: 269.89 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 319 +[2025-05-02 00:29:19,732] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.14 | optimizer_step: 16.66 +[2025-05-02 00:29:19,732] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 88.52 | bwd_microstep: 214.72 | bwd_inner_microstep: 136.59 | bwd_allreduce_microstep: 77.97 | step_microstep: 24.63 +[2025-05-02 00:29:19,734] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2164.13 | bwd: 3216.20 | bwd_inner: 3136.93 | bwd_allreduce: 78.48 | step: 25.84 + 10%|▉ | 836/8720 [2:13:53<30:53:20, 14.10s/it] {'loss': 1.0675, 'grad_norm': 6.479496479034424, 'learning_rate': 9.886790608081832e-06, 'epoch': 0.96} + 10%|▉ | 836/8720 [2:13:53<30:53:20, 14.10s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1923 +[2025-05-02 00:29:20,236] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 194.33 | bwd_microstep: 284.22 | bwd_inner_microstep: 284.21 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 899 +[2025-05-02 00:29:20,495] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 100.45 | bwd_microstep: 142.97 | bwd_inner_microstep: 142.95 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 00:29:20,971] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.64 | bwd_microstep: 272.06 | bwd_inner_microstep: 272.05 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 00:29:21,445] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.61 | bwd_microstep: 271.34 | bwd_inner_microstep: 271.33 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 00:29:21,917] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.21 | bwd_microstep: 270.83 | bwd_inner_microstep: 270.81 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 00:29:22,403] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.36 | bwd_microstep: 271.08 | bwd_inner_microstep: 271.06 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 00:29:22,877] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.28 | bwd_microstep: 270.94 | bwd_inner_microstep: 270.92 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 00:29:23,354] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.26 | bwd_microstep: 271.24 | bwd_inner_microstep: 271.22 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 00:29:23,829] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.12 | bwd_microstep: 271.30 | bwd_inner_microstep: 271.28 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 00:29:24,302] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.23 | bwd_microstep: 270.92 | bwd_inner_microstep: 270.91 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 00:29:24,776] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.37 | bwd_microstep: 270.62 | bwd_inner_microstep: 270.61 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 00:29:25,255] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.21 | bwd_microstep: 271.24 | bwd_inner_microstep: 271.22 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 00:29:25,735] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.26 | bwd_microstep: 271.11 | bwd_inner_microstep: 271.09 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 00:29:26,210] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.15 | bwd_microstep: 269.91 | bwd_inner_microstep: 269.90 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 00:29:26,685] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.06 | bwd_microstep: 269.97 | bwd_inner_microstep: 269.95 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1890 +[2025-05-02 00:29:27,276] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.15 | optimizer_step: 16.65 +[2025-05-02 00:29:27,277] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.06 | bwd_microstep: 358.01 | bwd_inner_microstep: 273.93 | bwd_allreduce_microstep: 84.03 | step_microstep: 24.54 +[2025-05-02 00:29:27,278] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2912.24 | bwd: 4307.79 | bwd_inner: 4223.44 | bwd_allreduce: 84.12 | step: 25.43 + 10%|▉ | 837/8720 [2:14:01<26:34:32, 12.14s/it] {'loss': 1.1759, 'grad_norm': 7.516662120819092, 'learning_rate': 9.886397308508726e-06, 'epoch': 0.96} + 10%|▉ | 837/8720 [2:14:01<26:34:32, 12.14s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 352 +[2025-05-02 00:29:27,504] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 83.49 | bwd_microstep: 120.47 | bwd_inner_microstep: 120.14 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.19 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 347 +[2025-05-02 00:29:27,723] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 84.23 | bwd_microstep: 118.23 | bwd_inner_microstep: 117.89 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.18 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 848 +[2025-05-02 00:29:27,967] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.00 | bwd_microstep: 132.59 | bwd_inner_microstep: 132.42 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 00:29:28,445] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.24 | bwd_microstep: 271.90 | bwd_inner_microstep: 271.88 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 00:29:28,922] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.46 | bwd_microstep: 271.83 | bwd_inner_microstep: 271.81 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 00:29:29,398] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.87 | bwd_microstep: 271.63 | bwd_inner_microstep: 271.61 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 00:29:29,875] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.72 | bwd_microstep: 271.57 | bwd_inner_microstep: 271.55 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 00:29:30,353] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.99 | bwd_microstep: 271.62 | bwd_inner_microstep: 271.61 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 00:29:30,846] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.26 | bwd_microstep: 286.22 | bwd_inner_microstep: 286.20 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 00:29:31,323] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.75 | bwd_microstep: 271.52 | bwd_inner_microstep: 271.50 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 00:29:31,804] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.59 | bwd_microstep: 272.56 | bwd_inner_microstep: 272.49 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 00:29:32,288] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.15 | bwd_microstep: 274.58 | bwd_inner_microstep: 274.49 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.05 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 835 +[2025-05-02 00:29:32,544] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 96.16 | bwd_microstep: 142.52 | bwd_inner_microstep: 142.47 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1850 +[2025-05-02 00:29:33,076] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 212.75 | bwd_microstep: 300.91 | bwd_inner_microstep: 300.89 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1923 +[2025-05-02 00:29:33,577] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 193.92 | bwd_microstep: 286.81 | bwd_inner_microstep: 286.79 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1352 +[2025-05-02 00:29:34,086] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.14 | optimizer_step: 16.81 +[2025-05-02 00:29:34,087] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 139.48 | bwd_microstep: 323.56 | bwd_inner_microstep: 222.29 | bwd_allreduce_microstep: 101.12 | step_microstep: 26.19 +[2025-05-02 00:29:34,088] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2593.74 | bwd: 3888.62 | bwd_inner: 3786.27 | bwd_allreduce: 101.49 | step: 27.54 + 10%|▉ | 838/8720 [2:14:07<23:04:24, 10.54s/it] {'loss': 0.4769, 'grad_norm': 3.9669010639190674, 'learning_rate': 9.886003334790875e-06, 'epoch': 0.96} + 10%|▉ | 838/8720 [2:14:07<23:04:24, 10.54s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1953 +[2025-05-02 00:29:35,583] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 453.39 | bwd_microstep: 1018.03 | bwd_inner_microstep: 1018.01 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1893 +[2025-05-02 00:29:37,853] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 602.73 | bwd_microstep: 1600.64 | bwd_inner_microstep: 1600.62 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1891 +[2025-05-02 00:29:40,386] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 922.08 | bwd_microstep: 1593.20 | bwd_inner_microstep: 1593.18 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 00:29:43,218] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 923.63 | bwd_microstep: 1598.79 | bwd_inner_microstep: 1598.77 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-02 00:29:45,840] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1152.63 | bwd_microstep: 1452.49 | bwd_inner_microstep: 1452.47 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 00:29:48,372] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1118.71 | bwd_microstep: 1397.38 | bwd_inner_microstep: 1397.36 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-02 00:29:50,901] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1207.21 | bwd_microstep: 1306.48 | bwd_inner_microstep: 1306.46 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 00:29:53,781] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 870.96 | bwd_microstep: 1651.30 | bwd_inner_microstep: 1651.29 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 00:29:56,305] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1111.12 | bwd_microstep: 1397.06 | bwd_inner_microstep: 1397.05 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.15 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 334 +[2025-05-02 00:29:57,130] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 501.45 | bwd_microstep: 170.57 | bwd_inner_microstep: 170.32 | bwd_allreduce_microstep: 0.10 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 00:29:59,655] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1207.98 | bwd_microstep: 1302.80 | bwd_inner_microstep: 1302.78 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 00:30:02,537] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 869.59 | bwd_microstep: 1651.37 | bwd_inner_microstep: 1651.35 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.13 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 00:30:05,059] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1110.91 | bwd_microstep: 1395.48 | bwd_inner_microstep: 1395.46 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 00:30:07,889] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 923.41 | bwd_microstep: 1596.49 | bwd_inner_microstep: 1596.48 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 00:30:10,414] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1063.11 | bwd_microstep: 1444.75 | bwd_inner_microstep: 1444.73 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2068 +[2025-05-02 00:30:12,434] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.05 | optimizer_step: 16.51 +[2025-05-02 00:30:12,435] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 934.16 | bwd_microstep: 753.14 | bwd_inner_microstep: 686.94 | bwd_allreduce_microstep: 66.15 | step_microstep: 23.47 +[2025-05-02 00:30:12,436] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 14972.84 | bwd: 21330.00 | bwd_inner: 21263.35 | bwd_allreduce: 66.30 | step: 24.80 + 10%|▉ | 839/8720 [2:14:46<41:19:59, 18.88s/it] {'loss': 0.9344, 'grad_norm': 7.38561487197876, 'learning_rate': 9.885608686982629e-06, 'epoch': 0.96} + 10%|▉ | 839/8720 [2:14:46<41:19:59, 18.88s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 377 +[2025-05-02 00:30:12,641] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 67.91 | bwd_microstep: 118.70 | bwd_inner_microstep: 118.48 | bwd_allreduce_microstep: 0.09 | step_microstep: 0.11 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1131 +[2025-05-02 00:30:12,936] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 117.98 | bwd_microstep: 162.66 | bwd_inner_microstep: 162.50 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1883 +[2025-05-02 00:30:13,411] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.93 | bwd_microstep: 272.28 | bwd_inner_microstep: 272.27 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-02 00:30:13,886] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.73 | bwd_microstep: 273.26 | bwd_inner_microstep: 273.25 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1359 +[2025-05-02 00:30:14,246] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 139.82 | bwd_microstep: 204.29 | bwd_inner_microstep: 204.12 | bwd_allreduce_microstep: 0.08 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 00:30:14,718] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 184.92 | bwd_microstep: 270.11 | bwd_inner_microstep: 270.09 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 00:30:15,194] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.60 | bwd_microstep: 270.05 | bwd_inner_microstep: 270.04 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 00:30:15,668] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.16 | bwd_microstep: 269.60 | bwd_inner_microstep: 269.59 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 00:30:16,143] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 185.99 | bwd_microstep: 270.02 | bwd_inner_microstep: 270.00 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 00:30:16,618] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.11 | bwd_microstep: 270.15 | bwd_inner_microstep: 270.14 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 00:30:17,094] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.63 | bwd_microstep: 270.11 | bwd_inner_microstep: 270.10 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 00:30:17,566] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 185.81 | bwd_microstep: 268.60 | bwd_inner_microstep: 268.59 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 00:30:18,039] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 185.40 | bwd_microstep: 270.19 | bwd_inner_microstep: 270.17 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 00:30:18,510] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 185.56 | bwd_microstep: 268.64 | bwd_inner_microstep: 268.62 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 00:30:18,979] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 185.21 | bwd_microstep: 268.47 | bwd_inner_microstep: 268.45 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 00:30:19,539] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.07 | optimizer_step: 16.53 +[2025-05-02 00:30:19,540] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 185.86 | bwd_microstep: 336.02 | bwd_inner_microstep: 269.33 | bwd_allreduce_microstep: 66.64 | step_microstep: 23.44 +[2025-05-02 00:30:19,541] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2743.33 | bwd: 4063.27 | bwd_inner: 3995.76 | bwd_allreduce: 67.02 | step: 24.54 + 10%|▉ | 840/8720 [2:14:53<33:35:41, 15.35s/it] {'loss': 0.942, 'grad_norm': 8.775407791137695, 'learning_rate': 9.885213365138438e-06, 'epoch': 0.96} + 10%|▉ | 840/8720 [2:14:53<33:35:41, 15.35s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1920 +[2025-05-02 00:30:20,023] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.50 | bwd_microstep: 274.06 | bwd_inner_microstep: 274.04 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1896 +[2025-05-02 00:30:20,500] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.19 | bwd_microstep: 273.63 | bwd_inner_microstep: 273.61 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-02 00:30:20,976] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.43 | bwd_microstep: 272.13 | bwd_inner_microstep: 272.11 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-02 00:30:21,455] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.81 | bwd_microstep: 272.37 | bwd_inner_microstep: 272.35 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 00:30:21,934] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.46 | bwd_microstep: 271.51 | bwd_inner_microstep: 271.49 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 847 +[2025-05-02 00:30:22,183] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 97.58 | bwd_microstep: 131.39 | bwd_inner_microstep: 131.12 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 845 +[2025-05-02 00:30:22,425] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.10 | bwd_microstep: 131.25 | bwd_inner_microstep: 131.08 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 00:30:22,901] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.80 | bwd_microstep: 271.30 | bwd_inner_microstep: 271.28 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 00:30:23,378] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.66 | bwd_microstep: 271.33 | bwd_inner_microstep: 271.31 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 00:30:23,853] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.88 | bwd_microstep: 270.26 | bwd_inner_microstep: 270.24 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 00:30:24,329] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.76 | bwd_microstep: 269.87 | bwd_inner_microstep: 269.85 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 00:30:24,804] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.40 | bwd_microstep: 270.25 | bwd_inner_microstep: 270.23 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 00:30:25,277] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 185.65 | bwd_microstep: 270.24 | bwd_inner_microstep: 270.22 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 00:30:25,750] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.76 | bwd_microstep: 269.25 | bwd_inner_microstep: 269.23 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 00:30:26,220] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 185.77 | bwd_microstep: 269.05 | bwd_inner_microstep: 269.03 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 00:30:26,782] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.06 | optimizer_step: 16.54 +[2025-05-02 00:30:26,783] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.18 | bwd_microstep: 336.76 | bwd_inner_microstep: 269.82 | bwd_allreduce_microstep: 66.89 | step_microstep: 23.48 +[2025-05-02 00:30:26,784] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2816.58 | bwd: 4124.67 | bwd_inner: 4057.07 | bwd_allreduce: 67.14 | step: 24.29 + 10%|▉ | 841/8720 [2:15:00<28:16:08, 12.92s/it] {'loss': 0.8282, 'grad_norm': 6.692353248596191, 'learning_rate': 9.88481736931284e-06, 'epoch': 0.96} + 10%|▉ | 841/8720 [2:15:00<28:16:08, 12.92s/it]dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 962 +[2025-05-02 00:30:27,055] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 103.74 | bwd_microstep: 148.86 | bwd_inner_microstep: 148.54 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.20 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1436 +[2025-05-02 00:30:27,427] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 143.98 | bwd_microstep: 213.17 | bwd_inner_microstep: 213.05 | bwd_allreduce_microstep: 0.04 | step_microstep: 0.09 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 354 +[2025-05-02 00:30:27,655] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 88.93 | bwd_microstep: 126.14 | bwd_inner_microstep: 125.94 | bwd_allreduce_microstep: 0.08 | step_microstep: 0.12 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1364 +[2025-05-02 00:30:28,024] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.17 | bwd_microstep: 205.63 | bwd_inner_microstep: 205.51 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 00:30:28,496] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 185.85 | bwd_microstep: 271.08 | bwd_inner_microstep: 271.06 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 00:30:28,972] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.25 | bwd_microstep: 271.38 | bwd_inner_microstep: 271.37 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-02 00:30:29,452] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.21 | bwd_microstep: 271.59 | bwd_inner_microstep: 271.58 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 00:30:29,927] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.09 | bwd_microstep: 271.16 | bwd_inner_microstep: 271.14 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 00:30:30,401] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.07 | bwd_microstep: 270.75 | bwd_inner_microstep: 270.73 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 00:30:30,877] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.18 | bwd_microstep: 270.94 | bwd_inner_microstep: 270.92 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 00:30:31,356] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.05 | bwd_microstep: 269.91 | bwd_inner_microstep: 269.89 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 00:30:31,835] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.32 | bwd_microstep: 269.73 | bwd_inner_microstep: 269.71 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.16 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 00:30:32,311] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.32 | bwd_microstep: 269.76 | bwd_inner_microstep: 269.75 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 00:30:32,790] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.02 | bwd_microstep: 269.60 | bwd_inner_microstep: 269.58 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 00:30:33,269] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.57 | bwd_microstep: 269.58 | bwd_inner_microstep: 269.56 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1938 +[2025-05-02 00:30:33,870] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.07 | optimizer_step: 16.45 +[2025-05-02 00:30:33,871] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.07 | bwd_microstep: 363.91 | bwd_inner_microstep: 287.44 | bwd_allreduce_microstep: 76.41 | step_microstep: 24.02 +[2025-05-02 00:30:33,872] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2724.42 | bwd: 4033.27 | bwd_inner: 3955.87 | bwd_allreduce: 76.82 | step: 25.56 + 10%|▉ | 842/8720 [2:15:07<24:26:26, 11.17s/it] {'loss': 0.9288, 'grad_norm': 10.625840187072754, 'learning_rate': 9.88442069956047e-06, 'epoch': 0.97} + 10%|▉ | 842/8720 [2:15:07<24:26:26, 11.17s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1899 +[2025-05-02 00:30:34,357] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.67 | bwd_microstep: 272.99 | bwd_inner_microstep: 272.97 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1367 +[2025-05-02 00:30:34,721] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.40 | bwd_microstep: 206.02 | bwd_inner_microstep: 205.96 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 00:30:35,197] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.17 | bwd_microstep: 271.45 | bwd_inner_microstep: 271.43 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 00:30:35,674] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.54 | bwd_microstep: 271.84 | bwd_inner_microstep: 271.82 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1360 +[2025-05-02 00:30:36,039] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.70 | bwd_microstep: 205.72 | bwd_inner_microstep: 205.57 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 00:30:36,516] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.95 | bwd_microstep: 271.70 | bwd_inner_microstep: 271.68 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-02 00:30:36,995] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.39 | bwd_microstep: 272.05 | bwd_inner_microstep: 272.03 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 00:30:37,474] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.46 | bwd_microstep: 271.56 | bwd_inner_microstep: 271.54 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 00:30:37,965] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.30 | bwd_microstep: 284.60 | bwd_inner_microstep: 284.58 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 00:30:38,445] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.75 | bwd_microstep: 271.54 | bwd_inner_microstep: 271.52 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 00:30:38,924] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.65 | bwd_microstep: 272.25 | bwd_inner_microstep: 272.24 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 319 +[2025-05-02 00:30:39,160] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 90.69 | bwd_microstep: 127.55 | bwd_inner_microstep: 127.22 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 00:30:39,668] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.23 | bwd_microstep: 299.99 | bwd_inner_microstep: 299.92 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 319 +[2025-05-02 00:30:39,924] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.27 | bwd_microstep: 141.65 | bwd_inner_microstep: 141.52 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 00:30:40,400] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.07 | bwd_microstep: 272.49 | bwd_inner_microstep: 272.47 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1928 +[2025-05-02 00:30:41,196] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.12 | optimizer_step: 16.71 +[2025-05-02 00:30:41,197] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 196.66 | bwd_microstep: 455.53 | bwd_inner_microstep: 372.12 | bwd_allreduce_microstep: 83.35 | step_microstep: 123.92 +[2025-05-02 00:30:41,198] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2725.52 | bwd: 4168.97 | bwd_inner: 4084.68 | bwd_allreduce: 83.71 | step: 124.89 + 10%|▉ | 843/8720 [2:15:14<21:54:55, 10.02s/it] {'loss': 0.9473, 'grad_norm': 9.041279792785645, 'learning_rate': 9.884023355936052e-06, 'epoch': 0.97} + 10%|▉ | 843/8720 [2:15:14<21:54:55, 10.02s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1927 +[2025-05-02 00:30:42,797] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 775.52 | bwd_microstep: 799.58 | bwd_inner_microstep: 799.56 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1883 +[2025-05-02 00:30:45,532] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 872.04 | bwd_microstep: 1655.93 | bwd_inner_microstep: 1655.91 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 342 +[2025-05-02 00:30:46,374] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 655.63 | bwd_microstep: 173.14 | bwd_inner_microstep: 172.83 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 00:30:49,250] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1208.46 | bwd_microstep: 1652.24 | bwd_inner_microstep: 1652.22 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 00:30:51,791] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 875.85 | bwd_microstep: 1647.21 | bwd_inner_microstep: 1647.19 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 00:30:54,623] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 926.05 | bwd_microstep: 1596.61 | bwd_inner_microstep: 1596.59 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 00:30:57,453] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1218.25 | bwd_microstep: 1595.28 | bwd_inner_microstep: 1595.27 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 00:30:59,979] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 969.12 | bwd_microstep: 1540.94 | bwd_inner_microstep: 1540.93 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 00:31:02,609] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1117.57 | bwd_microstep: 1400.77 | bwd_inner_microstep: 1400.75 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 00:31:03,233] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 338.99 | bwd_microstep: 269.37 | bwd_inner_microstep: 269.35 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 00:31:03,704] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 185.94 | bwd_microstep: 268.97 | bwd_inner_microstep: 268.95 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 00:31:04,177] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.03 | bwd_microstep: 269.49 | bwd_inner_microstep: 269.47 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 00:31:04,650] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.11 | bwd_microstep: 271.57 | bwd_inner_microstep: 271.55 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 00:31:05,121] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 185.96 | bwd_microstep: 269.15 | bwd_inner_microstep: 269.13 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 00:31:05,594] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.87 | bwd_microstep: 269.39 | bwd_inner_microstep: 269.37 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.16 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1849 +[2025-05-02 00:31:06,154] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.08 | optimizer_step: 16.57 +[2025-05-02 00:31:06,154] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 185.69 | bwd_microstep: 336.30 | bwd_inner_microstep: 269.32 | bwd_allreduce_microstep: 66.94 | step_microstep: 23.69 +[2025-05-02 00:31:06,156] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 10074.80 | bwd: 14015.97 | bwd_inner: 13948.47 | bwd_allreduce: 67.14 | step: 24.72 + 10%|▉ | 844/8720 [2:15:39<31:43:04, 14.50s/it] {'loss': 0.7225, 'grad_norm': 7.092741966247559, 'learning_rate': 9.883625338494406e-06, 'epoch': 0.97} + 10%|▉ | 844/8720 [2:15:39<31:43:04, 14.50s/it]dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1120 +[2025-05-02 00:31:06,453] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 116.83 | bwd_microstep: 161.24 | bwd_inner_microstep: 160.93 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 856 +[2025-05-02 00:31:06,691] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 91.95 | bwd_microstep: 131.56 | bwd_inner_microstep: 131.53 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 00:31:07,163] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.00 | bwd_microstep: 271.15 | bwd_inner_microstep: 271.13 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-02 00:31:07,636] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.15 | bwd_microstep: 270.70 | bwd_inner_microstep: 270.69 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.17 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 840 +[2025-05-02 00:31:07,865] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 89.76 | bwd_microstep: 125.04 | bwd_inner_microstep: 125.02 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 00:31:08,337] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.38 | bwd_microstep: 270.24 | bwd_inner_microstep: 270.22 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 326 +[2025-05-02 00:31:08,541] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 73.61 | bwd_microstep: 118.00 | bwd_inner_microstep: 117.85 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 00:31:09,014] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.91 | bwd_microstep: 271.03 | bwd_inner_microstep: 271.01 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 00:31:09,486] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.50 | bwd_microstep: 270.43 | bwd_inner_microstep: 270.41 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 00:31:09,961] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.85 | bwd_microstep: 271.50 | bwd_inner_microstep: 271.48 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 00:31:10,436] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.99 | bwd_microstep: 271.01 | bwd_inner_microstep: 270.99 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 00:31:10,913] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.30 | bwd_microstep: 271.21 | bwd_inner_microstep: 271.20 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 00:31:11,391] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.00 | bwd_microstep: 270.29 | bwd_inner_microstep: 270.27 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1341 +[2025-05-02 00:31:11,750] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 139.17 | bwd_microstep: 203.72 | bwd_inner_microstep: 203.71 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 316 +[2025-05-02 00:31:11,987] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 90.61 | bwd_microstep: 129.91 | bwd_inner_microstep: 129.67 | bwd_allreduce_microstep: 0.10 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 00:31:12,561] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.08 | optimizer_step: 16.49 +[2025-05-02 00:31:12,561] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.41 | bwd_microstep: 346.64 | bwd_inner_microstep: 270.57 | bwd_allreduce_microstep: 76.02 | step_microstep: 24.17 +[2025-05-02 00:31:12,563] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2471.11 | bwd: 3653.74 | bwd_inner: 3576.81 | bwd_allreduce: 76.34 | step: 25.30 + 10%|▉ | 845/8720 [2:15:46<26:24:18, 12.07s/it] {'loss': 0.7476, 'grad_norm': 7.17338228225708, 'learning_rate': 9.883226647290445e-06, 'epoch': 0.97} + 10%|▉ | 845/8720 [2:15:46<26:24:18, 12.07s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1904 +[2025-05-02 00:31:13,047] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.13 | bwd_microstep: 273.92 | bwd_inner_microstep: 273.90 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1887 +[2025-05-02 00:31:13,523] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.09 | bwd_microstep: 273.12 | bwd_inner_microstep: 273.10 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1888 +[2025-05-02 00:31:14,001] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.84 | bwd_microstep: 273.74 | bwd_inner_microstep: 273.72 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 351 +[2025-05-02 00:31:14,209] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 73.89 | bwd_microstep: 121.36 | bwd_inner_microstep: 121.23 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 00:31:14,685] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.67 | bwd_microstep: 272.24 | bwd_inner_microstep: 272.23 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 350 +[2025-05-02 00:31:14,897] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 79.25 | bwd_microstep: 120.47 | bwd_inner_microstep: 120.24 | bwd_allreduce_microstep: 0.09 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 00:31:15,373] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.39 | bwd_microstep: 271.93 | bwd_inner_microstep: 271.91 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 00:31:15,852] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.74 | bwd_microstep: 271.66 | bwd_inner_microstep: 271.64 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 00:31:16,331] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.69 | bwd_microstep: 271.58 | bwd_inner_microstep: 271.56 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 00:31:16,808] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.48 | bwd_microstep: 271.36 | bwd_inner_microstep: 271.34 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1346 +[2025-05-02 00:31:17,171] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 139.86 | bwd_microstep: 204.87 | bwd_inner_microstep: 204.85 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 00:31:17,647] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.12 | bwd_microstep: 271.37 | bwd_inner_microstep: 271.35 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 00:31:18,121] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.50 | bwd_microstep: 270.20 | bwd_inner_microstep: 270.18 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1340 +[2025-05-02 00:31:18,483] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 139.87 | bwd_microstep: 203.72 | bwd_inner_microstep: 203.71 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 00:31:18,957] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.91 | bwd_microstep: 270.04 | bwd_inner_microstep: 270.02 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 00:31:19,536] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.07 | optimizer_step: 16.54 +[2025-05-02 00:31:19,536] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.76 | bwd_microstep: 347.38 | bwd_inner_microstep: 270.80 | bwd_allreduce_microstep: 76.52 | step_microstep: 24.20 +[2025-05-02 00:31:19,538] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2682.84 | bwd: 3988.98 | bwd_inner: 3911.87 | bwd_allreduce: 76.71 | step: 25.14 + 10%|▉ | 846/8720 [2:15:53<23:03:29, 10.54s/it] {'loss': 0.7169, 'grad_norm': 5.0373640060424805, 'learning_rate': 9.88282728237917e-06, 'epoch': 0.97} + 10%|▉ | 846/8720 [2:15:53<23:03:29, 10.54s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1934 +[2025-05-02 00:31:20,041] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 194.54 | bwd_microstep: 286.00 | bwd_inner_microstep: 285.98 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.16 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1887 +[2025-05-02 00:31:20,521] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.97 | bwd_microstep: 273.03 | bwd_inner_microstep: 273.01 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 00:31:20,998] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.15 | bwd_microstep: 271.53 | bwd_inner_microstep: 271.51 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-02 00:31:21,478] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.82 | bwd_microstep: 272.56 | bwd_inner_microstep: 272.55 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 00:31:21,957] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.89 | bwd_microstep: 271.74 | bwd_inner_microstep: 271.72 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1371 +[2025-05-02 00:31:22,325] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.30 | bwd_microstep: 206.73 | bwd_inner_microstep: 206.71 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 00:31:22,800] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.58 | bwd_microstep: 271.62 | bwd_inner_microstep: 271.60 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 00:31:23,277] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.93 | bwd_microstep: 271.65 | bwd_inner_microstep: 271.63 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 326 +[2025-05-02 00:31:23,485] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 75.02 | bwd_microstep: 117.37 | bwd_inner_microstep: 117.05 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 00:31:23,958] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.90 | bwd_microstep: 271.68 | bwd_inner_microstep: 271.66 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 00:31:24,434] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.26 | bwd_microstep: 271.47 | bwd_inner_microstep: 271.46 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 00:31:24,907] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.56 | bwd_microstep: 270.56 | bwd_inner_microstep: 270.54 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 00:31:25,379] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.00 | bwd_microstep: 270.24 | bwd_inner_microstep: 270.22 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 00:31:25,853] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.15 | bwd_microstep: 270.62 | bwd_inner_microstep: 270.61 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1341 +[2025-05-02 00:31:26,211] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.08 | bwd_microstep: 203.55 | bwd_inner_microstep: 203.54 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1944 +[2025-05-02 00:31:26,799] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.45 | optimizer_step: 16.67 +[2025-05-02 00:31:26,799] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 194.12 | bwd_microstep: 355.03 | bwd_inner_microstep: 288.06 | bwd_allreduce_microstep: 66.93 | step_microstep: 24.13 +[2025-05-02 00:31:26,801] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2807.93 | bwd: 4155.41 | bwd_inner: 4087.93 | bwd_allreduce: 67.14 | step: 25.03 + 10%|▉ | 847/8720 [2:16:00<20:54:09, 9.56s/it] {'loss': 0.8728, 'grad_norm': 6.406965255737305, 'learning_rate': 9.882427243815684e-06, 'epoch': 0.97} + 10%|▉ | 847/8720 [2:16:00<20:54:09, 9.56s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1904 +[2025-05-02 00:31:27,283] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.63 | bwd_microstep: 274.32 | bwd_inner_microstep: 274.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1889 +[2025-05-02 00:31:27,760] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.59 | bwd_microstep: 273.99 | bwd_inner_microstep: 273.97 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1887 +[2025-05-02 00:31:28,239] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.17 | bwd_microstep: 273.98 | bwd_inner_microstep: 273.96 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1112 +[2025-05-02 00:31:28,533] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 118.85 | bwd_microstep: 161.94 | bwd_inner_microstep: 161.86 | bwd_allreduce_microstep: 0.04 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-02 00:31:29,010] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.51 | bwd_microstep: 272.79 | bwd_inner_microstep: 272.78 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-02 00:31:29,487] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.25 | bwd_microstep: 272.91 | bwd_inner_microstep: 272.90 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 00:31:29,963] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.84 | bwd_microstep: 272.57 | bwd_inner_microstep: 272.55 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.14 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 00:31:30,440] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.48 | bwd_microstep: 272.10 | bwd_inner_microstep: 272.08 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.11 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 842 +[2025-05-02 00:31:30,683] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.31 | bwd_microstep: 131.81 | bwd_inner_microstep: 131.79 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 00:31:31,161] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.50 | bwd_microstep: 272.42 | bwd_inner_microstep: 272.40 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 00:31:31,638] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.68 | bwd_microstep: 271.75 | bwd_inner_microstep: 271.73 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 00:31:32,117] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.94 | bwd_microstep: 271.84 | bwd_inner_microstep: 271.82 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 00:31:32,595] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.24 | bwd_microstep: 271.77 | bwd_inner_microstep: 271.76 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 00:31:33,072] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.17 | bwd_microstep: 270.40 | bwd_inner_microstep: 270.39 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 317 +[2025-05-02 00:31:33,300] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 90.52 | bwd_microstep: 120.84 | bwd_inner_microstep: 120.52 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 00:31:33,875] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.10 | optimizer_step: 16.64 +[2025-05-02 00:31:33,876] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.39 | bwd_microstep: 347.20 | bwd_inner_microstep: 270.87 | bwd_allreduce_microstep: 76.27 | step_microstep: 24.30 +[2025-05-02 00:31:33,877] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2748.75 | bwd: 4032.69 | bwd_inner: 3955.76 | bwd_allreduce: 76.52 | step: 25.48 + 10%|▉ | 848/8720 [2:16:07<19:16:23, 8.81s/it] {'loss': 0.8362, 'grad_norm': 8.358295440673828, 'learning_rate': 9.882026531655173e-06, 'epoch': 0.97} + 10%|▉ | 848/8720 [2:16:07<19:16:23, 8.81s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 459 +[2025-05-02 00:31:34,083] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 68.22 | bwd_microstep: 117.39 | bwd_inner_microstep: 117.08 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1982 +[2025-05-02 00:31:34,586] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.84 | bwd_microstep: 290.99 | bwd_inner_microstep: 290.98 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-02 00:31:35,061] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.38 | bwd_microstep: 272.61 | bwd_inner_microstep: 272.60 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1897 +[2025-05-02 00:31:35,540] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.97 | bwd_microstep: 273.98 | bwd_inner_microstep: 273.96 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-02 00:31:36,015] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.22 | bwd_microstep: 272.32 | bwd_inner_microstep: 272.30 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 00:31:36,491] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.96 | bwd_microstep: 271.87 | bwd_inner_microstep: 271.86 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 00:31:36,965] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.68 | bwd_microstep: 271.32 | bwd_inner_microstep: 271.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 00:31:37,441] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.39 | bwd_microstep: 271.39 | bwd_inner_microstep: 271.38 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 00:31:37,916] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.59 | bwd_microstep: 271.40 | bwd_inner_microstep: 271.38 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 00:31:38,394] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.95 | bwd_microstep: 272.17 | bwd_inner_microstep: 272.15 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 00:31:38,870] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.02 | bwd_microstep: 271.38 | bwd_inner_microstep: 271.36 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 00:31:39,350] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.32 | bwd_microstep: 271.62 | bwd_inner_microstep: 271.60 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 00:31:39,833] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.82 | bwd_microstep: 271.56 | bwd_inner_microstep: 271.54 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 00:31:40,314] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.70 | bwd_microstep: 271.63 | bwd_inner_microstep: 271.61 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 00:31:40,791] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.30 | bwd_microstep: 270.10 | bwd_inner_microstep: 270.09 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 00:31:41,369] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.10 | optimizer_step: 16.63 +[2025-05-02 00:31:41,369] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.00 | bwd_microstep: 347.98 | bwd_inner_microstep: 271.70 | bwd_allreduce_microstep: 76.22 | step_microstep: 24.21 +[2025-05-02 00:31:41,371] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2892.01 | bwd: 4289.74 | bwd_inner: 4212.95 | bwd_allreduce: 76.41 | step: 24.98 + 10%|▉ | 849/8720 [2:16:15<18:24:17, 8.42s/it] {'loss': 0.9555, 'grad_norm': 5.833810329437256, 'learning_rate': 9.881625145952924e-06, 'epoch': 0.97} + 10%|▉ | 849/8720 [2:16:15<18:24:17, 8.42s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1891 +[2025-05-02 00:31:41,856] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.95 | bwd_microstep: 273.64 | bwd_inner_microstep: 273.62 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 341 +[2025-05-02 00:31:42,063] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 78.13 | bwd_microstep: 114.07 | bwd_inner_microstep: 113.90 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-02 00:31:42,541] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.84 | bwd_microstep: 273.79 | bwd_inner_microstep: 273.77 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 00:31:43,018] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.10 | bwd_microstep: 273.99 | bwd_inner_microstep: 273.97 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 00:31:43,494] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.32 | bwd_microstep: 272.57 | bwd_inner_microstep: 272.56 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 00:31:43,972] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.31 | bwd_microstep: 273.04 | bwd_inner_microstep: 273.02 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 00:31:44,455] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.17 | bwd_microstep: 272.56 | bwd_inner_microstep: 272.54 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 00:31:44,936] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.17 | bwd_microstep: 272.90 | bwd_inner_microstep: 272.88 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 00:31:45,413] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.88 | bwd_microstep: 271.39 | bwd_inner_microstep: 271.37 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 00:31:45,893] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.46 | bwd_microstep: 271.34 | bwd_inner_microstep: 271.32 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 830 +[2025-05-02 00:31:46,156] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 111.33 | bwd_microstep: 129.78 | bwd_inner_microstep: 129.69 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 00:31:46,632] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.11 | bwd_microstep: 271.45 | bwd_inner_microstep: 271.44 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 00:31:47,109] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.74 | bwd_microstep: 271.54 | bwd_inner_microstep: 271.52 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 00:31:47,587] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.82 | bwd_microstep: 271.67 | bwd_inner_microstep: 271.65 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 00:31:48,067] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.21 | bwd_microstep: 271.59 | bwd_inner_microstep: 271.57 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1902 +[2025-05-02 00:31:48,661] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.07 | optimizer_step: 16.62 +[2025-05-02 00:31:48,661] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.24 | bwd_microstep: 357.49 | bwd_inner_microstep: 276.23 | bwd_allreduce_microstep: 81.21 | step_microstep: 24.28 +[2025-05-02 00:31:48,663] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2830.38 | bwd: 4142.84 | bwd_inner: 4061.11 | bwd_allreduce: 81.40 | step: 25.19 + 10%|▉ | 850/8720 [2:16:22<17:39:50, 8.08s/it] {'loss': 0.638, 'grad_norm': 5.2653937339782715, 'learning_rate': 9.881223086764311e-06, 'epoch': 0.97} + 10%|▉ | 850/8720 [2:16:22<17:39:50, 8.08s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1888 +[2025-05-02 00:31:49,150] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.53 | bwd_microstep: 274.33 | bwd_inner_microstep: 274.31 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1896 +[2025-05-02 00:31:49,634] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.40 | bwd_microstep: 275.57 | bwd_inner_microstep: 275.56 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1896 +[2025-05-02 00:31:50,118] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.30 | bwd_microstep: 275.35 | bwd_inner_microstep: 275.33 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 347 +[2025-05-02 00:31:50,343] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 88.69 | bwd_microstep: 119.53 | bwd_inner_microstep: 119.38 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1883 +[2025-05-02 00:31:50,824] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.89 | bwd_microstep: 274.52 | bwd_inner_microstep: 274.50 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-02 00:31:51,306] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.67 | bwd_microstep: 273.52 | bwd_inner_microstep: 273.50 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 00:31:51,788] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.06 | bwd_microstep: 273.54 | bwd_inner_microstep: 273.52 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 00:31:52,269] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.75 | bwd_microstep: 273.54 | bwd_inner_microstep: 273.53 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 00:31:52,748] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.09 | bwd_microstep: 273.30 | bwd_inner_microstep: 273.29 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 00:31:53,228] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.46 | bwd_microstep: 273.17 | bwd_inner_microstep: 273.16 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 00:31:53,709] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.55 | bwd_microstep: 273.28 | bwd_inner_microstep: 273.26 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1353 +[2025-05-02 00:31:54,074] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.64 | bwd_microstep: 206.18 | bwd_inner_microstep: 206.16 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 00:31:54,553] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.56 | bwd_microstep: 272.77 | bwd_inner_microstep: 272.75 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 00:31:55,035] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.56 | bwd_microstep: 272.58 | bwd_inner_microstep: 272.56 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 00:31:55,514] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.16 | bwd_microstep: 271.61 | bwd_inner_microstep: 271.59 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-02 00:31:56,106] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.11 | optimizer_step: 16.64 +[2025-05-02 00:31:56,107] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.30 | bwd_microstep: 360.30 | bwd_inner_microstep: 275.10 | bwd_allreduce_microstep: 85.15 | step_microstep: 24.23 +[2025-05-02 00:31:56,108] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2881.23 | bwd: 4243.11 | bwd_inner: 4157.52 | bwd_allreduce: 85.29 | step: 25.25 + 10%|▉ | 851/8720 [2:16:29<17:14:43, 7.89s/it] {'loss': 0.9015, 'grad_norm': 5.308845043182373, 'learning_rate': 9.880820354144804e-06, 'epoch': 0.98} + 10%|▉ | 851/8720 [2:16:29<17:14:43, 7.89s/it]dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 924 +[2025-05-02 00:31:56,379] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 103.24 | bwd_microstep: 145.88 | bwd_inner_microstep: 145.62 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.09 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 912 +[2025-05-02 00:31:56,643] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 103.19 | bwd_microstep: 144.64 | bwd_inner_microstep: 144.44 | bwd_allreduce_microstep: 0.08 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-02 00:31:57,123] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.67 | bwd_microstep: 274.10 | bwd_inner_microstep: 274.08 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 00:31:57,602] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.13 | bwd_microstep: 273.07 | bwd_inner_microstep: 273.05 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 6, images per sample: 6.0, dynamic token length: 1615 +[2025-05-02 00:31:58,035] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 165.74 | bwd_microstep: 246.62 | bwd_inner_microstep: 246.30 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 00:31:58,513] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.01 | bwd_microstep: 272.87 | bwd_inner_microstep: 272.85 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 00:31:58,994] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.34 | bwd_microstep: 272.77 | bwd_inner_microstep: 272.75 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1347 +[2025-05-02 00:31:59,360] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.44 | bwd_microstep: 205.43 | bwd_inner_microstep: 205.41 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 00:31:59,845] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.95 | bwd_microstep: 272.92 | bwd_inner_microstep: 272.91 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.16 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 00:32:00,324] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.41 | bwd_microstep: 272.55 | bwd_inner_microstep: 272.53 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 00:32:00,804] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.49 | bwd_microstep: 272.69 | bwd_inner_microstep: 272.68 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 324 +[2025-05-02 00:32:01,035] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 97.43 | bwd_microstep: 116.29 | bwd_inner_microstep: 115.96 | bwd_allreduce_microstep: 0.15 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 00:32:01,513] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.33 | bwd_microstep: 272.15 | bwd_inner_microstep: 272.13 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 831 +[2025-05-02 00:32:01,759] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 97.94 | bwd_microstep: 129.81 | bwd_inner_microstep: 129.64 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 00:32:02,242] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.50 | bwd_microstep: 272.40 | bwd_inner_microstep: 272.38 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 00:32:02,825] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.11 | optimizer_step: 16.76 +[2025-05-02 00:32:02,825] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.78 | bwd_microstep: 350.38 | bwd_inner_microstep: 271.43 | bwd_allreduce_microstep: 78.89 | step_microstep: 24.62 +[2025-05-02 00:32:02,827] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2593.17 | bwd: 3794.65 | bwd_inner: 3714.39 | bwd_allreduce: 79.45 | step: 25.82 + 10%|▉ | 852/8720 [2:16:36<16:28:32, 7.54s/it] {'loss': 1.462, 'grad_norm': 10.991435050964355, 'learning_rate': 9.880416948149968e-06, 'epoch': 0.98} + 10%|▉ | 852/8720 [2:16:36<16:28:32, 7.54s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1923 +[2025-05-02 00:32:03,330] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 193.97 | bwd_microstep: 285.87 | bwd_inner_microstep: 285.85 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1894 +[2025-05-02 00:32:03,812] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.43 | bwd_microstep: 274.39 | bwd_inner_microstep: 274.38 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1105 +[2025-05-02 00:32:04,110] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 115.20 | bwd_microstep: 161.76 | bwd_inner_microstep: 161.55 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-02 00:32:04,589] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.47 | bwd_microstep: 273.70 | bwd_inner_microstep: 273.69 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 344 +[2025-05-02 00:32:04,818] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 84.07 | bwd_microstep: 128.10 | bwd_inner_microstep: 127.88 | bwd_allreduce_microstep: 0.08 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 00:32:05,296] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.25 | bwd_microstep: 272.95 | bwd_inner_microstep: 272.93 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 00:32:05,774] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.63 | bwd_microstep: 272.24 | bwd_inner_microstep: 272.22 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 00:32:06,249] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.28 | bwd_microstep: 272.44 | bwd_inner_microstep: 272.43 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 00:32:06,726] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.04 | bwd_microstep: 272.79 | bwd_inner_microstep: 272.77 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 00:32:07,206] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.79 | bwd_microstep: 272.66 | bwd_inner_microstep: 272.64 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 00:32:07,686] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.90 | bwd_microstep: 271.93 | bwd_inner_microstep: 271.91 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 00:32:08,165] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.13 | bwd_microstep: 272.29 | bwd_inner_microstep: 272.28 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 322 +[2025-05-02 00:32:08,384] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 81.92 | bwd_microstep: 120.05 | bwd_inner_microstep: 119.90 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 00:32:08,860] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.72 | bwd_microstep: 271.11 | bwd_inner_microstep: 271.09 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 00:32:09,337] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.60 | bwd_microstep: 270.98 | bwd_inner_microstep: 270.96 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 842 +[2025-05-02 00:32:09,676] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.13 | optimizer_step: 16.73 +[2025-05-02 00:32:09,676] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.48 | bwd_microstep: 201.30 | bwd_inner_microstep: 135.04 | bwd_allreduce_microstep: 66.10 | step_microstep: 23.93 +[2025-05-02 00:32:09,677] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2638.55 | bwd: 3894.64 | bwd_inner: 3827.66 | bwd_allreduce: 66.41 | step: 25.07 + 10%|▉ | 853/8720 [2:16:43<16:01:17, 7.33s/it] {'loss': 0.7328, 'grad_norm': 6.711470603942871, 'learning_rate': 9.880012868835458e-06, 'epoch': 0.98} + 10%|▉ | 853/8720 [2:16:43<16:01:17, 7.33s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1982 +[2025-05-02 00:32:10,186] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 197.25 | bwd_microstep: 291.13 | bwd_inner_microstep: 291.11 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1914 +[2025-05-02 00:32:10,670] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.63 | bwd_microstep: 275.93 | bwd_inner_microstep: 275.91 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-02 00:32:11,148] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.12 | bwd_microstep: 273.48 | bwd_inner_microstep: 273.46 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.14 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-02 00:32:11,629] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.31 | bwd_microstep: 273.56 | bwd_inner_microstep: 273.54 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-02 00:32:12,111] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.26 | bwd_microstep: 273.58 | bwd_inner_microstep: 273.56 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-02 00:32:12,593] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.05 | bwd_microstep: 273.11 | bwd_inner_microstep: 273.09 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 844 +[2025-05-02 00:32:12,858] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 113.73 | bwd_microstep: 131.57 | bwd_inner_microstep: 131.26 | bwd_allreduce_microstep: 0.16 | step_microstep: 0.14 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 00:32:13,338] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.00 | bwd_microstep: 272.87 | bwd_inner_microstep: 272.85 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 00:32:13,820] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.76 | bwd_microstep: 272.62 | bwd_inner_microstep: 272.61 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 00:32:14,305] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.27 | bwd_microstep: 272.79 | bwd_inner_microstep: 272.78 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 00:32:14,785] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.12 | bwd_microstep: 272.26 | bwd_inner_microstep: 272.24 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.23 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 00:32:15,266] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.17 | bwd_microstep: 272.44 | bwd_inner_microstep: 272.42 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 00:32:15,745] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.28 | bwd_microstep: 272.11 | bwd_inner_microstep: 272.09 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 00:32:16,222] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.78 | bwd_microstep: 271.13 | bwd_inner_microstep: 271.11 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1891 +[2025-05-02 00:32:16,706] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.93 | bwd_microstep: 274.68 | bwd_inner_microstep: 274.66 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 352 +[2025-05-02 00:32:17,071] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.18 | optimizer_step: 16.81 +[2025-05-02 00:32:17,071] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 100.24 | bwd_microstep: 223.73 | bwd_inner_microstep: 133.18 | bwd_allreduce_microstep: 90.36 | step_microstep: 25.52 +[2025-05-02 00:32:17,072] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2865.49 | bwd: 4197.03 | bwd_inner: 4106.03 | bwd_allreduce: 90.53 | step: 26.80 + 10%|▉ | 854/8720 [2:16:50<16:03:40, 7.35s/it] {'loss': 1.0389, 'grad_norm': 5.207064628601074, 'learning_rate': 9.879608116257018e-06, 'epoch': 0.98} + 10%|▉ | 854/8720 [2:16:50<16:03:40, 7.35s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2067 +[2025-05-02 00:32:17,596] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 201.68 | bwd_microstep: 301.67 | bwd_inner_microstep: 301.65 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2052 +[2025-05-02 00:32:18,117] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 203.44 | bwd_microstep: 301.11 | bwd_inner_microstep: 301.09 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 396 +[2025-05-02 00:32:18,342] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 86.81 | bwd_microstep: 124.90 | bwd_inner_microstep: 124.75 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-02 00:32:18,822] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.99 | bwd_microstep: 274.72 | bwd_inner_microstep: 274.70 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1886 +[2025-05-02 00:32:19,302] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.88 | bwd_microstep: 274.53 | bwd_inner_microstep: 274.51 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1883 +[2025-05-02 00:32:19,782] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.71 | bwd_microstep: 274.45 | bwd_inner_microstep: 274.44 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 00:32:20,260] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.44 | bwd_microstep: 273.12 | bwd_inner_microstep: 273.11 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 00:32:20,738] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.41 | bwd_microstep: 272.84 | bwd_inner_microstep: 272.82 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 835 +[2025-05-02 00:32:20,982] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 102.81 | bwd_microstep: 125.60 | bwd_inner_microstep: 125.50 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 00:32:21,459] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.17 | bwd_microstep: 272.75 | bwd_inner_microstep: 272.73 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 326 +[2025-05-02 00:32:21,676] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 82.65 | bwd_microstep: 120.59 | bwd_inner_microstep: 120.44 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 00:32:22,151] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.19 | bwd_microstep: 271.38 | bwd_inner_microstep: 271.37 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 00:32:22,628] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.03 | bwd_microstep: 272.10 | bwd_inner_microstep: 272.08 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 00:32:23,102] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.56 | bwd_microstep: 271.28 | bwd_inner_microstep: 271.26 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 00:32:23,578] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.61 | bwd_microstep: 271.25 | bwd_inner_microstep: 271.24 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.21 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 00:32:24,166] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 3.03 | optimizer_step: 17.09 +[2025-05-02 00:32:24,166] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.67 | bwd_microstep: 357.09 | bwd_inner_microstep: 271.68 | bwd_allreduce_microstep: 85.36 | step_microstep: 26.71 +[2025-05-02 00:32:24,168] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2754.74 | bwd: 4059.44 | bwd_inner: 3973.43 | bwd_allreduce: 85.61 | step: 27.79 + 10%|▉ | 855/8720 [2:16:57<15:53:30, 7.27s/it] {'loss': 0.9803, 'grad_norm': 6.639869213104248, 'learning_rate': 9.879202690470493e-06, 'epoch': 0.98} + 10%|▉ | 855/8720 [2:16:57<15:53:30, 7.27s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2052 +[2025-05-02 00:32:24,690] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 201.48 | bwd_microstep: 300.65 | bwd_inner_microstep: 300.63 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1150 +[2025-05-02 00:32:24,991] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 120.75 | bwd_microstep: 165.28 | bwd_inner_microstep: 165.03 | bwd_allreduce_microstep: 0.14 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 00:32:25,468] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.37 | bwd_microstep: 272.71 | bwd_inner_microstep: 272.69 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-02 00:32:25,945] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.53 | bwd_microstep: 273.77 | bwd_inner_microstep: 273.75 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 00:32:26,422] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.64 | bwd_microstep: 272.96 | bwd_inner_microstep: 272.95 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 853 +[2025-05-02 00:32:26,670] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 100.44 | bwd_microstep: 132.79 | bwd_inner_microstep: 132.53 | bwd_allreduce_microstep: 0.14 | step_microstep: 0.10 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 327 +[2025-05-02 00:32:26,893] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 83.21 | bwd_microstep: 125.83 | bwd_inner_microstep: 125.68 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 00:32:27,369] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.40 | bwd_microstep: 272.46 | bwd_inner_microstep: 272.44 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 326 +[2025-05-02 00:32:27,591] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 82.36 | bwd_microstep: 126.34 | bwd_inner_microstep: 126.16 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 00:32:28,067] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.43 | bwd_microstep: 272.72 | bwd_inner_microstep: 272.70 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 835 +[2025-05-02 00:32:28,308] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 98.78 | bwd_microstep: 125.97 | bwd_inner_microstep: 125.70 | bwd_allreduce_microstep: 0.14 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 00:32:28,784] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.16 | bwd_microstep: 272.40 | bwd_inner_microstep: 272.38 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1344 +[2025-05-02 00:32:29,145] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.26 | bwd_microstep: 204.77 | bwd_inner_microstep: 204.58 | bwd_allreduce_microstep: 0.09 | step_microstep: 0.22 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 00:32:29,621] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.59 | bwd_microstep: 271.19 | bwd_inner_microstep: 271.17 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 00:32:30,098] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.67 | bwd_microstep: 271.36 | bwd_inner_microstep: 271.34 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1887 +[2025-05-02 00:32:30,687] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.16 | optimizer_step: 16.64 +[2025-05-02 00:32:30,687] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.16 | bwd_microstep: 359.40 | bwd_inner_microstep: 275.11 | bwd_allreduce_microstep: 84.24 | step_microstep: 25.04 +[2025-05-02 00:32:30,688] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2523.92 | bwd: 3720.75 | bwd_inner: 3634.96 | bwd_allreduce: 84.94 | step: 26.25 + 10%|▉ | 856/8720 [2:17:04<15:23:44, 7.05s/it] {'loss': 0.9834, 'grad_norm': 7.6635260581970215, 'learning_rate': 9.878796591531817e-06, 'epoch': 0.98} + 10%|▉ | 856/8720 [2:17:04<15:23:44, 7.05s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-02 00:32:31,171] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.29 | bwd_microstep: 273.69 | bwd_inner_microstep: 273.67 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 00:32:31,648] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.92 | bwd_microstep: 273.45 | bwd_inner_microstep: 273.43 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-02 00:32:32,124] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.27 | bwd_microstep: 272.94 | bwd_inner_microstep: 272.92 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 00:32:32,602] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.85 | bwd_microstep: 273.36 | bwd_inner_microstep: 273.34 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-02 00:32:33,081] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.14 | bwd_microstep: 273.96 | bwd_inner_microstep: 273.94 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.17 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1353 +[2025-05-02 00:32:33,443] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.81 | bwd_microstep: 205.90 | bwd_inner_microstep: 205.88 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 00:32:33,919] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.29 | bwd_microstep: 272.66 | bwd_inner_microstep: 272.64 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 00:32:34,396] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.04 | bwd_microstep: 272.83 | bwd_inner_microstep: 272.81 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 838 +[2025-05-02 00:32:34,633] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 96.63 | bwd_microstep: 126.20 | bwd_inner_microstep: 125.93 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 00:32:35,110] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.27 | bwd_microstep: 272.68 | bwd_inner_microstep: 272.66 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 00:32:35,589] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.15 | bwd_microstep: 272.70 | bwd_inner_microstep: 272.68 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.15 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 322 +[2025-05-02 00:32:35,835] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 109.10 | bwd_microstep: 122.15 | bwd_inner_microstep: 121.80 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 00:32:36,318] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.16 | bwd_microstep: 272.08 | bwd_inner_microstep: 272.06 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 00:32:36,798] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.89 | bwd_microstep: 272.30 | bwd_inner_microstep: 272.28 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 00:32:37,275] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.79 | bwd_microstep: 270.93 | bwd_inner_microstep: 270.91 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 1092 +[2025-05-02 00:32:37,673] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.12 | optimizer_step: 16.59 +[2025-05-02 00:32:37,673] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 111.01 | bwd_microstep: 246.18 | bwd_inner_microstep: 161.35 | bwd_allreduce_microstep: 84.72 | step_microstep: 24.90 +[2025-05-02 00:32:37,675] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2724.26 | bwd: 3974.05 | bwd_inner: 3888.44 | bwd_allreduce: 85.07 | step: 26.06 + 10%|▉ | 857/8720 [2:17:11<15:21:12, 7.03s/it] {'loss': 1.294, 'grad_norm': 11.42252254486084, 'learning_rate': 9.878389819497014e-06, 'epoch': 0.98} + 10%|▉ | 857/8720 [2:17:11<15:21:12, 7.03s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1917 +[2025-05-02 00:32:38,160] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.24 | bwd_microstep: 275.61 | bwd_inner_microstep: 275.60 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1895 +[2025-05-02 00:32:38,641] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.72 | bwd_microstep: 275.03 | bwd_inner_microstep: 275.01 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1894 +[2025-05-02 00:32:39,121] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.71 | bwd_microstep: 274.90 | bwd_inner_microstep: 274.89 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-02 00:32:39,598] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.28 | bwd_microstep: 273.59 | bwd_inner_microstep: 273.57 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-02 00:32:40,077] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.42 | bwd_microstep: 274.03 | bwd_inner_microstep: 274.01 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 00:32:40,555] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.53 | bwd_microstep: 273.30 | bwd_inner_microstep: 273.28 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 00:32:41,032] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.08 | bwd_microstep: 273.00 | bwd_inner_microstep: 272.99 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 00:32:41,510] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.55 | bwd_microstep: 272.47 | bwd_inner_microstep: 272.45 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1091 +[2025-05-02 00:32:41,800] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 115.71 | bwd_microstep: 160.87 | bwd_inner_microstep: 160.85 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 00:32:42,277] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.24 | bwd_microstep: 272.25 | bwd_inner_microstep: 272.24 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 00:32:42,755] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.91 | bwd_microstep: 272.77 | bwd_inner_microstep: 272.75 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 00:32:43,233] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.29 | bwd_microstep: 272.82 | bwd_inner_microstep: 272.80 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 00:32:43,712] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.54 | bwd_microstep: 272.61 | bwd_inner_microstep: 272.59 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1346 +[2025-05-02 00:32:44,073] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.23 | bwd_microstep: 205.86 | bwd_inner_microstep: 205.78 | bwd_allreduce_microstep: 0.03 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 00:32:44,551] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.64 | bwd_microstep: 272.86 | bwd_inner_microstep: 272.84 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 321 +[2025-05-02 00:32:44,886] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.13 | optimizer_step: 16.65 +[2025-05-02 00:32:44,887] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 81.56 | bwd_microstep: 216.47 | bwd_inner_microstep: 131.44 | bwd_allreduce_microstep: 84.86 | step_microstep: 25.08 +[2025-05-02 00:32:44,888] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2800.36 | bwd: 4138.46 | bwd_inner: 4053.15 | bwd_allreduce: 84.97 | step: 26.05 + 10%|▉ | 858/8720 [2:17:18<15:28:19, 7.08s/it] {'loss': 1.0858, 'grad_norm': 6.161701202392578, 'learning_rate': 9.877982374422205e-06, 'epoch': 0.98} + 10%|▉ | 858/8720 [2:17:18<15:28:19, 7.08s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1893 +[2025-05-02 00:32:45,373] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.49 | bwd_microstep: 274.28 | bwd_inner_microstep: 274.26 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-02 00:32:45,851] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.56 | bwd_microstep: 273.49 | bwd_inner_microstep: 273.47 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 00:32:46,329] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.87 | bwd_microstep: 272.94 | bwd_inner_microstep: 272.92 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.05 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 838 +[2025-05-02 00:32:46,565] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 96.44 | bwd_microstep: 126.17 | bwd_inner_microstep: 125.92 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 00:32:47,043] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.81 | bwd_microstep: 272.75 | bwd_inner_microstep: 272.74 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 00:32:47,520] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.35 | bwd_microstep: 272.89 | bwd_inner_microstep: 272.87 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 328 +[2025-05-02 00:32:47,738] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 82.87 | bwd_microstep: 121.99 | bwd_inner_microstep: 121.65 | bwd_allreduce_microstep: 0.14 | step_microstep: 0.09 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 842 +[2025-05-02 00:32:47,984] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 97.75 | bwd_microstep: 131.98 | bwd_inner_microstep: 131.71 | bwd_allreduce_microstep: 0.14 | step_microstep: 0.22 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 00:32:48,461] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.96 | bwd_microstep: 272.22 | bwd_inner_microstep: 272.20 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 00:32:48,936] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.97 | bwd_microstep: 271.05 | bwd_inner_microstep: 271.04 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.20 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 316 +[2025-05-02 00:32:49,148] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 81.68 | bwd_microstep: 116.71 | bwd_inner_microstep: 116.56 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 00:32:49,623] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.21 | bwd_microstep: 271.31 | bwd_inner_microstep: 271.29 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 00:32:50,097] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.98 | bwd_microstep: 270.95 | bwd_inner_microstep: 270.92 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 00:32:50,573] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.18 | bwd_microstep: 271.22 | bwd_inner_microstep: 271.20 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1342 +[2025-05-02 00:32:50,933] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.64 | bwd_microstep: 204.66 | bwd_inner_microstep: 204.50 | bwd_allreduce_microstep: 0.10 | step_microstep: 0.09 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1390 +[2025-05-02 00:32:51,410] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.16 | optimizer_step: 16.84 +[2025-05-02 00:32:51,411] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 142.95 | bwd_microstep: 293.82 | bwd_inner_microstep: 209.42 | bwd_allreduce_microstep: 84.24 | step_microstep: 25.20 +[2025-05-02 00:32:51,412] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2530.38 | bwd: 3718.55 | bwd_inner: 3632.82 | bwd_allreduce: 84.84 | step: 26.44 + 10%|▉ | 859/8720 [2:17:25<15:06:10, 6.92s/it] {'loss': 0.8009, 'grad_norm': 7.464057445526123, 'learning_rate': 9.877574256363604e-06, 'epoch': 0.99} + 10%|▉ | 859/8720 [2:17:25<15:06:10, 6.92s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2018 +[2025-05-02 00:32:51,925] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 198.12 | bwd_microstep: 295.35 | bwd_inner_microstep: 295.33 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1899 +[2025-05-02 00:32:52,405] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.55 | bwd_microstep: 275.26 | bwd_inner_microstep: 275.25 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-02 00:32:52,883] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.60 | bwd_microstep: 273.96 | bwd_inner_microstep: 273.94 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1883 +[2025-05-02 00:32:53,361] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.78 | bwd_microstep: 273.93 | bwd_inner_microstep: 273.91 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1372 +[2025-05-02 00:32:53,727] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 143.51 | bwd_microstep: 207.54 | bwd_inner_microstep: 207.52 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-02 00:32:54,207] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.34 | bwd_microstep: 273.96 | bwd_inner_microstep: 273.94 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-02 00:32:54,684] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.96 | bwd_microstep: 273.71 | bwd_inner_microstep: 273.69 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 00:32:55,161] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.57 | bwd_microstep: 272.61 | bwd_inner_microstep: 272.59 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 00:32:55,636] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.03 | bwd_microstep: 271.92 | bwd_inner_microstep: 271.90 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 00:32:56,110] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.76 | bwd_microstep: 271.05 | bwd_inner_microstep: 271.04 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1345 +[2025-05-02 00:32:56,471] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.35 | bwd_microstep: 205.84 | bwd_inner_microstep: 205.70 | bwd_allreduce_microstep: 0.08 | step_microstep: 0.09 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 317 +[2025-05-02 00:32:56,681] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 80.72 | bwd_microstep: 115.71 | bwd_inner_microstep: 115.49 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 00:32:57,156] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.89 | bwd_microstep: 271.69 | bwd_inner_microstep: 271.67 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 00:32:57,632] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.73 | bwd_microstep: 271.40 | bwd_inner_microstep: 271.38 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 00:32:58,107] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.35 | bwd_microstep: 270.82 | bwd_inner_microstep: 270.81 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 826 +[2025-05-02 00:32:58,456] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.10 | optimizer_step: 16.65 +[2025-05-02 00:32:58,457] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.99 | bwd_microstep: 215.33 | bwd_inner_microstep: 129.83 | bwd_allreduce_microstep: 85.31 | step_microstep: 24.94 +[2025-05-02 00:32:58,458] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2734.95 | bwd: 4040.14 | bwd_inner: 3954.16 | bwd_allreduce: 85.52 | step: 25.78 + 10%|▉ | 860/8720 [2:17:32<15:11:08, 6.96s/it] {'loss': 1.2006, 'grad_norm': 6.641077041625977, 'learning_rate': 9.877165465377516e-06, 'epoch': 0.99} + 10%|▉ | 860/8720 [2:17:32<15:11:08, 6.96s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1911 +[2025-05-02 00:32:58,943] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.03 | bwd_microstep: 275.93 | bwd_inner_microstep: 275.91 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1380 +[2025-05-02 00:32:59,312] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 144.51 | bwd_microstep: 208.39 | bwd_inner_microstep: 208.34 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 00:32:59,789] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.03 | bwd_microstep: 273.29 | bwd_inner_microstep: 273.27 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-02 00:33:00,269] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.82 | bwd_microstep: 273.86 | bwd_inner_microstep: 273.85 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1361 +[2025-05-02 00:33:00,635] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 142.59 | bwd_microstep: 207.11 | bwd_inner_microstep: 206.94 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-02 00:33:01,113] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.61 | bwd_microstep: 273.37 | bwd_inner_microstep: 273.36 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 00:33:01,590] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.81 | bwd_microstep: 272.87 | bwd_inner_microstep: 272.86 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-02 00:33:02,069] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.88 | bwd_microstep: 273.89 | bwd_inner_microstep: 273.87 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 00:33:02,547] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.25 | bwd_microstep: 273.04 | bwd_inner_microstep: 273.02 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 00:33:03,025] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.07 | bwd_microstep: 273.57 | bwd_inner_microstep: 273.55 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 00:33:03,503] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.82 | bwd_microstep: 272.97 | bwd_inner_microstep: 272.95 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 00:33:03,980] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.26 | bwd_microstep: 272.82 | bwd_inner_microstep: 272.80 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1349 +[2025-05-02 00:33:04,342] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.85 | bwd_microstep: 205.97 | bwd_inner_microstep: 205.89 | bwd_allreduce_microstep: 0.04 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 00:33:04,819] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.71 | bwd_microstep: 273.26 | bwd_inner_microstep: 273.24 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 00:33:05,297] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.95 | bwd_microstep: 272.94 | bwd_inner_microstep: 272.92 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 00:33:05,883] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.15 | optimizer_step: 16.63 +[2025-05-02 00:33:05,884] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.40 | bwd_microstep: 358.03 | bwd_inner_microstep: 273.29 | bwd_allreduce_microstep: 84.70 | step_microstep: 25.12 +[2025-05-02 00:33:05,885] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2888.29 | bwd: 4261.43 | bwd_inner: 4176.07 | bwd_allreduce: 84.96 | step: 26.06 + 10%|▉ | 861/8720 [2:17:39<15:29:34, 7.10s/it] {'loss': 1.1535, 'grad_norm': 7.072177886962891, 'learning_rate': 9.876756001520337e-06, 'epoch': 0.99} + 10%|▉ | 861/8720 [2:17:39<15:29:34, 7.10s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 437 +[2025-05-02 00:33:06,105] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 87.20 | bwd_microstep: 114.60 | bwd_inner_microstep: 114.30 | bwd_allreduce_microstep: 0.14 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1908 +[2025-05-02 00:33:06,587] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.24 | bwd_microstep: 276.31 | bwd_inner_microstep: 276.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1897 +[2025-05-02 00:33:07,067] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.48 | bwd_microstep: 275.44 | bwd_inner_microstep: 275.42 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-02 00:33:07,547] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.21 | bwd_microstep: 274.43 | bwd_inner_microstep: 274.42 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 00:33:08,025] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.77 | bwd_microstep: 273.26 | bwd_inner_microstep: 273.24 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 334 +[2025-05-02 00:33:08,247] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.19 | bwd_microstep: 115.13 | bwd_inner_microstep: 114.88 | bwd_allreduce_microstep: 0.09 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-02 00:33:08,725] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.83 | bwd_microstep: 273.40 | bwd_inner_microstep: 273.39 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 00:33:09,203] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.58 | bwd_microstep: 272.88 | bwd_inner_microstep: 272.87 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 00:33:09,681] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.52 | bwd_microstep: 272.77 | bwd_inner_microstep: 272.75 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 835 +[2025-05-02 00:33:09,917] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 97.02 | bwd_microstep: 125.77 | bwd_inner_microstep: 125.74 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 00:33:10,393] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.25 | bwd_microstep: 272.31 | bwd_inner_microstep: 272.29 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 00:33:10,868] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.89 | bwd_microstep: 272.04 | bwd_inner_microstep: 272.02 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 320 +[2025-05-02 00:33:11,090] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 90.11 | bwd_microstep: 117.55 | bwd_inner_microstep: 117.36 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 00:33:11,564] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.66 | bwd_microstep: 271.00 | bwd_inner_microstep: 270.99 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 829 +[2025-05-02 00:33:11,802] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.76 | bwd_microstep: 130.13 | bwd_inner_microstep: 129.80 | bwd_allreduce_microstep: 0.14 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 00:33:12,385] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.04 | optimizer_gradients: 2.14 | optimizer_step: 16.63 +[2025-05-02 00:33:12,386] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.99 | bwd_microstep: 355.70 | bwd_inner_microstep: 271.62 | bwd_allreduce_microstep: 84.04 | step_microstep: 24.93 +[2025-05-02 00:33:12,387] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2541.41 | bwd: 3692.82 | bwd_inner: 3607.63 | bwd_allreduce: 84.47 | step: 25.91 + 10%|▉ | 862/8720 [2:17:46<15:06:04, 6.92s/it] {'loss': 0.8223, 'grad_norm': 4.942794322967529, 'learning_rate': 9.876345864848563e-06, 'epoch': 0.99} + 10%|▉ | 862/8720 [2:17:46<15:06:04, 6.92s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 375 +[2025-05-02 00:33:12,601] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 81.34 | bwd_microstep: 115.01 | bwd_inner_microstep: 114.69 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1888 +[2025-05-02 00:33:13,081] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.86 | bwd_microstep: 275.25 | bwd_inner_microstep: 275.23 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-02 00:33:13,561] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.31 | bwd_microstep: 274.13 | bwd_inner_microstep: 274.11 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-02 00:33:14,041] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.58 | bwd_microstep: 274.46 | bwd_inner_microstep: 274.45 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 00:33:14,521] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.27 | bwd_microstep: 273.54 | bwd_inner_microstep: 273.53 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 00:33:15,000] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.44 | bwd_microstep: 273.74 | bwd_inner_microstep: 273.72 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 00:33:15,479] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.02 | bwd_microstep: 273.91 | bwd_inner_microstep: 273.89 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 326 +[2025-05-02 00:33:15,690] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 83.50 | bwd_microstep: 114.06 | bwd_inner_microstep: 113.91 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.09 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 317 +[2025-05-02 00:33:15,938] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 90.30 | bwd_microstep: 143.54 | bwd_inner_microstep: 143.19 | bwd_allreduce_microstep: 0.18 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 00:33:16,415] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.68 | bwd_microstep: 271.64 | bwd_inner_microstep: 271.62 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 321 +[2025-05-02 00:33:16,629] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 80.90 | bwd_microstep: 119.80 | bwd_inner_microstep: 119.65 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 00:33:17,104] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.16 | bwd_microstep: 271.65 | bwd_inner_microstep: 271.63 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 00:33:17,581] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.80 | bwd_microstep: 271.57 | bwd_inner_microstep: 271.55 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 00:33:18,060] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.83 | bwd_microstep: 271.64 | bwd_inner_microstep: 271.62 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 00:33:18,539] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.15 | bwd_microstep: 271.84 | bwd_inner_microstep: 271.82 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1084 +[2025-05-02 00:33:18,933] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.61 | optimizer_step: 16.60 +[2025-05-02 00:33:18,933] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 115.93 | bwd_microstep: 237.55 | bwd_inner_microstep: 160.18 | bwd_allreduce_microstep: 77.21 | step_microstep: 24.83 +[2025-05-02 00:33:18,935] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2536.76 | bwd: 3733.40 | bwd_inner: 3655.04 | bwd_allreduce: 77.61 | step: 25.74 + 10%|▉ | 863/8720 [2:17:52<14:51:27, 6.81s/it] {'loss': 0.7502, 'grad_norm': 5.3926825523376465, 'learning_rate': 9.875935055418773e-06, 'epoch': 0.99} + 10%|▉ | 863/8720 [2:17:52<14:51:27, 6.81s/it]dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 922 +[2025-05-02 00:33:19,204] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 101.88 | bwd_microstep: 145.84 | bwd_inner_microstep: 145.63 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1897 +[2025-05-02 00:33:19,686] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.70 | bwd_microstep: 275.83 | bwd_inner_microstep: 275.82 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 00:33:20,166] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.76 | bwd_microstep: 273.76 | bwd_inner_microstep: 273.75 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-02 00:33:20,647] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.86 | bwd_microstep: 273.92 | bwd_inner_microstep: 273.90 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 00:33:21,130] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.55 | bwd_microstep: 272.94 | bwd_inner_microstep: 272.92 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 00:33:21,615] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.01 | bwd_microstep: 273.34 | bwd_inner_microstep: 273.32 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 327 +[2025-05-02 00:33:21,862] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 97.62 | bwd_microstep: 128.23 | bwd_inner_microstep: 127.97 | bwd_allreduce_microstep: 0.10 | step_microstep: 0.11 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 843 +[2025-05-02 00:33:22,115] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 98.54 | bwd_microstep: 132.41 | bwd_inner_microstep: 132.19 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-02 00:33:22,596] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.20 | bwd_microstep: 273.86 | bwd_inner_microstep: 273.84 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-02 00:33:23,080] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.18 | bwd_microstep: 273.92 | bwd_inner_microstep: 273.91 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 00:33:23,562] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.28 | bwd_microstep: 272.93 | bwd_inner_microstep: 272.91 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 00:33:24,044] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.45 | bwd_microstep: 272.72 | bwd_inner_microstep: 272.70 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 00:33:24,526] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.03 | bwd_microstep: 271.47 | bwd_inner_microstep: 271.46 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 00:33:25,004] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.49 | bwd_microstep: 271.58 | bwd_inner_microstep: 271.56 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 00:33:25,484] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.06 | bwd_microstep: 271.44 | bwd_inner_microstep: 271.42 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 00:33:26,065] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.16 | optimizer_step: 16.77 +[2025-05-02 00:33:26,065] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.21 | bwd_microstep: 350.84 | bwd_inner_microstep: 271.93 | bwd_allreduce_microstep: 78.86 | step_microstep: 24.81 +[2025-05-02 00:33:26,067] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2754.40 | bwd: 4035.09 | bwd_inner: 3955.33 | bwd_allreduce: 79.20 | step: 25.92 + 10%|▉ | 864/8720 [2:17:59<15:04:07, 6.91s/it] {'loss': 1.2979, 'grad_norm': 8.156328201293945, 'learning_rate': 9.875523573287643e-06, 'epoch': 0.99} + 10%|▉ | 864/8720 [2:17:59<15:04:07, 6.91s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1972 +[2025-05-02 00:33:26,580] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 198.52 | bwd_microstep: 290.44 | bwd_inner_microstep: 290.42 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1926 +[2025-05-02 00:33:27,080] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.59 | bwd_microstep: 287.11 | bwd_inner_microstep: 287.09 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-02 00:33:27,559] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.12 | bwd_microstep: 274.32 | bwd_inner_microstep: 274.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1367 +[2025-05-02 00:33:27,926] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 142.06 | bwd_microstep: 207.27 | bwd_inner_microstep: 207.25 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-02 00:33:28,406] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.28 | bwd_microstep: 273.43 | bwd_inner_microstep: 273.42 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 347 +[2025-05-02 00:33:28,640] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 96.97 | bwd_microstep: 116.96 | bwd_inner_microstep: 116.68 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 00:33:29,122] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.18 | bwd_microstep: 272.60 | bwd_inner_microstep: 272.58 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 339 +[2025-05-02 00:33:29,349] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 86.15 | bwd_microstep: 125.22 | bwd_inner_microstep: 125.07 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 00:33:29,827] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.66 | bwd_microstep: 272.48 | bwd_inner_microstep: 272.46 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 00:33:30,305] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.01 | bwd_microstep: 272.31 | bwd_inner_microstep: 272.29 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.12 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1089 +[2025-05-02 00:33:30,600] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 115.12 | bwd_microstep: 160.79 | bwd_inner_microstep: 160.76 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 00:33:31,079] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.53 | bwd_microstep: 272.27 | bwd_inner_microstep: 272.25 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 319 +[2025-05-02 00:33:31,313] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 100.25 | bwd_microstep: 115.47 | bwd_inner_microstep: 115.14 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 00:33:31,790] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.05 | bwd_microstep: 271.27 | bwd_inner_microstep: 271.25 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 00:33:32,268] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.94 | bwd_microstep: 271.37 | bwd_inner_microstep: 271.35 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 00:33:32,851] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.14 | optimizer_step: 16.80 +[2025-05-02 00:33:32,851] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.93 | bwd_microstep: 349.96 | bwd_inner_microstep: 271.79 | bwd_allreduce_microstep: 78.11 | step_microstep: 24.68 +[2025-05-02 00:33:32,853] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2627.98 | bwd: 3833.34 | bwd_inner: 3754.29 | bwd_allreduce: 78.49 | step: 25.86 + 10%|▉ | 865/8720 [2:18:06<14:59:18, 6.87s/it] {'loss': 1.1391, 'grad_norm': 8.289584159851074, 'learning_rate': 9.875111418511949e-06, 'epoch': 0.99} + 10%|▉ | 865/8720 [2:18:06<14:59:18, 6.87s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1892 +[2025-05-02 00:33:33,341] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.30 | bwd_microstep: 274.49 | bwd_inner_microstep: 274.48 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1364 +[2025-05-02 00:33:33,708] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.08 | bwd_microstep: 207.26 | bwd_inner_microstep: 207.24 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-02 00:33:34,191] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.15 | bwd_microstep: 273.84 | bwd_inner_microstep: 273.83 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 00:33:34,671] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.36 | bwd_microstep: 273.85 | bwd_inner_microstep: 273.83 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1362 +[2025-05-02 00:33:35,040] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 142.52 | bwd_microstep: 207.05 | bwd_inner_microstep: 207.04 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.07 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 323 +[2025-05-02 00:33:35,258] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 80.80 | bwd_microstep: 121.34 | bwd_inner_microstep: 121.19 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 00:33:35,738] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.35 | bwd_microstep: 273.67 | bwd_inner_microstep: 273.65 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 00:33:36,220] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.77 | bwd_microstep: 273.04 | bwd_inner_microstep: 273.02 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 831 +[2025-05-02 00:33:36,457] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 92.82 | bwd_microstep: 130.38 | bwd_inner_microstep: 130.10 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 00:33:36,934] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.28 | bwd_microstep: 272.70 | bwd_inner_microstep: 272.68 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 00:33:37,413] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.94 | bwd_microstep: 272.67 | bwd_inner_microstep: 272.65 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 00:33:37,891] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.57 | bwd_microstep: 271.71 | bwd_inner_microstep: 271.69 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 00:33:38,366] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.34 | bwd_microstep: 271.69 | bwd_inner_microstep: 271.67 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 317 +[2025-05-02 00:33:38,578] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 82.83 | bwd_microstep: 115.06 | bwd_inner_microstep: 114.91 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 00:33:39,054] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.43 | bwd_microstep: 271.98 | bwd_inner_microstep: 271.96 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 00:33:39,622] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.11 | optimizer_step: 16.68 +[2025-05-02 00:33:39,622] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.45 | bwd_microstep: 338.85 | bwd_inner_microstep: 272.02 | bwd_allreduce_microstep: 66.79 | step_microstep: 23.94 +[2025-05-02 00:33:39,624] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2621.67 | bwd: 3849.65 | bwd_inner: 3782.04 | bwd_allreduce: 67.10 | step: 24.88 + 10%|▉ | 866/8720 [2:18:13<14:55:15, 6.84s/it] {'loss': 1.1695, 'grad_norm': 8.17810344696045, 'learning_rate': 9.874698591148546e-06, 'epoch': 0.99} + 10%|▉ | 866/8720 [2:18:13<14:55:15, 6.84s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 359 +[2025-05-02 00:33:39,833] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 69.47 | bwd_microstep: 121.04 | bwd_inner_microstep: 120.90 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-02 00:33:40,311] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.09 | bwd_microstep: 274.25 | bwd_inner_microstep: 274.23 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 00:33:40,792] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.05 | bwd_microstep: 274.17 | bwd_inner_microstep: 274.15 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 00:33:41,272] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.96 | bwd_microstep: 273.65 | bwd_inner_microstep: 273.63 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.07 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-02 00:33:41,753] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.10 | bwd_microstep: 274.48 | bwd_inner_microstep: 274.46 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 835 +[2025-05-02 00:33:42,000] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 96.26 | bwd_microstep: 132.65 | bwd_inner_microstep: 132.44 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.10 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 844 +[2025-05-02 00:33:42,249] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 98.13 | bwd_microstep: 132.27 | bwd_inner_microstep: 132.18 | bwd_allreduce_microstep: 0.04 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 00:33:42,730] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.36 | bwd_microstep: 273.53 | bwd_inner_microstep: 273.52 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 845 +[2025-05-02 00:33:42,976] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.36 | bwd_microstep: 132.44 | bwd_inner_microstep: 132.19 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 00:33:43,456] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.18 | bwd_microstep: 273.29 | bwd_inner_microstep: 273.27 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 00:33:43,933] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.13 | bwd_microstep: 272.76 | bwd_inner_microstep: 272.74 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 00:33:44,411] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.33 | bwd_microstep: 271.47 | bwd_inner_microstep: 271.45 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 00:33:44,888] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.17 | bwd_microstep: 272.00 | bwd_inner_microstep: 271.98 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 00:33:45,363] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.26 | bwd_microstep: 271.73 | bwd_inner_microstep: 271.71 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 00:33:45,839] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.24 | bwd_microstep: 271.49 | bwd_inner_microstep: 271.47 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 364 +[2025-05-02 00:33:46,157] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.22 | optimizer_step: 16.97 +[2025-05-02 00:33:46,157] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 73.85 | bwd_microstep: 206.09 | bwd_inner_microstep: 138.86 | bwd_allreduce_microstep: 67.08 | step_microstep: 24.28 +[2025-05-02 00:33:46,158] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2514.60 | bwd: 3727.37 | bwd_inner: 3659.29 | bwd_allreduce: 67.44 | step: 25.19 + 10%|▉ | 867/8720 [2:18:19<14:43:11, 6.75s/it] {'loss': 0.9452, 'grad_norm': 5.833354949951172, 'learning_rate': 9.874285091254394e-06, 'epoch': 0.99} + 10%|▉ | 867/8720 [2:18:19<14:43:11, 6.75s/it]dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1390 +[2025-05-02 00:33:46,528] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.64 | bwd_microstep: 208.45 | bwd_inner_microstep: 208.43 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1892 +[2025-05-02 00:33:47,008] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.87 | bwd_microstep: 275.13 | bwd_inner_microstep: 275.11 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-02 00:33:47,488] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.55 | bwd_microstep: 273.82 | bwd_inner_microstep: 273.80 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 00:33:47,967] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.11 | bwd_microstep: 272.88 | bwd_inner_microstep: 272.86 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-02 00:33:48,446] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.03 | bwd_microstep: 273.90 | bwd_inner_microstep: 273.87 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-02 00:33:48,926] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.90 | bwd_microstep: 273.78 | bwd_inner_microstep: 273.76 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 00:33:49,408] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.59 | bwd_microstep: 272.97 | bwd_inner_microstep: 272.95 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 00:33:49,886] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.08 | bwd_microstep: 272.93 | bwd_inner_microstep: 272.91 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 00:33:50,364] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.61 | bwd_microstep: 273.26 | bwd_inner_microstep: 273.24 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 00:33:50,842] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.95 | bwd_microstep: 272.54 | bwd_inner_microstep: 272.52 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 00:33:51,318] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.00 | bwd_microstep: 272.31 | bwd_inner_microstep: 272.29 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 00:33:51,794] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.13 | bwd_microstep: 272.54 | bwd_inner_microstep: 272.53 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 832 +[2025-05-02 00:33:52,032] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.08 | bwd_microstep: 130.15 | bwd_inner_microstep: 130.13 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 00:33:52,509] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.59 | bwd_microstep: 271.29 | bwd_inner_microstep: 271.27 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 00:33:52,984] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.68 | bwd_microstep: 271.25 | bwd_inner_microstep: 271.24 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1849 +[2025-05-02 00:33:53,547] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.04 | optimizer_gradients: 2.09 | optimizer_step: 16.60 +[2025-05-02 00:33:53,547] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.67 | bwd_microstep: 337.47 | bwd_inner_microstep: 271.30 | bwd_allreduce_microstep: 66.13 | step_microstep: 23.57 +[2025-05-02 00:33:53,548] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2876.17 | bwd: 4224.68 | bwd_inner: 4158.23 | bwd_allreduce: 66.21 | step: 24.53 + 10%|▉ | 868/8720 [2:18:27<15:08:16, 6.94s/it] {'loss': 1.3664, 'grad_norm': 6.381783962249756, 'learning_rate': 9.873870918886539e-06, 'epoch': 1.0} + 10%|▉ | 868/8720 [2:18:27<15:08:16, 6.94s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 00:33:54,029] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.19 | bwd_microstep: 272.37 | bwd_inner_microstep: 272.35 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1109 +[2025-05-02 00:33:54,322] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 115.88 | bwd_microstep: 162.10 | bwd_inner_microstep: 161.97 | bwd_allreduce_microstep: 0.04 | step_microstep: 0.18 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 855 +[2025-05-02 00:33:54,564] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.90 | bwd_microstep: 133.00 | bwd_inner_microstep: 132.88 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-02 00:33:55,041] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.27 | bwd_microstep: 273.80 | bwd_inner_microstep: 273.78 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 333 +[2025-05-02 00:33:55,257] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 80.32 | bwd_microstep: 120.64 | bwd_inner_microstep: 120.39 | bwd_allreduce_microstep: 0.09 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 00:33:55,733] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.98 | bwd_microstep: 272.71 | bwd_inner_microstep: 272.70 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 00:33:56,210] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.49 | bwd_microstep: 272.19 | bwd_inner_microstep: 272.17 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 00:33:56,688] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.18 | bwd_microstep: 272.70 | bwd_inner_microstep: 272.68 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 00:33:57,165] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.12 | bwd_microstep: 272.53 | bwd_inner_microstep: 272.52 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 00:33:57,639] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.01 | bwd_microstep: 271.30 | bwd_inner_microstep: 271.28 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 00:33:58,114] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.71 | bwd_microstep: 270.91 | bwd_inner_microstep: 270.89 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 00:33:58,590] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.17 | bwd_microstep: 270.89 | bwd_inner_microstep: 270.87 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 00:33:59,067] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.39 | bwd_microstep: 271.41 | bwd_inner_microstep: 271.39 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 00:33:59,545] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.63 | bwd_microstep: 271.23 | bwd_inner_microstep: 271.21 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 00:34:00,022] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.80 | bwd_microstep: 271.26 | bwd_inner_microstep: 271.25 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.13 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1896 +[2025-05-02 00:34:00,609] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.10 | optimizer_step: 16.58 +[2025-05-02 00:34:00,610] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.80 | bwd_microstep: 354.44 | bwd_inner_microstep: 275.65 | bwd_allreduce_microstep: 78.74 | step_microstep: 24.22 +[2025-05-02 00:34:00,611] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2741.53 | bwd: 4033.58 | bwd_inner: 3954.07 | bwd_allreduce: 79.02 | step: 25.22 + 10%|▉ | 869/8720 [2:18:34<15:13:01, 6.98s/it] {'loss': 1.0365, 'grad_norm': 7.2668561935424805, 'learning_rate': 9.873456074102123e-06, 'epoch': 1.0} + 10%|▉ | 869/8720 [2:18:34<15:13:01, 6.98s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1887 +[2025-05-02 00:34:01,097] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.13 | bwd_microstep: 273.84 | bwd_inner_microstep: 273.82 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 00:34:01,576] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.28 | bwd_microstep: 273.24 | bwd_inner_microstep: 273.22 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1360 +[2025-05-02 00:34:01,940] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.50 | bwd_microstep: 206.67 | bwd_inner_microstep: 206.65 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 00:34:02,419] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.40 | bwd_microstep: 272.69 | bwd_inner_microstep: 272.67 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 00:34:02,900] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.84 | bwd_microstep: 272.84 | bwd_inner_microstep: 272.82 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 00:34:03,382] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.03 | bwd_microstep: 272.83 | bwd_inner_microstep: 272.81 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 326 +[2025-05-02 00:34:03,600] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 83.60 | bwd_microstep: 116.63 | bwd_inner_microstep: 116.33 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 00:34:04,078] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.04 | bwd_microstep: 272.56 | bwd_inner_microstep: 272.54 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1092 +[2025-05-02 00:34:04,373] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 115.36 | bwd_microstep: 160.79 | bwd_inner_microstep: 160.76 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 00:34:04,851] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.40 | bwd_microstep: 272.50 | bwd_inner_microstep: 272.48 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 834 +[2025-05-02 00:34:05,093] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 96.49 | bwd_microstep: 125.90 | bwd_inner_microstep: 125.64 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 00:34:05,570] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.11 | bwd_microstep: 272.10 | bwd_inner_microstep: 272.09 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 00:34:06,051] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.73 | bwd_microstep: 271.93 | bwd_inner_microstep: 271.91 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 00:34:06,528] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.46 | bwd_microstep: 271.12 | bwd_inner_microstep: 271.10 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 00:34:07,007] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.39 | bwd_microstep: 271.25 | bwd_inner_microstep: 271.23 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 00:34:07,588] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.08 | optimizer_step: 16.59 +[2025-05-02 00:34:07,589] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.40 | bwd_microstep: 351.33 | bwd_inner_microstep: 271.78 | bwd_allreduce_microstep: 79.50 | step_microstep: 24.19 +[2025-05-02 00:34:07,590] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2696.76 | bwd: 3958.30 | bwd_inner: 3877.92 | bwd_allreduce: 79.81 | step: 25.15 + 10%|▉ | 870/8720 [2:18:41<15:12:57, 6.98s/it] {'loss': 0.7402, 'grad_norm': 7.077058792114258, 'learning_rate': 9.873040556958377e-06, 'epoch': 1.0} + 10%|▉ | 870/8720 [2:18:41<15:12:57, 6.98s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2116 +[2025-05-02 00:34:08,130] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 205.26 | bwd_microstep: 311.75 | bwd_inner_microstep: 311.73 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1935 +[2025-05-02 00:34:08,631] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.80 | bwd_microstep: 288.33 | bwd_inner_microstep: 288.32 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1891 +[2025-05-02 00:34:09,110] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.47 | bwd_microstep: 274.79 | bwd_inner_microstep: 274.77 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 00:34:09,588] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.71 | bwd_microstep: 273.28 | bwd_inner_microstep: 273.26 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-02 00:34:10,069] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.98 | bwd_microstep: 274.42 | bwd_inner_microstep: 274.40 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 337 +[2025-05-02 00:34:10,299] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.45 | bwd_microstep: 116.62 | bwd_inner_microstep: 116.46 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-02 00:34:10,777] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.49 | bwd_microstep: 273.50 | bwd_inner_microstep: 273.48 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 332 +[2025-05-02 00:34:10,993] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 80.29 | bwd_microstep: 119.21 | bwd_inner_microstep: 119.05 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 00:34:11,471] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.46 | bwd_microstep: 272.54 | bwd_inner_microstep: 272.52 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 00:34:11,951] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.31 | bwd_microstep: 272.70 | bwd_inner_microstep: 272.68 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 00:34:12,430] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.05 | bwd_microstep: 271.98 | bwd_inner_microstep: 271.96 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 00:34:12,909] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.89 | bwd_microstep: 271.33 | bwd_inner_microstep: 271.32 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 00:34:13,390] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.96 | bwd_microstep: 271.11 | bwd_inner_microstep: 271.09 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 00:34:13,868] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.03 | bwd_microstep: 271.13 | bwd_inner_microstep: 271.11 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 00:34:14,349] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.67 | bwd_microstep: 271.03 | bwd_inner_microstep: 271.01 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 00:34:14,930] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.07 | optimizer_step: 16.63 +[2025-05-02 00:34:14,931] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.47 | bwd_microstep: 350.70 | bwd_inner_microstep: 271.42 | bwd_allreduce_microstep: 79.22 | step_microstep: 24.07 +[2025-05-02 00:34:14,932] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2833.89 | bwd: 4184.46 | bwd_inner: 4104.67 | bwd_allreduce: 79.42 | step: 24.98 + 10%|▉ | 871/8720 [2:18:48<15:27:03, 7.09s/it] {'loss': 1.1233, 'grad_norm': 6.8967509269714355, 'learning_rate': 9.87262436751263e-06, 'epoch': 1.0} + 10%|▉ | 871/8720 [2:18:48<15:27:03, 7.09s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2101 +[2025-05-02 00:34:15,461] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 203.97 | bwd_microstep: 305.10 | bwd_inner_microstep: 305.08 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1906 +[2025-05-02 00:34:15,943] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.26 | bwd_microstep: 276.04 | bwd_inner_microstep: 276.02 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 00:34:16,423] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.78 | bwd_microstep: 273.61 | bwd_inner_microstep: 273.59 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-02 00:34:16,906] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.65 | bwd_microstep: 274.12 | bwd_inner_microstep: 274.10 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-02 00:34:17,386] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.14 | bwd_microstep: 273.20 | bwd_inner_microstep: 273.19 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1370 +[2025-05-02 00:34:17,757] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.24 | bwd_microstep: 208.01 | bwd_inner_microstep: 207.87 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 00:34:18,239] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.40 | bwd_microstep: 273.52 | bwd_inner_microstep: 273.50 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1351 +[2025-05-02 00:34:18,607] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 142.39 | bwd_microstep: 206.52 | bwd_inner_microstep: 206.37 | bwd_allreduce_microstep: 0.04 | step_microstep: 0.11 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 837 +[2025-05-02 00:34:18,846] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.28 | bwd_microstep: 126.46 | bwd_inner_microstep: 126.28 | bwd_allreduce_microstep: 0.09 | step_microstep: 0.17 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 00:34:19,323] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.05 | bwd_microstep: 271.87 | bwd_inner_microstep: 271.85 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 00:34:19,801] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.81 | bwd_microstep: 271.97 | bwd_inner_microstep: 271.96 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 00:34:20,278] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.13 | bwd_microstep: 271.80 | bwd_inner_microstep: 271.78 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 00:34:20,754] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.64 | bwd_microstep: 272.23 | bwd_inner_microstep: 272.22 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 00:34:21,228] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.80 | bwd_microstep: 271.49 | bwd_inner_microstep: 271.47 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 00:34:21,703] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.34 | bwd_microstep: 271.70 | bwd_inner_microstep: 271.69 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2008 +[2025-05-02 00:34:22,302] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.07 | optimizer_step: 16.59 +[2025-05-02 00:34:22,303] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 200.55 | bwd_microstep: 361.57 | bwd_inner_microstep: 295.28 | bwd_allreduce_microstep: 66.23 | step_microstep: 23.50 +[2025-05-02 00:34:22,304] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2860.11 | bwd: 4209.31 | bwd_inner: 4142.26 | bwd_allreduce: 66.58 | step: 24.55 + 10%|█ | 872/8720 [2:18:56<15:38:06, 7.17s/it] {'loss': 0.9098, 'grad_norm': 4.942166805267334, 'learning_rate': 9.8722075058223e-06, 'epoch': 1.0} + 10%|█ | 872/8720 [2:18:56<15:38:06, 7.17s/it]petrel_client is not installed. If you read data locally instead of from ceph, ignore it. +petrel_client is not installed. Using PIL to load images. +petrel_client is not installed. If you read data locally instead of from ceph, ignore it. +petrel_client is not installed. Using PIL to load images. +petrel_client is not installed. If you read data locally instead of from ceph, ignore it. +petrel_client is not installed. Using PIL to load images. +petrel_client is not installed. If you read data locally instead of from ceph, ignore it. +petrel_client is not installed. Using PIL to load images. +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 00:34:24,502] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.48 | bwd_microstep: 270.23 | bwd_inner_microstep: 270.21 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +[2025-05-02 00:34:26,587] [INFO] [real_accelerator.py:203:get_accelerator] Setting ds_accelerator to cuda (auto detect) +/home1/gmh/anaconda3/envs/promptbench/lib/python3.9/site-packages/timm/models/layers/__init__.py:48: FutureWarning: Importing from timm.models.layers is deprecated, please import via timm.layers + warnings.warn(f"Importing from {__name__} is deprecated, please import via timm.layers", FutureWarning) +[2025-05-02 00:34:32,556] [INFO] [real_accelerator.py:203:get_accelerator] Setting ds_accelerator to cuda (auto detect) +/home1/gmh/anaconda3/envs/promptbench/lib/python3.9/site-packages/timm/models/layers/__init__.py:48: FutureWarning: Importing from timm.models.layers is deprecated, please import via timm.layers + warnings.warn(f"Importing from {__name__} is deprecated, please import via timm.layers", FutureWarning) +[2025-05-02 00:34:38,614] [INFO] [real_accelerator.py:203:get_accelerator] Setting ds_accelerator to cuda (auto detect) +/home1/gmh/anaconda3/envs/promptbench/lib/python3.9/site-packages/timm/models/layers/__init__.py:48: FutureWarning: Importing from timm.models.layers is deprecated, please import via timm.layers + warnings.warn(f"Importing from {__name__} is deprecated, please import via timm.layers", FutureWarning) +[2025-05-02 00:34:44,826] [INFO] [real_accelerator.py:203:get_accelerator] Setting ds_accelerator to cuda (auto detect) +/home1/gmh/anaconda3/envs/promptbench/lib/python3.9/site-packages/timm/models/layers/__init__.py:48: FutureWarning: Importing from timm.models.layers is deprecated, please import via timm.layers + warnings.warn(f"Importing from {__name__} is deprecated, please import via timm.layers", FutureWarning) +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1896 +[2025-05-02 00:34:49,465] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 193.56 | bwd_microstep: 270.59 | bwd_inner_microstep: 270.57 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.21 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-02 00:34:49,943] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 185.63 | bwd_microstep: 270.56 | bwd_inner_microstep: 270.54 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 00:34:50,420] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.01 | bwd_microstep: 270.05 | bwd_inner_microstep: 270.03 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 00:34:50,894] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 185.85 | bwd_microstep: 269.96 | bwd_inner_microstep: 269.94 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 00:34:51,372] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.70 | bwd_microstep: 269.33 | bwd_inner_microstep: 269.31 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 00:34:51,846] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.26 | bwd_microstep: 269.67 | bwd_inner_microstep: 269.66 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 842 +[2025-05-02 00:34:52,099] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 104.16 | bwd_microstep: 129.84 | bwd_inner_microstep: 129.54 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 00:34:52,573] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 185.20 | bwd_microstep: 270.52 | bwd_inner_microstep: 270.51 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 00:34:53,049] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 185.62 | bwd_microstep: 270.14 | bwd_inner_microstep: 270.12 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 00:34:53,522] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 185.84 | bwd_microstep: 269.91 | bwd_inner_microstep: 269.89 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 00:34:53,999] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.29 | bwd_microstep: 269.89 | bwd_inner_microstep: 269.87 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 00:34:54,477] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 185.44 | bwd_microstep: 269.65 | bwd_inner_microstep: 269.63 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 00:34:54,949] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 185.42 | bwd_microstep: 268.73 | bwd_inner_microstep: 268.71 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 314 +[2025-05-02 00:34:55,171] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 84.00 | bwd_microstep: 122.72 | bwd_inner_microstep: 122.43 | bwd_allreduce_microstep: 0.14 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1990 +[2025-05-02 00:34:55,792] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.07 | optimizer_gradients: 2.03 | optimizer_step: 28.65 +[2025-05-02 00:34:55,793] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.61 | bwd_microstep: 371.89 | bwd_inner_microstep: 290.94 | bwd_allreduce_microstep: 80.90 | step_microstep: 37.13 +[2025-05-02 00:34:55,794] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2810.57 | bwd: 4133.73 | bwd_inner: 4052.01 | bwd_allreduce: 81.21 | step: 38.21 + 10%|█ | 873/8720 [2:19:29<32:50:40, 15.07s/it] {'loss': 0.5857, 'grad_norm': 5.192709445953369, 'learning_rate': 9.871789971944897e-06, 'epoch': 1.0} + 10%|█ | 873/8720 [2:19:29<32:50:40, 15.07s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 428 +[2025-05-02 00:34:56,011] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 80.32 | bwd_microstep: 115.10 | bwd_inner_microstep: 114.94 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-02 00:34:56,489] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.66 | bwd_microstep: 272.41 | bwd_inner_microstep: 272.39 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 859 +[2025-05-02 00:34:56,733] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.60 | bwd_microstep: 132.24 | bwd_inner_microstep: 132.09 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-02 00:34:57,210] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.08 | bwd_microstep: 271.84 | bwd_inner_microstep: 271.82 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.16 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-02 00:34:57,685] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.13 | bwd_microstep: 271.11 | bwd_inner_microstep: 271.09 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 328 +[2025-05-02 00:34:57,887] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 68.82 | bwd_microstep: 118.86 | bwd_inner_microstep: 118.62 | bwd_allreduce_microstep: 0.08 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 00:34:58,360] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.78 | bwd_microstep: 270.68 | bwd_inner_microstep: 270.66 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 00:34:58,832] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.02 | bwd_microstep: 270.19 | bwd_inner_microstep: 270.18 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.13 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 00:34:59,305] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.07 | bwd_microstep: 270.81 | bwd_inner_microstep: 270.79 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 00:34:59,779] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.02 | bwd_microstep: 270.78 | bwd_inner_microstep: 270.77 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 00:35:00,252] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.49 | bwd_microstep: 270.67 | bwd_inner_microstep: 270.65 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 00:35:00,725] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.35 | bwd_microstep: 271.13 | bwd_inner_microstep: 271.11 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 00:35:01,198] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.97 | bwd_microstep: 270.71 | bwd_inner_microstep: 270.69 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.13 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 00:35:01,672] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.16 | bwd_microstep: 270.10 | bwd_inner_microstep: 270.08 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 00:35:02,145] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.36 | bwd_microstep: 269.62 | bwd_inner_microstep: 269.60 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 00:35:02,711] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.13 | optimizer_step: 19.84 +[2025-05-02 00:35:02,712] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.93 | bwd_microstep: 336.83 | bwd_inner_microstep: 269.81 | bwd_allreduce_microstep: 66.97 | step_microstep: 27.20 +[2025-05-02 00:35:02,713] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2675.49 | bwd: 3953.12 | bwd_inner: 3885.42 | bwd_allreduce: 67.23 | step: 28.78 + 10%|█ | 874/8720 [2:19:36<27:30:39, 12.62s/it] {'loss': 0.9609, 'grad_norm': 7.757400035858154, 'learning_rate': 9.871371765938027e-06, 'epoch': 1.0} + 10%|█ | 874/8720 [2:19:36<27:30:39, 12.62s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 378 +[2025-05-02 00:35:02,921] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 70.20 | bwd_microstep: 119.46 | bwd_inner_microstep: 119.14 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 396 +[2025-05-02 00:35:03,123] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 68.58 | bwd_microstep: 119.32 | bwd_inner_microstep: 119.01 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1929 +[2025-05-02 00:35:03,618] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 193.35 | bwd_microstep: 286.19 | bwd_inner_microstep: 286.17 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1903 +[2025-05-02 00:35:04,095] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.12 | bwd_microstep: 273.99 | bwd_inner_microstep: 273.98 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.13 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 876 +[2025-05-02 00:35:04,343] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 97.76 | bwd_microstep: 134.00 | bwd_inner_microstep: 133.85 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1883 +[2025-05-02 00:35:04,821] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.09 | bwd_microstep: 272.43 | bwd_inner_microstep: 272.41 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-02 00:35:05,297] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.74 | bwd_microstep: 271.97 | bwd_inner_microstep: 271.95 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-02 00:35:05,777] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.23 | bwd_microstep: 271.94 | bwd_inner_microstep: 271.92 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 00:35:06,253] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.46 | bwd_microstep: 271.29 | bwd_inner_microstep: 271.28 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 00:35:06,730] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.43 | bwd_microstep: 271.18 | bwd_inner_microstep: 271.16 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 00:35:07,207] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.31 | bwd_microstep: 271.68 | bwd_inner_microstep: 271.67 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 00:35:07,682] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.20 | bwd_microstep: 271.06 | bwd_inner_microstep: 271.04 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 6, images per sample: 6.0, dynamic token length: 1607 +[2025-05-02 00:35:08,103] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 164.29 | bwd_microstep: 241.99 | bwd_inner_microstep: 241.97 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 00:35:08,576] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.98 | bwd_microstep: 271.16 | bwd_inner_microstep: 271.14 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 00:35:09,048] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 185.99 | bwd_microstep: 269.45 | bwd_inner_microstep: 269.44 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 00:35:09,614] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.19 | optimizer_step: 16.75 +[2025-05-02 00:35:09,615] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.36 | bwd_microstep: 337.11 | bwd_inner_microstep: 270.30 | bwd_allreduce_microstep: 66.76 | step_microstep: 23.98 +[2025-05-02 00:35:09,616] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2648.76 | bwd: 3954.27 | bwd_inner: 3886.56 | bwd_allreduce: 67.13 | step: 24.96 + 10%|█ | 875/8720 [2:19:43<23:46:04, 10.91s/it] {'loss': 0.9965, 'grad_norm': 6.40519905090332, 'learning_rate': 9.87095288785939e-06, 'epoch': 1.0} + 10%|█ | 875/8720 [2:19:43<23:46:04, 10.91s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1939 +[2025-05-02 00:35:10,117] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 194.43 | bwd_microstep: 286.56 | bwd_inner_microstep: 286.54 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1953 +[2025-05-02 00:35:10,615] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 194.16 | bwd_microstep: 288.24 | bwd_inner_microstep: 288.22 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1931 +[2025-05-02 00:35:11,111] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 193.77 | bwd_microstep: 286.59 | bwd_inner_microstep: 286.58 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-02 00:35:11,588] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.87 | bwd_microstep: 272.91 | bwd_inner_microstep: 272.90 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1897 +[2025-05-02 00:35:12,067] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.58 | bwd_microstep: 274.25 | bwd_inner_microstep: 274.23 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.13 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1890 +[2025-05-02 00:35:12,545] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.65 | bwd_microstep: 273.57 | bwd_inner_microstep: 273.56 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 00:35:13,021] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.85 | bwd_microstep: 272.04 | bwd_inner_microstep: 272.02 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-02 00:35:13,495] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.12 | bwd_microstep: 272.00 | bwd_inner_microstep: 271.98 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 328 +[2025-05-02 00:35:13,703] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 75.76 | bwd_microstep: 117.58 | bwd_inner_microstep: 117.45 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 00:35:14,177] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.77 | bwd_microstep: 271.47 | bwd_inner_microstep: 271.45 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 00:35:14,653] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.17 | bwd_microstep: 271.49 | bwd_inner_microstep: 271.47 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 00:35:15,127] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.43 | bwd_microstep: 271.17 | bwd_inner_microstep: 271.15 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 00:35:15,601] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.81 | bwd_microstep: 271.11 | bwd_inner_microstep: 271.09 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 00:35:16,075] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.32 | bwd_microstep: 271.42 | bwd_inner_microstep: 271.40 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 00:35:16,548] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.34 | bwd_microstep: 269.61 | bwd_inner_microstep: 269.59 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 830 +[2025-05-02 00:35:16,879] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.09 | optimizer_step: 19.89 +[2025-05-02 00:35:16,880] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 92.43 | bwd_microstep: 197.16 | bwd_inner_microstep: 130.79 | bwd_allreduce_microstep: 66.21 | step_microstep: 26.90 +[2025-05-02 00:35:16,881] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2812.18 | bwd: 4167.21 | bwd_inner: 4100.51 | bwd_allreduce: 66.33 | step: 28.02 + 10%|█ | 876/8720 [2:19:50<21:23:03, 9.81s/it] {'loss': 1.3822, 'grad_norm': 5.547830104827881, 'learning_rate': 9.87053333776677e-06, 'epoch': 1.0} + 10%|█ | 876/8720 [2:19:50<21:23:03, 9.81s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 00:35:17,357] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.51 | bwd_microstep: 269.25 | bwd_inner_microstep: 269.23 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1966 +[2025-05-02 00:35:17,857] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 194.93 | bwd_microstep: 289.85 | bwd_inner_microstep: 289.83 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1942 +[2025-05-02 00:35:18,354] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 194.60 | bwd_microstep: 287.76 | bwd_inner_microstep: 287.74 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1939 +[2025-05-02 00:35:18,853] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 194.27 | bwd_microstep: 287.70 | bwd_inner_microstep: 287.68 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1921 +[2025-05-02 00:35:19,354] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 193.87 | bwd_microstep: 286.08 | bwd_inner_microstep: 286.06 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-02 00:35:19,832] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.03 | bwd_microstep: 272.90 | bwd_inner_microstep: 272.88 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.13 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-02 00:35:20,311] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.10 | bwd_microstep: 273.13 | bwd_inner_microstep: 273.11 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 00:35:20,784] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.65 | bwd_microstep: 271.46 | bwd_inner_microstep: 271.44 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 00:35:21,260] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.16 | bwd_microstep: 271.93 | bwd_inner_microstep: 271.91 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 840 +[2025-05-02 00:35:21,494] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 92.68 | bwd_microstep: 126.09 | bwd_inner_microstep: 125.84 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-02 00:35:21,968] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.19 | bwd_microstep: 272.12 | bwd_inner_microstep: 272.10 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 00:35:22,442] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.66 | bwd_microstep: 271.59 | bwd_inner_microstep: 271.57 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 00:35:22,916] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.85 | bwd_microstep: 271.90 | bwd_inner_microstep: 271.89 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 00:35:23,388] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.77 | bwd_microstep: 270.03 | bwd_inner_microstep: 270.02 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 00:35:23,861] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.50 | bwd_microstep: 271.41 | bwd_inner_microstep: 271.39 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 830 +[2025-05-02 00:35:24,188] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.11 | optimizer_step: 16.41 +[2025-05-02 00:35:24,188] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.99 | bwd_microstep: 195.70 | bwd_inner_microstep: 129.94 | bwd_allreduce_microstep: 65.68 | step_microstep: 23.30 +[2025-05-02 00:35:24,189] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2840.45 | bwd: 4188.93 | bwd_inner: 4122.67 | bwd_allreduce: 65.87 | step: 24.08 + 10%|█ | 877/8720 [2:19:57<19:44:36, 9.06s/it] {'loss': 0.8172, 'grad_norm': 3.7401459217071533, 'learning_rate': 9.870113115718053e-06, 'epoch': 1.01} + 10%|█ | 877/8720 [2:19:57<19:44:36, 9.06s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 316 +[2025-05-02 00:35:24,389] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 66.84 | bwd_microstep: 114.88 | bwd_inner_microstep: 114.59 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-02 00:35:24,865] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.76 | bwd_microstep: 272.94 | bwd_inner_microstep: 272.93 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.14 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-02 00:35:25,342] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.50 | bwd_microstep: 273.52 | bwd_inner_microstep: 273.51 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 00:35:25,819] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.46 | bwd_microstep: 272.56 | bwd_inner_microstep: 272.54 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1116 +[2025-05-02 00:35:26,112] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 115.97 | bwd_microstep: 162.19 | bwd_inner_microstep: 162.03 | bwd_allreduce_microstep: 0.08 | step_microstep: 0.10 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 335 +[2025-05-02 00:35:26,322] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 79.14 | bwd_microstep: 116.96 | bwd_inner_microstep: 116.84 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1354 +[2025-05-02 00:35:26,683] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.61 | bwd_microstep: 205.60 | bwd_inner_microstep: 205.48 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 00:35:27,157] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.11 | bwd_microstep: 271.67 | bwd_inner_microstep: 271.65 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 326 +[2025-05-02 00:35:27,361] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 66.78 | bwd_microstep: 123.70 | bwd_inner_microstep: 123.52 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 00:35:27,834] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.36 | bwd_microstep: 271.38 | bwd_inner_microstep: 271.36 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 00:35:28,307] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.68 | bwd_microstep: 271.00 | bwd_inner_microstep: 270.98 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 00:35:28,781] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.41 | bwd_microstep: 272.15 | bwd_inner_microstep: 272.14 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 00:35:29,254] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.76 | bwd_microstep: 270.41 | bwd_inner_microstep: 270.39 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 00:35:29,727] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.87 | bwd_microstep: 270.57 | bwd_inner_microstep: 270.55 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 00:35:30,199] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.92 | bwd_microstep: 270.16 | bwd_inner_microstep: 270.14 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1342 +[2025-05-02 00:35:30,647] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.09 | optimizer_step: 16.38 +[2025-05-02 00:35:30,647] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.44 | bwd_microstep: 270.28 | bwd_inner_microstep: 204.22 | bwd_allreduce_microstep: 66.01 | step_microstep: 23.36 +[2025-05-02 00:35:30,648] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2485.35 | bwd: 3710.03 | bwd_inner: 3643.01 | bwd_allreduce: 66.48 | step: 24.51 + 10%|█ | 878/8720 [2:20:04<18:02:22, 8.28s/it] {'loss': 0.5017, 'grad_norm': 6.7749223709106445, 'learning_rate': 9.869692221771214e-06, 'epoch': 1.01} + 10%|█ | 878/8720 [2:20:04<18:02:22, 8.28s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 00:35:31,123] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.47 | bwd_microstep: 269.24 | bwd_inner_microstep: 269.22 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1493 +[2025-05-02 00:35:31,515] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 146.67 | bwd_microstep: 230.58 | bwd_inner_microstep: 230.57 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1928 +[2025-05-02 00:35:32,010] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 194.00 | bwd_microstep: 286.68 | bwd_inner_microstep: 286.66 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 347 +[2025-05-02 00:35:32,209] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 67.18 | bwd_microstep: 118.12 | bwd_inner_microstep: 117.99 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-02 00:35:32,686] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.88 | bwd_microstep: 273.19 | bwd_inner_microstep: 273.17 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 00:35:33,162] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.32 | bwd_microstep: 273.18 | bwd_inner_microstep: 273.17 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-02 00:35:33,639] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.85 | bwd_microstep: 273.48 | bwd_inner_microstep: 273.46 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 00:35:34,117] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.34 | bwd_microstep: 273.04 | bwd_inner_microstep: 273.02 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-02 00:35:34,608] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 201.74 | bwd_microstep: 274.57 | bwd_inner_microstep: 274.53 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 327 +[2025-05-02 00:35:34,808] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 70.82 | bwd_microstep: 115.45 | bwd_inner_microstep: 115.14 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.18 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 845 +[2025-05-02 00:35:35,050] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 92.86 | bwd_microstep: 134.46 | bwd_inner_microstep: 134.20 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.08 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1089 +[2025-05-02 00:35:35,339] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 113.97 | bwd_microstep: 160.40 | bwd_inner_microstep: 160.33 | bwd_allreduce_microstep: 0.03 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 00:35:35,817] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.18 | bwd_microstep: 273.36 | bwd_inner_microstep: 273.32 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 00:35:36,340] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.77 | bwd_microstep: 309.77 | bwd_inner_microstep: 309.76 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.25 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 00:35:36,852] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 212.03 | bwd_microstep: 277.62 | bwd_inner_microstep: 277.60 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 00:35:37,436] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.12 | optimizer_step: 16.46 +[2025-05-02 00:35:37,437] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.34 | bwd_microstep: 354.29 | bwd_inner_microstep: 271.69 | bwd_allreduce_microstep: 82.55 | step_microstep: 24.10 +[2025-05-02 00:35:37,438] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2612.11 | bwd: 3897.52 | bwd_inner: 3813.94 | bwd_allreduce: 82.95 | step: 25.08 + 10%|█ | 879/8720 [2:20:11<17:03:50, 7.83s/it] {'loss': 0.6833, 'grad_norm': 6.153369903564453, 'learning_rate': 9.86927065598432e-06, 'epoch': 1.01} + 10%|█ | 879/8720 [2:20:11<17:03:50, 7.83s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 316 +[2025-05-02 00:35:37,670] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 80.31 | bwd_microstep: 128.84 | bwd_inner_microstep: 128.82 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1921 +[2025-05-02 00:35:39,174] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 462.40 | bwd_microstep: 1018.21 | bwd_inner_microstep: 1018.20 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 888 +[2025-05-02 00:35:39,548] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 197.60 | bwd_microstep: 158.41 | bwd_inner_microstep: 158.30 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1926 +[2025-05-02 00:35:42,448] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1214.93 | bwd_microstep: 1666.73 | bwd_inner_microstep: 1666.72 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-02 00:35:44,987] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 872.53 | bwd_microstep: 1649.44 | bwd_inner_microstep: 1649.42 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1358 +[2025-05-02 00:35:47,064] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 531.31 | bwd_microstep: 1240.56 | bwd_inner_microstep: 1240.50 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-02 00:35:49,606] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1218.08 | bwd_microstep: 1308.82 | bwd_inner_microstep: 1308.80 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.67 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 338 +[2025-05-02 00:35:50,673] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 453.37 | bwd_microstep: 365.83 | bwd_inner_microstep: 365.49 | bwd_allreduce_microstep: 0.14 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 00:35:53,194] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1059.77 | bwd_microstep: 1445.70 | bwd_inner_microstep: 1445.68 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 00:35:55,828] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1119.20 | bwd_microstep: 1402.68 | bwd_inner_microstep: 1402.66 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1093 +[2025-05-02 00:35:57,497] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 751.91 | bwd_microstep: 900.03 | bwd_inner_microstep: 899.79 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 00:36:00,015] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1105.50 | bwd_microstep: 1396.96 | bwd_inner_microstep: 1396.94 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 00:36:02,848] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 924.93 | bwd_microstep: 1597.64 | bwd_inner_microstep: 1597.62 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 319 +[2025-05-02 00:36:03,742] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 459.50 | bwd_microstep: 417.74 | bwd_inner_microstep: 417.41 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.18 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 829 +[2025-05-02 00:36:05,008] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 679.35 | bwd_microstep: 573.08 | bwd_inner_microstep: 573.02 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 00:36:08,216] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.12 | optimizer_step: 16.71 +[2025-05-02 00:36:08,216] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1201.19 | bwd_microstep: 1966.87 | bwd_inner_microstep: 1597.61 | bwd_allreduce_microstep: 369.17 | step_microstep: 24.28 +[2025-05-02 00:36:08,217] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 12331.66 | bwd: 17237.65 | bwd_inner: 16867.11 | bwd_allreduce: 369.72 | step: 28.31 + 10%|█ | 880/8720 [2:20:42<32:05:01, 14.73s/it] {'loss': 0.9966, 'grad_norm': 8.382981300354004, 'learning_rate': 9.868848418415535e-06, 'epoch': 1.01} + 10%|█ | 880/8720 [2:20:42<32:05:01, 14.73s/it]dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1417 +[2025-05-02 00:36:10,347] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 780.98 | bwd_microstep: 1240.40 | bwd_inner_microstep: 1240.11 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.13 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 634 +[2025-05-02 00:36:10,925] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 464.07 | bwd_microstep: 99.26 | bwd_inner_microstep: 98.95 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2066 +[2025-05-02 00:36:11,442] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 201.01 | bwd_microstep: 298.78 | bwd_inner_microstep: 298.76 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1947 +[2025-05-02 00:36:11,938] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 194.02 | bwd_microstep: 286.06 | bwd_inner_microstep: 286.04 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.21 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1935 +[2025-05-02 00:36:12,438] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 192.68 | bwd_microstep: 287.56 | bwd_inner_microstep: 287.54 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1887 +[2025-05-02 00:36:12,910] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 185.62 | bwd_microstep: 271.03 | bwd_inner_microstep: 271.01 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-02 00:36:13,383] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.22 | bwd_microstep: 270.70 | bwd_inner_microstep: 270.69 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-02 00:36:13,857] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.50 | bwd_microstep: 270.95 | bwd_inner_microstep: 270.94 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 00:36:14,327] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 185.30 | bwd_microstep: 269.65 | bwd_inner_microstep: 269.63 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 333 +[2025-05-02 00:36:14,539] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 77.69 | bwd_microstep: 119.37 | bwd_inner_microstep: 119.23 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 00:36:15,011] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.06 | bwd_microstep: 269.63 | bwd_inner_microstep: 269.61 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 00:36:15,487] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 185.90 | bwd_microstep: 271.17 | bwd_inner_microstep: 271.16 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 00:36:15,965] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.91 | bwd_microstep: 270.19 | bwd_inner_microstep: 270.17 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 00:36:16,442] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.97 | bwd_microstep: 270.02 | bwd_inner_microstep: 270.01 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 00:36:16,916] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.15 | bwd_microstep: 268.94 | bwd_inner_microstep: 268.93 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1924 +[2025-05-02 00:36:17,517] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.14 | optimizer_step: 16.55 +[2025-05-02 00:36:17,518] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 193.00 | bwd_microstep: 364.79 | bwd_inner_microstep: 285.25 | bwd_allreduce_microstep: 79.49 | step_microstep: 24.46 +[2025-05-02 00:36:17,519] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 3779.77 | bwd: 5128.60 | bwd_inner: 5048.18 | bwd_allreduce: 79.87 | step: 25.84 + 10%|█ | 881/8720 [2:20:51<28:30:03, 13.09s/it] {'loss': 0.933, 'grad_norm': 3.482320785522461, 'learning_rate': 9.868425509123109e-06, 'epoch': 1.01} + 10%|█ | 881/8720 [2:20:51<28:30:03, 13.09s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1909 +[2025-05-02 00:36:18,005] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.90 | bwd_microstep: 273.84 | bwd_inner_microstep: 273.83 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 348 +[2025-05-02 00:36:18,250] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 90.35 | bwd_microstep: 137.72 | bwd_inner_microstep: 137.47 | bwd_allreduce_microstep: 0.10 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1896 +[2025-05-02 00:36:18,728] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.15 | bwd_microstep: 273.04 | bwd_inner_microstep: 273.02 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-02 00:36:19,206] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.50 | bwd_microstep: 272.12 | bwd_inner_microstep: 272.10 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1370 +[2025-05-02 00:36:19,570] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.79 | bwd_microstep: 206.07 | bwd_inner_microstep: 205.93 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 00:36:20,046] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.60 | bwd_microstep: 271.60 | bwd_inner_microstep: 271.58 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 845 +[2025-05-02 00:36:20,290] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.01 | bwd_microstep: 132.28 | bwd_inner_microstep: 132.23 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 00:36:20,765] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.44 | bwd_microstep: 271.04 | bwd_inner_microstep: 271.02 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 00:36:21,243] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.51 | bwd_microstep: 271.98 | bwd_inner_microstep: 271.96 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1347 +[2025-05-02 00:36:21,605] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.27 | bwd_microstep: 204.07 | bwd_inner_microstep: 203.95 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 00:36:22,081] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.69 | bwd_microstep: 271.24 | bwd_inner_microstep: 271.22 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 00:36:22,558] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.34 | bwd_microstep: 271.34 | bwd_inner_microstep: 271.32 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 834 +[2025-05-02 00:36:22,798] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.41 | bwd_microstep: 126.23 | bwd_inner_microstep: 126.11 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 00:36:23,272] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.37 | bwd_microstep: 269.93 | bwd_inner_microstep: 269.91 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 319 +[2025-05-02 00:36:23,514] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 91.38 | bwd_microstep: 131.05 | bwd_inner_microstep: 130.73 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 00:36:24,089] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.21 | optimizer_step: 16.62 +[2025-05-02 00:36:24,090] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 185.72 | bwd_microstep: 347.16 | bwd_inner_microstep: 269.76 | bwd_allreduce_microstep: 77.35 | step_microstep: 24.55 +[2025-05-02 00:36:24,091] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2524.11 | bwd: 3730.87 | bwd_inner: 3652.25 | bwd_allreduce: 77.83 | step: 25.73 + 10%|█ | 882/8720 [2:20:57<24:14:26, 11.13s/it] {'loss': 0.8676, 'grad_norm': 6.618492603302002, 'learning_rate': 9.868001928165389e-06, 'epoch': 1.01} + 10%|█ | 882/8720 [2:20:57<24:14:26, 11.13s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1905 +[2025-05-02 00:36:24,577] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.33 | bwd_microstep: 273.94 | bwd_inner_microstep: 273.92 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 844 +[2025-05-02 00:36:24,818] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.11 | bwd_microstep: 131.46 | bwd_inner_microstep: 131.31 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-02 00:36:25,293] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.89 | bwd_microstep: 271.89 | bwd_inner_microstep: 271.87 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 00:36:25,769] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.63 | bwd_microstep: 271.57 | bwd_inner_microstep: 271.56 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 00:36:26,245] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.51 | bwd_microstep: 271.26 | bwd_inner_microstep: 271.24 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 00:36:26,723] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.31 | bwd_microstep: 271.09 | bwd_inner_microstep: 271.07 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 00:36:27,203] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.15 | bwd_microstep: 271.89 | bwd_inner_microstep: 271.88 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 00:36:27,679] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.63 | bwd_microstep: 271.09 | bwd_inner_microstep: 271.07 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 836 +[2025-05-02 00:36:27,919] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 98.09 | bwd_microstep: 124.96 | bwd_inner_microstep: 124.90 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.10 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 325 +[2025-05-02 00:36:28,136] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 80.67 | bwd_microstep: 120.60 | bwd_inner_microstep: 120.38 | bwd_allreduce_microstep: 0.09 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 00:36:28,612] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.35 | bwd_microstep: 271.20 | bwd_inner_microstep: 271.18 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 00:36:29,087] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.27 | bwd_microstep: 270.74 | bwd_inner_microstep: 270.73 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 00:36:29,564] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.69 | bwd_microstep: 271.33 | bwd_inner_microstep: 271.31 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 00:36:30,043] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.96 | bwd_microstep: 270.88 | bwd_inner_microstep: 270.86 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 00:36:30,521] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.29 | bwd_microstep: 269.74 | bwd_inner_microstep: 269.72 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 828 +[2025-05-02 00:36:30,864] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.15 | optimizer_step: 16.54 +[2025-05-02 00:36:30,865] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.37 | bwd_microstep: 207.42 | bwd_inner_microstep: 129.62 | bwd_allreduce_microstep: 77.69 | step_microstep: 24.49 +[2025-05-02 00:36:30,866] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2610.90 | bwd: 3841.13 | bwd_inner: 3762.74 | bwd_allreduce: 77.93 | step: 25.45 + 10%|█ | 883/8720 [2:21:04<21:23:26, 9.83s/it] {'loss': 0.756, 'grad_norm': 7.642425060272217, 'learning_rate': 9.867577675600813e-06, 'epoch': 1.01} + 10%|█ | 883/8720 [2:21:04<21:23:26, 9.83s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 00:36:31,345] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.64 | bwd_microstep: 269.08 | bwd_inner_microstep: 269.06 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1150 +[2025-05-02 00:36:31,643] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 116.43 | bwd_microstep: 164.97 | bwd_inner_microstep: 164.77 | bwd_allreduce_microstep: 0.10 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2043 +[2025-05-02 00:36:32,154] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 199.92 | bwd_microstep: 296.44 | bwd_inner_microstep: 296.42 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 872 +[2025-05-02 00:36:32,399] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 96.98 | bwd_microstep: 133.64 | bwd_inner_microstep: 133.43 | bwd_allreduce_microstep: 0.09 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-02 00:36:32,876] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.42 | bwd_microstep: 273.10 | bwd_inner_microstep: 273.08 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1894 +[2025-05-02 00:36:33,353] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.78 | bwd_microstep: 273.50 | bwd_inner_microstep: 273.48 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 00:36:33,828] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.06 | bwd_microstep: 271.91 | bwd_inner_microstep: 271.89 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 00:36:34,301] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.36 | bwd_microstep: 270.97 | bwd_inner_microstep: 270.96 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 330 +[2025-05-02 00:36:34,502] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 69.02 | bwd_microstep: 118.04 | bwd_inner_microstep: 117.79 | bwd_allreduce_microstep: 0.10 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 00:36:34,977] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.13 | bwd_microstep: 271.73 | bwd_inner_microstep: 271.72 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 00:36:35,451] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.20 | bwd_microstep: 271.44 | bwd_inner_microstep: 271.42 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 00:36:35,922] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.02 | bwd_microstep: 269.81 | bwd_inner_microstep: 269.79 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 00:36:36,395] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.01 | bwd_microstep: 270.05 | bwd_inner_microstep: 270.03 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 00:36:36,870] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.43 | bwd_microstep: 270.47 | bwd_inner_microstep: 270.45 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 00:36:37,344] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.68 | bwd_microstep: 269.91 | bwd_inner_microstep: 269.89 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1850 +[2025-05-02 00:36:37,923] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.21 | optimizer_step: 16.73 +[2025-05-02 00:36:37,923] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.31 | bwd_microstep: 349.02 | bwd_inner_microstep: 270.31 | bwd_allreduce_microstep: 78.66 | step_microstep: 24.78 +[2025-05-02 00:36:37,925] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2726.08 | bwd: 4044.15 | bwd_inner: 3964.58 | bwd_allreduce: 79.03 | step: 25.57 + 10%|█ | 884/8720 [2:21:11<19:34:51, 9.00s/it] {'loss': 0.7848, 'grad_norm': 6.184631824493408, 'learning_rate': 9.867152751487913e-06, 'epoch': 1.01} + 10%|█ | 884/8720 [2:21:11<19:34:51, 9.00s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-02 00:36:38,408] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.91 | bwd_microstep: 272.41 | bwd_inner_microstep: 272.39 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1897 +[2025-05-02 00:36:38,889] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.88 | bwd_microstep: 274.05 | bwd_inner_microstep: 274.03 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 870 +[2025-05-02 00:36:39,165] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.83 | bwd_microstep: 161.03 | bwd_inner_microstep: 160.71 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1886 +[2025-05-02 00:36:39,644] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.38 | bwd_microstep: 273.17 | bwd_inner_microstep: 273.15 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1365 +[2025-05-02 00:36:40,013] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 142.26 | bwd_microstep: 206.26 | bwd_inner_microstep: 206.20 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.11 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1357 +[2025-05-02 00:36:40,382] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 142.79 | bwd_microstep: 205.69 | bwd_inner_microstep: 205.54 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 00:36:40,862] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.98 | bwd_microstep: 271.46 | bwd_inner_microstep: 271.44 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1352 +[2025-05-02 00:36:41,228] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.17 | bwd_microstep: 205.15 | bwd_inner_microstep: 205.06 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 00:36:41,712] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.11 | bwd_microstep: 271.93 | bwd_inner_microstep: 271.91 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 00:36:42,193] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.96 | bwd_microstep: 271.38 | bwd_inner_microstep: 271.37 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 00:36:42,668] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.39 | bwd_microstep: 271.20 | bwd_inner_microstep: 271.18 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 00:36:43,142] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.77 | bwd_microstep: 269.77 | bwd_inner_microstep: 269.75 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 00:36:43,615] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.22 | bwd_microstep: 270.27 | bwd_inner_microstep: 270.25 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 00:36:44,089] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.37 | bwd_microstep: 270.31 | bwd_inner_microstep: 270.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 00:36:44,561] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.63 | bwd_microstep: 270.32 | bwd_inner_microstep: 270.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 00:36:45,124] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.04 | optimizer_gradients: 2.09 | optimizer_step: 16.43 +[2025-05-02 00:36:45,124] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.68 | bwd_microstep: 337.51 | bwd_inner_microstep: 271.20 | bwd_allreduce_microstep: 66.26 | step_microstep: 23.34 +[2025-05-02 00:36:45,125] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2769.95 | bwd: 4102.03 | bwd_inner: 4034.85 | bwd_allreduce: 66.62 | step: 24.54 + 10%|█ | 885/8720 [2:21:18<18:24:18, 8.46s/it] {'loss': 0.9842, 'grad_norm': 5.716402053833008, 'learning_rate': 9.866727155885317e-06, 'epoch': 1.01} + 10%|█ | 885/8720 [2:21:18<18:24:18, 8.46s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 00:36:45,605] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.72 | bwd_microstep: 272.46 | bwd_inner_microstep: 272.44 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1893 +[2025-05-02 00:36:46,083] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.09 | bwd_microstep: 274.28 | bwd_inner_microstep: 274.27 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 348 +[2025-05-02 00:36:46,283] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 68.87 | bwd_microstep: 118.31 | bwd_inner_microstep: 118.19 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-02 00:36:46,759] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.82 | bwd_microstep: 273.71 | bwd_inner_microstep: 273.69 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-02 00:36:47,237] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.05 | bwd_microstep: 273.75 | bwd_inner_microstep: 273.73 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-02 00:36:47,716] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.92 | bwd_microstep: 273.46 | bwd_inner_microstep: 273.44 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 837 +[2025-05-02 00:36:47,955] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 100.12 | bwd_microstep: 125.93 | bwd_inner_microstep: 125.80 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 00:36:48,433] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.45 | bwd_microstep: 272.72 | bwd_inner_microstep: 272.71 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 00:36:48,911] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.52 | bwd_microstep: 272.38 | bwd_inner_microstep: 272.36 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 00:36:49,386] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.89 | bwd_microstep: 271.59 | bwd_inner_microstep: 271.57 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 00:36:49,860] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.03 | bwd_microstep: 271.79 | bwd_inner_microstep: 271.77 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1344 +[2025-05-02 00:36:50,219] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.38 | bwd_microstep: 204.03 | bwd_inner_microstep: 204.01 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 00:36:50,694] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.25 | bwd_microstep: 270.78 | bwd_inner_microstep: 270.76 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 00:36:51,173] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.75 | bwd_microstep: 271.34 | bwd_inner_microstep: 271.32 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 00:36:51,652] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.69 | bwd_microstep: 272.87 | bwd_inner_microstep: 272.86 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 843 +[2025-05-02 00:36:51,995] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.12 | optimizer_step: 16.47 +[2025-05-02 00:36:51,996] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.76 | bwd_microstep: 209.13 | bwd_inner_microstep: 132.49 | bwd_allreduce_microstep: 76.47 | step_microstep: 24.08 +[2025-05-02 00:36:51,997] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2661.03 | bwd: 3928.57 | bwd_inner: 3851.51 | bwd_allreduce: 76.62 | step: 25.03 + 10%|█ | 886/8720 [2:21:25<17:22:09, 7.98s/it] {'loss': 0.5598, 'grad_norm': 4.4388861656188965, 'learning_rate': 9.866300888851734e-06, 'epoch': 1.02} + 10%|█ | 886/8720 [2:21:25<17:22:09, 7.98s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 321 +[2025-05-02 00:36:52,216] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 79.69 | bwd_microstep: 117.63 | bwd_inner_microstep: 117.29 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1893 +[2025-05-02 00:36:52,696] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.59 | bwd_microstep: 274.80 | bwd_inner_microstep: 274.78 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-02 00:36:53,174] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.08 | bwd_microstep: 274.04 | bwd_inner_microstep: 274.02 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 00:36:53,650] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.78 | bwd_microstep: 272.56 | bwd_inner_microstep: 272.54 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 00:36:54,127] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.30 | bwd_microstep: 273.07 | bwd_inner_microstep: 273.05 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 00:36:54,602] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.10 | bwd_microstep: 272.96 | bwd_inner_microstep: 272.94 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 00:36:55,082] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.17 | bwd_microstep: 272.85 | bwd_inner_microstep: 272.83 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1089 +[2025-05-02 00:36:55,375] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 114.71 | bwd_microstep: 160.44 | bwd_inner_microstep: 160.26 | bwd_allreduce_microstep: 0.09 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 00:36:55,853] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.12 | bwd_microstep: 272.61 | bwd_inner_microstep: 272.59 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 00:36:56,333] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.60 | bwd_microstep: 272.26 | bwd_inner_microstep: 272.24 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 322 +[2025-05-02 00:36:56,560] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 90.37 | bwd_microstep: 120.86 | bwd_inner_microstep: 120.71 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 00:36:57,037] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.38 | bwd_microstep: 271.95 | bwd_inner_microstep: 271.93 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 00:36:57,513] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.74 | bwd_microstep: 271.10 | bwd_inner_microstep: 271.08 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 827 +[2025-05-02 00:36:57,755] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 96.37 | bwd_microstep: 129.58 | bwd_inner_microstep: 129.40 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 00:36:58,231] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.38 | bwd_microstep: 270.85 | bwd_inner_microstep: 270.84 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1908 +[2025-05-02 00:36:58,804] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.33 | optimizer_step: 16.80 +[2025-05-02 00:36:58,805] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.83 | bwd_microstep: 342.84 | bwd_inner_microstep: 276.70 | bwd_allreduce_microstep: 66.10 | step_microstep: 24.21 +[2025-05-02 00:36:58,806] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2640.87 | bwd: 3870.46 | bwd_inner: 3803.30 | bwd_allreduce: 66.54 | step: 25.29 + 10%|█ | 887/8720 [2:21:32<16:36:00, 7.63s/it] {'loss': 0.959, 'grad_norm': 8.40577507019043, 'learning_rate': 9.86587395044598e-06, 'epoch': 1.02} + 10%|█ | 887/8720 [2:21:32<16:36:00, 7.63s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1895 +[2025-05-02 00:36:59,289] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.14 | bwd_microstep: 274.31 | bwd_inner_microstep: 274.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1888 +[2025-05-02 00:36:59,768] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.23 | bwd_microstep: 274.49 | bwd_inner_microstep: 274.47 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1887 +[2025-05-02 00:37:00,246] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.07 | bwd_microstep: 274.56 | bwd_inner_microstep: 274.54 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-02 00:37:00,723] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.62 | bwd_microstep: 273.44 | bwd_inner_microstep: 273.43 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-02 00:37:01,199] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.36 | bwd_microstep: 272.90 | bwd_inner_microstep: 272.88 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-02 00:37:01,675] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.61 | bwd_microstep: 272.76 | bwd_inner_microstep: 272.74 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 00:37:02,152] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.72 | bwd_microstep: 273.27 | bwd_inner_microstep: 273.26 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 00:37:02,630] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.58 | bwd_microstep: 272.59 | bwd_inner_microstep: 272.58 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 320 +[2025-05-02 00:37:02,856] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 87.29 | bwd_microstep: 120.47 | bwd_inner_microstep: 120.17 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 00:37:03,330] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.14 | bwd_microstep: 271.04 | bwd_inner_microstep: 271.02 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 00:37:03,807] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.96 | bwd_microstep: 272.19 | bwd_inner_microstep: 272.17 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 00:37:04,285] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.71 | bwd_microstep: 271.33 | bwd_inner_microstep: 271.31 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 00:37:04,766] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.51 | bwd_microstep: 271.29 | bwd_inner_microstep: 271.27 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 00:37:05,245] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.57 | bwd_microstep: 271.10 | bwd_inner_microstep: 271.08 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 00:37:05,722] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.08 | bwd_microstep: 270.92 | bwd_inner_microstep: 270.91 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 00:37:06,301] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.10 | optimizer_step: 17.28 +[2025-05-02 00:37:06,301] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.75 | bwd_microstep: 349.23 | bwd_inner_microstep: 271.38 | bwd_allreduce_microstep: 77.79 | step_microstep: 24.91 +[2025-05-02 00:37:06,303] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2914.00 | bwd: 4285.94 | bwd_inner: 4207.57 | bwd_allreduce: 77.98 | step: 25.74 + 10%|█ | 888/8720 [2:21:40<16:30:45, 7.59s/it] {'loss': 0.9613, 'grad_norm': 5.847402572631836, 'learning_rate': 9.865446340726951e-06, 'epoch': 1.02} + 10%|█ | 888/8720 [2:21:40<16:30:45, 7.59s/it]dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 832 +[2025-05-02 00:37:06,570] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 112.49 | bwd_microstep: 129.49 | bwd_inner_microstep: 129.17 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1962 +[2025-05-02 00:37:07,074] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 196.84 | bwd_microstep: 289.55 | bwd_inner_microstep: 289.53 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1921 +[2025-05-02 00:37:07,573] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 194.10 | bwd_microstep: 286.23 | bwd_inner_microstep: 286.21 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1906 +[2025-05-02 00:37:08,055] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.19 | bwd_microstep: 275.62 | bwd_inner_microstep: 275.60 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-02 00:37:08,536] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.04 | bwd_microstep: 273.78 | bwd_inner_microstep: 273.76 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1886 +[2025-05-02 00:37:09,021] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.48 | bwd_microstep: 274.09 | bwd_inner_microstep: 274.07 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-02 00:37:09,506] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.96 | bwd_microstep: 273.14 | bwd_inner_microstep: 273.13 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-02 00:37:09,989] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.16 | bwd_microstep: 273.20 | bwd_inner_microstep: 273.18 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 00:37:10,472] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.93 | bwd_microstep: 272.85 | bwd_inner_microstep: 272.84 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 00:37:10,952] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.71 | bwd_microstep: 271.94 | bwd_inner_microstep: 271.92 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 00:37:11,434] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.89 | bwd_microstep: 272.20 | bwd_inner_microstep: 272.19 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 841 +[2025-05-02 00:37:11,684] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 100.38 | bwd_microstep: 131.79 | bwd_inner_microstep: 131.58 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.10 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1351 +[2025-05-02 00:37:12,046] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.18 | bwd_microstep: 205.52 | bwd_inner_microstep: 205.49 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 00:37:12,525] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.70 | bwd_microstep: 272.22 | bwd_inner_microstep: 272.20 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 00:37:13,003] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.36 | bwd_microstep: 271.12 | bwd_inner_microstep: 271.11 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.16 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 00:37:13,581] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.07 | optimizer_step: 16.41 +[2025-05-02 00:37:13,581] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.19 | bwd_microstep: 347.30 | bwd_inner_microstep: 271.31 | bwd_allreduce_microstep: 75.94 | step_microstep: 23.99 +[2025-05-02 00:37:13,583] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2818.16 | bwd: 4120.10 | bwd_inner: 4043.35 | bwd_allreduce: 76.28 | step: 25.08 + 10%|█ | 889/8720 [2:21:47<16:18:29, 7.50s/it] {'loss': 1.1934, 'grad_norm': 7.094006061553955, 'learning_rate': 9.865018059753648e-06, 'epoch': 1.02} + 10%|█ | 889/8720 [2:21:47<16:18:29, 7.50s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2066 +[2025-05-02 00:37:14,109] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 202.05 | bwd_microstep: 301.79 | bwd_inner_microstep: 301.77 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1893 +[2025-05-02 00:37:14,595] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.29 | bwd_microstep: 274.57 | bwd_inner_microstep: 274.55 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-02 00:37:15,071] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.13 | bwd_microstep: 272.85 | bwd_inner_microstep: 272.83 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-02 00:37:15,549] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.42 | bwd_microstep: 273.54 | bwd_inner_microstep: 273.52 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 852 +[2025-05-02 00:37:15,793] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 97.60 | bwd_microstep: 132.71 | bwd_inner_microstep: 132.47 | bwd_allreduce_microstep: 0.14 | step_microstep: 0.09 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 847 +[2025-05-02 00:37:16,033] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 92.94 | bwd_microstep: 132.30 | bwd_inner_microstep: 132.04 | bwd_allreduce_microstep: 0.14 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 00:37:16,510] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.35 | bwd_microstep: 272.87 | bwd_inner_microstep: 272.85 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-02 00:37:16,990] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.59 | bwd_microstep: 273.34 | bwd_inner_microstep: 273.32 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.15 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 00:37:17,469] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.74 | bwd_microstep: 272.60 | bwd_inner_microstep: 272.58 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 00:37:17,950] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.63 | bwd_microstep: 271.86 | bwd_inner_microstep: 271.85 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 00:37:18,430] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.03 | bwd_microstep: 271.97 | bwd_inner_microstep: 271.95 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.06 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 322 +[2025-05-02 00:37:18,659] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 92.87 | bwd_microstep: 118.64 | bwd_inner_microstep: 118.49 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1343 +[2025-05-02 00:37:19,021] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.06 | bwd_microstep: 204.49 | bwd_inner_microstep: 204.38 | bwd_allreduce_microstep: 0.03 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 00:37:19,497] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.62 | bwd_microstep: 271.15 | bwd_inner_microstep: 271.13 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 00:37:19,975] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.67 | bwd_microstep: 270.97 | bwd_inner_microstep: 270.95 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1994 +[2025-05-02 00:37:20,588] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.06 | optimizer_step: 16.37 +[2025-05-02 00:37:20,589] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 198.64 | bwd_microstep: 370.13 | bwd_inner_microstep: 293.88 | bwd_allreduce_microstep: 76.20 | step_microstep: 23.92 +[2025-05-02 00:37:20,590] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2704.29 | bwd: 3985.85 | bwd_inner: 3908.57 | bwd_allreduce: 76.63 | step: 25.18 + 10%|█ | 890/8720 [2:21:54<15:59:11, 7.35s/it] {'loss': 1.0106, 'grad_norm': 8.917562484741211, 'learning_rate': 9.864589107585155e-06, 'epoch': 1.02} + 10%|█ | 890/8720 [2:21:54<15:59:11, 7.35s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1919 +[2025-05-02 00:37:21,079] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.02 | bwd_microstep: 276.48 | bwd_inner_microstep: 276.47 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2005 +[2025-05-02 00:37:21,589] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 198.60 | bwd_microstep: 294.69 | bwd_inner_microstep: 294.67 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1997 +[2025-05-02 00:37:22,099] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 199.20 | bwd_microstep: 293.90 | bwd_inner_microstep: 293.88 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1953 +[2025-05-02 00:37:22,602] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 196.26 | bwd_microstep: 289.15 | bwd_inner_microstep: 289.14 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.15 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1893 +[2025-05-02 00:37:23,087] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.14 | bwd_microstep: 274.63 | bwd_inner_microstep: 274.62 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-02 00:37:23,572] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.54 | bwd_microstep: 273.85 | bwd_inner_microstep: 273.83 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-02 00:37:24,054] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.21 | bwd_microstep: 273.74 | bwd_inner_microstep: 273.73 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 00:37:24,546] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.15 | bwd_microstep: 283.93 | bwd_inner_microstep: 283.92 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 322 +[2025-05-02 00:37:24,760] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 80.76 | bwd_microstep: 118.36 | bwd_inner_microstep: 118.05 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 00:37:25,240] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.32 | bwd_microstep: 272.72 | bwd_inner_microstep: 272.64 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 00:37:25,724] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.63 | bwd_microstep: 274.14 | bwd_inner_microstep: 274.13 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 00:37:26,208] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.67 | bwd_microstep: 275.71 | bwd_inner_microstep: 275.65 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 00:37:26,748] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 212.31 | bwd_microstep: 309.28 | bwd_inner_microstep: 309.22 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 00:37:27,238] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 197.47 | bwd_microstep: 273.76 | bwd_inner_microstep: 273.70 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 00:37:27,718] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.09 | bwd_microstep: 274.02 | bwd_inner_microstep: 274.00 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 00:37:28,916] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.10 | optimizer_step: 65.90 +[2025-05-02 00:37:28,966] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 222.42 | bwd_microstep: 885.16 | bwd_inner_microstep: 752.89 | bwd_allreduce_microstep: 132.22 | step_microstep: 122.96 +[2025-05-02 00:37:28,967] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 3005.41 | bwd: 4943.58 | bwd_inner: 4810.61 | bwd_allreduce: 132.46 | step: 123.97 + 10%|█ | 891/8720 [2:22:02<16:39:17, 7.66s/it] {'loss': 1.14, 'grad_norm': 10.159034729003906, 'learning_rate': 9.86415948428065e-06, 'epoch': 1.02} + 10%|█ | 891/8720 [2:22:02<16:39:17, 7.66s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1934 +[2025-05-02 00:37:30,023] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 536.81 | bwd_microstep: 362.01 | bwd_inner_microstep: 361.99 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1981 +[2025-05-02 00:37:31,696] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 947.94 | bwd_microstep: 699.29 | bwd_inner_microstep: 699.27 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1940 +[2025-05-02 00:37:33,424] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 962.26 | bwd_microstep: 749.39 | bwd_inner_microstep: 749.37 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1934 +[2025-05-02 00:37:35,115] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 679.84 | bwd_microstep: 995.56 | bwd_inner_microstep: 995.54 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 368 +[2025-05-02 00:37:35,359] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 81.95 | bwd_microstep: 144.37 | bwd_inner_microstep: 144.35 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.32 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1911 +[2025-05-02 00:37:36,898] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 968.21 | bwd_microstep: 400.47 | bwd_inner_microstep: 400.45 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 855 +[2025-05-02 00:37:37,911] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 430.66 | bwd_microstep: 568.73 | bwd_inner_microstep: 568.67 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 00:37:39,286] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 553.73 | bwd_microstep: 760.74 | bwd_inner_microstep: 760.72 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1356 +[2025-05-02 00:37:40,355] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 725.50 | bwd_microstep: 327.68 | bwd_inner_microstep: 327.61 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 00:37:42,019] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 672.70 | bwd_microstep: 975.12 | bwd_inner_microstep: 975.11 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 840 +[2025-05-02 00:37:42,596] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.80 | bwd_microstep: 465.76 | bwd_inner_microstep: 465.75 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 838 +[2025-05-02 00:37:43,655] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 434.63 | bwd_microstep: 519.41 | bwd_inner_microstep: 519.35 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 00:37:45,226] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 210.49 | bwd_microstep: 1344.58 | bwd_inner_microstep: 1344.57 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 00:37:46,309] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 305.81 | bwd_microstep: 758.25 | bwd_inner_microstep: 758.17 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 00:37:47,551] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 872.35 | bwd_microstep: 349.21 | bwd_inner_microstep: 349.19 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 318 +[2025-05-02 00:37:48,764] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.07 | optimizer_step: 16.65 +[2025-05-02 00:37:48,764] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 439.11 | bwd_microstep: 727.58 | bwd_inner_microstep: 364.31 | bwd_allreduce_microstep: 363.10 | step_microstep: 24.19 +[2025-05-02 00:37:48,766] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 8916.59 | bwd: 10148.21 | bwd_inner: 9784.49 | bwd_allreduce: 363.24 | step: 29.98 + 10%|█ | 892/8720 [2:22:22<24:34:15, 11.30s/it] {'loss': 0.903, 'grad_norm': 4.771919250488281, 'learning_rate': 9.863729189899408e-06, 'epoch': 1.02} + 10%|█ | 892/8720 [2:22:22<24:34:15, 11.30s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1961 +[2025-05-02 00:37:50,407] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 264.51 | bwd_microstep: 1312.52 | bwd_inner_microstep: 1312.50 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2068 +[2025-05-02 00:37:51,871] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 323.88 | bwd_microstep: 1081.27 | bwd_inner_microstep: 1081.25 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1991 +[2025-05-02 00:37:53,524] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 611.85 | bwd_microstep: 1025.27 | bwd_inner_microstep: 1025.25 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1974 +[2025-05-02 00:37:55,021] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 601.73 | bwd_microstep: 835.07 | bwd_inner_microstep: 835.05 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1928 +[2025-05-02 00:37:56,223] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 861.42 | bwd_microstep: 322.67 | bwd_inner_microstep: 322.65 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.47 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1893 +[2025-05-02 00:37:57,905] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 966.98 | bwd_microstep: 684.74 | bwd_inner_microstep: 684.72 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 00:37:59,562] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 673.40 | bwd_microstep: 965.48 | bwd_inner_microstep: 965.46 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 00:38:01,210] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 477.15 | bwd_microstep: 1146.87 | bwd_inner_microstep: 1146.85 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 326 +[2025-05-02 00:38:01,442] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 84.62 | bwd_microstep: 127.90 | bwd_inner_microstep: 127.88 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.47 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 00:38:03,043] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 985.22 | bwd_microstep: 578.95 | bwd_inner_microstep: 578.94 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 00:38:05,088] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 918.48 | bwd_microstep: 1109.88 | bwd_inner_microstep: 1109.86 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 00:38:07,816] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 924.85 | bwd_microstep: 1596.27 | bwd_inner_microstep: 1596.25 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.14 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 00:38:10,349] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 969.27 | bwd_microstep: 1544.08 | bwd_inner_microstep: 1544.06 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 00:38:13,177] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 921.56 | bwd_microstep: 1595.95 | bwd_inner_microstep: 1595.93 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.13 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 00:38:15,701] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1061.72 | bwd_microstep: 1444.98 | bwd_inner_microstep: 1444.97 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 00:38:19,071] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.08 | optimizer_gradients: 2.07 | optimizer_step: 306.83 +[2025-05-02 00:38:19,072] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1118.86 | bwd_microstep: 1824.39 | bwd_inner_microstep: 1401.14 | bwd_allreduce_microstep: 423.18 | step_microstep: 315.21 +[2025-05-02 00:38:19,073] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 11765.28 | bwd: 17196.31 | bwd_inner: 16772.80 | bwd_allreduce: 423.25 | step: 323.56 + 10%|█ | 893/8720 [2:22:52<36:57:58, 17.00s/it] {'loss': 0.7823, 'grad_norm': 8.542582511901855, 'learning_rate': 9.863298224500793e-06, 'epoch': 1.02} + 10%|█ | 893/8720 [2:22:52<36:57:58, 17.00s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 00:38:21,606] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 919.10 | bwd_microstep: 1542.39 | bwd_inner_microstep: 1542.25 | bwd_allreduce_microstep: 0.09 | step_microstep: 0.15 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2067 +[2025-05-02 00:38:24,570] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 934.45 | bwd_microstep: 1717.13 | bwd_inner_microstep: 1717.11 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 872 +[2025-05-02 00:38:25,843] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 583.04 | bwd_microstep: 671.29 | bwd_inner_microstep: 670.95 | bwd_allreduce_microstep: 0.14 | step_microstep: 0.24 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1888 +[2025-05-02 00:38:28,375] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1208.59 | bwd_microstep: 1303.67 | bwd_inner_microstep: 1303.65 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.54 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1888 +[2025-05-02 00:38:31,258] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 873.69 | bwd_microstep: 1653.53 | bwd_inner_microstep: 1653.52 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.14 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-02 00:38:34,091] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1169.79 | bwd_microstep: 1597.22 | bwd_inner_microstep: 1597.20 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.14 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-02 00:38:36,623] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 967.92 | bwd_microstep: 1544.09 | bwd_inner_microstep: 1544.07 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.13 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-02 00:38:39,457] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 925.03 | bwd_microstep: 1598.83 | bwd_inner_microstep: 1598.82 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.14 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 00:38:41,974] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1055.46 | bwd_microstep: 1444.44 | bwd_inner_microstep: 1444.42 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.13 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 00:38:44,604] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1117.38 | bwd_microstep: 1399.39 | bwd_inner_microstep: 1399.37 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 00:38:47,141] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1213.55 | bwd_microstep: 1303.39 | bwd_inner_microstep: 1303.37 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.54 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 00:38:50,018] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 869.84 | bwd_microstep: 1650.90 | bwd_inner_microstep: 1650.88 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 00:38:52,539] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1109.06 | bwd_microstep: 1394.85 | bwd_inner_microstep: 1394.80 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.13 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 00:38:55,368] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 923.69 | bwd_microstep: 1595.77 | bwd_inner_microstep: 1595.75 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 00:38:57,884] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1056.08 | bwd_microstep: 1442.06 | bwd_inner_microstep: 1442.04 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 00:39:01,245] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.07 | optimizer_gradients: 50.64 | optimizer_step: 306.29 +[2025-05-02 00:39:01,246] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 923.67 | bwd_microstep: 1766.45 | bwd_inner_microstep: 1595.63 | bwd_allreduce_microstep: 170.73 | step_microstep: 362.72 +[2025-05-02 00:39:01,247] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 15899.34 | bwd: 23625.47 | bwd_inner: 23453.95 | bwd_allreduce: 170.99 | step: 365.50 + 10%|█ | 894/8720 [2:23:34<53:22:38, 24.55s/it] {'loss': 1.0746, 'grad_norm': 6.529347896575928, 'learning_rate': 9.862866588144263e-06, 'epoch': 1.03} + 10%|█ | 894/8720 [2:23:34<53:22:38, 24.55s/it]dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1570 +[2025-05-02 00:39:03,373] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 835.86 | bwd_microstep: 1268.49 | bwd_inner_microstep: 1268.31 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.13 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 358 +[2025-05-02 00:39:04,449] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 502.07 | bwd_microstep: 368.39 | bwd_inner_microstep: 368.19 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.13 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-02 00:39:07,016] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1053.52 | bwd_microstep: 1496.25 | bwd_inner_microstep: 1496.24 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-02 00:39:09,598] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1116.51 | bwd_microstep: 1400.11 | bwd_inner_microstep: 1400.10 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-02 00:39:12,481] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1212.90 | bwd_microstep: 1651.80 | bwd_inner_microstep: 1651.78 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.14 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 342 +[2025-05-02 00:39:13,332] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 611.66 | bwd_microstep: 222.21 | bwd_inner_microstep: 222.03 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-02 00:39:16,212] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1210.36 | bwd_microstep: 1651.71 | bwd_inner_microstep: 1651.69 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-02 00:39:18,744] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 870.16 | bwd_microstep: 1644.99 | bwd_inner_microstep: 1644.98 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 00:39:21,575] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1169.14 | bwd_microstep: 1597.44 | bwd_inner_microstep: 1597.42 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.15 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 837 +[2025-05-02 00:39:22,843] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 482.31 | bwd_microstep: 766.86 | bwd_inner_microstep: 766.69 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 00:39:25,674] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 975.58 | bwd_microstep: 1598.34 | bwd_inner_microstep: 1598.32 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.14 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 00:39:28,193] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1102.74 | bwd_microstep: 1396.20 | bwd_inner_microstep: 1396.18 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 00:39:30,821] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1119.57 | bwd_microstep: 1399.51 | bwd_inner_microstep: 1399.49 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.13 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 00:39:33,354] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1211.37 | bwd_microstep: 1301.90 | bwd_inner_microstep: 1301.88 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 00:39:36,235] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 868.75 | bwd_microstep: 1651.41 | bwd_inner_microstep: 1651.39 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 00:39:39,445] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.11 | optimizer_step: 16.83 +[2025-05-02 00:39:39,446] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1065.16 | bwd_microstep: 2103.85 | bwd_inner_microstep: 1444.09 | bwd_allreduce_microstep: 659.69 | step_microstep: 25.04 +[2025-05-02 00:39:39,447] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 15407.47 | bwd: 21519.56 | bwd_inner: 20858.98 | bwd_allreduce: 660.02 | step: 26.82 + 10%|█ | 895/8720 [2:24:13<62:16:07, 28.65s/it] {'loss': 0.9037, 'grad_norm': 10.874164581298828, 'learning_rate': 9.862434280889366e-06, 'epoch': 1.03} + 10%|█ | 895/8720 [2:24:13<62:16:07, 28.65s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 00:39:42,018] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1155.04 | bwd_microstep: 1350.73 | bwd_inner_microstep: 1350.65 | bwd_allreduce_microstep: 0.03 | step_microstep: 0.14 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1910 +[2025-05-02 00:39:44,605] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1117.26 | bwd_microstep: 1401.23 | bwd_inner_microstep: 1401.21 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 350 +[2025-05-02 00:39:45,696] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 707.39 | bwd_microstep: 367.49 | bwd_inner_microstep: 367.23 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1894 +[2025-05-02 00:39:48,221] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1061.59 | bwd_microstep: 1446.95 | bwd_inner_microstep: 1446.94 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 381 +[2025-05-02 00:39:49,103] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 410.47 | bwd_microstep: 367.33 | bwd_inner_microstep: 367.10 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.12 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1105 +[2025-05-02 00:39:50,718] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 508.14 | bwd_microstep: 1091.20 | bwd_inner_microstep: 1091.05 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.14 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 00:39:53,352] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1119.13 | bwd_microstep: 1400.26 | bwd_inner_microstep: 1400.24 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 00:39:55,887] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1212.95 | bwd_microstep: 1305.08 | bwd_inner_microstep: 1305.06 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.57 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 00:39:58,762] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 868.43 | bwd_microstep: 1650.07 | bwd_inner_microstep: 1650.05 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.12 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 838 +[2025-05-02 00:40:00,025] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 678.36 | bwd_microstep: 568.54 | bwd_inner_microstep: 568.38 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 00:40:02,538] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1054.30 | bwd_microstep: 1394.85 | bwd_inner_microstep: 1394.83 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.14 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 834 +[2025-05-02 00:40:03,795] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 433.11 | bwd_microstep: 568.95 | bwd_inner_microstep: 568.80 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.12 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1345 +[2025-05-02 00:40:05,865] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 531.10 | bwd_microstep: 1238.46 | bwd_inner_microstep: 1238.28 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 00:40:08,395] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1163.29 | bwd_microstep: 1349.75 | bwd_inner_microstep: 1349.74 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.13 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 828 +[2025-05-02 00:40:10,005] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 434.17 | bwd_microstep: 870.48 | bwd_inner_microstep: 870.29 | bwd_allreduce_microstep: 0.08 | step_microstep: 0.14 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 00:40:13,207] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 0.00 | optimizer_step: 109.09 +[2025-05-02 00:40:13,208] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 868.36 | bwd_microstep: 2004.06 | bwd_inner_microstep: 1639.85 | bwd_allreduce_microstep: 364.16 | step_microstep: 312.09 +[2025-05-02 00:40:13,209] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 13322.92 | bwd: 18375.58 | bwd_inner: 18009.98 | bwd_allreduce: 364.76 | step: 314.22 + 10%|█ | 896/8720 [2:24:46<65:35:44, 30.18s/it] {'loss': 0.7265, 'grad_norm': 6.778913974761963, 'learning_rate': 9.862001302795748e-06, 'epoch': 1.03} + 10%|█ | 896/8720 [2:24:46<65:35:44, 30.18s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 00:40:15,740] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 968.58 | bwd_microstep: 1540.33 | bwd_inner_microstep: 1540.31 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1921 +[2025-05-02 00:40:18,390] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1124.28 | bwd_microstep: 1409.76 | bwd_inner_microstep: 1409.75 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.13 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1899 +[2025-05-02 00:40:21,273] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1117.12 | bwd_microstep: 1651.11 | bwd_inner_microstep: 1651.09 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1887 +[2025-05-02 00:40:23,949] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1112.56 | bwd_microstep: 1546.52 | bwd_inner_microstep: 1546.50 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.14 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 00:40:26,625] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 920.56 | bwd_microstep: 1598.13 | bwd_inner_microstep: 1598.11 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.13 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 00:40:29,457] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1215.91 | bwd_microstep: 1597.19 | bwd_inner_microstep: 1597.17 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.15 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 00:40:31,985] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1063.81 | bwd_microstep: 1444.24 | bwd_inner_microstep: 1444.23 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 00:40:34,616] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1120.33 | bwd_microstep: 1401.11 | bwd_inner_microstep: 1401.09 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 00:40:37,441] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1206.41 | bwd_microstep: 1600.71 | bwd_inner_microstep: 1600.69 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.10 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 836 +[2025-05-02 00:40:38,752] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 480.28 | bwd_microstep: 765.82 | bwd_inner_microstep: 765.64 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.13 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 00:40:41,282] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 872.48 | bwd_microstep: 1640.56 | bwd_inner_microstep: 1640.54 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 00:40:44,111] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 922.72 | bwd_microstep: 1595.58 | bwd_inner_microstep: 1595.56 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 00:40:46,878] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1153.38 | bwd_microstep: 1595.80 | bwd_inner_microstep: 1595.79 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.15 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 00:40:49,455] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 920.77 | bwd_microstep: 1589.96 | bwd_inner_microstep: 1589.94 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.14 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 00:40:52,090] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1216.76 | bwd_microstep: 1398.98 | bwd_inner_microstep: 1398.89 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 00:40:55,361] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.11 | optimizer_step: 16.78 +[2025-05-02 00:40:55,362] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1212.51 | bwd_microstep: 2015.28 | bwd_inner_microstep: 1305.83 | bwd_allreduce_microstep: 709.41 | step_microstep: 24.52 +[2025-05-02 00:40:55,363] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 16628.21 | bwd: 24391.18 | bwd_inner: 23681.20 | bwd_allreduce: 709.59 | step: 26.27 + 10%|█ | 897/8720 [2:25:29<73:23:30, 33.77s/it] {'loss': 0.8009, 'grad_norm': 7.410303115844727, 'learning_rate': 9.86156765392314e-06, 'epoch': 1.03} + 10%|█ | 897/8720 [2:25:29<73:23:30, 33.77s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 316 +[2025-05-02 00:40:56,243] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 254.38 | bwd_microstep: 415.67 | bwd_inner_microstep: 415.48 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1957 +[2025-05-02 00:40:59,086] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1117.49 | bwd_microstep: 1708.35 | bwd_inner_microstep: 1708.33 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1946 +[2025-05-02 00:41:01,932] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1073.82 | bwd_microstep: 1754.21 | bwd_inner_microstep: 1754.19 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.14 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 895 +[2025-05-02 00:41:03,213] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 539.10 | bwd_microstep: 723.09 | bwd_inner_microstep: 722.93 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1894 +[2025-05-02 00:41:05,828] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1101.81 | bwd_microstep: 1452.55 | bwd_inner_microstep: 1452.53 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 861 +[2025-05-02 00:41:07,101] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 583.31 | bwd_microstep: 671.56 | bwd_inner_microstep: 671.46 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-02 00:41:09,635] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1208.99 | bwd_microstep: 1307.46 | bwd_inner_microstep: 1307.44 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.56 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-02 00:41:12,512] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 870.24 | bwd_microstep: 1650.06 | bwd_inner_microstep: 1650.05 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 00:41:15,036] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1110.69 | bwd_microstep: 1396.75 | bwd_inner_microstep: 1396.73 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-02 00:41:17,867] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 923.43 | bwd_microstep: 1598.73 | bwd_inner_microstep: 1598.71 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 00:41:20,389] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1058.65 | bwd_microstep: 1445.37 | bwd_inner_microstep: 1445.35 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.10 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1351 +[2025-05-02 00:41:22,514] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 583.73 | bwd_microstep: 1238.89 | bwd_inner_microstep: 1238.66 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.15 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 00:41:25,048] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 870.41 | bwd_microstep: 1646.11 | bwd_inner_microstep: 1646.01 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.13 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 00:41:27,879] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 925.03 | bwd_microstep: 1594.65 | bwd_inner_microstep: 1594.62 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.13 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 319 +[2025-05-02 00:41:28,773] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 459.44 | bwd_microstep: 418.60 | bwd_inner_microstep: 418.40 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 00:41:31,987] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.17 | optimizer_step: 16.80 +[2025-05-02 00:41:31,988] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 971.87 | bwd_microstep: 2201.24 | bwd_inner_microstep: 1542.24 | bwd_allreduce_microstep: 658.95 | step_microstep: 24.87 +[2025-05-02 00:41:31,989] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 13652.17 | bwd: 21223.40 | bwd_inner: 20563.36 | bwd_allreduce: 659.39 | step: 26.91 + 10%|█ | 898/8720 [2:26:05<75:14:30, 34.63s/it] {'loss': 1.2444, 'grad_norm': 6.880184173583984, 'learning_rate': 9.861133334331375e-06, 'epoch': 1.03} + 10%|█ | 898/8720 [2:26:05<75:14:30, 34.63s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1930 +[2025-05-02 00:41:34,640] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1171.78 | bwd_microstep: 1412.87 | bwd_inner_microstep: 1412.76 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.22 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1898 +[2025-05-02 00:41:37,533] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1219.24 | bwd_microstep: 1654.09 | bwd_inner_microstep: 1654.07 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1371 +[2025-05-02 00:41:39,508] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 817.25 | bwd_microstep: 1141.45 | bwd_inner_microstep: 1141.34 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.15 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 342 +[2025-05-02 00:41:40,391] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 308.15 | bwd_microstep: 514.78 | bwd_inner_microstep: 514.62 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-02 00:41:42,920] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 968.03 | bwd_microstep: 1543.35 | bwd_inner_microstep: 1543.33 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-02 00:41:45,751] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 922.50 | bwd_microstep: 1598.03 | bwd_inner_microstep: 1598.01 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.14 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1362 +[2025-05-02 00:41:47,885] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 875.14 | bwd_microstep: 1239.75 | bwd_inner_microstep: 1239.46 | bwd_allreduce_microstep: 0.14 | step_microstep: 0.22 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 00:41:50,415] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 920.79 | bwd_microstep: 1589.98 | bwd_inner_microstep: 1589.96 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.12 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 844 +[2025-05-02 00:41:51,975] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 286.13 | bwd_microstep: 1068.19 | bwd_inner_microstep: 1068.02 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.15 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 00:41:54,506] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 923.82 | bwd_microstep: 1589.95 | bwd_inner_microstep: 1589.94 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 00:41:57,140] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1117.81 | bwd_microstep: 1399.15 | bwd_inner_microstep: 1399.13 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.13 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 00:41:59,966] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1206.41 | bwd_microstep: 1600.75 | bwd_inner_microstep: 1600.73 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.17 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 320 +[2025-05-02 00:42:00,752] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 347.95 | bwd_microstep: 373.71 | bwd_inner_microstep: 373.56 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.11 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 323 +[2025-05-02 00:42:01,641] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 406.38 | bwd_microstep: 369.62 | bwd_inner_microstep: 369.35 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 00:42:04,454] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1149.99 | bwd_microstep: 1597.83 | bwd_inner_microstep: 1597.79 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.16 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 00:42:07,514] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.09 | optimizer_gradients: 0.00 | optimizer_step: 158.40 +[2025-05-02 00:42:07,514] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 920.58 | bwd_microstep: 1758.80 | bwd_inner_microstep: 1589.22 | bwd_allreduce_microstep: 169.47 | step_microstep: 361.31 +[2025-05-02 00:42:07,515] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 13561.73 | bwd: 20452.46 | bwd_inner: 20281.54 | bwd_allreduce: 170.05 | step: 412.64 + 10%|█ | 899/8720 [2:26:41<75:49:00, 34.90s/it] {'loss': 1.0773, 'grad_norm': 7.404858112335205, 'learning_rate': 9.860698344080368e-06, 'epoch': 1.03} + 10%|█ | 899/8720 [2:26:41<75:49:00, 34.90s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 00:42:10,048] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1114.56 | bwd_microstep: 1395.68 | bwd_inner_microstep: 1395.67 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.14 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1903 +[2025-05-02 00:42:12,877] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 921.45 | bwd_microstep: 1600.82 | bwd_inner_microstep: 1600.80 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.14 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1921 +[2025-05-02 00:42:15,727] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1172.91 | bwd_microstep: 1609.47 | bwd_inner_microstep: 1609.44 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.23 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1922 +[2025-05-02 00:42:18,381] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1123.64 | bwd_microstep: 1413.30 | bwd_inner_microstep: 1413.28 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 347 +[2025-05-02 00:42:19,459] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 599.24 | bwd_microstep: 366.58 | bwd_inner_microstep: 366.24 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.22 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-02 00:42:21,979] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1057.42 | bwd_microstep: 1445.39 | bwd_inner_microstep: 1445.33 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.14 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 00:42:24,612] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1117.91 | bwd_microstep: 1402.09 | bwd_inner_microstep: 1402.08 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.13 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 837 +[2025-05-02 00:42:25,878] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 731.39 | bwd_microstep: 517.30 | bwd_inner_microstep: 517.14 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 00:42:28,400] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1201.61 | bwd_microstep: 1303.64 | bwd_inner_microstep: 1303.62 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.57 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 00:42:31,275] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 869.48 | bwd_microstep: 1649.29 | bwd_inner_microstep: 1649.25 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.22 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1345 +[2025-05-02 00:42:33,355] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 823.37 | bwd_microstep: 1237.85 | bwd_inner_microstep: 1237.81 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.13 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 00:42:35,882] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1116.27 | bwd_microstep: 1393.49 | bwd_inner_microstep: 1393.47 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 00:42:38,407] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1207.16 | bwd_microstep: 1300.74 | bwd_inner_microstep: 1300.72 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.22 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 00:42:41,286] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 869.97 | bwd_microstep: 1649.26 | bwd_inner_microstep: 1649.18 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.17 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 00:42:43,808] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1111.14 | bwd_microstep: 1394.04 | bwd_inner_microstep: 1394.03 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 00:42:47,124] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.19 | optimizer_step: 113.66 +[2025-05-02 00:42:47,124] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 923.70 | bwd_microstep: 1959.44 | bwd_inner_microstep: 1595.86 | bwd_allreduce_microstep: 363.52 | step_microstep: 121.71 +[2025-05-02 00:42:47,125] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 15960.79 | bwd: 21638.59 | bwd_inner: 21274.03 | bwd_allreduce: 363.82 | step: 124.33 + 10%|█ | 900/8720 [2:27:20<78:52:39, 36.31s/it] {'loss': 0.6454, 'grad_norm': 9.846219062805176, 'learning_rate': 9.860262683230137e-06, 'epoch': 1.03} + 10%|█ | 900/8720 [2:27:20<78:52:39, 36.31s/it][INFO|trainer.py:3503] 2025-05-02 00:43:03,751 >> Saving model checkpoint to work_dirs/internvl_chat_v2_5/ak/checkpoint-900 +[INFO|configuration_utils.py:472] 2025-05-02 00:43:03,756 >> Configuration saved in work_dirs/internvl_chat_v2_5/ak/checkpoint-900/config.json +[INFO|configuration_utils.py:807] 2025-05-02 00:43:03,756 >> Configuration saved in work_dirs/internvl_chat_v2_5/ak/checkpoint-900/generation_config.json +[INFO|modeling_utils.py:2755] 2025-05-02 00:43:09,343 >> Model weights saved in work_dirs/internvl_chat_v2_5/ak/checkpoint-900/model.safetensors +[INFO|tokenization_utils_base.py:2702] 2025-05-02 00:43:09,345 >> tokenizer config file saved in work_dirs/internvl_chat_v2_5/ak/checkpoint-900/tokenizer_config.json +[INFO|tokenization_utils_base.py:2711] 2025-05-02 00:43:09,345 >> Special tokens file saved in work_dirs/internvl_chat_v2_5/ak/checkpoint-900/special_tokens_map.json +[INFO|tokenization_utils_base.py:2762] 2025-05-02 00:43:09,345 >> added tokens file saved in work_dirs/internvl_chat_v2_5/ak/checkpoint-900/added_tokens.json +[2025-05-02 00:43:09,563] [INFO] [logging.py:96:log_dist] [Rank 0] [Torch] Checkpoint global_step900 is about to be saved! +[2025-05-02 00:43:09,581] [INFO] [logging.py:96:log_dist] [Rank 0] Saving model checkpoint: work_dirs/internvl_chat_v2_5/ak/checkpoint-900/global_step900/mp_rank_00_model_states.pt +[2025-05-02 00:43:09,581] [INFO] [torch_checkpoint_engine.py:21:save] [Torch] Saving work_dirs/internvl_chat_v2_5/ak/checkpoint-900/global_step900/mp_rank_00_model_states.pt... +[2025-05-02 00:43:30,260] [INFO] [torch_checkpoint_engine.py:23:save] [Torch] Saved work_dirs/internvl_chat_v2_5/ak/checkpoint-900/global_step900/mp_rank_00_model_states.pt. +[2025-05-02 00:43:30,263] [INFO] [torch_checkpoint_engine.py:21:save] [Torch] Saving work_dirs/internvl_chat_v2_5/ak/checkpoint-900/global_step900/bf16_zero_pp_rank_0_mp_rank_00_optim_states.pt... +[2025-05-02 00:43:30,499] [INFO] [torch_checkpoint_engine.py:23:save] [Torch] Saved work_dirs/internvl_chat_v2_5/ak/checkpoint-900/global_step900/bf16_zero_pp_rank_0_mp_rank_00_optim_states.pt. +[2025-05-02 00:43:30,499] [INFO] [engine.py:3536:_save_zero_checkpoint] zero checkpoint saved work_dirs/internvl_chat_v2_5/ak/checkpoint-900/global_step900/bf16_zero_pp_rank_0_mp_rank_00_optim_states.pt +[2025-05-02 00:43:30,499] [INFO] [torch_checkpoint_engine.py:33:commit] [Torch] Checkpoint global_step900 is ready now! +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 00:43:33,101] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 923.92 | bwd_microstep: 1593.18 | bwd_inner_microstep: 1593.10 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2005 +[2025-05-02 00:43:35,761] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1222.77 | bwd_microstep: 1421.14 | bwd_inner_microstep: 1421.12 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 428 +[2025-05-02 00:43:36,842] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 501.37 | bwd_microstep: 372.91 | bwd_inner_microstep: 372.60 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1898 +[2025-05-02 00:43:39,480] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1218.82 | bwd_microstep: 1403.63 | bwd_inner_microstep: 1403.61 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1904 +[2025-05-02 00:43:42,309] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1212.54 | bwd_microstep: 1600.75 | bwd_inner_microstep: 1600.74 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-02 00:43:44,893] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 869.67 | bwd_microstep: 1649.74 | bwd_inner_microstep: 1649.73 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-02 00:43:47,412] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1103.60 | bwd_microstep: 1397.70 | bwd_inner_microstep: 1397.69 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 00:43:50,240] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 923.34 | bwd_microstep: 1597.45 | bwd_inner_microstep: 1597.43 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 6, images per sample: 6.0, dynamic token length: 1613 +[2025-05-02 00:43:52,725] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 900.47 | bwd_microstep: 1568.91 | bwd_inner_microstep: 1568.89 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 00:43:55,252] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 922.18 | bwd_microstep: 1589.40 | bwd_inner_microstep: 1589.39 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.15 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 00:43:57,771] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1059.69 | bwd_microstep: 1444.32 | bwd_inner_microstep: 1444.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 330 +[2025-05-02 00:43:58,647] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 304.14 | bwd_microstep: 417.17 | bwd_inner_microstep: 416.96 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.10 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1346 +[2025-05-02 00:44:00,723] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 824.73 | bwd_microstep: 1236.14 | bwd_inner_microstep: 1236.12 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 00:44:03,255] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1118.00 | bwd_microstep: 1398.88 | bwd_inner_microstep: 1398.86 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 00:44:05,776] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1206.17 | bwd_microstep: 1299.64 | bwd_inner_microstep: 1299.63 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1341 +[2025-05-02 00:44:08,638] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.08 | optimizer_gradients: 2.14 | optimizer_step: 373.62 +[2025-05-02 00:44:08,638] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 868.27 | bwd_microstep: 1405.03 | bwd_inner_microstep: 1238.44 | bwd_allreduce_microstep: 166.50 | step_microstep: 381.38 +[2025-05-02 00:44:08,639] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 15179.48 | bwd: 21396.08 | bwd_inner: 21228.75 | bwd_allreduce: 166.77 | step: 382.47 + 10%|█ | 901/8720 [2:28:42<108:19:10, 49.87s/it] {'loss': 0.8968, 'grad_norm': 5.986011981964111, 'learning_rate': 9.859826351840784e-06, 'epoch': 1.03} + 10%|█ | 901/8720 [2:28:42<108:19:10, 49.87s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 00:44:11,173] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 869.58 | bwd_microstep: 1642.86 | bwd_inner_microstep: 1642.85 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2005 +[2025-05-02 00:44:14,031] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1177.39 | bwd_microstep: 1617.91 | bwd_inner_microstep: 1617.90 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1883 +[2025-05-02 00:44:16,863] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 921.55 | bwd_microstep: 1599.53 | bwd_inner_microstep: 1599.51 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-02 00:44:19,387] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1060.61 | bwd_microstep: 1445.18 | bwd_inner_microstep: 1445.16 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1361 +[2025-05-02 00:44:21,518] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 778.00 | bwd_microstep: 1240.46 | bwd_inner_microstep: 1240.28 | bwd_allreduce_microstep: 0.08 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-02 00:44:24,044] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 921.41 | bwd_microstep: 1588.83 | bwd_inner_microstep: 1588.81 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 00:44:26,552] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1002.82 | bwd_microstep: 1445.25 | bwd_inner_microstep: 1445.23 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 00:44:29,383] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 923.89 | bwd_microstep: 1597.04 | bwd_inner_microstep: 1597.02 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 00:44:31,907] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1064.00 | bwd_microstep: 1443.12 | bwd_inner_microstep: 1443.11 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 00:44:34,536] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1117.38 | bwd_microstep: 1398.67 | bwd_inner_microstep: 1398.66 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 00:44:37,063] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1115.73 | bwd_microstep: 1395.73 | bwd_inner_microstep: 1395.72 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 00:44:39,937] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1015.87 | bwd_microstep: 1650.54 | bwd_inner_microstep: 1650.53 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 00:44:42,460] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1113.97 | bwd_microstep: 1393.28 | bwd_inner_microstep: 1393.26 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 00:44:45,285] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 921.60 | bwd_microstep: 1595.32 | bwd_inner_microstep: 1595.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 00:44:47,802] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1057.58 | bwd_microstep: 1442.79 | bwd_inner_microstep: 1442.77 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 316 +[2025-05-02 00:44:49,359] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.07 | optimizer_gradients: 50.91 | optimizer_step: 256.88 +[2025-05-02 00:44:49,360] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 302.95 | bwd_microstep: 788.67 | bwd_inner_microstep: 425.63 | bwd_allreduce_microstep: 362.88 | step_microstep: 313.52 +[2025-05-02 00:44:49,361] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 15364.13 | bwd: 23285.22 | bwd_inner: 22921.84 | bwd_allreduce: 363.00 | step: 314.50 + 10%|█ | 902/8720 [2:29:23<102:20:39, 47.13s/it] {'loss': 0.9443, 'grad_norm': 5.119144916534424, 'learning_rate': 9.859389349972505e-06, 'epoch': 1.03} + 10%|█ | 902/8720 [2:29:23<102:20:39, 47.13s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 00:44:51,891] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 969.29 | bwd_microstep: 1539.93 | bwd_inner_microstep: 1539.87 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2103 +[2025-05-02 00:44:54,919] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1131.47 | bwd_microstep: 1782.99 | bwd_inner_microstep: 1782.94 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.26 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 435 +[2025-05-02 00:44:55,778] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 669.54 | bwd_microstep: 172.93 | bwd_inner_microstep: 172.76 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.09 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1375 +[2025-05-02 00:44:58,114] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1079.18 | bwd_microstep: 1241.16 | bwd_inner_microstep: 1241.04 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-02 00:45:00,641] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1065.15 | bwd_microstep: 1445.91 | bwd_inner_microstep: 1445.89 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1887 +[2025-05-02 00:45:03,271] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1119.21 | bwd_microstep: 1403.51 | bwd_inner_microstep: 1403.49 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1889 +[2025-05-02 00:45:06,157] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1216.01 | bwd_microstep: 1651.43 | bwd_inner_microstep: 1651.41 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 328 +[2025-05-02 00:45:07,011] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 655.13 | bwd_microstep: 172.69 | bwd_inner_microstep: 172.44 | bwd_allreduce_microstep: 0.10 | step_microstep: 0.09 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 320 +[2025-05-02 00:45:08,097] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 658.07 | bwd_microstep: 415.41 | bwd_inner_microstep: 415.17 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 00:45:10,623] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 968.89 | bwd_microstep: 1541.37 | bwd_inner_microstep: 1541.35 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 00:45:13,255] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1117.35 | bwd_microstep: 1400.23 | bwd_inner_microstep: 1400.21 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 00:45:15,783] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1165.44 | bwd_microstep: 1346.99 | bwd_inner_microstep: 1346.97 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 318 +[2025-05-02 00:45:16,859] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 598.48 | bwd_microstep: 365.62 | bwd_inner_microstep: 365.47 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 00:45:19,382] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1014.90 | bwd_microstep: 1493.29 | bwd_inner_microstep: 1493.28 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 00:45:22,012] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1117.63 | bwd_microstep: 1399.06 | bwd_inner_microstep: 1399.04 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1903 +[2025-05-02 00:45:25,282] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.15 | optimizer_step: 16.57 +[2025-05-02 00:45:25,283] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1215.48 | bwd_microstep: 2014.19 | bwd_inner_microstep: 1307.94 | bwd_allreduce_microstep: 706.20 | step_microstep: 24.03 +[2025-05-02 00:45:25,284] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 15760.96 | bwd: 19386.86 | bwd_inner: 18679.57 | bwd_allreduce: 706.59 | step: 25.49 + 10%|█ | 903/8720 [2:29:59<95:01:56, 43.77s/it] {'loss': 1.0797, 'grad_norm': 5.921450138092041, 'learning_rate': 9.858951677685595e-06, 'epoch': 1.04} + 10%|█ | 903/8720 [2:29:59<95:01:56, 43.77s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1883 +[2025-05-02 00:45:28,121] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 923.79 | bwd_microstep: 1597.31 | bwd_inner_microstep: 1597.29 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.08 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 856 +[2025-05-02 00:45:29,496] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 537.03 | bwd_microstep: 819.79 | bwd_inner_microstep: 770.33 | bwd_allreduce_microstep: 49.37 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 342 +[2025-05-02 00:45:30,282] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 402.96 | bwd_microstep: 370.29 | bwd_inner_microstep: 369.98 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 00:45:33,100] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1157.01 | bwd_microstep: 1596.96 | bwd_inner_microstep: 1596.94 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 00:45:35,630] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 921.79 | bwd_microstep: 1590.58 | bwd_inner_microstep: 1590.57 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 00:45:38,148] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1057.18 | bwd_microstep: 1445.38 | bwd_inner_microstep: 1445.36 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 00:45:40,780] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1119.31 | bwd_microstep: 1401.30 | bwd_inner_microstep: 1401.29 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 00:45:43,315] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1210.74 | bwd_microstep: 1306.39 | bwd_inner_microstep: 1306.37 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.53 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 00:45:46,191] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 868.21 | bwd_microstep: 1652.34 | bwd_inner_microstep: 1652.32 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 00:45:48,716] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1111.37 | bwd_microstep: 1397.35 | bwd_inner_microstep: 1397.33 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 00:45:51,546] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 924.96 | bwd_microstep: 1597.71 | bwd_inner_microstep: 1597.69 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 00:45:54,069] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1061.57 | bwd_microstep: 1445.97 | bwd_inner_microstep: 1445.95 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 00:45:56,899] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 924.79 | bwd_microstep: 1596.63 | bwd_inner_microstep: 1596.61 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 00:45:59,422] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1058.63 | bwd_microstep: 1444.52 | bwd_inner_microstep: 1444.50 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 00:46:02,053] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1117.99 | bwd_microstep: 1399.63 | bwd_inner_microstep: 1399.61 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 00:46:05,317] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.16 | optimizer_step: 16.79 +[2025-05-02 00:46:05,317] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1212.65 | bwd_microstep: 2011.96 | bwd_inner_microstep: 1601.19 | bwd_allreduce_microstep: 410.73 | step_microstep: 24.42 +[2025-05-02 00:46:05,318] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 15609.72 | bwd: 22674.13 | bwd_inner: 22213.42 | bwd_allreduce: 460.26 | step: 25.98 + 10%|█ | 904/8720 [2:30:39<92:35:24, 42.65s/it] {'loss': 0.6492, 'grad_norm': 8.224006652832031, 'learning_rate': 9.858513335040434e-06, 'epoch': 1.04} + 10%|█ | 904/8720 [2:30:39<92:35:24, 42.65s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 315 +[2025-05-02 00:46:06,196] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 206.40 | bwd_microstep: 413.74 | bwd_inner_microstep: 413.56 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.17 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 1092 +[2025-05-02 00:46:07,807] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 692.19 | bwd_microstep: 900.37 | bwd_inner_microstep: 900.31 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1905 +[2025-05-02 00:46:10,629] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1155.15 | bwd_microstep: 1602.37 | bwd_inner_microstep: 1602.35 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-02 00:46:13,162] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 971.03 | bwd_microstep: 1542.68 | bwd_inner_microstep: 1542.58 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-02 00:46:15,790] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1117.32 | bwd_microstep: 1400.93 | bwd_inner_microstep: 1400.92 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 00:46:18,614] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1208.41 | bwd_microstep: 1600.25 | bwd_inner_microstep: 1600.23 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.11 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 846 +[2025-05-02 00:46:19,933] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 531.44 | bwd_microstep: 723.16 | bwd_inner_microstep: 722.84 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.20 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1352 +[2025-05-02 00:46:22,011] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 823.73 | bwd_microstep: 1238.52 | bwd_inner_microstep: 1238.39 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 00:46:24,535] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1115.40 | bwd_microstep: 1393.80 | bwd_inner_microstep: 1393.78 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 00:46:27,421] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1215.51 | bwd_microstep: 1651.22 | bwd_inner_microstep: 1651.20 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 325 +[2025-05-02 00:46:28,265] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 363.32 | bwd_microstep: 466.10 | bwd_inner_microstep: 465.95 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 00:46:30,800] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1166.05 | bwd_microstep: 1353.79 | bwd_inner_microstep: 1353.77 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.58 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 00:46:33,673] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 868.90 | bwd_microstep: 1648.78 | bwd_inner_microstep: 1648.76 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 833 +[2025-05-02 00:46:34,936] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 677.98 | bwd_microstep: 571.01 | bwd_inner_microstep: 570.91 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.13 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 00:46:37,754] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1157.09 | bwd_microstep: 1597.72 | bwd_inner_microstep: 1597.70 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 00:46:40,765] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.07 | optimizer_gradients: 2.07 | optimizer_step: 109.18 +[2025-05-02 00:46:40,765] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 923.26 | bwd_microstep: 1955.36 | bwd_inner_microstep: 1591.75 | bwd_allreduce_microstep: 363.56 | step_microstep: 116.86 +[2025-05-02 00:46:40,767] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 14192.97 | bwd: 20060.01 | bwd_inner: 19695.17 | bwd_allreduce: 364.09 | step: 118.99 + 10%|█ | 905/8720 [2:31:14<87:53:24, 40.49s/it] {'loss': 0.8387, 'grad_norm': 4.81063175201416, 'learning_rate': 9.858074322097499e-06, 'epoch': 1.04} + 10%|█ | 905/8720 [2:31:14<87:53:24, 40.49s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1850 +[2025-05-02 00:46:43,298] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1116.92 | bwd_microstep: 1394.99 | bwd_inner_microstep: 1394.98 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 346 +[2025-05-02 00:46:44,381] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 702.05 | bwd_microstep: 366.49 | bwd_inner_microstep: 366.19 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-02 00:46:46,903] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1062.51 | bwd_microstep: 1444.42 | bwd_inner_microstep: 1444.40 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-02 00:46:49,537] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1119.11 | bwd_microstep: 1401.29 | bwd_inner_microstep: 1401.27 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 6, images per sample: 6.0, dynamic token length: 1618 +[2025-05-02 00:46:52,023] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1096.72 | bwd_microstep: 1374.44 | bwd_inner_microstep: 1374.42 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 00:46:54,549] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1116.46 | bwd_microstep: 1393.87 | bwd_inner_microstep: 1393.85 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 00:46:57,080] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1208.82 | bwd_microstep: 1305.95 | bwd_inner_microstep: 1305.93 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.58 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 00:46:59,958] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 873.00 | bwd_microstep: 1649.64 | bwd_inner_microstep: 1649.62 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 00:47:02,481] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1111.54 | bwd_microstep: 1395.60 | bwd_inner_microstep: 1395.58 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 00:47:05,311] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 924.72 | bwd_microstep: 1596.38 | bwd_inner_microstep: 1596.36 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 00:47:07,836] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1063.50 | bwd_microstep: 1443.74 | bwd_inner_microstep: 1443.72 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 00:47:10,663] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 921.55 | bwd_microstep: 1595.90 | bwd_inner_microstep: 1595.88 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 00:47:13,187] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1015.22 | bwd_microstep: 1491.08 | bwd_inner_microstep: 1491.06 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 00:47:15,816] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1121.36 | bwd_microstep: 1398.34 | bwd_inner_microstep: 1398.33 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 00:47:18,348] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1119.22 | bwd_microstep: 1395.20 | bwd_inner_microstep: 1395.18 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1405 +[2025-05-02 00:47:21,217] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.07 | optimizer_gradients: 2.10 | optimizer_step: 365.84 +[2025-05-02 00:47:21,217] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 973.21 | bwd_microstep: 1409.35 | bwd_inner_microstep: 1243.12 | bwd_allreduce_microstep: 166.14 | step_microstep: 373.42 +[2025-05-02 00:47:21,218] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 16545.65 | bwd: 22056.70 | bwd_inner: 21889.98 | bwd_allreduce: 166.35 | step: 374.76 + 10%|█ | 906/8720 [2:31:54<87:51:22, 40.48s/it] {'loss': 0.4509, 'grad_norm': 7.039706230163574, 'learning_rate': 9.857634638917355e-06, 'epoch': 1.04} + 10%|█ | 906/8720 [2:31:54<87:51:22, 40.48s/it]dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1122 +[2025-05-02 00:47:22,839] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 704.73 | bwd_microstep: 895.94 | bwd_inner_microstep: 895.62 | bwd_allreduce_microstep: 0.15 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1928 +[2025-05-02 00:47:25,692] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1223.65 | bwd_microstep: 1614.23 | bwd_inner_microstep: 1614.21 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1887 +[2025-05-02 00:47:28,330] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1170.45 | bwd_microstep: 1401.89 | bwd_inner_microstep: 1401.87 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 00:47:31,160] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1213.23 | bwd_microstep: 1600.99 | bwd_inner_microstep: 1600.97 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 00:47:33,739] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 868.52 | bwd_microstep: 1646.23 | bwd_inner_microstep: 1646.21 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1351 +[2025-05-02 00:47:35,816] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 824.88 | bwd_microstep: 1237.08 | bwd_inner_microstep: 1237.07 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1098 +[2025-05-02 00:47:37,484] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 754.70 | bwd_microstep: 899.32 | bwd_inner_microstep: 899.15 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 00:47:40,315] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1218.42 | bwd_microstep: 1596.48 | bwd_inner_microstep: 1596.45 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 00:47:42,841] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1062.61 | bwd_microstep: 1444.76 | bwd_inner_microstep: 1444.73 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 00:47:45,671] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 924.16 | bwd_microstep: 1599.22 | bwd_inner_microstep: 1599.20 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 00:47:48,306] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1218.84 | bwd_microstep: 1400.06 | bwd_inner_microstep: 1400.04 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 00:47:51,137] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1212.55 | bwd_microstep: 1600.40 | bwd_inner_microstep: 1600.38 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 00:47:53,716] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 869.97 | bwd_microstep: 1644.54 | bwd_inner_microstep: 1644.19 | bwd_allreduce_microstep: 0.20 | step_microstep: 0.27 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 00:47:56,545] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1217.43 | bwd_microstep: 1594.79 | bwd_inner_microstep: 1594.77 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 00:47:59,075] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 971.37 | bwd_microstep: 1540.94 | bwd_inner_microstep: 1540.93 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 00:48:02,449] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.07 | optimizer_gradients: 2.11 | optimizer_step: 373.67 +[2025-05-02 00:48:02,450] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 972.12 | bwd_microstep: 1765.19 | bwd_inner_microstep: 1595.88 | bwd_allreduce_microstep: 169.26 | step_microstep: 381.31 +[2025-05-02 00:48:02,451] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 16427.39 | bwd: 23482.16 | bwd_inner: 23311.73 | bwd_allreduce: 169.69 | step: 382.79 + 10%|█ | 907/8720 [2:32:36<88:20:14, 40.70s/it] {'loss': 0.6183, 'grad_norm': 5.1184983253479, 'learning_rate': 9.857194285560666e-06, 'epoch': 1.04} + 10%|█ | 907/8720 [2:32:36<88:20:14, 40.70s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1918 +[2025-05-02 00:48:04,991] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1121.14 | bwd_microstep: 1398.42 | bwd_inner_microstep: 1398.41 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2201 +[2025-05-02 00:48:08,165] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 942.54 | bwd_microstep: 1924.66 | bwd_inner_microstep: 1924.65 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.10 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 383 +[2025-05-02 00:48:09,064] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 168.84 | bwd_microstep: 714.24 | bwd_inner_microstep: 714.11 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-02 00:48:11,593] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1018.88 | bwd_microstep: 1494.53 | bwd_inner_microstep: 1494.51 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 00:48:14,422] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 921.63 | bwd_microstep: 1598.59 | bwd_inner_microstep: 1598.58 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 00:48:16,949] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1062.76 | bwd_microstep: 1446.86 | bwd_inner_microstep: 1446.84 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1350 +[2025-05-02 00:48:19,077] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 778.95 | bwd_microstep: 1239.47 | bwd_inner_microstep: 1239.25 | bwd_allreduce_microstep: 0.14 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 00:48:21,607] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 972.79 | bwd_microstep: 1541.93 | bwd_inner_microstep: 1541.91 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 00:48:24,438] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 922.50 | bwd_microstep: 1597.66 | bwd_inner_microstep: 1597.64 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 00:48:26,965] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1062.86 | bwd_microstep: 1446.54 | bwd_inner_microstep: 1446.52 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 00:48:29,589] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1119.70 | bwd_microstep: 1398.67 | bwd_inner_microstep: 1398.65 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.13 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 00:48:32,120] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1117.26 | bwd_microstep: 1396.12 | bwd_inner_microstep: 1396.10 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 00:48:34,996] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1114.39 | bwd_microstep: 1649.91 | bwd_inner_microstep: 1649.89 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 00:48:37,524] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 871.04 | bwd_microstep: 1639.45 | bwd_inner_microstep: 1639.43 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 316 +[2025-05-02 00:48:38,352] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 598.28 | bwd_microstep: 169.19 | bwd_inner_microstep: 169.06 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1953 +[2025-05-02 00:48:41,735] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.09 | optimizer_step: 65.91 +[2025-05-02 00:48:41,784] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1215.87 | bwd_microstep: 2031.34 | bwd_inner_microstep: 1668.13 | bwd_allreduce_microstep: 363.15 | step_microstep: 170.09 +[2025-05-02 00:48:41,786] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 15009.21 | bwd: 22687.61 | bwd_inner: 22323.72 | bwd_allreduce: 363.44 | step: 171.40 + 10%|█ | 908/8720 [2:33:15<87:27:58, 40.31s/it] {'loss': 1.0728, 'grad_norm': 5.853854656219482, 'learning_rate': 9.85675326208818e-06, 'epoch': 1.04} + 10%|█ | 908/8720 [2:33:15<87:27:58, 40.31s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1897 +[2025-05-02 00:48:44,466] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 924.26 | bwd_microstep: 1599.28 | bwd_inner_microstep: 1599.26 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1953 +[2025-05-02 00:48:47,122] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1222.42 | bwd_microstep: 1417.47 | bwd_inner_microstep: 1417.45 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-02 00:48:49,946] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1207.74 | bwd_microstep: 1601.05 | bwd_inner_microstep: 1601.03 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.13 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 00:48:52,527] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 871.66 | bwd_microstep: 1644.55 | bwd_inner_microstep: 1644.53 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-02 00:48:55,341] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1151.45 | bwd_microstep: 1646.70 | bwd_inner_microstep: 1646.68 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 00:48:57,868] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 919.65 | bwd_microstep: 1592.27 | bwd_inner_microstep: 1592.25 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 00:49:00,683] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1152.98 | bwd_microstep: 1646.28 | bwd_inner_microstep: 1646.26 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 326 +[2025-05-02 00:49:01,276] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 152.09 | bwd_microstep: 426.71 | bwd_inner_microstep: 426.41 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 00:49:04,104] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 921.38 | bwd_microstep: 1596.00 | bwd_inner_microstep: 1595.98 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 00:49:06,624] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1056.56 | bwd_microstep: 1446.03 | bwd_inner_microstep: 1446.02 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 00:49:09,450] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 923.13 | bwd_microstep: 1596.49 | bwd_inner_microstep: 1596.47 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 00:49:12,070] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1152.33 | bwd_microstep: 1449.61 | bwd_inner_microstep: 1449.59 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 00:49:14,599] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1117.84 | bwd_microstep: 1393.50 | bwd_inner_microstep: 1393.48 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1850 +[2025-05-02 00:49:17,477] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1215.33 | bwd_microstep: 1647.15 | bwd_inner_microstep: 1647.13 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2105 +[2025-05-02 00:49:20,345] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1124.59 | bwd_microstep: 1727.44 | bwd_inner_microstep: 1727.42 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1961 +[2025-05-02 00:49:23,727] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 49.73 | optimizer_step: 306.27 +[2025-05-02 00:49:23,727] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1222.39 | bwd_microstep: 1782.33 | bwd_inner_microstep: 1614.43 | bwd_allreduce_microstep: 167.89 | step_microstep: 361.33 +[2025-05-02 00:49:23,728] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 16335.54 | bwd: 24212.89 | bwd_inner: 24044.47 | bwd_allreduce: 168.07 | step: 362.40 + 10%|█ | 909/8720 [2:33:57<88:29:18, 40.78s/it] {'loss': 0.764, 'grad_norm': 5.917619228363037, 'learning_rate': 9.856311568560748e-06, 'epoch': 1.04} + 10%|█ | 909/8720 [2:33:57<88:29:18, 40.78s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1899 +[2025-05-02 00:49:26,265] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 872.45 | bwd_microstep: 1644.12 | bwd_inner_microstep: 1644.10 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1921 +[2025-05-02 00:49:29,115] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 928.27 | bwd_microstep: 1611.94 | bwd_inner_microstep: 1611.92 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1921 +[2025-05-02 00:49:31,964] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 929.10 | bwd_microstep: 1608.54 | bwd_inner_microstep: 1608.52 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1896 +[2025-05-02 00:49:34,601] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1119.16 | bwd_microstep: 1402.29 | bwd_inner_microstep: 1402.27 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-02 00:49:37,137] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1213.53 | bwd_microstep: 1304.89 | bwd_inner_microstep: 1304.88 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.74 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 00:49:40,013] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 870.62 | bwd_microstep: 1650.34 | bwd_inner_microstep: 1650.32 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 00:49:42,540] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1111.78 | bwd_microstep: 1397.93 | bwd_inner_microstep: 1397.92 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 843 +[2025-05-02 00:49:44,100] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 485.50 | bwd_microstep: 871.35 | bwd_inner_microstep: 871.13 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 00:49:46,629] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 922.76 | bwd_microstep: 1589.80 | bwd_inner_microstep: 1589.78 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 00:49:49,149] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1058.94 | bwd_microstep: 1445.70 | bwd_inner_microstep: 1445.68 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 00:49:51,978] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 923.11 | bwd_microstep: 1597.10 | bwd_inner_microstep: 1597.09 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 00:49:54,505] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1063.51 | bwd_microstep: 1445.93 | bwd_inner_microstep: 1445.91 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 00:49:57,139] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1119.44 | bwd_microstep: 1402.46 | bwd_inner_microstep: 1402.45 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 00:49:59,670] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1210.85 | bwd_microstep: 1302.43 | bwd_inner_microstep: 1302.41 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 00:50:02,550] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 869.42 | bwd_microstep: 1651.52 | bwd_inner_microstep: 1651.50 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 00:50:05,759] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.09 | optimizer_step: 16.65 +[2025-05-02 00:50:05,760] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1114.46 | bwd_microstep: 2055.24 | bwd_inner_microstep: 1396.80 | bwd_allreduce_microstep: 658.39 | step_microstep: 24.12 +[2025-05-02 00:50:05,761] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 15812.65 | bwd: 23981.61 | bwd_inner: 23322.71 | bwd_allreduce: 658.52 | step: 25.72 + 10%|█ | 910/8720 [2:34:39<89:17:25, 41.16s/it] {'loss': 0.8599, 'grad_norm': 5.92339563369751, 'learning_rate': 9.855869205039304e-06, 'epoch': 1.04} + 10%|█ | 910/8720 [2:34:39<89:17:25, 41.16s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 00:50:08,398] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1172.00 | bwd_microstep: 1400.35 | bwd_inner_microstep: 1400.33 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1924 +[2025-05-02 00:50:11,296] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1219.91 | bwd_microstep: 1662.19 | bwd_inner_microstep: 1662.18 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1381 +[2025-05-02 00:50:13,277] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 725.09 | bwd_microstep: 1241.63 | bwd_inner_microstep: 1241.61 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1893 +[2025-05-02 00:50:15,903] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1157.01 | bwd_microstep: 1404.38 | bwd_inner_microstep: 1404.36 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 00:50:18,437] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1120.52 | bwd_microstep: 1398.44 | bwd_inner_microstep: 1398.43 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 00:50:21,319] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 869.19 | bwd_microstep: 1651.87 | bwd_inner_microstep: 1651.86 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 00:50:24,140] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1208.54 | bwd_microstep: 1596.60 | bwd_inner_microstep: 1596.58 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 00:50:26,676] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 923.42 | bwd_microstep: 1594.93 | bwd_inner_microstep: 1594.91 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 326 +[2025-05-02 00:50:27,551] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 304.69 | bwd_microstep: 416.17 | bwd_inner_microstep: 415.99 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 00:50:30,076] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1112.96 | bwd_microstep: 1396.15 | bwd_inner_microstep: 1396.13 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.15 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 00:50:32,897] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 920.31 | bwd_microstep: 1595.41 | bwd_inner_microstep: 1595.40 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 829 +[2025-05-02 00:50:34,167] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 483.71 | bwd_microstep: 772.00 | bwd_inner_microstep: 771.86 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 00:50:36,994] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 923.03 | bwd_microstep: 1594.68 | bwd_inner_microstep: 1594.66 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 00:50:39,616] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1206.84 | bwd_microstep: 1397.51 | bwd_inner_microstep: 1397.50 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 00:50:42,150] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1118.75 | bwd_microstep: 1397.40 | bwd_inner_microstep: 1397.39 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 315 +[2025-05-02 00:50:43,766] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 49.62 | optimizer_step: 306.32 +[2025-05-02 00:50:43,767] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 600.03 | bwd_microstep: 542.87 | bwd_inner_microstep: 376.39 | bwd_allreduce_microstep: 166.35 | step_microstep: 361.53 +[2025-05-02 00:50:43,768] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 15065.79 | bwd: 21062.66 | bwd_inner: 20895.73 | bwd_allreduce: 166.50 | step: 362.83 + 10%|█ | 911/8720 [2:35:17<87:13:42, 40.21s/it] {'loss': 0.8131, 'grad_norm': 23.31475257873535, 'learning_rate': 9.855426171584877e-06, 'epoch': 1.04} + 10%|█ | 911/8720 [2:35:17<87:13:42, 40.21s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1895 +[2025-05-02 00:50:46,301] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1067.06 | bwd_microstep: 1445.94 | bwd_inner_microstep: 1445.92 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-02 00:50:49,128] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 924.50 | bwd_microstep: 1596.78 | bwd_inner_microstep: 1596.76 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-02 00:50:51,653] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1063.32 | bwd_microstep: 1445.55 | bwd_inner_microstep: 1445.53 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-02 00:50:54,482] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 923.87 | bwd_microstep: 1596.75 | bwd_inner_microstep: 1596.74 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 00:50:57,007] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1063.36 | bwd_microstep: 1446.33 | bwd_inner_microstep: 1446.32 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 00:50:59,640] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1118.33 | bwd_microstep: 1403.06 | bwd_inner_microstep: 1403.04 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 00:51:02,173] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1212.71 | bwd_microstep: 1304.18 | bwd_inner_microstep: 1304.16 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.14 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 00:51:05,050] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 868.52 | bwd_microstep: 1650.43 | bwd_inner_microstep: 1650.41 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 00:51:07,581] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1018.86 | bwd_microstep: 1495.74 | bwd_inner_microstep: 1495.72 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 00:51:10,409] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 924.50 | bwd_microstep: 1594.99 | bwd_inner_microstep: 1594.98 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 00:51:12,935] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1062.99 | bwd_microstep: 1445.26 | bwd_inner_microstep: 1445.24 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 838 +[2025-05-02 00:51:14,192] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 285.23 | bwd_microstep: 767.95 | bwd_inner_microstep: 767.54 | bwd_allreduce_microstep: 0.19 | step_microstep: 0.25 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1346 +[2025-05-02 00:51:16,315] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 581.14 | bwd_microstep: 1237.15 | bwd_inner_microstep: 1237.07 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 00:51:18,846] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 872.57 | bwd_microstep: 1642.85 | bwd_inner_microstep: 1642.83 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 00:51:21,678] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 924.00 | bwd_microstep: 1596.61 | bwd_inner_microstep: 1596.59 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 00:51:24,692] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.12 | optimizer_step: 20.39 +[2025-05-02 00:51:24,693] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1015.62 | bwd_microstep: 1955.12 | bwd_inner_microstep: 1493.05 | bwd_allreduce_microstep: 461.99 | step_microstep: 28.12 +[2025-05-02 00:51:24,694] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 14926.35 | bwd: 23624.76 | bwd_inner: 23162.00 | bwd_allreduce: 462.30 | step: 30.38 + 10%|█ | 912/8720 [2:35:58<87:40:51, 40.43s/it] {'loss': 0.7046, 'grad_norm': 7.864853858947754, 'learning_rate': 9.85498246825859e-06, 'epoch': 1.05} + 10%|█ | 912/8720 [2:35:58<87:40:51, 40.43s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2016 +[2025-05-02 00:51:27,611] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1126.66 | bwd_microstep: 1671.14 | bwd_inner_microstep: 1671.13 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1934 +[2025-05-02 00:51:30,458] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 927.37 | bwd_microstep: 1612.96 | bwd_inner_microstep: 1612.94 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1892 +[2025-05-02 00:51:33,293] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 924.09 | bwd_microstep: 1600.26 | bwd_inner_microstep: 1600.24 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1125 +[2025-05-02 00:51:34,716] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 559.69 | bwd_microstep: 846.20 | bwd_inner_microstep: 846.19 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1889 +[2025-05-02 00:51:37,599] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 870.35 | bwd_microstep: 1651.06 | bwd_inner_microstep: 1651.05 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-02 00:51:40,221] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1110.78 | bwd_microstep: 1496.35 | bwd_inner_microstep: 1496.33 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 00:51:42,948] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 922.64 | bwd_microstep: 1597.80 | bwd_inner_microstep: 1597.79 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.17 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 00:51:45,767] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1205.35 | bwd_microstep: 1596.86 | bwd_inner_microstep: 1596.84 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-02 00:51:48,299] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 923.67 | bwd_microstep: 1590.00 | bwd_inner_microstep: 1589.98 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 00:51:50,932] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1169.16 | bwd_microstep: 1401.59 | bwd_inner_microstep: 1401.57 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 850 +[2025-05-02 00:51:52,210] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 736.33 | bwd_microstep: 525.31 | bwd_inner_microstep: 525.29 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.32 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 00:51:55,086] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 870.98 | bwd_microstep: 1649.02 | bwd_inner_microstep: 1649.00 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 00:51:57,606] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1107.36 | bwd_microstep: 1396.45 | bwd_inner_microstep: 1396.43 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 00:52:00,428] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 920.46 | bwd_microstep: 1596.48 | bwd_inner_microstep: 1596.46 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 00:52:02,948] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1055.84 | bwd_microstep: 1445.38 | bwd_inner_microstep: 1445.36 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 00:52:06,307] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.08 | optimizer_step: 361.91 +[2025-05-02 00:52:06,307] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 920.96 | bwd_microstep: 1763.35 | bwd_inner_microstep: 1597.05 | bwd_allreduce_microstep: 166.22 | step_microstep: 369.58 +[2025-05-02 00:52:06,309] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 15351.44 | bwd: 23440.23 | bwd_inner: 23273.66 | bwd_allreduce: 166.30 | step: 370.99 + 10%|█ | 913/8720 [2:36:40<88:26:34, 40.78s/it] {'loss': 1.0925, 'grad_norm': 4.90545129776001, 'learning_rate': 9.85453809512166e-06, 'epoch': 1.05} + 10%|█ | 913/8720 [2:36:40<88:26:34, 40.78s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 00:52:08,844] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1067.91 | bwd_microstep: 1447.13 | bwd_inner_microstep: 1447.12 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1921 +[2025-05-02 00:52:11,687] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 926.40 | bwd_microstep: 1611.34 | bwd_inner_microstep: 1611.32 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1914 +[2025-05-02 00:52:14,524] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 925.66 | bwd_microstep: 1602.97 | bwd_inner_microstep: 1602.96 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1919 +[2025-05-02 00:52:17,167] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1219.21 | bwd_microstep: 1407.98 | bwd_inner_microstep: 1407.96 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1908 +[2025-05-02 00:52:19,707] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1215.22 | bwd_microstep: 1309.33 | bwd_inner_microstep: 1309.31 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.75 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-02 00:52:22,583] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 869.11 | bwd_microstep: 1651.57 | bwd_inner_microstep: 1651.55 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 00:52:25,109] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1113.75 | bwd_microstep: 1397.81 | bwd_inner_microstep: 1397.79 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 00:52:27,937] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 923.71 | bwd_microstep: 1595.94 | bwd_inner_microstep: 1595.92 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 842 +[2025-05-02 00:52:29,208] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 484.74 | bwd_microstep: 772.50 | bwd_inner_microstep: 772.30 | bwd_allreduce_microstep: 0.09 | step_microstep: 0.09 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 328 +[2025-05-02 00:52:30,085] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 401.83 | bwd_microstep: 418.20 | bwd_inner_microstep: 418.06 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 00:52:32,614] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1019.68 | bwd_microstep: 1494.14 | bwd_inner_microstep: 1494.13 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 00:52:35,445] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 923.98 | bwd_microstep: 1596.59 | bwd_inner_microstep: 1596.57 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 00:52:37,969] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1063.40 | bwd_microstep: 1445.86 | bwd_inner_microstep: 1445.84 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 00:52:40,798] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 921.52 | bwd_microstep: 1597.82 | bwd_inner_microstep: 1597.80 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 00:52:43,326] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1064.04 | bwd_microstep: 1446.71 | bwd_inner_microstep: 1446.70 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 00:52:46,390] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.07 | optimizer_step: 16.68 +[2025-05-02 00:52:46,438] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1119.60 | bwd_microstep: 1815.59 | bwd_inner_microstep: 1399.29 | bwd_allreduce_microstep: 416.25 | step_microstep: 72.55 +[2025-05-02 00:52:46,440] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 15259.53 | bwd: 22611.52 | bwd_inner: 22194.68 | bwd_allreduce: 416.45 | step: 74.13 + 10%|█ | 914/8720 [2:37:20<88:02:18, 40.60s/it] {'loss': 0.9744, 'grad_norm': 8.030135154724121, 'learning_rate': 9.854093052235394e-06, 'epoch': 1.05} + 10%|█ | 914/8720 [2:37:20<88:02:18, 40.60s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 00:52:49,212] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 921.03 | bwd_microstep: 1597.15 | bwd_inner_microstep: 1597.12 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2105 +[2025-05-02 00:52:52,071] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1067.68 | bwd_microstep: 1774.94 | bwd_inner_microstep: 1774.92 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 852 +[2025-05-02 00:52:53,444] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 538.86 | bwd_microstep: 818.73 | bwd_inner_microstep: 818.71 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 00:52:55,978] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1119.33 | bwd_microstep: 1399.17 | bwd_inner_microstep: 1399.15 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 00:52:58,509] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1209.42 | bwd_microstep: 1305.27 | bwd_inner_microstep: 1305.25 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.76 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 00:53:01,383] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 869.99 | bwd_microstep: 1649.77 | bwd_inner_microstep: 1649.75 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 00:53:03,908] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1114.33 | bwd_microstep: 1395.12 | bwd_inner_microstep: 1395.10 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 00:53:06,735] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 922.90 | bwd_microstep: 1594.87 | bwd_inner_microstep: 1594.85 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1346 +[2025-05-02 00:53:08,869] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 877.82 | bwd_microstep: 1238.14 | bwd_inner_microstep: 1237.98 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.19 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 832 +[2025-05-02 00:53:10,138] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 679.53 | bwd_microstep: 573.29 | bwd_inner_microstep: 573.21 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 00:53:12,969] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1219.04 | bwd_microstep: 1596.06 | bwd_inner_microstep: 1596.04 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 318 +[2025-05-02 00:53:13,854] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 340.01 | bwd_microstep: 529.72 | bwd_inner_microstep: 529.42 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 00:53:16,379] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 867.00 | bwd_microstep: 1642.19 | bwd_inner_microstep: 1642.17 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 00:53:18,893] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1104.17 | bwd_microstep: 1393.69 | bwd_inner_microstep: 1393.67 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 00:53:21,719] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 922.86 | bwd_microstep: 1595.42 | bwd_inner_microstep: 1595.41 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 00:53:24,724] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.13 | optimizer_step: 16.66 +[2025-05-02 00:53:24,725] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1056.38 | bwd_microstep: 1907.48 | bwd_inner_microstep: 1443.99 | bwd_allreduce_microstep: 463.45 | step_microstep: 24.09 +[2025-05-02 00:53:24,726] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 14830.08 | bwd: 22011.13 | bwd_inner: 21546.80 | bwd_allreduce: 463.77 | step: 26.12 + 10%|█ | 915/8720 [2:37:58<86:29:23, 39.89s/it] {'loss': 1.0837, 'grad_norm': 10.267372131347656, 'learning_rate': 9.85364733966119e-06, 'epoch': 1.05} + 10%|█ | 915/8720 [2:37:58<86:29:23, 39.89s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1849 +[2025-05-02 00:53:27,602] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1113.13 | bwd_microstep: 1648.27 | bwd_inner_microstep: 1648.25 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1895 +[2025-05-02 00:53:30,233] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1118.04 | bwd_microstep: 1496.65 | bwd_inner_microstep: 1496.63 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.08 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 858 +[2025-05-02 00:53:31,698] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 388.28 | bwd_microstep: 872.40 | bwd_inner_microstep: 872.10 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 00:53:34,225] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1016.79 | bwd_microstep: 1493.63 | bwd_inner_microstep: 1493.61 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 843 +[2025-05-02 00:53:35,782] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 288.26 | bwd_microstep: 1067.17 | bwd_inner_microstep: 1067.02 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 00:53:38,306] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 921.06 | bwd_microstep: 1587.51 | bwd_inner_microstep: 1587.49 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 00:53:40,940] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1218.70 | bwd_microstep: 1400.21 | bwd_inner_microstep: 1400.20 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 00:53:43,471] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1115.90 | bwd_microstep: 1398.68 | bwd_inner_microstep: 1398.66 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 00:53:46,352] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1115.00 | bwd_microstep: 1651.26 | bwd_inner_microstep: 1651.21 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 00:53:48,885] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 973.61 | bwd_microstep: 1542.54 | bwd_inner_microstep: 1542.52 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 00:53:51,709] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 972.90 | bwd_microstep: 1594.60 | bwd_inner_microstep: 1594.58 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 00:53:54,237] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 923.89 | bwd_microstep: 1588.28 | bwd_inner_microstep: 1588.26 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 00:53:56,749] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1005.80 | bwd_microstep: 1443.86 | bwd_inner_microstep: 1443.84 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 00:53:59,576] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 921.94 | bwd_microstep: 1595.31 | bwd_inner_microstep: 1595.29 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1959 +[2025-05-02 00:54:02,220] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1065.21 | bwd_microstep: 1560.52 | bwd_inner_microstep: 1560.50 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 346 +[2025-05-02 00:54:03,502] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.04 | optimizer_gradients: 2.08 | optimizer_step: 16.64 +[2025-05-02 00:54:03,502] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 400.73 | bwd_microstep: 842.76 | bwd_inner_microstep: 677.65 | bwd_allreduce_microstep: 165.02 | step_microstep: 23.81 +[2025-05-02 00:54:03,504] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 14559.04 | bwd: 22783.71 | bwd_inner: 22617.96 | bwd_allreduce: 165.28 | step: 24.94 + 11%|█ | 916/8720 [2:38:37<85:45:12, 39.56s/it] {'loss': 0.8176, 'grad_norm': 7.814762115478516, 'learning_rate': 9.853200957460542e-06, 'epoch': 1.05} + 11%|█ | 916/8720 [2:38:37<85:45:12, 39.56s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 00:54:06,384] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 871.42 | bwd_microstep: 1649.19 | bwd_inner_microstep: 1649.13 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1962 +[2025-05-02 00:54:09,230] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1123.09 | bwd_microstep: 1707.64 | bwd_inner_microstep: 1707.63 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1893 +[2025-05-02 00:54:11,758] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 920.79 | bwd_microstep: 1591.06 | bwd_inner_microstep: 1591.04 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 362 +[2025-05-02 00:54:12,645] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 455.13 | bwd_microstep: 418.62 | bwd_inner_microstep: 418.49 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1892 +[2025-05-02 00:54:15,175] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1018.62 | bwd_microstep: 1495.52 | bwd_inner_microstep: 1495.51 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 00:54:18,004] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 922.51 | bwd_microstep: 1598.87 | bwd_inner_microstep: 1598.85 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 329 +[2025-05-02 00:54:18,898] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 458.78 | bwd_microstep: 419.89 | bwd_inner_microstep: 419.58 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 00:54:21,429] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1020.86 | bwd_microstep: 1493.46 | bwd_inner_microstep: 1493.45 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 00:54:24,260] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 922.46 | bwd_microstep: 1599.36 | bwd_inner_microstep: 1599.34 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 845 +[2025-05-02 00:54:25,529] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 484.18 | bwd_microstep: 771.57 | bwd_inner_microstep: 771.44 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 00:54:28,342] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1057.00 | bwd_microstep: 1597.84 | bwd_inner_microstep: 1597.82 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 00:54:30,874] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 923.15 | bwd_microstep: 1591.59 | bwd_inner_microstep: 1591.57 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 00:54:33,509] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1167.94 | bwd_microstep: 1401.35 | bwd_inner_microstep: 1401.33 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 00:54:36,341] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1213.39 | bwd_microstep: 1600.90 | bwd_inner_microstep: 1600.88 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 00:54:38,918] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 865.61 | bwd_microstep: 1647.43 | bwd_inner_microstep: 1647.42 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 318 +[2025-05-02 00:54:40,502] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.13 | optimizer_step: 16.77 +[2025-05-02 00:54:40,502] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 653.69 | bwd_microstep: 596.28 | bwd_inner_microstep: 180.22 | bwd_allreduce_microstep: 415.93 | step_microstep: 320.13 +[2025-05-02 00:54:40,503] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 14078.42 | bwd: 21180.67 | bwd_inner: 20763.88 | bwd_allreduce: 416.24 | step: 321.59 + 11%|█ | 917/8720 [2:39:14<84:04:43, 38.79s/it] {'loss': 0.6975, 'grad_norm': 5.449578762054443, 'learning_rate': 9.852753905695032e-06, 'epoch': 1.05} + 11%|█ | 917/8720 [2:39:14<84:04:43, 38.79s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 00:54:43,024] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1106.19 | bwd_microstep: 1393.79 | bwd_inner_microstep: 1393.78 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 391 +[2025-05-02 00:54:43,903] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 307.17 | bwd_microstep: 419.24 | bwd_inner_microstep: 419.08 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1893 +[2025-05-02 00:54:46,474] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1108.52 | bwd_microstep: 1447.79 | bwd_inner_microstep: 1447.78 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 355 +[2025-05-02 00:54:47,256] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 409.91 | bwd_microstep: 173.67 | bwd_inner_microstep: 173.53 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.13 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-02 00:54:50,141] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1216.52 | bwd_microstep: 1651.46 | bwd_inner_microstep: 1651.44 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-02 00:54:52,813] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1107.62 | bwd_microstep: 1546.50 | bwd_inner_microstep: 1546.49 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-02 00:54:55,492] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 925.07 | bwd_microstep: 1596.44 | bwd_inner_microstep: 1596.42 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 00:54:58,323] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1166.92 | bwd_microstep: 1597.05 | bwd_inner_microstep: 1597.02 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.12 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 333 +[2025-05-02 00:54:59,228] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 521.78 | bwd_microstep: 367.09 | bwd_inner_microstep: 366.77 | bwd_allreduce_microstep: 0.14 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 00:55:01,749] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1059.99 | bwd_microstep: 1445.57 | bwd_inner_microstep: 1445.55 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 00:55:04,577] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 924.38 | bwd_microstep: 1597.00 | bwd_inner_microstep: 1596.98 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 00:55:07,096] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1056.02 | bwd_microstep: 1445.34 | bwd_inner_microstep: 1445.32 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 00:55:09,728] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1119.14 | bwd_microstep: 1399.55 | bwd_inner_microstep: 1399.53 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 00:55:12,258] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1208.66 | bwd_microstep: 1303.50 | bwd_inner_microstep: 1303.48 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 319 +[2025-05-02 00:55:13,330] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 502.72 | bwd_microstep: 365.97 | bwd_inner_microstep: 365.74 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 00:55:16,071] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.07 | optimizer_step: 16.53 +[2025-05-02 00:55:16,072] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 1063.41 | bwd_microstep: 1637.24 | bwd_inner_microstep: 1446.62 | bwd_allreduce_microstep: 190.57 | step_microstep: 25.12 +[2025-05-02 00:55:16,073] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 14803.82 | bwd: 19387.34 | bwd_inner: 19195.75 | bwd_allreduce: 190.94 | step: 26.62 + 11%|█ | 918/8720 [2:39:49<81:58:25, 37.82s/it] {'loss': 1.2423, 'grad_norm': 6.227590560913086, 'learning_rate': 9.852306184426339e-06, 'epoch': 1.05} + 11%|█ | 918/8720 [2:39:49<81:58:25, 37.82s/it]dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 830 +[2025-05-02 00:55:16,314] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.97 | bwd_microstep: 128.57 | bwd_inner_microstep: 128.32 | bwd_allreduce_microstep: 0.10 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1908 +[2025-05-02 00:55:16,789] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.01 | bwd_microstep: 273.32 | bwd_inner_microstep: 273.30 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-02 00:55:17,263] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.38 | bwd_microstep: 271.65 | bwd_inner_microstep: 271.63 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-02 00:55:17,740] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.24 | bwd_microstep: 271.71 | bwd_inner_microstep: 271.69 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 00:55:18,213] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.95 | bwd_microstep: 270.18 | bwd_inner_microstep: 270.16 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-02 00:55:18,686] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.05 | bwd_microstep: 270.41 | bwd_inner_microstep: 270.40 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 00:55:19,160] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.57 | bwd_microstep: 270.83 | bwd_inner_microstep: 270.81 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.05 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 337 +[2025-05-02 00:55:19,376] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 84.00 | bwd_microstep: 119.03 | bwd_inner_microstep: 118.75 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 00:55:19,847] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 185.86 | bwd_microstep: 270.27 | bwd_inner_microstep: 270.25 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 00:55:20,321] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.29 | bwd_microstep: 270.42 | bwd_inner_microstep: 270.40 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 00:55:20,796] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.27 | bwd_microstep: 270.28 | bwd_inner_microstep: 270.26 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 00:55:21,267] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.09 | bwd_microstep: 269.95 | bwd_inner_microstep: 269.93 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 00:55:21,739] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.11 | bwd_microstep: 270.06 | bwd_inner_microstep: 270.05 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 00:55:22,210] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.58 | bwd_microstep: 270.19 | bwd_inner_microstep: 270.18 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 00:55:22,682] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 185.94 | bwd_microstep: 269.17 | bwd_inner_microstep: 269.15 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 00:55:23,262] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.10 | optimizer_step: 16.64 +[2025-05-02 00:55:23,262] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.16 | bwd_microstep: 354.25 | bwd_inner_microstep: 269.60 | bwd_allreduce_microstep: 84.59 | step_microstep: 25.13 +[2025-05-02 00:55:23,264] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2794.17 | bwd: 4120.34 | bwd_inner: 4034.99 | bwd_allreduce: 84.86 | step: 26.12 + 11%|█ | 919/8720 [2:39:57<62:02:56, 28.63s/it] {'loss': 0.9606, 'grad_norm': 6.771807670593262, 'learning_rate': 9.85185779371623e-06, 'epoch': 1.05} + 11%|█ | 919/8720 [2:39:57<62:02:56, 28.63s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 00:55:23,739] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.46 | bwd_microstep: 268.28 | bwd_inner_microstep: 268.26 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1910 +[2025-05-02 00:55:24,216] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.14 | bwd_microstep: 274.13 | bwd_inner_microstep: 274.12 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-02 00:55:24,690] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.13 | bwd_microstep: 271.42 | bwd_inner_microstep: 271.40 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-02 00:55:25,164] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.17 | bwd_microstep: 271.25 | bwd_inner_microstep: 271.24 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 00:55:25,638] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.96 | bwd_microstep: 270.84 | bwd_inner_microstep: 270.83 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 00:55:26,111] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.13 | bwd_microstep: 270.82 | bwd_inner_microstep: 270.81 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 00:55:26,586] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.89 | bwd_microstep: 270.27 | bwd_inner_microstep: 270.25 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 00:55:27,059] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.50 | bwd_microstep: 270.36 | bwd_inner_microstep: 270.35 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 00:55:27,533] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.86 | bwd_microstep: 270.72 | bwd_inner_microstep: 270.71 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 833 +[2025-05-02 00:55:27,778] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 105.59 | bwd_microstep: 124.31 | bwd_inner_microstep: 124.11 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.10 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 835 +[2025-05-02 00:55:28,026] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 107.21 | bwd_microstep: 124.43 | bwd_inner_microstep: 124.37 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.10 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 320 +[2025-05-02 00:55:28,255] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.88 | bwd_microstep: 117.94 | bwd_inner_microstep: 117.69 | bwd_allreduce_microstep: 0.09 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 00:55:28,727] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 185.95 | bwd_microstep: 269.19 | bwd_inner_microstep: 269.18 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 00:55:29,201] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.62 | bwd_microstep: 269.36 | bwd_inner_microstep: 269.35 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 00:55:29,674] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.91 | bwd_microstep: 269.98 | bwd_inner_microstep: 269.96 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 00:55:30,254] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.08 | optimizer_step: 16.59 +[2025-05-02 00:55:30,255] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.43 | bwd_microstep: 354.69 | bwd_inner_microstep: 270.16 | bwd_allreduce_microstep: 84.48 | step_microstep: 25.13 +[2025-05-02 00:55:30,256] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2740.47 | bwd: 3968.08 | bwd_inner: 3882.86 | bwd_allreduce: 84.71 | step: 26.08 + 11%|█ | 920/8720 [2:40:04<47:58:25, 22.14s/it] {'loss': 0.669, 'grad_norm': 6.321875095367432, 'learning_rate': 9.851408733626571e-06, 'epoch': 1.05} + 11%|█ | 920/8720 [2:40:04<47:58:25, 22.14s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 00:55:30,732] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.02 | bwd_microstep: 268.87 | bwd_inner_microstep: 268.85 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 388 +[2025-05-02 00:55:30,953] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.81 | bwd_microstep: 112.92 | bwd_inner_microstep: 112.77 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1897 +[2025-05-02 00:55:31,430] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.51 | bwd_microstep: 273.63 | bwd_inner_microstep: 273.61 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 360 +[2025-05-02 00:55:31,650] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 85.16 | bwd_microstep: 121.41 | bwd_inner_microstep: 121.22 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1886 +[2025-05-02 00:55:32,124] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.89 | bwd_microstep: 272.98 | bwd_inner_microstep: 272.97 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 854 +[2025-05-02 00:55:32,372] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 101.57 | bwd_microstep: 131.55 | bwd_inner_microstep: 131.37 | bwd_allreduce_microstep: 0.10 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 00:55:32,844] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.46 | bwd_microstep: 271.42 | bwd_inner_microstep: 271.40 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 848 +[2025-05-02 00:55:33,088] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 98.61 | bwd_microstep: 131.03 | bwd_inner_microstep: 130.96 | bwd_allreduce_microstep: 0.03 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-02 00:55:33,562] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.61 | bwd_microstep: 271.42 | bwd_inner_microstep: 271.41 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 00:55:34,035] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.67 | bwd_microstep: 271.21 | bwd_inner_microstep: 271.19 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 834 +[2025-05-02 00:55:34,270] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.67 | bwd_microstep: 124.95 | bwd_inner_microstep: 124.93 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.09 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 832 +[2025-05-02 00:55:34,508] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.82 | bwd_microstep: 129.10 | bwd_inner_microstep: 128.98 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 00:55:34,981] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.62 | bwd_microstep: 270.98 | bwd_inner_microstep: 270.96 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 00:55:35,453] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.18 | bwd_microstep: 269.89 | bwd_inner_microstep: 269.87 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 00:55:35,924] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.00 | bwd_microstep: 269.61 | bwd_inner_microstep: 269.60 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 00:55:36,506] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.09 | optimizer_step: 16.56 +[2025-05-02 00:55:36,506] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.22 | bwd_microstep: 354.61 | bwd_inner_microstep: 270.34 | bwd_allreduce_microstep: 84.22 | step_microstep: 25.06 +[2025-05-02 00:55:36,508] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2439.56 | bwd: 3545.68 | bwd_inner: 3460.53 | bwd_allreduce: 84.57 | step: 26.05 + 11%|█ | 921/8720 [2:40:10<37:38:24, 17.37s/it] {'loss': 0.6407, 'grad_norm': 6.671081066131592, 'learning_rate': 9.850959004219312e-06, 'epoch': 1.06} + 11%|█ | 921/8720 [2:40:10<37:38:24, 17.37s/it]dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 827 +[2025-05-02 00:55:36,750] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.24 | bwd_microstep: 129.31 | bwd_inner_microstep: 129.16 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.09 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1384 +[2025-05-02 00:55:37,113] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.37 | bwd_microstep: 207.22 | bwd_inner_microstep: 207.16 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1883 +[2025-05-02 00:55:37,588] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.36 | bwd_microstep: 272.72 | bwd_inner_microstep: 272.70 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.24 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-02 00:55:38,066] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.26 | bwd_microstep: 272.14 | bwd_inner_microstep: 272.13 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 00:55:38,539] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.95 | bwd_microstep: 271.51 | bwd_inner_microstep: 271.49 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 00:55:39,016] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.24 | bwd_microstep: 272.30 | bwd_inner_microstep: 272.29 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 329 +[2025-05-02 00:55:39,228] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 81.52 | bwd_microstep: 117.85 | bwd_inner_microstep: 117.69 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 00:55:39,702] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.47 | bwd_microstep: 270.91 | bwd_inner_microstep: 270.90 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 00:55:40,178] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.98 | bwd_microstep: 271.30 | bwd_inner_microstep: 271.28 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 00:55:40,655] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.08 | bwd_microstep: 271.16 | bwd_inner_microstep: 271.14 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 00:55:41,130] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.54 | bwd_microstep: 270.00 | bwd_inner_microstep: 269.98 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.22 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 00:55:41,607] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.35 | bwd_microstep: 270.78 | bwd_inner_microstep: 270.76 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 00:55:42,081] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.32 | bwd_microstep: 269.58 | bwd_inner_microstep: 269.56 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 318 +[2025-05-02 00:55:42,326] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 107.13 | bwd_microstep: 120.25 | bwd_inner_microstep: 119.90 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 00:55:42,805] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.22 | bwd_microstep: 269.79 | bwd_inner_microstep: 269.77 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 00:55:43,402] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.08 | optimizer_step: 16.55 +[2025-05-02 00:55:43,402] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.79 | bwd_microstep: 368.18 | bwd_inner_microstep: 270.31 | bwd_allreduce_microstep: 97.82 | step_microstep: 24.97 +[2025-05-02 00:55:43,404] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2670.45 | bwd: 3925.09 | bwd_inner: 3826.37 | bwd_allreduce: 98.17 | step: 26.50 + 11%|█ | 922/8720 [2:40:17<30:49:33, 14.23s/it] {'loss': 1.0247, 'grad_norm': 6.11132287979126, 'learning_rate': 9.850508605556499e-06, 'epoch': 1.06} + 11%|█ | 922/8720 [2:40:17<30:49:33, 14.23s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 00:55:43,879] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.60 | bwd_microstep: 269.32 | bwd_inner_microstep: 269.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1945 +[2025-05-02 00:55:44,379] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 197.02 | bwd_microstep: 287.49 | bwd_inner_microstep: 287.48 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 398 +[2025-05-02 00:55:44,597] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 88.11 | bwd_microstep: 116.82 | bwd_inner_microstep: 116.67 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1918 +[2025-05-02 00:55:45,076] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.17 | bwd_microstep: 275.37 | bwd_inner_microstep: 275.36 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1893 +[2025-05-02 00:55:45,555] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.68 | bwd_microstep: 273.80 | bwd_inner_microstep: 273.78 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-02 00:55:46,031] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.20 | bwd_microstep: 272.68 | bwd_inner_microstep: 272.66 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 00:55:46,506] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.42 | bwd_microstep: 272.22 | bwd_inner_microstep: 272.21 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.16 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 00:55:46,981] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.93 | bwd_microstep: 271.58 | bwd_inner_microstep: 271.56 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 00:55:47,456] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.89 | bwd_microstep: 271.92 | bwd_inner_microstep: 271.90 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.17 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 00:55:47,931] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.21 | bwd_microstep: 271.37 | bwd_inner_microstep: 271.35 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 844 +[2025-05-02 00:55:48,187] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 108.96 | bwd_microstep: 130.77 | bwd_inner_microstep: 130.48 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.11 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 837 +[2025-05-02 00:55:48,442] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 106.06 | bwd_microstep: 131.88 | bwd_inner_microstep: 131.70 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 00:55:48,919] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.96 | bwd_microstep: 270.86 | bwd_inner_microstep: 270.84 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 00:55:49,395] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.06 | bwd_microstep: 271.28 | bwd_inner_microstep: 271.26 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 00:55:49,871] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.53 | bwd_microstep: 271.11 | bwd_inner_microstep: 271.10 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 00:55:50,454] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.08 | optimizer_step: 16.48 +[2025-05-02 00:55:50,454] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.20 | bwd_microstep: 355.62 | bwd_inner_microstep: 271.59 | bwd_allreduce_microstep: 83.98 | step_microstep: 24.80 +[2025-05-02 00:55:50,455] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2752.65 | bwd: 4014.15 | bwd_inner: 3929.30 | bwd_allreduce: 84.32 | step: 26.02 + 11%|█ | 923/8720 [2:40:24<26:09:26, 12.08s/it] {'loss': 1.2415, 'grad_norm': 11.806069374084473, 'learning_rate': 9.850057537700272e-06, 'epoch': 1.06} + 11%|█ | 923/8720 [2:40:24<26:09:26, 12.08s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 00:55:50,933] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.17 | bwd_microstep: 269.60 | bwd_inner_microstep: 269.58 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1922 +[2025-05-02 00:55:51,428] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 194.42 | bwd_microstep: 285.94 | bwd_inner_microstep: 285.92 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1921 +[2025-05-02 00:55:51,923] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 193.50 | bwd_microstep: 285.80 | bwd_inner_microstep: 285.78 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1908 +[2025-05-02 00:55:52,403] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.13 | bwd_microstep: 274.91 | bwd_inner_microstep: 274.89 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1894 +[2025-05-02 00:55:52,880] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.53 | bwd_microstep: 273.67 | bwd_inner_microstep: 273.65 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-02 00:55:53,355] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.05 | bwd_microstep: 272.58 | bwd_inner_microstep: 272.56 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-02 00:55:53,832] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.42 | bwd_microstep: 272.79 | bwd_inner_microstep: 272.77 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 334 +[2025-05-02 00:55:54,065] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 90.19 | bwd_microstep: 128.44 | bwd_inner_microstep: 128.29 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 323 +[2025-05-02 00:55:54,285] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 86.22 | bwd_microstep: 119.78 | bwd_inner_microstep: 119.53 | bwd_allreduce_microstep: 0.10 | step_microstep: 0.10 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 836 +[2025-05-02 00:55:54,524] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 98.15 | bwd_microstep: 125.93 | bwd_inner_microstep: 125.73 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 00:55:54,998] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.90 | bwd_microstep: 271.42 | bwd_inner_microstep: 271.40 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 00:55:55,475] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.09 | bwd_microstep: 272.02 | bwd_inner_microstep: 272.00 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 836 +[2025-05-02 00:55:55,712] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 97.37 | bwd_microstep: 125.42 | bwd_inner_microstep: 125.18 | bwd_allreduce_microstep: 0.08 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 00:55:56,186] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.89 | bwd_microstep: 271.30 | bwd_inner_microstep: 271.28 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 828 +[2025-05-02 00:55:56,429] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 98.69 | bwd_microstep: 129.00 | bwd_inner_microstep: 128.89 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 316 +[2025-05-02 00:55:56,779] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.08 | optimizer_step: 16.63 +[2025-05-02 00:55:56,779] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 89.83 | bwd_microstep: 221.38 | bwd_inner_microstep: 136.73 | bwd_allreduce_microstep: 84.53 | step_microstep: 25.27 +[2025-05-02 00:55:56,781] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2452.25 | bwd: 3600.06 | bwd_inner: 3514.44 | bwd_allreduce: 84.89 | step: 26.28 + 11%|█ | 924/8720 [2:40:30<22:25:02, 10.35s/it] {'loss': 0.8315, 'grad_norm': 12.051263809204102, 'learning_rate': 9.849605800712862e-06, 'epoch': 1.06} + 11%|█ | 924/8720 [2:40:30<22:25:02, 10.35s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 00:55:57,260] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.37 | bwd_microstep: 271.02 | bwd_inner_microstep: 271.00 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 391 +[2025-05-02 00:55:57,481] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 89.33 | bwd_microstep: 117.89 | bwd_inner_microstep: 117.75 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1891 +[2025-05-02 00:55:57,958] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.79 | bwd_microstep: 273.53 | bwd_inner_microstep: 273.51 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 345 +[2025-05-02 00:55:58,187] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.60 | bwd_microstep: 121.30 | bwd_inner_microstep: 121.16 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1366 +[2025-05-02 00:55:58,551] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 142.61 | bwd_microstep: 206.33 | bwd_inner_microstep: 206.20 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 00:55:59,026] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.76 | bwd_microstep: 272.01 | bwd_inner_microstep: 271.99 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 00:55:59,502] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.72 | bwd_microstep: 271.69 | bwd_inner_microstep: 271.67 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 00:55:59,978] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.33 | bwd_microstep: 271.05 | bwd_inner_microstep: 271.04 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 00:56:00,452] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.98 | bwd_microstep: 271.28 | bwd_inner_microstep: 271.26 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 00:56:00,928] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.37 | bwd_microstep: 271.30 | bwd_inner_microstep: 271.29 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 00:56:01,404] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.92 | bwd_microstep: 271.44 | bwd_inner_microstep: 271.42 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 00:56:01,878] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.10 | bwd_microstep: 269.88 | bwd_inner_microstep: 269.86 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 00:56:02,353] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.17 | bwd_microstep: 269.94 | bwd_inner_microstep: 269.93 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 00:56:02,828] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.97 | bwd_microstep: 269.94 | bwd_inner_microstep: 269.92 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.22 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 00:56:03,302] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.30 | bwd_microstep: 269.97 | bwd_inner_microstep: 269.96 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1974 +[2025-05-02 00:56:03,914] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.13 | optimizer_step: 16.60 +[2025-05-02 00:56:03,915] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.58 | bwd_microstep: 376.03 | bwd_inner_microstep: 291.19 | bwd_allreduce_microstep: 84.79 | step_microstep: 25.22 +[2025-05-02 00:56:03,916] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2772.56 | bwd: 4074.67 | bwd_inner: 3989.19 | bwd_allreduce: 85.08 | step: 26.30 + 11%|█ | 925/8720 [2:40:37<20:19:30, 9.39s/it] {'loss': 0.6318, 'grad_norm': 8.576592445373535, 'learning_rate': 9.849153394656594e-06, 'epoch': 1.06} + 11%|█ | 925/8720 [2:40:37<20:19:30, 9.39s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1891 +[2025-05-02 00:56:04,398] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.09 | bwd_microstep: 272.95 | bwd_inner_microstep: 272.93 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1903 +[2025-05-02 00:56:04,877] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.09 | bwd_microstep: 274.78 | bwd_inner_microstep: 274.76 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1891 +[2025-05-02 00:56:05,355] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.58 | bwd_microstep: 274.04 | bwd_inner_microstep: 274.02 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1887 +[2025-05-02 00:56:05,833] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.62 | bwd_microstep: 273.63 | bwd_inner_microstep: 273.62 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 844 +[2025-05-02 00:56:06,077] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 96.96 | bwd_microstep: 131.52 | bwd_inner_microstep: 131.16 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.22 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1362 +[2025-05-02 00:56:06,438] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.34 | bwd_microstep: 205.85 | bwd_inner_microstep: 205.84 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 00:56:06,911] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.95 | bwd_microstep: 270.98 | bwd_inner_microstep: 270.96 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 331 +[2025-05-02 00:56:07,127] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 82.28 | bwd_microstep: 119.64 | bwd_inner_microstep: 119.22 | bwd_allreduce_microstep: 0.19 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 00:56:07,602] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.98 | bwd_microstep: 271.92 | bwd_inner_microstep: 271.90 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 00:56:08,078] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.62 | bwd_microstep: 272.00 | bwd_inner_microstep: 271.98 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 00:56:08,553] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.85 | bwd_microstep: 271.98 | bwd_inner_microstep: 271.96 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 00:56:09,030] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.15 | bwd_microstep: 272.73 | bwd_inner_microstep: 272.72 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 00:56:09,508] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.71 | bwd_microstep: 272.01 | bwd_inner_microstep: 271.99 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 00:56:09,985] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.55 | bwd_microstep: 272.10 | bwd_inner_microstep: 272.08 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 00:56:10,460] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.90 | bwd_microstep: 270.67 | bwd_inner_microstep: 270.64 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 00:56:11,044] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.18 | optimizer_step: 16.69 +[2025-05-02 00:56:11,045] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.17 | bwd_microstep: 356.57 | bwd_inner_microstep: 271.40 | bwd_allreduce_microstep: 85.12 | step_microstep: 25.52 +[2025-05-02 00:56:11,046] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2766.53 | bwd: 4083.46 | bwd_inner: 3997.31 | bwd_allreduce: 85.48 | step: 26.62 + 11%|█ | 926/8720 [2:40:44<18:51:23, 8.71s/it] {'loss': 0.8439, 'grad_norm': 9.263410568237305, 'learning_rate': 9.84870031959388e-06, 'epoch': 1.06} + 11%|█ | 926/8720 [2:40:44<18:51:23, 8.71s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1850 +[2025-05-02 00:56:11,525] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.41 | bwd_microstep: 270.10 | bwd_inner_microstep: 270.08 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2142 +[2025-05-02 00:56:12,061] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 206.38 | bwd_microstep: 314.19 | bwd_inner_microstep: 314.18 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1898 +[2025-05-02 00:56:12,541] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.14 | bwd_microstep: 275.82 | bwd_inner_microstep: 275.81 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-02 00:56:13,020] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.56 | bwd_microstep: 273.91 | bwd_inner_microstep: 273.89 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-02 00:56:13,496] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.66 | bwd_microstep: 273.22 | bwd_inner_microstep: 273.20 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-02 00:56:13,974] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.61 | bwd_microstep: 273.85 | bwd_inner_microstep: 273.83 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-02 00:56:14,452] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.85 | bwd_microstep: 273.85 | bwd_inner_microstep: 273.83 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1363 +[2025-05-02 00:56:14,818] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 143.97 | bwd_microstep: 206.95 | bwd_inner_microstep: 206.82 | bwd_allreduce_microstep: 0.09 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-02 00:56:15,295] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.91 | bwd_microstep: 273.57 | bwd_inner_microstep: 273.56 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 00:56:15,773] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.00 | bwd_microstep: 272.24 | bwd_inner_microstep: 272.23 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 00:56:16,249] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.02 | bwd_microstep: 272.42 | bwd_inner_microstep: 272.40 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 00:56:16,726] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.76 | bwd_microstep: 272.80 | bwd_inner_microstep: 272.78 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 845 +[2025-05-02 00:56:16,970] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 97.24 | bwd_microstep: 131.96 | bwd_inner_microstep: 131.92 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 335 +[2025-05-02 00:56:17,206] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 84.61 | bwd_microstep: 138.15 | bwd_inner_microstep: 138.00 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 00:56:17,681] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.53 | bwd_microstep: 271.18 | bwd_inner_microstep: 271.16 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 00:56:18,265] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.11 | optimizer_step: 16.65 +[2025-05-02 00:56:18,266] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.85 | bwd_microstep: 356.60 | bwd_inner_microstep: 271.29 | bwd_allreduce_microstep: 85.26 | step_microstep: 25.28 +[2025-05-02 00:56:18,267] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2792.20 | bwd: 4150.89 | bwd_inner: 4065.01 | bwd_allreduce: 85.51 | step: 26.21 + 11%|█ | 927/8720 [2:40:52<17:53:15, 8.26s/it] {'loss': 0.9148, 'grad_norm': 5.808866500854492, 'learning_rate': 9.848246575587229e-06, 'epoch': 1.06} + 11%|█ | 927/8720 [2:40:52<17:53:15, 8.26s/it]dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1443 +[2025-05-02 00:56:18,649] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 147.32 | bwd_microstep: 214.39 | bwd_inner_microstep: 214.35 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1903 +[2025-05-02 00:56:19,130] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.04 | bwd_microstep: 275.79 | bwd_inner_microstep: 275.77 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 868 +[2025-05-02 00:56:19,383] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 104.74 | bwd_microstep: 133.66 | bwd_inner_microstep: 133.37 | bwd_allreduce_microstep: 0.17 | step_microstep: 0.10 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 348 +[2025-05-02 00:56:19,601] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 83.43 | bwd_microstep: 120.25 | bwd_inner_microstep: 120.02 | bwd_allreduce_microstep: 0.09 | step_microstep: 0.14 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 00:56:20,079] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.29 | bwd_microstep: 273.44 | bwd_inner_microstep: 273.43 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 00:56:20,555] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.51 | bwd_microstep: 272.90 | bwd_inner_microstep: 272.89 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 00:56:21,031] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.62 | bwd_microstep: 272.39 | bwd_inner_microstep: 272.37 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 00:56:21,507] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.61 | bwd_microstep: 272.23 | bwd_inner_microstep: 272.21 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 00:56:21,984] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.68 | bwd_microstep: 272.52 | bwd_inner_microstep: 272.50 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 00:56:22,461] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.99 | bwd_microstep: 272.41 | bwd_inner_microstep: 272.39 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 00:56:22,939] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.59 | bwd_microstep: 272.34 | bwd_inner_microstep: 272.32 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 00:56:23,415] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.30 | bwd_microstep: 272.39 | bwd_inner_microstep: 272.38 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 00:56:23,890] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.81 | bwd_microstep: 270.95 | bwd_inner_microstep: 270.94 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.22 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 00:56:24,364] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.03 | bwd_microstep: 271.09 | bwd_inner_microstep: 271.07 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 00:56:24,840] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.34 | bwd_microstep: 271.00 | bwd_inner_microstep: 270.98 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1954 +[2025-05-02 00:56:25,452] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.13 | optimizer_step: 16.55 +[2025-05-02 00:56:25,452] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 196.60 | bwd_microstep: 374.37 | bwd_inner_microstep: 289.62 | bwd_allreduce_microstep: 84.69 | step_microstep: 24.99 +[2025-05-02 00:56:25,453] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2793.61 | bwd: 4112.20 | bwd_inner: 4026.68 | bwd_allreduce: 84.99 | step: 26.17 + 11%|█ | 928/8720 [2:40:59<17:11:09, 7.94s/it] {'loss': 0.8842, 'grad_norm': 7.933078765869141, 'learning_rate': 9.847792162699241e-06, 'epoch': 1.06} + 11%|█ | 928/8720 [2:40:59<17:11:09, 7.94s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1903 +[2025-05-02 00:56:25,938] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.02 | bwd_microstep: 275.08 | bwd_inner_microstep: 275.06 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 993 +[2025-05-02 00:56:26,209] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 107.02 | bwd_microstep: 150.62 | bwd_inner_microstep: 150.53 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1893 +[2025-05-02 00:56:26,689] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.33 | bwd_microstep: 275.16 | bwd_inner_microstep: 275.14 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1900 +[2025-05-02 00:56:27,171] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 192.01 | bwd_microstep: 275.35 | bwd_inner_microstep: 275.33 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-02 00:56:27,649] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.30 | bwd_microstep: 273.72 | bwd_inner_microstep: 273.70 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 00:56:28,125] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.56 | bwd_microstep: 272.23 | bwd_inner_microstep: 272.22 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 00:56:28,603] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.96 | bwd_microstep: 272.83 | bwd_inner_microstep: 272.82 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1098 +[2025-05-02 00:56:28,894] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 115.51 | bwd_microstep: 161.21 | bwd_inner_microstep: 161.09 | bwd_allreduce_microstep: 0.04 | step_microstep: 0.17 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 00:56:29,370] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.04 | bwd_microstep: 272.57 | bwd_inner_microstep: 272.55 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 327 +[2025-05-02 00:56:29,591] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 83.21 | bwd_microstep: 121.97 | bwd_inner_microstep: 121.83 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 839 +[2025-05-02 00:56:29,830] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 96.06 | bwd_microstep: 126.32 | bwd_inner_microstep: 126.08 | bwd_allreduce_microstep: 0.14 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 00:56:30,307] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.96 | bwd_microstep: 272.30 | bwd_inner_microstep: 272.29 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 00:56:30,784] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.52 | bwd_microstep: 271.21 | bwd_inner_microstep: 271.20 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 00:56:31,261] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.56 | bwd_microstep: 271.37 | bwd_inner_microstep: 271.36 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 00:56:31,741] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.71 | bwd_microstep: 271.36 | bwd_inner_microstep: 271.35 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 00:56:32,320] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.08 | optimizer_step: 16.49 +[2025-05-02 00:56:32,321] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.36 | bwd_microstep: 349.42 | bwd_inner_microstep: 271.98 | bwd_allreduce_microstep: 77.39 | step_microstep: 24.08 +[2025-05-02 00:56:32,322] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2668.81 | bwd: 3912.84 | bwd_inner: 3834.52 | bwd_allreduce: 77.79 | step: 25.19 + 11%|█ | 929/8720 [2:41:06<16:29:20, 7.62s/it] {'loss': 0.6612, 'grad_norm': 5.317251205444336, 'learning_rate': 9.847337080992612e-06, 'epoch': 1.07} + 11%|█ | 929/8720 [2:41:06<16:29:20, 7.62s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 435 +[2025-05-02 00:56:32,537] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 81.51 | bwd_microstep: 112.19 | bwd_inner_microstep: 112.05 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1954 +[2025-05-02 00:56:33,037] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.09 | bwd_microstep: 289.14 | bwd_inner_microstep: 289.13 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-02 00:56:33,514] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.25 | bwd_microstep: 273.51 | bwd_inner_microstep: 273.49 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1362 +[2025-05-02 00:56:33,876] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.44 | bwd_microstep: 207.32 | bwd_inner_microstep: 207.31 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 00:56:34,352] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.69 | bwd_microstep: 272.17 | bwd_inner_microstep: 272.15 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-02 00:56:34,828] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.20 | bwd_microstep: 273.03 | bwd_inner_microstep: 273.01 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 00:56:35,305] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.63 | bwd_microstep: 271.85 | bwd_inner_microstep: 271.83 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.13 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 00:56:35,784] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.58 | bwd_microstep: 272.11 | bwd_inner_microstep: 272.09 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 00:56:36,263] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.29 | bwd_microstep: 272.28 | bwd_inner_microstep: 272.26 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.13 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 323 +[2025-05-02 00:56:36,491] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 91.12 | bwd_microstep: 117.92 | bwd_inner_microstep: 117.61 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.10 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 325 +[2025-05-02 00:56:36,708] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 83.92 | bwd_microstep: 118.00 | bwd_inner_microstep: 117.68 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 00:56:37,184] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.98 | bwd_microstep: 271.11 | bwd_inner_microstep: 271.09 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 00:56:37,664] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.72 | bwd_microstep: 271.01 | bwd_inner_microstep: 271.00 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 00:56:38,143] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.50 | bwd_microstep: 270.69 | bwd_inner_microstep: 270.67 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 00:56:38,622] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.03 | bwd_microstep: 271.17 | bwd_inner_microstep: 271.15 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 00:56:39,202] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.17 | optimizer_step: 16.61 +[2025-05-02 00:56:39,203] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.47 | bwd_microstep: 349.37 | bwd_inner_microstep: 271.46 | bwd_allreduce_microstep: 77.85 | step_microstep: 24.62 +[2025-05-02 00:56:39,204] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2657.07 | bwd: 3912.95 | bwd_inner: 3834.13 | bwd_allreduce: 78.22 | step: 25.88 + 11%|█ | 930/8720 [2:41:12<16:00:33, 7.40s/it] {'loss': 0.7695, 'grad_norm': 8.17477035522461, 'learning_rate': 9.84688133053012e-06, 'epoch': 1.07} + 11%|█ | 930/8720 [2:41:12<16:00:33, 7.40s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 433 +[2025-05-02 00:56:39,431] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 82.95 | bwd_microstep: 120.74 | bwd_inner_microstep: 120.58 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2293 +[2025-05-02 00:56:39,985] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 210.69 | bwd_microstep: 326.27 | bwd_inner_microstep: 326.25 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1911 +[2025-05-02 00:56:40,469] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.04 | bwd_microstep: 276.20 | bwd_inner_microstep: 276.18 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1887 +[2025-05-02 00:56:40,949] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.41 | bwd_microstep: 274.33 | bwd_inner_microstep: 274.31 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 00:56:41,426] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.14 | bwd_microstep: 273.05 | bwd_inner_microstep: 273.03 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 00:56:41,904] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.72 | bwd_microstep: 272.58 | bwd_inner_microstep: 272.56 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 841 +[2025-05-02 00:56:42,160] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 108.83 | bwd_microstep: 131.08 | bwd_inner_microstep: 130.91 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 00:56:42,641] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.17 | bwd_microstep: 272.73 | bwd_inner_microstep: 272.71 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 00:56:43,122] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.76 | bwd_microstep: 272.53 | bwd_inner_microstep: 272.51 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 00:56:43,603] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.33 | bwd_microstep: 272.91 | bwd_inner_microstep: 272.89 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 00:56:44,083] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.14 | bwd_microstep: 272.05 | bwd_inner_microstep: 272.03 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 00:56:44,562] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.20 | bwd_microstep: 271.95 | bwd_inner_microstep: 271.93 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 00:56:45,041] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.64 | bwd_microstep: 271.01 | bwd_inner_microstep: 270.99 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 00:56:45,518] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.58 | bwd_microstep: 271.15 | bwd_inner_microstep: 271.13 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 00:56:45,997] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.68 | bwd_microstep: 272.35 | bwd_inner_microstep: 272.33 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 00:56:46,603] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.12 | optimizer_step: 16.51 +[2025-05-02 00:56:46,603] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.83 | bwd_microstep: 372.34 | bwd_inner_microstep: 272.93 | bwd_allreduce_microstep: 99.35 | step_microstep: 26.12 +[2025-05-02 00:56:46,605] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2854.70 | bwd: 4223.30 | bwd_inner: 4123.33 | bwd_allreduce: 99.57 | step: 27.27 + 11%|█ | 931/8720 [2:41:20<16:00:29, 7.40s/it] {'loss': 0.7326, 'grad_norm': 8.662299156188965, 'learning_rate': 9.846424911374647e-06, 'epoch': 1.07} + 11%|█ | 931/8720 [2:41:20<16:00:29, 7.40s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 00:56:47,087] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.36 | bwd_microstep: 270.57 | bwd_inner_microstep: 270.56 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 358 +[2025-05-02 00:56:47,312] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 92.93 | bwd_microstep: 116.53 | bwd_inner_microstep: 116.38 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1890 +[2025-05-02 00:56:47,790] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.46 | bwd_microstep: 274.64 | bwd_inner_microstep: 274.62 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1883 +[2025-05-02 00:56:48,269] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.93 | bwd_microstep: 274.56 | bwd_inner_microstep: 274.54 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 00:56:48,744] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.94 | bwd_microstep: 272.69 | bwd_inner_microstep: 272.67 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1371 +[2025-05-02 00:56:49,109] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.64 | bwd_microstep: 207.81 | bwd_inner_microstep: 207.59 | bwd_allreduce_microstep: 0.15 | step_microstep: 0.14 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 00:56:49,588] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.28 | bwd_microstep: 272.99 | bwd_inner_microstep: 272.97 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 00:56:50,067] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.66 | bwd_microstep: 273.04 | bwd_inner_microstep: 273.03 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 838 +[2025-05-02 00:56:50,317] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 108.46 | bwd_microstep: 125.31 | bwd_inner_microstep: 125.27 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 00:56:50,796] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.17 | bwd_microstep: 272.85 | bwd_inner_microstep: 272.83 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 00:56:51,274] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.14 | bwd_microstep: 272.78 | bwd_inner_microstep: 272.76 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 00:56:51,751] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.98 | bwd_microstep: 272.51 | bwd_inner_microstep: 272.50 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 00:56:52,228] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.72 | bwd_microstep: 272.63 | bwd_inner_microstep: 272.61 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 327 +[2025-05-02 00:56:52,461] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 92.27 | bwd_microstep: 126.99 | bwd_inner_microstep: 126.65 | bwd_allreduce_microstep: 0.15 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 00:56:52,938] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.23 | bwd_microstep: 272.23 | bwd_inner_microstep: 272.22 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 00:56:53,525] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.14 | optimizer_step: 16.48 +[2025-05-02 00:56:53,526] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.94 | bwd_microstep: 358.34 | bwd_inner_microstep: 272.84 | bwd_allreduce_microstep: 85.44 | step_microstep: 24.88 +[2025-05-02 00:56:53,527] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2699.78 | bwd: 3936.54 | bwd_inner: 3850.13 | bwd_allreduce: 85.84 | step: 25.90 + 11%|█ | 932/8720 [2:41:27<15:41:43, 7.26s/it] {'loss': 0.9255, 'grad_norm': 6.322269439697266, 'learning_rate': 9.845967823589162e-06, 'epoch': 1.07} + 11%|█ | 932/8720 [2:41:27<15:41:43, 7.26s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 00:56:54,007] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.76 | bwd_microstep: 271.16 | bwd_inner_microstep: 271.14 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1416 +[2025-05-02 00:56:54,383] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 145.77 | bwd_microstep: 213.22 | bwd_inner_microstep: 213.19 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 377 +[2025-05-02 00:56:54,604] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 69.44 | bwd_microstep: 138.80 | bwd_inner_microstep: 138.46 | bwd_allreduce_microstep: 0.16 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1901 +[2025-05-02 00:56:55,084] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.22 | bwd_microstep: 275.82 | bwd_inner_microstep: 275.80 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1894 +[2025-05-02 00:56:55,564] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.73 | bwd_microstep: 275.69 | bwd_inner_microstep: 275.68 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-02 00:56:56,043] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.67 | bwd_microstep: 273.67 | bwd_inner_microstep: 273.65 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1883 +[2025-05-02 00:56:56,521] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.84 | bwd_microstep: 274.54 | bwd_inner_microstep: 274.53 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 00:56:56,999] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.17 | bwd_microstep: 273.36 | bwd_inner_microstep: 273.34 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 00:56:57,479] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.66 | bwd_microstep: 273.35 | bwd_inner_microstep: 273.33 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 00:56:57,961] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.18 | bwd_microstep: 272.65 | bwd_inner_microstep: 272.63 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 00:56:58,440] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.64 | bwd_microstep: 272.80 | bwd_inner_microstep: 272.79 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 00:56:58,917] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.54 | bwd_microstep: 271.75 | bwd_inner_microstep: 271.73 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 00:56:59,395] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.40 | bwd_microstep: 272.97 | bwd_inner_microstep: 272.95 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 00:56:59,871] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.64 | bwd_microstep: 271.73 | bwd_inner_microstep: 271.71 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 00:57:00,347] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.02 | bwd_microstep: 271.73 | bwd_inner_microstep: 271.71 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 00:57:00,914] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.06 | optimizer_step: 19.94 +[2025-05-02 00:57:00,914] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.88 | bwd_microstep: 337.90 | bwd_inner_microstep: 272.11 | bwd_allreduce_microstep: 65.75 | step_microstep: 26.96 +[2025-05-02 00:57:00,915] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2861.26 | bwd: 4241.19 | bwd_inner: 4174.83 | bwd_allreduce: 66.00 | step: 27.76 + 11%|█ | 933/8720 [2:41:34<15:46:47, 7.30s/it] {'loss': 0.9346, 'grad_norm': 5.176520347595215, 'learning_rate': 9.845510067236725e-06, 'epoch': 1.07} + 11%|█ | 933/8720 [2:41:34<15:46:47, 7.30s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 317 +[2025-05-02 00:57:01,117] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 67.17 | bwd_microstep: 116.43 | bwd_inner_microstep: 116.20 | bwd_allreduce_microstep: 0.09 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1894 +[2025-05-02 00:57:01,597] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.76 | bwd_microstep: 274.94 | bwd_inner_microstep: 274.92 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1891 +[2025-05-02 00:57:02,076] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.41 | bwd_microstep: 274.68 | bwd_inner_microstep: 274.66 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 00:57:02,556] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.72 | bwd_microstep: 273.63 | bwd_inner_microstep: 273.61 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1889 +[2025-05-02 00:57:03,039] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.40 | bwd_microstep: 274.49 | bwd_inner_microstep: 274.48 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1366 +[2025-05-02 00:57:03,404] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.88 | bwd_microstep: 206.97 | bwd_inner_microstep: 206.95 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 00:57:03,882] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.14 | bwd_microstep: 272.70 | bwd_inner_microstep: 272.68 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1357 +[2025-05-02 00:57:04,246] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.40 | bwd_microstep: 206.63 | bwd_inner_microstep: 206.55 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.10 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 330 +[2025-05-02 00:57:04,447] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 68.57 | bwd_microstep: 117.59 | bwd_inner_microstep: 117.30 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 00:57:04,922] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.36 | bwd_microstep: 272.22 | bwd_inner_microstep: 272.20 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 00:57:05,397] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.90 | bwd_microstep: 272.33 | bwd_inner_microstep: 272.31 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 323 +[2025-05-02 00:57:05,599] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 72.53 | bwd_microstep: 116.17 | bwd_inner_microstep: 115.96 | bwd_allreduce_microstep: 0.09 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 00:57:06,073] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.35 | bwd_microstep: 272.15 | bwd_inner_microstep: 272.13 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 00:57:06,548] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.44 | bwd_microstep: 272.24 | bwd_inner_microstep: 272.23 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 00:57:07,022] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.05 | bwd_microstep: 271.08 | bwd_inner_microstep: 271.07 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1948 +[2025-05-02 00:57:07,619] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.09 | optimizer_step: 16.50 +[2025-05-02 00:57:07,620] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 196.76 | bwd_microstep: 362.20 | bwd_inner_microstep: 289.91 | bwd_allreduce_microstep: 72.25 | step_microstep: 23.50 +[2025-05-02 00:57:07,621] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2570.53 | bwd: 3856.50 | bwd_inner: 3783.30 | bwd_allreduce: 72.61 | step: 24.42 + 11%|█ | 934/8720 [2:41:41<15:23:41, 7.12s/it] {'loss': 1.106, 'grad_norm': 9.426248550415039, 'learning_rate': 9.84505164238049e-06, 'epoch': 1.07} + 11%|█ | 934/8720 [2:41:41<15:23:41, 7.12s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 344 +[2025-05-02 00:57:07,852] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 96.31 | bwd_microstep: 117.43 | bwd_inner_microstep: 117.15 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2105 +[2025-05-02 00:57:08,381] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 202.94 | bwd_microstep: 311.08 | bwd_inner_microstep: 311.06 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1988 +[2025-05-02 00:57:08,887] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 197.05 | bwd_microstep: 293.66 | bwd_inner_microstep: 293.64 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1386 +[2025-05-02 00:57:09,256] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 144.05 | bwd_microstep: 208.28 | bwd_inner_microstep: 208.25 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 873 +[2025-05-02 00:57:09,510] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 96.71 | bwd_microstep: 134.49 | bwd_inner_microstep: 134.30 | bwd_allreduce_microstep: 0.09 | step_microstep: 0.08 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 344 +[2025-05-02 00:57:09,716] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 75.04 | bwd_microstep: 118.35 | bwd_inner_microstep: 118.21 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 00:57:10,192] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.98 | bwd_microstep: 273.07 | bwd_inner_microstep: 273.05 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 00:57:10,670] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.04 | bwd_microstep: 273.19 | bwd_inner_microstep: 273.18 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 00:57:11,153] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.93 | bwd_microstep: 272.18 | bwd_inner_microstep: 272.16 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 00:57:11,629] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.94 | bwd_microstep: 271.20 | bwd_inner_microstep: 271.18 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 00:57:12,103] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.41 | bwd_microstep: 271.31 | bwd_inner_microstep: 271.29 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 00:57:12,581] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.04 | bwd_microstep: 272.42 | bwd_inner_microstep: 272.41 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 00:57:13,060] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.02 | bwd_microstep: 271.45 | bwd_inner_microstep: 271.43 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 00:57:13,540] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.70 | bwd_microstep: 271.30 | bwd_inner_microstep: 271.29 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 00:57:14,018] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.51 | bwd_microstep: 271.08 | bwd_inner_microstep: 271.06 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 827 +[2025-05-02 00:57:14,363] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.07 | optimizer_step: 16.51 +[2025-05-02 00:57:14,364] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.78 | bwd_microstep: 209.09 | bwd_inner_microstep: 129.98 | bwd_allreduce_microstep: 79.02 | step_microstep: 24.01 +[2025-05-02 00:57:14,365] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2602.07 | bwd: 3839.68 | bwd_inner: 3759.77 | bwd_allreduce: 79.30 | step: 25.00 + 11%|█ | 935/8720 [2:41:48<15:09:06, 7.01s/it] {'loss': 0.6011, 'grad_norm': 4.594846725463867, 'learning_rate': 9.844592549083701e-06, 'epoch': 1.07} + 11%|█ | 935/8720 [2:41:48<15:09:06, 7.01s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 00:57:14,846] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.22 | bwd_microstep: 270.32 | bwd_inner_microstep: 270.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1953 +[2025-05-02 00:57:15,349] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 196.73 | bwd_microstep: 288.90 | bwd_inner_microstep: 288.88 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 879 +[2025-05-02 00:57:15,600] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 97.10 | bwd_microstep: 134.84 | bwd_inner_microstep: 134.62 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1888 +[2025-05-02 00:57:16,081] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.16 | bwd_microstep: 274.29 | bwd_inner_microstep: 274.27 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1889 +[2025-05-02 00:57:16,564] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.81 | bwd_microstep: 274.40 | bwd_inner_microstep: 274.38 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1892 +[2025-05-02 00:57:17,050] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.75 | bwd_microstep: 275.12 | bwd_inner_microstep: 275.10 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-02 00:57:17,530] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.07 | bwd_microstep: 274.00 | bwd_inner_microstep: 273.99 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 845 +[2025-05-02 00:57:17,776] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.21 | bwd_microstep: 132.46 | bwd_inner_microstep: 132.25 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 00:57:18,254] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.38 | bwd_microstep: 272.55 | bwd_inner_microstep: 272.54 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 00:57:18,731] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.33 | bwd_microstep: 272.14 | bwd_inner_microstep: 272.12 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1355 +[2025-05-02 00:57:19,097] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 143.07 | bwd_microstep: 206.17 | bwd_inner_microstep: 206.15 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 318 +[2025-05-02 00:57:19,313] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 79.40 | bwd_microstep: 120.83 | bwd_inner_microstep: 120.53 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 00:57:19,789] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.04 | bwd_microstep: 270.74 | bwd_inner_microstep: 270.73 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 00:57:20,269] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.14 | bwd_microstep: 270.97 | bwd_inner_microstep: 270.96 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 00:57:20,751] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.75 | bwd_microstep: 271.00 | bwd_inner_microstep: 270.98 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1903 +[2025-05-02 00:57:21,338] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.15 | optimizer_step: 16.60 +[2025-05-02 00:57:21,339] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.71 | bwd_microstep: 356.32 | bwd_inner_microstep: 276.12 | bwd_allreduce_microstep: 80.14 | step_microstep: 24.59 +[2025-05-02 00:57:21,340] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2682.50 | bwd: 3965.14 | bwd_inner: 3883.99 | bwd_allreduce: 80.55 | step: 25.67 + 11%|█ | 936/8720 [2:41:55<15:07:45, 7.00s/it] {'loss': 1.0742, 'grad_norm': 8.451133728027344, 'learning_rate': 9.844132787409699e-06, 'epoch': 1.07} + 11%|█ | 936/8720 [2:41:55<15:07:45, 7.00s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 00:57:21,824] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.86 | bwd_microstep: 271.70 | bwd_inner_microstep: 271.68 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1905 +[2025-05-02 00:57:22,310] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.64 | bwd_microstep: 275.94 | bwd_inner_microstep: 275.92 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1889 +[2025-05-02 00:57:22,795] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.94 | bwd_microstep: 274.47 | bwd_inner_microstep: 274.45 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1896 +[2025-05-02 00:57:23,279] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.11 | bwd_microstep: 274.98 | bwd_inner_microstep: 274.96 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1889 +[2025-05-02 00:57:23,765] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.47 | bwd_microstep: 274.79 | bwd_inner_microstep: 274.78 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-02 00:57:24,247] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.76 | bwd_microstep: 273.97 | bwd_inner_microstep: 273.95 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1888 +[2025-05-02 00:57:24,732] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.38 | bwd_microstep: 274.35 | bwd_inner_microstep: 274.33 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1371 +[2025-05-02 00:57:25,099] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.85 | bwd_microstep: 207.76 | bwd_inner_microstep: 207.75 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 00:57:25,577] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.09 | bwd_microstep: 273.14 | bwd_inner_microstep: 273.12 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 00:57:26,055] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.27 | bwd_microstep: 272.33 | bwd_inner_microstep: 272.31 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 00:57:26,532] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.75 | bwd_microstep: 272.54 | bwd_inner_microstep: 272.53 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 00:57:27,008] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.54 | bwd_microstep: 272.61 | bwd_inner_microstep: 272.58 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 00:57:27,486] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.32 | bwd_microstep: 272.33 | bwd_inner_microstep: 272.32 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 321 +[2025-05-02 00:57:27,696] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 79.73 | bwd_microstep: 117.32 | bwd_inner_microstep: 117.03 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 00:57:28,176] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.64 | bwd_microstep: 272.18 | bwd_inner_microstep: 272.16 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 00:57:28,747] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.06 | optimizer_step: 20.01 +[2025-05-02 00:57:28,747] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.61 | bwd_microstep: 340.47 | bwd_inner_microstep: 271.54 | bwd_allreduce_microstep: 68.88 | step_microstep: 26.98 +[2025-05-02 00:57:28,748] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2863.58 | bwd: 4220.90 | bwd_inner: 4151.45 | bwd_allreduce: 69.07 | step: 27.87 + 11%|█ | 937/8720 [2:42:02<15:23:33, 7.12s/it] {'loss': 1.1211, 'grad_norm': 7.766535758972168, 'learning_rate': 9.843672357421914e-06, 'epoch': 1.07} + 11%|█ | 937/8720 [2:42:02<15:23:33, 7.12s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 323 +[2025-05-02 00:57:28,955] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 68.59 | bwd_microstep: 120.21 | bwd_inner_microstep: 120.00 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.09 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 922 +[2025-05-02 00:57:29,214] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 100.19 | bwd_microstep: 145.94 | bwd_inner_microstep: 145.92 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1181 +[2025-05-02 00:57:29,529] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 123.64 | bwd_microstep: 172.45 | bwd_inner_microstep: 172.31 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1889 +[2025-05-02 00:57:30,009] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.90 | bwd_microstep: 274.54 | bwd_inner_microstep: 274.52 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1360 +[2025-05-02 00:57:30,372] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.41 | bwd_microstep: 206.50 | bwd_inner_microstep: 206.48 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1883 +[2025-05-02 00:57:30,850] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.61 | bwd_microstep: 274.10 | bwd_inner_microstep: 274.08 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 845 +[2025-05-02 00:57:31,094] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.84 | bwd_microstep: 132.01 | bwd_inner_microstep: 131.99 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-02 00:57:31,570] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.27 | bwd_microstep: 273.31 | bwd_inner_microstep: 273.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 00:57:32,048] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.18 | bwd_microstep: 272.62 | bwd_inner_microstep: 272.60 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 00:57:32,528] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.83 | bwd_microstep: 272.59 | bwd_inner_microstep: 272.57 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.15 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 00:57:33,011] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.74 | bwd_microstep: 272.48 | bwd_inner_microstep: 272.46 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1353 +[2025-05-02 00:57:33,372] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.35 | bwd_microstep: 206.06 | bwd_inner_microstep: 206.04 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 00:57:33,847] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.62 | bwd_microstep: 272.29 | bwd_inner_microstep: 272.27 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 00:57:34,324] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.85 | bwd_microstep: 272.53 | bwd_inner_microstep: 272.51 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 00:57:34,803] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.93 | bwd_microstep: 271.29 | bwd_inner_microstep: 271.27 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 829 +[2025-05-02 00:57:35,130] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.07 | optimizer_gradients: 2.12 | optimizer_step: 16.71 +[2025-05-02 00:57:35,131] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.11 | bwd_microstep: 196.92 | bwd_inner_microstep: 130.55 | bwd_allreduce_microstep: 66.22 | step_microstep: 24.05 +[2025-05-02 00:57:35,132] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2458.74 | bwd: 3635.89 | bwd_inner: 3569.00 | bwd_allreduce: 66.42 | step: 25.09 + 11%|█ | 938/8720 [2:42:08<14:54:49, 6.90s/it] {'loss': 0.8128, 'grad_norm': 16.620817184448242, 'learning_rate': 9.843211259183868e-06, 'epoch': 1.08} + 11%|█ | 938/8720 [2:42:08<14:54:49, 6.90s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 00:57:35,610] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.34 | bwd_microstep: 270.37 | bwd_inner_microstep: 270.35 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1895 +[2025-05-02 00:57:36,090] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.49 | bwd_microstep: 274.96 | bwd_inner_microstep: 274.94 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1894 +[2025-05-02 00:57:36,574] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.58 | bwd_microstep: 274.96 | bwd_inner_microstep: 274.94 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-02 00:57:37,053] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.53 | bwd_microstep: 274.16 | bwd_inner_microstep: 274.15 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1889 +[2025-05-02 00:57:37,532] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.61 | bwd_microstep: 274.49 | bwd_inner_microstep: 274.47 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-02 00:57:38,009] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.42 | bwd_microstep: 273.73 | bwd_inner_microstep: 273.71 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1370 +[2025-05-02 00:57:38,376] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.44 | bwd_microstep: 207.99 | bwd_inner_microstep: 207.86 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.21 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-02 00:57:38,853] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.37 | bwd_microstep: 273.74 | bwd_inner_microstep: 273.72 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 00:57:39,329] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.71 | bwd_microstep: 272.06 | bwd_inner_microstep: 272.05 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.17 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 333 +[2025-05-02 00:57:39,543] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 83.16 | bwd_microstep: 117.09 | bwd_inner_microstep: 116.95 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.08 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1349 +[2025-05-02 00:57:39,908] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.52 | bwd_microstep: 205.49 | bwd_inner_microstep: 205.47 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 00:57:40,384] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.41 | bwd_microstep: 272.17 | bwd_inner_microstep: 272.15 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 322 +[2025-05-02 00:57:40,618] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 96.81 | bwd_microstep: 119.46 | bwd_inner_microstep: 119.11 | bwd_allreduce_microstep: 0.14 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 00:57:41,093] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.93 | bwd_microstep: 271.48 | bwd_inner_microstep: 271.47 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 00:57:41,568] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.82 | bwd_microstep: 271.13 | bwd_inner_microstep: 271.11 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 315 +[2025-05-02 00:57:41,881] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.16 | optimizer_step: 16.76 +[2025-05-02 00:57:41,882] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 74.69 | bwd_microstep: 200.79 | bwd_inner_microstep: 133.86 | bwd_allreduce_microstep: 66.80 | step_microstep: 24.03 +[2025-05-02 00:57:41,883] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2607.53 | bwd: 3854.17 | bwd_inner: 3786.50 | bwd_allreduce: 67.13 | step: 25.24 + 11%|█ | 939/8720 [2:42:15<14:48:56, 6.85s/it] {'loss': 1.0667, 'grad_norm': 8.15437126159668, 'learning_rate': 9.842749492759176e-06, 'epoch': 1.08} + 11%|█ | 939/8720 [2:42:15<14:48:56, 6.85s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 00:57:42,366] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.53 | bwd_microstep: 270.35 | bwd_inner_microstep: 270.33 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1759 +[2025-05-02 00:57:42,800] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 163.60 | bwd_microstep: 255.81 | bwd_inner_microstep: 255.79 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 435 +[2025-05-02 00:57:43,000] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 69.63 | bwd_microstep: 116.66 | bwd_inner_microstep: 116.53 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1917 +[2025-05-02 00:57:43,483] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.43 | bwd_microstep: 276.51 | bwd_inner_microstep: 276.49 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 856 +[2025-05-02 00:57:43,740] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 110.34 | bwd_microstep: 132.36 | bwd_inner_microstep: 132.13 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 00:57:44,216] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.61 | bwd_microstep: 272.76 | bwd_inner_microstep: 272.74 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-02 00:57:44,695] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.46 | bwd_microstep: 273.60 | bwd_inner_microstep: 273.58 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 00:57:45,175] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.95 | bwd_microstep: 272.97 | bwd_inner_microstep: 272.95 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 00:57:45,659] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.51 | bwd_microstep: 273.15 | bwd_inner_microstep: 273.13 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 00:57:46,144] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.59 | bwd_microstep: 272.49 | bwd_inner_microstep: 272.47 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 00:57:46,622] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.58 | bwd_microstep: 272.55 | bwd_inner_microstep: 272.53 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 00:57:47,101] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.44 | bwd_microstep: 272.47 | bwd_inner_microstep: 272.45 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 00:57:47,579] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.76 | bwd_microstep: 272.45 | bwd_inner_microstep: 272.43 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 00:57:48,058] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.02 | bwd_microstep: 271.20 | bwd_inner_microstep: 271.19 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 00:57:48,539] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.52 | bwd_microstep: 271.07 | bwd_inner_microstep: 271.05 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 00:57:49,134] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.05 | optimizer_step: 16.51 +[2025-05-02 00:57:49,134] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.11 | bwd_microstep: 359.69 | bwd_inner_microstep: 271.69 | bwd_allreduce_microstep: 87.94 | step_microstep: 24.19 +[2025-05-02 00:57:49,136] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2798.71 | bwd: 4136.10 | bwd_inner: 4047.54 | bwd_allreduce: 88.16 | step: 25.02 + 11%|█ | 940/8720 [2:42:22<15:04:22, 6.97s/it] {'loss': 0.78, 'grad_norm': 6.930126667022705, 'learning_rate': 9.842287058211543e-06, 'epoch': 1.08} + 11%|█ | 940/8720 [2:42:22<15:04:22, 6.97s/it]dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 827 +[2025-05-02 00:57:49,380] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 92.59 | bwd_microstep: 129.95 | bwd_inner_microstep: 129.81 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2341 +[2025-05-02 00:57:49,953] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 216.99 | bwd_microstep: 338.58 | bwd_inner_microstep: 338.56 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1888 +[2025-05-02 00:57:50,435] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.14 | bwd_microstep: 274.34 | bwd_inner_microstep: 274.32 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 00:57:50,914] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.13 | bwd_microstep: 272.69 | bwd_inner_microstep: 272.67 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 00:57:51,396] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.40 | bwd_microstep: 272.95 | bwd_inner_microstep: 272.93 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1356 +[2025-05-02 00:57:51,765] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.76 | bwd_microstep: 206.13 | bwd_inner_microstep: 206.03 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 00:57:52,243] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.93 | bwd_microstep: 272.49 | bwd_inner_microstep: 272.47 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 00:57:52,725] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.12 | bwd_microstep: 272.93 | bwd_inner_microstep: 272.91 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 00:57:53,205] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.96 | bwd_microstep: 272.22 | bwd_inner_microstep: 272.20 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.07 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 00:57:53,686] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.90 | bwd_microstep: 272.64 | bwd_inner_microstep: 272.62 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 00:57:54,165] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.75 | bwd_microstep: 271.90 | bwd_inner_microstep: 271.88 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 320 +[2025-05-02 00:57:54,392] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 89.90 | bwd_microstep: 118.72 | bwd_inner_microstep: 118.55 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 00:57:54,868] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.78 | bwd_microstep: 271.29 | bwd_inner_microstep: 271.27 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 00:57:55,348] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.91 | bwd_microstep: 271.13 | bwd_inner_microstep: 271.12 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2005 +[2025-05-02 00:57:55,861] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 198.11 | bwd_microstep: 294.60 | bwd_inner_microstep: 294.58 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1895 +[2025-05-02 00:57:56,447] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.05 | optimizer_step: 16.47 +[2025-05-02 00:57:56,448] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.02 | bwd_microstep: 352.19 | bwd_inner_microstep: 275.22 | bwd_allreduce_microstep: 76.92 | step_microstep: 24.20 +[2025-05-02 00:57:56,449] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2810.93 | bwd: 4164.80 | bwd_inner: 4087.20 | bwd_allreduce: 77.19 | step: 25.26 + 11%|█ | 941/8720 [2:42:30<15:17:25, 7.08s/it] {'loss': 0.912, 'grad_norm': 9.440176010131836, 'learning_rate': 9.841823955604772e-06, 'epoch': 1.08} + 11%|█ | 941/8720 [2:42:30<15:17:25, 7.08s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 00:57:56,934] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.54 | bwd_microstep: 272.91 | bwd_inner_microstep: 272.90 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1909 +[2025-05-02 00:57:57,419] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 191.08 | bwd_microstep: 276.34 | bwd_inner_microstep: 276.33 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 00:57:57,899] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.60 | bwd_microstep: 273.05 | bwd_inner_microstep: 273.03 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 00:57:58,378] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.94 | bwd_microstep: 273.07 | bwd_inner_microstep: 273.05 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 00:57:58,860] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.01 | bwd_microstep: 273.29 | bwd_inner_microstep: 273.27 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 00:57:59,340] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.26 | bwd_microstep: 272.51 | bwd_inner_microstep: 272.50 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 00:57:59,821] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.86 | bwd_microstep: 272.99 | bwd_inner_microstep: 272.98 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 00:58:00,301] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.89 | bwd_microstep: 272.95 | bwd_inner_microstep: 272.93 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 852 +[2025-05-02 00:58:00,552] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 100.92 | bwd_microstep: 132.54 | bwd_inner_microstep: 132.28 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 00:58:01,033] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.85 | bwd_microstep: 273.21 | bwd_inner_microstep: 273.19 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 00:58:01,512] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.08 | bwd_microstep: 272.84 | bwd_inner_microstep: 272.82 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 321 +[2025-05-02 00:58:01,735] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 89.19 | bwd_microstep: 118.32 | bwd_inner_microstep: 118.17 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 00:58:02,215] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.07 | bwd_microstep: 272.37 | bwd_inner_microstep: 272.35 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 00:58:02,695] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.71 | bwd_microstep: 272.51 | bwd_inner_microstep: 272.50 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 00:58:03,176] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.96 | bwd_microstep: 270.97 | bwd_inner_microstep: 270.95 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 00:58:03,757] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.05 | optimizer_step: 16.45 +[2025-05-02 00:58:03,758] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.69 | bwd_microstep: 347.96 | bwd_inner_microstep: 271.40 | bwd_allreduce_microstep: 76.50 | step_microstep: 24.11 +[2025-05-02 00:58:03,759] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2833.25 | bwd: 4147.91 | bwd_inner: 4070.69 | bwd_allreduce: 76.75 | step: 25.03 + 11%|█ | 942/8720 [2:42:37<15:26:23, 7.15s/it] {'loss': 0.7338, 'grad_norm': 5.7903218269348145, 'learning_rate': 9.84136018500275e-06, 'epoch': 1.08} + 11%|█ | 942/8720 [2:42:37<15:26:23, 7.15s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1911 +[2025-05-02 00:58:04,247] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.48 | bwd_microstep: 275.75 | bwd_inner_microstep: 275.73 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1144 +[2025-05-02 00:58:04,547] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 119.10 | bwd_microstep: 164.65 | bwd_inner_microstep: 164.63 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.08 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 848 +[2025-05-02 00:58:04,786] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.17 | bwd_microstep: 132.62 | bwd_inner_microstep: 132.37 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.15 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 845 +[2025-05-02 00:58:05,033] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 98.50 | bwd_microstep: 132.49 | bwd_inner_microstep: 132.09 | bwd_allreduce_microstep: 0.18 | step_microstep: 0.21 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 00:58:05,511] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.90 | bwd_microstep: 273.30 | bwd_inner_microstep: 273.28 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-02 00:58:05,993] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.80 | bwd_microstep: 273.38 | bwd_inner_microstep: 273.36 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 00:58:06,472] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.17 | bwd_microstep: 272.72 | bwd_inner_microstep: 272.70 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 00:58:06,951] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.90 | bwd_microstep: 272.68 | bwd_inner_microstep: 272.66 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1095 +[2025-05-02 00:58:07,243] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 117.28 | bwd_microstep: 161.13 | bwd_inner_microstep: 161.11 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 841 +[2025-05-02 00:58:07,481] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 92.45 | bwd_microstep: 132.42 | bwd_inner_microstep: 132.37 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 00:58:07,956] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.69 | bwd_microstep: 272.50 | bwd_inner_microstep: 272.49 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 00:58:08,435] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.69 | bwd_microstep: 273.01 | bwd_inner_microstep: 272.99 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 842 +[2025-05-02 00:58:08,677] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.65 | bwd_microstep: 132.43 | bwd_inner_microstep: 132.21 | bwd_allreduce_microstep: 0.14 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 00:58:09,151] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.63 | bwd_microstep: 271.09 | bwd_inner_microstep: 271.07 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 00:58:09,627] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.86 | bwd_microstep: 271.41 | bwd_inner_microstep: 271.40 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 898 +[2025-05-02 00:58:09,985] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.02 | optimizer_step: 24.34 +[2025-05-02 00:58:09,986] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 102.82 | bwd_microstep: 210.71 | bwd_inner_microstep: 144.50 | bwd_allreduce_microstep: 66.13 | step_microstep: 31.31 +[2025-05-02 00:58:09,987] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2417.80 | bwd: 3522.40 | bwd_inner: 3455.01 | bwd_allreduce: 66.70 | step: 32.43 + 11%|█ | 943/8720 [2:42:43<14:50:29, 6.87s/it] {'loss': 0.6869, 'grad_norm': 7.26835823059082, 'learning_rate': 9.840895746469463e-06, 'epoch': 1.08} + 11%|█ | 943/8720 [2:42:43<14:50:29, 6.87s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1915 +[2025-05-02 00:58:10,473] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.63 | bwd_microstep: 275.70 | bwd_inner_microstep: 275.69 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 371 +[2025-05-02 00:58:10,679] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 71.52 | bwd_microstep: 121.13 | bwd_inner_microstep: 121.00 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-02 00:58:11,156] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.49 | bwd_microstep: 274.09 | bwd_inner_microstep: 274.08 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1109 +[2025-05-02 00:58:11,447] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 115.40 | bwd_microstep: 161.92 | bwd_inner_microstep: 161.85 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 00:58:11,924] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.00 | bwd_microstep: 272.63 | bwd_inner_microstep: 272.61 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 00:58:12,399] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.86 | bwd_microstep: 272.49 | bwd_inner_microstep: 272.48 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 00:58:12,874] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.69 | bwd_microstep: 272.33 | bwd_inner_microstep: 272.31 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 00:58:13,350] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.24 | bwd_microstep: 272.52 | bwd_inner_microstep: 272.50 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 834 +[2025-05-02 00:58:13,584] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 92.76 | bwd_microstep: 125.80 | bwd_inner_microstep: 125.76 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 00:58:14,058] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.47 | bwd_microstep: 270.99 | bwd_inner_microstep: 270.97 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 00:58:14,537] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.24 | bwd_microstep: 272.05 | bwd_inner_microstep: 272.03 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 00:58:15,015] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.43 | bwd_microstep: 271.75 | bwd_inner_microstep: 271.73 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 00:58:15,495] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.16 | bwd_microstep: 272.47 | bwd_inner_microstep: 272.46 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 00:58:15,971] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.18 | bwd_microstep: 270.95 | bwd_inner_microstep: 270.93 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 00:58:16,448] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.17 | bwd_microstep: 271.01 | bwd_inner_microstep: 270.99 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 00:58:17,011] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.04 | optimizer_step: 16.45 +[2025-05-02 00:58:17,012] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.95 | bwd_microstep: 338.17 | bwd_inner_microstep: 271.54 | bwd_allreduce_microstep: 66.58 | step_microstep: 23.33 +[2025-05-02 00:58:17,013] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2725.87 | bwd: 4016.04 | bwd_inner: 3948.95 | bwd_allreduce: 66.74 | step: 24.44 + 11%|█ | 944/8720 [2:42:50<14:56:26, 6.92s/it] {'loss': 0.6508, 'grad_norm': 7.318880558013916, 'learning_rate': 9.840430640068988e-06, 'epoch': 1.08} + 11%|█ | 944/8720 [2:42:50<14:56:26, 6.92s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 00:58:17,490] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.55 | bwd_microstep: 270.16 | bwd_inner_microstep: 270.14 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2000 +[2025-05-02 00:58:18,000] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 199.89 | bwd_microstep: 294.39 | bwd_inner_microstep: 294.38 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1896 +[2025-05-02 00:58:18,478] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.73 | bwd_microstep: 274.90 | bwd_inner_microstep: 274.89 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-02 00:58:18,956] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.83 | bwd_microstep: 274.13 | bwd_inner_microstep: 274.11 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-02 00:58:19,434] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.34 | bwd_microstep: 273.68 | bwd_inner_microstep: 273.66 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 00:58:19,911] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.12 | bwd_microstep: 273.34 | bwd_inner_microstep: 273.32 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-02 00:58:20,388] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.30 | bwd_microstep: 273.28 | bwd_inner_microstep: 273.26 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 326 +[2025-05-02 00:58:20,589] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 71.25 | bwd_microstep: 116.32 | bwd_inner_microstep: 116.01 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 00:58:21,064] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.33 | bwd_microstep: 272.58 | bwd_inner_microstep: 272.56 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 00:58:21,541] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.27 | bwd_microstep: 273.14 | bwd_inner_microstep: 273.13 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 00:58:22,017] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.07 | bwd_microstep: 272.33 | bwd_inner_microstep: 272.32 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 00:58:22,492] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.05 | bwd_microstep: 272.14 | bwd_inner_microstep: 272.12 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 00:58:22,968] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.50 | bwd_microstep: 272.41 | bwd_inner_microstep: 272.39 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 00:58:23,443] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.82 | bwd_microstep: 271.27 | bwd_inner_microstep: 271.26 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 830 +[2025-05-02 00:58:23,679] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 92.80 | bwd_microstep: 129.94 | bwd_inner_microstep: 129.92 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 00:58:24,241] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.04 | optimizer_gradients: 2.06 | optimizer_step: 16.44 +[2025-05-02 00:58:24,241] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.16 | bwd_microstep: 337.38 | bwd_inner_microstep: 271.75 | bwd_allreduce_microstep: 65.58 | step_microstep: 23.32 +[2025-05-02 00:58:24,243] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2812.75 | bwd: 4151.44 | bwd_inner: 4085.28 | bwd_allreduce: 65.77 | step: 24.04 + 11%|█ | 945/8720 [2:42:57<15:08:28, 7.01s/it] {'loss': 0.8447, 'grad_norm': 10.14737319946289, 'learning_rate': 9.839964865865489e-06, 'epoch': 1.08} + 11%|█ | 945/8720 [2:42:57<15:08:28, 7.01s/it]dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 827 +[2025-05-02 00:58:24,484] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 92.60 | bwd_microstep: 129.97 | bwd_inner_microstep: 129.89 | bwd_allreduce_microstep: 0.04 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1895 +[2025-05-02 00:58:24,963] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.22 | bwd_microstep: 275.21 | bwd_inner_microstep: 275.19 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 345 +[2025-05-02 00:58:25,172] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 76.31 | bwd_microstep: 118.34 | bwd_inner_microstep: 118.02 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-02 00:58:25,649] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.68 | bwd_microstep: 273.78 | bwd_inner_microstep: 273.76 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 00:58:26,126] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.29 | bwd_microstep: 272.81 | bwd_inner_microstep: 272.80 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 00:58:26,603] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.18 | bwd_microstep: 273.03 | bwd_inner_microstep: 273.01 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 00:58:27,079] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.38 | bwd_microstep: 272.74 | bwd_inner_microstep: 272.73 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 00:58:27,554] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.84 | bwd_microstep: 272.16 | bwd_inner_microstep: 272.14 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 00:58:28,029] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.10 | bwd_microstep: 272.15 | bwd_inner_microstep: 272.13 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 00:58:28,506] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.49 | bwd_microstep: 272.48 | bwd_inner_microstep: 272.46 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 00:58:28,982] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.05 | bwd_microstep: 271.39 | bwd_inner_microstep: 271.37 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 00:58:29,457] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.29 | bwd_microstep: 272.22 | bwd_inner_microstep: 272.20 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 00:58:29,932] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.71 | bwd_microstep: 271.13 | bwd_inner_microstep: 271.12 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 00:58:30,408] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.51 | bwd_microstep: 272.07 | bwd_inner_microstep: 272.06 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 00:58:30,883] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.23 | bwd_microstep: 271.28 | bwd_inner_microstep: 271.27 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 00:58:31,456] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.04 | optimizer_step: 24.55 +[2025-05-02 00:58:31,456] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.39 | bwd_microstep: 338.36 | bwd_inner_microstep: 271.90 | bwd_allreduce_microstep: 66.41 | step_microstep: 31.67 +[2025-05-02 00:58:31,457] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2808.00 | bwd: 4129.17 | bwd_inner: 4062.11 | bwd_allreduce: 66.64 | step: 32.49 + 11%|█ | 946/8720 [2:43:05<15:16:17, 7.07s/it] {'loss': 0.6568, 'grad_norm': 10.611331939697266, 'learning_rate': 9.839498423923228e-06, 'epoch': 1.08} + 11%|█ | 946/8720 [2:43:05<15:16:17, 7.07s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 315 +[2025-05-02 00:58:31,667] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 68.85 | bwd_microstep: 123.12 | bwd_inner_microstep: 122.95 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.08 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 875 +[2025-05-02 00:58:31,914] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 97.15 | bwd_microstep: 135.26 | bwd_inner_microstep: 135.22 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.08 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 341 +[2025-05-02 00:58:32,121] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 75.55 | bwd_microstep: 118.29 | bwd_inner_microstep: 118.15 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.08 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1368 +[2025-05-02 00:58:32,485] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 142.50 | bwd_microstep: 207.00 | bwd_inner_microstep: 206.99 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-02 00:58:32,965] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.65 | bwd_microstep: 274.18 | bwd_inner_microstep: 274.16 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 00:58:33,442] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.16 | bwd_microstep: 273.49 | bwd_inner_microstep: 273.48 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-02 00:58:33,920] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.30 | bwd_microstep: 273.80 | bwd_inner_microstep: 273.78 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 334 +[2025-05-02 00:58:34,120] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 69.85 | bwd_microstep: 116.22 | bwd_inner_microstep: 116.00 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-02 00:58:34,597] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.77 | bwd_microstep: 273.23 | bwd_inner_microstep: 273.22 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1351 +[2025-05-02 00:58:34,959] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.73 | bwd_microstep: 205.84 | bwd_inner_microstep: 205.83 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 00:58:35,435] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.95 | bwd_microstep: 272.56 | bwd_inner_microstep: 272.54 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 00:58:35,910] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.83 | bwd_microstep: 272.46 | bwd_inner_microstep: 272.45 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 00:58:36,384] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.15 | bwd_microstep: 271.26 | bwd_inner_microstep: 271.24 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 00:58:36,861] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.35 | bwd_microstep: 271.44 | bwd_inner_microstep: 271.42 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 827 +[2025-05-02 00:58:37,098] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 92.77 | bwd_microstep: 129.83 | bwd_inner_microstep: 129.63 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 00:58:37,662] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.07 | optimizer_step: 16.65 +[2025-05-02 00:58:37,662] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.19 | bwd_microstep: 337.86 | bwd_inner_microstep: 271.34 | bwd_allreduce_microstep: 66.48 | step_microstep: 23.77 +[2025-05-02 00:58:37,663] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2382.47 | bwd: 3555.92 | bwd_inner: 3488.54 | bwd_allreduce: 66.79 | step: 24.62 + 11%|█ | 947/8720 [2:43:11<14:42:31, 6.81s/it] {'loss': 0.8166, 'grad_norm': 6.314939022064209, 'learning_rate': 9.839031314306556e-06, 'epoch': 1.09} + 11%|█ | 947/8720 [2:43:11<14:42:31, 6.81s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 354 +[2025-05-02 00:58:37,872] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 69.32 | bwd_microstep: 120.55 | bwd_inner_microstep: 120.29 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1971 +[2025-05-02 00:58:38,376] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 197.17 | bwd_microstep: 291.40 | bwd_inner_microstep: 291.38 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1911 +[2025-05-02 00:58:38,858] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.63 | bwd_microstep: 276.57 | bwd_inner_microstep: 276.56 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1912 +[2025-05-02 00:58:39,339] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.83 | bwd_microstep: 276.59 | bwd_inner_microstep: 276.57 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-02 00:58:39,820] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.48 | bwd_microstep: 274.44 | bwd_inner_microstep: 274.42 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-02 00:58:40,299] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.05 | bwd_microstep: 274.30 | bwd_inner_microstep: 274.25 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1889 +[2025-05-02 00:58:40,779] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.56 | bwd_microstep: 274.58 | bwd_inner_microstep: 274.56 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 341 +[2025-05-02 00:58:40,998] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 82.63 | bwd_microstep: 120.54 | bwd_inner_microstep: 120.35 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-02 00:58:41,478] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.01 | bwd_microstep: 274.43 | bwd_inner_microstep: 274.41 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1368 +[2025-05-02 00:58:41,842] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.54 | bwd_microstep: 206.95 | bwd_inner_microstep: 206.80 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 00:58:42,319] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.92 | bwd_microstep: 273.47 | bwd_inner_microstep: 273.45 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 00:58:42,796] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.85 | bwd_microstep: 272.70 | bwd_inner_microstep: 272.68 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 00:58:43,272] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.45 | bwd_microstep: 272.45 | bwd_inner_microstep: 272.44 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 00:58:43,749] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.05 | bwd_microstep: 272.55 | bwd_inner_microstep: 272.53 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 00:58:44,226] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.00 | bwd_microstep: 272.17 | bwd_inner_microstep: 272.15 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 00:58:44,793] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.08 | optimizer_step: 16.66 +[2025-05-02 00:58:44,793] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.15 | bwd_microstep: 339.61 | bwd_inner_microstep: 272.71 | bwd_allreduce_microstep: 66.85 | step_microstep: 23.84 +[2025-05-02 00:58:44,795] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2757.36 | bwd: 4093.36 | bwd_inner: 4025.68 | bwd_allreduce: 67.18 | step: 24.70 + 11%|█ | 948/8720 [2:43:18<14:54:48, 6.91s/it] {'loss': 0.9362, 'grad_norm': 5.902102947235107, 'learning_rate': 9.838563537079919e-06, 'epoch': 1.09} + 11%|█ | 948/8720 [2:43:18<14:54:48, 6.91s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1927 +[2025-05-02 00:58:45,298] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.56 | bwd_microstep: 286.67 | bwd_inner_microstep: 286.65 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-02 00:58:45,781] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.43 | bwd_microstep: 273.72 | bwd_inner_microstep: 273.70 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 00:58:46,262] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.17 | bwd_microstep: 273.19 | bwd_inner_microstep: 273.17 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1101 +[2025-05-02 00:58:46,558] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 118.04 | bwd_microstep: 161.29 | bwd_inner_microstep: 161.19 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-02 00:58:47,039] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.20 | bwd_microstep: 273.51 | bwd_inner_microstep: 273.49 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 00:58:47,520] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.75 | bwd_microstep: 272.58 | bwd_inner_microstep: 272.57 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1091 +[2025-05-02 00:58:47,816] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 115.66 | bwd_microstep: 160.52 | bwd_inner_microstep: 160.49 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 00:58:48,296] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.66 | bwd_microstep: 272.74 | bwd_inner_microstep: 272.72 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 00:58:48,776] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.74 | bwd_microstep: 272.53 | bwd_inner_microstep: 272.51 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 00:58:49,255] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.07 | bwd_microstep: 272.62 | bwd_inner_microstep: 272.61 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 00:58:49,734] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.74 | bwd_microstep: 272.71 | bwd_inner_microstep: 272.69 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 00:58:50,212] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.41 | bwd_microstep: 272.84 | bwd_inner_microstep: 272.82 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 00:58:50,686] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.53 | bwd_microstep: 271.01 | bwd_inner_microstep: 271.00 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 00:58:51,163] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.64 | bwd_microstep: 270.96 | bwd_inner_microstep: 270.94 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 00:58:51,643] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.78 | bwd_microstep: 270.97 | bwd_inner_microstep: 270.96 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 00:58:52,223] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.12 | optimizer_step: 16.61 +[2025-05-02 00:58:52,223] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.50 | bwd_microstep: 348.58 | bwd_inner_microstep: 271.32 | bwd_allreduce_microstep: 77.21 | step_microstep: 24.45 +[2025-05-02 00:58:52,225] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2879.50 | bwd: 4226.52 | bwd_inner: 4148.84 | bwd_allreduce: 77.36 | step: 25.34 + 11%|█ | 949/8720 [2:43:25<15:15:02, 7.07s/it] {'loss': 0.7006, 'grad_norm': 14.049994468688965, 'learning_rate': 9.838095092307851e-06, 'epoch': 1.09} + 11%|█ | 949/8720 [2:43:25<15:15:02, 7.07s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1849 +[2025-05-02 00:58:52,705] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.63 | bwd_microstep: 270.09 | bwd_inner_microstep: 270.07 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 358 +[2025-05-02 00:58:52,910] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 72.83 | bwd_microstep: 117.60 | bwd_inner_microstep: 117.43 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1890 +[2025-05-02 00:58:53,388] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.53 | bwd_microstep: 274.52 | bwd_inner_microstep: 274.50 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 00:58:53,865] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.15 | bwd_microstep: 272.82 | bwd_inner_microstep: 272.80 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 00:58:54,344] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.52 | bwd_microstep: 272.78 | bwd_inner_microstep: 272.76 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 334 +[2025-05-02 00:58:54,576] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.39 | bwd_microstep: 117.78 | bwd_inner_microstep: 117.47 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1355 +[2025-05-02 00:58:54,942] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.85 | bwd_microstep: 206.46 | bwd_inner_microstep: 206.30 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 00:58:55,423] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.68 | bwd_microstep: 272.46 | bwd_inner_microstep: 272.45 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 00:58:55,902] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.67 | bwd_microstep: 272.68 | bwd_inner_microstep: 272.66 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 00:58:56,382] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.31 | bwd_microstep: 272.55 | bwd_inner_microstep: 272.54 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 00:58:56,860] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.32 | bwd_microstep: 272.22 | bwd_inner_microstep: 272.20 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 00:58:57,339] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.19 | bwd_microstep: 271.42 | bwd_inner_microstep: 271.40 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.16 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 00:58:57,818] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.05 | bwd_microstep: 271.14 | bwd_inner_microstep: 271.12 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 00:58:58,296] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.17 | bwd_microstep: 271.23 | bwd_inner_microstep: 271.21 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 00:58:58,776] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.06 | bwd_microstep: 271.16 | bwd_inner_microstep: 271.15 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1945 +[2025-05-02 00:58:59,381] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.12 | optimizer_step: 16.71 +[2025-05-02 00:58:59,382] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 196.44 | bwd_microstep: 366.99 | bwd_inner_microstep: 289.45 | bwd_allreduce_microstep: 77.49 | step_microstep: 24.61 +[2025-05-02 00:58:59,383] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2763.40 | bwd: 4073.96 | bwd_inner: 3995.61 | bwd_allreduce: 77.87 | step: 25.82 + 11%|█ | 950/8720 [2:43:33<15:18:33, 7.09s/it] {'loss': 1.1248, 'grad_norm': 11.214289665222168, 'learning_rate': 9.837625980054983e-06, 'epoch': 1.09} + 11%|█ | 950/8720 [2:43:33<15:18:33, 7.09s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 00:58:59,869] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.15 | bwd_microstep: 272.84 | bwd_inner_microstep: 272.83 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1887 +[2025-05-02 00:59:00,353] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.86 | bwd_microstep: 275.18 | bwd_inner_microstep: 275.16 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-02 00:59:00,836] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.60 | bwd_microstep: 274.92 | bwd_inner_microstep: 274.90 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1888 +[2025-05-02 00:59:01,318] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.04 | bwd_microstep: 274.61 | bwd_inner_microstep: 274.59 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-02 00:59:01,799] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.50 | bwd_microstep: 273.61 | bwd_inner_microstep: 273.59 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.12 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 837 +[2025-05-02 00:59:02,041] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 96.34 | bwd_microstep: 126.05 | bwd_inner_microstep: 125.84 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 00:59:02,521] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.04 | bwd_microstep: 272.66 | bwd_inner_microstep: 272.64 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 330 +[2025-05-02 00:59:02,737] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 84.76 | bwd_microstep: 115.77 | bwd_inner_microstep: 115.61 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 00:59:03,216] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.45 | bwd_microstep: 272.98 | bwd_inner_microstep: 272.96 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 00:59:03,699] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.77 | bwd_microstep: 272.55 | bwd_inner_microstep: 272.53 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 322 +[2025-05-02 00:59:03,934] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.85 | bwd_microstep: 119.82 | bwd_inner_microstep: 119.63 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 00:59:04,416] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.05 | bwd_microstep: 272.87 | bwd_inner_microstep: 272.85 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 322 +[2025-05-02 00:59:04,631] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 82.66 | bwd_microstep: 116.41 | bwd_inner_microstep: 116.25 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 00:59:05,107] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.44 | bwd_microstep: 271.16 | bwd_inner_microstep: 271.14 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 00:59:05,586] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.92 | bwd_microstep: 271.30 | bwd_inner_microstep: 271.28 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 828 +[2025-05-02 00:59:05,929] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.21 | optimizer_step: 16.89 +[2025-05-02 00:59:05,930] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.42 | bwd_microstep: 207.60 | bwd_inner_microstep: 130.40 | bwd_allreduce_microstep: 77.04 | step_microstep: 24.89 +[2025-05-02 00:59:05,931] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2531.47 | bwd: 3690.39 | bwd_inner: 3612.36 | bwd_allreduce: 77.40 | step: 25.99 + 11%|█ | 951/8720 [2:43:39<14:57:15, 6.93s/it] {'loss': 0.6373, 'grad_norm': 8.444121360778809, 'learning_rate': 9.837156200386031e-06, 'epoch': 1.09} + 11%|█ | 951/8720 [2:43:39<14:57:15, 6.93s/it]dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 866 +[2025-05-02 00:59:06,185] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 97.87 | bwd_microstep: 134.11 | bwd_inner_microstep: 133.80 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1918 +[2025-05-02 00:59:06,668] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.15 | bwd_microstep: 276.46 | bwd_inner_microstep: 276.44 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1890 +[2025-05-02 00:59:07,150] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.25 | bwd_microstep: 274.82 | bwd_inner_microstep: 274.80 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-02 00:59:07,631] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.34 | bwd_microstep: 273.95 | bwd_inner_microstep: 273.93 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1109 +[2025-05-02 00:59:07,927] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 116.15 | bwd_microstep: 161.83 | bwd_inner_microstep: 161.79 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.11 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 334 +[2025-05-02 00:59:08,173] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.33 | bwd_microstep: 130.39 | bwd_inner_microstep: 130.07 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 00:59:08,652] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.91 | bwd_microstep: 273.16 | bwd_inner_microstep: 273.15 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1361 +[2025-05-02 00:59:09,019] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 142.11 | bwd_microstep: 206.99 | bwd_inner_microstep: 206.83 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 00:59:09,501] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.07 | bwd_microstep: 272.75 | bwd_inner_microstep: 272.73 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 00:59:09,980] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.34 | bwd_microstep: 272.46 | bwd_inner_microstep: 272.44 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 328 +[2025-05-02 00:59:10,199] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 85.22 | bwd_microstep: 117.54 | bwd_inner_microstep: 117.29 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 00:59:10,676] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.27 | bwd_microstep: 272.07 | bwd_inner_microstep: 272.05 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 00:59:11,154] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.27 | bwd_microstep: 270.93 | bwd_inner_microstep: 270.92 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 00:59:11,633] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.04 | bwd_microstep: 271.48 | bwd_inner_microstep: 271.47 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 00:59:12,115] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.46 | bwd_microstep: 271.17 | bwd_inner_microstep: 271.15 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1850 +[2025-05-02 00:59:12,693] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.09 | optimizer_step: 16.54 +[2025-05-02 00:59:12,693] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.98 | bwd_microstep: 348.06 | bwd_inner_microstep: 271.38 | bwd_allreduce_microstep: 76.62 | step_microstep: 24.19 +[2025-05-02 00:59:12,695] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2608.38 | bwd: 3828.27 | bwd_inner: 3750.42 | bwd_allreduce: 77.12 | step: 25.35 + 11%|█ | 952/8720 [2:43:46<14:50:42, 6.88s/it] {'loss': 1.1847, 'grad_norm': 10.110668182373047, 'learning_rate': 9.836685753365812e-06, 'epoch': 1.09} + 11%|█ | 952/8720 [2:43:46<14:50:42, 6.88s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 00:59:13,176] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.47 | bwd_microstep: 270.23 | bwd_inner_microstep: 270.21 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1936 +[2025-05-02 00:59:13,679] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 197.71 | bwd_microstep: 288.30 | bwd_inner_microstep: 288.28 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 00:59:14,160] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.80 | bwd_microstep: 272.98 | bwd_inner_microstep: 272.96 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.22 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 00:59:14,641] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.11 | bwd_microstep: 272.95 | bwd_inner_microstep: 272.93 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.22 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-02 00:59:15,124] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.48 | bwd_microstep: 273.60 | bwd_inner_microstep: 273.58 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 00:59:15,607] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.29 | bwd_microstep: 273.19 | bwd_inner_microstep: 273.17 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 00:59:16,088] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.08 | bwd_microstep: 272.48 | bwd_inner_microstep: 272.46 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 00:59:16,569] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.06 | bwd_microstep: 272.69 | bwd_inner_microstep: 272.67 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 00:59:17,048] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.27 | bwd_microstep: 272.28 | bwd_inner_microstep: 272.26 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.24 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 00:59:17,526] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.49 | bwd_microstep: 271.33 | bwd_inner_microstep: 271.31 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 00:59:18,004] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.38 | bwd_microstep: 272.33 | bwd_inner_microstep: 272.31 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 00:59:18,482] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.08 | bwd_microstep: 271.35 | bwd_inner_microstep: 271.34 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.13 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 00:59:18,961] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.95 | bwd_microstep: 271.68 | bwd_inner_microstep: 271.66 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 00:59:19,436] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.47 | bwd_microstep: 270.95 | bwd_inner_microstep: 270.93 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 00:59:19,914] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.68 | bwd_microstep: 270.91 | bwd_inner_microstep: 270.89 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 00:59:20,491] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.06 | optimizer_step: 16.53 +[2025-05-02 00:59:20,492] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.22 | bwd_microstep: 348.12 | bwd_inner_microstep: 271.69 | bwd_allreduce_microstep: 76.37 | step_microstep: 24.21 +[2025-05-02 00:59:20,493] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 3023.17 | bwd: 4445.38 | bwd_inner: 4368.66 | bwd_allreduce: 76.46 | step: 25.86 + 11%|█ | 953/8720 [2:43:54<15:26:14, 7.16s/it] {'loss': 0.9376, 'grad_norm': 18.07228660583496, 'learning_rate': 9.836214639059229e-06, 'epoch': 1.09} + 11%|█ | 953/8720 [2:43:54<15:26:14, 7.16s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 400 +[2025-05-02 00:59:20,720] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 83.82 | bwd_microstep: 121.53 | bwd_inner_microstep: 121.36 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1926 +[2025-05-02 00:59:21,216] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 193.83 | bwd_microstep: 287.41 | bwd_inner_microstep: 287.39 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 860 +[2025-05-02 00:59:21,458] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.21 | bwd_microstep: 133.17 | bwd_inner_microstep: 133.16 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1894 +[2025-05-02 00:59:21,938] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.59 | bwd_microstep: 274.90 | bwd_inner_microstep: 274.88 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-02 00:59:22,418] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.58 | bwd_microstep: 274.12 | bwd_inner_microstep: 274.10 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-02 00:59:22,897] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.61 | bwd_microstep: 273.41 | bwd_inner_microstep: 273.39 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-02 00:59:23,380] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.76 | bwd_microstep: 274.03 | bwd_inner_microstep: 274.02 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 00:59:23,860] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.12 | bwd_microstep: 272.26 | bwd_inner_microstep: 272.24 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 00:59:24,338] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.68 | bwd_microstep: 272.86 | bwd_inner_microstep: 272.84 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 00:59:24,819] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.30 | bwd_microstep: 272.56 | bwd_inner_microstep: 272.54 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 00:59:25,298] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.42 | bwd_microstep: 272.61 | bwd_inner_microstep: 272.59 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 00:59:25,775] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.21 | bwd_microstep: 272.18 | bwd_inner_microstep: 272.16 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 00:59:26,254] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.47 | bwd_microstep: 272.42 | bwd_inner_microstep: 272.40 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 323 +[2025-05-02 00:59:26,475] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 87.16 | bwd_microstep: 117.46 | bwd_inner_microstep: 117.31 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 00:59:26,952] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.51 | bwd_microstep: 272.52 | bwd_inner_microstep: 272.51 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 00:59:27,528] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.03 | optimizer_step: 16.53 +[2025-05-02 00:59:27,528] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.76 | bwd_microstep: 347.75 | bwd_inner_microstep: 271.47 | bwd_allreduce_microstep: 76.23 | step_microstep: 24.16 +[2025-05-02 00:59:27,530] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2718.67 | bwd: 4011.24 | bwd_inner: 3934.45 | bwd_allreduce: 76.42 | step: 25.04 + 11%|█ | 954/8720 [2:44:01<15:21:31, 7.12s/it] {'loss': 1.2311, 'grad_norm': 11.241827964782715, 'learning_rate': 9.835742857531278e-06, 'epoch': 1.09} + 11%|█ | 954/8720 [2:44:01<15:21:31, 7.12s/it]dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1342 +[2025-05-02 00:59:27,896] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.33 | bwd_microstep: 204.09 | bwd_inner_microstep: 203.93 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.08 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1436 +[2025-05-02 00:59:28,269] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 143.66 | bwd_microstep: 214.84 | bwd_inner_microstep: 214.67 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1908 +[2025-05-02 00:59:28,751] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.08 | bwd_microstep: 276.33 | bwd_inner_microstep: 276.31 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 00:59:29,228] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.95 | bwd_microstep: 273.20 | bwd_inner_microstep: 273.18 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 00:59:29,705] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.20 | bwd_microstep: 273.25 | bwd_inner_microstep: 273.24 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 00:59:30,183] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.28 | bwd_microstep: 273.19 | bwd_inner_microstep: 273.17 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 00:59:30,661] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.06 | bwd_microstep: 272.65 | bwd_inner_microstep: 272.63 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 837 +[2025-05-02 00:59:30,918] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 114.42 | bwd_microstep: 125.41 | bwd_inner_microstep: 125.37 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 00:59:31,394] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.64 | bwd_microstep: 271.24 | bwd_inner_microstep: 271.22 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 00:59:31,872] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.18 | bwd_microstep: 272.11 | bwd_inner_microstep: 272.09 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 00:59:32,351] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.44 | bwd_microstep: 272.08 | bwd_inner_microstep: 272.07 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.21 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 00:59:32,830] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.71 | bwd_microstep: 272.35 | bwd_inner_microstep: 272.34 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 00:59:33,307] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.78 | bwd_microstep: 271.11 | bwd_inner_microstep: 271.09 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 00:59:33,783] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.60 | bwd_microstep: 271.52 | bwd_inner_microstep: 271.50 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1343 +[2025-05-02 00:59:34,146] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.37 | bwd_microstep: 204.78 | bwd_inner_microstep: 204.67 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 00:59:34,726] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.05 | optimizer_step: 16.53 +[2025-05-02 00:59:34,726] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.58 | bwd_microstep: 348.83 | bwd_inner_microstep: 272.04 | bwd_allreduce_microstep: 76.74 | step_microstep: 24.74 +[2025-05-02 00:59:34,728] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2804.95 | bwd: 4097.06 | bwd_inner: 4019.53 | bwd_allreduce: 77.09 | step: 25.77 + 11%|█ | 955/8720 [2:44:08<15:24:26, 7.14s/it] {'loss': 0.9597, 'grad_norm': 10.195693969726562, 'learning_rate': 9.835270408847046e-06, 'epoch': 1.1} + 11%|█ | 955/8720 [2:44:08<15:24:26, 7.14s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 360 +[2025-05-02 00:59:34,934] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 69.87 | bwd_microstep: 115.35 | bwd_inner_microstep: 115.22 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 419 +[2025-05-02 00:59:35,144] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 71.87 | bwd_microstep: 125.31 | bwd_inner_microstep: 125.15 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1907 +[2025-05-02 00:59:35,626] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 191.03 | bwd_microstep: 276.28 | bwd_inner_microstep: 276.26 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1389 +[2025-05-02 00:59:35,994] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 144.73 | bwd_microstep: 208.96 | bwd_inner_microstep: 208.83 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1894 +[2025-05-02 00:59:36,472] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.38 | bwd_microstep: 274.46 | bwd_inner_microstep: 274.44 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1888 +[2025-05-02 00:59:36,950] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.49 | bwd_microstep: 274.22 | bwd_inner_microstep: 274.21 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-02 00:59:37,427] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.65 | bwd_microstep: 273.57 | bwd_inner_microstep: 273.56 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 00:59:37,903] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.60 | bwd_microstep: 273.01 | bwd_inner_microstep: 272.99 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 00:59:38,380] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.00 | bwd_microstep: 273.20 | bwd_inner_microstep: 273.18 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 00:59:38,855] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.30 | bwd_microstep: 272.20 | bwd_inner_microstep: 272.18 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 00:59:39,330] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.66 | bwd_microstep: 271.97 | bwd_inner_microstep: 271.95 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 00:59:39,806] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.13 | bwd_microstep: 271.99 | bwd_inner_microstep: 271.97 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 00:59:40,282] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.88 | bwd_microstep: 271.48 | bwd_inner_microstep: 271.46 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 830 +[2025-05-02 00:59:40,524] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 96.36 | bwd_microstep: 131.02 | bwd_inner_microstep: 130.89 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 316 +[2025-05-02 00:59:40,752] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 90.06 | bwd_microstep: 121.54 | bwd_inner_microstep: 121.24 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 00:59:41,328] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.08 | optimizer_step: 16.53 +[2025-05-02 00:59:41,329] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.93 | bwd_microstep: 347.53 | bwd_inner_microstep: 271.25 | bwd_allreduce_microstep: 76.23 | step_microstep: 24.16 +[2025-05-02 00:59:41,330] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2545.65 | bwd: 3782.17 | bwd_inner: 3704.97 | bwd_allreduce: 76.61 | step: 25.25 + 11%|█ | 956/8720 [2:44:15<15:03:19, 6.98s/it] {'loss': 0.7408, 'grad_norm': 6.2084059715271, 'learning_rate': 9.834797293071719e-06, 'epoch': 1.1} + 11%|█ | 956/8720 [2:44:15<15:03:19, 6.98s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1849 +[2025-05-02 00:59:41,810] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.67 | bwd_microstep: 270.10 | bwd_inner_microstep: 270.08 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 941 +[2025-05-02 00:59:42,077] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 103.60 | bwd_microstep: 146.99 | bwd_inner_microstep: 146.98 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1933 +[2025-05-02 00:59:42,575] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 194.56 | bwd_microstep: 288.30 | bwd_inner_microstep: 288.28 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-02 00:59:43,053] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.40 | bwd_microstep: 274.00 | bwd_inner_microstep: 273.98 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1893 +[2025-05-02 00:59:43,533] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.96 | bwd_microstep: 274.77 | bwd_inner_microstep: 274.76 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-02 00:59:44,009] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.35 | bwd_microstep: 273.31 | bwd_inner_microstep: 273.29 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1112 +[2025-05-02 00:59:44,301] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 115.60 | bwd_microstep: 162.19 | bwd_inner_microstep: 162.10 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-02 00:59:44,779] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.15 | bwd_microstep: 273.71 | bwd_inner_microstep: 273.69 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 00:59:45,256] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.92 | bwd_microstep: 273.22 | bwd_inner_microstep: 273.20 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 00:59:45,732] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.33 | bwd_microstep: 272.85 | bwd_inner_microstep: 272.83 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 00:59:46,209] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.32 | bwd_microstep: 272.61 | bwd_inner_microstep: 272.59 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 00:59:46,685] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.62 | bwd_microstep: 272.91 | bwd_inner_microstep: 272.90 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 00:59:47,162] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.76 | bwd_microstep: 272.46 | bwd_inner_microstep: 272.45 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 00:59:47,643] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.35 | bwd_microstep: 272.67 | bwd_inner_microstep: 272.66 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1350 +[2025-05-02 00:59:48,007] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.67 | bwd_microstep: 206.06 | bwd_inner_microstep: 205.93 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-02 00:59:48,586] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.05 | optimizer_step: 16.56 +[2025-05-02 00:59:48,587] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.18 | bwd_microstep: 349.74 | bwd_inner_microstep: 273.55 | bwd_allreduce_microstep: 76.14 | step_microstep: 24.19 +[2025-05-02 00:59:48,588] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2816.15 | bwd: 4155.93 | bwd_inner: 4079.24 | bwd_allreduce: 76.36 | step: 25.11 + 11%|█ | 957/8720 [2:44:22<15:13:57, 7.06s/it] {'loss': 0.9823, 'grad_norm': 7.858511924743652, 'learning_rate': 9.834323510270565e-06, 'epoch': 1.1} + 11%|█ | 957/8720 [2:44:22<15:13:57, 7.06s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1850 +[2025-05-02 00:59:49,068] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.30 | bwd_microstep: 270.26 | bwd_inner_microstep: 270.24 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1942 +[2025-05-02 00:59:49,568] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.78 | bwd_microstep: 288.68 | bwd_inner_microstep: 288.67 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-02 00:59:50,046] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.07 | bwd_microstep: 274.36 | bwd_inner_microstep: 274.34 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-02 00:59:50,524] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.84 | bwd_microstep: 273.74 | bwd_inner_microstep: 273.72 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1887 +[2025-05-02 00:59:51,005] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.57 | bwd_microstep: 274.57 | bwd_inner_microstep: 274.56 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-02 00:59:51,486] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.43 | bwd_microstep: 273.91 | bwd_inner_microstep: 273.90 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 00:59:51,966] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.36 | bwd_microstep: 272.87 | bwd_inner_microstep: 272.85 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 331 +[2025-05-02 00:59:52,194] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.49 | bwd_microstep: 114.82 | bwd_inner_microstep: 114.68 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.09 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 840 +[2025-05-02 00:59:52,432] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.72 | bwd_microstep: 126.36 | bwd_inner_microstep: 126.13 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.18 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 857 +[2025-05-02 00:59:52,678] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 97.39 | bwd_microstep: 133.06 | bwd_inner_microstep: 132.90 | bwd_allreduce_microstep: 0.08 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 00:59:53,157] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.86 | bwd_microstep: 273.20 | bwd_inner_microstep: 273.18 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 836 +[2025-05-02 00:59:53,396] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.37 | bwd_microstep: 125.95 | bwd_inner_microstep: 125.76 | bwd_allreduce_microstep: 0.09 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 00:59:53,875] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.96 | bwd_microstep: 272.29 | bwd_inner_microstep: 272.27 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 00:59:54,355] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.86 | bwd_microstep: 272.27 | bwd_inner_microstep: 272.26 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 00:59:54,832] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.76 | bwd_microstep: 271.32 | bwd_inner_microstep: 271.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 00:59:55,411] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.05 | optimizer_step: 16.55 +[2025-05-02 00:59:55,411] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.15 | bwd_microstep: 348.30 | bwd_inner_microstep: 271.90 | bwd_allreduce_microstep: 76.35 | step_microstep: 24.14 +[2025-05-02 00:59:55,413] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2654.58 | bwd: 3866.06 | bwd_inner: 3788.69 | bwd_allreduce: 76.71 | step: 25.24 + 11%|█ | 958/8720 [2:44:29<15:04:33, 6.99s/it] {'loss': 1.1077, 'grad_norm': 10.1671781539917, 'learning_rate': 9.833849060508948e-06, 'epoch': 1.1} + 11%|█ | 958/8720 [2:44:29<15:04:33, 6.99s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 316 +[2025-05-02 00:59:55,628] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 81.51 | bwd_microstep: 113.05 | bwd_inner_microstep: 112.90 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.09 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1367 +[2025-05-02 00:59:55,992] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.49 | bwd_microstep: 207.43 | bwd_inner_microstep: 207.23 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 00:59:56,468] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.65 | bwd_microstep: 272.09 | bwd_inner_microstep: 272.07 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 00:59:56,943] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.94 | bwd_microstep: 273.04 | bwd_inner_microstep: 273.03 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 00:59:57,418] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.02 | bwd_microstep: 272.32 | bwd_inner_microstep: 272.31 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 00:59:57,895] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.06 | bwd_microstep: 272.52 | bwd_inner_microstep: 272.50 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 00:59:58,371] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.54 | bwd_microstep: 272.49 | bwd_inner_microstep: 272.47 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 00:59:58,848] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.19 | bwd_microstep: 272.44 | bwd_inner_microstep: 272.42 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 00:59:59,324] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.74 | bwd_microstep: 272.03 | bwd_inner_microstep: 272.01 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 833 +[2025-05-02 00:59:59,555] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 90.67 | bwd_microstep: 125.90 | bwd_inner_microstep: 125.61 | bwd_allreduce_microstep: 0.17 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:00:00,032] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.79 | bwd_microstep: 272.32 | bwd_inner_microstep: 272.31 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 01:00:00,507] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.84 | bwd_microstep: 271.12 | bwd_inner_microstep: 271.10 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:00:00,981] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.36 | bwd_microstep: 271.01 | bwd_inner_microstep: 271.00 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 317 +[2025-05-02 01:00:01,188] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 70.49 | bwd_microstep: 119.91 | bwd_inner_microstep: 119.78 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:00:01,661] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.72 | bwd_microstep: 271.05 | bwd_inner_microstep: 271.03 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:00:02,226] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.06 | optimizer_step: 16.63 +[2025-05-02 01:00:02,226] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.26 | bwd_microstep: 338.00 | bwd_inner_microstep: 271.66 | bwd_allreduce_microstep: 66.29 | step_microstep: 23.67 +[2025-05-02 01:00:02,227] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2639.00 | bwd: 3896.80 | bwd_inner: 3829.51 | bwd_allreduce: 66.75 | step: 24.52 + 11%|█ | 959/8720 [2:44:35<14:57:30, 6.94s/it] {'loss': 0.4854, 'grad_norm': 10.259424209594727, 'learning_rate': 9.83337394385233e-06, 'epoch': 1.1} + 11%|█ | 959/8720 [2:44:35<14:57:30, 6.94s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2027 +[2025-05-02 01:00:02,744] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 200.08 | bwd_microstep: 296.00 | bwd_inner_microstep: 295.98 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1234 +[2025-05-02 01:00:03,057] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 121.40 | bwd_microstep: 177.42 | bwd_inner_microstep: 177.17 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.13 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1909 +[2025-05-02 01:00:03,539] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.86 | bwd_microstep: 276.33 | bwd_inner_microstep: 276.31 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 01:00:04,018] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.22 | bwd_microstep: 273.46 | bwd_inner_microstep: 273.44 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 01:00:04,496] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.74 | bwd_microstep: 273.25 | bwd_inner_microstep: 273.23 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1361 +[2025-05-02 01:00:04,862] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.57 | bwd_microstep: 206.79 | bwd_inner_microstep: 206.78 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 01:00:05,343] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.22 | bwd_microstep: 272.83 | bwd_inner_microstep: 272.81 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 01:00:05,823] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.38 | bwd_microstep: 273.21 | bwd_inner_microstep: 273.19 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 332 +[2025-05-02 01:00:06,049] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 81.12 | bwd_microstep: 128.92 | bwd_inner_microstep: 128.62 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:00:06,528] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.94 | bwd_microstep: 272.46 | bwd_inner_microstep: 272.44 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1092 +[2025-05-02 01:00:06,818] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 114.62 | bwd_microstep: 160.72 | bwd_inner_microstep: 160.67 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 01:00:07,295] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.15 | bwd_microstep: 272.97 | bwd_inner_microstep: 272.96 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:00:07,772] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.56 | bwd_microstep: 272.32 | bwd_inner_microstep: 272.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 01:00:08,248] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.56 | bwd_microstep: 272.22 | bwd_inner_microstep: 272.21 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 01:00:08,724] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.81 | bwd_microstep: 271.12 | bwd_inner_microstep: 271.11 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:00:09,290] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.07 | optimizer_step: 16.65 +[2025-05-02 01:00:09,290] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.63 | bwd_microstep: 339.33 | bwd_inner_microstep: 271.54 | bwd_allreduce_microstep: 67.74 | step_microstep: 23.76 +[2025-05-02 01:00:09,291] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2731.57 | bwd: 4039.41 | bwd_inner: 3970.83 | bwd_allreduce: 68.02 | step: 24.80 + 11%|█ | 960/8720 [2:44:43<15:02:14, 6.98s/it] {'loss': 0.9416, 'grad_norm': 5.890392303466797, 'learning_rate': 9.832898160366256e-06, 'epoch': 1.1} + 11%|█ | 960/8720 [2:44:43<15:02:14, 6.98s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 01:00:09,770] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.72 | bwd_microstep: 270.31 | bwd_inner_microstep: 270.29 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1979 +[2025-05-02 01:00:10,275] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 198.46 | bwd_microstep: 291.74 | bwd_inner_microstep: 291.72 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1897 +[2025-05-02 01:00:10,756] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.70 | bwd_microstep: 275.46 | bwd_inner_microstep: 275.44 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-02 01:00:11,235] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.06 | bwd_microstep: 273.80 | bwd_inner_microstep: 273.78 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-02 01:00:11,716] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.29 | bwd_microstep: 274.28 | bwd_inner_microstep: 274.26 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-02 01:00:12,196] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.17 | bwd_microstep: 273.64 | bwd_inner_microstep: 273.62 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 01:00:12,675] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.57 | bwd_microstep: 273.09 | bwd_inner_microstep: 273.07 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:00:13,155] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.31 | bwd_microstep: 272.60 | bwd_inner_microstep: 272.58 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:00:13,633] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.20 | bwd_microstep: 272.50 | bwd_inner_microstep: 272.49 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 321 +[2025-05-02 01:00:13,852] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 83.11 | bwd_microstep: 119.28 | bwd_inner_microstep: 119.08 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:00:14,331] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.38 | bwd_microstep: 272.46 | bwd_inner_microstep: 272.44 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1346 +[2025-05-02 01:00:14,695] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.34 | bwd_microstep: 205.15 | bwd_inner_microstep: 205.13 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:00:15,173] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.18 | bwd_microstep: 272.54 | bwd_inner_microstep: 272.53 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:00:15,652] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.76 | bwd_microstep: 272.34 | bwd_inner_microstep: 272.32 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:00:16,131] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.68 | bwd_microstep: 271.69 | bwd_inner_microstep: 271.67 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 829 +[2025-05-02 01:00:16,479] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.11 | optimizer_step: 16.72 +[2025-05-02 01:00:16,479] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.90 | bwd_microstep: 210.55 | bwd_inner_microstep: 130.40 | bwd_allreduce_microstep: 80.00 | step_microstep: 24.52 +[2025-05-02 01:00:16,481] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2783.51 | bwd: 4101.46 | bwd_inner: 4020.96 | bwd_allreduce: 80.10 | step: 25.51 + 11%|█ | 961/8720 [2:44:50<15:10:28, 7.04s/it] {'loss': 0.8651, 'grad_norm': 5.579110622406006, 'learning_rate': 9.832421710116367e-06, 'epoch': 1.1} + 11%|█ | 961/8720 [2:44:50<15:10:28, 7.04s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:00:16,962] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.98 | bwd_microstep: 270.53 | bwd_inner_microstep: 270.51 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 366 +[2025-05-02 01:00:17,199] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 99.17 | bwd_microstep: 119.76 | bwd_inner_microstep: 119.58 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-02 01:00:17,681] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.02 | bwd_microstep: 273.97 | bwd_inner_microstep: 273.95 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-02 01:00:18,163] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.71 | bwd_microstep: 273.64 | bwd_inner_microstep: 273.62 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1888 +[2025-05-02 01:00:18,645] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.86 | bwd_microstep: 274.61 | bwd_inner_microstep: 274.59 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 844 +[2025-05-02 01:00:18,890] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.61 | bwd_microstep: 132.07 | bwd_inner_microstep: 131.99 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 01:00:19,370] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.40 | bwd_microstep: 272.69 | bwd_inner_microstep: 272.67 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 01:00:19,850] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.79 | bwd_microstep: 273.33 | bwd_inner_microstep: 273.31 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:00:20,331] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.69 | bwd_microstep: 272.47 | bwd_inner_microstep: 272.45 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 01:00:20,810] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.88 | bwd_microstep: 272.70 | bwd_inner_microstep: 272.69 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 835 +[2025-05-02 01:00:21,056] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 100.54 | bwd_microstep: 125.39 | bwd_inner_microstep: 125.34 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:00:21,537] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.67 | bwd_microstep: 272.16 | bwd_inner_microstep: 272.14 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 01:00:22,015] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.74 | bwd_microstep: 271.94 | bwd_inner_microstep: 271.92 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:00:22,493] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.53 | bwd_microstep: 272.14 | bwd_inner_microstep: 272.12 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:00:22,970] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.02 | bwd_microstep: 271.08 | bwd_inner_microstep: 271.06 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1902 +[2025-05-02 01:00:23,556] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.15 | optimizer_step: 16.82 +[2025-05-02 01:00:23,557] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.93 | bwd_microstep: 353.29 | bwd_inner_microstep: 276.35 | bwd_allreduce_microstep: 76.89 | step_microstep: 24.68 +[2025-05-02 01:00:23,558] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2745.16 | bwd: 4001.85 | bwd_inner: 3924.34 | bwd_allreduce: 77.10 | step: 25.80 + 11%|█ | 962/8720 [2:44:57<15:11:46, 7.05s/it] {'loss': 0.9293, 'grad_norm': 7.145668029785156, 'learning_rate': 9.831944593168396e-06, 'epoch': 1.1} + 11%|█ | 962/8720 [2:44:57<15:11:46, 7.05s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1849 +[2025-05-02 01:00:24,040] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.22 | bwd_microstep: 270.71 | bwd_inner_microstep: 270.69 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2018 +[2025-05-02 01:00:24,552] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 198.50 | bwd_microstep: 296.25 | bwd_inner_microstep: 296.23 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-02 01:00:25,031] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.05 | bwd_microstep: 274.24 | bwd_inner_microstep: 274.23 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 01:00:25,509] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.83 | bwd_microstep: 273.22 | bwd_inner_microstep: 273.20 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 844 +[2025-05-02 01:00:25,749] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.52 | bwd_microstep: 131.97 | bwd_inner_microstep: 131.95 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 837 +[2025-05-02 01:00:25,980] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 90.86 | bwd_microstep: 126.11 | bwd_inner_microstep: 126.09 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 01:00:26,457] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.10 | bwd_microstep: 272.86 | bwd_inner_microstep: 272.84 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-02 01:00:26,934] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.66 | bwd_microstep: 273.34 | bwd_inner_microstep: 273.32 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 01:00:27,410] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.30 | bwd_microstep: 272.90 | bwd_inner_microstep: 272.88 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:00:27,887] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.01 | bwd_microstep: 272.51 | bwd_inner_microstep: 272.50 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 01:00:28,363] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.84 | bwd_microstep: 272.25 | bwd_inner_microstep: 272.23 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 832 +[2025-05-02 01:00:28,602] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.56 | bwd_microstep: 130.00 | bwd_inner_microstep: 129.88 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.10 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1344 +[2025-05-02 01:00:28,962] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 139.34 | bwd_microstep: 204.58 | bwd_inner_microstep: 204.45 | bwd_allreduce_microstep: 0.04 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:00:29,438] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.88 | bwd_microstep: 272.29 | bwd_inner_microstep: 272.27 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:00:29,914] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.57 | bwd_microstep: 271.01 | bwd_inner_microstep: 270.99 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 01:00:30,491] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.05 | optimizer_step: 16.53 +[2025-05-02 01:00:30,492] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.03 | bwd_microstep: 348.57 | bwd_inner_microstep: 271.82 | bwd_allreduce_microstep: 76.71 | step_microstep: 24.10 +[2025-05-02 01:00:30,493] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2688.98 | bwd: 3962.88 | bwd_inner: 3885.59 | bwd_allreduce: 76.92 | step: 25.04 + 11%|█ | 963/8720 [2:45:04<15:07:07, 7.02s/it] {'loss': 0.6915, 'grad_norm': 7.038058280944824, 'learning_rate': 9.831466809588168e-06, 'epoch': 1.1} + 11%|█ | 963/8720 [2:45:04<15:07:07, 7.02s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 01:00:30,973] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.35 | bwd_microstep: 270.23 | bwd_inner_microstep: 270.21 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 428 +[2025-05-02 01:00:31,199] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 78.69 | bwd_microstep: 133.12 | bwd_inner_microstep: 132.97 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-02 01:00:31,675] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.44 | bwd_microstep: 272.95 | bwd_inner_microstep: 272.93 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 01:00:32,151] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.41 | bwd_microstep: 272.82 | bwd_inner_microstep: 272.81 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-02 01:00:32,629] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.08 | bwd_microstep: 273.84 | bwd_inner_microstep: 273.82 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:00:33,105] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.24 | bwd_microstep: 272.52 | bwd_inner_microstep: 272.50 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 01:00:33,583] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.51 | bwd_microstep: 273.28 | bwd_inner_microstep: 273.27 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 839 +[2025-05-02 01:00:33,815] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 91.74 | bwd_microstep: 126.49 | bwd_inner_microstep: 126.36 | bwd_allreduce_microstep: 0.09 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 01:00:34,292] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.07 | bwd_microstep: 272.89 | bwd_inner_microstep: 272.88 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:00:34,767] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.19 | bwd_microstep: 272.48 | bwd_inner_microstep: 272.47 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 01:00:35,245] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.41 | bwd_microstep: 272.90 | bwd_inner_microstep: 272.89 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:00:35,722] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.96 | bwd_microstep: 272.31 | bwd_inner_microstep: 272.29 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 01:00:36,197] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.20 | bwd_microstep: 272.30 | bwd_inner_microstep: 272.28 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:00:36,671] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.68 | bwd_microstep: 271.04 | bwd_inner_microstep: 271.02 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:00:37,145] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.89 | bwd_microstep: 271.31 | bwd_inner_microstep: 271.30 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:00:37,710] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.04 | optimizer_gradients: 2.02 | optimizer_step: 16.51 +[2025-05-02 01:00:37,711] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.67 | bwd_microstep: 337.98 | bwd_inner_microstep: 272.34 | bwd_allreduce_microstep: 65.60 | step_microstep: 23.31 +[2025-05-02 01:00:37,712] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2808.25 | bwd: 4138.51 | bwd_inner: 4072.35 | bwd_allreduce: 65.83 | step: 24.12 + 11%|█ | 964/8720 [2:45:11<15:14:46, 7.08s/it] {'loss': 0.9593, 'grad_norm': 11.99721908569336, 'learning_rate': 9.8309883594416e-06, 'epoch': 1.11} + 11%|█ | 964/8720 [2:45:11<15:14:46, 7.08s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 01:00:38,189] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.40 | bwd_microstep: 270.24 | bwd_inner_microstep: 270.22 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.13 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 907 +[2025-05-02 01:00:38,452] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 103.67 | bwd_microstep: 144.40 | bwd_inner_microstep: 144.37 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1929 +[2025-05-02 01:00:38,950] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 194.71 | bwd_microstep: 288.03 | bwd_inner_microstep: 288.01 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1899 +[2025-05-02 01:00:39,431] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.16 | bwd_microstep: 275.95 | bwd_inner_microstep: 275.93 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1926 +[2025-05-02 01:00:39,930] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.60 | bwd_microstep: 287.27 | bwd_inner_microstep: 287.25 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1121 +[2025-05-02 01:00:40,225] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 118.65 | bwd_microstep: 162.89 | bwd_inner_microstep: 162.83 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 01:00:40,702] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.29 | bwd_microstep: 272.59 | bwd_inner_microstep: 272.58 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:00:41,180] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.94 | bwd_microstep: 272.43 | bwd_inner_microstep: 272.42 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:00:41,659] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.04 | bwd_microstep: 272.41 | bwd_inner_microstep: 272.39 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:00:42,139] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.62 | bwd_microstep: 272.09 | bwd_inner_microstep: 272.07 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 01:00:42,618] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.72 | bwd_microstep: 272.07 | bwd_inner_microstep: 272.05 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 01:00:43,097] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.36 | bwd_microstep: 271.07 | bwd_inner_microstep: 271.05 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 01:00:43,575] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.08 | bwd_microstep: 271.20 | bwd_inner_microstep: 271.18 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2244 +[2025-05-02 01:00:44,128] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 210.93 | bwd_microstep: 323.45 | bwd_inner_microstep: 323.43 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.22 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1982 +[2025-05-02 01:00:44,637] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 197.42 | bwd_microstep: 292.30 | bwd_inner_microstep: 292.28 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 375 +[2025-05-02 01:00:45,014] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.11 | optimizer_step: 16.55 +[2025-05-02 01:00:45,015] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 107.48 | bwd_microstep: 227.77 | bwd_inner_microstep: 128.44 | bwd_allreduce_microstep: 99.18 | step_microstep: 25.92 +[2025-05-02 01:00:45,016] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2825.69 | bwd: 4176.20 | bwd_inner: 4076.58 | bwd_allreduce: 99.28 | step: 27.11 + 11%|█ | 965/8720 [2:45:18<15:23:33, 7.15s/it] {'loss': 0.9624, 'grad_norm': 9.034096717834473, 'learning_rate': 9.8305092427947e-06, 'epoch': 1.11} + 11%|█ | 965/8720 [2:45:18<15:23:33, 7.15s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1890 +[2025-05-02 01:00:45,503] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.16 | bwd_microstep: 273.93 | bwd_inner_microstep: 273.91 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1909 +[2025-05-02 01:00:45,987] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.59 | bwd_microstep: 276.30 | bwd_inner_microstep: 276.28 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 01:00:46,466] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.34 | bwd_microstep: 273.22 | bwd_inner_microstep: 273.21 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 01:00:46,943] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.85 | bwd_microstep: 273.09 | bwd_inner_microstep: 273.07 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 01:00:47,420] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.28 | bwd_microstep: 273.23 | bwd_inner_microstep: 273.21 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-02 01:00:47,897] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.87 | bwd_microstep: 273.61 | bwd_inner_microstep: 273.60 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:00:48,371] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.65 | bwd_microstep: 271.19 | bwd_inner_microstep: 271.17 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 01:00:48,847] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.38 | bwd_microstep: 272.36 | bwd_inner_microstep: 272.34 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 842 +[2025-05-02 01:00:49,092] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 99.36 | bwd_microstep: 131.48 | bwd_inner_microstep: 131.36 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 01:00:49,568] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.15 | bwd_microstep: 272.59 | bwd_inner_microstep: 272.57 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1349 +[2025-05-02 01:00:49,929] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.64 | bwd_microstep: 205.57 | bwd_inner_microstep: 205.43 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.09 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 833 +[2025-05-02 01:00:50,170] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.65 | bwd_microstep: 130.76 | bwd_inner_microstep: 130.48 | bwd_allreduce_microstep: 0.15 | step_microstep: 0.10 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1089 +[2025-05-02 01:00:50,459] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 114.90 | bwd_microstep: 160.59 | bwd_inner_microstep: 160.56 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 326 +[2025-05-02 01:00:50,673] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 84.86 | bwd_microstep: 115.66 | bwd_inner_microstep: 115.31 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.09 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 322 +[2025-05-02 01:00:50,908] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 86.48 | bwd_microstep: 133.85 | bwd_inner_microstep: 133.50 | bwd_allreduce_microstep: 0.14 | step_microstep: 0.20 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 833 +[2025-05-02 01:00:51,258] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.06 | optimizer_step: 16.57 +[2025-05-02 01:00:51,258] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 100.73 | bwd_microstep: 211.40 | bwd_inner_microstep: 126.23 | bwd_allreduce_microstep: 85.06 | step_microstep: 24.88 +[2025-05-02 01:00:51,259] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2425.60 | bwd: 3548.98 | bwd_inner: 3462.42 | bwd_allreduce: 85.65 | step: 26.01 + 11%|█ | 966/8720 [2:45:25<14:48:23, 6.87s/it] {'loss': 0.7132, 'grad_norm': 7.617465496063232, 'learning_rate': 9.830029459713571e-06, 'epoch': 1.11} + 11%|█ | 966/8720 [2:45:25<14:48:23, 6.87s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 01:00:51,738] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.10 | bwd_microstep: 270.32 | bwd_inner_microstep: 270.30 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.10 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 368 +[2025-05-02 01:00:51,949] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 81.31 | bwd_microstep: 117.04 | bwd_inner_microstep: 116.72 | bwd_allreduce_microstep: 0.14 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1896 +[2025-05-02 01:00:52,428] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.51 | bwd_microstep: 274.67 | bwd_inner_microstep: 274.66 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1109 +[2025-05-02 01:00:52,722] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 115.72 | bwd_microstep: 162.18 | bwd_inner_microstep: 161.97 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-02 01:00:53,200] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.85 | bwd_microstep: 273.61 | bwd_inner_microstep: 273.59 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-02 01:00:53,679] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.05 | bwd_microstep: 273.69 | bwd_inner_microstep: 273.67 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 850 +[2025-05-02 01:00:53,926] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 98.93 | bwd_microstep: 132.81 | bwd_inner_microstep: 132.79 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1361 +[2025-05-02 01:00:54,289] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.48 | bwd_microstep: 206.73 | bwd_inner_microstep: 206.55 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 01:00:54,767] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.88 | bwd_microstep: 272.93 | bwd_inner_microstep: 272.92 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:00:55,243] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.61 | bwd_microstep: 272.55 | bwd_inner_microstep: 272.54 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 01:00:55,720] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.87 | bwd_microstep: 272.82 | bwd_inner_microstep: 272.80 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 01:00:56,197] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.10 | bwd_microstep: 272.98 | bwd_inner_microstep: 272.96 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:00:56,673] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.74 | bwd_microstep: 272.73 | bwd_inner_microstep: 272.71 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 01:00:57,148] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.29 | bwd_microstep: 271.34 | bwd_inner_microstep: 271.33 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:00:57,623] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.22 | bwd_microstep: 272.28 | bwd_inner_microstep: 272.26 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 831 +[2025-05-02 01:00:57,977] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.33 | optimizer_step: 16.53 +[2025-05-02 01:00:57,978] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 96.23 | bwd_microstep: 219.60 | bwd_inner_microstep: 135.31 | bwd_allreduce_microstep: 84.19 | step_microstep: 25.05 +[2025-05-02 01:00:57,979] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2609.56 | bwd: 3838.39 | bwd_inner: 3753.17 | bwd_allreduce: 84.62 | step: 26.11 + 11%|█ | 967/8720 [2:45:31<14:42:17, 6.83s/it] {'loss': 0.974, 'grad_norm': 6.81326961517334, 'learning_rate': 9.829549010264402e-06, 'epoch': 1.11} + 11%|█ | 967/8720 [2:45:31<14:42:17, 6.83s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 01:00:58,457] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.56 | bwd_microstep: 270.36 | bwd_inner_microstep: 270.34 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 899 +[2025-05-02 01:00:58,718] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 101.99 | bwd_microstep: 144.31 | bwd_inner_microstep: 144.21 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-02 01:00:59,198] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.66 | bwd_microstep: 274.62 | bwd_inner_microstep: 274.60 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1891 +[2025-05-02 01:00:59,680] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.13 | bwd_microstep: 274.81 | bwd_inner_microstep: 274.80 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-02 01:01:00,158] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.53 | bwd_microstep: 273.27 | bwd_inner_microstep: 273.25 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1357 +[2025-05-02 01:01:00,522] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 142.15 | bwd_microstep: 206.31 | bwd_inner_microstep: 206.20 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 01:01:01,002] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.98 | bwd_microstep: 273.28 | bwd_inner_microstep: 273.26 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:01:01,480] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.58 | bwd_microstep: 272.39 | bwd_inner_microstep: 272.37 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:01:01,959] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.15 | bwd_microstep: 272.42 | bwd_inner_microstep: 272.40 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:01:02,436] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.46 | bwd_microstep: 272.56 | bwd_inner_microstep: 272.54 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 01:01:02,913] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.20 | bwd_microstep: 272.44 | bwd_inner_microstep: 272.42 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:01:03,389] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.29 | bwd_microstep: 272.13 | bwd_inner_microstep: 272.12 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:01:03,863] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.93 | bwd_microstep: 271.09 | bwd_inner_microstep: 271.07 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:01:04,341] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.17 | bwd_microstep: 272.15 | bwd_inner_microstep: 272.14 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.14 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 01:01:04,819] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.72 | bwd_microstep: 270.97 | bwd_inner_microstep: 270.96 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 01:01:05,395] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.08 | optimizer_step: 16.52 +[2025-05-02 01:01:05,396] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.10 | bwd_microstep: 347.31 | bwd_inner_microstep: 271.54 | bwd_allreduce_microstep: 75.72 | step_microstep: 24.07 +[2025-05-02 01:01:05,397] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2886.27 | bwd: 4240.46 | bwd_inner: 4164.21 | bwd_allreduce: 75.94 | step: 25.06 + 11%|█ | 968/8720 [2:45:39<15:05:06, 7.01s/it] {'loss': 0.8198, 'grad_norm': 8.364028930664062, 'learning_rate': 9.829067894513478e-06, 'epoch': 1.11} + 11%|█ | 968/8720 [2:45:39<15:05:06, 7.01s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-02 01:01:05,880] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.31 | bwd_microstep: 272.43 | bwd_inner_microstep: 272.42 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-02 01:01:06,359] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.78 | bwd_microstep: 274.12 | bwd_inner_microstep: 274.10 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-02 01:01:06,838] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.59 | bwd_microstep: 274.54 | bwd_inner_microstep: 274.53 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-02 01:01:07,315] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.34 | bwd_microstep: 273.17 | bwd_inner_microstep: 273.15 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 840 +[2025-05-02 01:01:07,549] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 92.45 | bwd_microstep: 126.40 | bwd_inner_microstep: 126.21 | bwd_allreduce_microstep: 0.10 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 01:01:08,026] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.89 | bwd_microstep: 272.75 | bwd_inner_microstep: 272.74 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:01:08,501] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.95 | bwd_microstep: 271.80 | bwd_inner_microstep: 271.78 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 842 +[2025-05-02 01:01:08,740] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.80 | bwd_microstep: 131.76 | bwd_inner_microstep: 131.75 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:01:09,216] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.11 | bwd_microstep: 272.47 | bwd_inner_microstep: 272.45 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:01:09,692] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.92 | bwd_microstep: 272.57 | bwd_inner_microstep: 272.55 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:01:10,167] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.27 | bwd_microstep: 272.17 | bwd_inner_microstep: 272.15 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:01:10,642] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.97 | bwd_microstep: 272.26 | bwd_inner_microstep: 272.24 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 01:01:11,117] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.04 | bwd_microstep: 271.32 | bwd_inner_microstep: 271.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:01:11,591] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.53 | bwd_microstep: 271.37 | bwd_inner_microstep: 271.35 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 01:01:12,065] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.87 | bwd_microstep: 271.06 | bwd_inner_microstep: 271.04 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1911 +[2025-05-02 01:01:12,636] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.04 | optimizer_gradients: 2.07 | optimizer_step: 16.53 +[2025-05-02 01:01:12,637] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.25 | bwd_microstep: 343.15 | bwd_inner_microstep: 276.91 | bwd_allreduce_microstep: 66.19 | step_microstep: 23.46 +[2025-05-02 01:01:12,638] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2824.80 | bwd: 4143.37 | bwd_inner: 4076.69 | bwd_allreduce: 66.39 | step: 24.26 + 11%|█ | 969/8720 [2:45:46<15:14:02, 7.08s/it] {'loss': 0.8405, 'grad_norm': 8.986164093017578, 'learning_rate': 9.828586112527178e-06, 'epoch': 1.11} + 11%|█ | 969/8720 [2:45:46<15:14:02, 7.08s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:01:13,117] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.58 | bwd_microstep: 271.86 | bwd_inner_microstep: 271.85 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1921 +[2025-05-02 01:01:13,614] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.26 | bwd_microstep: 287.13 | bwd_inner_microstep: 287.11 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1924 +[2025-05-02 01:01:14,111] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.39 | bwd_microstep: 287.12 | bwd_inner_microstep: 287.11 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 849 +[2025-05-02 01:01:14,354] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 96.77 | bwd_microstep: 132.32 | bwd_inner_microstep: 132.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 01:01:14,832] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.07 | bwd_microstep: 273.26 | bwd_inner_microstep: 273.24 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 838 +[2025-05-02 01:01:15,065] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 92.81 | bwd_microstep: 126.35 | bwd_inner_microstep: 126.13 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 01:01:15,542] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.36 | bwd_microstep: 272.52 | bwd_inner_microstep: 272.50 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1094 +[2025-05-02 01:01:15,836] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 116.71 | bwd_microstep: 160.88 | bwd_inner_microstep: 160.86 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.11 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 326 +[2025-05-02 01:01:16,075] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 102.21 | bwd_microstep: 120.48 | bwd_inner_microstep: 120.20 | bwd_allreduce_microstep: 0.09 | step_microstep: 0.14 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 01:01:16,556] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.85 | bwd_microstep: 272.60 | bwd_inner_microstep: 272.58 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:01:17,034] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.30 | bwd_microstep: 272.31 | bwd_inner_microstep: 272.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 834 +[2025-05-02 01:01:17,278] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 102.37 | bwd_microstep: 125.79 | bwd_inner_microstep: 125.65 | bwd_allreduce_microstep: 0.08 | step_microstep: 0.09 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 322 +[2025-05-02 01:01:17,533] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 87.39 | bwd_microstep: 151.20 | bwd_inner_microstep: 151.05 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:01:18,011] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.21 | bwd_microstep: 272.39 | bwd_inner_microstep: 272.38 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:01:18,490] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.37 | bwd_microstep: 271.43 | bwd_inner_microstep: 271.42 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:01:19,079] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.06 | optimizer_step: 16.53 +[2025-05-02 01:01:19,079] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.66 | bwd_microstep: 357.00 | bwd_inner_microstep: 271.83 | bwd_allreduce_microstep: 85.12 | step_microstep: 24.28 +[2025-05-02 01:01:19,081] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2494.95 | bwd: 3654.74 | bwd_inner: 3568.62 | bwd_allreduce: 85.52 | step: 25.32 + 11%|█ | 970/8720 [2:45:52<14:49:28, 6.89s/it] {'loss': 0.7228, 'grad_norm': 6.8833441734313965, 'learning_rate': 9.828103664371969e-06, 'epoch': 1.11} + 11%|█ | 970/8720 [2:45:52<14:49:28, 6.89s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 319 +[2025-05-02 01:01:19,306] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 80.78 | bwd_microstep: 123.53 | bwd_inner_microstep: 123.38 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1990 +[2025-05-02 01:01:19,814] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 197.14 | bwd_microstep: 293.59 | bwd_inner_microstep: 293.57 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 899 +[2025-05-02 01:01:20,075] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 100.73 | bwd_microstep: 143.85 | bwd_inner_microstep: 143.68 | bwd_allreduce_microstep: 0.08 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1893 +[2025-05-02 01:01:20,557] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.47 | bwd_microstep: 275.25 | bwd_inner_microstep: 275.23 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 874 +[2025-05-02 01:01:20,805] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 98.23 | bwd_microstep: 134.48 | bwd_inner_microstep: 134.33 | bwd_allreduce_microstep: 0.08 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1887 +[2025-05-02 01:01:21,288] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.77 | bwd_microstep: 274.64 | bwd_inner_microstep: 274.63 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-02 01:01:21,769] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.62 | bwd_microstep: 273.40 | bwd_inner_microstep: 273.38 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-02 01:01:22,251] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.94 | bwd_microstep: 274.25 | bwd_inner_microstep: 274.23 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 01:01:22,729] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.35 | bwd_microstep: 272.27 | bwd_inner_microstep: 272.25 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 01:01:23,209] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.55 | bwd_microstep: 272.84 | bwd_inner_microstep: 272.82 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 01:01:23,686] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.97 | bwd_microstep: 272.87 | bwd_inner_microstep: 272.86 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 01:01:24,163] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.38 | bwd_microstep: 272.22 | bwd_inner_microstep: 272.20 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 01:01:24,639] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.79 | bwd_microstep: 272.04 | bwd_inner_microstep: 272.02 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:01:25,114] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.42 | bwd_microstep: 270.97 | bwd_inner_microstep: 270.95 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:01:25,590] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.48 | bwd_microstep: 270.99 | bwd_inner_microstep: 270.98 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 01:01:26,176] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.11 | optimizer_step: 16.66 +[2025-05-02 01:01:26,176] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.16 | bwd_microstep: 355.82 | bwd_inner_microstep: 271.61 | bwd_allreduce_microstep: 84.16 | step_microstep: 24.66 +[2025-05-02 01:01:26,178] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2739.47 | bwd: 4053.06 | bwd_inner: 3968.15 | bwd_allreduce: 84.44 | step: 25.53 + 11%|█ | 971/8720 [2:45:59<14:57:32, 6.95s/it] {'loss': 0.9198, 'grad_norm': 6.970702171325684, 'learning_rate': 9.827620550114411e-06, 'epoch': 1.11} + 11%|█ | 971/8720 [2:45:59<14:57:32, 6.95s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1910 +[2025-05-02 01:01:26,667] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.89 | bwd_microstep: 275.58 | bwd_inner_microstep: 275.56 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1923 +[2025-05-02 01:01:27,167] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.75 | bwd_microstep: 287.10 | bwd_inner_microstep: 287.08 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1893 +[2025-05-02 01:01:27,651] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.64 | bwd_microstep: 274.89 | bwd_inner_microstep: 274.87 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1889 +[2025-05-02 01:01:28,134] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.65 | bwd_microstep: 274.48 | bwd_inner_microstep: 274.46 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-02 01:01:28,615] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.89 | bwd_microstep: 273.38 | bwd_inner_microstep: 273.36 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:01:29,093] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.56 | bwd_microstep: 272.00 | bwd_inner_microstep: 271.99 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1099 +[2025-05-02 01:01:29,390] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 117.80 | bwd_microstep: 161.33 | bwd_inner_microstep: 161.31 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 330 +[2025-05-02 01:01:29,610] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 84.12 | bwd_microstep: 119.49 | bwd_inner_microstep: 119.34 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 01:01:30,089] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.39 | bwd_microstep: 272.86 | bwd_inner_microstep: 272.84 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 837 +[2025-05-02 01:01:30,328] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.89 | bwd_microstep: 126.05 | bwd_inner_microstep: 125.88 | bwd_allreduce_microstep: 0.09 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 01:01:30,808] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.30 | bwd_microstep: 273.13 | bwd_inner_microstep: 273.11 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:01:31,287] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.71 | bwd_microstep: 272.40 | bwd_inner_microstep: 272.39 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 01:01:31,769] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.14 | bwd_microstep: 273.09 | bwd_inner_microstep: 273.07 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 830 +[2025-05-02 01:01:32,021] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 102.67 | bwd_microstep: 129.72 | bwd_inner_microstep: 129.54 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.10 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 314 +[2025-05-02 01:01:32,244] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 91.30 | bwd_microstep: 115.68 | bwd_inner_microstep: 115.52 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1971 +[2025-05-02 01:01:32,876] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.11 | optimizer_step: 16.63 +[2025-05-02 01:01:32,876] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 196.31 | bwd_microstep: 392.19 | bwd_inner_microstep: 291.33 | bwd_allreduce_microstep: 100.81 | step_microstep: 25.97 +[2025-05-02 01:01:32,878] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2583.64 | bwd: 3793.44 | bwd_inner: 3691.70 | bwd_allreduce: 101.15 | step: 27.32 + 11%|█ | 972/8720 [2:46:06<14:47:44, 6.87s/it] {'loss': 0.8941, 'grad_norm': 5.265374183654785, 'learning_rate': 9.827136769821157e-06, 'epoch': 1.11} + 11%|█ | 972/8720 [2:46:06<14:47:44, 6.87s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 01:01:33,363] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.07 | bwd_microstep: 272.77 | bwd_inner_microstep: 272.75 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1981 +[2025-05-02 01:01:33,870] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 197.30 | bwd_microstep: 291.53 | bwd_inner_microstep: 291.52 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1915 +[2025-05-02 01:01:34,352] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.84 | bwd_microstep: 276.21 | bwd_inner_microstep: 276.19 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1906 +[2025-05-02 01:01:34,833] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.45 | bwd_microstep: 275.66 | bwd_inner_microstep: 275.64 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.21 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1910 +[2025-05-02 01:01:35,317] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.60 | bwd_microstep: 275.91 | bwd_inner_microstep: 275.89 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1899 +[2025-05-02 01:01:35,800] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.32 | bwd_microstep: 275.06 | bwd_inner_microstep: 275.04 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 358 +[2025-05-02 01:01:36,045] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 107.55 | bwd_microstep: 121.21 | bwd_inner_microstep: 120.92 | bwd_allreduce_microstep: 0.09 | step_microstep: 0.12 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 856 +[2025-05-02 01:01:36,318] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 105.75 | bwd_microstep: 149.50 | bwd_inner_microstep: 149.32 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-02 01:01:36,798] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.12 | bwd_microstep: 273.58 | bwd_inner_microstep: 273.56 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.20 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 840 +[2025-05-02 01:01:37,049] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 108.09 | bwd_microstep: 125.79 | bwd_inner_microstep: 125.57 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.11 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 844 +[2025-05-02 01:01:37,305] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 108.24 | bwd_microstep: 131.42 | bwd_inner_microstep: 131.19 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.11 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 330 +[2025-05-02 01:01:37,532] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.71 | bwd_microstep: 116.03 | bwd_inner_microstep: 115.71 | bwd_allreduce_microstep: 0.16 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:01:38,008] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.75 | bwd_microstep: 272.23 | bwd_inner_microstep: 272.21 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:01:38,484] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.93 | bwd_microstep: 272.54 | bwd_inner_microstep: 272.52 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:01:38,960] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.64 | bwd_microstep: 271.24 | bwd_inner_microstep: 271.22 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:01:39,564] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.09 | optimizer_gradients: 2.12 | optimizer_step: 16.71 +[2025-05-02 01:01:39,565] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.43 | bwd_microstep: 372.21 | bwd_inner_microstep: 272.78 | bwd_allreduce_microstep: 99.38 | step_microstep: 26.61 +[2025-05-02 01:01:39,567] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2611.42 | bwd: 3772.99 | bwd_inner: 3672.27 | bwd_allreduce: 99.86 | step: 28.04 + 11%|█ | 973/8720 [2:46:13<14:40:26, 6.82s/it] {'loss': 1.1569, 'grad_norm': 17.889633178710938, 'learning_rate': 9.82665232355895e-06, 'epoch': 1.12} + 11%|█ | 973/8720 [2:46:13<14:40:26, 6.82s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 01:01:40,048] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.62 | bwd_microstep: 270.14 | bwd_inner_microstep: 270.13 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.11 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 928 +[2025-05-02 01:01:40,312] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 102.39 | bwd_microstep: 146.12 | bwd_inner_microstep: 145.93 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 900 +[2025-05-02 01:01:40,573] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 102.93 | bwd_microstep: 143.86 | bwd_inner_microstep: 143.84 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1895 +[2025-05-02 01:01:41,053] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.65 | bwd_microstep: 274.74 | bwd_inner_microstep: 274.72 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 358 +[2025-05-02 01:01:41,306] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.45 | bwd_microstep: 144.24 | bwd_inner_microstep: 144.09 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1891 +[2025-05-02 01:01:41,786] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.33 | bwd_microstep: 274.83 | bwd_inner_microstep: 274.81 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 01:01:42,265] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.37 | bwd_microstep: 273.72 | bwd_inner_microstep: 273.70 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 01:01:42,743] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.55 | bwd_microstep: 272.95 | bwd_inner_microstep: 272.93 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 322 +[2025-05-02 01:01:42,968] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 83.19 | bwd_microstep: 127.83 | bwd_inner_microstep: 127.68 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 01:01:43,445] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.13 | bwd_microstep: 272.42 | bwd_inner_microstep: 272.40 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 01:01:43,921] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.85 | bwd_microstep: 272.37 | bwd_inner_microstep: 272.35 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:01:44,399] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.52 | bwd_microstep: 272.40 | bwd_inner_microstep: 272.38 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.22 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:01:44,876] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.82 | bwd_microstep: 271.35 | bwd_inner_microstep: 271.34 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:01:45,351] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.96 | bwd_microstep: 271.08 | bwd_inner_microstep: 271.06 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 01:01:45,825] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.88 | bwd_microstep: 270.88 | bwd_inner_microstep: 270.87 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 01:01:46,411] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.18 | optimizer_step: 16.90 +[2025-05-02 01:01:46,412] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.38 | bwd_microstep: 356.81 | bwd_inner_microstep: 271.47 | bwd_allreduce_microstep: 85.29 | step_microstep: 25.53 +[2025-05-02 01:01:46,413] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2646.73 | bwd: 3915.79 | bwd_inner: 3829.80 | bwd_allreduce: 85.54 | step: 26.70 + 11%|█ | 974/8720 [2:46:20<14:41:19, 6.83s/it] {'loss': 0.8245, 'grad_norm': 7.888168811798096, 'learning_rate': 9.826167211394627e-06, 'epoch': 1.12} + 11%|█ | 974/8720 [2:46:20<14:41:19, 6.83s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 392 +[2025-05-02 01:01:46,649] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 86.41 | bwd_microstep: 130.44 | bwd_inner_microstep: 130.11 | bwd_allreduce_microstep: 0.14 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-02 01:01:47,127] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.71 | bwd_microstep: 273.60 | bwd_inner_microstep: 273.58 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 01:01:47,605] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.83 | bwd_microstep: 272.84 | bwd_inner_microstep: 272.82 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 340 +[2025-05-02 01:01:47,831] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 86.33 | bwd_microstep: 126.46 | bwd_inner_microstep: 126.30 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1363 +[2025-05-02 01:01:48,194] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.99 | bwd_microstep: 206.95 | bwd_inner_microstep: 206.93 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.10 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 845 +[2025-05-02 01:01:48,436] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.34 | bwd_microstep: 132.04 | bwd_inner_microstep: 131.90 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 835 +[2025-05-02 01:01:48,673] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 97.49 | bwd_microstep: 125.56 | bwd_inner_microstep: 125.47 | bwd_allreduce_microstep: 0.03 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 01:01:49,150] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.39 | bwd_microstep: 272.49 | bwd_inner_microstep: 272.48 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:01:49,626] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.04 | bwd_microstep: 272.21 | bwd_inner_microstep: 272.19 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:01:50,105] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.39 | bwd_microstep: 272.34 | bwd_inner_microstep: 272.32 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:01:50,583] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.07 | bwd_microstep: 271.16 | bwd_inner_microstep: 271.14 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 01:01:51,062] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.61 | bwd_microstep: 271.12 | bwd_inner_microstep: 271.10 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 01:01:51,546] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.04 | bwd_microstep: 271.29 | bwd_inner_microstep: 271.27 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 316 +[2025-05-02 01:01:51,773] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 96.99 | bwd_microstep: 114.93 | bwd_inner_microstep: 114.76 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:01:52,248] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.26 | bwd_microstep: 270.81 | bwd_inner_microstep: 270.79 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:01:52,833] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.12 | optimizer_step: 16.59 +[2025-05-02 01:01:52,833] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.42 | bwd_microstep: 355.83 | bwd_inner_microstep: 271.56 | bwd_allreduce_microstep: 84.22 | step_microstep: 24.88 +[2025-05-02 01:01:52,835] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2485.94 | bwd: 3640.14 | bwd_inner: 3554.89 | bwd_allreduce: 84.64 | step: 25.99 + 11%|█ | 975/8720 [2:46:26<14:25:30, 6.70s/it] {'loss': 0.4834, 'grad_norm': 6.05470085144043, 'learning_rate': 9.825681433395113e-06, 'epoch': 1.12} + 11%|█ | 975/8720 [2:46:26<14:25:30, 6.70s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 01:01:53,317] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.49 | bwd_microstep: 273.21 | bwd_inner_microstep: 273.19 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1929 +[2025-05-02 01:01:53,816] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 196.27 | bwd_microstep: 287.78 | bwd_inner_microstep: 287.76 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1893 +[2025-05-02 01:01:54,295] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.37 | bwd_microstep: 274.63 | bwd_inner_microstep: 274.61 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-02 01:01:54,774] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.04 | bwd_microstep: 274.18 | bwd_inner_microstep: 274.16 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-02 01:01:55,253] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.50 | bwd_microstep: 273.26 | bwd_inner_microstep: 273.24 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1365 +[2025-05-02 01:01:55,618] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.52 | bwd_microstep: 207.33 | bwd_inner_microstep: 207.31 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 334 +[2025-05-02 01:01:55,857] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 106.56 | bwd_microstep: 116.04 | bwd_inner_microstep: 115.70 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.11 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1101 +[2025-05-02 01:01:56,158] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 118.99 | bwd_microstep: 161.70 | bwd_inner_microstep: 161.48 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.12 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1353 +[2025-05-02 01:01:56,529] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 142.06 | bwd_microstep: 206.06 | bwd_inner_microstep: 206.01 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:01:57,006] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.10 | bwd_microstep: 272.50 | bwd_inner_microstep: 272.48 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:01:57,484] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.39 | bwd_microstep: 272.40 | bwd_inner_microstep: 272.39 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:01:57,963] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.16 | bwd_microstep: 272.16 | bwd_inner_microstep: 272.15 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:01:58,442] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.88 | bwd_microstep: 272.65 | bwd_inner_microstep: 272.63 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 01:01:58,916] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.26 | bwd_microstep: 271.33 | bwd_inner_microstep: 271.31 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 01:01:59,393] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.37 | bwd_microstep: 272.42 | bwd_inner_microstep: 272.40 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:01:59,977] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.05 | optimizer_step: 16.54 +[2025-05-02 01:01:59,977] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.52 | bwd_microstep: 355.76 | bwd_inner_microstep: 271.69 | bwd_allreduce_microstep: 84.01 | step_microstep: 24.86 +[2025-05-02 01:01:59,979] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2781.11 | bwd: 4063.50 | bwd_inner: 3978.59 | bwd_allreduce: 84.37 | step: 25.79 + 11%|█ | 976/8720 [2:46:33<14:42:24, 6.84s/it] {'loss': 1.0411, 'grad_norm': 10.92614459991455, 'learning_rate': 9.825194989627431e-06, 'epoch': 1.12} + 11%|█ | 976/8720 [2:46:33<14:42:24, 6.84s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 01:02:00,458] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.43 | bwd_microstep: 270.68 | bwd_inner_microstep: 270.66 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1124 +[2025-05-02 01:02:00,755] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 119.28 | bwd_microstep: 163.42 | bwd_inner_microstep: 163.18 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-02 01:02:01,232] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.66 | bwd_microstep: 273.63 | bwd_inner_microstep: 273.62 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-02 01:02:01,709] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.48 | bwd_microstep: 273.50 | bwd_inner_microstep: 273.48 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-02 01:02:02,187] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.86 | bwd_microstep: 273.40 | bwd_inner_microstep: 273.38 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 01:02:02,665] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.75 | bwd_microstep: 273.04 | bwd_inner_microstep: 273.02 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 01:02:03,144] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.33 | bwd_microstep: 272.95 | bwd_inner_microstep: 272.93 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 323 +[2025-05-02 01:02:03,397] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 105.70 | bwd_microstep: 130.69 | bwd_inner_microstep: 130.36 | bwd_allreduce_microstep: 0.14 | step_microstep: 0.11 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 839 +[2025-05-02 01:02:03,659] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 111.27 | bwd_microstep: 130.26 | bwd_inner_microstep: 130.18 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.11 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1093 +[2025-05-02 01:02:03,952] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 115.59 | bwd_microstep: 160.85 | bwd_inner_microstep: 160.84 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:02:04,431] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.44 | bwd_microstep: 272.74 | bwd_inner_microstep: 272.73 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 01:02:04,909] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.51 | bwd_microstep: 272.33 | bwd_inner_microstep: 272.31 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:02:05,387] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.26 | bwd_microstep: 272.17 | bwd_inner_microstep: 272.15 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:02:05,863] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.22 | bwd_microstep: 271.01 | bwd_inner_microstep: 270.99 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 01:02:06,341] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.41 | bwd_microstep: 271.85 | bwd_inner_microstep: 271.71 | bwd_allreduce_microstep: 0.09 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:02:06,942] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.09 | optimizer_step: 16.54 +[2025-05-02 01:02:06,943] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.21 | bwd_microstep: 369.63 | bwd_inner_microstep: 271.66 | bwd_allreduce_microstep: 97.91 | step_microstep: 25.83 +[2025-05-02 01:02:06,944] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2713.01 | bwd: 3952.24 | bwd_inner: 3853.26 | bwd_allreduce: 98.41 | step: 26.97 + 11%|█ | 977/8720 [2:46:40<14:47:20, 6.88s/it] {'loss': 0.5169, 'grad_norm': 7.302582263946533, 'learning_rate': 9.824707880158693e-06, 'epoch': 1.12} + 11%|█ | 977/8720 [2:46:40<14:47:20, 6.88s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:02:07,427] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.37 | bwd_microstep: 271.04 | bwd_inner_microstep: 271.02 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1944 +[2025-05-02 01:02:07,927] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 196.02 | bwd_microstep: 289.06 | bwd_inner_microstep: 289.05 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-02 01:02:08,405] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.70 | bwd_microstep: 274.05 | bwd_inner_microstep: 274.03 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1892 +[2025-05-02 01:02:08,883] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.19 | bwd_microstep: 274.60 | bwd_inner_microstep: 274.59 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-02 01:02:09,362] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.81 | bwd_microstep: 273.61 | bwd_inner_microstep: 273.59 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 849 +[2025-05-02 01:02:09,605] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.95 | bwd_microstep: 132.48 | bwd_inner_microstep: 132.17 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-02 01:02:10,082] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.31 | bwd_microstep: 272.86 | bwd_inner_microstep: 272.84 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 01:02:10,560] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.02 | bwd_microstep: 272.83 | bwd_inner_microstep: 272.81 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 838 +[2025-05-02 01:02:10,800] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 99.12 | bwd_microstep: 126.35 | bwd_inner_microstep: 126.10 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.10 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1351 +[2025-05-02 01:02:11,163] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.12 | bwd_microstep: 205.88 | bwd_inner_microstep: 205.75 | bwd_allreduce_microstep: 0.09 | step_microstep: 0.10 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1356 +[2025-05-02 01:02:11,526] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.29 | bwd_microstep: 206.10 | bwd_inner_microstep: 206.09 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 01:02:12,003] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.87 | bwd_microstep: 272.94 | bwd_inner_microstep: 272.93 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:02:12,478] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.10 | bwd_microstep: 271.95 | bwd_inner_microstep: 271.94 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 326 +[2025-05-02 01:02:12,692] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 84.28 | bwd_microstep: 114.51 | bwd_inner_microstep: 114.17 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:02:13,166] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.00 | bwd_microstep: 271.23 | bwd_inner_microstep: 271.21 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 01:02:13,748] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.06 | optimizer_step: 16.51 +[2025-05-02 01:02:13,748] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.66 | bwd_microstep: 355.03 | bwd_inner_microstep: 271.35 | bwd_allreduce_microstep: 83.63 | step_microstep: 24.80 +[2025-05-02 01:02:13,750] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2641.51 | bwd: 3884.63 | bwd_inner: 3799.70 | bwd_allreduce: 84.19 | step: 25.85 + 11%|█ | 978/8720 [2:46:47<14:44:27, 6.85s/it] {'loss': 0.6536, 'grad_norm': 5.017934322357178, 'learning_rate': 9.824220105056098e-06, 'epoch': 1.12} + 11%|█ | 978/8720 [2:46:47<14:44:27, 6.85s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1850 +[2025-05-02 01:02:14,229] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.82 | bwd_microstep: 270.27 | bwd_inner_microstep: 270.25 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1954 +[2025-05-02 01:02:14,732] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 196.49 | bwd_microstep: 289.72 | bwd_inner_microstep: 289.70 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1953 +[2025-05-02 01:02:15,234] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 196.71 | bwd_microstep: 289.33 | bwd_inner_microstep: 289.31 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1886 +[2025-05-02 01:02:15,715] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.59 | bwd_microstep: 274.53 | bwd_inner_microstep: 274.51 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1358 +[2025-05-02 01:02:16,081] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 142.09 | bwd_microstep: 206.55 | bwd_inner_microstep: 206.53 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 01:02:16,562] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.59 | bwd_microstep: 272.97 | bwd_inner_microstep: 272.95 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 337 +[2025-05-02 01:02:16,809] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 107.59 | bwd_microstep: 121.24 | bwd_inner_microstep: 120.87 | bwd_allreduce_microstep: 0.15 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:02:17,292] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.25 | bwd_microstep: 272.67 | bwd_inner_microstep: 272.65 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 01:02:17,772] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.31 | bwd_microstep: 273.16 | bwd_inner_microstep: 273.14 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:02:18,252] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.22 | bwd_microstep: 272.58 | bwd_inner_microstep: 272.56 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:02:18,731] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.41 | bwd_microstep: 271.35 | bwd_inner_microstep: 271.33 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:02:19,211] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.46 | bwd_microstep: 272.68 | bwd_inner_microstep: 272.66 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 323 +[2025-05-02 01:02:19,451] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 104.10 | bwd_microstep: 119.13 | bwd_inner_microstep: 118.94 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 01:02:19,929] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.59 | bwd_microstep: 271.33 | bwd_inner_microstep: 271.32 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:02:20,406] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.36 | bwd_microstep: 271.19 | bwd_inner_microstep: 271.18 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 01:02:21,009] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.11 | optimizer_step: 16.61 +[2025-05-02 01:02:21,010] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.97 | bwd_microstep: 370.84 | bwd_inner_microstep: 271.88 | bwd_allreduce_microstep: 98.90 | step_microstep: 26.03 +[2025-05-02 01:02:21,011] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2825.14 | bwd: 4119.62 | bwd_inner: 4019.90 | bwd_allreduce: 99.19 | step: 27.22 + 11%|█ | 979/8720 [2:46:54<15:00:08, 6.98s/it] {'loss': 0.9296, 'grad_norm': 8.052139282226562, 'learning_rate': 9.823731664386947e-06, 'epoch': 1.12} + 11%|█ | 979/8720 [2:46:54<15:00:08, 6.98s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1850 +[2025-05-02 01:02:21,493] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.58 | bwd_microstep: 270.54 | bwd_inner_microstep: 270.53 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1921 +[2025-05-02 01:02:21,991] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 196.47 | bwd_microstep: 286.58 | bwd_inner_microstep: 286.56 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1926 +[2025-05-02 01:02:22,489] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.67 | bwd_microstep: 287.19 | bwd_inner_microstep: 287.17 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1130 +[2025-05-02 01:02:22,787] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 120.00 | bwd_microstep: 163.44 | bwd_inner_microstep: 163.42 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-02 01:02:23,265] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.01 | bwd_microstep: 274.23 | bwd_inner_microstep: 274.21 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-02 01:02:23,744] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.94 | bwd_microstep: 273.67 | bwd_inner_microstep: 273.65 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 01:02:24,220] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.06 | bwd_microstep: 272.12 | bwd_inner_microstep: 272.10 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 01:02:24,698] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.24 | bwd_microstep: 272.60 | bwd_inner_microstep: 272.58 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 839 +[2025-05-02 01:02:24,938] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 99.43 | bwd_microstep: 125.73 | bwd_inner_microstep: 125.65 | bwd_allreduce_microstep: 0.04 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:02:25,414] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.84 | bwd_microstep: 272.21 | bwd_inner_microstep: 272.19 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.22 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:02:25,892] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.93 | bwd_microstep: 272.73 | bwd_inner_microstep: 272.71 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 01:02:26,369] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.85 | bwd_microstep: 272.21 | bwd_inner_microstep: 272.19 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 834 +[2025-05-02 01:02:26,610] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 101.23 | bwd_microstep: 125.48 | bwd_inner_microstep: 125.32 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:02:27,086] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.74 | bwd_microstep: 271.41 | bwd_inner_microstep: 271.39 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:02:27,563] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.38 | bwd_microstep: 272.17 | bwd_inner_microstep: 272.15 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 01:02:28,147] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.07 | optimizer_step: 16.52 +[2025-05-02 01:02:28,147] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.84 | bwd_microstep: 357.09 | bwd_inner_microstep: 271.37 | bwd_allreduce_microstep: 85.68 | step_microstep: 25.03 +[2025-05-02 01:02:28,149] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2786.88 | bwd: 4069.45 | bwd_inner: 3983.23 | bwd_allreduce: 85.86 | step: 26.09 + 11%|█ | 980/8720 [2:47:01<15:06:10, 7.02s/it] {'loss': 0.6287, 'grad_norm': 9.735944747924805, 'learning_rate': 9.823242558218622e-06, 'epoch': 1.12} + 11%|█ | 980/8720 [2:47:01<15:06:10, 7.02s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 01:02:28,628] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.36 | bwd_microstep: 270.24 | bwd_inner_microstep: 270.22 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2024 +[2025-05-02 01:02:29,142] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 201.48 | bwd_microstep: 297.19 | bwd_inner_microstep: 297.17 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1100 +[2025-05-02 01:02:29,439] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 118.70 | bwd_microstep: 161.47 | bwd_inner_microstep: 161.23 | bwd_allreduce_microstep: 0.14 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-02 01:02:29,921] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.86 | bwd_microstep: 274.09 | bwd_inner_microstep: 274.07 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1371 +[2025-05-02 01:02:30,289] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.96 | bwd_microstep: 207.89 | bwd_inner_microstep: 207.82 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:02:30,769] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.69 | bwd_microstep: 273.09 | bwd_inner_microstep: 273.07 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:02:31,251] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.76 | bwd_microstep: 273.02 | bwd_inner_microstep: 273.00 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1093 +[2025-05-02 01:02:31,547] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 118.26 | bwd_microstep: 161.17 | bwd_inner_microstep: 161.05 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 01:02:32,026] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.43 | bwd_microstep: 272.84 | bwd_inner_microstep: 272.82 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:02:32,502] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.04 | bwd_microstep: 271.58 | bwd_inner_microstep: 271.57 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 01:02:32,977] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.18 | bwd_microstep: 271.40 | bwd_inner_microstep: 271.38 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:02:33,451] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.37 | bwd_microstep: 271.55 | bwd_inner_microstep: 271.53 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:02:33,928] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.99 | bwd_microstep: 271.85 | bwd_inner_microstep: 271.83 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:02:34,406] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.08 | bwd_microstep: 271.75 | bwd_inner_microstep: 271.74 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 01:02:34,885] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.92 | bwd_microstep: 271.59 | bwd_inner_microstep: 271.57 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:02:35,500] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.12 | optimizer_step: 16.54 +[2025-05-02 01:02:35,500] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.32 | bwd_microstep: 378.68 | bwd_inner_microstep: 272.26 | bwd_allreduce_microstep: 106.36 | step_microstep: 26.59 +[2025-05-02 01:02:35,502] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2849.01 | bwd: 4199.49 | bwd_inner: 4092.35 | bwd_allreduce: 106.68 | step: 27.67 + 11%|█▏ | 981/8720 [2:47:09<15:18:49, 7.12s/it] {'loss': 0.42, 'grad_norm': 6.234126091003418, 'learning_rate': 9.822752786618604e-06, 'epoch': 1.12} + 11%|█▏ | 981/8720 [2:47:09<15:18:49, 7.12s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1938 +[2025-05-02 01:02:36,009] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 196.42 | bwd_microstep: 287.61 | bwd_inner_microstep: 287.59 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2005 +[2025-05-02 01:02:36,521] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 199.14 | bwd_microstep: 294.96 | bwd_inner_microstep: 294.95 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1991 +[2025-05-02 01:02:37,027] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 197.39 | bwd_microstep: 294.15 | bwd_inner_microstep: 294.13 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1448 +[2025-05-02 01:02:37,405] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 147.71 | bwd_microstep: 215.56 | bwd_inner_microstep: 215.54 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 362 +[2025-05-02 01:02:37,630] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 88.73 | bwd_microstep: 122.70 | bwd_inner_microstep: 122.36 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1892 +[2025-05-02 01:02:38,110] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.45 | bwd_microstep: 274.95 | bwd_inner_microstep: 274.94 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1894 +[2025-05-02 01:02:38,591] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.93 | bwd_microstep: 274.88 | bwd_inner_microstep: 274.87 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-02 01:02:39,071] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.41 | bwd_microstep: 274.01 | bwd_inner_microstep: 273.99 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-02 01:02:39,550] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.83 | bwd_microstep: 273.76 | bwd_inner_microstep: 273.74 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 01:02:40,027] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.03 | bwd_microstep: 273.27 | bwd_inner_microstep: 273.26 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.07 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 850 +[2025-05-02 01:02:40,273] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 97.02 | bwd_microstep: 132.37 | bwd_inner_microstep: 132.31 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 01:02:40,751] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.27 | bwd_microstep: 272.79 | bwd_inner_microstep: 272.78 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 01:02:41,230] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.87 | bwd_microstep: 272.70 | bwd_inner_microstep: 272.68 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1347 +[2025-05-02 01:02:41,594] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.08 | bwd_microstep: 205.35 | bwd_inner_microstep: 205.29 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 01:02:42,077] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.80 | bwd_microstep: 272.29 | bwd_inner_microstep: 272.27 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 01:02:42,658] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.07 | optimizer_step: 16.68 +[2025-05-02 01:02:42,659] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.86 | bwd_microstep: 349.17 | bwd_inner_microstep: 271.81 | bwd_allreduce_microstep: 77.31 | step_microstep: 24.51 +[2025-05-02 01:02:42,660] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2766.56 | bwd: 4090.59 | bwd_inner: 4012.58 | bwd_allreduce: 77.58 | step: 25.52 + 11%|█▏ | 982/8720 [2:47:16<15:20:03, 7.13s/it] {'loss': 1.1049, 'grad_norm': 8.720979690551758, 'learning_rate': 9.82226234965446e-06, 'epoch': 1.13} + 11%|█▏ | 982/8720 [2:47:16<15:20:03, 7.13s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:02:43,147] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.75 | bwd_microstep: 270.47 | bwd_inner_microstep: 270.45 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.09 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1427 +[2025-05-02 01:02:43,524] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 146.93 | bwd_microstep: 213.91 | bwd_inner_microstep: 213.77 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.09 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 365 +[2025-05-02 01:02:43,746] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 83.34 | bwd_microstep: 124.15 | bwd_inner_microstep: 124.03 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-02 01:02:44,226] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.99 | bwd_microstep: 274.49 | bwd_inner_microstep: 274.47 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1927 +[2025-05-02 01:02:44,725] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.57 | bwd_microstep: 287.27 | bwd_inner_microstep: 287.25 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 346 +[2025-05-02 01:02:44,927] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 68.08 | bwd_microstep: 120.52 | bwd_inner_microstep: 120.29 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-02 01:02:45,406] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.71 | bwd_microstep: 274.43 | bwd_inner_microstep: 274.41 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-02 01:02:45,884] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.87 | bwd_microstep: 273.66 | bwd_inner_microstep: 273.64 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:02:46,363] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.49 | bwd_microstep: 272.56 | bwd_inner_microstep: 272.54 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 01:02:46,841] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.84 | bwd_microstep: 272.61 | bwd_inner_microstep: 272.59 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:02:47,321] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.94 | bwd_microstep: 272.35 | bwd_inner_microstep: 272.33 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 01:02:47,803] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.31 | bwd_microstep: 273.36 | bwd_inner_microstep: 273.34 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:02:48,283] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.28 | bwd_microstep: 272.64 | bwd_inner_microstep: 272.63 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:02:48,764] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.59 | bwd_microstep: 272.54 | bwd_inner_microstep: 272.52 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:02:49,243] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.59 | bwd_microstep: 271.13 | bwd_inner_microstep: 271.11 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:02:49,827] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.13 | optimizer_step: 16.65 +[2025-05-02 01:02:49,828] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.32 | bwd_microstep: 352.42 | bwd_inner_microstep: 271.82 | bwd_allreduce_microstep: 80.55 | step_microstep: 24.45 +[2025-05-02 01:02:49,829] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2761.25 | bwd: 4098.55 | bwd_inner: 4017.29 | bwd_allreduce: 80.84 | step: 25.36 + 11%|█▏ | 983/8720 [2:47:23<15:21:17, 7.14s/it] {'loss': 0.96, 'grad_norm': 7.295156002044678, 'learning_rate': 9.82177124739386e-06, 'epoch': 1.13} + 11%|█▏ | 983/8720 [2:47:23<15:21:17, 7.14s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 01:02:50,310] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.26 | bwd_microstep: 270.24 | bwd_inner_microstep: 270.23 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 634 +[2025-05-02 01:02:50,539] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 92.82 | bwd_microstep: 117.47 | bwd_inner_microstep: 117.16 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1898 +[2025-05-02 01:02:51,021] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.02 | bwd_microstep: 275.30 | bwd_inner_microstep: 275.28 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1896 +[2025-05-02 01:02:51,505] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.89 | bwd_microstep: 275.10 | bwd_inner_microstep: 275.09 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-02 01:02:51,986] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.90 | bwd_microstep: 273.54 | bwd_inner_microstep: 273.53 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 01:02:52,468] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.56 | bwd_microstep: 273.42 | bwd_inner_microstep: 273.40 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 01:02:52,947] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.08 | bwd_microstep: 273.02 | bwd_inner_microstep: 273.01 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 01:02:53,428] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.30 | bwd_microstep: 272.65 | bwd_inner_microstep: 272.63 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 01:02:53,910] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.21 | bwd_microstep: 273.29 | bwd_inner_microstep: 273.27 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 01:02:54,390] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.01 | bwd_microstep: 272.66 | bwd_inner_microstep: 272.64 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:02:54,868] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.10 | bwd_microstep: 272.20 | bwd_inner_microstep: 272.19 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 01:02:55,348] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.22 | bwd_microstep: 272.00 | bwd_inner_microstep: 271.98 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:02:55,827] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.24 | bwd_microstep: 272.31 | bwd_inner_microstep: 272.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:02:56,310] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.04 | bwd_microstep: 272.52 | bwd_inner_microstep: 272.51 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 321 +[2025-05-02 01:02:56,538] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 90.78 | bwd_microstep: 118.42 | bwd_inner_microstep: 118.12 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:02:57,117] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.42 | optimizer_step: 17.57 +[2025-05-02 01:02:57,118] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.04 | bwd_microstep: 348.27 | bwd_inner_microstep: 271.89 | bwd_allreduce_microstep: 76.33 | step_microstep: 25.84 +[2025-05-02 01:02:57,119] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2820.06 | bwd: 4132.48 | bwd_inner: 4055.32 | bwd_allreduce: 76.65 | step: 26.84 + 11%|█▏ | 984/8720 [2:47:30<15:26:47, 7.19s/it] {'loss': 0.6615, 'grad_norm': 9.250783920288086, 'learning_rate': 9.821279479904553e-06, 'epoch': 1.13} + 11%|█▏ | 984/8720 [2:47:30<15:26:47, 7.19s/it]dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1427 +[2025-05-02 01:02:57,500] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 144.65 | bwd_microstep: 213.48 | bwd_inner_microstep: 213.38 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2134 +[2025-05-02 01:02:58,037] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 206.13 | bwd_microstep: 314.00 | bwd_inner_microstep: 313.99 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 882 +[2025-05-02 01:02:58,288] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 100.23 | bwd_microstep: 135.29 | bwd_inner_microstep: 135.02 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 01:02:58,764] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.06 | bwd_microstep: 272.84 | bwd_inner_microstep: 272.82 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1347 +[2025-05-02 01:02:59,126] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.23 | bwd_microstep: 205.77 | bwd_inner_microstep: 205.75 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 01:02:59,602] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.20 | bwd_microstep: 272.67 | bwd_inner_microstep: 272.65 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 01:03:00,081] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.40 | bwd_microstep: 272.69 | bwd_inner_microstep: 272.67 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:03:00,558] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.68 | bwd_microstep: 272.59 | bwd_inner_microstep: 272.57 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 01:03:01,035] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.79 | bwd_microstep: 273.12 | bwd_inner_microstep: 273.10 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 01:03:01,511] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.51 | bwd_microstep: 272.92 | bwd_inner_microstep: 272.90 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:03:01,992] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.96 | bwd_microstep: 272.49 | bwd_inner_microstep: 272.47 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1089 +[2025-05-02 01:03:02,281] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 114.13 | bwd_microstep: 160.89 | bwd_inner_microstep: 160.87 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:03:02,757] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.17 | bwd_microstep: 272.34 | bwd_inner_microstep: 272.32 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 01:03:03,235] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.74 | bwd_microstep: 272.24 | bwd_inner_microstep: 272.23 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:03:03,710] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.91 | bwd_microstep: 271.19 | bwd_inner_microstep: 271.17 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 829 +[2025-05-02 01:03:04,040] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.23 | optimizer_step: 17.31 +[2025-05-02 01:03:04,040] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.54 | bwd_microstep: 196.45 | bwd_inner_microstep: 130.52 | bwd_allreduce_microstep: 65.85 | step_microstep: 24.59 +[2025-05-02 01:03:04,042] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2684.02 | bwd: 3951.00 | bwd_inner: 3884.48 | bwd_allreduce: 66.09 | step: 25.41 + 11%|█▏ | 985/8720 [2:47:37<15:16:19, 7.11s/it] {'loss': 0.7398, 'grad_norm': 11.859044075012207, 'learning_rate': 9.820787047254386e-06, 'epoch': 1.13} + 11%|█▏ | 985/8720 [2:47:37<15:16:19, 7.11s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1890 +[2025-05-02 01:03:04,525] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.80 | bwd_microstep: 273.85 | bwd_inner_microstep: 273.83 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1570 +[2025-05-02 01:03:04,932] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 150.60 | bwd_microstep: 240.24 | bwd_inner_microstep: 240.10 | bwd_allreduce_microstep: 0.03 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1899 +[2025-05-02 01:03:05,412] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.47 | bwd_microstep: 276.03 | bwd_inner_microstep: 276.01 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-02 01:03:05,892] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.45 | bwd_microstep: 274.84 | bwd_inner_microstep: 274.82 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-02 01:03:06,371] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.32 | bwd_microstep: 274.38 | bwd_inner_microstep: 274.36 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 01:03:06,849] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.86 | bwd_microstep: 273.39 | bwd_inner_microstep: 273.38 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 849 +[2025-05-02 01:03:07,090] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.40 | bwd_microstep: 132.82 | bwd_inner_microstep: 132.67 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-02 01:03:07,571] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.99 | bwd_microstep: 274.32 | bwd_inner_microstep: 274.31 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:03:08,052] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.90 | bwd_microstep: 273.17 | bwd_inner_microstep: 273.15 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 01:03:08,535] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.46 | bwd_microstep: 273.66 | bwd_inner_microstep: 273.64 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 839 +[2025-05-02 01:03:08,773] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.48 | bwd_microstep: 126.59 | bwd_inner_microstep: 126.44 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:03:09,251] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.46 | bwd_microstep: 273.13 | bwd_inner_microstep: 273.11 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:03:09,729] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.86 | bwd_microstep: 273.12 | bwd_inner_microstep: 273.10 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:03:10,205] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.30 | bwd_microstep: 272.58 | bwd_inner_microstep: 272.56 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 01:03:10,680] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.98 | bwd_microstep: 271.87 | bwd_inner_microstep: 271.85 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:03:11,248] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.31 | optimizer_step: 17.55 +[2025-05-02 01:03:11,248] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.88 | bwd_microstep: 339.23 | bwd_inner_microstep: 272.43 | bwd_allreduce_microstep: 66.75 | step_microstep: 24.82 +[2025-05-02 01:03:11,249] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2794.91 | bwd: 4123.29 | bwd_inner: 4055.84 | bwd_allreduce: 67.02 | step: 25.97 + 11%|█▏ | 986/8720 [2:47:44<15:20:03, 7.14s/it] {'loss': 0.8564, 'grad_norm': 4.131091117858887, 'learning_rate': 9.820293949511297e-06, 'epoch': 1.13} + 11%|█▏ | 986/8720 [2:47:44<15:20:03, 7.14s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 01:03:11,728] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.24 | bwd_microstep: 270.21 | bwd_inner_microstep: 270.19 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1926 +[2025-05-02 01:03:12,226] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 194.43 | bwd_microstep: 287.45 | bwd_inner_microstep: 287.43 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 389 +[2025-05-02 01:03:12,442] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 80.19 | bwd_microstep: 121.86 | bwd_inner_microstep: 121.69 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1888 +[2025-05-02 01:03:12,921] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.59 | bwd_microstep: 274.50 | bwd_inner_microstep: 274.48 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 334 +[2025-05-02 01:03:13,132] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 76.11 | bwd_microstep: 121.26 | bwd_inner_microstep: 121.13 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 332 +[2025-05-02 01:03:13,336] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 72.22 | bwd_microstep: 117.33 | bwd_inner_microstep: 117.07 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 01:03:13,814] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.78 | bwd_microstep: 272.98 | bwd_inner_microstep: 272.96 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 01:03:14,291] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.10 | bwd_microstep: 273.19 | bwd_inner_microstep: 273.17 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 327 +[2025-05-02 01:03:14,499] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 81.32 | bwd_microstep: 114.12 | bwd_inner_microstep: 113.99 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:03:14,974] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.14 | bwd_microstep: 272.59 | bwd_inner_microstep: 272.58 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 01:03:15,451] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.06 | bwd_microstep: 272.99 | bwd_inner_microstep: 272.97 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:03:15,926] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.08 | bwd_microstep: 271.21 | bwd_inner_microstep: 271.20 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:03:16,401] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.45 | bwd_microstep: 272.13 | bwd_inner_microstep: 272.11 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 01:03:16,877] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.46 | bwd_microstep: 271.24 | bwd_inner_microstep: 271.22 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:03:17,355] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.06 | bwd_microstep: 272.32 | bwd_inner_microstep: 272.31 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:03:17,934] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.22 | optimizer_step: 17.11 +[2025-05-02 01:03:17,934] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.92 | bwd_microstep: 347.74 | bwd_inner_microstep: 271.75 | bwd_allreduce_microstep: 75.94 | step_microstep: 24.85 +[2025-05-02 01:03:17,936] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2577.85 | bwd: 3833.18 | bwd_inner: 3756.41 | bwd_allreduce: 76.26 | step: 25.69 + 11%|█▏ | 987/8720 [2:47:51<15:02:33, 7.00s/it] {'loss': 0.9424, 'grad_norm': 8.42702579498291, 'learning_rate': 9.819800186743315e-06, 'epoch': 1.13} + 11%|█▏ | 987/8720 [2:47:51<15:02:33, 7.00s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 01:03:18,416] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.62 | bwd_microstep: 270.39 | bwd_inner_microstep: 270.38 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 375 +[2025-05-02 01:03:18,625] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 76.71 | bwd_microstep: 117.52 | bwd_inner_microstep: 117.33 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-02 01:03:19,103] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.04 | bwd_microstep: 273.73 | bwd_inner_microstep: 273.71 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1361 +[2025-05-02 01:03:19,465] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.60 | bwd_microstep: 206.71 | bwd_inner_microstep: 206.70 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 01:03:19,941] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.19 | bwd_microstep: 272.76 | bwd_inner_microstep: 272.74 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 840 +[2025-05-02 01:03:20,176] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 92.75 | bwd_microstep: 126.28 | bwd_inner_microstep: 126.09 | bwd_allreduce_microstep: 0.10 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 01:03:20,656] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.36 | bwd_microstep: 272.96 | bwd_inner_microstep: 272.94 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 01:03:21,136] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.47 | bwd_microstep: 272.95 | bwd_inner_microstep: 272.93 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:03:21,616] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.12 | bwd_microstep: 272.65 | bwd_inner_microstep: 272.63 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 01:03:22,096] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.42 | bwd_microstep: 272.85 | bwd_inner_microstep: 272.83 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:03:22,576] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.03 | bwd_microstep: 272.88 | bwd_inner_microstep: 272.86 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:03:23,056] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.27 | bwd_microstep: 271.37 | bwd_inner_microstep: 271.35 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:03:23,535] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.36 | bwd_microstep: 271.18 | bwd_inner_microstep: 271.17 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:03:24,011] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.12 | bwd_microstep: 271.38 | bwd_inner_microstep: 271.36 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 01:03:24,488] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.32 | bwd_microstep: 271.05 | bwd_inner_microstep: 271.03 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1551 +[2025-05-02 01:03:24,983] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.04 | optimizer_gradients: 2.21 | optimizer_step: 17.11 +[2025-05-02 01:03:24,983] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 151.66 | bwd_microstep: 305.35 | bwd_inner_microstep: 239.00 | bwd_allreduce_microstep: 66.20 | step_microstep: 24.06 +[2025-05-02 01:03:24,984] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2724.69 | bwd: 4022.07 | bwd_inner: 3955.18 | bwd_allreduce: 66.41 | step: 24.87 + 11%|█▏ | 988/8720 [2:47:58<15:04:07, 7.02s/it] {'loss': 0.6322, 'grad_norm': 6.973292350769043, 'learning_rate': 9.81930575901856e-06, 'epoch': 1.13} + 11%|█▏ | 988/8720 [2:47:58<15:04:07, 7.02s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 01:03:25,465] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.64 | bwd_microstep: 272.68 | bwd_inner_microstep: 272.66 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1895 +[2025-05-02 01:03:25,944] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.96 | bwd_microstep: 275.02 | bwd_inner_microstep: 275.00 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-02 01:03:26,421] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.66 | bwd_microstep: 274.00 | bwd_inner_microstep: 273.98 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-02 01:03:26,899] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.84 | bwd_microstep: 274.11 | bwd_inner_microstep: 274.09 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 01:03:27,375] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.44 | bwd_microstep: 272.99 | bwd_inner_microstep: 272.97 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 01:03:27,852] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.62 | bwd_microstep: 273.06 | bwd_inner_microstep: 273.04 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 334 +[2025-05-02 01:03:28,066] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 67.15 | bwd_microstep: 133.80 | bwd_inner_microstep: 133.52 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 334 +[2025-05-02 01:03:28,270] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 71.13 | bwd_microstep: 119.30 | bwd_inner_microstep: 119.17 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:03:28,745] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.86 | bwd_microstep: 272.57 | bwd_inner_microstep: 272.55 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 01:03:29,220] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.04 | bwd_microstep: 272.63 | bwd_inner_microstep: 272.61 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 325 +[2025-05-02 01:03:29,429] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 75.45 | bwd_microstep: 119.28 | bwd_inner_microstep: 118.98 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:03:29,906] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.56 | bwd_microstep: 272.77 | bwd_inner_microstep: 272.75 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:03:30,383] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.42 | bwd_microstep: 272.29 | bwd_inner_microstep: 272.27 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:03:30,863] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.89 | bwd_microstep: 271.38 | bwd_inner_microstep: 271.36 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.13 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 01:03:31,339] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.00 | bwd_microstep: 271.32 | bwd_inner_microstep: 271.30 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 01:03:31,929] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.24 | optimizer_step: 17.10 +[2025-05-02 01:03:31,930] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.65 | bwd_microstep: 357.42 | bwd_inner_microstep: 271.49 | bwd_allreduce_microstep: 85.88 | step_microstep: 24.86 +[2025-05-02 01:03:31,931] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2662.02 | bwd: 4004.69 | bwd_inner: 3917.90 | bwd_allreduce: 86.24 | step: 25.89 + 11%|█▏ | 989/8720 [2:48:05<15:01:24, 7.00s/it] {'loss': 1.0651, 'grad_norm': 11.872283935546875, 'learning_rate': 9.818810666405249e-06, 'epoch': 1.13} + 11%|█▏ | 989/8720 [2:48:05<15:01:24, 7.00s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1850 +[2025-05-02 01:03:32,411] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.80 | bwd_microstep: 270.02 | bwd_inner_microstep: 270.00 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2244 +[2025-05-02 01:03:32,962] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 209.33 | bwd_microstep: 322.25 | bwd_inner_microstep: 322.23 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-02 01:03:33,445] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.99 | bwd_microstep: 273.69 | bwd_inner_microstep: 273.68 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 01:03:33,926] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.43 | bwd_microstep: 273.26 | bwd_inner_microstep: 273.24 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-02 01:03:34,408] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.58 | bwd_microstep: 273.80 | bwd_inner_microstep: 273.78 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.17 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 01:03:34,890] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.21 | bwd_microstep: 273.07 | bwd_inner_microstep: 273.05 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 845 +[2025-05-02 01:03:35,142] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 101.01 | bwd_microstep: 132.09 | bwd_inner_microstep: 131.97 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 01:03:35,621] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.16 | bwd_microstep: 272.82 | bwd_inner_microstep: 272.80 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 01:03:36,101] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.51 | bwd_microstep: 272.82 | bwd_inner_microstep: 272.81 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:03:36,582] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.26 | bwd_microstep: 272.64 | bwd_inner_microstep: 272.62 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 01:03:37,059] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.02 | bwd_microstep: 271.29 | bwd_inner_microstep: 271.27 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1342 +[2025-05-02 01:03:37,420] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.14 | bwd_microstep: 204.64 | bwd_inner_microstep: 204.58 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:03:37,896] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.25 | bwd_microstep: 271.17 | bwd_inner_microstep: 271.16 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:03:38,372] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.86 | bwd_microstep: 271.07 | bwd_inner_microstep: 271.06 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 01:03:38,850] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.92 | bwd_microstep: 270.88 | bwd_inner_microstep: 270.86 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 315 +[2025-05-02 01:03:39,179] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.22 | optimizer_step: 17.13 +[2025-05-02 01:03:39,179] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 78.38 | bwd_microstep: 211.22 | bwd_inner_microstep: 134.44 | bwd_allreduce_microstep: 76.69 | step_microstep: 24.58 +[2025-05-02 01:03:39,180] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2789.47 | bwd: 4136.79 | bwd_inner: 4059.58 | bwd_allreduce: 76.84 | step: 25.58 + 11%|█▏ | 990/8720 [2:48:12<15:11:01, 7.07s/it] {'loss': 0.9397, 'grad_norm': 13.165420532226562, 'learning_rate': 9.818314908971681e-06, 'epoch': 1.14} + 11%|█▏ | 990/8720 [2:48:12<15:11:01, 7.07s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1849 +[2025-05-02 01:03:39,658] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.77 | bwd_microstep: 270.22 | bwd_inner_microstep: 270.21 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1950 +[2025-05-02 01:03:40,159] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 196.99 | bwd_microstep: 289.79 | bwd_inner_microstep: 289.77 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1899 +[2025-05-02 01:03:40,639] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.25 | bwd_microstep: 275.36 | bwd_inner_microstep: 275.34 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 856 +[2025-05-02 01:03:40,883] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.65 | bwd_microstep: 132.93 | bwd_inner_microstep: 132.89 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-02 01:03:41,360] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.31 | bwd_microstep: 273.34 | bwd_inner_microstep: 273.33 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 841 +[2025-05-02 01:03:41,599] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.30 | bwd_microstep: 132.00 | bwd_inner_microstep: 131.80 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 01:03:42,076] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.94 | bwd_microstep: 273.09 | bwd_inner_microstep: 273.07 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1098 +[2025-05-02 01:03:42,370] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 115.21 | bwd_microstep: 161.52 | bwd_inner_microstep: 161.32 | bwd_allreduce_microstep: 0.10 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 01:03:42,852] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.20 | bwd_microstep: 272.61 | bwd_inner_microstep: 272.60 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 01:03:43,333] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.00 | bwd_microstep: 272.55 | bwd_inner_microstep: 272.53 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 841 +[2025-05-02 01:03:43,575] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.78 | bwd_microstep: 131.87 | bwd_inner_microstep: 131.61 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:03:44,053] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.64 | bwd_microstep: 272.53 | bwd_inner_microstep: 272.51 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 830 +[2025-05-02 01:03:44,293] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.96 | bwd_microstep: 129.92 | bwd_inner_microstep: 129.86 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:03:44,769] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.27 | bwd_microstep: 271.25 | bwd_inner_microstep: 271.24 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2141 +[2025-05-02 01:03:45,307] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 206.63 | bwd_microstep: 314.72 | bwd_inner_microstep: 314.70 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1901 +[2025-05-02 01:03:45,880] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.12 | optimizer_step: 17.14 +[2025-05-02 01:03:45,880] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.27 | bwd_microstep: 341.84 | bwd_inner_microstep: 276.14 | bwd_allreduce_microstep: 65.65 | step_microstep: 24.15 +[2025-05-02 01:03:45,882] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2589.86 | bwd: 3815.67 | bwd_inner: 3748.93 | bwd_allreduce: 66.11 | step: 25.11 + 11%|█▏ | 991/8720 [2:48:19<14:56:36, 6.96s/it] {'loss': 0.9494, 'grad_norm': 6.921799659729004, 'learning_rate': 9.817818486786259e-06, 'epoch': 1.14} + 11%|█▏ | 991/8720 [2:48:19<14:56:36, 6.96s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1892 +[2025-05-02 01:03:46,366] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.17 | bwd_microstep: 274.69 | bwd_inner_microstep: 274.67 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2341 +[2025-05-02 01:03:46,938] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 217.88 | bwd_microstep: 339.11 | bwd_inner_microstep: 339.09 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1234 +[2025-05-02 01:03:47,251] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 121.21 | bwd_microstep: 177.39 | bwd_inner_microstep: 177.38 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1890 +[2025-05-02 01:03:47,730] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.76 | bwd_microstep: 275.15 | bwd_inner_microstep: 275.13 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 866 +[2025-05-02 01:03:47,973] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.85 | bwd_microstep: 134.18 | bwd_inner_microstep: 134.17 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 01:03:48,450] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.66 | bwd_microstep: 274.04 | bwd_inner_microstep: 274.02 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 857 +[2025-05-02 01:03:48,707] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 107.21 | bwd_microstep: 132.39 | bwd_inner_microstep: 132.37 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-02 01:03:49,185] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.29 | bwd_microstep: 273.87 | bwd_inner_microstep: 273.85 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 01:03:49,662] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.32 | bwd_microstep: 273.34 | bwd_inner_microstep: 273.32 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:03:50,140] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.30 | bwd_microstep: 273.04 | bwd_inner_microstep: 273.02 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 01:03:50,621] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.76 | bwd_microstep: 272.93 | bwd_inner_microstep: 272.92 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:03:51,097] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.96 | bwd_microstep: 272.03 | bwd_inner_microstep: 272.01 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 01:03:51,572] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.61 | bwd_microstep: 271.50 | bwd_inner_microstep: 271.48 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:03:52,047] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.42 | bwd_microstep: 271.59 | bwd_inner_microstep: 271.57 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 01:03:52,526] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.43 | bwd_microstep: 271.43 | bwd_inner_microstep: 271.41 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 01:03:53,090] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.17 | optimizer_step: 17.09 +[2025-05-02 01:03:53,091] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.70 | bwd_microstep: 337.21 | bwd_inner_microstep: 272.07 | bwd_allreduce_microstep: 65.09 | step_microstep: 24.10 +[2025-05-02 01:03:53,092] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2810.27 | bwd: 4123.90 | bwd_inner: 4058.50 | bwd_allreduce: 65.17 | step: 24.79 + 11%|█▏ | 992/8720 [2:48:26<15:06:08, 7.04s/it] {'loss': 0.8761, 'grad_norm': 8.229231834411621, 'learning_rate': 9.817321399917467e-06, 'epoch': 1.14} + 11%|█▏ | 992/8720 [2:48:26<15:06:08, 7.04s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 313 +[2025-05-02 01:03:53,317] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 82.02 | bwd_microstep: 124.31 | bwd_inner_microstep: 124.17 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1906 +[2025-05-02 01:03:53,797] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.65 | bwd_microstep: 276.49 | bwd_inner_microstep: 276.47 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1917 +[2025-05-02 01:03:54,281] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.67 | bwd_microstep: 277.11 | bwd_inner_microstep: 277.09 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1895 +[2025-05-02 01:03:54,761] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.41 | bwd_microstep: 275.74 | bwd_inner_microstep: 275.72 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.15 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1886 +[2025-05-02 01:03:55,243] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.23 | bwd_microstep: 275.04 | bwd_inner_microstep: 275.03 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-02 01:03:55,724] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.13 | bwd_microstep: 274.94 | bwd_inner_microstep: 274.92 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 01:03:56,206] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.88 | bwd_microstep: 273.40 | bwd_inner_microstep: 273.38 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 01:03:56,688] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.39 | bwd_microstep: 273.55 | bwd_inner_microstep: 273.53 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:03:57,164] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.98 | bwd_microstep: 272.96 | bwd_inner_microstep: 272.95 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:03:57,642] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.75 | bwd_microstep: 273.16 | bwd_inner_microstep: 273.15 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:03:58,123] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.60 | bwd_microstep: 272.81 | bwd_inner_microstep: 272.79 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 01:03:58,599] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.67 | bwd_microstep: 271.63 | bwd_inner_microstep: 271.61 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 318 +[2025-05-02 01:03:58,795] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 66.55 | bwd_microstep: 116.61 | bwd_inner_microstep: 116.46 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 01:03:59,269] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.77 | bwd_microstep: 271.46 | bwd_inner_microstep: 271.44 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:03:59,748] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.89 | bwd_microstep: 271.45 | bwd_inner_microstep: 271.43 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 01:04:00,326] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.25 | optimizer_step: 17.15 +[2025-05-02 01:04:00,327] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.02 | bwd_microstep: 347.77 | bwd_inner_microstep: 271.83 | bwd_allreduce_microstep: 75.89 | step_microstep: 24.83 +[2025-05-02 01:04:00,328] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2800.29 | bwd: 4148.46 | bwd_inner: 4072.03 | bwd_allreduce: 76.08 | step: 25.77 + 11%|█▏ | 993/8720 [2:48:34<15:13:50, 7.10s/it] {'loss': 0.8468, 'grad_norm': 7.071552276611328, 'learning_rate': 9.816823648433886e-06, 'epoch': 1.14} + 11%|█▏ | 993/8720 [2:48:34<15:13:50, 7.10s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1895 +[2025-05-02 01:04:00,814] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.27 | bwd_microstep: 274.11 | bwd_inner_microstep: 274.09 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1986 +[2025-05-02 01:04:01,322] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 198.15 | bwd_microstep: 293.01 | bwd_inner_microstep: 292.99 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1890 +[2025-05-02 01:04:01,803] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.38 | bwd_microstep: 274.55 | bwd_inner_microstep: 274.54 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.13 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1890 +[2025-05-02 01:04:02,285] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.01 | bwd_microstep: 274.29 | bwd_inner_microstep: 274.27 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1379 +[2025-05-02 01:04:02,654] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 143.38 | bwd_microstep: 207.73 | bwd_inner_microstep: 207.65 | bwd_allreduce_microstep: 0.04 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-02 01:04:03,134] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.39 | bwd_microstep: 274.16 | bwd_inner_microstep: 274.14 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-02 01:04:03,615] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.47 | bwd_microstep: 272.88 | bwd_inner_microstep: 272.86 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-02 01:04:04,096] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.64 | bwd_microstep: 273.08 | bwd_inner_microstep: 273.06 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 01:04:04,575] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.41 | bwd_microstep: 272.65 | bwd_inner_microstep: 272.63 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 01:04:05,054] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.54 | bwd_microstep: 272.60 | bwd_inner_microstep: 272.58 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 325 +[2025-05-02 01:04:05,308] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.49 | bwd_microstep: 140.55 | bwd_inner_microstep: 140.25 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:04:05,787] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.85 | bwd_microstep: 272.33 | bwd_inner_microstep: 272.31 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:04:06,267] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.11 | bwd_microstep: 272.40 | bwd_inner_microstep: 272.38 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 321 +[2025-05-02 01:04:06,498] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.73 | bwd_microstep: 118.52 | bwd_inner_microstep: 118.35 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.13 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:04:06,979] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.17 | bwd_microstep: 272.60 | bwd_inner_microstep: 272.59 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:04:07,560] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.25 | optimizer_step: 17.30 +[2025-05-02 01:04:07,560] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.31 | bwd_microstep: 349.42 | bwd_inner_microstep: 272.99 | bwd_allreduce_microstep: 76.37 | step_microstep: 25.39 +[2025-05-02 01:04:07,562] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2792.91 | bwd: 4114.93 | bwd_inner: 4037.77 | bwd_allreduce: 76.69 | step: 26.49 + 11%|█▏ | 994/8720 [2:48:41<15:19:04, 7.14s/it] {'loss': 0.8251, 'grad_norm': 6.878813743591309, 'learning_rate': 9.816325232404187e-06, 'epoch': 1.14} + 11%|█▏ | 994/8720 [2:48:41<15:19:04, 7.14s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 317 +[2025-05-02 01:04:07,785] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 80.54 | bwd_microstep: 120.78 | bwd_inner_microstep: 120.52 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.10 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 915 +[2025-05-02 01:04:08,049] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 103.07 | bwd_microstep: 145.08 | bwd_inner_microstep: 144.99 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1888 +[2025-05-02 01:04:08,527] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.18 | bwd_microstep: 274.35 | bwd_inner_microstep: 274.33 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1886 +[2025-05-02 01:04:09,005] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.46 | bwd_microstep: 274.22 | bwd_inner_microstep: 274.20 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 01:04:09,481] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.12 | bwd_microstep: 272.99 | bwd_inner_microstep: 272.97 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:04:09,958] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.44 | bwd_microstep: 272.48 | bwd_inner_microstep: 272.46 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 01:04:10,436] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.53 | bwd_microstep: 272.67 | bwd_inner_microstep: 272.65 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 01:04:10,915] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.33 | bwd_microstep: 272.94 | bwd_inner_microstep: 272.92 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:04:11,394] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.12 | bwd_microstep: 272.50 | bwd_inner_microstep: 272.48 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:04:11,875] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.39 | bwd_microstep: 272.43 | bwd_inner_microstep: 272.41 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:04:12,353] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.83 | bwd_microstep: 271.22 | bwd_inner_microstep: 271.20 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1346 +[2025-05-02 01:04:12,717] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.01 | bwd_microstep: 205.52 | bwd_inner_microstep: 205.43 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:04:13,194] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.85 | bwd_microstep: 271.31 | bwd_inner_microstep: 271.29 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 01:04:13,668] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.83 | bwd_microstep: 271.01 | bwd_inner_microstep: 270.99 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 01:04:14,143] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.48 | bwd_microstep: 270.78 | bwd_inner_microstep: 270.76 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 473 +[2025-05-02 01:04:14,458] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.16 | optimizer_step: 17.29 +[2025-05-02 01:04:14,458] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 73.48 | bwd_microstep: 203.70 | bwd_inner_microstep: 137.37 | bwd_allreduce_microstep: 66.18 | step_microstep: 24.56 +[2025-05-02 01:04:14,459] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2659.35 | bwd: 3944.03 | bwd_inner: 3877.13 | bwd_allreduce: 66.41 | step: 25.41 + 11%|█▏ | 995/8720 [2:48:48<15:09:37, 7.07s/it] {'loss': 0.6403, 'grad_norm': 8.971515655517578, 'learning_rate': 9.815826151897134e-06, 'epoch': 1.14} + 11%|█▏ | 995/8720 [2:48:48<15:09:37, 7.07s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1952 +[2025-05-02 01:04:14,965] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 197.19 | bwd_microstep: 288.39 | bwd_inner_microstep: 288.37 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1925 +[2025-05-02 01:04:15,463] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 196.10 | bwd_microstep: 286.67 | bwd_inner_microstep: 286.65 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1921 +[2025-05-02 01:04:15,960] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 194.08 | bwd_microstep: 286.55 | bwd_inner_microstep: 286.53 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1901 +[2025-05-02 01:04:16,441] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.14 | bwd_microstep: 275.37 | bwd_inner_microstep: 275.36 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-02 01:04:16,920] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.77 | bwd_microstep: 273.67 | bwd_inner_microstep: 273.65 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1883 +[2025-05-02 01:04:17,400] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.51 | bwd_microstep: 273.84 | bwd_inner_microstep: 273.82 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 01:04:17,881] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.92 | bwd_microstep: 273.10 | bwd_inner_microstep: 273.08 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 01:04:18,361] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.81 | bwd_microstep: 272.74 | bwd_inner_microstep: 272.72 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:04:18,840] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.63 | bwd_microstep: 271.96 | bwd_inner_microstep: 271.94 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:04:19,320] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.97 | bwd_microstep: 272.09 | bwd_inner_microstep: 272.08 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 01:04:19,800] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.91 | bwd_microstep: 273.35 | bwd_inner_microstep: 273.34 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 01:04:20,282] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.22 | bwd_microstep: 272.62 | bwd_inner_microstep: 272.60 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 01:04:20,762] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.91 | bwd_microstep: 272.33 | bwd_inner_microstep: 272.32 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 01:04:21,242] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.82 | bwd_microstep: 272.36 | bwd_inner_microstep: 272.34 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:04:21,720] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.61 | bwd_microstep: 272.19 | bwd_inner_microstep: 272.17 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 836 +[2025-05-02 01:04:22,057] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.24 | optimizer_step: 17.28 +[2025-05-02 01:04:22,058] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.25 | bwd_microstep: 202.90 | bwd_inner_microstep: 126.39 | bwd_allreduce_microstep: 76.40 | step_microstep: 24.93 +[2025-05-02 01:04:22,059] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2939.45 | bwd: 4340.14 | bwd_inner: 4263.39 | bwd_allreduce: 76.47 | step: 25.71 + 11%|█▏ | 996/8720 [2:48:55<15:30:08, 7.23s/it] {'loss': 0.9256, 'grad_norm': 5.283729553222656, 'learning_rate': 9.815326406981581e-06, 'epoch': 1.14} + 11%|█▏ | 996/8720 [2:48:55<15:30:08, 7.23s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:04:22,537] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.17 | bwd_microstep: 270.28 | bwd_inner_microstep: 270.26 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1921 +[2025-05-02 01:04:23,034] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.32 | bwd_microstep: 286.71 | bwd_inner_microstep: 286.70 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-02 01:04:23,515] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.10 | bwd_microstep: 274.50 | bwd_inner_microstep: 274.48 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 01:04:23,993] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.87 | bwd_microstep: 273.09 | bwd_inner_microstep: 273.07 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 01:04:24,473] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.06 | bwd_microstep: 272.81 | bwd_inner_microstep: 272.79 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 01:04:24,955] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.03 | bwd_microstep: 272.62 | bwd_inner_microstep: 272.60 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.12 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1098 +[2025-05-02 01:04:25,253] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 116.70 | bwd_microstep: 161.14 | bwd_inner_microstep: 160.95 | bwd_allreduce_microstep: 0.10 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 01:04:25,733] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.28 | bwd_microstep: 273.48 | bwd_inner_microstep: 273.47 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 01:04:26,216] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.51 | bwd_microstep: 272.83 | bwd_inner_microstep: 272.81 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:04:26,699] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.20 | bwd_microstep: 272.32 | bwd_inner_microstep: 272.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:04:27,179] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.97 | bwd_microstep: 272.66 | bwd_inner_microstep: 272.64 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-02 01:04:27,660] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.39 | bwd_microstep: 273.03 | bwd_inner_microstep: 273.01 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.11 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 323 +[2025-05-02 01:04:27,900] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 87.71 | bwd_microstep: 135.87 | bwd_inner_microstep: 135.70 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:04:28,376] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.59 | bwd_microstep: 272.05 | bwd_inner_microstep: 272.03 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 01:04:28,857] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.33 | bwd_microstep: 272.15 | bwd_inner_microstep: 272.13 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1085 +[2025-05-02 01:04:29,255] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.24 | optimizer_step: 17.24 +[2025-05-02 01:04:29,256] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 117.88 | bwd_microstep: 238.56 | bwd_inner_microstep: 160.24 | bwd_allreduce_microstep: 78.22 | step_microstep: 25.25 +[2025-05-02 01:04:29,257] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2780.73 | bwd: 4094.12 | bwd_inner: 4015.25 | bwd_allreduce: 78.43 | step: 26.36 + 11%|█▏ | 997/8720 [2:49:03<15:29:02, 7.22s/it] {'loss': 0.5894, 'grad_norm': 10.486958503723145, 'learning_rate': 9.814825997726475e-06, 'epoch': 1.14} + 11%|█▏ | 997/8720 [2:49:03<15:29:02, 7.22s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1897 +[2025-05-02 01:04:29,870] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.67 | bwd_microstep: 274.73 | bwd_inner_microstep: 274.71 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1984 +[2025-05-02 01:04:30,381] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 199.57 | bwd_microstep: 292.24 | bwd_inner_microstep: 292.23 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1370 +[2025-05-02 01:04:30,748] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.43 | bwd_microstep: 207.29 | bwd_inner_microstep: 207.21 | bwd_allreduce_microstep: 0.03 | step_microstep: 0.13 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1366 +[2025-05-02 01:04:31,120] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.62 | bwd_microstep: 207.02 | bwd_inner_microstep: 206.90 | bwd_allreduce_microstep: 0.03 | step_microstep: 0.22 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 01:04:31,605] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.59 | bwd_microstep: 273.39 | bwd_inner_microstep: 273.37 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1364 +[2025-05-02 01:04:31,973] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 142.23 | bwd_microstep: 207.02 | bwd_inner_microstep: 207.01 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 01:04:32,454] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.11 | bwd_microstep: 272.92 | bwd_inner_microstep: 272.90 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:04:32,934] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.50 | bwd_microstep: 272.29 | bwd_inner_microstep: 272.28 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 01:04:33,416] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.50 | bwd_microstep: 272.97 | bwd_inner_microstep: 272.95 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 01:04:33,898] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.99 | bwd_microstep: 272.56 | bwd_inner_microstep: 272.54 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:04:34,378] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.45 | bwd_microstep: 272.48 | bwd_inner_microstep: 272.46 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:04:34,859] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.06 | bwd_microstep: 272.21 | bwd_inner_microstep: 272.20 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:04:35,338] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.73 | bwd_microstep: 272.34 | bwd_inner_microstep: 272.32 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 01:04:35,813] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.40 | bwd_microstep: 270.98 | bwd_inner_microstep: 270.97 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:04:36,290] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.70 | bwd_microstep: 271.16 | bwd_inner_microstep: 271.15 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 01:04:36,867] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.04 | optimizer_gradients: 2.20 | optimizer_step: 17.12 +[2025-05-02 01:04:36,868] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.87 | bwd_microstep: 347.64 | bwd_inner_microstep: 272.03 | bwd_allreduce_microstep: 75.57 | step_microstep: 24.11 +[2025-05-02 01:04:36,869] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2886.00 | bwd: 4259.32 | bwd_inner: 4183.22 | bwd_allreduce: 75.76 | step: 25.41 + 11%|█▏ | 998/8720 [2:49:10<15:44:03, 7.34s/it] {'loss': 0.7549, 'grad_norm': 7.006043910980225, 'learning_rate': 9.814324924200853e-06, 'epoch': 1.14} + 11%|█▏ | 998/8720 [2:49:10<15:44:03, 7.34s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1991 +[2025-05-02 01:04:37,379] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 197.60 | bwd_microstep: 293.43 | bwd_inner_microstep: 293.41 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1995 +[2025-05-02 01:04:37,888] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 199.03 | bwd_microstep: 294.49 | bwd_inner_microstep: 294.48 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 420 +[2025-05-02 01:04:38,101] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 80.45 | bwd_microstep: 119.47 | bwd_inner_microstep: 119.33 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1923 +[2025-05-02 01:04:38,597] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 193.72 | bwd_microstep: 287.16 | bwd_inner_microstep: 287.14 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1931 +[2025-05-02 01:04:39,096] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.07 | bwd_microstep: 287.91 | bwd_inner_microstep: 287.89 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 867 +[2025-05-02 01:04:39,340] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 96.76 | bwd_microstep: 133.75 | bwd_inner_microstep: 133.73 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 859 +[2025-05-02 01:04:39,580] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.19 | bwd_microstep: 133.21 | bwd_inner_microstep: 133.20 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 01:04:40,056] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.93 | bwd_microstep: 272.80 | bwd_inner_microstep: 272.79 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-02 01:04:40,534] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.83 | bwd_microstep: 273.84 | bwd_inner_microstep: 273.83 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 01:04:41,011] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.21 | bwd_microstep: 272.92 | bwd_inner_microstep: 272.90 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-02 01:04:41,489] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.51 | bwd_microstep: 273.60 | bwd_inner_microstep: 273.58 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 01:04:41,968] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.27 | bwd_microstep: 272.83 | bwd_inner_microstep: 272.82 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:04:42,449] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.44 | bwd_microstep: 272.23 | bwd_inner_microstep: 272.21 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:04:42,933] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.27 | bwd_microstep: 272.31 | bwd_inner_microstep: 272.29 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.16 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:04:43,412] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.90 | bwd_microstep: 272.22 | bwd_inner_microstep: 272.20 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:04:43,995] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.22 | optimizer_step: 17.13 +[2025-05-02 01:04:43,995] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.52 | bwd_microstep: 351.59 | bwd_inner_microstep: 271.72 | bwd_allreduce_microstep: 79.81 | step_microstep: 24.86 +[2025-05-02 01:04:43,997] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2753.39 | bwd: 4083.79 | bwd_inner: 4003.54 | bwd_allreduce: 79.96 | step: 25.84 + 11%|█▏ | 999/8720 [2:49:17<15:35:58, 7.27s/it] {'loss': 0.903, 'grad_norm': 8.712738990783691, 'learning_rate': 9.813823186473848e-06, 'epoch': 1.15} + 11%|█▏ | 999/8720 [2:49:17<15:35:58, 7.27s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1895 +[2025-05-02 01:04:44,483] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.67 | bwd_microstep: 274.53 | bwd_inner_microstep: 274.52 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1926 +[2025-05-02 01:04:44,985] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.72 | bwd_microstep: 287.33 | bwd_inner_microstep: 287.31 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1922 +[2025-05-02 01:04:45,486] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.40 | bwd_microstep: 287.00 | bwd_inner_microstep: 286.99 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1901 +[2025-05-02 01:04:45,969] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.21 | bwd_microstep: 275.63 | bwd_inner_microstep: 275.61 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 01:04:46,449] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.85 | bwd_microstep: 273.63 | bwd_inner_microstep: 273.61 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 01:04:46,929] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.28 | bwd_microstep: 273.49 | bwd_inner_microstep: 273.47 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 01:04:47,408] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.99 | bwd_microstep: 273.11 | bwd_inner_microstep: 273.10 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.14 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 01:04:47,886] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.80 | bwd_microstep: 272.98 | bwd_inner_microstep: 272.96 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:04:48,362] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.97 | bwd_microstep: 272.44 | bwd_inner_microstep: 272.42 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:04:48,838] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.48 | bwd_microstep: 272.70 | bwd_inner_microstep: 272.69 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1345 +[2025-05-02 01:04:49,201] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.55 | bwd_microstep: 205.60 | bwd_inner_microstep: 205.46 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:04:49,682] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.69 | bwd_microstep: 271.43 | bwd_inner_microstep: 271.41 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:04:50,164] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.99 | bwd_microstep: 272.52 | bwd_inner_microstep: 272.50 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 831 +[2025-05-02 01:04:50,404] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.97 | bwd_microstep: 130.15 | bwd_inner_microstep: 129.92 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:04:50,881] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.29 | bwd_microstep: 271.22 | bwd_inner_microstep: 271.20 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:04:51,461] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.21 | optimizer_step: 17.11 +[2025-05-02 01:04:51,462] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.64 | bwd_microstep: 349.95 | bwd_inner_microstep: 271.77 | bwd_allreduce_microstep: 78.13 | step_microstep: 24.87 +[2025-05-02 01:04:51,463] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2893.13 | bwd: 4263.75 | bwd_inner: 4184.93 | bwd_allreduce: 78.38 | step: 25.89 + 11%|█▏ | 1000/8720 [2:49:25<15:43:19, 7.33s/it] {'loss': 0.7928, 'grad_norm': 9.196516990661621, 'learning_rate': 9.813320784614679e-06, 'epoch': 1.15} + 11%|█▏ | 1000/8720 [2:49:25<15:43:19, 7.33s/it][INFO|trainer.py:3503] 2025-05-02 01:04:54,409 >> Saving model checkpoint to work_dirs/internvl_chat_v2_5/ak/checkpoint-1000 +[INFO|configuration_utils.py:472] 2025-05-02 01:04:54,412 >> Configuration saved in work_dirs/internvl_chat_v2_5/ak/checkpoint-1000/config.json +[INFO|configuration_utils.py:807] 2025-05-02 01:04:54,412 >> Configuration saved in work_dirs/internvl_chat_v2_5/ak/checkpoint-1000/generation_config.json +[INFO|modeling_utils.py:2755] 2025-05-02 01:04:59,459 >> Model weights saved in work_dirs/internvl_chat_v2_5/ak/checkpoint-1000/model.safetensors +[INFO|tokenization_utils_base.py:2702] 2025-05-02 01:04:59,460 >> tokenizer config file saved in work_dirs/internvl_chat_v2_5/ak/checkpoint-1000/tokenizer_config.json +[INFO|tokenization_utils_base.py:2711] 2025-05-02 01:04:59,460 >> Special tokens file saved in work_dirs/internvl_chat_v2_5/ak/checkpoint-1000/special_tokens_map.json +[INFO|tokenization_utils_base.py:2762] 2025-05-02 01:04:59,461 >> added tokens file saved in work_dirs/internvl_chat_v2_5/ak/checkpoint-1000/added_tokens.json +[2025-05-02 01:04:59,583] [INFO] [logging.py:96:log_dist] [Rank 0] [Torch] Checkpoint global_step1000 is about to be saved! +[2025-05-02 01:04:59,600] [INFO] [logging.py:96:log_dist] [Rank 0] Saving model checkpoint: work_dirs/internvl_chat_v2_5/ak/checkpoint-1000/global_step1000/mp_rank_00_model_states.pt +[2025-05-02 01:04:59,600] [INFO] [torch_checkpoint_engine.py:21:save] [Torch] Saving work_dirs/internvl_chat_v2_5/ak/checkpoint-1000/global_step1000/mp_rank_00_model_states.pt... +[2025-05-02 01:05:04,064] [INFO] [torch_checkpoint_engine.py:23:save] [Torch] Saved work_dirs/internvl_chat_v2_5/ak/checkpoint-1000/global_step1000/mp_rank_00_model_states.pt. +[2025-05-02 01:05:04,066] [INFO] [torch_checkpoint_engine.py:21:save] [Torch] Saving work_dirs/internvl_chat_v2_5/ak/checkpoint-1000/global_step1000/bf16_zero_pp_rank_0_mp_rank_00_optim_states.pt... +[2025-05-02 01:05:04,263] [INFO] [torch_checkpoint_engine.py:23:save] [Torch] Saved work_dirs/internvl_chat_v2_5/ak/checkpoint-1000/global_step1000/bf16_zero_pp_rank_0_mp_rank_00_optim_states.pt. +[2025-05-02 01:05:04,264] [INFO] [engine.py:3536:_save_zero_checkpoint] zero checkpoint saved work_dirs/internvl_chat_v2_5/ak/checkpoint-1000/global_step1000/bf16_zero_pp_rank_0_mp_rank_00_optim_states.pt +[2025-05-02 01:05:04,264] [INFO] [torch_checkpoint_engine.py:33:commit] [Torch] Checkpoint global_step1000 is ready now! +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 01:05:04,753] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.72 | bwd_microstep: 268.01 | bwd_inner_microstep: 267.99 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1907 +[2025-05-02 01:05:05,230] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.38 | bwd_microstep: 273.62 | bwd_inner_microstep: 273.60 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 357 +[2025-05-02 01:05:05,436] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 73.00 | bwd_microstep: 120.43 | bwd_inner_microstep: 120.30 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1887 +[2025-05-02 01:05:05,911] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.06 | bwd_microstep: 272.72 | bwd_inner_microstep: 272.71 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-02 01:05:06,385] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.89 | bwd_microstep: 271.72 | bwd_inner_microstep: 271.70 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1116 +[2025-05-02 01:05:06,678] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 115.06 | bwd_microstep: 161.29 | bwd_inner_microstep: 161.27 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.13 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 01:05:07,151] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.81 | bwd_microstep: 271.11 | bwd_inner_microstep: 271.09 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 01:05:07,625] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.66 | bwd_microstep: 270.91 | bwd_inner_microstep: 270.89 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:05:08,101] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.70 | bwd_microstep: 271.27 | bwd_inner_microstep: 271.25 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:05:08,578] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.80 | bwd_microstep: 271.69 | bwd_inner_microstep: 271.67 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 01:05:09,054] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.61 | bwd_microstep: 271.40 | bwd_inner_microstep: 271.39 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 01:05:09,531] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.89 | bwd_microstep: 271.32 | bwd_inner_microstep: 271.31 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 01:05:10,006] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.86 | bwd_microstep: 270.32 | bwd_inner_microstep: 270.31 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 01:05:10,484] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.96 | bwd_microstep: 270.06 | bwd_inner_microstep: 270.04 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 01:05:10,960] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.53 | bwd_microstep: 270.07 | bwd_inner_microstep: 270.06 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:05:11,537] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.09 | optimizer_gradients: 2.14 | optimizer_step: 16.96 +[2025-05-02 01:05:11,537] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.19 | bwd_microstep: 347.99 | bwd_inner_microstep: 270.56 | bwd_allreduce_microstep: 77.37 | step_microstep: 24.87 +[2025-05-02 01:05:11,539] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2808.80 | bwd: 4153.97 | bwd_inner: 4076.17 | bwd_allreduce: 77.51 | step: 25.75 + 11%|█▏ | 1001/8720 [2:49:45<23:55:03, 11.15s/it] {'loss': 0.5979, 'grad_norm': 6.200523853302002, 'learning_rate': 9.81281771869266e-06, 'epoch': 1.15} + 11%|█▏ | 1001/8720 [2:49:45<23:55:03, 11.15s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 01:05:12,018] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.75 | bwd_microstep: 269.32 | bwd_inner_microstep: 269.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1938 +[2025-05-02 01:05:12,517] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.34 | bwd_microstep: 286.39 | bwd_inner_microstep: 286.37 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1911 +[2025-05-02 01:05:12,995] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.19 | bwd_microstep: 274.95 | bwd_inner_microstep: 274.93 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 866 +[2025-05-02 01:05:13,237] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.27 | bwd_microstep: 133.21 | bwd_inner_microstep: 133.01 | bwd_allreduce_microstep: 0.10 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-02 01:05:13,713] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.37 | bwd_microstep: 272.12 | bwd_inner_microstep: 272.10 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-02 01:05:14,187] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.89 | bwd_microstep: 272.00 | bwd_inner_microstep: 271.99 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-02 01:05:14,662] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.54 | bwd_microstep: 271.86 | bwd_inner_microstep: 271.85 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-02 01:05:15,137] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.42 | bwd_microstep: 272.01 | bwd_inner_microstep: 271.99 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 848 +[2025-05-02 01:05:15,377] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.94 | bwd_microstep: 131.83 | bwd_inner_microstep: 131.59 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 01:05:15,850] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.07 | bwd_microstep: 271.24 | bwd_inner_microstep: 271.22 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 01:05:16,323] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.71 | bwd_microstep: 271.13 | bwd_inner_microstep: 271.12 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 332 +[2025-05-02 01:05:16,554] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 97.72 | bwd_microstep: 115.50 | bwd_inner_microstep: 115.19 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.22 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 01:05:17,031] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.79 | bwd_microstep: 271.57 | bwd_inner_microstep: 271.55 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:05:17,506] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.12 | bwd_microstep: 271.09 | bwd_inner_microstep: 271.07 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.05 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1344 +[2025-05-02 01:05:17,870] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 139.80 | bwd_microstep: 203.51 | bwd_inner_microstep: 203.43 | bwd_allreduce_microstep: 0.04 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 01:05:18,444] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.12 | optimizer_step: 16.79 +[2025-05-02 01:05:18,445] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.06 | bwd_microstep: 346.74 | bwd_inner_microstep: 270.13 | bwd_allreduce_microstep: 76.56 | step_microstep: 24.45 +[2025-05-02 01:05:18,446] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2678.65 | bwd: 3934.58 | bwd_inner: 3856.91 | bwd_allreduce: 76.98 | step: 25.44 + 11%|█▏ | 1002/8720 [2:49:52<21:10:56, 9.88s/it] {'loss': 0.8261, 'grad_norm': 5.919750690460205, 'learning_rate': 9.812313988777195e-06, 'epoch': 1.15} + 11%|█▏ | 1002/8720 [2:49:52<21:10:56, 9.88s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:05:18,925] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.17 | bwd_microstep: 269.44 | bwd_inner_microstep: 269.42 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1131 +[2025-05-02 01:05:19,221] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 117.86 | bwd_microstep: 163.36 | bwd_inner_microstep: 163.17 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1903 +[2025-05-02 01:05:19,699] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.61 | bwd_microstep: 274.59 | bwd_inner_microstep: 274.58 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 847 +[2025-05-02 01:05:19,939] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.40 | bwd_microstep: 131.86 | bwd_inner_microstep: 131.60 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.18 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 844 +[2025-05-02 01:05:20,179] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.15 | bwd_microstep: 131.56 | bwd_inner_microstep: 131.32 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 01:05:20,654] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.92 | bwd_microstep: 272.31 | bwd_inner_microstep: 272.29 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 01:05:21,128] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.37 | bwd_microstep: 271.29 | bwd_inner_microstep: 271.27 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 332 +[2025-05-02 01:05:21,360] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 81.81 | bwd_microstep: 129.21 | bwd_inner_microstep: 128.99 | bwd_allreduce_microstep: 0.08 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 01:05:21,834] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.59 | bwd_microstep: 271.59 | bwd_inner_microstep: 271.57 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 01:05:22,308] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.64 | bwd_microstep: 271.85 | bwd_inner_microstep: 271.83 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 01:05:22,782] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.86 | bwd_microstep: 271.29 | bwd_inner_microstep: 271.27 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:05:23,255] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.59 | bwd_microstep: 270.16 | bwd_inner_microstep: 270.14 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:05:23,727] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.24 | bwd_microstep: 270.27 | bwd_inner_microstep: 270.25 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 01:05:24,198] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.69 | bwd_microstep: 270.07 | bwd_inner_microstep: 270.06 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 01:05:24,672] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.31 | bwd_microstep: 269.96 | bwd_inner_microstep: 269.94 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:05:25,237] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.19 | optimizer_step: 16.98 +[2025-05-02 01:05:25,238] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.13 | bwd_microstep: 338.09 | bwd_inner_microstep: 270.79 | bwd_allreduce_microstep: 67.25 | step_microstep: 24.27 +[2025-05-02 01:05:25,239] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2635.08 | bwd: 3876.99 | bwd_inner: 3808.55 | bwd_allreduce: 67.76 | step: 25.19 + 12%|█▏ | 1003/8720 [2:49:58<19:11:36, 8.95s/it] {'loss': 0.6433, 'grad_norm': 8.336246490478516, 'learning_rate': 9.811809594937783e-06, 'epoch': 1.15} + 12%|█▏ | 1003/8720 [2:49:58<19:11:36, 8.95s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:05:25,715] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.20 | bwd_microstep: 269.33 | bwd_inner_microstep: 269.31 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1935 +[2025-05-02 01:05:26,213] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.44 | bwd_microstep: 287.27 | bwd_inner_microstep: 287.25 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1911 +[2025-05-02 01:05:26,696] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.22 | bwd_microstep: 275.96 | bwd_inner_microstep: 275.94 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1899 +[2025-05-02 01:05:27,176] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.73 | bwd_microstep: 274.97 | bwd_inner_microstep: 274.96 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1887 +[2025-05-02 01:05:27,654] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.17 | bwd_microstep: 274.04 | bwd_inner_microstep: 274.02 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-02 01:05:28,133] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.81 | bwd_microstep: 273.25 | bwd_inner_microstep: 273.23 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-02 01:05:28,610] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.73 | bwd_microstep: 272.96 | bwd_inner_microstep: 272.94 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-02 01:05:29,088] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.89 | bwd_microstep: 272.86 | bwd_inner_microstep: 272.84 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 01:05:29,564] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.13 | bwd_microstep: 272.49 | bwd_inner_microstep: 272.48 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 331 +[2025-05-02 01:05:29,770] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 68.98 | bwd_microstep: 122.93 | bwd_inner_microstep: 122.66 | bwd_allreduce_microstep: 0.10 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:05:30,244] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.43 | bwd_microstep: 271.87 | bwd_inner_microstep: 271.85 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:05:30,720] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.50 | bwd_microstep: 271.78 | bwd_inner_microstep: 271.76 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:05:31,196] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.40 | bwd_microstep: 271.91 | bwd_inner_microstep: 271.89 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:05:31,673] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.45 | bwd_microstep: 270.90 | bwd_inner_microstep: 270.88 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 832 +[2025-05-02 01:05:31,928] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 101.29 | bwd_microstep: 133.07 | bwd_inner_microstep: 132.97 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 01:05:32,522] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 8.66 | optimizer_step: 23.93 +[2025-05-02 01:05:32,522] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.66 | bwd_microstep: 349.76 | bwd_inner_microstep: 270.97 | bwd_allreduce_microstep: 78.73 | step_microstep: 38.49 +[2025-05-02 01:05:32,524] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2812.75 | bwd: 4165.40 | bwd_inner: 4086.03 | bwd_allreduce: 78.97 | step: 39.27 + 12%|█▏ | 1004/8720 [2:50:06<18:07:07, 8.45s/it] {'loss': 0.6818, 'grad_norm': 4.729243755340576, 'learning_rate': 9.81130453724401e-06, 'epoch': 1.15} + 12%|█▏ | 1004/8720 [2:50:06<18:07:07, 8.45s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 01:05:33,005] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.14 | bwd_microstep: 269.75 | bwd_inner_microstep: 269.73 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2068 +[2025-05-02 01:05:33,523] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 200.57 | bwd_microstep: 301.67 | bwd_inner_microstep: 301.65 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1919 +[2025-05-02 01:05:34,004] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.29 | bwd_microstep: 275.33 | bwd_inner_microstep: 275.31 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1892 +[2025-05-02 01:05:34,486] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.16 | bwd_microstep: 273.59 | bwd_inner_microstep: 273.57 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.11 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1367 +[2025-05-02 01:05:34,852] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.84 | bwd_microstep: 206.99 | bwd_inner_microstep: 206.97 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-02 01:05:35,335] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.33 | bwd_microstep: 273.21 | bwd_inner_microstep: 273.20 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 01:05:35,816] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.04 | bwd_microstep: 272.29 | bwd_inner_microstep: 272.27 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 01:05:36,297] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.01 | bwd_microstep: 272.16 | bwd_inner_microstep: 272.14 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 01:05:36,775] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.63 | bwd_microstep: 272.16 | bwd_inner_microstep: 272.14 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:05:37,253] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.51 | bwd_microstep: 271.85 | bwd_inner_microstep: 271.84 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:05:37,735] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.72 | bwd_microstep: 271.88 | bwd_inner_microstep: 271.86 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:05:38,214] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.76 | bwd_microstep: 271.63 | bwd_inner_microstep: 271.61 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 01:05:38,694] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.64 | bwd_microstep: 270.84 | bwd_inner_microstep: 270.83 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:05:39,177] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.50 | bwd_microstep: 270.72 | bwd_inner_microstep: 270.70 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:05:39,661] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.16 | bwd_microstep: 270.69 | bwd_inner_microstep: 270.67 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:05:40,252] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.18 | optimizer_step: 17.08 +[2025-05-02 01:05:40,252] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.67 | bwd_microstep: 353.03 | bwd_inner_microstep: 271.28 | bwd_allreduce_microstep: 81.69 | step_microstep: 25.05 +[2025-05-02 01:05:40,254] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2973.50 | bwd: 4397.80 | bwd_inner: 4315.78 | bwd_allreduce: 81.78 | step: 26.48 + 12%|█▏ | 1005/8720 [2:50:14<17:39:04, 8.24s/it] {'loss': 0.6923, 'grad_norm': 11.24741268157959, 'learning_rate': 9.810798815765552e-06, 'epoch': 1.15} + 12%|█▏ | 1005/8720 [2:50:14<17:39:04, 8.24s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1972 +[2025-05-02 01:05:40,764] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 197.40 | bwd_microstep: 289.55 | bwd_inner_microstep: 289.53 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1946 +[2025-05-02 01:05:41,264] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 194.89 | bwd_microstep: 287.96 | bwd_inner_microstep: 287.94 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1927 +[2025-05-02 01:05:41,762] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 193.90 | bwd_microstep: 286.40 | bwd_inner_microstep: 286.38 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-02 01:05:42,239] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.35 | bwd_microstep: 273.25 | bwd_inner_microstep: 273.23 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 01:05:42,715] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.12 | bwd_microstep: 272.57 | bwd_inner_microstep: 272.56 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 01:05:43,191] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.74 | bwd_microstep: 272.83 | bwd_inner_microstep: 272.81 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 01:05:43,668] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.43 | bwd_microstep: 272.64 | bwd_inner_microstep: 272.62 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.14 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 01:05:44,144] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.18 | bwd_microstep: 272.50 | bwd_inner_microstep: 272.48 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 01:05:44,619] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.64 | bwd_microstep: 272.25 | bwd_inner_microstep: 272.23 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:05:45,095] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.35 | bwd_microstep: 271.83 | bwd_inner_microstep: 271.81 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:05:45,570] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.63 | bwd_microstep: 272.16 | bwd_inner_microstep: 272.14 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:05:46,046] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.34 | bwd_microstep: 272.22 | bwd_inner_microstep: 272.20 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:05:46,521] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.81 | bwd_microstep: 271.85 | bwd_inner_microstep: 271.83 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 829 +[2025-05-02 01:05:46,759] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.88 | bwd_microstep: 129.65 | bwd_inner_microstep: 129.51 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 01:05:47,231] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.42 | bwd_microstep: 270.36 | bwd_inner_microstep: 270.34 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1918 +[2025-05-02 01:05:47,817] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.13 | optimizer_step: 17.05 +[2025-05-02 01:05:47,817] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.37 | bwd_microstep: 353.78 | bwd_inner_microstep: 276.54 | bwd_allreduce_microstep: 77.19 | step_microstep: 24.98 +[2025-05-02 01:05:47,819] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2935.16 | bwd: 4341.83 | bwd_inner: 4264.21 | bwd_allreduce: 77.33 | step: 25.85 + 12%|█▏ | 1006/8720 [2:50:21<17:13:02, 8.04s/it] {'loss': 0.8254, 'grad_norm': 5.523841857910156, 'learning_rate': 9.810292430572187e-06, 'epoch': 1.15} + 12%|█▏ | 1006/8720 [2:50:21<17:13:02, 8.04s/it]dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1367 +[2025-05-02 01:05:48,190] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.42 | bwd_microstep: 206.91 | bwd_inner_microstep: 206.66 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1952 +[2025-05-02 01:05:48,692] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.77 | bwd_microstep: 288.75 | bwd_inner_microstep: 288.73 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 911 +[2025-05-02 01:05:48,955] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 103.41 | bwd_microstep: 144.34 | bwd_inner_microstep: 144.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-02 01:05:49,430] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.21 | bwd_microstep: 272.67 | bwd_inner_microstep: 272.65 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 342 +[2025-05-02 01:05:49,643] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 79.44 | bwd_microstep: 118.63 | bwd_inner_microstep: 118.36 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-02 01:05:50,119] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.87 | bwd_microstep: 273.10 | bwd_inner_microstep: 273.08 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 838 +[2025-05-02 01:05:50,353] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.10 | bwd_microstep: 126.06 | bwd_inner_microstep: 125.90 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 01:05:50,829] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.22 | bwd_microstep: 272.85 | bwd_inner_microstep: 272.83 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 01:05:51,306] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.57 | bwd_microstep: 272.79 | bwd_inner_microstep: 272.77 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 01:05:51,784] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.95 | bwd_microstep: 273.13 | bwd_inner_microstep: 273.12 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:05:52,262] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.86 | bwd_microstep: 272.73 | bwd_inner_microstep: 272.71 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.17 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:05:52,740] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.33 | bwd_microstep: 272.70 | bwd_inner_microstep: 272.68 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:05:53,215] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.10 | bwd_microstep: 272.38 | bwd_inner_microstep: 272.36 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 01:05:53,691] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.25 | bwd_microstep: 272.06 | bwd_inner_microstep: 272.05 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:05:54,166] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.27 | bwd_microstep: 272.41 | bwd_inner_microstep: 272.40 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 832 +[2025-05-02 01:05:54,502] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.21 | optimizer_step: 23.27 +[2025-05-02 01:05:54,502] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.36 | bwd_microstep: 197.71 | bwd_inner_microstep: 130.65 | bwd_allreduce_microstep: 66.91 | step_microstep: 30.66 +[2025-05-02 01:05:54,503] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2588.86 | bwd: 3809.30 | bwd_inner: 3741.37 | bwd_allreduce: 67.25 | step: 31.76 + 12%|█▏ | 1007/8720 [2:50:28<16:20:45, 7.63s/it] {'loss': 0.8056, 'grad_norm': 5.193687915802002, 'learning_rate': 9.809785381733771e-06, 'epoch': 1.15} + 12%|█▏ | 1007/8720 [2:50:28<16:20:45, 7.63s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1849 +[2025-05-02 01:05:54,982] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.91 | bwd_microstep: 270.18 | bwd_inner_microstep: 270.16 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1936 +[2025-05-02 01:05:55,481] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.71 | bwd_microstep: 288.08 | bwd_inner_microstep: 288.06 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.17 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-02 01:05:55,960] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.76 | bwd_microstep: 273.89 | bwd_inner_microstep: 273.87 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-02 01:05:56,437] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.53 | bwd_microstep: 273.17 | bwd_inner_microstep: 273.15 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 01:05:56,912] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.34 | bwd_microstep: 272.68 | bwd_inner_microstep: 272.67 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 837 +[2025-05-02 01:05:57,145] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 91.90 | bwd_microstep: 126.09 | bwd_inner_microstep: 125.96 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 01:05:57,623] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.55 | bwd_microstep: 272.38 | bwd_inner_microstep: 272.36 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:05:58,103] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.02 | bwd_microstep: 272.31 | bwd_inner_microstep: 272.29 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 01:05:58,583] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.68 | bwd_microstep: 272.49 | bwd_inner_microstep: 272.48 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:05:59,061] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.83 | bwd_microstep: 272.15 | bwd_inner_microstep: 272.13 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:05:59,539] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.73 | bwd_microstep: 272.15 | bwd_inner_microstep: 272.14 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:06:00,018] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.27 | bwd_microstep: 272.27 | bwd_inner_microstep: 272.25 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:06:00,494] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.91 | bwd_microstep: 271.08 | bwd_inner_microstep: 271.06 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 01:06:00,966] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.06 | bwd_microstep: 270.76 | bwd_inner_microstep: 270.74 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:06:01,440] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.73 | bwd_microstep: 270.93 | bwd_inner_microstep: 270.91 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 01:06:02,014] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.06 | optimizer_step: 17.00 +[2025-05-02 01:06:02,014] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.15 | bwd_microstep: 344.69 | bwd_inner_microstep: 271.56 | bwd_allreduce_microstep: 73.09 | step_microstep: 24.16 +[2025-05-02 01:06:02,015] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2922.76 | bwd: 4295.34 | bwd_inner: 4221.80 | bwd_allreduce: 73.23 | step: 25.12 + 12%|█▏ | 1008/8720 [2:50:35<16:16:06, 7.59s/it] {'loss': 0.5079, 'grad_norm': 5.750156402587891, 'learning_rate': 9.809277669320264e-06, 'epoch': 1.16} + 12%|█▏ | 1008/8720 [2:50:35<16:16:06, 7.59s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:06:02,493] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.74 | bwd_microstep: 270.53 | bwd_inner_microstep: 270.52 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2092 +[2025-05-02 01:06:03,016] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 203.24 | bwd_microstep: 304.12 | bwd_inner_microstep: 304.10 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1939 +[2025-05-02 01:06:03,515] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 194.88 | bwd_microstep: 288.62 | bwd_inner_microstep: 288.60 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1902 +[2025-05-02 01:06:03,997] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.86 | bwd_microstep: 275.53 | bwd_inner_microstep: 275.51 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1905 +[2025-05-02 01:06:04,481] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.64 | bwd_microstep: 275.72 | bwd_inner_microstep: 275.70 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-02 01:06:04,965] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.03 | bwd_microstep: 273.82 | bwd_inner_microstep: 273.80 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.15 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-02 01:06:05,447] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.98 | bwd_microstep: 272.75 | bwd_inner_microstep: 272.73 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-02 01:06:05,932] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.13 | bwd_microstep: 273.28 | bwd_inner_microstep: 273.26 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:06:06,412] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.02 | bwd_microstep: 272.12 | bwd_inner_microstep: 272.11 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:06:06,895] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.87 | bwd_microstep: 272.44 | bwd_inner_microstep: 272.42 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:06:07,373] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.00 | bwd_microstep: 272.74 | bwd_inner_microstep: 272.72 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 01:06:07,852] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.14 | bwd_microstep: 272.36 | bwd_inner_microstep: 272.34 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1346 +[2025-05-02 01:06:08,216] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.42 | bwd_microstep: 205.13 | bwd_inner_microstep: 205.11 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 01:06:08,695] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.72 | bwd_microstep: 271.24 | bwd_inner_microstep: 271.22 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:06:09,171] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.50 | bwd_microstep: 270.95 | bwd_inner_microstep: 270.93 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 01:06:09,757] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.14 | optimizer_step: 26.87 +[2025-05-02 01:06:09,757] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.37 | bwd_microstep: 346.90 | bwd_inner_microstep: 271.08 | bwd_allreduce_microstep: 75.77 | step_microstep: 34.49 +[2025-05-02 01:06:09,758] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2985.16 | bwd: 4418.25 | bwd_inner: 4342.16 | bwd_allreduce: 75.86 | step: 35.47 + 12%|█▏ | 1009/8720 [2:50:43<16:21:46, 7.64s/it] {'loss': 0.5596, 'grad_norm': 17.151813507080078, 'learning_rate': 9.80876929340171e-06, 'epoch': 1.16} + 12%|█▏ | 1009/8720 [2:50:43<16:21:46, 7.64s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:06:10,239] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.77 | bwd_microstep: 270.60 | bwd_inner_microstep: 270.59 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2067 +[2025-05-02 01:06:10,759] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 202.26 | bwd_microstep: 302.93 | bwd_inner_microstep: 302.91 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 347 +[2025-05-02 01:06:10,960] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 72.38 | bwd_microstep: 115.55 | bwd_inner_microstep: 115.36 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-02 01:06:11,438] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.09 | bwd_microstep: 274.12 | bwd_inner_microstep: 274.10 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-02 01:06:11,917] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.52 | bwd_microstep: 273.97 | bwd_inner_microstep: 273.96 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-02 01:06:12,397] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.57 | bwd_microstep: 273.69 | bwd_inner_microstep: 273.67 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 335 +[2025-05-02 01:06:12,624] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.20 | bwd_microstep: 115.87 | bwd_inner_microstep: 115.73 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 840 +[2025-05-02 01:06:12,859] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 92.84 | bwd_microstep: 126.70 | bwd_inner_microstep: 126.46 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 01:06:13,339] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.14 | bwd_microstep: 272.67 | bwd_inner_microstep: 272.66 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 844 +[2025-05-02 01:06:13,582] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.06 | bwd_microstep: 132.04 | bwd_inner_microstep: 131.94 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-02 01:06:14,062] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.99 | bwd_microstep: 273.74 | bwd_inner_microstep: 273.72 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 834 +[2025-05-02 01:06:14,309] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 103.32 | bwd_microstep: 125.70 | bwd_inner_microstep: 125.68 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:06:14,785] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.86 | bwd_microstep: 271.16 | bwd_inner_microstep: 271.14 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 01:06:15,262] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.60 | bwd_microstep: 271.89 | bwd_inner_microstep: 271.87 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 01:06:15,739] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.81 | bwd_microstep: 271.26 | bwd_inner_microstep: 271.24 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 832 +[2025-05-02 01:06:16,081] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.10 | optimizer_step: 16.94 +[2025-05-02 01:06:16,082] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.54 | bwd_microstep: 206.82 | bwd_inner_microstep: 130.64 | bwd_allreduce_microstep: 76.05 | step_microstep: 24.55 +[2025-05-02 01:06:16,083] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2452.64 | bwd: 3578.81 | bwd_inner: 3501.80 | bwd_allreduce: 76.39 | step: 25.48 + 12%|█▏ | 1010/8720 [2:50:49<15:30:58, 7.24s/it] {'loss': 0.7256, 'grad_norm': 5.85920524597168, 'learning_rate': 9.808260254048245e-06, 'epoch': 1.16} + 12%|█▏ | 1010/8720 [2:50:49<15:30:58, 7.24s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:06:16,564] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.61 | bwd_microstep: 270.22 | bwd_inner_microstep: 270.20 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1134 +[2025-05-02 01:06:16,863] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 118.81 | bwd_microstep: 164.07 | bwd_inner_microstep: 163.97 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-02 01:06:17,341] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.57 | bwd_microstep: 273.62 | bwd_inner_microstep: 273.60 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1892 +[2025-05-02 01:06:17,823] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.58 | bwd_microstep: 274.73 | bwd_inner_microstep: 274.71 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1120 +[2025-05-02 01:06:18,124] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 118.30 | bwd_microstep: 162.99 | bwd_inner_microstep: 162.87 | bwd_allreduce_microstep: 0.03 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-02 01:06:18,609] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.50 | bwd_microstep: 273.69 | bwd_inner_microstep: 273.67 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-02 01:06:19,094] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.87 | bwd_microstep: 273.78 | bwd_inner_microstep: 273.77 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-02 01:06:19,579] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.37 | bwd_microstep: 273.37 | bwd_inner_microstep: 273.35 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 01:06:20,064] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.44 | bwd_microstep: 272.89 | bwd_inner_microstep: 272.88 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:06:20,546] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.16 | bwd_microstep: 272.51 | bwd_inner_microstep: 272.49 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 01:06:21,029] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.14 | bwd_microstep: 273.02 | bwd_inner_microstep: 273.00 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:06:21,506] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.93 | bwd_microstep: 271.15 | bwd_inner_microstep: 271.13 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 01:06:21,982] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.96 | bwd_microstep: 270.76 | bwd_inner_microstep: 270.75 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:06:22,459] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.06 | bwd_microstep: 270.93 | bwd_inner_microstep: 270.91 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1850 +[2025-05-02 01:06:22,936] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.95 | bwd_microstep: 270.71 | bwd_inner_microstep: 270.69 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1850 +[2025-05-02 01:06:23,521] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.90 | optimizer_step: 16.90 +[2025-05-02 01:06:23,522] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.24 | bwd_microstep: 350.69 | bwd_inner_microstep: 271.23 | bwd_allreduce_microstep: 79.42 | step_microstep: 25.63 +[2025-05-02 01:06:23,523] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2874.04 | bwd: 4219.21 | bwd_inner: 4139.23 | bwd_allreduce: 79.61 | step: 26.72 + 12%|█▏ | 1011/8720 [2:50:57<15:38:22, 7.30s/it] {'loss': 0.8265, 'grad_norm': 10.076432228088379, 'learning_rate': 9.807750551330099e-06, 'epoch': 1.16} + 12%|█▏ | 1011/8720 [2:50:57<15:38:22, 7.30s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1940 +[2025-05-02 01:06:24,029] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.18 | bwd_microstep: 287.91 | bwd_inner_microstep: 287.89 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1926 +[2025-05-02 01:06:24,529] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 194.99 | bwd_microstep: 287.43 | bwd_inner_microstep: 287.41 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1896 +[2025-05-02 01:06:25,009] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.95 | bwd_microstep: 274.87 | bwd_inner_microstep: 274.85 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1128 +[2025-05-02 01:06:25,306] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 118.06 | bwd_microstep: 163.59 | bwd_inner_microstep: 163.57 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 01:06:25,784] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.50 | bwd_microstep: 272.91 | bwd_inner_microstep: 272.89 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 848 +[2025-05-02 01:06:26,024] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.65 | bwd_microstep: 132.87 | bwd_inner_microstep: 132.65 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1356 +[2025-05-02 01:06:26,385] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.62 | bwd_microstep: 206.17 | bwd_inner_microstep: 206.14 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1363 +[2025-05-02 01:06:26,746] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.27 | bwd_microstep: 206.87 | bwd_inner_microstep: 206.80 | bwd_allreduce_microstep: 0.04 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 01:06:27,221] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.47 | bwd_microstep: 272.39 | bwd_inner_microstep: 272.37 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 838 +[2025-05-02 01:06:27,453] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 91.73 | bwd_microstep: 126.01 | bwd_inner_microstep: 125.99 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1351 +[2025-05-02 01:06:27,814] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.82 | bwd_microstep: 205.92 | bwd_inner_microstep: 205.91 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 01:06:28,289] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.37 | bwd_microstep: 272.56 | bwd_inner_microstep: 272.54 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 01:06:28,765] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.30 | bwd_microstep: 272.61 | bwd_inner_microstep: 272.59 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 837 +[2025-05-02 01:06:28,996] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 91.22 | bwd_microstep: 126.16 | bwd_inner_microstep: 126.10 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:06:29,472] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.38 | bwd_microstep: 272.68 | bwd_inner_microstep: 272.66 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:06:30,037] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.04 | optimizer_gradients: 2.10 | optimizer_step: 16.93 +[2025-05-02 01:06:30,037] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.22 | bwd_microstep: 337.70 | bwd_inner_microstep: 271.62 | bwd_allreduce_microstep: 66.04 | step_microstep: 23.95 +[2025-05-02 01:06:30,039] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2525.46 | bwd: 3718.71 | bwd_inner: 3651.98 | bwd_allreduce: 66.30 | step: 24.93 + 12%|█▏ | 1012/8720 [2:51:03<15:07:48, 7.07s/it] {'loss': 0.9678, 'grad_norm': 7.585807800292969, 'learning_rate': 9.807240185317593e-06, 'epoch': 1.16} + 12%|█▏ | 1012/8720 [2:51:03<15:07:48, 7.07s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 01:06:30,516] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.47 | bwd_microstep: 270.68 | bwd_inner_microstep: 270.66 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 346 +[2025-05-02 01:06:30,715] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 67.53 | bwd_microstep: 118.15 | bwd_inner_microstep: 117.97 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 334 +[2025-05-02 01:06:30,914] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 67.25 | bwd_microstep: 118.42 | bwd_inner_microstep: 118.13 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.09 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1366 +[2025-05-02 01:06:31,277] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.21 | bwd_microstep: 207.53 | bwd_inner_microstep: 207.43 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.09 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 844 +[2025-05-02 01:06:31,518] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.91 | bwd_microstep: 132.16 | bwd_inner_microstep: 132.14 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 01:06:31,995] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.29 | bwd_microstep: 273.75 | bwd_inner_microstep: 273.74 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:06:32,472] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.26 | bwd_microstep: 272.97 | bwd_inner_microstep: 272.95 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 01:06:32,950] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.35 | bwd_microstep: 273.71 | bwd_inner_microstep: 273.70 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 01:06:33,427] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.66 | bwd_microstep: 272.99 | bwd_inner_microstep: 272.97 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:06:33,904] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.60 | bwd_microstep: 273.01 | bwd_inner_microstep: 272.99 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:06:34,378] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.56 | bwd_microstep: 272.41 | bwd_inner_microstep: 272.39 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:06:34,854] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.30 | bwd_microstep: 272.52 | bwd_inner_microstep: 272.51 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 01:06:35,329] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.82 | bwd_microstep: 271.84 | bwd_inner_microstep: 271.82 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:06:35,806] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.44 | bwd_microstep: 272.78 | bwd_inner_microstep: 272.76 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 830 +[2025-05-02 01:06:36,045] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 92.99 | bwd_microstep: 130.96 | bwd_inner_microstep: 130.72 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.14 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 318 +[2025-05-02 01:06:36,375] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.07 | optimizer_step: 16.96 +[2025-05-02 01:06:36,376] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 82.44 | bwd_microstep: 209.77 | bwd_inner_microstep: 133.30 | bwd_allreduce_microstep: 76.37 | step_microstep: 24.66 +[2025-05-02 01:06:36,377] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2430.82 | bwd: 3643.75 | bwd_inner: 3566.32 | bwd_allreduce: 76.81 | step: 25.67 + 12%|█▏ | 1013/8720 [2:51:10<14:39:43, 6.85s/it] {'loss': 0.8717, 'grad_norm': 14.161308288574219, 'learning_rate': 9.806729156081136e-06, 'epoch': 1.16} + 12%|█▏ | 1013/8720 [2:51:10<14:39:43, 6.85s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2436 +[2025-05-02 01:06:36,974] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 222.79 | bwd_microstep: 351.01 | bwd_inner_microstep: 350.99 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-02 01:06:37,455] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.91 | bwd_microstep: 273.49 | bwd_inner_microstep: 273.47 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-02 01:06:37,939] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.41 | bwd_microstep: 273.26 | bwd_inner_microstep: 273.24 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-02 01:06:38,419] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.61 | bwd_microstep: 273.29 | bwd_inner_microstep: 273.27 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 848 +[2025-05-02 01:06:38,665] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.44 | bwd_microstep: 132.35 | bwd_inner_microstep: 132.23 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 01:06:39,144] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.17 | bwd_microstep: 273.07 | bwd_inner_microstep: 273.05 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 01:06:39,622] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.08 | bwd_microstep: 272.61 | bwd_inner_microstep: 272.59 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 01:06:40,100] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.97 | bwd_microstep: 272.63 | bwd_inner_microstep: 272.62 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 01:06:40,580] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.10 | bwd_microstep: 272.56 | bwd_inner_microstep: 272.54 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:06:41,064] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.18 | bwd_microstep: 272.42 | bwd_inner_microstep: 272.40 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:06:41,542] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.51 | bwd_microstep: 272.61 | bwd_inner_microstep: 272.59 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1347 +[2025-05-02 01:06:41,905] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.33 | bwd_microstep: 205.70 | bwd_inner_microstep: 205.61 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:06:42,378] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.24 | bwd_microstep: 271.17 | bwd_inner_microstep: 271.15 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 01:06:42,853] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.76 | bwd_microstep: 272.18 | bwd_inner_microstep: 272.16 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 01:06:43,329] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.02 | bwd_microstep: 271.55 | bwd_inner_microstep: 271.53 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 317 +[2025-05-02 01:06:43,639] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.04 | optimizer_gradients: 2.10 | optimizer_step: 16.92 +[2025-05-02 01:06:43,639] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 72.68 | bwd_microstep: 198.74 | bwd_inner_microstep: 132.72 | bwd_allreduce_microstep: 65.94 | step_microstep: 23.79 +[2025-05-02 01:06:43,640] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2788.81 | bwd: 4158.66 | bwd_inner: 4092.19 | bwd_allreduce: 66.08 | step: 24.66 + 12%|█▏ | 1014/8720 [2:51:17<14:55:29, 6.97s/it] {'loss': 0.7705, 'grad_norm': 16.150163650512695, 'learning_rate': 9.806217463691234e-06, 'epoch': 1.16} + 12%|█▏ | 1014/8720 [2:51:17<14:55:29, 6.97s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1888 +[2025-05-02 01:06:44,122] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.57 | bwd_microstep: 273.80 | bwd_inner_microstep: 273.78 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1430 +[2025-05-02 01:06:44,496] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 145.57 | bwd_microstep: 213.51 | bwd_inner_microstep: 213.49 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 400 +[2025-05-02 01:06:44,699] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 75.13 | bwd_microstep: 115.13 | bwd_inner_microstep: 114.81 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-02 01:06:45,175] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.58 | bwd_microstep: 273.45 | bwd_inner_microstep: 273.43 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-02 01:06:45,653] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.54 | bwd_microstep: 273.79 | bwd_inner_microstep: 273.78 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-02 01:06:46,130] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.75 | bwd_microstep: 273.13 | bwd_inner_microstep: 273.11 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 01:06:46,609] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.97 | bwd_microstep: 273.42 | bwd_inner_microstep: 273.40 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-02 01:06:47,087] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.25 | bwd_microstep: 273.63 | bwd_inner_microstep: 273.61 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1347 +[2025-05-02 01:06:47,449] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.75 | bwd_microstep: 205.46 | bwd_inner_microstep: 205.44 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 01:06:47,925] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.80 | bwd_microstep: 272.70 | bwd_inner_microstep: 272.68 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:06:48,401] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.02 | bwd_microstep: 272.19 | bwd_inner_microstep: 272.17 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:06:48,879] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.75 | bwd_microstep: 272.20 | bwd_inner_microstep: 272.18 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:06:49,357] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.56 | bwd_microstep: 272.28 | bwd_inner_microstep: 272.26 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 01:06:49,835] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.79 | bwd_microstep: 272.32 | bwd_inner_microstep: 272.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:06:50,315] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.84 | bwd_microstep: 272.25 | bwd_inner_microstep: 272.23 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:06:50,906] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.15 | optimizer_step: 17.13 +[2025-05-02 01:06:50,907] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.64 | bwd_microstep: 352.42 | bwd_inner_microstep: 271.30 | bwd_allreduce_microstep: 81.07 | step_microstep: 25.05 +[2025-05-02 01:06:50,908] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2808.18 | bwd: 4161.68 | bwd_inner: 4080.03 | bwd_allreduce: 81.26 | step: 25.99 + 12%|█▏ | 1015/8720 [2:51:24<15:06:51, 7.06s/it] {'loss': 1.2523, 'grad_norm': 17.34882164001465, 'learning_rate': 9.805705108218481e-06, 'epoch': 1.16} + 12%|█▏ | 1015/8720 [2:51:24<15:06:51, 7.06s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:06:51,389] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.23 | bwd_microstep: 270.25 | bwd_inner_microstep: 270.23 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-02 01:06:51,872] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.31 | bwd_microstep: 273.78 | bwd_inner_microstep: 273.77 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 01:06:52,354] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.32 | bwd_microstep: 272.82 | bwd_inner_microstep: 272.80 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-02 01:06:52,837] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.67 | bwd_microstep: 273.87 | bwd_inner_microstep: 273.85 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 01:06:53,318] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.08 | bwd_microstep: 273.43 | bwd_inner_microstep: 273.42 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 856 +[2025-05-02 01:06:53,562] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.81 | bwd_microstep: 133.03 | bwd_inner_microstep: 132.89 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-02 01:06:54,042] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.68 | bwd_microstep: 273.47 | bwd_inner_microstep: 273.45 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-02 01:06:54,523] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.34 | bwd_microstep: 274.11 | bwd_inner_microstep: 274.09 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-02 01:06:55,003] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.24 | bwd_microstep: 273.37 | bwd_inner_microstep: 273.35 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 01:06:55,480] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.59 | bwd_microstep: 272.90 | bwd_inner_microstep: 272.88 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:06:55,956] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.06 | bwd_microstep: 272.31 | bwd_inner_microstep: 272.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 01:06:56,432] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.59 | bwd_microstep: 272.58 | bwd_inner_microstep: 272.56 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:06:56,909] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.10 | bwd_microstep: 272.28 | bwd_inner_microstep: 272.26 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 328 +[2025-05-02 01:06:57,127] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 82.20 | bwd_microstep: 120.83 | bwd_inner_microstep: 120.70 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:06:57,604] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.11 | bwd_microstep: 272.60 | bwd_inner_microstep: 272.58 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 396 +[2025-05-02 01:06:57,915] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.14 | optimizer_step: 17.13 +[2025-05-02 01:06:57,916] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 73.57 | bwd_microstep: 200.50 | bwd_inner_microstep: 133.73 | bwd_allreduce_microstep: 66.69 | step_microstep: 24.34 +[2025-05-02 01:06:57,917] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2699.57 | bwd: 4002.16 | bwd_inner: 3934.92 | bwd_allreduce: 66.85 | step: 25.19 + 12%|█▏ | 1016/8720 [2:51:31<15:04:36, 7.05s/it] {'loss': 1.3083, 'grad_norm': 6.732432842254639, 'learning_rate': 9.805192089733565e-06, 'epoch': 1.17} + 12%|█▏ | 1016/8720 [2:51:31<15:04:36, 7.05s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1915 +[2025-05-02 01:06:58,402] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.60 | bwd_microstep: 275.72 | bwd_inner_microstep: 275.70 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 01:06:58,879] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.44 | bwd_microstep: 272.75 | bwd_inner_microstep: 272.73 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 01:06:59,355] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.29 | bwd_microstep: 273.32 | bwd_inner_microstep: 273.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 01:06:59,832] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.95 | bwd_microstep: 272.35 | bwd_inner_microstep: 272.33 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 01:07:00,307] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.98 | bwd_microstep: 272.54 | bwd_inner_microstep: 272.52 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 01:07:00,783] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.60 | bwd_microstep: 272.71 | bwd_inner_microstep: 272.69 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 01:07:01,261] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.03 | bwd_microstep: 272.81 | bwd_inner_microstep: 272.79 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1351 +[2025-05-02 01:07:01,622] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.08 | bwd_microstep: 205.37 | bwd_inner_microstep: 205.35 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.09 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 321 +[2025-05-02 01:07:01,824] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 70.10 | bwd_microstep: 118.34 | bwd_inner_microstep: 118.14 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 833 +[2025-05-02 01:07:02,054] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 90.52 | bwd_microstep: 126.03 | bwd_inner_microstep: 125.95 | bwd_allreduce_microstep: 0.04 | step_microstep: 0.08 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 837 +[2025-05-02 01:07:02,286] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 91.34 | bwd_microstep: 126.00 | bwd_inner_microstep: 125.94 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:07:02,762] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.23 | bwd_microstep: 272.13 | bwd_inner_microstep: 272.11 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1342 +[2025-05-02 01:07:03,123] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.89 | bwd_microstep: 204.09 | bwd_inner_microstep: 204.03 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:07:03,597] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.74 | bwd_microstep: 271.07 | bwd_inner_microstep: 271.05 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 01:07:04,071] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.27 | bwd_microstep: 270.83 | bwd_inner_microstep: 270.81 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 01:07:04,638] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.14 | optimizer_step: 17.10 +[2025-05-02 01:07:04,638] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.14 | bwd_microstep: 340.43 | bwd_inner_microstep: 271.42 | bwd_allreduce_microstep: 68.96 | step_microstep: 24.29 +[2025-05-02 01:07:04,639] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2603.94 | bwd: 3846.53 | bwd_inner: 3776.93 | bwd_allreduce: 69.20 | step: 25.16 + 12%|█▏ | 1017/8720 [2:51:38<14:52:03, 6.95s/it] {'loss': 0.5099, 'grad_norm': 5.07474422454834, 'learning_rate': 9.804678408307263e-06, 'epoch': 1.17} + 12%|█▏ | 1017/8720 [2:51:38<14:52:03, 6.95s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1849 +[2025-05-02 01:07:05,117] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.81 | bwd_microstep: 270.20 | bwd_inner_microstep: 270.19 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1988 +[2025-05-02 01:07:05,625] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 197.66 | bwd_microstep: 293.08 | bwd_inner_microstep: 293.06 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1938 +[2025-05-02 01:07:06,125] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.67 | bwd_microstep: 287.66 | bwd_inner_microstep: 287.64 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1891 +[2025-05-02 01:07:06,605] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.15 | bwd_microstep: 274.58 | bwd_inner_microstep: 274.56 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1888 +[2025-05-02 01:07:07,083] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.97 | bwd_microstep: 274.28 | bwd_inner_microstep: 274.26 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1883 +[2025-05-02 01:07:07,562] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.06 | bwd_microstep: 273.96 | bwd_inner_microstep: 273.94 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 860 +[2025-05-02 01:07:07,804] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.69 | bwd_microstep: 133.08 | bwd_inner_microstep: 133.06 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-02 01:07:08,281] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.64 | bwd_microstep: 273.42 | bwd_inner_microstep: 273.40 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 01:07:08,758] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.79 | bwd_microstep: 273.02 | bwd_inner_microstep: 273.00 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 6, images per sample: 6.0, dynamic token length: 1607 +[2025-05-02 01:07:09,181] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 164.63 | bwd_microstep: 243.91 | bwd_inner_microstep: 243.89 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:07:09,659] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.26 | bwd_microstep: 272.98 | bwd_inner_microstep: 272.96 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:07:10,138] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.17 | bwd_microstep: 272.95 | bwd_inner_microstep: 272.93 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 01:07:10,617] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.15 | bwd_microstep: 271.75 | bwd_inner_microstep: 271.74 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:07:11,095] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.58 | bwd_microstep: 271.65 | bwd_inner_microstep: 271.63 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 01:07:11,573] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.65 | bwd_microstep: 271.73 | bwd_inner_microstep: 271.71 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:07:12,139] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.04 | optimizer_gradients: 2.15 | optimizer_step: 17.20 +[2025-05-02 01:07:12,140] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.65 | bwd_microstep: 338.13 | bwd_inner_microstep: 272.26 | bwd_allreduce_microstep: 65.83 | step_microstep: 24.31 +[2025-05-02 01:07:12,141] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2917.24 | bwd: 4296.41 | bwd_inner: 4230.25 | bwd_allreduce: 65.91 | step: 25.39 + 12%|█▏ | 1018/8720 [2:51:45<15:13:14, 7.11s/it] {'loss': 0.9706, 'grad_norm': 8.453988075256348, 'learning_rate': 9.80416406401044e-06, 'epoch': 1.17} + 12%|█▏ | 1018/8720 [2:51:45<15:13:14, 7.11s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1928 +[2025-05-02 01:07:12,644] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.22 | bwd_microstep: 286.25 | bwd_inner_microstep: 286.23 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1927 +[2025-05-02 01:07:13,143] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 194.80 | bwd_microstep: 286.86 | bwd_inner_microstep: 286.85 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 368 +[2025-05-02 01:07:13,351] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 75.82 | bwd_microstep: 117.51 | bwd_inner_microstep: 117.37 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1890 +[2025-05-02 01:07:13,829] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.11 | bwd_microstep: 274.32 | bwd_inner_microstep: 274.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 01:07:14,305] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.87 | bwd_microstep: 272.70 | bwd_inner_microstep: 272.68 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 01:07:14,782] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.79 | bwd_microstep: 273.23 | bwd_inner_microstep: 273.21 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 01:07:15,259] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.14 | bwd_microstep: 272.75 | bwd_inner_microstep: 272.74 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 01:07:15,737] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.15 | bwd_microstep: 272.93 | bwd_inner_microstep: 272.92 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 843 +[2025-05-02 01:07:15,977] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.01 | bwd_microstep: 132.18 | bwd_inner_microstep: 131.91 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 01:07:16,453] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.23 | bwd_microstep: 272.85 | bwd_inner_microstep: 272.83 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 325 +[2025-05-02 01:07:16,654] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 69.33 | bwd_microstep: 118.32 | bwd_inner_microstep: 118.11 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:07:17,129] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.45 | bwd_microstep: 272.24 | bwd_inner_microstep: 272.23 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:07:17,604] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.27 | bwd_microstep: 271.98 | bwd_inner_microstep: 271.96 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:07:18,080] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.30 | bwd_microstep: 272.54 | bwd_inner_microstep: 272.52 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 324 +[2025-05-02 01:07:18,316] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 81.87 | bwd_microstep: 139.51 | bwd_inner_microstep: 139.29 | bwd_allreduce_microstep: 0.09 | step_microstep: 0.09 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 1008 +[2025-05-02 01:07:18,679] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.19 | optimizer_step: 17.41 +[2025-05-02 01:07:18,680] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 105.56 | bwd_microstep: 219.64 | bwd_inner_microstep: 152.50 | bwd_allreduce_microstep: 66.97 | step_microstep: 24.71 +[2025-05-02 01:07:18,681] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2510.63 | bwd: 3755.89 | bwd_inner: 3687.88 | bwd_allreduce: 67.32 | step: 25.58 + 12%|█▏ | 1019/8720 [2:51:52<14:51:01, 6.94s/it] {'loss': 1.1925, 'grad_norm': 13.777215003967285, 'learning_rate': 9.803649056914064e-06, 'epoch': 1.17} + 12%|█▏ | 1019/8720 [2:51:52<14:51:01, 6.94s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1924 +[2025-05-02 01:07:19,182] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 194.36 | bwd_microstep: 286.98 | bwd_inner_microstep: 286.96 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1921 +[2025-05-02 01:07:19,680] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.14 | bwd_microstep: 286.81 | bwd_inner_microstep: 286.79 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1904 +[2025-05-02 01:07:20,160] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.79 | bwd_microstep: 275.79 | bwd_inner_microstep: 275.77 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1899 +[2025-05-02 01:07:20,641] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.85 | bwd_microstep: 275.46 | bwd_inner_microstep: 275.44 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.15 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1895 +[2025-05-02 01:07:21,123] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.30 | bwd_microstep: 275.04 | bwd_inner_microstep: 275.02 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.13 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1886 +[2025-05-02 01:07:21,604] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.37 | bwd_microstep: 274.26 | bwd_inner_microstep: 274.24 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 341 +[2025-05-02 01:07:21,839] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 92.69 | bwd_microstep: 123.07 | bwd_inner_microstep: 122.92 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 01:07:22,318] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.60 | bwd_microstep: 273.34 | bwd_inner_microstep: 273.32 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-02 01:07:22,802] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.39 | bwd_microstep: 274.05 | bwd_inner_microstep: 274.04 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 01:07:23,286] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.31 | bwd_microstep: 272.82 | bwd_inner_microstep: 272.80 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:07:23,772] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.18 | bwd_microstep: 272.63 | bwd_inner_microstep: 272.62 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 01:07:24,251] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.59 | bwd_microstep: 272.85 | bwd_inner_microstep: 272.83 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 01:07:24,733] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.22 | bwd_microstep: 272.94 | bwd_inner_microstep: 272.92 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:07:25,216] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.07 | bwd_microstep: 272.62 | bwd_inner_microstep: 272.61 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.16 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:07:25,696] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.66 | bwd_microstep: 272.30 | bwd_inner_microstep: 272.28 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:07:26,286] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.13 | optimizer_step: 16.95 +[2025-05-02 01:07:26,287] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.76 | bwd_microstep: 354.79 | bwd_inner_microstep: 273.33 | bwd_allreduce_microstep: 81.41 | step_microstep: 24.67 +[2025-05-02 01:07:26,288] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2938.90 | bwd: 4335.77 | bwd_inner: 4253.92 | bwd_allreduce: 81.55 | step: 25.88 + 12%|█▏ | 1020/8720 [2:52:00<15:16:33, 7.14s/it] {'loss': 0.9537, 'grad_norm': 4.558841228485107, 'learning_rate': 9.803133387089183e-06, 'epoch': 1.17} + 12%|█▏ | 1020/8720 [2:52:00<15:16:33, 7.14s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 01:07:26,769] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.20 | bwd_microstep: 270.23 | bwd_inner_microstep: 270.21 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1962 +[2025-05-02 01:07:27,274] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 196.34 | bwd_microstep: 290.37 | bwd_inner_microstep: 290.35 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.14 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1921 +[2025-05-02 01:07:27,775] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.19 | bwd_microstep: 286.56 | bwd_inner_microstep: 286.54 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 371 +[2025-05-02 01:07:27,994] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 86.44 | bwd_microstep: 117.13 | bwd_inner_microstep: 116.88 | bwd_allreduce_microstep: 0.10 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1889 +[2025-05-02 01:07:28,475] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.39 | bwd_microstep: 274.71 | bwd_inner_microstep: 274.69 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1900 +[2025-05-02 01:07:28,959] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.49 | bwd_microstep: 275.51 | bwd_inner_microstep: 275.50 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-02 01:07:29,439] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.12 | bwd_microstep: 274.42 | bwd_inner_microstep: 274.40 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-02 01:07:29,920] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.13 | bwd_microstep: 273.04 | bwd_inner_microstep: 273.03 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 01:07:30,399] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.98 | bwd_microstep: 273.20 | bwd_inner_microstep: 273.18 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 327 +[2025-05-02 01:07:30,614] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 80.26 | bwd_microstep: 119.02 | bwd_inner_microstep: 118.81 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 01:07:31,093] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.67 | bwd_microstep: 272.95 | bwd_inner_microstep: 272.93 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 839 +[2025-05-02 01:07:31,331] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.40 | bwd_microstep: 126.22 | bwd_inner_microstep: 126.11 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 01:07:31,810] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.68 | bwd_microstep: 273.06 | bwd_inner_microstep: 273.04 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:07:32,290] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.90 | bwd_microstep: 272.47 | bwd_inner_microstep: 272.45 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:07:32,767] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.10 | bwd_microstep: 271.33 | bwd_inner_microstep: 271.31 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 01:07:33,345] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.08 | optimizer_step: 16.92 +[2025-05-02 01:07:33,346] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.49 | bwd_microstep: 348.28 | bwd_inner_microstep: 271.52 | bwd_allreduce_microstep: 76.71 | step_microstep: 24.52 +[2025-05-02 01:07:33,347] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2729.44 | bwd: 4018.56 | bwd_inner: 3941.09 | bwd_allreduce: 76.98 | step: 25.54 + 12%|█▏ | 1021/8720 [2:52:07<15:13:14, 7.12s/it] {'loss': 0.8548, 'grad_norm': 4.995029449462891, 'learning_rate': 9.802617054606942e-06, 'epoch': 1.17} + 12%|█▏ | 1021/8720 [2:52:07<15:13:14, 7.12s/it]dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1103 +[2025-05-02 01:07:33,647] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 117.53 | bwd_microstep: 161.15 | bwd_inner_microstep: 161.13 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1931 +[2025-05-02 01:07:34,145] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 194.78 | bwd_microstep: 287.99 | bwd_inner_microstep: 287.97 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1905 +[2025-05-02 01:07:34,625] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.01 | bwd_microstep: 275.79 | bwd_inner_microstep: 275.77 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1902 +[2025-05-02 01:07:35,105] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.82 | bwd_microstep: 275.45 | bwd_inner_microstep: 275.43 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.15 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1362 +[2025-05-02 01:07:35,466] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.43 | bwd_microstep: 206.37 | bwd_inner_microstep: 206.29 | bwd_allreduce_microstep: 0.04 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-02 01:07:35,943] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.34 | bwd_microstep: 274.00 | bwd_inner_microstep: 273.98 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1366 +[2025-05-02 01:07:36,306] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.52 | bwd_microstep: 206.61 | bwd_inner_microstep: 206.54 | bwd_allreduce_microstep: 0.03 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 01:07:36,783] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.82 | bwd_microstep: 273.17 | bwd_inner_microstep: 273.15 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 835 +[2025-05-02 01:07:37,013] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 90.30 | bwd_microstep: 125.94 | bwd_inner_microstep: 125.83 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.14 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 01:07:37,490] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.13 | bwd_microstep: 272.99 | bwd_inner_microstep: 272.97 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:07:37,967] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.61 | bwd_microstep: 272.66 | bwd_inner_microstep: 272.64 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 844 +[2025-05-02 01:07:38,207] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.27 | bwd_microstep: 132.15 | bwd_inner_microstep: 132.13 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:07:38,682] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.68 | bwd_microstep: 272.04 | bwd_inner_microstep: 272.02 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:07:39,156] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.64 | bwd_microstep: 271.06 | bwd_inner_microstep: 271.04 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 01:07:39,632] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.25 | bwd_microstep: 271.37 | bwd_inner_microstep: 271.35 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1914 +[2025-05-02 01:07:40,205] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.09 | optimizer_step: 16.93 +[2025-05-02 01:07:40,205] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.73 | bwd_microstep: 344.00 | bwd_inner_microstep: 276.72 | bwd_allreduce_microstep: 67.23 | step_microstep: 24.13 +[2025-05-02 01:07:40,207] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2663.58 | bwd: 3922.79 | bwd_inner: 3854.99 | bwd_allreduce: 67.46 | step: 25.18 + 12%|█▏ | 1022/8720 [2:52:13<15:03:08, 7.04s/it] {'loss': 0.8515, 'grad_norm': 7.044328212738037, 'learning_rate': 9.802100059538573e-06, 'epoch': 1.17} + 12%|█▏ | 1022/8720 [2:52:13<15:03:08, 7.04s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:07:40,688] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.16 | bwd_microstep: 272.73 | bwd_inner_microstep: 272.72 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.13 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1902 +[2025-05-02 01:07:41,170] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.22 | bwd_microstep: 276.28 | bwd_inner_microstep: 276.27 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1375 +[2025-05-02 01:07:41,535] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 142.18 | bwd_microstep: 207.99 | bwd_inner_microstep: 207.89 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.18 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 347 +[2025-05-02 01:07:41,746] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 78.31 | bwd_microstep: 118.78 | bwd_inner_microstep: 118.47 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-02 01:07:42,223] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.20 | bwd_microstep: 273.34 | bwd_inner_microstep: 273.33 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1096 +[2025-05-02 01:07:42,515] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 116.72 | bwd_microstep: 161.45 | bwd_inner_microstep: 161.25 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 01:07:42,992] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.35 | bwd_microstep: 272.85 | bwd_inner_microstep: 272.83 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 01:07:43,472] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.93 | bwd_microstep: 272.70 | bwd_inner_microstep: 272.68 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:07:43,953] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.16 | bwd_microstep: 272.35 | bwd_inner_microstep: 272.33 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:07:44,433] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.95 | bwd_microstep: 272.18 | bwd_inner_microstep: 272.16 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:07:44,910] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.40 | bwd_microstep: 271.37 | bwd_inner_microstep: 271.35 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 317 +[2025-05-02 01:07:45,154] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.21 | bwd_microstep: 129.71 | bwd_inner_microstep: 129.41 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 01:07:45,633] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.81 | bwd_microstep: 272.11 | bwd_inner_microstep: 272.09 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:07:46,110] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.83 | bwd_microstep: 271.02 | bwd_inner_microstep: 271.00 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 318 +[2025-05-02 01:07:46,343] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 89.50 | bwd_microstep: 126.15 | bwd_inner_microstep: 125.90 | bwd_allreduce_microstep: 0.10 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:07:46,921] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.10 | optimizer_step: 16.93 +[2025-05-02 01:07:46,921] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.45 | bwd_microstep: 348.22 | bwd_inner_microstep: 271.64 | bwd_allreduce_microstep: 76.53 | step_microstep: 24.69 +[2025-05-02 01:07:46,923] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2594.01 | bwd: 3819.36 | bwd_inner: 3741.49 | bwd_allreduce: 77.09 | step: 25.99 + 12%|█▏ | 1023/8720 [2:52:20<14:50:39, 6.94s/it] {'loss': 0.491, 'grad_norm': 7.045907497406006, 'learning_rate': 9.801582401955408e-06, 'epoch': 1.17} + 12%|█▏ | 1023/8720 [2:52:20<14:50:39, 6.94s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 01:07:47,404] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.32 | bwd_microstep: 270.25 | bwd_inner_microstep: 270.23 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1493 +[2025-05-02 01:07:47,801] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 149.25 | bwd_microstep: 231.30 | bwd_inner_microstep: 231.29 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1389 +[2025-05-02 01:07:48,168] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.33 | bwd_microstep: 209.07 | bwd_inner_microstep: 209.05 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1903 +[2025-05-02 01:07:48,649] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.94 | bwd_microstep: 275.81 | bwd_inner_microstep: 275.79 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1894 +[2025-05-02 01:07:49,129] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.10 | bwd_microstep: 275.17 | bwd_inner_microstep: 275.15 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1886 +[2025-05-02 01:07:49,608] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.45 | bwd_microstep: 274.52 | bwd_inner_microstep: 274.50 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-02 01:07:50,085] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.20 | bwd_microstep: 273.51 | bwd_inner_microstep: 273.49 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-02 01:07:50,563] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.06 | bwd_microstep: 273.78 | bwd_inner_microstep: 273.76 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 836 +[2025-05-02 01:07:50,793] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 90.86 | bwd_microstep: 125.95 | bwd_inner_microstep: 125.93 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 01:07:51,270] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.48 | bwd_microstep: 273.21 | bwd_inner_microstep: 273.19 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:07:51,746] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.82 | bwd_microstep: 272.56 | bwd_inner_microstep: 272.55 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:07:52,222] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.45 | bwd_microstep: 272.76 | bwd_inner_microstep: 272.75 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:07:52,699] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.02 | bwd_microstep: 272.36 | bwd_inner_microstep: 272.34 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 01:07:53,174] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.74 | bwd_microstep: 271.15 | bwd_inner_microstep: 271.13 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 831 +[2025-05-02 01:07:53,418] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.16 | bwd_microstep: 129.92 | bwd_inner_microstep: 129.72 | bwd_allreduce_microstep: 0.08 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:07:53,995] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.11 | optimizer_step: 17.24 +[2025-05-02 01:07:53,995] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.90 | bwd_microstep: 348.24 | bwd_inner_microstep: 271.50 | bwd_allreduce_microstep: 76.69 | step_microstep: 24.92 +[2025-05-02 01:07:53,997] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2740.75 | bwd: 4049.59 | bwd_inner: 3972.40 | bwd_allreduce: 76.84 | step: 25.74 + 12%|█▏ | 1024/8720 [2:52:27<14:55:35, 6.98s/it] {'loss': 1.1032, 'grad_norm': 9.273268699645996, 'learning_rate': 9.801064081928862e-06, 'epoch': 1.17} + 12%|█▏ | 1024/8720 [2:52:27<14:55:35, 6.98s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:07:54,477] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.70 | bwd_microstep: 270.38 | bwd_inner_microstep: 270.37 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2013 +[2025-05-02 01:07:54,991] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 199.84 | bwd_microstep: 296.25 | bwd_inner_microstep: 296.24 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 941 +[2025-05-02 01:07:55,256] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 101.94 | bwd_microstep: 147.05 | bwd_inner_microstep: 147.01 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 345 +[2025-05-02 01:07:55,463] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 74.70 | bwd_microstep: 117.81 | bwd_inner_microstep: 117.64 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:07:55,940] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.79 | bwd_microstep: 272.41 | bwd_inner_microstep: 272.39 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:07:56,415] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.73 | bwd_microstep: 272.24 | bwd_inner_microstep: 272.22 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:07:56,890] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.47 | bwd_microstep: 272.21 | bwd_inner_microstep: 272.20 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:07:57,367] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.30 | bwd_microstep: 272.44 | bwd_inner_microstep: 272.42 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 323 +[2025-05-02 01:07:57,572] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 73.64 | bwd_microstep: 117.33 | bwd_inner_microstep: 117.19 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 01:07:58,046] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.29 | bwd_microstep: 271.31 | bwd_inner_microstep: 271.29 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:07:58,520] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.50 | bwd_microstep: 271.18 | bwd_inner_microstep: 271.16 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:07:58,995] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.73 | bwd_microstep: 271.07 | bwd_inner_microstep: 271.05 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 01:07:59,468] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.45 | bwd_microstep: 270.94 | bwd_inner_microstep: 270.92 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 01:07:59,943] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.01 | bwd_microstep: 271.11 | bwd_inner_microstep: 271.09 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 314 +[2025-05-02 01:08:00,142] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 67.85 | bwd_microstep: 117.98 | bwd_inner_microstep: 117.75 | bwd_allreduce_microstep: 0.08 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1849 +[2025-05-02 01:08:00,705] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.04 | optimizer_gradients: 2.10 | optimizer_step: 16.93 +[2025-05-02 01:08:00,706] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.25 | bwd_microstep: 338.04 | bwd_inner_microstep: 271.33 | bwd_allreduce_microstep: 66.66 | step_microstep: 23.82 +[2025-05-02 01:08:00,707] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2581.88 | bwd: 3849.81 | bwd_inner: 3782.43 | bwd_allreduce: 66.89 | step: 24.66 + 12%|█▏ | 1025/8720 [2:52:34<14:44:57, 6.90s/it] {'loss': 0.3419, 'grad_norm': 6.678262710571289, 'learning_rate': 9.800545099530442e-06, 'epoch': 1.18} + 12%|█▏ | 1025/8720 [2:52:34<14:44:57, 6.90s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 364 +[2025-05-02 01:08:00,916] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 71.41 | bwd_microstep: 119.14 | bwd_inner_microstep: 119.01 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1948 +[2025-05-02 01:08:01,414] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 194.70 | bwd_microstep: 289.01 | bwd_inner_microstep: 288.99 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1890 +[2025-05-02 01:08:01,892] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.30 | bwd_microstep: 274.36 | bwd_inner_microstep: 274.35 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1883 +[2025-05-02 01:08:02,370] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.89 | bwd_microstep: 273.83 | bwd_inner_microstep: 273.81 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-02 01:08:02,848] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.38 | bwd_microstep: 274.11 | bwd_inner_microstep: 274.09 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 337 +[2025-05-02 01:08:03,057] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 78.07 | bwd_microstep: 116.60 | bwd_inner_microstep: 116.47 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-02 01:08:03,533] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.72 | bwd_microstep: 273.61 | bwd_inner_microstep: 273.60 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 01:08:04,011] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.27 | bwd_microstep: 272.81 | bwd_inner_microstep: 272.79 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:08:04,486] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.16 | bwd_microstep: 272.37 | bwd_inner_microstep: 272.36 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 01:08:04,963] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.97 | bwd_microstep: 272.71 | bwd_inner_microstep: 272.69 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 01:08:05,440] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.78 | bwd_microstep: 273.21 | bwd_inner_microstep: 273.19 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 01:08:05,920] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.92 | bwd_microstep: 272.83 | bwd_inner_microstep: 272.82 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:08:06,399] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.71 | bwd_microstep: 272.59 | bwd_inner_microstep: 272.57 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:08:06,877] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.28 | bwd_microstep: 272.19 | bwd_inner_microstep: 272.17 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:08:07,352] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.68 | bwd_microstep: 271.19 | bwd_inner_microstep: 271.17 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:08:07,925] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.04 | optimizer_gradients: 2.11 | optimizer_step: 16.90 +[2025-05-02 01:08:07,926] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.48 | bwd_microstep: 344.24 | bwd_inner_microstep: 271.53 | bwd_allreduce_microstep: 72.67 | step_microstep: 23.82 +[2025-05-02 01:08:07,927] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2793.42 | bwd: 4144.84 | bwd_inner: 4071.65 | bwd_allreduce: 72.84 | step: 24.57 + 12%|█▏ | 1026/8720 [2:52:41<14:57:06, 7.00s/it] {'loss': 0.9713, 'grad_norm': 8.151395797729492, 'learning_rate': 9.800025454831752e-06, 'epoch': 1.18} + 12%|█▏ | 1026/8720 [2:52:41<14:57:06, 7.00s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1916 +[2025-05-02 01:08:08,413] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 191.07 | bwd_microstep: 275.29 | bwd_inner_microstep: 275.28 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1910 +[2025-05-02 01:08:08,892] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.83 | bwd_microstep: 276.00 | bwd_inner_microstep: 275.99 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1898 +[2025-05-02 01:08:09,373] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.11 | bwd_microstep: 275.72 | bwd_inner_microstep: 275.70 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1883 +[2025-05-02 01:08:09,853] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.65 | bwd_microstep: 274.14 | bwd_inner_microstep: 274.12 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-02 01:08:10,330] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.19 | bwd_microstep: 274.00 | bwd_inner_microstep: 273.98 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-02 01:08:10,810] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.43 | bwd_microstep: 273.53 | bwd_inner_microstep: 273.51 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-02 01:08:11,289] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.29 | bwd_microstep: 272.91 | bwd_inner_microstep: 272.89 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 01:08:11,770] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.17 | bwd_microstep: 272.59 | bwd_inner_microstep: 272.57 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:08:12,250] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.75 | bwd_microstep: 272.33 | bwd_inner_microstep: 272.31 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 01:08:12,727] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.46 | bwd_microstep: 272.51 | bwd_inner_microstep: 272.50 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 835 +[2025-05-02 01:08:12,966] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.28 | bwd_microstep: 125.88 | bwd_inner_microstep: 125.70 | bwd_allreduce_microstep: 0.09 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:08:13,445] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.59 | bwd_microstep: 272.33 | bwd_inner_microstep: 272.31 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:08:13,925] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.20 | bwd_microstep: 272.08 | bwd_inner_microstep: 272.07 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 01:08:14,403] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.34 | bwd_microstep: 270.97 | bwd_inner_microstep: 270.96 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 01:08:14,881] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.19 | bwd_microstep: 270.91 | bwd_inner_microstep: 270.89 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2005 +[2025-05-02 01:08:15,496] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.14 | optimizer_step: 17.11 +[2025-05-02 01:08:15,497] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 198.99 | bwd_microstep: 371.81 | bwd_inner_microstep: 295.08 | bwd_allreduce_microstep: 76.68 | step_microstep: 25.00 +[2025-05-02 01:08:15,498] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2933.19 | bwd: 4323.04 | bwd_inner: 4245.86 | bwd_allreduce: 76.82 | step: 25.78 + 12%|█▏ | 1027/8720 [2:52:49<15:19:13, 7.17s/it] {'loss': 1.1113, 'grad_norm': 7.345034122467041, 'learning_rate': 9.799505147904482e-06, 'epoch': 1.18} + 12%|█▏ | 1027/8720 [2:52:49<15:19:13, 7.17s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1921 +[2025-05-02 01:08:16,003] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 194.90 | bwd_microstep: 286.44 | bwd_inner_microstep: 286.43 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 865 +[2025-05-02 01:08:16,253] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 98.64 | bwd_microstep: 133.80 | bwd_inner_microstep: 133.70 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-02 01:08:16,736] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.13 | bwd_microstep: 274.54 | bwd_inner_microstep: 274.52 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-02 01:08:17,221] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.06 | bwd_microstep: 274.32 | bwd_inner_microstep: 274.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-02 01:08:17,708] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.71 | bwd_microstep: 274.44 | bwd_inner_microstep: 274.42 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 848 +[2025-05-02 01:08:17,957] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 96.21 | bwd_microstep: 132.30 | bwd_inner_microstep: 132.23 | bwd_allreduce_microstep: 0.03 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 01:08:18,437] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.25 | bwd_microstep: 273.30 | bwd_inner_microstep: 273.28 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-02 01:08:18,922] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.05 | bwd_microstep: 274.15 | bwd_inner_microstep: 274.14 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 835 +[2025-05-02 01:08:19,167] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 98.89 | bwd_microstep: 125.79 | bwd_inner_microstep: 125.65 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 01:08:19,649] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.54 | bwd_microstep: 273.22 | bwd_inner_microstep: 273.21 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 01:08:20,129] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.86 | bwd_microstep: 273.35 | bwd_inner_microstep: 273.34 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:08:20,610] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.64 | bwd_microstep: 273.01 | bwd_inner_microstep: 273.00 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:08:21,092] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.70 | bwd_microstep: 273.07 | bwd_inner_microstep: 273.06 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 01:08:21,571] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.52 | bwd_microstep: 272.67 | bwd_inner_microstep: 272.66 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:08:22,050] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.58 | bwd_microstep: 272.92 | bwd_inner_microstep: 272.90 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:08:22,615] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.04 | optimizer_gradients: 2.10 | optimizer_step: 16.91 +[2025-05-02 01:08:22,615] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.53 | bwd_microstep: 338.60 | bwd_inner_microstep: 272.12 | bwd_allreduce_microstep: 66.43 | step_microstep: 23.75 +[2025-05-02 01:08:22,616] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2754.80 | bwd: 4026.01 | bwd_inner: 3958.94 | bwd_allreduce: 66.70 | step: 24.77 + 12%|█▏ | 1028/8720 [2:52:56<15:17:02, 7.15s/it] {'loss': 0.7218, 'grad_norm': 5.972289562225342, 'learning_rate': 9.798984178820417e-06, 'epoch': 1.18} + 12%|█▏ | 1028/8720 [2:52:56<15:17:02, 7.15s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 01:08:23,096] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.96 | bwd_microstep: 271.19 | bwd_inner_microstep: 271.18 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1889 +[2025-05-02 01:08:23,575] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.21 | bwd_microstep: 275.52 | bwd_inner_microstep: 275.50 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1886 +[2025-05-02 01:08:24,056] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.03 | bwd_microstep: 275.03 | bwd_inner_microstep: 275.01 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 01:08:24,537] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.16 | bwd_microstep: 274.06 | bwd_inner_microstep: 274.04 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-02 01:08:25,020] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.20 | bwd_microstep: 274.43 | bwd_inner_microstep: 274.41 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 01:08:25,500] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.46 | bwd_microstep: 273.28 | bwd_inner_microstep: 273.26 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1354 +[2025-05-02 01:08:25,870] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 143.26 | bwd_microstep: 206.22 | bwd_inner_microstep: 206.15 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 01:08:26,352] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.44 | bwd_microstep: 273.23 | bwd_inner_microstep: 273.21 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 330 +[2025-05-02 01:08:26,583] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 91.92 | bwd_microstep: 120.43 | bwd_inner_microstep: 120.29 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 01:08:27,062] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.53 | bwd_microstep: 273.03 | bwd_inner_microstep: 273.01 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 325 +[2025-05-02 01:08:27,294] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.45 | bwd_microstep: 118.54 | bwd_inner_microstep: 118.38 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:08:27,773] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.73 | bwd_microstep: 272.91 | bwd_inner_microstep: 272.89 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:08:28,256] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.66 | bwd_microstep: 273.07 | bwd_inner_microstep: 273.05 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 318 +[2025-05-02 01:08:28,486] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 97.26 | bwd_microstep: 114.63 | bwd_inner_microstep: 114.45 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:08:28,964] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.85 | bwd_microstep: 272.57 | bwd_inner_microstep: 272.55 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.16 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:08:29,549] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.23 | optimizer_step: 17.23 +[2025-05-02 01:08:29,549] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.05 | bwd_microstep: 352.41 | bwd_inner_microstep: 272.11 | bwd_allreduce_microstep: 80.23 | step_microstep: 25.28 +[2025-05-02 01:08:29,550] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2694.79 | bwd: 3920.63 | bwd_inner: 3839.61 | bwd_allreduce: 80.52 | step: 26.37 + 12%|█▏ | 1029/8720 [2:53:03<15:08:34, 7.09s/it] {'loss': 0.8028, 'grad_norm': 6.481639862060547, 'learning_rate': 9.798462547651431e-06, 'epoch': 1.18} + 12%|█▏ | 1029/8720 [2:53:03<15:08:34, 7.09s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1849 +[2025-05-02 01:08:30,033] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.85 | bwd_microstep: 270.09 | bwd_inner_microstep: 270.07 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2008 +[2025-05-02 01:08:30,548] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 200.42 | bwd_microstep: 294.98 | bwd_inner_microstep: 294.97 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 01:08:31,028] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.65 | bwd_microstep: 273.02 | bwd_inner_microstep: 273.01 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.13 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1889 +[2025-05-02 01:08:31,510] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.89 | bwd_microstep: 274.59 | bwd_inner_microstep: 274.57 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-02 01:08:31,990] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.81 | bwd_microstep: 273.47 | bwd_inner_microstep: 273.46 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-02 01:08:32,471] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.81 | bwd_microstep: 273.53 | bwd_inner_microstep: 273.51 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 340 +[2025-05-02 01:08:32,691] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 83.60 | bwd_microstep: 120.12 | bwd_inner_microstep: 119.82 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.23 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 01:08:33,171] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.16 | bwd_microstep: 272.75 | bwd_inner_microstep: 272.74 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.15 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 01:08:33,654] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.19 | bwd_microstep: 273.05 | bwd_inner_microstep: 273.03 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-02 01:08:34,130] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.23 | bwd_microstep: 273.17 | bwd_inner_microstep: 273.16 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1105 +[2025-05-02 01:08:34,429] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 119.41 | bwd_microstep: 161.36 | bwd_inner_microstep: 161.28 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 01:08:34,904] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.95 | bwd_microstep: 272.95 | bwd_inner_microstep: 272.94 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 837 +[2025-05-02 01:08:35,136] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 91.41 | bwd_microstep: 125.96 | bwd_inner_microstep: 125.83 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 01:08:35,612] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.99 | bwd_microstep: 272.72 | bwd_inner_microstep: 272.70 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 01:08:36,094] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.32 | bwd_microstep: 272.87 | bwd_inner_microstep: 272.85 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:08:36,661] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.25 | optimizer_step: 17.09 +[2025-05-02 01:08:36,662] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.96 | bwd_microstep: 339.11 | bwd_inner_microstep: 272.90 | bwd_allreduce_microstep: 66.16 | step_microstep: 24.39 +[2025-05-02 01:08:36,663] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2760.31 | bwd: 4043.83 | bwd_inner: 3976.90 | bwd_allreduce: 66.45 | step: 25.57 + 12%|█▏ | 1030/8720 [2:53:10<15:09:20, 7.09s/it] {'loss': 0.752, 'grad_norm': 3.539091110229492, 'learning_rate': 9.79794025446949e-06, 'epoch': 1.18} + 12%|█▏ | 1030/8720 [2:53:10<15:09:20, 7.09s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:08:37,142] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.80 | bwd_microstep: 271.32 | bwd_inner_microstep: 271.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 384 +[2025-05-02 01:08:37,356] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 77.41 | bwd_microstep: 123.35 | bwd_inner_microstep: 123.21 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 865 +[2025-05-02 01:08:37,610] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 106.18 | bwd_microstep: 133.19 | bwd_inner_microstep: 133.17 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1890 +[2025-05-02 01:08:38,090] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.35 | bwd_microstep: 274.70 | bwd_inner_microstep: 274.68 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-02 01:08:38,568] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.70 | bwd_microstep: 274.29 | bwd_inner_microstep: 274.27 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-02 01:08:39,045] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.48 | bwd_microstep: 273.34 | bwd_inner_microstep: 273.32 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 01:08:39,522] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.33 | bwd_microstep: 273.01 | bwd_inner_microstep: 273.00 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-02 01:08:39,999] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.78 | bwd_microstep: 273.02 | bwd_inner_microstep: 273.01 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 01:08:40,477] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.80 | bwd_microstep: 273.15 | bwd_inner_microstep: 273.13 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 01:08:40,956] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.43 | bwd_microstep: 273.47 | bwd_inner_microstep: 273.46 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 01:08:41,434] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.56 | bwd_microstep: 272.90 | bwd_inner_microstep: 272.89 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 01:08:41,913] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.41 | bwd_microstep: 272.96 | bwd_inner_microstep: 272.94 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.13 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:08:42,392] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.93 | bwd_microstep: 272.75 | bwd_inner_microstep: 272.73 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.17 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:08:42,873] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.17 | bwd_microstep: 272.43 | bwd_inner_microstep: 272.42 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 01:08:43,352] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.94 | bwd_microstep: 272.92 | bwd_inner_microstep: 272.90 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:08:43,932] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.17 | optimizer_step: 17.10 +[2025-05-02 01:08:43,933] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.60 | bwd_microstep: 348.17 | bwd_inner_microstep: 271.63 | bwd_allreduce_microstep: 76.49 | step_microstep: 24.85 +[2025-05-02 01:08:43,934] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2823.54 | bwd: 4155.02 | bwd_inner: 4078.08 | bwd_allreduce: 76.62 | step: 25.87 + 12%|█▏ | 1031/8720 [2:53:17<15:16:02, 7.15s/it] {'loss': 0.7323, 'grad_norm': 5.453628063201904, 'learning_rate': 9.797417299346651e-06, 'epoch': 1.18} + 12%|█▏ | 1031/8720 [2:53:17<15:16:02, 7.15s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:08:44,414] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.79 | bwd_microstep: 270.32 | bwd_inner_microstep: 270.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1934 +[2025-05-02 01:08:44,912] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.92 | bwd_microstep: 287.56 | bwd_inner_microstep: 287.55 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 368 +[2025-05-02 01:08:45,120] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 76.26 | bwd_microstep: 118.07 | bwd_inner_microstep: 117.84 | bwd_allreduce_microstep: 0.09 | step_microstep: 0.09 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 346 +[2025-05-02 01:08:45,329] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 79.85 | bwd_microstep: 116.37 | bwd_inner_microstep: 116.25 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.08 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 340 +[2025-05-02 01:08:45,529] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 67.40 | bwd_microstep: 119.63 | bwd_inner_microstep: 119.50 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-02 01:08:46,007] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.83 | bwd_microstep: 273.66 | bwd_inner_microstep: 273.64 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1371 +[2025-05-02 01:08:46,372] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.32 | bwd_microstep: 207.52 | bwd_inner_microstep: 207.39 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-02 01:08:46,850] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.49 | bwd_microstep: 273.12 | bwd_inner_microstep: 273.10 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 01:08:47,327] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.56 | bwd_microstep: 273.23 | bwd_inner_microstep: 273.22 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.17 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 01:08:47,805] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.45 | bwd_microstep: 272.78 | bwd_inner_microstep: 272.77 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:08:48,281] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.22 | bwd_microstep: 272.40 | bwd_inner_microstep: 272.39 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:08:48,761] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.82 | bwd_microstep: 272.22 | bwd_inner_microstep: 272.20 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 325 +[2025-05-02 01:08:48,978] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 82.45 | bwd_microstep: 118.98 | bwd_inner_microstep: 118.64 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 01:08:49,456] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.54 | bwd_microstep: 272.41 | bwd_inner_microstep: 272.39 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.07 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 01:08:49,936] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.94 | bwd_microstep: 272.06 | bwd_inner_microstep: 272.04 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:08:50,526] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.14 | optimizer_step: 17.01 +[2025-05-02 01:08:50,526] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.20 | bwd_microstep: 357.15 | bwd_inner_microstep: 272.73 | bwd_allreduce_microstep: 84.37 | step_microstep: 24.43 +[2025-05-02 01:08:50,528] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2523.69 | bwd: 3777.58 | bwd_inner: 3692.10 | bwd_allreduce: 84.81 | step: 25.51 + 12%|█▏ | 1032/8720 [2:53:24<14:54:36, 6.98s/it] {'loss': 0.7529, 'grad_norm': 11.631656646728516, 'learning_rate': 9.796893682355063e-06, 'epoch': 1.18} + 12%|█▏ | 1032/8720 [2:53:24<14:54:36, 6.98s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 317 +[2025-05-02 01:08:50,743] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 78.28 | bwd_microstep: 116.05 | bwd_inner_microstep: 115.89 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1925 +[2025-05-02 01:08:51,242] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 194.47 | bwd_microstep: 287.20 | bwd_inner_microstep: 287.18 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1903 +[2025-05-02 01:08:51,730] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.42 | bwd_microstep: 275.92 | bwd_inner_microstep: 275.90 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-02 01:08:52,208] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.19 | bwd_microstep: 274.26 | bwd_inner_microstep: 274.24 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 346 +[2025-05-02 01:08:52,424] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 80.74 | bwd_microstep: 119.59 | bwd_inner_microstep: 119.33 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1886 +[2025-05-02 01:08:52,901] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.23 | bwd_microstep: 274.34 | bwd_inner_microstep: 274.33 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.14 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 01:08:53,377] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.27 | bwd_microstep: 273.07 | bwd_inner_microstep: 273.05 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-02 01:08:53,854] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.01 | bwd_microstep: 273.40 | bwd_inner_microstep: 273.38 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 01:08:54,331] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.17 | bwd_microstep: 273.01 | bwd_inner_microstep: 272.99 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:08:54,810] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.91 | bwd_microstep: 272.46 | bwd_inner_microstep: 272.44 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:08:55,289] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.98 | bwd_microstep: 272.64 | bwd_inner_microstep: 272.62 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 01:08:55,769] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.98 | bwd_microstep: 272.75 | bwd_inner_microstep: 272.74 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 01:08:56,252] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.72 | bwd_microstep: 272.68 | bwd_inner_microstep: 272.66 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:08:56,730] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.60 | bwd_microstep: 271.01 | bwd_inner_microstep: 270.99 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:08:57,212] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.36 | bwd_microstep: 271.91 | bwd_inner_microstep: 271.90 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 318 +[2025-05-02 01:08:57,574] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.17 | optimizer_step: 17.04 +[2025-05-02 01:08:57,575] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.07 | bwd_microstep: 224.42 | bwd_inner_microstep: 148.10 | bwd_allreduce_microstep: 76.22 | step_microstep: 24.70 +[2025-05-02 01:08:57,576] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2710.01 | bwd: 4024.75 | bwd_inner: 3947.87 | bwd_allreduce: 76.44 | step: 25.65 + 12%|█▏ | 1033/8720 [2:53:31<14:57:02, 7.00s/it] {'loss': 0.8562, 'grad_norm': 6.309861183166504, 'learning_rate': 9.796369403566967e-06, 'epoch': 1.18} + 12%|█▏ | 1033/8720 [2:53:31<14:57:02, 7.00s/it]dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 828 +[2025-05-02 01:08:57,820] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 92.66 | bwd_microstep: 129.78 | bwd_inner_microstep: 129.74 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 371 +[2025-05-02 01:08:58,035] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 81.33 | bwd_microstep: 118.39 | bwd_inner_microstep: 118.07 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1889 +[2025-05-02 01:08:58,514] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.24 | bwd_microstep: 274.21 | bwd_inner_microstep: 274.20 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 01:08:58,995] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.43 | bwd_microstep: 273.13 | bwd_inner_microstep: 273.11 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-02 01:08:59,476] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.27 | bwd_microstep: 273.16 | bwd_inner_microstep: 273.14 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 01:08:59,956] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.21 | bwd_microstep: 272.50 | bwd_inner_microstep: 272.49 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:09:00,436] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.10 | bwd_microstep: 272.44 | bwd_inner_microstep: 272.42 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 01:09:00,916] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.26 | bwd_microstep: 272.61 | bwd_inner_microstep: 272.60 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 01:09:01,393] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.76 | bwd_microstep: 272.36 | bwd_inner_microstep: 272.35 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 326 +[2025-05-02 01:09:01,609] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 81.28 | bwd_microstep: 119.27 | bwd_inner_microstep: 118.96 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:09:02,087] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.86 | bwd_microstep: 272.37 | bwd_inner_microstep: 272.35 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:09:02,567] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.34 | bwd_microstep: 272.29 | bwd_inner_microstep: 272.28 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 01:09:03,047] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.71 | bwd_microstep: 272.72 | bwd_inner_microstep: 272.70 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:09:03,525] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.84 | bwd_microstep: 271.04 | bwd_inner_microstep: 271.02 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 01:09:04,007] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.89 | bwd_microstep: 271.31 | bwd_inner_microstep: 271.30 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 01:09:04,575] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.04 | optimizer_gradients: 2.14 | optimizer_step: 17.10 +[2025-05-02 01:09:04,575] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.77 | bwd_microstep: 338.39 | bwd_inner_microstep: 271.73 | bwd_allreduce_microstep: 66.62 | step_microstep: 24.09 +[2025-05-02 01:09:04,576] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2702.57 | bwd: 3976.08 | bwd_inner: 3908.58 | bwd_allreduce: 66.94 | step: 25.07 + 12%|█▏ | 1034/8720 [2:53:38<14:56:48, 7.00s/it] {'loss': 0.9062, 'grad_norm': 11.610512733459473, 'learning_rate': 9.795844463054695e-06, 'epoch': 1.19} + 12%|█▏ | 1034/8720 [2:53:38<14:56:48, 7.00s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:09:05,057] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.84 | bwd_microstep: 271.46 | bwd_inner_microstep: 271.44 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.14 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 879 +[2025-05-02 01:09:05,299] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.10 | bwd_microstep: 134.88 | bwd_inner_microstep: 134.79 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-02 01:09:05,778] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.48 | bwd_microstep: 274.45 | bwd_inner_microstep: 274.43 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-02 01:09:06,258] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.63 | bwd_microstep: 273.51 | bwd_inner_microstep: 273.49 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 01:09:06,739] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.69 | bwd_microstep: 273.37 | bwd_inner_microstep: 273.35 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 01:09:07,221] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.85 | bwd_microstep: 272.88 | bwd_inner_microstep: 272.86 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 333 +[2025-05-02 01:09:07,445] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 86.83 | bwd_microstep: 119.48 | bwd_inner_microstep: 119.16 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 01:09:07,924] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.56 | bwd_microstep: 272.68 | bwd_inner_microstep: 272.66 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:09:08,403] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.85 | bwd_microstep: 272.38 | bwd_inner_microstep: 272.37 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 835 +[2025-05-02 01:09:08,641] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.05 | bwd_microstep: 125.85 | bwd_inner_microstep: 125.67 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:09:09,118] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.24 | bwd_microstep: 272.26 | bwd_inner_microstep: 272.25 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 01:09:09,596] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.18 | bwd_microstep: 272.26 | bwd_inner_microstep: 272.24 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:09:10,072] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.55 | bwd_microstep: 271.17 | bwd_inner_microstep: 271.15 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:09:10,551] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.89 | bwd_microstep: 272.04 | bwd_inner_microstep: 272.03 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 832 +[2025-05-02 01:09:10,791] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.77 | bwd_microstep: 129.88 | bwd_inner_microstep: 129.86 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1342 +[2025-05-02 01:09:11,243] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 3.04 | optimizer_step: 17.07 +[2025-05-02 01:09:11,243] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 139.43 | bwd_microstep: 271.62 | bwd_inner_microstep: 204.64 | bwd_allreduce_microstep: 66.82 | step_microstep: 25.49 +[2025-05-02 01:09:11,245] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2582.58 | bwd: 3780.24 | bwd_inner: 3712.51 | bwd_allreduce: 67.15 | step: 26.59 + 12%|█▏ | 1035/8720 [2:53:44<14:43:59, 6.90s/it] {'loss': 0.6613, 'grad_norm': 11.721264839172363, 'learning_rate': 9.795318860890666e-06, 'epoch': 1.19} + 12%|█▏ | 1035/8720 [2:53:44<14:43:59, 6.90s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:09:11,725] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.31 | bwd_microstep: 270.33 | bwd_inner_microstep: 270.31 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1405 +[2025-05-02 01:09:12,099] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 143.12 | bwd_microstep: 210.14 | bwd_inner_microstep: 210.13 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1903 +[2025-05-02 01:09:12,579] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.20 | bwd_microstep: 275.89 | bwd_inner_microstep: 275.87 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 350 +[2025-05-02 01:09:12,800] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 80.04 | bwd_microstep: 124.26 | bwd_inner_microstep: 124.09 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.12 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 343 +[2025-05-02 01:09:13,012] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 75.09 | bwd_microstep: 122.92 | bwd_inner_microstep: 122.65 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 01:09:13,493] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.21 | bwd_microstep: 273.21 | bwd_inner_microstep: 273.19 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1883 +[2025-05-02 01:09:13,970] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.12 | bwd_microstep: 273.94 | bwd_inner_microstep: 273.92 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 01:09:14,446] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.45 | bwd_microstep: 273.42 | bwd_inner_microstep: 273.40 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-02 01:09:14,924] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.83 | bwd_microstep: 273.71 | bwd_inner_microstep: 273.69 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:09:15,404] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.03 | bwd_microstep: 272.51 | bwd_inner_microstep: 272.49 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:09:15,880] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.65 | bwd_microstep: 272.38 | bwd_inner_microstep: 272.36 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:09:16,357] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.35 | bwd_microstep: 272.61 | bwd_inner_microstep: 272.59 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 01:09:16,833] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.30 | bwd_microstep: 272.63 | bwd_inner_microstep: 272.62 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:09:17,312] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.74 | bwd_microstep: 271.09 | bwd_inner_microstep: 271.08 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:09:17,786] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.31 | bwd_microstep: 270.93 | bwd_inner_microstep: 270.91 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:09:18,352] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.16 | optimizer_step: 17.05 +[2025-05-02 01:09:18,352] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.77 | bwd_microstep: 337.81 | bwd_inner_microstep: 271.50 | bwd_allreduce_microstep: 66.26 | step_microstep: 24.11 +[2025-05-02 01:09:18,353] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2747.22 | bwd: 4067.82 | bwd_inner: 4000.89 | bwd_allreduce: 66.51 | step: 25.08 + 12%|█▏ | 1036/8720 [2:53:52<14:51:45, 6.96s/it] {'loss': 0.9054, 'grad_norm': 6.746552467346191, 'learning_rate': 9.794792597147397e-06, 'epoch': 1.19} + 12%|█▏ | 1036/8720 [2:53:52<14:51:45, 6.96s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 01:09:18,831] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.63 | bwd_microstep: 270.21 | bwd_inner_microstep: 270.19 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 396 +[2025-05-02 01:09:19,030] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 67.64 | bwd_microstep: 118.07 | bwd_inner_microstep: 117.76 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1906 +[2025-05-02 01:09:19,510] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.64 | bwd_microstep: 275.77 | bwd_inner_microstep: 275.75 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1903 +[2025-05-02 01:09:19,993] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.03 | bwd_microstep: 275.52 | bwd_inner_microstep: 275.51 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1900 +[2025-05-02 01:09:20,477] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.50 | bwd_microstep: 275.57 | bwd_inner_microstep: 275.55 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 01:09:20,960] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.47 | bwd_microstep: 274.08 | bwd_inner_microstep: 274.06 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-02 01:09:21,439] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.95 | bwd_microstep: 273.77 | bwd_inner_microstep: 273.75 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:09:21,918] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.73 | bwd_microstep: 272.61 | bwd_inner_microstep: 272.60 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:09:22,397] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.11 | bwd_microstep: 272.37 | bwd_inner_microstep: 272.36 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 838 +[2025-05-02 01:09:22,641] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.93 | bwd_microstep: 130.06 | bwd_inner_microstep: 129.81 | bwd_allreduce_microstep: 0.14 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:09:23,119] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.95 | bwd_microstep: 272.18 | bwd_inner_microstep: 272.16 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:09:23,597] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.11 | bwd_microstep: 272.43 | bwd_inner_microstep: 272.41 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:09:24,075] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.74 | bwd_microstep: 271.38 | bwd_inner_microstep: 271.37 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:09:24,553] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.50 | bwd_microstep: 272.44 | bwd_inner_microstep: 272.42 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 01:09:25,030] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.08 | bwd_microstep: 271.22 | bwd_inner_microstep: 271.21 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 388 +[2025-05-02 01:09:25,360] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.13 | optimizer_step: 17.07 +[2025-05-02 01:09:25,361] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 81.30 | bwd_microstep: 208.92 | bwd_inner_microstep: 132.56 | bwd_allreduce_microstep: 76.20 | step_microstep: 24.75 +[2025-05-02 01:09:25,362] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2697.98 | bwd: 4006.67 | bwd_inner: 3929.59 | bwd_allreduce: 76.50 | step: 25.72 + 12%|█▏ | 1037/8720 [2:53:59<14:53:27, 6.98s/it] {'loss': 0.9942, 'grad_norm': 14.4953031539917, 'learning_rate': 9.794265671897494e-06, 'epoch': 1.19} + 12%|█▏ | 1037/8720 [2:53:59<14:53:27, 6.98s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1890 +[2025-05-02 01:09:25,847] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.67 | bwd_microstep: 273.64 | bwd_inner_microstep: 273.63 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2053 +[2025-05-02 01:09:26,368] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 201.84 | bwd_microstep: 301.66 | bwd_inner_microstep: 301.64 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1890 +[2025-05-02 01:09:26,848] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.60 | bwd_microstep: 274.33 | bwd_inner_microstep: 274.31 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 362 +[2025-05-02 01:09:27,076] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 89.86 | bwd_microstep: 121.01 | bwd_inner_microstep: 120.82 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-02 01:09:27,556] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.71 | bwd_microstep: 273.74 | bwd_inner_microstep: 273.72 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 01:09:28,036] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.02 | bwd_microstep: 274.06 | bwd_inner_microstep: 274.04 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 338 +[2025-05-02 01:09:28,279] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 106.50 | bwd_microstep: 120.56 | bwd_inner_microstep: 120.40 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1353 +[2025-05-02 01:09:28,642] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.10 | bwd_microstep: 205.74 | bwd_inner_microstep: 205.61 | bwd_allreduce_microstep: 0.04 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 01:09:29,120] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.93 | bwd_microstep: 272.53 | bwd_inner_microstep: 272.51 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 332 +[2025-05-02 01:09:29,360] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 104.16 | bwd_microstep: 116.42 | bwd_inner_microstep: 116.20 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 01:09:29,838] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.13 | bwd_microstep: 272.80 | bwd_inner_microstep: 272.78 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 01:09:30,318] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.71 | bwd_microstep: 272.69 | bwd_inner_microstep: 272.67 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:09:30,794] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.29 | bwd_microstep: 271.01 | bwd_inner_microstep: 270.99 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 01:09:31,271] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.58 | bwd_microstep: 271.04 | bwd_inner_microstep: 271.02 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:09:31,752] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.47 | bwd_microstep: 271.33 | bwd_inner_microstep: 271.31 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 827 +[2025-05-02 01:09:32,097] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.20 | optimizer_step: 17.14 +[2025-05-02 01:09:32,098] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 96.62 | bwd_microstep: 207.33 | bwd_inner_microstep: 130.10 | bwd_allreduce_microstep: 77.14 | step_microstep: 25.10 +[2025-05-02 01:09:32,099] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2624.80 | bwd: 3799.99 | bwd_inner: 3721.95 | bwd_allreduce: 77.44 | step: 26.02 + 12%|█▏ | 1038/8720 [2:54:05<14:44:07, 6.91s/it] {'loss': 0.905, 'grad_norm': 5.610448837280273, 'learning_rate': 9.79373808521365e-06, 'epoch': 1.19} + 12%|█▏ | 1038/8720 [2:54:05<14:44:07, 6.91s/it]dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1130 +[2025-05-02 01:09:32,401] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 115.64 | bwd_microstep: 163.26 | bwd_inner_microstep: 163.23 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2141 +[2025-05-02 01:09:32,938] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 204.24 | bwd_microstep: 315.08 | bwd_inner_microstep: 315.06 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 879 +[2025-05-02 01:09:33,184] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.69 | bwd_microstep: 135.62 | bwd_inner_microstep: 135.24 | bwd_allreduce_microstep: 0.16 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-02 01:09:33,665] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.32 | bwd_microstep: 274.04 | bwd_inner_microstep: 274.02 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1104 +[2025-05-02 01:09:33,958] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 117.74 | bwd_microstep: 161.57 | bwd_inner_microstep: 161.50 | bwd_allreduce_microstep: 0.04 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 01:09:34,437] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.10 | bwd_microstep: 273.85 | bwd_inner_microstep: 273.84 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1352 +[2025-05-02 01:09:34,800] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.76 | bwd_microstep: 205.86 | bwd_inner_microstep: 205.79 | bwd_allreduce_microstep: 0.03 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:09:35,276] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.28 | bwd_microstep: 272.71 | bwd_inner_microstep: 272.69 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.13 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 845 +[2025-05-02 01:09:35,520] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.87 | bwd_microstep: 132.25 | bwd_inner_microstep: 132.02 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 01:09:35,996] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.40 | bwd_microstep: 272.81 | bwd_inner_microstep: 272.79 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 01:09:36,473] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.86 | bwd_microstep: 272.70 | bwd_inner_microstep: 272.69 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 6, images per sample: 6.0, dynamic token length: 1607 +[2025-05-02 01:09:36,896] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 163.71 | bwd_microstep: 243.17 | bwd_inner_microstep: 243.16 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.21 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:09:37,374] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.11 | bwd_microstep: 272.49 | bwd_inner_microstep: 272.48 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:09:37,851] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.85 | bwd_microstep: 272.54 | bwd_inner_microstep: 272.52 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 831 +[2025-05-02 01:09:38,088] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 92.76 | bwd_microstep: 130.10 | bwd_inner_microstep: 130.02 | bwd_allreduce_microstep: 0.04 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:09:38,653] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.72 | optimizer_step: 17.12 +[2025-05-02 01:09:38,653] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.06 | bwd_microstep: 337.90 | bwd_inner_microstep: 271.45 | bwd_allreduce_microstep: 66.41 | step_microstep: 24.99 +[2025-05-02 01:09:38,654] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2533.09 | bwd: 3736.09 | bwd_inner: 3668.60 | bwd_allreduce: 66.85 | step: 26.33 + 12%|█▏ | 1039/8720 [2:54:12<14:30:28, 6.80s/it] {'loss': 0.7095, 'grad_norm': 7.813261032104492, 'learning_rate': 9.793209837168655e-06, 'epoch': 1.19} + 12%|█▏ | 1039/8720 [2:54:12<14:30:28, 6.80s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-02 01:09:39,136] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.58 | bwd_microstep: 272.57 | bwd_inner_microstep: 272.55 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1986 +[2025-05-02 01:09:39,642] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 197.90 | bwd_microstep: 292.91 | bwd_inner_microstep: 292.89 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1948 +[2025-05-02 01:09:40,142] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.36 | bwd_microstep: 288.94 | bwd_inner_microstep: 288.92 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1933 +[2025-05-02 01:09:40,642] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 194.90 | bwd_microstep: 287.82 | bwd_inner_microstep: 287.80 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1909 +[2025-05-02 01:09:41,126] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.54 | bwd_microstep: 276.09 | bwd_inner_microstep: 276.08 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-02 01:09:41,612] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.22 | bwd_microstep: 273.46 | bwd_inner_microstep: 273.44 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 856 +[2025-05-02 01:09:41,860] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 96.56 | bwd_microstep: 133.07 | bwd_inner_microstep: 132.78 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 01:09:42,339] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.56 | bwd_microstep: 273.27 | bwd_inner_microstep: 273.25 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 01:09:42,820] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.82 | bwd_microstep: 273.23 | bwd_inner_microstep: 273.21 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 850 +[2025-05-02 01:09:43,064] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.01 | bwd_microstep: 132.40 | bwd_inner_microstep: 132.31 | bwd_allreduce_microstep: 0.04 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 01:09:43,543] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.91 | bwd_microstep: 273.19 | bwd_inner_microstep: 273.17 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 01:09:44,023] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.96 | bwd_microstep: 272.57 | bwd_inner_microstep: 272.55 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:09:44,501] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.92 | bwd_microstep: 272.29 | bwd_inner_microstep: 272.28 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:09:44,979] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.49 | bwd_microstep: 270.96 | bwd_inner_microstep: 270.95 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1345 +[2025-05-02 01:09:45,343] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 139.55 | bwd_microstep: 205.41 | bwd_inner_microstep: 205.40 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:09:45,922] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.13 | optimizer_step: 16.97 +[2025-05-02 01:09:45,922] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.91 | bwd_microstep: 349.05 | bwd_inner_microstep: 272.79 | bwd_allreduce_microstep: 76.21 | step_microstep: 24.57 +[2025-05-02 01:09:45,924] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2800.80 | bwd: 4147.28 | bwd_inner: 4070.41 | bwd_allreduce: 76.46 | step: 25.53 + 12%|█▏ | 1040/8720 [2:54:19<14:48:27, 6.94s/it] {'loss': 0.9553, 'grad_norm': 7.138336658477783, 'learning_rate': 9.792680927835388e-06, 'epoch': 1.19} + 12%|█▏ | 1040/8720 [2:54:19<14:48:27, 6.94s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1893 +[2025-05-02 01:09:46,410] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.52 | bwd_microstep: 274.28 | bwd_inner_microstep: 274.27 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1910 +[2025-05-02 01:09:46,894] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.55 | bwd_microstep: 276.41 | bwd_inner_microstep: 276.39 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-02 01:09:47,372] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.75 | bwd_microstep: 274.02 | bwd_inner_microstep: 274.01 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-02 01:09:47,850] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.94 | bwd_microstep: 273.48 | bwd_inner_microstep: 273.47 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 860 +[2025-05-02 01:09:48,094] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.43 | bwd_microstep: 133.22 | bwd_inner_microstep: 133.20 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-02 01:09:48,573] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.29 | bwd_microstep: 274.21 | bwd_inner_microstep: 274.19 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-02 01:09:49,052] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.24 | bwd_microstep: 273.45 | bwd_inner_microstep: 273.43 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 01:09:49,533] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.14 | bwd_microstep: 273.31 | bwd_inner_microstep: 273.29 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-02 01:09:50,014] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.83 | bwd_microstep: 273.13 | bwd_inner_microstep: 273.11 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 01:09:50,494] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.22 | bwd_microstep: 272.66 | bwd_inner_microstep: 272.64 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:09:50,974] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.53 | bwd_microstep: 272.12 | bwd_inner_microstep: 272.10 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 320 +[2025-05-02 01:09:51,202] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 90.61 | bwd_microstep: 118.40 | bwd_inner_microstep: 118.16 | bwd_allreduce_microstep: 0.09 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:09:51,677] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.17 | bwd_microstep: 270.93 | bwd_inner_microstep: 270.91 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:09:52,153] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.34 | bwd_microstep: 271.02 | bwd_inner_microstep: 271.00 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 01:09:52,631] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.70 | bwd_microstep: 271.15 | bwd_inner_microstep: 271.13 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 832 +[2025-05-02 01:09:52,978] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.16 | optimizer_step: 18.07 +[2025-05-02 01:09:52,978] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.67 | bwd_microstep: 211.02 | bwd_inner_microstep: 134.52 | bwd_allreduce_microstep: 76.39 | step_microstep: 25.33 +[2025-05-02 01:09:52,979] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2733.57 | bwd: 4012.82 | bwd_inner: 3935.92 | bwd_allreduce: 76.52 | step: 26.17 + 12%|█▏ | 1041/8720 [2:54:26<14:52:40, 6.97s/it] {'loss': 0.7429, 'grad_norm': 5.540779113769531, 'learning_rate': 9.79215135728682e-06, 'epoch': 1.19} + 12%|█▏ | 1041/8720 [2:54:26<14:52:40, 6.97s/it]dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1342 +[2025-05-02 01:09:53,343] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 139.80 | bwd_microstep: 203.91 | bwd_inner_microstep: 203.89 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1408 +[2025-05-02 01:09:53,712] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 143.95 | bwd_microstep: 210.48 | bwd_inner_microstep: 210.39 | bwd_allreduce_microstep: 0.04 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1922 +[2025-05-02 01:09:54,209] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 194.94 | bwd_microstep: 286.94 | bwd_inner_microstep: 286.92 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1908 +[2025-05-02 01:09:54,691] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.39 | bwd_microstep: 276.24 | bwd_inner_microstep: 276.22 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 855 +[2025-05-02 01:09:54,937] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 98.24 | bwd_microstep: 133.03 | bwd_inner_microstep: 132.80 | bwd_allreduce_microstep: 0.14 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 01:09:55,415] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.46 | bwd_microstep: 273.27 | bwd_inner_microstep: 273.26 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 01:09:55,894] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.73 | bwd_microstep: 272.91 | bwd_inner_microstep: 272.89 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 332 +[2025-05-02 01:09:56,116] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 80.57 | bwd_microstep: 126.60 | bwd_inner_microstep: 126.45 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 01:09:56,593] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.14 | bwd_microstep: 272.57 | bwd_inner_microstep: 272.56 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:09:57,070] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.34 | bwd_microstep: 272.15 | bwd_inner_microstep: 272.13 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:09:57,546] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.81 | bwd_microstep: 272.48 | bwd_inner_microstep: 272.46 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:09:58,021] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.34 | bwd_microstep: 271.39 | bwd_inner_microstep: 271.37 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 01:09:58,495] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.65 | bwd_microstep: 270.90 | bwd_inner_microstep: 270.88 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:09:58,970] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.99 | bwd_microstep: 271.09 | bwd_inner_microstep: 271.07 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 01:09:59,445] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.15 | bwd_microstep: 271.13 | bwd_inner_microstep: 271.11 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 01:10:00,010] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.25 | optimizer_step: 17.43 +[2025-05-02 01:10:00,011] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.92 | bwd_microstep: 338.13 | bwd_inner_microstep: 271.53 | bwd_allreduce_microstep: 66.55 | step_microstep: 24.78 +[2025-05-02 01:10:00,012] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2728.13 | bwd: 4023.26 | bwd_inner: 3955.97 | bwd_allreduce: 66.87 | step: 25.63 + 12%|█▏ | 1042/8720 [2:54:33<14:54:46, 6.99s/it] {'loss': 0.837, 'grad_norm': 10.163107872009277, 'learning_rate': 9.79162112559601e-06, 'epoch': 1.19} + 12%|█▏ | 1042/8720 [2:54:33<14:54:46, 6.99s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2293 +[2025-05-02 01:10:00,567] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 209.87 | bwd_microstep: 325.62 | bwd_inner_microstep: 325.60 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 383 +[2025-05-02 01:10:00,770] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 72.86 | bwd_microstep: 116.45 | bwd_inner_microstep: 116.12 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 01:10:01,247] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.69 | bwd_microstep: 273.23 | bwd_inner_microstep: 273.21 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-02 01:10:01,726] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.58 | bwd_microstep: 273.83 | bwd_inner_microstep: 273.81 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-02 01:10:02,206] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.45 | bwd_microstep: 274.62 | bwd_inner_microstep: 274.60 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1361 +[2025-05-02 01:10:02,569] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.59 | bwd_microstep: 206.86 | bwd_inner_microstep: 206.84 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 01:10:03,047] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.58 | bwd_microstep: 273.48 | bwd_inner_microstep: 273.46 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 01:10:03,527] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.03 | bwd_microstep: 273.05 | bwd_inner_microstep: 273.03 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:10:04,008] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.01 | bwd_microstep: 272.96 | bwd_inner_microstep: 272.95 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 01:10:04,490] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.60 | bwd_microstep: 272.59 | bwd_inner_microstep: 272.58 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 836 +[2025-05-02 01:10:04,732] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 100.26 | bwd_microstep: 125.85 | bwd_inner_microstep: 125.83 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:10:05,210] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.30 | bwd_microstep: 272.11 | bwd_inner_microstep: 272.09 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 01:10:05,690] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.98 | bwd_microstep: 272.90 | bwd_inner_microstep: 272.89 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 01:10:06,168] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.87 | bwd_microstep: 271.22 | bwd_inner_microstep: 271.20 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:10:06,648] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.99 | bwd_microstep: 271.11 | bwd_inner_microstep: 271.10 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:10:07,232] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.15 | optimizer_step: 17.04 +[2025-05-02 01:10:07,232] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.73 | bwd_microstep: 353.24 | bwd_inner_microstep: 272.90 | bwd_allreduce_microstep: 80.29 | step_microstep: 24.77 +[2025-05-02 01:10:07,233] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2789.04 | bwd: 4129.17 | bwd_inner: 4048.28 | bwd_allreduce: 80.49 | step: 25.71 + 12%|█▏ | 1043/8720 [2:54:40<15:03:31, 7.06s/it] {'loss': 1.0485, 'grad_norm': 8.417685508728027, 'learning_rate': 9.791090232836112e-06, 'epoch': 1.2} + 12%|█▏ | 1043/8720 [2:54:40<15:03:31, 7.06s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1850 +[2025-05-02 01:10:07,714] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.73 | bwd_microstep: 270.13 | bwd_inner_microstep: 270.12 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1957 +[2025-05-02 01:10:08,219] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 197.46 | bwd_microstep: 290.38 | bwd_inner_microstep: 290.37 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 368 +[2025-05-02 01:10:08,428] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 78.64 | bwd_microstep: 115.59 | bwd_inner_microstep: 115.42 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 360 +[2025-05-02 01:10:08,661] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 81.81 | bwd_microstep: 135.79 | bwd_inner_microstep: 135.66 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1894 +[2025-05-02 01:10:09,140] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.90 | bwd_microstep: 275.08 | bwd_inner_microstep: 275.06 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 01:10:09,617] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.80 | bwd_microstep: 273.45 | bwd_inner_microstep: 273.44 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.13 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 01:10:10,093] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.07 | bwd_microstep: 272.78 | bwd_inner_microstep: 272.77 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:10:10,569] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.33 | bwd_microstep: 272.52 | bwd_inner_microstep: 272.50 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 01:10:11,045] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.49 | bwd_microstep: 273.36 | bwd_inner_microstep: 273.34 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:10:11,522] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.05 | bwd_microstep: 272.56 | bwd_inner_microstep: 272.54 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 01:10:12,000] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.00 | bwd_microstep: 272.88 | bwd_inner_microstep: 272.87 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 834 +[2025-05-02 01:10:12,231] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 92.16 | bwd_microstep: 125.79 | bwd_inner_microstep: 125.67 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:10:12,707] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.17 | bwd_microstep: 272.41 | bwd_inner_microstep: 272.39 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:10:13,183] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.52 | bwd_microstep: 272.26 | bwd_inner_microstep: 272.24 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 01:10:13,662] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.20 | bwd_microstep: 272.95 | bwd_inner_microstep: 272.93 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 01:10:14,241] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.19 | optimizer_step: 17.04 +[2025-05-02 01:10:14,241] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.56 | bwd_microstep: 348.95 | bwd_inner_microstep: 271.63 | bwd_allreduce_microstep: 77.26 | step_microstep: 24.81 +[2025-05-02 01:10:14,243] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2712.62 | bwd: 4016.93 | bwd_inner: 3939.02 | bwd_allreduce: 77.49 | step: 25.77 + 12%|█▏ | 1044/8720 [2:54:47<15:01:24, 7.05s/it] {'loss': 0.8075, 'grad_norm': 9.96063232421875, 'learning_rate': 9.79055867908037e-06, 'epoch': 1.2} + 12%|█▏ | 1044/8720 [2:54:47<15:01:24, 7.05s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 01:10:14,723] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.38 | bwd_microstep: 270.29 | bwd_inner_microstep: 270.28 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 866 +[2025-05-02 01:10:14,966] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.16 | bwd_microstep: 133.95 | bwd_inner_microstep: 133.76 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1900 +[2025-05-02 01:10:15,447] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.70 | bwd_microstep: 275.60 | bwd_inner_microstep: 275.58 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 01:10:15,927] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.18 | bwd_microstep: 273.28 | bwd_inner_microstep: 273.27 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:10:16,408] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.01 | bwd_microstep: 272.30 | bwd_inner_microstep: 272.28 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 839 +[2025-05-02 01:10:16,658] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 105.30 | bwd_microstep: 125.73 | bwd_inner_microstep: 125.49 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.19 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 325 +[2025-05-02 01:10:16,895] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 96.38 | bwd_microstep: 118.45 | bwd_inner_microstep: 118.25 | bwd_allreduce_microstep: 0.08 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:10:17,378] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.08 | bwd_microstep: 272.60 | bwd_inner_microstep: 272.58 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 844 +[2025-05-02 01:10:17,620] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.37 | bwd_microstep: 131.97 | bwd_inner_microstep: 131.91 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.10 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 835 +[2025-05-02 01:10:17,857] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.45 | bwd_microstep: 127.05 | bwd_inner_microstep: 126.78 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:10:18,336] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.24 | bwd_microstep: 273.14 | bwd_inner_microstep: 273.12 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.13 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:10:18,813] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.22 | bwd_microstep: 271.32 | bwd_inner_microstep: 271.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 01:10:19,289] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.76 | bwd_microstep: 271.20 | bwd_inner_microstep: 271.18 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 01:10:19,766] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.95 | bwd_microstep: 271.32 | bwd_inner_microstep: 271.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:10:20,243] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.06 | bwd_microstep: 271.22 | bwd_inner_microstep: 271.20 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1950 +[2025-05-02 01:10:20,850] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.12 | optimizer_step: 17.10 +[2025-05-02 01:10:20,851] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 196.21 | bwd_microstep: 365.63 | bwd_inner_microstep: 289.96 | bwd_allreduce_microstep: 75.61 | step_microstep: 24.85 +[2025-05-02 01:10:20,852] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2563.09 | bwd: 3725.17 | bwd_inner: 3648.29 | bwd_allreduce: 76.11 | step: 26.05 + 12%|█▏ | 1045/8720 [2:54:54<14:44:32, 6.91s/it] {'loss': 0.8573, 'grad_norm': 9.50327205657959, 'learning_rate': 9.790026464402121e-06, 'epoch': 1.2} + 12%|█▏ | 1045/8720 [2:54:54<14:44:32, 6.91s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 342 +[2025-05-02 01:10:21,070] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 79.06 | bwd_microstep: 117.19 | bwd_inner_microstep: 117.00 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1917 +[2025-05-02 01:10:21,552] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.87 | bwd_microstep: 276.32 | bwd_inner_microstep: 276.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1907 +[2025-05-02 01:10:22,032] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.30 | bwd_microstep: 276.05 | bwd_inner_microstep: 276.03 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1889 +[2025-05-02 01:10:22,511] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.77 | bwd_microstep: 274.40 | bwd_inner_microstep: 274.38 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-02 01:10:22,989] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.44 | bwd_microstep: 274.07 | bwd_inner_microstep: 274.05 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-02 01:10:23,466] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.26 | bwd_microstep: 273.64 | bwd_inner_microstep: 273.62 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 01:10:23,943] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.63 | bwd_microstep: 272.89 | bwd_inner_microstep: 272.87 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:10:24,419] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.66 | bwd_microstep: 272.70 | bwd_inner_microstep: 272.68 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 01:10:24,896] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.85 | bwd_microstep: 272.77 | bwd_inner_microstep: 272.75 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:10:25,372] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.37 | bwd_microstep: 272.82 | bwd_inner_microstep: 272.80 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:10:25,847] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.08 | bwd_microstep: 272.23 | bwd_inner_microstep: 272.21 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 832 +[2025-05-02 01:10:26,084] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 92.58 | bwd_microstep: 130.34 | bwd_inner_microstep: 130.33 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:10:26,558] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.19 | bwd_microstep: 271.30 | bwd_inner_microstep: 271.29 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 828 +[2025-05-02 01:10:26,798] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.26 | bwd_microstep: 129.70 | bwd_inner_microstep: 129.47 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:10:27,271] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.52 | bwd_microstep: 271.24 | bwd_inner_microstep: 271.23 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 01:10:27,835] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.04 | optimizer_gradients: 2.16 | optimizer_step: 17.05 +[2025-05-02 01:10:27,835] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.81 | bwd_microstep: 337.42 | bwd_inner_microstep: 271.66 | bwd_allreduce_microstep: 65.72 | step_microstep: 24.06 +[2025-05-02 01:10:27,836] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2716.37 | bwd: 3995.12 | bwd_inner: 3928.73 | bwd_allreduce: 65.97 | step: 24.83 + 12%|█▏ | 1046/8720 [2:55:01<14:47:00, 6.94s/it] {'loss': 0.6712, 'grad_norm': 7.056827545166016, 'learning_rate': 9.789493588874785e-06, 'epoch': 1.2} + 12%|█▏ | 1046/8720 [2:55:01<14:47:00, 6.94s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 01:10:28,315] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.52 | bwd_microstep: 270.49 | bwd_inner_microstep: 270.47 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1443 +[2025-05-02 01:10:28,690] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 144.37 | bwd_microstep: 215.54 | bwd_inner_microstep: 215.46 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1939 +[2025-05-02 01:10:29,189] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.35 | bwd_microstep: 288.46 | bwd_inner_microstep: 288.45 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1917 +[2025-05-02 01:10:29,671] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.30 | bwd_microstep: 276.31 | bwd_inner_microstep: 276.29 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1897 +[2025-05-02 01:10:30,150] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.13 | bwd_microstep: 275.21 | bwd_inner_microstep: 275.19 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1905 +[2025-05-02 01:10:30,630] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.47 | bwd_microstep: 275.86 | bwd_inner_microstep: 275.84 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1892 +[2025-05-02 01:10:31,109] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.97 | bwd_microstep: 274.91 | bwd_inner_microstep: 274.89 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 862 +[2025-05-02 01:10:31,353] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 96.55 | bwd_microstep: 133.43 | bwd_inner_microstep: 133.42 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-02 01:10:31,830] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.37 | bwd_microstep: 273.70 | bwd_inner_microstep: 273.68 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 01:10:32,307] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.07 | bwd_microstep: 272.82 | bwd_inner_microstep: 272.81 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1357 +[2025-05-02 01:10:32,670] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.21 | bwd_microstep: 206.92 | bwd_inner_microstep: 206.79 | bwd_allreduce_microstep: 0.04 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:10:33,144] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.56 | bwd_microstep: 271.94 | bwd_inner_microstep: 271.92 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 326 +[2025-05-02 01:10:33,345] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 69.62 | bwd_microstep: 118.51 | bwd_inner_microstep: 118.17 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:10:33,819] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.00 | bwd_microstep: 271.19 | bwd_inner_microstep: 271.17 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 01:10:34,293] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.23 | bwd_microstep: 271.16 | bwd_inner_microstep: 271.14 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 01:10:34,858] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.04 | optimizer_gradients: 2.12 | optimizer_step: 17.09 +[2025-05-02 01:10:34,859] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.76 | bwd_microstep: 337.58 | bwd_inner_microstep: 271.58 | bwd_allreduce_microstep: 65.94 | step_microstep: 24.04 +[2025-05-02 01:10:34,860] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2718.20 | bwd: 4034.09 | bwd_inner: 3967.37 | bwd_allreduce: 66.24 | step: 24.98 + 12%|█▏ | 1047/8720 [2:55:08<14:50:15, 6.96s/it] {'loss': 1.0363, 'grad_norm': 5.738027572631836, 'learning_rate': 9.788960052571887e-06, 'epoch': 1.2} + 12%|█▏ | 1047/8720 [2:55:08<14:50:15, 6.96s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 01:10:35,336] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.08 | bwd_microstep: 270.40 | bwd_inner_microstep: 270.39 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1891 +[2025-05-02 01:10:35,816] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.59 | bwd_microstep: 274.86 | bwd_inner_microstep: 274.84 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1379 +[2025-05-02 01:10:36,181] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.84 | bwd_microstep: 208.73 | bwd_inner_microstep: 208.60 | bwd_allreduce_microstep: 0.04 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 01:10:36,659] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.16 | bwd_microstep: 274.20 | bwd_inner_microstep: 274.18 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 01:10:37,138] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.23 | bwd_microstep: 273.98 | bwd_inner_microstep: 273.96 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 01:10:37,616] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.65 | bwd_microstep: 273.94 | bwd_inner_microstep: 273.92 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 01:10:38,095] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.07 | bwd_microstep: 273.76 | bwd_inner_microstep: 273.74 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 852 +[2025-05-02 01:10:38,336] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.54 | bwd_microstep: 132.85 | bwd_inner_microstep: 132.79 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.09 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 840 +[2025-05-02 01:10:38,567] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 91.14 | bwd_microstep: 126.65 | bwd_inner_microstep: 126.64 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 01:10:39,044] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.71 | bwd_microstep: 273.73 | bwd_inner_microstep: 273.71 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 326 +[2025-05-02 01:10:39,245] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 67.83 | bwd_microstep: 119.85 | bwd_inner_microstep: 119.53 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 01:10:39,722] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.75 | bwd_microstep: 273.60 | bwd_inner_microstep: 273.58 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:10:40,200] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.83 | bwd_microstep: 273.16 | bwd_inner_microstep: 273.15 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:10:40,677] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.51 | bwd_microstep: 272.74 | bwd_inner_microstep: 272.73 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 318 +[2025-05-02 01:10:40,876] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 67.23 | bwd_microstep: 118.95 | bwd_inner_microstep: 118.80 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 830 +[2025-05-02 01:10:41,204] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.14 | optimizer_step: 17.49 +[2025-05-02 01:10:41,205] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 92.27 | bwd_microstep: 197.68 | bwd_inner_microstep: 131.26 | bwd_allreduce_microstep: 66.25 | step_microstep: 24.57 +[2025-05-02 01:10:41,206] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2445.13 | bwd: 3639.15 | bwd_inner: 3571.98 | bwd_allreduce: 66.59 | step: 25.52 + 12%|█▏ | 1048/8720 [2:55:14<14:26:33, 6.78s/it] {'loss': 0.8533, 'grad_norm': 8.20974063873291, 'learning_rate': 9.78842585556703e-06, 'epoch': 1.2} + 12%|█▏ | 1048/8720 [2:55:14<14:26:33, 6.78s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 314 +[2025-05-02 01:10:41,409] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 67.79 | bwd_microstep: 117.00 | bwd_inner_microstep: 116.85 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.09 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1234 +[2025-05-02 01:10:41,721] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 120.76 | bwd_microstep: 177.30 | bwd_inner_microstep: 177.28 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1390 +[2025-05-02 01:10:42,088] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 143.34 | bwd_microstep: 209.03 | bwd_inner_microstep: 209.01 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1897 +[2025-05-02 01:10:42,567] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.79 | bwd_microstep: 275.24 | bwd_inner_microstep: 275.22 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 345 +[2025-05-02 01:10:42,765] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 69.86 | bwd_microstep: 115.90 | bwd_inner_microstep: 115.77 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-02 01:10:43,241] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.66 | bwd_microstep: 273.33 | bwd_inner_microstep: 273.31 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 01:10:43,718] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.33 | bwd_microstep: 273.29 | bwd_inner_microstep: 273.27 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-02 01:10:44,195] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.86 | bwd_microstep: 273.53 | bwd_inner_microstep: 273.52 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 01:10:44,672] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.77 | bwd_microstep: 272.86 | bwd_inner_microstep: 272.84 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 01:10:45,149] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.58 | bwd_microstep: 272.79 | bwd_inner_microstep: 272.77 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 01:10:45,624] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.52 | bwd_microstep: 272.57 | bwd_inner_microstep: 272.56 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:10:46,100] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.85 | bwd_microstep: 272.50 | bwd_inner_microstep: 272.48 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:10:46,575] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.09 | bwd_microstep: 272.50 | bwd_inner_microstep: 272.48 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 320 +[2025-05-02 01:10:46,773] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 69.19 | bwd_microstep: 115.72 | bwd_inner_microstep: 115.45 | bwd_allreduce_microstep: 0.10 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:10:47,248] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.65 | bwd_microstep: 272.32 | bwd_inner_microstep: 272.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 01:10:47,815] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.04 | optimizer_gradients: 2.12 | optimizer_step: 16.98 +[2025-05-02 01:10:47,815] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.26 | bwd_microstep: 338.63 | bwd_inner_microstep: 272.83 | bwd_allreduce_microstep: 65.76 | step_microstep: 23.96 +[2025-05-02 01:10:47,816] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2543.06 | bwd: 3804.58 | bwd_inner: 3738.05 | bwd_allreduce: 66.04 | step: 24.76 + 12%|█▏ | 1049/8720 [2:55:21<14:20:03, 6.73s/it] {'loss': 0.9603, 'grad_norm': 9.364129066467285, 'learning_rate': 9.787890997933918e-06, 'epoch': 1.2} + 12%|█▏ | 1049/8720 [2:55:21<14:20:03, 6.73s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 01:10:48,293] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.05 | bwd_microstep: 270.15 | bwd_inner_microstep: 270.13 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1935 +[2025-05-02 01:10:48,794] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 196.41 | bwd_microstep: 287.98 | bwd_inner_microstep: 287.96 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1935 +[2025-05-02 01:10:49,294] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 196.52 | bwd_microstep: 288.13 | bwd_inner_microstep: 288.11 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1887 +[2025-05-02 01:10:49,773] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.49 | bwd_microstep: 274.57 | bwd_inner_microstep: 274.55 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.11 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1110 +[2025-05-02 01:10:50,068] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 118.41 | bwd_microstep: 161.95 | bwd_inner_microstep: 161.87 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.08 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 848 +[2025-05-02 01:10:50,308] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.54 | bwd_microstep: 132.58 | bwd_inner_microstep: 132.31 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 843 +[2025-05-02 01:10:50,549] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.11 | bwd_microstep: 131.87 | bwd_inner_microstep: 131.84 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 01:10:51,024] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.02 | bwd_microstep: 272.63 | bwd_inner_microstep: 272.61 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 01:10:51,500] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.91 | bwd_microstep: 272.43 | bwd_inner_microstep: 272.41 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 842 +[2025-05-02 01:10:51,740] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.46 | bwd_microstep: 132.25 | bwd_inner_microstep: 132.23 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:10:52,215] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.87 | bwd_microstep: 272.50 | bwd_inner_microstep: 272.48 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 01:10:52,692] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.23 | bwd_microstep: 272.21 | bwd_inner_microstep: 272.19 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:10:53,170] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.63 | bwd_microstep: 272.39 | bwd_inner_microstep: 272.37 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:10:53,647] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.77 | bwd_microstep: 271.33 | bwd_inner_microstep: 271.31 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 01:10:54,126] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.54 | bwd_microstep: 272.56 | bwd_inner_microstep: 272.54 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 01:10:54,691] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.19 | optimizer_step: 17.24 +[2025-05-02 01:10:54,692] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.76 | bwd_microstep: 337.39 | bwd_inner_microstep: 271.56 | bwd_allreduce_microstep: 65.78 | step_microstep: 24.48 +[2025-05-02 01:10:54,693] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2674.44 | bwd: 3922.97 | bwd_inner: 3856.48 | bwd_allreduce: 66.05 | step: 25.42 + 12%|█▏ | 1050/8720 [2:55:28<14:25:40, 6.77s/it] {'loss': 0.7405, 'grad_norm': 6.033413887023926, 'learning_rate': 9.787355479746336e-06, 'epoch': 1.2} + 12%|█▏ | 1050/8720 [2:55:28<14:25:40, 6.77s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1946 +[2025-05-02 01:10:55,196] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 194.94 | bwd_microstep: 288.00 | bwd_inner_microstep: 287.99 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 411 +[2025-05-02 01:10:55,409] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 80.94 | bwd_microstep: 118.05 | bwd_inner_microstep: 117.92 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1921 +[2025-05-02 01:10:55,905] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 194.29 | bwd_microstep: 286.67 | bwd_inner_microstep: 286.66 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-02 01:10:56,384] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.80 | bwd_microstep: 274.17 | bwd_inner_microstep: 274.15 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 342 +[2025-05-02 01:10:56,595] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 71.02 | bwd_microstep: 126.91 | bwd_inner_microstep: 126.77 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 345 +[2025-05-02 01:10:56,806] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 72.80 | bwd_microstep: 123.92 | bwd_inner_microstep: 123.73 | bwd_allreduce_microstep: 0.08 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 01:10:57,283] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.26 | bwd_microstep: 272.88 | bwd_inner_microstep: 272.87 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 840 +[2025-05-02 01:10:57,514] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 90.74 | bwd_microstep: 126.30 | bwd_inner_microstep: 126.19 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 834 +[2025-05-02 01:10:57,747] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 92.06 | bwd_microstep: 125.82 | bwd_inner_microstep: 125.76 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.09 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 837 +[2025-05-02 01:10:57,982] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.70 | bwd_microstep: 126.18 | bwd_inner_microstep: 126.02 | bwd_allreduce_microstep: 0.08 | step_microstep: 0.10 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 323 +[2025-05-02 01:10:58,197] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 73.69 | bwd_microstep: 126.95 | bwd_inner_microstep: 126.74 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:10:58,673] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.37 | bwd_microstep: 272.22 | bwd_inner_microstep: 272.21 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:10:59,148] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.11 | bwd_microstep: 271.34 | bwd_inner_microstep: 271.32 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:10:59,622] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.21 | bwd_microstep: 271.23 | bwd_inner_microstep: 271.22 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:11:00,096] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.61 | bwd_microstep: 270.92 | bwd_inner_microstep: 270.91 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 01:11:00,661] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.20 | optimizer_step: 17.23 +[2025-05-02 01:11:00,662] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.87 | bwd_microstep: 337.76 | bwd_inner_microstep: 271.47 | bwd_allreduce_microstep: 66.25 | step_microstep: 24.48 +[2025-05-02 01:11:00,663] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2280.13 | bwd: 3419.44 | bwd_inner: 3352.07 | bwd_allreduce: 66.68 | step: 25.49 + 12%|█▏ | 1051/8720 [2:55:34<13:54:49, 6.53s/it] {'loss': 0.6895, 'grad_norm': 9.446151733398438, 'learning_rate': 9.786819301078172e-06, 'epoch': 1.21} + 12%|█▏ | 1051/8720 [2:55:34<13:54:49, 6.53s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 458 +[2025-05-02 01:11:00,877] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 73.43 | bwd_microstep: 121.98 | bwd_inner_microstep: 121.64 | bwd_allreduce_microstep: 0.14 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1899 +[2025-05-02 01:11:01,357] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.85 | bwd_microstep: 276.03 | bwd_inner_microstep: 276.01 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 360 +[2025-05-02 01:11:01,561] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 68.00 | bwd_microstep: 121.90 | bwd_inner_microstep: 121.60 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-02 01:11:02,040] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.70 | bwd_microstep: 274.30 | bwd_inner_microstep: 274.29 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-02 01:11:02,518] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.60 | bwd_microstep: 273.81 | bwd_inner_microstep: 273.79 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-02 01:11:02,995] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.22 | bwd_microstep: 272.76 | bwd_inner_microstep: 272.74 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 835 +[2025-05-02 01:11:03,226] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 90.78 | bwd_microstep: 126.05 | bwd_inner_microstep: 125.84 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 01:11:03,704] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.90 | bwd_microstep: 272.72 | bwd_inner_microstep: 272.70 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 01:11:04,182] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.35 | bwd_microstep: 272.73 | bwd_inner_microstep: 272.71 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 01:11:04,657] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.91 | bwd_microstep: 271.37 | bwd_inner_microstep: 271.35 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:11:05,132] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.45 | bwd_microstep: 272.02 | bwd_inner_microstep: 272.00 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:11:05,609] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.32 | bwd_microstep: 272.27 | bwd_inner_microstep: 272.25 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:11:06,086] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.09 | bwd_microstep: 272.28 | bwd_inner_microstep: 272.26 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 01:11:06,565] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.19 | bwd_microstep: 272.68 | bwd_inner_microstep: 272.66 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 319 +[2025-05-02 01:11:06,767] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 69.05 | bwd_microstep: 118.93 | bwd_inner_microstep: 118.63 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 01:11:07,333] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.13 | optimizer_step: 17.12 +[2025-05-02 01:11:07,334] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.51 | bwd_microstep: 339.40 | bwd_inner_microstep: 271.77 | bwd_allreduce_microstep: 67.59 | step_microstep: 24.17 +[2025-05-02 01:11:07,335] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2561.05 | bwd: 3831.32 | bwd_inner: 3762.43 | bwd_allreduce: 68.15 | step: 25.10 + 12%|█▏ | 1052/8720 [2:55:41<14:00:04, 6.57s/it] {'loss': 0.8128, 'grad_norm': 6.860091686248779, 'learning_rate': 9.786282462003398e-06, 'epoch': 1.21} + 12%|█▏ | 1052/8720 [2:55:41<14:00:04, 6.57s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1893 +[2025-05-02 01:11:07,817] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.89 | bwd_microstep: 274.15 | bwd_inner_microstep: 274.13 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1949 +[2025-05-02 01:11:08,320] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 197.04 | bwd_microstep: 289.72 | bwd_inner_microstep: 289.70 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1350 +[2025-05-02 01:11:08,683] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.69 | bwd_microstep: 205.84 | bwd_inner_microstep: 205.82 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 01:11:09,161] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.53 | bwd_microstep: 272.73 | bwd_inner_microstep: 272.72 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 847 +[2025-05-02 01:11:09,405] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.69 | bwd_microstep: 132.19 | bwd_inner_microstep: 132.11 | bwd_allreduce_microstep: 0.03 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 01:11:09,884] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.56 | bwd_microstep: 272.90 | bwd_inner_microstep: 272.88 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:11:10,364] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.27 | bwd_microstep: 272.72 | bwd_inner_microstep: 272.70 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:11:10,845] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.36 | bwd_microstep: 272.68 | bwd_inner_microstep: 272.67 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:11:11,326] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.29 | bwd_microstep: 272.54 | bwd_inner_microstep: 272.53 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1353 +[2025-05-02 01:11:11,694] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.43 | bwd_microstep: 206.26 | bwd_inner_microstep: 206.24 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.13 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 01:11:12,174] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.45 | bwd_microstep: 271.28 | bwd_inner_microstep: 271.26 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 01:11:12,651] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.43 | bwd_microstep: 271.16 | bwd_inner_microstep: 271.15 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 320 +[2025-05-02 01:11:12,867] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 78.53 | bwd_microstep: 121.59 | bwd_inner_microstep: 121.45 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 01:11:13,343] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.75 | bwd_microstep: 271.26 | bwd_inner_microstep: 271.24 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 314 +[2025-05-02 01:11:13,553] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 74.79 | bwd_microstep: 120.73 | bwd_inner_microstep: 120.53 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1935 +[2025-05-02 01:11:14,143] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.19 | optimizer_step: 17.22 +[2025-05-02 01:11:14,144] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 194.32 | bwd_microstep: 355.51 | bwd_inner_microstep: 288.73 | bwd_allreduce_microstep: 66.74 | step_microstep: 24.44 +[2025-05-02 01:11:14,145] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2617.68 | bwd: 3883.34 | bwd_inner: 3815.95 | bwd_allreduce: 66.96 | step: 25.41 + 12%|█▏ | 1053/8720 [2:55:47<14:09:03, 6.64s/it] {'loss': 0.7293, 'grad_norm': 8.263572692871094, 'learning_rate': 9.785744962596075e-06, 'epoch': 1.21} + 12%|█▏ | 1053/8720 [2:55:47<14:09:03, 6.64s/it]dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1381 +[2025-05-02 01:11:14,517] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 144.38 | bwd_microstep: 207.97 | bwd_inner_microstep: 207.95 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1387 +[2025-05-02 01:11:14,884] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 142.96 | bwd_microstep: 208.75 | bwd_inner_microstep: 208.74 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1889 +[2025-05-02 01:11:15,364] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.49 | bwd_microstep: 274.69 | bwd_inner_microstep: 274.67 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-02 01:11:15,844] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.21 | bwd_microstep: 273.88 | bwd_inner_microstep: 273.87 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 858 +[2025-05-02 01:11:16,090] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 97.90 | bwd_microstep: 133.51 | bwd_inner_microstep: 133.48 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 01:11:16,567] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.77 | bwd_microstep: 273.24 | bwd_inner_microstep: 273.23 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1351 +[2025-05-02 01:11:16,930] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.45 | bwd_microstep: 206.20 | bwd_inner_microstep: 206.13 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 01:11:17,406] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.98 | bwd_microstep: 272.77 | bwd_inner_microstep: 272.75 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:11:17,883] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.84 | bwd_microstep: 272.71 | bwd_inner_microstep: 272.69 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:11:18,360] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.99 | bwd_microstep: 272.62 | bwd_inner_microstep: 272.61 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:11:18,837] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.64 | bwd_microstep: 272.39 | bwd_inner_microstep: 272.37 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 836 +[2025-05-02 01:11:19,069] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 90.90 | bwd_microstep: 126.24 | bwd_inner_microstep: 126.14 | bwd_allreduce_microstep: 0.04 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:11:19,544] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.06 | bwd_microstep: 272.37 | bwd_inner_microstep: 272.35 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:11:20,020] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.28 | bwd_microstep: 271.50 | bwd_inner_microstep: 271.48 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:11:20,498] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.96 | bwd_microstep: 271.40 | bwd_inner_microstep: 271.38 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 01:11:21,088] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.24 | optimizer_step: 17.52 +[2025-05-02 01:11:21,089] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.93 | bwd_microstep: 355.60 | bwd_inner_microstep: 272.07 | bwd_allreduce_microstep: 83.47 | step_microstep: 25.53 +[2025-05-02 01:11:21,090] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2694.45 | bwd: 3965.90 | bwd_inner: 3881.92 | bwd_allreduce: 83.64 | step: 26.41 + 12%|█▏ | 1054/8720 [2:55:54<14:20:32, 6.74s/it] {'loss': 0.6298, 'grad_norm': 7.08443546295166, 'learning_rate': 9.785206802930363e-06, 'epoch': 1.21} + 12%|█▏ | 1054/8720 [2:55:54<14:20:32, 6.74s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 01:11:21,572] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.00 | bwd_microstep: 270.47 | bwd_inner_microstep: 270.45 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1967 +[2025-05-02 01:11:22,080] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 198.11 | bwd_microstep: 291.35 | bwd_inner_microstep: 291.33 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1927 +[2025-05-02 01:11:22,581] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.94 | bwd_microstep: 287.34 | bwd_inner_microstep: 287.32 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1887 +[2025-05-02 01:11:23,063] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.79 | bwd_microstep: 274.59 | bwd_inner_microstep: 274.57 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-02 01:11:23,542] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.47 | bwd_microstep: 273.72 | bwd_inner_microstep: 273.70 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 01:11:24,021] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.63 | bwd_microstep: 272.98 | bwd_inner_microstep: 272.96 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 01:11:24,500] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.35 | bwd_microstep: 272.90 | bwd_inner_microstep: 272.89 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1354 +[2025-05-02 01:11:24,866] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 142.20 | bwd_microstep: 206.18 | bwd_inner_microstep: 206.14 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 01:11:25,349] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.77 | bwd_microstep: 272.34 | bwd_inner_microstep: 272.32 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:11:25,828] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.76 | bwd_microstep: 272.14 | bwd_inner_microstep: 272.12 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:11:26,310] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.82 | bwd_microstep: 272.28 | bwd_inner_microstep: 272.26 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 01:11:26,788] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.97 | bwd_microstep: 272.39 | bwd_inner_microstep: 272.37 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:11:27,268] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.57 | bwd_microstep: 272.10 | bwd_inner_microstep: 272.08 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.14 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 836 +[2025-05-02 01:11:27,505] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.66 | bwd_microstep: 125.91 | bwd_inner_microstep: 125.65 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 01:11:27,984] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.56 | bwd_microstep: 272.40 | bwd_inner_microstep: 272.39 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:11:28,561] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.15 | optimizer_step: 17.07 +[2025-05-02 01:11:28,561] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.23 | bwd_microstep: 348.27 | bwd_inner_microstep: 272.46 | bwd_allreduce_microstep: 75.77 | step_microstep: 24.10 +[2025-05-02 01:11:28,563] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2892.46 | bwd: 4257.43 | bwd_inner: 4181.03 | bwd_allreduce: 75.98 | step: 25.30 + 12%|█▏ | 1055/8720 [2:56:02<14:48:35, 6.96s/it] {'loss': 0.7549, 'grad_norm': 7.052214622497559, 'learning_rate': 9.784667983080502e-06, 'epoch': 1.21} + 12%|█▏ | 1055/8720 [2:56:02<14:48:35, 6.96s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 01:11:29,040] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.83 | bwd_microstep: 270.64 | bwd_inner_microstep: 270.62 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1941 +[2025-05-02 01:11:29,543] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 198.63 | bwd_microstep: 288.41 | bwd_inner_microstep: 288.39 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1917 +[2025-05-02 01:11:30,026] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.19 | bwd_microstep: 276.38 | bwd_inner_microstep: 276.36 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1913 +[2025-05-02 01:11:30,510] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 191.42 | bwd_microstep: 275.81 | bwd_inner_microstep: 275.79 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 01:11:30,989] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.31 | bwd_microstep: 273.08 | bwd_inner_microstep: 273.06 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 336 +[2025-05-02 01:11:31,228] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 96.79 | bwd_microstep: 122.80 | bwd_inner_microstep: 122.56 | bwd_allreduce_microstep: 0.09 | step_microstep: 0.10 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1360 +[2025-05-02 01:11:31,592] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.18 | bwd_microstep: 206.77 | bwd_inner_microstep: 206.70 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:11:32,071] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.43 | bwd_microstep: 272.60 | bwd_inner_microstep: 272.58 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:11:32,551] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.54 | bwd_microstep: 272.68 | bwd_inner_microstep: 272.67 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:11:33,031] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.03 | bwd_microstep: 272.54 | bwd_inner_microstep: 272.52 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1345 +[2025-05-02 01:11:33,393] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.28 | bwd_microstep: 205.40 | bwd_inner_microstep: 205.38 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 01:11:33,872] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.30 | bwd_microstep: 272.87 | bwd_inner_microstep: 272.85 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 01:11:34,354] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.03 | bwd_microstep: 272.45 | bwd_inner_microstep: 272.43 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:11:34,837] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.26 | bwd_microstep: 272.52 | bwd_inner_microstep: 272.50 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 01:11:35,320] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.18 | bwd_microstep: 272.25 | bwd_inner_microstep: 272.24 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 01:11:35,905] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.15 | optimizer_step: 17.05 +[2025-05-02 01:11:35,906] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.36 | bwd_microstep: 352.81 | bwd_inner_microstep: 271.58 | bwd_allreduce_microstep: 81.18 | step_microstep: 24.71 +[2025-05-02 01:11:35,907] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2842.35 | bwd: 4180.07 | bwd_inner: 4098.29 | bwd_allreduce: 81.34 | step: 25.77 + 12%|█▏ | 1056/8720 [2:56:09<15:03:26, 7.07s/it] {'loss': 0.611, 'grad_norm': 9.54610824584961, 'learning_rate': 9.784128503120835e-06, 'epoch': 1.21} + 12%|█▏ | 1056/8720 [2:56:09<15:03:26, 7.07s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 01:11:36,387] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.71 | bwd_microstep: 270.39 | bwd_inner_microstep: 270.38 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1924 +[2025-05-02 01:11:36,888] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 196.10 | bwd_microstep: 287.22 | bwd_inner_microstep: 287.20 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 857 +[2025-05-02 01:11:37,132] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.24 | bwd_microstep: 133.19 | bwd_inner_microstep: 132.94 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1883 +[2025-05-02 01:11:37,612] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.95 | bwd_microstep: 274.14 | bwd_inner_microstep: 274.12 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-02 01:11:38,089] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.44 | bwd_microstep: 273.52 | bwd_inner_microstep: 273.50 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-02 01:11:38,569] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.50 | bwd_microstep: 273.45 | bwd_inner_microstep: 273.43 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 01:11:39,050] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.21 | bwd_microstep: 273.22 | bwd_inner_microstep: 273.21 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 01:11:39,528] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.88 | bwd_microstep: 272.08 | bwd_inner_microstep: 272.06 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.15 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 01:11:40,010] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.61 | bwd_microstep: 272.66 | bwd_inner_microstep: 272.65 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 328 +[2025-05-02 01:11:40,232] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 88.10 | bwd_microstep: 118.73 | bwd_inner_microstep: 118.58 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.11 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 835 +[2025-05-02 01:11:40,469] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.19 | bwd_microstep: 126.16 | bwd_inner_microstep: 126.13 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:11:40,946] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.07 | bwd_microstep: 271.18 | bwd_inner_microstep: 271.16 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:11:41,425] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.01 | bwd_microstep: 271.20 | bwd_inner_microstep: 271.18 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1850 +[2025-05-02 01:11:41,901] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.69 | bwd_microstep: 270.73 | bwd_inner_microstep: 270.72 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 01:11:42,379] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.49 | bwd_microstep: 270.94 | bwd_inner_microstep: 270.92 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 314 +[2025-05-02 01:11:42,709] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.16 | optimizer_step: 17.04 +[2025-05-02 01:11:42,709] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 81.87 | bwd_microstep: 208.20 | bwd_inner_microstep: 131.31 | bwd_allreduce_microstep: 76.73 | step_microstep: 24.73 +[2025-05-02 01:11:42,711] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2622.66 | bwd: 3867.10 | bwd_inner: 3789.58 | bwd_allreduce: 76.97 | step: 25.84 + 12%|█▏ | 1057/8720 [2:56:16<14:53:00, 6.99s/it] {'loss': 0.8522, 'grad_norm': 6.943994522094727, 'learning_rate': 9.783588363125789e-06, 'epoch': 1.21} + 12%|█▏ | 1057/8720 [2:56:16<14:53:00, 6.99s/it]dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1759 +[2025-05-02 01:11:43,150] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 162.64 | bwd_microstep: 255.15 | bwd_inner_microstep: 255.06 | bwd_allreduce_microstep: 0.04 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1904 +[2025-05-02 01:11:43,633] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.93 | bwd_microstep: 275.87 | bwd_inner_microstep: 275.85 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1372 +[2025-05-02 01:11:44,002] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 144.22 | bwd_microstep: 207.70 | bwd_inner_microstep: 207.63 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-02 01:11:44,480] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.25 | bwd_microstep: 274.31 | bwd_inner_microstep: 274.29 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-02 01:11:44,959] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.60 | bwd_microstep: 273.74 | bwd_inner_microstep: 273.72 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 855 +[2025-05-02 01:11:45,200] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.64 | bwd_microstep: 133.31 | bwd_inner_microstep: 133.29 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 01:11:45,677] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.91 | bwd_microstep: 272.94 | bwd_inner_microstep: 272.92 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 01:11:46,154] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.61 | bwd_microstep: 272.94 | bwd_inner_microstep: 272.92 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1351 +[2025-05-02 01:11:46,516] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.56 | bwd_microstep: 206.16 | bwd_inner_microstep: 206.08 | bwd_allreduce_microstep: 0.04 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 01:11:46,993] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.58 | bwd_microstep: 272.93 | bwd_inner_microstep: 272.91 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:11:47,469] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.87 | bwd_microstep: 272.37 | bwd_inner_microstep: 272.35 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 01:11:47,946] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.63 | bwd_microstep: 272.77 | bwd_inner_microstep: 272.76 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:11:48,421] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.04 | bwd_microstep: 272.13 | bwd_inner_microstep: 272.11 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:11:48,896] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.12 | bwd_microstep: 271.14 | bwd_inner_microstep: 271.12 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:11:49,371] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.83 | bwd_microstep: 271.43 | bwd_inner_microstep: 271.41 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 318 +[2025-05-02 01:11:49,684] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.04 | optimizer_gradients: 2.12 | optimizer_step: 17.05 +[2025-05-02 01:11:49,685] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 77.01 | bwd_microstep: 198.60 | bwd_inner_microstep: 131.99 | bwd_allreduce_microstep: 66.42 | step_microstep: 23.99 +[2025-05-02 01:11:49,686] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2697.19 | bwd: 4003.52 | bwd_inner: 3936.49 | bwd_allreduce: 66.61 | step: 24.93 + 12%|█▏ | 1058/8720 [2:56:23<14:52:10, 6.99s/it] {'loss': 0.9713, 'grad_norm': 12.521921157836914, 'learning_rate': 9.783047563169883e-06, 'epoch': 1.21} + 12%|█▏ | 1058/8720 [2:56:23<14:52:10, 6.99s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:11:50,164] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.86 | bwd_microstep: 270.57 | bwd_inner_microstep: 270.55 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 388 +[2025-05-02 01:11:50,362] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 68.36 | bwd_microstep: 117.27 | bwd_inner_microstep: 117.13 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.08 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 384 +[2025-05-02 01:11:50,560] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 69.82 | bwd_microstep: 114.75 | bwd_inner_microstep: 114.47 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.08 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1098 +[2025-05-02 01:11:50,849] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 114.26 | bwd_microstep: 161.45 | bwd_inner_microstep: 161.25 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:11:51,324] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.51 | bwd_microstep: 272.20 | bwd_inner_microstep: 272.18 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 01:11:51,800] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.02 | bwd_microstep: 272.48 | bwd_inner_microstep: 272.46 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 01:11:52,275] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.22 | bwd_microstep: 272.45 | bwd_inner_microstep: 272.44 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 01:11:52,752] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.31 | bwd_microstep: 273.06 | bwd_inner_microstep: 273.05 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 01:11:53,228] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.97 | bwd_microstep: 272.42 | bwd_inner_microstep: 272.41 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:11:53,705] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.39 | bwd_microstep: 272.71 | bwd_inner_microstep: 272.69 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:11:54,180] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.07 | bwd_microstep: 272.36 | bwd_inner_microstep: 272.35 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 835 +[2025-05-02 01:11:54,410] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 90.69 | bwd_microstep: 125.98 | bwd_inner_microstep: 125.96 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:11:54,886] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.78 | bwd_microstep: 272.44 | bwd_inner_microstep: 272.43 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 320 +[2025-05-02 01:11:55,084] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 66.75 | bwd_microstep: 118.17 | bwd_inner_microstep: 118.04 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 01:11:55,557] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.91 | bwd_microstep: 271.22 | bwd_inner_microstep: 271.21 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:11:56,121] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.04 | optimizer_gradients: 2.15 | optimizer_step: 17.04 +[2025-05-02 01:11:56,122] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.87 | bwd_microstep: 337.48 | bwd_inner_microstep: 271.76 | bwd_allreduce_microstep: 65.68 | step_microstep: 23.91 +[2025-05-02 01:11:56,123] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2479.55 | bwd: 3697.09 | bwd_inner: 3630.48 | bwd_allreduce: 66.08 | step: 24.78 + 12%|█▏ | 1059/8720 [2:56:29<14:31:01, 6.82s/it] {'loss': 0.8487, 'grad_norm': 16.058889389038086, 'learning_rate': 9.78250610332773e-06, 'epoch': 1.21} + 12%|█▏ | 1059/8720 [2:56:29<14:31:01, 6.82s/it]dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1379 +[2025-05-02 01:11:56,492] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 142.57 | bwd_microstep: 207.65 | bwd_inner_microstep: 207.63 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1944 +[2025-05-02 01:11:56,992] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 196.06 | bwd_microstep: 288.88 | bwd_inner_microstep: 288.87 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1889 +[2025-05-02 01:11:57,471] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.81 | bwd_microstep: 274.76 | bwd_inner_microstep: 274.74 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 860 +[2025-05-02 01:11:57,714] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.62 | bwd_microstep: 134.07 | bwd_inner_microstep: 133.87 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 01:11:58,192] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.12 | bwd_microstep: 273.53 | bwd_inner_microstep: 273.52 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1365 +[2025-05-02 01:11:58,559] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 142.09 | bwd_microstep: 207.26 | bwd_inner_microstep: 207.17 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 01:11:59,039] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.18 | bwd_microstep: 272.84 | bwd_inner_microstep: 272.82 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1347 +[2025-05-02 01:11:59,404] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.37 | bwd_microstep: 205.82 | bwd_inner_microstep: 205.80 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:11:59,886] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.53 | bwd_microstep: 272.66 | bwd_inner_microstep: 272.64 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 836 +[2025-05-02 01:12:00,125] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.13 | bwd_microstep: 125.90 | bwd_inner_microstep: 125.86 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 841 +[2025-05-02 01:12:00,367] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.76 | bwd_microstep: 131.95 | bwd_inner_microstep: 131.68 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 01:12:00,846] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.92 | bwd_microstep: 273.05 | bwd_inner_microstep: 273.03 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 01:12:01,324] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.79 | bwd_microstep: 272.17 | bwd_inner_microstep: 272.15 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:12:01,800] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.28 | bwd_microstep: 272.41 | bwd_inner_microstep: 272.40 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:12:02,275] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.01 | bwd_microstep: 272.38 | bwd_inner_microstep: 272.36 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 01:12:02,839] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.04 | optimizer_gradients: 2.12 | optimizer_step: 17.07 +[2025-05-02 01:12:02,840] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.97 | bwd_microstep: 337.70 | bwd_inner_microstep: 271.88 | bwd_allreduce_microstep: 65.77 | step_microstep: 24.08 +[2025-05-02 01:12:02,841] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2601.90 | bwd: 3823.11 | bwd_inner: 3756.44 | bwd_allreduce: 66.11 | step: 25.07 + 12%|█▏ | 1060/8720 [2:56:36<14:26:55, 6.79s/it] {'loss': 0.6015, 'grad_norm': 6.224308490753174, 'learning_rate': 9.781963983674028e-06, 'epoch': 1.22} + 12%|█▏ | 1060/8720 [2:56:36<14:26:55, 6.79s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:12:03,319] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.79 | bwd_microstep: 270.56 | bwd_inner_microstep: 270.54 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1952 +[2025-05-02 01:12:03,819] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.54 | bwd_microstep: 289.59 | bwd_inner_microstep: 289.57 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1933 +[2025-05-02 01:12:04,318] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.01 | bwd_microstep: 288.28 | bwd_inner_microstep: 288.26 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1358 +[2025-05-02 01:12:04,680] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.36 | bwd_microstep: 206.40 | bwd_inner_microstep: 206.38 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-02 01:12:05,158] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.07 | bwd_microstep: 273.35 | bwd_inner_microstep: 273.34 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 01:12:05,638] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.90 | bwd_microstep: 273.40 | bwd_inner_microstep: 273.38 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 01:12:06,118] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.47 | bwd_microstep: 272.93 | bwd_inner_microstep: 272.91 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 01:12:06,596] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.80 | bwd_microstep: 272.57 | bwd_inner_microstep: 272.55 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 01:12:07,074] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.54 | bwd_microstep: 272.80 | bwd_inner_microstep: 272.78 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 01:12:07,552] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.49 | bwd_microstep: 272.58 | bwd_inner_microstep: 272.56 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 836 +[2025-05-02 01:12:07,783] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 91.04 | bwd_microstep: 126.11 | bwd_inner_microstep: 126.03 | bwd_allreduce_microstep: 0.04 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:12:08,259] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.07 | bwd_microstep: 272.73 | bwd_inner_microstep: 272.71 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:12:08,734] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.93 | bwd_microstep: 272.08 | bwd_inner_microstep: 272.06 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 01:12:09,211] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.28 | bwd_microstep: 272.18 | bwd_inner_microstep: 272.16 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 01:12:09,687] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.74 | bwd_microstep: 272.32 | bwd_inner_microstep: 272.30 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 01:12:10,253] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.13 | optimizer_step: 17.04 +[2025-05-02 01:12:10,253] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.64 | bwd_microstep: 337.33 | bwd_inner_microstep: 271.61 | bwd_allreduce_microstep: 65.68 | step_microstep: 24.22 +[2025-05-02 01:12:10,254] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2881.34 | bwd: 4245.22 | bwd_inner: 4179.15 | bwd_allreduce: 65.81 | step: 25.00 + 12%|█▏ | 1061/8720 [2:56:44<14:50:40, 6.98s/it] {'loss': 1.0395, 'grad_norm': 10.478015899658203, 'learning_rate': 9.781421204283573e-06, 'epoch': 1.22} + 12%|█▏ | 1061/8720 [2:56:44<14:50:40, 6.98s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 315 +[2025-05-02 01:12:10,456] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 70.07 | bwd_microstep: 113.72 | bwd_inner_microstep: 113.58 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2113 +[2025-05-02 01:12:10,988] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 204.57 | bwd_microstep: 312.89 | bwd_inner_microstep: 312.88 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2103 +[2025-05-02 01:12:11,519] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 205.31 | bwd_microstep: 310.60 | bwd_inner_microstep: 310.58 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 400 +[2025-05-02 01:12:11,724] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 69.21 | bwd_microstep: 122.06 | bwd_inner_microstep: 121.94 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-02 01:12:12,201] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.78 | bwd_microstep: 274.31 | bwd_inner_microstep: 274.29 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1368 +[2025-05-02 01:12:12,564] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.33 | bwd_microstep: 207.28 | bwd_inner_microstep: 207.19 | bwd_allreduce_microstep: 0.03 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 01:12:13,041] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.29 | bwd_microstep: 273.24 | bwd_inner_microstep: 273.22 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 01:12:13,518] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.30 | bwd_microstep: 272.78 | bwd_inner_microstep: 272.76 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 841 +[2025-05-02 01:12:13,768] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.08 | bwd_microstep: 139.29 | bwd_inner_microstep: 139.01 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 329 +[2025-05-02 01:12:13,997] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 82.80 | bwd_microstep: 130.16 | bwd_inner_microstep: 129.86 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 01:12:14,474] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.26 | bwd_microstep: 272.56 | bwd_inner_microstep: 272.54 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 325 +[2025-05-02 01:12:14,694] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 80.91 | bwd_microstep: 123.77 | bwd_inner_microstep: 123.61 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:12:15,171] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.61 | bwd_microstep: 272.33 | bwd_inner_microstep: 272.31 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 01:12:15,647] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.21 | bwd_microstep: 270.92 | bwd_inner_microstep: 270.90 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 01:12:16,124] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.27 | bwd_microstep: 271.16 | bwd_inner_microstep: 271.14 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 01:12:16,704] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.18 | optimizer_step: 17.21 +[2025-05-02 01:12:16,704] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.90 | bwd_microstep: 347.74 | bwd_inner_microstep: 271.52 | bwd_allreduce_microstep: 76.17 | step_microstep: 25.15 +[2025-05-02 01:12:16,706] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2454.60 | bwd: 3714.90 | bwd_inner: 3637.48 | bwd_allreduce: 76.69 | step: 26.14 + 12%|█▏ | 1062/8720 [2:56:50<14:30:29, 6.82s/it] {'loss': 0.747, 'grad_norm': 4.7060160636901855, 'learning_rate': 9.780877765231245e-06, 'epoch': 1.22} + 12%|█▏ | 1062/8720 [2:56:50<14:30:29, 6.82s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 01:12:17,187] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.35 | bwd_microstep: 270.25 | bwd_inner_microstep: 270.23 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1908 +[2025-05-02 01:12:17,669] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.13 | bwd_microstep: 276.12 | bwd_inner_microstep: 276.10 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1899 +[2025-05-02 01:12:18,150] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.90 | bwd_microstep: 275.38 | bwd_inner_microstep: 275.36 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1894 +[2025-05-02 01:12:18,630] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.91 | bwd_microstep: 274.99 | bwd_inner_microstep: 274.97 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 01:12:19,108] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.65 | bwd_microstep: 273.17 | bwd_inner_microstep: 273.15 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 01:12:19,586] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.90 | bwd_microstep: 273.71 | bwd_inner_microstep: 273.69 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 01:12:20,065] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.90 | bwd_microstep: 273.25 | bwd_inner_microstep: 273.23 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-02 01:12:20,545] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.46 | bwd_microstep: 273.94 | bwd_inner_microstep: 273.93 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 01:12:21,025] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.17 | bwd_microstep: 273.54 | bwd_inner_microstep: 273.52 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1093 +[2025-05-02 01:12:21,318] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 115.35 | bwd_microstep: 160.87 | bwd_inner_microstep: 160.85 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 01:12:21,797] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.33 | bwd_microstep: 272.75 | bwd_inner_microstep: 272.73 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 330 +[2025-05-02 01:12:22,028] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 89.24 | bwd_microstep: 123.56 | bwd_inner_microstep: 123.41 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:12:22,506] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.88 | bwd_microstep: 272.60 | bwd_inner_microstep: 272.58 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:12:22,986] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.84 | bwd_microstep: 272.44 | bwd_inner_microstep: 272.42 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:12:23,464] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.36 | bwd_microstep: 271.28 | bwd_inner_microstep: 271.26 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 01:12:24,043] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.16 | optimizer_step: 17.18 +[2025-05-02 01:12:24,044] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.45 | bwd_microstep: 348.95 | bwd_inner_microstep: 272.02 | bwd_allreduce_microstep: 76.88 | step_microstep: 24.40 +[2025-05-02 01:12:24,045] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2849.50 | bwd: 4186.82 | bwd_inner: 4109.50 | bwd_allreduce: 77.00 | step: 25.22 + 12%|█▏ | 1063/8720 [2:56:57<14:50:10, 6.98s/it] {'loss': 0.9307, 'grad_norm': 16.932193756103516, 'learning_rate': 9.780333666592023e-06, 'epoch': 1.22} + 12%|█▏ | 1063/8720 [2:56:57<14:50:10, 6.98s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 01:12:24,524] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.84 | bwd_microstep: 270.63 | bwd_inner_microstep: 270.61 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 853 +[2025-05-02 01:12:24,769] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 97.27 | bwd_microstep: 133.27 | bwd_inner_microstep: 133.14 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1886 +[2025-05-02 01:12:25,247] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.95 | bwd_microstep: 274.58 | bwd_inner_microstep: 274.56 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-02 01:12:25,726] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.61 | bwd_microstep: 273.70 | bwd_inner_microstep: 273.68 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-02 01:12:26,205] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.28 | bwd_microstep: 273.52 | bwd_inner_microstep: 273.51 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 01:12:26,682] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.72 | bwd_microstep: 273.05 | bwd_inner_microstep: 273.03 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-02 01:12:27,160] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.33 | bwd_microstep: 273.69 | bwd_inner_microstep: 273.68 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1353 +[2025-05-02 01:12:27,524] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.71 | bwd_microstep: 206.24 | bwd_inner_microstep: 206.09 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-02 01:12:28,003] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.96 | bwd_microstep: 273.54 | bwd_inner_microstep: 273.52 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:12:28,481] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.85 | bwd_microstep: 272.76 | bwd_inner_microstep: 272.75 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:12:28,961] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.87 | bwd_microstep: 272.59 | bwd_inner_microstep: 272.58 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 836 +[2025-05-02 01:12:29,206] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 97.28 | bwd_microstep: 131.74 | bwd_inner_microstep: 131.71 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:12:29,685] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.65 | bwd_microstep: 272.41 | bwd_inner_microstep: 272.39 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:12:30,163] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.51 | bwd_microstep: 272.60 | bwd_inner_microstep: 272.58 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:12:30,642] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.37 | bwd_microstep: 272.54 | bwd_inner_microstep: 272.53 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:12:31,209] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.20 | optimizer_step: 17.31 +[2025-05-02 01:12:31,210] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.99 | bwd_microstep: 339.24 | bwd_inner_microstep: 272.83 | bwd_allreduce_microstep: 66.36 | step_microstep: 24.52 +[2025-05-02 01:12:31,211] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2788.88 | bwd: 4086.17 | bwd_inner: 4019.21 | bwd_allreduce: 66.59 | step: 25.34 + 12%|█▏ | 1064/8720 [2:57:04<14:57:20, 7.03s/it] {'loss': 0.8445, 'grad_norm': 8.656472206115723, 'learning_rate': 9.77978890844097e-06, 'epoch': 1.22} + 12%|█▏ | 1064/8720 [2:57:04<14:57:20, 7.03s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 01:12:31,691] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.08 | bwd_microstep: 270.68 | bwd_inner_microstep: 270.66 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1928 +[2025-05-02 01:12:32,193] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.16 | bwd_microstep: 287.62 | bwd_inner_microstep: 287.60 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-02 01:12:32,673] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.86 | bwd_microstep: 273.15 | bwd_inner_microstep: 273.13 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-02 01:12:33,151] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.75 | bwd_microstep: 273.28 | bwd_inner_microstep: 273.26 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 01:12:33,630] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.68 | bwd_microstep: 273.29 | bwd_inner_microstep: 273.27 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 01:12:34,110] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.54 | bwd_microstep: 273.01 | bwd_inner_microstep: 272.99 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:12:34,589] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.16 | bwd_microstep: 272.87 | bwd_inner_microstep: 272.86 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-02 01:12:35,073] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.75 | bwd_microstep: 273.44 | bwd_inner_microstep: 273.42 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 01:12:35,559] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.41 | bwd_microstep: 272.83 | bwd_inner_microstep: 272.81 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 01:12:36,039] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.50 | bwd_microstep: 273.04 | bwd_inner_microstep: 273.03 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:12:36,521] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.37 | bwd_microstep: 272.62 | bwd_inner_microstep: 272.60 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:12:37,002] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.58 | bwd_microstep: 272.44 | bwd_inner_microstep: 272.42 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 01:12:37,482] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.67 | bwd_microstep: 272.22 | bwd_inner_microstep: 272.20 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 01:12:37,963] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.89 | bwd_microstep: 271.03 | bwd_inner_microstep: 271.01 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 01:12:38,442] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.74 | bwd_microstep: 270.93 | bwd_inner_microstep: 270.91 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 01:12:39,026] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.21 | optimizer_step: 17.69 +[2025-05-02 01:12:39,026] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.16 | bwd_microstep: 351.50 | bwd_inner_microstep: 271.58 | bwd_allreduce_microstep: 79.87 | step_microstep: 25.63 +[2025-05-02 01:12:39,028] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 3023.88 | bwd: 4453.96 | bwd_inner: 4373.76 | bwd_allreduce: 79.96 | step: 26.40 + 12%|█▏ | 1065/8720 [2:57:12<15:27:20, 7.27s/it] {'loss': 0.5788, 'grad_norm': 12.086640357971191, 'learning_rate': 9.779243490853245e-06, 'epoch': 1.22} + 12%|█▏ | 1065/8720 [2:57:12<15:27:20, 7.27s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1999 +[2025-05-02 01:12:39,546] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 200.92 | bwd_microstep: 293.80 | bwd_inner_microstep: 293.78 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1570 +[2025-05-02 01:12:39,956] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 150.30 | bwd_microstep: 239.85 | bwd_inner_microstep: 239.77 | bwd_allreduce_microstep: 0.03 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1961 +[2025-05-02 01:12:40,463] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 198.61 | bwd_microstep: 290.35 | bwd_inner_microstep: 290.34 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.14 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-02 01:12:40,944] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.31 | bwd_microstep: 274.43 | bwd_inner_microstep: 274.41 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1367 +[2025-05-02 01:12:41,312] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.13 | bwd_microstep: 207.37 | bwd_inner_microstep: 207.36 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 01:12:41,792] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.97 | bwd_microstep: 273.24 | bwd_inner_microstep: 273.22 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 01:12:42,271] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.57 | bwd_microstep: 272.98 | bwd_inner_microstep: 272.96 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 01:12:42,752] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.88 | bwd_microstep: 272.92 | bwd_inner_microstep: 272.91 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:12:43,234] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.11 | bwd_microstep: 272.80 | bwd_inner_microstep: 272.79 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 01:12:43,716] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.46 | bwd_microstep: 272.82 | bwd_inner_microstep: 272.80 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:12:44,195] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.39 | bwd_microstep: 272.50 | bwd_inner_microstep: 272.48 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:12:44,674] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.09 | bwd_microstep: 271.58 | bwd_inner_microstep: 271.56 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:12:45,153] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.14 | bwd_microstep: 271.55 | bwd_inner_microstep: 271.53 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 01:12:45,632] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.02 | bwd_microstep: 271.58 | bwd_inner_microstep: 271.56 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:12:46,109] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.46 | bwd_microstep: 271.37 | bwd_inner_microstep: 271.36 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 01:12:46,675] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.26 | optimizer_step: 17.51 +[2025-05-02 01:12:46,675] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.92 | bwd_microstep: 338.15 | bwd_inner_microstep: 271.66 | bwd_allreduce_microstep: 66.45 | step_microstep: 24.76 +[2025-05-02 01:12:46,676] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2957.90 | bwd: 4367.33 | bwd_inner: 4300.48 | bwd_allreduce: 66.58 | step: 25.74 + 12%|█▏ | 1066/8720 [2:57:20<15:41:41, 7.38s/it] {'loss': 0.5378, 'grad_norm': 8.334813117980957, 'learning_rate': 9.778697413904093e-06, 'epoch': 1.22} + 12%|█▏ | 1066/8720 [2:57:20<15:41:41, 7.38s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 01:12:47,155] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.07 | bwd_microstep: 270.45 | bwd_inner_microstep: 270.43 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2027 +[2025-05-02 01:12:47,666] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 199.69 | bwd_microstep: 296.74 | bwd_inner_microstep: 296.72 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1920 +[2025-05-02 01:12:48,149] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.92 | bwd_microstep: 276.31 | bwd_inner_microstep: 276.29 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1379 +[2025-05-02 01:12:48,514] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.26 | bwd_microstep: 208.29 | bwd_inner_microstep: 208.27 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 01:12:48,991] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.37 | bwd_microstep: 273.11 | bwd_inner_microstep: 273.09 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 01:12:49,468] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.89 | bwd_microstep: 273.13 | bwd_inner_microstep: 273.11 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 01:12:49,944] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.09 | bwd_microstep: 272.65 | bwd_inner_microstep: 272.64 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 01:12:50,419] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.93 | bwd_microstep: 272.82 | bwd_inner_microstep: 272.80 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 01:12:50,896] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.01 | bwd_microstep: 272.82 | bwd_inner_microstep: 272.80 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 01:12:51,373] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.35 | bwd_microstep: 272.96 | bwd_inner_microstep: 272.95 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:12:51,850] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.08 | bwd_microstep: 272.38 | bwd_inner_microstep: 272.36 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 01:12:52,327] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.72 | bwd_microstep: 272.86 | bwd_inner_microstep: 272.84 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:12:52,802] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.92 | bwd_microstep: 272.13 | bwd_inner_microstep: 272.11 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 01:12:53,278] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.06 | bwd_microstep: 271.41 | bwd_inner_microstep: 271.39 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:12:53,755] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.88 | bwd_microstep: 271.08 | bwd_inner_microstep: 271.06 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:12:54,332] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.04 | optimizer_gradients: 2.16 | optimizer_step: 17.03 +[2025-05-02 01:12:54,333] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.87 | bwd_microstep: 347.65 | bwd_inner_microstep: 271.86 | bwd_allreduce_microstep: 75.74 | step_microstep: 24.30 +[2025-05-02 01:12:54,334] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2982.83 | bwd: 4396.80 | bwd_inner: 4320.74 | bwd_allreduce: 75.83 | step: 24.93 + 12%|█▏ | 1067/8720 [2:57:28<15:52:05, 7.46s/it] {'loss': 0.5597, 'grad_norm': 11.950666427612305, 'learning_rate': 9.778150677668856e-06, 'epoch': 1.22} + 12%|█▏ | 1067/8720 [2:57:28<15:52:05, 7.46s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 01:12:54,812] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.86 | bwd_microstep: 271.08 | bwd_inner_microstep: 271.06 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1921 +[2025-05-02 01:12:55,310] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.58 | bwd_microstep: 287.48 | bwd_inner_microstep: 287.47 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.13 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1891 +[2025-05-02 01:12:55,791] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.43 | bwd_microstep: 275.43 | bwd_inner_microstep: 275.42 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-02 01:12:56,272] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.92 | bwd_microstep: 274.85 | bwd_inner_microstep: 274.83 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1366 +[2025-05-02 01:12:56,635] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.96 | bwd_microstep: 207.14 | bwd_inner_microstep: 207.12 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-02 01:12:57,114] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.55 | bwd_microstep: 273.45 | bwd_inner_microstep: 273.43 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 01:12:57,591] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.59 | bwd_microstep: 272.98 | bwd_inner_microstep: 272.97 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 322 +[2025-05-02 01:12:57,790] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 66.97 | bwd_microstep: 118.54 | bwd_inner_microstep: 118.38 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:12:58,266] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.35 | bwd_microstep: 272.64 | bwd_inner_microstep: 272.62 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:12:58,742] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.50 | bwd_microstep: 272.69 | bwd_inner_microstep: 272.67 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 326 +[2025-05-02 01:12:58,948] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 73.28 | bwd_microstep: 119.53 | bwd_inner_microstep: 119.40 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:12:59,423] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.66 | bwd_microstep: 272.32 | bwd_inner_microstep: 272.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 01:12:59,897] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.72 | bwd_microstep: 271.23 | bwd_inner_microstep: 271.22 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:13:00,372] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.53 | bwd_microstep: 271.36 | bwd_inner_microstep: 271.34 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 01:13:00,847] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.98 | bwd_microstep: 271.54 | bwd_inner_microstep: 271.52 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:13:01,413] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.13 | optimizer_step: 17.10 +[2025-05-02 01:13:01,413] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.13 | bwd_microstep: 337.77 | bwd_inner_microstep: 271.77 | bwd_allreduce_microstep: 65.95 | step_microstep: 24.22 +[2025-05-02 01:13:01,414] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2743.75 | bwd: 4070.07 | bwd_inner: 4003.60 | bwd_allreduce: 66.13 | step: 25.31 + 12%|█▏ | 1068/8720 [2:57:35<15:37:16, 7.35s/it] {'loss': 0.3047, 'grad_norm': 4.18209171295166, 'learning_rate': 9.777603282222961e-06, 'epoch': 1.22} + 12%|█▏ | 1068/8720 [2:57:35<15:37:16, 7.35s/it]dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1345 +[2025-05-02 01:13:01,779] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.71 | bwd_microstep: 205.24 | bwd_inner_microstep: 205.03 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1962 +[2025-05-02 01:13:02,281] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.89 | bwd_microstep: 290.69 | bwd_inner_microstep: 290.67 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-02 01:13:02,758] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.63 | bwd_microstep: 273.81 | bwd_inner_microstep: 273.79 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-02 01:13:03,237] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.75 | bwd_microstep: 274.12 | bwd_inner_microstep: 274.10 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1360 +[2025-05-02 01:13:03,600] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.19 | bwd_microstep: 206.67 | bwd_inner_microstep: 206.65 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:13:04,075] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.90 | bwd_microstep: 272.41 | bwd_inner_microstep: 272.40 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:13:04,551] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.86 | bwd_microstep: 271.36 | bwd_inner_microstep: 271.35 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:13:05,031] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.45 | bwd_microstep: 272.62 | bwd_inner_microstep: 272.60 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 01:13:05,513] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.98 | bwd_microstep: 272.40 | bwd_inner_microstep: 272.38 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:13:05,991] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.55 | bwd_microstep: 271.21 | bwd_inner_microstep: 271.20 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:13:06,469] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.05 | bwd_microstep: 271.49 | bwd_inner_microstep: 271.47 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:13:06,949] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.33 | bwd_microstep: 272.37 | bwd_inner_microstep: 272.35 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 323 +[2025-05-02 01:13:07,162] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 78.25 | bwd_microstep: 119.58 | bwd_inner_microstep: 119.26 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:13:07,638] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.82 | bwd_microstep: 271.31 | bwd_inner_microstep: 271.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:13:08,112] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.71 | bwd_microstep: 271.13 | bwd_inner_microstep: 271.11 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 01:13:08,677] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.04 | optimizer_gradients: 2.12 | optimizer_step: 17.08 +[2025-05-02 01:13:08,677] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.65 | bwd_microstep: 337.66 | bwd_inner_microstep: 271.76 | bwd_allreduce_microstep: 65.85 | step_microstep: 24.04 +[2025-05-02 01:13:08,678] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2818.41 | bwd: 4154.12 | bwd_inner: 4087.48 | bwd_allreduce: 66.17 | step: 24.86 + 12%|█▏ | 1069/8720 [2:57:42<15:33:53, 7.32s/it] {'loss': 0.6461, 'grad_norm': 9.560783386230469, 'learning_rate': 9.777055227641928e-06, 'epoch': 1.23} + 12%|█▏ | 1069/8720 [2:57:42<15:33:53, 7.32s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1890 +[2025-05-02 01:13:09,160] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.79 | bwd_microstep: 273.96 | bwd_inner_microstep: 273.95 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1910 +[2025-05-02 01:13:09,642] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.84 | bwd_microstep: 276.90 | bwd_inner_microstep: 276.88 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1887 +[2025-05-02 01:13:10,120] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.84 | bwd_microstep: 274.58 | bwd_inner_microstep: 274.56 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-02 01:13:10,597] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.75 | bwd_microstep: 273.63 | bwd_inner_microstep: 273.61 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-02 01:13:11,074] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.77 | bwd_microstep: 273.64 | bwd_inner_microstep: 273.62 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 01:13:11,551] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.77 | bwd_microstep: 272.78 | bwd_inner_microstep: 272.76 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.16 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 01:13:12,028] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.90 | bwd_microstep: 273.03 | bwd_inner_microstep: 273.01 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:13:12,506] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.32 | bwd_microstep: 272.60 | bwd_inner_microstep: 272.58 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 834 +[2025-05-02 01:13:12,738] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 91.76 | bwd_microstep: 126.08 | bwd_inner_microstep: 125.99 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 01:13:13,213] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.65 | bwd_microstep: 272.71 | bwd_inner_microstep: 272.70 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:13:13,689] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.46 | bwd_microstep: 272.60 | bwd_inner_microstep: 272.58 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:13:14,165] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.12 | bwd_microstep: 272.62 | bwd_inner_microstep: 272.61 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:13:14,641] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.82 | bwd_microstep: 272.38 | bwd_inner_microstep: 272.36 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:13:15,117] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.26 | bwd_microstep: 272.54 | bwd_inner_microstep: 272.53 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 01:13:15,591] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.62 | bwd_microstep: 271.29 | bwd_inner_microstep: 271.28 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:13:16,157] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.04 | optimizer_gradients: 2.12 | optimizer_step: 17.05 +[2025-05-02 01:13:16,158] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.17 | bwd_microstep: 339.25 | bwd_inner_microstep: 272.88 | bwd_allreduce_microstep: 66.32 | step_microstep: 23.93 +[2025-05-02 01:13:16,159] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2922.60 | bwd: 4290.62 | bwd_inner: 4223.90 | bwd_allreduce: 66.45 | step: 24.75 + 12%|█▏ | 1070/8720 [2:57:49<15:39:46, 7.37s/it] {'loss': 0.8887, 'grad_norm': 9.881577491760254, 'learning_rate': 9.776506514001371e-06, 'epoch': 1.23} + 12%|█▏ | 1070/8720 [2:57:49<15:39:46, 7.37s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 01:13:16,636] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.86 | bwd_microstep: 270.35 | bwd_inner_microstep: 270.34 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1958 +[2025-05-02 01:13:17,139] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 197.59 | bwd_microstep: 290.48 | bwd_inner_microstep: 290.46 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 411 +[2025-05-02 01:13:17,347] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 66.92 | bwd_microstep: 127.90 | bwd_inner_microstep: 127.77 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1910 +[2025-05-02 01:13:17,829] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.82 | bwd_microstep: 276.37 | bwd_inner_microstep: 276.36 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1887 +[2025-05-02 01:13:18,308] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.78 | bwd_microstep: 274.81 | bwd_inner_microstep: 274.79 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 326 +[2025-05-02 01:13:18,530] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 85.69 | bwd_microstep: 120.60 | bwd_inner_microstep: 120.45 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1357 +[2025-05-02 01:13:18,894] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.84 | bwd_microstep: 206.43 | bwd_inner_microstep: 206.41 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 01:13:19,375] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.16 | bwd_microstep: 273.05 | bwd_inner_microstep: 273.03 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 01:13:19,857] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.55 | bwd_microstep: 273.04 | bwd_inner_microstep: 273.02 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:13:20,337] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.58 | bwd_microstep: 272.57 | bwd_inner_microstep: 272.55 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 01:13:20,818] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.82 | bwd_microstep: 272.90 | bwd_inner_microstep: 272.89 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 01:13:21,296] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.16 | bwd_microstep: 272.39 | bwd_inner_microstep: 272.37 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 01:13:21,774] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.94 | bwd_microstep: 271.36 | bwd_inner_microstep: 271.34 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:13:22,250] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.82 | bwd_microstep: 271.17 | bwd_inner_microstep: 271.16 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:13:22,727] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.85 | bwd_microstep: 271.05 | bwd_inner_microstep: 271.04 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 01:13:23,306] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.15 | optimizer_step: 17.09 +[2025-05-02 01:13:23,306] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.12 | bwd_microstep: 348.90 | bwd_inner_microstep: 271.58 | bwd_allreduce_microstep: 77.27 | step_microstep: 24.77 +[2025-05-02 01:13:23,307] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2752.13 | bwd: 4093.41 | bwd_inner: 4015.60 | bwd_allreduce: 77.46 | step: 25.67 + 12%|█▏ | 1071/8720 [2:57:57<15:31:13, 7.30s/it] {'loss': 0.6943, 'grad_norm': 11.370951652526855, 'learning_rate': 9.775957141376992e-06, 'epoch': 1.23} + 12%|█▏ | 1071/8720 [2:57:57<15:31:13, 7.30s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 01:13:23,787] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.47 | bwd_microstep: 270.14 | bwd_inner_microstep: 270.13 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1970 +[2025-05-02 01:13:24,292] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 198.79 | bwd_microstep: 291.45 | bwd_inner_microstep: 291.43 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 01:13:24,769] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.33 | bwd_microstep: 273.07 | bwd_inner_microstep: 273.05 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1097 +[2025-05-02 01:13:25,064] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 117.68 | bwd_microstep: 161.31 | bwd_inner_microstep: 161.28 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.09 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1357 +[2025-05-02 01:13:25,427] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.42 | bwd_microstep: 206.98 | bwd_inner_microstep: 206.84 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.18 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 842 +[2025-05-02 01:13:25,668] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.84 | bwd_microstep: 132.69 | bwd_inner_microstep: 132.45 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 01:13:26,145] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.91 | bwd_microstep: 273.26 | bwd_inner_microstep: 273.24 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1092 +[2025-05-02 01:13:26,436] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 116.04 | bwd_microstep: 160.86 | bwd_inner_microstep: 160.84 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:13:26,912] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.45 | bwd_microstep: 272.99 | bwd_inner_microstep: 272.97 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:13:27,388] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.25 | bwd_microstep: 272.88 | bwd_inner_microstep: 272.86 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:13:27,865] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.39 | bwd_microstep: 272.78 | bwd_inner_microstep: 272.76 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:13:28,342] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.60 | bwd_microstep: 272.85 | bwd_inner_microstep: 272.84 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.16 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:13:28,819] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.22 | bwd_microstep: 271.96 | bwd_inner_microstep: 271.94 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:13:29,294] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.79 | bwd_microstep: 271.71 | bwd_inner_microstep: 271.69 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:13:29,770] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.21 | bwd_microstep: 271.68 | bwd_inner_microstep: 271.66 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:13:30,348] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.15 | optimizer_step: 17.06 +[2025-05-02 01:13:30,348] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.08 | bwd_microstep: 348.37 | bwd_inner_microstep: 272.17 | bwd_allreduce_microstep: 76.15 | step_microstep: 24.71 +[2025-05-02 01:13:30,350] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2742.20 | bwd: 4025.07 | bwd_inner: 3948.18 | bwd_allreduce: 76.43 | step: 25.76 + 12%|█▏ | 1072/8720 [2:58:04<15:21:03, 7.23s/it] {'loss': 0.4342, 'grad_norm': 7.857018947601318, 'learning_rate': 9.775407109844585e-06, 'epoch': 1.23} + 12%|█▏ | 1072/8720 [2:58:04<15:21:03, 7.23s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:13:30,832] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.31 | bwd_microstep: 271.13 | bwd_inner_microstep: 271.11 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1900 +[2025-05-02 01:13:31,314] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.88 | bwd_microstep: 275.92 | bwd_inner_microstep: 275.90 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1890 +[2025-05-02 01:13:31,794] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.29 | bwd_microstep: 275.77 | bwd_inner_microstep: 275.75 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-02 01:13:32,275] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.36 | bwd_microstep: 274.30 | bwd_inner_microstep: 274.28 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-02 01:13:32,757] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.37 | bwd_microstep: 274.81 | bwd_inner_microstep: 274.79 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:13:33,234] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.00 | bwd_microstep: 273.18 | bwd_inner_microstep: 273.16 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:13:33,713] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.48 | bwd_microstep: 273.12 | bwd_inner_microstep: 273.10 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 01:13:34,190] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.43 | bwd_microstep: 273.33 | bwd_inner_microstep: 273.31 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 841 +[2025-05-02 01:13:34,431] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.47 | bwd_microstep: 131.94 | bwd_inner_microstep: 131.92 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 01:13:34,908] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.02 | bwd_microstep: 273.14 | bwd_inner_microstep: 273.13 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:13:35,387] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.47 | bwd_microstep: 272.85 | bwd_inner_microstep: 272.83 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 319 +[2025-05-02 01:13:35,607] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 89.69 | bwd_microstep: 115.04 | bwd_inner_microstep: 114.89 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 01:13:36,083] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.83 | bwd_microstep: 271.83 | bwd_inner_microstep: 271.81 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 832 +[2025-05-02 01:13:36,328] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.88 | bwd_microstep: 130.14 | bwd_inner_microstep: 130.09 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:13:36,805] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.08 | bwd_microstep: 271.55 | bwd_inner_microstep: 271.54 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 832 +[2025-05-02 01:13:37,162] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.14 | optimizer_step: 17.06 +[2025-05-02 01:13:37,163] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 105.87 | bwd_microstep: 208.09 | bwd_inner_microstep: 130.60 | bwd_allreduce_microstep: 77.33 | step_microstep: 24.66 +[2025-05-02 01:13:37,164] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2650.08 | bwd: 3866.18 | bwd_inner: 3788.31 | bwd_allreduce: 77.45 | step: 25.77 + 12%|█▏ | 1073/8720 [2:58:10<15:05:13, 7.10s/it] {'loss': 0.7867, 'grad_norm': 10.904343605041504, 'learning_rate': 9.774856419480033e-06, 'epoch': 1.23} + 12%|█▏ | 1073/8720 [2:58:10<15:05:13, 7.10s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 389 +[2025-05-02 01:13:37,380] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 80.37 | bwd_microstep: 115.30 | bwd_inner_microstep: 115.14 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1954 +[2025-05-02 01:13:37,884] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 196.59 | bwd_microstep: 289.53 | bwd_inner_microstep: 289.51 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 922 +[2025-05-02 01:13:38,148] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 102.04 | bwd_microstep: 145.82 | bwd_inner_microstep: 145.67 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 898 +[2025-05-02 01:13:38,409] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 99.92 | bwd_microstep: 143.83 | bwd_inner_microstep: 143.53 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.12 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 337 +[2025-05-02 01:13:38,632] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 89.19 | bwd_microstep: 117.29 | bwd_inner_microstep: 117.02 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 01:13:39,112] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.48 | bwd_microstep: 273.38 | bwd_inner_microstep: 273.36 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 01:13:39,593] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.38 | bwd_microstep: 273.41 | bwd_inner_microstep: 273.40 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 01:13:40,072] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.86 | bwd_microstep: 272.79 | bwd_inner_microstep: 272.77 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 325 +[2025-05-02 01:13:40,310] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 100.49 | bwd_microstep: 118.22 | bwd_inner_microstep: 117.99 | bwd_allreduce_microstep: 0.08 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:13:40,788] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.40 | bwd_microstep: 272.66 | bwd_inner_microstep: 272.64 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:13:41,267] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.19 | bwd_microstep: 272.47 | bwd_inner_microstep: 272.45 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 321 +[2025-05-02 01:13:41,490] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 81.54 | bwd_microstep: 125.71 | bwd_inner_microstep: 125.40 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.26 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 01:13:41,966] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.15 | bwd_microstep: 271.34 | bwd_inner_microstep: 271.32 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 315 +[2025-05-02 01:13:42,178] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 75.27 | bwd_microstep: 120.97 | bwd_inner_microstep: 120.84 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 01:13:42,652] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.93 | bwd_microstep: 271.22 | bwd_inner_microstep: 271.20 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 895 +[2025-05-02 01:13:42,993] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.20 | optimizer_step: 17.25 +[2025-05-02 01:13:42,993] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 98.68 | bwd_microstep: 204.13 | bwd_inner_microstep: 136.83 | bwd_allreduce_microstep: 67.22 | step_microstep: 24.57 +[2025-05-02 01:13:42,994] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2240.14 | bwd: 3288.20 | bwd_inner: 3219.43 | bwd_allreduce: 67.84 | step: 25.87 + 12%|█▏ | 1074/8720 [2:58:16<14:16:24, 6.72s/it] {'loss': 0.746, 'grad_norm': 4.894636631011963, 'learning_rate': 9.77430507035931e-06, 'epoch': 1.23} + 12%|█▏ | 1074/8720 [2:58:16<14:16:24, 6.72s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 01:13:43,475] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.83 | bwd_microstep: 272.06 | bwd_inner_microstep: 272.04 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 400 +[2025-05-02 01:13:43,688] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 82.96 | bwd_microstep: 115.78 | bwd_inner_microstep: 115.65 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-02 01:13:44,165] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.81 | bwd_microstep: 274.06 | bwd_inner_microstep: 274.04 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-02 01:13:44,643] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.98 | bwd_microstep: 273.52 | bwd_inner_microstep: 273.50 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-02 01:13:45,121] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.72 | bwd_microstep: 273.57 | bwd_inner_microstep: 273.56 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 01:13:45,598] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.65 | bwd_microstep: 273.04 | bwd_inner_microstep: 273.03 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 01:13:46,077] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.66 | bwd_microstep: 274.02 | bwd_inner_microstep: 274.00 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-02 01:13:46,555] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.62 | bwd_microstep: 273.79 | bwd_inner_microstep: 273.77 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 01:13:47,034] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.41 | bwd_microstep: 273.35 | bwd_inner_microstep: 273.34 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 01:13:47,514] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.22 | bwd_microstep: 272.88 | bwd_inner_microstep: 272.86 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 837 +[2025-05-02 01:13:47,746] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 91.34 | bwd_microstep: 126.49 | bwd_inner_microstep: 126.24 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 842 +[2025-05-02 01:13:47,989] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.05 | bwd_microstep: 131.86 | bwd_inner_microstep: 131.84 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:13:48,467] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.00 | bwd_microstep: 272.60 | bwd_inner_microstep: 272.58 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 836 +[2025-05-02 01:13:48,708] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 96.13 | bwd_microstep: 125.89 | bwd_inner_microstep: 125.67 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 01:13:49,184] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.46 | bwd_microstep: 270.98 | bwd_inner_microstep: 270.96 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 01:13:49,771] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.20 | optimizer_step: 17.27 +[2025-05-02 01:13:49,772] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.81 | bwd_microstep: 354.53 | bwd_inner_microstep: 271.50 | bwd_allreduce_microstep: 82.98 | step_microstep: 25.18 +[2025-05-02 01:13:49,773] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2628.33 | bwd: 3858.48 | bwd_inner: 3774.62 | bwd_allreduce: 83.31 | step: 26.23 + 12%|█▏ | 1075/8720 [2:58:23<14:18:36, 6.74s/it] {'loss': 0.5918, 'grad_norm': 4.304069519042969, 'learning_rate': 9.773753062558485e-06, 'epoch': 1.23} + 12%|█▏ | 1075/8720 [2:58:23<14:18:36, 6.74s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 01:13:50,255] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.81 | bwd_microstep: 270.39 | bwd_inner_microstep: 270.37 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1942 +[2025-05-02 01:13:50,758] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 196.47 | bwd_microstep: 288.79 | bwd_inner_microstep: 288.77 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1905 +[2025-05-02 01:13:51,242] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.78 | bwd_microstep: 276.06 | bwd_inner_microstep: 276.04 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1903 +[2025-05-02 01:13:51,724] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.72 | bwd_microstep: 275.65 | bwd_inner_microstep: 275.64 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-02 01:13:52,204] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.79 | bwd_microstep: 274.12 | bwd_inner_microstep: 274.10 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-02 01:13:52,686] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.59 | bwd_microstep: 274.22 | bwd_inner_microstep: 274.21 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 01:13:53,167] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.95 | bwd_microstep: 273.50 | bwd_inner_microstep: 273.49 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 01:13:53,648] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.98 | bwd_microstep: 273.50 | bwd_inner_microstep: 273.48 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 01:13:54,128] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.61 | bwd_microstep: 272.99 | bwd_inner_microstep: 272.97 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 01:13:54,606] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.36 | bwd_microstep: 272.71 | bwd_inner_microstep: 272.69 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 323 +[2025-05-02 01:13:54,817] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 76.09 | bwd_microstep: 118.75 | bwd_inner_microstep: 118.52 | bwd_allreduce_microstep: 0.09 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:13:55,293] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.31 | bwd_microstep: 272.86 | bwd_inner_microstep: 272.84 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 842 +[2025-05-02 01:13:55,534] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.85 | bwd_microstep: 132.26 | bwd_inner_microstep: 131.96 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 01:13:56,012] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.74 | bwd_microstep: 272.88 | bwd_inner_microstep: 272.86 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:13:56,487] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.77 | bwd_microstep: 271.39 | bwd_inner_microstep: 271.37 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:13:57,052] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.20 | optimizer_step: 17.22 +[2025-05-02 01:13:57,052] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.74 | bwd_microstep: 338.08 | bwd_inner_microstep: 271.86 | bwd_allreduce_microstep: 66.17 | step_microstep: 24.47 +[2025-05-02 01:13:57,054] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2818.24 | bwd: 4158.21 | bwd_inner: 4091.27 | bwd_allreduce: 66.44 | step: 25.40 + 12%|█▏ | 1076/8720 [2:58:30<14:39:07, 6.90s/it] {'loss': 0.6735, 'grad_norm': 8.637699127197266, 'learning_rate': 9.773200396153711e-06, 'epoch': 1.23} + 12%|█▏ | 1076/8720 [2:58:30<14:39:07, 6.90s/it]dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 827 +[2025-05-02 01:13:57,295] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 92.55 | bwd_microstep: 130.01 | bwd_inner_microstep: 129.86 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1915 +[2025-05-02 01:13:57,778] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.23 | bwd_microstep: 276.53 | bwd_inner_microstep: 276.51 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.13 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1891 +[2025-05-02 01:13:58,259] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.86 | bwd_microstep: 274.92 | bwd_inner_microstep: 274.90 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1889 +[2025-05-02 01:13:58,738] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.78 | bwd_microstep: 274.74 | bwd_inner_microstep: 274.72 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-02 01:13:59,217] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.82 | bwd_microstep: 274.44 | bwd_inner_microstep: 274.43 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 337 +[2025-05-02 01:13:59,422] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 70.11 | bwd_microstep: 121.11 | bwd_inner_microstep: 120.90 | bwd_allreduce_microstep: 0.08 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-02 01:13:59,898] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.71 | bwd_microstep: 273.60 | bwd_inner_microstep: 273.58 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-02 01:14:00,376] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.70 | bwd_microstep: 273.59 | bwd_inner_microstep: 273.57 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 01:14:00,855] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.22 | bwd_microstep: 273.60 | bwd_inner_microstep: 273.59 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 01:14:01,333] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.81 | bwd_microstep: 272.86 | bwd_inner_microstep: 272.85 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 01:14:01,812] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.92 | bwd_microstep: 272.97 | bwd_inner_microstep: 272.95 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 01:14:02,289] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.46 | bwd_microstep: 273.16 | bwd_inner_microstep: 273.14 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 325 +[2025-05-02 01:14:02,492] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 68.60 | bwd_microstep: 121.27 | bwd_inner_microstep: 121.02 | bwd_allreduce_microstep: 0.10 | step_microstep: 0.09 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 321 +[2025-05-02 01:14:02,699] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 75.46 | bwd_microstep: 117.47 | bwd_inner_microstep: 117.30 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:14:03,175] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.16 | bwd_microstep: 272.42 | bwd_inner_microstep: 272.40 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 835 +[2025-05-02 01:14:03,502] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.20 | optimizer_step: 17.39 +[2025-05-02 01:14:03,502] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 92.61 | bwd_microstep: 195.68 | bwd_inner_microstep: 128.58 | bwd_allreduce_microstep: 67.02 | step_microstep: 24.62 +[2025-05-02 01:14:03,503] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2476.72 | bwd: 3698.44 | bwd_inner: 3630.53 | bwd_allreduce: 67.34 | step: 25.72 + 12%|█▏ | 1077/8720 [2:58:37<14:21:46, 6.77s/it] {'loss': 0.7694, 'grad_norm': 7.130340099334717, 'learning_rate': 9.77264707122124e-06, 'epoch': 1.24} + 12%|█▏ | 1077/8720 [2:58:37<14:21:46, 6.77s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 01:14:03,981] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.77 | bwd_microstep: 270.35 | bwd_inner_microstep: 270.33 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2244 +[2025-05-02 01:14:04,529] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 208.60 | bwd_microstep: 322.72 | bwd_inner_microstep: 322.70 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1891 +[2025-05-02 01:14:05,010] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.72 | bwd_microstep: 275.00 | bwd_inner_microstep: 274.99 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 345 +[2025-05-02 01:14:05,234] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 91.08 | bwd_microstep: 117.21 | bwd_inner_microstep: 117.02 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1890 +[2025-05-02 01:14:05,716] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.28 | bwd_microstep: 274.57 | bwd_inner_microstep: 274.55 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-02 01:14:06,198] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.86 | bwd_microstep: 273.70 | bwd_inner_microstep: 273.68 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.08 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 852 +[2025-05-02 01:14:06,448] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 97.73 | bwd_microstep: 132.75 | bwd_inner_microstep: 132.60 | bwd_allreduce_microstep: 0.08 | step_microstep: 0.10 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1096 +[2025-05-02 01:14:06,742] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 115.29 | bwd_microstep: 161.18 | bwd_inner_microstep: 161.03 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 01:14:07,221] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.26 | bwd_microstep: 273.02 | bwd_inner_microstep: 273.00 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 01:14:07,702] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.69 | bwd_microstep: 273.06 | bwd_inner_microstep: 273.04 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 01:14:08,184] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.79 | bwd_microstep: 273.00 | bwd_inner_microstep: 272.98 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:14:08,663] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.37 | bwd_microstep: 272.57 | bwd_inner_microstep: 272.56 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 834 +[2025-05-02 01:14:08,904] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.30 | bwd_microstep: 127.99 | bwd_inner_microstep: 127.65 | bwd_allreduce_microstep: 0.14 | step_microstep: 0.22 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:14:09,383] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.14 | bwd_microstep: 271.39 | bwd_inner_microstep: 271.38 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:14:09,859] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.51 | bwd_microstep: 271.23 | bwd_inner_microstep: 271.21 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 833 +[2025-05-02 01:14:10,193] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.17 | optimizer_step: 17.20 +[2025-05-02 01:14:10,193] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 90.10 | bwd_microstep: 204.23 | bwd_inner_microstep: 136.28 | bwd_allreduce_microstep: 67.80 | step_microstep: 24.46 +[2025-05-02 01:14:10,195] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2582.14 | bwd: 3794.07 | bwd_inner: 3725.19 | bwd_allreduce: 68.19 | step: 25.56 + 12%|█▏ | 1078/8720 [2:58:43<14:18:51, 6.74s/it] {'loss': 0.8048, 'grad_norm': 5.032370090484619, 'learning_rate': 9.772093087837408e-06, 'epoch': 1.24} + 12%|█▏ | 1078/8720 [2:58:43<14:18:51, 6.74s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:14:10,674] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.42 | bwd_microstep: 270.57 | bwd_inner_microstep: 270.55 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1926 +[2025-05-02 01:14:11,173] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.23 | bwd_microstep: 287.47 | bwd_inner_microstep: 287.46 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1903 +[2025-05-02 01:14:11,655] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.71 | bwd_microstep: 275.82 | bwd_inner_microstep: 275.80 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 852 +[2025-05-02 01:14:11,899] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.03 | bwd_microstep: 133.15 | bwd_inner_microstep: 133.10 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.09 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 852 +[2025-05-02 01:14:12,141] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.15 | bwd_microstep: 132.80 | bwd_inner_microstep: 132.66 | bwd_allreduce_microstep: 0.10 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 01:14:12,617] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.89 | bwd_microstep: 273.16 | bwd_inner_microstep: 273.14 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 835 +[2025-05-02 01:14:12,863] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 101.77 | bwd_microstep: 125.80 | bwd_inner_microstep: 125.71 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.11 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 329 +[2025-05-02 01:14:13,089] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 88.47 | bwd_microstep: 120.71 | bwd_inner_microstep: 120.56 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 01:14:13,568] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.04 | bwd_microstep: 272.90 | bwd_inner_microstep: 272.89 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:14:14,051] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.89 | bwd_microstep: 272.42 | bwd_inner_microstep: 272.41 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.06 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 836 +[2025-05-02 01:14:14,308] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 111.79 | bwd_microstep: 125.40 | bwd_inner_microstep: 125.21 | bwd_allreduce_microstep: 0.08 | step_microstep: 0.14 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 01:14:14,794] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.73 | bwd_microstep: 273.70 | bwd_inner_microstep: 273.68 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:14:15,273] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.63 | bwd_microstep: 272.70 | bwd_inner_microstep: 272.68 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:14:15,752] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.69 | bwd_microstep: 272.27 | bwd_inner_microstep: 272.26 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:14:16,230] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.81 | bwd_microstep: 272.29 | bwd_inner_microstep: 272.27 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 827 +[2025-05-02 01:14:16,590] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.15 | optimizer_step: 17.08 +[2025-05-02 01:14:16,591] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 99.09 | bwd_microstep: 219.62 | bwd_inner_microstep: 142.76 | bwd_allreduce_microstep: 76.76 | step_microstep: 24.85 +[2025-05-02 01:14:16,592] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2480.01 | bwd: 3600.90 | bwd_inner: 3523.23 | bwd_allreduce: 77.10 | step: 25.93 + 12%|█▏ | 1079/8720 [2:58:50<14:05:34, 6.64s/it] {'loss': 0.7867, 'grad_norm': 13.008925437927246, 'learning_rate': 9.771538446078648e-06, 'epoch': 1.24} + 12%|█▏ | 1079/8720 [2:58:50<14:05:34, 6.64s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 01:14:17,072] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.27 | bwd_microstep: 270.34 | bwd_inner_microstep: 270.32 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1916 +[2025-05-02 01:14:17,556] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.51 | bwd_microstep: 276.34 | bwd_inner_microstep: 276.32 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1912 +[2025-05-02 01:14:18,039] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.66 | bwd_microstep: 276.63 | bwd_inner_microstep: 276.61 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-02 01:14:18,519] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.84 | bwd_microstep: 274.47 | bwd_inner_microstep: 274.46 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 01:14:18,997] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.52 | bwd_microstep: 273.22 | bwd_inner_microstep: 273.20 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 01:14:19,474] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.55 | bwd_microstep: 273.39 | bwd_inner_microstep: 273.37 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1350 +[2025-05-02 01:14:19,836] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.72 | bwd_microstep: 205.99 | bwd_inner_microstep: 205.92 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 01:14:20,313] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.11 | bwd_microstep: 273.12 | bwd_inner_microstep: 273.10 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 01:14:20,790] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.09 | bwd_microstep: 272.37 | bwd_inner_microstep: 272.35 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 332 +[2025-05-02 01:14:21,007] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 82.37 | bwd_microstep: 118.70 | bwd_inner_microstep: 118.48 | bwd_allreduce_microstep: 0.08 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 01:14:21,485] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.31 | bwd_microstep: 272.43 | bwd_inner_microstep: 272.41 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 01:14:21,967] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.40 | bwd_microstep: 272.96 | bwd_inner_microstep: 272.94 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:14:22,447] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.05 | bwd_microstep: 272.46 | bwd_inner_microstep: 272.45 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:14:22,927] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.60 | bwd_microstep: 272.37 | bwd_inner_microstep: 272.35 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1342 +[2025-05-02 01:14:23,294] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.54 | bwd_microstep: 204.59 | bwd_inner_microstep: 204.44 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:14:23,890] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.16 | optimizer_step: 17.07 +[2025-05-02 01:14:23,891] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.23 | bwd_microstep: 358.28 | bwd_inner_microstep: 271.98 | bwd_allreduce_microstep: 86.24 | step_microstep: 24.73 +[2025-05-02 01:14:23,892] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2816.39 | bwd: 4167.73 | bwd_inner: 4080.76 | bwd_allreduce: 86.52 | step: 25.67 + 12%|█▏ | 1080/8720 [2:58:57<14:30:40, 6.84s/it] {'loss': 0.476, 'grad_norm': 10.103532791137695, 'learning_rate': 9.770983146021475e-06, 'epoch': 1.24} + 12%|█▏ | 1080/8720 [2:58:57<14:30:40, 6.84s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:14:24,373] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.70 | bwd_microstep: 270.61 | bwd_inner_microstep: 270.60 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 341 +[2025-05-02 01:14:24,599] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 89.82 | bwd_microstep: 119.19 | bwd_inner_microstep: 118.88 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:14:25,078] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.52 | bwd_microstep: 272.67 | bwd_inner_microstep: 272.66 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:14:25,558] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.55 | bwd_microstep: 272.67 | bwd_inner_microstep: 272.65 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 01:14:26,040] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.13 | bwd_microstep: 272.95 | bwd_inner_microstep: 272.94 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:14:26,523] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.17 | bwd_microstep: 272.73 | bwd_inner_microstep: 272.71 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:14:27,006] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.02 | bwd_microstep: 272.44 | bwd_inner_microstep: 272.42 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 01:14:27,488] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.85 | bwd_microstep: 272.73 | bwd_inner_microstep: 272.71 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:14:27,966] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.58 | bwd_microstep: 272.41 | bwd_inner_microstep: 272.39 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 01:14:28,446] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.62 | bwd_microstep: 272.27 | bwd_inner_microstep: 272.25 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 01:14:28,925] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.20 | bwd_microstep: 272.31 | bwd_inner_microstep: 272.29 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 01:14:29,406] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.19 | bwd_microstep: 272.25 | bwd_inner_microstep: 272.23 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:14:29,883] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.14 | bwd_microstep: 271.31 | bwd_inner_microstep: 271.29 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 01:14:30,360] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.67 | bwd_microstep: 271.20 | bwd_inner_microstep: 271.19 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:14:30,838] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.81 | bwd_microstep: 271.30 | bwd_inner_microstep: 271.29 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 01:14:31,422] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.15 | optimizer_step: 17.08 +[2025-05-02 01:14:31,422] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.47 | bwd_microstep: 351.71 | bwd_inner_microstep: 271.73 | bwd_allreduce_microstep: 79.93 | step_microstep: 24.79 +[2025-05-02 01:14:31,424] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2920.01 | bwd: 4280.78 | bwd_inner: 4200.27 | bwd_allreduce: 80.13 | step: 25.64 + 12%|█▏ | 1081/8720 [2:59:05<14:57:04, 7.05s/it] {'loss': 0.7708, 'grad_norm': 14.843026161193848, 'learning_rate': 9.770427187742506e-06, 'epoch': 1.24} + 12%|█▏ | 1081/8720 [2:59:05<14:57:04, 7.05s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1850 +[2025-05-02 01:14:31,904] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.56 | bwd_microstep: 270.26 | bwd_inner_microstep: 270.24 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1990 +[2025-05-02 01:14:32,413] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 197.75 | bwd_microstep: 294.01 | bwd_inner_microstep: 294.00 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1922 +[2025-05-02 01:14:32,913] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 194.70 | bwd_microstep: 287.41 | bwd_inner_microstep: 287.40 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1886 +[2025-05-02 01:14:33,396] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.01 | bwd_microstep: 274.52 | bwd_inner_microstep: 274.50 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1364 +[2025-05-02 01:14:33,767] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.96 | bwd_microstep: 207.10 | bwd_inner_microstep: 207.05 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-02 01:14:34,252] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.51 | bwd_microstep: 274.38 | bwd_inner_microstep: 274.37 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1366 +[2025-05-02 01:14:34,620] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 142.09 | bwd_microstep: 207.11 | bwd_inner_microstep: 207.09 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:14:35,098] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.28 | bwd_microstep: 272.56 | bwd_inner_microstep: 272.54 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:14:35,576] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.62 | bwd_microstep: 272.75 | bwd_inner_microstep: 272.73 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:14:36,055] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.74 | bwd_microstep: 272.69 | bwd_inner_microstep: 272.67 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 01:14:36,536] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.11 | bwd_microstep: 272.83 | bwd_inner_microstep: 272.81 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:14:37,020] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.23 | bwd_microstep: 272.74 | bwd_inner_microstep: 272.72 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:14:37,500] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.07 | bwd_microstep: 272.52 | bwd_inner_microstep: 272.50 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 01:14:37,980] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.78 | bwd_microstep: 271.51 | bwd_inner_microstep: 271.49 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 01:14:38,460] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.97 | bwd_microstep: 271.19 | bwd_inner_microstep: 271.17 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 829 +[2025-05-02 01:14:38,805] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.14 | optimizer_step: 17.08 +[2025-05-02 01:14:38,805] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.26 | bwd_microstep: 207.97 | bwd_inner_microstep: 131.30 | bwd_allreduce_microstep: 76.50 | step_microstep: 24.73 +[2025-05-02 01:14:38,807] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2847.25 | bwd: 4201.57 | bwd_inner: 4124.64 | bwd_allreduce: 76.56 | step: 25.56 + 12%|█▏ | 1082/8720 [2:59:12<15:09:49, 7.15s/it] {'loss': 0.4506, 'grad_norm': 8.814289093017578, 'learning_rate': 9.769870571318438e-06, 'epoch': 1.24} + 12%|█▏ | 1082/8720 [2:59:12<15:09:49, 7.15s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 316 +[2025-05-02 01:14:39,031] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 79.14 | bwd_microstep: 124.01 | bwd_inner_microstep: 123.81 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 411 +[2025-05-02 01:14:39,246] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 85.56 | bwd_microstep: 114.35 | bwd_inner_microstep: 114.10 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1386 +[2025-05-02 01:14:39,616] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 143.05 | bwd_microstep: 208.98 | bwd_inner_microstep: 208.85 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-02 01:14:40,096] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.04 | bwd_microstep: 273.34 | bwd_inner_microstep: 273.32 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 858 +[2025-05-02 01:14:40,346] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 98.86 | bwd_microstep: 133.56 | bwd_inner_microstep: 133.36 | bwd_allreduce_microstep: 0.10 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 01:14:40,825] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.25 | bwd_microstep: 272.66 | bwd_inner_microstep: 272.65 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-02 01:14:41,308] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.70 | bwd_microstep: 273.57 | bwd_inner_microstep: 273.55 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1349 +[2025-05-02 01:14:41,674] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.83 | bwd_microstep: 205.75 | bwd_inner_microstep: 205.73 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 01:14:42,154] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.47 | bwd_microstep: 272.82 | bwd_inner_microstep: 272.80 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 01:14:42,633] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.89 | bwd_microstep: 273.00 | bwd_inner_microstep: 272.98 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 327 +[2025-05-02 01:14:42,850] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 77.57 | bwd_microstep: 123.97 | bwd_inner_microstep: 123.84 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:14:43,324] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.25 | bwd_microstep: 272.37 | bwd_inner_microstep: 272.35 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:14:43,802] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.48 | bwd_microstep: 272.26 | bwd_inner_microstep: 272.24 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:14:44,283] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.26 | bwd_microstep: 272.39 | bwd_inner_microstep: 272.37 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 01:14:44,765] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.77 | bwd_microstep: 271.19 | bwd_inner_microstep: 271.17 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:14:45,355] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.13 | optimizer_step: 17.12 +[2025-05-02 01:14:45,355] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.44 | bwd_microstep: 353.69 | bwd_inner_microstep: 272.78 | bwd_allreduce_microstep: 80.86 | step_microstep: 24.88 +[2025-05-02 01:14:45,357] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2508.16 | bwd: 3718.01 | bwd_inner: 3636.07 | bwd_allreduce: 81.30 | step: 25.93 + 12%|█▏ | 1083/8720 [2:59:19<14:46:53, 6.97s/it] {'loss': 1.0353, 'grad_norm': 10.678814888000488, 'learning_rate': 9.769313296826066e-06, 'epoch': 1.24} + 12%|█▏ | 1083/8720 [2:59:19<14:46:53, 6.97s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 318 +[2025-05-02 01:14:45,586] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 79.69 | bwd_microstep: 128.76 | bwd_inner_microstep: 128.45 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 358 +[2025-05-02 01:14:45,799] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 79.26 | bwd_microstep: 118.60 | bwd_inner_microstep: 118.29 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1899 +[2025-05-02 01:14:46,283] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.68 | bwd_microstep: 275.49 | bwd_inner_microstep: 275.47 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1883 +[2025-05-02 01:14:46,763] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.19 | bwd_microstep: 274.27 | bwd_inner_microstep: 274.25 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-02 01:14:47,241] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.89 | bwd_microstep: 274.00 | bwd_inner_microstep: 273.98 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 01:14:47,719] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.21 | bwd_microstep: 272.87 | bwd_inner_microstep: 272.86 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:14:48,196] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.83 | bwd_microstep: 272.65 | bwd_inner_microstep: 272.63 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 01:14:48,674] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.49 | bwd_microstep: 273.47 | bwd_inner_microstep: 273.45 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1362 +[2025-05-02 01:14:49,036] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.36 | bwd_microstep: 206.76 | bwd_inner_microstep: 206.74 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:14:49,512] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.72 | bwd_microstep: 272.62 | bwd_inner_microstep: 272.61 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 01:14:49,989] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.43 | bwd_microstep: 272.75 | bwd_inner_microstep: 272.73 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 835 +[2025-05-02 01:14:50,220] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 90.75 | bwd_microstep: 126.05 | bwd_inner_microstep: 125.92 | bwd_allreduce_microstep: 0.08 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:14:50,696] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.67 | bwd_microstep: 272.63 | bwd_inner_microstep: 272.61 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 842 +[2025-05-02 01:14:50,936] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.38 | bwd_microstep: 131.82 | bwd_inner_microstep: 131.80 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:14:51,412] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.53 | bwd_microstep: 272.64 | bwd_inner_microstep: 272.62 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 01:14:51,978] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.14 | optimizer_step: 17.03 +[2025-05-02 01:14:51,978] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.08 | bwd_microstep: 338.09 | bwd_inner_microstep: 271.91 | bwd_allreduce_microstep: 66.14 | step_microstep: 23.99 +[2025-05-02 01:14:51,979] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2562.89 | bwd: 3783.57 | bwd_inner: 3716.45 | bwd_allreduce: 66.53 | step: 24.98 + 12%|█▏ | 1084/8720 [2:59:25<14:33:31, 6.86s/it] {'loss': 0.7563, 'grad_norm': 5.9687418937683105, 'learning_rate': 9.768755364342273e-06, 'epoch': 1.24} + 12%|█▏ | 1084/8720 [2:59:25<14:33:31, 6.86s/it]dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 829 +[2025-05-02 01:14:52,220] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 92.12 | bwd_microstep: 130.00 | bwd_inner_microstep: 129.94 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1903 +[2025-05-02 01:14:52,701] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.56 | bwd_microstep: 276.31 | bwd_inner_microstep: 276.29 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1894 +[2025-05-02 01:14:53,182] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.29 | bwd_microstep: 275.32 | bwd_inner_microstep: 275.31 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-02 01:14:53,660] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.55 | bwd_microstep: 273.86 | bwd_inner_microstep: 273.84 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-02 01:14:54,138] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.69 | bwd_microstep: 273.65 | bwd_inner_microstep: 273.64 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 01:14:54,616] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.90 | bwd_microstep: 273.59 | bwd_inner_microstep: 273.58 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 01:14:55,095] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.19 | bwd_microstep: 273.56 | bwd_inner_microstep: 273.55 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 834 +[2025-05-02 01:14:55,326] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 91.52 | bwd_microstep: 126.17 | bwd_inner_microstep: 126.05 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 01:14:55,803] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.57 | bwd_microstep: 273.14 | bwd_inner_microstep: 273.12 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:14:56,280] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.83 | bwd_microstep: 272.90 | bwd_inner_microstep: 272.88 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:14:56,755] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.67 | bwd_microstep: 271.81 | bwd_inner_microstep: 271.80 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:14:57,233] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.94 | bwd_microstep: 272.79 | bwd_inner_microstep: 272.77 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 01:14:57,711] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.19 | bwd_microstep: 272.22 | bwd_inner_microstep: 272.20 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 01:14:58,188] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.15 | bwd_microstep: 271.83 | bwd_inner_microstep: 271.81 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:14:58,665] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.43 | bwd_microstep: 271.72 | bwd_inner_microstep: 271.70 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 01:14:59,246] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.18 | optimizer_step: 17.61 +[2025-05-02 01:14:59,246] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.28 | bwd_microstep: 350.14 | bwd_inner_microstep: 272.09 | bwd_allreduce_microstep: 78.00 | step_microstep: 25.39 +[2025-05-02 01:14:59,248] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2834.62 | bwd: 4159.06 | bwd_inner: 4080.57 | bwd_allreduce: 78.16 | step: 26.14 + 12%|█▏ | 1085/8720 [2:59:32<14:48:58, 6.99s/it] {'loss': 0.7193, 'grad_norm': 14.912076950073242, 'learning_rate': 9.768196773944036e-06, 'epoch': 1.24} + 12%|█▏ | 1085/8720 [2:59:32<14:48:58, 6.99s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:14:59,732] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.09 | bwd_microstep: 271.15 | bwd_inner_microstep: 271.13 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1899 +[2025-05-02 01:15:00,216] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.65 | bwd_microstep: 275.57 | bwd_inner_microstep: 275.55 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 859 +[2025-05-02 01:15:00,458] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.70 | bwd_microstep: 133.12 | bwd_inner_microstep: 133.08 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 01:15:00,935] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.87 | bwd_microstep: 273.57 | bwd_inner_microstep: 273.55 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 01:15:01,412] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.16 | bwd_microstep: 272.90 | bwd_inner_microstep: 272.88 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:15:01,891] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.38 | bwd_microstep: 272.49 | bwd_inner_microstep: 272.47 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:15:02,368] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.80 | bwd_microstep: 272.72 | bwd_inner_microstep: 272.70 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:15:02,845] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.08 | bwd_microstep: 272.51 | bwd_inner_microstep: 272.50 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:15:03,320] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.14 | bwd_microstep: 272.38 | bwd_inner_microstep: 272.36 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:15:03,796] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.92 | bwd_microstep: 272.53 | bwd_inner_microstep: 272.51 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 322 +[2025-05-02 01:15:04,000] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 69.05 | bwd_microstep: 121.38 | bwd_inner_microstep: 121.09 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 324 +[2025-05-02 01:15:04,206] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 75.77 | bwd_microstep: 116.85 | bwd_inner_microstep: 116.72 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:15:04,681] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.35 | bwd_microstep: 272.31 | bwd_inner_microstep: 272.29 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:15:05,156] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.14 | bwd_microstep: 272.02 | bwd_inner_microstep: 272.00 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:15:05,631] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.38 | bwd_microstep: 271.42 | bwd_inner_microstep: 271.41 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:15:06,197] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.14 | optimizer_step: 17.17 +[2025-05-02 01:15:06,198] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.63 | bwd_microstep: 338.31 | bwd_inner_microstep: 271.85 | bwd_allreduce_microstep: 66.41 | step_microstep: 24.33 +[2025-05-02 01:15:06,199] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2691.85 | bwd: 3981.28 | bwd_inner: 3914.18 | bwd_allreduce: 66.67 | step: 25.14 + 12%|█▏ | 1086/8720 [2:59:39<14:47:25, 6.97s/it] {'loss': 0.6656, 'grad_norm': 12.764320373535156, 'learning_rate': 9.767637525708416e-06, 'epoch': 1.25} + 12%|█▏ | 1086/8720 [2:59:39<14:47:25, 6.97s/it]dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 827 +[2025-05-02 01:15:06,439] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 91.64 | bwd_microstep: 129.83 | bwd_inner_microstep: 129.78 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1908 +[2025-05-02 01:15:06,920] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.38 | bwd_microstep: 275.98 | bwd_inner_microstep: 275.96 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1913 +[2025-05-02 01:15:07,401] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.82 | bwd_microstep: 275.90 | bwd_inner_microstep: 275.89 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1883 +[2025-05-02 01:15:07,879] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.70 | bwd_microstep: 273.96 | bwd_inner_microstep: 273.94 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 349 +[2025-05-02 01:15:08,094] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 75.55 | bwd_microstep: 125.15 | bwd_inner_microstep: 125.02 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 01:15:08,570] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.33 | bwd_microstep: 273.00 | bwd_inner_microstep: 272.99 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 839 +[2025-05-02 01:15:08,805] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.29 | bwd_microstep: 127.46 | bwd_inner_microstep: 127.21 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:15:09,281] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.88 | bwd_microstep: 272.42 | bwd_inner_microstep: 272.40 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:15:09,757] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.79 | bwd_microstep: 272.41 | bwd_inner_microstep: 272.39 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:15:10,233] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.29 | bwd_microstep: 272.38 | bwd_inner_microstep: 272.37 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:15:10,710] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.72 | bwd_microstep: 272.43 | bwd_inner_microstep: 272.41 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:15:11,189] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.14 | bwd_microstep: 272.62 | bwd_inner_microstep: 272.60 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 01:15:11,668] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.52 | bwd_microstep: 272.35 | bwd_inner_microstep: 272.33 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:15:12,145] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.56 | bwd_microstep: 272.12 | bwd_inner_microstep: 272.10 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:15:12,619] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.87 | bwd_microstep: 271.19 | bwd_inner_microstep: 271.17 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 01:15:13,183] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.04 | optimizer_gradients: 2.09 | optimizer_step: 18.02 +[2025-05-02 01:15:13,184] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.59 | bwd_microstep: 337.22 | bwd_inner_microstep: 271.52 | bwd_allreduce_microstep: 65.66 | step_microstep: 24.90 +[2025-05-02 01:15:13,185] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2711.78 | bwd: 3996.47 | bwd_inner: 3930.10 | bwd_allreduce: 65.94 | step: 25.72 + 12%|█▏ | 1087/8720 [2:59:46<14:47:43, 6.98s/it] {'loss': 0.5606, 'grad_norm': 5.467056751251221, 'learning_rate': 9.767077619712571e-06, 'epoch': 1.25} + 12%|█▏ | 1087/8720 [2:59:46<14:47:43, 6.98s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1966 +[2025-05-02 01:15:13,692] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 198.19 | bwd_microstep: 289.77 | bwd_inner_microstep: 289.75 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 359 +[2025-05-02 01:15:13,899] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 71.19 | bwd_microstep: 122.31 | bwd_inner_microstep: 122.18 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 01:15:14,374] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.52 | bwd_microstep: 272.77 | bwd_inner_microstep: 272.76 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 334 +[2025-05-02 01:15:14,574] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 67.86 | bwd_microstep: 119.63 | bwd_inner_microstep: 119.51 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 01:15:15,051] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.96 | bwd_microstep: 273.28 | bwd_inner_microstep: 273.26 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1355 +[2025-05-02 01:15:15,413] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.89 | bwd_microstep: 205.98 | bwd_inner_microstep: 205.96 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 01:15:15,890] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.33 | bwd_microstep: 273.21 | bwd_inner_microstep: 273.19 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1356 +[2025-05-02 01:15:16,252] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.62 | bwd_microstep: 206.26 | bwd_inner_microstep: 206.24 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:15:16,729] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.62 | bwd_microstep: 272.66 | bwd_inner_microstep: 272.64 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 845 +[2025-05-02 01:15:16,970] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.83 | bwd_microstep: 132.05 | bwd_inner_microstep: 132.03 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 01:15:17,446] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.85 | bwd_microstep: 272.81 | bwd_inner_microstep: 272.79 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 01:15:17,923] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.98 | bwd_microstep: 272.83 | bwd_inner_microstep: 272.82 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:15:18,399] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.30 | bwd_microstep: 272.29 | bwd_inner_microstep: 272.27 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:15:18,873] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.75 | bwd_microstep: 272.09 | bwd_inner_microstep: 272.07 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:15:19,349] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.79 | bwd_microstep: 272.69 | bwd_inner_microstep: 272.67 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 319 +[2025-05-02 01:15:19,658] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.19 | optimizer_step: 17.16 +[2025-05-02 01:15:19,658] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 68.83 | bwd_microstep: 202.27 | bwd_inner_microstep: 135.96 | bwd_allreduce_microstep: 66.23 | step_microstep: 24.39 +[2025-05-02 01:15:19,659] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2478.28 | bwd: 3732.93 | bwd_inner: 3666.17 | bwd_allreduce: 66.38 | step: 25.13 + 12%|█▏ | 1088/8720 [2:59:53<14:28:23, 6.83s/it] {'loss': 1.0865, 'grad_norm': 11.26888656616211, 'learning_rate': 9.766517056033747e-06, 'epoch': 1.25} + 12%|█▏ | 1088/8720 [2:59:53<14:28:23, 6.83s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 01:15:20,137] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.57 | bwd_microstep: 270.30 | bwd_inner_microstep: 270.28 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1957 +[2025-05-02 01:15:20,638] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.82 | bwd_microstep: 290.11 | bwd_inner_microstep: 290.10 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1898 +[2025-05-02 01:15:21,118] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.87 | bwd_microstep: 275.21 | bwd_inner_microstep: 275.19 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-02 01:15:21,595] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.37 | bwd_microstep: 273.65 | bwd_inner_microstep: 273.63 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1883 +[2025-05-02 01:15:22,074] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.71 | bwd_microstep: 274.25 | bwd_inner_microstep: 274.23 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1365 +[2025-05-02 01:15:22,438] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.73 | bwd_microstep: 207.39 | bwd_inner_microstep: 207.21 | bwd_allreduce_microstep: 0.09 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 01:15:22,917] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.02 | bwd_microstep: 273.23 | bwd_inner_microstep: 273.21 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 01:15:23,395] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.29 | bwd_microstep: 272.76 | bwd_inner_microstep: 272.75 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 01:15:23,873] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.01 | bwd_microstep: 272.53 | bwd_inner_microstep: 272.51 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:15:24,351] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.19 | bwd_microstep: 272.31 | bwd_inner_microstep: 272.29 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 01:15:24,833] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.12 | bwd_microstep: 272.86 | bwd_inner_microstep: 272.84 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 325 +[2025-05-02 01:15:25,047] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 80.01 | bwd_microstep: 118.48 | bwd_inner_microstep: 118.33 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:15:25,525] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.45 | bwd_microstep: 272.78 | bwd_inner_microstep: 272.76 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:15:26,005] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.07 | bwd_microstep: 272.81 | bwd_inner_microstep: 272.80 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:15:26,482] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.43 | bwd_microstep: 272.94 | bwd_inner_microstep: 272.92 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 01:15:27,049] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.04 | optimizer_gradients: 2.24 | optimizer_step: 17.33 +[2025-05-02 01:15:27,050] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.44 | bwd_microstep: 338.89 | bwd_inner_microstep: 271.89 | bwd_allreduce_microstep: 66.96 | step_microstep: 24.51 +[2025-05-02 01:15:27,051] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2865.78 | bwd: 4230.57 | bwd_inner: 4162.98 | bwd_allreduce: 67.22 | step: 25.42 + 12%|█▏ | 1089/8720 [3:00:00<14:49:49, 7.00s/it] {'loss': 0.9412, 'grad_norm': 10.718652725219727, 'learning_rate': 9.765955834749282e-06, 'epoch': 1.25} + 12%|█▏ | 1089/8720 [3:00:00<14:49:49, 7.00s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 01:15:27,529] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.48 | bwd_microstep: 270.61 | bwd_inner_microstep: 270.59 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 348 +[2025-05-02 01:15:27,748] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 85.20 | bwd_microstep: 119.97 | bwd_inner_microstep: 119.66 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1892 +[2025-05-02 01:15:28,227] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.91 | bwd_microstep: 275.01 | bwd_inner_microstep: 274.99 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 357 +[2025-05-02 01:15:28,440] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 82.83 | bwd_microstep: 115.14 | bwd_inner_microstep: 114.95 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-02 01:15:28,917] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.20 | bwd_microstep: 273.83 | bwd_inner_microstep: 273.81 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-02 01:15:29,395] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.43 | bwd_microstep: 273.68 | bwd_inner_microstep: 273.66 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 01:15:29,871] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.14 | bwd_microstep: 272.53 | bwd_inner_microstep: 272.51 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 01:15:30,348] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.60 | bwd_microstep: 272.71 | bwd_inner_microstep: 272.69 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 840 +[2025-05-02 01:15:30,582] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 91.85 | bwd_microstep: 126.41 | bwd_inner_microstep: 126.21 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.09 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 329 +[2025-05-02 01:15:30,789] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 71.25 | bwd_microstep: 121.49 | bwd_inner_microstep: 121.18 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.19 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 326 +[2025-05-02 01:15:31,005] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 85.26 | bwd_microstep: 115.17 | bwd_inner_microstep: 115.04 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 321 +[2025-05-02 01:15:31,204] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 70.16 | bwd_microstep: 115.85 | bwd_inner_microstep: 115.69 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 834 +[2025-05-02 01:15:31,436] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 91.25 | bwd_microstep: 126.33 | bwd_inner_microstep: 126.12 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:15:31,911] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.83 | bwd_microstep: 271.15 | bwd_inner_microstep: 271.14 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 830 +[2025-05-02 01:15:32,147] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 91.94 | bwd_microstep: 130.23 | bwd_inner_microstep: 130.17 | bwd_allreduce_microstep: 0.03 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:15:32,712] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.04 | optimizer_gradients: 2.12 | optimizer_step: 17.03 +[2025-05-02 01:15:32,712] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.33 | bwd_microstep: 337.85 | bwd_inner_microstep: 271.82 | bwd_allreduce_microstep: 65.99 | step_microstep: 23.91 +[2025-05-02 01:15:32,713] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2175.39 | bwd: 3218.14 | bwd_inner: 3150.46 | bwd_allreduce: 66.70 | step: 25.30 + 12%|█▎ | 1090/8720 [3:00:06<13:58:48, 6.60s/it] {'loss': 0.8335, 'grad_norm': 9.80468463897705, 'learning_rate': 9.765393955936602e-06, 'epoch': 1.25} + 12%|█▎ | 1090/8720 [3:00:06<13:58:48, 6.60s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 01:15:33,190] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.42 | bwd_microstep: 270.29 | bwd_inner_microstep: 270.28 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 3522 +[2025-05-02 01:15:34,001] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 290.87 | bwd_microstep: 504.66 | bwd_inner_microstep: 504.64 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2098 +[2025-05-02 01:15:34,526] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 204.04 | bwd_microstep: 305.69 | bwd_inner_microstep: 305.67 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.12 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 362 +[2025-05-02 01:15:34,734] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 76.57 | bwd_microstep: 117.37 | bwd_inner_microstep: 117.16 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.08 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 344 +[2025-05-02 01:15:34,955] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 88.50 | bwd_microstep: 119.25 | bwd_inner_microstep: 118.94 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-02 01:15:35,434] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.32 | bwd_microstep: 274.22 | bwd_inner_microstep: 274.20 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-02 01:15:35,916] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.16 | bwd_microstep: 273.88 | bwd_inner_microstep: 273.87 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 329 +[2025-05-02 01:15:36,152] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 96.12 | bwd_microstep: 119.97 | bwd_inner_microstep: 119.72 | bwd_allreduce_microstep: 0.09 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 01:15:36,637] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.70 | bwd_microstep: 273.53 | bwd_inner_microstep: 273.51 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1096 +[2025-05-02 01:15:36,931] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 115.68 | bwd_microstep: 161.29 | bwd_inner_microstep: 161.10 | bwd_allreduce_microstep: 0.09 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 01:15:37,409] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.14 | bwd_microstep: 272.71 | bwd_inner_microstep: 272.69 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 334 +[2025-05-02 01:15:37,643] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 101.84 | bwd_microstep: 114.97 | bwd_inner_microstep: 114.65 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:15:38,121] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.86 | bwd_microstep: 271.39 | bwd_inner_microstep: 271.37 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 830 +[2025-05-02 01:15:38,365] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.01 | bwd_microstep: 130.43 | bwd_inner_microstep: 130.12 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 01:15:38,842] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.83 | bwd_microstep: 270.86 | bwd_inner_microstep: 270.84 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:15:39,423] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.03 | optimizer_step: 17.21 +[2025-05-02 01:15:39,423] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.64 | bwd_microstep: 347.64 | bwd_inner_microstep: 271.74 | bwd_allreduce_microstep: 75.84 | step_microstep: 25.03 +[2025-05-02 01:15:39,425] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2574.33 | bwd: 3828.29 | bwd_inner: 3750.79 | bwd_allreduce: 76.53 | step: 26.17 + 13%|█▎ | 1091/8720 [3:00:13<14:03:09, 6.63s/it] {'loss': 0.8567, 'grad_norm': 9.502992630004883, 'learning_rate': 9.76483141967323e-06, 'epoch': 1.25} + 13%|█▎ | 1091/8720 [3:00:13<14:03:09, 6.63s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1947 +[2025-05-02 01:15:39,933] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 197.10 | bwd_microstep: 288.71 | bwd_inner_microstep: 288.69 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1234 +[2025-05-02 01:15:40,249] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 121.95 | bwd_microstep: 177.39 | bwd_inner_microstep: 177.21 | bwd_allreduce_microstep: 0.10 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1915 +[2025-05-02 01:15:40,734] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.57 | bwd_microstep: 276.67 | bwd_inner_microstep: 276.66 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1894 +[2025-05-02 01:15:41,212] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.10 | bwd_microstep: 274.85 | bwd_inner_microstep: 274.83 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1130 +[2025-05-02 01:15:41,507] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 116.76 | bwd_microstep: 163.71 | bwd_inner_microstep: 163.67 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 01:15:41,985] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.62 | bwd_microstep: 273.19 | bwd_inner_microstep: 273.17 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 01:15:42,463] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.61 | bwd_microstep: 272.77 | bwd_inner_microstep: 272.76 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:15:42,941] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.61 | bwd_microstep: 272.52 | bwd_inner_microstep: 272.50 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 321 +[2025-05-02 01:15:43,153] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 82.84 | bwd_microstep: 115.34 | bwd_inner_microstep: 115.20 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 01:15:43,625] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.90 | bwd_microstep: 271.22 | bwd_inner_microstep: 271.20 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:15:44,101] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.25 | bwd_microstep: 272.25 | bwd_inner_microstep: 272.23 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 01:15:44,576] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.47 | bwd_microstep: 271.13 | bwd_inner_microstep: 271.11 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:15:45,050] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.30 | bwd_microstep: 271.29 | bwd_inner_microstep: 271.27 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 01:15:45,524] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.57 | bwd_microstep: 271.17 | bwd_inner_microstep: 271.15 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2056 +[2025-05-02 01:15:46,045] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 203.19 | bwd_microstep: 302.16 | bwd_inner_microstep: 302.14 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1962 +[2025-05-02 01:15:46,637] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.04 | optimizer_gradients: 2.15 | optimizer_step: 17.07 +[2025-05-02 01:15:46,637] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 196.62 | bwd_microstep: 357.14 | bwd_inner_microstep: 291.08 | bwd_allreduce_microstep: 66.02 | step_microstep: 23.96 +[2025-05-02 01:15:46,638] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2803.17 | bwd: 4131.56 | bwd_inner: 4064.90 | bwd_allreduce: 66.27 | step: 24.83 + 13%|█▎ | 1092/8720 [3:00:20<14:25:11, 6.81s/it] {'loss': 0.6642, 'grad_norm': 5.578075408935547, 'learning_rate': 9.764268226036773e-06, 'epoch': 1.25} + 13%|█▎ | 1092/8720 [3:00:20<14:25:11, 6.81s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 01:15:47,120] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.28 | bwd_microstep: 272.83 | bwd_inner_microstep: 272.81 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 405 +[2025-05-02 01:15:47,335] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 77.20 | bwd_microstep: 124.50 | bwd_inner_microstep: 124.37 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1905 +[2025-05-02 01:15:47,816] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.15 | bwd_microstep: 276.09 | bwd_inner_microstep: 276.08 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1890 +[2025-05-02 01:15:48,295] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.83 | bwd_microstep: 274.93 | bwd_inner_microstep: 274.92 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1888 +[2025-05-02 01:15:48,774] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.63 | bwd_microstep: 274.61 | bwd_inner_microstep: 274.59 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1109 +[2025-05-02 01:15:49,067] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 115.89 | bwd_microstep: 162.20 | bwd_inner_microstep: 162.12 | bwd_allreduce_microstep: 0.04 | step_microstep: 0.09 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1112 +[2025-05-02 01:15:49,362] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 115.17 | bwd_microstep: 162.52 | bwd_inner_microstep: 162.33 | bwd_allreduce_microstep: 0.10 | step_microstep: 0.10 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1362 +[2025-05-02 01:15:49,727] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.13 | bwd_microstep: 206.73 | bwd_inner_microstep: 206.71 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 01:15:50,206] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.05 | bwd_microstep: 272.72 | bwd_inner_microstep: 272.70 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 01:15:50,684] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.43 | bwd_microstep: 272.61 | bwd_inner_microstep: 272.59 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:15:51,163] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.55 | bwd_microstep: 272.47 | bwd_inner_microstep: 272.45 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:15:51,639] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.25 | bwd_microstep: 271.12 | bwd_inner_microstep: 271.10 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:15:52,116] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.46 | bwd_microstep: 272.33 | bwd_inner_microstep: 272.31 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:15:52,593] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.04 | bwd_microstep: 272.35 | bwd_inner_microstep: 272.33 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 321 +[2025-05-02 01:15:52,807] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 81.42 | bwd_microstep: 117.61 | bwd_inner_microstep: 117.29 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:15:53,370] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.04 | optimizer_gradients: 2.14 | optimizer_step: 17.07 +[2025-05-02 01:15:53,370] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.81 | bwd_microstep: 337.21 | bwd_inner_microstep: 271.63 | bwd_allreduce_microstep: 65.53 | step_microstep: 24.04 +[2025-05-02 01:15:53,371] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2605.93 | bwd: 3842.92 | bwd_inner: 3776.43 | bwd_allreduce: 65.94 | step: 24.99 + 13%|█▎ | 1093/8720 [3:00:27<14:22:19, 6.78s/it] {'loss': 1.0046, 'grad_norm': 10.697800636291504, 'learning_rate': 9.76370437510493e-06, 'epoch': 1.25} + 13%|█▎ | 1093/8720 [3:00:27<14:22:19, 6.78s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 01:15:53,849] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.02 | bwd_microstep: 270.40 | bwd_inner_microstep: 270.39 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1905 +[2025-05-02 01:15:54,332] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.61 | bwd_microstep: 276.12 | bwd_inner_microstep: 276.10 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1897 +[2025-05-02 01:15:54,813] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.68 | bwd_microstep: 275.43 | bwd_inner_microstep: 275.42 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1886 +[2025-05-02 01:15:55,297] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.02 | bwd_microstep: 275.32 | bwd_inner_microstep: 275.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-02 01:15:55,779] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.27 | bwd_microstep: 274.40 | bwd_inner_microstep: 274.38 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 01:15:56,262] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.51 | bwd_microstep: 273.48 | bwd_inner_microstep: 273.46 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 01:15:56,744] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.17 | bwd_microstep: 272.73 | bwd_inner_microstep: 272.71 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-02 01:15:57,223] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.48 | bwd_microstep: 273.03 | bwd_inner_microstep: 273.02 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 01:15:57,700] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.26 | bwd_microstep: 272.56 | bwd_inner_microstep: 272.54 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:15:58,176] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.93 | bwd_microstep: 272.54 | bwd_inner_microstep: 272.52 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:15:58,653] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.98 | bwd_microstep: 272.77 | bwd_inner_microstep: 272.75 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:15:59,129] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.68 | bwd_microstep: 272.34 | bwd_inner_microstep: 272.32 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:15:59,604] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.87 | bwd_microstep: 271.26 | bwd_inner_microstep: 271.24 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:16:00,078] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.32 | bwd_microstep: 271.28 | bwd_inner_microstep: 271.26 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:16:00,552] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.25 | bwd_microstep: 271.39 | bwd_inner_microstep: 271.37 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:16:01,117] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.13 | optimizer_step: 17.11 +[2025-05-02 01:16:01,118] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.74 | bwd_microstep: 337.35 | bwd_inner_microstep: 271.78 | bwd_allreduce_microstep: 65.53 | step_microstep: 24.10 +[2025-05-02 01:16:01,119] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 3019.48 | bwd: 4432.42 | bwd_inner: 4366.58 | bwd_allreduce: 65.61 | step: 24.78 + 13%|█▎ | 1094/8720 [3:00:34<14:58:57, 7.07s/it] {'loss': 0.8388, 'grad_norm': 12.320189476013184, 'learning_rate': 9.763139866955494e-06, 'epoch': 1.25} + 13%|█▎ | 1094/8720 [3:00:34<14:58:57, 7.07s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:16:01,596] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.55 | bwd_microstep: 270.49 | bwd_inner_microstep: 270.47 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 993 +[2025-05-02 01:16:01,866] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 105.56 | bwd_microstep: 150.79 | bwd_inner_microstep: 150.59 | bwd_allreduce_microstep: 0.08 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1902 +[2025-05-02 01:16:02,347] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.08 | bwd_microstep: 275.96 | bwd_inner_microstep: 275.94 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-02 01:16:02,823] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.37 | bwd_microstep: 273.46 | bwd_inner_microstep: 273.45 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 333 +[2025-05-02 01:16:03,021] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 66.81 | bwd_microstep: 117.99 | bwd_inner_microstep: 117.86 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.08 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1356 +[2025-05-02 01:16:03,381] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.33 | bwd_microstep: 206.03 | bwd_inner_microstep: 206.01 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 327 +[2025-05-02 01:16:03,578] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 66.54 | bwd_microstep: 117.58 | bwd_inner_microstep: 117.46 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.08 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 330 +[2025-05-02 01:16:03,775] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 66.75 | bwd_microstep: 116.78 | bwd_inner_microstep: 116.66 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.08 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 842 +[2025-05-02 01:16:04,014] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.43 | bwd_microstep: 132.45 | bwd_inner_microstep: 132.43 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:16:04,490] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.45 | bwd_microstep: 272.50 | bwd_inner_microstep: 272.48 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:16:04,965] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.47 | bwd_microstep: 272.70 | bwd_inner_microstep: 272.68 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:16:05,440] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.04 | bwd_microstep: 272.36 | bwd_inner_microstep: 272.34 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:16:05,916] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.68 | bwd_microstep: 272.67 | bwd_inner_microstep: 272.66 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1346 +[2025-05-02 01:16:06,277] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.21 | bwd_microstep: 205.58 | bwd_inner_microstep: 205.56 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 316 +[2025-05-02 01:16:06,473] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 66.72 | bwd_microstep: 116.54 | bwd_inner_microstep: 116.42 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.08 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1385 +[2025-05-02 01:16:06,930] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.93 | optimizer_step: 17.06 +[2025-05-02 01:16:06,930] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 143.19 | bwd_microstep: 274.82 | bwd_inner_microstep: 209.22 | bwd_allreduce_microstep: 65.55 | step_microstep: 24.86 +[2025-05-02 01:16:06,931] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2208.92 | bwd: 3348.77 | bwd_inner: 3282.31 | bwd_allreduce: 65.86 | step: 25.72 + 13%|█▎ | 1095/8720 [3:00:40<14:10:47, 6.69s/it] {'loss': 0.6305, 'grad_norm': 6.705943584442139, 'learning_rate': 9.762574701666345e-06, 'epoch': 1.26} + 13%|█▎ | 1095/8720 [3:00:40<14:10:47, 6.69s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 01:16:07,413] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.95 | bwd_microstep: 272.94 | bwd_inner_microstep: 272.92 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1912 +[2025-05-02 01:16:07,895] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.57 | bwd_microstep: 276.44 | bwd_inner_microstep: 276.42 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 873 +[2025-05-02 01:16:08,140] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 97.83 | bwd_microstep: 134.69 | bwd_inner_microstep: 134.67 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-02 01:16:08,618] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.83 | bwd_microstep: 274.41 | bwd_inner_microstep: 274.39 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-02 01:16:09,096] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.14 | bwd_microstep: 273.74 | bwd_inner_microstep: 273.73 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 01:16:09,573] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.26 | bwd_microstep: 273.79 | bwd_inner_microstep: 273.78 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 01:16:10,051] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.65 | bwd_microstep: 273.50 | bwd_inner_microstep: 273.49 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 01:16:10,528] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.92 | bwd_microstep: 273.07 | bwd_inner_microstep: 273.05 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 01:16:11,004] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.71 | bwd_microstep: 272.79 | bwd_inner_microstep: 272.78 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:16:11,479] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.93 | bwd_microstep: 272.50 | bwd_inner_microstep: 272.48 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:16:11,955] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.38 | bwd_microstep: 272.45 | bwd_inner_microstep: 272.43 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 01:16:12,431] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.97 | bwd_microstep: 272.64 | bwd_inner_microstep: 272.62 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 01:16:12,908] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.18 | bwd_microstep: 273.05 | bwd_inner_microstep: 273.03 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 328 +[2025-05-02 01:16:13,104] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 66.93 | bwd_microstep: 116.01 | bwd_inner_microstep: 115.88 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:16:13,578] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.09 | bwd_microstep: 272.11 | bwd_inner_microstep: 272.09 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1345 +[2025-05-02 01:16:14,027] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.14 | optimizer_step: 17.09 +[2025-05-02 01:16:14,027] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.08 | bwd_microstep: 271.17 | bwd_inner_microstep: 205.92 | bwd_allreduce_microstep: 65.20 | step_microstep: 24.24 +[2025-05-02 01:16:14,028] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2760.18 | bwd: 4075.32 | bwd_inner: 4009.71 | bwd_allreduce: 65.33 | step: 24.93 + 13%|█▎ | 1096/8720 [3:00:47<14:26:00, 6.82s/it] {'loss': 0.8699, 'grad_norm': 9.079769134521484, 'learning_rate': 9.762008879315456e-06, 'epoch': 1.26} + 13%|█▎ | 1096/8720 [3:00:47<14:26:00, 6.82s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 321 +[2025-05-02 01:16:14,252] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 66.77 | bwd_microstep: 139.71 | bwd_inner_microstep: 139.46 | bwd_allreduce_microstep: 0.09 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1913 +[2025-05-02 01:16:14,733] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.93 | bwd_microstep: 276.19 | bwd_inner_microstep: 276.18 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1895 +[2025-05-02 01:16:15,213] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.04 | bwd_microstep: 275.35 | bwd_inner_microstep: 275.34 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1889 +[2025-05-02 01:16:15,694] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.47 | bwd_microstep: 275.36 | bwd_inner_microstep: 275.35 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1886 +[2025-05-02 01:16:16,177] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.39 | bwd_microstep: 274.24 | bwd_inner_microstep: 274.22 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.20 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1360 +[2025-05-02 01:16:16,548] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 142.82 | bwd_microstep: 206.72 | bwd_inner_microstep: 206.70 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 01:16:17,027] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.22 | bwd_microstep: 272.10 | bwd_inner_microstep: 272.08 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.17 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:16:17,510] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.30 | bwd_microstep: 272.37 | bwd_inner_microstep: 272.35 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 837 +[2025-05-02 01:16:17,761] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 106.07 | bwd_microstep: 125.93 | bwd_inner_microstep: 125.69 | bwd_allreduce_microstep: 0.08 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:16:18,240] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.60 | bwd_microstep: 272.24 | bwd_inner_microstep: 272.23 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 832 +[2025-05-02 01:16:18,496] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 105.18 | bwd_microstep: 129.94 | bwd_inner_microstep: 129.74 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.12 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 832 +[2025-05-02 01:16:18,736] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 92.81 | bwd_microstep: 129.99 | bwd_inner_microstep: 129.80 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:16:19,211] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.69 | bwd_microstep: 270.95 | bwd_inner_microstep: 270.93 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 01:16:19,691] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.85 | bwd_microstep: 270.87 | bwd_inner_microstep: 270.86 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 828 +[2025-05-02 01:16:19,936] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 96.34 | bwd_microstep: 129.65 | bwd_inner_microstep: 129.49 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 01:16:20,515] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.17 | optimizer_step: 17.23 +[2025-05-02 01:16:20,516] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.51 | bwd_microstep: 349.49 | bwd_inner_microstep: 271.19 | bwd_allreduce_microstep: 78.24 | step_microstep: 25.37 +[2025-05-02 01:16:20,517] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2493.60 | bwd: 3671.19 | bwd_inner: 3591.80 | bwd_allreduce: 78.65 | step: 26.75 + 13%|█▎ | 1097/8720 [3:00:54<14:13:35, 6.72s/it] {'loss': 0.5375, 'grad_norm': 6.340414524078369, 'learning_rate': 9.76144239998089e-06, 'epoch': 1.26} + 13%|█▎ | 1097/8720 [3:00:54<14:13:35, 6.72s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1850 +[2025-05-02 01:16:21,001] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.90 | bwd_microstep: 270.27 | bwd_inner_microstep: 270.23 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.12 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 932 +[2025-05-02 01:16:21,272] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 105.31 | bwd_microstep: 146.63 | bwd_inner_microstep: 146.58 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1890 +[2025-05-02 01:16:21,755] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.67 | bwd_microstep: 274.35 | bwd_inner_microstep: 274.33 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 346 +[2025-05-02 01:16:21,992] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 90.05 | bwd_microstep: 128.39 | bwd_inner_microstep: 128.23 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 01:16:22,471] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.61 | bwd_microstep: 272.67 | bwd_inner_microstep: 272.66 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.13 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 01:16:22,951] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.47 | bwd_microstep: 272.80 | bwd_inner_microstep: 272.79 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 01:16:23,434] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.01 | bwd_microstep: 272.52 | bwd_inner_microstep: 272.50 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 01:16:23,916] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.07 | bwd_microstep: 273.42 | bwd_inner_microstep: 273.40 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.20 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 327 +[2025-05-02 01:16:24,171] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 89.82 | bwd_microstep: 145.70 | bwd_inner_microstep: 145.40 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:16:24,649] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.45 | bwd_microstep: 272.33 | bwd_inner_microstep: 272.31 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:16:25,132] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.05 | bwd_microstep: 272.36 | bwd_inner_microstep: 272.34 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:16:25,615] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.77 | bwd_microstep: 272.33 | bwd_inner_microstep: 272.31 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.16 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:16:26,100] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.25 | bwd_microstep: 271.22 | bwd_inner_microstep: 271.20 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 01:16:26,580] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.13 | bwd_microstep: 272.49 | bwd_inner_microstep: 272.47 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.21 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 01:16:27,059] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.18 | bwd_microstep: 271.40 | bwd_inner_microstep: 271.38 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:16:27,652] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.20 | optimizer_step: 17.36 +[2025-05-02 01:16:27,652] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.03 | bwd_microstep: 359.76 | bwd_inner_microstep: 271.78 | bwd_allreduce_microstep: 87.92 | step_microstep: 25.45 +[2025-05-02 01:16:27,654] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2729.35 | bwd: 4048.78 | bwd_inner: 3960.02 | bwd_allreduce: 88.21 | step: 27.11 + 13%|█▎ | 1098/8720 [3:01:01<14:29:23, 6.84s/it] {'loss': 0.9986, 'grad_norm': 15.267786026000977, 'learning_rate': 9.760875263740801e-06, 'epoch': 1.26} + 13%|█▎ | 1098/8720 [3:01:01<14:29:23, 6.84s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 01:16:28,136] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.55 | bwd_microstep: 270.36 | bwd_inner_microstep: 270.34 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1443 +[2025-05-02 01:16:28,513] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 143.66 | bwd_microstep: 215.26 | bwd_inner_microstep: 215.20 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.14 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1921 +[2025-05-02 01:16:29,014] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 194.04 | bwd_microstep: 287.17 | bwd_inner_microstep: 287.16 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1917 +[2025-05-02 01:16:29,499] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.32 | bwd_microstep: 276.34 | bwd_inner_microstep: 276.32 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1911 +[2025-05-02 01:16:29,985] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.91 | bwd_microstep: 276.51 | bwd_inner_microstep: 276.49 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 359 +[2025-05-02 01:16:30,227] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 90.89 | bwd_microstep: 131.00 | bwd_inner_microstep: 130.70 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 01:16:30,707] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.24 | bwd_microstep: 273.35 | bwd_inner_microstep: 273.34 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-02 01:16:31,190] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.05 | bwd_microstep: 273.22 | bwd_inner_microstep: 273.21 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 01:16:31,669] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.46 | bwd_microstep: 272.65 | bwd_inner_microstep: 272.64 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 845 +[2025-05-02 01:16:31,913] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.67 | bwd_microstep: 132.77 | bwd_inner_microstep: 132.51 | bwd_allreduce_microstep: 0.10 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:16:32,391] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.43 | bwd_microstep: 272.10 | bwd_inner_microstep: 272.08 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1349 +[2025-05-02 01:16:32,760] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.83 | bwd_microstep: 205.94 | bwd_inner_microstep: 205.74 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.21 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:16:33,240] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.17 | bwd_microstep: 272.63 | bwd_inner_microstep: 272.61 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:16:33,720] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.95 | bwd_microstep: 272.37 | bwd_inner_microstep: 272.35 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 01:16:34,200] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.12 | bwd_microstep: 271.41 | bwd_inner_microstep: 271.39 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.07 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 01:16:34,782] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.22 | optimizer_step: 17.39 +[2025-05-02 01:16:34,783] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.53 | bwd_microstep: 349.46 | bwd_inner_microstep: 271.60 | bwd_allreduce_microstep: 77.81 | step_microstep: 25.44 +[2025-05-02 01:16:34,785] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2736.44 | bwd: 4052.66 | bwd_inner: 3973.79 | bwd_allreduce: 78.24 | step: 26.74 + 13%|█▎ | 1099/8720 [3:01:08<14:40:11, 6.93s/it] {'loss': 0.6316, 'grad_norm': 6.964020729064941, 'learning_rate': 9.760307470673432e-06, 'epoch': 1.26} + 13%|█▎ | 1099/8720 [3:01:08<14:40:11, 6.93s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 01:16:35,267] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.81 | bwd_microstep: 271.85 | bwd_inner_microstep: 271.83 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 879 +[2025-05-02 01:16:35,517] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 97.64 | bwd_microstep: 135.02 | bwd_inner_microstep: 134.71 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1896 +[2025-05-02 01:16:35,997] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.61 | bwd_microstep: 275.07 | bwd_inner_microstep: 275.05 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1901 +[2025-05-02 01:16:36,482] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.82 | bwd_microstep: 275.69 | bwd_inner_microstep: 275.67 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-02 01:16:36,965] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.73 | bwd_microstep: 273.31 | bwd_inner_microstep: 273.29 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 01:16:37,448] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.96 | bwd_microstep: 272.47 | bwd_inner_microstep: 272.45 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 01:16:37,931] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.84 | bwd_microstep: 272.57 | bwd_inner_microstep: 272.55 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 01:16:38,417] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.67 | bwd_microstep: 272.95 | bwd_inner_microstep: 272.94 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:16:38,899] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.76 | bwd_microstep: 272.79 | bwd_inner_microstep: 272.77 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.14 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 01:16:39,379] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.70 | bwd_microstep: 271.34 | bwd_inner_microstep: 271.32 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:16:39,862] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.55 | bwd_microstep: 271.16 | bwd_inner_microstep: 271.15 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:16:40,344] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.01 | bwd_microstep: 271.12 | bwd_inner_microstep: 271.10 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 01:16:40,823] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.20 | bwd_microstep: 271.04 | bwd_inner_microstep: 271.03 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1984 +[2025-05-02 01:16:41,333] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 197.25 | bwd_microstep: 292.34 | bwd_inner_microstep: 292.32 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1963 +[2025-05-02 01:16:41,842] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 198.08 | bwd_microstep: 290.42 | bwd_inner_microstep: 290.40 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1911 +[2025-05-02 01:16:42,431] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.24 | optimizer_step: 17.39 +[2025-05-02 01:16:42,431] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.33 | bwd_microstep: 355.11 | bwd_inner_microstep: 277.26 | bwd_allreduce_microstep: 77.77 | step_microstep: 25.43 +[2025-05-02 01:16:42,433] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2944.58 | bwd: 4344.29 | bwd_inner: 4265.90 | bwd_allreduce: 77.96 | step: 26.55 + 13%|█▎ | 1100/8720 [3:01:16<15:07:27, 7.15s/it] {'loss': 1.2456, 'grad_norm': 8.238819122314453, 'learning_rate': 9.759739020857118e-06, 'epoch': 1.26} + 13%|█▎ | 1100/8720 [3:01:16<15:07:27, 7.15s/it][INFO|trainer.py:3503] 2025-05-02 01:16:44,941 >> Saving model checkpoint to work_dirs/internvl_chat_v2_5/ak/checkpoint-1100 +[INFO|configuration_utils.py:472] 2025-05-02 01:16:44,945 >> Configuration saved in work_dirs/internvl_chat_v2_5/ak/checkpoint-1100/config.json +[INFO|configuration_utils.py:807] 2025-05-02 01:16:44,945 >> Configuration saved in work_dirs/internvl_chat_v2_5/ak/checkpoint-1100/generation_config.json +[INFO|modeling_utils.py:2755] 2025-05-02 01:16:50,064 >> Model weights saved in work_dirs/internvl_chat_v2_5/ak/checkpoint-1100/model.safetensors +[INFO|tokenization_utils_base.py:2702] 2025-05-02 01:16:50,066 >> tokenizer config file saved in work_dirs/internvl_chat_v2_5/ak/checkpoint-1100/tokenizer_config.json +[INFO|tokenization_utils_base.py:2711] 2025-05-02 01:16:50,066 >> Special tokens file saved in work_dirs/internvl_chat_v2_5/ak/checkpoint-1100/special_tokens_map.json +[INFO|tokenization_utils_base.py:2762] 2025-05-02 01:16:50,066 >> added tokens file saved in work_dirs/internvl_chat_v2_5/ak/checkpoint-1100/added_tokens.json +[2025-05-02 01:16:50,198] [INFO] [logging.py:96:log_dist] [Rank 0] [Torch] Checkpoint global_step1100 is about to be saved! +[2025-05-02 01:16:50,215] [INFO] [logging.py:96:log_dist] [Rank 0] Saving model checkpoint: work_dirs/internvl_chat_v2_5/ak/checkpoint-1100/global_step1100/mp_rank_00_model_states.pt +[2025-05-02 01:16:50,216] [INFO] [torch_checkpoint_engine.py:21:save] [Torch] Saving work_dirs/internvl_chat_v2_5/ak/checkpoint-1100/global_step1100/mp_rank_00_model_states.pt... +[2025-05-02 01:16:54,766] [INFO] [torch_checkpoint_engine.py:23:save] [Torch] Saved work_dirs/internvl_chat_v2_5/ak/checkpoint-1100/global_step1100/mp_rank_00_model_states.pt. +[2025-05-02 01:16:54,768] [INFO] [torch_checkpoint_engine.py:21:save] [Torch] Saving work_dirs/internvl_chat_v2_5/ak/checkpoint-1100/global_step1100/bf16_zero_pp_rank_0_mp_rank_00_optim_states.pt... +[2025-05-02 01:16:54,966] [INFO] [torch_checkpoint_engine.py:23:save] [Torch] Saved work_dirs/internvl_chat_v2_5/ak/checkpoint-1100/global_step1100/bf16_zero_pp_rank_0_mp_rank_00_optim_states.pt. +[2025-05-02 01:16:54,967] [INFO] [engine.py:3536:_save_zero_checkpoint] zero checkpoint saved work_dirs/internvl_chat_v2_5/ak/checkpoint-1100/global_step1100/bf16_zero_pp_rank_0_mp_rank_00_optim_states.pt +[2025-05-02 01:16:54,967] [INFO] [torch_checkpoint_engine.py:33:commit] [Torch] Checkpoint global_step1100 is ready now! +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1377 +[2025-05-02 01:16:55,353] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 143.71 | bwd_microstep: 205.76 | bwd_inner_microstep: 205.47 | bwd_allreduce_microstep: 0.15 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1925 +[2025-05-02 01:16:55,847] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 192.65 | bwd_microstep: 284.97 | bwd_inner_microstep: 284.95 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1928 +[2025-05-02 01:16:56,340] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 192.51 | bwd_microstep: 285.17 | bwd_inner_microstep: 285.15 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1892 +[2025-05-02 01:16:56,818] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.68 | bwd_microstep: 272.63 | bwd_inner_microstep: 272.61 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 857 +[2025-05-02 01:16:57,069] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 101.62 | bwd_microstep: 132.50 | bwd_inner_microstep: 132.26 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 01:16:57,545] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.75 | bwd_microstep: 271.32 | bwd_inner_microstep: 271.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.13 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 01:16:58,023] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.87 | bwd_microstep: 271.20 | bwd_inner_microstep: 271.18 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 840 +[2025-05-02 01:16:58,263] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.15 | bwd_microstep: 125.63 | bwd_inner_microstep: 125.37 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 01:16:58,738] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.47 | bwd_microstep: 271.15 | bwd_inner_microstep: 271.13 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 01:16:59,214] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.26 | bwd_microstep: 271.43 | bwd_inner_microstep: 271.41 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 01:16:59,694] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.88 | bwd_microstep: 272.22 | bwd_inner_microstep: 272.21 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 01:17:00,176] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.18 | bwd_microstep: 271.58 | bwd_inner_microstep: 271.56 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:17:00,656] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.98 | bwd_microstep: 270.99 | bwd_inner_microstep: 270.97 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 321 +[2025-05-02 01:17:00,903] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 96.82 | bwd_microstep: 128.69 | bwd_inner_microstep: 128.37 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 01:17:01,376] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 185.74 | bwd_microstep: 269.99 | bwd_inner_microstep: 269.98 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:17:01,958] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.07 | optimizer_gradients: 2.15 | optimizer_step: 22.05 +[2025-05-02 01:17:01,958] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.24 | bwd_microstep: 347.60 | bwd_inner_microstep: 270.61 | bwd_allreduce_microstep: 76.93 | step_microstep: 30.20 +[2025-05-02 01:17:01,960] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2692.13 | bwd: 3952.91 | bwd_inner: 3874.61 | bwd_allreduce: 77.50 | step: 31.35 + 13%|█▎ | 1101/8720 [3:01:35<22:58:59, 10.86s/it] {'loss': 0.5946, 'grad_norm': 5.931203365325928, 'learning_rate': 9.759169914370283e-06, 'epoch': 1.26} + 13%|█▎ | 1101/8720 [3:01:35<22:58:59, 10.86s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1910 +[2025-05-02 01:17:02,446] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.49 | bwd_microstep: 274.48 | bwd_inner_microstep: 274.47 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1914 +[2025-05-02 01:17:02,924] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.95 | bwd_microstep: 274.82 | bwd_inner_microstep: 274.81 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1899 +[2025-05-02 01:17:03,402] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.50 | bwd_microstep: 273.94 | bwd_inner_microstep: 273.92 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-02 01:17:03,877] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.57 | bwd_microstep: 272.46 | bwd_inner_microstep: 272.44 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1887 +[2025-05-02 01:17:04,356] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.62 | bwd_microstep: 273.48 | bwd_inner_microstep: 273.46 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 01:17:04,835] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.08 | bwd_microstep: 272.31 | bwd_inner_microstep: 272.29 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 01:17:05,313] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.34 | bwd_microstep: 271.72 | bwd_inner_microstep: 271.71 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 835 +[2025-05-02 01:17:05,549] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.26 | bwd_microstep: 125.19 | bwd_inner_microstep: 125.13 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 01:17:06,025] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.47 | bwd_microstep: 271.54 | bwd_inner_microstep: 271.52 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:17:06,501] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.99 | bwd_microstep: 271.14 | bwd_inner_microstep: 271.12 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 01:17:06,979] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.28 | bwd_microstep: 272.02 | bwd_inner_microstep: 272.00 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:17:07,459] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.10 | bwd_microstep: 271.26 | bwd_inner_microstep: 271.24 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:17:07,936] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.12 | bwd_microstep: 271.33 | bwd_inner_microstep: 271.31 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 01:17:08,414] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.95 | bwd_microstep: 272.05 | bwd_inner_microstep: 272.03 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 835 +[2025-05-02 01:17:08,656] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 99.73 | bwd_microstep: 125.00 | bwd_inner_microstep: 124.94 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.09 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 833 +[2025-05-02 01:17:08,999] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.11 | optimizer_step: 16.63 +[2025-05-02 01:17:09,000] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.22 | bwd_microstep: 209.55 | bwd_inner_microstep: 132.36 | bwd_allreduce_microstep: 77.03 | step_microstep: 24.25 +[2025-05-02 01:17:09,001] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2729.30 | bwd: 4002.33 | bwd_inner: 3924.81 | bwd_allreduce: 77.14 | step: 25.05 + 13%|█▎ | 1102/8720 [3:01:42<20:33:21, 9.71s/it] {'loss': 0.8775, 'grad_norm': 4.048156261444092, 'learning_rate': 9.758600151291447e-06, 'epoch': 1.26} + 13%|█▎ | 1102/8720 [3:01:42<20:33:21, 9.71s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:17:09,482] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.30 | bwd_microstep: 270.35 | bwd_inner_microstep: 270.34 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-02 01:17:09,961] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.67 | bwd_microstep: 272.88 | bwd_inner_microstep: 272.87 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 01:17:10,439] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.49 | bwd_microstep: 272.24 | bwd_inner_microstep: 272.23 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 01:17:10,919] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.59 | bwd_microstep: 271.66 | bwd_inner_microstep: 271.65 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:17:11,398] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.00 | bwd_microstep: 270.97 | bwd_inner_microstep: 270.95 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1358 +[2025-05-02 01:17:11,764] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.02 | bwd_microstep: 205.73 | bwd_inner_microstep: 205.71 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:17:12,243] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.13 | bwd_microstep: 271.29 | bwd_inner_microstep: 271.27 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1092 +[2025-05-02 01:17:12,535] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 114.31 | bwd_microstep: 160.40 | bwd_inner_microstep: 160.34 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 01:17:13,012] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.52 | bwd_microstep: 271.66 | bwd_inner_microstep: 271.65 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:17:13,492] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.33 | bwd_microstep: 271.61 | bwd_inner_microstep: 271.59 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.16 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1346 +[2025-05-02 01:17:13,857] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.73 | bwd_microstep: 204.91 | bwd_inner_microstep: 204.90 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 01:17:14,336] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.54 | bwd_microstep: 271.64 | bwd_inner_microstep: 271.62 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:17:14,811] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.70 | bwd_microstep: 270.64 | bwd_inner_microstep: 270.62 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:17:15,290] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.40 | bwd_microstep: 270.59 | bwd_inner_microstep: 270.57 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:17:15,766] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.26 | bwd_microstep: 270.59 | bwd_inner_microstep: 270.57 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:17:16,352] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.10 | optimizer_step: 22.05 +[2025-05-02 01:17:16,352] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.93 | bwd_microstep: 350.84 | bwd_inner_microstep: 271.18 | bwd_allreduce_microstep: 79.61 | step_microstep: 29.91 +[2025-05-02 01:17:16,354] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2834.52 | bwd: 4178.05 | bwd_inner: 4098.05 | bwd_allreduce: 79.72 | step: 31.01 + 13%|█▎ | 1103/8720 [3:01:50<19:03:16, 9.01s/it] {'loss': 0.5545, 'grad_norm': 10.41741943359375, 'learning_rate': 9.758029731699213e-06, 'epoch': 1.26} + 13%|█▎ | 1103/8720 [3:01:50<19:03:16, 9.01s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:17:16,833] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.78 | bwd_microstep: 269.38 | bwd_inner_microstep: 269.36 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1904 +[2025-05-02 01:17:17,314] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.30 | bwd_microstep: 274.74 | bwd_inner_microstep: 274.72 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-02 01:17:17,791] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.51 | bwd_microstep: 272.77 | bwd_inner_microstep: 272.75 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1883 +[2025-05-02 01:17:18,269] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.64 | bwd_microstep: 273.35 | bwd_inner_microstep: 273.33 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-02 01:17:18,745] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.70 | bwd_microstep: 272.62 | bwd_inner_microstep: 272.61 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-02 01:17:19,222] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.02 | bwd_microstep: 272.98 | bwd_inner_microstep: 272.96 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 01:17:19,700] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.97 | bwd_microstep: 272.27 | bwd_inner_microstep: 272.25 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-02 01:17:20,177] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.85 | bwd_microstep: 272.90 | bwd_inner_microstep: 272.88 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-02 01:17:20,657] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.90 | bwd_microstep: 272.59 | bwd_inner_microstep: 272.57 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 844 +[2025-05-02 01:17:20,904] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.77 | bwd_microstep: 132.14 | bwd_inner_microstep: 131.92 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.10 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 838 +[2025-05-02 01:17:21,147] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 100.11 | bwd_microstep: 126.03 | bwd_inner_microstep: 125.79 | bwd_allreduce_microstep: 0.14 | step_microstep: 0.09 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1089 +[2025-05-02 01:17:21,439] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 115.06 | bwd_microstep: 160.25 | bwd_inner_microstep: 160.04 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:17:21,912] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.46 | bwd_microstep: 269.89 | bwd_inner_microstep: 269.87 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 01:17:22,387] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.05 | bwd_microstep: 270.41 | bwd_inner_microstep: 270.39 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 01:17:22,864] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.84 | bwd_microstep: 270.28 | bwd_inner_microstep: 270.26 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 01:17:23,438] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.07 | optimizer_step: 16.41 +[2025-05-02 01:17:23,439] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.23 | bwd_microstep: 346.92 | bwd_inner_microstep: 270.57 | bwd_allreduce_microstep: 76.29 | step_microstep: 23.26 +[2025-05-02 01:17:23,440] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2752.84 | bwd: 4029.61 | bwd_inner: 3952.31 | bwd_allreduce: 76.76 | step: 24.10 + 13%|█▎ | 1104/8720 [3:01:57<17:49:56, 8.43s/it] {'loss': 0.7673, 'grad_norm': 5.759009838104248, 'learning_rate': 9.757458655672278e-06, 'epoch': 1.27} + 13%|█▎ | 1104/8720 [3:01:57<17:49:56, 8.43s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 01:17:23,919] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.79 | bwd_microstep: 271.74 | bwd_inner_microstep: 271.72 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1385 +[2025-05-02 01:17:24,282] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.75 | bwd_microstep: 208.12 | bwd_inner_microstep: 208.11 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1901 +[2025-05-02 01:17:24,761] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.40 | bwd_microstep: 274.91 | bwd_inner_microstep: 274.89 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1105 +[2025-05-02 01:17:25,052] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 114.79 | bwd_microstep: 161.55 | bwd_inner_microstep: 161.34 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.22 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1888 +[2025-05-02 01:17:25,531] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.42 | bwd_microstep: 274.14 | bwd_inner_microstep: 274.12 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1893 +[2025-05-02 01:17:26,010] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.15 | bwd_microstep: 274.58 | bwd_inner_microstep: 274.56 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-02 01:17:26,487] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.19 | bwd_microstep: 273.08 | bwd_inner_microstep: 273.06 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-02 01:17:26,964] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.89 | bwd_microstep: 272.72 | bwd_inner_microstep: 272.70 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 01:17:27,439] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.21 | bwd_microstep: 272.48 | bwd_inner_microstep: 272.46 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 839 +[2025-05-02 01:17:27,677] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.05 | bwd_microstep: 126.13 | bwd_inner_microstep: 125.98 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 01:17:28,153] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.49 | bwd_microstep: 271.91 | bwd_inner_microstep: 271.90 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 01:17:28,631] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.13 | bwd_microstep: 272.33 | bwd_inner_microstep: 272.32 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:17:29,110] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.78 | bwd_microstep: 271.85 | bwd_inner_microstep: 271.83 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:17:29,586] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.20 | bwd_microstep: 271.11 | bwd_inner_microstep: 271.09 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 01:17:30,065] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.40 | bwd_microstep: 270.84 | bwd_inner_microstep: 270.82 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 827 +[2025-05-02 01:17:30,410] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.11 | optimizer_step: 16.43 +[2025-05-02 01:17:30,411] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 96.15 | bwd_microstep: 207.27 | bwd_inner_microstep: 130.20 | bwd_allreduce_microstep: 76.92 | step_microstep: 24.01 +[2025-05-02 01:17:30,412] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2705.48 | bwd: 3974.84 | bwd_inner: 3897.18 | bwd_allreduce: 77.14 | step: 25.03 + 13%|█▎ | 1105/8720 [3:02:04<16:54:24, 7.99s/it] {'loss': 1.4243, 'grad_norm': 10.289196968078613, 'learning_rate': 9.756886923289433e-06, 'epoch': 1.27} + 13%|█▎ | 1105/8720 [3:02:04<16:54:24, 7.99s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 01:17:30,895] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.69 | bwd_microstep: 271.93 | bwd_inner_microstep: 271.91 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1888 +[2025-05-02 01:17:31,374] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.70 | bwd_microstep: 274.23 | bwd_inner_microstep: 274.21 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1371 +[2025-05-02 01:17:31,736] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.92 | bwd_microstep: 207.62 | bwd_inner_microstep: 207.60 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-02 01:17:32,214] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.50 | bwd_microstep: 274.08 | bwd_inner_microstep: 274.06 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-02 01:17:32,692] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.80 | bwd_microstep: 274.16 | bwd_inner_microstep: 274.14 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1363 +[2025-05-02 01:17:33,054] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.42 | bwd_microstep: 206.30 | bwd_inner_microstep: 206.28 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1347 +[2025-05-02 01:17:33,413] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 139.83 | bwd_microstep: 205.12 | bwd_inner_microstep: 205.10 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.07 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1353 +[2025-05-02 01:17:33,773] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.01 | bwd_microstep: 205.63 | bwd_inner_microstep: 205.62 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:17:34,248] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.48 | bwd_microstep: 272.34 | bwd_inner_microstep: 272.32 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:17:34,723] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.62 | bwd_microstep: 272.48 | bwd_inner_microstep: 272.46 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 838 +[2025-05-02 01:17:34,956] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 92.16 | bwd_microstep: 126.29 | bwd_inner_microstep: 126.19 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:17:35,430] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.34 | bwd_microstep: 272.12 | bwd_inner_microstep: 272.10 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 01:17:35,905] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.66 | bwd_microstep: 271.01 | bwd_inner_microstep: 271.00 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:17:36,380] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.41 | bwd_microstep: 271.31 | bwd_inner_microstep: 271.29 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 01:17:36,855] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.85 | bwd_microstep: 270.89 | bwd_inner_microstep: 270.88 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2008 +[2025-05-02 01:17:37,472] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.06 | optimizer_step: 16.34 +[2025-05-02 01:17:37,472] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 197.77 | bwd_microstep: 376.98 | bwd_inner_microstep: 295.64 | bwd_allreduce_microstep: 81.28 | step_microstep: 23.94 +[2025-05-02 01:17:37,474] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2731.89 | bwd: 4052.52 | bwd_inner: 3970.82 | bwd_allreduce: 81.41 | step: 24.78 + 13%|█▎ | 1106/8720 [3:02:11<16:18:49, 7.71s/it] {'loss': 0.8318, 'grad_norm': 5.479996681213379, 'learning_rate': 9.756314534629551e-06, 'epoch': 1.27} + 13%|█▎ | 1106/8720 [3:02:11<16:18:49, 7.71s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1933 +[2025-05-02 01:17:37,979] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.69 | bwd_microstep: 286.79 | bwd_inner_microstep: 286.77 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 448 +[2025-05-02 01:17:38,239] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 90.87 | bwd_microstep: 152.13 | bwd_inner_microstep: 151.83 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1910 +[2025-05-02 01:17:38,722] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.17 | bwd_microstep: 276.29 | bwd_inner_microstep: 276.27 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 01:17:39,203] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.09 | bwd_microstep: 273.27 | bwd_inner_microstep: 273.25 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 324 +[2025-05-02 01:17:39,455] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.11 | bwd_microstep: 136.05 | bwd_inner_microstep: 135.90 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 01:17:39,932] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.39 | bwd_microstep: 272.50 | bwd_inner_microstep: 272.48 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 01:17:40,410] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.16 | bwd_microstep: 272.44 | bwd_inner_microstep: 272.42 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:17:40,885] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.88 | bwd_microstep: 272.32 | bwd_inner_microstep: 272.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:17:41,362] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.67 | bwd_microstep: 272.42 | bwd_inner_microstep: 272.40 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1355 +[2025-05-02 01:17:41,730] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 143.07 | bwd_microstep: 206.30 | bwd_inner_microstep: 206.16 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 01:17:42,207] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.64 | bwd_microstep: 271.82 | bwd_inner_microstep: 271.81 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:17:42,686] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.89 | bwd_microstep: 272.22 | bwd_inner_microstep: 272.21 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:17:43,164] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.67 | bwd_microstep: 271.08 | bwd_inner_microstep: 271.06 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:17:43,641] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.23 | bwd_microstep: 271.22 | bwd_inner_microstep: 271.20 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 827 +[2025-05-02 01:17:43,882] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.38 | bwd_microstep: 129.89 | bwd_inner_microstep: 129.57 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1893 +[2025-05-02 01:17:44,457] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.11 | optimizer_step: 16.64 +[2025-05-02 01:17:44,458] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.07 | bwd_microstep: 344.62 | bwd_inner_microstep: 275.50 | bwd_allreduce_microstep: 69.01 | step_microstep: 24.06 +[2025-05-02 01:17:44,459] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2690.61 | bwd: 3981.45 | bwd_inner: 3911.33 | bwd_allreduce: 69.46 | step: 25.11 + 13%|█▎ | 1107/8720 [3:02:18<15:50:55, 7.49s/it] {'loss': 0.7084, 'grad_norm': 7.630951881408691, 'learning_rate': 9.755741489771607e-06, 'epoch': 1.27} + 13%|█▎ | 1107/8720 [3:02:18<15:50:55, 7.49s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 348 +[2025-05-02 01:17:44,671] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 71.27 | bwd_microstep: 121.38 | bwd_inner_microstep: 121.25 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1925 +[2025-05-02 01:17:45,168] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 193.82 | bwd_microstep: 286.52 | bwd_inner_microstep: 286.50 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 866 +[2025-05-02 01:17:45,411] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.00 | bwd_microstep: 133.49 | bwd_inner_microstep: 133.38 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 01:17:45,888] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.56 | bwd_microstep: 272.83 | bwd_inner_microstep: 272.82 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1362 +[2025-05-02 01:17:46,253] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.20 | bwd_microstep: 206.14 | bwd_inner_microstep: 206.12 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-02 01:17:46,732] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.91 | bwd_microstep: 272.77 | bwd_inner_microstep: 272.75 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-02 01:17:47,214] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.43 | bwd_microstep: 273.08 | bwd_inner_microstep: 273.06 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 01:17:47,693] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.22 | bwd_microstep: 272.55 | bwd_inner_microstep: 272.53 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 01:17:48,172] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.06 | bwd_microstep: 272.45 | bwd_inner_microstep: 272.43 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:17:48,650] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.62 | bwd_microstep: 272.28 | bwd_inner_microstep: 272.27 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:17:49,128] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.72 | bwd_microstep: 272.03 | bwd_inner_microstep: 272.02 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:17:49,606] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.50 | bwd_microstep: 271.95 | bwd_inner_microstep: 271.93 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:17:50,082] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.39 | bwd_microstep: 270.97 | bwd_inner_microstep: 270.95 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:17:50,559] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.01 | bwd_microstep: 270.98 | bwd_inner_microstep: 270.96 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:17:51,038] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.04 | bwd_microstep: 270.90 | bwd_inner_microstep: 270.89 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:17:51,617] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.11 | optimizer_step: 16.60 +[2025-05-02 01:17:51,618] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.92 | bwd_microstep: 348.72 | bwd_inner_microstep: 271.46 | bwd_allreduce_microstep: 77.21 | step_microstep: 24.40 +[2025-05-02 01:17:51,619] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2754.31 | bwd: 4089.10 | bwd_inner: 4011.35 | bwd_allreduce: 77.39 | step: 25.40 + 13%|█▎ | 1108/8720 [3:02:25<15:38:07, 7.39s/it] {'loss': 1.1564, 'grad_norm': 14.607735633850098, 'learning_rate': 9.755167788794656e-06, 'epoch': 1.27} + 13%|█▎ | 1108/8720 [3:02:25<15:38:07, 7.39s/it]dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1340 +[2025-05-02 01:17:51,988] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 143.00 | bwd_microstep: 203.77 | bwd_inner_microstep: 203.66 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2201 +[2025-05-02 01:17:52,535] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 208.54 | bwd_microstep: 321.80 | bwd_inner_microstep: 321.78 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2000 +[2025-05-02 01:17:53,044] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 199.33 | bwd_microstep: 294.10 | bwd_inner_microstep: 294.08 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1450 +[2025-05-02 01:17:53,422] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 146.56 | bwd_microstep: 215.77 | bwd_inner_microstep: 215.68 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1915 +[2025-05-02 01:17:53,904] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.79 | bwd_microstep: 276.50 | bwd_inner_microstep: 276.49 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1891 +[2025-05-02 01:17:54,383] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.13 | bwd_microstep: 274.64 | bwd_inner_microstep: 274.62 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 01:17:54,862] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.61 | bwd_microstep: 273.44 | bwd_inner_microstep: 273.43 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-02 01:17:55,340] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.94 | bwd_microstep: 273.81 | bwd_inner_microstep: 273.79 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 01:17:55,820] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.70 | bwd_microstep: 272.97 | bwd_inner_microstep: 272.95 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 835 +[2025-05-02 01:17:56,061] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 97.86 | bwd_microstep: 125.50 | bwd_inner_microstep: 125.46 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 01:17:56,541] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.56 | bwd_microstep: 272.97 | bwd_inner_microstep: 272.95 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.14 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 01:17:57,021] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.52 | bwd_microstep: 272.92 | bwd_inner_microstep: 272.91 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:17:57,500] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.57 | bwd_microstep: 272.38 | bwd_inner_microstep: 272.36 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 835 +[2025-05-02 01:17:57,739] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.95 | bwd_microstep: 125.56 | bwd_inner_microstep: 125.51 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:17:58,218] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.71 | bwd_microstep: 272.25 | bwd_inner_microstep: 272.23 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:17:58,800] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.12 | optimizer_step: 16.53 +[2025-05-02 01:17:58,801] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.09 | bwd_microstep: 349.56 | bwd_inner_microstep: 272.61 | bwd_allreduce_microstep: 76.89 | step_microstep: 24.44 +[2025-05-02 01:17:58,802] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2778.51 | bwd: 4098.02 | bwd_inner: 4020.52 | bwd_allreduce: 77.09 | step: 25.56 + 13%|█▎ | 1109/8720 [3:02:32<15:29:57, 7.33s/it] {'loss': 0.9396, 'grad_norm': 7.0537333488464355, 'learning_rate': 9.754593431777847e-06, 'epoch': 1.27} + 13%|█▎ | 1109/8720 [3:02:32<15:29:57, 7.33s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:17:59,284] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.77 | bwd_microstep: 270.39 | bwd_inner_microstep: 270.37 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1949 +[2025-05-02 01:17:59,788] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.69 | bwd_microstep: 289.36 | bwd_inner_microstep: 289.34 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1914 +[2025-05-02 01:18:00,277] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.92 | bwd_microstep: 276.27 | bwd_inner_microstep: 276.25 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 381 +[2025-05-02 01:18:00,503] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 83.12 | bwd_microstep: 127.57 | bwd_inner_microstep: 127.42 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 01:18:00,981] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.75 | bwd_microstep: 273.13 | bwd_inner_microstep: 273.11 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 6, images per sample: 6.0, dynamic token length: 1618 +[2025-05-02 01:18:01,408] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 166.14 | bwd_microstep: 245.49 | bwd_inner_microstep: 245.47 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 01:18:01,884] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.96 | bwd_microstep: 272.93 | bwd_inner_microstep: 272.91 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 01:18:02,360] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.64 | bwd_microstep: 272.52 | bwd_inner_microstep: 272.51 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 326 +[2025-05-02 01:18:02,575] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 83.63 | bwd_microstep: 117.26 | bwd_inner_microstep: 117.08 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.10 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1358 +[2025-05-02 01:18:02,942] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.38 | bwd_microstep: 206.56 | bwd_inner_microstep: 206.45 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:18:03,420] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.53 | bwd_microstep: 272.13 | bwd_inner_microstep: 272.11 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:18:03,899] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.03 | bwd_microstep: 271.91 | bwd_inner_microstep: 271.90 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:18:04,382] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.10 | bwd_microstep: 272.16 | bwd_inner_microstep: 272.14 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:18:04,859] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.09 | bwd_microstep: 270.83 | bwd_inner_microstep: 270.81 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 828 +[2025-05-02 01:18:05,110] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 99.51 | bwd_microstep: 129.60 | bwd_inner_microstep: 129.29 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 01:18:05,694] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.11 | optimizer_step: 16.53 +[2025-05-02 01:18:05,695] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.36 | bwd_microstep: 353.73 | bwd_inner_microstep: 271.30 | bwd_allreduce_microstep: 82.38 | step_microstep: 24.47 +[2025-05-02 01:18:05,696] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2649.23 | bwd: 3921.96 | bwd_inner: 3838.62 | bwd_allreduce: 82.73 | step: 25.64 + 13%|█▎ | 1110/8720 [3:02:39<15:13:11, 7.20s/it] {'loss': 0.9081, 'grad_norm': 7.964339733123779, 'learning_rate': 9.754018418800426e-06, 'epoch': 1.27} + 13%|█▎ | 1110/8720 [3:02:39<15:13:11, 7.20s/it]dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 827 +[2025-05-02 01:18:05,943] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.38 | bwd_microstep: 129.94 | bwd_inner_microstep: 129.62 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.10 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 922 +[2025-05-02 01:18:06,207] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 101.91 | bwd_microstep: 145.63 | bwd_inner_microstep: 145.38 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1893 +[2025-05-02 01:18:06,687] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.36 | bwd_microstep: 274.76 | bwd_inner_microstep: 274.75 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1367 +[2025-05-02 01:18:07,053] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.00 | bwd_microstep: 207.31 | bwd_inner_microstep: 207.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-02 01:18:07,531] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.77 | bwd_microstep: 273.54 | bwd_inner_microstep: 273.52 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1355 +[2025-05-02 01:18:07,895] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.24 | bwd_microstep: 206.28 | bwd_inner_microstep: 206.13 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-02 01:18:08,375] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.00 | bwd_microstep: 273.22 | bwd_inner_microstep: 273.21 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 01:18:08,855] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.91 | bwd_microstep: 272.76 | bwd_inner_microstep: 272.74 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 01:18:09,339] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.50 | bwd_microstep: 272.85 | bwd_inner_microstep: 272.84 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:18:09,818] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.70 | bwd_microstep: 272.44 | bwd_inner_microstep: 272.43 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 329 +[2025-05-02 01:18:10,046] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 88.39 | bwd_microstep: 121.74 | bwd_inner_microstep: 121.43 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 330 +[2025-05-02 01:18:10,268] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 84.48 | bwd_microstep: 121.92 | bwd_inner_microstep: 121.65 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 01:18:10,747] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.14 | bwd_microstep: 272.72 | bwd_inner_microstep: 272.70 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:18:11,225] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.34 | bwd_microstep: 272.40 | bwd_inner_microstep: 272.38 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:18:11,704] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.27 | bwd_microstep: 272.40 | bwd_inner_microstep: 272.39 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:18:12,284] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.16 | optimizer_step: 16.79 +[2025-05-02 01:18:12,285] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.96 | bwd_microstep: 349.82 | bwd_inner_microstep: 272.81 | bwd_allreduce_microstep: 76.96 | step_microstep: 24.67 +[2025-05-02 01:18:12,286] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2536.00 | bwd: 3739.85 | bwd_inner: 3661.46 | bwd_allreduce: 77.59 | step: 25.72 + 13%|█▎ | 1111/8720 [3:02:46<14:49:53, 7.02s/it] {'loss': 0.8928, 'grad_norm': 12.486407279968262, 'learning_rate': 9.753442749941716e-06, 'epoch': 1.27} + 13%|█▎ | 1111/8720 [3:02:46<14:49:53, 7.02s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:18:12,770] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.27 | bwd_microstep: 270.43 | bwd_inner_microstep: 270.41 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2142 +[2025-05-02 01:18:13,307] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 206.75 | bwd_microstep: 314.32 | bwd_inner_microstep: 314.31 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1901 +[2025-05-02 01:18:13,787] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.24 | bwd_microstep: 275.42 | bwd_inner_microstep: 275.40 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-02 01:18:14,265] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.70 | bwd_microstep: 274.23 | bwd_inner_microstep: 274.21 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-02 01:18:14,743] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.34 | bwd_microstep: 273.86 | bwd_inner_microstep: 273.84 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 01:18:15,220] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.21 | bwd_microstep: 273.22 | bwd_inner_microstep: 273.20 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1361 +[2025-05-02 01:18:15,583] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.37 | bwd_microstep: 206.55 | bwd_inner_microstep: 206.53 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 01:18:16,059] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.02 | bwd_microstep: 272.87 | bwd_inner_microstep: 272.85 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 850 +[2025-05-02 01:18:16,299] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.66 | bwd_microstep: 132.63 | bwd_inner_microstep: 132.22 | bwd_allreduce_microstep: 0.14 | step_microstep: 0.23 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:18:16,776] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.50 | bwd_microstep: 272.22 | bwd_inner_microstep: 272.20 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1094 +[2025-05-02 01:18:17,071] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 118.11 | bwd_microstep: 160.76 | bwd_inner_microstep: 160.74 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:18:17,551] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.15 | bwd_microstep: 272.70 | bwd_inner_microstep: 272.68 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.14 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 837 +[2025-05-02 01:18:17,798] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 97.29 | bwd_microstep: 131.73 | bwd_inner_microstep: 131.58 | bwd_allreduce_microstep: 0.10 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:18:18,277] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.29 | bwd_microstep: 272.49 | bwd_inner_microstep: 272.47 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1344 +[2025-05-02 01:18:18,639] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.25 | bwd_microstep: 204.48 | bwd_inner_microstep: 204.46 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 318 +[2025-05-02 01:18:18,980] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.09 | optimizer_step: 16.37 +[2025-05-02 01:18:18,981] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 88.40 | bwd_microstep: 213.19 | bwd_inner_microstep: 136.74 | bwd_allreduce_microstep: 76.35 | step_microstep: 23.94 +[2025-05-02 01:18:18,982] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2581.22 | bwd: 3821.17 | bwd_inner: 3743.96 | bwd_allreduce: 76.65 | step: 25.05 + 13%|█▎ | 1112/8720 [3:02:52<14:37:30, 6.92s/it] {'loss': 0.8583, 'grad_norm': 7.060497760772705, 'learning_rate': 9.752866425281146e-06, 'epoch': 1.28} + 13%|█▎ | 1112/8720 [3:02:52<14:37:30, 6.92s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:18:19,463] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.19 | bwd_microstep: 270.68 | bwd_inner_microstep: 270.66 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1379 +[2025-05-02 01:18:19,830] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.58 | bwd_microstep: 208.16 | bwd_inner_microstep: 208.10 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1887 +[2025-05-02 01:18:20,315] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.65 | bwd_microstep: 274.63 | bwd_inner_microstep: 274.61 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-02 01:18:20,798] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.98 | bwd_microstep: 273.95 | bwd_inner_microstep: 273.94 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 01:18:21,277] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.81 | bwd_microstep: 272.62 | bwd_inner_microstep: 272.60 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1889 +[2025-05-02 01:18:21,757] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.14 | bwd_microstep: 274.62 | bwd_inner_microstep: 274.61 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 01:18:22,239] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.51 | bwd_microstep: 273.24 | bwd_inner_microstep: 273.22 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 01:18:22,721] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.52 | bwd_microstep: 272.88 | bwd_inner_microstep: 272.87 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 01:18:23,199] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.92 | bwd_microstep: 272.69 | bwd_inner_microstep: 272.67 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 01:18:23,677] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.33 | bwd_microstep: 272.63 | bwd_inner_microstep: 272.61 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:18:24,154] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.67 | bwd_microstep: 272.52 | bwd_inner_microstep: 272.50 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:18:24,631] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.49 | bwd_microstep: 272.59 | bwd_inner_microstep: 272.57 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:18:25,107] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.20 | bwd_microstep: 272.41 | bwd_inner_microstep: 272.40 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 318 +[2025-05-02 01:18:25,321] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 84.15 | bwd_microstep: 115.21 | bwd_inner_microstep: 115.02 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:18:25,797] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.29 | bwd_microstep: 271.71 | bwd_inner_microstep: 271.69 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 01:18:26,375] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.07 | optimizer_gradients: 2.10 | optimizer_step: 16.42 +[2025-05-02 01:18:26,375] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.66 | bwd_microstep: 348.88 | bwd_inner_microstep: 271.67 | bwd_allreduce_microstep: 77.16 | step_microstep: 24.07 +[2025-05-02 01:18:26,377] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2862.73 | bwd: 4219.49 | bwd_inner: 4141.80 | bwd_allreduce: 77.32 | step: 24.98 + 13%|█▎ | 1113/8720 [3:03:00<14:55:26, 7.06s/it] {'loss': 1.0567, 'grad_norm': 11.46663761138916, 'learning_rate': 9.752289444898224e-06, 'epoch': 1.28} + 13%|█▎ | 1113/8720 [3:03:00<14:55:26, 7.06s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1886 +[2025-05-02 01:18:26,862] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.95 | bwd_microstep: 273.73 | bwd_inner_microstep: 273.72 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 388 +[2025-05-02 01:18:27,074] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 78.43 | bwd_microstep: 119.42 | bwd_inner_microstep: 119.19 | bwd_allreduce_microstep: 0.08 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 01:18:27,551] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.99 | bwd_microstep: 273.35 | bwd_inner_microstep: 273.33 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 327 +[2025-05-02 01:18:27,761] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 74.79 | bwd_microstep: 121.96 | bwd_inner_microstep: 121.67 | bwd_allreduce_microstep: 0.10 | step_microstep: 0.16 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-02 01:18:28,236] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.59 | bwd_microstep: 273.22 | bwd_inner_microstep: 273.21 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-02 01:18:28,713] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.01 | bwd_microstep: 273.14 | bwd_inner_microstep: 273.12 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 328 +[2025-05-02 01:18:28,933] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 89.50 | bwd_microstep: 115.12 | bwd_inner_microstep: 114.94 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.09 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 331 +[2025-05-02 01:18:29,153] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 78.84 | bwd_microstep: 125.66 | bwd_inner_microstep: 125.42 | bwd_allreduce_microstep: 0.10 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 01:18:29,631] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.11 | bwd_microstep: 272.82 | bwd_inner_microstep: 272.80 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1094 +[2025-05-02 01:18:29,925] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 115.48 | bwd_microstep: 160.98 | bwd_inner_microstep: 160.94 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 01:18:30,407] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.95 | bwd_microstep: 272.98 | bwd_inner_microstep: 272.96 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.06 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 323 +[2025-05-02 01:18:30,629] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 83.18 | bwd_microstep: 122.69 | bwd_inner_microstep: 122.54 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 01:18:31,106] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.62 | bwd_microstep: 271.44 | bwd_inner_microstep: 271.42 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 01:18:31,583] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.77 | bwd_microstep: 271.22 | bwd_inner_microstep: 271.21 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 01:18:32,059] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.09 | bwd_microstep: 271.11 | bwd_inner_microstep: 271.09 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 371 +[2025-05-02 01:18:32,404] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.11 | optimizer_step: 16.38 +[2025-05-02 01:18:32,405] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 84.74 | bwd_microstep: 220.85 | bwd_inner_microstep: 144.21 | bwd_allreduce_microstep: 76.51 | step_microstep: 23.90 +[2025-05-02 01:18:32,406] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2298.71 | bwd: 3439.82 | bwd_inner: 3362.10 | bwd_allreduce: 76.92 | step: 25.07 + 13%|█▎ | 1114/8720 [3:03:06<14:16:02, 6.75s/it] {'loss': 0.9008, 'grad_norm': 10.816823959350586, 'learning_rate': 9.75171180887255e-06, 'epoch': 1.28} + 13%|█▎ | 1114/8720 [3:03:06<14:16:02, 6.75s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1892 +[2025-05-02 01:18:32,892] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.14 | bwd_microstep: 274.34 | bwd_inner_microstep: 274.32 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1150 +[2025-05-02 01:18:33,194] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 120.49 | bwd_microstep: 165.24 | bwd_inner_microstep: 165.06 | bwd_allreduce_microstep: 0.09 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1920 +[2025-05-02 01:18:33,675] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.92 | bwd_microstep: 276.45 | bwd_inner_microstep: 276.44 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 384 +[2025-05-02 01:18:33,889] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 85.06 | bwd_microstep: 114.32 | bwd_inner_microstep: 114.02 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1893 +[2025-05-02 01:18:34,370] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.25 | bwd_microstep: 274.99 | bwd_inner_microstep: 274.97 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 351 +[2025-05-02 01:18:34,611] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 101.00 | bwd_microstep: 121.14 | bwd_inner_microstep: 120.95 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1887 +[2025-05-02 01:18:35,097] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.36 | bwd_microstep: 274.47 | bwd_inner_microstep: 274.46 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1109 +[2025-05-02 01:18:35,395] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 115.83 | bwd_microstep: 162.09 | bwd_inner_microstep: 162.07 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 01:18:35,874] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.30 | bwd_microstep: 273.26 | bwd_inner_microstep: 273.24 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 01:18:36,352] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.49 | bwd_microstep: 272.57 | bwd_inner_microstep: 272.55 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 840 +[2025-05-02 01:18:36,598] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 100.50 | bwd_microstep: 126.40 | bwd_inner_microstep: 126.33 | bwd_allreduce_microstep: 0.03 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:18:37,074] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.81 | bwd_microstep: 272.34 | bwd_inner_microstep: 272.32 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 321 +[2025-05-02 01:18:37,305] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.86 | bwd_microstep: 120.96 | bwd_inner_microstep: 120.70 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:18:37,781] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.21 | bwd_microstep: 271.26 | bwd_inner_microstep: 271.25 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 01:18:38,257] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.02 | bwd_microstep: 271.16 | bwd_inner_microstep: 271.14 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:18:38,834] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.04 | optimizer_step: 16.37 +[2025-05-02 01:18:38,834] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.86 | bwd_microstep: 348.19 | bwd_inner_microstep: 271.58 | bwd_allreduce_microstep: 76.56 | step_microstep: 23.97 +[2025-05-02 01:18:38,836] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2501.74 | bwd: 3619.29 | bwd_inner: 3541.61 | bwd_allreduce: 77.03 | step: 25.12 + 13%|█▎ | 1115/8720 [3:03:12<14:03:37, 6.66s/it] {'loss': 0.8832, 'grad_norm': 9.213582038879395, 'learning_rate': 9.751133517283821e-06, 'epoch': 1.28} + 13%|█▎ | 1115/8720 [3:03:12<14:03:37, 6.66s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:18:39,317] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.36 | bwd_microstep: 270.64 | bwd_inner_microstep: 270.62 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1894 +[2025-05-02 01:18:39,796] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.09 | bwd_microstep: 275.03 | bwd_inner_microstep: 275.01 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1894 +[2025-05-02 01:18:40,276] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.63 | bwd_microstep: 274.87 | bwd_inner_microstep: 274.85 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 337 +[2025-05-02 01:18:40,477] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 68.73 | bwd_microstep: 118.84 | bwd_inner_microstep: 118.53 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-02 01:18:40,954] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.87 | bwd_microstep: 273.57 | bwd_inner_microstep: 273.56 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 01:18:41,433] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.61 | bwd_microstep: 273.04 | bwd_inner_microstep: 273.03 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 01:18:41,914] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.26 | bwd_microstep: 272.94 | bwd_inner_microstep: 272.92 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 333 +[2025-05-02 01:18:42,139] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 84.63 | bwd_microstep: 123.77 | bwd_inner_microstep: 123.56 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:18:42,617] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.07 | bwd_microstep: 272.42 | bwd_inner_microstep: 272.40 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 836 +[2025-05-02 01:18:42,857] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.78 | bwd_microstep: 125.81 | bwd_inner_microstep: 125.71 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:18:43,335] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.29 | bwd_microstep: 272.64 | bwd_inner_microstep: 272.62 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:18:43,816] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.26 | bwd_microstep: 272.39 | bwd_inner_microstep: 272.37 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:18:44,297] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.42 | bwd_microstep: 272.53 | bwd_inner_microstep: 272.51 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:18:44,780] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.70 | bwd_microstep: 272.53 | bwd_inner_microstep: 272.51 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:18:45,258] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.70 | bwd_microstep: 271.36 | bwd_inner_microstep: 271.35 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.10 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 316 +[2025-05-02 01:18:45,594] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.06 | optimizer_step: 16.41 +[2025-05-02 01:18:45,594] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 80.06 | bwd_microstep: 216.61 | bwd_inner_microstep: 140.32 | bwd_allreduce_microstep: 76.19 | step_microstep: 23.79 +[2025-05-02 01:18:45,595] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2591.10 | bwd: 3859.06 | bwd_inner: 3782.03 | bwd_allreduce: 76.49 | step: 24.73 + 13%|█▎ | 1116/8720 [3:03:19<14:07:24, 6.69s/it] {'loss': 0.6496, 'grad_norm': 6.42125940322876, 'learning_rate': 9.750554570211818e-06, 'epoch': 1.28} + 13%|█▎ | 1116/8720 [3:03:19<14:07:24, 6.69s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1925 +[2025-05-02 01:18:46,098] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.27 | bwd_microstep: 286.72 | bwd_inner_microstep: 286.70 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1910 +[2025-05-02 01:18:46,579] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.69 | bwd_microstep: 276.24 | bwd_inner_microstep: 276.22 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-02 01:18:47,057] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.90 | bwd_microstep: 273.83 | bwd_inner_microstep: 273.81 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 01:18:47,534] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.73 | bwd_microstep: 272.73 | bwd_inner_microstep: 272.72 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 01:18:48,010] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.35 | bwd_microstep: 272.86 | bwd_inner_microstep: 272.85 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 01:18:48,486] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.33 | bwd_microstep: 272.94 | bwd_inner_microstep: 272.93 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 842 +[2025-05-02 01:18:48,726] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.10 | bwd_microstep: 131.96 | bwd_inner_microstep: 131.71 | bwd_allreduce_microstep: 0.15 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:18:49,202] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.92 | bwd_microstep: 272.44 | bwd_inner_microstep: 272.42 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:18:49,678] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.99 | bwd_microstep: 272.63 | bwd_inner_microstep: 272.61 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:18:50,154] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.38 | bwd_microstep: 272.57 | bwd_inner_microstep: 272.55 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:18:50,631] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.98 | bwd_microstep: 272.34 | bwd_inner_microstep: 272.32 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 01:18:51,106] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.69 | bwd_microstep: 271.12 | bwd_inner_microstep: 271.10 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 01:18:51,583] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.23 | bwd_microstep: 270.99 | bwd_inner_microstep: 270.98 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 01:18:52,062] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.58 | bwd_microstep: 270.97 | bwd_inner_microstep: 270.95 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1886 +[2025-05-02 01:18:52,547] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.60 | bwd_microstep: 274.19 | bwd_inner_microstep: 274.17 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.13 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 01:18:53,138] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.08 | optimizer_step: 16.40 +[2025-05-02 01:18:53,139] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.38 | bwd_microstep: 358.95 | bwd_inner_microstep: 273.55 | bwd_allreduce_microstep: 85.35 | step_microstep: 23.94 +[2025-05-02 01:18:53,140] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2926.78 | bwd: 4323.52 | bwd_inner: 4237.60 | bwd_allreduce: 85.55 | step: 24.86 + 13%|█▎ | 1117/8720 [3:03:26<14:39:58, 6.94s/it] {'loss': 1.0271, 'grad_norm': 6.760204315185547, 'learning_rate': 9.749974967736415e-06, 'epoch': 1.28} + 13%|█▎ | 1117/8720 [3:03:26<14:39:58, 6.94s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 01:18:53,623] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.47 | bwd_microstep: 272.22 | bwd_inner_microstep: 272.21 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1904 +[2025-05-02 01:18:54,108] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.79 | bwd_microstep: 275.67 | bwd_inner_microstep: 275.66 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 01:18:54,589] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.77 | bwd_microstep: 273.22 | bwd_inner_microstep: 273.21 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-02 01:18:55,071] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.47 | bwd_microstep: 273.69 | bwd_inner_microstep: 273.68 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 01:18:55,551] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.32 | bwd_microstep: 272.77 | bwd_inner_microstep: 272.75 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1350 +[2025-05-02 01:18:55,920] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.05 | bwd_microstep: 205.54 | bwd_inner_microstep: 205.49 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 01:18:56,398] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.36 | bwd_microstep: 272.85 | bwd_inner_microstep: 272.84 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 01:18:56,877] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.26 | bwd_microstep: 272.89 | bwd_inner_microstep: 272.87 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 01:18:57,358] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.77 | bwd_microstep: 273.02 | bwd_inner_microstep: 273.00 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 01:18:57,839] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.23 | bwd_microstep: 272.73 | bwd_inner_microstep: 272.71 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 01:18:58,323] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.71 | bwd_microstep: 272.67 | bwd_inner_microstep: 272.65 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 01:18:58,800] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.38 | bwd_microstep: 272.06 | bwd_inner_microstep: 272.04 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1346 +[2025-05-02 01:18:59,166] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.87 | bwd_microstep: 205.56 | bwd_inner_microstep: 205.43 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 01:18:59,642] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.43 | bwd_microstep: 271.22 | bwd_inner_microstep: 271.21 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 834 +[2025-05-02 01:18:59,885] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 97.27 | bwd_microstep: 125.60 | bwd_inner_microstep: 125.56 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 320 +[2025-05-02 01:19:00,218] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.10 | optimizer_step: 16.40 +[2025-05-02 01:19:00,218] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 83.56 | bwd_microstep: 210.11 | bwd_inner_microstep: 133.60 | bwd_allreduce_microstep: 76.35 | step_microstep: 23.98 +[2025-05-02 01:19:00,220] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2726.30 | bwd: 4021.90 | bwd_inner: 3944.97 | bwd_allreduce: 76.52 | step: 25.09 + 13%|█▎ | 1118/8720 [3:03:33<14:44:59, 6.98s/it] {'loss': 0.7616, 'grad_norm': 5.676209926605225, 'learning_rate': 9.749394709937577e-06, 'epoch': 1.28} + 13%|█▎ | 1118/8720 [3:03:33<14:44:59, 6.98s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:19:00,700] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.56 | bwd_microstep: 270.45 | bwd_inner_microstep: 270.43 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2116 +[2025-05-02 01:19:01,237] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 205.79 | bwd_microstep: 312.98 | bwd_inner_microstep: 312.96 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1904 +[2025-05-02 01:19:01,723] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.73 | bwd_microstep: 275.75 | bwd_inner_microstep: 275.73 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1116 +[2025-05-02 01:19:02,020] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 115.73 | bwd_microstep: 162.62 | bwd_inner_microstep: 162.60 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 01:19:02,500] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.50 | bwd_microstep: 272.56 | bwd_inner_microstep: 272.54 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.13 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 01:19:02,981] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.19 | bwd_microstep: 272.86 | bwd_inner_microstep: 272.84 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 01:19:03,464] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.17 | bwd_microstep: 272.49 | bwd_inner_microstep: 272.47 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:19:03,948] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.45 | bwd_microstep: 272.60 | bwd_inner_microstep: 272.59 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 01:19:04,431] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.18 | bwd_microstep: 272.25 | bwd_inner_microstep: 272.23 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1090 +[2025-05-02 01:19:04,729] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 118.01 | bwd_microstep: 160.80 | bwd_inner_microstep: 160.61 | bwd_allreduce_microstep: 0.08 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:19:05,206] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.49 | bwd_microstep: 271.11 | bwd_inner_microstep: 271.09 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:19:05,684] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.53 | bwd_microstep: 271.25 | bwd_inner_microstep: 271.23 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1344 +[2025-05-02 01:19:06,046] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 139.75 | bwd_microstep: 204.54 | bwd_inner_microstep: 204.53 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:19:06,524] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.74 | bwd_microstep: 272.30 | bwd_inner_microstep: 272.28 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.13 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 01:19:07,006] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.01 | bwd_microstep: 272.76 | bwd_inner_microstep: 272.74 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 01:19:07,581] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.04 | optimizer_step: 16.57 +[2025-05-02 01:19:07,582] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.51 | bwd_microstep: 347.81 | bwd_inner_microstep: 271.26 | bwd_allreduce_microstep: 76.51 | step_microstep: 23.73 +[2025-05-02 01:19:07,583] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2837.92 | bwd: 4185.17 | bwd_inner: 4108.13 | bwd_allreduce: 76.73 | step: 24.90 + 13%|█▎ | 1119/8720 [3:03:41<14:59:12, 7.10s/it] {'loss': 0.7091, 'grad_norm': 13.37508487701416, 'learning_rate': 9.748813796895356e-06, 'epoch': 1.28} + 13%|█▎ | 1119/8720 [3:03:41<14:59:12, 7.10s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:19:08,062] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.40 | bwd_microstep: 270.34 | bwd_inner_microstep: 270.33 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-02 01:19:08,540] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.68 | bwd_microstep: 274.16 | bwd_inner_microstep: 274.14 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-02 01:19:09,020] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.12 | bwd_microstep: 273.62 | bwd_inner_microstep: 273.61 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.16 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1359 +[2025-05-02 01:19:09,387] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 143.37 | bwd_microstep: 206.64 | bwd_inner_microstep: 206.56 | bwd_allreduce_microstep: 0.04 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 01:19:09,865] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.96 | bwd_microstep: 272.63 | bwd_inner_microstep: 272.61 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 01:19:10,345] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.92 | bwd_microstep: 272.62 | bwd_inner_microstep: 272.61 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 01:19:10,825] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.93 | bwd_microstep: 272.72 | bwd_inner_microstep: 272.70 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 328 +[2025-05-02 01:19:11,043] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 80.51 | bwd_microstep: 121.80 | bwd_inner_microstep: 121.63 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:19:11,520] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.20 | bwd_microstep: 272.20 | bwd_inner_microstep: 272.18 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:19:11,999] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.67 | bwd_microstep: 272.40 | bwd_inner_microstep: 272.38 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:19:12,479] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.30 | bwd_microstep: 272.41 | bwd_inner_microstep: 272.40 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 836 +[2025-05-02 01:19:12,725] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 100.69 | bwd_microstep: 125.48 | bwd_inner_microstep: 125.44 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.13 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:19:13,209] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.15 | bwd_microstep: 272.48 | bwd_inner_microstep: 272.46 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:19:13,694] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.90 | bwd_microstep: 272.56 | bwd_inner_microstep: 272.54 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:19:14,173] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.45 | bwd_microstep: 271.49 | bwd_inner_microstep: 271.47 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1086 +[2025-05-02 01:19:14,568] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.11 | optimizer_step: 16.59 +[2025-05-02 01:19:14,569] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 118.07 | bwd_microstep: 236.67 | bwd_inner_microstep: 160.09 | bwd_allreduce_microstep: 76.48 | step_microstep: 24.39 +[2025-05-02 01:19:14,570] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2699.95 | bwd: 3960.31 | bwd_inner: 3883.21 | bwd_allreduce: 76.67 | step: 25.51 + 13%|█▎ | 1120/8720 [3:03:48<14:54:56, 7.07s/it] {'loss': 0.4692, 'grad_norm': 10.676127433776855, 'learning_rate': 9.748232228689899e-06, 'epoch': 1.28} + 13%|█▎ | 1120/8720 [3:03:48<14:54:56, 7.07s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1923 +[2025-05-02 01:19:15,075] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.16 | bwd_microstep: 286.28 | bwd_inner_microstep: 286.26 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2141 +[2025-05-02 01:19:15,611] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 204.45 | bwd_microstep: 314.74 | bwd_inner_microstep: 314.72 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2014 +[2025-05-02 01:19:16,124] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 200.87 | bwd_microstep: 295.85 | bwd_inner_microstep: 295.83 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1911 +[2025-05-02 01:19:16,606] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.34 | bwd_microstep: 276.37 | bwd_inner_microstep: 276.35 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 872 +[2025-05-02 01:19:16,851] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 96.89 | bwd_microstep: 134.26 | bwd_inner_microstep: 134.17 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 01:19:17,329] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.68 | bwd_microstep: 273.74 | bwd_inner_microstep: 273.73 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 01:19:17,805] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.35 | bwd_microstep: 272.87 | bwd_inner_microstep: 272.85 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-02 01:19:18,282] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.23 | bwd_microstep: 273.38 | bwd_inner_microstep: 273.36 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-02 01:19:18,759] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.64 | bwd_microstep: 273.49 | bwd_inner_microstep: 273.47 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 01:19:19,237] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.57 | bwd_microstep: 273.06 | bwd_inner_microstep: 273.05 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 01:19:19,713] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.73 | bwd_microstep: 273.04 | bwd_inner_microstep: 273.02 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:19:20,190] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.10 | bwd_microstep: 272.70 | bwd_inner_microstep: 272.68 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 01:19:20,667] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.22 | bwd_microstep: 272.81 | bwd_inner_microstep: 272.79 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:19:21,143] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.00 | bwd_microstep: 272.32 | bwd_inner_microstep: 272.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 326 +[2025-05-02 01:19:21,345] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 69.29 | bwd_microstep: 119.49 | bwd_inner_microstep: 119.18 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:19:21,911] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.04 | optimizer_gradients: 2.18 | optimizer_step: 16.75 +[2025-05-02 01:19:21,912] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.65 | bwd_microstep: 340.06 | bwd_inner_microstep: 272.92 | bwd_allreduce_microstep: 67.09 | step_microstep: 23.97 +[2025-05-02 01:19:21,913] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2840.89 | bwd: 4224.49 | bwd_inner: 4156.75 | bwd_allreduce: 67.35 | step: 24.82 + 13%|█▎ | 1121/8720 [3:03:55<15:05:17, 7.15s/it] {'loss': 0.6892, 'grad_norm': 3.7459394931793213, 'learning_rate': 9.74765000540144e-06, 'epoch': 1.29} + 13%|█▎ | 1121/8720 [3:03:55<15:05:17, 7.15s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 315 +[2025-05-02 01:19:22,117] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 68.23 | bwd_microstep: 117.51 | bwd_inner_microstep: 117.33 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1923 +[2025-05-02 01:19:22,613] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 194.79 | bwd_microstep: 286.53 | bwd_inner_microstep: 286.51 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1891 +[2025-05-02 01:19:23,093] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.16 | bwd_microstep: 274.86 | bwd_inner_microstep: 274.84 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 339 +[2025-05-02 01:19:23,309] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 79.29 | bwd_microstep: 123.42 | bwd_inner_microstep: 123.12 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 01:19:23,786] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.30 | bwd_microstep: 272.90 | bwd_inner_microstep: 272.89 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-02 01:19:24,263] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.71 | bwd_microstep: 273.13 | bwd_inner_microstep: 273.12 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 341 +[2025-05-02 01:19:24,471] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 73.29 | bwd_microstep: 120.79 | bwd_inner_microstep: 120.67 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:19:24,947] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.19 | bwd_microstep: 272.56 | bwd_inner_microstep: 272.55 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1347 +[2025-05-02 01:19:25,310] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.82 | bwd_microstep: 205.78 | bwd_inner_microstep: 205.76 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:19:25,787] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.51 | bwd_microstep: 272.57 | bwd_inner_microstep: 272.55 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 01:19:26,266] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.88 | bwd_microstep: 272.97 | bwd_inner_microstep: 272.95 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 01:19:26,743] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.33 | bwd_microstep: 272.75 | bwd_inner_microstep: 272.74 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 01:19:27,219] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.89 | bwd_microstep: 272.19 | bwd_inner_microstep: 272.17 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:19:27,693] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.38 | bwd_microstep: 271.16 | bwd_inner_microstep: 271.14 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 01:19:28,169] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.37 | bwd_microstep: 271.17 | bwd_inner_microstep: 271.15 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1988 +[2025-05-02 01:19:28,767] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.13 | optimizer_step: 16.66 +[2025-05-02 01:19:28,768] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 198.09 | bwd_microstep: 360.71 | bwd_inner_microstep: 293.87 | bwd_allreduce_microstep: 66.79 | step_microstep: 23.81 +[2025-05-02 01:19:28,769] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2637.96 | bwd: 3941.06 | bwd_inner: 3873.51 | bwd_allreduce: 67.09 | step: 24.64 + 13%|█▎ | 1122/8720 [3:04:02<14:54:04, 7.06s/it] {'loss': 0.8137, 'grad_norm': 13.517590522766113, 'learning_rate': 9.747067127110306e-06, 'epoch': 1.29} + 13%|█▎ | 1122/8720 [3:04:02<14:54:04, 7.06s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-02 01:19:29,252] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.19 | bwd_microstep: 273.17 | bwd_inner_microstep: 273.15 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1891 +[2025-05-02 01:19:29,732] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.10 | bwd_microstep: 274.96 | bwd_inner_microstep: 274.95 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1886 +[2025-05-02 01:19:30,212] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.63 | bwd_microstep: 275.20 | bwd_inner_microstep: 275.18 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1370 +[2025-05-02 01:19:30,578] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.90 | bwd_microstep: 207.90 | bwd_inner_microstep: 207.74 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 01:19:31,056] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.07 | bwd_microstep: 273.22 | bwd_inner_microstep: 273.20 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-02 01:19:31,536] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.97 | bwd_microstep: 273.42 | bwd_inner_microstep: 273.40 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 837 +[2025-05-02 01:19:31,772] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.08 | bwd_microstep: 126.16 | bwd_inner_microstep: 126.04 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 01:19:32,250] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.03 | bwd_microstep: 272.88 | bwd_inner_microstep: 272.86 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 01:19:32,727] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.51 | bwd_microstep: 273.04 | bwd_inner_microstep: 273.02 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 01:19:33,205] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.38 | bwd_microstep: 273.16 | bwd_inner_microstep: 273.15 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 01:19:33,682] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.61 | bwd_microstep: 272.93 | bwd_inner_microstep: 272.92 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 01:19:34,158] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.41 | bwd_microstep: 272.73 | bwd_inner_microstep: 272.71 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 333 +[2025-05-02 01:19:34,361] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 68.71 | bwd_microstep: 120.73 | bwd_inner_microstep: 120.51 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.09 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 320 +[2025-05-02 01:19:34,565] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 73.76 | bwd_microstep: 116.34 | bwd_inner_microstep: 116.21 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:19:35,041] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.87 | bwd_microstep: 272.33 | bwd_inner_microstep: 272.32 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1098 +[2025-05-02 01:19:35,428] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.25 | optimizer_step: 20.12 +[2025-05-02 01:19:35,429] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 115.10 | bwd_microstep: 229.51 | bwd_inner_microstep: 162.00 | bwd_allreduce_microstep: 67.36 | step_microstep: 27.54 +[2025-05-02 01:19:35,430] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2572.02 | bwd: 3807.75 | bwd_inner: 3739.51 | bwd_allreduce: 67.64 | step: 28.46 + 13%|█▎ | 1123/8720 [3:04:09<14:38:47, 6.94s/it] {'loss': 1.1523, 'grad_norm': 7.144784450531006, 'learning_rate': 9.746483593896911e-06, 'epoch': 1.29} + 13%|█▎ | 1123/8720 [3:04:09<14:38:47, 6.94s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 01:19:35,910] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.91 | bwd_microstep: 271.99 | bwd_inner_microstep: 271.97 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1948 +[2025-05-02 01:19:36,411] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 196.38 | bwd_microstep: 289.23 | bwd_inner_microstep: 289.21 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1911 +[2025-05-02 01:19:36,894] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.19 | bwd_microstep: 276.56 | bwd_inner_microstep: 276.54 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1888 +[2025-05-02 01:19:37,374] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.17 | bwd_microstep: 275.16 | bwd_inner_microstep: 275.15 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-02 01:19:37,854] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.07 | bwd_microstep: 274.05 | bwd_inner_microstep: 274.03 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 01:19:38,330] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.62 | bwd_microstep: 272.77 | bwd_inner_microstep: 272.75 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1109 +[2025-05-02 01:19:38,623] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 115.60 | bwd_microstep: 162.09 | bwd_inner_microstep: 162.07 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:19:39,098] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.93 | bwd_microstep: 272.39 | bwd_inner_microstep: 272.37 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 01:19:39,573] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.18 | bwd_microstep: 272.63 | bwd_inner_microstep: 272.61 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 01:19:40,051] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.95 | bwd_microstep: 272.20 | bwd_inner_microstep: 272.18 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:19:40,538] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.42 | bwd_microstep: 272.40 | bwd_inner_microstep: 272.39 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 01:19:41,025] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.72 | bwd_microstep: 272.37 | bwd_inner_microstep: 272.35 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.15 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 01:19:41,508] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.36 | bwd_microstep: 271.35 | bwd_inner_microstep: 271.34 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.13 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:19:41,986] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.72 | bwd_microstep: 271.31 | bwd_inner_microstep: 271.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 829 +[2025-05-02 01:19:42,230] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 96.31 | bwd_microstep: 129.87 | bwd_inner_microstep: 129.67 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.13 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 315 +[2025-05-02 01:19:42,577] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.07 | optimizer_gradients: 2.24 | optimizer_step: 20.70 +[2025-05-02 01:19:42,578] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 82.96 | bwd_microstep: 218.36 | bwd_inner_microstep: 135.48 | bwd_allreduce_microstep: 82.73 | step_microstep: 29.45 +[2025-05-02 01:19:42,580] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2753.14 | bwd: 4074.81 | bwd_inner: 3991.49 | bwd_allreduce: 82.91 | step: 30.60 + 13%|█▎ | 1124/8720 [3:04:16<14:46:44, 7.00s/it] {'loss': 1.0295, 'grad_norm': 9.668963432312012, 'learning_rate': 9.745899405841764e-06, 'epoch': 1.29} + 13%|█▎ | 1124/8720 [3:04:16<14:46:44, 7.00s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:19:43,066] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.27 | bwd_microstep: 270.70 | bwd_inner_microstep: 270.38 | bwd_allreduce_microstep: 0.16 | step_microstep: 0.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1959 +[2025-05-02 01:19:43,576] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 199.34 | bwd_microstep: 290.26 | bwd_inner_microstep: 290.24 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1917 +[2025-05-02 01:19:44,060] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.28 | bwd_microstep: 276.56 | bwd_inner_microstep: 276.54 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1910 +[2025-05-02 01:19:44,551] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.91 | bwd_microstep: 276.57 | bwd_inner_microstep: 276.56 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1895 +[2025-05-02 01:19:45,034] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.07 | bwd_microstep: 275.07 | bwd_inner_microstep: 275.05 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1888 +[2025-05-02 01:19:45,517] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.29 | bwd_microstep: 274.56 | bwd_inner_microstep: 274.54 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 852 +[2025-05-02 01:19:45,779] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 110.88 | bwd_microstep: 132.04 | bwd_inner_microstep: 131.95 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 01:19:46,258] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.81 | bwd_microstep: 272.72 | bwd_inner_microstep: 272.70 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 01:19:46,741] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.35 | bwd_microstep: 272.98 | bwd_inner_microstep: 272.97 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 01:19:47,223] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.11 | bwd_microstep: 273.61 | bwd_inner_microstep: 273.60 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 841 +[2025-05-02 01:19:47,486] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 114.32 | bwd_microstep: 131.01 | bwd_inner_microstep: 130.84 | bwd_allreduce_microstep: 0.08 | step_microstep: 0.14 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 01:19:47,966] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.50 | bwd_microstep: 272.76 | bwd_inner_microstep: 272.74 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 321 +[2025-05-02 01:19:48,211] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 110.88 | bwd_microstep: 116.03 | bwd_inner_microstep: 115.69 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:19:48,691] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.94 | bwd_microstep: 272.27 | bwd_inner_microstep: 272.25 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:19:49,172] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.48 | bwd_microstep: 272.36 | bwd_inner_microstep: 272.34 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 01:19:49,785] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.07 | optimizer_gradients: 2.16 | optimizer_step: 29.05 +[2025-05-02 01:19:49,785] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.24 | bwd_microstep: 369.70 | bwd_inner_microstep: 272.69 | bwd_allreduce_microstep: 96.92 | step_microstep: 38.15 +[2025-05-02 01:19:49,787] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2807.22 | bwd: 4049.34 | bwd_inner: 3951.16 | bwd_allreduce: 97.47 | step: 39.73 + 13%|█▎ | 1125/8720 [3:04:23<14:54:13, 7.06s/it] {'loss': 1.0571, 'grad_norm': 7.180612087249756, 'learning_rate': 9.745314563025458e-06, 'epoch': 1.29} + 13%|█▎ | 1125/8720 [3:04:23<14:54:13, 7.06s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1904 +[2025-05-02 01:19:50,273] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.76 | bwd_microstep: 275.34 | bwd_inner_microstep: 275.32 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1403 +[2025-05-02 01:19:50,643] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 145.32 | bwd_microstep: 210.41 | bwd_inner_microstep: 210.40 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1896 +[2025-05-02 01:19:51,124] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.54 | bwd_microstep: 275.61 | bwd_inner_microstep: 275.59 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1894 +[2025-05-02 01:19:51,607] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 191.37 | bwd_microstep: 276.16 | bwd_inner_microstep: 276.15 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-02 01:19:52,087] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.73 | bwd_microstep: 274.84 | bwd_inner_microstep: 274.82 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-02 01:19:52,568] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.38 | bwd_microstep: 274.52 | bwd_inner_microstep: 274.51 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 01:19:53,047] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.77 | bwd_microstep: 273.78 | bwd_inner_microstep: 273.76 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 01:19:53,526] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.80 | bwd_microstep: 273.54 | bwd_inner_microstep: 273.52 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1116 +[2025-05-02 01:19:53,823] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 117.96 | bwd_microstep: 162.62 | bwd_inner_microstep: 162.33 | bwd_allreduce_microstep: 0.14 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 01:19:54,306] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.00 | bwd_microstep: 273.37 | bwd_inner_microstep: 273.35 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 836 +[2025-05-02 01:19:54,554] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 106.38 | bwd_microstep: 125.34 | bwd_inner_microstep: 125.25 | bwd_allreduce_microstep: 0.04 | step_microstep: 0.11 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1101 +[2025-05-02 01:19:54,850] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 117.91 | bwd_microstep: 161.46 | bwd_inner_microstep: 161.22 | bwd_allreduce_microstep: 0.14 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 01:19:55,328] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.08 | bwd_microstep: 272.44 | bwd_inner_microstep: 272.42 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 01:19:55,808] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.57 | bwd_microstep: 272.49 | bwd_inner_microstep: 272.47 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:19:56,288] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.50 | bwd_microstep: 271.99 | bwd_inner_microstep: 271.97 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:19:56,874] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.08 | optimizer_gradients: 2.11 | optimizer_step: 16.54 +[2025-05-02 01:19:56,874] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.15 | bwd_microstep: 353.16 | bwd_inner_microstep: 272.57 | bwd_allreduce_microstep: 80.54 | step_microstep: 24.87 +[2025-05-02 01:19:56,876] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2761.85 | bwd: 4027.17 | bwd_inner: 3945.64 | bwd_allreduce: 80.96 | step: 25.97 + 13%|█▎ | 1126/8720 [3:04:30<14:55:06, 7.07s/it] {'loss': 0.7657, 'grad_norm': 7.217925548553467, 'learning_rate': 9.744729065528682e-06, 'epoch': 1.29} + 13%|█▎ | 1126/8720 [3:04:30<14:55:06, 7.07s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:19:57,358] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.61 | bwd_microstep: 270.61 | bwd_inner_microstep: 270.60 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1963 +[2025-05-02 01:19:57,864] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 196.87 | bwd_microstep: 290.07 | bwd_inner_microstep: 290.05 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1436 +[2025-05-02 01:19:58,242] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 146.81 | bwd_microstep: 214.74 | bwd_inner_microstep: 214.65 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1892 +[2025-05-02 01:19:58,725] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.36 | bwd_microstep: 274.86 | bwd_inner_microstep: 274.84 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 342 +[2025-05-02 01:19:58,959] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 102.37 | bwd_microstep: 116.56 | bwd_inner_microstep: 116.39 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-02 01:19:59,439] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.05 | bwd_microstep: 273.25 | bwd_inner_microstep: 273.23 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 01:19:59,921] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.07 | bwd_microstep: 273.13 | bwd_inner_microstep: 273.11 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 01:20:00,401] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.71 | bwd_microstep: 273.36 | bwd_inner_microstep: 273.34 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 01:20:00,882] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.09 | bwd_microstep: 272.58 | bwd_inner_microstep: 272.56 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 01:20:01,365] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.20 | bwd_microstep: 272.75 | bwd_inner_microstep: 272.74 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 327 +[2025-05-02 01:20:01,617] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 108.95 | bwd_microstep: 125.28 | bwd_inner_microstep: 124.92 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.43 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:20:02,101] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.84 | bwd_microstep: 272.78 | bwd_inner_microstep: 272.76 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.12 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 836 +[2025-05-02 01:20:02,366] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 117.86 | bwd_microstep: 125.21 | bwd_inner_microstep: 125.09 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.13 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 318 +[2025-05-02 01:20:02,623] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 102.95 | bwd_microstep: 134.37 | bwd_inner_microstep: 134.02 | bwd_allreduce_microstep: 0.14 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:20:03,101] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.49 | bwd_microstep: 272.35 | bwd_inner_microstep: 272.34 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:20:03,707] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.15 | optimizer_step: 20.08 +[2025-05-02 01:20:03,708] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.64 | bwd_microstep: 369.80 | bwd_inner_microstep: 271.72 | bwd_allreduce_microstep: 98.03 | step_microstep: 29.65 +[2025-05-02 01:20:03,709] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2666.43 | bwd: 3831.85 | bwd_inner: 3732.54 | bwd_allreduce: 98.58 | step: 31.14 + 13%|█▎ | 1127/8720 [3:04:37<14:45:54, 7.00s/it] {'loss': 0.8409, 'grad_norm': 9.203863143920898, 'learning_rate': 9.744142913432214e-06, 'epoch': 1.29} + 13%|█▎ | 1127/8720 [3:04:37<14:45:54, 7.00s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 01:20:04,191] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.44 | bwd_microstep: 270.31 | bwd_inner_microstep: 270.29 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1909 +[2025-05-02 01:20:04,672] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.69 | bwd_microstep: 276.24 | bwd_inner_microstep: 276.22 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1893 +[2025-05-02 01:20:05,151] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.21 | bwd_microstep: 274.83 | bwd_inner_microstep: 274.81 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-02 01:20:05,629] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.26 | bwd_microstep: 273.64 | bwd_inner_microstep: 273.62 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-02 01:20:06,105] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.06 | bwd_microstep: 273.59 | bwd_inner_microstep: 273.57 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.17 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 01:20:06,582] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.74 | bwd_microstep: 272.59 | bwd_inner_microstep: 272.57 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 01:20:07,059] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.02 | bwd_microstep: 272.89 | bwd_inner_microstep: 272.87 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:20:07,536] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.46 | bwd_microstep: 272.49 | bwd_inner_microstep: 272.47 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 331 +[2025-05-02 01:20:07,757] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 84.00 | bwd_microstep: 123.91 | bwd_inner_microstep: 123.77 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 01:20:08,234] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.85 | bwd_microstep: 272.78 | bwd_inner_microstep: 272.76 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:20:08,710] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.57 | bwd_microstep: 272.56 | bwd_inner_microstep: 272.54 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 01:20:09,185] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.15 | bwd_microstep: 271.97 | bwd_inner_microstep: 271.95 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 01:20:09,659] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.31 | bwd_microstep: 271.20 | bwd_inner_microstep: 271.18 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:20:10,134] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.48 | bwd_microstep: 271.24 | bwd_inner_microstep: 271.22 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:20:10,608] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.33 | bwd_microstep: 271.18 | bwd_inner_microstep: 271.16 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 01:20:11,191] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.13 | optimizer_step: 16.53 +[2025-05-02 01:20:11,192] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.30 | bwd_microstep: 356.08 | bwd_inner_microstep: 271.36 | bwd_allreduce_microstep: 84.66 | step_microstep: 25.10 +[2025-05-02 01:20:11,193] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2913.60 | bwd: 4297.51 | bwd_inner: 4212.41 | bwd_allreduce: 84.80 | step: 26.03 + 13%|█▎ | 1128/8720 [3:04:44<15:04:05, 7.15s/it] {'loss': 0.8409, 'grad_norm': 12.35628604888916, 'learning_rate': 9.743556106816922e-06, 'epoch': 1.29} + 13%|█▎ | 1128/8720 [3:04:44<15:04:05, 7.15s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 01:20:11,673] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.12 | bwd_microstep: 270.85 | bwd_inner_microstep: 270.83 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1988 +[2025-05-02 01:20:12,181] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 198.36 | bwd_microstep: 293.42 | bwd_inner_microstep: 293.41 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1954 +[2025-05-02 01:20:12,683] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 196.64 | bwd_microstep: 289.76 | bwd_inner_microstep: 289.75 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1893 +[2025-05-02 01:20:13,163] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.23 | bwd_microstep: 275.19 | bwd_inner_microstep: 275.18 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1891 +[2025-05-02 01:20:13,643] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.65 | bwd_microstep: 274.85 | bwd_inner_microstep: 274.83 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-02 01:20:14,122] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.85 | bwd_microstep: 274.02 | bwd_inner_microstep: 274.00 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 01:20:14,599] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.05 | bwd_microstep: 273.07 | bwd_inner_microstep: 273.05 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 01:20:15,080] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.08 | bwd_microstep: 272.70 | bwd_inner_microstep: 272.68 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.16 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 01:20:15,561] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.03 | bwd_microstep: 272.70 | bwd_inner_microstep: 272.68 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:20:16,038] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.89 | bwd_microstep: 272.01 | bwd_inner_microstep: 272.00 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 01:20:16,516] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.58 | bwd_microstep: 272.18 | bwd_inner_microstep: 272.16 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:20:16,996] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.43 | bwd_microstep: 272.69 | bwd_inner_microstep: 272.67 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:20:17,475] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.29 | bwd_microstep: 272.26 | bwd_inner_microstep: 272.24 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:20:17,956] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.28 | bwd_microstep: 272.21 | bwd_inner_microstep: 272.20 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 321 +[2025-05-02 01:20:18,186] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.01 | bwd_microstep: 119.70 | bwd_inner_microstep: 119.48 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 01:20:18,776] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.14 | optimizer_step: 20.10 +[2025-05-02 01:20:18,777] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.27 | bwd_microstep: 357.45 | bwd_inner_microstep: 272.46 | bwd_allreduce_microstep: 84.94 | step_microstep: 28.59 +[2025-05-02 01:20:18,778] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2946.42 | bwd: 4335.10 | bwd_inner: 4249.70 | bwd_allreduce: 85.09 | step: 29.78 + 13%|█▎ | 1129/8720 [3:04:52<15:20:38, 7.28s/it] {'loss': 0.925, 'grad_norm': 10.43679141998291, 'learning_rate': 9.742968645763762e-06, 'epoch': 1.29} + 13%|█▎ | 1129/8720 [3:04:52<15:20:38, 7.28s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:20:19,256] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.48 | bwd_microstep: 270.41 | bwd_inner_microstep: 270.39 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1896 +[2025-05-02 01:20:19,736] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.02 | bwd_microstep: 275.03 | bwd_inner_microstep: 275.01 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 362 +[2025-05-02 01:20:19,947] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 83.21 | bwd_microstep: 114.78 | bwd_inner_microstep: 114.64 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 334 +[2025-05-02 01:20:20,160] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 81.30 | bwd_microstep: 119.17 | bwd_inner_microstep: 118.83 | bwd_allreduce_microstep: 0.14 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 01:20:20,637] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.08 | bwd_microstep: 272.66 | bwd_inner_microstep: 272.64 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:20:21,114] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.67 | bwd_microstep: 272.57 | bwd_inner_microstep: 272.55 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:20:21,592] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.39 | bwd_microstep: 272.61 | bwd_inner_microstep: 272.59 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:20:22,068] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.76 | bwd_microstep: 272.41 | bwd_inner_microstep: 272.39 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1346 +[2025-05-02 01:20:22,429] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.86 | bwd_microstep: 205.15 | bwd_inner_microstep: 205.13 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 01:20:22,905] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.08 | bwd_microstep: 272.18 | bwd_inner_microstep: 272.16 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:20:23,381] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.10 | bwd_microstep: 271.05 | bwd_inner_microstep: 271.03 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 318 +[2025-05-02 01:20:23,594] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 81.62 | bwd_microstep: 118.17 | bwd_inner_microstep: 117.92 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:20:24,068] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.93 | bwd_microstep: 271.16 | bwd_inner_microstep: 271.14 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 01:20:24,542] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.85 | bwd_microstep: 270.87 | bwd_inner_microstep: 270.86 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.21 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:20:25,017] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.55 | bwd_microstep: 270.89 | bwd_inner_microstep: 270.87 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 01:20:25,601] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.14 | optimizer_step: 16.55 +[2025-05-02 01:20:25,601] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.28 | bwd_microstep: 356.42 | bwd_inner_microstep: 271.52 | bwd_allreduce_microstep: 84.85 | step_microstep: 25.05 +[2025-05-02 01:20:25,603] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2647.88 | bwd: 3905.58 | bwd_inner: 3819.84 | bwd_allreduce: 85.17 | step: 26.21 + 13%|█▎ | 1130/8720 [3:04:59<15:03:22, 7.14s/it] {'loss': 0.6773, 'grad_norm': 9.756842613220215, 'learning_rate': 9.742380530353782e-06, 'epoch': 1.3} + 13%|█▎ | 1130/8720 [3:04:59<15:03:22, 7.14s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1923 +[2025-05-02 01:20:26,104] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 194.84 | bwd_microstep: 286.15 | bwd_inner_microstep: 286.13 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1893 +[2025-05-02 01:20:26,582] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.49 | bwd_microstep: 274.65 | bwd_inner_microstep: 274.63 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-02 01:20:27,060] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.39 | bwd_microstep: 273.43 | bwd_inner_microstep: 273.41 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-02 01:20:27,538] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.50 | bwd_microstep: 274.04 | bwd_inner_microstep: 274.02 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 01:20:28,015] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.60 | bwd_microstep: 272.81 | bwd_inner_microstep: 272.79 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-02 01:20:28,493] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.23 | bwd_microstep: 273.69 | bwd_inner_microstep: 273.67 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.23 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 01:20:28,972] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.03 | bwd_microstep: 273.22 | bwd_inner_microstep: 273.20 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-02 01:20:29,450] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.96 | bwd_microstep: 273.32 | bwd_inner_microstep: 273.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 01:20:29,927] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.97 | bwd_microstep: 272.74 | bwd_inner_microstep: 272.73 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 01:20:30,403] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.16 | bwd_microstep: 272.17 | bwd_inner_microstep: 272.15 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:20:30,879] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.07 | bwd_microstep: 272.02 | bwd_inner_microstep: 272.01 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:20:31,353] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.16 | bwd_microstep: 271.17 | bwd_inner_microstep: 271.15 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 01:20:31,829] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.40 | bwd_microstep: 271.36 | bwd_inner_microstep: 271.34 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:20:32,304] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.18 | bwd_microstep: 270.98 | bwd_inner_microstep: 270.96 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 01:20:32,778] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.60 | bwd_microstep: 270.93 | bwd_inner_microstep: 270.91 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 396 +[2025-05-02 01:20:33,130] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.22 | optimizer_step: 16.62 +[2025-05-02 01:20:33,131] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 85.68 | bwd_microstep: 227.79 | bwd_inner_microstep: 142.13 | bwd_allreduce_microstep: 85.54 | step_microstep: 25.33 +[2025-05-02 01:20:33,132] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2918.97 | bwd: 4330.48 | bwd_inner: 4244.60 | bwd_allreduce: 85.61 | step: 26.32 + 13%|█▎ | 1131/8720 [3:05:06<15:17:59, 7.26s/it] {'loss': 0.8048, 'grad_norm': 8.480745315551758, 'learning_rate': 9.741791760668122e-06, 'epoch': 1.3} + 13%|█▎ | 1131/8720 [3:05:06<15:17:59, 7.26s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 377 +[2025-05-02 01:20:33,376] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 87.51 | bwd_microstep: 137.79 | bwd_inner_microstep: 137.59 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2134 +[2025-05-02 01:20:33,910] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 203.56 | bwd_microstep: 313.84 | bwd_inner_microstep: 313.82 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 353 +[2025-05-02 01:20:34,137] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 87.94 | bwd_microstep: 125.30 | bwd_inner_microstep: 125.02 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 847 +[2025-05-02 01:20:34,381] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 98.06 | bwd_microstep: 132.24 | bwd_inner_microstep: 132.08 | bwd_allreduce_microstep: 0.08 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 01:20:34,859] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.97 | bwd_microstep: 273.06 | bwd_inner_microstep: 273.05 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 01:20:35,334] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.38 | bwd_microstep: 272.44 | bwd_inner_microstep: 272.42 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 01:20:35,811] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.61 | bwd_microstep: 272.45 | bwd_inner_microstep: 272.43 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 01:20:36,288] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.71 | bwd_microstep: 272.66 | bwd_inner_microstep: 272.64 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:20:36,764] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.61 | bwd_microstep: 272.32 | bwd_inner_microstep: 272.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:20:37,243] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.44 | bwd_microstep: 272.27 | bwd_inner_microstep: 272.25 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:20:37,721] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.20 | bwd_microstep: 272.16 | bwd_inner_microstep: 272.14 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:20:38,196] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.52 | bwd_microstep: 271.08 | bwd_inner_microstep: 271.06 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 829 +[2025-05-02 01:20:38,432] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 91.81 | bwd_microstep: 129.80 | bwd_inner_microstep: 129.76 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:20:38,907] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.60 | bwd_microstep: 271.25 | bwd_inner_microstep: 271.24 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 827 +[2025-05-02 01:20:39,147] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.99 | bwd_microstep: 129.76 | bwd_inner_microstep: 129.71 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 01:20:39,728] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.18 | optimizer_step: 16.60 +[2025-05-02 01:20:39,728] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.09 | bwd_microstep: 352.12 | bwd_inner_microstep: 271.59 | bwd_allreduce_microstep: 80.48 | step_microstep: 24.59 +[2025-05-02 01:20:39,730] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2544.71 | bwd: 3770.64 | bwd_inner: 3689.25 | bwd_allreduce: 80.80 | step: 25.58 + 13%|█▎ | 1132/8720 [3:05:13<14:52:53, 7.06s/it] {'loss': 0.5171, 'grad_norm': 12.101226806640625, 'learning_rate': 9.741202336788011e-06, 'epoch': 1.3} + 13%|█▎ | 1132/8720 [3:05:13<14:52:53, 7.06s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 467 +[2025-05-02 01:20:39,961] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 84.93 | bwd_microstep: 124.42 | bwd_inner_microstep: 124.18 | bwd_allreduce_microstep: 0.08 | step_microstep: 0.10 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 398 +[2025-05-02 01:20:40,187] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 85.85 | bwd_microstep: 124.37 | bwd_inner_microstep: 124.17 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-02 01:20:40,668] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.16 | bwd_microstep: 274.26 | bwd_inner_microstep: 274.24 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-02 01:20:41,149] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.81 | bwd_microstep: 272.94 | bwd_inner_microstep: 272.92 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:20:41,627] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.81 | bwd_microstep: 272.51 | bwd_inner_microstep: 272.49 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1347 +[2025-05-02 01:20:41,992] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.44 | bwd_microstep: 205.38 | bwd_inner_microstep: 205.37 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 01:20:42,471] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.45 | bwd_microstep: 273.06 | bwd_inner_microstep: 273.04 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 01:20:42,950] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.97 | bwd_microstep: 273.10 | bwd_inner_microstep: 273.08 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:20:43,429] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.97 | bwd_microstep: 273.18 | bwd_inner_microstep: 273.16 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 01:20:43,906] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.12 | bwd_microstep: 273.35 | bwd_inner_microstep: 273.33 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:20:44,384] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.50 | bwd_microstep: 273.20 | bwd_inner_microstep: 273.18 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:20:44,864] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.42 | bwd_microstep: 272.73 | bwd_inner_microstep: 272.71 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:20:45,342] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.81 | bwd_microstep: 272.94 | bwd_inner_microstep: 272.92 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1344 +[2025-05-02 01:20:45,703] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.46 | bwd_microstep: 204.81 | bwd_inner_microstep: 204.76 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:20:46,181] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.22 | bwd_microstep: 272.69 | bwd_inner_microstep: 272.67 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:20:46,747] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.07 | optimizer_step: 16.49 +[2025-05-02 01:20:46,747] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.45 | bwd_microstep: 339.87 | bwd_inner_microstep: 272.10 | bwd_allreduce_microstep: 67.72 | step_microstep: 23.62 +[2025-05-02 01:20:46,748] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2718.06 | bwd: 4002.85 | bwd_inner: 3934.45 | bwd_allreduce: 67.93 | step: 24.61 + 13%|█▎ | 1133/8720 [3:05:20<14:51:08, 7.05s/it] {'loss': 0.5736, 'grad_norm': 9.405835151672363, 'learning_rate': 9.740612258794768e-06, 'epoch': 1.3} + 13%|█▎ | 1133/8720 [3:05:20<14:51:08, 7.05s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:20:47,227] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.78 | bwd_microstep: 270.82 | bwd_inner_microstep: 270.80 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1912 +[2025-05-02 01:20:47,712] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 191.06 | bwd_microstep: 277.18 | bwd_inner_microstep: 277.17 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-02 01:20:48,191] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.32 | bwd_microstep: 274.23 | bwd_inner_microstep: 274.21 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1883 +[2025-05-02 01:20:48,670] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.32 | bwd_microstep: 274.76 | bwd_inner_microstep: 274.74 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-02 01:20:49,149] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.51 | bwd_microstep: 274.34 | bwd_inner_microstep: 274.32 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:20:49,626] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.92 | bwd_microstep: 272.87 | bwd_inner_microstep: 272.85 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1099 +[2025-05-02 01:20:49,922] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 118.81 | bwd_microstep: 160.92 | bwd_inner_microstep: 160.77 | bwd_allreduce_microstep: 0.10 | step_microstep: 0.09 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 327 +[2025-05-02 01:20:50,130] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 71.85 | bwd_microstep: 121.98 | bwd_inner_microstep: 121.81 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.10 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 329 +[2025-05-02 01:20:50,333] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 68.49 | bwd_microstep: 120.47 | bwd_inner_microstep: 120.10 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 01:20:50,811] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.46 | bwd_microstep: 272.43 | bwd_inner_microstep: 272.41 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:20:51,290] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.81 | bwd_microstep: 272.12 | bwd_inner_microstep: 272.10 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:20:51,769] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.70 | bwd_microstep: 272.32 | bwd_inner_microstep: 272.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 322 +[2025-05-02 01:20:52,013] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 91.99 | bwd_microstep: 133.43 | bwd_inner_microstep: 133.28 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1346 +[2025-05-02 01:20:52,375] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 139.86 | bwd_microstep: 205.28 | bwd_inner_microstep: 205.19 | bwd_allreduce_microstep: 0.04 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:20:52,853] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.16 | bwd_microstep: 271.71 | bwd_inner_microstep: 271.70 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.13 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:20:53,430] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.21 | optimizer_step: 16.92 +[2025-05-02 01:20:53,430] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.82 | bwd_microstep: 348.49 | bwd_inner_microstep: 271.15 | bwd_allreduce_microstep: 77.28 | step_microstep: 24.92 +[2025-05-02 01:20:53,432] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2563.52 | bwd: 3823.43 | bwd_inner: 3745.10 | bwd_allreduce: 77.67 | step: 25.98 + 13%|█▎ | 1134/8720 [3:05:27<14:37:15, 6.94s/it] {'loss': 1.0706, 'grad_norm': 20.814756393432617, 'learning_rate': 9.7400215267698e-06, 'epoch': 1.3} + 13%|█▎ | 1134/8720 [3:05:27<14:37:15, 6.94s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:20:53,913] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.56 | bwd_microstep: 270.39 | bwd_inner_microstep: 270.37 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1366 +[2025-05-02 01:20:54,276] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.65 | bwd_microstep: 207.12 | bwd_inner_microstep: 206.99 | bwd_allreduce_microstep: 0.08 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-02 01:20:54,754] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.01 | bwd_microstep: 273.60 | bwd_inner_microstep: 273.58 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-02 01:20:55,231] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.26 | bwd_microstep: 272.95 | bwd_inner_microstep: 272.94 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-02 01:20:55,708] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.36 | bwd_microstep: 273.10 | bwd_inner_microstep: 273.08 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 01:20:56,186] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.41 | bwd_microstep: 273.59 | bwd_inner_microstep: 273.57 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 01:20:56,664] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.66 | bwd_microstep: 273.22 | bwd_inner_microstep: 273.21 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 01:20:57,143] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.16 | bwd_microstep: 272.93 | bwd_inner_microstep: 272.92 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 835 +[2025-05-02 01:20:57,382] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.92 | bwd_microstep: 125.91 | bwd_inner_microstep: 125.71 | bwd_allreduce_microstep: 0.10 | step_microstep: 0.11 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1351 +[2025-05-02 01:20:57,747] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.16 | bwd_microstep: 206.00 | bwd_inner_microstep: 205.90 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:20:58,223] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.40 | bwd_microstep: 271.27 | bwd_inner_microstep: 271.25 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:20:58,702] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.86 | bwd_microstep: 272.72 | bwd_inner_microstep: 272.70 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:20:59,182] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.33 | bwd_microstep: 272.56 | bwd_inner_microstep: 272.54 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 01:20:59,658] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.47 | bwd_microstep: 271.48 | bwd_inner_microstep: 271.46 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 316 +[2025-05-02 01:20:59,864] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 73.55 | bwd_microstep: 118.97 | bwd_inner_microstep: 118.77 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1967 +[2025-05-02 01:21:00,456] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.09 | optimizer_step: 16.48 +[2025-05-02 01:21:00,456] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 196.41 | bwd_microstep: 356.91 | bwd_inner_microstep: 291.11 | bwd_allreduce_microstep: 65.75 | step_microstep: 23.49 +[2025-05-02 01:21:00,457] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2719.88 | bwd: 4012.79 | bwd_inner: 3946.19 | bwd_allreduce: 66.12 | step: 24.40 + 13%|█▎ | 1135/8720 [3:05:34<14:40:22, 6.96s/it] {'loss': 0.6393, 'grad_norm': 7.840903282165527, 'learning_rate': 9.73943014079461e-06, 'epoch': 1.3} + 13%|█▎ | 1135/8720 [3:05:34<14:40:22, 6.96s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1915 +[2025-05-02 01:21:00,943] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.32 | bwd_microstep: 275.73 | bwd_inner_microstep: 275.71 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1938 +[2025-05-02 01:21:01,443] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 196.55 | bwd_microstep: 288.17 | bwd_inner_microstep: 288.15 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 396 +[2025-05-02 01:21:01,646] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 76.92 | bwd_microstep: 113.64 | bwd_inner_microstep: 113.41 | bwd_allreduce_microstep: 0.08 | step_microstep: 0.08 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1128 +[2025-05-02 01:21:01,939] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 115.48 | bwd_microstep: 163.72 | bwd_inner_microstep: 163.57 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1891 +[2025-05-02 01:21:02,418] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.16 | bwd_microstep: 274.89 | bwd_inner_microstep: 274.88 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-02 01:21:02,900] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.72 | bwd_microstep: 273.87 | bwd_inner_microstep: 273.86 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-02 01:21:03,384] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.48 | bwd_microstep: 273.39 | bwd_inner_microstep: 273.37 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.16 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 01:21:03,866] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.91 | bwd_microstep: 272.96 | bwd_inner_microstep: 272.94 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 01:21:04,346] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.14 | bwd_microstep: 272.52 | bwd_inner_microstep: 272.50 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 01:21:04,827] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.43 | bwd_microstep: 272.42 | bwd_inner_microstep: 272.40 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 01:21:05,309] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.07 | bwd_microstep: 272.59 | bwd_inner_microstep: 272.57 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 328 +[2025-05-02 01:21:05,546] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 102.15 | bwd_microstep: 115.65 | bwd_inner_microstep: 115.50 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:21:06,024] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.13 | bwd_microstep: 272.54 | bwd_inner_microstep: 272.52 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 01:21:06,503] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.47 | bwd_microstep: 271.99 | bwd_inner_microstep: 271.98 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:21:06,982] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.08 | bwd_microstep: 271.05 | bwd_inner_microstep: 271.03 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:21:07,561] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.14 | optimizer_step: 16.39 +[2025-05-02 01:21:07,562] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.00 | bwd_microstep: 348.32 | bwd_inner_microstep: 271.76 | bwd_allreduce_microstep: 76.50 | step_microstep: 24.05 +[2025-05-02 01:21:07,563] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2755.65 | bwd: 4033.51 | bwd_inner: 3956.24 | bwd_allreduce: 76.78 | step: 25.07 + 13%|█▎ | 1136/8720 [3:05:41<14:45:42, 7.01s/it] {'loss': 0.92, 'grad_norm': 8.91197395324707, 'learning_rate': 9.738838100950786e-06, 'epoch': 1.3} + 13%|█▎ | 1136/8720 [3:05:41<14:45:42, 7.01s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 01:21:08,045] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.89 | bwd_microstep: 270.68 | bwd_inner_microstep: 270.66 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1894 +[2025-05-02 01:21:08,527] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.72 | bwd_microstep: 275.39 | bwd_inner_microstep: 275.38 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 01:21:09,006] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.75 | bwd_microstep: 273.82 | bwd_inner_microstep: 273.80 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 01:21:09,483] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.96 | bwd_microstep: 273.02 | bwd_inner_microstep: 273.00 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 333 +[2025-05-02 01:21:09,688] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 68.56 | bwd_microstep: 123.56 | bwd_inner_microstep: 123.38 | bwd_allreduce_microstep: 0.08 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 01:21:10,164] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.13 | bwd_microstep: 273.32 | bwd_inner_microstep: 273.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 01:21:10,643] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.18 | bwd_microstep: 273.80 | bwd_inner_microstep: 273.78 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:21:11,121] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.16 | bwd_microstep: 273.22 | bwd_inner_microstep: 273.20 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:21:11,599] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.50 | bwd_microstep: 272.97 | bwd_inner_microstep: 272.95 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:21:12,076] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.72 | bwd_microstep: 273.15 | bwd_inner_microstep: 273.14 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1093 +[2025-05-02 01:21:12,370] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 116.34 | bwd_microstep: 161.10 | bwd_inner_microstep: 161.06 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 01:21:12,849] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.44 | bwd_microstep: 272.75 | bwd_inner_microstep: 272.74 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:21:13,329] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.74 | bwd_microstep: 271.67 | bwd_inner_microstep: 271.65 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:21:13,808] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.31 | bwd_microstep: 272.58 | bwd_inner_microstep: 272.56 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:21:14,287] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.46 | bwd_microstep: 271.82 | bwd_inner_microstep: 271.80 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:21:14,867] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.12 | optimizer_step: 16.43 +[2025-05-02 01:21:14,867] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.92 | bwd_microstep: 348.79 | bwd_inner_microstep: 272.07 | bwd_allreduce_microstep: 76.66 | step_microstep: 24.13 +[2025-05-02 01:21:14,869] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2827.43 | bwd: 4181.68 | bwd_inner: 4104.51 | bwd_allreduce: 76.83 | step: 24.94 + 13%|█▎ | 1137/8720 [3:05:48<14:56:55, 7.10s/it] {'loss': 0.6554, 'grad_norm': 9.04140567779541, 'learning_rate': 9.738245407320007e-06, 'epoch': 1.3} + 13%|█▎ | 1137/8720 [3:05:48<14:56:55, 7.10s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 451 +[2025-05-02 01:21:15,101] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 85.69 | bwd_microstep: 124.60 | bwd_inner_microstep: 124.43 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1914 +[2025-05-02 01:21:15,585] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.87 | bwd_microstep: 276.18 | bwd_inner_microstep: 276.17 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1896 +[2025-05-02 01:21:16,068] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.12 | bwd_microstep: 274.96 | bwd_inner_microstep: 274.94 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:21:16,553] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.02 | bwd_microstep: 272.65 | bwd_inner_microstep: 272.63 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:21:17,038] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.94 | bwd_microstep: 272.56 | bwd_inner_microstep: 272.55 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 01:21:17,521] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.57 | bwd_microstep: 272.21 | bwd_inner_microstep: 272.19 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:21:18,000] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.98 | bwd_microstep: 272.44 | bwd_inner_microstep: 272.42 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 01:21:18,480] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.87 | bwd_microstep: 272.47 | bwd_inner_microstep: 272.45 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 328 +[2025-05-02 01:21:18,714] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 100.14 | bwd_microstep: 115.30 | bwd_inner_microstep: 115.06 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:21:19,190] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.89 | bwd_microstep: 271.31 | bwd_inner_microstep: 271.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 01:21:19,668] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.31 | bwd_microstep: 272.31 | bwd_inner_microstep: 272.29 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 01:21:20,146] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.03 | bwd_microstep: 271.38 | bwd_inner_microstep: 271.36 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.13 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:21:20,626] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.16 | bwd_microstep: 272.19 | bwd_inner_microstep: 272.17 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:21:21,106] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.88 | bwd_microstep: 271.21 | bwd_inner_microstep: 271.19 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1085 +[2025-05-02 01:21:21,401] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 115.14 | bwd_microstep: 159.68 | bwd_inner_microstep: 159.64 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:21:21,983] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.13 | optimizer_step: 16.46 +[2025-05-02 01:21:21,984] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.39 | bwd_microstep: 348.03 | bwd_inner_microstep: 271.40 | bwd_allreduce_microstep: 76.58 | step_microstep: 24.11 +[2025-05-02 01:21:21,985] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2751.58 | bwd: 4019.55 | bwd_inner: 3942.31 | bwd_allreduce: 76.78 | step: 25.22 + 13%|█▎ | 1138/8720 [3:05:55<14:57:30, 7.10s/it] {'loss': 0.6367, 'grad_norm': 7.840020179748535, 'learning_rate': 9.737652059984041e-06, 'epoch': 1.3} + 13%|█▎ | 1138/8720 [3:05:55<14:57:30, 7.10s/it]dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1708 +[2025-05-02 01:21:22,424] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 161.32 | bwd_microstep: 255.50 | bwd_inner_microstep: 255.48 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 527 +[2025-05-02 01:21:22,652] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 85.48 | bwd_microstep: 127.02 | bwd_inner_microstep: 126.83 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1955 +[2025-05-02 01:21:23,155] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 197.40 | bwd_microstep: 289.79 | bwd_inner_microstep: 289.78 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1904 +[2025-05-02 01:21:23,638] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.69 | bwd_microstep: 275.76 | bwd_inner_microstep: 275.74 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-02 01:21:24,117] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.46 | bwd_microstep: 274.55 | bwd_inner_microstep: 274.53 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1894 +[2025-05-02 01:21:24,597] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.00 | bwd_microstep: 275.00 | bwd_inner_microstep: 274.98 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1360 +[2025-05-02 01:21:24,959] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.50 | bwd_microstep: 206.64 | bwd_inner_microstep: 206.62 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 01:21:25,435] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.15 | bwd_microstep: 272.93 | bwd_inner_microstep: 272.91 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1348 +[2025-05-02 01:21:25,800] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 143.64 | bwd_microstep: 205.79 | bwd_inner_microstep: 205.75 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.09 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 326 +[2025-05-02 01:21:26,008] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 78.04 | bwd_microstep: 115.91 | bwd_inner_microstep: 115.76 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:21:26,483] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.44 | bwd_microstep: 272.50 | bwd_inner_microstep: 272.48 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:21:26,958] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.38 | bwd_microstep: 272.60 | bwd_inner_microstep: 272.58 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:21:27,434] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.60 | bwd_microstep: 272.49 | bwd_inner_microstep: 272.47 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:21:27,911] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.87 | bwd_microstep: 272.48 | bwd_inner_microstep: 272.46 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 320 +[2025-05-02 01:21:28,111] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 70.38 | bwd_microstep: 116.67 | bwd_inner_microstep: 116.50 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 01:21:28,675] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.04 | optimizer_gradients: 2.10 | optimizer_step: 16.38 +[2025-05-02 01:21:28,676] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.23 | bwd_microstep: 337.91 | bwd_inner_microstep: 271.70 | bwd_allreduce_microstep: 66.17 | step_microstep: 23.24 +[2025-05-02 01:21:28,677] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2575.33 | bwd: 3843.59 | bwd_inner: 3776.75 | bwd_allreduce: 66.41 | step: 24.26 + 13%|█▎ | 1139/8720 [3:06:02<14:41:45, 6.98s/it] {'loss': 1.1145, 'grad_norm': 10.57170581817627, 'learning_rate': 9.737058059024756e-06, 'epoch': 1.31} + 13%|█▎ | 1139/8720 [3:06:02<14:41:45, 6.98s/it]dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 828 +[2025-05-02 01:21:28,917] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 91.83 | bwd_microstep: 129.87 | bwd_inner_microstep: 129.58 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1234 +[2025-05-02 01:21:29,230] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 121.36 | bwd_microstep: 177.19 | bwd_inner_microstep: 177.17 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 912 +[2025-05-02 01:21:29,492] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 103.45 | bwd_microstep: 144.50 | bwd_inner_microstep: 144.45 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-02 01:21:29,968] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.53 | bwd_microstep: 273.61 | bwd_inner_microstep: 273.59 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 346 +[2025-05-02 01:21:30,184] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 81.74 | bwd_microstep: 118.82 | bwd_inner_microstep: 118.59 | bwd_allreduce_microstep: 0.08 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-02 01:21:30,660] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.66 | bwd_microstep: 273.29 | bwd_inner_microstep: 273.27 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 01:21:31,137] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.69 | bwd_microstep: 273.02 | bwd_inner_microstep: 273.01 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 01:21:31,614] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.99 | bwd_microstep: 273.53 | bwd_inner_microstep: 273.51 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 01:21:32,093] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.74 | bwd_microstep: 273.56 | bwd_inner_microstep: 273.54 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:21:32,570] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.09 | bwd_microstep: 272.68 | bwd_inner_microstep: 272.67 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1358 +[2025-05-02 01:21:32,932] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.11 | bwd_microstep: 206.32 | bwd_inner_microstep: 206.30 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:21:33,408] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.58 | bwd_microstep: 272.43 | bwd_inner_microstep: 272.41 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 01:21:33,884] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.18 | bwd_microstep: 272.53 | bwd_inner_microstep: 272.52 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:21:34,361] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.76 | bwd_microstep: 272.62 | bwd_inner_microstep: 272.60 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1094 +[2025-05-02 01:21:34,654] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 114.84 | bwd_microstep: 161.15 | bwd_inner_microstep: 161.08 | bwd_allreduce_microstep: 0.03 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:21:35,233] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.11 | optimizer_step: 16.43 +[2025-05-02 01:21:35,233] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.02 | bwd_microstep: 349.76 | bwd_inner_microstep: 271.84 | bwd_allreduce_microstep: 77.87 | step_microstep: 24.18 +[2025-05-02 01:21:35,235] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2538.30 | bwd: 3744.95 | bwd_inner: 3666.23 | bwd_allreduce: 78.17 | step: 25.10 + 13%|█▎ | 1140/8720 [3:06:08<14:25:46, 6.85s/it] {'loss': 0.7513, 'grad_norm': 6.7841010093688965, 'learning_rate': 9.736463404524095e-06, 'epoch': 1.31} + 13%|█▎ | 1140/8720 [3:06:08<14:25:46, 6.85s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 01:21:35,715] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.66 | bwd_microstep: 270.11 | bwd_inner_microstep: 270.10 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 864 +[2025-05-02 01:21:35,961] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 97.32 | bwd_microstep: 134.12 | bwd_inner_microstep: 133.93 | bwd_allreduce_microstep: 0.10 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-02 01:21:36,439] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.25 | bwd_microstep: 273.97 | bwd_inner_microstep: 273.95 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 01:21:36,916] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.95 | bwd_microstep: 273.40 | bwd_inner_microstep: 273.38 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 01:21:37,395] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.93 | bwd_microstep: 273.59 | bwd_inner_microstep: 273.57 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-02 01:21:37,876] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.02 | bwd_microstep: 272.97 | bwd_inner_microstep: 272.96 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:21:38,358] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.10 | bwd_microstep: 272.42 | bwd_inner_microstep: 272.41 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 01:21:38,837] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.30 | bwd_microstep: 272.50 | bwd_inner_microstep: 272.49 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 01:21:39,315] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.78 | bwd_microstep: 272.70 | bwd_inner_microstep: 272.69 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 01:21:39,796] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.42 | bwd_microstep: 272.75 | bwd_inner_microstep: 272.73 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 01:21:40,277] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.49 | bwd_microstep: 272.82 | bwd_inner_microstep: 272.80 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:21:40,760] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.24 | bwd_microstep: 272.50 | bwd_inner_microstep: 272.48 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 01:21:41,243] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.64 | bwd_microstep: 272.79 | bwd_inner_microstep: 272.77 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:21:41,721] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.20 | bwd_microstep: 272.50 | bwd_inner_microstep: 272.48 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 01:21:42,199] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.21 | bwd_microstep: 272.59 | bwd_inner_microstep: 272.57 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:21:42,774] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.11 | optimizer_step: 16.39 +[2025-05-02 01:21:42,775] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.46 | bwd_microstep: 348.19 | bwd_inner_microstep: 271.44 | bwd_allreduce_microstep: 76.70 | step_microstep: 23.94 +[2025-05-02 01:21:42,776] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2921.60 | bwd: 4299.96 | bwd_inner: 4222.77 | bwd_allreduce: 76.85 | step: 24.83 + 13%|█▎ | 1141/8720 [3:06:16<14:51:44, 7.06s/it] {'loss': 1.0028, 'grad_norm': 13.164379119873047, 'learning_rate': 9.7358680965641e-06, 'epoch': 1.31} + 13%|█▎ | 1141/8720 [3:06:16<14:51:44, 7.06s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1958 +[2025-05-02 01:21:43,284] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.88 | bwd_microstep: 289.29 | bwd_inner_microstep: 289.27 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2054 +[2025-05-02 01:21:43,803] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 202.18 | bwd_microstep: 301.58 | bwd_inner_microstep: 301.57 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1911 +[2025-05-02 01:21:44,285] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.54 | bwd_microstep: 276.59 | bwd_inner_microstep: 276.58 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1907 +[2025-05-02 01:21:44,765] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.73 | bwd_microstep: 276.24 | bwd_inner_microstep: 276.22 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1895 +[2025-05-02 01:21:45,245] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.50 | bwd_microstep: 275.22 | bwd_inner_microstep: 275.20 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1372 +[2025-05-02 01:21:45,609] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.61 | bwd_microstep: 207.64 | bwd_inner_microstep: 207.62 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 01:21:46,087] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.22 | bwd_microstep: 273.55 | bwd_inner_microstep: 273.53 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 01:21:46,565] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.54 | bwd_microstep: 272.99 | bwd_inner_microstep: 272.97 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 333 +[2025-05-02 01:21:46,765] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 67.77 | bwd_microstep: 119.27 | bwd_inner_microstep: 118.97 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:21:47,240] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.50 | bwd_microstep: 272.40 | bwd_inner_microstep: 272.38 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 322 +[2025-05-02 01:21:47,442] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 68.70 | bwd_microstep: 119.73 | bwd_inner_microstep: 119.61 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:21:47,916] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.09 | bwd_microstep: 272.05 | bwd_inner_microstep: 272.03 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:21:48,391] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.67 | bwd_microstep: 271.15 | bwd_inner_microstep: 271.13 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:21:48,866] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.16 | bwd_microstep: 271.30 | bwd_inner_microstep: 271.28 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 01:21:49,340] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.75 | bwd_microstep: 271.15 | bwd_inner_microstep: 271.13 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1978 +[2025-05-02 01:21:49,937] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.13 | optimizer_step: 16.58 +[2025-05-02 01:21:49,938] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 198.28 | bwd_microstep: 358.88 | bwd_inner_microstep: 291.95 | bwd_allreduce_microstep: 66.89 | step_microstep: 24.58 +[2025-05-02 01:21:49,939] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2759.86 | bwd: 4129.09 | bwd_inner: 4061.53 | bwd_allreduce: 67.12 | step: 25.38 + 13%|█▎ | 1142/8720 [3:06:23<14:55:28, 7.09s/it] {'loss': 0.878, 'grad_norm': 7.13540506362915, 'learning_rate': 9.735272135226906e-06, 'epoch': 1.31} + 13%|█▎ | 1142/8720 [3:06:23<14:55:28, 7.09s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-02 01:21:50,422] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.91 | bwd_microstep: 273.41 | bwd_inner_microstep: 273.39 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1907 +[2025-05-02 01:21:50,903] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.63 | bwd_microstep: 276.22 | bwd_inner_microstep: 276.21 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-02 01:21:51,382] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.64 | bwd_microstep: 274.00 | bwd_inner_microstep: 273.98 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1891 +[2025-05-02 01:21:51,861] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.13 | bwd_microstep: 274.87 | bwd_inner_microstep: 274.85 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.16 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1892 +[2025-05-02 01:21:52,342] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.36 | bwd_microstep: 274.91 | bwd_inner_microstep: 274.89 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 01:21:52,822] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.15 | bwd_microstep: 273.19 | bwd_inner_microstep: 273.17 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 01:21:53,301] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.11 | bwd_microstep: 273.06 | bwd_inner_microstep: 273.04 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:21:53,782] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.11 | bwd_microstep: 272.68 | bwd_inner_microstep: 272.66 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:21:54,265] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.69 | bwd_microstep: 272.68 | bwd_inner_microstep: 272.66 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:21:54,749] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.28 | bwd_microstep: 271.23 | bwd_inner_microstep: 271.21 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:21:55,232] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.40 | bwd_microstep: 271.06 | bwd_inner_microstep: 271.04 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 317 +[2025-05-02 01:21:55,453] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 83.37 | bwd_microstep: 121.76 | bwd_inner_microstep: 121.58 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:21:55,929] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.84 | bwd_microstep: 270.99 | bwd_inner_microstep: 270.98 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-02 01:21:56,412] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.10 | bwd_microstep: 274.02 | bwd_inner_microstep: 274.00 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 01:21:56,893] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.02 | bwd_microstep: 272.61 | bwd_inner_microstep: 272.60 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1351 +[2025-05-02 01:21:57,357] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.17 | optimizer_step: 16.59 +[2025-05-02 01:21:57,358] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.09 | bwd_microstep: 283.14 | bwd_inner_microstep: 206.34 | bwd_allreduce_microstep: 76.66 | step_microstep: 24.55 +[2025-05-02 01:21:57,359] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2864.42 | bwd: 4229.87 | bwd_inner: 4152.72 | bwd_allreduce: 76.78 | step: 25.56 + 13%|█▎ | 1143/8720 [3:06:31<15:07:55, 7.19s/it] {'loss': 0.7171, 'grad_norm': 5.181005477905273, 'learning_rate': 9.73467552059473e-06, 'epoch': 1.31} + 13%|█▎ | 1143/8720 [3:06:31<15:07:55, 7.19s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:21:57,844] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.15 | bwd_microstep: 272.23 | bwd_inner_microstep: 272.22 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2067 +[2025-05-02 01:21:58,367] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 202.53 | bwd_microstep: 303.22 | bwd_inner_microstep: 303.21 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1913 +[2025-05-02 01:21:58,850] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.16 | bwd_microstep: 276.13 | bwd_inner_microstep: 276.11 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.07 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 876 +[2025-05-02 01:21:59,098] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 97.89 | bwd_microstep: 134.57 | bwd_inner_microstep: 134.55 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1365 +[2025-05-02 01:21:59,462] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.73 | bwd_microstep: 206.69 | bwd_inner_microstep: 206.51 | bwd_allreduce_microstep: 0.10 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-02 01:21:59,942] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.94 | bwd_microstep: 273.48 | bwd_inner_microstep: 273.46 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 01:22:00,424] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.29 | bwd_microstep: 273.08 | bwd_inner_microstep: 273.07 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 339 +[2025-05-02 01:22:00,644] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 81.53 | bwd_microstep: 122.58 | bwd_inner_microstep: 122.34 | bwd_allreduce_microstep: 0.09 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 01:22:01,123] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.33 | bwd_microstep: 272.91 | bwd_inner_microstep: 272.90 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:22:01,602] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.93 | bwd_microstep: 272.35 | bwd_inner_microstep: 272.33 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 01:22:02,084] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.23 | bwd_microstep: 272.85 | bwd_inner_microstep: 272.84 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 01:22:02,565] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.27 | bwd_microstep: 272.23 | bwd_inner_microstep: 272.21 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:22:03,046] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.58 | bwd_microstep: 272.23 | bwd_inner_microstep: 272.21 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 320 +[2025-05-02 01:22:03,275] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 92.19 | bwd_microstep: 118.12 | bwd_inner_microstep: 117.92 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:22:03,752] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.75 | bwd_microstep: 271.20 | bwd_inner_microstep: 271.19 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:22:04,334] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.17 | optimizer_step: 16.68 +[2025-05-02 01:22:04,334] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.67 | bwd_microstep: 352.86 | bwd_inner_microstep: 271.66 | bwd_allreduce_microstep: 81.15 | step_microstep: 24.54 +[2025-05-02 01:22:04,336] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2690.78 | bwd: 3966.81 | bwd_inner: 3884.85 | bwd_allreduce: 81.48 | step: 25.51 + 13%|█▎ | 1144/8720 [3:06:38<14:59:44, 7.13s/it] {'loss': 0.9173, 'grad_norm': 6.741818428039551, 'learning_rate': 9.734078252749883e-06, 'epoch': 1.31} + 13%|█▎ | 1144/8720 [3:06:38<14:59:44, 7.13s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:22:04,819] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.51 | bwd_microstep: 270.53 | bwd_inner_microstep: 270.51 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 993 +[2025-05-02 01:22:05,092] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 103.39 | bwd_microstep: 150.85 | bwd_inner_microstep: 150.56 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1988 +[2025-05-02 01:22:05,600] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 196.59 | bwd_microstep: 293.72 | bwd_inner_microstep: 293.70 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1929 +[2025-05-02 01:22:06,106] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 198.02 | bwd_microstep: 287.38 | bwd_inner_microstep: 287.36 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 01:22:06,588] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.11 | bwd_microstep: 273.09 | bwd_inner_microstep: 273.08 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 01:22:07,070] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.32 | bwd_microstep: 272.47 | bwd_inner_microstep: 272.45 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 01:22:07,551] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.92 | bwd_microstep: 272.25 | bwd_inner_microstep: 272.23 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 01:22:08,031] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.20 | bwd_microstep: 273.18 | bwd_inner_microstep: 273.16 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 01:22:08,510] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.98 | bwd_microstep: 272.66 | bwd_inner_microstep: 272.64 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:22:08,988] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.10 | bwd_microstep: 272.41 | bwd_inner_microstep: 272.39 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 01:22:09,469] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.06 | bwd_microstep: 272.47 | bwd_inner_microstep: 272.46 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:22:09,947] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.22 | bwd_microstep: 272.15 | bwd_inner_microstep: 272.14 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:22:10,424] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.90 | bwd_microstep: 272.17 | bwd_inner_microstep: 272.16 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:22:10,900] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.42 | bwd_microstep: 271.21 | bwd_inner_microstep: 271.19 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 01:22:11,377] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.27 | bwd_microstep: 271.14 | bwd_inner_microstep: 271.12 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2124 +[2025-05-02 01:22:12,002] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.11 | optimizer_step: 16.56 +[2025-05-02 01:22:12,003] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 205.81 | bwd_microstep: 380.41 | bwd_inner_microstep: 313.83 | bwd_allreduce_microstep: 66.54 | step_microstep: 23.83 +[2025-05-02 01:22:12,004] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2961.44 | bwd: 4378.13 | bwd_inner: 4311.02 | bwd_allreduce: 66.74 | step: 24.67 + 13%|█▎ | 1145/8720 [3:06:45<15:20:05, 7.29s/it] {'loss': 0.8432, 'grad_norm': 5.863167762756348, 'learning_rate': 9.73348033177477e-06, 'epoch': 1.31} + 13%|█▎ | 1145/8720 [3:06:45<15:20:05, 7.29s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1894 +[2025-05-02 01:22:12,488] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.24 | bwd_microstep: 274.27 | bwd_inner_microstep: 274.25 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 392 +[2025-05-02 01:22:12,700] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 73.67 | bwd_microstep: 124.69 | bwd_inner_microstep: 124.56 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1911 +[2025-05-02 01:22:13,183] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.30 | bwd_microstep: 276.63 | bwd_inner_microstep: 276.61 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1381 +[2025-05-02 01:22:13,549] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 142.63 | bwd_microstep: 208.28 | bwd_inner_microstep: 208.26 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-02 01:22:14,031] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.84 | bwd_microstep: 274.93 | bwd_inner_microstep: 274.91 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 353 +[2025-05-02 01:22:14,264] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.77 | bwd_microstep: 119.78 | bwd_inner_microstep: 119.48 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 01:22:14,747] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.24 | bwd_microstep: 273.13 | bwd_inner_microstep: 273.11 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 01:22:15,227] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.15 | bwd_microstep: 273.11 | bwd_inner_microstep: 273.09 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:22:15,706] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.26 | bwd_microstep: 272.80 | bwd_inner_microstep: 272.79 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:22:16,186] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.82 | bwd_microstep: 272.75 | bwd_inner_microstep: 272.74 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-02 01:22:16,666] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.54 | bwd_microstep: 273.81 | bwd_inner_microstep: 273.79 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:22:17,145] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.31 | bwd_microstep: 271.55 | bwd_inner_microstep: 271.53 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 320 +[2025-05-02 01:22:17,380] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.11 | bwd_microstep: 120.16 | bwd_inner_microstep: 119.83 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.20 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1344 +[2025-05-02 01:22:17,743] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.65 | bwd_microstep: 204.46 | bwd_inner_microstep: 204.44 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1342 +[2025-05-02 01:22:18,105] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 139.89 | bwd_microstep: 204.27 | bwd_inner_microstep: 204.23 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 01:22:18,683] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.24 | optimizer_step: 16.85 +[2025-05-02 01:22:18,683] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.13 | bwd_microstep: 348.93 | bwd_inner_microstep: 271.32 | bwd_allreduce_microstep: 77.55 | step_microstep: 24.89 +[2025-05-02 01:22:18,685] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2573.18 | bwd: 3793.66 | bwd_inner: 3715.09 | bwd_allreduce: 77.92 | step: 26.22 + 13%|█▎ | 1146/8720 [3:06:52<14:57:03, 7.11s/it] {'loss': 0.9383, 'grad_norm': 11.839463233947754, 'learning_rate': 9.732881757751877e-06, 'epoch': 1.31} + 13%|█▎ | 1146/8720 [3:06:52<14:57:03, 7.11s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1909 +[2025-05-02 01:22:19,173] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.66 | bwd_microstep: 275.70 | bwd_inner_microstep: 275.69 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 467 +[2025-05-02 01:22:19,402] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.82 | bwd_microstep: 117.11 | bwd_inner_microstep: 116.96 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1891 +[2025-05-02 01:22:19,884] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.01 | bwd_microstep: 274.59 | bwd_inner_microstep: 274.57 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1889 +[2025-05-02 01:22:20,369] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.09 | bwd_microstep: 274.66 | bwd_inner_microstep: 274.65 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1883 +[2025-05-02 01:22:20,856] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.62 | bwd_microstep: 274.35 | bwd_inner_microstep: 274.33 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.14 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-02 01:22:21,341] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.82 | bwd_microstep: 273.77 | bwd_inner_microstep: 273.75 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:22:21,821] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.76 | bwd_microstep: 272.50 | bwd_inner_microstep: 272.49 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:22:22,302] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.59 | bwd_microstep: 272.60 | bwd_inner_microstep: 272.58 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1343 +[2025-05-02 01:22:22,668] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 142.31 | bwd_microstep: 204.56 | bwd_inner_microstep: 204.46 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:22:23,146] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.73 | bwd_microstep: 272.60 | bwd_inner_microstep: 272.58 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 833 +[2025-05-02 01:22:23,384] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.91 | bwd_microstep: 125.61 | bwd_inner_microstep: 125.48 | bwd_allreduce_microstep: 0.09 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:22:23,862] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.98 | bwd_microstep: 272.19 | bwd_inner_microstep: 272.17 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:22:24,341] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.63 | bwd_microstep: 272.45 | bwd_inner_microstep: 272.43 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:22:24,820] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.61 | bwd_microstep: 272.12 | bwd_inner_microstep: 272.11 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:22:25,299] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.35 | bwd_microstep: 271.16 | bwd_inner_microstep: 271.14 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.13 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:22:25,878] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.14 | optimizer_step: 16.42 +[2025-05-02 01:22:25,879] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.88 | bwd_microstep: 347.42 | bwd_inner_microstep: 271.71 | bwd_allreduce_microstep: 75.65 | step_microstep: 24.16 +[2025-05-02 01:22:25,880] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2785.36 | bwd: 4073.49 | bwd_inner: 3997.13 | bwd_allreduce: 75.93 | step: 25.33 + 13%|█▎ | 1147/8720 [3:06:59<15:00:17, 7.13s/it] {'loss': 0.7589, 'grad_norm': 8.195635795593262, 'learning_rate': 9.732282530763788e-06, 'epoch': 1.32} + 13%|█▎ | 1147/8720 [3:06:59<15:00:17, 7.13s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-02 01:22:26,364] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.66 | bwd_microstep: 273.06 | bwd_inner_microstep: 273.04 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 864 +[2025-05-02 01:22:26,608] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.45 | bwd_microstep: 133.57 | bwd_inner_microstep: 133.55 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-02 01:22:27,088] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.52 | bwd_microstep: 274.17 | bwd_inner_microstep: 274.15 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-02 01:22:27,565] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.70 | bwd_microstep: 273.97 | bwd_inner_microstep: 273.95 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 01:22:28,041] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.95 | bwd_microstep: 273.44 | bwd_inner_microstep: 273.42 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1355 +[2025-05-02 01:22:28,403] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.23 | bwd_microstep: 206.33 | bwd_inner_microstep: 206.24 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:22:28,879] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.49 | bwd_microstep: 272.43 | bwd_inner_microstep: 272.41 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 01:22:29,356] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.35 | bwd_microstep: 272.75 | bwd_inner_microstep: 272.74 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.22 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 327 +[2025-05-02 01:22:29,558] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 71.75 | bwd_microstep: 117.11 | bwd_inner_microstep: 116.89 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:22:30,034] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.23 | bwd_microstep: 272.65 | bwd_inner_microstep: 272.64 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 837 +[2025-05-02 01:22:30,267] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 92.09 | bwd_microstep: 126.33 | bwd_inner_microstep: 126.31 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:22:30,743] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.95 | bwd_microstep: 272.30 | bwd_inner_microstep: 272.28 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:22:31,220] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.59 | bwd_microstep: 271.80 | bwd_inner_microstep: 271.78 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:22:31,697] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.95 | bwd_microstep: 271.12 | bwd_inner_microstep: 271.10 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 01:22:32,175] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.66 | bwd_microstep: 271.03 | bwd_inner_microstep: 271.01 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2103 +[2025-05-02 01:22:32,809] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.10 | optimizer_step: 16.49 +[2025-05-02 01:22:32,809] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 203.29 | bwd_microstep: 388.11 | bwd_inner_microstep: 311.21 | bwd_allreduce_microstep: 76.85 | step_microstep: 24.24 +[2025-05-02 01:22:32,811] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2672.55 | bwd: 3970.22 | bwd_inner: 3892.79 | bwd_allreduce: 77.04 | step: 25.33 + 13%|█▎ | 1148/8720 [3:07:06<14:52:30, 7.07s/it] {'loss': 0.5602, 'grad_norm': 6.845881938934326, 'learning_rate': 9.731682650893176e-06, 'epoch': 1.32} + 13%|█▎ | 1148/8720 [3:07:06<14:52:30, 7.07s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1935 +[2025-05-02 01:22:33,316] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.89 | bwd_microstep: 287.19 | bwd_inner_microstep: 287.17 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 392 +[2025-05-02 01:22:33,517] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 69.23 | bwd_microstep: 118.74 | bwd_inner_microstep: 118.60 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1920 +[2025-05-02 01:22:33,998] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.75 | bwd_microstep: 276.65 | bwd_inner_microstep: 276.63 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1904 +[2025-05-02 01:22:34,480] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.37 | bwd_microstep: 275.75 | bwd_inner_microstep: 275.73 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 01:22:34,958] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.75 | bwd_microstep: 273.43 | bwd_inner_microstep: 273.41 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 349 +[2025-05-02 01:22:35,162] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 74.30 | bwd_microstep: 116.92 | bwd_inner_microstep: 116.75 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-02 01:22:35,638] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.02 | bwd_microstep: 273.09 | bwd_inner_microstep: 273.07 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 01:22:36,118] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.87 | bwd_microstep: 273.36 | bwd_inner_microstep: 273.35 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.17 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 01:22:36,598] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.54 | bwd_microstep: 273.26 | bwd_inner_microstep: 273.24 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:22:37,080] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.23 | bwd_microstep: 272.51 | bwd_inner_microstep: 272.50 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 01:22:37,562] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.30 | bwd_microstep: 272.73 | bwd_inner_microstep: 272.71 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:22:38,041] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.11 | bwd_microstep: 272.35 | bwd_inner_microstep: 272.33 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:22:38,521] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.18 | bwd_microstep: 272.33 | bwd_inner_microstep: 272.31 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 318 +[2025-05-02 01:22:38,757] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 102.55 | bwd_microstep: 115.20 | bwd_inner_microstep: 115.06 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 835 +[2025-05-02 01:22:38,994] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.95 | bwd_microstep: 126.06 | bwd_inner_microstep: 125.99 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:22:39,571] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.09 | optimizer_step: 16.42 +[2025-05-02 01:22:39,572] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.33 | bwd_microstep: 348.30 | bwd_inner_microstep: 271.81 | bwd_allreduce_microstep: 76.43 | step_microstep: 23.97 +[2025-05-02 01:22:39,573] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2611.02 | bwd: 3847.94 | bwd_inner: 3770.78 | bwd_allreduce: 76.71 | step: 25.17 + 13%|█▎ | 1149/8720 [3:07:13<14:40:41, 6.98s/it] {'loss': 0.731, 'grad_norm': 5.378937244415283, 'learning_rate': 9.7310821182228e-06, 'epoch': 1.32} + 13%|█▎ | 1149/8720 [3:07:13<14:40:41, 6.98s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:22:40,054] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.52 | bwd_microstep: 270.42 | bwd_inner_microstep: 270.40 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2056 +[2025-05-02 01:22:40,577] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 201.33 | bwd_microstep: 302.01 | bwd_inner_microstep: 302.00 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2001 +[2025-05-02 01:22:41,092] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 199.16 | bwd_microstep: 294.97 | bwd_inner_microstep: 294.95 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 439 +[2025-05-02 01:22:41,345] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.13 | bwd_microstep: 139.88 | bwd_inner_microstep: 139.67 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1893 +[2025-05-02 01:22:41,827] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.77 | bwd_microstep: 275.03 | bwd_inner_microstep: 275.01 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1895 +[2025-05-02 01:22:42,307] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.64 | bwd_microstep: 275.15 | bwd_inner_microstep: 275.13 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 347 +[2025-05-02 01:22:42,508] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 68.99 | bwd_microstep: 119.24 | bwd_inner_microstep: 119.09 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-02 01:22:42,985] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.80 | bwd_microstep: 273.74 | bwd_inner_microstep: 273.72 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1357 +[2025-05-02 01:22:43,347] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.89 | bwd_microstep: 206.29 | bwd_inner_microstep: 206.16 | bwd_allreduce_microstep: 0.04 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:22:43,823] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.95 | bwd_microstep: 272.85 | bwd_inner_microstep: 272.83 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 01:22:44,299] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.37 | bwd_microstep: 273.04 | bwd_inner_microstep: 273.02 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:22:44,775] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.31 | bwd_microstep: 272.15 | bwd_inner_microstep: 272.13 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:22:45,251] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.83 | bwd_microstep: 272.67 | bwd_inner_microstep: 272.65 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:22:45,729] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.24 | bwd_microstep: 272.60 | bwd_inner_microstep: 272.59 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1353 +[2025-05-02 01:22:46,093] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.86 | bwd_microstep: 206.14 | bwd_inner_microstep: 206.10 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2098 +[2025-05-02 01:22:46,706] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.10 | optimizer_step: 16.36 +[2025-05-02 01:22:46,706] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 202.68 | bwd_microstep: 371.91 | bwd_inner_microstep: 305.66 | bwd_allreduce_microstep: 66.20 | step_microstep: 23.35 +[2025-05-02 01:22:46,707] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2746.17 | bwd: 4098.14 | bwd_inner: 4031.21 | bwd_allreduce: 66.48 | step: 24.24 + 13%|█▎ | 1150/8720 [3:07:20<14:46:21, 7.03s/it] {'loss': 1.1068, 'grad_norm': 10.671951293945312, 'learning_rate': 9.730480932835514e-06, 'epoch': 1.32} + 13%|█▎ | 1150/8720 [3:07:20<14:46:21, 7.03s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2067 +[2025-05-02 01:22:47,232] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 202.35 | bwd_microstep: 302.42 | bwd_inner_microstep: 302.40 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1908 +[2025-05-02 01:22:47,713] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.30 | bwd_microstep: 276.31 | bwd_inner_microstep: 276.29 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1902 +[2025-05-02 01:22:48,194] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.07 | bwd_microstep: 275.76 | bwd_inner_microstep: 275.74 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1896 +[2025-05-02 01:22:48,675] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.69 | bwd_microstep: 275.14 | bwd_inner_microstep: 275.12 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1122 +[2025-05-02 01:22:48,974] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 118.72 | bwd_microstep: 163.28 | bwd_inner_microstep: 163.16 | bwd_allreduce_microstep: 0.03 | step_microstep: 0.18 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 864 +[2025-05-02 01:22:49,220] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.55 | bwd_microstep: 133.66 | bwd_inner_microstep: 133.41 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-02 01:22:49,699] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.08 | bwd_microstep: 273.06 | bwd_inner_microstep: 273.04 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 01:22:50,180] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.44 | bwd_microstep: 273.02 | bwd_inner_microstep: 273.00 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-02 01:22:50,661] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.56 | bwd_microstep: 273.41 | bwd_inner_microstep: 273.39 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 01:22:51,143] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.08 | bwd_microstep: 272.73 | bwd_inner_microstep: 272.71 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 01:22:51,624] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.15 | bwd_microstep: 272.84 | bwd_inner_microstep: 272.83 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:22:52,104] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.87 | bwd_microstep: 272.67 | bwd_inner_microstep: 272.66 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 01:22:52,584] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.29 | bwd_microstep: 272.88 | bwd_inner_microstep: 272.86 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 01:22:53,063] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.94 | bwd_microstep: 272.91 | bwd_inner_microstep: 272.89 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:22:53,543] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.87 | bwd_microstep: 272.58 | bwd_inner_microstep: 272.56 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 01:22:54,135] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.08 | optimizer_step: 16.39 +[2025-05-02 01:22:54,135] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.90 | bwd_microstep: 358.67 | bwd_inner_microstep: 272.01 | bwd_allreduce_microstep: 86.61 | step_microstep: 24.14 +[2025-05-02 01:22:54,137] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2873.50 | bwd: 4241.44 | bwd_inner: 4154.08 | bwd_allreduce: 86.87 | step: 25.13 + 13%|█▎ | 1151/8720 [3:07:27<15:01:36, 7.15s/it] {'loss': 1.0086, 'grad_norm': 8.157928466796875, 'learning_rate': 9.729879094814258e-06, 'epoch': 1.32} + 13%|█▎ | 1151/8720 [3:07:27<15:01:36, 7.15s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 01:22:54,618] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.84 | bwd_microstep: 270.33 | bwd_inner_microstep: 270.31 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1994 +[2025-05-02 01:22:55,130] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 199.51 | bwd_microstep: 294.03 | bwd_inner_microstep: 294.02 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1929 +[2025-05-02 01:22:55,630] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.79 | bwd_microstep: 287.52 | bwd_inner_microstep: 287.51 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 01:22:56,112] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.00 | bwd_microstep: 273.33 | bwd_inner_microstep: 273.31 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 327 +[2025-05-02 01:22:56,329] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 84.44 | bwd_microstep: 115.64 | bwd_inner_microstep: 115.48 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-02 01:22:56,809] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.30 | bwd_microstep: 273.42 | bwd_inner_microstep: 273.40 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 01:22:57,291] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.73 | bwd_microstep: 273.18 | bwd_inner_microstep: 273.17 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 01:22:57,773] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.39 | bwd_microstep: 272.84 | bwd_inner_microstep: 272.82 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:22:58,255] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.01 | bwd_microstep: 272.26 | bwd_inner_microstep: 272.24 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.22 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1358 +[2025-05-02 01:22:58,623] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.51 | bwd_microstep: 206.47 | bwd_inner_microstep: 206.26 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.13 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 01:22:59,105] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.40 | bwd_microstep: 272.77 | bwd_inner_microstep: 272.75 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:22:59,587] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.73 | bwd_microstep: 272.35 | bwd_inner_microstep: 272.33 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:23:00,068] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.89 | bwd_microstep: 272.58 | bwd_inner_microstep: 272.56 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 327 +[2025-05-02 01:23:00,313] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 111.52 | bwd_microstep: 116.15 | bwd_inner_microstep: 115.96 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:23:00,793] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.83 | bwd_microstep: 272.13 | bwd_inner_microstep: 272.12 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 01:23:01,395] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.20 | optimizer_step: 16.50 +[2025-05-02 01:23:01,395] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.94 | bwd_microstep: 369.69 | bwd_inner_microstep: 271.33 | bwd_allreduce_microstep: 98.30 | step_microstep: 26.05 +[2025-05-02 01:23:01,397] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2804.41 | bwd: 4114.76 | bwd_inner: 4015.63 | bwd_allreduce: 98.62 | step: 27.43 + 13%|█▎ | 1152/8720 [3:07:35<15:05:44, 7.18s/it] {'loss': 0.6996, 'grad_norm': 7.362151145935059, 'learning_rate': 9.729276604242064e-06, 'epoch': 1.32} + 13%|█▎ | 1152/8720 [3:07:35<15:05:44, 7.18s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:23:01,878] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.49 | bwd_microstep: 270.51 | bwd_inner_microstep: 270.49 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1892 +[2025-05-02 01:23:02,360] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.55 | bwd_microstep: 274.97 | bwd_inner_microstep: 274.96 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1887 +[2025-05-02 01:23:02,840] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.39 | bwd_microstep: 274.58 | bwd_inner_microstep: 274.56 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 01:23:03,317] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.63 | bwd_microstep: 272.94 | bwd_inner_microstep: 272.93 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 01:23:03,793] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.41 | bwd_microstep: 272.06 | bwd_inner_microstep: 272.05 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 01:23:04,269] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.58 | bwd_microstep: 272.53 | bwd_inner_microstep: 272.51 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:23:04,747] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.75 | bwd_microstep: 272.48 | bwd_inner_microstep: 272.46 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 01:23:05,224] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.27 | bwd_microstep: 272.93 | bwd_inner_microstep: 272.91 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 01:23:05,701] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.00 | bwd_microstep: 272.86 | bwd_inner_microstep: 272.85 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 01:23:06,175] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.40 | bwd_microstep: 271.29 | bwd_inner_microstep: 271.27 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:23:06,650] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.02 | bwd_microstep: 272.05 | bwd_inner_microstep: 272.03 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 01:23:07,124] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.05 | bwd_microstep: 271.03 | bwd_inner_microstep: 271.01 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:23:07,600] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.08 | bwd_microstep: 271.22 | bwd_inner_microstep: 271.21 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 01:23:08,075] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.18 | bwd_microstep: 270.98 | bwd_inner_microstep: 270.96 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:23:08,549] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.98 | bwd_microstep: 271.02 | bwd_inner_microstep: 271.00 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 01:23:09,134] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.18 | optimizer_step: 16.45 +[2025-05-02 01:23:09,135] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.15 | bwd_microstep: 356.63 | bwd_inner_microstep: 271.63 | bwd_allreduce_microstep: 84.95 | step_microstep: 24.91 +[2025-05-02 01:23:09,136] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 3017.61 | bwd: 4440.09 | bwd_inner: 4354.82 | bwd_allreduce: 85.03 | step: 25.96 + 13%|█▎ | 1153/8720 [3:07:42<15:26:41, 7.35s/it] {'loss': 0.5684, 'grad_norm': 10.713187217712402, 'learning_rate': 9.728673461202054e-06, 'epoch': 1.32} + 13%|█▎ | 1153/8720 [3:07:42<15:26:41, 7.35s/it]dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1337 +[2025-05-02 01:23:09,502] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 143.26 | bwd_microstep: 203.74 | bwd_inner_microstep: 203.62 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 418 +[2025-05-02 01:23:09,736] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 92.06 | bwd_microstep: 127.81 | bwd_inner_microstep: 127.66 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1889 +[2025-05-02 01:23:10,215] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.10 | bwd_microstep: 274.68 | bwd_inner_microstep: 274.67 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1886 +[2025-05-02 01:23:10,693] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.05 | bwd_microstep: 274.31 | bwd_inner_microstep: 274.29 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1377 +[2025-05-02 01:23:11,059] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.67 | bwd_microstep: 208.04 | bwd_inner_microstep: 208.03 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-02 01:23:11,538] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.68 | bwd_microstep: 274.62 | bwd_inner_microstep: 274.60 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1883 +[2025-05-02 01:23:12,017] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.20 | bwd_microstep: 274.38 | bwd_inner_microstep: 274.36 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-02 01:23:12,496] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.21 | bwd_microstep: 274.43 | bwd_inner_microstep: 274.41 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:23:12,973] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.51 | bwd_microstep: 272.49 | bwd_inner_microstep: 272.48 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 850 +[2025-05-02 01:23:13,220] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 99.30 | bwd_microstep: 132.13 | bwd_inner_microstep: 132.10 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:23:13,698] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.00 | bwd_microstep: 272.66 | bwd_inner_microstep: 272.64 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:23:14,176] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.81 | bwd_microstep: 272.52 | bwd_inner_microstep: 272.50 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:23:14,653] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.51 | bwd_microstep: 272.41 | bwd_inner_microstep: 272.39 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:23:15,129] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.29 | bwd_microstep: 272.26 | bwd_inner_microstep: 272.24 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 838 +[2025-05-02 01:23:15,370] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 99.64 | bwd_microstep: 126.24 | bwd_inner_microstep: 126.01 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:23:15,955] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.18 | optimizer_step: 16.63 +[2025-05-02 01:23:15,956] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.04 | bwd_microstep: 356.81 | bwd_inner_microstep: 271.91 | bwd_allreduce_microstep: 84.85 | step_microstep: 25.29 +[2025-05-02 01:23:15,957] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2652.02 | bwd: 3889.61 | bwd_inner: 3803.96 | bwd_allreduce: 85.13 | step: 26.25 + 13%|█▎ | 1154/8720 [3:07:49<15:06:39, 7.19s/it] {'loss': 0.7378, 'grad_norm': 4.666125774383545, 'learning_rate': 9.728069665777437e-06, 'epoch': 1.32} + 13%|█▎ | 1154/8720 [3:07:49<15:06:39, 7.19s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 01:23:16,437] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.67 | bwd_microstep: 270.69 | bwd_inner_microstep: 270.67 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2062 +[2025-05-02 01:23:16,958] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 203.40 | bwd_microstep: 302.36 | bwd_inner_microstep: 302.35 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1971 +[2025-05-02 01:23:17,464] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 198.66 | bwd_microstep: 291.19 | bwd_inner_microstep: 291.17 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1914 +[2025-05-02 01:23:17,947] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.94 | bwd_microstep: 276.15 | bwd_inner_microstep: 276.13 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.22 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1903 +[2025-05-02 01:23:18,428] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.90 | bwd_microstep: 275.70 | bwd_inner_microstep: 275.68 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1893 +[2025-05-02 01:23:18,908] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.79 | bwd_microstep: 274.64 | bwd_inner_microstep: 274.62 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-02 01:23:19,386] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.55 | bwd_microstep: 273.69 | bwd_inner_microstep: 273.67 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 01:23:19,865] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.50 | bwd_microstep: 273.46 | bwd_inner_microstep: 273.44 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 01:23:20,343] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.05 | bwd_microstep: 273.29 | bwd_inner_microstep: 273.28 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 340 +[2025-05-02 01:23:20,572] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 84.50 | bwd_microstep: 130.48 | bwd_inner_microstep: 130.21 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:23:21,047] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.39 | bwd_microstep: 272.29 | bwd_inner_microstep: 272.27 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 01:23:21,523] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.55 | bwd_microstep: 272.63 | bwd_inner_microstep: 272.61 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 01:23:22,001] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.46 | bwd_microstep: 272.26 | bwd_inner_microstep: 272.24 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:23:22,478] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.50 | bwd_microstep: 272.63 | bwd_inner_microstep: 272.61 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:23:22,958] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.97 | bwd_microstep: 272.59 | bwd_inner_microstep: 272.58 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 01:23:23,538] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.14 | optimizer_step: 16.57 +[2025-05-02 01:23:23,539] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.97 | bwd_microstep: 349.52 | bwd_inner_microstep: 272.01 | bwd_allreduce_microstep: 77.46 | step_microstep: 24.53 +[2025-05-02 01:23:23,540] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2943.50 | bwd: 4353.62 | bwd_inner: 4275.63 | bwd_allreduce: 77.62 | step: 25.47 + 13%|█▎ | 1155/8720 [3:07:57<15:21:27, 7.31s/it] {'loss': 0.8275, 'grad_norm': 9.904031753540039, 'learning_rate': 9.727465218051521e-06, 'epoch': 1.32} + 13%|█▎ | 1155/8720 [3:07:57<15:21:27, 7.31s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:23:24,021] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.56 | bwd_microstep: 270.37 | bwd_inner_microstep: 270.35 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1708 +[2025-05-02 01:23:24,454] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 159.92 | bwd_microstep: 256.89 | bwd_inner_microstep: 256.80 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-02 01:23:24,933] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.73 | bwd_microstep: 274.34 | bwd_inner_microstep: 274.33 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1887 +[2025-05-02 01:23:25,416] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.43 | bwd_microstep: 274.78 | bwd_inner_microstep: 274.76 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-02 01:23:25,898] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.98 | bwd_microstep: 274.18 | bwd_inner_microstep: 274.16 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1883 +[2025-05-02 01:23:26,379] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.92 | bwd_microstep: 274.46 | bwd_inner_microstep: 274.44 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-02 01:23:26,862] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.01 | bwd_microstep: 273.45 | bwd_inner_microstep: 273.43 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 337 +[2025-05-02 01:23:27,098] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 102.11 | bwd_microstep: 115.81 | bwd_inner_microstep: 115.65 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 01:23:27,578] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.28 | bwd_microstep: 273.02 | bwd_inner_microstep: 273.00 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:23:28,057] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.31 | bwd_microstep: 272.62 | bwd_inner_microstep: 272.61 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 01:23:28,539] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.96 | bwd_microstep: 273.04 | bwd_inner_microstep: 273.02 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:23:29,021] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.58 | bwd_microstep: 272.46 | bwd_inner_microstep: 272.45 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 834 +[2025-05-02 01:23:29,273] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 105.20 | bwd_microstep: 125.46 | bwd_inner_microstep: 125.32 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:23:29,757] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.69 | bwd_microstep: 272.52 | bwd_inner_microstep: 272.50 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:23:30,239] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.43 | bwd_microstep: 272.61 | bwd_inner_microstep: 272.59 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:23:30,823] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.13 | optimizer_step: 16.63 +[2025-05-02 01:23:30,824] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.33 | bwd_microstep: 351.43 | bwd_inner_microstep: 271.69 | bwd_allreduce_microstep: 79.69 | step_microstep: 24.54 +[2025-05-02 01:23:30,825] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2823.01 | bwd: 4127.49 | bwd_inner: 4047.13 | bwd_allreduce: 79.95 | step: 25.64 + 13%|█▎ | 1156/8720 [3:08:04<15:20:26, 7.30s/it] {'loss': 0.8681, 'grad_norm': 10.275312423706055, 'learning_rate': 9.726860118107693e-06, 'epoch': 1.33} + 13%|█▎ | 1156/8720 [3:08:04<15:20:26, 7.30s/it]dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 827 +[2025-05-02 01:23:31,071] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.11 | bwd_microstep: 130.04 | bwd_inner_microstep: 129.88 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 433 +[2025-05-02 01:23:31,307] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 85.98 | bwd_microstep: 134.04 | bwd_inner_microstep: 133.73 | bwd_allreduce_microstep: 0.14 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1926 +[2025-05-02 01:23:31,808] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 194.82 | bwd_microstep: 287.29 | bwd_inner_microstep: 287.27 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-02 01:23:32,288] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.71 | bwd_microstep: 273.80 | bwd_inner_microstep: 273.79 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-02 01:23:32,768] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.88 | bwd_microstep: 273.41 | bwd_inner_microstep: 273.39 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1364 +[2025-05-02 01:23:33,134] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.91 | bwd_microstep: 207.10 | bwd_inner_microstep: 207.00 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-02 01:23:33,617] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.01 | bwd_microstep: 273.43 | bwd_inner_microstep: 273.41 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 01:23:34,096] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.54 | bwd_microstep: 272.75 | bwd_inner_microstep: 272.73 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 01:23:34,578] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.30 | bwd_microstep: 272.71 | bwd_inner_microstep: 272.69 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:23:35,059] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.57 | bwd_microstep: 272.42 | bwd_inner_microstep: 272.41 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:23:35,536] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.54 | bwd_microstep: 271.25 | bwd_inner_microstep: 271.24 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 01:23:36,017] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.90 | bwd_microstep: 272.12 | bwd_inner_microstep: 272.10 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1345 +[2025-05-02 01:23:36,384] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 142.78 | bwd_microstep: 205.75 | bwd_inner_microstep: 205.60 | bwd_allreduce_microstep: 0.08 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 01:23:36,860] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.56 | bwd_microstep: 271.32 | bwd_inner_microstep: 271.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:23:37,337] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.26 | bwd_microstep: 271.11 | bwd_inner_microstep: 271.09 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 316 +[2025-05-02 01:23:37,660] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.21 | optimizer_step: 16.88 +[2025-05-02 01:23:37,661] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 83.20 | bwd_microstep: 202.90 | bwd_inner_microstep: 129.93 | bwd_allreduce_microstep: 72.81 | step_microstep: 24.12 +[2025-05-02 01:23:37,662] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2628.68 | bwd: 3891.51 | bwd_inner: 3817.70 | bwd_allreduce: 73.25 | step: 25.20 + 13%|█▎ | 1157/8720 [3:08:11<15:02:42, 7.16s/it] {'loss': 0.6614, 'grad_norm': 12.124893188476562, 'learning_rate': 9.726254366029435e-06, 'epoch': 1.33} + 13%|█▎ | 1157/8720 [3:08:11<15:02:42, 7.16s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1849 +[2025-05-02 01:23:38,139] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.45 | bwd_microstep: 269.98 | bwd_inner_microstep: 269.96 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1708 +[2025-05-02 01:23:38,571] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 160.04 | bwd_microstep: 256.37 | bwd_inner_microstep: 256.35 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-02 01:23:39,048] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.45 | bwd_microstep: 273.64 | bwd_inner_microstep: 273.63 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 01:23:39,526] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.60 | bwd_microstep: 273.27 | bwd_inner_microstep: 273.25 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-02 01:23:40,003] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.47 | bwd_microstep: 273.26 | bwd_inner_microstep: 273.24 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.06 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 845 +[2025-05-02 01:23:40,272] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 97.62 | bwd_microstep: 156.04 | bwd_inner_microstep: 155.75 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.13 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 01:23:40,754] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.23 | bwd_microstep: 272.94 | bwd_inner_microstep: 272.92 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:23:41,234] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.90 | bwd_microstep: 273.19 | bwd_inner_microstep: 273.17 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 836 +[2025-05-02 01:23:41,469] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.77 | bwd_microstep: 126.26 | bwd_inner_microstep: 126.00 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:23:41,944] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.98 | bwd_microstep: 272.22 | bwd_inner_microstep: 272.20 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:23:42,422] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.06 | bwd_microstep: 272.71 | bwd_inner_microstep: 272.69 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 844 +[2025-05-02 01:23:42,671] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.14 | bwd_microstep: 137.23 | bwd_inner_microstep: 137.04 | bwd_allreduce_microstep: 0.09 | step_microstep: 0.10 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 839 +[2025-05-02 01:23:42,907] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.91 | bwd_microstep: 126.34 | bwd_inner_microstep: 126.05 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:23:43,386] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.31 | bwd_microstep: 272.69 | bwd_inner_microstep: 272.67 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 01:23:43,864] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.31 | bwd_microstep: 272.40 | bwd_inner_microstep: 272.38 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 01:23:44,444] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.09 | optimizer_step: 16.45 +[2025-05-02 01:23:44,445] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.76 | bwd_microstep: 349.36 | bwd_inner_microstep: 271.94 | bwd_allreduce_microstep: 77.36 | step_microstep: 24.23 +[2025-05-02 01:23:44,446] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2610.68 | bwd: 3877.97 | bwd_inner: 3799.38 | bwd_allreduce: 77.83 | step: 25.22 + 13%|█▎ | 1158/8720 [3:08:18<14:48:22, 7.05s/it] {'loss': 0.5735, 'grad_norm': 6.434968948364258, 'learning_rate': 9.72564796190032e-06, 'epoch': 1.33} + 13%|█▎ | 1158/8720 [3:08:18<14:48:22, 7.05s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2114 +[2025-05-02 01:23:44,987] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 205.91 | bwd_microstep: 312.12 | bwd_inner_microstep: 312.11 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2141 +[2025-05-02 01:23:45,520] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 204.16 | bwd_microstep: 314.80 | bwd_inner_microstep: 314.79 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1890 +[2025-05-02 01:23:45,999] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.12 | bwd_microstep: 274.47 | bwd_inner_microstep: 274.45 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-02 01:23:46,477] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.85 | bwd_microstep: 273.67 | bwd_inner_microstep: 273.66 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1355 +[2025-05-02 01:23:46,840] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.17 | bwd_microstep: 206.38 | bwd_inner_microstep: 206.36 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-02 01:23:47,318] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.13 | bwd_microstep: 273.36 | bwd_inner_microstep: 273.34 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 01:23:47,794] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.08 | bwd_microstep: 273.05 | bwd_inner_microstep: 273.03 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 01:23:48,271] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.94 | bwd_microstep: 273.12 | bwd_inner_microstep: 273.10 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 01:23:48,751] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.18 | bwd_microstep: 273.21 | bwd_inner_microstep: 273.19 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 01:23:49,232] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.16 | bwd_microstep: 273.18 | bwd_inner_microstep: 273.16 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1099 +[2025-05-02 01:23:49,524] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 115.89 | bwd_microstep: 161.23 | bwd_inner_microstep: 161.09 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:23:50,001] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.84 | bwd_microstep: 272.55 | bwd_inner_microstep: 272.53 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 01:23:50,476] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.00 | bwd_microstep: 271.98 | bwd_inner_microstep: 271.96 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:23:50,955] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.38 | bwd_microstep: 272.13 | bwd_inner_microstep: 272.11 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 318 +[2025-05-02 01:23:51,195] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 104.05 | bwd_microstep: 115.83 | bwd_inner_microstep: 115.53 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:23:51,780] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.11 | optimizer_step: 16.38 +[2025-05-02 01:23:51,780] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.00 | bwd_microstep: 356.23 | bwd_inner_microstep: 271.75 | bwd_allreduce_microstep: 84.42 | step_microstep: 24.63 +[2025-05-02 01:23:51,782] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2845.52 | bwd: 4197.38 | bwd_inner: 4112.23 | bwd_allreduce: 84.71 | step: 25.62 + 13%|█▎ | 1159/8720 [3:08:25<14:59:06, 7.13s/it] {'loss': 0.7051, 'grad_norm': 7.341969966888428, 'learning_rate': 9.72504090580401e-06, 'epoch': 1.33} + 13%|█▎ | 1159/8720 [3:08:25<14:59:06, 7.13s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 01:23:52,263] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.47 | bwd_microstep: 270.49 | bwd_inner_microstep: 270.47 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1899 +[2025-05-02 01:23:52,745] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.62 | bwd_microstep: 275.51 | bwd_inner_microstep: 275.49 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1889 +[2025-05-02 01:23:53,229] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.04 | bwd_microstep: 274.83 | bwd_inner_microstep: 274.81 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1360 +[2025-05-02 01:23:53,596] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 142.02 | bwd_microstep: 206.57 | bwd_inner_microstep: 206.55 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-02 01:23:54,075] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.40 | bwd_microstep: 273.61 | bwd_inner_microstep: 273.59 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-02 01:23:54,554] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.16 | bwd_microstep: 273.58 | bwd_inner_microstep: 273.57 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 01:23:55,035] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.87 | bwd_microstep: 273.22 | bwd_inner_microstep: 273.20 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 338 +[2025-05-02 01:23:55,256] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 84.59 | bwd_microstep: 118.53 | bwd_inner_microstep: 118.21 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 01:23:55,735] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.15 | bwd_microstep: 273.15 | bwd_inner_microstep: 273.13 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.12 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1360 +[2025-05-02 01:23:56,099] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.64 | bwd_microstep: 206.53 | bwd_inner_microstep: 206.51 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 01:23:56,578] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.06 | bwd_microstep: 273.15 | bwd_inner_microstep: 273.13 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 01:23:57,057] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.44 | bwd_microstep: 272.71 | bwd_inner_microstep: 272.70 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 01:23:57,535] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.33 | bwd_microstep: 272.70 | bwd_inner_microstep: 272.68 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 324 +[2025-05-02 01:23:57,755] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 85.68 | bwd_microstep: 118.08 | bwd_inner_microstep: 117.95 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:23:58,231] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.81 | bwd_microstep: 272.51 | bwd_inner_microstep: 272.49 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:23:58,796] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.08 | optimizer_step: 16.39 +[2025-05-02 01:23:58,796] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.65 | bwd_microstep: 338.70 | bwd_inner_microstep: 271.85 | bwd_allreduce_microstep: 66.80 | step_microstep: 23.45 +[2025-05-02 01:23:58,798] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2716.60 | bwd: 3993.92 | bwd_inner: 3926.43 | bwd_allreduce: 67.03 | step: 24.46 + 13%|█▎ | 1160/8720 [3:08:32<14:54:25, 7.10s/it] {'loss': 0.8417, 'grad_norm': 5.761847972869873, 'learning_rate': 9.724433197824255e-06, 'epoch': 1.33} + 13%|█▎ | 1160/8720 [3:08:32<14:54:25, 7.10s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 01:23:59,275] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.62 | bwd_microstep: 270.38 | bwd_inner_microstep: 270.36 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1889 +[2025-05-02 01:23:59,754] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.44 | bwd_microstep: 274.72 | bwd_inner_microstep: 274.71 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1890 +[2025-05-02 01:24:00,233] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.23 | bwd_microstep: 274.83 | bwd_inner_microstep: 274.81 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1890 +[2025-05-02 01:24:00,713] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.73 | bwd_microstep: 274.77 | bwd_inner_microstep: 274.75 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-02 01:24:01,192] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.09 | bwd_microstep: 274.18 | bwd_inner_microstep: 274.16 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-02 01:24:01,672] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.08 | bwd_microstep: 273.59 | bwd_inner_microstep: 273.58 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-02 01:24:02,153] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.28 | bwd_microstep: 274.29 | bwd_inner_microstep: 274.27 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 01:24:02,637] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.53 | bwd_microstep: 273.43 | bwd_inner_microstep: 273.41 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 01:24:03,123] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.84 | bwd_microstep: 273.11 | bwd_inner_microstep: 273.09 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 01:24:03,602] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.11 | bwd_microstep: 272.96 | bwd_inner_microstep: 272.95 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 01:24:04,085] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.55 | bwd_microstep: 272.99 | bwd_inner_microstep: 272.97 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:24:04,566] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.59 | bwd_microstep: 271.33 | bwd_inner_microstep: 271.31 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 01:24:05,046] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.19 | bwd_microstep: 272.81 | bwd_inner_microstep: 272.80 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:24:05,525] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.27 | bwd_microstep: 272.53 | bwd_inner_microstep: 272.51 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 01:24:06,003] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.39 | bwd_microstep: 271.05 | bwd_inner_microstep: 271.03 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:24:06,580] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.04 | optimizer_gradients: 2.09 | optimizer_step: 16.40 +[2025-05-02 01:24:06,581] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.70 | bwd_microstep: 348.35 | bwd_inner_microstep: 271.72 | bwd_allreduce_microstep: 76.58 | step_microstep: 23.25 +[2025-05-02 01:24:06,582] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 3023.29 | bwd: 4445.33 | bwd_inner: 4368.43 | bwd_allreduce: 76.66 | step: 24.00 + 13%|█▎ | 1161/8720 [3:08:40<15:20:12, 7.30s/it] {'loss': 0.998, 'grad_norm': 14.972740173339844, 'learning_rate': 9.723824838044897e-06, 'epoch': 1.33} + 13%|█▎ | 1161/8720 [3:08:40<15:20:12, 7.30s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1946 +[2025-05-02 01:24:07,086] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 196.25 | bwd_microstep: 288.09 | bwd_inner_microstep: 288.07 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1109 +[2025-05-02 01:24:07,378] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 115.99 | bwd_microstep: 161.79 | bwd_inner_microstep: 161.77 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 01:24:07,856] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.11 | bwd_microstep: 273.35 | bwd_inner_microstep: 273.33 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 01:24:08,333] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.19 | bwd_microstep: 273.03 | bwd_inner_microstep: 273.02 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 01:24:08,809] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.77 | bwd_microstep: 272.66 | bwd_inner_microstep: 272.64 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1347 +[2025-05-02 01:24:09,170] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.99 | bwd_microstep: 205.45 | bwd_inner_microstep: 205.38 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 01:24:09,646] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.23 | bwd_microstep: 272.83 | bwd_inner_microstep: 272.81 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 328 +[2025-05-02 01:24:09,860] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 83.80 | bwd_microstep: 116.41 | bwd_inner_microstep: 116.10 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:24:10,338] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.23 | bwd_microstep: 272.71 | bwd_inner_microstep: 272.69 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:24:10,814] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.12 | bwd_microstep: 271.27 | bwd_inner_microstep: 271.25 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:24:11,293] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.73 | bwd_microstep: 272.20 | bwd_inner_microstep: 272.18 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 01:24:11,772] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.20 | bwd_microstep: 272.18 | bwd_inner_microstep: 272.16 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:24:12,255] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.69 | bwd_microstep: 271.30 | bwd_inner_microstep: 271.28 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:24:12,729] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.60 | bwd_microstep: 271.13 | bwd_inner_microstep: 271.11 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 01:24:13,203] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.81 | bwd_microstep: 271.15 | bwd_inner_microstep: 271.13 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 01:24:13,769] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.04 | optimizer_gradients: 2.12 | optimizer_step: 16.42 +[2025-05-02 01:24:13,770] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.66 | bwd_microstep: 338.85 | bwd_inner_microstep: 271.67 | bwd_allreduce_microstep: 67.14 | step_microstep: 23.42 +[2025-05-02 01:24:13,771] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2794.04 | bwd: 4104.49 | bwd_inner: 4036.67 | bwd_allreduce: 67.34 | step: 24.30 + 13%|█▎ | 1162/8720 [3:08:47<15:15:44, 7.27s/it] {'loss': 0.6868, 'grad_norm': 11.388609886169434, 'learning_rate': 9.72321582654987e-06, 'epoch': 1.33} + 13%|█▎ | 1162/8720 [3:08:47<15:15:44, 7.27s/it]dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 827 +[2025-05-02 01:24:14,011] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 91.69 | bwd_microstep: 129.74 | bwd_inner_microstep: 129.65 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1974 +[2025-05-02 01:24:14,516] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 197.83 | bwd_microstep: 291.62 | bwd_inner_microstep: 291.60 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1897 +[2025-05-02 01:24:14,996] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.18 | bwd_microstep: 275.19 | bwd_inner_microstep: 275.17 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 337 +[2025-05-02 01:24:15,209] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 81.12 | bwd_microstep: 117.81 | bwd_inner_microstep: 117.68 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-02 01:24:15,686] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.62 | bwd_microstep: 273.51 | bwd_inner_microstep: 273.49 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-02 01:24:16,167] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.12 | bwd_microstep: 273.31 | bwd_inner_microstep: 273.30 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 01:24:16,648] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.54 | bwd_microstep: 272.50 | bwd_inner_microstep: 272.48 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:24:17,128] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.44 | bwd_microstep: 272.07 | bwd_inner_microstep: 272.05 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:24:17,606] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.00 | bwd_microstep: 271.03 | bwd_inner_microstep: 271.01 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.15 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:24:18,085] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.97 | bwd_microstep: 271.33 | bwd_inner_microstep: 271.31 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:24:18,566] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.00 | bwd_microstep: 271.24 | bwd_inner_microstep: 271.22 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 01:24:19,047] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.87 | bwd_microstep: 271.33 | bwd_inner_microstep: 271.31 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:24:19,526] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.86 | bwd_microstep: 271.07 | bwd_inner_microstep: 271.06 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:24:20,005] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.12 | bwd_microstep: 271.22 | bwd_inner_microstep: 271.20 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 01:24:20,486] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.42 | bwd_microstep: 270.86 | bwd_inner_microstep: 270.84 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 01:24:21,064] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.11 | optimizer_step: 16.45 +[2025-05-02 01:24:21,064] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.18 | bwd_microstep: 348.27 | bwd_inner_microstep: 271.54 | bwd_allreduce_microstep: 76.68 | step_microstep: 24.18 +[2025-05-02 01:24:21,066] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2817.53 | bwd: 4152.15 | bwd_inner: 4074.96 | bwd_allreduce: 76.87 | step: 25.30 + 13%|█▎ | 1163/8720 [3:08:54<15:16:38, 7.28s/it] {'loss': 0.4989, 'grad_norm': 11.091547012329102, 'learning_rate': 9.72260616342319e-06, 'epoch': 1.33} + 13%|█▎ | 1163/8720 [3:08:54<15:16:38, 7.28s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 01:24:21,549] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.24 | bwd_microstep: 271.86 | bwd_inner_microstep: 271.84 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1967 +[2025-05-02 01:24:22,051] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 196.22 | bwd_microstep: 290.65 | bwd_inner_microstep: 290.63 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1915 +[2025-05-02 01:24:22,531] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.36 | bwd_microstep: 275.95 | bwd_inner_microstep: 275.93 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-02 01:24:23,010] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.15 | bwd_microstep: 274.00 | bwd_inner_microstep: 273.98 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1896 +[2025-05-02 01:24:23,489] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.86 | bwd_microstep: 274.71 | bwd_inner_microstep: 274.69 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-02 01:24:23,968] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.34 | bwd_microstep: 273.19 | bwd_inner_microstep: 273.17 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-02 01:24:24,448] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.39 | bwd_microstep: 273.52 | bwd_inner_microstep: 273.50 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 341 +[2025-05-02 01:24:24,682] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 100.49 | bwd_microstep: 115.50 | bwd_inner_microstep: 115.19 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:24:25,160] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.41 | bwd_microstep: 272.71 | bwd_inner_microstep: 272.69 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 01:24:25,639] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.41 | bwd_microstep: 272.73 | bwd_inner_microstep: 272.71 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 01:24:26,119] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.55 | bwd_microstep: 272.84 | bwd_inner_microstep: 272.82 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:24:26,599] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.16 | bwd_microstep: 272.51 | bwd_inner_microstep: 272.50 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 332 +[2025-05-02 01:24:26,836] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 101.43 | bwd_microstep: 116.10 | bwd_inner_microstep: 115.85 | bwd_allreduce_microstep: 0.10 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 01:24:27,315] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.71 | bwd_microstep: 272.76 | bwd_inner_microstep: 272.74 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 01:24:27,795] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.41 | bwd_microstep: 271.55 | bwd_inner_microstep: 271.54 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 01:24:28,373] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.08 | optimizer_step: 16.43 +[2025-05-02 01:24:28,374] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.45 | bwd_microstep: 348.52 | bwd_inner_microstep: 271.96 | bwd_allreduce_microstep: 76.51 | step_microstep: 24.01 +[2025-05-02 01:24:28,375] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2851.24 | bwd: 4149.15 | bwd_inner: 4071.86 | bwd_allreduce: 76.78 | step: 24.97 + 13%|█▎ | 1164/8720 [3:09:02<15:17:44, 7.29s/it] {'loss': 0.6723, 'grad_norm': 12.62190055847168, 'learning_rate': 9.721995848748972e-06, 'epoch': 1.33} + 13%|█▎ | 1164/8720 [3:09:02<15:17:44, 7.29s/it]dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 830 +[2025-05-02 01:24:28,624] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 96.44 | bwd_microstep: 129.83 | bwd_inner_microstep: 129.67 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1906 +[2025-05-02 01:24:29,106] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.25 | bwd_microstep: 275.81 | bwd_inner_microstep: 275.79 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1895 +[2025-05-02 01:24:29,588] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.01 | bwd_microstep: 275.05 | bwd_inner_microstep: 275.03 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1891 +[2025-05-02 01:24:30,069] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.05 | bwd_microstep: 274.70 | bwd_inner_microstep: 274.69 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1892 +[2025-05-02 01:24:30,553] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.26 | bwd_microstep: 274.93 | bwd_inner_microstep: 274.91 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 860 +[2025-05-02 01:24:30,808] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 99.64 | bwd_microstep: 134.13 | bwd_inner_microstep: 133.86 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1887 +[2025-05-02 01:24:31,293] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.82 | bwd_microstep: 275.30 | bwd_inner_microstep: 275.28 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 344 +[2025-05-02 01:24:31,542] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.79 | bwd_microstep: 134.56 | bwd_inner_microstep: 134.41 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1892 +[2025-05-02 01:24:32,022] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.47 | bwd_microstep: 274.70 | bwd_inner_microstep: 274.68 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 842 +[2025-05-02 01:24:32,264] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.79 | bwd_microstep: 131.65 | bwd_inner_microstep: 131.60 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:24:32,741] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.70 | bwd_microstep: 272.30 | bwd_inner_microstep: 272.28 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 850 +[2025-05-02 01:24:32,988] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 96.94 | bwd_microstep: 132.57 | bwd_inner_microstep: 132.37 | bwd_allreduce_microstep: 0.08 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 01:24:33,465] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.45 | bwd_microstep: 272.52 | bwd_inner_microstep: 272.50 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 01:24:33,944] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.19 | bwd_microstep: 272.65 | bwd_inner_microstep: 272.63 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:24:34,425] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.11 | bwd_microstep: 272.40 | bwd_inner_microstep: 272.38 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 01:24:35,013] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.16 | optimizer_step: 16.50 +[2025-05-02 01:24:35,014] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.68 | bwd_microstep: 356.73 | bwd_inner_microstep: 271.41 | bwd_allreduce_microstep: 85.27 | step_microstep: 24.43 +[2025-05-02 01:24:35,015] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2554.17 | bwd: 3759.91 | bwd_inner: 3673.59 | bwd_allreduce: 85.67 | step: 25.51 + 13%|█▎ | 1165/8720 [3:09:08<14:53:09, 7.09s/it] {'loss': 0.7752, 'grad_norm': 6.638096809387207, 'learning_rate': 9.72138488261142e-06, 'epoch': 1.34} + 13%|█▎ | 1165/8720 [3:09:08<14:53:09, 7.09s/it]dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1340 +[2025-05-02 01:24:35,384] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.55 | bwd_microstep: 204.51 | bwd_inner_microstep: 204.03 | bwd_allreduce_microstep: 0.21 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2067 +[2025-05-02 01:24:35,906] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 200.91 | bwd_microstep: 303.17 | bwd_inner_microstep: 303.15 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1961 +[2025-05-02 01:24:36,409] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.76 | bwd_microstep: 290.42 | bwd_inner_microstep: 290.40 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1934 +[2025-05-02 01:24:36,910] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.28 | bwd_microstep: 288.17 | bwd_inner_microstep: 288.15 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 404 +[2025-05-02 01:24:37,138] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 87.20 | bwd_microstep: 123.58 | bwd_inner_microstep: 123.27 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.18 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 359 +[2025-05-02 01:24:37,359] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 83.67 | bwd_microstep: 120.32 | bwd_inner_microstep: 120.04 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-02 01:24:37,838] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.54 | bwd_microstep: 273.75 | bwd_inner_microstep: 273.73 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-02 01:24:38,320] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.97 | bwd_microstep: 274.77 | bwd_inner_microstep: 274.76 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-02 01:24:38,800] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.46 | bwd_microstep: 273.38 | bwd_inner_microstep: 273.36 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 01:24:39,278] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.25 | bwd_microstep: 272.92 | bwd_inner_microstep: 272.90 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 332 +[2025-05-02 01:24:39,484] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 68.71 | bwd_microstep: 123.60 | bwd_inner_microstep: 123.29 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:24:39,959] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.33 | bwd_microstep: 272.44 | bwd_inner_microstep: 272.42 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 327 +[2025-05-02 01:24:40,177] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 80.49 | bwd_microstep: 122.49 | bwd_inner_microstep: 122.19 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:24:40,655] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.13 | bwd_microstep: 272.62 | bwd_inner_microstep: 272.60 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 01:24:41,133] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.10 | bwd_microstep: 271.44 | bwd_inner_microstep: 271.42 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:24:41,724] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.21 | optimizer_step: 16.56 +[2025-05-02 01:24:41,724] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.48 | bwd_microstep: 357.05 | bwd_inner_microstep: 271.80 | bwd_allreduce_microstep: 85.19 | step_microstep: 24.57 +[2025-05-02 01:24:41,726] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2559.47 | bwd: 3844.76 | bwd_inner: 3757.86 | bwd_allreduce: 85.89 | step: 25.75 + 13%|█▎ | 1166/8720 [3:09:15<14:38:34, 6.98s/it] {'loss': 0.7145, 'grad_norm': 7.029405117034912, 'learning_rate': 9.720773265094819e-06, 'epoch': 1.34} + 13%|█▎ | 1166/8720 [3:09:15<14:38:34, 6.98s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:24:42,208] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.29 | bwd_microstep: 270.39 | bwd_inner_microstep: 270.37 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 882 +[2025-05-02 01:24:42,457] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 97.99 | bwd_microstep: 135.15 | bwd_inner_microstep: 135.08 | bwd_allreduce_microstep: 0.03 | step_microstep: 0.10 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 867 +[2025-05-02 01:24:42,709] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 100.31 | bwd_microstep: 134.11 | bwd_inner_microstep: 133.81 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 01:24:43,189] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.28 | bwd_microstep: 273.39 | bwd_inner_microstep: 273.38 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 01:24:43,671] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.31 | bwd_microstep: 273.44 | bwd_inner_microstep: 273.42 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 01:24:44,156] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.64 | bwd_microstep: 272.53 | bwd_inner_microstep: 272.51 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:24:44,638] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.31 | bwd_microstep: 272.25 | bwd_inner_microstep: 272.23 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 01:24:45,120] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.22 | bwd_microstep: 272.44 | bwd_inner_microstep: 272.42 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 01:24:45,604] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.07 | bwd_microstep: 273.19 | bwd_inner_microstep: 273.17 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 325 +[2025-05-02 01:24:45,839] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.14 | bwd_microstep: 122.44 | bwd_inner_microstep: 122.22 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 01:24:46,317] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.87 | bwd_microstep: 272.26 | bwd_inner_microstep: 272.24 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 841 +[2025-05-02 01:24:46,560] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.54 | bwd_microstep: 132.21 | bwd_inner_microstep: 132.11 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:24:47,036] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.21 | bwd_microstep: 272.44 | bwd_inner_microstep: 272.42 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 01:24:47,513] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.30 | bwd_microstep: 272.79 | bwd_inner_microstep: 272.78 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:24:47,988] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.28 | bwd_microstep: 272.35 | bwd_inner_microstep: 272.33 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:24:48,554] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.04 | optimizer_gradients: 2.18 | optimizer_step: 16.64 +[2025-05-02 01:24:48,554] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.05 | bwd_microstep: 339.23 | bwd_inner_microstep: 272.60 | bwd_allreduce_microstep: 66.59 | step_microstep: 23.78 +[2025-05-02 01:24:48,555] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2644.44 | bwd: 3860.68 | bwd_inner: 3793.21 | bwd_allreduce: 66.94 | step: 24.78 + 13%|█▎ | 1167/8720 [3:09:22<14:32:45, 6.93s/it] {'loss': 0.7702, 'grad_norm': 17.472108840942383, 'learning_rate': 9.720160996283554e-06, 'epoch': 1.34} + 13%|█▎ | 1167/8720 [3:09:22<14:32:45, 6.93s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:24:49,035] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.04 | bwd_microstep: 271.47 | bwd_inner_microstep: 271.45 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-02 01:24:49,514] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.24 | bwd_microstep: 273.80 | bwd_inner_microstep: 273.78 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1891 +[2025-05-02 01:24:49,994] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.83 | bwd_microstep: 274.93 | bwd_inner_microstep: 274.91 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-02 01:24:50,476] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.83 | bwd_microstep: 273.50 | bwd_inner_microstep: 273.48 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-02 01:24:50,956] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.01 | bwd_microstep: 273.28 | bwd_inner_microstep: 273.26 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 01:24:51,437] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.78 | bwd_microstep: 273.10 | bwd_inner_microstep: 273.08 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 840 +[2025-05-02 01:24:51,679] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 96.20 | bwd_microstep: 126.02 | bwd_inner_microstep: 125.95 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.10 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1096 +[2025-05-02 01:24:51,972] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 114.90 | bwd_microstep: 161.07 | bwd_inner_microstep: 161.05 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:24:52,450] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.48 | bwd_microstep: 272.61 | bwd_inner_microstep: 272.59 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 01:24:52,929] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.80 | bwd_microstep: 272.23 | bwd_inner_microstep: 272.22 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:24:53,411] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.22 | bwd_microstep: 272.73 | bwd_inner_microstep: 272.71 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:24:53,891] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.01 | bwd_microstep: 272.40 | bwd_inner_microstep: 272.38 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:24:54,370] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.25 | bwd_microstep: 272.50 | bwd_inner_microstep: 272.48 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1346 +[2025-05-02 01:24:54,736] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.81 | bwd_microstep: 205.63 | bwd_inner_microstep: 205.62 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:24:55,213] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.32 | bwd_microstep: 272.37 | bwd_inner_microstep: 272.36 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1986 +[2025-05-02 01:24:55,810] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.18 | optimizer_step: 16.61 +[2025-05-02 01:24:55,810] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 197.87 | bwd_microstep: 360.68 | bwd_inner_microstep: 293.88 | bwd_allreduce_microstep: 66.75 | step_microstep: 23.85 +[2025-05-02 01:24:55,812] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2815.27 | bwd: 4128.36 | bwd_inner: 4061.21 | bwd_allreduce: 66.86 | step: 25.05 + 13%|█▎ | 1168/8720 [3:09:29<14:44:51, 7.03s/it] {'loss': 0.6812, 'grad_norm': 17.594642639160156, 'learning_rate': 9.719548076262093e-06, 'epoch': 1.34} + 13%|█▎ | 1168/8720 [3:09:29<14:44:51, 7.03s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1888 +[2025-05-02 01:24:56,294] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.78 | bwd_microstep: 273.79 | bwd_inner_microstep: 273.77 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.06 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1377 +[2025-05-02 01:24:56,659] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.49 | bwd_microstep: 207.75 | bwd_inner_microstep: 207.71 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 01:24:57,135] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.50 | bwd_microstep: 273.19 | bwd_inner_microstep: 273.17 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 01:24:57,613] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.63 | bwd_microstep: 273.46 | bwd_inner_microstep: 273.44 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-02 01:24:58,091] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.73 | bwd_microstep: 273.33 | bwd_inner_microstep: 273.31 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 336 +[2025-05-02 01:24:58,294] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 69.51 | bwd_microstep: 119.55 | bwd_inner_microstep: 119.41 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:24:58,770] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.22 | bwd_microstep: 272.70 | bwd_inner_microstep: 272.68 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 839 +[2025-05-02 01:24:59,002] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 91.64 | bwd_microstep: 126.26 | bwd_inner_microstep: 126.23 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 01:24:59,478] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.04 | bwd_microstep: 272.70 | bwd_inner_microstep: 272.68 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:24:59,955] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.10 | bwd_microstep: 272.71 | bwd_inner_microstep: 272.69 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.21 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 325 +[2025-05-02 01:25:00,166] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 76.31 | bwd_microstep: 119.70 | bwd_inner_microstep: 119.40 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:25:00,642] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.63 | bwd_microstep: 272.40 | bwd_inner_microstep: 272.38 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.13 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:25:01,117] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.78 | bwd_microstep: 271.16 | bwd_inner_microstep: 271.14 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:25:01,593] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.75 | bwd_microstep: 272.02 | bwd_inner_microstep: 272.00 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 01:25:02,069] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.71 | bwd_microstep: 271.18 | bwd_inner_microstep: 271.16 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2054 +[2025-05-02 01:25:02,680] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.13 | optimizer_step: 16.87 +[2025-05-02 01:25:02,680] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 202.09 | bwd_microstep: 369.86 | bwd_inner_microstep: 302.83 | bwd_allreduce_microstep: 66.99 | step_microstep: 24.07 +[2025-05-02 01:25:02,681] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2649.64 | bwd: 3941.79 | bwd_inner: 3874.08 | bwd_allreduce: 67.25 | step: 25.29 + 13%|█▎ | 1169/8720 [3:09:36<14:38:40, 6.98s/it] {'loss': 0.7058, 'grad_norm': 10.735097885131836, 'learning_rate': 9.718934505115e-06, 'epoch': 1.34} + 13%|█▎ | 1169/8720 [3:09:36<14:38:40, 6.98s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1934 +[2025-05-02 01:25:03,184] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.59 | bwd_microstep: 287.60 | bwd_inner_microstep: 287.58 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1934 +[2025-05-02 01:25:03,685] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.79 | bwd_microstep: 288.48 | bwd_inner_microstep: 288.46 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1915 +[2025-05-02 01:25:04,166] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.95 | bwd_microstep: 276.47 | bwd_inner_microstep: 276.45 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 01:25:04,645] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.09 | bwd_microstep: 273.18 | bwd_inner_microstep: 273.16 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-02 01:25:05,123] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.15 | bwd_microstep: 273.45 | bwd_inner_microstep: 273.43 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-02 01:25:05,601] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.03 | bwd_microstep: 273.64 | bwd_inner_microstep: 273.62 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:25:06,076] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.91 | bwd_microstep: 272.46 | bwd_inner_microstep: 272.44 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 844 +[2025-05-02 01:25:06,318] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.24 | bwd_microstep: 132.15 | bwd_inner_microstep: 131.97 | bwd_allreduce_microstep: 0.08 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 01:25:06,795] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.43 | bwd_microstep: 272.46 | bwd_inner_microstep: 272.45 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 01:25:07,272] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.33 | bwd_microstep: 272.43 | bwd_inner_microstep: 272.42 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:25:07,748] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.37 | bwd_microstep: 272.53 | bwd_inner_microstep: 272.51 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 01:25:08,226] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.57 | bwd_microstep: 273.06 | bwd_inner_microstep: 273.04 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:25:08,703] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.99 | bwd_microstep: 272.33 | bwd_inner_microstep: 272.31 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 832 +[2025-05-02 01:25:08,947] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 98.18 | bwd_microstep: 129.86 | bwd_inner_microstep: 129.81 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.12 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1343 +[2025-05-02 01:25:09,309] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.81 | bwd_microstep: 204.52 | bwd_inner_microstep: 204.47 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 317 +[2025-05-02 01:25:09,635] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.04 | optimizer_gradients: 2.09 | optimizer_step: 16.45 +[2025-05-02 01:25:09,635] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 79.99 | bwd_microstep: 207.60 | bwd_inner_microstep: 132.81 | bwd_allreduce_microstep: 74.69 | step_microstep: 23.29 +[2025-05-02 01:25:09,636] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2692.13 | bwd: 3982.27 | bwd_inner: 3906.97 | bwd_allreduce: 74.83 | step: 24.14 + 13%|█▎ | 1170/8720 [3:09:43<14:37:32, 6.97s/it] {'loss': 0.8042, 'grad_norm': 11.995433807373047, 'learning_rate': 9.718320282926924e-06, 'epoch': 1.34} + 13%|█▎ | 1170/8720 [3:09:43<14:37:32, 6.97s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 351 +[2025-05-02 01:25:09,841] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 68.09 | bwd_microstep: 118.94 | bwd_inner_microstep: 118.80 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 398 +[2025-05-02 01:25:10,040] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 68.56 | bwd_microstep: 117.30 | bwd_inner_microstep: 117.17 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 371 +[2025-05-02 01:25:10,238] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 67.98 | bwd_microstep: 117.61 | bwd_inner_microstep: 117.49 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1886 +[2025-05-02 01:25:10,715] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.92 | bwd_microstep: 274.40 | bwd_inner_microstep: 274.38 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1887 +[2025-05-02 01:25:11,195] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.56 | bwd_microstep: 274.35 | bwd_inner_microstep: 274.34 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-02 01:25:11,672] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.35 | bwd_microstep: 273.48 | bwd_inner_microstep: 273.46 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1098 +[2025-05-02 01:25:11,963] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 115.03 | bwd_microstep: 161.15 | bwd_inner_microstep: 161.06 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:25:12,440] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.76 | bwd_microstep: 272.64 | bwd_inner_microstep: 272.62 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 01:25:12,919] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.51 | bwd_microstep: 272.90 | bwd_inner_microstep: 272.88 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 01:25:13,398] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.90 | bwd_microstep: 273.30 | bwd_inner_microstep: 273.29 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:25:13,878] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.67 | bwd_microstep: 272.63 | bwd_inner_microstep: 272.61 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1353 +[2025-05-02 01:25:14,246] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.71 | bwd_microstep: 206.41 | bwd_inner_microstep: 206.36 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 01:25:14,728] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.91 | bwd_microstep: 272.66 | bwd_inner_microstep: 272.65 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1355 +[2025-05-02 01:25:15,097] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.04 | bwd_microstep: 206.60 | bwd_inner_microstep: 206.46 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.10 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 835 +[2025-05-02 01:25:15,334] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.32 | bwd_microstep: 125.98 | bwd_inner_microstep: 125.72 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:25:15,912] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.09 | optimizer_step: 16.42 +[2025-05-02 01:25:15,913] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.94 | bwd_microstep: 349.76 | bwd_inner_microstep: 272.75 | bwd_allreduce_microstep: 76.91 | step_microstep: 24.09 +[2025-05-02 01:25:15,914] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2392.93 | bwd: 3590.23 | bwd_inner: 3512.14 | bwd_allreduce: 77.41 | step: 25.11 + 13%|█▎ | 1171/8720 [3:09:49<14:11:13, 6.77s/it] {'loss': 1.1856, 'grad_norm': 9.871371269226074, 'learning_rate': 9.717705409782602e-06, 'epoch': 1.34} + 13%|█▎ | 1171/8720 [3:09:49<14:11:13, 6.77s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:25:16,397] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.87 | bwd_microstep: 270.58 | bwd_inner_microstep: 270.57 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.15 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 488 +[2025-05-02 01:25:16,610] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 76.80 | bwd_microstep: 120.51 | bwd_inner_microstep: 120.20 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1982 +[2025-05-02 01:25:17,115] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 198.17 | bwd_microstep: 291.88 | bwd_inner_microstep: 291.86 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-02 01:25:17,591] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.29 | bwd_microstep: 273.73 | bwd_inner_microstep: 273.72 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1883 +[2025-05-02 01:25:18,069] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.49 | bwd_microstep: 273.99 | bwd_inner_microstep: 273.97 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 01:25:18,544] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.71 | bwd_microstep: 272.52 | bwd_inner_microstep: 272.50 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:25:19,020] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.92 | bwd_microstep: 272.45 | bwd_inner_microstep: 272.43 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 01:25:19,496] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.25 | bwd_microstep: 272.55 | bwd_inner_microstep: 272.53 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:25:19,971] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.60 | bwd_microstep: 272.05 | bwd_inner_microstep: 272.03 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 01:25:20,447] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.33 | bwd_microstep: 272.74 | bwd_inner_microstep: 272.72 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:25:20,922] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.61 | bwd_microstep: 272.29 | bwd_inner_microstep: 272.27 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:25:21,399] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.50 | bwd_microstep: 272.72 | bwd_inner_microstep: 272.70 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 01:25:21,874] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.83 | bwd_microstep: 271.93 | bwd_inner_microstep: 271.92 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:25:22,347] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.33 | bwd_microstep: 270.84 | bwd_inner_microstep: 270.82 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 01:25:22,820] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.75 | bwd_microstep: 270.88 | bwd_inner_microstep: 270.87 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.15 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 827 +[2025-05-02 01:25:23,147] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.04 | optimizer_gradients: 2.11 | optimizer_step: 16.47 +[2025-05-02 01:25:23,147] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 92.83 | bwd_microstep: 196.88 | bwd_inner_microstep: 130.25 | bwd_allreduce_microstep: 66.48 | step_microstep: 23.47 +[2025-05-02 01:25:23,148] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2815.02 | bwd: 4148.57 | bwd_inner: 4081.48 | bwd_allreduce: 66.65 | step: 24.47 + 13%|█▎ | 1172/8720 [3:09:56<14:28:43, 6.91s/it] {'loss': 0.5544, 'grad_norm': 8.897899627685547, 'learning_rate': 9.71708988576687e-06, 'epoch': 1.34} + 13%|█▎ | 1172/8720 [3:09:56<14:28:43, 6.91s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-02 01:25:23,630] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.26 | bwd_microstep: 273.52 | bwd_inner_microstep: 273.50 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1972 +[2025-05-02 01:25:24,135] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 198.53 | bwd_microstep: 291.60 | bwd_inner_microstep: 291.58 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 889 +[2025-05-02 01:25:24,382] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 97.34 | bwd_microstep: 135.68 | bwd_inner_microstep: 135.61 | bwd_allreduce_microstep: 0.03 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1901 +[2025-05-02 01:25:24,864] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.07 | bwd_microstep: 275.73 | bwd_inner_microstep: 275.72 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 359 +[2025-05-02 01:25:25,063] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 67.92 | bwd_microstep: 118.03 | bwd_inner_microstep: 117.86 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.11 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 867 +[2025-05-02 01:25:25,306] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.41 | bwd_microstep: 134.76 | bwd_inner_microstep: 134.53 | bwd_allreduce_microstep: 0.10 | step_microstep: 0.09 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1365 +[2025-05-02 01:25:25,669] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.19 | bwd_microstep: 207.16 | bwd_inner_microstep: 207.06 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 853 +[2025-05-02 01:25:25,913] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 96.71 | bwd_microstep: 133.09 | bwd_inner_microstep: 132.80 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 01:25:26,388] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.87 | bwd_microstep: 272.76 | bwd_inner_microstep: 272.75 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 01:25:26,865] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.98 | bwd_microstep: 272.93 | bwd_inner_microstep: 272.91 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:25:27,342] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.65 | bwd_microstep: 272.36 | bwd_inner_microstep: 272.34 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:25:27,819] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.38 | bwd_microstep: 272.56 | bwd_inner_microstep: 272.54 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 01:25:28,295] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.09 | bwd_microstep: 272.71 | bwd_inner_microstep: 272.69 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:25:28,771] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.42 | bwd_microstep: 272.22 | bwd_inner_microstep: 272.20 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:25:29,247] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.02 | bwd_microstep: 272.24 | bwd_inner_microstep: 272.22 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 829 +[2025-05-02 01:25:29,572] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.04 | optimizer_gradients: 2.11 | optimizer_step: 16.43 +[2025-05-02 01:25:29,573] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 92.38 | bwd_microstep: 196.96 | bwd_inner_microstep: 130.39 | bwd_allreduce_microstep: 66.48 | step_microstep: 23.30 +[2025-05-02 01:25:29,574] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2486.00 | bwd: 3674.38 | bwd_inner: 3606.82 | bwd_allreduce: 66.93 | step: 24.20 + 13%|█▎ | 1173/8720 [3:10:03<14:10:29, 6.76s/it] {'loss': 1.2584, 'grad_norm': 20.66610336303711, 'learning_rate': 9.716473710964642e-06, 'epoch': 1.35} + 13%|█▎ | 1173/8720 [3:10:03<14:10:29, 6.76s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 367 +[2025-05-02 01:25:29,782] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 72.90 | bwd_microstep: 117.42 | bwd_inner_microstep: 117.29 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1923 +[2025-05-02 01:25:30,278] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 194.82 | bwd_microstep: 286.92 | bwd_inner_microstep: 286.90 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 362 +[2025-05-02 01:25:30,491] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 76.89 | bwd_microstep: 122.03 | bwd_inner_microstep: 121.71 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1125 +[2025-05-02 01:25:30,788] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 117.58 | bwd_microstep: 163.19 | bwd_inner_microstep: 163.17 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-02 01:25:31,264] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.49 | bwd_microstep: 272.97 | bwd_inner_microstep: 272.96 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 01:25:31,741] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.80 | bwd_microstep: 273.20 | bwd_inner_microstep: 273.18 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 01:25:32,218] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.72 | bwd_microstep: 273.18 | bwd_inner_microstep: 273.16 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:25:32,694] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.76 | bwd_microstep: 272.47 | bwd_inner_microstep: 272.45 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 845 +[2025-05-02 01:25:32,934] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.84 | bwd_microstep: 132.40 | bwd_inner_microstep: 132.11 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 325 +[2025-05-02 01:25:33,136] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 69.81 | bwd_microstep: 118.89 | bwd_inner_microstep: 118.57 | bwd_allreduce_microstep: 0.15 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:25:33,610] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.55 | bwd_microstep: 272.24 | bwd_inner_microstep: 272.22 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:25:34,087] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.05 | bwd_microstep: 272.27 | bwd_inner_microstep: 272.25 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 01:25:34,561] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.12 | bwd_microstep: 271.16 | bwd_inner_microstep: 271.15 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:25:35,037] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.31 | bwd_microstep: 271.23 | bwd_inner_microstep: 271.22 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 01:25:35,516] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.56 | bwd_microstep: 271.10 | bwd_inner_microstep: 271.08 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 316 +[2025-05-02 01:25:35,866] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.13 | optimizer_step: 16.44 +[2025-05-02 01:25:35,867] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.72 | bwd_microstep: 209.64 | bwd_inner_microstep: 132.99 | bwd_allreduce_microstep: 76.55 | step_microstep: 24.08 +[2025-05-02 01:25:35,868] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2416.60 | bwd: 3600.39 | bwd_inner: 3522.61 | bwd_allreduce: 77.06 | step: 24.96 + 13%|█▎ | 1174/8720 [3:10:09<13:52:48, 6.62s/it] {'loss': 0.5815, 'grad_norm': 6.510145664215088, 'learning_rate': 9.715856885460932e-06, 'epoch': 1.35} + 13%|█▎ | 1174/8720 [3:10:09<13:52:48, 6.62s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1897 +[2025-05-02 01:25:36,355] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.54 | bwd_microstep: 274.60 | bwd_inner_microstep: 274.58 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2092 +[2025-05-02 01:25:36,880] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 204.01 | bwd_microstep: 304.46 | bwd_inner_microstep: 304.44 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1895 +[2025-05-02 01:25:37,361] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.32 | bwd_microstep: 274.85 | bwd_inner_microstep: 274.83 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-02 01:25:37,842] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.55 | bwd_microstep: 273.28 | bwd_inner_microstep: 273.26 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1889 +[2025-05-02 01:25:38,320] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.07 | bwd_microstep: 274.51 | bwd_inner_microstep: 274.49 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-02 01:25:38,798] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.47 | bwd_microstep: 274.20 | bwd_inner_microstep: 274.19 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 01:25:39,275] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.69 | bwd_microstep: 272.65 | bwd_inner_microstep: 272.64 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1352 +[2025-05-02 01:25:39,635] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.80 | bwd_microstep: 205.82 | bwd_inner_microstep: 205.80 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 01:25:40,112] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.42 | bwd_microstep: 272.70 | bwd_inner_microstep: 272.68 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:25:40,588] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.04 | bwd_microstep: 272.61 | bwd_inner_microstep: 272.60 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 325 +[2025-05-02 01:25:40,808] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 68.61 | bwd_microstep: 138.65 | bwd_inner_microstep: 138.52 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:25:41,283] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.27 | bwd_microstep: 272.26 | bwd_inner_microstep: 272.24 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 325 +[2025-05-02 01:25:41,494] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 79.41 | bwd_microstep: 117.19 | bwd_inner_microstep: 117.05 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:25:41,970] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.31 | bwd_microstep: 272.57 | bwd_inner_microstep: 272.55 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:25:42,445] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.12 | bwd_microstep: 271.20 | bwd_inner_microstep: 271.18 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 01:25:43,026] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.09 | optimizer_step: 16.43 +[2025-05-02 01:25:43,026] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.91 | bwd_microstep: 348.72 | bwd_inner_microstep: 272.25 | bwd_allreduce_microstep: 76.41 | step_microstep: 24.11 +[2025-05-02 01:25:43,028] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2755.25 | bwd: 4120.33 | bwd_inner: 4043.37 | bwd_allreduce: 76.59 | step: 24.87 + 13%|█▎ | 1175/8720 [3:10:16<14:12:59, 6.78s/it] {'loss': 0.5674, 'grad_norm': 6.768063068389893, 'learning_rate': 9.71523940934084e-06, 'epoch': 1.35} + 13%|█▎ | 1175/8720 [3:10:16<14:12:59, 6.78s/it]dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 828 +[2025-05-02 01:25:43,274] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.98 | bwd_microstep: 130.09 | bwd_inner_microstep: 129.85 | bwd_allreduce_microstep: 0.10 | step_microstep: 0.10 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1551 +[2025-05-02 01:25:43,680] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 151.90 | bwd_microstep: 238.05 | bwd_inner_microstep: 238.03 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1988 +[2025-05-02 01:25:44,186] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 197.32 | bwd_microstep: 293.47 | bwd_inner_microstep: 293.45 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1904 +[2025-05-02 01:25:44,666] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.30 | bwd_microstep: 275.56 | bwd_inner_microstep: 275.54 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-02 01:25:45,143] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.66 | bwd_microstep: 273.85 | bwd_inner_microstep: 273.84 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-02 01:25:45,620] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.78 | bwd_microstep: 273.30 | bwd_inner_microstep: 273.28 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-02 01:25:46,099] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.91 | bwd_microstep: 274.18 | bwd_inner_microstep: 274.16 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-02 01:25:46,580] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.37 | bwd_microstep: 273.71 | bwd_inner_microstep: 273.69 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-02 01:25:47,059] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.66 | bwd_microstep: 272.92 | bwd_inner_microstep: 272.91 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 842 +[2025-05-02 01:25:47,307] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 99.95 | bwd_microstep: 131.95 | bwd_inner_microstep: 131.66 | bwd_allreduce_microstep: 0.18 | step_microstep: 0.13 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:25:47,785] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.88 | bwd_microstep: 272.35 | bwd_inner_microstep: 272.34 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 01:25:48,262] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.99 | bwd_microstep: 272.42 | bwd_inner_microstep: 272.41 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 01:25:48,738] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.63 | bwd_microstep: 272.56 | bwd_inner_microstep: 272.54 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:25:49,214] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.58 | bwd_microstep: 272.67 | bwd_inner_microstep: 272.65 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:25:49,692] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.06 | bwd_microstep: 272.44 | bwd_inner_microstep: 272.42 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:25:50,270] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.07 | optimizer_gradients: 2.10 | optimizer_step: 16.44 +[2025-05-02 01:25:50,270] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.54 | bwd_microstep: 349.76 | bwd_inner_microstep: 273.62 | bwd_allreduce_microstep: 76.09 | step_microstep: 24.10 +[2025-05-02 01:25:50,272] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2807.22 | bwd: 4149.34 | bwd_inner: 4072.44 | bwd_allreduce: 76.39 | step: 24.96 + 13%|█▎ | 1176/8720 [3:10:24<14:30:15, 6.92s/it] {'loss': 0.9736, 'grad_norm': 8.31578254699707, 'learning_rate': 9.714621282689551e-06, 'epoch': 1.35} + 13%|█▎ | 1176/8720 [3:10:24<14:30:15, 6.92s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:25:50,752] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.50 | bwd_microstep: 270.58 | bwd_inner_microstep: 270.56 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1901 +[2025-05-02 01:25:51,233] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.94 | bwd_microstep: 275.68 | bwd_inner_microstep: 275.66 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 867 +[2025-05-02 01:25:51,476] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.17 | bwd_microstep: 133.96 | bwd_inner_microstep: 133.84 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1883 +[2025-05-02 01:25:51,954] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.89 | bwd_microstep: 274.28 | bwd_inner_microstep: 274.26 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 841 +[2025-05-02 01:25:52,194] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.44 | bwd_microstep: 131.99 | bwd_inner_microstep: 131.73 | bwd_allreduce_microstep: 0.14 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 01:25:52,672] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.05 | bwd_microstep: 273.40 | bwd_inner_microstep: 273.38 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 01:25:53,150] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.13 | bwd_microstep: 272.89 | bwd_inner_microstep: 272.88 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:25:53,628] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.87 | bwd_microstep: 272.56 | bwd_inner_microstep: 272.54 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 01:25:54,109] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.35 | bwd_microstep: 272.95 | bwd_inner_microstep: 272.93 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 843 +[2025-05-02 01:25:54,355] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.46 | bwd_microstep: 131.86 | bwd_inner_microstep: 131.85 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 01:25:54,833] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.82 | bwd_microstep: 272.74 | bwd_inner_microstep: 272.73 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:25:55,312] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.66 | bwd_microstep: 272.50 | bwd_inner_microstep: 272.48 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 324 +[2025-05-02 01:25:55,540] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 88.20 | bwd_microstep: 122.90 | bwd_inner_microstep: 122.75 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 01:25:56,017] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.89 | bwd_microstep: 271.17 | bwd_inner_microstep: 271.16 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 01:25:56,493] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.06 | bwd_microstep: 270.97 | bwd_inner_microstep: 270.95 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1889 +[2025-05-02 01:25:57,076] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.19 | optimizer_step: 16.59 +[2025-05-02 01:25:57,076] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.33 | bwd_microstep: 351.35 | bwd_inner_microstep: 275.08 | bwd_allreduce_microstep: 76.22 | step_microstep: 24.54 +[2025-05-02 01:25:57,078] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2637.44 | bwd: 3871.85 | bwd_inner: 3794.82 | bwd_allreduce: 76.54 | step: 25.45 + 13%|█▎ | 1177/8720 [3:10:30<14:25:47, 6.89s/it] {'loss': 0.7612, 'grad_norm': 9.456669807434082, 'learning_rate': 9.714002505592346e-06, 'epoch': 1.35} + 13%|█▎ | 1177/8720 [3:10:30<14:25:47, 6.89s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:25:57,560] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.06 | bwd_microstep: 271.09 | bwd_inner_microstep: 271.07 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1927 +[2025-05-02 01:25:58,058] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.37 | bwd_microstep: 287.54 | bwd_inner_microstep: 287.53 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1900 +[2025-05-02 01:25:58,540] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.32 | bwd_microstep: 275.43 | bwd_inner_microstep: 275.41 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 01:25:59,018] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.35 | bwd_microstep: 272.78 | bwd_inner_microstep: 272.76 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 01:25:59,500] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.33 | bwd_microstep: 273.22 | bwd_inner_microstep: 273.21 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 01:25:59,981] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.35 | bwd_microstep: 272.98 | bwd_inner_microstep: 272.97 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:26:00,461] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.83 | bwd_microstep: 272.58 | bwd_inner_microstep: 272.56 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 01:26:00,939] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.15 | bwd_microstep: 272.54 | bwd_inner_microstep: 272.53 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 330 +[2025-05-02 01:26:01,173] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 89.66 | bwd_microstep: 126.79 | bwd_inner_microstep: 126.49 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:26:01,649] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.79 | bwd_microstep: 271.25 | bwd_inner_microstep: 271.23 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:26:02,126] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.20 | bwd_microstep: 271.11 | bwd_inner_microstep: 271.09 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 829 +[2025-05-02 01:26:02,371] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 96.46 | bwd_microstep: 129.72 | bwd_inner_microstep: 129.57 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:26:02,849] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.68 | bwd_microstep: 271.13 | bwd_inner_microstep: 271.11 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:26:03,330] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.04 | bwd_microstep: 270.94 | bwd_inner_microstep: 270.92 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 01:26:03,807] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.08 | bwd_microstep: 271.03 | bwd_inner_microstep: 271.02 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 827 +[2025-05-02 01:26:04,143] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.16 | optimizer_step: 16.60 +[2025-05-02 01:26:04,144] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.93 | bwd_microstep: 203.20 | bwd_inner_microstep: 136.62 | bwd_allreduce_microstep: 66.49 | step_microstep: 23.82 +[2025-05-02 01:26:04,145] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2733.25 | bwd: 4013.37 | bwd_inner: 3946.17 | bwd_allreduce: 66.75 | step: 24.73 + 14%|█▎ | 1178/8720 [3:10:37<14:32:25, 6.94s/it] {'loss': 0.947, 'grad_norm': 13.0733642578125, 'learning_rate': 9.713383078134593e-06, 'epoch': 1.35} + 14%|█▎ | 1178/8720 [3:10:37<14:32:25, 6.94s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1966 +[2025-05-02 01:26:04,652] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 196.93 | bwd_microstep: 289.71 | bwd_inner_microstep: 289.69 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2293 +[2025-05-02 01:26:05,204] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 210.98 | bwd_microstep: 325.62 | bwd_inner_microstep: 325.60 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-02 01:26:05,681] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.28 | bwd_microstep: 273.36 | bwd_inner_microstep: 273.35 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1387 +[2025-05-02 01:26:06,047] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.48 | bwd_microstep: 208.88 | bwd_inner_microstep: 208.71 | bwd_allreduce_microstep: 0.08 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1888 +[2025-05-02 01:26:06,528] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.31 | bwd_microstep: 274.42 | bwd_inner_microstep: 274.40 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-02 01:26:07,009] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.87 | bwd_microstep: 273.17 | bwd_inner_microstep: 273.15 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 01:26:07,488] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.50 | bwd_microstep: 272.51 | bwd_inner_microstep: 272.50 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 840 +[2025-05-02 01:26:07,735] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 96.58 | bwd_microstep: 132.37 | bwd_inner_microstep: 132.18 | bwd_allreduce_microstep: 0.08 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:26:08,215] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.30 | bwd_microstep: 271.75 | bwd_inner_microstep: 271.73 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 325 +[2025-05-02 01:26:08,428] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 79.38 | bwd_microstep: 118.57 | bwd_inner_microstep: 118.31 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:26:08,906] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.85 | bwd_microstep: 272.69 | bwd_inner_microstep: 272.68 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:26:09,384] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.78 | bwd_microstep: 271.37 | bwd_inner_microstep: 271.36 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 318 +[2025-05-02 01:26:09,606] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 80.68 | bwd_microstep: 127.18 | bwd_inner_microstep: 126.88 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:26:10,080] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.41 | bwd_microstep: 271.17 | bwd_inner_microstep: 271.16 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 01:26:10,554] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.46 | bwd_microstep: 270.80 | bwd_inner_microstep: 270.78 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 01:26:11,119] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.17 | optimizer_step: 16.71 +[2025-05-02 01:26:11,119] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.49 | bwd_microstep: 338.48 | bwd_inner_microstep: 271.44 | bwd_allreduce_microstep: 67.00 | step_microstep: 23.96 +[2025-05-02 01:26:11,120] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2686.96 | bwd: 3992.12 | bwd_inner: 3924.03 | bwd_allreduce: 67.47 | step: 24.86 + 14%|█▎ | 1179/8720 [3:10:44<14:33:38, 6.95s/it] {'loss': 0.58, 'grad_norm': 7.509927272796631, 'learning_rate': 9.712763000401753e-06, 'epoch': 1.35} + 14%|█▎ | 1179/8720 [3:10:44<14:33:38, 6.95s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 01:26:11,599] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.01 | bwd_microstep: 270.50 | bwd_inner_microstep: 270.48 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1286 +[2025-05-02 01:26:11,948] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 134.55 | bwd_microstep: 200.02 | bwd_inner_microstep: 199.80 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1946 +[2025-05-02 01:26:12,448] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.95 | bwd_microstep: 288.61 | bwd_inner_microstep: 288.59 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-02 01:26:12,926] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.90 | bwd_microstep: 274.01 | bwd_inner_microstep: 273.99 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.13 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 01:26:13,405] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.67 | bwd_microstep: 272.88 | bwd_inner_microstep: 272.87 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-02 01:26:13,885] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.23 | bwd_microstep: 273.70 | bwd_inner_microstep: 273.69 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 337 +[2025-05-02 01:26:14,107] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 83.59 | bwd_microstep: 124.67 | bwd_inner_microstep: 124.50 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 01:26:14,586] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.60 | bwd_microstep: 272.87 | bwd_inner_microstep: 272.85 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:26:15,066] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.00 | bwd_microstep: 272.68 | bwd_inner_microstep: 272.66 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:26:15,546] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.78 | bwd_microstep: 272.71 | bwd_inner_microstep: 272.69 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 01:26:16,028] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.92 | bwd_microstep: 272.64 | bwd_inner_microstep: 272.62 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 844 +[2025-05-02 01:26:16,280] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 100.27 | bwd_microstep: 131.94 | bwd_inner_microstep: 131.84 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:26:16,756] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.60 | bwd_microstep: 271.28 | bwd_inner_microstep: 271.26 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 01:26:17,235] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.88 | bwd_microstep: 271.12 | bwd_inner_microstep: 271.10 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:26:17,714] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.97 | bwd_microstep: 272.11 | bwd_inner_microstep: 272.10 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 01:26:18,302] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.19 | optimizer_step: 16.64 +[2025-05-02 01:26:18,303] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.02 | bwd_microstep: 353.34 | bwd_inner_microstep: 271.61 | bwd_allreduce_microstep: 81.67 | step_microstep: 24.59 +[2025-05-02 01:26:18,304] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2775.59 | bwd: 4095.14 | bwd_inner: 4012.72 | bwd_allreduce: 81.98 | step: 25.61 + 14%|█▎ | 1180/8720 [3:10:52<14:42:20, 7.02s/it] {'loss': 0.9738, 'grad_norm': 7.918092250823975, 'learning_rate': 9.71214227247937e-06, 'epoch': 1.35} + 14%|█▎ | 1180/8720 [3:10:52<14:42:20, 7.02s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1850 +[2025-05-02 01:26:18,785] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.35 | bwd_microstep: 270.66 | bwd_inner_microstep: 270.65 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2142 +[2025-05-02 01:26:19,323] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 205.03 | bwd_microstep: 314.92 | bwd_inner_microstep: 314.90 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2103 +[2025-05-02 01:26:19,855] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 203.51 | bwd_microstep: 310.58 | bwd_inner_microstep: 310.57 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-02 01:26:20,333] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.62 | bwd_microstep: 273.95 | bwd_inner_microstep: 273.93 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-02 01:26:20,811] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.05 | bwd_microstep: 273.34 | bwd_inner_microstep: 273.33 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1368 +[2025-05-02 01:26:21,176] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.85 | bwd_microstep: 207.21 | bwd_inner_microstep: 207.09 | bwd_allreduce_microstep: 0.08 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-02 01:26:21,658] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.20 | bwd_microstep: 273.46 | bwd_inner_microstep: 273.44 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 01:26:22,138] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.94 | bwd_microstep: 273.02 | bwd_inner_microstep: 273.00 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 01:26:22,617] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.64 | bwd_microstep: 272.70 | bwd_inner_microstep: 272.68 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:26:23,097] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.45 | bwd_microstep: 272.31 | bwd_inner_microstep: 272.29 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:26:23,576] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.00 | bwd_microstep: 272.52 | bwd_inner_microstep: 272.50 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.14 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:26:24,055] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.28 | bwd_microstep: 272.18 | bwd_inner_microstep: 272.16 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:26:24,535] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.30 | bwd_microstep: 272.30 | bwd_inner_microstep: 272.29 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:26:25,015] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.95 | bwd_microstep: 272.20 | bwd_inner_microstep: 272.19 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1342 +[2025-05-02 01:26:25,377] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.30 | bwd_microstep: 204.43 | bwd_inner_microstep: 204.41 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 422 +[2025-05-02 01:26:25,724] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.24 | optimizer_step: 16.90 +[2025-05-02 01:26:25,724] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.67 | bwd_microstep: 211.65 | bwd_inner_microstep: 133.84 | bwd_allreduce_microstep: 77.71 | step_microstep: 24.94 +[2025-05-02 01:26:25,726] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2854.77 | bwd: 4247.47 | bwd_inner: 4169.29 | bwd_allreduce: 77.87 | step: 25.93 + 14%|█▎ | 1181/8720 [3:10:59<14:57:18, 7.14s/it] {'loss': 0.7295, 'grad_norm': 8.805668830871582, 'learning_rate': 9.711520894453087e-06, 'epoch': 1.35} + 14%|█▎ | 1181/8720 [3:10:59<14:57:18, 7.14s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1899 +[2025-05-02 01:26:26,213] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.82 | bwd_microstep: 274.59 | bwd_inner_microstep: 274.58 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2053 +[2025-05-02 01:26:26,734] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 202.37 | bwd_microstep: 301.18 | bwd_inner_microstep: 301.16 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1994 +[2025-05-02 01:26:27,240] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 196.64 | bwd_microstep: 294.01 | bwd_inner_microstep: 293.99 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 383 +[2025-05-02 01:26:27,440] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 67.83 | bwd_microstep: 118.30 | bwd_inner_microstep: 117.98 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1909 +[2025-05-02 01:26:27,920] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.01 | bwd_microstep: 276.34 | bwd_inner_microstep: 276.32 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1911 +[2025-05-02 01:26:28,402] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.55 | bwd_microstep: 276.51 | bwd_inner_microstep: 276.49 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 371 +[2025-05-02 01:26:28,602] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 67.76 | bwd_microstep: 117.91 | bwd_inner_microstep: 117.66 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1895 +[2025-05-02 01:26:29,082] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.40 | bwd_microstep: 275.15 | bwd_inner_microstep: 275.14 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 344 +[2025-05-02 01:26:29,292] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 72.67 | bwd_microstep: 123.54 | bwd_inner_microstep: 123.40 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 01:26:29,767] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.34 | bwd_microstep: 272.89 | bwd_inner_microstep: 272.87 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 01:26:30,243] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.75 | bwd_microstep: 272.74 | bwd_inner_microstep: 272.73 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 320 +[2025-05-02 01:26:30,444] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 68.25 | bwd_microstep: 118.90 | bwd_inner_microstep: 118.73 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:26:30,920] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.21 | bwd_microstep: 272.52 | bwd_inner_microstep: 272.50 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:26:31,396] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.50 | bwd_microstep: 271.26 | bwd_inner_microstep: 271.24 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 01:26:31,870] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.89 | bwd_microstep: 271.26 | bwd_inner_microstep: 271.24 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:26:32,434] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.08 | optimizer_step: 16.47 +[2025-05-02 01:26:32,434] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.12 | bwd_microstep: 338.22 | bwd_inner_microstep: 271.52 | bwd_allreduce_microstep: 66.66 | step_microstep: 23.53 +[2025-05-02 01:26:32,435] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2561.86 | bwd: 3875.37 | bwd_inner: 3807.75 | bwd_allreduce: 67.04 | step: 24.46 + 14%|█▎ | 1182/8720 [3:11:06<14:40:50, 7.01s/it] {'loss': 0.9513, 'grad_norm': 10.665440559387207, 'learning_rate': 9.710898866408626e-06, 'epoch': 1.36} + 14%|█▎ | 1182/8720 [3:11:06<14:40:50, 7.01s/it]dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1340 +[2025-05-02 01:26:32,799] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.48 | bwd_microstep: 203.71 | bwd_inner_microstep: 203.61 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1927 +[2025-05-02 01:26:33,296] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.42 | bwd_microstep: 287.19 | bwd_inner_microstep: 287.17 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1926 +[2025-05-02 01:26:33,793] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 194.92 | bwd_microstep: 287.56 | bwd_inner_microstep: 287.54 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1919 +[2025-05-02 01:26:34,276] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 191.51 | bwd_microstep: 276.59 | bwd_inner_microstep: 276.57 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 01:26:34,752] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.56 | bwd_microstep: 273.25 | bwd_inner_microstep: 273.24 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:26:35,228] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.15 | bwd_microstep: 272.54 | bwd_inner_microstep: 272.52 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 01:26:35,705] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.59 | bwd_microstep: 272.98 | bwd_inner_microstep: 272.97 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 01:26:36,181] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.52 | bwd_microstep: 272.75 | bwd_inner_microstep: 272.73 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:26:36,658] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.34 | bwd_microstep: 272.64 | bwd_inner_microstep: 272.62 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 01:26:37,135] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.78 | bwd_microstep: 273.02 | bwd_inner_microstep: 273.00 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:26:37,610] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.36 | bwd_microstep: 272.59 | bwd_inner_microstep: 272.57 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:26:38,087] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.17 | bwd_microstep: 272.38 | bwd_inner_microstep: 272.37 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 835 +[2025-05-02 01:26:38,317] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 90.57 | bwd_microstep: 125.90 | bwd_inner_microstep: 125.88 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:26:38,791] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.95 | bwd_microstep: 271.23 | bwd_inner_microstep: 271.21 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:26:39,264] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.67 | bwd_microstep: 270.96 | bwd_inner_microstep: 270.94 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:26:39,828] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.04 | optimizer_gradients: 2.11 | optimizer_step: 16.43 +[2025-05-02 01:26:39,828] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.13 | bwd_microstep: 337.34 | bwd_inner_microstep: 271.76 | bwd_allreduce_microstep: 65.54 | step_microstep: 23.41 +[2025-05-02 01:26:39,830] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2884.85 | bwd: 4242.65 | bwd_inner: 4176.70 | bwd_allreduce: 65.67 | step: 24.22 + 14%|█▎ | 1183/8720 [3:11:13<14:55:09, 7.13s/it] {'loss': 0.7887, 'grad_norm': 9.844825744628906, 'learning_rate': 9.71027618843181e-06, 'epoch': 1.36} + 14%|█▎ | 1183/8720 [3:11:13<14:55:09, 7.13s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:26:40,309] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.22 | bwd_microstep: 271.99 | bwd_inner_microstep: 271.97 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1888 +[2025-05-02 01:26:40,787] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.75 | bwd_microstep: 274.33 | bwd_inner_microstep: 274.31 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 345 +[2025-05-02 01:26:41,004] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 86.99 | bwd_microstep: 116.35 | bwd_inner_microstep: 116.13 | bwd_allreduce_microstep: 0.08 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-02 01:26:41,480] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.32 | bwd_microstep: 273.83 | bwd_inner_microstep: 273.81 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 01:26:41,960] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.43 | bwd_microstep: 273.55 | bwd_inner_microstep: 273.53 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 01:26:42,440] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.59 | bwd_microstep: 273.14 | bwd_inner_microstep: 273.12 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1096 +[2025-05-02 01:26:42,733] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 115.44 | bwd_microstep: 160.93 | bwd_inner_microstep: 160.75 | bwd_allreduce_microstep: 0.09 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 01:26:43,211] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.31 | bwd_microstep: 272.88 | bwd_inner_microstep: 272.87 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 01:26:43,688] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.27 | bwd_microstep: 272.67 | bwd_inner_microstep: 272.65 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:26:44,166] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.09 | bwd_microstep: 272.47 | bwd_inner_microstep: 272.46 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 01:26:44,646] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.16 | bwd_microstep: 272.67 | bwd_inner_microstep: 272.65 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 328 +[2025-05-02 01:26:44,876] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 92.99 | bwd_microstep: 118.23 | bwd_inner_microstep: 118.08 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 01:26:45,355] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.84 | bwd_microstep: 272.79 | bwd_inner_microstep: 272.77 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:26:45,835] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.67 | bwd_microstep: 271.16 | bwd_inner_microstep: 271.15 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:26:46,313] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.47 | bwd_microstep: 271.17 | bwd_inner_microstep: 271.15 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:26:46,890] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.08 | optimizer_step: 16.46 +[2025-05-02 01:26:46,890] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.23 | bwd_microstep: 348.12 | bwd_inner_microstep: 271.65 | bwd_allreduce_microstep: 76.43 | step_microstep: 23.47 +[2025-05-02 01:26:46,891] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2746.43 | bwd: 4016.35 | bwd_inner: 3939.11 | bwd_allreduce: 76.77 | step: 24.32 + 14%|█▎ | 1184/8720 [3:11:20<14:52:36, 7.11s/it] {'loss': 1.3118, 'grad_norm': 11.232419967651367, 'learning_rate': 9.70965286060854e-06, 'epoch': 1.36} + 14%|█▎ | 1184/8720 [3:11:20<14:52:36, 7.11s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1890 +[2025-05-02 01:26:47,374] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.26 | bwd_microstep: 274.26 | bwd_inner_microstep: 274.24 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1930 +[2025-05-02 01:26:47,874] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 197.13 | bwd_microstep: 287.72 | bwd_inner_microstep: 287.71 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 01:26:48,353] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.26 | bwd_microstep: 273.57 | bwd_inner_microstep: 273.55 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-02 01:26:48,830] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.08 | bwd_microstep: 273.56 | bwd_inner_microstep: 273.54 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 01:26:49,306] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.29 | bwd_microstep: 273.10 | bwd_inner_microstep: 273.09 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-02 01:26:49,783] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.90 | bwd_microstep: 273.04 | bwd_inner_microstep: 273.02 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 01:26:50,260] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.64 | bwd_microstep: 273.39 | bwd_inner_microstep: 273.38 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 331 +[2025-05-02 01:26:50,460] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 67.69 | bwd_microstep: 120.17 | bwd_inner_microstep: 120.03 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.09 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 838 +[2025-05-02 01:26:50,692] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 91.66 | bwd_microstep: 126.27 | bwd_inner_microstep: 126.25 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 843 +[2025-05-02 01:26:50,932] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.64 | bwd_microstep: 132.23 | bwd_inner_microstep: 131.96 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:26:51,408] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.04 | bwd_microstep: 272.65 | bwd_inner_microstep: 272.63 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 01:26:51,886] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.11 | bwd_microstep: 272.85 | bwd_inner_microstep: 272.83 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:26:52,362] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.06 | bwd_microstep: 272.43 | bwd_inner_microstep: 272.41 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 322 +[2025-05-02 01:26:52,572] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 80.73 | bwd_microstep: 116.45 | bwd_inner_microstep: 116.31 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 320 +[2025-05-02 01:26:52,773] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 68.68 | bwd_microstep: 118.30 | bwd_inner_microstep: 118.01 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:26:53,337] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.04 | optimizer_gradients: 2.09 | optimizer_step: 16.41 +[2025-05-02 01:26:53,337] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.46 | bwd_microstep: 339.40 | bwd_inner_microstep: 273.19 | bwd_allreduce_microstep: 66.17 | step_microstep: 23.27 +[2025-05-02 01:26:53,339] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2483.37 | bwd: 3699.46 | bwd_inner: 3632.28 | bwd_allreduce: 66.57 | step: 24.13 + 14%|█▎ | 1185/8720 [3:11:27<14:27:38, 6.91s/it] {'loss': 1.0275, 'grad_norm': 9.307294845581055, 'learning_rate': 9.709028883024817e-06, 'epoch': 1.36} + 14%|█▎ | 1185/8720 [3:11:27<14:27:38, 6.91s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:26:53,816] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.27 | bwd_microstep: 270.38 | bwd_inner_microstep: 270.36 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 419 +[2025-05-02 01:26:54,022] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 72.42 | bwd_microstep: 121.40 | bwd_inner_microstep: 121.14 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 360 +[2025-05-02 01:26:54,221] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 69.78 | bwd_microstep: 115.95 | bwd_inner_microstep: 115.64 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 01:26:54,697] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.63 | bwd_microstep: 273.77 | bwd_inner_microstep: 273.76 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1105 +[2025-05-02 01:26:54,989] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 116.09 | bwd_microstep: 161.89 | bwd_inner_microstep: 161.76 | bwd_allreduce_microstep: 0.10 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 01:26:55,465] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.25 | bwd_microstep: 273.00 | bwd_inner_microstep: 272.98 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 847 +[2025-05-02 01:26:55,706] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.78 | bwd_microstep: 132.41 | bwd_inner_microstep: 132.29 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:26:56,181] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.63 | bwd_microstep: 272.48 | bwd_inner_microstep: 272.46 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 834 +[2025-05-02 01:26:56,414] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 92.74 | bwd_microstep: 126.09 | bwd_inner_microstep: 125.94 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:26:56,895] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.01 | bwd_microstep: 272.56 | bwd_inner_microstep: 272.54 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 01:26:57,373] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.48 | bwd_microstep: 272.18 | bwd_inner_microstep: 272.16 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 321 +[2025-05-02 01:26:57,597] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 91.03 | bwd_microstep: 117.14 | bwd_inner_microstep: 116.82 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:26:58,076] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.25 | bwd_microstep: 272.11 | bwd_inner_microstep: 272.09 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 832 +[2025-05-02 01:26:58,317] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.41 | bwd_microstep: 130.07 | bwd_inner_microstep: 129.86 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:26:58,793] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.69 | bwd_microstep: 271.25 | bwd_inner_microstep: 271.23 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:26:59,377] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.12 | optimizer_step: 16.41 +[2025-05-02 01:26:59,377] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.43 | bwd_microstep: 354.59 | bwd_inner_microstep: 271.77 | bwd_allreduce_microstep: 82.77 | step_microstep: 24.01 +[2025-05-02 01:26:59,379] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2321.59 | bwd: 3437.39 | bwd_inner: 3353.01 | bwd_allreduce: 83.44 | step: 25.12 + 14%|█▎ | 1186/8720 [3:11:33<13:54:51, 6.65s/it] {'loss': 0.9061, 'grad_norm': 11.138641357421875, 'learning_rate': 9.708404255766726e-06, 'epoch': 1.36} + 14%|█▎ | 1186/8720 [3:11:33<13:54:51, 6.65s/it]dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1341 +[2025-05-02 01:26:59,746] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 142.16 | bwd_microstep: 203.73 | bwd_inner_microstep: 203.69 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1889 +[2025-05-02 01:27:00,227] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.87 | bwd_microstep: 274.77 | bwd_inner_microstep: 274.75 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1887 +[2025-05-02 01:27:00,708] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.16 | bwd_microstep: 274.61 | bwd_inner_microstep: 274.59 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-02 01:27:01,191] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.32 | bwd_microstep: 273.73 | bwd_inner_microstep: 273.71 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1355 +[2025-05-02 01:27:01,555] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.63 | bwd_microstep: 206.33 | bwd_inner_microstep: 206.24 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 844 +[2025-05-02 01:27:01,801] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 98.14 | bwd_microstep: 131.75 | bwd_inner_microstep: 131.73 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:27:02,276] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.56 | bwd_microstep: 272.56 | bwd_inner_microstep: 272.54 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 01:27:02,756] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.97 | bwd_microstep: 273.55 | bwd_inner_microstep: 273.53 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:27:03,234] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.46 | bwd_microstep: 271.67 | bwd_inner_microstep: 271.66 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 01:27:03,715] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.43 | bwd_microstep: 272.75 | bwd_inner_microstep: 272.73 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:27:04,195] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.91 | bwd_microstep: 273.09 | bwd_inner_microstep: 273.07 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 01:27:04,674] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.00 | bwd_microstep: 272.69 | bwd_inner_microstep: 272.67 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 835 +[2025-05-02 01:27:04,915] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.72 | bwd_microstep: 126.04 | bwd_inner_microstep: 125.83 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 01:27:05,394] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.94 | bwd_microstep: 272.82 | bwd_inner_microstep: 272.80 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:27:05,871] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.34 | bwd_microstep: 271.62 | bwd_inner_microstep: 271.60 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 01:27:06,439] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.06 | optimizer_step: 16.53 +[2025-05-02 01:27:06,439] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.36 | bwd_microstep: 339.19 | bwd_inner_microstep: 271.97 | bwd_allreduce_microstep: 67.17 | step_microstep: 23.71 +[2025-05-02 01:27:06,441] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2742.63 | bwd: 4010.94 | bwd_inner: 3943.13 | bwd_allreduce: 67.40 | step: 24.65 + 14%|█▎ | 1187/8720 [3:11:40<14:10:15, 6.77s/it] {'loss': 0.6113, 'grad_norm': 14.258207321166992, 'learning_rate': 9.70777897892044e-06, 'epoch': 1.36} + 14%|█▎ | 1187/8720 [3:11:40<14:10:15, 6.77s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1850 +[2025-05-02 01:27:06,918] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.45 | bwd_microstep: 270.18 | bwd_inner_microstep: 270.16 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.14 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1967 +[2025-05-02 01:27:07,421] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.96 | bwd_microstep: 291.05 | bwd_inner_microstep: 291.04 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1949 +[2025-05-02 01:27:07,920] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.44 | bwd_microstep: 289.38 | bwd_inner_microstep: 289.36 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 898 +[2025-05-02 01:27:08,178] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 99.83 | bwd_microstep: 143.78 | bwd_inner_microstep: 143.51 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1920 +[2025-05-02 01:27:08,658] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.40 | bwd_microstep: 276.36 | bwd_inner_microstep: 276.35 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1883 +[2025-05-02 01:27:09,137] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.86 | bwd_microstep: 273.89 | bwd_inner_microstep: 273.87 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 01:27:09,614] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.82 | bwd_microstep: 273.26 | bwd_inner_microstep: 273.24 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 01:27:10,092] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.49 | bwd_microstep: 273.10 | bwd_inner_microstep: 273.09 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:27:10,570] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.45 | bwd_microstep: 272.59 | bwd_inner_microstep: 272.57 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 01:27:11,048] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.95 | bwd_microstep: 273.00 | bwd_inner_microstep: 272.98 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 01:27:11,527] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.01 | bwd_microstep: 272.71 | bwd_inner_microstep: 272.69 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:27:12,007] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.87 | bwd_microstep: 272.50 | bwd_inner_microstep: 272.48 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 01:27:12,488] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.16 | bwd_microstep: 272.40 | bwd_inner_microstep: 272.39 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:27:12,972] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.95 | bwd_microstep: 272.15 | bwd_inner_microstep: 272.14 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:27:13,449] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.82 | bwd_microstep: 271.28 | bwd_inner_microstep: 271.26 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 01:27:14,028] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.13 | optimizer_step: 16.43 +[2025-05-02 01:27:14,029] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.95 | bwd_microstep: 347.29 | bwd_inner_microstep: 271.40 | bwd_allreduce_microstep: 75.85 | step_microstep: 24.08 +[2025-05-02 01:27:14,030] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2944.07 | bwd: 4344.98 | bwd_inner: 4268.55 | bwd_allreduce: 76.05 | step: 25.24 + 14%|█▎ | 1188/8720 [3:11:47<14:40:58, 7.02s/it] {'loss': 0.8845, 'grad_norm': 12.033834457397461, 'learning_rate': 9.707153052572229e-06, 'epoch': 1.36} + 14%|█▎ | 1188/8720 [3:11:47<14:40:58, 7.02s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 01:27:14,509] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.87 | bwd_microstep: 269.99 | bwd_inner_microstep: 269.97 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1961 +[2025-05-02 01:27:15,014] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 196.73 | bwd_microstep: 290.31 | bwd_inner_microstep: 290.29 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1234 +[2025-05-02 01:27:15,327] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 121.52 | bwd_microstep: 177.71 | bwd_inner_microstep: 177.56 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1931 +[2025-05-02 01:27:15,827] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 197.75 | bwd_microstep: 287.85 | bwd_inner_microstep: 287.83 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 01:27:16,304] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.30 | bwd_microstep: 273.27 | bwd_inner_microstep: 273.25 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:27:16,780] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.53 | bwd_microstep: 272.62 | bwd_inner_microstep: 272.60 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1354 +[2025-05-02 01:27:17,142] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.36 | bwd_microstep: 206.37 | bwd_inner_microstep: 206.23 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 01:27:17,619] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.06 | bwd_microstep: 272.82 | bwd_inner_microstep: 272.80 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 01:27:18,097] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.25 | bwd_microstep: 272.71 | bwd_inner_microstep: 272.69 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 839 +[2025-05-02 01:27:18,342] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 103.02 | bwd_microstep: 125.74 | bwd_inner_microstep: 125.59 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:27:18,821] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.37 | bwd_microstep: 272.33 | bwd_inner_microstep: 272.31 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 317 +[2025-05-02 01:27:19,039] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 79.56 | bwd_microstep: 122.86 | bwd_inner_microstep: 122.68 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.13 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:27:19,516] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.58 | bwd_microstep: 271.21 | bwd_inner_microstep: 271.20 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 320 +[2025-05-02 01:27:19,738] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 83.37 | bwd_microstep: 121.99 | bwd_inner_microstep: 121.80 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:27:20,214] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.99 | bwd_microstep: 271.07 | bwd_inner_microstep: 271.05 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:27:20,792] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.15 | optimizer_step: 16.67 +[2025-05-02 01:27:20,792] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.49 | bwd_microstep: 348.06 | bwd_inner_microstep: 271.57 | bwd_allreduce_microstep: 76.44 | step_microstep: 24.53 +[2025-05-02 01:27:20,794] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2613.45 | bwd: 3857.00 | bwd_inner: 3779.51 | bwd_allreduce: 76.91 | step: 25.55 + 14%|█▎ | 1189/8720 [3:11:54<14:31:17, 6.94s/it] {'loss': 0.6719, 'grad_norm': 14.053651809692383, 'learning_rate': 9.706526476808443e-06, 'epoch': 1.36} + 14%|█▎ | 1189/8720 [3:11:54<14:31:17, 6.94s/it]dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1342 +[2025-05-02 01:27:21,160] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.11 | bwd_microstep: 203.61 | bwd_inner_microstep: 203.53 | bwd_allreduce_microstep: 0.03 | step_microstep: 0.10 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 843 +[2025-05-02 01:27:21,400] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 92.70 | bwd_microstep: 132.02 | bwd_inner_microstep: 131.95 | bwd_allreduce_microstep: 0.04 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-02 01:27:21,877] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.08 | bwd_microstep: 273.65 | bwd_inner_microstep: 273.63 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1356 +[2025-05-02 01:27:22,241] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.78 | bwd_microstep: 205.90 | bwd_inner_microstep: 205.88 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 01:27:22,718] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.26 | bwd_microstep: 273.07 | bwd_inner_microstep: 273.06 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:27:23,196] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.27 | bwd_microstep: 272.73 | bwd_inner_microstep: 272.71 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 01:27:23,672] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.89 | bwd_microstep: 273.03 | bwd_inner_microstep: 273.01 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:27:24,148] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.41 | bwd_microstep: 272.50 | bwd_inner_microstep: 272.48 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:27:24,624] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.43 | bwd_microstep: 272.51 | bwd_inner_microstep: 272.48 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 327 +[2025-05-02 01:27:24,842] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 81.50 | bwd_microstep: 122.10 | bwd_inner_microstep: 121.83 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:27:25,319] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.09 | bwd_microstep: 272.52 | bwd_inner_microstep: 272.51 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:27:25,794] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.71 | bwd_microstep: 271.95 | bwd_inner_microstep: 271.93 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:27:26,268] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.21 | bwd_microstep: 272.16 | bwd_inner_microstep: 272.14 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:27:26,743] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.93 | bwd_microstep: 271.30 | bwd_inner_microstep: 271.28 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:27:27,217] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.32 | bwd_microstep: 270.97 | bwd_inner_microstep: 270.96 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1086 +[2025-05-02 01:27:27,596] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.20 | optimizer_step: 16.59 +[2025-05-02 01:27:27,597] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 114.33 | bwd_microstep: 226.59 | bwd_inner_microstep: 160.06 | bwd_allreduce_microstep: 66.38 | step_microstep: 23.82 +[2025-05-02 01:27:27,598] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2636.74 | bwd: 3886.68 | bwd_inner: 3819.59 | bwd_allreduce: 66.62 | step: 24.61 + 14%|█▎ | 1190/8720 [3:12:01<14:25:56, 6.90s/it] {'loss': 0.867, 'grad_norm': 12.386037826538086, 'learning_rate': 9.70589925171553e-06, 'epoch': 1.36} + 14%|█▎ | 1190/8720 [3:12:01<14:25:56, 6.90s/it]dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1134 +[2025-05-02 01:27:27,899] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 118.13 | bwd_microstep: 163.54 | bwd_inner_microstep: 163.49 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1923 +[2025-05-02 01:27:28,396] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 194.58 | bwd_microstep: 286.70 | bwd_inner_microstep: 286.68 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1920 +[2025-05-02 01:27:28,876] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.07 | bwd_microstep: 276.21 | bwd_inner_microstep: 276.20 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1896 +[2025-05-02 01:27:29,355] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.52 | bwd_microstep: 274.64 | bwd_inner_microstep: 274.62 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 346 +[2025-05-02 01:27:29,556] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 71.29 | bwd_microstep: 116.73 | bwd_inner_microstep: 116.47 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1895 +[2025-05-02 01:27:30,034] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.19 | bwd_microstep: 274.82 | bwd_inner_microstep: 274.80 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 01:27:30,510] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.60 | bwd_microstep: 273.38 | bwd_inner_microstep: 273.36 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 846 +[2025-05-02 01:27:30,753] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 96.02 | bwd_microstep: 132.32 | bwd_inner_microstep: 132.05 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-02 01:27:31,231] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.13 | bwd_microstep: 273.46 | bwd_inner_microstep: 273.44 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 01:27:31,708] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.58 | bwd_microstep: 272.94 | bwd_inner_microstep: 272.93 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 01:27:32,184] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.46 | bwd_microstep: 272.66 | bwd_inner_microstep: 272.65 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1109 +[2025-05-02 01:27:32,478] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 115.98 | bwd_microstep: 161.97 | bwd_inner_microstep: 161.93 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:27:32,954] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.97 | bwd_microstep: 272.53 | bwd_inner_microstep: 272.51 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 326 +[2025-05-02 01:27:33,174] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 84.99 | bwd_microstep: 120.58 | bwd_inner_microstep: 120.39 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:27:33,650] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.43 | bwd_microstep: 272.27 | bwd_inner_microstep: 272.25 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 01:27:34,233] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.19 | optimizer_step: 16.63 +[2025-05-02 01:27:34,234] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.75 | bwd_microstep: 351.10 | bwd_inner_microstep: 272.61 | bwd_allreduce_microstep: 78.44 | step_microstep: 24.53 +[2025-05-02 01:27:34,235] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2561.40 | bwd: 3795.92 | bwd_inner: 3716.51 | bwd_allreduce: 78.81 | step: 25.47 + 14%|█▎ | 1191/8720 [3:12:07<14:16:00, 6.82s/it] {'loss': 0.9575, 'grad_norm': 6.183663845062256, 'learning_rate': 9.705271377380026e-06, 'epoch': 1.37} + 14%|█▎ | 1191/8720 [3:12:07<14:16:00, 6.82s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:27:34,717] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.42 | bwd_microstep: 270.52 | bwd_inner_microstep: 270.50 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1385 +[2025-05-02 01:27:35,086] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 142.27 | bwd_microstep: 208.26 | bwd_inner_microstep: 208.24 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.11 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 867 +[2025-05-02 01:27:35,333] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.61 | bwd_microstep: 133.86 | bwd_inner_microstep: 133.82 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-02 01:27:35,813] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.40 | bwd_microstep: 273.97 | bwd_inner_microstep: 273.96 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 01:27:36,292] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.99 | bwd_microstep: 272.58 | bwd_inner_microstep: 272.57 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 01:27:36,767] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.75 | bwd_microstep: 272.55 | bwd_inner_microstep: 272.53 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 01:27:37,245] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.48 | bwd_microstep: 273.06 | bwd_inner_microstep: 273.04 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 01:27:37,722] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.55 | bwd_microstep: 273.54 | bwd_inner_microstep: 273.52 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:27:38,199] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.67 | bwd_microstep: 272.27 | bwd_inner_microstep: 272.25 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 01:27:38,677] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.01 | bwd_microstep: 272.79 | bwd_inner_microstep: 272.78 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:27:39,153] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.41 | bwd_microstep: 272.34 | bwd_inner_microstep: 272.32 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:27:39,630] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.87 | bwd_microstep: 272.33 | bwd_inner_microstep: 272.31 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:27:40,104] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.27 | bwd_microstep: 271.12 | bwd_inner_microstep: 271.10 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 318 +[2025-05-02 01:27:40,320] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 79.07 | bwd_microstep: 121.63 | bwd_inner_microstep: 121.32 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:27:40,794] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.57 | bwd_microstep: 271.27 | bwd_inner_microstep: 271.25 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 01:27:41,358] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.14 | optimizer_step: 16.64 +[2025-05-02 01:27:41,358] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.45 | bwd_microstep: 337.69 | bwd_inner_microstep: 271.37 | bwd_allreduce_microstep: 66.28 | step_microstep: 23.86 +[2025-05-02 01:27:41,360] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2761.48 | bwd: 4069.85 | bwd_inner: 4002.94 | bwd_allreduce: 66.48 | step: 24.71 + 14%|█▎ | 1192/8720 [3:12:15<14:27:13, 6.91s/it] {'loss': 0.5367, 'grad_norm': 6.473178863525391, 'learning_rate': 9.704642853888549e-06, 'epoch': 1.37} + 14%|█▎ | 1192/8720 [3:12:15<14:27:13, 6.91s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1888 +[2025-05-02 01:27:41,842] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.91 | bwd_microstep: 273.70 | bwd_inner_microstep: 273.68 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1915 +[2025-05-02 01:27:42,324] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.04 | bwd_microstep: 276.49 | bwd_inner_microstep: 276.47 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-02 01:27:42,802] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.92 | bwd_microstep: 273.90 | bwd_inner_microstep: 273.88 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 01:27:43,279] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.79 | bwd_microstep: 273.14 | bwd_inner_microstep: 273.13 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 01:27:43,756] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.02 | bwd_microstep: 273.09 | bwd_inner_microstep: 273.07 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-02 01:27:44,234] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.97 | bwd_microstep: 273.04 | bwd_inner_microstep: 273.02 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 01:27:44,711] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.57 | bwd_microstep: 273.42 | bwd_inner_microstep: 273.40 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:27:45,187] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.03 | bwd_microstep: 272.42 | bwd_inner_microstep: 272.40 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 01:27:45,663] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.80 | bwd_microstep: 272.85 | bwd_inner_microstep: 272.83 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:27:46,139] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.20 | bwd_microstep: 272.32 | bwd_inner_microstep: 272.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:27:46,616] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.72 | bwd_microstep: 272.49 | bwd_inner_microstep: 272.47 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:27:47,092] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.33 | bwd_microstep: 272.53 | bwd_inner_microstep: 272.51 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 832 +[2025-05-02 01:27:47,329] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 92.66 | bwd_microstep: 130.23 | bwd_inner_microstep: 129.96 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:27:47,803] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.07 | bwd_microstep: 271.06 | bwd_inner_microstep: 271.04 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:27:48,278] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.71 | bwd_microstep: 271.12 | bwd_inner_microstep: 271.11 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 01:27:48,842] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.04 | optimizer_gradients: 2.07 | optimizer_step: 16.41 +[2025-05-02 01:27:48,843] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.66 | bwd_microstep: 337.65 | bwd_inner_microstep: 271.60 | bwd_allreduce_microstep: 66.00 | step_microstep: 23.37 +[2025-05-02 01:27:48,844] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2921.13 | bwd: 4289.46 | bwd_inner: 4222.93 | bwd_allreduce: 66.19 | step: 24.19 + 14%|█▎ | 1193/8720 [3:12:22<14:48:38, 7.08s/it] {'loss': 0.7454, 'grad_norm': 6.450857639312744, 'learning_rate': 9.704013681327817e-06, 'epoch': 1.37} + 14%|█▎ | 1193/8720 [3:12:22<14:48:38, 7.08s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:27:49,321] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.53 | bwd_microstep: 270.37 | bwd_inner_microstep: 270.36 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1957 +[2025-05-02 01:27:49,823] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 196.23 | bwd_microstep: 289.63 | bwd_inner_microstep: 289.61 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1903 +[2025-05-02 01:27:50,303] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.32 | bwd_microstep: 275.63 | bwd_inner_microstep: 275.61 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-02 01:27:50,781] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.54 | bwd_microstep: 273.78 | bwd_inner_microstep: 273.76 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 01:27:51,258] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.92 | bwd_microstep: 272.62 | bwd_inner_microstep: 272.60 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 01:27:51,735] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.75 | bwd_microstep: 272.74 | bwd_inner_microstep: 272.72 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 01:27:52,215] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.61 | bwd_microstep: 272.93 | bwd_inner_microstep: 272.92 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 01:27:52,695] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.82 | bwd_microstep: 273.10 | bwd_inner_microstep: 273.09 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 01:27:53,175] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.38 | bwd_microstep: 272.82 | bwd_inner_microstep: 272.80 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:27:53,654] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.78 | bwd_microstep: 272.57 | bwd_inner_microstep: 272.56 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:27:54,133] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.53 | bwd_microstep: 271.36 | bwd_inner_microstep: 271.35 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:27:54,612] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.95 | bwd_microstep: 272.25 | bwd_inner_microstep: 272.24 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 01:27:55,090] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.59 | bwd_microstep: 271.14 | bwd_inner_microstep: 271.13 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:27:55,570] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.36 | bwd_microstep: 271.20 | bwd_inner_microstep: 271.18 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 01:27:56,048] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.86 | bwd_microstep: 271.12 | bwd_inner_microstep: 271.10 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:27:56,631] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.12 | optimizer_step: 16.42 +[2025-05-02 01:27:56,632] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.71 | bwd_microstep: 354.67 | bwd_inner_microstep: 271.79 | bwd_allreduce_microstep: 82.82 | step_microstep: 24.11 +[2025-05-02 01:27:56,633] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 3026.55 | bwd: 4457.96 | bwd_inner: 4374.82 | bwd_allreduce: 82.91 | step: 24.98 + 14%|█▎ | 1194/8720 [3:12:30<15:15:08, 7.30s/it] {'loss': 0.8822, 'grad_norm': 11.338871002197266, 'learning_rate': 9.703383859784631e-06, 'epoch': 1.37} + 14%|█▎ | 1194/8720 [3:12:30<15:15:08, 7.30s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1940 +[2025-05-02 01:27:57,141] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 197.87 | bwd_microstep: 287.49 | bwd_inner_microstep: 287.47 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1899 +[2025-05-02 01:27:57,622] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.96 | bwd_microstep: 274.91 | bwd_inner_microstep: 274.89 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1903 +[2025-05-02 01:27:58,105] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.09 | bwd_microstep: 275.37 | bwd_inner_microstep: 275.35 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1893 +[2025-05-02 01:27:58,586] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.43 | bwd_microstep: 274.59 | bwd_inner_microstep: 274.57 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1887 +[2025-05-02 01:27:59,066] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.60 | bwd_microstep: 274.76 | bwd_inner_microstep: 274.74 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1358 +[2025-05-02 01:27:59,430] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.59 | bwd_microstep: 206.44 | bwd_inner_microstep: 206.42 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 01:27:59,907] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.60 | bwd_microstep: 273.32 | bwd_inner_microstep: 273.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-02 01:28:00,386] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.44 | bwd_microstep: 274.36 | bwd_inner_microstep: 274.34 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 01:28:00,863] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.67 | bwd_microstep: 273.46 | bwd_inner_microstep: 273.44 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 01:28:01,339] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.40 | bwd_microstep: 273.52 | bwd_inner_microstep: 273.50 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:28:01,816] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.67 | bwd_microstep: 273.04 | bwd_inner_microstep: 273.03 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:28:02,293] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.55 | bwd_microstep: 273.21 | bwd_inner_microstep: 273.20 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 326 +[2025-05-02 01:28:02,503] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 77.28 | bwd_microstep: 118.43 | bwd_inner_microstep: 118.30 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:28:02,979] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.38 | bwd_microstep: 272.80 | bwd_inner_microstep: 272.79 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1345 +[2025-05-02 01:28:03,339] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.41 | bwd_microstep: 205.10 | bwd_inner_microstep: 205.08 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 829 +[2025-05-02 01:28:03,664] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.09 | optimizer_step: 16.37 +[2025-05-02 01:28:03,665] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 91.86 | bwd_microstep: 196.57 | bwd_inner_microstep: 130.13 | bwd_allreduce_microstep: 66.36 | step_microstep: 23.31 +[2025-05-02 01:28:03,666] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2724.52 | bwd: 4027.40 | bwd_inner: 3960.61 | bwd_allreduce: 66.47 | step: 24.18 + 14%|█▎ | 1195/8720 [3:12:37<15:05:03, 7.22s/it] {'loss': 0.9716, 'grad_norm': 10.64245891571045, 'learning_rate': 9.702753389345887e-06, 'epoch': 1.37} + 14%|█▎ | 1195/8720 [3:12:37<15:05:03, 7.22s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:28:04,144] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.89 | bwd_microstep: 270.67 | bwd_inner_microstep: 270.65 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 987 +[2025-05-02 01:28:04,411] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 103.69 | bwd_microstep: 149.83 | bwd_inner_microstep: 149.81 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1890 +[2025-05-02 01:28:04,891] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.15 | bwd_microstep: 274.87 | bwd_inner_microstep: 274.85 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1892 +[2025-05-02 01:28:05,370] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.92 | bwd_microstep: 274.97 | bwd_inner_microstep: 274.96 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-02 01:28:05,848] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.26 | bwd_microstep: 273.55 | bwd_inner_microstep: 273.53 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1883 +[2025-05-02 01:28:06,326] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.73 | bwd_microstep: 274.56 | bwd_inner_microstep: 274.54 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1361 +[2025-05-02 01:28:06,688] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.87 | bwd_microstep: 206.67 | bwd_inner_microstep: 206.54 | bwd_allreduce_microstep: 0.04 | step_microstep: 0.09 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 332 +[2025-05-02 01:28:06,888] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 67.26 | bwd_microstep: 119.42 | bwd_inner_microstep: 119.28 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:28:07,364] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.68 | bwd_microstep: 272.54 | bwd_inner_microstep: 272.52 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:28:07,839] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.18 | bwd_microstep: 272.43 | bwd_inner_microstep: 272.41 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1353 +[2025-05-02 01:28:08,203] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 139.93 | bwd_microstep: 205.98 | bwd_inner_microstep: 205.84 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.09 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 323 +[2025-05-02 01:28:08,411] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 77.26 | bwd_microstep: 118.10 | bwd_inner_microstep: 117.77 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 01:28:08,888] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.28 | bwd_microstep: 272.83 | bwd_inner_microstep: 272.81 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 01:28:09,364] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.35 | bwd_microstep: 272.79 | bwd_inner_microstep: 272.77 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:28:09,838] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.95 | bwd_microstep: 272.20 | bwd_inner_microstep: 272.18 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:28:10,401] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.04 | optimizer_gradients: 2.07 | optimizer_step: 16.37 +[2025-05-02 01:28:10,402] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.91 | bwd_microstep: 337.92 | bwd_inner_microstep: 271.62 | bwd_allreduce_microstep: 66.26 | step_microstep: 23.75 +[2025-05-02 01:28:10,403] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2601.04 | bwd: 3869.39 | bwd_inner: 3802.20 | bwd_allreduce: 66.68 | step: 24.71 + 14%|█▎ | 1196/8720 [3:12:44<14:46:54, 7.07s/it] {'loss': 0.6829, 'grad_norm': 5.477819442749023, 'learning_rate': 9.70212227009856e-06, 'epoch': 1.37} + 14%|█▎ | 1196/8720 [3:12:44<14:46:54, 7.07s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:28:10,881] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.75 | bwd_microstep: 270.55 | bwd_inner_microstep: 270.53 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1759 +[2025-05-02 01:28:11,312] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 160.68 | bwd_microstep: 255.70 | bwd_inner_microstep: 255.68 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1387 +[2025-05-02 01:28:11,677] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 142.64 | bwd_microstep: 208.84 | bwd_inner_microstep: 208.82 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1886 +[2025-05-02 01:28:12,155] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.52 | bwd_microstep: 274.16 | bwd_inner_microstep: 274.15 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 01:28:12,634] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.70 | bwd_microstep: 273.09 | bwd_inner_microstep: 273.07 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 01:28:13,114] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.77 | bwd_microstep: 272.63 | bwd_inner_microstep: 272.62 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 01:28:13,596] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.57 | bwd_microstep: 273.22 | bwd_inner_microstep: 273.20 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 333 +[2025-05-02 01:28:13,815] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 82.88 | bwd_microstep: 119.50 | bwd_inner_microstep: 119.18 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 326 +[2025-05-02 01:28:14,028] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 78.58 | bwd_microstep: 119.04 | bwd_inner_microstep: 118.86 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:28:14,507] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.61 | bwd_microstep: 272.46 | bwd_inner_microstep: 272.45 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 01:28:14,986] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.14 | bwd_microstep: 272.69 | bwd_inner_microstep: 272.67 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:28:15,465] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.63 | bwd_microstep: 272.63 | bwd_inner_microstep: 272.61 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 01:28:15,941] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.40 | bwd_microstep: 272.71 | bwd_inner_microstep: 272.70 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 01:28:16,419] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.14 | bwd_microstep: 272.73 | bwd_inner_microstep: 272.71 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1348 +[2025-05-02 01:28:16,784] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.08 | bwd_microstep: 205.29 | bwd_inner_microstep: 205.23 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:28:17,366] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.09 | optimizer_step: 16.43 +[2025-05-02 01:28:17,366] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.15 | bwd_microstep: 352.50 | bwd_inner_microstep: 272.69 | bwd_allreduce_microstep: 79.76 | step_microstep: 24.17 +[2025-05-02 01:28:17,367] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2678.93 | bwd: 3987.82 | bwd_inner: 3907.30 | bwd_allreduce: 80.05 | step: 25.17 + 14%|█▎ | 1197/8720 [3:12:51<14:42:47, 7.04s/it] {'loss': 1.0039, 'grad_norm': 8.504487991333008, 'learning_rate': 9.701490502129726e-06, 'epoch': 1.37} + 14%|█▎ | 1197/8720 [3:12:51<14:42:47, 7.04s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1939 +[2025-05-02 01:28:17,875] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 197.18 | bwd_microstep: 287.35 | bwd_inner_microstep: 287.33 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1907 +[2025-05-02 01:28:18,356] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.93 | bwd_microstep: 275.63 | bwd_inner_microstep: 275.61 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-02 01:28:18,837] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.50 | bwd_microstep: 273.92 | bwd_inner_microstep: 273.90 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 01:28:19,318] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.08 | bwd_microstep: 273.05 | bwd_inner_microstep: 273.03 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 01:28:19,797] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.10 | bwd_microstep: 272.76 | bwd_inner_microstep: 272.74 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 01:28:20,275] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.00 | bwd_microstep: 272.42 | bwd_inner_microstep: 272.40 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 01:28:20,756] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.82 | bwd_microstep: 273.02 | bwd_inner_microstep: 273.00 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 834 +[2025-05-02 01:28:20,997] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 98.19 | bwd_microstep: 125.27 | bwd_inner_microstep: 125.21 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 01:28:21,476] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.45 | bwd_microstep: 272.06 | bwd_inner_microstep: 272.04 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 321 +[2025-05-02 01:28:21,697] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 90.89 | bwd_microstep: 114.60 | bwd_inner_microstep: 114.45 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:28:22,173] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.98 | bwd_microstep: 272.33 | bwd_inner_microstep: 272.32 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:28:22,650] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.89 | bwd_microstep: 271.09 | bwd_inner_microstep: 271.07 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:28:23,126] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.26 | bwd_microstep: 271.19 | bwd_inner_microstep: 271.17 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 01:28:23,607] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.28 | bwd_microstep: 270.90 | bwd_inner_microstep: 270.88 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:28:24,086] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.69 | bwd_microstep: 271.05 | bwd_inner_microstep: 271.03 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 01:28:24,667] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.13 | optimizer_step: 16.46 +[2025-05-02 01:28:24,667] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.60 | bwd_microstep: 348.39 | bwd_inner_microstep: 271.37 | bwd_allreduce_microstep: 76.97 | step_microstep: 24.20 +[2025-05-02 01:28:24,669] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2831.45 | bwd: 4145.06 | bwd_inner: 4067.59 | bwd_allreduce: 77.13 | step: 25.24 + 14%|█▎ | 1198/8720 [3:12:58<14:52:27, 7.12s/it] {'loss': 0.8192, 'grad_norm': 6.262847900390625, 'learning_rate': 9.700858085526547e-06, 'epoch': 1.37} + 14%|█▎ | 1198/8720 [3:12:58<14:52:27, 7.12s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1958 +[2025-05-02 01:28:25,175] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.20 | bwd_microstep: 288.99 | bwd_inner_microstep: 288.98 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 967 +[2025-05-02 01:28:25,446] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 104.99 | bwd_microstep: 149.91 | bwd_inner_microstep: 149.77 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.09 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 435 +[2025-05-02 01:28:25,660] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 80.40 | bwd_microstep: 120.49 | bwd_inner_microstep: 120.25 | bwd_allreduce_microstep: 0.10 | step_microstep: 0.10 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 941 +[2025-05-02 01:28:25,927] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 104.01 | bwd_microstep: 147.66 | bwd_inner_microstep: 147.45 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1894 +[2025-05-02 01:28:26,406] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.30 | bwd_microstep: 274.89 | bwd_inner_microstep: 274.87 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-02 01:28:26,886] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.18 | bwd_microstep: 274.17 | bwd_inner_microstep: 274.15 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 01:28:27,365] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.41 | bwd_microstep: 273.04 | bwd_inner_microstep: 273.02 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 01:28:27,845] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.11 | bwd_microstep: 273.05 | bwd_inner_microstep: 273.03 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:28:28,324] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.56 | bwd_microstep: 272.29 | bwd_inner_microstep: 272.27 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 01:28:28,803] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.83 | bwd_microstep: 272.81 | bwd_inner_microstep: 272.79 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:28:29,282] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.65 | bwd_microstep: 272.52 | bwd_inner_microstep: 272.50 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:28:29,761] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.13 | bwd_microstep: 272.59 | bwd_inner_microstep: 272.57 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 01:28:30,242] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.05 | bwd_microstep: 272.82 | bwd_inner_microstep: 272.80 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:28:30,720] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.85 | bwd_microstep: 272.26 | bwd_inner_microstep: 272.24 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.16 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:28:31,201] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.83 | bwd_microstep: 272.28 | bwd_inner_microstep: 272.26 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:28:31,778] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.14 | optimizer_step: 16.41 +[2025-05-02 01:28:31,779] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.17 | bwd_microstep: 348.33 | bwd_inner_microstep: 271.52 | bwd_allreduce_microstep: 76.77 | step_microstep: 24.07 +[2025-05-02 01:28:31,780] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2751.35 | bwd: 4058.14 | bwd_inner: 3980.56 | bwd_allreduce: 77.10 | step: 25.27 + 14%|█▍ | 1199/8720 [3:13:05<14:52:03, 7.12s/it] {'loss': 0.7136, 'grad_norm': 4.249776363372803, 'learning_rate': 9.700225020376271e-06, 'epoch': 1.37} + 14%|█▍ | 1199/8720 [3:13:05<14:52:03, 7.12s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:28:32,261] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.15 | bwd_microstep: 270.50 | bwd_inner_microstep: 270.48 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1909 +[2025-05-02 01:28:32,745] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.15 | bwd_microstep: 276.31 | bwd_inner_microstep: 276.29 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 01:28:33,222] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.11 | bwd_microstep: 273.39 | bwd_inner_microstep: 273.37 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 343 +[2025-05-02 01:28:33,435] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 72.40 | bwd_microstep: 127.15 | bwd_inner_microstep: 126.95 | bwd_allreduce_microstep: 0.09 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-02 01:28:33,912] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.52 | bwd_microstep: 272.96 | bwd_inner_microstep: 272.95 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 01:28:34,390] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.91 | bwd_microstep: 273.04 | bwd_inner_microstep: 272.77 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 01:28:34,869] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.18 | bwd_microstep: 273.42 | bwd_inner_microstep: 273.41 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:28:35,347] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.61 | bwd_microstep: 271.93 | bwd_inner_microstep: 271.92 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 01:28:35,825] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.88 | bwd_microstep: 272.57 | bwd_inner_microstep: 272.55 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:28:36,303] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.32 | bwd_microstep: 272.35 | bwd_inner_microstep: 272.33 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 832 +[2025-05-02 01:28:36,544] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.90 | bwd_microstep: 130.44 | bwd_inner_microstep: 130.23 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 322 +[2025-05-02 01:28:36,763] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 83.71 | bwd_microstep: 119.37 | bwd_inner_microstep: 119.20 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:28:37,240] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.04 | bwd_microstep: 271.20 | bwd_inner_microstep: 271.18 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:28:37,717] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.60 | bwd_microstep: 271.13 | bwd_inner_microstep: 271.12 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1849 +[2025-05-02 01:28:38,195] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.02 | bwd_microstep: 270.65 | bwd_inner_microstep: 270.63 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2084 +[2025-05-02 01:28:38,824] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.18 | optimizer_step: 16.59 +[2025-05-02 01:28:38,824] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 203.80 | bwd_microstep: 381.81 | bwd_inner_microstep: 303.91 | bwd_allreduce_microstep: 77.85 | step_microstep: 24.63 +[2025-05-02 01:28:38,826] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2713.95 | bwd: 4028.33 | bwd_inner: 3949.38 | bwd_allreduce: 78.32 | step: 25.66 + 14%|█▍ | 1200/8720 [3:13:12<14:49:17, 7.10s/it] {'loss': 1.0529, 'grad_norm': 9.619600296020508, 'learning_rate': 9.699591306766238e-06, 'epoch': 1.38} + 14%|█▍ | 1200/8720 [3:13:12<14:49:17, 7.10s/it][INFO|trainer.py:3503] 2025-05-02 01:28:41,311 >> Saving model checkpoint to work_dirs/internvl_chat_v2_5/ak/checkpoint-1200 +[INFO|configuration_utils.py:472] 2025-05-02 01:28:41,315 >> Configuration saved in work_dirs/internvl_chat_v2_5/ak/checkpoint-1200/config.json +[INFO|configuration_utils.py:807] 2025-05-02 01:28:41,315 >> Configuration saved in work_dirs/internvl_chat_v2_5/ak/checkpoint-1200/generation_config.json +[INFO|modeling_utils.py:2755] 2025-05-02 01:28:46,460 >> Model weights saved in work_dirs/internvl_chat_v2_5/ak/checkpoint-1200/model.safetensors +[INFO|tokenization_utils_base.py:2702] 2025-05-02 01:28:46,462 >> tokenizer config file saved in work_dirs/internvl_chat_v2_5/ak/checkpoint-1200/tokenizer_config.json +[INFO|tokenization_utils_base.py:2711] 2025-05-02 01:28:46,462 >> Special tokens file saved in work_dirs/internvl_chat_v2_5/ak/checkpoint-1200/special_tokens_map.json +[INFO|tokenization_utils_base.py:2762] 2025-05-02 01:28:46,462 >> added tokens file saved in work_dirs/internvl_chat_v2_5/ak/checkpoint-1200/added_tokens.json +[2025-05-02 01:28:46,569] [INFO] [logging.py:96:log_dist] [Rank 0] [Torch] Checkpoint global_step1200 is about to be saved! +[2025-05-02 01:28:46,587] [INFO] [logging.py:96:log_dist] [Rank 0] Saving model checkpoint: work_dirs/internvl_chat_v2_5/ak/checkpoint-1200/global_step1200/mp_rank_00_model_states.pt +[2025-05-02 01:28:46,587] [INFO] [torch_checkpoint_engine.py:21:save] [Torch] Saving work_dirs/internvl_chat_v2_5/ak/checkpoint-1200/global_step1200/mp_rank_00_model_states.pt... +[2025-05-02 01:28:51,166] [INFO] [torch_checkpoint_engine.py:23:save] [Torch] Saved work_dirs/internvl_chat_v2_5/ak/checkpoint-1200/global_step1200/mp_rank_00_model_states.pt. +[2025-05-02 01:28:51,168] [INFO] [torch_checkpoint_engine.py:21:save] [Torch] Saving work_dirs/internvl_chat_v2_5/ak/checkpoint-1200/global_step1200/bf16_zero_pp_rank_0_mp_rank_00_optim_states.pt... +[2025-05-02 01:28:51,422] [INFO] [torch_checkpoint_engine.py:23:save] [Torch] Saved work_dirs/internvl_chat_v2_5/ak/checkpoint-1200/global_step1200/bf16_zero_pp_rank_0_mp_rank_00_optim_states.pt. +[2025-05-02 01:28:51,422] [INFO] [engine.py:3536:_save_zero_checkpoint] zero checkpoint saved work_dirs/internvl_chat_v2_5/ak/checkpoint-1200/global_step1200/bf16_zero_pp_rank_0_mp_rank_00_optim_states.pt +[2025-05-02 01:28:51,422] [INFO] [torch_checkpoint_engine.py:33:commit] [Torch] Checkpoint global_step1200 is ready now! +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 435 +[2025-05-02 01:28:51,669] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 72.57 | bwd_microstep: 135.52 | bwd_inner_microstep: 135.38 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.09 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 383 +[2025-05-02 01:28:51,869] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 68.60 | bwd_microstep: 118.17 | bwd_inner_microstep: 118.01 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 360 +[2025-05-02 01:28:52,080] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 75.02 | bwd_microstep: 122.02 | bwd_inner_microstep: 121.86 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-02 01:28:52,556] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.62 | bwd_microstep: 272.65 | bwd_inner_microstep: 272.63 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 01:28:53,032] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.80 | bwd_microstep: 271.48 | bwd_inner_microstep: 271.46 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 01:28:53,509] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.19 | bwd_microstep: 270.92 | bwd_inner_microstep: 270.91 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:28:53,987] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.98 | bwd_microstep: 270.55 | bwd_inner_microstep: 270.53 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:28:54,462] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.78 | bwd_microstep: 270.50 | bwd_inner_microstep: 270.48 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 01:28:54,938] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.33 | bwd_microstep: 270.80 | bwd_inner_microstep: 270.79 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:28:55,414] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.99 | bwd_microstep: 270.86 | bwd_inner_microstep: 270.84 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 01:28:55,892] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.06 | bwd_microstep: 271.32 | bwd_inner_microstep: 271.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:28:56,365] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.57 | bwd_microstep: 269.66 | bwd_inner_microstep: 269.64 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:28:56,840] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.92 | bwd_microstep: 269.25 | bwd_inner_microstep: 269.24 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 01:28:57,313] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.29 | bwd_microstep: 269.13 | bwd_inner_microstep: 269.11 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 01:28:57,788] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.67 | bwd_microstep: 269.30 | bwd_inner_microstep: 269.28 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 01:28:58,370] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.07 | optimizer_gradients: 2.20 | optimizer_step: 22.65 +[2025-05-02 01:28:58,371] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 185.86 | bwd_microstep: 347.46 | bwd_inner_microstep: 269.52 | bwd_allreduce_microstep: 77.88 | step_microstep: 31.06 +[2025-05-02 01:28:58,372] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2647.91 | bwd: 3969.66 | bwd_inner: 3891.12 | bwd_allreduce: 78.12 | step: 32.27 + 14%|█▍ | 1201/8720 [3:13:32<22:37:17, 10.83s/it] {'loss': 0.781, 'grad_norm': 12.469979286193848, 'learning_rate': 9.69895694478388e-06, 'epoch': 1.38} + 14%|█▍ | 1201/8720 [3:13:32<22:37:17, 10.83s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1908 +[2025-05-02 01:28:58,859] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.47 | bwd_microstep: 274.10 | bwd_inner_microstep: 274.08 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1902 +[2025-05-02 01:28:59,338] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.13 | bwd_microstep: 274.41 | bwd_inner_microstep: 274.40 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1896 +[2025-05-02 01:28:59,817] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.39 | bwd_microstep: 273.80 | bwd_inner_microstep: 273.78 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-02 01:29:00,295] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.82 | bwd_microstep: 272.57 | bwd_inner_microstep: 272.55 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1366 +[2025-05-02 01:29:00,658] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.24 | bwd_microstep: 205.90 | bwd_inner_microstep: 205.88 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 01:29:01,132] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.74 | bwd_microstep: 272.37 | bwd_inner_microstep: 272.36 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-02 01:29:01,608] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.78 | bwd_microstep: 272.70 | bwd_inner_microstep: 272.68 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:29:02,081] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.20 | bwd_microstep: 271.00 | bwd_inner_microstep: 270.98 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 01:29:02,555] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.21 | bwd_microstep: 271.82 | bwd_inner_microstep: 271.80 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:29:03,031] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.56 | bwd_microstep: 271.40 | bwd_inner_microstep: 271.38 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 01:29:03,509] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.80 | bwd_microstep: 271.19 | bwd_inner_microstep: 271.17 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:29:03,986] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.10 | bwd_microstep: 271.31 | bwd_inner_microstep: 271.29 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:29:04,462] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.71 | bwd_microstep: 270.01 | bwd_inner_microstep: 269.99 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:29:04,937] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 185.87 | bwd_microstep: 270.01 | bwd_inner_microstep: 269.99 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:29:05,413] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.77 | bwd_microstep: 269.84 | bwd_inner_microstep: 269.82 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 01:29:05,994] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.24 | optimizer_step: 19.04 +[2025-05-02 01:29:05,994] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.22 | bwd_microstep: 348.39 | bwd_inner_microstep: 270.57 | bwd_allreduce_microstep: 77.77 | step_microstep: 27.12 +[2025-05-02 01:29:05,996] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2950.71 | bwd: 4360.83 | bwd_inner: 4282.73 | bwd_allreduce: 77.86 | step: 27.87 + 14%|█▍ | 1202/8720 [3:13:39<20:36:31, 9.87s/it] {'loss': 0.7743, 'grad_norm': 8.53622055053711, 'learning_rate': 9.698321934516711e-06, 'epoch': 1.38} + 14%|█▍ | 1202/8720 [3:13:39<20:36:31, 9.87s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1966 +[2025-05-02 01:29:06,503] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.12 | bwd_microstep: 288.55 | bwd_inner_microstep: 288.53 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1974 +[2025-05-02 01:29:07,003] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 194.67 | bwd_microstep: 290.03 | bwd_inner_microstep: 290.01 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1933 +[2025-05-02 01:29:07,501] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 193.67 | bwd_microstep: 286.70 | bwd_inner_microstep: 286.68 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1416 +[2025-05-02 01:29:07,875] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 144.39 | bwd_microstep: 212.03 | bwd_inner_microstep: 211.91 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 01:29:08,352] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.47 | bwd_microstep: 271.79 | bwd_inner_microstep: 271.77 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 01:29:08,830] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.65 | bwd_microstep: 272.04 | bwd_inner_microstep: 272.02 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 01:29:09,308] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.15 | bwd_microstep: 271.96 | bwd_inner_microstep: 271.94 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:29:09,784] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.16 | bwd_microstep: 271.20 | bwd_inner_microstep: 271.18 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:29:10,258] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.58 | bwd_microstep: 270.97 | bwd_inner_microstep: 270.95 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:29:10,732] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.81 | bwd_microstep: 271.29 | bwd_inner_microstep: 271.27 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:29:11,205] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.21 | bwd_microstep: 271.18 | bwd_inner_microstep: 271.16 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:29:11,677] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.48 | bwd_microstep: 270.92 | bwd_inner_microstep: 270.90 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:29:12,150] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.06 | bwd_microstep: 270.92 | bwd_inner_microstep: 270.90 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:29:12,624] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.97 | bwd_microstep: 271.09 | bwd_inner_microstep: 271.07 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1086 +[2025-05-02 01:29:12,912] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 113.78 | bwd_microstep: 159.12 | bwd_inner_microstep: 159.10 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:29:13,490] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.12 | optimizer_step: 17.44 +[2025-05-02 01:29:13,490] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.17 | bwd_microstep: 349.75 | bwd_inner_microstep: 270.44 | bwd_allreduce_microstep: 79.25 | step_microstep: 25.19 +[2025-05-02 01:29:13,492] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2901.02 | bwd: 4299.55 | bwd_inner: 4219.85 | bwd_allreduce: 79.43 | step: 26.12 + 14%|█▍ | 1203/8720 [3:13:47<19:07:11, 9.16s/it] {'loss': 0.671, 'grad_norm': 10.41939926147461, 'learning_rate': 9.697686276052343e-06, 'epoch': 1.38} + 14%|█▍ | 1203/8720 [3:13:47<19:07:11, 9.16s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 324 +[2025-05-02 01:29:13,712] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 80.53 | bwd_microstep: 118.27 | bwd_inner_microstep: 118.01 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 504 +[2025-05-02 01:29:13,933] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 84.65 | bwd_microstep: 121.31 | bwd_inner_microstep: 121.10 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1892 +[2025-05-02 01:29:14,413] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.15 | bwd_microstep: 274.24 | bwd_inner_microstep: 274.22 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1883 +[2025-05-02 01:29:14,889] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.48 | bwd_microstep: 273.14 | bwd_inner_microstep: 273.13 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 349 +[2025-05-02 01:29:15,089] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 68.60 | bwd_microstep: 118.87 | bwd_inner_microstep: 118.74 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 01:29:15,564] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.77 | bwd_microstep: 272.34 | bwd_inner_microstep: 272.32 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 01:29:16,039] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.54 | bwd_microstep: 271.95 | bwd_inner_microstep: 271.93 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 01:29:16,515] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.28 | bwd_microstep: 271.81 | bwd_inner_microstep: 271.79 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 01:29:16,989] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.66 | bwd_microstep: 271.80 | bwd_inner_microstep: 271.78 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:29:17,464] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.11 | bwd_microstep: 271.23 | bwd_inner_microstep: 271.21 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:29:17,937] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.77 | bwd_microstep: 271.30 | bwd_inner_microstep: 271.28 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 832 +[2025-05-02 01:29:18,173] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 91.86 | bwd_microstep: 129.77 | bwd_inner_microstep: 129.71 | bwd_allreduce_microstep: 0.03 | step_microstep: 0.08 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 318 +[2025-05-02 01:29:18,381] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 76.62 | bwd_microstep: 117.92 | bwd_inner_microstep: 117.60 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:29:18,853] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.36 | bwd_microstep: 269.93 | bwd_inner_microstep: 269.91 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 01:29:19,328] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.16 | bwd_microstep: 269.97 | bwd_inner_microstep: 269.95 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2136 +[2025-05-02 01:29:19,966] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.11 | optimizer_step: 17.43 +[2025-05-02 01:29:19,967] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 205.43 | bwd_microstep: 389.83 | bwd_inner_microstep: 313.27 | bwd_allreduce_microstep: 76.51 | step_microstep: 25.16 +[2025-05-02 01:29:19,968] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2482.67 | bwd: 3713.74 | bwd_inner: 3636.14 | bwd_allreduce: 76.94 | step: 26.07 + 14%|█▍ | 1204/8720 [3:13:53<17:26:18, 8.35s/it] {'loss': 1.1546, 'grad_norm': 14.881627082824707, 'learning_rate': 9.697049969478474e-06, 'epoch': 1.38} + 14%|█▍ | 1204/8720 [3:13:53<17:26:18, 8.35s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:29:20,449] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.23 | bwd_microstep: 270.42 | bwd_inner_microstep: 270.41 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 388 +[2025-05-02 01:29:20,667] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 68.41 | bwd_microstep: 136.36 | bwd_inner_microstep: 136.17 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-02 01:29:21,143] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.90 | bwd_microstep: 272.85 | bwd_inner_microstep: 272.83 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 01:29:21,618] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.76 | bwd_microstep: 272.74 | bwd_inner_microstep: 272.72 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-02 01:29:22,094] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.60 | bwd_microstep: 273.08 | bwd_inner_microstep: 273.06 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-02 01:29:22,571] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.80 | bwd_microstep: 272.61 | bwd_inner_microstep: 272.59 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-02 01:29:23,046] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.45 | bwd_microstep: 272.16 | bwd_inner_microstep: 272.15 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 01:29:23,523] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.24 | bwd_microstep: 272.22 | bwd_inner_microstep: 272.08 | bwd_allreduce_microstep: 0.09 | step_microstep: 0.12 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 846 +[2025-05-02 01:29:23,765] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.77 | bwd_microstep: 132.26 | bwd_inner_microstep: 132.03 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 01:29:24,242] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.32 | bwd_microstep: 271.73 | bwd_inner_microstep: 271.71 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:29:24,721] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.09 | bwd_microstep: 271.69 | bwd_inner_microstep: 271.67 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 01:29:25,197] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.32 | bwd_microstep: 271.89 | bwd_inner_microstep: 271.87 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 01:29:25,674] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.32 | bwd_microstep: 271.47 | bwd_inner_microstep: 271.45 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:29:26,152] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.40 | bwd_microstep: 271.67 | bwd_inner_microstep: 271.66 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:29:26,630] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.54 | bwd_microstep: 271.26 | bwd_inner_microstep: 271.24 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:29:27,209] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.11 | optimizer_step: 17.41 +[2025-05-02 01:29:27,210] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.81 | bwd_microstep: 349.79 | bwd_inner_microstep: 271.05 | bwd_allreduce_microstep: 78.69 | step_microstep: 25.22 +[2025-05-02 01:29:27,211] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2790.63 | bwd: 4154.25 | bwd_inner: 4074.73 | bwd_allreduce: 79.02 | step: 26.07 + 14%|█▍ | 1205/8720 [3:14:00<16:44:28, 8.02s/it] {'loss': 0.8464, 'grad_norm': 12.58445930480957, 'learning_rate': 9.696413014882889e-06, 'epoch': 1.38} + 14%|█▍ | 1205/8720 [3:14:00<16:44:28, 8.02s/it]dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 833 +[2025-05-02 01:29:27,451] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 92.95 | bwd_microstep: 125.16 | bwd_inner_microstep: 125.08 | bwd_allreduce_microstep: 0.03 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2628 +[2025-05-02 01:29:28,068] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 229.97 | bwd_microstep: 369.25 | bwd_inner_microstep: 369.24 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1952 +[2025-05-02 01:29:28,572] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 197.87 | bwd_microstep: 288.64 | bwd_inner_microstep: 288.62 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1910 +[2025-05-02 01:29:29,056] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.05 | bwd_microstep: 276.00 | bwd_inner_microstep: 275.98 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 381 +[2025-05-02 01:29:29,280] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 88.85 | bwd_microstep: 118.08 | bwd_inner_microstep: 117.70 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.13 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1934 +[2025-05-02 01:29:29,781] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.23 | bwd_microstep: 287.63 | bwd_inner_microstep: 287.61 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-02 01:29:30,263] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.10 | bwd_microstep: 273.57 | bwd_inner_microstep: 273.55 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-02 01:29:30,742] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.18 | bwd_microstep: 273.54 | bwd_inner_microstep: 273.52 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 01:29:31,223] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.11 | bwd_microstep: 273.08 | bwd_inner_microstep: 273.06 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 01:29:31,707] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.91 | bwd_microstep: 272.93 | bwd_inner_microstep: 272.91 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 837 +[2025-05-02 01:29:31,959] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 106.57 | bwd_microstep: 125.46 | bwd_inner_microstep: 125.24 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:29:32,436] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.66 | bwd_microstep: 272.83 | bwd_inner_microstep: 272.81 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:29:32,914] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.09 | bwd_microstep: 272.40 | bwd_inner_microstep: 272.38 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:29:33,394] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.90 | bwd_microstep: 272.20 | bwd_inner_microstep: 272.19 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:29:33,869] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.22 | bwd_microstep: 270.81 | bwd_inner_microstep: 270.80 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:29:34,450] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.07 | optimizer_gradients: 2.16 | optimizer_step: 17.42 +[2025-05-02 01:29:34,450] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.34 | bwd_microstep: 348.73 | bwd_inner_microstep: 271.53 | bwd_allreduce_microstep: 77.14 | step_microstep: 25.87 +[2025-05-02 01:29:34,452] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2795.62 | bwd: 4120.42 | bwd_inner: 4042.30 | bwd_allreduce: 77.50 | step: 26.78 + 14%|█▍ | 1206/8720 [3:14:08<16:15:03, 7.79s/it] {'loss': 0.7015, 'grad_norm': 4.549617290496826, 'learning_rate': 9.695775412353465e-06, 'epoch': 1.38} + 14%|█▍ | 1206/8720 [3:14:08<16:15:03, 7.79s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 01:29:34,933] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.68 | bwd_microstep: 270.41 | bwd_inner_microstep: 270.39 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1971 +[2025-05-02 01:29:35,439] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.77 | bwd_microstep: 291.04 | bwd_inner_microstep: 291.02 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1946 +[2025-05-02 01:29:35,940] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 196.31 | bwd_microstep: 288.66 | bwd_inner_microstep: 288.65 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 898 +[2025-05-02 01:29:36,203] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 101.19 | bwd_microstep: 143.49 | bwd_inner_microstep: 143.44 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.10 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 381 +[2025-05-02 01:29:36,421] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 87.44 | bwd_microstep: 115.18 | bwd_inner_microstep: 114.88 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-02 01:29:36,900] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.36 | bwd_microstep: 274.10 | bwd_inner_microstep: 274.08 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-02 01:29:37,383] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.63 | bwd_microstep: 273.60 | bwd_inner_microstep: 273.58 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-02 01:29:37,867] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.12 | bwd_microstep: 274.01 | bwd_inner_microstep: 273.99 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 01:29:38,347] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.92 | bwd_microstep: 272.20 | bwd_inner_microstep: 272.18 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 01:29:38,828] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.78 | bwd_microstep: 271.88 | bwd_inner_microstep: 271.86 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 836 +[2025-05-02 01:29:39,067] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 97.09 | bwd_microstep: 125.57 | bwd_inner_microstep: 125.37 | bwd_allreduce_microstep: 0.10 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:29:39,545] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.19 | bwd_microstep: 272.93 | bwd_inner_microstep: 272.91 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 01:29:40,026] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.36 | bwd_microstep: 272.58 | bwd_inner_microstep: 272.56 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.05 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 325 +[2025-05-02 01:29:40,249] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 88.07 | bwd_microstep: 118.18 | bwd_inner_microstep: 117.87 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:29:40,725] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.81 | bwd_microstep: 271.07 | bwd_inner_microstep: 271.05 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 01:29:41,314] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.14 | optimizer_step: 17.42 +[2025-05-02 01:29:41,315] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.52 | bwd_microstep: 356.21 | bwd_inner_microstep: 271.16 | bwd_allreduce_microstep: 85.00 | step_microstep: 25.12 +[2025-05-02 01:29:41,316] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2646.86 | bwd: 3891.24 | bwd_inner: 3805.12 | bwd_allreduce: 85.42 | step: 26.19 + 14%|█▍ | 1207/8720 [3:14:15<15:40:18, 7.51s/it] {'loss': 0.7155, 'grad_norm': 8.8899507522583, 'learning_rate': 9.695137161978169e-06, 'epoch': 1.38} + 14%|█▍ | 1207/8720 [3:14:15<15:40:18, 7.51s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 01:29:41,797] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.39 | bwd_microstep: 270.23 | bwd_inner_microstep: 270.21 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1929 +[2025-05-02 01:29:42,297] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.65 | bwd_microstep: 287.21 | bwd_inner_microstep: 287.19 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1920 +[2025-05-02 01:29:42,781] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.62 | bwd_microstep: 276.34 | bwd_inner_microstep: 276.32 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.21 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1393 +[2025-05-02 01:29:43,148] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 144.29 | bwd_microstep: 208.81 | bwd_inner_microstep: 208.80 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 01:29:43,625] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.07 | bwd_microstep: 273.10 | bwd_inner_microstep: 273.08 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 855 +[2025-05-02 01:29:43,872] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 97.99 | bwd_microstep: 132.74 | bwd_inner_microstep: 132.61 | bwd_allreduce_microstep: 0.08 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 01:29:44,352] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.41 | bwd_microstep: 272.79 | bwd_inner_microstep: 272.77 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:29:44,834] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.04 | bwd_microstep: 272.27 | bwd_inner_microstep: 272.25 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 01:29:45,312] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.14 | bwd_microstep: 272.42 | bwd_inner_microstep: 272.40 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:29:45,788] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.38 | bwd_microstep: 272.10 | bwd_inner_microstep: 272.08 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:29:46,264] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.25 | bwd_microstep: 271.83 | bwd_inner_microstep: 271.81 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:29:46,743] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.08 | bwd_microstep: 272.50 | bwd_inner_microstep: 272.49 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:29:47,224] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.85 | bwd_microstep: 271.97 | bwd_inner_microstep: 271.96 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:29:47,701] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.94 | bwd_microstep: 272.09 | bwd_inner_microstep: 272.07 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:29:48,180] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.77 | bwd_microstep: 270.96 | bwd_inner_microstep: 270.94 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:29:48,760] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.15 | optimizer_step: 17.33 +[2025-05-02 01:29:48,761] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.95 | bwd_microstep: 348.36 | bwd_inner_microstep: 271.43 | bwd_allreduce_microstep: 76.88 | step_microstep: 24.94 +[2025-05-02 01:29:48,762] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2882.46 | bwd: 4245.76 | bwd_inner: 4168.43 | bwd_allreduce: 77.03 | step: 25.97 + 14%|█▍ | 1208/8720 [3:14:22<15:37:47, 7.49s/it] {'loss': 0.6211, 'grad_norm': 6.299281120300293, 'learning_rate': 9.694498263845055e-06, 'epoch': 1.39} + 14%|█▍ | 1208/8720 [3:14:22<15:37:47, 7.49s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:29:49,242] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.11 | bwd_microstep: 270.17 | bwd_inner_microstep: 270.16 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1933 +[2025-05-02 01:29:49,744] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.77 | bwd_microstep: 287.27 | bwd_inner_microstep: 287.25 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1903 +[2025-05-02 01:29:50,228] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.88 | bwd_microstep: 275.25 | bwd_inner_microstep: 275.23 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:29:50,710] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.82 | bwd_microstep: 272.02 | bwd_inner_microstep: 272.00 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 01:29:51,192] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.44 | bwd_microstep: 273.22 | bwd_inner_microstep: 273.20 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 838 +[2025-05-02 01:29:51,430] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.81 | bwd_microstep: 125.74 | bwd_inner_microstep: 125.67 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:29:51,908] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.38 | bwd_microstep: 272.28 | bwd_inner_microstep: 272.26 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:29:52,385] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.26 | bwd_microstep: 272.18 | bwd_inner_microstep: 272.16 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:29:52,861] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.63 | bwd_microstep: 271.88 | bwd_inner_microstep: 271.86 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 01:29:53,336] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.19 | bwd_microstep: 271.95 | bwd_inner_microstep: 271.94 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:29:53,812] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.98 | bwd_microstep: 272.30 | bwd_inner_microstep: 272.28 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 01:29:54,286] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.32 | bwd_microstep: 270.68 | bwd_inner_microstep: 270.66 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:29:54,761] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.98 | bwd_microstep: 270.80 | bwd_inner_microstep: 270.78 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:29:55,239] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.38 | bwd_microstep: 270.79 | bwd_inner_microstep: 270.77 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 01:29:55,715] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.99 | bwd_microstep: 270.82 | bwd_inner_microstep: 270.80 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 316 +[2025-05-02 01:29:56,057] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.11 | optimizer_step: 17.40 +[2025-05-02 01:29:56,057] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.29 | bwd_microstep: 206.60 | bwd_inner_microstep: 129.50 | bwd_allreduce_microstep: 76.94 | step_microstep: 24.99 +[2025-05-02 01:29:56,059] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2824.87 | bwd: 4153.98 | bwd_inner: 4076.60 | bwd_allreduce: 77.02 | step: 25.76 + 14%|█▍ | 1209/8720 [3:14:29<15:30:23, 7.43s/it] {'loss': 0.5578, 'grad_norm': 7.787139415740967, 'learning_rate': 9.693858718042271e-06, 'epoch': 1.39} + 14%|█▍ | 1209/8720 [3:14:29<15:30:23, 7.43s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 315 +[2025-05-02 01:29:56,275] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 81.38 | bwd_microstep: 113.43 | bwd_inner_microstep: 113.29 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1904 +[2025-05-02 01:29:56,757] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.24 | bwd_microstep: 275.74 | bwd_inner_microstep: 275.72 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1899 +[2025-05-02 01:29:57,241] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.90 | bwd_microstep: 275.39 | bwd_inner_microstep: 275.37 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 340 +[2025-05-02 01:29:57,455] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 83.21 | bwd_microstep: 116.20 | bwd_inner_microstep: 115.92 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-02 01:29:57,934] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.61 | bwd_microstep: 274.01 | bwd_inner_microstep: 273.99 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 01:29:58,416] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.75 | bwd_microstep: 272.89 | bwd_inner_microstep: 272.87 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 842 +[2025-05-02 01:29:58,659] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.69 | bwd_microstep: 131.87 | bwd_inner_microstep: 131.74 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 01:29:59,138] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.78 | bwd_microstep: 272.94 | bwd_inner_microstep: 272.92 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 327 +[2025-05-02 01:29:59,353] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 81.01 | bwd_microstep: 118.32 | bwd_inner_microstep: 118.17 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 325 +[2025-05-02 01:29:59,568] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 79.91 | bwd_microstep: 119.53 | bwd_inner_microstep: 119.27 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 01:30:00,044] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.31 | bwd_microstep: 271.89 | bwd_inner_microstep: 271.87 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:30:00,520] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.15 | bwd_microstep: 271.96 | bwd_inner_microstep: 271.94 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 832 +[2025-05-02 01:30:00,757] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 92.80 | bwd_microstep: 130.12 | bwd_inner_microstep: 130.01 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:30:01,233] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.40 | bwd_microstep: 271.34 | bwd_inner_microstep: 271.33 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:30:01,707] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.82 | bwd_microstep: 271.04 | bwd_inner_microstep: 271.02 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 01:30:02,276] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.16 | optimizer_step: 17.64 +[2025-05-02 01:30:02,277] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.69 | bwd_microstep: 341.95 | bwd_inner_microstep: 271.26 | bwd_allreduce_microstep: 70.64 | step_microstep: 24.89 +[2025-05-02 01:30:02,278] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2395.33 | bwd: 3528.73 | bwd_inner: 3456.89 | bwd_allreduce: 71.12 | step: 25.91 + 14%|█▍ | 1210/8720 [3:14:36<14:44:40, 7.07s/it] {'loss': 0.9269, 'grad_norm': 13.1220121383667, 'learning_rate': 9.693218524658045e-06, 'epoch': 1.39} + 14%|█▍ | 1210/8720 [3:14:36<14:44:40, 7.07s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1887 +[2025-05-02 01:30:02,760] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.33 | bwd_microstep: 273.50 | bwd_inner_microstep: 273.48 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1915 +[2025-05-02 01:30:03,242] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.89 | bwd_microstep: 276.14 | bwd_inner_microstep: 276.13 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1900 +[2025-05-02 01:30:03,721] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.26 | bwd_microstep: 275.35 | bwd_inner_microstep: 275.33 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 01:30:04,198] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.44 | bwd_microstep: 273.33 | bwd_inner_microstep: 273.32 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 350 +[2025-05-02 01:30:04,428] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 86.66 | bwd_microstep: 126.98 | bwd_inner_microstep: 126.69 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 01:30:04,904] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.36 | bwd_microstep: 272.94 | bwd_inner_microstep: 272.93 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1357 +[2025-05-02 01:30:05,266] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.32 | bwd_microstep: 206.36 | bwd_inner_microstep: 206.34 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:30:05,742] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.56 | bwd_microstep: 272.01 | bwd_inner_microstep: 271.99 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 01:30:06,218] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.21 | bwd_microstep: 272.58 | bwd_inner_microstep: 272.56 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 326 +[2025-05-02 01:30:06,434] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 69.65 | bwd_microstep: 133.30 | bwd_inner_microstep: 132.99 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 01:30:06,910] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.88 | bwd_microstep: 272.30 | bwd_inner_microstep: 272.28 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:30:07,385] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.09 | bwd_microstep: 272.02 | bwd_inner_microstep: 272.00 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 01:30:07,858] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.76 | bwd_microstep: 270.95 | bwd_inner_microstep: 270.93 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 01:30:08,333] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.29 | bwd_microstep: 270.87 | bwd_inner_microstep: 270.86 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:30:08,809] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.29 | bwd_microstep: 272.20 | bwd_inner_microstep: 272.18 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:30:09,380] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.14 | optimizer_step: 17.58 +[2025-05-02 01:30:09,380] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.66 | bwd_microstep: 342.20 | bwd_inner_microstep: 271.58 | bwd_allreduce_microstep: 70.58 | step_microstep: 24.82 +[2025-05-02 01:30:09,381] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2742.37 | bwd: 4083.09 | bwd_inner: 4011.71 | bwd_allreduce: 70.93 | step: 25.63 + 14%|█▍ | 1211/8720 [3:14:43<14:45:52, 7.08s/it] {'loss': 0.6987, 'grad_norm': 6.385833740234375, 'learning_rate': 9.692577683780706e-06, 'epoch': 1.39} + 14%|█▍ | 1211/8720 [3:14:43<14:45:52, 7.08s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1921 +[2025-05-02 01:30:09,882] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 194.30 | bwd_microstep: 286.22 | bwd_inner_microstep: 286.21 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1921 +[2025-05-02 01:30:10,378] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 194.21 | bwd_microstep: 286.46 | bwd_inner_microstep: 286.44 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 01:30:10,855] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.70 | bwd_microstep: 273.21 | bwd_inner_microstep: 273.19 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1361 +[2025-05-02 01:30:11,218] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.49 | bwd_microstep: 206.07 | bwd_inner_microstep: 205.97 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:30:11,694] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.60 | bwd_microstep: 272.04 | bwd_inner_microstep: 272.02 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1354 +[2025-05-02 01:30:12,056] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.59 | bwd_microstep: 205.77 | bwd_inner_microstep: 205.75 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 01:30:12,534] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.12 | bwd_microstep: 272.36 | bwd_inner_microstep: 272.34 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 01:30:13,011] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.46 | bwd_microstep: 272.48 | bwd_inner_microstep: 272.46 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:30:13,487] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.12 | bwd_microstep: 272.00 | bwd_inner_microstep: 271.98 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 01:30:13,964] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.08 | bwd_microstep: 272.49 | bwd_inner_microstep: 272.47 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:30:14,440] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.64 | bwd_microstep: 272.10 | bwd_inner_microstep: 272.08 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 319 +[2025-05-02 01:30:14,643] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 69.50 | bwd_microstep: 120.22 | bwd_inner_microstep: 120.08 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:30:15,117] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.77 | bwd_microstep: 270.93 | bwd_inner_microstep: 270.91 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:30:15,591] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.27 | bwd_microstep: 271.09 | bwd_inner_microstep: 271.07 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:30:16,067] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.57 | bwd_microstep: 271.17 | bwd_inner_microstep: 271.16 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 01:30:16,649] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.20 | optimizer_step: 17.77 +[2025-05-02 01:30:16,649] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.14 | bwd_microstep: 350.04 | bwd_inner_microstep: 271.38 | bwd_allreduce_microstep: 78.60 | step_microstep: 25.78 +[2025-05-02 01:30:16,651] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2809.26 | bwd: 4174.68 | bwd_inner: 4095.55 | bwd_allreduce: 78.80 | step: 26.66 + 14%|█▍ | 1212/8720 [3:14:50<14:52:58, 7.14s/it] {'loss': 0.7825, 'grad_norm': 17.567811965942383, 'learning_rate': 9.691936195498663e-06, 'epoch': 1.39} + 14%|█▍ | 1212/8720 [3:14:50<14:52:58, 7.14s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1941 +[2025-05-02 01:30:17,158] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 197.07 | bwd_microstep: 287.48 | bwd_inner_microstep: 287.46 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 377 +[2025-05-02 01:30:17,384] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 89.85 | bwd_microstep: 118.22 | bwd_inner_microstep: 117.90 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1908 +[2025-05-02 01:30:17,867] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.16 | bwd_microstep: 276.10 | bwd_inner_microstep: 276.08 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1905 +[2025-05-02 01:30:18,354] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.44 | bwd_microstep: 276.09 | bwd_inner_microstep: 276.07 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-02 01:30:18,837] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.70 | bwd_microstep: 273.54 | bwd_inner_microstep: 273.52 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 01:30:19,315] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.05 | bwd_microstep: 272.96 | bwd_inner_microstep: 272.94 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1358 +[2025-05-02 01:30:19,680] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.11 | bwd_microstep: 206.60 | bwd_inner_microstep: 206.47 | bwd_allreduce_microstep: 0.04 | step_microstep: 0.20 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1353 +[2025-05-02 01:30:20,045] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.23 | bwd_microstep: 206.11 | bwd_inner_microstep: 206.06 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 01:30:20,524] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.16 | bwd_microstep: 273.12 | bwd_inner_microstep: 273.10 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 01:30:21,003] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.35 | bwd_microstep: 272.69 | bwd_inner_microstep: 272.67 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:30:21,482] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.13 | bwd_microstep: 272.48 | bwd_inner_microstep: 272.46 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:30:21,960] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.90 | bwd_microstep: 272.49 | bwd_inner_microstep: 272.48 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:30:22,437] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.75 | bwd_microstep: 271.62 | bwd_inner_microstep: 271.60 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 831 +[2025-05-02 01:30:22,684] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 98.88 | bwd_microstep: 129.82 | bwd_inner_microstep: 129.78 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 01:30:23,160] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.46 | bwd_microstep: 270.98 | bwd_inner_microstep: 270.96 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1850 +[2025-05-02 01:30:23,728] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.15 | optimizer_step: 17.64 +[2025-05-02 01:30:23,728] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.49 | bwd_microstep: 338.96 | bwd_inner_microstep: 271.10 | bwd_allreduce_microstep: 67.82 | step_microstep: 24.87 +[2025-05-02 01:30:23,730] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2738.38 | bwd: 4019.35 | bwd_inner: 3950.73 | bwd_allreduce: 68.10 | step: 26.09 + 14%|█▍ | 1213/8720 [3:14:57<14:50:39, 7.12s/it] {'loss': 0.8842, 'grad_norm': 13.060226440429688, 'learning_rate': 9.69129405990042e-06, 'epoch': 1.39} + 14%|█▍ | 1213/8720 [3:14:57<14:50:39, 7.12s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1928 +[2025-05-02 01:30:24,231] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.00 | bwd_microstep: 286.38 | bwd_inner_microstep: 286.36 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 473 +[2025-05-02 01:30:24,452] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 86.21 | bwd_microstep: 120.05 | bwd_inner_microstep: 119.92 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.10 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 377 +[2025-05-02 01:30:24,659] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 69.79 | bwd_microstep: 123.10 | bwd_inner_microstep: 122.97 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1914 +[2025-05-02 01:30:25,139] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.75 | bwd_microstep: 276.02 | bwd_inner_microstep: 276.00 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 338 +[2025-05-02 01:30:25,339] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 68.69 | bwd_microstep: 117.35 | bwd_inner_microstep: 117.22 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1347 +[2025-05-02 01:30:25,698] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 139.42 | bwd_microstep: 205.74 | bwd_inner_microstep: 205.73 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.13 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 01:30:26,174] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.97 | bwd_microstep: 272.92 | bwd_inner_microstep: 272.90 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:30:26,650] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.11 | bwd_microstep: 272.43 | bwd_inner_microstep: 272.41 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 01:30:27,127] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.72 | bwd_microstep: 272.89 | bwd_inner_microstep: 272.87 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:30:27,604] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.32 | bwd_microstep: 272.42 | bwd_inner_microstep: 272.40 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 834 +[2025-05-02 01:30:27,835] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 91.02 | bwd_microstep: 125.69 | bwd_inner_microstep: 125.64 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 01:30:28,311] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.19 | bwd_microstep: 272.07 | bwd_inner_microstep: 272.05 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:30:28,786] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.08 | bwd_microstep: 271.25 | bwd_inner_microstep: 271.24 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 01:30:29,261] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.20 | bwd_microstep: 271.26 | bwd_inner_microstep: 271.25 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:30:29,737] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.86 | bwd_microstep: 271.27 | bwd_inner_microstep: 271.25 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 01:30:30,302] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.26 | optimizer_step: 17.60 +[2025-05-02 01:30:30,303] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.26 | bwd_microstep: 338.71 | bwd_inner_microstep: 271.28 | bwd_allreduce_microstep: 67.39 | step_microstep: 24.98 +[2025-05-02 01:30:30,304] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2531.32 | bwd: 3769.63 | bwd_inner: 3701.56 | bwd_allreduce: 67.62 | step: 25.93 + 14%|█▍ | 1214/8720 [3:15:04<14:30:06, 6.96s/it] {'loss': 0.8058, 'grad_norm': 11.054791450500488, 'learning_rate': 9.690651277074568e-06, 'epoch': 1.39} + 14%|█▍ | 1214/8720 [3:15:04<14:30:06, 6.96s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 01:30:30,784] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.72 | bwd_microstep: 270.58 | bwd_inner_microstep: 270.57 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2436 +[2025-05-02 01:30:31,375] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 222.99 | bwd_microstep: 351.69 | bwd_inner_microstep: 351.67 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 366 +[2025-05-02 01:30:31,590] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 77.86 | bwd_microstep: 123.87 | bwd_inner_microstep: 123.56 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1904 +[2025-05-02 01:30:32,070] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.21 | bwd_microstep: 275.72 | bwd_inner_microstep: 275.70 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 848 +[2025-05-02 01:30:32,314] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 97.19 | bwd_microstep: 132.24 | bwd_inner_microstep: 132.07 | bwd_allreduce_microstep: 0.10 | step_microstep: 0.15 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 01:30:32,790] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.50 | bwd_microstep: 272.08 | bwd_inner_microstep: 272.07 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 834 +[2025-05-02 01:30:33,032] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 99.93 | bwd_microstep: 125.54 | bwd_inner_microstep: 125.34 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 01:30:33,513] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.26 | bwd_microstep: 272.91 | bwd_inner_microstep: 272.89 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 01:30:33,991] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.68 | bwd_microstep: 272.47 | bwd_inner_microstep: 272.45 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:30:34,469] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.28 | bwd_microstep: 272.25 | bwd_inner_microstep: 272.24 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:30:34,949] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.74 | bwd_microstep: 272.52 | bwd_inner_microstep: 272.50 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:30:35,429] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.75 | bwd_microstep: 272.31 | bwd_inner_microstep: 272.29 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1350 +[2025-05-02 01:30:35,794] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.92 | bwd_microstep: 205.37 | bwd_inner_microstep: 205.30 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 01:30:36,272] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.30 | bwd_microstep: 271.72 | bwd_inner_microstep: 271.71 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:30:36,749] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.29 | bwd_microstep: 272.46 | bwd_inner_microstep: 272.45 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:30:37,332] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.11 | optimizer_step: 23.04 +[2025-05-02 01:30:37,332] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.80 | bwd_microstep: 347.81 | bwd_inner_microstep: 271.30 | bwd_allreduce_microstep: 76.47 | step_microstep: 30.80 +[2025-05-02 01:30:37,334] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2708.06 | bwd: 4011.65 | bwd_inner: 3934.18 | bwd_allreduce: 76.90 | step: 32.08 + 14%|█▍ | 1215/8720 [3:15:11<14:32:51, 6.98s/it] {'loss': 0.3688, 'grad_norm': 10.255642890930176, 'learning_rate': 9.690007847109786e-06, 'epoch': 1.39} + 14%|█▍ | 1215/8720 [3:15:11<14:32:51, 6.98s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1850 +[2025-05-02 01:30:37,814] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.60 | bwd_microstep: 270.05 | bwd_inner_microstep: 270.03 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1892 +[2025-05-02 01:30:38,292] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.44 | bwd_microstep: 274.47 | bwd_inner_microstep: 274.45 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-02 01:30:38,769] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.97 | bwd_microstep: 273.22 | bwd_inner_microstep: 273.20 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 01:30:39,247] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.75 | bwd_microstep: 272.82 | bwd_inner_microstep: 272.80 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-02 01:30:39,725] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.62 | bwd_microstep: 273.55 | bwd_inner_microstep: 273.53 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 01:30:40,204] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.81 | bwd_microstep: 273.08 | bwd_inner_microstep: 273.07 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 01:30:40,683] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.94 | bwd_microstep: 272.63 | bwd_inner_microstep: 272.61 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 839 +[2025-05-02 01:30:40,924] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 96.02 | bwd_microstep: 127.07 | bwd_inner_microstep: 126.78 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 01:30:41,404] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.23 | bwd_microstep: 272.84 | bwd_inner_microstep: 272.82 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:30:41,883] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.88 | bwd_microstep: 272.69 | bwd_inner_microstep: 272.68 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:30:42,361] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.46 | bwd_microstep: 272.57 | bwd_inner_microstep: 272.55 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:30:42,837] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.59 | bwd_microstep: 272.75 | bwd_inner_microstep: 272.73 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:30:43,313] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.36 | bwd_microstep: 272.53 | bwd_inner_microstep: 272.52 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:30:43,788] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.29 | bwd_microstep: 272.31 | bwd_inner_microstep: 272.29 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 832 +[2025-05-02 01:30:44,027] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.60 | bwd_microstep: 130.36 | bwd_inner_microstep: 130.30 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:30:44,592] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.04 | optimizer_gradients: 2.10 | optimizer_step: 16.89 +[2025-05-02 01:30:44,593] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.67 | bwd_microstep: 338.32 | bwd_inner_microstep: 272.07 | bwd_allreduce_microstep: 66.21 | step_microstep: 23.87 +[2025-05-02 01:30:44,594] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2827.89 | bwd: 4141.30 | bwd_inner: 4074.47 | bwd_allreduce: 66.43 | step: 24.69 + 14%|█▍ | 1216/8720 [3:15:18<14:43:14, 7.06s/it] {'loss': 0.9022, 'grad_norm': 8.641026496887207, 'learning_rate': 9.689363770094847e-06, 'epoch': 1.39} + 14%|█▍ | 1216/8720 [3:15:18<14:43:14, 7.06s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 01:30:45,071] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.50 | bwd_microstep: 270.23 | bwd_inner_microstep: 270.21 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1941 +[2025-05-02 01:30:45,570] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.47 | bwd_microstep: 288.19 | bwd_inner_microstep: 288.17 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 898 +[2025-05-02 01:30:45,828] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 100.05 | bwd_microstep: 143.72 | bwd_inner_microstep: 143.42 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 346 +[2025-05-02 01:30:46,039] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 78.19 | bwd_microstep: 119.67 | bwd_inner_microstep: 119.44 | bwd_allreduce_microstep: 0.09 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-02 01:30:46,516] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.24 | bwd_microstep: 273.78 | bwd_inner_microstep: 273.76 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 01:30:46,992] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.23 | bwd_microstep: 272.84 | bwd_inner_microstep: 272.82 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-02 01:30:47,470] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.10 | bwd_microstep: 273.09 | bwd_inner_microstep: 273.08 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 01:30:47,947] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.69 | bwd_microstep: 273.26 | bwd_inner_microstep: 273.24 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:30:48,423] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.26 | bwd_microstep: 272.40 | bwd_inner_microstep: 272.39 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:30:48,899] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.51 | bwd_microstep: 272.44 | bwd_inner_microstep: 272.42 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 01:30:49,378] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.22 | bwd_microstep: 272.67 | bwd_inner_microstep: 272.65 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 01:30:49,856] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.67 | bwd_microstep: 272.17 | bwd_inner_microstep: 272.15 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 01:30:50,333] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.46 | bwd_microstep: 272.31 | bwd_inner_microstep: 272.29 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:30:50,810] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.03 | bwd_microstep: 271.24 | bwd_inner_microstep: 271.23 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 01:30:51,288] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.74 | bwd_microstep: 271.21 | bwd_inner_microstep: 271.19 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 829 +[2025-05-02 01:30:51,663] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.10 | optimizer_step: 22.47 +[2025-05-02 01:30:51,664] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 100.58 | bwd_microstep: 225.49 | bwd_inner_microstep: 134.97 | bwd_allreduce_microstep: 90.40 | step_microstep: 30.25 +[2025-05-02 01:30:51,665] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2733.62 | bwd: 4044.75 | bwd_inner: 3953.56 | bwd_allreduce: 90.65 | step: 31.00 + 14%|█▍ | 1217/8720 [3:15:25<14:43:31, 7.07s/it] {'loss': 0.7007, 'grad_norm': 6.405899524688721, 'learning_rate': 9.688719046118607e-06, 'epoch': 1.4} + 14%|█▍ | 1217/8720 [3:15:25<14:43:31, 7.07s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:30:52,145] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.55 | bwd_microstep: 270.16 | bwd_inner_microstep: 270.14 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1968 +[2025-05-02 01:30:52,652] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 198.72 | bwd_microstep: 290.71 | bwd_inner_microstep: 290.69 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-02 01:30:53,133] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.78 | bwd_microstep: 274.01 | bwd_inner_microstep: 273.99 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 852 +[2025-05-02 01:30:53,389] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 104.49 | bwd_microstep: 132.52 | bwd_inner_microstep: 132.50 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 847 +[2025-05-02 01:30:53,630] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.82 | bwd_microstep: 132.13 | bwd_inner_microstep: 132.06 | bwd_allreduce_microstep: 0.03 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 01:30:54,109] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.04 | bwd_microstep: 272.91 | bwd_inner_microstep: 272.89 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 01:30:54,588] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.27 | bwd_microstep: 272.77 | bwd_inner_microstep: 272.76 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 01:30:55,067] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.26 | bwd_microstep: 272.66 | bwd_inner_microstep: 272.64 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:30:55,545] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.00 | bwd_microstep: 272.28 | bwd_inner_microstep: 272.26 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1094 +[2025-05-02 01:30:55,837] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 115.03 | bwd_microstep: 160.81 | bwd_inner_microstep: 160.74 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:30:56,315] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.27 | bwd_microstep: 272.32 | bwd_inner_microstep: 272.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:30:56,793] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.44 | bwd_microstep: 272.48 | bwd_inner_microstep: 272.46 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 321 +[2025-05-02 01:30:57,009] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 84.41 | bwd_microstep: 116.38 | bwd_inner_microstep: 116.06 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:30:57,483] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.74 | bwd_microstep: 270.95 | bwd_inner_microstep: 270.93 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 01:30:57,957] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.11 | bwd_microstep: 271.10 | bwd_inner_microstep: 271.08 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 01:30:58,523] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.10 | optimizer_step: 16.48 +[2025-05-02 01:30:58,523] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.47 | bwd_microstep: 339.05 | bwd_inner_microstep: 271.86 | bwd_allreduce_microstep: 67.14 | step_microstep: 23.50 +[2025-05-02 01:30:58,524] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2665.07 | bwd: 3893.28 | bwd_inner: 3825.44 | bwd_allreduce: 67.41 | step: 24.40 + 14%|█▍ | 1218/8720 [3:15:32<14:35:36, 7.00s/it] {'loss': 1.0194, 'grad_norm': 9.3902587890625, 'learning_rate': 9.688073675270016e-06, 'epoch': 1.4} + 14%|█▍ | 1218/8720 [3:15:32<14:35:36, 7.00s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 01:30:59,001] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.12 | bwd_microstep: 270.10 | bwd_inner_microstep: 270.08 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1286 +[2025-05-02 01:30:59,348] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 133.60 | bwd_microstep: 199.80 | bwd_inner_microstep: 199.78 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-02 01:30:59,826] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.40 | bwd_microstep: 274.16 | bwd_inner_microstep: 274.14 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 351 +[2025-05-02 01:31:00,026] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 68.31 | bwd_microstep: 118.90 | bwd_inner_microstep: 118.77 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-02 01:31:00,502] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.89 | bwd_microstep: 273.40 | bwd_inner_microstep: 273.39 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1368 +[2025-05-02 01:31:00,865] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.74 | bwd_microstep: 207.13 | bwd_inner_microstep: 207.00 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 01:31:01,341] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.11 | bwd_microstep: 272.49 | bwd_inner_microstep: 272.47 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 01:31:01,818] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.82 | bwd_microstep: 272.94 | bwd_inner_microstep: 272.92 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:31:02,294] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.80 | bwd_microstep: 272.66 | bwd_inner_microstep: 272.64 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 838 +[2025-05-02 01:31:02,525] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 91.19 | bwd_microstep: 126.33 | bwd_inner_microstep: 126.17 | bwd_allreduce_microstep: 0.08 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:31:03,000] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.32 | bwd_microstep: 272.15 | bwd_inner_microstep: 272.13 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 01:31:03,475] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.08 | bwd_microstep: 271.33 | bwd_inner_microstep: 271.31 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:31:03,949] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.07 | bwd_microstep: 271.33 | bwd_inner_microstep: 271.32 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 01:31:04,425] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.03 | bwd_microstep: 272.03 | bwd_inner_microstep: 272.01 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:31:04,899] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.93 | bwd_microstep: 271.01 | bwd_inner_microstep: 270.99 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1341 +[2025-05-02 01:31:05,348] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.04 | optimizer_gradients: 2.09 | optimizer_step: 16.43 +[2025-05-02 01:31:05,348] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.03 | bwd_microstep: 271.04 | bwd_inner_microstep: 204.84 | bwd_allreduce_microstep: 66.11 | step_microstep: 23.28 +[2025-05-02 01:31:05,349] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2645.19 | bwd: 3916.87 | bwd_inner: 3850.03 | bwd_allreduce: 66.35 | step: 24.11 + 14%|█▍ | 1219/8720 [3:15:39<14:28:48, 6.95s/it] {'loss': 0.7271, 'grad_norm': 10.856406211853027, 'learning_rate': 9.687427657638112e-06, 'epoch': 1.4} + 14%|█▍ | 1219/8720 [3:15:39<14:28:48, 6.95s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 01:31:05,827] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.01 | bwd_microstep: 270.45 | bwd_inner_microstep: 270.43 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1968 +[2025-05-02 01:31:06,328] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.94 | bwd_microstep: 290.52 | bwd_inner_microstep: 290.50 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-02 01:31:06,805] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.48 | bwd_microstep: 273.55 | bwd_inner_microstep: 273.54 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1883 +[2025-05-02 01:31:07,282] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.83 | bwd_microstep: 273.99 | bwd_inner_microstep: 273.98 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 01:31:07,758] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.07 | bwd_microstep: 273.26 | bwd_inner_microstep: 273.24 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-02 01:31:08,236] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.65 | bwd_microstep: 273.47 | bwd_inner_microstep: 273.46 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:31:08,712] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.76 | bwd_microstep: 272.36 | bwd_inner_microstep: 272.35 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 01:31:09,189] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.29 | bwd_microstep: 272.77 | bwd_inner_microstep: 272.75 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 01:31:09,665] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.02 | bwd_microstep: 272.38 | bwd_inner_microstep: 272.36 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 837 +[2025-05-02 01:31:09,896] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 91.54 | bwd_microstep: 126.11 | bwd_inner_microstep: 125.99 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:31:10,373] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.25 | bwd_microstep: 272.25 | bwd_inner_microstep: 272.23 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 01:31:10,848] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.98 | bwd_microstep: 271.01 | bwd_inner_microstep: 270.99 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.16 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:31:11,321] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.30 | bwd_microstep: 270.91 | bwd_inner_microstep: 270.89 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 832 +[2025-05-02 01:31:11,560] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.02 | bwd_microstep: 130.02 | bwd_inner_microstep: 129.78 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 01:31:12,036] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.55 | bwd_microstep: 271.00 | bwd_inner_microstep: 270.99 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.14 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 01:31:12,610] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.07 | optimizer_step: 16.53 +[2025-05-02 01:31:12,610] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.76 | bwd_microstep: 345.62 | bwd_inner_microstep: 271.24 | bwd_allreduce_microstep: 74.34 | step_microstep: 23.61 +[2025-05-02 01:31:12,611] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2825.16 | bwd: 4159.74 | bwd_inner: 4084.70 | bwd_allreduce: 74.59 | step: 24.72 + 14%|█▍ | 1220/8720 [3:15:46<14:40:25, 7.04s/it] {'loss': 0.7847, 'grad_norm': 9.277361869812012, 'learning_rate': 9.68678099331202e-06, 'epoch': 1.4} + 14%|█▍ | 1220/8720 [3:15:46<14:40:25, 7.04s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2041 +[2025-05-02 01:31:13,129] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 200.99 | bwd_microstep: 297.30 | bwd_inner_microstep: 297.29 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.13 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1886 +[2025-05-02 01:31:13,607] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.82 | bwd_microstep: 274.20 | bwd_inner_microstep: 274.18 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1889 +[2025-05-02 01:31:14,085] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.48 | bwd_microstep: 274.30 | bwd_inner_microstep: 274.28 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-02 01:31:14,562] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.11 | bwd_microstep: 273.93 | bwd_inner_microstep: 273.91 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 01:31:15,039] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.74 | bwd_microstep: 272.78 | bwd_inner_microstep: 272.76 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-02 01:31:15,515] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.13 | bwd_microstep: 272.93 | bwd_inner_microstep: 272.91 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-02 01:31:15,993] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.81 | bwd_microstep: 273.44 | bwd_inner_microstep: 273.42 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 01:31:16,473] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.73 | bwd_microstep: 272.84 | bwd_inner_microstep: 272.83 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 837 +[2025-05-02 01:31:16,710] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.76 | bwd_microstep: 125.73 | bwd_inner_microstep: 125.56 | bwd_allreduce_microstep: 0.10 | step_microstep: 0.10 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 847 +[2025-05-02 01:31:16,952] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.95 | bwd_microstep: 132.17 | bwd_inner_microstep: 132.10 | bwd_allreduce_microstep: 0.03 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:31:17,429] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.29 | bwd_microstep: 272.16 | bwd_inner_microstep: 272.15 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:31:17,906] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.17 | bwd_microstep: 271.98 | bwd_inner_microstep: 271.96 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:31:18,380] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.55 | bwd_microstep: 271.93 | bwd_inner_microstep: 271.92 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 832 +[2025-05-02 01:31:18,620] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.77 | bwd_microstep: 129.83 | bwd_inner_microstep: 129.70 | bwd_allreduce_microstep: 0.09 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 01:31:19,093] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.12 | bwd_microstep: 270.99 | bwd_inner_microstep: 270.97 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:31:19,669] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.10 | optimizer_step: 16.41 +[2025-05-02 01:31:19,670] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.85 | bwd_microstep: 348.78 | bwd_inner_microstep: 272.55 | bwd_allreduce_microstep: 76.18 | step_microstep: 24.17 +[2025-05-02 01:31:19,671] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2741.96 | bwd: 4035.37 | bwd_inner: 3958.50 | bwd_allreduce: 76.45 | step: 25.18 + 14%|█▍ | 1221/8720 [3:15:53<14:40:59, 7.05s/it] {'loss': 0.6679, 'grad_norm': 5.935354709625244, 'learning_rate': 9.68613368238096e-06, 'epoch': 1.4} + 14%|█▍ | 1221/8720 [3:15:53<14:40:59, 7.05s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2141 +[2025-05-02 01:31:20,213] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 204.79 | bwd_microstep: 313.79 | bwd_inner_microstep: 313.78 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2628 +[2025-05-02 01:31:20,827] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 229.72 | bwd_microstep: 370.06 | bwd_inner_microstep: 370.04 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-02 01:31:21,306] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.86 | bwd_microstep: 273.80 | bwd_inner_microstep: 273.78 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-02 01:31:21,782] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.39 | bwd_microstep: 273.05 | bwd_inner_microstep: 273.04 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:31:22,258] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.78 | bwd_microstep: 271.86 | bwd_inner_microstep: 271.84 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:31:22,735] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.16 | bwd_microstep: 272.09 | bwd_inner_microstep: 272.08 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 01:31:23,215] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.60 | bwd_microstep: 272.63 | bwd_inner_microstep: 272.61 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1351 +[2025-05-02 01:31:23,580] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.49 | bwd_microstep: 206.27 | bwd_inner_microstep: 206.19 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 01:31:24,061] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.33 | bwd_microstep: 273.26 | bwd_inner_microstep: 273.24 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1350 +[2025-05-02 01:31:24,426] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.83 | bwd_microstep: 205.56 | bwd_inner_microstep: 205.54 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:31:24,910] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.36 | bwd_microstep: 272.97 | bwd_inner_microstep: 272.96 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 837 +[2025-05-02 01:31:25,148] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.56 | bwd_microstep: 126.23 | bwd_inner_microstep: 126.04 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:31:25,629] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.87 | bwd_microstep: 272.96 | bwd_inner_microstep: 272.95 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:31:26,109] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.99 | bwd_microstep: 271.70 | bwd_inner_microstep: 271.68 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1343 +[2025-05-02 01:31:26,473] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.68 | bwd_microstep: 204.87 | bwd_inner_microstep: 204.60 | bwd_allreduce_microstep: 0.10 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:31:27,053] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.18 | optimizer_step: 16.61 +[2025-05-02 01:31:27,053] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.54 | bwd_microstep: 348.38 | bwd_inner_microstep: 271.75 | bwd_allreduce_microstep: 76.58 | step_microstep: 24.70 +[2025-05-02 01:31:27,055] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2838.60 | bwd: 4229.59 | bwd_inner: 4152.19 | bwd_allreduce: 76.87 | step: 25.87 + 14%|█▍ | 1222/8720 [3:16:00<14:53:26, 7.15s/it] {'loss': 0.5284, 'grad_norm': 9.927603721618652, 'learning_rate': 9.685485724934233e-06, 'epoch': 1.4} + 14%|█▍ | 1222/8720 [3:16:00<14:53:26, 7.15s/it]dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1092 +[2025-05-02 01:31:27,354] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 115.57 | bwd_microstep: 160.46 | bwd_inner_microstep: 160.25 | bwd_allreduce_microstep: 0.09 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 01:31:27,831] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.70 | bwd_microstep: 273.37 | bwd_inner_microstep: 273.35 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1355 +[2025-05-02 01:31:28,194] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.66 | bwd_microstep: 206.08 | bwd_inner_microstep: 205.95 | bwd_allreduce_microstep: 0.08 | step_microstep: 0.09 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 837 +[2025-05-02 01:31:28,425] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 90.83 | bwd_microstep: 126.13 | bwd_inner_microstep: 126.12 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 01:31:28,901] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.14 | bwd_microstep: 272.57 | bwd_inner_microstep: 272.56 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 01:31:29,377] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.15 | bwd_microstep: 272.50 | bwd_inner_microstep: 272.48 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:31:29,852] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.90 | bwd_microstep: 272.30 | bwd_inner_microstep: 272.29 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:31:30,329] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.39 | bwd_microstep: 272.48 | bwd_inner_microstep: 272.46 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 01:31:30,805] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.72 | bwd_microstep: 272.32 | bwd_inner_microstep: 272.31 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:31:31,281] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.45 | bwd_microstep: 272.25 | bwd_inner_microstep: 272.24 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:31:31,756] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.83 | bwd_microstep: 272.09 | bwd_inner_microstep: 272.07 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 01:31:32,232] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.70 | bwd_microstep: 272.02 | bwd_inner_microstep: 272.01 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:31:32,707] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.95 | bwd_microstep: 271.05 | bwd_inner_microstep: 271.03 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:31:33,184] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.75 | bwd_microstep: 271.39 | bwd_inner_microstep: 271.37 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 01:31:33,662] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.25 | bwd_microstep: 271.05 | bwd_inner_microstep: 271.03 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 01:31:34,234] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.13 | optimizer_step: 16.57 +[2025-05-02 01:31:34,235] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.95 | bwd_microstep: 343.67 | bwd_inner_microstep: 271.73 | bwd_allreduce_microstep: 71.89 | step_microstep: 23.79 +[2025-05-02 01:31:34,236] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2794.67 | bwd: 4101.80 | bwd_inner: 4029.29 | bwd_allreduce: 72.14 | step: 24.60 + 14%|█▍ | 1223/8720 [3:16:07<14:54:26, 7.16s/it] {'loss': 0.5034, 'grad_norm': 15.638381004333496, 'learning_rate': 9.684837121061234e-06, 'epoch': 1.4} + 14%|█▍ | 1223/8720 [3:16:07<14:54:26, 7.16s/it]dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 907 +[2025-05-02 01:31:34,502] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 102.38 | bwd_microstep: 144.66 | bwd_inner_microstep: 144.36 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2141 +[2025-05-02 01:31:35,036] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 204.11 | bwd_microstep: 314.23 | bwd_inner_microstep: 314.21 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1912 +[2025-05-02 01:31:35,518] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.53 | bwd_microstep: 276.37 | bwd_inner_microstep: 276.35 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-02 01:31:35,997] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.64 | bwd_microstep: 273.89 | bwd_inner_microstep: 273.87 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 338 +[2025-05-02 01:31:36,225] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 87.83 | bwd_microstep: 122.82 | bwd_inner_microstep: 122.68 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-02 01:31:36,705] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.89 | bwd_microstep: 273.54 | bwd_inner_microstep: 273.52 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 01:31:37,186] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.35 | bwd_microstep: 272.63 | bwd_inner_microstep: 272.61 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 01:31:37,667] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.98 | bwd_microstep: 272.99 | bwd_inner_microstep: 272.97 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 01:31:38,151] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.93 | bwd_microstep: 272.78 | bwd_inner_microstep: 272.76 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.10 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 334 +[2025-05-02 01:31:38,392] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 98.92 | bwd_microstep: 120.19 | bwd_inner_microstep: 119.86 | bwd_allreduce_microstep: 0.14 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:31:38,874] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.98 | bwd_microstep: 272.20 | bwd_inner_microstep: 272.19 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:31:39,352] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.09 | bwd_microstep: 272.20 | bwd_inner_microstep: 272.18 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:31:39,832] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.21 | bwd_microstep: 272.32 | bwd_inner_microstep: 272.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:31:40,313] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.77 | bwd_microstep: 272.00 | bwd_inner_microstep: 271.98 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:31:40,791] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.76 | bwd_microstep: 272.19 | bwd_inner_microstep: 272.17 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 01:31:41,369] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.19 | optimizer_step: 16.79 +[2025-05-02 01:31:41,370] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.00 | bwd_microstep: 348.71 | bwd_inner_microstep: 271.83 | bwd_allreduce_microstep: 76.82 | step_microstep: 24.83 +[2025-05-02 01:31:41,371] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2754.99 | bwd: 4053.78 | bwd_inner: 3975.97 | bwd_allreduce: 77.20 | step: 25.99 + 14%|█▍ | 1224/8720 [3:16:15<14:53:31, 7.15s/it] {'loss': 1.0348, 'grad_norm': 6.876908779144287, 'learning_rate': 9.68418787085145e-06, 'epoch': 1.4} + 14%|█▍ | 1224/8720 [3:16:15<14:53:31, 7.15s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1957 +[2025-05-02 01:31:41,880] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.75 | bwd_microstep: 289.53 | bwd_inner_microstep: 289.51 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1940 +[2025-05-02 01:31:42,382] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 196.12 | bwd_microstep: 288.18 | bwd_inner_microstep: 288.16 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1935 +[2025-05-02 01:31:42,884] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 196.04 | bwd_microstep: 288.04 | bwd_inner_microstep: 288.02 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1896 +[2025-05-02 01:31:43,367] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.85 | bwd_microstep: 275.26 | bwd_inner_microstep: 275.24 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-02 01:31:43,847] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.64 | bwd_microstep: 273.08 | bwd_inner_microstep: 273.06 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-02 01:31:44,330] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.16 | bwd_microstep: 273.72 | bwd_inner_microstep: 273.70 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 841 +[2025-05-02 01:31:44,576] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 97.84 | bwd_microstep: 131.49 | bwd_inner_microstep: 131.40 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.10 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 326 +[2025-05-02 01:31:44,831] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 91.53 | bwd_microstep: 146.03 | bwd_inner_microstep: 145.70 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:31:45,309] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.34 | bwd_microstep: 272.16 | bwd_inner_microstep: 272.15 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 01:31:45,788] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.70 | bwd_microstep: 272.50 | bwd_inner_microstep: 272.48 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:31:46,266] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.77 | bwd_microstep: 272.53 | bwd_inner_microstep: 272.51 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 321 +[2025-05-02 01:31:46,487] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 81.65 | bwd_microstep: 123.53 | bwd_inner_microstep: 123.20 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:31:46,964] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.63 | bwd_microstep: 271.15 | bwd_inner_microstep: 271.13 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.17 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:31:47,441] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.40 | bwd_microstep: 272.25 | bwd_inner_microstep: 272.23 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 01:31:47,918] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.45 | bwd_microstep: 271.03 | bwd_inner_microstep: 271.01 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:31:48,500] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 3.45 | optimizer_step: 17.18 +[2025-05-02 01:31:48,500] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.17 | bwd_microstep: 349.50 | bwd_inner_microstep: 271.98 | bwd_allreduce_microstep: 77.47 | step_microstep: 26.95 +[2025-05-02 01:31:48,502] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2742.67 | bwd: 4070.03 | bwd_inner: 3991.61 | bwd_allreduce: 77.84 | step: 28.03 + 14%|█▍ | 1225/8720 [3:16:22<14:52:35, 7.15s/it] {'loss': 0.6299, 'grad_norm': 9.926246643066406, 'learning_rate': 9.683537974394452e-06, 'epoch': 1.4} + 14%|█▍ | 1225/8720 [3:16:22<14:52:35, 7.15s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 01:31:48,982] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.35 | bwd_microstep: 270.18 | bwd_inner_microstep: 270.17 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1930 +[2025-05-02 01:31:49,481] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.88 | bwd_microstep: 287.20 | bwd_inner_microstep: 287.18 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.06 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 364 +[2025-05-02 01:31:49,707] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 84.87 | bwd_microstep: 125.48 | bwd_inner_microstep: 125.14 | bwd_allreduce_microstep: 0.17 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1892 +[2025-05-02 01:31:50,188] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.59 | bwd_microstep: 274.80 | bwd_inner_microstep: 274.78 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1888 +[2025-05-02 01:31:50,669] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.11 | bwd_microstep: 274.40 | bwd_inner_microstep: 274.38 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1883 +[2025-05-02 01:31:51,152] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.80 | bwd_microstep: 274.18 | bwd_inner_microstep: 274.17 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:31:51,632] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.18 | bwd_microstep: 272.52 | bwd_inner_microstep: 272.50 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 840 +[2025-05-02 01:31:51,872] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 96.25 | bwd_microstep: 125.96 | bwd_inner_microstep: 125.93 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1349 +[2025-05-02 01:31:52,236] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.49 | bwd_microstep: 206.03 | bwd_inner_microstep: 206.01 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 01:31:52,715] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.18 | bwd_microstep: 272.42 | bwd_inner_microstep: 272.40 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:31:53,196] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.55 | bwd_microstep: 272.56 | bwd_inner_microstep: 272.54 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:31:53,677] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.88 | bwd_microstep: 271.25 | bwd_inner_microstep: 271.23 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:31:54,159] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.37 | bwd_microstep: 271.28 | bwd_inner_microstep: 271.26 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:31:54,636] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.68 | bwd_microstep: 271.13 | bwd_inner_microstep: 271.11 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:31:55,113] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.06 | bwd_microstep: 271.25 | bwd_inner_microstep: 271.24 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 01:31:55,700] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.20 | optimizer_step: 16.80 +[2025-05-02 01:31:55,701] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.93 | bwd_microstep: 355.55 | bwd_inner_microstep: 271.77 | bwd_allreduce_microstep: 83.71 | step_microstep: 24.54 +[2025-05-02 01:31:55,702] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2777.78 | bwd: 4096.22 | bwd_inner: 4011.87 | bwd_allreduce: 83.97 | step: 25.61 + 14%|█▍ | 1226/8720 [3:16:29<14:54:31, 7.16s/it] {'loss': 0.7152, 'grad_norm': 10.002599716186523, 'learning_rate': 9.682887431779901e-06, 'epoch': 1.41} + 14%|█▍ | 1226/8720 [3:16:29<14:54:31, 7.16s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1919 +[2025-05-02 01:31:56,190] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.55 | bwd_microstep: 275.73 | bwd_inner_microstep: 275.71 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 962 +[2025-05-02 01:31:56,462] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 105.62 | bwd_microstep: 149.71 | bwd_inner_microstep: 149.70 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1911 +[2025-05-02 01:31:56,946] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.42 | bwd_microstep: 276.47 | bwd_inner_microstep: 276.45 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1941 +[2025-05-02 01:31:57,445] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.86 | bwd_microstep: 288.22 | bwd_inner_microstep: 288.20 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1892 +[2025-05-02 01:31:57,924] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.04 | bwd_microstep: 274.48 | bwd_inner_microstep: 274.46 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 356 +[2025-05-02 01:31:58,160] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 98.87 | bwd_microstep: 121.46 | bwd_inner_microstep: 121.34 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1893 +[2025-05-02 01:31:58,643] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.48 | bwd_microstep: 274.95 | bwd_inner_microstep: 274.93 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 01:31:59,119] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.44 | bwd_microstep: 272.93 | bwd_inner_microstep: 272.91 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:31:59,595] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.79 | bwd_microstep: 272.65 | bwd_inner_microstep: 272.63 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 01:32:00,077] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.75 | bwd_microstep: 272.36 | bwd_inner_microstep: 272.34 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:32:00,557] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.73 | bwd_microstep: 272.51 | bwd_inner_microstep: 272.49 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 01:32:01,034] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.87 | bwd_microstep: 272.84 | bwd_inner_microstep: 272.82 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1089 +[2025-05-02 01:32:01,323] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 114.32 | bwd_microstep: 160.80 | bwd_inner_microstep: 160.79 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:32:01,803] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.80 | bwd_microstep: 271.99 | bwd_inner_microstep: 271.97 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:32:02,279] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.03 | bwd_microstep: 271.38 | bwd_inner_microstep: 271.36 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 01:32:02,843] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.04 | optimizer_gradients: 2.18 | optimizer_step: 16.78 +[2025-05-02 01:32:02,843] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.14 | bwd_microstep: 337.55 | bwd_inner_microstep: 272.08 | bwd_allreduce_microstep: 65.42 | step_microstep: 23.82 +[2025-05-02 01:32:02,844] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2785.41 | bwd: 4066.03 | bwd_inner: 4000.21 | bwd_allreduce: 65.54 | step: 24.57 + 14%|█▍ | 1227/8720 [3:16:36<14:53:35, 7.16s/it] {'loss': 0.6086, 'grad_norm': 5.597358226776123, 'learning_rate': 9.682236243097548e-06, 'epoch': 1.41} + 14%|█▍ | 1227/8720 [3:16:36<14:53:35, 7.16s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 01:32:03,321] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.01 | bwd_microstep: 270.13 | bwd_inner_microstep: 270.12 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1894 +[2025-05-02 01:32:03,804] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.26 | bwd_microstep: 274.88 | bwd_inner_microstep: 274.86 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1893 +[2025-05-02 01:32:04,288] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.72 | bwd_microstep: 274.84 | bwd_inner_microstep: 274.82 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1887 +[2025-05-02 01:32:04,766] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.07 | bwd_microstep: 274.40 | bwd_inner_microstep: 274.38 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1888 +[2025-05-02 01:32:05,244] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.18 | bwd_microstep: 274.53 | bwd_inner_microstep: 274.51 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 01:32:05,722] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.24 | bwd_microstep: 273.16 | bwd_inner_microstep: 273.14 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 855 +[2025-05-02 01:32:05,977] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 105.03 | bwd_microstep: 132.26 | bwd_inner_microstep: 132.25 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-02 01:32:06,454] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.80 | bwd_microstep: 273.49 | bwd_inner_microstep: 273.48 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-02 01:32:06,931] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.78 | bwd_microstep: 273.33 | bwd_inner_microstep: 273.31 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 01:32:07,407] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.37 | bwd_microstep: 272.83 | bwd_inner_microstep: 272.81 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:32:07,884] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.16 | bwd_microstep: 272.24 | bwd_inner_microstep: 272.22 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:32:08,361] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.86 | bwd_microstep: 271.11 | bwd_inner_microstep: 271.09 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:32:08,841] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.76 | bwd_microstep: 270.96 | bwd_inner_microstep: 270.94 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:32:09,318] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.17 | bwd_microstep: 271.14 | bwd_inner_microstep: 271.13 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:32:09,798] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.13 | bwd_microstep: 271.10 | bwd_inner_microstep: 271.08 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1416 +[2025-05-02 01:32:10,287] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.17 | optimizer_step: 16.93 +[2025-05-02 01:32:10,288] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 144.73 | bwd_microstep: 301.68 | bwd_inner_microstep: 213.26 | bwd_allreduce_microstep: 88.26 | step_microstep: 24.76 +[2025-05-02 01:32:10,289] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2890.91 | bwd: 4252.10 | bwd_inner: 4163.48 | bwd_allreduce: 88.31 | step: 25.46 + 14%|█▍ | 1228/8720 [3:16:44<15:04:23, 7.24s/it] {'loss': 1.0291, 'grad_norm': 9.966293334960938, 'learning_rate': 9.681584408437236e-06, 'epoch': 1.41} + 14%|█▍ | 1228/8720 [3:16:44<15:04:23, 7.24s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1888 +[2025-05-02 01:32:10,775] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.71 | bwd_microstep: 273.91 | bwd_inner_microstep: 273.89 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1899 +[2025-05-02 01:32:11,258] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.49 | bwd_microstep: 275.49 | bwd_inner_microstep: 275.47 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-02 01:32:11,741] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.40 | bwd_microstep: 274.25 | bwd_inner_microstep: 274.23 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 01:32:12,223] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.58 | bwd_microstep: 273.10 | bwd_inner_microstep: 273.09 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 01:32:12,701] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.33 | bwd_microstep: 272.57 | bwd_inner_microstep: 272.56 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 01:32:13,182] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.54 | bwd_microstep: 272.72 | bwd_inner_microstep: 272.70 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.15 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 01:32:13,660] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.65 | bwd_microstep: 272.58 | bwd_inner_microstep: 272.57 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 01:32:14,142] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.37 | bwd_microstep: 272.63 | bwd_inner_microstep: 272.61 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 01:32:14,620] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.41 | bwd_microstep: 272.41 | bwd_inner_microstep: 272.39 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:32:15,102] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.60 | bwd_microstep: 272.16 | bwd_inner_microstep: 272.14 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:32:15,580] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.32 | bwd_microstep: 272.33 | bwd_inner_microstep: 272.32 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 01:32:16,058] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.74 | bwd_microstep: 272.71 | bwd_inner_microstep: 272.69 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 01:32:16,540] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.35 | bwd_microstep: 272.80 | bwd_inner_microstep: 272.79 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:32:17,021] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.11 | bwd_microstep: 272.34 | bwd_inner_microstep: 272.32 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:32:17,501] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.25 | bwd_microstep: 271.14 | bwd_inner_microstep: 271.12 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1894 +[2025-05-02 01:32:18,095] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.16 | optimizer_step: 16.75 +[2025-05-02 01:32:18,096] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.41 | bwd_microstep: 361.33 | bwd_inner_microstep: 275.39 | bwd_allreduce_microstep: 85.89 | step_microstep: 24.36 +[2025-05-02 01:32:18,097] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 3018.85 | bwd: 4454.50 | bwd_inner: 4368.29 | bwd_allreduce: 85.97 | step: 25.39 + 14%|█▍ | 1229/8720 [3:16:51<15:25:26, 7.41s/it] {'loss': 0.6304, 'grad_norm': 15.93503475189209, 'learning_rate': 9.680931927888892e-06, 'epoch': 1.41} + 14%|█▍ | 1229/8720 [3:16:51<15:25:26, 7.41s/it]dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1368 +[2025-05-02 01:32:18,467] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.19 | bwd_microstep: 206.67 | bwd_inner_microstep: 206.63 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-02 01:32:18,949] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.68 | bwd_microstep: 273.87 | bwd_inner_microstep: 273.86 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 329 +[2025-05-02 01:32:19,180] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 96.34 | bwd_microstep: 116.70 | bwd_inner_microstep: 116.52 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 01:32:19,662] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.29 | bwd_microstep: 272.97 | bwd_inner_microstep: 272.95 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 01:32:20,145] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.40 | bwd_microstep: 273.11 | bwd_inner_microstep: 273.09 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 01:32:20,623] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.10 | bwd_microstep: 272.97 | bwd_inner_microstep: 272.96 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 01:32:21,101] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.11 | bwd_microstep: 272.52 | bwd_inner_microstep: 272.50 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 01:32:21,581] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.28 | bwd_microstep: 272.55 | bwd_inner_microstep: 272.54 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:32:22,063] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.23 | bwd_microstep: 272.44 | bwd_inner_microstep: 272.42 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1354 +[2025-05-02 01:32:22,430] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.75 | bwd_microstep: 206.16 | bwd_inner_microstep: 206.10 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:32:22,909] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.77 | bwd_microstep: 272.49 | bwd_inner_microstep: 272.47 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1345 +[2025-05-02 01:32:23,272] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.98 | bwd_microstep: 205.26 | bwd_inner_microstep: 205.13 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 01:32:23,751] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.71 | bwd_microstep: 272.57 | bwd_inner_microstep: 272.55 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:32:24,225] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.18 | bwd_microstep: 271.04 | bwd_inner_microstep: 271.02 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 319 +[2025-05-02 01:32:24,449] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 92.74 | bwd_microstep: 115.23 | bwd_inner_microstep: 115.08 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2341 +[2025-05-02 01:32:25,125] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 3.05 | optimizer_step: 16.72 +[2025-05-02 01:32:25,125] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 218.26 | bwd_microstep: 415.93 | bwd_inner_microstep: 339.27 | bwd_allreduce_microstep: 76.60 | step_microstep: 25.21 +[2025-05-02 01:32:25,127] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2713.65 | bwd: 3992.59 | bwd_inner: 3915.17 | bwd_allreduce: 76.88 | step: 26.22 + 14%|█▍ | 1230/8720 [3:16:58<15:10:54, 7.30s/it] {'loss': 0.6331, 'grad_norm': 13.446878433227539, 'learning_rate': 9.680278801542536e-06, 'epoch': 1.41} + 14%|█▍ | 1230/8720 [3:16:58<15:10:54, 7.30s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1942 +[2025-05-02 01:32:25,631] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 196.86 | bwd_microstep: 287.53 | bwd_inner_microstep: 287.51 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1905 +[2025-05-02 01:32:26,112] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.84 | bwd_microstep: 275.84 | bwd_inner_microstep: 275.82 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1894 +[2025-05-02 01:32:26,592] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.83 | bwd_microstep: 274.83 | bwd_inner_microstep: 274.81 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1883 +[2025-05-02 01:32:27,071] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.03 | bwd_microstep: 274.18 | bwd_inner_microstep: 274.16 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1121 +[2025-05-02 01:32:27,370] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 119.13 | bwd_microstep: 162.87 | bwd_inner_microstep: 162.80 | bwd_allreduce_microstep: 0.03 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-02 01:32:27,851] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.41 | bwd_microstep: 274.13 | bwd_inner_microstep: 274.11 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1889 +[2025-05-02 01:32:28,332] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.40 | bwd_microstep: 274.44 | bwd_inner_microstep: 274.43 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 859 +[2025-05-02 01:32:28,580] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 98.56 | bwd_microstep: 133.11 | bwd_inner_microstep: 132.94 | bwd_allreduce_microstep: 0.08 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-02 01:32:29,058] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.05 | bwd_microstep: 273.16 | bwd_inner_microstep: 273.14 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 329 +[2025-05-02 01:32:29,272] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 82.75 | bwd_microstep: 115.83 | bwd_inner_microstep: 115.68 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:32:29,750] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.12 | bwd_microstep: 272.59 | bwd_inner_microstep: 272.58 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 01:32:30,228] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.17 | bwd_microstep: 272.70 | bwd_inner_microstep: 272.69 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 325 +[2025-05-02 01:32:30,435] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 75.08 | bwd_microstep: 119.27 | bwd_inner_microstep: 119.13 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1093 +[2025-05-02 01:32:30,725] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 114.51 | bwd_microstep: 161.11 | bwd_inner_microstep: 161.00 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.08 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 833 +[2025-05-02 01:32:30,955] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 90.36 | bwd_microstep: 125.86 | bwd_inner_microstep: 125.64 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 323 +[2025-05-02 01:32:31,271] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.23 | optimizer_step: 16.75 +[2025-05-02 01:32:31,271] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 78.00 | bwd_microstep: 199.70 | bwd_inner_microstep: 132.58 | bwd_allreduce_microstep: 67.04 | step_microstep: 24.03 +[2025-05-02 01:32:31,272] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2366.78 | bwd: 3497.24 | bwd_inner: 3429.08 | bwd_allreduce: 67.49 | step: 25.00 + 14%|█▍ | 1231/8720 [3:17:05<14:27:40, 6.95s/it] {'loss': 1.0236, 'grad_norm': 6.7591986656188965, 'learning_rate': 9.679625029488273e-06, 'epoch': 1.41} + 14%|█▍ | 1231/8720 [3:17:05<14:27:40, 6.95s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:32:31,750] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.52 | bwd_microstep: 270.48 | bwd_inner_microstep: 270.46 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2066 +[2025-05-02 01:32:32,270] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 203.51 | bwd_microstep: 302.05 | bwd_inner_microstep: 302.03 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 900 +[2025-05-02 01:32:32,531] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 103.57 | bwd_microstep: 143.60 | bwd_inner_microstep: 143.58 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 873 +[2025-05-02 01:32:32,774] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.48 | bwd_microstep: 134.46 | bwd_inner_microstep: 134.17 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1896 +[2025-05-02 01:32:33,254] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.08 | bwd_microstep: 274.81 | bwd_inner_microstep: 274.79 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-02 01:32:33,731] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.86 | bwd_microstep: 273.46 | bwd_inner_microstep: 273.45 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 341 +[2025-05-02 01:32:33,947] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 81.42 | bwd_microstep: 121.06 | bwd_inner_microstep: 120.81 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-02 01:32:34,423] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.85 | bwd_microstep: 273.03 | bwd_inner_microstep: 273.01 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-02 01:32:34,900] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.57 | bwd_microstep: 273.77 | bwd_inner_microstep: 273.76 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1355 +[2025-05-02 01:32:35,261] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.57 | bwd_microstep: 205.93 | bwd_inner_microstep: 205.91 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 01:32:35,736] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.94 | bwd_microstep: 272.71 | bwd_inner_microstep: 272.69 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:32:36,213] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.43 | bwd_microstep: 272.45 | bwd_inner_microstep: 272.43 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.14 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:32:36,689] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.21 | bwd_microstep: 272.72 | bwd_inner_microstep: 272.70 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 01:32:37,165] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.70 | bwd_microstep: 272.23 | bwd_inner_microstep: 272.21 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:32:37,641] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.37 | bwd_microstep: 272.36 | bwd_inner_microstep: 272.35 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 01:32:38,213] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.04 | optimizer_gradients: 2.21 | optimizer_step: 17.37 +[2025-05-02 01:32:38,213] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.85 | bwd_microstep: 343.80 | bwd_inner_microstep: 271.43 | bwd_allreduce_microstep: 72.32 | step_microstep: 24.34 +[2025-05-02 01:32:38,215] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2694.67 | bwd: 3978.96 | bwd_inner: 3905.88 | bwd_allreduce: 72.60 | step: 25.38 + 14%|█▍ | 1232/8720 [3:17:11<14:27:12, 6.95s/it] {'loss': 0.6622, 'grad_norm': 4.47556734085083, 'learning_rate': 9.678970611816304e-06, 'epoch': 1.41} + 14%|█▍ | 1232/8720 [3:17:11<14:27:12, 6.95s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1850 +[2025-05-02 01:32:38,691] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.86 | bwd_microstep: 270.05 | bwd_inner_microstep: 270.03 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 517 +[2025-05-02 01:32:38,913] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 82.82 | bwd_microstep: 124.84 | bwd_inner_microstep: 124.71 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1999 +[2025-05-02 01:32:39,422] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 199.13 | bwd_microstep: 294.54 | bwd_inner_microstep: 294.53 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1949 +[2025-05-02 01:32:39,922] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.69 | bwd_microstep: 289.62 | bwd_inner_microstep: 289.60 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1997 +[2025-05-02 01:32:40,430] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 199.44 | bwd_microstep: 294.05 | bwd_inner_microstep: 294.03 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1368 +[2025-05-02 01:32:40,794] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.80 | bwd_microstep: 207.14 | bwd_inner_microstep: 207.08 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-02 01:32:41,270] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.14 | bwd_microstep: 273.47 | bwd_inner_microstep: 273.46 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 01:32:41,746] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.35 | bwd_microstep: 272.69 | bwd_inner_microstep: 272.68 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 01:32:42,225] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.59 | bwd_microstep: 273.07 | bwd_inner_microstep: 273.06 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 01:32:42,705] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.18 | bwd_microstep: 273.06 | bwd_inner_microstep: 273.04 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 01:32:43,185] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.17 | bwd_microstep: 272.55 | bwd_inner_microstep: 272.53 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 01:32:43,666] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.99 | bwd_microstep: 272.95 | bwd_inner_microstep: 272.93 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:32:44,146] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.62 | bwd_microstep: 272.46 | bwd_inner_microstep: 272.45 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 01:32:44,626] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.81 | bwd_microstep: 271.31 | bwd_inner_microstep: 271.29 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 01:32:45,103] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.96 | bwd_microstep: 271.01 | bwd_inner_microstep: 270.99 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 01:32:45,683] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.25 | optimizer_step: 16.96 +[2025-05-02 01:32:45,683] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.54 | bwd_microstep: 348.93 | bwd_inner_microstep: 271.54 | bwd_allreduce_microstep: 77.33 | step_microstep: 24.97 +[2025-05-02 01:32:45,685] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2891.78 | bwd: 4281.78 | bwd_inner: 4203.96 | bwd_allreduce: 77.48 | step: 25.76 + 14%|█▍ | 1233/8720 [3:17:19<14:46:41, 7.11s/it] {'loss': 0.7891, 'grad_norm': 5.95867919921875, 'learning_rate': 9.67831554861691e-06, 'epoch': 1.41} + 14%|█▍ | 1233/8720 [3:17:19<14:46:41, 7.11s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1898 +[2025-05-02 01:32:46,174] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 191.24 | bwd_microstep: 274.44 | bwd_inner_microstep: 274.43 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1950 +[2025-05-02 01:32:46,676] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 197.49 | bwd_microstep: 289.14 | bwd_inner_microstep: 289.12 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-02 01:32:47,155] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.28 | bwd_microstep: 273.40 | bwd_inner_microstep: 273.39 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 01:32:47,630] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.77 | bwd_microstep: 272.67 | bwd_inner_microstep: 272.66 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 01:32:48,108] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.13 | bwd_microstep: 273.36 | bwd_inner_microstep: 273.34 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 01:32:48,585] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.75 | bwd_microstep: 272.59 | bwd_inner_microstep: 272.58 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 331 +[2025-05-02 01:32:48,806] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 83.58 | bwd_microstep: 123.71 | bwd_inner_microstep: 123.58 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 845 +[2025-05-02 01:32:49,047] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.49 | bwd_microstep: 132.93 | bwd_inner_microstep: 132.72 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1354 +[2025-05-02 01:32:49,410] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 142.42 | bwd_microstep: 206.17 | bwd_inner_microstep: 206.11 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.09 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 836 +[2025-05-02 01:32:49,641] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 90.43 | bwd_microstep: 126.08 | bwd_inner_microstep: 125.81 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:32:50,117] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.16 | bwd_microstep: 272.42 | bwd_inner_microstep: 272.40 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:32:50,592] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.91 | bwd_microstep: 272.27 | bwd_inner_microstep: 272.25 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 321 +[2025-05-02 01:32:50,797] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 69.48 | bwd_microstep: 121.30 | bwd_inner_microstep: 121.06 | bwd_allreduce_microstep: 0.09 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:32:51,271] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.88 | bwd_microstep: 270.96 | bwd_inner_microstep: 270.94 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:32:51,748] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.83 | bwd_microstep: 270.85 | bwd_inner_microstep: 270.83 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1849 +[2025-05-02 01:32:52,313] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.23 | optimizer_step: 16.92 +[2025-05-02 01:32:52,313] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.76 | bwd_microstep: 338.53 | bwd_inner_microstep: 271.58 | bwd_allreduce_microstep: 66.91 | step_microstep: 24.14 +[2025-05-02 01:32:52,314] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2560.31 | bwd: 3790.90 | bwd_inner: 3722.96 | bwd_allreduce: 67.29 | step: 25.05 + 14%|█▍ | 1234/8720 [3:17:26<14:28:40, 6.96s/it] {'loss': 0.6952, 'grad_norm': 6.685602188110352, 'learning_rate': 9.67765983998047e-06, 'epoch': 1.42} + 14%|█▍ | 1234/8720 [3:17:26<14:28:40, 6.96s/it]dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1390 +[2025-05-02 01:32:52,686] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 144.12 | bwd_microstep: 208.54 | bwd_inner_microstep: 208.52 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.07 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 922 +[2025-05-02 01:32:52,948] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 101.25 | bwd_microstep: 145.84 | bwd_inner_microstep: 145.79 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1915 +[2025-05-02 01:32:53,430] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.61 | bwd_microstep: 276.06 | bwd_inner_microstep: 276.04 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 881 +[2025-05-02 01:32:53,676] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 96.96 | bwd_microstep: 135.01 | bwd_inner_microstep: 135.00 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 866 +[2025-05-02 01:32:53,917] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.43 | bwd_microstep: 134.08 | bwd_inner_microstep: 133.84 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 01:32:54,398] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.51 | bwd_microstep: 273.53 | bwd_inner_microstep: 273.51 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 01:32:54,879] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.12 | bwd_microstep: 273.38 | bwd_inner_microstep: 273.36 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 858 +[2025-05-02 01:32:55,128] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 98.97 | bwd_microstep: 133.07 | bwd_inner_microstep: 133.03 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 329 +[2025-05-02 01:32:55,349] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 83.77 | bwd_microstep: 121.34 | bwd_inner_microstep: 121.14 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 01:32:55,828] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.56 | bwd_microstep: 273.13 | bwd_inner_microstep: 273.11 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 01:32:56,310] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.15 | bwd_microstep: 272.66 | bwd_inner_microstep: 272.64 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 336 +[2025-05-02 01:32:56,553] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 91.16 | bwd_microstep: 134.36 | bwd_inner_microstep: 134.05 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.11 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 326 +[2025-05-02 01:32:56,780] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 85.16 | bwd_microstep: 125.52 | bwd_inner_microstep: 125.24 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 836 +[2025-05-02 01:32:57,017] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.66 | bwd_microstep: 126.17 | bwd_inner_microstep: 126.14 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:32:57,493] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.67 | bwd_microstep: 271.24 | bwd_inner_microstep: 271.22 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 01:32:58,079] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.20 | optimizer_step: 16.78 +[2025-05-02 01:32:58,080] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.09 | bwd_microstep: 355.92 | bwd_inner_microstep: 271.44 | bwd_allreduce_microstep: 84.43 | step_microstep: 25.30 +[2025-05-02 01:32:58,081] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2206.81 | bwd: 3259.97 | bwd_inner: 3174.28 | bwd_allreduce: 84.89 | step: 26.62 + 14%|█▍ | 1235/8720 [3:17:31<13:43:48, 6.60s/it] {'loss': 0.885, 'grad_norm': 6.350120544433594, 'learning_rate': 9.677003485997444e-06, 'epoch': 1.42} + 14%|█▍ | 1235/8720 [3:17:31<13:43:48, 6.60s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 01:32:58,559] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.99 | bwd_microstep: 270.24 | bwd_inner_microstep: 270.23 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2001 +[2025-05-02 01:32:59,067] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 198.15 | bwd_microstep: 294.34 | bwd_inner_microstep: 294.32 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1946 +[2025-05-02 01:32:59,568] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.66 | bwd_microstep: 288.53 | bwd_inner_microstep: 288.52 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1929 +[2025-05-02 01:33:00,069] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 194.93 | bwd_microstep: 287.22 | bwd_inner_microstep: 287.20 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1883 +[2025-05-02 01:33:00,549] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.63 | bwd_microstep: 273.80 | bwd_inner_microstep: 273.78 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-02 01:33:01,030] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.12 | bwd_microstep: 273.29 | bwd_inner_microstep: 273.27 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-02 01:33:01,511] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.14 | bwd_microstep: 272.88 | bwd_inner_microstep: 272.86 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 326 +[2025-05-02 01:33:01,747] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 91.79 | bwd_microstep: 126.17 | bwd_inner_microstep: 126.01 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 01:33:02,225] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.33 | bwd_microstep: 272.79 | bwd_inner_microstep: 272.77 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 327 +[2025-05-02 01:33:02,443] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 82.47 | bwd_microstep: 119.88 | bwd_inner_microstep: 119.71 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.11 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 329 +[2025-05-02 01:33:02,661] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 80.30 | bwd_microstep: 122.35 | bwd_inner_microstep: 122.11 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:33:03,140] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.93 | bwd_microstep: 272.28 | bwd_inner_microstep: 272.26 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.07 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 831 +[2025-05-02 01:33:03,381] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.63 | bwd_microstep: 130.01 | bwd_inner_microstep: 129.87 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:33:03,859] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.44 | bwd_microstep: 272.25 | bwd_inner_microstep: 272.24 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 01:33:04,338] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.25 | bwd_microstep: 271.03 | bwd_inner_microstep: 271.01 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 01:33:04,921] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.24 | optimizer_step: 17.35 +[2025-05-02 01:33:04,922] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.47 | bwd_microstep: 350.46 | bwd_inner_microstep: 273.72 | bwd_allreduce_microstep: 76.70 | step_microstep: 25.35 +[2025-05-02 01:33:04,923] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2631.85 | bwd: 3897.60 | bwd_inner: 3820.02 | bwd_allreduce: 77.03 | step: 26.46 + 14%|█▍ | 1236/8720 [3:17:38<13:52:41, 6.68s/it] {'loss': 0.7256, 'grad_norm': 6.339244365692139, 'learning_rate': 9.67634648675839e-06, 'epoch': 1.42} + 14%|█▍ | 1236/8720 [3:17:38<13:52:41, 6.68s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 01:33:05,407] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.94 | bwd_microstep: 271.84 | bwd_inner_microstep: 271.82 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 504 +[2025-05-02 01:33:05,620] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 82.24 | bwd_microstep: 117.03 | bwd_inner_microstep: 116.89 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1930 +[2025-05-02 01:33:06,118] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.18 | bwd_microstep: 287.13 | bwd_inner_microstep: 287.11 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1917 +[2025-05-02 01:33:06,600] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.24 | bwd_microstep: 276.24 | bwd_inner_microstep: 276.22 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 895 +[2025-05-02 01:33:06,862] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 111.28 | bwd_microstep: 135.71 | bwd_inner_microstep: 135.41 | bwd_allreduce_microstep: 0.14 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1898 +[2025-05-02 01:33:07,344] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.33 | bwd_microstep: 274.88 | bwd_inner_microstep: 274.87 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 01:33:07,823] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.70 | bwd_microstep: 272.61 | bwd_inner_microstep: 272.59 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-02 01:33:08,305] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.41 | bwd_microstep: 273.90 | bwd_inner_microstep: 273.88 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 01:33:08,783] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.48 | bwd_microstep: 272.25 | bwd_inner_microstep: 272.23 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 847 +[2025-05-02 01:33:09,027] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 96.34 | bwd_microstep: 132.14 | bwd_inner_microstep: 131.96 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.10 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 843 +[2025-05-02 01:33:09,278] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.16 | bwd_microstep: 138.12 | bwd_inner_microstep: 137.94 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:33:09,756] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.66 | bwd_microstep: 272.33 | bwd_inner_microstep: 272.31 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:33:10,235] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.75 | bwd_microstep: 272.27 | bwd_inner_microstep: 272.26 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 320 +[2025-05-02 01:33:10,459] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 80.41 | bwd_microstep: 127.59 | bwd_inner_microstep: 127.28 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:33:10,936] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.85 | bwd_microstep: 271.23 | bwd_inner_microstep: 271.21 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 01:33:11,516] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.14 | optimizer_step: 17.10 +[2025-05-02 01:33:11,517] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.32 | bwd_microstep: 348.98 | bwd_inner_microstep: 271.68 | bwd_allreduce_microstep: 77.25 | step_microstep: 25.54 +[2025-05-02 01:33:11,518] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2542.93 | bwd: 3744.33 | bwd_inner: 3665.81 | bwd_allreduce: 77.79 | step: 26.85 + 14%|█▍ | 1237/8720 [3:17:45<13:49:34, 6.65s/it] {'loss': 0.6266, 'grad_norm': 12.541607856750488, 'learning_rate': 9.675688842353946e-06, 'epoch': 1.42} + 14%|█▍ | 1237/8720 [3:17:45<13:49:34, 6.65s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 01:33:11,999] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.22 | bwd_microstep: 270.17 | bwd_inner_microstep: 270.15 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1905 +[2025-05-02 01:33:12,483] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.45 | bwd_microstep: 276.00 | bwd_inner_microstep: 275.98 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1373 +[2025-05-02 01:33:12,853] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 142.93 | bwd_microstep: 207.70 | bwd_inner_microstep: 207.53 | bwd_allreduce_microstep: 0.08 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-02 01:33:13,334] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.81 | bwd_microstep: 273.20 | bwd_inner_microstep: 273.19 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 862 +[2025-05-02 01:33:13,587] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 102.22 | bwd_microstep: 133.86 | bwd_inner_microstep: 133.62 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 01:33:14,066] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.64 | bwd_microstep: 273.10 | bwd_inner_microstep: 273.09 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 01:33:14,545] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.01 | bwd_microstep: 273.17 | bwd_inner_microstep: 273.16 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 01:33:15,025] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.02 | bwd_microstep: 272.48 | bwd_inner_microstep: 272.47 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 01:33:15,505] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.59 | bwd_microstep: 272.45 | bwd_inner_microstep: 272.44 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.13 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 01:33:15,983] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.05 | bwd_microstep: 272.31 | bwd_inner_microstep: 272.29 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 01:33:16,461] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.68 | bwd_microstep: 272.35 | bwd_inner_microstep: 272.33 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:33:16,939] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.02 | bwd_microstep: 272.18 | bwd_inner_microstep: 272.16 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:33:17,416] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.23 | bwd_microstep: 272.19 | bwd_inner_microstep: 272.17 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 01:33:17,892] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.32 | bwd_microstep: 271.09 | bwd_inner_microstep: 271.07 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 01:33:18,365] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.50 | bwd_microstep: 270.64 | bwd_inner_microstep: 270.62 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 01:33:18,927] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.04 | optimizer_gradients: 2.12 | optimizer_step: 17.15 +[2025-05-02 01:33:18,928] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.04 | bwd_microstep: 336.70 | bwd_inner_microstep: 271.16 | bwd_allreduce_microstep: 65.50 | step_microstep: 24.01 +[2025-05-02 01:33:18,929] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2877.38 | bwd: 4219.65 | bwd_inner: 4153.45 | bwd_allreduce: 65.77 | step: 24.95 + 14%|█▍ | 1238/8720 [3:17:52<14:17:45, 6.88s/it] {'loss': 0.8265, 'grad_norm': 16.561826705932617, 'learning_rate': 9.675030552874844e-06, 'epoch': 1.42} + 14%|█▍ | 1238/8720 [3:17:52<14:17:45, 6.88s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 01:33:19,406] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.97 | bwd_microstep: 270.39 | bwd_inner_microstep: 270.37 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 932 +[2025-05-02 01:33:19,670] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 103.37 | bwd_microstep: 146.49 | bwd_inner_microstep: 146.26 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-02 01:33:20,148] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.50 | bwd_microstep: 274.18 | bwd_inner_microstep: 274.16 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-02 01:33:20,627] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.54 | bwd_microstep: 273.73 | bwd_inner_microstep: 273.71 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 849 +[2025-05-02 01:33:20,870] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 96.40 | bwd_microstep: 132.67 | bwd_inner_microstep: 132.41 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 01:33:21,346] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.20 | bwd_microstep: 272.80 | bwd_inner_microstep: 272.78 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 01:33:21,822] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.36 | bwd_microstep: 272.97 | bwd_inner_microstep: 272.95 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:33:22,297] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.36 | bwd_microstep: 272.51 | bwd_inner_microstep: 272.49 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:33:22,775] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.28 | bwd_microstep: 272.40 | bwd_inner_microstep: 272.38 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:33:23,253] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.55 | bwd_microstep: 272.55 | bwd_inner_microstep: 272.53 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 01:33:23,733] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.50 | bwd_microstep: 273.09 | bwd_inner_microstep: 273.07 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:33:24,212] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.30 | bwd_microstep: 272.56 | bwd_inner_microstep: 272.54 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 01:33:24,691] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.98 | bwd_microstep: 271.43 | bwd_inner_microstep: 271.41 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:33:25,172] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.39 | bwd_microstep: 272.30 | bwd_inner_microstep: 272.28 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 01:33:25,652] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.16 | bwd_microstep: 272.42 | bwd_inner_microstep: 272.40 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:33:26,230] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.13 | optimizer_step: 16.66 +[2025-05-02 01:33:26,231] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.68 | bwd_microstep: 347.61 | bwd_inner_microstep: 271.86 | bwd_allreduce_microstep: 75.70 | step_microstep: 24.33 +[2025-05-02 01:33:26,232] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2841.21 | bwd: 4170.14 | bwd_inner: 4093.63 | bwd_allreduce: 76.02 | step: 25.16 + 14%|█▍ | 1239/8720 [3:17:59<14:33:35, 7.01s/it] {'loss': 0.6274, 'grad_norm': 11.567801475524902, 'learning_rate': 9.674371618411905e-06, 'epoch': 1.42} + 14%|█▍ | 1239/8720 [3:17:59<14:33:35, 7.01s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 01:33:26,712] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.50 | bwd_microstep: 270.25 | bwd_inner_microstep: 270.23 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 462 +[2025-05-02 01:33:26,945] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 88.10 | bwd_microstep: 127.58 | bwd_inner_microstep: 127.27 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.08 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 457 +[2025-05-02 01:33:27,155] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 76.01 | bwd_microstep: 120.39 | bwd_inner_microstep: 120.26 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.08 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1405 +[2025-05-02 01:33:27,524] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 144.41 | bwd_microstep: 210.66 | bwd_inner_microstep: 210.64 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1120 +[2025-05-02 01:33:27,819] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 117.43 | bwd_microstep: 162.81 | bwd_inner_microstep: 162.79 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 01:33:28,295] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.94 | bwd_microstep: 273.29 | bwd_inner_microstep: 273.27 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:33:28,772] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.83 | bwd_microstep: 272.92 | bwd_inner_microstep: 272.91 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:33:29,249] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.06 | bwd_microstep: 272.54 | bwd_inner_microstep: 272.52 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 325 +[2025-05-02 01:33:29,478] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 86.77 | bwd_microstep: 125.56 | bwd_inner_microstep: 125.36 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:33:29,954] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.62 | bwd_microstep: 272.27 | bwd_inner_microstep: 272.25 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:33:30,431] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.51 | bwd_microstep: 271.25 | bwd_inner_microstep: 271.23 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 01:33:30,907] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.05 | bwd_microstep: 272.30 | bwd_inner_microstep: 272.28 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 01:33:31,381] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.73 | bwd_microstep: 271.09 | bwd_inner_microstep: 271.07 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:33:31,855] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.31 | bwd_microstep: 271.10 | bwd_inner_microstep: 271.08 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:33:32,330] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.30 | bwd_microstep: 271.30 | bwd_inner_microstep: 271.29 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:33:32,937] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.19 | optimizer_step: 17.11 +[2025-05-02 01:33:32,937] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.02 | bwd_microstep: 374.30 | bwd_inner_microstep: 271.79 | bwd_allreduce_microstep: 102.46 | step_microstep: 26.52 +[2025-05-02 01:33:32,939] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2583.29 | bwd: 3839.66 | bwd_inner: 3736.38 | bwd_allreduce: 102.76 | step: 27.38 + 14%|█▍ | 1240/8720 [3:18:06<14:22:17, 6.92s/it] {'loss': 0.5651, 'grad_norm': 20.356426239013672, 'learning_rate': 9.673712039056033e-06, 'epoch': 1.42} + 14%|█▍ | 1240/8720 [3:18:06<14:22:17, 6.92s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 01:33:33,421] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.17 | bwd_microstep: 270.27 | bwd_inner_microstep: 270.26 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1981 +[2025-05-02 01:33:33,931] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 199.22 | bwd_microstep: 291.87 | bwd_inner_microstep: 291.85 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1887 +[2025-05-02 01:33:34,413] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.42 | bwd_microstep: 274.54 | bwd_inner_microstep: 274.52 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-02 01:33:34,893] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.26 | bwd_microstep: 273.23 | bwd_inner_microstep: 273.22 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 01:33:35,373] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.41 | bwd_microstep: 272.59 | bwd_inner_microstep: 272.58 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 835 +[2025-05-02 01:33:35,629] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 112.91 | bwd_microstep: 125.29 | bwd_inner_microstep: 125.10 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.12 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 845 +[2025-05-02 01:33:35,897] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 114.92 | bwd_microstep: 131.49 | bwd_inner_microstep: 131.24 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 01:33:36,378] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.21 | bwd_microstep: 272.66 | bwd_inner_microstep: 272.65 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:33:36,858] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.45 | bwd_microstep: 272.18 | bwd_inner_microstep: 272.16 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:33:37,338] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.74 | bwd_microstep: 272.44 | bwd_inner_microstep: 272.42 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:33:37,816] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.95 | bwd_microstep: 272.18 | bwd_inner_microstep: 272.16 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 321 +[2025-05-02 01:33:38,049] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 98.63 | bwd_microstep: 118.56 | bwd_inner_microstep: 118.40 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:33:38,527] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.67 | bwd_microstep: 271.27 | bwd_inner_microstep: 271.25 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:33:39,004] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.70 | bwd_microstep: 271.31 | bwd_inner_microstep: 271.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 01:33:39,479] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.26 | bwd_microstep: 270.91 | bwd_inner_microstep: 270.89 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 01:33:40,065] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.16 | optimizer_step: 16.74 +[2025-05-02 01:33:40,066] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.82 | bwd_microstep: 357.13 | bwd_inner_microstep: 271.37 | bwd_allreduce_microstep: 85.72 | step_microstep: 25.18 +[2025-05-02 01:33:40,067] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2788.27 | bwd: 4018.04 | bwd_inner: 3931.39 | bwd_allreduce: 86.09 | step: 26.45 + 14%|█▍ | 1241/8720 [3:18:13<14:29:59, 6.98s/it] {'loss': 0.7274, 'grad_norm': 10.88502311706543, 'learning_rate': 9.673051814898233e-06, 'epoch': 1.42} + 14%|█▍ | 1241/8720 [3:18:13<14:29:59, 6.98s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:33:40,546] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.22 | bwd_microstep: 270.66 | bwd_inner_microstep: 270.64 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1551 +[2025-05-02 01:33:40,950] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 150.45 | bwd_microstep: 238.52 | bwd_inner_microstep: 238.33 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.09 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1389 +[2025-05-02 01:33:41,319] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 144.87 | bwd_microstep: 209.04 | bwd_inner_microstep: 208.93 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.10 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 341 +[2025-05-02 01:33:41,535] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 82.25 | bwd_microstep: 119.56 | bwd_inner_microstep: 119.19 | bwd_allreduce_microstep: 0.15 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1888 +[2025-05-02 01:33:42,013] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.80 | bwd_microstep: 274.51 | bwd_inner_microstep: 274.49 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1894 +[2025-05-02 01:33:42,493] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.93 | bwd_microstep: 274.85 | bwd_inner_microstep: 274.83 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 341 +[2025-05-02 01:33:42,726] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 97.09 | bwd_microstep: 118.57 | bwd_inner_microstep: 118.44 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 01:33:43,204] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.63 | bwd_microstep: 274.01 | bwd_inner_microstep: 273.99 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 01:33:43,680] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.60 | bwd_microstep: 273.10 | bwd_inner_microstep: 273.08 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 326 +[2025-05-02 01:33:43,913] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.67 | bwd_microstep: 120.18 | bwd_inner_microstep: 120.01 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-02 01:33:44,390] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.34 | bwd_microstep: 273.60 | bwd_inner_microstep: 273.59 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 01:33:44,867] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.15 | bwd_microstep: 272.84 | bwd_inner_microstep: 272.82 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 01:33:45,343] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.10 | bwd_microstep: 271.37 | bwd_inner_microstep: 271.35 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:33:45,820] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.27 | bwd_microstep: 271.35 | bwd_inner_microstep: 271.33 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 01:33:46,297] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.58 | bwd_microstep: 271.10 | bwd_inner_microstep: 271.08 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2089 +[2025-05-02 01:33:46,919] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.04 | optimizer_gradients: 2.09 | optimizer_step: 16.60 +[2025-05-02 01:33:46,919] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 203.78 | bwd_microstep: 378.12 | bwd_inner_microstep: 304.83 | bwd_allreduce_microstep: 73.25 | step_microstep: 23.53 +[2025-05-02 01:33:46,920] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2661.43 | bwd: 3911.49 | bwd_inner: 3837.11 | bwd_allreduce: 73.78 | step: 24.59 + 14%|█▍ | 1242/8720 [3:18:20<14:25:09, 6.94s/it] {'loss': 0.7324, 'grad_norm': 5.83687162399292, 'learning_rate': 9.672390946029588e-06, 'epoch': 1.42} + 14%|█▍ | 1242/8720 [3:18:20<14:25:09, 6.94s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1957 +[2025-05-02 01:33:47,426] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 196.38 | bwd_microstep: 289.18 | bwd_inner_microstep: 289.16 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 01:33:47,903] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.20 | bwd_microstep: 273.22 | bwd_inner_microstep: 273.20 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-02 01:33:48,383] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.49 | bwd_microstep: 274.11 | bwd_inner_microstep: 274.09 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-02 01:33:48,860] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.72 | bwd_microstep: 273.40 | bwd_inner_microstep: 273.39 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:33:49,335] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.33 | bwd_microstep: 272.34 | bwd_inner_microstep: 272.32 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 01:33:49,812] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.13 | bwd_microstep: 272.42 | bwd_inner_microstep: 272.40 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:33:50,289] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.23 | bwd_microstep: 273.12 | bwd_inner_microstep: 273.10 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 837 +[2025-05-02 01:33:50,526] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.75 | bwd_microstep: 125.98 | bwd_inner_microstep: 125.79 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:33:51,004] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.71 | bwd_microstep: 272.60 | bwd_inner_microstep: 272.58 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 01:33:51,483] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.50 | bwd_microstep: 272.91 | bwd_inner_microstep: 272.89 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:33:51,960] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.84 | bwd_microstep: 272.51 | bwd_inner_microstep: 272.49 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:33:52,435] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.37 | bwd_microstep: 272.42 | bwd_inner_microstep: 272.40 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 01:33:52,912] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.31 | bwd_microstep: 272.86 | bwd_inner_microstep: 272.84 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.14 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:33:53,386] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.78 | bwd_microstep: 271.22 | bwd_inner_microstep: 271.20 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:33:53,861] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.71 | bwd_microstep: 271.33 | bwd_inner_microstep: 271.31 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 320 +[2025-05-02 01:33:54,190] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.11 | optimizer_step: 16.68 +[2025-05-02 01:33:54,191] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 81.95 | bwd_microstep: 208.42 | bwd_inner_microstep: 132.62 | bwd_allreduce_microstep: 75.64 | step_microstep: 24.31 +[2025-05-02 01:33:54,192] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2825.13 | bwd: 4168.05 | bwd_inner: 4091.85 | bwd_allreduce: 75.81 | step: 25.18 + 14%|█▍ | 1243/8720 [3:18:27<14:37:27, 7.04s/it] {'loss': 1.0153, 'grad_norm': 11.217443466186523, 'learning_rate': 9.671729432541276e-06, 'epoch': 1.43} + 14%|█▍ | 1243/8720 [3:18:27<14:37:27, 7.04s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1920 +[2025-05-02 01:33:54,681] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.14 | bwd_microstep: 275.89 | bwd_inner_microstep: 275.87 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.13 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1931 +[2025-05-02 01:33:55,183] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.95 | bwd_microstep: 287.80 | bwd_inner_microstep: 287.78 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1934 +[2025-05-02 01:33:55,682] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 196.03 | bwd_microstep: 288.09 | bwd_inner_microstep: 288.07 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-02 01:33:56,163] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.74 | bwd_microstep: 273.32 | bwd_inner_microstep: 273.30 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 01:33:56,645] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.53 | bwd_microstep: 272.78 | bwd_inner_microstep: 272.76 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-02 01:33:57,127] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.95 | bwd_microstep: 273.16 | bwd_inner_microstep: 273.14 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 01:33:57,608] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.75 | bwd_microstep: 273.35 | bwd_inner_microstep: 273.33 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 01:33:58,087] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.74 | bwd_microstep: 272.71 | bwd_inner_microstep: 272.70 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 01:33:58,567] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.37 | bwd_microstep: 272.74 | bwd_inner_microstep: 272.72 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:33:59,046] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.69 | bwd_microstep: 272.32 | bwd_inner_microstep: 272.31 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 328 +[2025-05-02 01:33:59,272] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 89.66 | bwd_microstep: 117.90 | bwd_inner_microstep: 117.76 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 01:33:59,749] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.46 | bwd_microstep: 272.42 | bwd_inner_microstep: 272.41 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:34:00,229] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.83 | bwd_microstep: 272.35 | bwd_inner_microstep: 272.33 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:34:00,706] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.02 | bwd_microstep: 272.19 | bwd_inner_microstep: 272.17 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:34:01,184] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.97 | bwd_microstep: 271.12 | bwd_inner_microstep: 271.10 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 01:34:01,763] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.17 | optimizer_step: 16.63 +[2025-05-02 01:34:01,764] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.73 | bwd_microstep: 347.49 | bwd_inner_microstep: 271.47 | bwd_allreduce_microstep: 75.97 | step_microstep: 24.31 +[2025-05-02 01:34:01,765] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2932.15 | bwd: 4315.67 | bwd_inner: 4239.25 | bwd_allreduce: 76.11 | step: 25.35 + 14%|█▍ | 1244/8720 [3:18:35<14:57:13, 7.20s/it] {'loss': 0.8306, 'grad_norm': 7.440922737121582, 'learning_rate': 9.67106727452456e-06, 'epoch': 1.43} + 14%|█▍ | 1244/8720 [3:18:35<14:57:13, 7.20s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 01:34:02,245] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.43 | bwd_microstep: 270.07 | bwd_inner_microstep: 270.06 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1950 +[2025-05-02 01:34:02,749] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 196.28 | bwd_microstep: 289.27 | bwd_inner_microstep: 289.26 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1897 +[2025-05-02 01:34:03,230] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.84 | bwd_microstep: 275.02 | bwd_inner_microstep: 275.01 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1894 +[2025-05-02 01:34:03,711] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.88 | bwd_microstep: 274.98 | bwd_inner_microstep: 274.96 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-02 01:34:04,191] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.57 | bwd_microstep: 273.68 | bwd_inner_microstep: 273.67 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 344 +[2025-05-02 01:34:04,417] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 90.12 | bwd_microstep: 119.06 | bwd_inner_microstep: 118.74 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 01:34:04,897] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.93 | bwd_microstep: 273.22 | bwd_inner_microstep: 273.20 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 01:34:05,378] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.45 | bwd_microstep: 273.03 | bwd_inner_microstep: 273.01 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 333 +[2025-05-02 01:34:05,615] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.49 | bwd_microstep: 123.47 | bwd_inner_microstep: 123.32 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:34:06,092] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.89 | bwd_microstep: 272.24 | bwd_inner_microstep: 272.22 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 01:34:06,573] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.30 | bwd_microstep: 273.19 | bwd_inner_microstep: 273.17 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 323 +[2025-05-02 01:34:06,798] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 90.68 | bwd_microstep: 118.50 | bwd_inner_microstep: 118.33 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 835 +[2025-05-02 01:34:07,034] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.81 | bwd_microstep: 126.09 | bwd_inner_microstep: 126.04 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 01:34:07,512] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.00 | bwd_microstep: 271.48 | bwd_inner_microstep: 271.46 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:34:07,989] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.93 | bwd_microstep: 271.15 | bwd_inner_microstep: 271.13 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.17 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:34:08,557] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.17 | optimizer_step: 16.81 +[2025-05-02 01:34:08,557] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.44 | bwd_microstep: 339.18 | bwd_inner_microstep: 271.75 | bwd_allreduce_microstep: 67.38 | step_microstep: 24.12 +[2025-05-02 01:34:08,558] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2635.69 | bwd: 3843.71 | bwd_inner: 3775.44 | bwd_allreduce: 67.71 | step: 25.19 + 14%|█▍ | 1245/8720 [3:18:42<14:41:48, 7.08s/it] {'loss': 0.7603, 'grad_norm': 10.487914085388184, 'learning_rate': 9.670404472070792e-06, 'epoch': 1.43} + 14%|█▍ | 1245/8720 [3:18:42<14:41:48, 7.08s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:34:09,037] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.98 | bwd_microstep: 270.57 | bwd_inner_microstep: 270.56 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-02 01:34:09,518] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.68 | bwd_microstep: 274.51 | bwd_inner_microstep: 274.49 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1883 +[2025-05-02 01:34:09,999] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.62 | bwd_microstep: 274.32 | bwd_inner_microstep: 274.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 345 +[2025-05-02 01:34:10,216] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 82.24 | bwd_microstep: 121.72 | bwd_inner_microstep: 121.59 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 864 +[2025-05-02 01:34:10,461] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.61 | bwd_microstep: 134.34 | bwd_inner_microstep: 134.16 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 01:34:10,941] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.06 | bwd_microstep: 273.24 | bwd_inner_microstep: 273.22 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:34:11,421] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.28 | bwd_microstep: 272.37 | bwd_inner_microstep: 272.35 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 01:34:11,901] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.44 | bwd_microstep: 273.12 | bwd_inner_microstep: 273.10 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:34:12,382] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.67 | bwd_microstep: 272.41 | bwd_inner_microstep: 272.40 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 01:34:12,862] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.60 | bwd_microstep: 272.37 | bwd_inner_microstep: 272.35 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:34:13,344] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.13 | bwd_microstep: 272.07 | bwd_inner_microstep: 272.06 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 01:34:13,824] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.04 | bwd_microstep: 272.12 | bwd_inner_microstep: 272.10 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 01:34:14,304] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.98 | bwd_microstep: 272.05 | bwd_inner_microstep: 272.03 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:34:14,780] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.53 | bwd_microstep: 271.08 | bwd_inner_microstep: 271.06 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:34:15,260] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.01 | bwd_microstep: 271.15 | bwd_inner_microstep: 271.13 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 01:34:15,840] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.18 | optimizer_step: 16.84 +[2025-05-02 01:34:15,841] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.34 | bwd_microstep: 348.53 | bwd_inner_microstep: 271.72 | bwd_allreduce_microstep: 76.76 | step_microstep: 24.72 +[2025-05-02 01:34:15,842] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2814.80 | bwd: 4146.03 | bwd_inner: 4068.68 | bwd_allreduce: 76.95 | step: 25.55 + 14%|█▍ | 1246/8720 [3:18:49<14:49:26, 7.14s/it] {'loss': 0.5605, 'grad_norm': 12.522101402282715, 'learning_rate': 9.669741025271418e-06, 'epoch': 1.43} + 14%|█▍ | 1246/8720 [3:18:49<14:49:26, 7.14s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 01:34:16,324] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.69 | bwd_microstep: 270.54 | bwd_inner_microstep: 270.52 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1934 +[2025-05-02 01:34:16,823] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.03 | bwd_microstep: 287.81 | bwd_inner_microstep: 287.79 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 01:34:17,299] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.26 | bwd_microstep: 272.79 | bwd_inner_microstep: 272.77 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 01:34:17,776] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.71 | bwd_microstep: 273.15 | bwd_inner_microstep: 273.13 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 01:34:18,253] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.98 | bwd_microstep: 272.78 | bwd_inner_microstep: 272.76 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 01:34:18,731] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.89 | bwd_microstep: 273.09 | bwd_inner_microstep: 273.07 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 01:34:19,208] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.97 | bwd_microstep: 272.84 | bwd_inner_microstep: 272.82 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:34:19,685] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.13 | bwd_microstep: 272.64 | bwd_inner_microstep: 272.62 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 01:34:20,161] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.87 | bwd_microstep: 272.52 | bwd_inner_microstep: 272.50 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:34:20,637] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.28 | bwd_microstep: 272.61 | bwd_inner_microstep: 272.59 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:34:21,113] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.50 | bwd_microstep: 271.44 | bwd_inner_microstep: 271.42 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.21 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1344 +[2025-05-02 01:34:21,477] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.14 | bwd_microstep: 204.86 | bwd_inner_microstep: 204.68 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 01:34:21,955] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.29 | bwd_microstep: 271.54 | bwd_inner_microstep: 271.52 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 01:34:22,432] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.35 | bwd_microstep: 271.51 | bwd_inner_microstep: 271.49 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:34:22,910] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.76 | bwd_microstep: 271.46 | bwd_inner_microstep: 271.44 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:34:23,490] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.21 | optimizer_step: 16.90 +[2025-05-02 01:34:23,490] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.04 | bwd_microstep: 348.68 | bwd_inner_microstep: 271.67 | bwd_allreduce_microstep: 76.94 | step_microstep: 24.84 +[2025-05-02 01:34:23,492] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2973.59 | bwd: 4380.28 | bwd_inner: 4302.83 | bwd_allreduce: 77.09 | step: 26.06 + 14%|█▍ | 1247/8720 [3:18:57<15:08:20, 7.29s/it] {'loss': 0.8216, 'grad_norm': 11.876556396484375, 'learning_rate': 9.669076934217967e-06, 'epoch': 1.43} + 14%|█▍ | 1247/8720 [3:18:57<15:08:20, 7.29s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 01:34:23,974] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.03 | bwd_microstep: 270.56 | bwd_inner_microstep: 270.54 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 859 +[2025-05-02 01:34:24,217] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.59 | bwd_microstep: 134.83 | bwd_inner_microstep: 134.52 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-02 01:34:24,696] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.74 | bwd_microstep: 273.99 | bwd_inner_microstep: 273.98 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-02 01:34:25,175] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.96 | bwd_microstep: 273.74 | bwd_inner_microstep: 273.72 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.09 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 328 +[2025-05-02 01:34:25,436] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 81.32 | bwd_microstep: 164.46 | bwd_inner_microstep: 164.32 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 01:34:25,913] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.49 | bwd_microstep: 273.12 | bwd_inner_microstep: 273.10 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 01:34:26,393] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.06 | bwd_microstep: 272.99 | bwd_inner_microstep: 272.97 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 01:34:26,871] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.97 | bwd_microstep: 273.03 | bwd_inner_microstep: 273.01 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:34:27,348] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.61 | bwd_microstep: 272.82 | bwd_inner_microstep: 272.80 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.07 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:34:27,824] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.29 | bwd_microstep: 272.60 | bwd_inner_microstep: 272.58 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:34:28,298] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.39 | bwd_microstep: 271.20 | bwd_inner_microstep: 271.18 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 833 +[2025-05-02 01:34:28,551] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 90.79 | bwd_microstep: 146.64 | bwd_inner_microstep: 146.51 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 01:34:29,025] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.36 | bwd_microstep: 271.48 | bwd_inner_microstep: 271.46 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:34:29,500] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.59 | bwd_microstep: 271.16 | bwd_inner_microstep: 271.14 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1961 +[2025-05-02 01:34:30,002] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 196.08 | bwd_microstep: 290.23 | bwd_inner_microstep: 290.21 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1923 +[2025-05-02 01:34:30,591] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.15 | optimizer_step: 16.66 +[2025-05-02 01:34:30,592] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 194.45 | bwd_microstep: 355.31 | bwd_inner_microstep: 287.91 | bwd_allreduce_microstep: 67.32 | step_microstep: 23.79 +[2025-05-02 01:34:30,593] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2729.43 | bwd: 4088.22 | bwd_inner: 4020.10 | bwd_allreduce: 67.58 | step: 24.81 + 14%|█▍ | 1248/8720 [3:19:04<15:00:59, 7.23s/it] {'loss': 0.5285, 'grad_norm': 8.631609916687012, 'learning_rate': 9.66841219900206e-06, 'epoch': 1.43} + 14%|█▍ | 1248/8720 [3:19:04<15:00:59, 7.23s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:34:31,073] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.51 | bwd_microstep: 271.98 | bwd_inner_microstep: 271.96 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1427 +[2025-05-02 01:34:31,450] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 147.14 | bwd_microstep: 214.15 | bwd_inner_microstep: 213.96 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1934 +[2025-05-02 01:34:31,949] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.62 | bwd_microstep: 288.35 | bwd_inner_microstep: 288.33 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1886 +[2025-05-02 01:34:32,428] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.06 | bwd_microstep: 274.66 | bwd_inner_microstep: 274.64 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-02 01:34:32,907] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.07 | bwd_microstep: 274.48 | bwd_inner_microstep: 274.47 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 01:34:33,385] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.68 | bwd_microstep: 273.77 | bwd_inner_microstep: 273.75 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 01:34:33,861] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.08 | bwd_microstep: 272.61 | bwd_inner_microstep: 272.59 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:34:34,337] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.78 | bwd_microstep: 272.36 | bwd_inner_microstep: 272.34 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 01:34:34,814] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.32 | bwd_microstep: 272.85 | bwd_inner_microstep: 272.83 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:34:35,292] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.79 | bwd_microstep: 272.84 | bwd_inner_microstep: 272.83 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1345 +[2025-05-02 01:34:35,654] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.58 | bwd_microstep: 205.70 | bwd_inner_microstep: 205.50 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:34:36,130] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.80 | bwd_microstep: 271.35 | bwd_inner_microstep: 271.33 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:34:36,606] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.54 | bwd_microstep: 271.39 | bwd_inner_microstep: 271.37 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 828 +[2025-05-02 01:34:36,851] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 92.75 | bwd_microstep: 137.64 | bwd_inner_microstep: 137.31 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1850 +[2025-05-02 01:34:37,326] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.52 | bwd_microstep: 271.06 | bwd_inner_microstep: 271.04 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 01:34:37,890] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.04 | optimizer_gradients: 2.11 | optimizer_step: 16.66 +[2025-05-02 01:34:37,890] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.80 | bwd_microstep: 337.72 | bwd_inner_microstep: 271.58 | bwd_allreduce_microstep: 66.08 | step_microstep: 23.62 +[2025-05-02 01:34:37,891] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2836.77 | bwd: 4183.01 | bwd_inner: 4115.91 | bwd_allreduce: 66.48 | step: 24.77 + 14%|█▍ | 1249/8720 [3:19:11<15:03:14, 7.25s/it] {'loss': 0.6319, 'grad_norm': 7.842474460601807, 'learning_rate': 9.667746819715408e-06, 'epoch': 1.43} + 14%|█▍ | 1249/8720 [3:19:11<15:03:14, 7.25s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 429 +[2025-05-02 01:34:38,134] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 71.99 | bwd_microstep: 152.81 | bwd_inner_microstep: 152.61 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1945 +[2025-05-02 01:34:38,635] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 197.12 | bwd_microstep: 289.28 | bwd_inner_microstep: 289.26 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 347 +[2025-05-02 01:34:38,867] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 67.73 | bwd_microstep: 150.54 | bwd_inner_microstep: 150.42 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-02 01:34:39,345] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.57 | bwd_microstep: 273.93 | bwd_inner_microstep: 273.91 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 01:34:39,824] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.79 | bwd_microstep: 273.77 | bwd_inner_microstep: 273.75 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-02 01:34:40,306] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.34 | bwd_microstep: 274.65 | bwd_inner_microstep: 274.64 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-02 01:34:40,788] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.16 | bwd_microstep: 274.71 | bwd_inner_microstep: 274.69 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 348 +[2025-05-02 01:34:41,055] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 96.04 | bwd_microstep: 154.32 | bwd_inner_microstep: 154.16 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 01:34:41,534] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.39 | bwd_microstep: 273.27 | bwd_inner_microstep: 273.25 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 01:34:42,013] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.13 | bwd_microstep: 272.71 | bwd_inner_microstep: 272.69 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 01:34:42,496] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.50 | bwd_microstep: 272.96 | bwd_inner_microstep: 272.95 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:34:42,975] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.38 | bwd_microstep: 272.51 | bwd_inner_microstep: 272.49 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:34:43,454] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.36 | bwd_microstep: 272.44 | bwd_inner_microstep: 272.42 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:34:43,933] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.65 | bwd_microstep: 272.44 | bwd_inner_microstep: 272.42 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1351 +[2025-05-02 01:34:44,297] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.96 | bwd_microstep: 206.22 | bwd_inner_microstep: 205.96 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:34:44,862] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.10 | optimizer_step: 16.68 +[2025-05-02 01:34:44,863] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.17 | bwd_microstep: 339.03 | bwd_inner_microstep: 272.84 | bwd_allreduce_microstep: 66.10 | step_microstep: 23.79 +[2025-05-02 01:34:44,864] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2649.93 | bwd: 4025.67 | bwd_inner: 3958.58 | bwd_allreduce: 66.49 | step: 24.97 + 14%|█▍ | 1250/8720 [3:19:18<14:52:36, 7.17s/it] {'loss': 1.0861, 'grad_norm': 10.831257820129395, 'learning_rate': 9.667080796449806e-06, 'epoch': 1.43} + 14%|█▍ | 1250/8720 [3:19:18<14:52:36, 7.17s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 01:34:45,342] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.29 | bwd_microstep: 270.43 | bwd_inner_microstep: 270.42 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1910 +[2025-05-02 01:34:45,823] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.52 | bwd_microstep: 276.45 | bwd_inner_microstep: 276.43 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1909 +[2025-05-02 01:34:46,305] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.72 | bwd_microstep: 276.61 | bwd_inner_microstep: 276.59 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1883 +[2025-05-02 01:34:46,785] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.63 | bwd_microstep: 274.50 | bwd_inner_microstep: 274.48 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1379 +[2025-05-02 01:34:47,156] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 144.53 | bwd_microstep: 208.54 | bwd_inner_microstep: 208.39 | bwd_allreduce_microstep: 0.08 | step_microstep: 0.11 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1365 +[2025-05-02 01:34:47,522] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.51 | bwd_microstep: 207.52 | bwd_inner_microstep: 207.37 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 01:34:48,002] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.94 | bwd_microstep: 273.68 | bwd_inner_microstep: 273.66 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 853 +[2025-05-02 01:34:48,270] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 96.05 | bwd_microstep: 153.34 | bwd_inner_microstep: 153.01 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 01:34:48,749] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.60 | bwd_microstep: 272.80 | bwd_inner_microstep: 272.78 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 01:34:49,229] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.81 | bwd_microstep: 273.17 | bwd_inner_microstep: 273.16 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 329 +[2025-05-02 01:34:49,478] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 83.83 | bwd_microstep: 149.57 | bwd_inner_microstep: 149.37 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 01:34:49,955] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.84 | bwd_microstep: 272.86 | bwd_inner_microstep: 272.84 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 01:34:50,434] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.00 | bwd_microstep: 273.09 | bwd_inner_microstep: 273.08 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:34:50,911] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.73 | bwd_microstep: 272.53 | bwd_inner_microstep: 272.52 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.07 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 315 +[2025-05-02 01:34:51,157] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 78.95 | bwd_microstep: 150.80 | bwd_inner_microstep: 150.47 | bwd_allreduce_microstep: 0.14 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 01:34:51,721] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.04 | optimizer_gradients: 2.16 | optimizer_step: 16.62 +[2025-05-02 01:34:51,721] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.78 | bwd_microstep: 337.41 | bwd_inner_microstep: 271.52 | bwd_allreduce_microstep: 65.84 | step_microstep: 23.60 +[2025-05-02 01:34:51,723] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2617.39 | bwd: 3943.45 | bwd_inner: 3876.29 | bwd_allreduce: 66.37 | step: 24.88 + 14%|█▍ | 1251/8720 [3:19:25<14:40:52, 7.08s/it] {'loss': 1.0101, 'grad_norm': 4.769201278686523, 'learning_rate': 9.666414129297144e-06, 'epoch': 1.43} + 14%|█▍ | 1251/8720 [3:19:25<14:40:52, 7.08s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1982 +[2025-05-02 01:34:52,231] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 197.19 | bwd_microstep: 291.45 | bwd_inner_microstep: 291.44 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1925 +[2025-05-02 01:34:52,730] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 196.85 | bwd_microstep: 287.38 | bwd_inner_microstep: 287.37 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1368 +[2025-05-02 01:34:53,094] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.07 | bwd_microstep: 207.27 | bwd_inner_microstep: 207.08 | bwd_allreduce_microstep: 0.10 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 01:34:53,570] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.89 | bwd_microstep: 272.99 | bwd_inner_microstep: 272.97 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 836 +[2025-05-02 01:34:53,818] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 91.06 | bwd_microstep: 142.59 | bwd_inner_microstep: 142.40 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 332 +[2025-05-02 01:34:54,058] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 76.34 | bwd_microstep: 151.18 | bwd_inner_microstep: 150.99 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 01:34:54,534] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.74 | bwd_microstep: 272.78 | bwd_inner_microstep: 272.77 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 01:34:55,012] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.30 | bwd_microstep: 273.28 | bwd_inner_microstep: 273.26 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 6, images per sample: 6.0, dynamic token length: 1607 +[2025-05-02 01:34:55,440] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 165.42 | bwd_microstep: 244.78 | bwd_inner_microstep: 244.62 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:34:55,917] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.92 | bwd_microstep: 272.47 | bwd_inner_microstep: 272.45 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1349 +[2025-05-02 01:34:56,280] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.49 | bwd_microstep: 206.09 | bwd_inner_microstep: 205.87 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:34:56,757] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.28 | bwd_microstep: 272.71 | bwd_inner_microstep: 272.69 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 321 +[2025-05-02 01:34:56,990] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 68.07 | bwd_microstep: 151.23 | bwd_inner_microstep: 150.92 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 01:34:57,464] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.88 | bwd_microstep: 271.54 | bwd_inner_microstep: 271.52 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:34:57,939] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.77 | bwd_microstep: 271.27 | bwd_inner_microstep: 271.26 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:34:58,503] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.04 | optimizer_gradients: 2.09 | optimizer_step: 16.63 +[2025-05-02 01:34:58,503] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.91 | bwd_microstep: 337.93 | bwd_inner_microstep: 271.98 | bwd_allreduce_microstep: 65.91 | step_microstep: 23.50 +[2025-05-02 01:34:58,505] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2580.87 | bwd: 3927.02 | bwd_inner: 3859.83 | bwd_allreduce: 66.47 | step: 24.59 + 14%|█▍ | 1252/8720 [3:19:32<14:29:46, 6.99s/it] {'loss': 0.7769, 'grad_norm': 12.570406913757324, 'learning_rate': 9.665746818349397e-06, 'epoch': 1.44} + 14%|█▍ | 1252/8720 [3:19:32<14:29:46, 6.99s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:34:58,983] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.94 | bwd_microstep: 270.53 | bwd_inner_microstep: 270.52 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1935 +[2025-05-02 01:34:59,483] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 196.48 | bwd_microstep: 288.16 | bwd_inner_microstep: 288.14 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 912 +[2025-05-02 01:34:59,744] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 101.65 | bwd_microstep: 145.39 | bwd_inner_microstep: 145.24 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1897 +[2025-05-02 01:35:00,224] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.96 | bwd_microstep: 275.52 | bwd_inner_microstep: 275.51 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-02 01:35:00,703] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.45 | bwd_microstep: 274.28 | bwd_inner_microstep: 274.26 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 01:35:01,180] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.42 | bwd_microstep: 273.19 | bwd_inner_microstep: 273.17 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 01:35:01,659] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.05 | bwd_microstep: 273.31 | bwd_inner_microstep: 273.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 01:35:02,138] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.37 | bwd_microstep: 273.91 | bwd_inner_microstep: 273.89 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:35:02,619] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.95 | bwd_microstep: 272.35 | bwd_inner_microstep: 272.33 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:35:03,100] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.87 | bwd_microstep: 272.76 | bwd_inner_microstep: 272.74 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:35:03,579] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.08 | bwd_microstep: 272.65 | bwd_inner_microstep: 272.63 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:35:04,058] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.89 | bwd_microstep: 272.68 | bwd_inner_microstep: 272.67 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:35:04,539] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.81 | bwd_microstep: 272.89 | bwd_inner_microstep: 272.88 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 323 +[2025-05-02 01:35:04,785] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 79.18 | bwd_microstep: 151.16 | bwd_inner_microstep: 151.00 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:35:05,262] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.71 | bwd_microstep: 271.33 | bwd_inner_microstep: 271.31 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 317 +[2025-05-02 01:35:05,621] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.04 | optimizer_gradients: 2.12 | optimizer_step: 16.62 +[2025-05-02 01:35:05,622] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 78.78 | bwd_microstep: 242.76 | bwd_inner_microstep: 168.74 | bwd_allreduce_microstep: 73.87 | step_microstep: 23.54 +[2025-05-02 01:35:05,623] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2723.26 | bwd: 4102.92 | bwd_inner: 4028.47 | bwd_allreduce: 74.02 | step: 24.59 + 14%|█▍ | 1253/8720 [3:19:39<14:34:31, 7.03s/it] {'loss': 0.5904, 'grad_norm': 19.381484985351562, 'learning_rate': 9.665078863698627e-06, 'epoch': 1.44} + 14%|█▍ | 1253/8720 [3:19:39<14:34:31, 7.03s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2134 +[2025-05-02 01:35:06,160] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 204.18 | bwd_microstep: 313.78 | bwd_inner_microstep: 313.76 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1997 +[2025-05-02 01:35:06,668] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 198.20 | bwd_microstep: 294.34 | bwd_inner_microstep: 294.32 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 898 +[2025-05-02 01:35:06,925] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 99.93 | bwd_microstep: 143.74 | bwd_inner_microstep: 143.62 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1910 +[2025-05-02 01:35:07,406] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.65 | bwd_microstep: 276.51 | bwd_inner_microstep: 276.49 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1899 +[2025-05-02 01:35:07,888] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 191.09 | bwd_microstep: 275.43 | bwd_inner_microstep: 275.41 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 843 +[2025-05-02 01:35:08,152] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.89 | bwd_microstep: 154.58 | bwd_inner_microstep: 154.28 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-02 01:35:08,632] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.94 | bwd_microstep: 274.14 | bwd_inner_microstep: 274.12 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-02 01:35:09,114] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.26 | bwd_microstep: 274.01 | bwd_inner_microstep: 274.00 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-02 01:35:09,594] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.57 | bwd_microstep: 273.93 | bwd_inner_microstep: 273.91 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 838 +[2025-05-02 01:35:09,853] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.25 | bwd_microstep: 147.88 | bwd_inner_microstep: 147.64 | bwd_allreduce_microstep: 0.09 | step_microstep: 0.10 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 327 +[2025-05-02 01:35:10,102] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 85.95 | bwd_microstep: 147.61 | bwd_inner_microstep: 147.30 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:35:10,581] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.16 | bwd_microstep: 272.68 | bwd_inner_microstep: 272.66 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 321 +[2025-05-02 01:35:10,846] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.47 | bwd_microstep: 150.30 | bwd_inner_microstep: 149.96 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.18 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 833 +[2025-05-02 01:35:11,103] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.81 | bwd_microstep: 144.02 | bwd_inner_microstep: 143.85 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 01:35:11,581] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.23 | bwd_microstep: 272.42 | bwd_inner_microstep: 272.41 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 01:35:12,159] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.15 | optimizer_step: 16.61 +[2025-05-02 01:35:12,160] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.39 | bwd_microstep: 348.34 | bwd_inner_microstep: 271.75 | bwd_allreduce_microstep: 76.52 | step_microstep: 24.33 +[2025-05-02 01:35:12,161] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2474.61 | bwd: 3763.85 | bwd_inner: 3685.79 | bwd_allreduce: 77.11 | step: 25.65 + 14%|█▍ | 1254/8720 [3:19:45<14:16:13, 6.88s/it] {'loss': 0.7914, 'grad_norm': 5.197090148925781, 'learning_rate': 9.66441026543699e-06, 'epoch': 1.44} + 14%|█▍ | 1254/8720 [3:19:45<14:16:13, 6.88s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 317 +[2025-05-02 01:35:12,410] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 78.85 | bwd_microstep: 149.16 | bwd_inner_microstep: 148.91 | bwd_allreduce_microstep: 0.10 | step_microstep: 0.11 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 451 +[2025-05-02 01:35:12,651] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 77.67 | bwd_microstep: 147.83 | bwd_inner_microstep: 147.51 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1888 +[2025-05-02 01:35:13,128] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.02 | bwd_microstep: 274.35 | bwd_inner_microstep: 274.33 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1109 +[2025-05-02 01:35:13,424] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 115.49 | bwd_microstep: 162.43 | bwd_inner_microstep: 162.20 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 01:35:13,903] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.43 | bwd_microstep: 272.89 | bwd_inner_microstep: 272.87 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-02 01:35:14,386] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.60 | bwd_microstep: 273.53 | bwd_inner_microstep: 273.51 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:35:14,863] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.78 | bwd_microstep: 272.22 | bwd_inner_microstep: 272.20 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-02 01:35:15,344] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.21 | bwd_microstep: 273.50 | bwd_inner_microstep: 273.49 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 01:35:15,825] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.32 | bwd_microstep: 272.63 | bwd_inner_microstep: 272.61 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 01:35:16,306] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.47 | bwd_microstep: 273.18 | bwd_inner_microstep: 273.17 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 01:35:16,786] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.09 | bwd_microstep: 272.89 | bwd_inner_microstep: 272.87 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:35:17,263] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.08 | bwd_microstep: 271.85 | bwd_inner_microstep: 271.83 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.14 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:35:17,741] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.18 | bwd_microstep: 272.24 | bwd_inner_microstep: 272.22 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:35:18,219] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.92 | bwd_microstep: 272.36 | bwd_inner_microstep: 272.34 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:35:18,697] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.66 | bwd_microstep: 272.50 | bwd_inner_microstep: 272.48 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:35:19,277] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.13 | optimizer_step: 16.65 +[2025-05-02 01:35:19,278] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.63 | bwd_microstep: 347.74 | bwd_inner_microstep: 271.70 | bwd_allreduce_microstep: 75.98 | step_microstep: 24.36 +[2025-05-02 01:35:19,279] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2721.00 | bwd: 4081.34 | bwd_inner: 4004.40 | bwd_allreduce: 76.33 | step: 25.43 + 14%|█▍ | 1255/8720 [3:19:53<14:24:56, 6.95s/it] {'loss': 1.029, 'grad_norm': 14.548486709594727, 'learning_rate': 9.66374102365673e-06, 'epoch': 1.44} + 14%|█▍ | 1255/8720 [3:19:53<14:24:56, 6.95s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 01:35:19,759] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.63 | bwd_microstep: 270.55 | bwd_inner_microstep: 270.53 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1888 +[2025-05-02 01:35:20,238] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.82 | bwd_microstep: 274.61 | bwd_inner_microstep: 274.59 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1370 +[2025-05-02 01:35:20,602] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 142.25 | bwd_microstep: 206.77 | bwd_inner_microstep: 206.75 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 845 +[2025-05-02 01:35:20,846] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 96.32 | bwd_microstep: 132.57 | bwd_inner_microstep: 132.32 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-02 01:35:21,323] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.30 | bwd_microstep: 274.04 | bwd_inner_microstep: 274.02 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1116 +[2025-05-02 01:35:21,617] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 115.11 | bwd_microstep: 162.12 | bwd_inner_microstep: 162.00 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-02 01:35:22,096] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.61 | bwd_microstep: 272.96 | bwd_inner_microstep: 272.94 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-02 01:35:22,575] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.18 | bwd_microstep: 273.18 | bwd_inner_microstep: 273.16 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 01:35:23,052] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.73 | bwd_microstep: 272.51 | bwd_inner_microstep: 272.49 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1347 +[2025-05-02 01:35:23,413] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.42 | bwd_microstep: 205.44 | bwd_inner_microstep: 205.29 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 01:35:23,888] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.96 | bwd_microstep: 272.75 | bwd_inner_microstep: 272.73 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 01:35:24,364] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.13 | bwd_microstep: 272.56 | bwd_inner_microstep: 272.54 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1092 +[2025-05-02 01:35:24,653] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 114.68 | bwd_microstep: 161.06 | bwd_inner_microstep: 160.87 | bwd_allreduce_microstep: 0.10 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 01:35:25,129] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.99 | bwd_microstep: 272.37 | bwd_inner_microstep: 272.36 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:35:25,606] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.01 | bwd_microstep: 272.19 | bwd_inner_microstep: 272.17 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:35:26,182] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.17 | optimizer_step: 16.60 +[2025-05-02 01:35:26,182] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.16 | bwd_microstep: 347.83 | bwd_inner_microstep: 271.42 | bwd_allreduce_microstep: 76.36 | step_microstep: 24.27 +[2025-05-02 01:35:26,184] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2680.01 | bwd: 3943.60 | bwd_inner: 3866.20 | bwd_allreduce: 76.84 | step: 25.25 + 14%|█▍ | 1256/8720 [3:19:59<14:23:03, 6.94s/it] {'loss': 0.6909, 'grad_norm': 9.286955833435059, 'learning_rate': 9.663071138450173e-06, 'epoch': 1.44} + 14%|█▍ | 1256/8720 [3:19:59<14:23:03, 6.94s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 01:35:26,663] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.38 | bwd_microstep: 270.24 | bwd_inner_microstep: 270.22 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2043 +[2025-05-02 01:35:27,178] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 200.72 | bwd_microstep: 298.63 | bwd_inner_microstep: 298.61 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1901 +[2025-05-02 01:35:27,659] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.72 | bwd_microstep: 275.60 | bwd_inner_microstep: 275.58 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1894 +[2025-05-02 01:35:28,139] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.26 | bwd_microstep: 274.93 | bwd_inner_microstep: 274.91 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1926 +[2025-05-02 01:35:28,639] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.34 | bwd_microstep: 287.41 | bwd_inner_microstep: 287.39 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-02 01:35:29,121] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.77 | bwd_microstep: 273.33 | bwd_inner_microstep: 273.31 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-02 01:35:29,603] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.37 | bwd_microstep: 273.57 | bwd_inner_microstep: 273.56 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.17 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 01:35:30,083] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.41 | bwd_microstep: 273.30 | bwd_inner_microstep: 273.29 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 326 +[2025-05-02 01:35:30,310] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 87.50 | bwd_microstep: 124.16 | bwd_inner_microstep: 123.96 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.11 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 329 +[2025-05-02 01:35:30,533] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 85.02 | bwd_microstep: 121.62 | bwd_inner_microstep: 121.46 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 01:35:31,013] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.16 | bwd_microstep: 272.86 | bwd_inner_microstep: 272.84 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 322 +[2025-05-02 01:35:31,246] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.00 | bwd_microstep: 120.63 | bwd_inner_microstep: 120.47 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 01:35:31,723] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.44 | bwd_microstep: 272.11 | bwd_inner_microstep: 272.09 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:35:32,204] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.18 | bwd_microstep: 272.20 | bwd_inner_microstep: 272.18 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:35:32,685] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.00 | bwd_microstep: 272.42 | bwd_inner_microstep: 272.41 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 321 +[2025-05-02 01:35:33,020] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.16 | optimizer_step: 16.77 +[2025-05-02 01:35:33,021] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 82.93 | bwd_microstep: 211.95 | bwd_inner_microstep: 135.13 | bwd_allreduce_microstep: 76.65 | step_microstep: 24.70 +[2025-05-02 01:35:33,022] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2629.84 | bwd: 3895.01 | bwd_inner: 3817.60 | bwd_allreduce: 76.86 | step: 25.73 + 14%|█▍ | 1257/8720 [3:20:06<14:19:16, 6.91s/it] {'loss': 0.5955, 'grad_norm': 16.386932373046875, 'learning_rate': 9.66240060990974e-06, 'epoch': 1.44} + 14%|█▍ | 1257/8720 [3:20:06<14:19:16, 6.91s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:35:33,504] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.94 | bwd_microstep: 270.46 | bwd_inner_microstep: 270.44 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2024 +[2025-05-02 01:35:34,018] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 199.87 | bwd_microstep: 296.46 | bwd_inner_microstep: 296.44 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1897 +[2025-05-02 01:35:34,498] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.30 | bwd_microstep: 275.21 | bwd_inner_microstep: 275.19 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 01:35:34,976] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.62 | bwd_microstep: 273.39 | bwd_inner_microstep: 273.37 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 01:35:35,453] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.69 | bwd_microstep: 272.81 | bwd_inner_microstep: 272.79 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 01:35:35,931] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.38 | bwd_microstep: 273.16 | bwd_inner_microstep: 273.15 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 01:35:36,408] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.11 | bwd_microstep: 273.41 | bwd_inner_microstep: 273.39 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 844 +[2025-05-02 01:35:36,649] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.35 | bwd_microstep: 132.30 | bwd_inner_microstep: 132.02 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 01:35:37,127] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.49 | bwd_microstep: 272.88 | bwd_inner_microstep: 272.86 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 841 +[2025-05-02 01:35:37,369] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.22 | bwd_microstep: 132.58 | bwd_inner_microstep: 132.31 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:35:37,846] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.99 | bwd_microstep: 273.06 | bwd_inner_microstep: 273.04 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:35:38,321] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.91 | bwd_microstep: 272.27 | bwd_inner_microstep: 272.25 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 01:35:38,797] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.99 | bwd_microstep: 272.58 | bwd_inner_microstep: 272.57 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:35:39,273] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.17 | bwd_microstep: 272.45 | bwd_inner_microstep: 272.44 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 01:35:39,752] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.19 | bwd_microstep: 272.89 | bwd_inner_microstep: 272.88 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:35:40,319] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.14 | optimizer_step: 16.63 +[2025-05-02 01:35:40,319] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.09 | bwd_microstep: 339.36 | bwd_inner_microstep: 272.83 | bwd_allreduce_microstep: 66.49 | step_microstep: 23.74 +[2025-05-02 01:35:40,320] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2840.04 | bwd: 4175.31 | bwd_inner: 4108.00 | bwd_allreduce: 66.80 | step: 24.61 + 14%|█▍ | 1258/8720 [3:20:14<14:33:37, 7.02s/it] {'loss': 1.1424, 'grad_norm': 14.558794021606445, 'learning_rate': 9.661729438127945e-06, 'epoch': 1.44} + 14%|█▍ | 1258/8720 [3:20:14<14:33:37, 7.02s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 01:35:40,798] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.59 | bwd_microstep: 270.54 | bwd_inner_microstep: 270.52 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2098 +[2025-05-02 01:35:41,321] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 202.41 | bwd_microstep: 305.69 | bwd_inner_microstep: 305.68 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1936 +[2025-05-02 01:35:41,822] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 196.71 | bwd_microstep: 288.51 | bwd_inner_microstep: 288.49 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1896 +[2025-05-02 01:35:42,301] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.87 | bwd_microstep: 275.03 | bwd_inner_microstep: 275.01 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 865 +[2025-05-02 01:35:42,546] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 96.80 | bwd_microstep: 133.77 | bwd_inner_microstep: 133.74 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 01:35:43,023] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.29 | bwd_microstep: 273.24 | bwd_inner_microstep: 273.23 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-02 01:35:43,501] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.62 | bwd_microstep: 273.55 | bwd_inner_microstep: 273.54 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 01:35:43,979] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.17 | bwd_microstep: 273.03 | bwd_inner_microstep: 273.01 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 01:35:44,455] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.61 | bwd_microstep: 272.88 | bwd_inner_microstep: 272.86 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:35:44,934] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.70 | bwd_microstep: 273.06 | bwd_inner_microstep: 273.04 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 322 +[2025-05-02 01:35:45,165] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 91.38 | bwd_microstep: 124.06 | bwd_inner_microstep: 123.79 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:35:45,644] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.04 | bwd_microstep: 272.37 | bwd_inner_microstep: 272.36 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:35:46,121] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.16 | bwd_microstep: 271.20 | bwd_inner_microstep: 271.18 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:35:46,599] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.94 | bwd_microstep: 271.23 | bwd_inner_microstep: 271.21 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:35:47,077] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.59 | bwd_microstep: 271.17 | bwd_inner_microstep: 271.15 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:35:47,652] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.13 | optimizer_step: 16.77 +[2025-05-02 01:35:47,653] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.78 | bwd_microstep: 346.71 | bwd_inner_microstep: 271.47 | bwd_allreduce_microstep: 75.18 | step_microstep: 23.98 +[2025-05-02 01:35:47,654] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2844.32 | bwd: 4196.08 | bwd_inner: 4120.35 | bwd_allreduce: 75.35 | step: 24.91 + 14%|█▍ | 1259/8720 [3:20:21<14:45:02, 7.12s/it] {'loss': 0.8491, 'grad_norm': 16.159387588500977, 'learning_rate': 9.661057623197378e-06, 'epoch': 1.44} + 14%|█▍ | 1259/8720 [3:20:21<14:45:02, 7.12s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2024 +[2025-05-02 01:35:48,168] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 197.86 | bwd_microstep: 296.11 | bwd_inner_microstep: 296.09 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 419 +[2025-05-02 01:35:48,381] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 77.79 | bwd_microstep: 120.56 | bwd_inner_microstep: 120.25 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1926 +[2025-05-02 01:35:48,878] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 193.81 | bwd_microstep: 287.33 | bwd_inner_microstep: 287.32 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 01:35:49,354] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.60 | bwd_microstep: 272.92 | bwd_inner_microstep: 272.90 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 840 +[2025-05-02 01:35:49,586] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 91.88 | bwd_microstep: 126.12 | bwd_inner_microstep: 125.97 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:35:50,062] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.46 | bwd_microstep: 272.40 | bwd_inner_microstep: 272.38 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:35:50,538] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.12 | bwd_microstep: 272.68 | bwd_inner_microstep: 272.66 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 01:35:51,013] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.81 | bwd_microstep: 272.36 | bwd_inner_microstep: 272.34 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 01:35:51,490] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.71 | bwd_microstep: 272.64 | bwd_inner_microstep: 272.62 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:35:51,966] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.23 | bwd_microstep: 271.31 | bwd_inner_microstep: 271.29 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:35:52,441] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.72 | bwd_microstep: 271.37 | bwd_inner_microstep: 271.35 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:35:52,915] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.79 | bwd_microstep: 271.13 | bwd_inner_microstep: 271.12 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:35:53,389] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.41 | bwd_microstep: 271.17 | bwd_inner_microstep: 271.15 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:35:53,864] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.22 | bwd_microstep: 271.24 | bwd_inner_microstep: 271.23 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 01:35:54,339] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.17 | bwd_microstep: 271.20 | bwd_inner_microstep: 271.18 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2001 +[2025-05-02 01:35:54,937] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.19 | optimizer_step: 16.96 +[2025-05-02 01:35:54,938] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 197.30 | bwd_microstep: 361.19 | bwd_inner_microstep: 295.02 | bwd_allreduce_microstep: 66.12 | step_microstep: 24.37 +[2025-05-02 01:35:54,939] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2827.60 | bwd: 4181.77 | bwd_inner: 4114.93 | bwd_allreduce: 66.37 | step: 25.11 + 14%|█▍ | 1260/8720 [3:20:28<14:51:10, 7.17s/it] {'loss': 0.6901, 'grad_norm': 11.056672096252441, 'learning_rate': 9.660385165210728e-06, 'epoch': 1.44} + 14%|█▍ | 1260/8720 [3:20:28<14:51:10, 7.17s/it]dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 842 +[2025-05-02 01:35:55,184] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.70 | bwd_microstep: 132.10 | bwd_inner_microstep: 132.01 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1899 +[2025-05-02 01:35:55,665] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.41 | bwd_microstep: 275.67 | bwd_inner_microstep: 275.65 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-02 01:35:56,145] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.81 | bwd_microstep: 274.00 | bwd_inner_microstep: 273.98 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-02 01:35:56,623] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.63 | bwd_microstep: 273.96 | bwd_inner_microstep: 273.94 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-02 01:35:57,101] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.39 | bwd_microstep: 273.48 | bwd_inner_microstep: 273.47 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-02 01:35:57,581] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.16 | bwd_microstep: 274.36 | bwd_inner_microstep: 274.34 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-02 01:35:58,059] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.97 | bwd_microstep: 273.72 | bwd_inner_microstep: 273.71 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 01:35:58,535] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.67 | bwd_microstep: 272.96 | bwd_inner_microstep: 272.95 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 01:35:59,013] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.16 | bwd_microstep: 273.03 | bwd_inner_microstep: 273.01 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:35:59,490] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.29 | bwd_microstep: 272.67 | bwd_inner_microstep: 272.65 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 01:35:59,969] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.84 | bwd_microstep: 273.12 | bwd_inner_microstep: 273.10 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 01:36:00,447] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.30 | bwd_microstep: 271.37 | bwd_inner_microstep: 271.36 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:36:00,925] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.83 | bwd_microstep: 271.34 | bwd_inner_microstep: 271.32 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.14 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:36:01,403] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.79 | bwd_microstep: 272.36 | bwd_inner_microstep: 272.34 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:36:01,879] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.81 | bwd_microstep: 272.62 | bwd_inner_microstep: 272.60 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:36:02,444] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.14 | optimizer_step: 16.67 +[2025-05-02 01:36:02,445] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.23 | bwd_microstep: 337.86 | bwd_inner_microstep: 271.77 | bwd_allreduce_microstep: 66.04 | step_microstep: 23.71 +[2025-05-02 01:36:02,446] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2926.71 | bwd: 4294.64 | bwd_inner: 4228.20 | bwd_allreduce: 66.17 | step: 24.71 + 14%|█▍ | 1261/8720 [3:20:36<15:03:42, 7.27s/it] {'loss': 0.7988, 'grad_norm': 11.310868263244629, 'learning_rate': 9.65971206426077e-06, 'epoch': 1.45} + 14%|█▍ | 1261/8720 [3:20:36<15:03:42, 7.27s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1949 +[2025-05-02 01:36:02,950] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.63 | bwd_microstep: 288.57 | bwd_inner_microstep: 288.55 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 343 +[2025-05-02 01:36:03,152] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 72.05 | bwd_microstep: 117.59 | bwd_inner_microstep: 117.26 | bwd_allreduce_microstep: 0.14 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 01:36:03,628] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.94 | bwd_microstep: 273.54 | bwd_inner_microstep: 273.52 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 01:36:04,106] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.14 | bwd_microstep: 273.42 | bwd_inner_microstep: 273.41 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 846 +[2025-05-02 01:36:04,348] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.88 | bwd_microstep: 132.71 | bwd_inner_microstep: 132.57 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 01:36:04,824] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.68 | bwd_microstep: 272.93 | bwd_inner_microstep: 272.92 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 839 +[2025-05-02 01:36:05,056] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 92.08 | bwd_microstep: 126.34 | bwd_inner_microstep: 126.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 329 +[2025-05-02 01:36:05,254] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 67.63 | bwd_microstep: 117.42 | bwd_inner_microstep: 117.10 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:36:05,730] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.21 | bwd_microstep: 272.25 | bwd_inner_microstep: 272.23 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 01:36:06,207] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.01 | bwd_microstep: 272.69 | bwd_inner_microstep: 272.67 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:36:06,684] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.58 | bwd_microstep: 273.10 | bwd_inner_microstep: 273.08 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:36:07,160] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.05 | bwd_microstep: 272.52 | bwd_inner_microstep: 272.50 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:36:07,639] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.11 | bwd_microstep: 272.58 | bwd_inner_microstep: 272.56 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:36:08,118] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.48 | bwd_microstep: 271.26 | bwd_inner_microstep: 271.24 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 317 +[2025-05-02 01:36:08,344] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 88.15 | bwd_microstep: 119.86 | bwd_inner_microstep: 119.70 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 01:36:08,924] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.14 | optimizer_step: 16.62 +[2025-05-02 01:36:08,925] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.72 | bwd_microstep: 350.47 | bwd_inner_microstep: 274.06 | bwd_allreduce_microstep: 76.36 | step_microstep: 24.39 +[2025-05-02 01:36:08,926] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2495.05 | bwd: 3707.33 | bwd_inner: 3629.86 | bwd_allreduce: 76.81 | step: 25.44 + 14%|█▍ | 1262/8720 [3:20:42<14:34:13, 7.03s/it] {'loss': 0.7067, 'grad_norm': 14.097967147827148, 'learning_rate': 9.65903832044037e-06, 'epoch': 1.45} + 14%|█▍ | 1262/8720 [3:20:42<14:34:13, 7.03s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:36:09,408] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.01 | bwd_microstep: 271.30 | bwd_inner_microstep: 271.28 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1888 +[2025-05-02 01:36:09,889] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.15 | bwd_microstep: 274.44 | bwd_inner_microstep: 274.42 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 01:36:10,366] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.67 | bwd_microstep: 273.30 | bwd_inner_microstep: 273.28 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-02 01:36:10,844] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.98 | bwd_microstep: 273.45 | bwd_inner_microstep: 273.43 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.17 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1110 +[2025-05-02 01:36:11,141] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 118.54 | bwd_microstep: 162.30 | bwd_inner_microstep: 162.12 | bwd_allreduce_microstep: 0.09 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 01:36:11,623] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.08 | bwd_microstep: 273.32 | bwd_inner_microstep: 273.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 326 +[2025-05-02 01:36:11,869] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 87.84 | bwd_microstep: 141.16 | bwd_inner_microstep: 141.01 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-02 01:36:12,348] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.20 | bwd_microstep: 273.45 | bwd_inner_microstep: 273.44 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1093 +[2025-05-02 01:36:12,642] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 116.15 | bwd_microstep: 161.12 | bwd_inner_microstep: 161.08 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:36:13,121] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.55 | bwd_microstep: 272.75 | bwd_inner_microstep: 272.73 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:36:13,602] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.10 | bwd_microstep: 272.45 | bwd_inner_microstep: 272.43 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:36:14,084] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.02 | bwd_microstep: 272.34 | bwd_inner_microstep: 272.32 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:36:14,564] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.39 | bwd_microstep: 271.04 | bwd_inner_microstep: 271.03 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 01:36:15,040] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.09 | bwd_microstep: 270.94 | bwd_inner_microstep: 270.92 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1936 +[2025-05-02 01:36:15,542] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 196.11 | bwd_microstep: 288.13 | bwd_inner_microstep: 288.12 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 848 +[2025-05-02 01:36:15,885] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.12 | optimizer_step: 16.67 +[2025-05-02 01:36:15,886] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.10 | bwd_microstep: 209.28 | bwd_inner_microstep: 133.28 | bwd_allreduce_microstep: 75.85 | step_microstep: 24.36 +[2025-05-02 01:36:15,887] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2686.61 | bwd: 3960.84 | bwd_inner: 3884.26 | bwd_allreduce: 76.08 | step: 25.39 + 14%|█▍ | 1263/8720 [3:20:49<14:31:22, 7.01s/it] {'loss': 0.9052, 'grad_norm': 7.4935736656188965, 'learning_rate': 9.658363933842473e-06, 'epoch': 1.45} + 14%|█▍ | 1263/8720 [3:20:49<14:31:22, 7.01s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1849 +[2025-05-02 01:36:16,365] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.06 | bwd_microstep: 270.01 | bwd_inner_microstep: 269.99 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 879 +[2025-05-02 01:36:16,611] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 97.13 | bwd_microstep: 135.33 | bwd_inner_microstep: 135.20 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1911 +[2025-05-02 01:36:17,091] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.20 | bwd_microstep: 276.37 | bwd_inner_microstep: 276.36 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1887 +[2025-05-02 01:36:17,569] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.83 | bwd_microstep: 274.54 | bwd_inner_microstep: 274.52 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-02 01:36:18,047] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.54 | bwd_microstep: 273.60 | bwd_inner_microstep: 273.58 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 335 +[2025-05-02 01:36:18,263] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 78.47 | bwd_microstep: 125.34 | bwd_inner_microstep: 125.04 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 01:36:18,739] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.12 | bwd_microstep: 272.74 | bwd_inner_microstep: 272.72 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 842 +[2025-05-02 01:36:18,981] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.91 | bwd_microstep: 131.94 | bwd_inner_microstep: 131.75 | bwd_allreduce_microstep: 0.09 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 01:36:19,457] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.68 | bwd_microstep: 272.73 | bwd_inner_microstep: 272.71 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 841 +[2025-05-02 01:36:19,696] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.96 | bwd_microstep: 131.73 | bwd_inner_microstep: 131.71 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 326 +[2025-05-02 01:36:19,928] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 75.98 | bwd_microstep: 142.21 | bwd_inner_microstep: 141.89 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 01:36:20,405] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.53 | bwd_microstep: 272.83 | bwd_inner_microstep: 272.82 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:36:20,881] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.52 | bwd_microstep: 272.82 | bwd_inner_microstep: 272.80 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 01:36:21,357] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.42 | bwd_microstep: 272.35 | bwd_inner_microstep: 272.34 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1344 +[2025-05-02 01:36:21,716] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.65 | bwd_microstep: 204.42 | bwd_inner_microstep: 204.41 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 01:36:22,280] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.09 | optimizer_step: 16.61 +[2025-05-02 01:36:22,280] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.74 | bwd_microstep: 338.26 | bwd_inner_microstep: 271.71 | bwd_allreduce_microstep: 66.51 | step_microstep: 23.52 +[2025-05-02 01:36:22,281] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2463.49 | bwd: 3667.28 | bwd_inner: 3599.69 | bwd_allreduce: 66.93 | step: 24.50 + 14%|█▍ | 1264/8720 [3:20:56<14:08:13, 6.83s/it] {'loss': 0.9007, 'grad_norm': 9.70638656616211, 'learning_rate': 9.657688904560126e-06, 'epoch': 1.45} + 14%|█▍ | 1264/8720 [3:20:56<14:08:13, 6.83s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:36:22,760] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.95 | bwd_microstep: 270.94 | bwd_inner_microstep: 270.92 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.20 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 899 +[2025-05-02 01:36:23,023] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 103.68 | bwd_microstep: 144.62 | bwd_inner_microstep: 144.39 | bwd_allreduce_microstep: 0.14 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1896 +[2025-05-02 01:36:23,504] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.02 | bwd_microstep: 275.55 | bwd_inner_microstep: 275.53 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1887 +[2025-05-02 01:36:23,985] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.83 | bwd_microstep: 275.02 | bwd_inner_microstep: 275.00 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 01:36:24,462] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.17 | bwd_microstep: 273.86 | bwd_inner_microstep: 273.84 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:36:24,940] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.78 | bwd_microstep: 273.08 | bwd_inner_microstep: 273.06 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 843 +[2025-05-02 01:36:25,181] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.62 | bwd_microstep: 132.81 | bwd_inner_microstep: 132.59 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:36:25,658] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.29 | bwd_microstep: 272.97 | bwd_inner_microstep: 272.95 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 01:36:26,135] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.32 | bwd_microstep: 272.89 | bwd_inner_microstep: 272.87 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 01:36:26,612] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.58 | bwd_microstep: 272.88 | bwd_inner_microstep: 272.87 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:36:27,089] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.72 | bwd_microstep: 272.78 | bwd_inner_microstep: 272.76 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:36:27,566] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.41 | bwd_microstep: 271.58 | bwd_inner_microstep: 271.56 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:36:28,043] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.25 | bwd_microstep: 271.84 | bwd_inner_microstep: 271.83 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:36:28,521] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.23 | bwd_microstep: 271.31 | bwd_inner_microstep: 271.29 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:36:29,002] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.90 | bwd_microstep: 271.41 | bwd_inner_microstep: 271.39 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:36:29,569] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.13 | optimizer_step: 16.67 +[2025-05-02 01:36:29,570] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.00 | bwd_microstep: 337.79 | bwd_inner_microstep: 271.93 | bwd_allreduce_microstep: 65.81 | step_microstep: 24.09 +[2025-05-02 01:36:29,571] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2842.45 | bwd: 4161.36 | bwd_inner: 4094.82 | bwd_allreduce: 66.09 | step: 25.01 + 15%|█▍ | 1265/8720 [3:21:03<14:25:27, 6.97s/it] {'loss': 0.4718, 'grad_norm': 9.324116706848145, 'learning_rate': 9.657013232686456e-06, 'epoch': 1.45} + 15%|█▍ | 1265/8720 [3:21:03<14:25:27, 6.97s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-02 01:36:30,056] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.77 | bwd_microstep: 273.64 | bwd_inner_microstep: 273.63 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 867 +[2025-05-02 01:36:30,314] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 105.95 | bwd_microstep: 133.49 | bwd_inner_microstep: 133.34 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1892 +[2025-05-02 01:36:30,796] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.47 | bwd_microstep: 274.86 | bwd_inner_microstep: 274.84 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1893 +[2025-05-02 01:36:31,276] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.60 | bwd_microstep: 275.06 | bwd_inner_microstep: 275.04 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-02 01:36:31,756] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.70 | bwd_microstep: 274.46 | bwd_inner_microstep: 274.44 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-02 01:36:32,240] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 191.30 | bwd_microstep: 273.70 | bwd_inner_microstep: 273.68 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-02 01:36:32,721] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.22 | bwd_microstep: 273.63 | bwd_inner_microstep: 273.61 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.10 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1369 +[2025-05-02 01:36:33,090] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 143.84 | bwd_microstep: 207.63 | bwd_inner_microstep: 207.53 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.11 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 342 +[2025-05-02 01:36:33,346] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 115.87 | bwd_microstep: 121.14 | bwd_inner_microstep: 120.85 | bwd_allreduce_microstep: 0.10 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 01:36:33,826] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.41 | bwd_microstep: 273.40 | bwd_inner_microstep: 273.38 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1360 +[2025-05-02 01:36:34,192] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.50 | bwd_microstep: 206.49 | bwd_inner_microstep: 206.45 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.11 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 842 +[2025-05-02 01:36:34,453] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 111.00 | bwd_microstep: 131.30 | bwd_inner_microstep: 131.02 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.11 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 325 +[2025-05-02 01:36:34,685] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 99.46 | bwd_microstep: 116.65 | bwd_inner_microstep: 116.39 | bwd_allreduce_microstep: 0.09 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 01:36:35,162] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.89 | bwd_microstep: 272.90 | bwd_inner_microstep: 272.88 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:36:35,640] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.28 | bwd_microstep: 272.49 | bwd_inner_microstep: 272.48 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1346 +[2025-05-02 01:36:36,117] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.16 | optimizer_step: 16.69 +[2025-05-02 01:36:36,117] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.79 | bwd_microstep: 295.07 | bwd_inner_microstep: 206.10 | bwd_allreduce_microstep: 88.92 | step_microstep: 25.07 +[2025-05-02 01:36:36,118] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2561.66 | bwd: 3676.02 | bwd_inner: 3585.85 | bwd_allreduce: 89.34 | step: 26.23 + 15%|█▍ | 1266/8720 [3:21:09<14:09:41, 6.84s/it] {'loss': 0.9007, 'grad_norm': 8.114941596984863, 'learning_rate': 9.656336918314683e-06, 'epoch': 1.45} + 15%|█▍ | 1266/8720 [3:21:09<14:09:41, 6.84s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:36:36,596] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.68 | bwd_microstep: 270.30 | bwd_inner_microstep: 270.28 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1905 +[2025-05-02 01:36:37,078] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.71 | bwd_microstep: 276.07 | bwd_inner_microstep: 276.06 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1370 +[2025-05-02 01:36:37,443] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 142.03 | bwd_microstep: 207.53 | bwd_inner_microstep: 207.42 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-02 01:36:37,920] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.54 | bwd_microstep: 273.33 | bwd_inner_microstep: 273.31 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 01:36:38,398] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.11 | bwd_microstep: 273.13 | bwd_inner_microstep: 273.11 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 01:36:38,875] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.91 | bwd_microstep: 273.50 | bwd_inner_microstep: 273.49 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:36:39,353] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.99 | bwd_microstep: 272.67 | bwd_inner_microstep: 272.65 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-02 01:36:39,831] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.21 | bwd_microstep: 273.31 | bwd_inner_microstep: 273.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 01:36:40,310] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.61 | bwd_microstep: 272.81 | bwd_inner_microstep: 272.79 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 01:36:40,789] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.47 | bwd_microstep: 273.05 | bwd_inner_microstep: 273.03 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 842 +[2025-05-02 01:36:41,046] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 108.64 | bwd_microstep: 131.34 | bwd_inner_microstep: 131.07 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:36:41,525] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.15 | bwd_microstep: 272.63 | bwd_inner_microstep: 272.61 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:36:42,004] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.79 | bwd_microstep: 272.59 | bwd_inner_microstep: 272.57 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:36:42,482] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.58 | bwd_microstep: 272.54 | bwd_inner_microstep: 272.52 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 01:36:42,956] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.62 | bwd_microstep: 270.76 | bwd_inner_microstep: 270.74 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1849 +[2025-05-02 01:36:43,540] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.18 | optimizer_step: 16.67 +[2025-05-02 01:36:43,540] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.36 | bwd_microstep: 356.30 | bwd_inner_microstep: 271.47 | bwd_allreduce_microstep: 84.79 | step_microstep: 25.26 +[2025-05-02 01:36:43,542] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2893.07 | bwd: 4241.94 | bwd_inner: 4156.47 | bwd_allreduce: 85.05 | step: 26.15 + 15%|█▍ | 1267/8720 [3:21:17<14:31:21, 7.01s/it] {'loss': 0.8739, 'grad_norm': 7.281574249267578, 'learning_rate': 9.655659961538111e-06, 'epoch': 1.45} + 15%|█▍ | 1267/8720 [3:21:17<14:31:21, 7.01s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1936 +[2025-05-02 01:36:44,045] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.40 | bwd_microstep: 287.21 | bwd_inner_microstep: 287.19 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1928 +[2025-05-02 01:36:44,543] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.30 | bwd_microstep: 287.86 | bwd_inner_microstep: 287.84 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 388 +[2025-05-02 01:36:44,754] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 81.99 | bwd_microstep: 113.34 | bwd_inner_microstep: 113.02 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1916 +[2025-05-02 01:36:45,236] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 191.37 | bwd_microstep: 276.28 | bwd_inner_microstep: 276.26 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 366 +[2025-05-02 01:36:45,441] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 70.37 | bwd_microstep: 122.13 | bwd_inner_microstep: 121.99 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-02 01:36:45,918] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.96 | bwd_microstep: 273.96 | bwd_inner_microstep: 273.94 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 01:36:46,395] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.23 | bwd_microstep: 272.98 | bwd_inner_microstep: 272.96 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1362 +[2025-05-02 01:36:46,760] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 144.02 | bwd_microstep: 206.86 | bwd_inner_microstep: 206.71 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 844 +[2025-05-02 01:36:47,002] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.86 | bwd_microstep: 131.98 | bwd_inner_microstep: 131.97 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 01:36:47,477] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.80 | bwd_microstep: 272.88 | bwd_inner_microstep: 272.87 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 01:36:47,954] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.58 | bwd_microstep: 272.42 | bwd_inner_microstep: 272.41 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 322 +[2025-05-02 01:36:48,190] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 101.70 | bwd_microstep: 114.80 | bwd_inner_microstep: 114.54 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:36:48,667] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.49 | bwd_microstep: 272.27 | bwd_inner_microstep: 272.25 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:36:49,148] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.23 | bwd_microstep: 272.37 | bwd_inner_microstep: 272.35 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:36:49,628] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.44 | bwd_microstep: 271.42 | bwd_inner_microstep: 271.40 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 01:36:50,209] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.16 | optimizer_step: 16.75 +[2025-05-02 01:36:50,210] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.48 | bwd_microstep: 349.09 | bwd_inner_microstep: 271.75 | bwd_allreduce_microstep: 77.29 | step_microstep: 24.69 +[2025-05-02 01:36:50,211] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2581.88 | bwd: 3797.96 | bwd_inner: 3719.62 | bwd_allreduce: 77.71 | step: 25.61 + 15%|█▍ | 1268/8720 [3:21:23<14:18:27, 6.91s/it] {'loss': 1.0333, 'grad_norm': 12.405553817749023, 'learning_rate': 9.654982362450135e-06, 'epoch': 1.45} + 15%|█▍ | 1268/8720 [3:21:23<14:18:27, 6.91s/it]dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1390 +[2025-05-02 01:36:50,585] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.39 | bwd_microstep: 208.64 | bwd_inner_microstep: 208.45 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.10 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 360 +[2025-05-02 01:36:50,821] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 91.47 | bwd_microstep: 126.70 | bwd_inner_microstep: 126.38 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1377 +[2025-05-02 01:36:51,188] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.26 | bwd_microstep: 207.99 | bwd_inner_microstep: 207.98 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-02 01:36:51,671] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.53 | bwd_microstep: 273.11 | bwd_inner_microstep: 273.09 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 324 +[2025-05-02 01:36:51,924] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 91.25 | bwd_microstep: 143.91 | bwd_inner_microstep: 143.76 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 01:36:52,403] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.30 | bwd_microstep: 272.86 | bwd_inner_microstep: 272.84 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 01:36:52,884] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.81 | bwd_microstep: 272.90 | bwd_inner_microstep: 272.89 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 01:36:53,364] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.70 | bwd_microstep: 272.32 | bwd_inner_microstep: 272.31 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1344 +[2025-05-02 01:36:53,727] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.71 | bwd_microstep: 204.38 | bwd_inner_microstep: 204.36 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:36:54,205] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.70 | bwd_microstep: 272.31 | bwd_inner_microstep: 272.29 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:36:54,686] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.48 | bwd_microstep: 271.29 | bwd_inner_microstep: 271.27 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:36:55,166] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.34 | bwd_microstep: 272.43 | bwd_inner_microstep: 272.41 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1341 +[2025-05-02 01:36:55,533] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.87 | bwd_microstep: 204.58 | bwd_inner_microstep: 204.50 | bwd_allreduce_microstep: 0.03 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 01:36:56,010] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.35 | bwd_microstep: 270.76 | bwd_inner_microstep: 270.74 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:36:56,487] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.98 | bwd_microstep: 271.16 | bwd_inner_microstep: 271.15 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 01:36:57,064] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.17 | optimizer_step: 16.68 +[2025-05-02 01:36:57,065] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.75 | bwd_microstep: 347.52 | bwd_inner_microstep: 271.47 | bwd_allreduce_microstep: 76.01 | step_microstep: 23.94 +[2025-05-02 01:36:57,066] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2631.50 | bwd: 3892.93 | bwd_inner: 3815.97 | bwd_allreduce: 76.43 | step: 25.01 + 15%|█▍ | 1269/8720 [3:21:30<14:16:08, 6.89s/it] {'loss': 0.6619, 'grad_norm': 16.20069122314453, 'learning_rate': 9.654304121144244e-06, 'epoch': 1.46} + 15%|█▍ | 1269/8720 [3:21:30<14:16:08, 6.89s/it]dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1430 +[2025-05-02 01:36:57,446] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 146.58 | bwd_microstep: 213.55 | bwd_inner_microstep: 213.53 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1914 +[2025-05-02 01:36:57,928] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.24 | bwd_microstep: 276.36 | bwd_inner_microstep: 276.35 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-02 01:36:58,407] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.10 | bwd_microstep: 274.20 | bwd_inner_microstep: 274.18 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 01:36:58,885] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.73 | bwd_microstep: 272.75 | bwd_inner_microstep: 272.73 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 01:36:59,364] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.31 | bwd_microstep: 272.77 | bwd_inner_microstep: 272.75 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:36:59,847] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.91 | bwd_microstep: 272.43 | bwd_inner_microstep: 272.41 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:37:00,329] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.97 | bwd_microstep: 272.42 | bwd_inner_microstep: 272.40 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 01:37:00,807] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.42 | bwd_microstep: 272.21 | bwd_inner_microstep: 272.19 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:37:01,285] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.47 | bwd_microstep: 271.40 | bwd_inner_microstep: 271.38 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1344 +[2025-05-02 01:37:01,649] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.01 | bwd_microstep: 204.61 | bwd_inner_microstep: 204.44 | bwd_allreduce_microstep: 0.10 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:37:02,129] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.14 | bwd_microstep: 272.10 | bwd_inner_microstep: 272.08 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 01:37:02,611] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.88 | bwd_microstep: 271.14 | bwd_inner_microstep: 271.13 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 01:37:03,090] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.65 | bwd_microstep: 271.10 | bwd_inner_microstep: 271.08 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:37:03,569] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.44 | bwd_microstep: 271.08 | bwd_inner_microstep: 271.06 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 01:37:04,047] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.22 | bwd_microstep: 271.37 | bwd_inner_microstep: 271.35 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1905 +[2025-05-02 01:37:04,635] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.27 | optimizer_step: 16.81 +[2025-05-02 01:37:04,635] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.85 | bwd_microstep: 353.60 | bwd_inner_microstep: 276.37 | bwd_allreduce_microstep: 77.18 | step_microstep: 24.80 +[2025-05-02 01:37:04,637] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2928.55 | bwd: 4313.13 | bwd_inner: 4235.46 | bwd_allreduce: 77.38 | step: 25.92 + 15%|█▍ | 1270/8720 [3:21:38<14:41:16, 7.10s/it] {'loss': 0.5896, 'grad_norm': 13.029751777648926, 'learning_rate': 9.653625237714005e-06, 'epoch': 1.46} + 15%|█▍ | 1270/8720 [3:21:38<14:41:16, 7.10s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1883 +[2025-05-02 01:37:05,123] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.62 | bwd_microstep: 273.73 | bwd_inner_microstep: 273.71 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1925 +[2025-05-02 01:37:05,625] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.52 | bwd_microstep: 287.07 | bwd_inner_microstep: 287.05 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1384 +[2025-05-02 01:37:05,999] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 143.97 | bwd_microstep: 208.47 | bwd_inner_microstep: 208.46 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-02 01:37:06,487] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.11 | bwd_microstep: 273.99 | bwd_inner_microstep: 273.98 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1883 +[2025-05-02 01:37:06,973] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.91 | bwd_microstep: 274.05 | bwd_inner_microstep: 274.03 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 01:37:07,455] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.36 | bwd_microstep: 273.08 | bwd_inner_microstep: 273.06 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.15 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 833 +[2025-05-02 01:37:07,701] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 100.61 | bwd_microstep: 125.66 | bwd_inner_microstep: 125.39 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:37:08,185] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.86 | bwd_microstep: 272.58 | bwd_inner_microstep: 272.56 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 840 +[2025-05-02 01:37:08,438] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 102.68 | bwd_microstep: 126.06 | bwd_inner_microstep: 126.01 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 01:37:08,918] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.87 | bwd_microstep: 272.83 | bwd_inner_microstep: 272.82 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:37:09,397] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.52 | bwd_microstep: 272.46 | bwd_inner_microstep: 272.44 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 01:37:09,881] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.10 | bwd_microstep: 272.39 | bwd_inner_microstep: 272.37 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 01:37:10,361] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.88 | bwd_microstep: 272.15 | bwd_inner_microstep: 272.14 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1341 +[2025-05-02 01:37:10,725] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.43 | bwd_microstep: 204.34 | bwd_inner_microstep: 204.33 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 01:37:11,205] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.92 | bwd_microstep: 271.36 | bwd_inner_microstep: 271.34 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1997 +[2025-05-02 01:37:11,823] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.19 | optimizer_step: 16.72 +[2025-05-02 01:37:11,824] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 197.92 | bwd_microstep: 377.20 | bwd_inner_microstep: 294.75 | bwd_allreduce_microstep: 82.39 | step_microstep: 24.73 +[2025-05-02 01:37:11,825] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2769.82 | bwd: 4057.49 | bwd_inner: 3974.46 | bwd_allreduce: 82.61 | step: 26.12 + 15%|█▍ | 1271/8720 [3:21:45<14:44:32, 7.12s/it] {'loss': 0.6718, 'grad_norm': 8.186785697937012, 'learning_rate': 9.652945712253082e-06, 'epoch': 1.46} + 15%|█▍ | 1271/8720 [3:21:45<14:44:32, 7.12s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1918 +[2025-05-02 01:37:12,316] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 191.36 | bwd_microstep: 275.65 | bwd_inner_microstep: 275.63 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1905 +[2025-05-02 01:37:12,799] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.60 | bwd_microstep: 276.04 | bwd_inner_microstep: 276.03 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 857 +[2025-05-02 01:37:13,049] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 99.55 | bwd_microstep: 132.94 | bwd_inner_microstep: 132.79 | bwd_allreduce_microstep: 0.10 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-02 01:37:13,530] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.56 | bwd_microstep: 274.12 | bwd_inner_microstep: 274.10 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-02 01:37:14,011] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.43 | bwd_microstep: 273.52 | bwd_inner_microstep: 273.50 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 345 +[2025-05-02 01:37:14,235] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 81.66 | bwd_microstep: 125.72 | bwd_inner_microstep: 125.46 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-02 01:37:14,714] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.44 | bwd_microstep: 273.69 | bwd_inner_microstep: 273.67 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1352 +[2025-05-02 01:37:15,080] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.89 | bwd_microstep: 206.18 | bwd_inner_microstep: 206.17 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:37:15,564] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.70 | bwd_microstep: 273.09 | bwd_inner_microstep: 273.08 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 325 +[2025-05-02 01:37:15,804] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.26 | bwd_microstep: 128.14 | bwd_inner_microstep: 127.96 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 01:37:16,288] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.21 | bwd_microstep: 273.03 | bwd_inner_microstep: 273.02 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 01:37:16,767] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.79 | bwd_microstep: 272.55 | bwd_inner_microstep: 272.53 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 01:37:17,246] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.61 | bwd_microstep: 272.43 | bwd_inner_microstep: 272.41 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:37:17,727] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.64 | bwd_microstep: 272.58 | bwd_inner_microstep: 272.57 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:37:18,207] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.03 | bwd_microstep: 271.83 | bwd_inner_microstep: 271.81 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:37:18,789] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.26 | optimizer_step: 17.02 +[2025-05-02 01:37:18,790] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.63 | bwd_microstep: 350.44 | bwd_inner_microstep: 273.08 | bwd_allreduce_microstep: 77.31 | step_microstep: 25.10 +[2025-05-02 01:37:18,791] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2681.00 | bwd: 3952.01 | bwd_inner: 3873.89 | bwd_allreduce: 77.61 | step: 26.13 + 15%|█▍ | 1272/8720 [3:21:52<14:38:30, 7.08s/it] {'loss': 0.8392, 'grad_norm': 7.146930694580078, 'learning_rate': 9.652265544855224e-06, 'epoch': 1.46} + 15%|█▍ | 1272/8720 [3:21:52<14:38:30, 7.08s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:37:19,274] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.10 | bwd_microstep: 270.97 | bwd_inner_microstep: 270.96 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1982 +[2025-05-02 01:37:19,780] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 197.26 | bwd_microstep: 292.29 | bwd_inner_microstep: 292.28 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1924 +[2025-05-02 01:37:20,281] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 197.44 | bwd_microstep: 286.99 | bwd_inner_microstep: 286.97 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1899 +[2025-05-02 01:37:20,764] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.36 | bwd_microstep: 276.11 | bwd_inner_microstep: 276.10 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 864 +[2025-05-02 01:37:21,011] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.96 | bwd_microstep: 133.45 | bwd_inner_microstep: 133.43 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1892 +[2025-05-02 01:37:21,492] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.90 | bwd_microstep: 274.77 | bwd_inner_microstep: 274.75 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 01:37:21,972] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.51 | bwd_microstep: 273.28 | bwd_inner_microstep: 273.26 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1362 +[2025-05-02 01:37:22,336] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.90 | bwd_microstep: 206.73 | bwd_inner_microstep: 206.71 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 01:37:22,815] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.83 | bwd_microstep: 273.50 | bwd_inner_microstep: 273.48 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 845 +[2025-05-02 01:37:23,056] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.81 | bwd_microstep: 132.75 | bwd_inner_microstep: 132.58 | bwd_allreduce_microstep: 0.09 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:37:23,532] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.07 | bwd_microstep: 272.75 | bwd_inner_microstep: 272.73 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:37:24,007] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.90 | bwd_microstep: 272.29 | bwd_inner_microstep: 272.28 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 01:37:24,482] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.16 | bwd_microstep: 271.25 | bwd_inner_microstep: 271.24 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:37:24,956] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.35 | bwd_microstep: 271.30 | bwd_inner_microstep: 271.28 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:37:25,433] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.81 | bwd_microstep: 272.68 | bwd_inner_microstep: 272.67 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 828 +[2025-05-02 01:37:25,759] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.04 | optimizer_gradients: 2.12 | optimizer_step: 16.54 +[2025-05-02 01:37:25,759] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 92.57 | bwd_microstep: 197.12 | bwd_inner_microstep: 130.53 | bwd_allreduce_microstep: 66.44 | step_microstep: 23.48 +[2025-05-02 01:37:25,761] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2704.63 | bwd: 3978.28 | bwd_inner: 3911.29 | bwd_allreduce: 66.55 | step: 24.31 + 15%|█▍ | 1273/8720 [3:21:59<14:34:18, 7.04s/it] {'loss': 0.9245, 'grad_norm': 8.070219993591309, 'learning_rate': 9.65158473561427e-06, 'epoch': 1.46} + 15%|█▍ | 1273/8720 [3:21:59<14:34:18, 7.04s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:37:26,238] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.33 | bwd_microstep: 270.46 | bwd_inner_microstep: 270.44 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1935 +[2025-05-02 01:37:26,737] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 196.34 | bwd_microstep: 288.04 | bwd_inner_microstep: 288.03 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1906 +[2025-05-02 01:37:27,218] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.95 | bwd_microstep: 276.12 | bwd_inner_microstep: 276.11 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.15 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1886 +[2025-05-02 01:37:27,697] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.46 | bwd_microstep: 274.61 | bwd_inner_microstep: 274.59 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1927 +[2025-05-02 01:37:28,196] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 196.01 | bwd_microstep: 287.20 | bwd_inner_microstep: 287.18 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-02 01:37:28,674] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.96 | bwd_microstep: 273.62 | bwd_inner_microstep: 273.60 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 01:37:29,152] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.85 | bwd_microstep: 272.94 | bwd_inner_microstep: 272.92 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 01:37:29,629] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.47 | bwd_microstep: 273.08 | bwd_inner_microstep: 273.06 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 01:37:30,105] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.28 | bwd_microstep: 272.75 | bwd_inner_microstep: 272.74 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 334 +[2025-05-02 01:37:30,316] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 76.05 | bwd_microstep: 120.45 | bwd_inner_microstep: 120.14 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 01:37:30,792] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.19 | bwd_microstep: 272.78 | bwd_inner_microstep: 272.76 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 01:37:31,269] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.67 | bwd_microstep: 273.02 | bwd_inner_microstep: 273.00 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:37:31,742] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.62 | bwd_microstep: 271.04 | bwd_inner_microstep: 271.03 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 01:37:32,217] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.24 | bwd_microstep: 271.36 | bwd_inner_microstep: 271.35 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1086 +[2025-05-02 01:37:32,507] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 115.61 | bwd_microstep: 159.94 | bwd_inner_microstep: 159.92 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 828 +[2025-05-02 01:37:32,845] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.14 | optimizer_step: 16.62 +[2025-05-02 01:37:32,846] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.38 | bwd_microstep: 207.47 | bwd_inner_microstep: 130.27 | bwd_allreduce_microstep: 77.05 | step_microstep: 24.49 +[2025-05-02 01:37:32,848] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2751.14 | bwd: 4064.93 | bwd_inner: 3987.26 | bwd_allreduce: 77.22 | step: 25.37 + 15%|█▍ | 1274/8720 [3:22:06<14:35:50, 7.06s/it] {'loss': 0.7079, 'grad_norm': 7.923083782196045, 'learning_rate': 9.650903284624145e-06, 'epoch': 1.46} + 15%|█▍ | 1274/8720 [3:22:06<14:35:50, 7.06s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2052 +[2025-05-02 01:37:33,374] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 203.18 | bwd_microstep: 300.99 | bwd_inner_microstep: 300.97 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1909 +[2025-05-02 01:37:33,860] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.45 | bwd_microstep: 276.38 | bwd_inner_microstep: 276.36 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1888 +[2025-05-02 01:37:34,344] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.94 | bwd_microstep: 274.50 | bwd_inner_microstep: 274.49 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-02 01:37:34,826] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.71 | bwd_microstep: 273.77 | bwd_inner_microstep: 273.75 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 01:37:35,305] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.70 | bwd_microstep: 273.19 | bwd_inner_microstep: 273.17 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 01:37:35,787] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.67 | bwd_microstep: 273.37 | bwd_inner_microstep: 273.35 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.05 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1360 +[2025-05-02 01:37:36,157] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.70 | bwd_microstep: 206.77 | bwd_inner_microstep: 206.63 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 01:37:36,637] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.30 | bwd_microstep: 273.27 | bwd_inner_microstep: 273.25 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 01:37:37,118] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.34 | bwd_microstep: 272.98 | bwd_inner_microstep: 272.96 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 01:37:37,598] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.51 | bwd_microstep: 272.67 | bwd_inner_microstep: 272.66 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 01:37:38,076] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.20 | bwd_microstep: 272.35 | bwd_inner_microstep: 272.33 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:37:38,555] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.63 | bwd_microstep: 273.01 | bwd_inner_microstep: 272.99 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.14 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:37:39,035] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.84 | bwd_microstep: 272.63 | bwd_inner_microstep: 272.62 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 01:37:39,513] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.60 | bwd_microstep: 271.44 | bwd_inner_microstep: 271.42 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2068 +[2025-05-02 01:37:40,037] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 204.07 | bwd_microstep: 303.26 | bwd_inner_microstep: 303.24 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1925 +[2025-05-02 01:37:40,640] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.15 | optimizer_step: 16.54 +[2025-05-02 01:37:40,641] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.07 | bwd_microstep: 365.12 | bwd_inner_microstep: 287.77 | bwd_allreduce_microstep: 77.30 | step_microstep: 24.30 +[2025-05-02 01:37:40,642] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 3010.55 | bwd: 4455.73 | bwd_inner: 4377.97 | bwd_allreduce: 77.46 | step: 25.25 + 15%|█▍ | 1275/8720 [3:22:14<15:03:10, 7.28s/it] {'loss': 0.7995, 'grad_norm': 4.624721527099609, 'learning_rate': 9.650221191978866e-06, 'epoch': 1.46} + 15%|█▍ | 1275/8720 [3:22:14<15:03:10, 7.28s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1910 +[2025-05-02 01:37:41,130] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.73 | bwd_microstep: 275.69 | bwd_inner_microstep: 275.67 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1926 +[2025-05-02 01:37:41,629] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.55 | bwd_microstep: 287.74 | bwd_inner_microstep: 287.72 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1894 +[2025-05-02 01:37:42,108] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.31 | bwd_microstep: 275.12 | bwd_inner_microstep: 275.10 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 347 +[2025-05-02 01:37:42,309] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 68.47 | bwd_microstep: 118.98 | bwd_inner_microstep: 118.67 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-02 01:37:42,786] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.50 | bwd_microstep: 274.08 | bwd_inner_microstep: 274.07 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 852 +[2025-05-02 01:37:43,028] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.30 | bwd_microstep: 132.67 | bwd_inner_microstep: 132.63 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 01:37:43,504] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.07 | bwd_microstep: 272.67 | bwd_inner_microstep: 272.65 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 01:37:43,983] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.36 | bwd_microstep: 272.84 | bwd_inner_microstep: 272.82 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:37:44,459] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.69 | bwd_microstep: 272.40 | bwd_inner_microstep: 272.39 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:37:44,935] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.31 | bwd_microstep: 272.34 | bwd_inner_microstep: 272.33 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:37:45,411] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.73 | bwd_microstep: 272.57 | bwd_inner_microstep: 272.55 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 322 +[2025-05-02 01:37:45,625] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 81.53 | bwd_microstep: 117.67 | bwd_inner_microstep: 117.34 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:37:46,100] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.39 | bwd_microstep: 272.13 | bwd_inner_microstep: 272.11 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 831 +[2025-05-02 01:37:46,338] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 92.46 | bwd_microstep: 130.05 | bwd_inner_microstep: 129.83 | bwd_allreduce_microstep: 0.09 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:37:46,812] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.44 | bwd_microstep: 271.87 | bwd_inner_microstep: 271.85 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 01:37:47,379] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.12 | optimizer_step: 16.92 +[2025-05-02 01:37:47,380] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.61 | bwd_microstep: 339.09 | bwd_inner_microstep: 271.75 | bwd_allreduce_microstep: 67.30 | step_microstep: 23.93 +[2025-05-02 01:37:47,381] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2604.15 | bwd: 3857.97 | bwd_inner: 3789.65 | bwd_allreduce: 67.69 | step: 24.93 + 15%|█▍ | 1276/8720 [3:22:21<14:42:53, 7.12s/it] {'loss': 0.6112, 'grad_norm': 7.0314788818359375, 'learning_rate': 9.649538457772536e-06, 'epoch': 1.46} + 15%|█▍ | 1276/8720 [3:22:21<14:42:53, 7.12s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 01:37:47,861] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.32 | bwd_microstep: 272.23 | bwd_inner_microstep: 272.21 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 405 +[2025-05-02 01:37:48,083] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 79.80 | bwd_microstep: 127.57 | bwd_inner_microstep: 127.27 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1904 +[2025-05-02 01:37:48,564] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.46 | bwd_microstep: 275.71 | bwd_inner_microstep: 275.70 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1131 +[2025-05-02 01:37:48,860] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 117.87 | bwd_microstep: 163.88 | bwd_inner_microstep: 163.67 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.20 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1364 +[2025-05-02 01:37:49,224] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.31 | bwd_microstep: 206.97 | bwd_inner_microstep: 206.95 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-02 01:37:49,702] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.35 | bwd_microstep: 273.44 | bwd_inner_microstep: 273.42 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-02 01:37:50,181] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.03 | bwd_microstep: 274.12 | bwd_inner_microstep: 274.10 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1350 +[2025-05-02 01:37:50,548] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.87 | bwd_microstep: 205.92 | bwd_inner_microstep: 205.78 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 01:37:51,028] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.12 | bwd_microstep: 273.07 | bwd_inner_microstep: 273.06 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1352 +[2025-05-02 01:37:51,395] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.74 | bwd_microstep: 206.04 | bwd_inner_microstep: 206.02 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 01:37:51,876] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.22 | bwd_microstep: 272.65 | bwd_inner_microstep: 272.63 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.14 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 01:37:52,357] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.16 | bwd_microstep: 271.99 | bwd_inner_microstep: 271.98 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:37:52,841] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.38 | bwd_microstep: 272.22 | bwd_inner_microstep: 272.20 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:37:53,320] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.41 | bwd_microstep: 272.36 | bwd_inner_microstep: 272.34 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1350 +[2025-05-02 01:37:53,683] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.57 | bwd_microstep: 206.07 | bwd_inner_microstep: 205.97 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:37:54,261] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.19 | optimizer_step: 16.64 +[2025-05-02 01:37:54,261] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.77 | bwd_microstep: 348.48 | bwd_inner_microstep: 271.92 | bwd_allreduce_microstep: 76.50 | step_microstep: 24.41 +[2025-05-02 01:37:54,263] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2645.02 | bwd: 3922.82 | bwd_inner: 3845.28 | bwd_allreduce: 76.95 | step: 25.84 + 15%|█▍ | 1277/8720 [3:22:28<14:34:06, 7.05s/it] {'loss': 0.7461, 'grad_norm': 6.197144031524658, 'learning_rate': 9.648855082099348e-06, 'epoch': 1.46} + 15%|█▍ | 1277/8720 [3:22:28<14:34:06, 7.05s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 317 +[2025-05-02 01:37:54,486] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 80.02 | bwd_microstep: 121.55 | bwd_inner_microstep: 121.24 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1896 +[2025-05-02 01:37:54,968] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.55 | bwd_microstep: 275.15 | bwd_inner_microstep: 275.13 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-02 01:37:55,450] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.53 | bwd_microstep: 273.20 | bwd_inner_microstep: 273.18 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:37:55,930] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.57 | bwd_microstep: 272.50 | bwd_inner_microstep: 272.48 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 01:37:56,411] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.96 | bwd_microstep: 272.75 | bwd_inner_microstep: 272.73 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1347 +[2025-05-02 01:37:56,776] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.15 | bwd_microstep: 205.80 | bwd_inner_microstep: 205.67 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 01:37:57,254] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.11 | bwd_microstep: 272.44 | bwd_inner_microstep: 272.42 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:37:57,732] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.04 | bwd_microstep: 272.30 | bwd_inner_microstep: 272.28 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 01:37:58,211] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.49 | bwd_microstep: 272.81 | bwd_inner_microstep: 272.79 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 01:37:58,690] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.63 | bwd_microstep: 273.00 | bwd_inner_microstep: 272.98 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:37:59,169] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.03 | bwd_microstep: 272.39 | bwd_inner_microstep: 272.38 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 01:37:59,647] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.76 | bwd_microstep: 272.81 | bwd_inner_microstep: 272.79 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:38:00,124] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.22 | bwd_microstep: 272.47 | bwd_inner_microstep: 272.45 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:38:00,603] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.37 | bwd_microstep: 272.73 | bwd_inner_microstep: 272.71 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 01:38:01,082] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.60 | bwd_microstep: 271.07 | bwd_inner_microstep: 271.05 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 01:38:01,663] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.19 | optimizer_step: 16.65 +[2025-05-02 01:38:01,664] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.87 | bwd_microstep: 348.63 | bwd_inner_microstep: 272.12 | bwd_allreduce_microstep: 76.45 | step_microstep: 24.32 +[2025-05-02 01:38:01,665] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2865.53 | bwd: 4221.64 | bwd_inner: 4144.46 | bwd_allreduce: 76.74 | step: 25.26 + 15%|█▍ | 1278/8720 [3:22:35<14:47:14, 7.15s/it] {'loss': 1.1891, 'grad_norm': 16.546733856201172, 'learning_rate': 9.648171065053585e-06, 'epoch': 1.47} + 15%|█▍ | 1278/8720 [3:22:35<14:47:14, 7.15s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-02 01:38:02,150] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.22 | bwd_microstep: 272.90 | bwd_inner_microstep: 272.89 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 360 +[2025-05-02 01:38:02,374] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 89.24 | bwd_microstep: 118.75 | bwd_inner_microstep: 118.56 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1890 +[2025-05-02 01:38:02,854] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.28 | bwd_microstep: 274.47 | bwd_inner_microstep: 274.45 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1367 +[2025-05-02 01:38:03,221] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 142.81 | bwd_microstep: 207.54 | bwd_inner_microstep: 207.46 | bwd_allreduce_microstep: 0.03 | step_microstep: 0.10 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1359 +[2025-05-02 01:38:03,588] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 143.16 | bwd_microstep: 206.76 | bwd_inner_microstep: 206.61 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-02 01:38:04,070] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.07 | bwd_microstep: 274.42 | bwd_inner_microstep: 274.40 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:38:04,550] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.01 | bwd_microstep: 272.54 | bwd_inner_microstep: 272.52 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 01:38:05,032] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.46 | bwd_microstep: 272.42 | bwd_inner_microstep: 272.40 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:38:05,510] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.83 | bwd_microstep: 272.53 | bwd_inner_microstep: 272.52 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 01:38:05,989] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.92 | bwd_microstep: 272.94 | bwd_inner_microstep: 272.92 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.16 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:38:06,471] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.05 | bwd_microstep: 272.20 | bwd_inner_microstep: 272.18 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:38:06,949] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.65 | bwd_microstep: 272.57 | bwd_inner_microstep: 272.56 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:38:07,426] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.49 | bwd_microstep: 272.44 | bwd_inner_microstep: 272.43 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:38:07,904] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.92 | bwd_microstep: 271.30 | bwd_inner_microstep: 271.28 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:38:08,382] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.53 | bwd_microstep: 271.70 | bwd_inner_microstep: 271.68 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 01:38:08,959] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.19 | optimizer_step: 16.67 +[2025-05-02 01:38:08,960] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.38 | bwd_microstep: 347.61 | bwd_inner_microstep: 271.56 | bwd_allreduce_microstep: 76.00 | step_microstep: 24.30 +[2025-05-02 01:38:08,961] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2824.65 | bwd: 4153.16 | bwd_inner: 4076.48 | bwd_allreduce: 76.29 | step: 25.31 + 15%|█▍ | 1279/8720 [3:22:42<14:52:25, 7.20s/it] {'loss': 0.5801, 'grad_norm': 18.00411033630371, 'learning_rate': 9.647486406729614e-06, 'epoch': 1.47} + 15%|█▍ | 1279/8720 [3:22:42<14:52:25, 7.20s/it]dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1493 +[2025-05-02 01:38:09,363] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 149.56 | bwd_microstep: 230.28 | bwd_inner_microstep: 230.25 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1961 +[2025-05-02 01:38:09,864] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 196.07 | bwd_microstep: 289.82 | bwd_inner_microstep: 289.80 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1902 +[2025-05-02 01:38:10,345] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.65 | bwd_microstep: 275.57 | bwd_inner_microstep: 275.56 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1883 +[2025-05-02 01:38:10,825] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.29 | bwd_microstep: 274.15 | bwd_inner_microstep: 274.14 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1369 +[2025-05-02 01:38:11,190] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 142.05 | bwd_microstep: 207.35 | bwd_inner_microstep: 207.27 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 01:38:11,670] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.00 | bwd_microstep: 272.81 | bwd_inner_microstep: 272.79 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 844 +[2025-05-02 01:38:11,916] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.26 | bwd_microstep: 132.23 | bwd_inner_microstep: 131.97 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-02 01:38:12,398] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.29 | bwd_microstep: 272.97 | bwd_inner_microstep: 272.96 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 837 +[2025-05-02 01:38:12,645] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 99.27 | bwd_microstep: 125.92 | bwd_inner_microstep: 125.65 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:38:13,123] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.32 | bwd_microstep: 272.20 | bwd_inner_microstep: 272.18 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 01:38:13,603] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.51 | bwd_microstep: 271.22 | bwd_inner_microstep: 271.21 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 01:38:14,081] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.29 | bwd_microstep: 271.25 | bwd_inner_microstep: 271.23 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 318 +[2025-05-02 01:38:14,317] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.07 | bwd_microstep: 123.46 | bwd_inner_microstep: 123.29 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:38:14,794] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.31 | bwd_microstep: 271.38 | bwd_inner_microstep: 271.36 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 01:38:15,271] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.47 | bwd_microstep: 270.96 | bwd_inner_microstep: 270.95 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 01:38:15,848] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.23 | optimizer_step: 16.78 +[2025-05-02 01:38:15,848] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.77 | bwd_microstep: 348.09 | bwd_inner_microstep: 271.37 | bwd_allreduce_microstep: 76.66 | step_microstep: 24.39 +[2025-05-02 01:38:15,849] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2657.77 | bwd: 3909.78 | bwd_inner: 3832.06 | bwd_allreduce: 77.06 | step: 25.61 + 15%|█▍ | 1280/8720 [3:22:49<14:40:47, 7.10s/it] {'loss': 0.8647, 'grad_norm': 11.25998592376709, 'learning_rate': 9.646801107221891e-06, 'epoch': 1.47} + 15%|█▍ | 1280/8720 [3:22:49<14:40:47, 7.10s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:38:16,327] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.31 | bwd_microstep: 270.30 | bwd_inner_microstep: 270.28 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1936 +[2025-05-02 01:38:16,827] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.80 | bwd_microstep: 288.03 | bwd_inner_microstep: 288.01 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1916 +[2025-05-02 01:38:17,309] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.94 | bwd_microstep: 276.17 | bwd_inner_microstep: 276.16 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 01:38:17,787] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.53 | bwd_microstep: 272.78 | bwd_inner_microstep: 272.77 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-02 01:38:18,265] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.10 | bwd_microstep: 274.19 | bwd_inner_microstep: 274.18 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 01:38:18,743] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.58 | bwd_microstep: 272.97 | bwd_inner_microstep: 272.95 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 321 +[2025-05-02 01:38:18,960] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 82.05 | bwd_microstep: 120.42 | bwd_inner_microstep: 120.20 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 326 +[2025-05-02 01:38:19,179] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 86.36 | bwd_microstep: 118.09 | bwd_inner_microstep: 117.93 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:38:19,656] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.89 | bwd_microstep: 272.45 | bwd_inner_microstep: 272.44 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 01:38:20,135] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.35 | bwd_microstep: 272.61 | bwd_inner_microstep: 272.59 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:38:20,613] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.42 | bwd_microstep: 272.30 | bwd_inner_microstep: 272.28 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:38:21,093] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.20 | bwd_microstep: 272.33 | bwd_inner_microstep: 272.31 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 01:38:21,572] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.78 | bwd_microstep: 271.50 | bwd_inner_microstep: 271.48 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 830 +[2025-05-02 01:38:21,812] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.50 | bwd_microstep: 130.03 | bwd_inner_microstep: 129.80 | bwd_allreduce_microstep: 0.10 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 01:38:22,289] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.49 | bwd_microstep: 271.41 | bwd_inner_microstep: 271.39 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 01:38:22,867] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.22 | optimizer_step: 16.74 +[2025-05-02 01:38:22,867] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.57 | bwd_microstep: 348.07 | bwd_inner_microstep: 271.65 | bwd_allreduce_microstep: 76.37 | step_microstep: 24.67 +[2025-05-02 01:38:22,869] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2716.53 | bwd: 4003.72 | bwd_inner: 3926.57 | bwd_allreduce: 76.63 | step: 25.54 + 15%|█▍ | 1281/8720 [3:22:56<14:37:37, 7.08s/it] {'loss': 0.4473, 'grad_norm': 12.094983100891113, 'learning_rate': 9.646115166624967e-06, 'epoch': 1.47} + 15%|█▍ | 1281/8720 [3:22:56<14:37:37, 7.08s/it]dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 842 +[2025-05-02 01:38:23,116] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.47 | bwd_microstep: 131.90 | bwd_inner_microstep: 131.84 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.08 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 915 +[2025-05-02 01:38:23,378] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 102.80 | bwd_microstep: 145.52 | bwd_inner_microstep: 145.34 | bwd_allreduce_microstep: 0.10 | step_microstep: 0.09 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1422 +[2025-05-02 01:38:23,753] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 145.79 | bwd_microstep: 213.30 | bwd_inner_microstep: 213.29 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1897 +[2025-05-02 01:38:24,233] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.84 | bwd_microstep: 275.13 | bwd_inner_microstep: 275.11 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-02 01:38:24,711] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.58 | bwd_microstep: 274.10 | bwd_inner_microstep: 274.08 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 345 +[2025-05-02 01:38:24,910] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 67.58 | bwd_microstep: 118.41 | bwd_inner_microstep: 118.28 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-02 01:38:25,387] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.77 | bwd_microstep: 273.33 | bwd_inner_microstep: 273.32 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 01:38:25,863] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.93 | bwd_microstep: 272.79 | bwd_inner_microstep: 272.77 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 01:38:26,350] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.03 | bwd_microstep: 273.12 | bwd_inner_microstep: 273.10 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 328 +[2025-05-02 01:38:26,562] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 76.23 | bwd_microstep: 120.75 | bwd_inner_microstep: 120.44 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 322 +[2025-05-02 01:38:26,781] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 85.74 | bwd_microstep: 118.28 | bwd_inner_microstep: 118.15 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1345 +[2025-05-02 01:38:27,142] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.52 | bwd_microstep: 205.06 | bwd_inner_microstep: 205.04 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:38:27,617] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.60 | bwd_microstep: 271.98 | bwd_inner_microstep: 271.96 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:38:28,092] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.08 | bwd_microstep: 271.11 | bwd_inner_microstep: 271.09 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 01:38:28,567] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.25 | bwd_microstep: 271.07 | bwd_inner_microstep: 271.05 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:38:29,130] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.23 | optimizer_step: 16.75 +[2025-05-02 01:38:29,130] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.80 | bwd_microstep: 337.53 | bwd_inner_microstep: 271.36 | bwd_allreduce_microstep: 66.12 | step_microstep: 23.94 +[2025-05-02 01:38:29,132] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2403.71 | bwd: 3573.45 | bwd_inner: 3506.34 | bwd_allreduce: 66.51 | step: 25.07 + 15%|█▍ | 1282/8720 [3:23:02<14:07:05, 6.83s/it] {'loss': 0.731, 'grad_norm': 10.73851490020752, 'learning_rate': 9.645428585033474e-06, 'epoch': 1.47} + 15%|█▍ | 1282/8720 [3:23:02<14:07:05, 6.83s/it]dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1356 +[2025-05-02 01:38:29,498] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.99 | bwd_microstep: 205.88 | bwd_inner_microstep: 205.71 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1995 +[2025-05-02 01:38:30,007] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 199.85 | bwd_microstep: 294.23 | bwd_inner_microstep: 294.21 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1931 +[2025-05-02 01:38:30,504] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.07 | bwd_microstep: 287.71 | bwd_inner_microstep: 287.69 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 378 +[2025-05-02 01:38:30,718] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 73.02 | bwd_microstep: 126.97 | bwd_inner_microstep: 126.66 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 351 +[2025-05-02 01:38:30,923] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 68.66 | bwd_microstep: 122.86 | bwd_inner_microstep: 122.70 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.11 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1118 +[2025-05-02 01:38:31,217] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 117.21 | bwd_microstep: 162.40 | bwd_inner_microstep: 162.34 | bwd_allreduce_microstep: 0.03 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-02 01:38:31,695] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.76 | bwd_microstep: 273.78 | bwd_inner_microstep: 273.76 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-02 01:38:32,173] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.01 | bwd_microstep: 273.76 | bwd_inner_microstep: 273.74 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 01:38:32,651] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.74 | bwd_microstep: 273.20 | bwd_inner_microstep: 273.18 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-02 01:38:33,131] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.84 | bwd_microstep: 274.34 | bwd_inner_microstep: 274.33 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 01:38:33,610] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.50 | bwd_microstep: 272.86 | bwd_inner_microstep: 272.84 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1092 +[2025-05-02 01:38:33,901] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 114.78 | bwd_microstep: 161.08 | bwd_inner_microstep: 160.96 | bwd_allreduce_microstep: 0.08 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:38:34,377] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.11 | bwd_microstep: 272.65 | bwd_inner_microstep: 272.64 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:38:34,854] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.27 | bwd_microstep: 272.71 | bwd_inner_microstep: 272.69 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:38:35,332] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.88 | bwd_microstep: 272.42 | bwd_inner_microstep: 272.40 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:38:35,912] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.24 | optimizer_step: 16.76 +[2025-05-02 01:38:35,912] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.88 | bwd_microstep: 349.03 | bwd_inner_microstep: 272.68 | bwd_allreduce_microstep: 76.30 | step_microstep: 24.72 +[2025-05-02 01:38:35,914] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2608.29 | bwd: 3895.97 | bwd_inner: 3818.64 | bwd_allreduce: 76.75 | step: 25.64 + 15%|█▍ | 1283/8720 [3:23:09<14:05:09, 6.82s/it] {'loss': 0.6767, 'grad_norm': 6.949886798858643, 'learning_rate': 9.644741362542134e-06, 'epoch': 1.47} + 15%|█▍ | 1283/8720 [3:23:09<14:05:09, 6.82s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 318 +[2025-05-02 01:38:36,125] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 75.09 | bwd_microstep: 114.80 | bwd_inner_microstep: 114.58 | bwd_allreduce_microstep: 0.09 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1909 +[2025-05-02 01:38:36,605] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.80 | bwd_microstep: 276.10 | bwd_inner_microstep: 276.08 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1887 +[2025-05-02 01:38:37,083] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.33 | bwd_microstep: 274.48 | bwd_inner_microstep: 274.47 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 01:38:37,559] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.23 | bwd_microstep: 272.67 | bwd_inner_microstep: 272.65 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-02 01:38:38,037] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.93 | bwd_microstep: 273.21 | bwd_inner_microstep: 273.19 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:38:38,514] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.07 | bwd_microstep: 272.69 | bwd_inner_microstep: 272.68 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:38:38,991] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.54 | bwd_microstep: 272.65 | bwd_inner_microstep: 272.63 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 01:38:39,468] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.73 | bwd_microstep: 273.24 | bwd_inner_microstep: 273.22 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 01:38:39,943] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.95 | bwd_microstep: 272.24 | bwd_inner_microstep: 272.23 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 835 +[2025-05-02 01:38:40,174] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 90.29 | bwd_microstep: 126.08 | bwd_inner_microstep: 125.88 | bwd_allreduce_microstep: 0.10 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 01:38:40,650] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.53 | bwd_microstep: 272.31 | bwd_inner_microstep: 272.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:38:41,127] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.54 | bwd_microstep: 272.16 | bwd_inner_microstep: 272.14 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1094 +[2025-05-02 01:38:41,418] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 114.96 | bwd_microstep: 161.12 | bwd_inner_microstep: 161.02 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:38:41,893] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.10 | bwd_microstep: 271.22 | bwd_inner_microstep: 271.21 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:38:42,370] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.76 | bwd_microstep: 271.39 | bwd_inner_microstep: 271.37 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 01:38:42,934] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.17 | optimizer_step: 16.60 +[2025-05-02 01:38:42,935] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.00 | bwd_microstep: 337.92 | bwd_inner_microstep: 271.85 | bwd_allreduce_microstep: 66.03 | step_microstep: 23.63 +[2025-05-02 01:38:42,936] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2730.57 | bwd: 4014.35 | bwd_inner: 3947.58 | bwd_allreduce: 66.29 | step: 24.43 + 15%|█▍ | 1284/8720 [3:23:16<14:12:32, 6.88s/it] {'loss': 0.5911, 'grad_norm': 6.354833602905273, 'learning_rate': 9.644053499245762e-06, 'epoch': 1.47} + 15%|█▍ | 1284/8720 [3:23:16<14:12:32, 6.88s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1933 +[2025-05-02 01:38:43,438] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.12 | bwd_microstep: 287.39 | bwd_inner_microstep: 287.38 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1910 +[2025-05-02 01:38:43,920] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.09 | bwd_microstep: 276.22 | bwd_inner_microstep: 276.20 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 380 +[2025-05-02 01:38:44,132] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 72.62 | bwd_microstep: 126.17 | bwd_inner_microstep: 126.04 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.08 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 347 +[2025-05-02 01:38:44,337] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 71.98 | bwd_microstep: 119.30 | bwd_inner_microstep: 119.04 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-02 01:38:44,814] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.93 | bwd_microstep: 274.20 | bwd_inner_microstep: 274.19 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-02 01:38:45,293] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.96 | bwd_microstep: 273.84 | bwd_inner_microstep: 273.82 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-02 01:38:45,771] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.46 | bwd_microstep: 273.27 | bwd_inner_microstep: 273.25 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 01:38:46,251] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.10 | bwd_microstep: 273.00 | bwd_inner_microstep: 272.98 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:38:46,728] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.82 | bwd_microstep: 272.53 | bwd_inner_microstep: 272.51 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:38:47,204] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.38 | bwd_microstep: 272.60 | bwd_inner_microstep: 272.59 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 835 +[2025-05-02 01:38:47,435] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 90.37 | bwd_microstep: 125.99 | bwd_inner_microstep: 125.97 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:38:47,909] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.15 | bwd_microstep: 271.40 | bwd_inner_microstep: 271.38 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:38:48,383] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.14 | bwd_microstep: 271.31 | bwd_inner_microstep: 271.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:38:48,858] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.84 | bwd_microstep: 272.04 | bwd_inner_microstep: 272.02 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 01:38:49,332] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.39 | bwd_microstep: 271.32 | bwd_inner_microstep: 271.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:38:49,897] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.04 | optimizer_gradients: 2.15 | optimizer_step: 16.56 +[2025-05-02 01:38:49,897] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.62 | bwd_microstep: 337.96 | bwd_inner_microstep: 271.80 | bwd_allreduce_microstep: 66.12 | step_microstep: 23.54 +[2025-05-02 01:38:49,898] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2695.72 | bwd: 3998.59 | bwd_inner: 3931.85 | bwd_allreduce: 66.34 | step: 24.32 + 15%|█▍ | 1285/8720 [3:23:23<14:15:31, 6.90s/it] {'loss': 0.6308, 'grad_norm': 9.197545051574707, 'learning_rate': 9.643364995239257e-06, 'epoch': 1.47} + 15%|█▍ | 1285/8720 [3:23:23<14:15:31, 6.90s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:38:50,375] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.24 | bwd_microstep: 270.39 | bwd_inner_microstep: 270.38 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1891 +[2025-05-02 01:38:50,855] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.04 | bwd_microstep: 274.97 | bwd_inner_microstep: 274.95 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-02 01:38:51,334] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.42 | bwd_microstep: 273.87 | bwd_inner_microstep: 273.85 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1358 +[2025-05-02 01:38:51,698] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.79 | bwd_microstep: 206.49 | bwd_inner_microstep: 206.42 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 01:38:52,179] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.10 | bwd_microstep: 272.67 | bwd_inner_microstep: 272.65 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1351 +[2025-05-02 01:38:52,547] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.60 | bwd_microstep: 205.84 | bwd_inner_microstep: 205.83 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 01:38:53,030] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.77 | bwd_microstep: 272.83 | bwd_inner_microstep: 272.81 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:38:53,511] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.82 | bwd_microstep: 272.82 | bwd_inner_microstep: 272.80 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1091 +[2025-05-02 01:38:53,809] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 118.46 | bwd_microstep: 160.70 | bwd_inner_microstep: 160.53 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.10 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 321 +[2025-05-02 01:38:54,035] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 82.80 | bwd_microstep: 126.57 | bwd_inner_microstep: 126.36 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:38:54,511] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.92 | bwd_microstep: 271.03 | bwd_inner_microstep: 271.01 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:38:54,989] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.10 | bwd_microstep: 272.39 | bwd_inner_microstep: 272.38 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:38:55,468] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.57 | bwd_microstep: 272.48 | bwd_inner_microstep: 272.46 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:38:55,945] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.95 | bwd_microstep: 271.34 | bwd_inner_microstep: 271.33 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 01:38:56,422] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.82 | bwd_microstep: 271.04 | bwd_inner_microstep: 271.02 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 01:38:56,998] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.18 | optimizer_step: 16.70 +[2025-05-02 01:38:56,998] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.84 | bwd_microstep: 347.40 | bwd_inner_microstep: 271.54 | bwd_allreduce_microstep: 75.81 | step_microstep: 24.37 +[2025-05-02 01:38:57,000] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2744.88 | bwd: 4042.92 | bwd_inner: 3966.38 | bwd_allreduce: 76.09 | step: 25.34 + 15%|█▍ | 1286/8720 [3:23:30<14:22:48, 6.96s/it] {'loss': 0.3402, 'grad_norm': 7.116298675537109, 'learning_rate': 9.642675850617606e-06, 'epoch': 1.47} + 15%|█▍ | 1286/8720 [3:23:30<14:22:48, 6.96s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 01:38:57,480] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.00 | bwd_microstep: 270.32 | bwd_inner_microstep: 270.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2033 +[2025-05-02 01:38:57,997] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 200.44 | bwd_microstep: 297.41 | bwd_inner_microstep: 297.39 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-02 01:38:58,479] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.68 | bwd_microstep: 273.97 | bwd_inner_microstep: 273.96 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 339 +[2025-05-02 01:38:58,724] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 96.33 | bwd_microstep: 129.85 | bwd_inner_microstep: 129.55 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-02 01:38:59,203] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.19 | bwd_microstep: 273.66 | bwd_inner_microstep: 273.64 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 845 +[2025-05-02 01:38:59,445] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.07 | bwd_microstep: 132.21 | bwd_inner_microstep: 132.02 | bwd_allreduce_microstep: 0.08 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:38:59,923] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.39 | bwd_microstep: 272.53 | bwd_inner_microstep: 272.52 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.16 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1362 +[2025-05-02 01:39:00,288] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.37 | bwd_microstep: 206.69 | bwd_inner_microstep: 206.66 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:39:00,766] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.48 | bwd_microstep: 271.37 | bwd_inner_microstep: 271.35 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 01:39:01,246] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.37 | bwd_microstep: 272.99 | bwd_inner_microstep: 272.97 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:39:01,725] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.84 | bwd_microstep: 271.43 | bwd_inner_microstep: 271.41 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:39:02,204] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.08 | bwd_microstep: 272.67 | bwd_inner_microstep: 272.65 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 01:39:02,685] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.59 | bwd_microstep: 272.35 | bwd_inner_microstep: 272.34 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 322 +[2025-05-02 01:39:02,901] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 81.45 | bwd_microstep: 118.89 | bwd_inner_microstep: 118.58 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:39:03,376] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.94 | bwd_microstep: 271.14 | bwd_inner_microstep: 271.13 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 01:39:03,953] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.14 | optimizer_step: 16.67 +[2025-05-02 01:39:03,954] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.83 | bwd_microstep: 348.47 | bwd_inner_microstep: 271.20 | bwd_allreduce_microstep: 77.22 | step_microstep: 24.40 +[2025-05-02 01:39:03,955] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2685.66 | bwd: 3956.08 | bwd_inner: 3877.81 | bwd_allreduce: 77.59 | step: 25.47 + 15%|█▍ | 1287/8720 [3:23:37<14:22:23, 6.96s/it] {'loss': 0.5189, 'grad_norm': 14.030721664428711, 'learning_rate': 9.641986065475888e-06, 'epoch': 1.48} + 15%|█▍ | 1287/8720 [3:23:37<14:22:23, 6.96s/it]dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1352 +[2025-05-02 01:39:04,324] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.03 | bwd_microstep: 205.28 | bwd_inner_microstep: 205.21 | bwd_allreduce_microstep: 0.03 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1944 +[2025-05-02 01:39:04,825] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 196.97 | bwd_microstep: 288.73 | bwd_inner_microstep: 288.71 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-02 01:39:05,303] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.90 | bwd_microstep: 273.48 | bwd_inner_microstep: 273.46 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 01:39:05,781] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.75 | bwd_microstep: 273.42 | bwd_inner_microstep: 273.41 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 01:39:06,257] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.14 | bwd_microstep: 272.68 | bwd_inner_microstep: 272.66 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1098 +[2025-05-02 01:39:06,547] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 114.73 | bwd_microstep: 160.99 | bwd_inner_microstep: 160.97 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 01:39:07,024] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.88 | bwd_microstep: 272.85 | bwd_inner_microstep: 272.84 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 327 +[2025-05-02 01:39:07,231] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 78.12 | bwd_microstep: 115.96 | bwd_inner_microstep: 115.83 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:39:07,706] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.23 | bwd_microstep: 272.63 | bwd_inner_microstep: 272.61 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.17 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1346 +[2025-05-02 01:39:08,068] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.88 | bwd_microstep: 205.32 | bwd_inner_microstep: 205.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:39:08,544] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.14 | bwd_microstep: 272.49 | bwd_inner_microstep: 272.47 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:39:09,020] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.64 | bwd_microstep: 272.27 | bwd_inner_microstep: 272.25 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:39:09,494] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.95 | bwd_microstep: 272.16 | bwd_inner_microstep: 272.14 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:39:09,968] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.14 | bwd_microstep: 271.07 | bwd_inner_microstep: 271.06 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:39:10,442] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.17 | bwd_microstep: 271.20 | bwd_inner_microstep: 271.19 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1850 +[2025-05-02 01:39:11,006] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.13 | optimizer_step: 16.65 +[2025-05-02 01:39:11,006] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.80 | bwd_microstep: 337.68 | bwd_inner_microstep: 271.36 | bwd_allreduce_microstep: 66.27 | step_microstep: 23.67 +[2025-05-02 01:39:11,008] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2743.20 | bwd: 4038.27 | bwd_inner: 3971.50 | bwd_allreduce: 66.44 | step: 24.65 + 15%|█▍ | 1288/8720 [3:23:44<14:25:35, 6.99s/it] {'loss': 0.5236, 'grad_norm': 10.3230562210083, 'learning_rate': 9.641295639909265e-06, 'epoch': 1.48} + 15%|█▍ | 1288/8720 [3:23:44<14:25:35, 6.99s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 420 +[2025-05-02 01:39:11,218] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 72.88 | bwd_microstep: 119.49 | bwd_inner_microstep: 119.36 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1921 +[2025-05-02 01:39:11,713] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 193.91 | bwd_microstep: 286.60 | bwd_inner_microstep: 286.58 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1922 +[2025-05-02 01:39:12,212] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 196.05 | bwd_microstep: 286.89 | bwd_inner_microstep: 286.87 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 860 +[2025-05-02 01:39:12,453] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.04 | bwd_microstep: 132.98 | bwd_inner_microstep: 132.96 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:39:12,927] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.27 | bwd_microstep: 272.48 | bwd_inner_microstep: 272.46 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:39:13,405] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.33 | bwd_microstep: 272.15 | bwd_inner_microstep: 272.14 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 834 +[2025-05-02 01:39:13,643] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 96.00 | bwd_microstep: 125.65 | bwd_inner_microstep: 125.43 | bwd_allreduce_microstep: 0.14 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:39:14,123] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.34 | bwd_microstep: 272.25 | bwd_inner_microstep: 272.23 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 01:39:14,604] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.81 | bwd_microstep: 272.92 | bwd_inner_microstep: 272.90 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:39:15,086] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.16 | bwd_microstep: 272.02 | bwd_inner_microstep: 272.01 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:39:15,564] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.31 | bwd_microstep: 271.87 | bwd_inner_microstep: 271.85 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1350 +[2025-05-02 01:39:15,929] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.29 | bwd_microstep: 206.25 | bwd_inner_microstep: 206.13 | bwd_allreduce_microstep: 0.03 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:39:16,406] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.18 | bwd_microstep: 271.77 | bwd_inner_microstep: 271.75 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:39:16,886] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.84 | bwd_microstep: 271.68 | bwd_inner_microstep: 271.66 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:39:17,363] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.17 | bwd_microstep: 271.11 | bwd_inner_microstep: 271.10 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:39:17,941] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.14 | optimizer_step: 16.67 +[2025-05-02 01:39:17,942] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.88 | bwd_microstep: 347.64 | bwd_inner_microstep: 271.46 | bwd_allreduce_microstep: 76.13 | step_microstep: 24.35 +[2025-05-02 01:39:17,943] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2677.11 | bwd: 3953.85 | bwd_inner: 3876.92 | bwd_allreduce: 76.45 | step: 25.34 + 15%|█▍ | 1289/8720 [3:23:51<14:23:35, 6.97s/it] {'loss': 1.0581, 'grad_norm': 19.903535842895508, 'learning_rate': 9.640604574012993e-06, 'epoch': 1.48} + 15%|█▍ | 1289/8720 [3:23:51<14:23:35, 6.97s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1930 +[2025-05-02 01:39:18,447] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 194.93 | bwd_microstep: 286.74 | bwd_inner_microstep: 286.73 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1888 +[2025-05-02 01:39:18,926] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.02 | bwd_microstep: 274.27 | bwd_inner_microstep: 274.25 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 341 +[2025-05-02 01:39:19,134] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 77.45 | bwd_microstep: 117.78 | bwd_inner_microstep: 117.47 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 01:39:19,611] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.67 | bwd_microstep: 273.19 | bwd_inner_microstep: 273.17 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-02 01:39:20,090] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.21 | bwd_microstep: 273.88 | bwd_inner_microstep: 273.86 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 01:39:20,568] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.63 | bwd_microstep: 272.47 | bwd_inner_microstep: 272.45 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.15 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1347 +[2025-05-02 01:39:20,933] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.28 | bwd_microstep: 205.64 | bwd_inner_microstep: 205.52 | bwd_allreduce_microstep: 0.03 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 01:39:21,412] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.58 | bwd_microstep: 272.60 | bwd_inner_microstep: 272.58 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:39:21,889] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.98 | bwd_microstep: 272.23 | bwd_inner_microstep: 272.21 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:39:22,368] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.08 | bwd_microstep: 272.27 | bwd_inner_microstep: 272.25 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:39:22,848] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.16 | bwd_microstep: 272.47 | bwd_inner_microstep: 272.45 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:39:23,327] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.65 | bwd_microstep: 272.15 | bwd_inner_microstep: 272.13 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 01:39:23,806] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.45 | bwd_microstep: 272.89 | bwd_inner_microstep: 272.88 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.11 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 321 +[2025-05-02 01:39:24,034] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 89.13 | bwd_microstep: 121.89 | bwd_inner_microstep: 121.57 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:39:24,511] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.62 | bwd_microstep: 271.21 | bwd_inner_microstep: 271.19 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 01:39:25,086] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.14 | optimizer_step: 16.62 +[2025-05-02 01:39:25,086] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.77 | bwd_microstep: 347.20 | bwd_inner_microstep: 271.30 | bwd_allreduce_microstep: 75.85 | step_microstep: 23.63 +[2025-05-02 01:39:25,087] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2757.26 | bwd: 4078.95 | bwd_inner: 4002.13 | bwd_allreduce: 76.23 | step: 24.74 + 15%|█▍ | 1290/8720 [3:23:58<14:29:46, 7.02s/it] {'loss': 0.638, 'grad_norm': 15.876734733581543, 'learning_rate': 9.639912867882413e-06, 'epoch': 1.48} + 15%|█▍ | 1290/8720 [3:23:58<14:29:46, 7.02s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 435 +[2025-05-02 01:39:25,287] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 69.72 | bwd_microstep: 112.44 | bwd_inner_microstep: 112.11 | bwd_allreduce_microstep: 0.15 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1892 +[2025-05-02 01:39:25,765] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.42 | bwd_microstep: 274.76 | bwd_inner_microstep: 274.75 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1896 +[2025-05-02 01:39:26,245] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.18 | bwd_microstep: 274.85 | bwd_inner_microstep: 274.83 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 01:39:26,721] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.55 | bwd_microstep: 272.86 | bwd_inner_microstep: 272.84 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.10 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 335 +[2025-05-02 01:39:26,921] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 67.71 | bwd_microstep: 118.49 | bwd_inner_microstep: 118.31 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 01:39:27,397] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.44 | bwd_microstep: 273.04 | bwd_inner_microstep: 273.03 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 01:39:27,873] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.65 | bwd_microstep: 272.86 | bwd_inner_microstep: 272.84 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.11 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1353 +[2025-05-02 01:39:28,235] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.42 | bwd_microstep: 206.09 | bwd_inner_microstep: 205.98 | bwd_allreduce_microstep: 0.03 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 01:39:28,712] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.17 | bwd_microstep: 272.83 | bwd_inner_microstep: 272.81 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1091 +[2025-05-02 01:39:29,005] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 114.82 | bwd_microstep: 160.74 | bwd_inner_microstep: 160.62 | bwd_allreduce_microstep: 0.03 | step_microstep: 0.10 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 325 +[2025-05-02 01:39:29,221] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 83.98 | bwd_microstep: 115.51 | bwd_inner_microstep: 115.35 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.09 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1346 +[2025-05-02 01:39:29,586] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.95 | bwd_microstep: 205.97 | bwd_inner_microstep: 205.93 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:39:30,063] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.68 | bwd_microstep: 272.56 | bwd_inner_microstep: 272.54 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:39:30,540] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.03 | bwd_microstep: 271.13 | bwd_inner_microstep: 271.11 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:39:31,016] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.36 | bwd_microstep: 271.18 | bwd_inner_microstep: 271.16 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.17 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 01:39:31,582] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.14 | optimizer_step: 17.02 +[2025-05-02 01:39:31,583] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.57 | bwd_microstep: 338.01 | bwd_inner_microstep: 271.31 | bwd_allreduce_microstep: 66.66 | step_microstep: 24.07 +[2025-05-02 01:39:31,584] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2501.35 | bwd: 3713.46 | bwd_inner: 3645.68 | bwd_allreduce: 67.12 | step: 25.44 + 15%|█▍ | 1291/8720 [3:24:05<14:10:04, 6.87s/it] {'loss': 1.2929, 'grad_norm': 17.70690155029297, 'learning_rate': 9.639220521612956e-06, 'epoch': 1.48} + 15%|█▍ | 1291/8720 [3:24:05<14:10:04, 6.87s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 383 +[2025-05-02 01:39:31,789] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 67.77 | bwd_microstep: 119.57 | bwd_inner_microstep: 119.27 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1982 +[2025-05-02 01:39:32,292] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.77 | bwd_microstep: 292.16 | bwd_inner_microstep: 292.14 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1949 +[2025-05-02 01:39:32,791] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.53 | bwd_microstep: 289.05 | bwd_inner_microstep: 289.03 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 383 +[2025-05-02 01:39:33,003] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 76.17 | bwd_microstep: 121.36 | bwd_inner_microstep: 121.03 | bwd_allreduce_microstep: 0.14 | step_microstep: 0.09 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 391 +[2025-05-02 01:39:33,224] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 82.38 | bwd_microstep: 123.70 | bwd_inner_microstep: 123.57 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1898 +[2025-05-02 01:39:33,703] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.77 | bwd_microstep: 275.01 | bwd_inner_microstep: 274.99 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-02 01:39:34,181] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.82 | bwd_microstep: 273.94 | bwd_inner_microstep: 273.92 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1892 +[2025-05-02 01:39:34,662] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.26 | bwd_microstep: 274.73 | bwd_inner_microstep: 274.71 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 843 +[2025-05-02 01:39:34,902] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.77 | bwd_microstep: 132.21 | bwd_inner_microstep: 131.94 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 01:39:35,379] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.94 | bwd_microstep: 272.72 | bwd_inner_microstep: 272.71 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:39:35,856] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.11 | bwd_microstep: 272.30 | bwd_inner_microstep: 272.28 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 01:39:36,336] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.75 | bwd_microstep: 272.82 | bwd_inner_microstep: 272.80 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 01:39:36,819] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.64 | bwd_microstep: 272.67 | bwd_inner_microstep: 272.65 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:39:37,297] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.60 | bwd_microstep: 271.99 | bwd_inner_microstep: 271.98 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 01:39:37,775] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.38 | bwd_microstep: 272.25 | bwd_inner_microstep: 272.23 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 01:39:38,342] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.16 | optimizer_step: 16.79 +[2025-05-02 01:39:38,342] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.64 | bwd_microstep: 339.08 | bwd_inner_microstep: 272.75 | bwd_allreduce_microstep: 66.27 | step_microstep: 24.07 +[2025-05-02 01:39:38,343] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2598.99 | bwd: 3875.63 | bwd_inner: 3808.17 | bwd_allreduce: 66.76 | step: 24.94 + 15%|█▍ | 1292/8720 [3:24:12<14:06:01, 6.83s/it] {'loss': 0.8642, 'grad_norm': 11.193924903869629, 'learning_rate': 9.638527535300142e-06, 'epoch': 1.48} + 15%|█▍ | 1292/8720 [3:24:12<14:06:01, 6.83s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 01:39:38,823] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.06 | bwd_microstep: 271.81 | bwd_inner_microstep: 271.79 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 866 +[2025-05-02 01:39:39,065] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.85 | bwd_microstep: 133.82 | bwd_inner_microstep: 133.60 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-02 01:39:39,543] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.12 | bwd_microstep: 273.90 | bwd_inner_microstep: 273.88 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1883 +[2025-05-02 01:39:40,022] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.67 | bwd_microstep: 274.12 | bwd_inner_microstep: 274.10 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 01:39:40,498] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.47 | bwd_microstep: 272.73 | bwd_inner_microstep: 272.71 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 01:39:40,976] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.69 | bwd_microstep: 273.07 | bwd_inner_microstep: 273.05 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:39:41,453] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.69 | bwd_microstep: 272.56 | bwd_inner_microstep: 272.54 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 847 +[2025-05-02 01:39:41,694] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.35 | bwd_microstep: 132.37 | bwd_inner_microstep: 132.18 | bwd_allreduce_microstep: 0.10 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:39:42,170] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.29 | bwd_microstep: 272.61 | bwd_inner_microstep: 272.59 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 01:39:42,647] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.18 | bwd_microstep: 272.13 | bwd_inner_microstep: 272.12 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.11 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 321 +[2025-05-02 01:39:42,869] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 88.84 | bwd_microstep: 117.21 | bwd_inner_microstep: 116.99 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 01:39:43,347] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.66 | bwd_microstep: 272.71 | bwd_inner_microstep: 272.69 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 01:39:43,826] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.35 | bwd_microstep: 272.68 | bwd_inner_microstep: 272.66 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 01:39:44,302] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.54 | bwd_microstep: 271.20 | bwd_inner_microstep: 271.18 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 830 +[2025-05-02 01:39:44,543] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.36 | bwd_microstep: 129.67 | bwd_inner_microstep: 129.58 | bwd_allreduce_microstep: 0.04 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:39:45,120] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.21 | optimizer_step: 16.74 +[2025-05-02 01:39:45,120] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.05 | bwd_microstep: 348.10 | bwd_inner_microstep: 271.50 | bwd_allreduce_microstep: 76.56 | step_microstep: 24.64 +[2025-05-02 01:39:45,122] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2628.88 | bwd: 3860.76 | bwd_inner: 3783.23 | bwd_allreduce: 76.93 | step: 25.69 + 15%|█▍ | 1293/8720 [3:24:18<14:03:55, 6.82s/it] {'loss': 0.7127, 'grad_norm': 9.322830200195312, 'learning_rate': 9.637833909039574e-06, 'epoch': 1.48} + 15%|█▍ | 1293/8720 [3:24:18<14:03:55, 6.82s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 319 +[2025-05-02 01:39:45,342] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 80.51 | bwd_microstep: 118.72 | bwd_inner_microstep: 118.52 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1390 +[2025-05-02 01:39:45,708] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.43 | bwd_microstep: 209.05 | bwd_inner_microstep: 208.95 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1897 +[2025-05-02 01:39:46,187] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.51 | bwd_microstep: 275.28 | bwd_inner_microstep: 275.26 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 359 +[2025-05-02 01:39:46,392] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 74.96 | bwd_microstep: 117.31 | bwd_inner_microstep: 116.99 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.09 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 874 +[2025-05-02 01:39:46,638] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 97.49 | bwd_microstep: 134.98 | bwd_inner_microstep: 134.93 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-02 01:39:47,115] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.62 | bwd_microstep: 273.67 | bwd_inner_microstep: 273.65 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1887 +[2025-05-02 01:39:47,594] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.46 | bwd_microstep: 274.68 | bwd_inner_microstep: 274.67 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-02 01:39:48,072] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.74 | bwd_microstep: 273.11 | bwd_inner_microstep: 273.09 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 837 +[2025-05-02 01:39:48,304] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 92.30 | bwd_microstep: 126.08 | bwd_inner_microstep: 126.07 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:39:48,779] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.65 | bwd_microstep: 272.52 | bwd_inner_microstep: 272.51 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:39:49,253] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.74 | bwd_microstep: 271.17 | bwd_inner_microstep: 271.15 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:39:49,730] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.41 | bwd_microstep: 272.65 | bwd_inner_microstep: 272.63 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:39:50,207] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.43 | bwd_microstep: 272.51 | bwd_inner_microstep: 272.49 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:39:50,681] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.51 | bwd_microstep: 271.21 | bwd_inner_microstep: 271.19 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 01:39:51,154] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.45 | bwd_microstep: 271.20 | bwd_inner_microstep: 271.18 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:39:51,722] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.19 | optimizer_step: 16.78 +[2025-05-02 01:39:51,722] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.79 | bwd_microstep: 340.07 | bwd_inner_microstep: 271.74 | bwd_allreduce_microstep: 68.29 | step_microstep: 23.91 +[2025-05-02 01:39:51,724] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2556.72 | bwd: 3774.30 | bwd_inner: 3705.17 | bwd_allreduce: 68.61 | step: 24.91 + 15%|█▍ | 1294/8720 [3:24:25<13:55:42, 6.75s/it] {'loss': 0.5037, 'grad_norm': 12.537710189819336, 'learning_rate': 9.63713964292695e-06, 'epoch': 1.48} + 15%|█▍ | 1294/8720 [3:24:25<13:55:42, 6.75s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:39:52,201] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.75 | bwd_microstep: 270.45 | bwd_inner_microstep: 270.44 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.06 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 488 +[2025-05-02 01:39:52,403] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 69.39 | bwd_microstep: 118.98 | bwd_inner_microstep: 118.80 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1927 +[2025-05-02 01:39:52,900] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 193.88 | bwd_microstep: 287.26 | bwd_inner_microstep: 287.24 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1896 +[2025-05-02 01:39:53,379] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.37 | bwd_microstep: 274.88 | bwd_inner_microstep: 274.86 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1890 +[2025-05-02 01:39:53,859] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.55 | bwd_microstep: 274.52 | bwd_inner_microstep: 274.50 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-02 01:39:54,337] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.70 | bwd_microstep: 273.75 | bwd_inner_microstep: 273.73 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 852 +[2025-05-02 01:39:54,585] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 98.53 | bwd_microstep: 132.75 | bwd_inner_microstep: 132.43 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-02 01:39:55,069] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.23 | bwd_microstep: 274.39 | bwd_inner_microstep: 274.37 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 01:39:55,550] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.17 | bwd_microstep: 273.45 | bwd_inner_microstep: 273.44 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1352 +[2025-05-02 01:39:55,914] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.36 | bwd_microstep: 206.07 | bwd_inner_microstep: 206.04 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:39:56,392] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.06 | bwd_microstep: 272.25 | bwd_inner_microstep: 272.23 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 836 +[2025-05-02 01:39:56,628] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.87 | bwd_microstep: 125.87 | bwd_inner_microstep: 125.68 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:39:57,105] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.24 | bwd_microstep: 272.10 | bwd_inner_microstep: 272.08 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:39:57,583] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.73 | bwd_microstep: 270.98 | bwd_inner_microstep: 270.97 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.14 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 01:39:58,059] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.49 | bwd_microstep: 270.62 | bwd_inner_microstep: 270.60 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.15 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1340 +[2025-05-02 01:39:58,523] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.24 | optimizer_step: 16.88 +[2025-05-02 01:39:58,523] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 139.50 | bwd_microstep: 282.24 | bwd_inner_microstep: 204.69 | bwd_allreduce_microstep: 77.37 | step_microstep: 24.81 +[2025-05-02 01:39:58,525] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2619.47 | bwd: 3880.65 | bwd_inner: 3802.29 | bwd_allreduce: 77.69 | step: 26.06 + 15%|█▍ | 1295/8720 [3:24:32<13:57:29, 6.77s/it] {'loss': 0.8091, 'grad_norm': 9.057734489440918, 'learning_rate': 9.636444737058052e-06, 'epoch': 1.48} + 15%|█▍ | 1295/8720 [3:24:32<13:57:29, 6.77s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1944 +[2025-05-02 01:39:59,032] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 196.58 | bwd_microstep: 288.08 | bwd_inner_microstep: 288.06 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1130 +[2025-05-02 01:39:59,332] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 119.19 | bwd_microstep: 163.56 | bwd_inner_microstep: 163.54 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 350 +[2025-05-02 01:39:59,539] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 72.35 | bwd_microstep: 120.83 | bwd_inner_microstep: 120.69 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-02 01:40:00,016] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.83 | bwd_microstep: 274.06 | bwd_inner_microstep: 274.04 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 01:40:00,493] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.56 | bwd_microstep: 272.98 | bwd_inner_microstep: 272.96 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 01:40:00,971] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.70 | bwd_microstep: 272.98 | bwd_inner_microstep: 272.96 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 331 +[2025-05-02 01:40:01,173] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 69.45 | bwd_microstep: 119.55 | bwd_inner_microstep: 119.21 | bwd_allreduce_microstep: 0.14 | step_microstep: 0.12 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1116 +[2025-05-02 01:40:01,466] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 115.43 | bwd_microstep: 162.21 | bwd_inner_microstep: 162.19 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 01:40:01,942] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.28 | bwd_microstep: 272.95 | bwd_inner_microstep: 272.93 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 01:40:02,419] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.32 | bwd_microstep: 272.99 | bwd_inner_microstep: 272.97 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 01:40:02,896] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.19 | bwd_microstep: 272.51 | bwd_inner_microstep: 272.50 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:40:03,372] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.42 | bwd_microstep: 272.18 | bwd_inner_microstep: 272.17 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:40:03,849] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.40 | bwd_microstep: 272.44 | bwd_inner_microstep: 272.42 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 01:40:04,327] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.78 | bwd_microstep: 272.34 | bwd_inner_microstep: 272.32 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 01:40:04,806] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.31 | bwd_microstep: 271.33 | bwd_inner_microstep: 271.31 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:40:05,386] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.15 | optimizer_step: 16.69 +[2025-05-02 01:40:05,386] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.83 | bwd_microstep: 347.84 | bwd_inner_microstep: 271.60 | bwd_allreduce_microstep: 76.19 | step_microstep: 24.47 +[2025-05-02 01:40:05,388] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2645.33 | bwd: 3928.87 | bwd_inner: 3851.96 | bwd_allreduce: 76.46 | step: 25.45 + 15%|█▍ | 1296/8720 [3:24:39<14:00:54, 6.80s/it] {'loss': 1.0715, 'grad_norm': 12.880520820617676, 'learning_rate': 9.635749191528753e-06, 'epoch': 1.49} + 15%|█▍ | 1296/8720 [3:24:39<14:00:54, 6.80s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 01:40:05,868] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.71 | bwd_microstep: 270.22 | bwd_inner_microstep: 270.20 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.14 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1962 +[2025-05-02 01:40:06,372] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 198.37 | bwd_microstep: 290.21 | bwd_inner_microstep: 290.19 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1435 +[2025-05-02 01:40:06,748] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 146.77 | bwd_microstep: 214.60 | bwd_inner_microstep: 214.58 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1904 +[2025-05-02 01:40:07,230] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.29 | bwd_microstep: 275.75 | bwd_inner_microstep: 275.74 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1894 +[2025-05-02 01:40:07,710] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.76 | bwd_microstep: 275.09 | bwd_inner_microstep: 275.08 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 344 +[2025-05-02 01:40:07,909] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 67.95 | bwd_microstep: 118.00 | bwd_inner_microstep: 117.86 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-02 01:40:08,387] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.77 | bwd_microstep: 273.68 | bwd_inner_microstep: 273.67 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-02 01:40:08,864] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.95 | bwd_microstep: 273.65 | bwd_inner_microstep: 273.63 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-02 01:40:09,342] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.19 | bwd_microstep: 273.40 | bwd_inner_microstep: 273.38 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 01:40:09,821] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.49 | bwd_microstep: 272.84 | bwd_inner_microstep: 272.82 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 01:40:10,297] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.12 | bwd_microstep: 273.33 | bwd_inner_microstep: 273.31 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 01:40:10,772] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.65 | bwd_microstep: 272.01 | bwd_inner_microstep: 271.99 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:40:11,247] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.24 | bwd_microstep: 272.57 | bwd_inner_microstep: 272.55 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:40:11,723] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.70 | bwd_microstep: 272.27 | bwd_inner_microstep: 272.26 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:40:12,197] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.84 | bwd_microstep: 271.16 | bwd_inner_microstep: 271.14 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:40:12,760] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.04 | optimizer_gradients: 2.18 | optimizer_step: 16.71 +[2025-05-02 01:40:12,761] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.59 | bwd_microstep: 337.65 | bwd_inner_microstep: 271.43 | bwd_allreduce_microstep: 66.17 | step_microstep: 23.76 +[2025-05-02 01:40:12,762] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2864.13 | bwd: 4236.45 | bwd_inner: 4169.85 | bwd_allreduce: 66.31 | step: 24.56 + 15%|█▍ | 1297/8720 [3:24:46<14:22:10, 6.97s/it] {'loss': 0.8644, 'grad_norm': 22.43410301208496, 'learning_rate': 9.635053006435011e-06, 'epoch': 1.49} + 15%|█▍ | 1297/8720 [3:24:46<14:22:10, 6.97s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 317 +[2025-05-02 01:40:12,988] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 67.28 | bwd_microstep: 141.63 | bwd_inner_microstep: 141.45 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1962 +[2025-05-02 01:40:13,490] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 196.57 | bwd_microstep: 290.21 | bwd_inner_microstep: 290.20 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1899 +[2025-05-02 01:40:13,971] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.55 | bwd_microstep: 275.21 | bwd_inner_microstep: 275.19 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1396 +[2025-05-02 01:40:14,339] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 144.25 | bwd_microstep: 209.20 | bwd_inner_microstep: 209.08 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 01:40:14,814] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.72 | bwd_microstep: 272.59 | bwd_inner_microstep: 272.57 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 848 +[2025-05-02 01:40:15,054] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.61 | bwd_microstep: 132.93 | bwd_inner_microstep: 132.68 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 845 +[2025-05-02 01:40:15,293] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 92.74 | bwd_microstep: 132.60 | bwd_inner_microstep: 132.38 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.09 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 329 +[2025-05-02 01:40:15,500] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 74.76 | bwd_microstep: 118.73 | bwd_inner_microstep: 118.50 | bwd_allreduce_microstep: 0.09 | step_microstep: 0.09 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 845 +[2025-05-02 01:40:15,740] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.09 | bwd_microstep: 132.79 | bwd_inner_microstep: 132.66 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 01:40:16,216] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.04 | bwd_microstep: 273.10 | bwd_inner_microstep: 273.09 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-02 01:40:16,692] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.80 | bwd_microstep: 273.77 | bwd_inner_microstep: 273.75 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 01:40:17,168] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.49 | bwd_microstep: 272.55 | bwd_inner_microstep: 272.53 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 838 +[2025-05-02 01:40:17,404] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.23 | bwd_microstep: 126.74 | bwd_inner_microstep: 126.53 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:40:17,882] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.00 | bwd_microstep: 272.63 | bwd_inner_microstep: 272.61 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 01:40:18,359] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.71 | bwd_microstep: 271.35 | bwd_inner_microstep: 271.34 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 01:40:18,945] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.16 | optimizer_step: 16.73 +[2025-05-02 01:40:18,946] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.57 | bwd_microstep: 354.10 | bwd_inner_microstep: 271.46 | bwd_allreduce_microstep: 82.59 | step_microstep: 24.34 +[2025-05-02 01:40:18,947] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2363.14 | bwd: 3550.25 | bwd_inner: 3466.15 | bwd_allreduce: 83.22 | step: 25.33 + 15%|█▍ | 1298/8720 [3:24:52<13:53:02, 6.73s/it] {'loss': 0.6703, 'grad_norm': 9.325450897216797, 'learning_rate': 9.634356181872877e-06, 'epoch': 1.49} + 15%|█▍ | 1298/8720 [3:24:52<13:53:02, 6.73s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 01:40:19,427] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.51 | bwd_microstep: 270.22 | bwd_inner_microstep: 270.20 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1940 +[2025-05-02 01:40:19,929] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.87 | bwd_microstep: 288.71 | bwd_inner_microstep: 288.69 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 01:40:20,412] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.22 | bwd_microstep: 273.11 | bwd_inner_microstep: 273.09 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 01:40:20,890] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.06 | bwd_microstep: 272.74 | bwd_inner_microstep: 272.72 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 01:40:21,368] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.94 | bwd_microstep: 272.87 | bwd_inner_microstep: 272.85 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 01:40:21,848] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.87 | bwd_microstep: 272.65 | bwd_inner_microstep: 272.63 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 843 +[2025-05-02 01:40:22,093] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.20 | bwd_microstep: 131.90 | bwd_inner_microstep: 131.72 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 01:40:22,571] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.98 | bwd_microstep: 272.62 | bwd_inner_microstep: 272.60 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:40:23,053] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.08 | bwd_microstep: 272.51 | bwd_inner_microstep: 272.49 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:40:23,532] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.05 | bwd_microstep: 272.12 | bwd_inner_microstep: 272.11 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 01:40:24,015] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.18 | bwd_microstep: 272.45 | bwd_inner_microstep: 272.44 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 322 +[2025-05-02 01:40:24,244] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 89.47 | bwd_microstep: 120.99 | bwd_inner_microstep: 120.75 | bwd_allreduce_microstep: 0.09 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:40:24,721] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.95 | bwd_microstep: 271.46 | bwd_inner_microstep: 271.44 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:40:25,201] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.90 | bwd_microstep: 271.24 | bwd_inner_microstep: 271.23 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1342 +[2025-05-02 01:40:25,566] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.05 | bwd_microstep: 204.60 | bwd_inner_microstep: 204.46 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:40:26,132] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.19 | optimizer_step: 16.68 +[2025-05-02 01:40:26,132] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.48 | bwd_microstep: 338.28 | bwd_inner_microstep: 271.72 | bwd_allreduce_microstep: 66.51 | step_microstep: 23.67 +[2025-05-02 01:40:26,133] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2777.42 | bwd: 4078.53 | bwd_inner: 4011.21 | bwd_allreduce: 66.86 | step: 24.60 + 15%|█▍ | 1299/8720 [3:24:59<14:09:37, 6.87s/it] {'loss': 0.5332, 'grad_norm': 10.357630729675293, 'learning_rate': 9.633658717938486e-06, 'epoch': 1.49} + 15%|█▍ | 1299/8720 [3:24:59<14:09:37, 6.87s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:40:26,611] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.74 | bwd_microstep: 270.48 | bwd_inner_microstep: 270.47 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1905 +[2025-05-02 01:40:27,091] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.85 | bwd_microstep: 275.91 | bwd_inner_microstep: 275.89 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1894 +[2025-05-02 01:40:27,570] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.24 | bwd_microstep: 274.90 | bwd_inner_microstep: 274.88 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-02 01:40:28,047] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.49 | bwd_microstep: 273.55 | bwd_inner_microstep: 273.53 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 01:40:28,523] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.40 | bwd_microstep: 273.56 | bwd_inner_microstep: 273.54 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:40:29,000] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.87 | bwd_microstep: 272.67 | bwd_inner_microstep: 272.65 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 01:40:29,477] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.31 | bwd_microstep: 273.07 | bwd_inner_microstep: 273.05 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:40:29,953] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.24 | bwd_microstep: 272.61 | bwd_inner_microstep: 272.60 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 01:40:30,428] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.87 | bwd_microstep: 272.09 | bwd_inner_microstep: 272.07 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:40:30,904] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.37 | bwd_microstep: 272.40 | bwd_inner_microstep: 272.38 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 832 +[2025-05-02 01:40:31,142] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.46 | bwd_microstep: 130.21 | bwd_inner_microstep: 129.93 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:40:31,617] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.44 | bwd_microstep: 271.61 | bwd_inner_microstep: 271.59 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:40:32,093] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.61 | bwd_microstep: 272.27 | bwd_inner_microstep: 272.25 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 320 +[2025-05-02 01:40:32,307] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 81.25 | bwd_microstep: 117.11 | bwd_inner_microstep: 116.97 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:40:32,783] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.04 | bwd_microstep: 271.06 | bwd_inner_microstep: 271.05 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:40:33,359] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.17 | optimizer_step: 16.71 +[2025-05-02 01:40:33,359] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.83 | bwd_microstep: 347.85 | bwd_inner_microstep: 271.90 | bwd_allreduce_microstep: 75.90 | step_microstep: 23.79 +[2025-05-02 01:40:33,360] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2811.75 | bwd: 4141.39 | bwd_inner: 4064.80 | bwd_allreduce: 76.15 | step: 24.57 + 15%|█▍ | 1300/8720 [3:25:07<14:22:47, 6.98s/it] {'loss': 0.5309, 'grad_norm': 10.994900703430176, 'learning_rate': 9.632960614728059e-06, 'epoch': 1.49} + 15%|█▍ | 1300/8720 [3:25:07<14:22:47, 6.98s/it][INFO|trainer.py:3503] 2025-05-02 01:40:35,814 >> Saving model checkpoint to work_dirs/internvl_chat_v2_5/ak/checkpoint-1300 +[INFO|configuration_utils.py:472] 2025-05-02 01:40:35,817 >> Configuration saved in work_dirs/internvl_chat_v2_5/ak/checkpoint-1300/config.json +[INFO|configuration_utils.py:807] 2025-05-02 01:40:35,818 >> Configuration saved in work_dirs/internvl_chat_v2_5/ak/checkpoint-1300/generation_config.json +[INFO|modeling_utils.py:2755] 2025-05-02 01:40:40,881 >> Model weights saved in work_dirs/internvl_chat_v2_5/ak/checkpoint-1300/model.safetensors +[INFO|tokenization_utils_base.py:2702] 2025-05-02 01:40:40,883 >> tokenizer config file saved in work_dirs/internvl_chat_v2_5/ak/checkpoint-1300/tokenizer_config.json +[INFO|tokenization_utils_base.py:2711] 2025-05-02 01:40:40,883 >> Special tokens file saved in work_dirs/internvl_chat_v2_5/ak/checkpoint-1300/special_tokens_map.json +[INFO|tokenization_utils_base.py:2762] 2025-05-02 01:40:40,883 >> added tokens file saved in work_dirs/internvl_chat_v2_5/ak/checkpoint-1300/added_tokens.json +[2025-05-02 01:40:40,994] [INFO] [logging.py:96:log_dist] [Rank 0] [Torch] Checkpoint global_step1300 is about to be saved! +[2025-05-02 01:40:41,011] [INFO] [logging.py:96:log_dist] [Rank 0] Saving model checkpoint: work_dirs/internvl_chat_v2_5/ak/checkpoint-1300/global_step1300/mp_rank_00_model_states.pt +[2025-05-02 01:40:41,011] [INFO] [torch_checkpoint_engine.py:21:save] [Torch] Saving work_dirs/internvl_chat_v2_5/ak/checkpoint-1300/global_step1300/mp_rank_00_model_states.pt... +[2025-05-02 01:40:45,451] [INFO] [torch_checkpoint_engine.py:23:save] [Torch] Saved work_dirs/internvl_chat_v2_5/ak/checkpoint-1300/global_step1300/mp_rank_00_model_states.pt. +[2025-05-02 01:40:45,452] [INFO] [torch_checkpoint_engine.py:21:save] [Torch] Saving work_dirs/internvl_chat_v2_5/ak/checkpoint-1300/global_step1300/bf16_zero_pp_rank_0_mp_rank_00_optim_states.pt... +[2025-05-02 01:40:45,651] [INFO] [torch_checkpoint_engine.py:23:save] [Torch] Saved work_dirs/internvl_chat_v2_5/ak/checkpoint-1300/global_step1300/bf16_zero_pp_rank_0_mp_rank_00_optim_states.pt. +[2025-05-02 01:40:45,651] [INFO] [engine.py:3536:_save_zero_checkpoint] zero checkpoint saved work_dirs/internvl_chat_v2_5/ak/checkpoint-1300/global_step1300/bf16_zero_pp_rank_0_mp_rank_00_optim_states.pt +[2025-05-02 01:40:45,651] [INFO] [torch_checkpoint_engine.py:33:commit] [Torch] Checkpoint global_step1300 is ready now! +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 828 +[2025-05-02 01:40:45,909] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 92.53 | bwd_microstep: 128.36 | bwd_inner_microstep: 128.23 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.09 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1448 +[2025-05-02 01:40:46,281] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 144.70 | bwd_microstep: 213.63 | bwd_inner_microstep: 213.60 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 01:40:46,753] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.47 | bwd_microstep: 270.81 | bwd_inner_microstep: 270.80 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-02 01:40:47,228] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.52 | bwd_microstep: 271.89 | bwd_inner_microstep: 271.87 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1886 +[2025-05-02 01:40:47,701] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.66 | bwd_microstep: 271.94 | bwd_inner_microstep: 271.92 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-02 01:40:48,175] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.85 | bwd_microstep: 271.24 | bwd_inner_microstep: 271.22 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-02 01:40:48,650] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.74 | bwd_microstep: 271.61 | bwd_inner_microstep: 271.60 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.15 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1358 +[2025-05-02 01:40:49,010] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 139.16 | bwd_microstep: 204.78 | bwd_inner_microstep: 204.71 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:40:49,486] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.76 | bwd_microstep: 270.95 | bwd_inner_microstep: 270.93 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 01:40:49,964] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.88 | bwd_microstep: 271.44 | bwd_inner_microstep: 271.43 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:40:50,439] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.42 | bwd_microstep: 270.91 | bwd_inner_microstep: 270.90 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 01:40:50,915] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.98 | bwd_microstep: 271.69 | bwd_inner_microstep: 271.68 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 840 +[2025-05-02 01:40:51,153] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.52 | bwd_microstep: 125.16 | bwd_inner_microstep: 124.98 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:40:51,628] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.29 | bwd_microstep: 270.10 | bwd_inner_microstep: 270.08 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:40:52,102] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.50 | bwd_microstep: 270.80 | bwd_inner_microstep: 270.79 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:40:52,664] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.20 | optimizer_step: 16.70 +[2025-05-02 01:40:52,665] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 185.46 | bwd_microstep: 337.28 | bwd_inner_microstep: 270.22 | bwd_allreduce_microstep: 67.01 | step_microstep: 23.87 +[2025-05-02 01:40:52,666] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2714.14 | bwd: 3992.70 | bwd_inner: 3924.98 | bwd_allreduce: 67.22 | step: 25.01 + 15%|█▍ | 1301/8720 [3:25:26<22:00:00, 10.68s/it] {'loss': 0.7871, 'grad_norm': 8.83453369140625, 'learning_rate': 9.632261872337915e-06, 'epoch': 1.49} + 15%|█▍ | 1301/8720 [3:25:26<22:00:00, 10.68s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:40:53,142] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.23 | bwd_microstep: 269.55 | bwd_inner_microstep: 269.54 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2141 +[2025-05-02 01:40:53,673] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 203.12 | bwd_microstep: 313.06 | bwd_inner_microstep: 313.04 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1900 +[2025-05-02 01:40:54,151] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.34 | bwd_microstep: 274.32 | bwd_inner_microstep: 274.30 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 01:40:54,625] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.43 | bwd_microstep: 271.93 | bwd_inner_microstep: 271.91 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-02 01:40:55,099] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.60 | bwd_microstep: 272.05 | bwd_inner_microstep: 272.03 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.14 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 01:40:55,574] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.41 | bwd_microstep: 271.28 | bwd_inner_microstep: 271.26 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 01:40:56,049] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.62 | bwd_microstep: 271.55 | bwd_inner_microstep: 271.53 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 328 +[2025-05-02 01:40:56,259] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 79.23 | bwd_microstep: 117.38 | bwd_inner_microstep: 117.25 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 333 +[2025-05-02 01:40:56,462] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 69.08 | bwd_microstep: 120.68 | bwd_inner_microstep: 120.55 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 01:40:56,935] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.34 | bwd_microstep: 271.54 | bwd_inner_microstep: 271.52 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:40:57,412] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.88 | bwd_microstep: 271.72 | bwd_inner_microstep: 271.71 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1089 +[2025-05-02 01:40:57,702] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 114.95 | bwd_microstep: 159.95 | bwd_inner_microstep: 159.79 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:40:58,175] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.51 | bwd_microstep: 270.41 | bwd_inner_microstep: 270.39 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:40:58,648] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.12 | bwd_microstep: 270.57 | bwd_inner_microstep: 270.55 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1086 +[2025-05-02 01:40:58,936] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 114.37 | bwd_microstep: 159.18 | bwd_inner_microstep: 158.98 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1893 +[2025-05-02 01:40:59,505] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.21 | optimizer_step: 16.76 +[2025-05-02 01:40:59,506] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.71 | bwd_microstep: 341.24 | bwd_inner_microstep: 274.34 | bwd_allreduce_microstep: 66.85 | step_microstep: 24.07 +[2025-05-02 01:40:59,507] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2639.66 | bwd: 3926.50 | bwd_inner: 3858.74 | bwd_allreduce: 67.28 | step: 25.15 + 15%|█▍ | 1302/8720 [3:25:33<19:37:36, 9.53s/it] {'loss': 1.0431, 'grad_norm': 11.796008110046387, 'learning_rate': 9.631562490864453e-06, 'epoch': 1.49} + 15%|█▍ | 1302/8720 [3:25:33<19:37:36, 9.53s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 345 +[2025-05-02 01:40:59,715] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 69.74 | bwd_microstep: 119.99 | bwd_inner_microstep: 119.75 | bwd_allreduce_microstep: 0.09 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1994 +[2025-05-02 01:41:00,220] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 196.89 | bwd_microstep: 291.99 | bwd_inner_microstep: 291.97 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1941 +[2025-05-02 01:41:00,716] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 193.90 | bwd_microstep: 286.94 | bwd_inner_microstep: 286.92 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1930 +[2025-05-02 01:41:01,212] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 193.48 | bwd_microstep: 286.05 | bwd_inner_microstep: 286.03 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1891 +[2025-05-02 01:41:01,689] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.24 | bwd_microstep: 273.35 | bwd_inner_microstep: 273.33 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-02 01:41:02,165] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.50 | bwd_microstep: 272.08 | bwd_inner_microstep: 272.06 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1366 +[2025-05-02 01:41:02,528] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.36 | bwd_microstep: 206.08 | bwd_inner_microstep: 206.05 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 01:41:03,007] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.96 | bwd_microstep: 271.86 | bwd_inner_microstep: 271.84 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-02 01:41:03,485] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.85 | bwd_microstep: 272.21 | bwd_inner_microstep: 272.19 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 01:41:03,964] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.05 | bwd_microstep: 271.48 | bwd_inner_microstep: 271.46 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 01:41:04,441] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.59 | bwd_microstep: 271.53 | bwd_inner_microstep: 271.51 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:41:04,919] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.84 | bwd_microstep: 271.47 | bwd_inner_microstep: 271.45 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:41:05,401] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.17 | bwd_microstep: 271.12 | bwd_inner_microstep: 271.11 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:41:05,877] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.78 | bwd_microstep: 271.07 | bwd_inner_microstep: 271.05 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:41:06,352] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.52 | bwd_microstep: 270.72 | bwd_inner_microstep: 270.70 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:41:06,930] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.21 | optimizer_step: 16.76 +[2025-05-02 01:41:06,930] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.44 | bwd_microstep: 346.62 | bwd_inner_microstep: 270.33 | bwd_allreduce_microstep: 76.24 | step_microstep: 24.69 +[2025-05-02 01:41:06,932] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2854.96 | bwd: 4254.60 | bwd_inner: 4177.84 | bwd_allreduce: 76.39 | step: 25.56 + 15%|█▍ | 1303/8720 [3:25:40<18:19:38, 8.90s/it] {'loss': 0.9404, 'grad_norm': 6.733796119689941, 'learning_rate': 9.630862470404161e-06, 'epoch': 1.49} + 15%|█▍ | 1303/8720 [3:25:40<18:19:38, 8.90s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:41:07,413] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.63 | bwd_microstep: 270.82 | bwd_inner_microstep: 270.80 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-02 01:41:07,893] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.90 | bwd_microstep: 273.36 | bwd_inner_microstep: 273.34 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1883 +[2025-05-02 01:41:08,370] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.99 | bwd_microstep: 273.64 | bwd_inner_microstep: 273.63 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 01:41:08,847] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.84 | bwd_microstep: 272.52 | bwd_inner_microstep: 272.50 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 01:41:09,325] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.05 | bwd_microstep: 273.06 | bwd_inner_microstep: 273.04 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-02 01:41:09,806] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.31 | bwd_microstep: 273.21 | bwd_inner_microstep: 273.20 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 01:41:10,289] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.12 | bwd_microstep: 272.80 | bwd_inner_microstep: 272.78 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 01:41:10,769] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.11 | bwd_microstep: 272.54 | bwd_inner_microstep: 272.52 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 846 +[2025-05-02 01:41:11,016] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 96.39 | bwd_microstep: 131.60 | bwd_inner_microstep: 131.49 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:41:11,493] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.54 | bwd_microstep: 271.76 | bwd_inner_microstep: 271.74 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 01:41:11,972] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.25 | bwd_microstep: 272.13 | bwd_inner_microstep: 272.11 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:41:12,447] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.18 | bwd_microstep: 270.70 | bwd_inner_microstep: 270.69 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 01:41:12,925] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.71 | bwd_microstep: 272.12 | bwd_inner_microstep: 272.11 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:41:13,402] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.52 | bwd_microstep: 272.09 | bwd_inner_microstep: 272.08 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:41:13,875] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.52 | bwd_microstep: 270.50 | bwd_inner_microstep: 270.48 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 01:41:14,438] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.19 | optimizer_step: 16.79 +[2025-05-02 01:41:14,439] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.50 | bwd_microstep: 337.61 | bwd_inner_microstep: 270.85 | bwd_allreduce_microstep: 66.71 | step_microstep: 24.10 +[2025-05-02 01:41:14,440] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2920.22 | bwd: 4280.49 | bwd_inner: 4213.35 | bwd_allreduce: 66.85 | step: 24.98 + 15%|█▍ | 1304/8720 [3:25:48<17:27:59, 8.48s/it] {'loss': 0.4593, 'grad_norm': 9.825555801391602, 'learning_rate': 9.630161811053615e-06, 'epoch': 1.5} + 15%|█▍ | 1304/8720 [3:25:48<17:27:59, 8.48s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1909 +[2025-05-02 01:41:14,925] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.67 | bwd_microstep: 274.81 | bwd_inner_microstep: 274.79 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-02 01:41:15,402] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.41 | bwd_microstep: 273.09 | bwd_inner_microstep: 273.07 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-02 01:41:15,879] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.75 | bwd_microstep: 272.93 | bwd_inner_microstep: 272.92 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 346 +[2025-05-02 01:41:16,098] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 79.84 | bwd_microstep: 124.08 | bwd_inner_microstep: 123.77 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-02 01:41:16,574] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.84 | bwd_microstep: 272.57 | bwd_inner_microstep: 272.55 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1105 +[2025-05-02 01:41:16,865] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 115.04 | bwd_microstep: 161.50 | bwd_inner_microstep: 161.43 | bwd_allreduce_microstep: 0.03 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 01:41:17,341] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.46 | bwd_microstep: 272.58 | bwd_inner_microstep: 272.56 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 847 +[2025-05-02 01:41:17,583] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.53 | bwd_microstep: 132.27 | bwd_inner_microstep: 132.25 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 01:41:18,060] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.46 | bwd_microstep: 272.66 | bwd_inner_microstep: 272.64 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 01:41:18,536] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.88 | bwd_microstep: 273.00 | bwd_inner_microstep: 272.98 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 330 +[2025-05-02 01:41:18,742] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 71.00 | bwd_microstep: 121.12 | bwd_inner_microstep: 121.00 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:41:19,217] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.61 | bwd_microstep: 272.02 | bwd_inner_microstep: 272.01 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 01:41:19,693] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.07 | bwd_microstep: 272.42 | bwd_inner_microstep: 272.40 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 01:41:20,169] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.21 | bwd_microstep: 272.18 | bwd_inner_microstep: 272.16 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 321 +[2025-05-02 01:41:20,381] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 79.33 | bwd_microstep: 119.24 | bwd_inner_microstep: 119.06 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 01:41:20,946] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.27 | optimizer_step: 16.93 +[2025-05-02 01:41:20,946] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.96 | bwd_microstep: 338.99 | bwd_inner_microstep: 271.24 | bwd_allreduce_microstep: 67.71 | step_microstep: 24.27 +[2025-05-02 01:41:20,948] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2508.78 | bwd: 3725.51 | bwd_inner: 3656.98 | bwd_allreduce: 68.04 | step: 25.21 + 15%|█▍ | 1305/8720 [3:25:54<16:14:45, 7.89s/it] {'loss': 0.6307, 'grad_norm': 5.531989097595215, 'learning_rate': 9.629460512909484e-06, 'epoch': 1.5} + 15%|█▍ | 1305/8720 [3:25:54<16:14:45, 7.89s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:41:21,425] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.20 | bwd_microstep: 269.81 | bwd_inner_microstep: 269.79 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1909 +[2025-05-02 01:41:21,906] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.06 | bwd_microstep: 276.05 | bwd_inner_microstep: 276.03 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1125 +[2025-05-02 01:41:22,200] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 116.46 | bwd_microstep: 163.06 | bwd_inner_microstep: 163.00 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1889 +[2025-05-02 01:41:22,678] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.21 | bwd_microstep: 274.75 | bwd_inner_microstep: 274.73 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1371 +[2025-05-02 01:41:23,042] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 142.56 | bwd_microstep: 206.98 | bwd_inner_microstep: 206.96 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 01:41:23,518] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.12 | bwd_microstep: 272.39 | bwd_inner_microstep: 272.37 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 01:41:23,995] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.42 | bwd_microstep: 273.07 | bwd_inner_microstep: 273.05 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 01:41:24,472] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.98 | bwd_microstep: 273.28 | bwd_inner_microstep: 273.26 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:41:24,948] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.45 | bwd_microstep: 272.44 | bwd_inner_microstep: 272.42 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 01:41:25,426] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.03 | bwd_microstep: 273.46 | bwd_inner_microstep: 273.44 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:41:25,904] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.91 | bwd_microstep: 272.85 | bwd_inner_microstep: 272.83 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:41:26,384] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.10 | bwd_microstep: 272.71 | bwd_inner_microstep: 272.69 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 01:41:26,866] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.62 | bwd_microstep: 272.22 | bwd_inner_microstep: 272.20 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:41:27,348] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.23 | bwd_microstep: 272.34 | bwd_inner_microstep: 272.32 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.10 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 834 +[2025-05-02 01:41:27,592] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 98.02 | bwd_microstep: 126.07 | bwd_inner_microstep: 125.84 | bwd_allreduce_microstep: 0.10 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:41:28,193] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.17 | optimizer_step: 22.16 +[2025-05-02 01:41:28,194] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.53 | bwd_microstep: 359.27 | bwd_inner_microstep: 272.19 | bwd_allreduce_microstep: 87.03 | step_microstep: 30.80 +[2025-05-02 01:41:28,195] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2807.57 | bwd: 4130.76 | bwd_inner: 4043.16 | bwd_allreduce: 87.22 | step: 31.68 + 15%|█▍ | 1306/8720 [3:26:01<15:50:54, 7.70s/it] {'loss': 1.0887, 'grad_norm': 10.051407814025879, 'learning_rate': 9.628758576068519e-06, 'epoch': 1.5} + 15%|█▍ | 1306/8720 [3:26:01<15:50:54, 7.70s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 01:41:28,674] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.04 | bwd_microstep: 270.29 | bwd_inner_microstep: 270.27 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 422 +[2025-05-02 01:41:28,886] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 84.72 | bwd_microstep: 114.92 | bwd_inner_microstep: 114.78 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1925 +[2025-05-02 01:41:29,384] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.21 | bwd_microstep: 286.68 | bwd_inner_microstep: 286.66 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1422 +[2025-05-02 01:41:29,759] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 144.32 | bwd_microstep: 213.22 | bwd_inner_microstep: 213.09 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1905 +[2025-05-02 01:41:30,246] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.69 | bwd_microstep: 275.89 | bwd_inner_microstep: 275.88 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1899 +[2025-05-02 01:41:30,729] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.27 | bwd_microstep: 275.11 | bwd_inner_microstep: 275.09 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-02 01:41:31,207] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.60 | bwd_microstep: 273.51 | bwd_inner_microstep: 273.49 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1371 +[2025-05-02 01:41:31,572] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.22 | bwd_microstep: 207.56 | bwd_inner_microstep: 207.45 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-02 01:41:32,052] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.87 | bwd_microstep: 272.95 | bwd_inner_microstep: 272.93 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-02 01:41:32,529] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.27 | bwd_microstep: 273.44 | bwd_inner_microstep: 273.43 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 835 +[2025-05-02 01:41:32,759] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 90.36 | bwd_microstep: 125.87 | bwd_inner_microstep: 125.63 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.08 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1347 +[2025-05-02 01:41:33,118] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.19 | bwd_microstep: 205.48 | bwd_inner_microstep: 205.46 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 01:41:33,594] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.22 | bwd_microstep: 273.13 | bwd_inner_microstep: 273.12 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:41:34,070] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.02 | bwd_microstep: 272.42 | bwd_inner_microstep: 272.40 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1342 +[2025-05-02 01:41:34,430] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 139.52 | bwd_microstep: 204.40 | bwd_inner_microstep: 204.26 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.08 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 316 +[2025-05-02 01:41:34,741] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.15 | optimizer_step: 16.54 +[2025-05-02 01:41:34,741] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 76.09 | bwd_microstep: 198.91 | bwd_inner_microstep: 132.64 | bwd_allreduce_microstep: 66.12 | step_microstep: 23.53 +[2025-05-02 01:41:34,742] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2518.32 | bwd: 3743.88 | bwd_inner: 3676.65 | bwd_allreduce: 66.54 | step: 24.53 + 15%|█▍ | 1307/8720 [3:26:08<15:08:12, 7.35s/it] {'loss': 0.7915, 'grad_norm': 9.363215446472168, 'learning_rate': 9.628056000627561e-06, 'epoch': 1.5} + 15%|█▍ | 1307/8720 [3:26:08<15:08:12, 7.35s/it]dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 897 +[2025-05-02 01:41:35,007] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 102.24 | bwd_microstep: 143.58 | bwd_inner_microstep: 143.28 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1966 +[2025-05-02 01:41:35,507] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.71 | bwd_microstep: 290.40 | bwd_inner_microstep: 290.38 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1898 +[2025-05-02 01:41:35,986] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.88 | bwd_microstep: 275.19 | bwd_inner_microstep: 275.17 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 362 +[2025-05-02 01:41:36,186] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 71.19 | bwd_microstep: 115.09 | bwd_inner_microstep: 114.95 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 01:41:36,661] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.96 | bwd_microstep: 273.22 | bwd_inner_microstep: 273.20 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1363 +[2025-05-02 01:41:37,027] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 143.89 | bwd_microstep: 206.88 | bwd_inner_microstep: 206.78 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-02 01:41:37,503] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.88 | bwd_microstep: 273.04 | bwd_inner_microstep: 273.03 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-02 01:41:37,981] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.91 | bwd_microstep: 273.68 | bwd_inner_microstep: 273.66 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-02 01:41:38,458] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.94 | bwd_microstep: 273.45 | bwd_inner_microstep: 273.43 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:41:38,934] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.33 | bwd_microstep: 272.51 | bwd_inner_microstep: 272.49 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 842 +[2025-05-02 01:41:39,173] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.12 | bwd_microstep: 131.84 | bwd_inner_microstep: 131.78 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:41:39,648] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.66 | bwd_microstep: 272.49 | bwd_inner_microstep: 272.48 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 837 +[2025-05-02 01:41:39,880] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 91.28 | bwd_microstep: 125.90 | bwd_inner_microstep: 125.88 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:41:40,355] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.76 | bwd_microstep: 272.40 | bwd_inner_microstep: 272.38 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:41:40,831] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.23 | bwd_microstep: 272.35 | bwd_inner_microstep: 272.33 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:41:41,401] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.15 | optimizer_step: 20.94 +[2025-05-02 01:41:41,402] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.76 | bwd_microstep: 340.03 | bwd_inner_microstep: 271.57 | bwd_allreduce_microstep: 68.41 | step_microstep: 28.57 +[2025-05-02 01:41:41,403] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2581.46 | bwd: 3812.09 | bwd_inner: 3742.90 | bwd_allreduce: 68.73 | step: 29.44 + 15%|█▌ | 1308/8720 [3:26:15<14:42:30, 7.14s/it] {'loss': 0.6652, 'grad_norm': 9.091567039489746, 'learning_rate': 9.627352786683543e-06, 'epoch': 1.5} + 15%|█▌ | 1308/8720 [3:26:15<14:42:30, 7.14s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:41:41,880] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.98 | bwd_microstep: 270.05 | bwd_inner_microstep: 270.03 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2089 +[2025-05-02 01:41:42,402] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 202.38 | bwd_microstep: 304.64 | bwd_inner_microstep: 304.62 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1902 +[2025-05-02 01:41:42,882] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.36 | bwd_microstep: 275.50 | bwd_inner_microstep: 275.48 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-02 01:41:43,361] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.15 | bwd_microstep: 274.87 | bwd_inner_microstep: 274.85 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 01:41:43,837] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.60 | bwd_microstep: 272.76 | bwd_inner_microstep: 272.74 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 01:41:44,315] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.25 | bwd_microstep: 272.92 | bwd_inner_microstep: 272.90 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 845 +[2025-05-02 01:41:44,556] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.28 | bwd_microstep: 132.27 | bwd_inner_microstep: 132.19 | bwd_allreduce_microstep: 0.04 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:41:45,032] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.45 | bwd_microstep: 272.48 | bwd_inner_microstep: 272.46 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 01:41:45,508] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.85 | bwd_microstep: 272.81 | bwd_inner_microstep: 272.79 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 01:41:45,982] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.29 | bwd_microstep: 272.57 | bwd_inner_microstep: 272.55 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:41:46,458] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.10 | bwd_microstep: 272.28 | bwd_inner_microstep: 272.27 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 321 +[2025-05-02 01:41:46,673] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 78.40 | bwd_microstep: 123.36 | bwd_inner_microstep: 123.04 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 832 +[2025-05-02 01:41:46,912] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.16 | bwd_microstep: 130.36 | bwd_inner_microstep: 130.33 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 01:41:47,390] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.00 | bwd_microstep: 272.36 | bwd_inner_microstep: 272.34 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:41:47,865] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.69 | bwd_microstep: 270.99 | bwd_inner_microstep: 270.97 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 01:41:48,449] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.15 | optimizer_step: 16.34 +[2025-05-02 01:41:48,449] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.55 | bwd_microstep: 354.00 | bwd_inner_microstep: 271.24 | bwd_allreduce_microstep: 82.71 | step_microstep: 24.02 +[2025-05-02 01:41:48,451] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2727.20 | bwd: 4044.25 | bwd_inner: 3960.86 | bwd_allreduce: 82.96 | step: 24.80 + 15%|█▌ | 1309/8720 [3:26:22<14:38:53, 7.12s/it] {'loss': 0.4826, 'grad_norm': 9.303877830505371, 'learning_rate': 9.626648934333482e-06, 'epoch': 1.5} + 15%|█▌ | 1309/8720 [3:26:22<14:38:53, 7.12s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:41:48,932] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.39 | bwd_microstep: 270.43 | bwd_inner_microstep: 270.42 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 419 +[2025-05-02 01:41:49,155] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 88.16 | bwd_microstep: 117.20 | bwd_inner_microstep: 116.93 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1896 +[2025-05-02 01:41:49,637] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.03 | bwd_microstep: 275.04 | bwd_inner_microstep: 275.02 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1894 +[2025-05-02 01:41:50,121] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.58 | bwd_microstep: 274.64 | bwd_inner_microstep: 274.62 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1892 +[2025-05-02 01:41:50,603] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.22 | bwd_microstep: 275.32 | bwd_inner_microstep: 275.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 340 +[2025-05-02 01:41:50,830] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 89.24 | bwd_microstep: 119.15 | bwd_inner_microstep: 118.94 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 01:41:51,309] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.29 | bwd_microstep: 273.21 | bwd_inner_microstep: 273.20 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 01:41:51,789] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.45 | bwd_microstep: 272.86 | bwd_inner_microstep: 272.84 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 01:41:52,269] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.50 | bwd_microstep: 272.62 | bwd_inner_microstep: 272.60 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 01:41:52,749] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.70 | bwd_microstep: 273.00 | bwd_inner_microstep: 272.98 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 01:41:53,232] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.82 | bwd_microstep: 273.03 | bwd_inner_microstep: 273.01 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:41:53,711] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.15 | bwd_microstep: 272.44 | bwd_inner_microstep: 272.42 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:41:54,191] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.49 | bwd_microstep: 272.31 | bwd_inner_microstep: 272.29 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:41:54,668] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.29 | bwd_microstep: 271.21 | bwd_inner_microstep: 271.19 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:41:55,146] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.34 | bwd_microstep: 272.25 | bwd_inner_microstep: 272.24 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 01:41:55,735] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.15 | optimizer_step: 27.17 +[2025-05-02 01:41:55,736] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.69 | bwd_microstep: 348.16 | bwd_inner_microstep: 271.93 | bwd_allreduce_microstep: 76.18 | step_microstep: 34.89 +[2025-05-02 01:41:55,737] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2817.96 | bwd: 4132.91 | bwd_inner: 4056.03 | bwd_allreduce: 76.43 | step: 35.73 + 15%|█▌ | 1310/8720 [3:26:29<14:45:05, 7.17s/it] {'loss': 0.5316, 'grad_norm': 6.1412553787231445, 'learning_rate': 9.62594444367448e-06, 'epoch': 1.5} + 15%|█▌ | 1310/8720 [3:26:29<14:45:05, 7.17s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 316 +[2025-05-02 01:41:55,957] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 78.08 | bwd_microstep: 121.17 | bwd_inner_microstep: 120.97 | bwd_allreduce_microstep: 0.08 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2113 +[2025-05-02 01:41:56,492] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 204.94 | bwd_microstep: 312.76 | bwd_inner_microstep: 312.74 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1962 +[2025-05-02 01:41:56,998] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 197.03 | bwd_microstep: 289.95 | bwd_inner_microstep: 289.93 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 369 +[2025-05-02 01:41:57,245] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.65 | bwd_microstep: 131.94 | bwd_inner_microstep: 131.79 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 01:41:57,724] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.77 | bwd_microstep: 273.90 | bwd_inner_microstep: 273.89 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 345 +[2025-05-02 01:41:57,955] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.78 | bwd_microstep: 116.56 | bwd_inner_microstep: 116.40 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-02 01:41:58,435] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.51 | bwd_microstep: 273.59 | bwd_inner_microstep: 273.57 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1371 +[2025-05-02 01:41:58,801] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 142.20 | bwd_microstep: 207.34 | bwd_inner_microstep: 207.31 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 844 +[2025-05-02 01:41:59,051] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 96.58 | bwd_microstep: 133.67 | bwd_inner_microstep: 133.64 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 01:41:59,534] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.55 | bwd_microstep: 272.65 | bwd_inner_microstep: 272.63 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 01:42:00,013] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.84 | bwd_microstep: 272.78 | bwd_inner_microstep: 272.77 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:42:00,492] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.65 | bwd_microstep: 272.35 | bwd_inner_microstep: 272.34 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 01:42:00,972] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.10 | bwd_microstep: 272.70 | bwd_inner_microstep: 272.68 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:42:01,451] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.32 | bwd_microstep: 271.16 | bwd_inner_microstep: 271.14 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1343 +[2025-05-02 01:42:01,814] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.45 | bwd_microstep: 204.37 | bwd_inner_microstep: 204.35 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.07 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 828 +[2025-05-02 01:42:02,156] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.13 | optimizer_step: 16.35 +[2025-05-02 01:42:02,156] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.57 | bwd_microstep: 206.99 | bwd_inner_microstep: 130.24 | bwd_allreduce_microstep: 76.59 | step_microstep: 24.02 +[2025-05-02 01:42:02,158] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2464.62 | bwd: 3633.98 | bwd_inner: 3556.55 | bwd_allreduce: 76.83 | step: 25.09 + 15%|█▌ | 1311/8720 [3:26:35<14:17:19, 6.94s/it] {'loss': 0.941, 'grad_norm': 6.381507873535156, 'learning_rate': 9.625239314803736e-06, 'epoch': 1.5} + 15%|█▌ | 1311/8720 [3:26:35<14:17:19, 6.94s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 01:42:02,638] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.64 | bwd_microstep: 270.18 | bwd_inner_microstep: 270.16 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1934 +[2025-05-02 01:42:03,138] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.14 | bwd_microstep: 287.58 | bwd_inner_microstep: 287.56 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 884 +[2025-05-02 01:42:03,391] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 100.98 | bwd_microstep: 135.50 | bwd_inner_microstep: 135.28 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-02 01:42:03,868] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.94 | bwd_microstep: 273.48 | bwd_inner_microstep: 273.46 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-02 01:42:04,346] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.95 | bwd_microstep: 273.78 | bwd_inner_microstep: 273.76 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 01:42:04,823] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.53 | bwd_microstep: 273.12 | bwd_inner_microstep: 273.10 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-02 01:42:05,304] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.74 | bwd_microstep: 273.68 | bwd_inner_microstep: 273.66 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 842 +[2025-05-02 01:42:05,546] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.94 | bwd_microstep: 131.99 | bwd_inner_microstep: 131.93 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.10 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 327 +[2025-05-02 01:42:05,764] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 83.41 | bwd_microstep: 118.73 | bwd_inner_microstep: 118.58 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:42:06,241] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.48 | bwd_microstep: 272.49 | bwd_inner_microstep: 272.47 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 01:42:06,718] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.03 | bwd_microstep: 272.47 | bwd_inner_microstep: 272.46 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:42:07,198] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.92 | bwd_microstep: 272.22 | bwd_inner_microstep: 272.20 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:42:07,679] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.94 | bwd_microstep: 272.24 | bwd_inner_microstep: 272.22 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:42:08,155] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.45 | bwd_microstep: 271.00 | bwd_inner_microstep: 270.98 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.13 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:42:08,633] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.55 | bwd_microstep: 272.11 | bwd_inner_microstep: 272.10 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 01:42:09,209] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.11 | optimizer_step: 16.35 +[2025-05-02 01:42:09,210] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.21 | bwd_microstep: 347.94 | bwd_inner_microstep: 271.82 | bwd_allreduce_microstep: 76.07 | step_microstep: 23.46 +[2025-05-02 01:42:09,211] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2731.49 | bwd: 4018.58 | bwd_inner: 3941.78 | bwd_allreduce: 76.34 | step: 24.52 + 15%|█▌ | 1312/8720 [3:26:42<14:21:14, 6.98s/it] {'loss': 0.4084, 'grad_norm': 8.690458297729492, 'learning_rate': 9.624533547818531e-06, 'epoch': 1.5} + 15%|█▌ | 1312/8720 [3:26:42<14:21:14, 6.98s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1883 +[2025-05-02 01:42:09,693] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.78 | bwd_microstep: 273.48 | bwd_inner_microstep: 273.46 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2062 +[2025-05-02 01:42:10,214] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 203.33 | bwd_microstep: 302.06 | bwd_inner_microstep: 302.04 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 388 +[2025-05-02 01:42:10,420] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 78.10 | bwd_microstep: 114.31 | bwd_inner_microstep: 114.11 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-02 01:42:10,897] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.79 | bwd_microstep: 274.01 | bwd_inner_microstep: 273.99 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 01:42:11,374] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.48 | bwd_microstep: 272.80 | bwd_inner_microstep: 272.78 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-02 01:42:11,852] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.06 | bwd_microstep: 273.85 | bwd_inner_microstep: 273.83 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 01:42:12,329] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.77 | bwd_microstep: 272.69 | bwd_inner_microstep: 272.67 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1360 +[2025-05-02 01:42:12,693] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 142.02 | bwd_microstep: 206.34 | bwd_inner_microstep: 206.17 | bwd_allreduce_microstep: 0.08 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:42:13,171] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.87 | bwd_microstep: 272.43 | bwd_inner_microstep: 272.41 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1105 +[2025-05-02 01:42:13,465] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 115.28 | bwd_microstep: 161.56 | bwd_inner_microstep: 161.39 | bwd_allreduce_microstep: 0.08 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:42:13,941] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.86 | bwd_microstep: 272.16 | bwd_inner_microstep: 272.14 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 844 +[2025-05-02 01:42:14,184] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.60 | bwd_microstep: 132.13 | bwd_inner_microstep: 131.87 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.15 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 01:42:14,663] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.30 | bwd_microstep: 273.01 | bwd_inner_microstep: 272.99 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:42:15,143] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.75 | bwd_microstep: 272.47 | bwd_inner_microstep: 272.45 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:42:15,624] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.79 | bwd_microstep: 272.38 | bwd_inner_microstep: 272.36 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:42:16,215] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.21 | optimizer_step: 16.47 +[2025-05-02 01:42:16,215] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.16 | bwd_microstep: 357.81 | bwd_inner_microstep: 271.82 | bwd_allreduce_microstep: 85.93 | step_microstep: 24.50 +[2025-05-02 01:42:16,217] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2705.62 | bwd: 4003.57 | bwd_inner: 3916.58 | bwd_allreduce: 86.41 | step: 25.57 + 15%|█▌ | 1313/8720 [3:26:49<14:22:19, 6.99s/it] {'loss': 0.9471, 'grad_norm': 9.923386573791504, 'learning_rate': 9.623827142816233e-06, 'epoch': 1.51} + 15%|█▌ | 1313/8720 [3:26:49<14:22:19, 6.99s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:42:16,698] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.91 | bwd_microstep: 270.46 | bwd_inner_microstep: 270.44 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2054 +[2025-05-02 01:42:17,220] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 202.75 | bwd_microstep: 300.91 | bwd_inner_microstep: 300.89 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 388 +[2025-05-02 01:42:17,449] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 90.60 | bwd_microstep: 120.74 | bwd_inner_microstep: 120.44 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.11 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 865 +[2025-05-02 01:42:17,694] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.65 | bwd_microstep: 133.75 | bwd_inner_microstep: 133.62 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1893 +[2025-05-02 01:42:18,175] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.67 | bwd_microstep: 274.58 | bwd_inner_microstep: 274.56 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 01:42:18,655] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.25 | bwd_microstep: 272.84 | bwd_inner_microstep: 272.82 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 01:42:19,136] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.21 | bwd_microstep: 272.83 | bwd_inner_microstep: 272.81 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 01:42:19,618] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.31 | bwd_microstep: 272.77 | bwd_inner_microstep: 272.75 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.15 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:42:20,096] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.82 | bwd_microstep: 272.49 | bwd_inner_microstep: 272.47 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 01:42:20,574] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.75 | bwd_microstep: 272.45 | bwd_inner_microstep: 272.44 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:42:21,051] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.50 | bwd_microstep: 272.32 | bwd_inner_microstep: 272.30 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:42:21,530] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.42 | bwd_microstep: 272.20 | bwd_inner_microstep: 272.18 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:42:22,006] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.36 | bwd_microstep: 272.49 | bwd_inner_microstep: 272.47 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 01:42:22,482] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.91 | bwd_microstep: 272.24 | bwd_inner_microstep: 272.22 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:42:22,957] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.03 | bwd_microstep: 271.20 | bwd_inner_microstep: 271.18 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 01:42:23,527] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.18 | optimizer_step: 22.81 +[2025-05-02 01:42:23,528] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.45 | bwd_microstep: 337.92 | bwd_inner_microstep: 271.35 | bwd_allreduce_microstep: 66.52 | step_microstep: 30.15 +[2025-05-02 01:42:23,529] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2832.23 | bwd: 4162.22 | bwd_inner: 4095.00 | bwd_allreduce: 66.78 | step: 31.29 + 15%|█▌ | 1314/8720 [3:26:57<14:34:15, 7.08s/it] {'loss': 0.6543, 'grad_norm': 8.152563095092773, 'learning_rate': 9.623120099894301e-06, 'epoch': 1.51} + 15%|█▌ | 1314/8720 [3:26:57<14:34:15, 7.08s/it]dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1347 +[2025-05-02 01:42:23,894] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.32 | bwd_microstep: 205.27 | bwd_inner_microstep: 205.11 | bwd_allreduce_microstep: 0.08 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1904 +[2025-05-02 01:42:24,374] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.31 | bwd_microstep: 275.56 | bwd_inner_microstep: 275.55 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-02 01:42:24,850] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.55 | bwd_microstep: 273.08 | bwd_inner_microstep: 273.06 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 01:42:25,329] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.19 | bwd_microstep: 272.83 | bwd_inner_microstep: 272.82 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 01:42:25,811] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.36 | bwd_microstep: 272.44 | bwd_inner_microstep: 272.42 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 01:42:26,292] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.09 | bwd_microstep: 272.41 | bwd_inner_microstep: 272.39 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:42:26,771] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.77 | bwd_microstep: 272.04 | bwd_inner_microstep: 272.03 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 01:42:27,251] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.66 | bwd_microstep: 272.43 | bwd_inner_microstep: 272.41 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 840 +[2025-05-02 01:42:27,497] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.50 | bwd_microstep: 134.17 | bwd_inner_microstep: 133.93 | bwd_allreduce_microstep: 0.08 | step_microstep: 0.10 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1348 +[2025-05-02 01:42:27,862] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.75 | bwd_microstep: 205.87 | bwd_inner_microstep: 205.71 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:42:28,344] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.74 | bwd_microstep: 272.63 | bwd_inner_microstep: 272.61 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:42:28,826] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.57 | bwd_microstep: 272.12 | bwd_inner_microstep: 272.10 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:42:29,305] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.48 | bwd_microstep: 272.35 | bwd_inner_microstep: 272.33 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 01:42:29,785] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.44 | bwd_microstep: 272.66 | bwd_inner_microstep: 272.64 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:42:30,265] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.31 | bwd_microstep: 271.27 | bwd_inner_microstep: 271.26 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:42:30,842] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.15 | optimizer_step: 16.64 +[2025-05-02 01:42:30,843] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.25 | bwd_microstep: 347.66 | bwd_inner_microstep: 271.76 | bwd_allreduce_microstep: 75.86 | step_microstep: 24.53 +[2025-05-02 01:42:30,844] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2823.88 | bwd: 4164.86 | bwd_inner: 4088.20 | bwd_allreduce: 76.21 | step: 25.48 + 15%|█▌ | 1315/8720 [3:27:04<14:42:48, 7.15s/it] {'loss': 0.6867, 'grad_norm': 17.376712799072266, 'learning_rate': 9.622412419150284e-06, 'epoch': 1.51} + 15%|█▌ | 1315/8720 [3:27:04<14:42:48, 7.15s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 345 +[2025-05-02 01:42:31,072] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 80.19 | bwd_microstep: 126.50 | bwd_inner_microstep: 126.35 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1904 +[2025-05-02 01:42:31,554] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.02 | bwd_microstep: 275.52 | bwd_inner_microstep: 275.51 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1911 +[2025-05-02 01:42:32,037] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.62 | bwd_microstep: 276.34 | bwd_inner_microstep: 276.33 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1903 +[2025-05-02 01:42:32,520] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.75 | bwd_microstep: 275.92 | bwd_inner_microstep: 275.90 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1892 +[2025-05-02 01:42:33,000] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.88 | bwd_microstep: 274.90 | bwd_inner_microstep: 274.88 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1096 +[2025-05-02 01:42:33,291] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 115.33 | bwd_microstep: 161.51 | bwd_inner_microstep: 161.27 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-02 01:42:33,768] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.98 | bwd_microstep: 273.81 | bwd_inner_microstep: 273.79 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:42:34,243] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.12 | bwd_microstep: 272.26 | bwd_inner_microstep: 272.24 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 333 +[2025-05-02 01:42:34,442] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 67.40 | bwd_microstep: 118.58 | bwd_inner_microstep: 118.31 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:42:34,919] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.21 | bwd_microstep: 272.45 | bwd_inner_microstep: 272.44 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:42:35,395] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.41 | bwd_microstep: 272.25 | bwd_inner_microstep: 272.23 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:42:35,874] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.32 | bwd_microstep: 272.47 | bwd_inner_microstep: 272.45 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:42:36,354] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.86 | bwd_microstep: 271.04 | bwd_inner_microstep: 271.02 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:42:36,833] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.01 | bwd_microstep: 271.26 | bwd_inner_microstep: 271.24 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 01:42:37,313] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.23 | bwd_microstep: 272.28 | bwd_inner_microstep: 272.27 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2323 +[2025-05-02 01:42:37,994] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.19 | optimizer_step: 19.57 +[2025-05-02 01:42:37,994] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 217.90 | bwd_microstep: 416.05 | bwd_inner_microstep: 337.83 | bwd_allreduce_microstep: 78.17 | step_microstep: 27.58 +[2025-05-02 01:42:37,996] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2743.91 | bwd: 4103.21 | bwd_inner: 4024.17 | bwd_allreduce: 78.52 | step: 28.56 + 15%|█▌ | 1316/8720 [3:27:11<14:42:38, 7.15s/it] {'loss': 0.7371, 'grad_norm': 13.710931777954102, 'learning_rate': 9.621704100681811e-06, 'epoch': 1.51} + 15%|█▌ | 1316/8720 [3:27:11<14:42:38, 7.15s/it]dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 1010 +[2025-05-02 01:42:38,276] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 106.23 | bwd_microstep: 151.78 | bwd_inner_microstep: 151.46 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1936 +[2025-05-02 01:42:38,777] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.55 | bwd_microstep: 288.00 | bwd_inner_microstep: 287.99 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1901 +[2025-05-02 01:42:39,264] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.57 | bwd_microstep: 275.72 | bwd_inner_microstep: 275.70 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1887 +[2025-05-02 01:42:39,745] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.63 | bwd_microstep: 274.60 | bwd_inner_microstep: 274.58 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 01:42:40,226] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.33 | bwd_microstep: 272.63 | bwd_inner_microstep: 272.62 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1353 +[2025-05-02 01:42:40,591] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.41 | bwd_microstep: 206.27 | bwd_inner_microstep: 206.13 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 01:42:41,070] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.65 | bwd_microstep: 272.95 | bwd_inner_microstep: 272.93 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 01:42:41,548] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.03 | bwd_microstep: 272.80 | bwd_inner_microstep: 272.78 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:42:42,026] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.22 | bwd_microstep: 272.21 | bwd_inner_microstep: 272.19 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 01:42:42,508] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.95 | bwd_microstep: 272.60 | bwd_inner_microstep: 272.58 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:42:42,986] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.13 | bwd_microstep: 272.46 | bwd_inner_microstep: 272.45 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 831 +[2025-05-02 01:42:43,226] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.89 | bwd_microstep: 129.89 | bwd_inner_microstep: 129.81 | bwd_allreduce_microstep: 0.04 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:42:43,704] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.40 | bwd_microstep: 272.13 | bwd_inner_microstep: 272.11 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:42:44,182] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.40 | bwd_microstep: 272.39 | bwd_inner_microstep: 272.37 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 01:42:44,659] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.03 | bwd_microstep: 271.08 | bwd_inner_microstep: 271.07 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1944 +[2025-05-02 01:42:45,264] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.26 | optimizer_step: 16.70 +[2025-05-02 01:42:45,264] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 196.50 | bwd_microstep: 365.75 | bwd_inner_microstep: 289.16 | bwd_allreduce_microstep: 76.54 | step_microstep: 24.66 +[2025-05-02 01:42:45,266] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2805.57 | bwd: 4143.33 | bwd_inner: 4065.99 | bwd_allreduce: 76.87 | step: 25.62 + 15%|█▌ | 1317/8720 [3:27:19<14:46:50, 7.19s/it] {'loss': 1.035, 'grad_norm': 14.336921691894531, 'learning_rate': 9.62099514458661e-06, 'epoch': 1.51} + 15%|█▌ | 1317/8720 [3:27:19<14:46:50, 7.19s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 322 +[2025-05-02 01:42:45,482] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 79.77 | bwd_microstep: 115.82 | bwd_inner_microstep: 115.67 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1892 +[2025-05-02 01:42:45,963] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.91 | bwd_microstep: 275.27 | bwd_inner_microstep: 275.25 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 852 +[2025-05-02 01:42:46,205] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.51 | bwd_microstep: 133.32 | bwd_inner_microstep: 133.19 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-02 01:42:46,683] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.98 | bwd_microstep: 274.18 | bwd_inner_microstep: 274.16 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 01:42:47,162] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.15 | bwd_microstep: 273.39 | bwd_inner_microstep: 273.37 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 331 +[2025-05-02 01:42:47,376] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 78.21 | bwd_microstep: 121.40 | bwd_inner_microstep: 121.16 | bwd_allreduce_microstep: 0.09 | step_microstep: 0.09 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 834 +[2025-05-02 01:42:47,607] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 90.42 | bwd_microstep: 126.40 | bwd_inner_microstep: 126.36 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:42:48,085] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.51 | bwd_microstep: 273.50 | bwd_inner_microstep: 273.48 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 01:42:48,563] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.36 | bwd_microstep: 272.95 | bwd_inner_microstep: 272.94 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 834 +[2025-05-02 01:42:48,797] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.14 | bwd_microstep: 126.12 | bwd_inner_microstep: 125.93 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1089 +[2025-05-02 01:42:49,088] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 115.61 | bwd_microstep: 161.16 | bwd_inner_microstep: 160.97 | bwd_allreduce_microstep: 0.10 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 01:42:49,565] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.01 | bwd_microstep: 272.61 | bwd_inner_microstep: 272.59 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 01:42:50,040] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.75 | bwd_microstep: 271.72 | bwd_inner_microstep: 271.70 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 01:42:50,519] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.33 | bwd_microstep: 273.25 | bwd_inner_microstep: 273.24 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 01:42:50,995] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.29 | bwd_microstep: 271.69 | bwd_inner_microstep: 271.67 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:42:51,573] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.13 | optimizer_step: 16.47 +[2025-05-02 01:42:51,573] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.49 | bwd_microstep: 348.49 | bwd_inner_microstep: 272.33 | bwd_allreduce_microstep: 76.11 | step_microstep: 24.30 +[2025-05-02 01:42:51,575] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2441.15 | bwd: 3591.35 | bwd_inner: 3514.11 | bwd_allreduce: 76.60 | step: 25.24 + 15%|█▌ | 1318/8720 [3:27:25<14:14:11, 6.92s/it] {'loss': 0.5106, 'grad_norm': 7.551886558532715, 'learning_rate': 9.620285550962485e-06, 'epoch': 1.51} + 15%|█▌ | 1318/8720 [3:27:25<14:14:11, 6.92s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1893 +[2025-05-02 01:42:52,061] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.41 | bwd_microstep: 274.30 | bwd_inner_microstep: 274.28 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 916 +[2025-05-02 01:42:52,324] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 104.26 | bwd_microstep: 145.16 | bwd_inner_microstep: 144.89 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-02 01:42:52,801] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.96 | bwd_microstep: 273.29 | bwd_inner_microstep: 273.28 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 01:42:53,280] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.79 | bwd_microstep: 273.54 | bwd_inner_microstep: 273.53 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 841 +[2025-05-02 01:42:53,522] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.88 | bwd_microstep: 132.31 | bwd_inner_microstep: 132.05 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:42:54,000] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.02 | bwd_microstep: 272.51 | bwd_inner_microstep: 272.50 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 01:42:54,479] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.39 | bwd_microstep: 273.03 | bwd_inner_microstep: 273.01 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 01:42:54,961] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.46 | bwd_microstep: 272.38 | bwd_inner_microstep: 272.36 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1352 +[2025-05-02 01:42:55,325] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.25 | bwd_microstep: 206.03 | bwd_inner_microstep: 206.01 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 01:42:55,804] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.13 | bwd_microstep: 272.77 | bwd_inner_microstep: 272.76 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 01:42:56,285] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.28 | bwd_microstep: 272.79 | bwd_inner_microstep: 272.78 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:42:56,765] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.28 | bwd_microstep: 272.47 | bwd_inner_microstep: 272.45 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:42:57,245] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.14 | bwd_microstep: 272.43 | bwd_inner_microstep: 272.41 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 01:42:57,722] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.70 | bwd_microstep: 271.09 | bwd_inner_microstep: 271.07 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 826 +[2025-05-02 01:42:57,964] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 96.11 | bwd_microstep: 129.40 | bwd_inner_microstep: 129.26 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2128 +[2025-05-02 01:42:58,601] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.14 | optimizer_step: 16.46 +[2025-05-02 01:42:58,602] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 205.49 | bwd_microstep: 390.55 | bwd_inner_microstep: 314.25 | bwd_allreduce_microstep: 76.25 | step_microstep: 24.12 +[2025-05-02 01:42:58,603] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2713.22 | bwd: 4004.12 | bwd_inner: 3926.90 | bwd_allreduce: 76.62 | step: 25.04 + 15%|█▌ | 1319/8720 [3:27:32<14:17:56, 6.96s/it] {'loss': 0.7256, 'grad_norm': 8.82111930847168, 'learning_rate': 9.619575319907338e-06, 'epoch': 1.51} + 15%|█▌ | 1319/8720 [3:27:32<14:17:56, 6.96s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 01:42:59,087] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.73 | bwd_microstep: 272.23 | bwd_inner_microstep: 272.21 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1955 +[2025-05-02 01:42:59,590] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 197.49 | bwd_microstep: 290.10 | bwd_inner_microstep: 290.08 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1925 +[2025-05-02 01:43:00,088] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.04 | bwd_microstep: 287.71 | bwd_inner_microstep: 287.69 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1896 +[2025-05-02 01:43:00,567] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.36 | bwd_microstep: 275.14 | bwd_inner_microstep: 275.12 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1888 +[2025-05-02 01:43:01,046] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.08 | bwd_microstep: 274.53 | bwd_inner_microstep: 274.51 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1893 +[2025-05-02 01:43:01,525] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.20 | bwd_microstep: 274.86 | bwd_inner_microstep: 274.84 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-02 01:43:02,002] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.67 | bwd_microstep: 273.41 | bwd_inner_microstep: 273.39 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-02 01:43:02,479] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.80 | bwd_microstep: 273.73 | bwd_inner_microstep: 273.71 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:43:02,956] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.38 | bwd_microstep: 272.42 | bwd_inner_microstep: 272.40 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 841 +[2025-05-02 01:43:03,198] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.37 | bwd_microstep: 132.40 | bwd_inner_microstep: 132.12 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:43:03,675] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.26 | bwd_microstep: 272.58 | bwd_inner_microstep: 272.56 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1346 +[2025-05-02 01:43:04,037] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.76 | bwd_microstep: 205.71 | bwd_inner_microstep: 205.56 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 01:43:04,513] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.40 | bwd_microstep: 272.36 | bwd_inner_microstep: 272.34 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 01:43:04,992] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.67 | bwd_microstep: 270.98 | bwd_inner_microstep: 270.96 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:43:05,470] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.71 | bwd_microstep: 271.36 | bwd_inner_microstep: 271.34 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1952 +[2025-05-02 01:43:06,070] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.13 | optimizer_step: 16.45 +[2025-05-02 01:43:06,070] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 196.52 | bwd_microstep: 363.46 | bwd_inner_microstep: 290.08 | bwd_allreduce_microstep: 73.34 | step_microstep: 23.36 +[2025-05-02 01:43:06,071] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2901.14 | bwd: 4283.04 | bwd_inner: 4208.98 | bwd_allreduce: 73.64 | step: 24.10 + 15%|█▌ | 1320/8720 [3:27:39<14:36:44, 7.11s/it] {'loss': 0.6644, 'grad_norm': 4.26966667175293, 'learning_rate': 9.618864451519154e-06, 'epoch': 1.51} + 15%|█▌ | 1320/8720 [3:27:39<14:36:44, 7.11s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 360 +[2025-05-02 01:43:06,274] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 67.36 | bwd_microstep: 117.16 | bwd_inner_microstep: 117.03 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1892 +[2025-05-02 01:43:06,753] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.64 | bwd_microstep: 274.76 | bwd_inner_microstep: 274.75 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 01:43:07,232] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.56 | bwd_microstep: 273.60 | bwd_inner_microstep: 273.58 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 01:43:07,711] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.89 | bwd_microstep: 273.39 | bwd_inner_microstep: 273.38 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 01:43:08,190] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.74 | bwd_microstep: 273.37 | bwd_inner_microstep: 273.35 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 01:43:08,667] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.39 | bwd_microstep: 273.24 | bwd_inner_microstep: 273.22 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 01:43:09,145] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.74 | bwd_microstep: 273.11 | bwd_inner_microstep: 273.09 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 01:43:09,624] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.07 | bwd_microstep: 272.76 | bwd_inner_microstep: 272.74 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 325 +[2025-05-02 01:43:09,830] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 72.33 | bwd_microstep: 119.09 | bwd_inner_microstep: 118.94 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:43:10,306] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.06 | bwd_microstep: 272.64 | bwd_inner_microstep: 272.62 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:43:10,782] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.22 | bwd_microstep: 272.39 | bwd_inner_microstep: 272.38 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1345 +[2025-05-02 01:43:11,145] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.39 | bwd_microstep: 205.67 | bwd_inner_microstep: 205.66 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:43:11,623] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.19 | bwd_microstep: 272.35 | bwd_inner_microstep: 272.34 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 01:43:12,101] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.01 | bwd_microstep: 271.34 | bwd_inner_microstep: 271.33 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:43:12,578] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.68 | bwd_microstep: 271.10 | bwd_inner_microstep: 271.08 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:43:13,155] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 3.08 | optimizer_step: 16.45 +[2025-05-02 01:43:13,156] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.82 | bwd_microstep: 347.58 | bwd_inner_microstep: 271.41 | bwd_allreduce_microstep: 76.11 | step_microstep: 25.13 +[2025-05-02 01:43:13,157] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2733.80 | bwd: 4063.61 | bwd_inner: 3986.95 | bwd_allreduce: 76.30 | step: 25.95 + 15%|█▌ | 1321/8720 [3:27:46<14:35:50, 7.10s/it] {'loss': 0.675, 'grad_norm': 14.533732414245605, 'learning_rate': 9.618152945896008e-06, 'epoch': 1.51} + 15%|█▌ | 1321/8720 [3:27:46<14:35:50, 7.10s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 01:43:13,638] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.80 | bwd_microstep: 270.82 | bwd_inner_microstep: 270.80 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1904 +[2025-05-02 01:43:14,119] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.33 | bwd_microstep: 276.20 | bwd_inner_microstep: 276.18 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1896 +[2025-05-02 01:43:14,598] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.96 | bwd_microstep: 275.43 | bwd_inner_microstep: 275.41 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1895 +[2025-05-02 01:43:15,079] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.63 | bwd_microstep: 275.56 | bwd_inner_microstep: 275.55 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-02 01:43:15,558] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.06 | bwd_microstep: 274.75 | bwd_inner_microstep: 274.74 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.13 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 348 +[2025-05-02 01:43:15,765] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 78.01 | bwd_microstep: 116.23 | bwd_inner_microstep: 116.11 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.08 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1367 +[2025-05-02 01:43:16,128] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.92 | bwd_microstep: 207.52 | bwd_inner_microstep: 207.51 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1886 +[2025-05-02 01:43:16,608] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.80 | bwd_microstep: 275.25 | bwd_inner_microstep: 275.23 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1366 +[2025-05-02 01:43:16,973] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 142.77 | bwd_microstep: 206.63 | bwd_inner_microstep: 206.54 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.08 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 851 +[2025-05-02 01:43:17,215] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 96.31 | bwd_microstep: 132.45 | bwd_inner_microstep: 132.27 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.09 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 845 +[2025-05-02 01:43:17,456] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.42 | bwd_microstep: 131.93 | bwd_inner_microstep: 131.73 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.08 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 324 +[2025-05-02 01:43:17,662] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 71.16 | bwd_microstep: 121.12 | bwd_inner_microstep: 121.00 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:43:18,138] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.25 | bwd_microstep: 272.62 | bwd_inner_microstep: 272.61 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:43:18,612] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.60 | bwd_microstep: 270.91 | bwd_inner_microstep: 270.90 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 317 +[2025-05-02 01:43:18,812] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 68.36 | bwd_microstep: 118.03 | bwd_inner_microstep: 117.90 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:43:19,377] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.04 | optimizer_gradients: 2.12 | optimizer_step: 16.45 +[2025-05-02 01:43:19,377] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.49 | bwd_microstep: 339.68 | bwd_inner_microstep: 271.81 | bwd_allreduce_microstep: 67.82 | step_microstep: 23.44 +[2025-05-02 01:43:19,378] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2387.60 | bwd: 3565.23 | bwd_inner: 3496.35 | bwd_allreduce: 68.32 | step: 24.49 + 15%|█▌ | 1322/8720 [3:27:53<14:03:03, 6.84s/it] {'loss': 1.1669, 'grad_norm': 9.190814018249512, 'learning_rate': 9.61744080313606e-06, 'epoch': 1.52} + 15%|█▌ | 1322/8720 [3:27:53<14:03:03, 6.84s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:43:19,856] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.65 | bwd_microstep: 270.40 | bwd_inner_microstep: 270.38 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1939 +[2025-05-02 01:43:20,355] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.46 | bwd_microstep: 288.53 | bwd_inner_microstep: 288.52 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1914 +[2025-05-02 01:43:20,836] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.10 | bwd_microstep: 275.98 | bwd_inner_microstep: 275.96 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1914 +[2025-05-02 01:43:21,316] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.53 | bwd_microstep: 276.04 | bwd_inner_microstep: 276.02 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1130 +[2025-05-02 01:43:21,610] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 115.93 | bwd_microstep: 163.81 | bwd_inner_microstep: 163.79 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 340 +[2025-05-02 01:43:21,812] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 68.54 | bwd_microstep: 121.10 | bwd_inner_microstep: 120.93 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1371 +[2025-05-02 01:43:22,175] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.79 | bwd_microstep: 207.61 | bwd_inner_microstep: 207.59 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 01:43:22,651] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.22 | bwd_microstep: 273.01 | bwd_inner_microstep: 272.99 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 340 +[2025-05-02 01:43:22,850] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 67.68 | bwd_microstep: 118.45 | bwd_inner_microstep: 118.14 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 01:43:23,326] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.41 | bwd_microstep: 272.81 | bwd_inner_microstep: 272.79 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 01:43:23,806] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.59 | bwd_microstep: 273.24 | bwd_inner_microstep: 273.22 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:43:24,282] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.55 | bwd_microstep: 272.56 | bwd_inner_microstep: 272.54 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 01:43:24,758] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.52 | bwd_microstep: 272.98 | bwd_inner_microstep: 272.97 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1349 +[2025-05-02 01:43:25,120] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.51 | bwd_microstep: 205.84 | bwd_inner_microstep: 205.82 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:43:25,595] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.88 | bwd_microstep: 272.60 | bwd_inner_microstep: 272.58 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1344 +[2025-05-02 01:43:26,044] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.04 | optimizer_gradients: 2.12 | optimizer_step: 16.47 +[2025-05-02 01:43:26,045] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 139.70 | bwd_microstep: 271.43 | bwd_inner_microstep: 205.16 | bwd_allreduce_microstep: 66.10 | step_microstep: 23.38 +[2025-05-02 01:43:26,046] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2566.82 | bwd: 3836.44 | bwd_inner: 3769.60 | bwd_allreduce: 66.29 | step: 24.16 + 15%|█▌ | 1323/8720 [3:27:59<13:56:39, 6.79s/it] {'loss': 0.733, 'grad_norm': 5.0641913414001465, 'learning_rate': 9.61672802333756e-06, 'epoch': 1.52} + 15%|█▌ | 1323/8720 [3:27:59<13:56:39, 6.79s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 01:43:26,526] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.68 | bwd_microstep: 271.91 | bwd_inner_microstep: 271.90 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2056 +[2025-05-02 01:43:27,046] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 203.31 | bwd_microstep: 301.96 | bwd_inner_microstep: 301.94 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1984 +[2025-05-02 01:43:27,555] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 199.60 | bwd_microstep: 292.36 | bwd_inner_microstep: 292.34 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1887 +[2025-05-02 01:43:28,036] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.10 | bwd_microstep: 274.47 | bwd_inner_microstep: 274.46 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 350 +[2025-05-02 01:43:28,269] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 96.00 | bwd_microstep: 118.02 | bwd_inner_microstep: 117.73 | bwd_allreduce_microstep: 0.10 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-02 01:43:28,750] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.43 | bwd_microstep: 273.33 | bwd_inner_microstep: 273.31 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 01:43:29,230] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.53 | bwd_microstep: 272.78 | bwd_inner_microstep: 272.77 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 842 +[2025-05-02 01:43:29,477] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.64 | bwd_microstep: 131.69 | bwd_inner_microstep: 131.64 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:43:29,955] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.90 | bwd_microstep: 272.37 | bwd_inner_microstep: 272.36 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 833 +[2025-05-02 01:43:30,195] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.61 | bwd_microstep: 125.83 | bwd_inner_microstep: 125.58 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:43:30,674] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.85 | bwd_microstep: 272.31 | bwd_inner_microstep: 272.29 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:43:31,154] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.86 | bwd_microstep: 272.27 | bwd_inner_microstep: 272.25 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 01:43:31,634] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.38 | bwd_microstep: 272.36 | bwd_inner_microstep: 272.34 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.15 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:43:32,115] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.92 | bwd_microstep: 271.08 | bwd_inner_microstep: 271.06 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 01:43:32,594] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.58 | bwd_microstep: 270.99 | bwd_inner_microstep: 270.97 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 01:43:33,176] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.13 | optimizer_step: 16.49 +[2025-05-02 01:43:33,177] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.40 | bwd_microstep: 352.24 | bwd_inner_microstep: 273.58 | bwd_allreduce_microstep: 78.61 | step_microstep: 24.26 +[2025-05-02 01:43:33,178] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2761.39 | bwd: 4046.04 | bwd_inner: 3966.57 | bwd_allreduce: 78.90 | step: 25.45 + 15%|█▌ | 1324/8720 [3:28:06<14:09:24, 6.89s/it] {'loss': 0.6137, 'grad_norm': 8.15362548828125, 'learning_rate': 9.616014606598846e-06, 'epoch': 1.52} + 15%|█▌ | 1324/8720 [3:28:06<14:09:24, 6.89s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 01:43:33,662] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.15 | bwd_microstep: 272.20 | bwd_inner_microstep: 272.19 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1922 +[2025-05-02 01:43:34,163] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.71 | bwd_microstep: 286.78 | bwd_inner_microstep: 286.76 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1883 +[2025-05-02 01:43:34,646] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.38 | bwd_microstep: 274.30 | bwd_inner_microstep: 274.28 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-02 01:43:35,128] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.36 | bwd_microstep: 274.14 | bwd_inner_microstep: 274.13 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1372 +[2025-05-02 01:43:35,498] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 143.63 | bwd_microstep: 207.72 | bwd_inner_microstep: 207.70 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-02 01:43:35,978] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.84 | bwd_microstep: 273.80 | bwd_inner_microstep: 273.78 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 01:43:36,461] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.57 | bwd_microstep: 273.20 | bwd_inner_microstep: 273.19 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 852 +[2025-05-02 01:43:36,714] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 98.03 | bwd_microstep: 134.47 | bwd_inner_microstep: 134.25 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1360 +[2025-05-02 01:43:37,080] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.05 | bwd_microstep: 206.51 | bwd_inner_microstep: 206.48 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 01:43:37,558] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.66 | bwd_microstep: 273.06 | bwd_inner_microstep: 273.04 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:43:38,040] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.24 | bwd_microstep: 273.17 | bwd_inner_microstep: 273.15 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 01:43:38,521] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.77 | bwd_microstep: 273.18 | bwd_inner_microstep: 273.17 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1356 +[2025-05-02 01:43:38,887] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 142.17 | bwd_microstep: 206.58 | bwd_inner_microstep: 206.39 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.10 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 322 +[2025-05-02 01:43:39,125] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 91.97 | bwd_microstep: 130.46 | bwd_inner_microstep: 130.26 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:43:39,601] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.24 | bwd_microstep: 271.37 | bwd_inner_microstep: 271.36 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 01:43:40,169] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.15 | optimizer_step: 16.60 +[2025-05-02 01:43:40,169] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.44 | bwd_microstep: 339.01 | bwd_inner_microstep: 272.00 | bwd_allreduce_microstep: 66.96 | step_microstep: 23.75 +[2025-05-02 01:43:40,170] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2701.84 | bwd: 3970.05 | bwd_inner: 3902.19 | bwd_allreduce: 67.33 | step: 24.75 + 15%|█▌ | 1325/8720 [3:28:13<14:12:58, 6.92s/it] {'loss': 1.1853, 'grad_norm': 10.116191864013672, 'learning_rate': 9.615300553018346e-06, 'epoch': 1.52} + 15%|█▌ | 1325/8720 [3:28:13<14:12:58, 6.92s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 01:43:40,649] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.56 | bwd_microstep: 270.70 | bwd_inner_microstep: 270.68 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-02 01:43:41,127] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.07 | bwd_microstep: 274.21 | bwd_inner_microstep: 274.19 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-02 01:43:41,606] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.08 | bwd_microstep: 274.24 | bwd_inner_microstep: 274.22 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-02 01:43:42,084] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.43 | bwd_microstep: 273.46 | bwd_inner_microstep: 273.44 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-02 01:43:42,563] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.04 | bwd_microstep: 273.58 | bwd_inner_microstep: 273.56 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 01:43:43,041] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.61 | bwd_microstep: 272.98 | bwd_inner_microstep: 272.97 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1352 +[2025-05-02 01:43:43,405] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.86 | bwd_microstep: 205.93 | bwd_inner_microstep: 205.91 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 333 +[2025-05-02 01:43:43,610] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 68.55 | bwd_microstep: 123.57 | bwd_inner_microstep: 123.44 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 01:43:44,085] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.13 | bwd_microstep: 272.63 | bwd_inner_microstep: 272.61 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:43:44,561] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.54 | bwd_microstep: 272.51 | bwd_inner_microstep: 272.49 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:43:45,038] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.06 | bwd_microstep: 272.71 | bwd_inner_microstep: 272.69 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:43:45,516] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.36 | bwd_microstep: 272.75 | bwd_inner_microstep: 272.73 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:43:45,993] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.44 | bwd_microstep: 272.44 | bwd_inner_microstep: 272.42 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 01:43:46,468] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.64 | bwd_microstep: 271.21 | bwd_inner_microstep: 271.20 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:43:46,943] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.90 | bwd_microstep: 272.05 | bwd_inner_microstep: 272.04 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 318 +[2025-05-02 01:43:47,260] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.15 | optimizer_step: 16.56 +[2025-05-02 01:43:47,261] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 79.44 | bwd_microstep: 200.13 | bwd_inner_microstep: 131.43 | bwd_allreduce_microstep: 68.56 | step_microstep: 23.67 +[2025-05-02 01:43:47,262] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2739.41 | bwd: 4075.13 | bwd_inner: 4006.11 | bwd_allreduce: 68.66 | step: 24.42 + 15%|█▌ | 1326/8720 [3:28:21<14:19:10, 6.97s/it] {'loss': 0.8376, 'grad_norm': 13.291200637817383, 'learning_rate': 9.61458586269457e-06, 'epoch': 1.52} + 15%|█▌ | 1326/8720 [3:28:21<14:19:10, 6.97s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:43:47,740] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.76 | bwd_microstep: 270.37 | bwd_inner_microstep: 270.35 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1883 +[2025-05-02 01:43:48,219] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.56 | bwd_microstep: 274.41 | bwd_inner_microstep: 274.39 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1883 +[2025-05-02 01:43:48,699] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.72 | bwd_microstep: 274.41 | bwd_inner_microstep: 274.39 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1358 +[2025-05-02 01:43:49,062] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.34 | bwd_microstep: 206.13 | bwd_inner_microstep: 206.12 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 01:43:49,539] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.32 | bwd_microstep: 273.20 | bwd_inner_microstep: 273.18 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 844 +[2025-05-02 01:43:49,780] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.26 | bwd_microstep: 132.03 | bwd_inner_microstep: 131.94 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 01:43:50,257] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.51 | bwd_microstep: 273.32 | bwd_inner_microstep: 273.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-02 01:43:50,735] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.11 | bwd_microstep: 273.25 | bwd_inner_microstep: 273.23 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.13 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 853 +[2025-05-02 01:43:50,980] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.58 | bwd_microstep: 132.77 | bwd_inner_microstep: 132.69 | bwd_allreduce_microstep: 0.03 | step_microstep: 0.11 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1352 +[2025-05-02 01:43:51,344] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.33 | bwd_microstep: 206.03 | bwd_inner_microstep: 206.02 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:43:51,822] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.01 | bwd_microstep: 272.39 | bwd_inner_microstep: 272.37 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1351 +[2025-05-02 01:43:52,187] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.58 | bwd_microstep: 205.97 | bwd_inner_microstep: 205.95 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:43:52,664] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.62 | bwd_microstep: 271.05 | bwd_inner_microstep: 271.03 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 316 +[2025-05-02 01:43:52,887] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 91.94 | bwd_microstep: 115.06 | bwd_inner_microstep: 114.76 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:43:53,363] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.00 | bwd_microstep: 271.03 | bwd_inner_microstep: 271.01 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:43:53,943] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.21 | optimizer_step: 17.27 +[2025-05-02 01:43:53,944] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.55 | bwd_microstep: 349.26 | bwd_inner_microstep: 271.54 | bwd_allreduce_microstep: 77.66 | step_microstep: 25.18 +[2025-05-02 01:43:53,945] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2586.85 | bwd: 3800.75 | bwd_inner: 3722.33 | bwd_allreduce: 77.96 | step: 26.32 + 15%|█▌ | 1327/8720 [3:28:27<14:08:29, 6.89s/it] {'loss': 0.7062, 'grad_norm': 14.336994171142578, 'learning_rate': 9.61387053572612e-06, 'epoch': 1.52} + 15%|█▌ | 1327/8720 [3:28:27<14:08:29, 6.89s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-02 01:43:54,431] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.16 | bwd_microstep: 273.32 | bwd_inner_microstep: 273.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1930 +[2025-05-02 01:43:54,931] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.99 | bwd_microstep: 287.90 | bwd_inner_microstep: 287.88 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 879 +[2025-05-02 01:43:55,176] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.29 | bwd_microstep: 135.02 | bwd_inner_microstep: 134.79 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-02 01:43:55,655] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.94 | bwd_microstep: 273.49 | bwd_inner_microstep: 273.48 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-02 01:43:56,138] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.14 | bwd_microstep: 274.44 | bwd_inner_microstep: 274.42 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-02 01:43:56,621] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.36 | bwd_microstep: 273.97 | bwd_inner_microstep: 273.95 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 334 +[2025-05-02 01:43:56,876] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 90.84 | bwd_microstep: 145.12 | bwd_inner_microstep: 144.96 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:43:57,354] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.39 | bwd_microstep: 272.27 | bwd_inner_microstep: 272.26 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1093 +[2025-05-02 01:43:57,652] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 117.67 | bwd_microstep: 161.41 | bwd_inner_microstep: 161.27 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 321 +[2025-05-02 01:43:57,879] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 87.46 | bwd_microstep: 122.32 | bwd_inner_microstep: 122.00 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 01:43:58,356] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.37 | bwd_microstep: 271.17 | bwd_inner_microstep: 271.15 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:43:58,834] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.27 | bwd_microstep: 271.34 | bwd_inner_microstep: 271.32 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:43:59,315] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.47 | bwd_microstep: 271.16 | bwd_inner_microstep: 271.14 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 01:43:59,793] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.80 | bwd_microstep: 271.50 | bwd_inner_microstep: 271.49 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:44:00,271] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.91 | bwd_microstep: 271.14 | bwd_inner_microstep: 271.13 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 01:44:00,852] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.18 | optimizer_step: 16.57 +[2025-05-02 01:44:00,853] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.51 | bwd_microstep: 350.52 | bwd_inner_microstep: 271.73 | bwd_allreduce_microstep: 78.74 | step_microstep: 24.46 +[2025-05-02 01:44:00,854] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2663.19 | bwd: 3926.19 | bwd_inner: 3846.37 | bwd_allreduce: 79.19 | step: 25.50 + 15%|█▌ | 1328/8720 [3:28:34<14:09:12, 6.89s/it] {'loss': 0.7301, 'grad_norm': 10.953056335449219, 'learning_rate': 9.613154572211687e-06, 'epoch': 1.52} + 15%|█▌ | 1328/8720 [3:28:34<14:09:12, 6.89s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2053 +[2025-05-02 01:44:01,382] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 202.80 | bwd_microstep: 301.28 | bwd_inner_microstep: 301.26 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 895 +[2025-05-02 01:44:01,630] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.28 | bwd_microstep: 136.24 | bwd_inner_microstep: 136.16 | bwd_allreduce_microstep: 0.04 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1905 +[2025-05-02 01:44:02,115] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.47 | bwd_microstep: 276.17 | bwd_inner_microstep: 276.15 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 872 +[2025-05-02 01:44:02,364] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 98.76 | bwd_microstep: 134.78 | bwd_inner_microstep: 134.58 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1900 +[2025-05-02 01:44:02,847] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.12 | bwd_microstep: 275.56 | bwd_inner_microstep: 275.54 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 348 +[2025-05-02 01:44:03,073] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 84.98 | bwd_microstep: 124.60 | bwd_inner_microstep: 124.48 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-02 01:44:03,552] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.22 | bwd_microstep: 273.57 | bwd_inner_microstep: 273.55 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-02 01:44:04,037] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.04 | bwd_microstep: 274.31 | bwd_inner_microstep: 274.29 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 01:44:04,518] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.14 | bwd_microstep: 273.53 | bwd_inner_microstep: 273.52 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1100 +[2025-05-02 01:44:04,815] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 118.23 | bwd_microstep: 161.50 | bwd_inner_microstep: 161.36 | bwd_allreduce_microstep: 0.09 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 01:44:05,294] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.88 | bwd_microstep: 272.95 | bwd_inner_microstep: 272.93 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 334 +[2025-05-02 01:44:05,507] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 69.61 | bwd_microstep: 129.14 | bwd_inner_microstep: 129.01 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 01:44:05,983] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.19 | bwd_microstep: 272.84 | bwd_inner_microstep: 272.82 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:44:06,460] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.12 | bwd_microstep: 272.36 | bwd_inner_microstep: 272.35 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:44:06,937] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.29 | bwd_microstep: 272.46 | bwd_inner_microstep: 272.44 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:44:07,503] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.25 | optimizer_step: 16.73 +[2025-05-02 01:44:07,503] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.26 | bwd_microstep: 338.89 | bwd_inner_microstep: 271.87 | bwd_allreduce_microstep: 66.98 | step_microstep: 24.00 +[2025-05-02 01:44:07,504] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2558.06 | bwd: 3790.27 | bwd_inner: 3722.42 | bwd_allreduce: 67.35 | step: 24.95 + 15%|█▌ | 1329/8720 [3:28:41<14:00:02, 6.82s/it] {'loss': 0.9759, 'grad_norm': 7.436770915985107, 'learning_rate': 9.612437972250044e-06, 'epoch': 1.52} + 15%|█▌ | 1329/8720 [3:28:41<14:00:02, 6.82s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1849 +[2025-05-02 01:44:07,983] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.15 | bwd_microstep: 270.26 | bwd_inner_microstep: 270.24 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2436 +[2025-05-02 01:44:08,571] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 220.75 | bwd_microstep: 352.37 | bwd_inner_microstep: 352.36 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2136 +[2025-05-02 01:44:09,107] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 205.16 | bwd_microstep: 314.09 | bwd_inner_microstep: 314.07 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1911 +[2025-05-02 01:44:09,588] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.66 | bwd_microstep: 276.33 | bwd_inner_microstep: 276.31 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-02 01:44:10,069] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.03 | bwd_microstep: 274.32 | bwd_inner_microstep: 274.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-02 01:44:10,551] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.57 | bwd_microstep: 274.19 | bwd_inner_microstep: 274.17 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1892 +[2025-05-02 01:44:11,034] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.70 | bwd_microstep: 274.87 | bwd_inner_microstep: 274.85 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 01:44:11,514] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.89 | bwd_microstep: 273.08 | bwd_inner_microstep: 273.06 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1096 +[2025-05-02 01:44:11,807] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 116.14 | bwd_microstep: 161.05 | bwd_inner_microstep: 160.96 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 01:44:12,286] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.40 | bwd_microstep: 272.80 | bwd_inner_microstep: 272.78 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 842 +[2025-05-02 01:44:12,529] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.25 | bwd_microstep: 132.47 | bwd_inner_microstep: 132.22 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 834 +[2025-05-02 01:44:12,769] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 97.07 | bwd_microstep: 125.71 | bwd_inner_microstep: 125.48 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:44:13,248] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.07 | bwd_microstep: 272.52 | bwd_inner_microstep: 272.50 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:44:13,729] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.14 | bwd_microstep: 272.50 | bwd_inner_microstep: 272.49 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 01:44:14,208] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.33 | bwd_microstep: 271.22 | bwd_inner_microstep: 271.20 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:44:14,790] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.17 | optimizer_step: 16.49 +[2025-05-02 01:44:14,791] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.50 | bwd_microstep: 348.90 | bwd_inner_microstep: 271.67 | bwd_allreduce_microstep: 77.17 | step_microstep: 24.18 +[2025-05-02 01:44:14,792] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2812.45 | bwd: 4166.77 | bwd_inner: 4088.70 | bwd_allreduce: 77.56 | step: 25.25 + 15%|█▌ | 1330/8720 [3:28:48<14:17:17, 6.96s/it] {'loss': 0.8359, 'grad_norm': 11.975810050964355, 'learning_rate': 9.61172073594006e-06, 'epoch': 1.53} + 15%|█▌ | 1330/8720 [3:28:48<14:17:17, 6.96s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2092 +[2025-05-02 01:44:15,323] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 203.76 | bwd_microstep: 304.19 | bwd_inner_microstep: 304.17 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 879 +[2025-05-02 01:44:15,570] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.33 | bwd_microstep: 134.86 | bwd_inner_microstep: 134.65 | bwd_allreduce_microstep: 0.09 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1897 +[2025-05-02 01:44:16,052] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.90 | bwd_microstep: 275.30 | bwd_inner_microstep: 275.28 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1886 +[2025-05-02 01:44:16,535] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.52 | bwd_microstep: 274.32 | bwd_inner_microstep: 274.30 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 350 +[2025-05-02 01:44:16,750] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 80.28 | bwd_microstep: 120.28 | bwd_inner_microstep: 120.00 | bwd_allreduce_microstep: 0.14 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1887 +[2025-05-02 01:44:17,232] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.12 | bwd_microstep: 274.67 | bwd_inner_microstep: 274.65 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-02 01:44:17,714] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.55 | bwd_microstep: 273.64 | bwd_inner_microstep: 273.62 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-02 01:44:18,196] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.89 | bwd_microstep: 273.52 | bwd_inner_microstep: 273.50 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-02 01:44:18,678] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.36 | bwd_microstep: 273.08 | bwd_inner_microstep: 273.07 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.07 +dynamic ViT batch size: 6, images per sample: 6.0, dynamic token length: 1615 +[2025-05-02 01:44:19,111] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 165.85 | bwd_microstep: 245.02 | bwd_inner_microstep: 245.00 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 01:44:19,592] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.50 | bwd_microstep: 272.84 | bwd_inner_microstep: 272.82 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 01:44:20,072] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.58 | bwd_microstep: 272.80 | bwd_inner_microstep: 272.78 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1358 +[2025-05-02 01:44:20,436] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.36 | bwd_microstep: 206.46 | bwd_inner_microstep: 206.44 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 01:44:20,914] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.01 | bwd_microstep: 272.24 | bwd_inner_microstep: 272.22 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:44:21,389] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.76 | bwd_microstep: 271.32 | bwd_inner_microstep: 271.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 01:44:21,971] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.16 | optimizer_step: 16.46 +[2025-05-02 01:44:21,971] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.99 | bwd_microstep: 351.82 | bwd_inner_microstep: 271.78 | bwd_allreduce_microstep: 79.99 | step_microstep: 24.09 +[2025-05-02 01:44:21,972] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2764.40 | bwd: 4096.39 | bwd_inner: 4015.68 | bwd_allreduce: 80.24 | step: 25.03 + 15%|█▌ | 1331/8720 [3:28:55<14:25:17, 7.03s/it] {'loss': 0.849, 'grad_norm': 6.574762344360352, 'learning_rate': 9.611002863380684e-06, 'epoch': 1.53} + 15%|█▌ | 1331/8720 [3:28:55<14:25:17, 7.03s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 01:44:22,453] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.74 | bwd_microstep: 270.19 | bwd_inner_microstep: 270.17 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-02 01:44:22,935] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.78 | bwd_microstep: 274.11 | bwd_inner_microstep: 274.09 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 01:44:23,418] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.55 | bwd_microstep: 273.20 | bwd_inner_microstep: 273.18 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 01:44:23,896] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.05 | bwd_microstep: 273.03 | bwd_inner_microstep: 273.01 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 332 +[2025-05-02 01:44:24,122] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 83.01 | bwd_microstep: 126.83 | bwd_inner_microstep: 126.54 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 01:44:24,602] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.82 | bwd_microstep: 273.13 | bwd_inner_microstep: 273.12 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-02 01:44:25,082] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.12 | bwd_microstep: 273.77 | bwd_inner_microstep: 273.76 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 01:44:25,563] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.05 | bwd_microstep: 273.05 | bwd_inner_microstep: 273.04 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 01:44:26,046] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.79 | bwd_microstep: 273.15 | bwd_inner_microstep: 273.13 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 01:44:26,530] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.06 | bwd_microstep: 272.77 | bwd_inner_microstep: 272.75 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:44:27,011] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.70 | bwd_microstep: 272.53 | bwd_inner_microstep: 272.52 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1092 +[2025-05-02 01:44:27,304] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 115.66 | bwd_microstep: 160.95 | bwd_inner_microstep: 160.86 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.11 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 322 +[2025-05-02 01:44:27,534] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 83.19 | bwd_microstep: 131.14 | bwd_inner_microstep: 130.86 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 01:44:28,011] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.50 | bwd_microstep: 272.25 | bwd_inner_microstep: 272.24 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1343 +[2025-05-02 01:44:28,374] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.74 | bwd_microstep: 205.21 | bwd_inner_microstep: 205.15 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 01:44:28,955] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.16 | optimizer_step: 16.43 +[2025-05-02 01:44:28,955] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.55 | bwd_microstep: 349.55 | bwd_inner_microstep: 271.55 | bwd_allreduce_microstep: 77.96 | step_microstep: 24.12 +[2025-05-02 01:44:28,956] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2684.93 | bwd: 3974.96 | bwd_inner: 3896.08 | bwd_allreduce: 78.33 | step: 25.08 + 15%|█▌ | 1332/8720 [3:29:02<14:23:37, 7.01s/it] {'loss': 1.2013, 'grad_norm': 17.9012393951416, 'learning_rate': 9.610284354670958e-06, 'epoch': 1.53} + 15%|█▌ | 1332/8720 [3:29:02<14:23:37, 7.01s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 01:44:29,438] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.23 | bwd_microstep: 270.52 | bwd_inner_microstep: 270.50 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1908 +[2025-05-02 01:44:29,923] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.09 | bwd_microstep: 276.26 | bwd_inner_microstep: 276.25 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1891 +[2025-05-02 01:44:30,407] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.46 | bwd_microstep: 274.84 | bwd_inner_microstep: 274.82 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 01:44:30,887] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.37 | bwd_microstep: 273.01 | bwd_inner_microstep: 272.99 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 01:44:31,371] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.19 | bwd_microstep: 272.99 | bwd_inner_microstep: 272.97 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1353 +[2025-05-02 01:44:31,740] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.00 | bwd_microstep: 206.40 | bwd_inner_microstep: 206.26 | bwd_allreduce_microstep: 0.08 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:44:32,223] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.82 | bwd_microstep: 272.53 | bwd_inner_microstep: 272.51 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:44:32,704] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.26 | bwd_microstep: 272.70 | bwd_inner_microstep: 272.68 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 01:44:33,186] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.04 | bwd_microstep: 272.93 | bwd_inner_microstep: 272.91 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:44:33,666] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.59 | bwd_microstep: 272.57 | bwd_inner_microstep: 272.56 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:44:34,148] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.12 | bwd_microstep: 272.15 | bwd_inner_microstep: 272.13 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 01:44:34,626] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.46 | bwd_microstep: 271.31 | bwd_inner_microstep: 271.29 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 01:44:35,105] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.70 | bwd_microstep: 272.51 | bwd_inner_microstep: 272.49 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.16 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:44:35,582] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.46 | bwd_microstep: 271.57 | bwd_inner_microstep: 271.55 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 01:44:36,059] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.79 | bwd_microstep: 271.15 | bwd_inner_microstep: 271.13 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 01:44:36,625] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.13 | optimizer_step: 16.44 +[2025-05-02 01:44:36,625] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.96 | bwd_microstep: 337.92 | bwd_inner_microstep: 271.69 | bwd_allreduce_microstep: 66.18 | step_microstep: 23.45 +[2025-05-02 01:44:36,626] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2974.13 | bwd: 4361.39 | bwd_inner: 4294.75 | bwd_allreduce: 66.36 | step: 24.51 + 15%|█▌ | 1333/8720 [3:29:10<14:47:40, 7.21s/it] {'loss': 0.8167, 'grad_norm': 14.698409080505371, 'learning_rate': 9.609565209910009e-06, 'epoch': 1.53} + 15%|█▌ | 1333/8720 [3:29:10<14:47:40, 7.21s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1889 +[2025-05-02 01:44:37,109] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.47 | bwd_microstep: 274.04 | bwd_inner_microstep: 274.02 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1963 +[2025-05-02 01:44:37,615] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 199.15 | bwd_microstep: 290.68 | bwd_inner_microstep: 290.66 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1894 +[2025-05-02 01:44:38,094] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.14 | bwd_microstep: 274.94 | bwd_inner_microstep: 274.92 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 872 +[2025-05-02 01:44:38,338] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.82 | bwd_microstep: 134.27 | bwd_inner_microstep: 134.25 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1892 +[2025-05-02 01:44:38,816] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.81 | bwd_microstep: 274.91 | bwd_inner_microstep: 274.89 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-02 01:44:39,296] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.04 | bwd_microstep: 274.61 | bwd_inner_microstep: 274.59 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 01:44:39,774] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.55 | bwd_microstep: 273.18 | bwd_inner_microstep: 273.16 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 01:44:40,252] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.58 | bwd_microstep: 273.25 | bwd_inner_microstep: 273.23 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-02 01:44:40,732] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.93 | bwd_microstep: 273.67 | bwd_inner_microstep: 273.65 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 837 +[2025-05-02 01:44:40,972] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.56 | bwd_microstep: 126.23 | bwd_inner_microstep: 126.21 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 835 +[2025-05-02 01:44:41,209] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.42 | bwd_microstep: 126.06 | bwd_inner_microstep: 125.80 | bwd_allreduce_microstep: 0.14 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 01:44:41,687] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.95 | bwd_microstep: 272.32 | bwd_inner_microstep: 272.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:44:42,166] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.56 | bwd_microstep: 272.45 | bwd_inner_microstep: 272.43 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:44:42,644] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.32 | bwd_microstep: 271.79 | bwd_inner_microstep: 271.77 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:44:43,124] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.27 | bwd_microstep: 271.33 | bwd_inner_microstep: 271.31 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 01:44:43,704] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.19 | optimizer_step: 16.43 +[2025-05-02 01:44:43,704] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.58 | bwd_microstep: 349.45 | bwd_inner_microstep: 271.67 | bwd_allreduce_microstep: 77.73 | step_microstep: 24.32 +[2025-05-02 01:44:43,706] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2746.83 | bwd: 4033.18 | bwd_inner: 3954.87 | bwd_allreduce: 77.93 | step: 25.23 + 15%|█▌ | 1334/8720 [3:29:17<14:42:47, 7.17s/it] {'loss': 0.7414, 'grad_norm': 8.040807723999023, 'learning_rate': 9.608845429197053e-06, 'epoch': 1.53} + 15%|█▌ | 1334/8720 [3:29:17<14:42:47, 7.17s/it]dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 847 +[2025-05-02 01:44:43,953] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.67 | bwd_microstep: 132.26 | bwd_inner_microstep: 132.19 | bwd_allreduce_microstep: 0.03 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1939 +[2025-05-02 01:44:44,452] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 194.82 | bwd_microstep: 288.87 | bwd_inner_microstep: 288.85 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1913 +[2025-05-02 01:44:44,935] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 191.58 | bwd_microstep: 276.34 | bwd_inner_microstep: 276.32 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1927 +[2025-05-02 01:44:45,433] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.08 | bwd_microstep: 287.82 | bwd_inner_microstep: 287.80 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 847 +[2025-05-02 01:44:45,673] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.34 | bwd_microstep: 132.58 | bwd_inner_microstep: 132.34 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-02 01:44:46,149] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.02 | bwd_microstep: 273.51 | bwd_inner_microstep: 273.49 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 01:44:46,626] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.28 | bwd_microstep: 272.99 | bwd_inner_microstep: 272.97 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 01:44:47,103] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.49 | bwd_microstep: 273.16 | bwd_inner_microstep: 273.15 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 01:44:47,581] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.36 | bwd_microstep: 273.36 | bwd_inner_microstep: 273.34 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 01:44:48,059] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.36 | bwd_microstep: 273.10 | bwd_inner_microstep: 273.08 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1092 +[2025-05-02 01:44:48,350] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 115.56 | bwd_microstep: 161.19 | bwd_inner_microstep: 161.04 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 01:44:48,825] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.88 | bwd_microstep: 272.29 | bwd_inner_microstep: 272.27 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.17 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:44:49,302] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.30 | bwd_microstep: 272.57 | bwd_inner_microstep: 272.56 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:44:49,779] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.81 | bwd_microstep: 273.05 | bwd_inner_microstep: 273.03 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:44:50,255] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.03 | bwd_microstep: 271.54 | bwd_inner_microstep: 271.52 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:44:50,836] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.17 | optimizer_step: 16.39 +[2025-05-02 01:44:50,837] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.74 | bwd_microstep: 350.10 | bwd_inner_microstep: 273.19 | bwd_allreduce_microstep: 76.86 | step_microstep: 24.04 +[2025-05-02 01:44:50,838] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2770.03 | bwd: 4084.78 | bwd_inner: 4007.15 | bwd_allreduce: 77.21 | step: 24.99 + 15%|█▌ | 1335/8720 [3:29:24<14:41:13, 7.16s/it] {'loss': 1.1007, 'grad_norm': 7.540387153625488, 'learning_rate': 9.608125012631396e-06, 'epoch': 1.53} + 15%|█▌ | 1335/8720 [3:29:24<14:41:13, 7.16s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:44:51,320] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.53 | bwd_microstep: 270.52 | bwd_inner_microstep: 270.50 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1908 +[2025-05-02 01:44:51,803] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.82 | bwd_microstep: 276.29 | bwd_inner_microstep: 276.27 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-02 01:44:52,284] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.26 | bwd_microstep: 273.68 | bwd_inner_microstep: 273.66 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-02 01:44:52,766] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.26 | bwd_microstep: 274.10 | bwd_inner_microstep: 274.08 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 01:44:53,250] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.60 | bwd_microstep: 273.56 | bwd_inner_microstep: 273.54 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 01:44:53,734] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.20 | bwd_microstep: 273.05 | bwd_inner_microstep: 273.04 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-02 01:44:54,218] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.41 | bwd_microstep: 273.89 | bwd_inner_microstep: 273.87 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:44:54,698] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.98 | bwd_microstep: 272.84 | bwd_inner_microstep: 272.83 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 841 +[2025-05-02 01:44:54,947] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 97.04 | bwd_microstep: 132.31 | bwd_inner_microstep: 132.07 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:44:55,424] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.94 | bwd_microstep: 272.31 | bwd_inner_microstep: 272.29 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 01:44:55,905] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.38 | bwd_microstep: 272.49 | bwd_inner_microstep: 272.48 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 01:44:56,389] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.74 | bwd_microstep: 272.81 | bwd_inner_microstep: 272.79 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 01:44:56,870] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.46 | bwd_microstep: 273.12 | bwd_inner_microstep: 273.11 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:44:57,349] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.34 | bwd_microstep: 272.61 | bwd_inner_microstep: 272.59 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 01:44:57,830] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.87 | bwd_microstep: 272.77 | bwd_inner_microstep: 272.75 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 835 +[2025-05-02 01:44:58,196] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.12 | optimizer_step: 16.45 +[2025-05-02 01:44:58,197] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 99.09 | bwd_microstep: 222.21 | bwd_inner_microstep: 145.38 | bwd_allreduce_microstep: 76.73 | step_microstep: 24.18 +[2025-05-02 01:44:58,198] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2840.48 | bwd: 4178.60 | bwd_inner: 4101.28 | bwd_allreduce: 76.91 | step: 25.03 + 15%|█▌ | 1336/8720 [3:29:31<14:48:30, 7.22s/it] {'loss': 0.6395, 'grad_norm': 9.104426383972168, 'learning_rate': 9.607403960312427e-06, 'epoch': 1.53} + 15%|█▌ | 1336/8720 [3:29:31<14:48:30, 7.22s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 01:44:58,681] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.22 | bwd_microstep: 271.52 | bwd_inner_microstep: 271.50 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2101 +[2025-05-02 01:44:59,209] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 204.74 | bwd_microstep: 306.03 | bwd_inner_microstep: 306.02 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1886 +[2025-05-02 01:44:59,688] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.70 | bwd_microstep: 274.60 | bwd_inner_microstep: 274.58 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1886 +[2025-05-02 01:45:00,167] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.93 | bwd_microstep: 274.45 | bwd_inner_microstep: 274.43 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1353 +[2025-05-02 01:45:00,530] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.69 | bwd_microstep: 206.24 | bwd_inner_microstep: 206.23 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-02 01:45:01,010] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.33 | bwd_microstep: 273.68 | bwd_inner_microstep: 273.67 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 01:45:01,490] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.82 | bwd_microstep: 273.04 | bwd_inner_microstep: 273.02 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:45:01,971] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.07 | bwd_microstep: 272.64 | bwd_inner_microstep: 272.62 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:45:02,454] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.00 | bwd_microstep: 272.56 | bwd_inner_microstep: 272.54 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 01:45:02,934] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.23 | bwd_microstep: 272.96 | bwd_inner_microstep: 272.95 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:45:03,412] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.04 | bwd_microstep: 271.44 | bwd_inner_microstep: 271.43 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:45:03,890] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.63 | bwd_microstep: 271.52 | bwd_inner_microstep: 271.50 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 318 +[2025-05-02 01:45:04,109] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 81.75 | bwd_microstep: 121.81 | bwd_inner_microstep: 121.52 | bwd_allreduce_microstep: 0.14 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:45:04,586] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.96 | bwd_microstep: 271.29 | bwd_inner_microstep: 271.28 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1084 +[2025-05-02 01:45:04,881] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 117.55 | bwd_microstep: 159.84 | bwd_inner_microstep: 159.83 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 01:45:05,459] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.16 | optimizer_step: 16.53 +[2025-05-02 01:45:05,459] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.47 | bwd_microstep: 348.81 | bwd_inner_microstep: 271.47 | bwd_allreduce_microstep: 77.28 | step_microstep: 24.09 +[2025-05-02 01:45:05,460] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2807.79 | bwd: 4142.48 | bwd_inner: 4064.64 | bwd_allreduce: 77.48 | step: 24.95 + 15%|█▌ | 1337/8720 [3:29:39<14:49:54, 7.23s/it] {'loss': 0.6636, 'grad_norm': 7.565845966339111, 'learning_rate': 9.606682272339624e-06, 'epoch': 1.53} + 15%|█▌ | 1337/8720 [3:29:39<14:49:54, 7.23s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1946 +[2025-05-02 01:45:05,965] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.28 | bwd_microstep: 288.47 | bwd_inner_microstep: 288.45 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 377 +[2025-05-02 01:45:06,177] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 75.76 | bwd_microstep: 120.97 | bwd_inner_microstep: 120.69 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 378 +[2025-05-02 01:45:06,389] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 81.34 | bwd_microstep: 116.70 | bwd_inner_microstep: 116.45 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1893 +[2025-05-02 01:45:06,868] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.53 | bwd_microstep: 275.06 | bwd_inner_microstep: 275.04 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1896 +[2025-05-02 01:45:07,347] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.24 | bwd_microstep: 275.18 | bwd_inner_microstep: 275.16 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1883 +[2025-05-02 01:45:07,826] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.76 | bwd_microstep: 274.38 | bwd_inner_microstep: 274.36 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 01:45:08,304] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.37 | bwd_microstep: 273.20 | bwd_inner_microstep: 273.18 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 01:45:08,780] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.38 | bwd_microstep: 272.90 | bwd_inner_microstep: 272.88 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 846 +[2025-05-02 01:45:09,028] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 98.88 | bwd_microstep: 132.36 | bwd_inner_microstep: 132.21 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 01:45:09,506] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.71 | bwd_microstep: 272.39 | bwd_inner_microstep: 272.38 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 01:45:09,983] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.10 | bwd_microstep: 272.33 | bwd_inner_microstep: 272.31 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 321 +[2025-05-02 01:45:10,211] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 92.87 | bwd_microstep: 117.76 | bwd_inner_microstep: 117.44 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 319 +[2025-05-02 01:45:10,428] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 80.61 | bwd_microstep: 120.65 | bwd_inner_microstep: 120.48 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:45:10,904] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.37 | bwd_microstep: 271.18 | bwd_inner_microstep: 271.16 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 01:45:11,380] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.66 | bwd_microstep: 271.03 | bwd_inner_microstep: 271.01 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 01:45:11,969] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.22 | optimizer_step: 16.63 +[2025-05-02 01:45:11,969] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.77 | bwd_microstep: 356.69 | bwd_inner_microstep: 271.29 | bwd_allreduce_microstep: 85.36 | step_microstep: 24.59 +[2025-05-02 01:45:11,971] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2506.30 | bwd: 3711.34 | bwd_inner: 3624.71 | bwd_allreduce: 85.88 | step: 25.53 + 15%|█▌ | 1338/8720 [3:29:45<14:23:11, 7.02s/it] {'loss': 0.8584, 'grad_norm': 13.985496520996094, 'learning_rate': 9.605959948812555e-06, 'epoch': 1.53} + 15%|█▌ | 1338/8720 [3:29:45<14:23:11, 7.02s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1896 +[2025-05-02 01:45:12,457] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.34 | bwd_microstep: 274.29 | bwd_inner_microstep: 274.28 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 378 +[2025-05-02 01:45:12,690] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 87.63 | bwd_microstep: 128.62 | bwd_inner_microstep: 128.27 | bwd_allreduce_microstep: 0.16 | step_microstep: 0.14 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 367 +[2025-05-02 01:45:12,921] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 92.61 | bwd_microstep: 122.55 | bwd_inner_microstep: 122.39 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1367 +[2025-05-02 01:45:13,288] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.92 | bwd_microstep: 207.48 | bwd_inner_microstep: 207.31 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.10 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 839 +[2025-05-02 01:45:13,532] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.04 | bwd_microstep: 132.11 | bwd_inner_microstep: 132.03 | bwd_allreduce_microstep: 0.04 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 01:45:14,012] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.11 | bwd_microstep: 272.94 | bwd_inner_microstep: 272.92 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 848 +[2025-05-02 01:45:14,255] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.84 | bwd_microstep: 132.50 | bwd_inner_microstep: 132.24 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-02 01:45:14,735] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.00 | bwd_microstep: 273.12 | bwd_inner_microstep: 273.10 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-02 01:45:15,214] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.76 | bwd_microstep: 273.71 | bwd_inner_microstep: 273.69 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:45:15,694] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.41 | bwd_microstep: 272.63 | bwd_inner_microstep: 272.61 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:45:16,175] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.79 | bwd_microstep: 272.39 | bwd_inner_microstep: 272.37 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 834 +[2025-05-02 01:45:16,418] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 97.50 | bwd_microstep: 125.68 | bwd_inner_microstep: 125.43 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:45:16,896] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.59 | bwd_microstep: 272.24 | bwd_inner_microstep: 272.23 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:45:17,373] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.93 | bwd_microstep: 271.28 | bwd_inner_microstep: 271.26 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 01:45:17,852] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.23 | bwd_microstep: 272.30 | bwd_inner_microstep: 272.28 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:45:18,432] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.21 | optimizer_step: 16.69 +[2025-05-02 01:45:18,433] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.49 | bwd_microstep: 349.48 | bwd_inner_microstep: 271.86 | bwd_allreduce_microstep: 77.56 | step_microstep: 24.65 +[2025-05-02 01:45:18,434] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2494.83 | bwd: 3653.44 | bwd_inner: 3574.37 | bwd_allreduce: 78.24 | step: 25.75 + 15%|█▌ | 1339/8720 [3:29:52<14:02:41, 6.85s/it] {'loss': 0.7198, 'grad_norm': 8.336788177490234, 'learning_rate': 9.605236989830873e-06, 'epoch': 1.54} + 15%|█▌ | 1339/8720 [3:29:52<14:02:41, 6.85s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1887 +[2025-05-02 01:45:18,920] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.96 | bwd_microstep: 273.74 | bwd_inner_microstep: 273.72 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 1105 +[2025-05-02 01:45:19,204] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 107.19 | bwd_microstep: 161.99 | bwd_inner_microstep: 161.72 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2116 +[2025-05-02 01:45:19,738] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 204.96 | bwd_microstep: 312.50 | bwd_inner_microstep: 312.48 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.15 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-02 01:45:20,218] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.68 | bwd_microstep: 273.96 | bwd_inner_microstep: 273.94 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-02 01:45:20,700] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.34 | bwd_microstep: 273.14 | bwd_inner_microstep: 273.13 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 345 +[2025-05-02 01:45:20,939] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 97.98 | bwd_microstep: 119.42 | bwd_inner_microstep: 119.15 | bwd_allreduce_microstep: 0.08 | step_microstep: 0.12 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 840 +[2025-05-02 01:45:21,194] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 105.53 | bwd_microstep: 126.09 | bwd_inner_microstep: 125.91 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 01:45:21,674] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.76 | bwd_microstep: 272.74 | bwd_inner_microstep: 272.73 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 01:45:22,155] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.02 | bwd_microstep: 273.00 | bwd_inner_microstep: 272.98 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:45:22,635] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.02 | bwd_microstep: 272.19 | bwd_inner_microstep: 272.17 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:45:23,115] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.06 | bwd_microstep: 272.25 | bwd_inner_microstep: 272.23 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:45:23,593] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.60 | bwd_microstep: 272.18 | bwd_inner_microstep: 272.16 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.15 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:45:24,070] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.22 | bwd_microstep: 272.54 | bwd_inner_microstep: 272.52 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:45:24,549] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.90 | bwd_microstep: 271.33 | bwd_inner_microstep: 271.31 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1342 +[2025-05-02 01:45:24,912] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.34 | bwd_microstep: 204.88 | bwd_inner_microstep: 204.82 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.10 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1343 +[2025-05-02 01:45:25,377] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.20 | optimizer_step: 16.59 +[2025-05-02 01:45:25,378] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.68 | bwd_microstep: 283.32 | bwd_inner_microstep: 204.97 | bwd_allreduce_microstep: 78.27 | step_microstep: 24.59 +[2025-05-02 01:45:25,379] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2680.85 | bwd: 3935.33 | bwd_inner: 3856.03 | bwd_allreduce: 78.65 | step: 25.90 + 15%|█▌ | 1340/8720 [3:29:59<14:06:04, 6.88s/it] {'loss': 0.7672, 'grad_norm': 6.311938762664795, 'learning_rate': 9.604513395494323e-06, 'epoch': 1.54} + 15%|█▌ | 1340/8720 [3:29:59<14:06:04, 6.88s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 01:45:25,863] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.86 | bwd_microstep: 271.02 | bwd_inner_microstep: 271.00 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1930 +[2025-05-02 01:45:26,364] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 196.12 | bwd_microstep: 287.58 | bwd_inner_microstep: 287.57 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1899 +[2025-05-02 01:45:26,850] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.83 | bwd_microstep: 275.30 | bwd_inner_microstep: 275.28 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1371 +[2025-05-02 01:45:27,216] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.55 | bwd_microstep: 207.12 | bwd_inner_microstep: 207.10 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-02 01:45:27,697] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.58 | bwd_microstep: 274.44 | bwd_inner_microstep: 274.42 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-02 01:45:28,178] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.74 | bwd_microstep: 273.63 | bwd_inner_microstep: 273.62 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-02 01:45:28,659] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.89 | bwd_microstep: 273.87 | bwd_inner_microstep: 273.86 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 01:45:29,139] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.73 | bwd_microstep: 273.43 | bwd_inner_microstep: 273.41 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 01:45:29,618] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.54 | bwd_microstep: 273.22 | bwd_inner_microstep: 273.20 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 01:45:30,096] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.14 | bwd_microstep: 272.82 | bwd_inner_microstep: 272.80 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 01:45:30,576] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.54 | bwd_microstep: 272.98 | bwd_inner_microstep: 272.96 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.05 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 333 +[2025-05-02 01:45:30,792] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 81.20 | bwd_microstep: 118.95 | bwd_inner_microstep: 118.69 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 01:45:31,270] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.08 | bwd_microstep: 272.76 | bwd_inner_microstep: 272.74 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:45:31,746] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.49 | bwd_microstep: 272.64 | bwd_inner_microstep: 272.62 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.06 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1346 +[2025-05-02 01:45:32,108] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.55 | bwd_microstep: 205.38 | bwd_inner_microstep: 205.37 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:45:32,676] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.38 | optimizer_step: 16.95 +[2025-05-02 01:45:32,676] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.04 | bwd_microstep: 339.63 | bwd_inner_microstep: 272.55 | bwd_allreduce_microstep: 67.03 | step_microstep: 24.34 +[2025-05-02 01:45:32,677] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2823.56 | bwd: 4164.83 | bwd_inner: 4097.27 | bwd_allreduce: 67.19 | step: 25.42 + 15%|█▌ | 1341/8720 [3:30:06<14:21:22, 7.00s/it] {'loss': 0.6108, 'grad_norm': 8.08592700958252, 'learning_rate': 9.603789165902732e-06, 'epoch': 1.54} + 15%|█▌ | 1341/8720 [3:30:06<14:21:22, 7.00s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 01:45:33,156] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.28 | bwd_microstep: 270.75 | bwd_inner_microstep: 270.73 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1921 +[2025-05-02 01:45:33,653] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 194.62 | bwd_microstep: 287.17 | bwd_inner_microstep: 287.16 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1883 +[2025-05-02 01:45:34,131] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.51 | bwd_microstep: 274.23 | bwd_inner_microstep: 274.21 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 01:45:34,608] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.11 | bwd_microstep: 273.09 | bwd_inner_microstep: 273.08 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 01:45:35,085] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.07 | bwd_microstep: 272.83 | bwd_inner_microstep: 272.81 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:45:35,562] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.22 | bwd_microstep: 272.77 | bwd_inner_microstep: 272.75 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 01:45:36,039] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.85 | bwd_microstep: 273.09 | bwd_inner_microstep: 273.08 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:45:36,516] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.40 | bwd_microstep: 272.65 | bwd_inner_microstep: 272.64 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:45:36,991] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.96 | bwd_microstep: 272.36 | bwd_inner_microstep: 272.34 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:45:37,468] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.27 | bwd_microstep: 272.69 | bwd_inner_microstep: 272.67 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:45:37,944] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.01 | bwd_microstep: 272.79 | bwd_inner_microstep: 272.78 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:45:38,424] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.00 | bwd_microstep: 272.67 | bwd_inner_microstep: 272.65 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:45:38,905] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.73 | bwd_microstep: 271.23 | bwd_inner_microstep: 271.22 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 01:45:39,386] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.90 | bwd_microstep: 271.08 | bwd_inner_microstep: 271.06 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 01:45:39,863] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.33 | bwd_microstep: 271.18 | bwd_inner_microstep: 271.16 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 315 +[2025-05-02 01:45:40,217] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.20 | optimizer_step: 16.54 +[2025-05-02 01:45:40,217] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 88.49 | bwd_microstep: 225.05 | bwd_inner_microstep: 147.78 | bwd_allreduce_microstep: 77.17 | step_microstep: 24.20 +[2025-05-02 01:45:40,219] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2923.42 | bwd: 4325.67 | bwd_inner: 4248.15 | bwd_allreduce: 77.24 | step: 24.90 + 15%|█▌ | 1342/8720 [3:30:13<14:41:08, 7.17s/it] {'loss': 0.704, 'grad_norm': 10.945293426513672, 'learning_rate': 9.603064301156018e-06, 'epoch': 1.54} + 15%|█▌ | 1342/8720 [3:30:13<14:41:08, 7.17s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1850 +[2025-05-02 01:45:40,700] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.33 | bwd_microstep: 270.42 | bwd_inner_microstep: 270.40 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1940 +[2025-05-02 01:45:41,202] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 196.51 | bwd_microstep: 288.59 | bwd_inner_microstep: 288.58 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 01:45:41,683] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.98 | bwd_microstep: 273.73 | bwd_inner_microstep: 273.72 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1886 +[2025-05-02 01:45:42,163] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.00 | bwd_microstep: 274.59 | bwd_inner_microstep: 274.57 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1883 +[2025-05-02 01:45:42,642] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.93 | bwd_microstep: 274.38 | bwd_inner_microstep: 274.37 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 01:45:43,120] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.52 | bwd_microstep: 273.57 | bwd_inner_microstep: 273.55 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 333 +[2025-05-02 01:45:43,331] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 76.85 | bwd_microstep: 120.68 | bwd_inner_microstep: 120.39 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 01:45:43,807] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.75 | bwd_microstep: 273.14 | bwd_inner_microstep: 273.13 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 01:45:44,286] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.22 | bwd_microstep: 273.02 | bwd_inner_microstep: 273.00 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 01:45:44,766] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.28 | bwd_microstep: 272.21 | bwd_inner_microstep: 272.19 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:45:45,248] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.86 | bwd_microstep: 272.43 | bwd_inner_microstep: 272.41 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:45:45,725] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.27 | bwd_microstep: 271.21 | bwd_inner_microstep: 271.20 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.16 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:45:46,207] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.34 | bwd_microstep: 272.13 | bwd_inner_microstep: 272.11 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:45:46,684] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.45 | bwd_microstep: 271.31 | bwd_inner_microstep: 271.29 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:45:47,164] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.22 | bwd_microstep: 271.37 | bwd_inner_microstep: 271.36 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 01:45:47,743] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.16 | optimizer_step: 16.90 +[2025-05-02 01:45:47,744] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.68 | bwd_microstep: 348.79 | bwd_inner_microstep: 271.60 | bwd_allreduce_microstep: 77.13 | step_microstep: 24.67 +[2025-05-02 01:45:47,745] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2914.82 | bwd: 4301.61 | bwd_inner: 4223.93 | bwd_allreduce: 77.34 | step: 25.56 + 15%|█▌ | 1343/8720 [3:30:21<14:54:19, 7.27s/it] {'loss': 0.6778, 'grad_norm': 7.689907550811768, 'learning_rate': 9.602338801354187e-06, 'epoch': 1.54} + 15%|█▌ | 1343/8720 [3:30:21<14:54:19, 7.27s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 01:45:48,226] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.78 | bwd_microstep: 270.12 | bwd_inner_microstep: 270.10 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1954 +[2025-05-02 01:45:48,732] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 198.05 | bwd_microstep: 289.98 | bwd_inner_microstep: 289.96 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-02 01:45:49,212] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.80 | bwd_microstep: 273.38 | bwd_inner_microstep: 273.36 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1105 +[2025-05-02 01:45:49,505] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 115.34 | bwd_microstep: 161.87 | bwd_inner_microstep: 161.85 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-02 01:45:49,985] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.80 | bwd_microstep: 273.68 | bwd_inner_microstep: 273.66 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1889 +[2025-05-02 01:45:50,468] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.49 | bwd_microstep: 274.66 | bwd_inner_microstep: 274.64 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 01:45:50,952] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.50 | bwd_microstep: 273.49 | bwd_inner_microstep: 273.48 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-02 01:45:51,433] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.88 | bwd_microstep: 273.72 | bwd_inner_microstep: 273.70 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 838 +[2025-05-02 01:45:51,671] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.31 | bwd_microstep: 126.26 | bwd_inner_microstep: 126.23 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 01:45:52,149] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.20 | bwd_microstep: 272.70 | bwd_inner_microstep: 272.68 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:45:52,626] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.13 | bwd_microstep: 272.31 | bwd_inner_microstep: 272.30 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 01:45:53,105] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.78 | bwd_microstep: 272.26 | bwd_inner_microstep: 272.24 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 01:45:53,580] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.39 | bwd_microstep: 272.35 | bwd_inner_microstep: 272.33 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 01:45:54,056] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.07 | bwd_microstep: 271.56 | bwd_inner_microstep: 271.54 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:45:54,534] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.35 | bwd_microstep: 272.41 | bwd_inner_microstep: 272.39 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 01:45:55,101] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.04 | optimizer_gradients: 2.15 | optimizer_step: 16.50 +[2025-05-02 01:45:55,101] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.12 | bwd_microstep: 340.46 | bwd_inner_microstep: 271.64 | bwd_allreduce_microstep: 68.78 | step_microstep: 23.41 +[2025-05-02 01:45:55,102] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2858.60 | bwd: 4191.24 | bwd_inner: 4122.11 | bwd_allreduce: 68.87 | step: 24.24 + 15%|█▌ | 1344/8720 [3:30:28<14:57:12, 7.30s/it] {'loss': 0.8673, 'grad_norm': 13.620467185974121, 'learning_rate': 9.601612666597329e-06, 'epoch': 1.54} + 15%|█▌ | 1344/8720 [3:30:28<14:57:12, 7.30s/it]dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 827 +[2025-05-02 01:45:55,344] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.08 | bwd_microstep: 129.95 | bwd_inner_microstep: 129.72 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2084 +[2025-05-02 01:45:55,868] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 204.01 | bwd_microstep: 304.75 | bwd_inner_microstep: 304.74 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1940 +[2025-05-02 01:45:56,367] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.44 | bwd_microstep: 288.88 | bwd_inner_microstep: 288.86 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1902 +[2025-05-02 01:45:56,849] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.28 | bwd_microstep: 275.59 | bwd_inner_microstep: 275.57 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 351 +[2025-05-02 01:45:57,067] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 86.49 | bwd_microstep: 116.20 | bwd_inner_microstep: 115.96 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 855 +[2025-05-02 01:45:57,311] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.60 | bwd_microstep: 133.60 | bwd_inner_microstep: 133.50 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1360 +[2025-05-02 01:45:57,675] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.83 | bwd_microstep: 206.55 | bwd_inner_microstep: 206.53 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 01:45:58,153] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.75 | bwd_microstep: 272.97 | bwd_inner_microstep: 272.95 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 01:45:58,632] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.86 | bwd_microstep: 273.08 | bwd_inner_microstep: 273.06 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 01:45:59,108] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.36 | bwd_microstep: 272.73 | bwd_inner_microstep: 272.71 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:45:59,583] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.97 | bwd_microstep: 272.20 | bwd_inner_microstep: 272.18 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 01:46:00,060] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.13 | bwd_microstep: 272.22 | bwd_inner_microstep: 272.20 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 01:46:00,537] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.14 | bwd_microstep: 272.43 | bwd_inner_microstep: 272.41 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1349 +[2025-05-02 01:46:00,900] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.67 | bwd_microstep: 205.99 | bwd_inner_microstep: 205.98 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:46:01,377] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.84 | bwd_microstep: 272.29 | bwd_inner_microstep: 272.27 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:46:01,951] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.04 | optimizer_gradients: 2.14 | optimizer_step: 16.53 +[2025-05-02 01:46:01,951] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.62 | bwd_microstep: 344.92 | bwd_inner_microstep: 271.96 | bwd_allreduce_microstep: 72.92 | step_microstep: 23.46 +[2025-05-02 01:46:01,952] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2654.77 | bwd: 3914.40 | bwd_inner: 3840.74 | bwd_allreduce: 73.17 | step: 24.48 + 15%|█▌ | 1345/8720 [3:30:35<14:40:33, 7.16s/it] {'loss': 0.8385, 'grad_norm': 12.771524429321289, 'learning_rate': 9.600885896985625e-06, 'epoch': 1.54} + 15%|█▌ | 1345/8720 [3:30:35<14:40:33, 7.16s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:46:02,431] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.47 | bwd_microstep: 270.50 | bwd_inner_microstep: 270.48 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1915 +[2025-05-02 01:46:02,912] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.79 | bwd_microstep: 276.38 | bwd_inner_microstep: 276.36 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1890 +[2025-05-02 01:46:03,392] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.36 | bwd_microstep: 274.86 | bwd_inner_microstep: 274.84 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-02 01:46:03,871] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.31 | bwd_microstep: 274.28 | bwd_inner_microstep: 274.27 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 01:46:04,348] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.67 | bwd_microstep: 273.26 | bwd_inner_microstep: 273.24 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1356 +[2025-05-02 01:46:04,709] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.60 | bwd_microstep: 206.57 | bwd_inner_microstep: 206.47 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 332 +[2025-05-02 01:46:04,932] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 81.99 | bwd_microstep: 125.97 | bwd_inner_microstep: 125.82 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 01:46:05,410] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.04 | bwd_microstep: 272.29 | bwd_inner_microstep: 272.28 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 321 +[2025-05-02 01:46:05,636] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 81.45 | bwd_microstep: 128.57 | bwd_inner_microstep: 128.32 | bwd_allreduce_microstep: 0.10 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:46:06,114] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.73 | bwd_microstep: 272.77 | bwd_inner_microstep: 272.75 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1343 +[2025-05-02 01:46:06,478] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.34 | bwd_microstep: 204.71 | bwd_inner_microstep: 204.63 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:46:06,957] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.77 | bwd_microstep: 272.51 | bwd_inner_microstep: 272.49 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:46:07,437] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.80 | bwd_microstep: 272.49 | bwd_inner_microstep: 272.47 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 01:46:07,918] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.54 | bwd_microstep: 272.87 | bwd_inner_microstep: 272.86 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.12 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 318 +[2025-05-02 01:46:08,132] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 83.27 | bwd_microstep: 115.07 | bwd_inner_microstep: 114.93 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:46:08,709] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.16 | optimizer_step: 16.54 +[2025-05-02 01:46:08,710] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.17 | bwd_microstep: 348.84 | bwd_inner_microstep: 272.06 | bwd_allreduce_microstep: 76.73 | step_microstep: 23.98 +[2025-05-02 01:46:08,711] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2606.00 | bwd: 3862.05 | bwd_inner: 3784.40 | bwd_allreduce: 77.05 | step: 25.14 + 15%|█▌ | 1346/8720 [3:30:42<14:25:29, 7.04s/it] {'loss': 0.6791, 'grad_norm': 9.704886436462402, 'learning_rate': 9.600158492619344e-06, 'epoch': 1.54} + 15%|█▌ | 1346/8720 [3:30:42<14:25:29, 7.04s/it]dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 828 +[2025-05-02 01:46:08,952] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 92.58 | bwd_microstep: 130.11 | bwd_inner_microstep: 129.98 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1983 +[2025-05-02 01:46:09,457] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 198.39 | bwd_microstep: 292.36 | bwd_inner_microstep: 292.35 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-02 01:46:09,937] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.25 | bwd_microstep: 274.13 | bwd_inner_microstep: 274.12 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1883 +[2025-05-02 01:46:10,418] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.72 | bwd_microstep: 274.29 | bwd_inner_microstep: 274.27 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1887 +[2025-05-02 01:46:10,900] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.45 | bwd_microstep: 274.55 | bwd_inner_microstep: 274.54 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1096 +[2025-05-02 01:46:11,193] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 115.32 | bwd_microstep: 161.23 | bwd_inner_microstep: 161.22 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-02 01:46:11,672] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.39 | bwd_microstep: 273.35 | bwd_inner_microstep: 273.33 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.11 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 860 +[2025-05-02 01:46:11,919] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 96.36 | bwd_microstep: 133.80 | bwd_inner_microstep: 133.62 | bwd_allreduce_microstep: 0.10 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-02 01:46:12,397] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.99 | bwd_microstep: 273.56 | bwd_inner_microstep: 273.54 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 01:46:12,876] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.46 | bwd_microstep: 272.97 | bwd_inner_microstep: 272.95 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 01:46:13,356] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.20 | bwd_microstep: 272.72 | bwd_inner_microstep: 272.71 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-02 01:46:13,837] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.83 | bwd_microstep: 273.78 | bwd_inner_microstep: 273.77 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1092 +[2025-05-02 01:46:14,131] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 115.38 | bwd_microstep: 161.10 | bwd_inner_microstep: 161.09 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:46:14,613] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.44 | bwd_microstep: 273.05 | bwd_inner_microstep: 273.03 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:46:15,093] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.56 | bwd_microstep: 272.82 | bwd_inner_microstep: 272.80 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:46:15,672] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.12 | optimizer_step: 16.59 +[2025-05-02 01:46:15,672] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.94 | bwd_microstep: 348.93 | bwd_inner_microstep: 273.55 | bwd_allreduce_microstep: 75.34 | step_microstep: 23.72 +[2025-05-02 01:46:15,674] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2701.91 | bwd: 3962.84 | bwd_inner: 3886.89 | bwd_allreduce: 75.58 | step: 24.83 + 15%|█▌ | 1347/8720 [3:30:49<14:22:26, 7.02s/it] {'loss': 0.841, 'grad_norm': 5.810220241546631, 'learning_rate': 9.599430453598842e-06, 'epoch': 1.54} + 15%|█▌ | 1347/8720 [3:30:49<14:22:26, 7.02s/it]dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1337 +[2025-05-02 01:46:16,039] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 142.79 | bwd_microstep: 203.92 | bwd_inner_microstep: 203.71 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.08 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 451 +[2025-05-02 01:46:16,242] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 73.51 | bwd_microstep: 115.93 | bwd_inner_microstep: 115.80 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1967 +[2025-05-02 01:46:16,746] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 197.52 | bwd_microstep: 290.72 | bwd_inner_microstep: 290.70 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 01:46:17,221] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.08 | bwd_microstep: 272.41 | bwd_inner_microstep: 272.39 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:46:17,695] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.58 | bwd_microstep: 272.38 | bwd_inner_microstep: 272.36 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:46:18,171] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.49 | bwd_microstep: 272.42 | bwd_inner_microstep: 272.40 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:46:18,647] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.86 | bwd_microstep: 272.42 | bwd_inner_microstep: 272.40 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 01:46:19,123] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.26 | bwd_microstep: 272.65 | bwd_inner_microstep: 272.63 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 01:46:19,599] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.13 | bwd_microstep: 272.71 | bwd_inner_microstep: 272.69 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:46:20,074] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.05 | bwd_microstep: 272.26 | bwd_inner_microstep: 272.24 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:46:20,549] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.53 | bwd_microstep: 272.12 | bwd_inner_microstep: 272.10 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:46:21,023] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.05 | bwd_microstep: 271.25 | bwd_inner_microstep: 271.23 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:46:21,496] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.53 | bwd_microstep: 270.87 | bwd_inner_microstep: 270.85 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:46:21,970] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.84 | bwd_microstep: 271.10 | bwd_inner_microstep: 271.09 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:46:22,444] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.18 | bwd_microstep: 271.16 | bwd_inner_microstep: 271.14 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 01:46:23,020] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.19 | optimizer_step: 16.70 +[2025-05-02 01:46:23,020] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.28 | bwd_microstep: 348.74 | bwd_inner_microstep: 271.77 | bwd_allreduce_microstep: 76.92 | step_microstep: 24.56 +[2025-05-02 01:46:23,022] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2858.43 | bwd: 4223.08 | bwd_inner: 4145.53 | bwd_allreduce: 77.17 | step: 25.27 + 15%|█▌ | 1348/8720 [3:30:56<14:34:33, 7.12s/it] {'loss': 0.3614, 'grad_norm': 5.24542760848999, 'learning_rate': 9.59870178002456e-06, 'epoch': 1.55} + 15%|█▌ | 1348/8720 [3:30:56<14:34:33, 7.12s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1888 +[2025-05-02 01:46:23,509] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.78 | bwd_microstep: 273.98 | bwd_inner_microstep: 273.97 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1952 +[2025-05-02 01:46:24,011] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 196.77 | bwd_microstep: 288.91 | bwd_inner_microstep: 288.89 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 391 +[2025-05-02 01:46:24,229] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 88.43 | bwd_microstep: 115.55 | bwd_inner_microstep: 115.25 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 388 +[2025-05-02 01:46:24,450] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 85.41 | bwd_microstep: 119.01 | bwd_inner_microstep: 118.68 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 351 +[2025-05-02 01:46:24,705] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 89.43 | bwd_microstep: 149.68 | bwd_inner_microstep: 149.42 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 01:46:25,185] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.82 | bwd_microstep: 273.64 | bwd_inner_microstep: 273.62 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 841 +[2025-05-02 01:46:25,428] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.18 | bwd_microstep: 132.04 | bwd_inner_microstep: 131.74 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 336 +[2025-05-02 01:46:25,655] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.65 | bwd_microstep: 116.84 | bwd_inner_microstep: 116.68 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 837 +[2025-05-02 01:46:25,898] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.63 | bwd_microstep: 132.26 | bwd_inner_microstep: 132.05 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:46:26,375] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.56 | bwd_microstep: 272.26 | bwd_inner_microstep: 272.24 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 01:46:26,855] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.43 | bwd_microstep: 272.28 | bwd_inner_microstep: 272.27 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 322 +[2025-05-02 01:46:27,100] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.58 | bwd_microstep: 127.59 | bwd_inner_microstep: 127.44 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:46:27,577] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.98 | bwd_microstep: 272.27 | bwd_inner_microstep: 272.25 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:46:28,058] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.76 | bwd_microstep: 272.19 | bwd_inner_microstep: 272.17 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:46:28,534] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.79 | bwd_microstep: 271.04 | bwd_inner_microstep: 271.02 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 01:46:29,104] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.19 | optimizer_step: 16.68 +[2025-05-02 01:46:29,105] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.91 | bwd_microstep: 341.42 | bwd_inner_microstep: 271.46 | bwd_allreduce_microstep: 69.92 | step_microstep: 23.99 +[2025-05-02 01:46:29,106] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2342.73 | bwd: 3431.10 | bwd_inner: 3359.45 | bwd_allreduce: 70.65 | step: 25.11 + 15%|█▌ | 1349/8720 [3:31:02<13:56:16, 6.81s/it] {'loss': 0.8109, 'grad_norm': 6.137126922607422, 'learning_rate': 9.597972471997028e-06, 'epoch': 1.55} + 15%|█▌ | 1349/8720 [3:31:02<13:56:16, 6.81s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 315 +[2025-05-02 01:46:29,313] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 68.71 | bwd_microstep: 119.58 | bwd_inner_microstep: 119.45 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1971 +[2025-05-02 01:46:29,817] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 197.88 | bwd_microstep: 291.01 | bwd_inner_microstep: 290.99 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-02 01:46:30,295] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.07 | bwd_microstep: 274.32 | bwd_inner_microstep: 274.31 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-02 01:46:30,771] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.09 | bwd_microstep: 272.84 | bwd_inner_microstep: 272.82 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 01:46:31,250] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.23 | bwd_microstep: 273.26 | bwd_inner_microstep: 273.24 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 01:46:31,727] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.86 | bwd_microstep: 273.17 | bwd_inner_microstep: 273.15 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 840 +[2025-05-02 01:46:31,961] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 92.81 | bwd_microstep: 126.26 | bwd_inner_microstep: 126.14 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 01:46:32,438] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.84 | bwd_microstep: 272.79 | bwd_inner_microstep: 272.77 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:46:32,912] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.54 | bwd_microstep: 272.11 | bwd_inner_microstep: 272.09 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:46:33,388] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.17 | bwd_microstep: 272.44 | bwd_inner_microstep: 272.42 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 328 +[2025-05-02 01:46:33,603] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 78.42 | bwd_microstep: 120.39 | bwd_inner_microstep: 120.27 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 835 +[2025-05-02 01:46:33,839] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.86 | bwd_microstep: 126.22 | bwd_inner_microstep: 126.07 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:46:34,317] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.17 | bwd_microstep: 272.33 | bwd_inner_microstep: 272.32 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:46:34,796] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.31 | bwd_microstep: 271.32 | bwd_inner_microstep: 271.31 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 832 +[2025-05-02 01:46:35,051] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 102.76 | bwd_microstep: 129.89 | bwd_inner_microstep: 129.60 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 01:46:35,631] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.20 | optimizer_step: 16.71 +[2025-05-02 01:46:35,631] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.40 | bwd_microstep: 346.86 | bwd_inner_microstep: 271.33 | bwd_allreduce_microstep: 75.47 | step_microstep: 24.73 +[2025-05-02 01:46:35,633] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2516.81 | bwd: 3714.89 | bwd_inner: 3638.39 | bwd_allreduce: 75.87 | step: 25.76 + 15%|█▌ | 1350/8720 [3:31:09<13:45:52, 6.72s/it] {'loss': 0.6298, 'grad_norm': 9.333969116210938, 'learning_rate': 9.597242529616866e-06, 'epoch': 1.55} + 15%|█▌ | 1350/8720 [3:31:09<13:45:52, 6.72s/it]dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 827 +[2025-05-02 01:46:35,884] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 92.63 | bwd_microstep: 136.77 | bwd_inner_microstep: 136.45 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.10 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 1010 +[2025-05-02 01:46:36,154] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 102.48 | bwd_microstep: 151.77 | bwd_inner_microstep: 151.52 | bwd_allreduce_microstep: 0.10 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1990 +[2025-05-02 01:46:36,664] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 198.51 | bwd_microstep: 293.79 | bwd_inner_microstep: 293.77 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1979 +[2025-05-02 01:46:37,175] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 199.28 | bwd_microstep: 291.85 | bwd_inner_microstep: 291.83 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.15 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 434 +[2025-05-02 01:46:37,399] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 83.74 | bwd_microstep: 124.38 | bwd_inner_microstep: 124.16 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1892 +[2025-05-02 01:46:37,880] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.63 | bwd_microstep: 274.92 | bwd_inner_microstep: 274.90 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.07 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-02 01:46:38,363] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.43 | bwd_microstep: 273.89 | bwd_inner_microstep: 273.88 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1368 +[2025-05-02 01:46:38,730] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 142.60 | bwd_microstep: 206.88 | bwd_inner_microstep: 206.86 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:46:39,209] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.49 | bwd_microstep: 272.66 | bwd_inner_microstep: 272.64 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 01:46:39,690] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.80 | bwd_microstep: 273.13 | bwd_inner_microstep: 273.11 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1099 +[2025-05-02 01:46:39,986] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 117.82 | bwd_microstep: 161.44 | bwd_inner_microstep: 161.32 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:46:40,465] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.59 | bwd_microstep: 272.47 | bwd_inner_microstep: 272.45 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:46:40,944] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.80 | bwd_microstep: 271.55 | bwd_inner_microstep: 271.53 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 01:46:41,423] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.47 | bwd_microstep: 271.37 | bwd_inner_microstep: 271.36 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:46:41,905] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.91 | bwd_microstep: 271.32 | bwd_inner_microstep: 271.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:46:42,492] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.22 | optimizer_step: 16.71 +[2025-05-02 01:46:42,493] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.27 | bwd_microstep: 353.36 | bwd_inner_microstep: 271.62 | bwd_allreduce_microstep: 81.69 | step_microstep: 24.68 +[2025-05-02 01:46:42,494] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2635.07 | bwd: 3901.62 | bwd_inner: 3818.88 | bwd_allreduce: 82.07 | step: 25.87 + 15%|█▌ | 1351/8720 [3:31:16<13:50:51, 6.77s/it] {'loss': 0.7933, 'grad_norm': 10.597959518432617, 'learning_rate': 9.596511952984777e-06, 'epoch': 1.55} + 15%|█▌ | 1351/8720 [3:31:16<13:50:51, 6.77s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1850 +[2025-05-02 01:46:42,976] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.87 | bwd_microstep: 270.21 | bwd_inner_microstep: 270.20 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2140 +[2025-05-02 01:46:43,515] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 205.98 | bwd_microstep: 314.05 | bwd_inner_microstep: 314.03 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1890 +[2025-05-02 01:46:43,996] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.90 | bwd_microstep: 274.43 | bwd_inner_microstep: 274.42 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-02 01:46:44,476] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.59 | bwd_microstep: 273.64 | bwd_inner_microstep: 273.62 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 01:46:44,957] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.67 | bwd_microstep: 273.08 | bwd_inner_microstep: 273.06 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:46:45,437] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.50 | bwd_microstep: 272.28 | bwd_inner_microstep: 272.26 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 01:46:45,915] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.47 | bwd_microstep: 272.45 | bwd_inner_microstep: 272.43 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:46:46,396] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.44 | bwd_microstep: 272.56 | bwd_inner_microstep: 272.54 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 01:46:46,878] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.42 | bwd_microstep: 272.98 | bwd_inner_microstep: 272.96 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 01:46:47,358] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.37 | bwd_microstep: 272.61 | bwd_inner_microstep: 272.60 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 324 +[2025-05-02 01:46:47,583] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 83.59 | bwd_microstep: 125.09 | bwd_inner_microstep: 124.89 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 835 +[2025-05-02 01:46:47,818] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.78 | bwd_microstep: 126.12 | bwd_inner_microstep: 125.89 | bwd_allreduce_microstep: 0.14 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 01:46:48,297] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.50 | bwd_microstep: 272.46 | bwd_inner_microstep: 272.44 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.21 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:46:48,776] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.31 | bwd_microstep: 271.35 | bwd_inner_microstep: 271.33 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 317 +[2025-05-02 01:46:49,005] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 82.44 | bwd_microstep: 131.39 | bwd_inner_microstep: 131.13 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:46:49,585] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.29 | optimizer_step: 16.98 +[2025-05-02 01:46:49,585] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.84 | bwd_microstep: 349.07 | bwd_inner_microstep: 271.81 | bwd_allreduce_microstep: 77.21 | step_microstep: 24.98 +[2025-05-02 01:46:49,587] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2726.29 | bwd: 4043.82 | bwd_inner: 3965.72 | bwd_allreduce: 77.56 | step: 26.09 + 16%|█▌ | 1352/8720 [3:31:23<14:02:48, 6.86s/it] {'loss': 0.4627, 'grad_norm': 7.669371128082275, 'learning_rate': 9.595780742201555e-06, 'epoch': 1.55} + 16%|█▌ | 1352/8720 [3:31:23<14:02:48, 6.86s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:46:50,068] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.83 | bwd_microstep: 270.43 | bwd_inner_microstep: 270.41 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1961 +[2025-05-02 01:46:50,573] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 196.07 | bwd_microstep: 290.55 | bwd_inner_microstep: 290.54 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 388 +[2025-05-02 01:46:50,811] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 105.13 | bwd_microstep: 114.88 | bwd_inner_microstep: 114.73 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-02 01:46:51,290] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.09 | bwd_microstep: 273.63 | bwd_inner_microstep: 273.62 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 01:46:51,769] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.17 | bwd_microstep: 273.14 | bwd_inner_microstep: 273.13 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-02 01:46:52,249] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.40 | bwd_microstep: 273.73 | bwd_inner_microstep: 273.71 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 01:46:52,728] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.47 | bwd_microstep: 273.06 | bwd_inner_microstep: 273.04 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 01:46:53,209] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.10 | bwd_microstep: 272.56 | bwd_inner_microstep: 272.54 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:46:53,686] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.80 | bwd_microstep: 272.47 | bwd_inner_microstep: 272.45 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:46:54,165] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.43 | bwd_microstep: 272.35 | bwd_inner_microstep: 272.33 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 01:46:54,640] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.57 | bwd_microstep: 271.51 | bwd_inner_microstep: 271.50 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 321 +[2025-05-02 01:46:54,849] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 76.63 | bwd_microstep: 118.68 | bwd_inner_microstep: 118.55 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 01:46:55,323] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.82 | bwd_microstep: 271.38 | bwd_inner_microstep: 271.37 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.17 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:46:55,798] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.74 | bwd_microstep: 271.27 | bwd_inner_microstep: 271.25 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 319 +[2025-05-02 01:46:56,013] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 76.39 | bwd_microstep: 123.60 | bwd_inner_microstep: 123.47 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 01:46:56,575] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.04 | optimizer_gradients: 2.13 | optimizer_step: 16.55 +[2025-05-02 01:46:56,575] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.74 | bwd_microstep: 337.52 | bwd_inner_microstep: 271.46 | bwd_allreduce_microstep: 66.00 | step_microstep: 23.47 +[2025-05-02 01:46:56,576] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2710.06 | bwd: 3980.82 | bwd_inner: 3914.17 | bwd_allreduce: 66.24 | step: 24.51 + 16%|█▌ | 1353/8720 [3:31:30<14:07:15, 6.90s/it] {'loss': 0.5411, 'grad_norm': 7.608511447906494, 'learning_rate': 9.595048897368082e-06, 'epoch': 1.55} + 16%|█▌ | 1353/8720 [3:31:30<14:07:15, 6.90s/it]dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 827 +[2025-05-02 01:46:56,817] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 92.47 | bwd_microstep: 130.08 | bwd_inner_microstep: 129.95 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.08 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 473 +[2025-05-02 01:46:57,029] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 79.97 | bwd_microstep: 118.99 | bwd_inner_microstep: 118.68 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1380 +[2025-05-02 01:46:57,396] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 142.86 | bwd_microstep: 207.94 | bwd_inner_microstep: 207.92 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-02 01:46:57,874] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.60 | bwd_microstep: 273.93 | bwd_inner_microstep: 273.92 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-02 01:46:58,353] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.85 | bwd_microstep: 273.44 | bwd_inner_microstep: 273.42 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 350 +[2025-05-02 01:46:58,580] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 89.50 | bwd_microstep: 119.45 | bwd_inner_microstep: 119.23 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 01:46:59,060] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.07 | bwd_microstep: 273.05 | bwd_inner_microstep: 273.03 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 01:46:59,540] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.59 | bwd_microstep: 273.59 | bwd_inner_microstep: 273.57 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1355 +[2025-05-02 01:46:59,904] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.88 | bwd_microstep: 206.17 | bwd_inner_microstep: 206.13 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:47:00,380] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.95 | bwd_microstep: 272.23 | bwd_inner_microstep: 272.22 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1095 +[2025-05-02 01:47:00,675] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 118.13 | bwd_microstep: 161.00 | bwd_inner_microstep: 160.93 | bwd_allreduce_microstep: 0.04 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 01:47:01,150] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.75 | bwd_microstep: 272.49 | bwd_inner_microstep: 272.47 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-02 01:47:01,628] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.20 | bwd_microstep: 273.16 | bwd_inner_microstep: 273.14 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:47:02,104] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.79 | bwd_microstep: 272.23 | bwd_inner_microstep: 272.22 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:47:02,582] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.11 | bwd_microstep: 272.14 | bwd_inner_microstep: 272.12 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:47:03,157] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.04 | optimizer_gradients: 2.19 | optimizer_step: 16.54 +[2025-05-02 01:47:03,157] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.98 | bwd_microstep: 346.83 | bwd_inner_microstep: 271.56 | bwd_allreduce_microstep: 75.22 | step_microstep: 23.53 +[2025-05-02 01:47:03,158] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2548.39 | bwd: 3746.79 | bwd_inner: 3670.63 | bwd_allreduce: 75.57 | step: 24.50 + 16%|█▌ | 1354/8720 [3:31:36<13:55:25, 6.80s/it] {'loss': 0.6819, 'grad_norm': 25.61524772644043, 'learning_rate': 9.594316418585323e-06, 'epoch': 1.55} + 16%|█▌ | 1354/8720 [3:31:36<13:55:25, 6.80s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:47:03,638] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.31 | bwd_microstep: 271.65 | bwd_inner_microstep: 271.63 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1948 +[2025-05-02 01:47:04,140] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 198.37 | bwd_microstep: 289.02 | bwd_inner_microstep: 289.00 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1888 +[2025-05-02 01:47:04,618] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.19 | bwd_microstep: 274.41 | bwd_inner_microstep: 274.39 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1887 +[2025-05-02 01:47:05,098] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.71 | bwd_microstep: 274.41 | bwd_inner_microstep: 274.39 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 852 +[2025-05-02 01:47:05,340] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.60 | bwd_microstep: 133.20 | bwd_inner_microstep: 132.94 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1349 +[2025-05-02 01:47:05,701] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.92 | bwd_microstep: 205.62 | bwd_inner_microstep: 205.51 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 01:47:06,179] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.79 | bwd_microstep: 272.85 | bwd_inner_microstep: 272.83 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 01:47:06,658] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.30 | bwd_microstep: 273.07 | bwd_inner_microstep: 273.05 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:47:07,136] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.42 | bwd_microstep: 272.62 | bwd_inner_microstep: 272.60 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 01:47:07,616] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.46 | bwd_microstep: 272.74 | bwd_inner_microstep: 272.72 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 834 +[2025-05-02 01:47:07,854] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 96.28 | bwd_microstep: 125.57 | bwd_inner_microstep: 125.55 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:47:08,333] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.15 | bwd_microstep: 272.74 | bwd_inner_microstep: 272.72 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:47:08,812] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.00 | bwd_microstep: 272.39 | bwd_inner_microstep: 272.37 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:47:09,288] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.22 | bwd_microstep: 271.25 | bwd_inner_microstep: 271.24 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:47:09,765] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.07 | bwd_microstep: 272.32 | bwd_inner_microstep: 272.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:47:10,328] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.04 | optimizer_gradients: 2.16 | optimizer_step: 16.55 +[2025-05-02 01:47:10,329] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.33 | bwd_microstep: 337.63 | bwd_inner_microstep: 271.61 | bwd_allreduce_microstep: 65.96 | step_microstep: 23.49 +[2025-05-02 01:47:10,330] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2795.80 | bwd: 4091.58 | bwd_inner: 4024.90 | bwd_allreduce: 66.21 | step: 24.40 + 16%|█▌ | 1355/8720 [3:31:44<14:08:48, 6.91s/it] {'loss': 0.8503, 'grad_norm': 32.42165756225586, 'learning_rate': 9.593583305954336e-06, 'epoch': 1.55} + 16%|█▌ | 1355/8720 [3:31:44<14:08:48, 6.91s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1892 +[2025-05-02 01:47:10,813] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.84 | bwd_microstep: 274.20 | bwd_inner_microstep: 274.18 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.15 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1925 +[2025-05-02 01:47:11,311] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.54 | bwd_microstep: 287.26 | bwd_inner_microstep: 287.25 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1896 +[2025-05-02 01:47:11,790] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.11 | bwd_microstep: 274.94 | bwd_inner_microstep: 274.92 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-02 01:47:12,267] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.55 | bwd_microstep: 273.56 | bwd_inner_microstep: 273.54 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 853 +[2025-05-02 01:47:12,509] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.57 | bwd_microstep: 132.64 | bwd_inner_microstep: 132.62 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-02 01:47:12,984] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.51 | bwd_microstep: 272.87 | bwd_inner_microstep: 272.85 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 349 +[2025-05-02 01:47:13,198] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 74.39 | bwd_microstep: 126.84 | bwd_inner_microstep: 126.51 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 01:47:13,674] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.96 | bwd_microstep: 272.78 | bwd_inner_microstep: 272.76 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 01:47:14,151] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.00 | bwd_microstep: 272.30 | bwd_inner_microstep: 272.29 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:47:14,625] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.11 | bwd_microstep: 271.22 | bwd_inner_microstep: 271.20 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:47:15,099] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.60 | bwd_microstep: 271.06 | bwd_inner_microstep: 271.05 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:47:15,573] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.55 | bwd_microstep: 271.38 | bwd_inner_microstep: 271.36 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 01:47:16,050] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.07 | bwd_microstep: 272.42 | bwd_inner_microstep: 272.40 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:47:16,524] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.96 | bwd_microstep: 271.20 | bwd_inner_microstep: 271.18 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 317 +[2025-05-02 01:47:16,738] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 75.84 | bwd_microstep: 124.14 | bwd_inner_microstep: 123.99 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 01:47:17,303] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.04 | optimizer_gradients: 2.20 | optimizer_step: 16.57 +[2025-05-02 01:47:17,304] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.45 | bwd_microstep: 338.25 | bwd_inner_microstep: 271.75 | bwd_allreduce_microstep: 66.46 | step_microstep: 23.64 +[2025-05-02 01:47:17,305] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2700.77 | bwd: 4007.10 | bwd_inner: 3939.96 | bwd_allreduce: 66.70 | step: 24.52 + 16%|█▌ | 1356/8720 [3:31:51<14:10:53, 6.93s/it] {'loss': 0.688, 'grad_norm': 18.547134399414062, 'learning_rate': 9.592849559576263e-06, 'epoch': 1.55} + 16%|█▌ | 1356/8720 [3:31:51<14:10:53, 6.93s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 457 +[2025-05-02 01:47:17,506] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 68.27 | bwd_microstep: 115.33 | bwd_inner_microstep: 115.20 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1887 +[2025-05-02 01:47:17,984] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.79 | bwd_microstep: 274.54 | bwd_inner_microstep: 274.52 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-02 01:47:18,463] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.56 | bwd_microstep: 273.57 | bwd_inner_microstep: 273.56 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1888 +[2025-05-02 01:47:18,943] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.76 | bwd_microstep: 274.41 | bwd_inner_microstep: 274.39 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 850 +[2025-05-02 01:47:19,190] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 98.15 | bwd_microstep: 132.47 | bwd_inner_microstep: 132.37 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1356 +[2025-05-02 01:47:19,555] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.41 | bwd_microstep: 206.44 | bwd_inner_microstep: 206.42 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 01:47:20,036] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.31 | bwd_microstep: 273.30 | bwd_inner_microstep: 273.28 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 01:47:20,517] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.40 | bwd_microstep: 272.93 | bwd_inner_microstep: 272.91 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 01:47:21,000] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.43 | bwd_microstep: 272.97 | bwd_inner_microstep: 272.95 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 01:47:21,482] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.06 | bwd_microstep: 272.88 | bwd_inner_microstep: 272.86 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 01:47:21,959] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.24 | bwd_microstep: 272.70 | bwd_inner_microstep: 272.68 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 01:47:22,439] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.37 | bwd_microstep: 272.77 | bwd_inner_microstep: 272.75 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 01:47:22,923] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.59 | bwd_microstep: 273.29 | bwd_inner_microstep: 273.27 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:47:23,405] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.37 | bwd_microstep: 272.64 | bwd_inner_microstep: 272.62 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 01:47:23,884] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.64 | bwd_microstep: 272.72 | bwd_inner_microstep: 272.70 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 01:47:24,467] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.19 | optimizer_step: 16.51 +[2025-05-02 01:47:24,468] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.75 | bwd_microstep: 351.31 | bwd_inner_microstep: 273.29 | bwd_allreduce_microstep: 77.97 | step_microstep: 24.17 +[2025-05-02 01:47:24,469] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2759.72 | bwd: 4084.31 | bwd_inner: 4005.82 | bwd_allreduce: 78.16 | step: 25.17 + 16%|█▌ | 1357/8720 [3:31:58<14:19:22, 7.00s/it] {'loss': 1.483, 'grad_norm': 12.317950248718262, 'learning_rate': 9.592115179552333e-06, 'epoch': 1.56} + 16%|█▌ | 1357/8720 [3:31:58<14:19:22, 7.00s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:47:24,951] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.17 | bwd_microstep: 270.54 | bwd_inner_microstep: 270.52 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1941 +[2025-05-02 01:47:25,453] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 196.62 | bwd_microstep: 288.74 | bwd_inner_microstep: 288.72 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 391 +[2025-05-02 01:47:25,665] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 76.99 | bwd_microstep: 121.49 | bwd_inner_microstep: 121.36 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1899 +[2025-05-02 01:47:26,144] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.04 | bwd_microstep: 275.44 | bwd_inner_microstep: 275.42 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-02 01:47:26,623] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.07 | bwd_microstep: 274.51 | bwd_inner_microstep: 274.49 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 01:47:27,098] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.18 | bwd_microstep: 272.52 | bwd_inner_microstep: 272.50 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 01:47:27,575] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.28 | bwd_microstep: 273.60 | bwd_inner_microstep: 273.58 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 01:47:28,052] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.78 | bwd_microstep: 273.01 | bwd_inner_microstep: 272.99 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 01:47:28,528] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.55 | bwd_microstep: 272.74 | bwd_inner_microstep: 272.72 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1349 +[2025-05-02 01:47:28,889] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.17 | bwd_microstep: 205.34 | bwd_inner_microstep: 205.32 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:47:29,364] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.86 | bwd_microstep: 271.10 | bwd_inner_microstep: 271.08 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:47:29,840] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.06 | bwd_microstep: 272.25 | bwd_inner_microstep: 272.23 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:47:30,315] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.59 | bwd_microstep: 271.83 | bwd_inner_microstep: 271.81 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 01:47:30,789] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.56 | bwd_microstep: 271.10 | bwd_inner_microstep: 271.08 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 01:47:31,263] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.34 | bwd_microstep: 270.87 | bwd_inner_microstep: 270.85 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 01:47:31,826] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.04 | optimizer_gradients: 2.17 | optimizer_step: 16.54 +[2025-05-02 01:47:31,826] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.36 | bwd_microstep: 337.36 | bwd_inner_microstep: 271.06 | bwd_allreduce_microstep: 66.26 | step_microstep: 23.51 +[2025-05-02 01:47:31,827] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2861.36 | bwd: 4222.45 | bwd_inner: 4155.79 | bwd_allreduce: 66.39 | step: 24.20 + 16%|█▌ | 1358/8720 [3:32:05<14:32:15, 7.11s/it] {'loss': 0.8369, 'grad_norm': 13.190701484680176, 'learning_rate': 9.591380165983866e-06, 'epoch': 1.56} + 16%|█▌ | 1358/8720 [3:32:05<14:32:15, 7.11s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1849 +[2025-05-02 01:47:32,305] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.07 | bwd_microstep: 270.27 | bwd_inner_microstep: 270.26 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1214 +[2025-05-02 01:47:32,618] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 122.94 | bwd_microstep: 175.40 | bwd_inner_microstep: 175.24 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.08 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 889 +[2025-05-02 01:47:32,865] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 96.91 | bwd_microstep: 135.88 | bwd_inner_microstep: 135.71 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-02 01:47:33,342] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.51 | bwd_microstep: 274.18 | bwd_inner_microstep: 274.17 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 01:47:33,818] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.33 | bwd_microstep: 272.75 | bwd_inner_microstep: 272.73 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 01:47:34,293] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.01 | bwd_microstep: 272.79 | bwd_inner_microstep: 272.77 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 01:47:34,771] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.14 | bwd_microstep: 273.45 | bwd_inner_microstep: 273.43 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 01:47:35,248] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.13 | bwd_microstep: 273.18 | bwd_inner_microstep: 273.16 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 01:47:35,725] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.14 | bwd_microstep: 273.12 | bwd_inner_microstep: 273.11 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:47:36,201] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.47 | bwd_microstep: 272.61 | bwd_inner_microstep: 272.59 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:47:36,676] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.96 | bwd_microstep: 272.36 | bwd_inner_microstep: 272.34 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 01:47:37,151] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.83 | bwd_microstep: 272.22 | bwd_inner_microstep: 272.20 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 01:47:37,628] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.64 | bwd_microstep: 272.88 | bwd_inner_microstep: 272.86 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:47:38,105] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.32 | bwd_microstep: 272.46 | bwd_inner_microstep: 272.44 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 833 +[2025-05-02 01:47:38,336] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 91.15 | bwd_microstep: 125.87 | bwd_inner_microstep: 125.86 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 321 +[2025-05-02 01:47:38,639] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.04 | optimizer_gradients: 2.18 | optimizer_step: 16.54 +[2025-05-02 01:47:38,640] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 68.03 | bwd_microstep: 199.45 | bwd_inner_microstep: 133.07 | bwd_allreduce_microstep: 66.30 | step_microstep: 23.49 +[2025-05-02 01:47:38,641] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2641.34 | bwd: 3908.90 | bwd_inner: 3841.97 | bwd_allreduce: 66.52 | step: 24.35 + 16%|█▌ | 1359/8720 [3:32:12<14:21:16, 7.02s/it] {'loss': 0.6187, 'grad_norm': 11.602165222167969, 'learning_rate': 9.590644518972263e-06, 'epoch': 1.56} + 16%|█▌ | 1359/8720 [3:32:12<14:21:16, 7.02s/it]dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1345 +[2025-05-02 01:47:39,006] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.18 | bwd_microstep: 205.14 | bwd_inner_microstep: 204.92 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-02 01:47:39,484] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.02 | bwd_microstep: 274.24 | bwd_inner_microstep: 274.22 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-02 01:47:39,962] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.35 | bwd_microstep: 273.78 | bwd_inner_microstep: 273.77 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 01:47:40,442] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.04 | bwd_microstep: 273.56 | bwd_inner_microstep: 273.54 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 839 +[2025-05-02 01:47:40,688] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 102.91 | bwd_microstep: 125.96 | bwd_inner_microstep: 125.76 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.18 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1365 +[2025-05-02 01:47:41,055] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.19 | bwd_microstep: 207.11 | bwd_inner_microstep: 207.03 | bwd_allreduce_microstep: 0.03 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:47:41,538] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.10 | bwd_microstep: 272.74 | bwd_inner_microstep: 272.72 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 01:47:42,019] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.68 | bwd_microstep: 273.28 | bwd_inner_microstep: 273.27 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 01:47:42,498] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.57 | bwd_microstep: 272.87 | bwd_inner_microstep: 272.86 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:47:42,978] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.37 | bwd_microstep: 272.69 | bwd_inner_microstep: 272.68 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1093 +[2025-05-02 01:47:43,273] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 115.34 | bwd_microstep: 160.80 | bwd_inner_microstep: 160.78 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:47:43,750] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.06 | bwd_microstep: 272.25 | bwd_inner_microstep: 272.24 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1355 +[2025-05-02 01:47:44,116] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.36 | bwd_microstep: 206.37 | bwd_inner_microstep: 206.28 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 01:47:44,594] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.80 | bwd_microstep: 272.59 | bwd_inner_microstep: 272.57 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:47:45,073] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.63 | bwd_microstep: 271.40 | bwd_inner_microstep: 271.38 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 01:47:45,658] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.18 | optimizer_step: 16.71 +[2025-05-02 01:47:45,659] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.60 | bwd_microstep: 354.72 | bwd_inner_microstep: 271.44 | bwd_allreduce_microstep: 83.23 | step_microstep: 24.64 +[2025-05-02 01:47:45,660] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2712.84 | bwd: 3989.59 | bwd_inner: 3905.45 | bwd_allreduce: 83.65 | step: 25.75 + 16%|█▌ | 1360/8720 [3:32:19<14:21:12, 7.02s/it] {'loss': 0.631, 'grad_norm': 8.098679542541504, 'learning_rate': 9.589908238619022e-06, 'epoch': 1.56} + 16%|█▌ | 1360/8720 [3:32:19<14:21:12, 7.02s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 315 +[2025-05-02 01:47:45,888] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 81.28 | bwd_microstep: 125.10 | bwd_inner_microstep: 124.82 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2014 +[2025-05-02 01:47:46,401] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 199.49 | bwd_microstep: 295.63 | bwd_inner_microstep: 295.61 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1952 +[2025-05-02 01:47:46,904] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 196.36 | bwd_microstep: 289.25 | bwd_inner_microstep: 289.24 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 881 +[2025-05-02 01:47:47,154] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 98.33 | bwd_microstep: 135.09 | bwd_inner_microstep: 134.96 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-02 01:47:47,633] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.39 | bwd_microstep: 274.13 | bwd_inner_microstep: 274.11 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 01:47:48,113] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.48 | bwd_microstep: 273.18 | bwd_inner_microstep: 273.16 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-02 01:47:48,590] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.46 | bwd_microstep: 272.93 | bwd_inner_microstep: 272.91 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 01:47:49,067] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.64 | bwd_microstep: 273.22 | bwd_inner_microstep: 273.20 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 01:47:49,547] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.94 | bwd_microstep: 272.71 | bwd_inner_microstep: 272.69 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 01:47:50,026] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.64 | bwd_microstep: 272.76 | bwd_inner_microstep: 272.74 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 323 +[2025-05-02 01:47:50,258] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 83.58 | bwd_microstep: 131.90 | bwd_inner_microstep: 131.77 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 01:47:50,733] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.58 | bwd_microstep: 272.13 | bwd_inner_microstep: 272.11 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 323 +[2025-05-02 01:47:50,936] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 68.37 | bwd_microstep: 121.52 | bwd_inner_microstep: 121.27 | bwd_allreduce_microstep: 0.10 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 01:47:51,410] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.51 | bwd_microstep: 271.16 | bwd_inner_microstep: 271.14 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 01:47:51,884] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.74 | bwd_microstep: 271.34 | bwd_inner_microstep: 271.32 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 01:47:52,450] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.18 | optimizer_step: 16.67 +[2025-05-02 01:47:52,450] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.37 | bwd_microstep: 337.30 | bwd_inner_microstep: 271.81 | bwd_allreduce_microstep: 65.45 | step_microstep: 23.85 +[2025-05-02 01:47:52,451] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2609.84 | bwd: 3889.41 | bwd_inner: 3823.02 | bwd_allreduce: 65.79 | step: 24.82 + 16%|█▌ | 1361/8720 [3:32:26<14:12:34, 6.95s/it] {'loss': 0.9352, 'grad_norm': 19.276626586914062, 'learning_rate': 9.589171325025719e-06, 'epoch': 1.56} + 16%|█▌ | 1361/8720 [3:32:26<14:12:34, 6.95s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 01:47:52,930] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.62 | bwd_microstep: 270.39 | bwd_inner_microstep: 270.37 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1899 +[2025-05-02 01:47:53,410] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.74 | bwd_microstep: 275.42 | bwd_inner_microstep: 275.40 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1888 +[2025-05-02 01:47:53,889] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.08 | bwd_microstep: 274.38 | bwd_inner_microstep: 274.36 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 01:47:54,366] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.59 | bwd_microstep: 273.41 | bwd_inner_microstep: 273.40 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 01:47:54,844] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.97 | bwd_microstep: 273.44 | bwd_inner_microstep: 273.42 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 01:47:55,323] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.43 | bwd_microstep: 273.58 | bwd_inner_microstep: 273.56 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:47:55,802] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.94 | bwd_microstep: 272.77 | bwd_inner_microstep: 272.75 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 01:47:56,283] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.08 | bwd_microstep: 273.35 | bwd_inner_microstep: 273.33 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 01:47:56,765] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.36 | bwd_microstep: 272.00 | bwd_inner_microstep: 271.98 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 01:47:57,245] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.84 | bwd_microstep: 272.66 | bwd_inner_microstep: 272.65 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.15 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 01:47:57,725] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.39 | bwd_microstep: 272.15 | bwd_inner_microstep: 272.13 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:47:58,208] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.12 | bwd_microstep: 272.02 | bwd_inner_microstep: 272.00 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:47:58,688] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.57 | bwd_microstep: 271.42 | bwd_inner_microstep: 271.40 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:47:59,166] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.78 | bwd_microstep: 271.03 | bwd_inner_microstep: 271.01 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 01:47:59,646] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.68 | bwd_microstep: 271.02 | bwd_inner_microstep: 271.00 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1850 +[2025-05-02 01:48:00,224] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.26 | optimizer_step: 16.81 +[2025-05-02 01:48:00,224] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.81 | bwd_microstep: 348.33 | bwd_inner_microstep: 271.28 | bwd_allreduce_microstep: 76.99 | step_microstep: 24.78 +[2025-05-02 01:48:00,225] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 3016.63 | bwd: 4437.37 | bwd_inner: 4360.05 | bwd_allreduce: 77.08 | step: 25.71 + 16%|█▌ | 1362/8720 [3:32:33<14:42:47, 7.20s/it] {'loss': 0.4333, 'grad_norm': 10.54880428314209, 'learning_rate': 9.588433778294023e-06, 'epoch': 1.56} + 16%|█▌ | 1362/8720 [3:32:33<14:42:47, 7.20s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1910 +[2025-05-02 01:48:00,714] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.64 | bwd_microstep: 275.85 | bwd_inner_microstep: 275.83 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1934 +[2025-05-02 01:48:01,218] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 196.21 | bwd_microstep: 288.19 | bwd_inner_microstep: 288.17 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1910 +[2025-05-02 01:48:01,707] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.28 | bwd_microstep: 276.26 | bwd_inner_microstep: 276.25 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1889 +[2025-05-02 01:48:02,189] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.82 | bwd_microstep: 274.45 | bwd_inner_microstep: 274.44 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1887 +[2025-05-02 01:48:02,670] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.17 | bwd_microstep: 274.42 | bwd_inner_microstep: 274.41 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 01:48:03,148] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.13 | bwd_microstep: 272.69 | bwd_inner_microstep: 272.67 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 01:48:03,629] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.73 | bwd_microstep: 272.59 | bwd_inner_microstep: 272.57 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 01:48:04,111] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.63 | bwd_microstep: 272.90 | bwd_inner_microstep: 272.88 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 334 +[2025-05-02 01:48:04,368] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 96.10 | bwd_microstep: 139.09 | bwd_inner_microstep: 138.94 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:48:04,846] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.73 | bwd_microstep: 272.37 | bwd_inner_microstep: 272.35 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:48:05,327] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.91 | bwd_microstep: 272.35 | bwd_inner_microstep: 272.33 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 321 +[2025-05-02 01:48:05,551] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 89.63 | bwd_microstep: 117.87 | bwd_inner_microstep: 117.57 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:48:06,029] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.06 | bwd_microstep: 272.28 | bwd_inner_microstep: 272.27 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:48:06,508] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.25 | bwd_microstep: 272.31 | bwd_inner_microstep: 272.29 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.16 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1346 +[2025-05-02 01:48:06,873] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.34 | bwd_microstep: 205.37 | bwd_inner_microstep: 205.22 | bwd_allreduce_microstep: 0.08 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2053 +[2025-05-02 01:48:07,497] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.20 | optimizer_step: 16.74 +[2025-05-02 01:48:07,497] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 201.19 | bwd_microstep: 378.30 | bwd_inner_microstep: 302.16 | bwd_allreduce_microstep: 76.09 | step_microstep: 24.71 +[2025-05-02 01:48:07,499] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2798.41 | bwd: 4137.36 | bwd_inner: 4060.44 | bwd_allreduce: 76.47 | step: 25.91 + 16%|█▌ | 1363/8720 [3:32:41<14:45:25, 7.22s/it] {'loss': 0.6896, 'grad_norm': 8.205760955810547, 'learning_rate': 9.587695598525687e-06, 'epoch': 1.56} + 16%|█▌ | 1363/8720 [3:32:41<14:45:25, 7.22s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 01:48:07,982] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.04 | bwd_microstep: 272.19 | bwd_inner_microstep: 272.17 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1974 +[2025-05-02 01:48:08,491] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 198.49 | bwd_microstep: 292.23 | bwd_inner_microstep: 292.21 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1889 +[2025-05-02 01:48:08,976] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.26 | bwd_microstep: 275.28 | bwd_inner_microstep: 275.27 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 343 +[2025-05-02 01:48:09,207] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 91.03 | bwd_microstep: 121.98 | bwd_inner_microstep: 121.66 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 350 +[2025-05-02 01:48:09,423] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 82.72 | bwd_microstep: 117.68 | bwd_inner_microstep: 117.53 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 01:48:09,902] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.44 | bwd_microstep: 273.56 | bwd_inner_microstep: 273.54 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 01:48:10,382] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.17 | bwd_microstep: 273.30 | bwd_inner_microstep: 273.29 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1353 +[2025-05-02 01:48:10,745] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.62 | bwd_microstep: 206.11 | bwd_inner_microstep: 206.09 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 843 +[2025-05-02 01:48:10,984] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 92.99 | bwd_microstep: 132.14 | bwd_inner_microstep: 132.02 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:48:11,461] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.56 | bwd_microstep: 272.79 | bwd_inner_microstep: 272.78 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:48:11,939] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.83 | bwd_microstep: 272.93 | bwd_inner_microstep: 272.91 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:48:12,415] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.22 | bwd_microstep: 271.75 | bwd_inner_microstep: 271.73 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 01:48:12,892] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.42 | bwd_microstep: 271.15 | bwd_inner_microstep: 271.13 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 831 +[2025-05-02 01:48:13,133] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.11 | bwd_microstep: 130.00 | bwd_inner_microstep: 129.74 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:48:13,609] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.64 | bwd_microstep: 271.05 | bwd_inner_microstep: 271.04 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 315 +[2025-05-02 01:48:13,946] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.54 | optimizer_step: 17.00 +[2025-05-02 01:48:13,946] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 85.60 | bwd_microstep: 210.07 | bwd_inner_microstep: 133.11 | bwd_allreduce_microstep: 76.79 | step_microstep: 25.29 +[2025-05-02 01:48:13,948] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2485.84 | bwd: 3664.29 | bwd_inner: 3586.43 | bwd_allreduce: 77.16 | step: 26.31 + 16%|█▌ | 1364/8720 [3:32:47<14:16:54, 6.99s/it] {'loss': 0.791, 'grad_norm': 17.600065231323242, 'learning_rate': 9.586956785822555e-06, 'epoch': 1.56} + 16%|█▌ | 1364/8720 [3:32:47<14:16:54, 6.99s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 01:48:14,430] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.30 | bwd_microstep: 270.33 | bwd_inner_microstep: 270.31 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1915 +[2025-05-02 01:48:14,913] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.83 | bwd_microstep: 276.45 | bwd_inner_microstep: 276.43 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 01:48:15,391] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.44 | bwd_microstep: 273.31 | bwd_inner_microstep: 273.30 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 01:48:15,868] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.84 | bwd_microstep: 273.00 | bwd_inner_microstep: 272.98 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 01:48:16,346] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.46 | bwd_microstep: 273.23 | bwd_inner_microstep: 273.21 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1360 +[2025-05-02 01:48:16,706] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.04 | bwd_microstep: 206.57 | bwd_inner_microstep: 206.55 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 01:48:17,182] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.96 | bwd_microstep: 273.07 | bwd_inner_microstep: 273.05 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 846 +[2025-05-02 01:48:17,421] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.33 | bwd_microstep: 132.16 | bwd_inner_microstep: 131.99 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 01:48:17,897] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.50 | bwd_microstep: 272.67 | bwd_inner_microstep: 272.66 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 330 +[2025-05-02 01:48:18,096] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 67.08 | bwd_microstep: 118.71 | bwd_inner_microstep: 118.46 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 01:48:18,572] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.53 | bwd_microstep: 272.84 | bwd_inner_microstep: 272.82 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:48:19,049] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.08 | bwd_microstep: 272.55 | bwd_inner_microstep: 272.53 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:48:19,529] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.90 | bwd_microstep: 272.44 | bwd_inner_microstep: 272.42 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 01:48:20,003] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.88 | bwd_microstep: 271.32 | bwd_inner_microstep: 271.31 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 01:48:20,480] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.98 | bwd_microstep: 271.09 | bwd_inner_microstep: 271.07 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 01:48:21,046] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.14 | optimizer_step: 16.57 +[2025-05-02 01:48:21,046] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.90 | bwd_microstep: 338.56 | bwd_inner_microstep: 271.44 | bwd_allreduce_microstep: 67.08 | step_microstep: 23.62 +[2025-05-02 01:48:21,047] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2751.78 | bwd: 4068.35 | bwd_inner: 4000.60 | bwd_allreduce: 67.34 | step: 24.63 + 16%|█▌ | 1365/8720 [3:32:54<14:20:45, 7.02s/it] {'loss': 0.9148, 'grad_norm': 16.314298629760742, 'learning_rate': 9.586217340286555e-06, 'epoch': 1.57} + 16%|█▌ | 1365/8720 [3:32:54<14:20:45, 7.02s/it]dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 826 +[2025-05-02 01:48:21,301] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 106.44 | bwd_microstep: 128.88 | bwd_inner_microstep: 128.63 | bwd_allreduce_microstep: 0.10 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1904 +[2025-05-02 01:48:21,781] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.32 | bwd_microstep: 275.66 | bwd_inner_microstep: 275.64 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1361 +[2025-05-02 01:48:22,150] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 143.80 | bwd_microstep: 206.57 | bwd_inner_microstep: 206.55 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-02 01:48:22,628] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.12 | bwd_microstep: 273.95 | bwd_inner_microstep: 273.93 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:48:23,109] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.73 | bwd_microstep: 273.16 | bwd_inner_microstep: 273.14 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:48:23,586] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.75 | bwd_microstep: 273.06 | bwd_inner_microstep: 273.04 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 01:48:24,063] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.54 | bwd_microstep: 272.84 | bwd_inner_microstep: 272.82 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:48:24,539] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.39 | bwd_microstep: 272.58 | bwd_inner_microstep: 272.56 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.13 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 01:48:25,016] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.14 | bwd_microstep: 272.56 | bwd_inner_microstep: 272.54 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:48:25,494] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.99 | bwd_microstep: 271.77 | bwd_inner_microstep: 271.75 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.15 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 01:48:25,973] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.65 | bwd_microstep: 272.79 | bwd_inner_microstep: 272.77 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:48:26,450] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.39 | bwd_microstep: 272.97 | bwd_inner_microstep: 272.96 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:48:26,926] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.00 | bwd_microstep: 271.83 | bwd_inner_microstep: 271.81 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:48:27,401] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.25 | bwd_microstep: 271.65 | bwd_inner_microstep: 271.64 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 01:48:27,876] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.99 | bwd_microstep: 271.71 | bwd_inner_microstep: 271.69 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1935 +[2025-05-02 01:48:28,465] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.14 | optimizer_step: 16.63 +[2025-05-02 01:48:28,465] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.94 | bwd_microstep: 354.52 | bwd_inner_microstep: 288.57 | bwd_allreduce_microstep: 65.90 | step_microstep: 23.59 +[2025-05-02 01:48:28,466] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2906.12 | bwd: 4236.50 | bwd_inner: 4170.11 | bwd_allreduce: 66.06 | step: 24.59 + 16%|█▌ | 1366/8720 [3:33:02<14:35:14, 7.14s/it] {'loss': 0.4124, 'grad_norm': 14.576095581054688, 'learning_rate': 9.585477262019702e-06, 'epoch': 1.57} + 16%|█▌ | 1366/8720 [3:33:02<14:35:14, 7.14s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-02 01:48:28,948] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.81 | bwd_microstep: 272.74 | bwd_inner_microstep: 272.72 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2114 +[2025-05-02 01:48:29,482] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 205.74 | bwd_microstep: 312.55 | bwd_inner_microstep: 312.53 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1920 +[2025-05-02 01:48:29,967] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.11 | bwd_microstep: 276.41 | bwd_inner_microstep: 276.39 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 01:48:30,444] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.71 | bwd_microstep: 273.20 | bwd_inner_microstep: 273.18 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 01:48:30,925] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.26 | bwd_microstep: 272.71 | bwd_inner_microstep: 272.70 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 331 +[2025-05-02 01:48:31,133] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 80.18 | bwd_microstep: 114.44 | bwd_inner_microstep: 114.31 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.08 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 842 +[2025-05-02 01:48:31,385] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 107.14 | bwd_microstep: 131.60 | bwd_inner_microstep: 131.57 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:48:31,861] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.91 | bwd_microstep: 272.51 | bwd_inner_microstep: 272.49 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 321 +[2025-05-02 01:48:32,074] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 84.79 | bwd_microstep: 115.23 | bwd_inner_microstep: 114.98 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:48:32,549] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.91 | bwd_microstep: 272.64 | bwd_inner_microstep: 272.62 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:48:33,024] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.09 | bwd_microstep: 271.32 | bwd_inner_microstep: 271.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:48:33,500] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.25 | bwd_microstep: 272.54 | bwd_inner_microstep: 272.53 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:48:33,980] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.93 | bwd_microstep: 272.39 | bwd_inner_microstep: 272.37 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:48:34,457] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.75 | bwd_microstep: 271.19 | bwd_inner_microstep: 271.17 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 317 +[2025-05-02 01:48:34,683] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 91.15 | bwd_microstep: 117.37 | bwd_inner_microstep: 117.13 | bwd_allreduce_microstep: 0.09 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 01:48:35,267] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.20 | optimizer_step: 16.58 +[2025-05-02 01:48:35,267] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.04 | bwd_microstep: 352.92 | bwd_inner_microstep: 271.64 | bwd_allreduce_microstep: 81.23 | step_microstep: 24.31 +[2025-05-02 01:48:35,269] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2644.42 | bwd: 3871.82 | bwd_inner: 3789.78 | bwd_allreduce: 81.50 | step: 25.31 + 16%|█▌ | 1367/8720 [3:33:09<14:22:44, 7.04s/it] {'loss': 0.6104, 'grad_norm': 17.10765838623047, 'learning_rate': 9.584736551124103e-06, 'epoch': 1.57} + 16%|█▌ | 1367/8720 [3:33:09<14:22:44, 7.04s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:48:35,750] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.84 | bwd_microstep: 270.54 | bwd_inner_microstep: 270.52 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 880 +[2025-05-02 01:48:36,000] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 98.61 | bwd_microstep: 135.25 | bwd_inner_microstep: 135.22 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1893 +[2025-05-02 01:48:36,481] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.85 | bwd_microstep: 274.93 | bwd_inner_microstep: 274.91 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1380 +[2025-05-02 01:48:36,851] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.95 | bwd_microstep: 208.34 | bwd_inner_microstep: 208.20 | bwd_allreduce_microstep: 0.03 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-02 01:48:37,332] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.26 | bwd_microstep: 273.54 | bwd_inner_microstep: 273.52 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-02 01:48:37,811] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.90 | bwd_microstep: 273.05 | bwd_inner_microstep: 273.03 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 01:48:38,292] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.71 | bwd_microstep: 272.67 | bwd_inner_microstep: 272.65 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:48:38,775] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.14 | bwd_microstep: 272.39 | bwd_inner_microstep: 272.38 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:48:39,255] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.13 | bwd_microstep: 272.35 | bwd_inner_microstep: 272.34 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:48:39,732] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.96 | bwd_microstep: 272.07 | bwd_inner_microstep: 272.05 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:48:40,211] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.68 | bwd_microstep: 272.21 | bwd_inner_microstep: 272.19 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:48:40,690] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.37 | bwd_microstep: 272.14 | bwd_inner_microstep: 272.12 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 01:48:41,170] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.81 | bwd_microstep: 271.12 | bwd_inner_microstep: 271.10 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 01:48:41,649] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.95 | bwd_microstep: 271.01 | bwd_inner_microstep: 270.99 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:48:42,126] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.42 | bwd_microstep: 271.24 | bwd_inner_microstep: 271.22 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:48:42,708] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.19 | optimizer_step: 16.56 +[2025-05-02 01:48:42,708] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.34 | bwd_microstep: 350.89 | bwd_inner_microstep: 271.84 | bwd_allreduce_microstep: 79.00 | step_microstep: 24.22 +[2025-05-02 01:48:42,709] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2876.53 | bwd: 4233.79 | bwd_inner: 4154.29 | bwd_allreduce: 79.16 | step: 25.16 + 16%|█▌ | 1368/8720 [3:33:16<14:37:22, 7.16s/it] {'loss': 0.5024, 'grad_norm': 10.42374038696289, 'learning_rate': 9.583995207701947e-06, 'epoch': 1.57} + 16%|█▌ | 1368/8720 [3:33:16<14:37:22, 7.16s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 01:48:43,190] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.61 | bwd_microstep: 270.15 | bwd_inner_microstep: 270.14 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1944 +[2025-05-02 01:48:43,693] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.48 | bwd_microstep: 289.10 | bwd_inner_microstep: 289.08 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1922 +[2025-05-02 01:48:44,193] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 194.75 | bwd_microstep: 287.25 | bwd_inner_microstep: 287.24 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1891 +[2025-05-02 01:48:44,675] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.19 | bwd_microstep: 274.69 | bwd_inner_microstep: 274.67 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 01:48:45,155] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.48 | bwd_microstep: 273.30 | bwd_inner_microstep: 273.28 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 01:48:45,635] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.36 | bwd_microstep: 273.05 | bwd_inner_microstep: 273.03 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 330 +[2025-05-02 01:48:45,854] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 82.30 | bwd_microstep: 120.09 | bwd_inner_microstep: 119.87 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 01:48:46,332] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.53 | bwd_microstep: 272.72 | bwd_inner_microstep: 272.70 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 01:48:46,810] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.15 | bwd_microstep: 272.58 | bwd_inner_microstep: 272.56 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 01:48:47,288] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.59 | bwd_microstep: 272.08 | bwd_inner_microstep: 272.06 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 324 +[2025-05-02 01:48:47,523] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 92.38 | bwd_microstep: 126.46 | bwd_inner_microstep: 126.27 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 837 +[2025-05-02 01:48:47,760] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.66 | bwd_microstep: 126.61 | bwd_inner_microstep: 126.35 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:48:48,238] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.55 | bwd_microstep: 272.22 | bwd_inner_microstep: 272.20 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:48:48,718] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.30 | bwd_microstep: 271.36 | bwd_inner_microstep: 271.34 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.15 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 01:48:49,194] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.79 | bwd_microstep: 271.07 | bwd_inner_microstep: 271.06 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 01:48:49,785] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.18 | optimizer_step: 16.59 +[2025-05-02 01:48:49,785] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.00 | bwd_microstep: 358.47 | bwd_inner_microstep: 271.33 | bwd_allreduce_microstep: 87.09 | step_microstep: 24.34 +[2025-05-02 01:48:49,787] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2728.76 | bwd: 4031.27 | bwd_inner: 3943.30 | bwd_allreduce: 87.41 | step: 25.37 + 16%|█▌ | 1369/8720 [3:33:23<14:34:11, 7.14s/it] {'loss': 0.3596, 'grad_norm': 5.415369987487793, 'learning_rate': 9.583253231855511e-06, 'epoch': 1.57} + 16%|█▌ | 1369/8720 [3:33:23<14:34:11, 7.14s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1906 +[2025-05-02 01:48:50,273] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.55 | bwd_microstep: 275.13 | bwd_inner_microstep: 275.11 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 451 +[2025-05-02 01:48:50,489] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 86.48 | bwd_microstep: 113.23 | bwd_inner_microstep: 113.08 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.09 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1116 +[2025-05-02 01:48:50,783] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 115.09 | bwd_microstep: 162.21 | bwd_inner_microstep: 162.10 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-02 01:48:51,264] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.29 | bwd_microstep: 274.41 | bwd_inner_microstep: 274.39 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-02 01:48:51,746] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.47 | bwd_microstep: 273.73 | bwd_inner_microstep: 273.71 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-02 01:48:52,230] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.57 | bwd_microstep: 272.81 | bwd_inner_microstep: 272.80 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 336 +[2025-05-02 01:48:52,448] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 87.03 | bwd_microstep: 115.10 | bwd_inner_microstep: 114.96 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 01:48:52,925] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.64 | bwd_microstep: 272.68 | bwd_inner_microstep: 272.66 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:48:53,403] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.67 | bwd_microstep: 272.64 | bwd_inner_microstep: 272.62 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 330 +[2025-05-02 01:48:53,636] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 92.45 | bwd_microstep: 124.62 | bwd_inner_microstep: 124.29 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.11 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 321 +[2025-05-02 01:48:53,855] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 84.41 | bwd_microstep: 117.99 | bwd_inner_microstep: 117.84 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:48:54,332] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.48 | bwd_microstep: 272.51 | bwd_inner_microstep: 272.49 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:48:54,811] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.00 | bwd_microstep: 272.17 | bwd_inner_microstep: 272.16 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:48:55,287] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.40 | bwd_microstep: 270.97 | bwd_inner_microstep: 270.96 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 01:48:55,765] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.38 | bwd_microstep: 272.27 | bwd_inner_microstep: 272.25 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 830 +[2025-05-02 01:48:56,108] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.18 | optimizer_step: 16.56 +[2025-05-02 01:48:56,109] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.56 | bwd_microstep: 206.40 | bwd_inner_microstep: 130.34 | bwd_allreduce_microstep: 75.93 | step_microstep: 24.24 +[2025-05-02 01:48:56,110] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2443.11 | bwd: 3568.98 | bwd_inner: 3491.97 | bwd_allreduce: 76.33 | step: 25.24 + 16%|█▌ | 1370/8720 [3:33:29<14:04:14, 6.89s/it] {'loss': 0.838, 'grad_norm': 12.77534294128418, 'learning_rate': 9.582510623687165e-06, 'epoch': 1.57} + 16%|█▌ | 1370/8720 [3:33:29<14:04:14, 6.89s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 437 +[2025-05-02 01:48:56,335] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 83.37 | bwd_microstep: 120.52 | bwd_inner_microstep: 120.26 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2068 +[2025-05-02 01:48:56,857] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 201.15 | bwd_microstep: 301.87 | bwd_inner_microstep: 301.85 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1908 +[2025-05-02 01:48:57,340] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.42 | bwd_microstep: 276.28 | bwd_inner_microstep: 276.26 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1905 +[2025-05-02 01:48:57,824] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.20 | bwd_microstep: 275.95 | bwd_inner_microstep: 275.94 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1897 +[2025-05-02 01:48:58,304] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.49 | bwd_microstep: 275.20 | bwd_inner_microstep: 275.18 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-02 01:48:58,786] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.66 | bwd_microstep: 273.74 | bwd_inner_microstep: 273.72 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 347 +[2025-05-02 01:48:59,015] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 92.64 | bwd_microstep: 117.61 | bwd_inner_microstep: 117.30 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-02 01:48:59,498] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.89 | bwd_microstep: 274.16 | bwd_inner_microstep: 274.15 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 01:48:59,981] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.90 | bwd_microstep: 272.76 | bwd_inner_microstep: 272.75 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 01:49:00,465] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.11 | bwd_microstep: 272.98 | bwd_inner_microstep: 272.96 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.14 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 01:49:00,943] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.40 | bwd_microstep: 272.65 | bwd_inner_microstep: 272.63 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:49:01,422] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.04 | bwd_microstep: 272.53 | bwd_inner_microstep: 272.51 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:49:01,901] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.34 | bwd_microstep: 272.38 | bwd_inner_microstep: 272.36 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:49:02,378] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.49 | bwd_microstep: 271.20 | bwd_inner_microstep: 271.18 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 01:49:02,853] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.26 | bwd_microstep: 271.07 | bwd_inner_microstep: 271.05 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1340 +[2025-05-02 01:49:03,315] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.19 | optimizer_step: 16.54 +[2025-05-02 01:49:03,315] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.03 | bwd_microstep: 281.12 | bwd_inner_microstep: 204.76 | bwd_allreduce_microstep: 76.26 | step_microstep: 24.23 +[2025-05-02 01:49:03,316] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2785.02 | bwd: 4102.10 | bwd_inner: 4025.00 | bwd_allreduce: 76.51 | step: 25.28 + 16%|█▌ | 1371/8720 [3:33:37<14:15:41, 6.99s/it] {'loss': 0.8303, 'grad_norm': 6.553836822509766, 'learning_rate': 9.581767383299358e-06, 'epoch': 1.57} + 16%|█▌ | 1371/8720 [3:33:37<14:15:41, 6.99s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:49:03,798] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.34 | bwd_microstep: 270.49 | bwd_inner_microstep: 270.48 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1924 +[2025-05-02 01:49:04,298] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.73 | bwd_microstep: 286.98 | bwd_inner_microstep: 286.96 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1122 +[2025-05-02 01:49:04,592] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 117.84 | bwd_microstep: 162.55 | bwd_inner_microstep: 162.53 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1130 +[2025-05-02 01:49:04,885] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 115.23 | bwd_microstep: 163.48 | bwd_inner_microstep: 163.40 | bwd_allreduce_microstep: 0.04 | step_microstep: 0.08 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1098 +[2025-05-02 01:49:05,175] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 114.73 | bwd_microstep: 161.22 | bwd_inner_microstep: 161.17 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.09 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1356 +[2025-05-02 01:49:05,536] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.43 | bwd_microstep: 205.79 | bwd_inner_microstep: 205.62 | bwd_allreduce_microstep: 0.08 | step_microstep: 0.18 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1365 +[2025-05-02 01:49:05,899] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.83 | bwd_microstep: 206.99 | bwd_inner_microstep: 206.89 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 01:49:06,377] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.61 | bwd_microstep: 272.76 | bwd_inner_microstep: 272.75 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 326 +[2025-05-02 01:49:06,584] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 71.37 | bwd_microstep: 121.31 | bwd_inner_microstep: 121.12 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 01:49:07,057] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.21 | bwd_microstep: 271.38 | bwd_inner_microstep: 271.37 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:49:07,534] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.54 | bwd_microstep: 272.34 | bwd_inner_microstep: 272.33 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 01:49:08,011] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.03 | bwd_microstep: 272.72 | bwd_inner_microstep: 272.70 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:49:08,485] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.66 | bwd_microstep: 270.89 | bwd_inner_microstep: 270.88 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 01:49:08,960] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.05 | bwd_microstep: 270.97 | bwd_inner_microstep: 270.95 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:49:09,436] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.11 | bwd_microstep: 271.21 | bwd_inner_microstep: 271.19 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:49:10,002] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.23 | optimizer_step: 16.69 +[2025-05-02 01:49:10,002] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.57 | bwd_microstep: 338.00 | bwd_inner_microstep: 271.59 | bwd_allreduce_microstep: 66.37 | step_microstep: 23.92 +[2025-05-02 01:49:10,003] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2589.02 | bwd: 3819.20 | bwd_inner: 3751.95 | bwd_allreduce: 66.74 | step: 24.91 + 16%|█▌ | 1372/8720 [3:33:43<14:04:30, 6.90s/it] {'loss': 0.5297, 'grad_norm': 21.26362419128418, 'learning_rate': 9.581023510794631e-06, 'epoch': 1.57} + 16%|█▌ | 1372/8720 [3:33:43<14:04:30, 6.90s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1917 +[2025-05-02 01:49:10,488] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.91 | bwd_microstep: 275.64 | bwd_inner_microstep: 275.62 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1981 +[2025-05-02 01:49:10,992] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 196.40 | bwd_microstep: 292.02 | bwd_inner_microstep: 292.00 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1910 +[2025-05-02 01:49:11,474] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.68 | bwd_microstep: 276.51 | bwd_inner_microstep: 276.49 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.16 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1889 +[2025-05-02 01:49:11,954] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.11 | bwd_microstep: 274.71 | bwd_inner_microstep: 274.69 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 865 +[2025-05-02 01:49:12,198] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.99 | bwd_microstep: 133.92 | bwd_inner_microstep: 133.64 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.22 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-02 01:49:12,678] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.08 | bwd_microstep: 273.83 | bwd_inner_microstep: 273.81 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1358 +[2025-05-02 01:49:13,043] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.71 | bwd_microstep: 206.43 | bwd_inner_microstep: 206.36 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 01:49:13,524] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.26 | bwd_microstep: 273.02 | bwd_inner_microstep: 273.00 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 01:49:14,002] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.52 | bwd_microstep: 272.50 | bwd_inner_microstep: 272.48 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 01:49:14,483] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.42 | bwd_microstep: 272.66 | bwd_inner_microstep: 272.65 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 01:49:14,961] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.88 | bwd_microstep: 272.80 | bwd_inner_microstep: 272.78 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:49:15,441] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.82 | bwd_microstep: 272.06 | bwd_inner_microstep: 272.04 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 833 +[2025-05-02 01:49:15,680] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.47 | bwd_microstep: 125.59 | bwd_inner_microstep: 125.52 | bwd_allreduce_microstep: 0.03 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:49:16,158] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.23 | bwd_microstep: 272.35 | bwd_inner_microstep: 272.33 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 01:49:16,638] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.36 | bwd_microstep: 272.58 | bwd_inner_microstep: 272.56 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 01:49:17,219] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.22 | optimizer_step: 16.73 +[2025-05-02 01:49:17,220] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.05 | bwd_microstep: 350.04 | bwd_inner_microstep: 271.52 | bwd_allreduce_microstep: 78.46 | step_microstep: 24.66 +[2025-05-02 01:49:17,221] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2789.54 | bwd: 4116.72 | bwd_inner: 4037.52 | bwd_allreduce: 78.74 | step: 25.91 + 16%|█▌ | 1373/8720 [3:33:50<14:16:17, 6.99s/it] {'loss': 0.7406, 'grad_norm': 7.312009334564209, 'learning_rate': 9.580279006275614e-06, 'epoch': 1.57} + 16%|█▌ | 1373/8720 [3:33:50<14:16:17, 6.99s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 01:49:17,702] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.67 | bwd_microstep: 270.17 | bwd_inner_microstep: 270.15 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1925 +[2025-05-02 01:49:18,203] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 194.66 | bwd_microstep: 287.34 | bwd_inner_microstep: 287.32 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1883 +[2025-05-02 01:49:18,684] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.83 | bwd_microstep: 274.10 | bwd_inner_microstep: 274.08 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 01:49:19,163] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.30 | bwd_microstep: 272.73 | bwd_inner_microstep: 272.71 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 853 +[2025-05-02 01:49:19,405] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.53 | bwd_microstep: 133.34 | bwd_inner_microstep: 133.08 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:49:19,879] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.57 | bwd_microstep: 272.18 | bwd_inner_microstep: 272.17 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 01:49:20,356] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.62 | bwd_microstep: 272.89 | bwd_inner_microstep: 272.88 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 01:49:20,832] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.81 | bwd_microstep: 272.81 | bwd_inner_microstep: 272.79 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 01:49:21,310] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.38 | bwd_microstep: 272.90 | bwd_inner_microstep: 272.89 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 01:49:21,787] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.45 | bwd_microstep: 272.71 | bwd_inner_microstep: 272.69 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:49:22,265] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.27 | bwd_microstep: 272.86 | bwd_inner_microstep: 272.84 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:49:22,741] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.04 | bwd_microstep: 272.42 | bwd_inner_microstep: 272.40 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:49:23,218] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.41 | bwd_microstep: 272.46 | bwd_inner_microstep: 272.45 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:49:23,696] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.42 | bwd_microstep: 272.59 | bwd_inner_microstep: 272.57 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1346 +[2025-05-02 01:49:24,063] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.88 | bwd_microstep: 205.55 | bwd_inner_microstep: 205.52 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.11 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1345 +[2025-05-02 01:49:24,529] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.07 | optimizer_gradients: 2.25 | optimizer_step: 16.88 +[2025-05-02 01:49:24,529] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.02 | bwd_microstep: 283.39 | bwd_inner_microstep: 206.09 | bwd_allreduce_microstep: 77.14 | step_microstep: 24.88 +[2025-05-02 01:49:24,531] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2828.54 | bwd: 4180.50 | bwd_inner: 4102.72 | bwd_allreduce: 77.30 | step: 25.78 + 16%|█▌ | 1374/8720 [3:33:58<14:27:48, 7.09s/it] {'loss': 0.5918, 'grad_norm': 12.889321327209473, 'learning_rate': 9.579533869845017e-06, 'epoch': 1.58} + 16%|█▌ | 1374/8720 [3:33:58<14:27:48, 7.09s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 01:49:25,012] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.79 | bwd_microstep: 270.27 | bwd_inner_microstep: 270.25 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1924 +[2025-05-02 01:49:25,514] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.34 | bwd_microstep: 286.85 | bwd_inner_microstep: 286.83 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1913 +[2025-05-02 01:49:25,998] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.91 | bwd_microstep: 276.03 | bwd_inner_microstep: 276.01 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1899 +[2025-05-02 01:49:26,481] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.86 | bwd_microstep: 274.99 | bwd_inner_microstep: 274.97 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 870 +[2025-05-02 01:49:26,736] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 101.37 | bwd_microstep: 134.00 | bwd_inner_microstep: 133.72 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-02 01:49:27,216] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.26 | bwd_microstep: 273.85 | bwd_inner_microstep: 273.83 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-02 01:49:27,696] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.51 | bwd_microstep: 273.87 | bwd_inner_microstep: 273.85 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1883 +[2025-05-02 01:49:28,176] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.57 | bwd_microstep: 273.95 | bwd_inner_microstep: 273.94 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 344 +[2025-05-02 01:49:28,387] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 75.13 | bwd_microstep: 121.87 | bwd_inner_microstep: 121.72 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 01:49:28,864] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.73 | bwd_microstep: 273.37 | bwd_inner_microstep: 273.35 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 329 +[2025-05-02 01:49:29,077] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 76.74 | bwd_microstep: 122.47 | bwd_inner_microstep: 122.33 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 01:49:29,553] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.19 | bwd_microstep: 273.03 | bwd_inner_microstep: 273.02 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:49:30,031] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.99 | bwd_microstep: 272.61 | bwd_inner_microstep: 272.59 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:49:30,509] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.03 | bwd_microstep: 272.64 | bwd_inner_microstep: 272.62 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:49:30,986] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.53 | bwd_microstep: 271.26 | bwd_inner_microstep: 271.25 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:49:31,565] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.25 | optimizer_step: 16.70 +[2025-05-02 01:49:31,566] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.20 | bwd_microstep: 349.30 | bwd_inner_microstep: 272.75 | bwd_allreduce_microstep: 76.49 | step_microstep: 24.55 +[2025-05-02 01:49:31,567] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2710.83 | bwd: 4020.40 | bwd_inner: 3943.14 | bwd_allreduce: 76.79 | step: 25.42 + 16%|█▌ | 1375/8720 [3:34:05<14:25:46, 7.07s/it] {'loss': 0.8574, 'grad_norm': 8.427602767944336, 'learning_rate': 9.578788101605645e-06, 'epoch': 1.58} + 16%|█▌ | 1375/8720 [3:34:05<14:25:46, 7.07s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:49:32,049] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.38 | bwd_microstep: 270.46 | bwd_inner_microstep: 270.44 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1895 +[2025-05-02 01:49:32,531] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.04 | bwd_microstep: 275.29 | bwd_inner_microstep: 275.27 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1899 +[2025-05-02 01:49:33,015] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.26 | bwd_microstep: 275.53 | bwd_inner_microstep: 275.52 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 01:49:33,495] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.20 | bwd_microstep: 273.22 | bwd_inner_microstep: 273.20 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-02 01:49:33,975] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.78 | bwd_microstep: 273.71 | bwd_inner_microstep: 273.69 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1105 +[2025-05-02 01:49:34,269] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 115.49 | bwd_microstep: 161.47 | bwd_inner_microstep: 161.30 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 01:49:34,747] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.62 | bwd_microstep: 272.99 | bwd_inner_microstep: 272.97 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 01:49:35,228] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.44 | bwd_microstep: 272.93 | bwd_inner_microstep: 272.91 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 857 +[2025-05-02 01:49:35,482] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 102.19 | bwd_microstep: 133.20 | bwd_inner_microstep: 132.97 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 01:49:35,962] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.20 | bwd_microstep: 272.95 | bwd_inner_microstep: 272.93 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.15 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:49:36,442] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.02 | bwd_microstep: 273.06 | bwd_inner_microstep: 273.04 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 01:49:36,921] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.52 | bwd_microstep: 273.11 | bwd_inner_microstep: 273.09 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:49:37,401] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.37 | bwd_microstep: 271.29 | bwd_inner_microstep: 271.27 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 01:49:37,882] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.27 | bwd_microstep: 271.16 | bwd_inner_microstep: 271.14 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 01:49:38,359] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.60 | bwd_microstep: 270.93 | bwd_inner_microstep: 270.92 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 827 +[2025-05-02 01:49:38,700] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.16 | optimizer_step: 16.55 +[2025-05-02 01:49:38,700] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.77 | bwd_microstep: 207.06 | bwd_inner_microstep: 130.06 | bwd_allreduce_microstep: 76.84 | step_microstep: 24.17 +[2025-05-02 01:49:38,702] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2764.78 | bwd: 4048.39 | bwd_inner: 3970.78 | bwd_allreduce: 77.08 | step: 25.24 + 16%|█▌ | 1376/8720 [3:34:12<14:27:58, 7.09s/it] {'loss': 0.6894, 'grad_norm': 11.816575050354004, 'learning_rate': 9.578041701660385e-06, 'epoch': 1.58} + 16%|█▌ | 1376/8720 [3:34:12<14:27:58, 7.09s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 01:49:39,184] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.65 | bwd_microstep: 270.29 | bwd_inner_microstep: 270.28 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 388 +[2025-05-02 01:49:39,391] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 74.01 | bwd_microstep: 117.29 | bwd_inner_microstep: 117.15 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1892 +[2025-05-02 01:49:39,871] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.80 | bwd_microstep: 275.23 | bwd_inner_microstep: 275.21 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 343 +[2025-05-02 01:49:40,084] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 80.50 | bwd_microstep: 119.52 | bwd_inner_microstep: 119.31 | bwd_allreduce_microstep: 0.08 | step_microstep: 0.13 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1883 +[2025-05-02 01:49:40,564] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.69 | bwd_microstep: 274.22 | bwd_inner_microstep: 274.20 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 01:49:41,045] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.05 | bwd_microstep: 273.22 | bwd_inner_microstep: 273.20 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 338 +[2025-05-02 01:49:41,288] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 104.08 | bwd_microstep: 119.38 | bwd_inner_microstep: 119.23 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.09 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 841 +[2025-05-02 01:49:41,531] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.62 | bwd_microstep: 132.51 | bwd_inner_microstep: 132.44 | bwd_allreduce_microstep: 0.03 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 01:49:42,010] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.25 | bwd_microstep: 273.05 | bwd_inner_microstep: 273.03 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 01:49:42,490] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.08 | bwd_microstep: 273.23 | bwd_inner_microstep: 273.21 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:49:42,970] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.32 | bwd_microstep: 272.57 | bwd_inner_microstep: 272.55 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 01:49:43,450] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.14 | bwd_microstep: 273.16 | bwd_inner_microstep: 273.14 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:49:43,927] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.61 | bwd_microstep: 271.25 | bwd_inner_microstep: 271.23 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:49:44,405] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.93 | bwd_microstep: 271.39 | bwd_inner_microstep: 271.37 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:49:44,883] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.76 | bwd_microstep: 271.38 | bwd_inner_microstep: 271.36 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 830 +[2025-05-02 01:49:45,222] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.19 | optimizer_step: 16.61 +[2025-05-02 01:49:45,223] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.10 | bwd_microstep: 206.57 | bwd_inner_microstep: 130.36 | bwd_allreduce_microstep: 76.11 | step_microstep: 24.25 +[2025-05-02 01:49:45,224] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2523.26 | bwd: 3694.32 | bwd_inner: 3617.40 | bwd_allreduce: 76.39 | step: 25.20 + 16%|█▌ | 1377/8720 [3:34:18<14:06:57, 6.92s/it] {'loss': 0.7253, 'grad_norm': 6.109982967376709, 'learning_rate': 9.577294670112216e-06, 'epoch': 1.58} + 16%|█▌ | 1377/8720 [3:34:18<14:06:57, 6.92s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 01:49:45,705] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.71 | bwd_microstep: 270.39 | bwd_inner_microstep: 270.37 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 367 +[2025-05-02 01:49:45,910] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 71.47 | bwd_microstep: 117.91 | bwd_inner_microstep: 117.77 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1888 +[2025-05-02 01:49:46,389] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.94 | bwd_microstep: 274.62 | bwd_inner_microstep: 274.60 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1368 +[2025-05-02 01:49:46,753] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 142.31 | bwd_microstep: 207.27 | bwd_inner_microstep: 207.25 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 856 +[2025-05-02 01:49:46,996] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 96.01 | bwd_microstep: 133.23 | bwd_inner_microstep: 133.12 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:49:47,470] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.59 | bwd_microstep: 272.04 | bwd_inner_microstep: 272.02 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 01:49:47,947] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.12 | bwd_microstep: 272.51 | bwd_inner_microstep: 272.49 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-02 01:49:48,426] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.09 | bwd_microstep: 273.44 | bwd_inner_microstep: 273.42 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1362 +[2025-05-02 01:49:48,791] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.78 | bwd_microstep: 206.26 | bwd_inner_microstep: 206.16 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.10 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 333 +[2025-05-02 01:49:49,009] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 82.91 | bwd_microstep: 119.34 | bwd_inner_microstep: 119.19 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 01:49:49,487] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.12 | bwd_microstep: 272.77 | bwd_inner_microstep: 272.75 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 01:49:49,967] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.03 | bwd_microstep: 272.95 | bwd_inner_microstep: 272.93 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:49:50,446] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.04 | bwd_microstep: 272.61 | bwd_inner_microstep: 272.59 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1350 +[2025-05-02 01:49:50,812] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.77 | bwd_microstep: 206.45 | bwd_inner_microstep: 206.32 | bwd_allreduce_microstep: 0.08 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:49:51,290] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.85 | bwd_microstep: 272.34 | bwd_inner_microstep: 272.32 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:49:51,866] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.04 | optimizer_gradients: 2.17 | optimizer_step: 16.59 +[2025-05-02 01:49:51,866] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.44 | bwd_microstep: 347.51 | bwd_inner_microstep: 271.60 | bwd_allreduce_microstep: 75.87 | step_microstep: 23.55 +[2025-05-02 01:49:51,868] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2559.87 | bwd: 3791.71 | bwd_inner: 3714.99 | bwd_allreduce: 76.25 | step: 24.49 + 16%|█▌ | 1378/8720 [3:34:25<13:56:35, 6.84s/it] {'loss': 0.8341, 'grad_norm': 7.5460405349731445, 'learning_rate': 9.576547007064196e-06, 'epoch': 1.58} + 16%|█▌ | 1378/8720 [3:34:25<13:56:35, 6.84s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:49:52,345] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.39 | bwd_microstep: 270.54 | bwd_inner_microstep: 270.52 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1899 +[2025-05-02 01:49:52,827] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.21 | bwd_microstep: 275.65 | bwd_inner_microstep: 275.63 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1895 +[2025-05-02 01:49:53,309] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.68 | bwd_microstep: 275.09 | bwd_inner_microstep: 275.07 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-02 01:49:53,787] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.00 | bwd_microstep: 273.68 | bwd_inner_microstep: 273.67 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 01:49:54,266] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.75 | bwd_microstep: 272.99 | bwd_inner_microstep: 272.98 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 01:49:54,744] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.08 | bwd_microstep: 273.32 | bwd_inner_microstep: 273.30 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.14 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 01:49:55,226] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.02 | bwd_microstep: 273.20 | bwd_inner_microstep: 273.18 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:49:55,705] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.14 | bwd_microstep: 272.58 | bwd_inner_microstep: 272.57 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 01:49:56,184] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.81 | bwd_microstep: 272.45 | bwd_inner_microstep: 272.43 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 01:49:56,663] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.60 | bwd_microstep: 272.41 | bwd_inner_microstep: 272.39 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1344 +[2025-05-02 01:49:57,026] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.66 | bwd_microstep: 204.56 | bwd_inner_microstep: 204.53 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:49:57,503] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.13 | bwd_microstep: 271.48 | bwd_inner_microstep: 271.46 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 01:49:57,981] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.33 | bwd_microstep: 271.58 | bwd_inner_microstep: 271.56 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:49:58,461] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.92 | bwd_microstep: 271.27 | bwd_inner_microstep: 271.25 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:49:58,940] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.47 | bwd_microstep: 271.19 | bwd_inner_microstep: 271.17 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 01:49:59,520] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.15 | optimizer_step: 16.58 +[2025-05-02 01:49:59,521] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.68 | bwd_microstep: 350.15 | bwd_inner_microstep: 272.06 | bwd_allreduce_microstep: 78.04 | step_microstep: 24.24 +[2025-05-02 01:49:59,522] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2972.52 | bwd: 4372.18 | bwd_inner: 4293.78 | bwd_allreduce: 78.12 | step: 25.37 + 16%|█▌ | 1379/8720 [3:34:33<14:26:33, 7.08s/it] {'loss': 0.8605, 'grad_norm': 10.833151817321777, 'learning_rate': 9.57579871261948e-06, 'epoch': 1.58} + 16%|█▌ | 1379/8720 [3:34:33<14:26:33, 7.08s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 315 +[2025-05-02 01:49:59,745] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 79.12 | bwd_microstep: 122.51 | bwd_inner_microstep: 122.35 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1894 +[2025-05-02 01:50:00,228] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.31 | bwd_microstep: 275.39 | bwd_inner_microstep: 275.37 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 341 +[2025-05-02 01:50:00,455] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 91.69 | bwd_microstep: 117.69 | bwd_inner_microstep: 117.54 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 01:50:00,935] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.85 | bwd_microstep: 274.07 | bwd_inner_microstep: 274.06 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 01:50:01,420] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.04 | bwd_microstep: 273.98 | bwd_inner_microstep: 273.96 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 01:50:01,902] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.99 | bwd_microstep: 273.36 | bwd_inner_microstep: 273.34 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 01:50:02,383] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.27 | bwd_microstep: 273.35 | bwd_inner_microstep: 273.34 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 6, images per sample: 6.0, dynamic token length: 1607 +[2025-05-02 01:50:02,809] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 164.18 | bwd_microstep: 243.76 | bwd_inner_microstep: 243.74 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:50:03,286] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.32 | bwd_microstep: 272.03 | bwd_inner_microstep: 272.01 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 01:50:03,764] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.58 | bwd_microstep: 272.74 | bwd_inner_microstep: 272.72 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:50:04,241] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.97 | bwd_microstep: 271.41 | bwd_inner_microstep: 271.39 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 01:50:04,716] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.93 | bwd_microstep: 271.07 | bwd_inner_microstep: 271.05 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 01:50:05,193] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.90 | bwd_microstep: 271.73 | bwd_inner_microstep: 271.71 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 01:50:05,666] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.60 | bwd_microstep: 270.78 | bwd_inner_microstep: 270.76 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 315 +[2025-05-02 01:50:05,867] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 73.22 | bwd_microstep: 115.07 | bwd_inner_microstep: 114.77 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 01:50:06,430] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.15 | optimizer_step: 16.61 +[2025-05-02 01:50:06,431] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.37 | bwd_microstep: 337.72 | bwd_inner_microstep: 271.59 | bwd_allreduce_microstep: 66.08 | step_microstep: 23.66 +[2025-05-02 01:50:06,432] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2672.01 | bwd: 3936.72 | bwd_inner: 3869.81 | bwd_allreduce: 66.39 | step: 24.67 + 16%|█▌ | 1380/8720 [3:34:40<14:20:02, 7.03s/it] {'loss': 0.625, 'grad_norm': 13.587566375732422, 'learning_rate': 9.575049786881304e-06, 'epoch': 1.58} + 16%|█▌ | 1380/8720 [3:34:40<14:20:02, 7.03s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 314 +[2025-05-02 01:50:06,642] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 70.77 | bwd_microstep: 121.35 | bwd_inner_microstep: 121.22 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 400 +[2025-05-02 01:50:06,848] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 74.45 | bwd_microstep: 119.06 | bwd_inner_microstep: 118.91 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1930 +[2025-05-02 01:50:07,345] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 194.55 | bwd_microstep: 287.38 | bwd_inner_microstep: 287.36 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-02 01:50:07,823] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.01 | bwd_microstep: 273.98 | bwd_inner_microstep: 273.97 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 334 +[2025-05-02 01:50:08,051] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 85.18 | bwd_microstep: 127.23 | bwd_inner_microstep: 126.91 | bwd_allreduce_microstep: 0.14 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1890 +[2025-05-02 01:50:08,533] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.54 | bwd_microstep: 274.68 | bwd_inner_microstep: 274.66 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-02 01:50:09,010] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.52 | bwd_microstep: 274.01 | bwd_inner_microstep: 273.99 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 328 +[2025-05-02 01:50:09,223] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 79.47 | bwd_microstep: 118.55 | bwd_inner_microstep: 118.26 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:50:09,700] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.96 | bwd_microstep: 272.55 | bwd_inner_microstep: 272.53 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 01:50:10,180] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.78 | bwd_microstep: 272.76 | bwd_inner_microstep: 272.75 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 837 +[2025-05-02 01:50:10,416] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.59 | bwd_microstep: 126.07 | bwd_inner_microstep: 125.94 | bwd_allreduce_microstep: 0.09 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:50:10,895] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.76 | bwd_microstep: 272.38 | bwd_inner_microstep: 272.36 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:50:11,376] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.02 | bwd_microstep: 272.27 | bwd_inner_microstep: 272.25 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:50:11,853] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.22 | bwd_microstep: 271.26 | bwd_inner_microstep: 271.24 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1850 +[2025-05-02 01:50:12,329] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.65 | bwd_microstep: 271.31 | bwd_inner_microstep: 271.29 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1924 +[2025-05-02 01:50:12,928] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.17 | optimizer_step: 16.58 +[2025-05-02 01:50:12,929] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 194.35 | bwd_microstep: 364.22 | bwd_inner_microstep: 287.68 | bwd_allreduce_microstep: 76.49 | step_microstep: 24.17 +[2025-05-02 01:50:12,930] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2490.48 | bwd: 3719.13 | bwd_inner: 3641.50 | bwd_allreduce: 77.00 | step: 25.10 + 16%|█▌ | 1381/8720 [3:34:46<14:00:27, 6.87s/it] {'loss': 0.7364, 'grad_norm': 6.958860874176025, 'learning_rate': 9.57430022995299e-06, 'epoch': 1.58} + 16%|█▌ | 1381/8720 [3:34:46<14:00:27, 6.87s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 01:50:13,413] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.67 | bwd_microstep: 271.99 | bwd_inner_microstep: 271.97 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2201 +[2025-05-02 01:50:13,959] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 208.99 | bwd_microstep: 321.77 | bwd_inner_microstep: 321.75 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 437 +[2025-05-02 01:50:14,164] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 68.37 | bwd_microstep: 123.27 | bwd_inner_microstep: 122.97 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1897 +[2025-05-02 01:50:14,643] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.83 | bwd_microstep: 275.00 | bwd_inner_microstep: 274.99 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 01:50:15,120] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.47 | bwd_microstep: 272.88 | bwd_inner_microstep: 272.86 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-02 01:50:15,598] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.83 | bwd_microstep: 273.41 | bwd_inner_microstep: 273.40 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 837 +[2025-05-02 01:50:15,830] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 91.83 | bwd_microstep: 126.30 | bwd_inner_microstep: 126.09 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.11 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 835 +[2025-05-02 01:50:16,061] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 91.17 | bwd_microstep: 125.85 | bwd_inner_microstep: 125.64 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.18 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 838 +[2025-05-02 01:50:16,292] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 91.66 | bwd_microstep: 126.26 | bwd_inner_microstep: 126.02 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 01:50:16,768] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.28 | bwd_microstep: 272.76 | bwd_inner_microstep: 272.74 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1349 +[2025-05-02 01:50:17,128] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 139.70 | bwd_microstep: 205.66 | bwd_inner_microstep: 205.58 | bwd_allreduce_microstep: 0.03 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:50:17,604] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.51 | bwd_microstep: 272.10 | bwd_inner_microstep: 272.08 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:50:18,077] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.48 | bwd_microstep: 271.13 | bwd_inner_microstep: 271.12 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 01:50:18,551] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.01 | bwd_microstep: 270.99 | bwd_inner_microstep: 270.97 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 01:50:19,025] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.45 | bwd_microstep: 271.24 | bwd_inner_microstep: 271.22 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 01:50:19,588] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.04 | optimizer_gradients: 2.14 | optimizer_step: 16.58 +[2025-05-02 01:50:19,588] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.35 | bwd_microstep: 338.33 | bwd_inner_microstep: 271.68 | bwd_allreduce_microstep: 66.61 | step_microstep: 23.57 +[2025-05-02 01:50:19,590] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2572.34 | bwd: 3819.06 | bwd_inner: 3751.14 | bwd_allreduce: 67.20 | step: 24.53 + 16%|█▌ | 1382/8720 [3:34:53<13:52:30, 6.81s/it] {'loss': 0.6891, 'grad_norm': 14.235064506530762, 'learning_rate': 9.57355004193795e-06, 'epoch': 1.58} + 16%|█▌ | 1382/8720 [3:34:53<13:52:30, 6.81s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2168 +[2025-05-02 01:50:20,133] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 207.10 | bwd_microstep: 316.12 | bwd_inner_microstep: 316.11 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.07 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 362 +[2025-05-02 01:50:20,339] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 74.28 | bwd_microstep: 118.34 | bwd_inner_microstep: 118.03 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1889 +[2025-05-02 01:50:20,819] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.83 | bwd_microstep: 274.45 | bwd_inner_microstep: 274.43 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1358 +[2025-05-02 01:50:21,183] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.22 | bwd_microstep: 206.45 | bwd_inner_microstep: 206.37 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 01:50:21,660] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.56 | bwd_microstep: 272.97 | bwd_inner_microstep: 272.95 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1350 +[2025-05-02 01:50:22,023] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.13 | bwd_microstep: 205.78 | bwd_inner_microstep: 205.64 | bwd_allreduce_microstep: 0.04 | step_microstep: 0.09 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 845 +[2025-05-02 01:50:22,261] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 92.70 | bwd_microstep: 132.24 | bwd_inner_microstep: 131.94 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 333 +[2025-05-02 01:50:22,465] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 69.15 | bwd_microstep: 121.45 | bwd_inner_microstep: 121.31 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 01:50:22,940] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.19 | bwd_microstep: 272.50 | bwd_inner_microstep: 272.48 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:50:23,415] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.38 | bwd_microstep: 272.41 | bwd_inner_microstep: 272.39 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:50:23,892] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.68 | bwd_microstep: 272.50 | bwd_inner_microstep: 272.49 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:50:24,367] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.21 | bwd_microstep: 272.29 | bwd_inner_microstep: 272.27 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:50:24,842] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.97 | bwd_microstep: 272.25 | bwd_inner_microstep: 272.23 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:50:25,318] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.11 | bwd_microstep: 272.08 | bwd_inner_microstep: 272.07 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:50:25,793] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.04 | bwd_microstep: 271.42 | bwd_inner_microstep: 271.40 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:50:26,358] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.13 | optimizer_step: 16.51 +[2025-05-02 01:50:26,359] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.42 | bwd_microstep: 338.55 | bwd_inner_microstep: 271.65 | bwd_allreduce_microstep: 66.85 | step_microstep: 23.52 +[2025-05-02 01:50:26,360] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2606.70 | bwd: 3891.93 | bwd_inner: 3823.88 | bwd_allreduce: 67.35 | step: 24.45 + 16%|█▌ | 1383/8720 [3:35:00<13:51:03, 6.80s/it] {'loss': 0.763, 'grad_norm': 9.229952812194824, 'learning_rate': 9.572799222939688e-06, 'epoch': 1.59} + 16%|█▌ | 1383/8720 [3:35:00<13:51:03, 6.80s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 01:50:26,838] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.48 | bwd_microstep: 270.30 | bwd_inner_microstep: 270.28 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1908 +[2025-05-02 01:50:27,319] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.82 | bwd_microstep: 276.03 | bwd_inner_microstep: 276.01 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 880 +[2025-05-02 01:50:27,564] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.23 | bwd_microstep: 134.84 | bwd_inner_microstep: 134.75 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 01:50:28,039] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.63 | bwd_microstep: 273.40 | bwd_inner_microstep: 273.38 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-02 01:50:28,517] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.63 | bwd_microstep: 273.39 | bwd_inner_microstep: 273.37 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-02 01:50:28,995] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.07 | bwd_microstep: 273.59 | bwd_inner_microstep: 273.57 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 01:50:29,473] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.57 | bwd_microstep: 273.09 | bwd_inner_microstep: 273.07 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 839 +[2025-05-02 01:50:29,707] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 92.95 | bwd_microstep: 126.31 | bwd_inner_microstep: 126.04 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.13 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1348 +[2025-05-02 01:50:30,068] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.20 | bwd_microstep: 205.23 | bwd_inner_microstep: 205.22 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:50:30,545] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.01 | bwd_microstep: 272.44 | bwd_inner_microstep: 272.42 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:50:31,022] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.96 | bwd_microstep: 272.34 | bwd_inner_microstep: 272.32 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:50:31,501] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.10 | bwd_microstep: 272.31 | bwd_inner_microstep: 272.29 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 319 +[2025-05-02 01:50:31,718] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 81.22 | bwd_microstep: 120.13 | bwd_inner_microstep: 119.82 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.12 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1345 +[2025-05-02 01:50:32,082] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 139.91 | bwd_microstep: 205.55 | bwd_inner_microstep: 205.53 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:50:32,556] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.21 | bwd_microstep: 270.88 | bwd_inner_microstep: 270.87 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 321 +[2025-05-02 01:50:32,919] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.24 | optimizer_step: 16.71 +[2025-05-02 01:50:32,920] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 87.16 | bwd_microstep: 236.49 | bwd_inner_microstep: 160.17 | bwd_allreduce_microstep: 76.15 | step_microstep: 24.26 +[2025-05-02 01:50:32,921] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2518.86 | bwd: 3756.39 | bwd_inner: 3679.27 | bwd_allreduce: 76.47 | step: 25.13 + 16%|█▌ | 1384/8720 [3:35:06<13:42:19, 6.73s/it] {'loss': 0.5722, 'grad_norm': 7.4184441566467285, 'learning_rate': 9.572047773061783e-06, 'epoch': 1.59} + 16%|█▌ | 1384/8720 [3:35:06<13:42:19, 6.73s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:50:33,399] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.45 | bwd_microstep: 270.32 | bwd_inner_microstep: 270.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-02 01:50:33,878] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.04 | bwd_microstep: 274.44 | bwd_inner_microstep: 274.42 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.13 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1889 +[2025-05-02 01:50:34,359] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.50 | bwd_microstep: 274.40 | bwd_inner_microstep: 274.38 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-02 01:50:34,840] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.30 | bwd_microstep: 273.58 | bwd_inner_microstep: 273.56 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-02 01:50:35,322] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.30 | bwd_microstep: 273.65 | bwd_inner_microstep: 273.64 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-02 01:50:35,803] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.49 | bwd_microstep: 273.53 | bwd_inner_microstep: 273.51 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 01:50:36,284] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.79 | bwd_microstep: 272.88 | bwd_inner_microstep: 272.86 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 01:50:36,767] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.64 | bwd_microstep: 272.81 | bwd_inner_microstep: 272.79 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 01:50:37,245] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.49 | bwd_microstep: 272.55 | bwd_inner_microstep: 272.54 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:50:37,724] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.43 | bwd_microstep: 272.64 | bwd_inner_microstep: 272.62 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 01:50:38,202] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.05 | bwd_microstep: 272.29 | bwd_inner_microstep: 272.27 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 01:50:38,677] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.66 | bwd_microstep: 271.14 | bwd_inner_microstep: 271.12 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:50:39,152] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.03 | bwd_microstep: 271.15 | bwd_inner_microstep: 271.14 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:50:39,630] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.31 | bwd_microstep: 272.40 | bwd_inner_microstep: 272.38 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 01:50:40,109] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.39 | bwd_microstep: 272.36 | bwd_inner_microstep: 272.34 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 01:50:40,681] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.21 | optimizer_step: 16.67 +[2025-05-02 01:50:40,682] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.32 | bwd_microstep: 343.44 | bwd_inner_microstep: 271.53 | bwd_allreduce_microstep: 71.87 | step_microstep: 23.89 +[2025-05-02 01:50:40,683] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 3010.86 | bwd: 4433.59 | bwd_inner: 4361.40 | bwd_allreduce: 71.95 | step: 24.89 + 16%|█▌ | 1385/8720 [3:35:14<14:20:12, 7.04s/it] {'loss': 0.6035, 'grad_norm': 8.267311096191406, 'learning_rate': 9.571295692407912e-06, 'epoch': 1.59} + 16%|█▌ | 1385/8720 [3:35:14<14:20:12, 7.04s/it]dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1435 +[2025-05-02 01:50:41,061] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 144.46 | bwd_microstep: 214.25 | bwd_inner_microstep: 214.14 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.09 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 383 +[2025-05-02 01:50:41,266] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 68.84 | bwd_microstep: 122.03 | bwd_inner_microstep: 121.84 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1929 +[2025-05-02 01:50:41,764] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.95 | bwd_microstep: 287.40 | bwd_inner_microstep: 287.38 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.16 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1888 +[2025-05-02 01:50:42,242] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.61 | bwd_microstep: 274.24 | bwd_inner_microstep: 274.22 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-02 01:50:42,719] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.88 | bwd_microstep: 272.79 | bwd_inner_microstep: 272.77 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 334 +[2025-05-02 01:50:42,923] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 69.19 | bwd_microstep: 119.48 | bwd_inner_microstep: 119.18 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.24 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 329 +[2025-05-02 01:50:43,142] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 85.37 | bwd_microstep: 118.57 | bwd_inner_microstep: 118.44 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 335 +[2025-05-02 01:50:43,350] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 72.56 | bwd_microstep: 122.48 | bwd_inner_microstep: 122.34 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.10 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 323 +[2025-05-02 01:50:43,557] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 72.44 | bwd_microstep: 120.86 | bwd_inner_microstep: 120.73 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.10 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1345 +[2025-05-02 01:50:43,917] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.15 | bwd_microstep: 205.06 | bwd_inner_microstep: 204.90 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.10 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1344 +[2025-05-02 01:50:44,275] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 139.21 | bwd_microstep: 204.05 | bwd_inner_microstep: 203.99 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:50:44,749] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.05 | bwd_microstep: 271.86 | bwd_inner_microstep: 271.84 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:50:45,225] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.08 | bwd_microstep: 270.98 | bwd_inner_microstep: 270.97 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:50:45,700] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.60 | bwd_microstep: 270.92 | bwd_inner_microstep: 270.90 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:50:46,176] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.39 | bwd_microstep: 270.78 | bwd_inner_microstep: 270.76 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 317 +[2025-05-02 01:50:46,510] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.25 | optimizer_step: 16.79 +[2025-05-02 01:50:46,511] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 84.00 | bwd_microstep: 209.76 | bwd_inner_microstep: 132.70 | bwd_allreduce_microstep: 76.93 | step_microstep: 24.72 +[2025-05-02 01:50:46,512] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2198.52 | bwd: 3355.65 | bwd_inner: 3277.34 | bwd_allreduce: 77.50 | step: 26.12 + 16%|█▌ | 1386/8720 [3:35:20<13:35:52, 6.67s/it] {'loss': 0.7677, 'grad_norm': 10.19886589050293, 'learning_rate': 9.570542981081833e-06, 'epoch': 1.59} + 16%|█▌ | 1386/8720 [3:35:20<13:35:52, 6.67s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1899 +[2025-05-02 01:50:46,999] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.19 | bwd_microstep: 274.55 | bwd_inner_microstep: 274.54 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2113 +[2025-05-02 01:50:47,532] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 203.10 | bwd_microstep: 311.82 | bwd_inner_microstep: 311.81 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2053 +[2025-05-02 01:50:48,052] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 200.35 | bwd_microstep: 301.56 | bwd_inner_microstep: 301.54 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1130 +[2025-05-02 01:50:48,348] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 116.26 | bwd_microstep: 163.29 | bwd_inner_microstep: 163.20 | bwd_allreduce_microstep: 0.04 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-02 01:50:48,831] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.81 | bwd_microstep: 274.03 | bwd_inner_microstep: 274.01 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-02 01:50:49,315] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.54 | bwd_microstep: 273.97 | bwd_inner_microstep: 273.95 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 337 +[2025-05-02 01:50:49,543] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 87.38 | bwd_microstep: 123.19 | bwd_inner_microstep: 123.04 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-02 01:50:50,021] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.08 | bwd_microstep: 273.16 | bwd_inner_microstep: 273.14 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-02 01:50:50,503] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.87 | bwd_microstep: 273.55 | bwd_inner_microstep: 273.53 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 01:50:50,986] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.00 | bwd_microstep: 272.72 | bwd_inner_microstep: 272.70 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 838 +[2025-05-02 01:50:51,230] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 101.29 | bwd_microstep: 125.51 | bwd_inner_microstep: 125.29 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.18 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1351 +[2025-05-02 01:50:51,596] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.54 | bwd_microstep: 205.85 | bwd_inner_microstep: 205.80 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.10 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1356 +[2025-05-02 01:50:51,962] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.65 | bwd_microstep: 205.94 | bwd_inner_microstep: 205.78 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:50:52,441] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.18 | bwd_microstep: 271.91 | bwd_inner_microstep: 271.90 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:50:52,920] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.01 | bwd_microstep: 270.99 | bwd_inner_microstep: 270.98 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 01:50:53,502] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.19 | optimizer_step: 16.75 +[2025-05-02 01:50:53,502] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.09 | bwd_microstep: 348.71 | bwd_inner_microstep: 271.22 | bwd_allreduce_microstep: 77.44 | step_microstep: 24.66 +[2025-05-02 01:50:53,504] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2685.94 | bwd: 3970.87 | bwd_inner: 3892.47 | bwd_allreduce: 77.91 | step: 25.78 + 16%|█▌ | 1387/8720 [3:35:27<13:47:23, 6.77s/it] {'loss': 1.1169, 'grad_norm': 7.676445960998535, 'learning_rate': 9.569789639187392e-06, 'epoch': 1.59} + 16%|█▌ | 1387/8720 [3:35:27<13:47:23, 6.77s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:50:53,985] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.67 | bwd_microstep: 270.47 | bwd_inner_microstep: 270.45 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1759 +[2025-05-02 01:50:54,422] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 164.16 | bwd_microstep: 255.07 | bwd_inner_microstep: 255.05 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 422 +[2025-05-02 01:50:54,634] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 71.36 | bwd_microstep: 127.61 | bwd_inner_microstep: 127.36 | bwd_allreduce_microstep: 0.10 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1913 +[2025-05-02 01:50:55,116] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.78 | bwd_microstep: 276.00 | bwd_inner_microstep: 275.98 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1894 +[2025-05-02 01:50:55,595] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.89 | bwd_microstep: 274.86 | bwd_inner_microstep: 274.85 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 865 +[2025-05-02 01:50:55,839] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.39 | bwd_microstep: 133.96 | bwd_inner_microstep: 133.76 | bwd_allreduce_microstep: 0.08 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-02 01:50:56,317] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.29 | bwd_microstep: 274.03 | bwd_inner_microstep: 274.01 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-02 01:50:56,795] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.46 | bwd_microstep: 273.66 | bwd_inner_microstep: 273.64 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 01:50:57,271] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.79 | bwd_microstep: 272.57 | bwd_inner_microstep: 272.56 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 844 +[2025-05-02 01:50:57,512] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.07 | bwd_microstep: 132.10 | bwd_inner_microstep: 131.96 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:50:57,988] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.84 | bwd_microstep: 272.34 | bwd_inner_microstep: 272.33 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 01:50:58,466] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.39 | bwd_microstep: 272.92 | bwd_inner_microstep: 272.91 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 01:50:58,943] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.94 | bwd_microstep: 272.75 | bwd_inner_microstep: 272.74 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 01:50:59,420] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.22 | bwd_microstep: 272.69 | bwd_inner_microstep: 272.67 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:50:59,897] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.13 | bwd_microstep: 272.26 | bwd_inner_microstep: 272.24 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 01:51:00,462] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.04 | optimizer_gradients: 2.14 | optimizer_step: 16.54 +[2025-05-02 01:51:00,462] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.47 | bwd_microstep: 338.16 | bwd_inner_microstep: 271.79 | bwd_allreduce_microstep: 66.32 | step_microstep: 23.58 +[2025-05-02 01:51:00,463] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2683.57 | bwd: 3991.52 | bwd_inner: 3924.41 | bwd_allreduce: 66.57 | step: 24.45 + 16%|█▌ | 1388/8720 [3:35:34<13:54:10, 6.83s/it] {'loss': 0.758, 'grad_norm': 11.065876007080078, 'learning_rate': 9.569035666828526e-06, 'epoch': 1.59} + 16%|█▌ | 1388/8720 [3:35:34<13:54:10, 6.83s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1899 +[2025-05-02 01:51:00,948] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.72 | bwd_microstep: 274.68 | bwd_inner_microstep: 274.67 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 898 +[2025-05-02 01:51:01,206] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 100.53 | bwd_microstep: 143.74 | bwd_inner_microstep: 143.53 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1919 +[2025-05-02 01:51:01,690] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 191.84 | bwd_microstep: 276.53 | bwd_inner_microstep: 276.51 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1900 +[2025-05-02 01:51:02,170] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.49 | bwd_microstep: 275.36 | bwd_inner_microstep: 275.34 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 350 +[2025-05-02 01:51:02,376] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 76.06 | bwd_microstep: 117.22 | bwd_inner_microstep: 117.08 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-02 01:51:02,852] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.93 | bwd_microstep: 273.25 | bwd_inner_microstep: 273.23 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 01:51:03,328] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.29 | bwd_microstep: 272.71 | bwd_inner_microstep: 272.69 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 01:51:03,805] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.52 | bwd_microstep: 272.90 | bwd_inner_microstep: 272.88 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 322 +[2025-05-02 01:51:04,004] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 68.06 | bwd_microstep: 118.16 | bwd_inner_microstep: 117.91 | bwd_allreduce_microstep: 0.10 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 01:51:04,480] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.20 | bwd_microstep: 272.99 | bwd_inner_microstep: 272.97 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1094 +[2025-05-02 01:51:04,771] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 115.27 | bwd_microstep: 161.26 | bwd_inner_microstep: 161.12 | bwd_allreduce_microstep: 0.10 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:51:05,246] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.91 | bwd_microstep: 272.48 | bwd_inner_microstep: 272.46 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:51:05,723] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.75 | bwd_microstep: 272.30 | bwd_inner_microstep: 272.28 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 01:51:06,199] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.33 | bwd_microstep: 272.36 | bwd_inner_microstep: 272.34 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:51:06,674] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.97 | bwd_microstep: 271.26 | bwd_inner_microstep: 271.24 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 01:51:07,237] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.15 | optimizer_step: 16.62 +[2025-05-02 01:51:07,237] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.53 | bwd_microstep: 337.51 | bwd_inner_microstep: 271.33 | bwd_allreduce_microstep: 66.13 | step_microstep: 23.73 +[2025-05-02 01:51:07,238] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2625.13 | bwd: 3884.78 | bwd_inner: 3817.68 | bwd_allreduce: 66.55 | step: 24.64 + 16%|█▌ | 1389/8720 [3:35:40<13:52:10, 6.81s/it] {'loss': 0.8426, 'grad_norm': 8.6209077835083, 'learning_rate': 9.56828106410925e-06, 'epoch': 1.59} + 16%|█▌ | 1389/8720 [3:35:40<13:52:10, 6.81s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 01:51:07,717] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.24 | bwd_microstep: 270.30 | bwd_inner_microstep: 270.28 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1949 +[2025-05-02 01:51:08,217] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.66 | bwd_microstep: 289.58 | bwd_inner_microstep: 289.56 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1910 +[2025-05-02 01:51:08,698] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.41 | bwd_microstep: 276.30 | bwd_inner_microstep: 276.28 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1922 +[2025-05-02 01:51:09,195] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.25 | bwd_microstep: 286.86 | bwd_inner_microstep: 286.84 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1117 +[2025-05-02 01:51:09,489] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 116.95 | bwd_microstep: 162.68 | bwd_inner_microstep: 162.51 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.18 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1364 +[2025-05-02 01:51:09,852] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.81 | bwd_microstep: 206.80 | bwd_inner_microstep: 206.78 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 01:51:10,329] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.97 | bwd_microstep: 272.88 | bwd_inner_microstep: 272.86 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-02 01:51:10,806] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.84 | bwd_microstep: 273.43 | bwd_inner_microstep: 273.42 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 328 +[2025-05-02 01:51:11,021] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 81.34 | bwd_microstep: 119.09 | bwd_inner_microstep: 118.79 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 01:51:11,497] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.30 | bwd_microstep: 272.91 | bwd_inner_microstep: 272.89 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 326 +[2025-05-02 01:51:11,737] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 84.52 | bwd_microstep: 142.20 | bwd_inner_microstep: 142.07 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 321 +[2025-05-02 01:51:11,953] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 80.40 | bwd_microstep: 120.56 | bwd_inner_microstep: 120.25 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:51:12,432] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.36 | bwd_microstep: 272.49 | bwd_inner_microstep: 272.47 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 317 +[2025-05-02 01:51:12,632] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 69.47 | bwd_microstep: 117.52 | bwd_inner_microstep: 117.32 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:51:13,105] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.78 | bwd_microstep: 270.91 | bwd_inner_microstep: 270.89 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 01:51:13,668] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.04 | optimizer_gradients: 2.16 | optimizer_step: 16.53 +[2025-05-02 01:51:13,669] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.64 | bwd_microstep: 337.71 | bwd_inner_microstep: 271.42 | bwd_allreduce_microstep: 66.25 | step_microstep: 23.46 +[2025-05-02 01:51:13,670] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2468.66 | bwd: 3692.34 | bwd_inner: 3624.84 | bwd_allreduce: 66.76 | step: 24.54 + 16%|█▌ | 1390/8720 [3:35:47<13:38:09, 6.70s/it] {'loss': 0.5485, 'grad_norm': 13.4180908203125, 'learning_rate': 9.567525831133678e-06, 'epoch': 1.59} + 16%|█▌ | 1390/8720 [3:35:47<13:38:09, 6.70s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1926 +[2025-05-02 01:51:14,175] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.81 | bwd_microstep: 286.48 | bwd_inner_microstep: 286.46 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-02 01:51:14,653] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.61 | bwd_microstep: 273.82 | bwd_inner_microstep: 273.80 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-02 01:51:15,130] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.63 | bwd_microstep: 274.04 | bwd_inner_microstep: 274.02 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 01:51:15,606] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.23 | bwd_microstep: 273.19 | bwd_inner_microstep: 273.17 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 01:51:16,087] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.60 | bwd_microstep: 272.59 | bwd_inner_microstep: 272.57 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 01:51:16,564] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.00 | bwd_microstep: 272.90 | bwd_inner_microstep: 272.89 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:51:17,039] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.23 | bwd_microstep: 272.75 | bwd_inner_microstep: 272.73 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1346 +[2025-05-02 01:51:17,401] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.51 | bwd_microstep: 205.65 | bwd_inner_microstep: 205.52 | bwd_allreduce_microstep: 0.03 | step_microstep: 0.09 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1092 +[2025-05-02 01:51:17,694] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 114.73 | bwd_microstep: 160.80 | bwd_inner_microstep: 160.78 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 01:51:18,172] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.07 | bwd_microstep: 273.60 | bwd_inner_microstep: 273.58 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:51:18,647] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.44 | bwd_microstep: 272.64 | bwd_inner_microstep: 272.62 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:51:19,123] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.48 | bwd_microstep: 272.61 | bwd_inner_microstep: 272.60 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:51:19,603] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.50 | bwd_microstep: 272.69 | bwd_inner_microstep: 272.67 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:51:20,079] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.73 | bwd_microstep: 272.69 | bwd_inner_microstep: 272.67 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:51:20,557] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.02 | bwd_microstep: 272.79 | bwd_inner_microstep: 272.77 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1911 +[2025-05-02 01:51:21,131] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.14 | optimizer_step: 16.67 +[2025-05-02 01:51:21,131] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.73 | bwd_microstep: 343.51 | bwd_inner_microstep: 277.62 | bwd_allreduce_microstep: 65.85 | step_microstep: 23.76 +[2025-05-02 01:51:21,132] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2906.03 | bwd: 4272.77 | bwd_inner: 4206.49 | bwd_allreduce: 66.01 | step: 24.54 + 16%|█▌ | 1391/8720 [3:35:54<14:06:05, 6.93s/it] {'loss': 0.6155, 'grad_norm': 15.047542572021484, 'learning_rate': 9.566769968006e-06, 'epoch': 1.6} + 16%|█▌ | 1391/8720 [3:35:54<14:06:05, 6.93s/it]dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1373 +[2025-05-02 01:51:21,508] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 145.70 | bwd_microstep: 207.30 | bwd_inner_microstep: 207.28 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 922 +[2025-05-02 01:51:21,769] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 102.32 | bwd_microstep: 145.37 | bwd_inner_microstep: 145.34 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1150 +[2025-05-02 01:51:22,066] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 117.68 | bwd_microstep: 165.38 | bwd_inner_microstep: 165.36 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1917 +[2025-05-02 01:51:22,546] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.18 | bwd_microstep: 276.17 | bwd_inner_microstep: 276.16 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1892 +[2025-05-02 01:51:23,030] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.40 | bwd_microstep: 274.85 | bwd_inner_microstep: 274.83 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 01:51:23,506] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.35 | bwd_microstep: 273.44 | bwd_inner_microstep: 273.42 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-02 01:51:23,984] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.16 | bwd_microstep: 274.28 | bwd_inner_microstep: 274.27 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:51:24,460] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.74 | bwd_microstep: 272.36 | bwd_inner_microstep: 272.34 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 326 +[2025-05-02 01:51:24,703] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 103.07 | bwd_microstep: 120.64 | bwd_inner_microstep: 120.43 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.08 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1094 +[2025-05-02 01:51:24,992] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 114.32 | bwd_microstep: 160.58 | bwd_inner_microstep: 160.57 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 01:51:25,468] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.07 | bwd_microstep: 273.09 | bwd_inner_microstep: 273.07 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1346 +[2025-05-02 01:51:25,827] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.27 | bwd_microstep: 205.08 | bwd_inner_microstep: 205.07 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:51:26,305] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.41 | bwd_microstep: 272.49 | bwd_inner_microstep: 272.47 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:51:26,780] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.71 | bwd_microstep: 272.26 | bwd_inner_microstep: 272.24 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 01:51:27,257] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.52 | bwd_microstep: 272.80 | bwd_inner_microstep: 272.78 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 327 +[2025-05-02 01:51:27,569] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.04 | optimizer_gradients: 2.14 | optimizer_step: 16.57 +[2025-05-02 01:51:27,569] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 68.58 | bwd_microstep: 206.62 | bwd_inner_microstep: 134.45 | bwd_allreduce_microstep: 72.09 | step_microstep: 23.56 +[2025-05-02 01:51:27,570] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2486.19 | bwd: 3672.75 | bwd_inner: 3600.16 | bwd_allreduce: 72.20 | step: 24.45 + 16%|█▌ | 1392/8720 [3:36:01<13:48:03, 6.78s/it] {'loss': 0.9326, 'grad_norm': 12.007862091064453, 'learning_rate': 9.566013474830497e-06, 'epoch': 1.6} + 16%|█▌ | 1392/8720 [3:36:01<13:48:03, 6.78s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:51:28,049] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.72 | bwd_microstep: 270.54 | bwd_inner_microstep: 270.52 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1886 +[2025-05-02 01:51:28,527] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.79 | bwd_microstep: 274.36 | bwd_inner_microstep: 274.34 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 846 +[2025-05-02 01:51:28,769] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.54 | bwd_microstep: 132.37 | bwd_inner_microstep: 132.20 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.09 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 329 +[2025-05-02 01:51:28,991] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 82.22 | bwd_microstep: 124.47 | bwd_inner_microstep: 124.15 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 01:51:29,474] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.72 | bwd_microstep: 273.02 | bwd_inner_microstep: 273.00 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 840 +[2025-05-02 01:51:29,706] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 91.82 | bwd_microstep: 126.56 | bwd_inner_microstep: 126.32 | bwd_allreduce_microstep: 0.14 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 01:51:30,183] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.79 | bwd_microstep: 272.71 | bwd_inner_microstep: 272.69 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 01:51:30,659] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.72 | bwd_microstep: 272.30 | bwd_inner_microstep: 272.28 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 01:51:31,136] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.33 | bwd_microstep: 273.17 | bwd_inner_microstep: 273.15 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 840 +[2025-05-02 01:51:31,370] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 92.90 | bwd_microstep: 126.34 | bwd_inner_microstep: 126.22 | bwd_allreduce_microstep: 0.08 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:51:31,845] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.05 | bwd_microstep: 272.34 | bwd_inner_microstep: 272.32 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:51:32,321] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.00 | bwd_microstep: 271.97 | bwd_inner_microstep: 271.95 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:51:32,798] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.37 | bwd_microstep: 272.14 | bwd_inner_microstep: 272.12 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 01:51:33,277] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.24 | bwd_microstep: 271.12 | bwd_inner_microstep: 271.11 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 01:51:33,757] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.76 | bwd_microstep: 271.07 | bwd_inner_microstep: 271.06 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:51:34,334] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.17 | optimizer_step: 16.59 +[2025-05-02 01:51:34,335] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.89 | bwd_microstep: 348.47 | bwd_inner_microstep: 271.57 | bwd_allreduce_microstep: 76.85 | step_microstep: 24.03 +[2025-05-02 01:51:34,336] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2617.53 | bwd: 3853.03 | bwd_inner: 3775.07 | bwd_allreduce: 77.32 | step: 25.14 + 16%|█▌ | 1393/8720 [3:36:08<13:47:25, 6.78s/it] {'loss': 0.6255, 'grad_norm': 14.45335865020752, 'learning_rate': 9.565256351711542e-06, 'epoch': 1.6} + 16%|█▌ | 1393/8720 [3:36:08<13:47:25, 6.78s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:51:34,814] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.45 | bwd_microstep: 270.29 | bwd_inner_microstep: 270.27 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1903 +[2025-05-02 01:51:35,295] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.55 | bwd_microstep: 275.93 | bwd_inner_microstep: 275.91 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1893 +[2025-05-02 01:51:35,774] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.75 | bwd_microstep: 275.02 | bwd_inner_microstep: 275.00 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 01:51:36,253] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.91 | bwd_microstep: 273.38 | bwd_inner_microstep: 273.36 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-02 01:51:36,731] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.39 | bwd_microstep: 273.49 | bwd_inner_microstep: 273.47 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 01:51:37,211] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.95 | bwd_microstep: 273.21 | bwd_inner_microstep: 273.19 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 01:51:37,693] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.78 | bwd_microstep: 272.80 | bwd_inner_microstep: 272.78 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:51:38,172] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.86 | bwd_microstep: 272.48 | bwd_inner_microstep: 272.46 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:51:38,652] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.28 | bwd_microstep: 272.76 | bwd_inner_microstep: 272.74 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 01:51:39,132] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.98 | bwd_microstep: 272.68 | bwd_inner_microstep: 272.66 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:51:39,611] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.58 | bwd_microstep: 272.47 | bwd_inner_microstep: 272.45 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:51:40,088] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.30 | bwd_microstep: 271.41 | bwd_inner_microstep: 271.39 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 01:51:40,567] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.78 | bwd_microstep: 271.46 | bwd_inner_microstep: 271.44 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-02 01:51:41,051] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.70 | bwd_microstep: 273.85 | bwd_inner_microstep: 273.84 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-02 01:51:41,533] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.45 | bwd_microstep: 273.84 | bwd_inner_microstep: 273.82 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 01:51:42,114] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.16 | optimizer_step: 16.60 +[2025-05-02 01:51:42,114] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.70 | bwd_microstep: 350.40 | bwd_inner_microstep: 273.87 | bwd_allreduce_microstep: 76.48 | step_microstep: 24.34 +[2025-05-02 01:51:42,116] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 3024.06 | bwd: 4445.47 | bwd_inner: 4368.66 | bwd_allreduce: 76.57 | step: 25.08 + 16%|█▌ | 1394/8720 [3:36:15<14:24:09, 7.08s/it] {'loss': 0.7689, 'grad_norm': 10.152921676635742, 'learning_rate': 9.564498598753588e-06, 'epoch': 1.6} + 16%|█▌ | 1394/8720 [3:36:15<14:24:09, 7.08s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 01:51:42,599] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.08 | bwd_microstep: 271.93 | bwd_inner_microstep: 271.91 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1991 +[2025-05-02 01:51:43,108] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 198.16 | bwd_microstep: 293.70 | bwd_inner_microstep: 293.68 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.15 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2043 +[2025-05-02 01:51:43,622] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 199.60 | bwd_microstep: 298.16 | bwd_inner_microstep: 298.15 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 855 +[2025-05-02 01:51:43,863] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.62 | bwd_microstep: 133.19 | bwd_inner_microstep: 132.94 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-02 01:51:44,343] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.45 | bwd_microstep: 274.10 | bwd_inner_microstep: 274.09 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 01:51:44,819] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.98 | bwd_microstep: 272.56 | bwd_inner_microstep: 272.54 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:51:45,293] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.34 | bwd_microstep: 272.16 | bwd_inner_microstep: 272.14 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 01:51:45,770] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.83 | bwd_microstep: 272.85 | bwd_inner_microstep: 272.83 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 335 +[2025-05-02 01:51:45,986] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 68.00 | bwd_microstep: 135.26 | bwd_inner_microstep: 135.00 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1349 +[2025-05-02 01:51:46,347] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.15 | bwd_microstep: 205.84 | bwd_inner_microstep: 205.82 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 01:51:46,824] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.18 | bwd_microstep: 272.70 | bwd_inner_microstep: 272.68 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:51:47,301] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.55 | bwd_microstep: 272.50 | bwd_inner_microstep: 272.48 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 835 +[2025-05-02 01:51:47,540] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.90 | bwd_microstep: 126.06 | bwd_inner_microstep: 125.82 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:51:48,017] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.67 | bwd_microstep: 272.35 | bwd_inner_microstep: 272.33 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:51:48,494] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.20 | bwd_microstep: 272.16 | bwd_inner_microstep: 272.15 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:51:49,071] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.16 | optimizer_step: 16.58 +[2025-05-02 01:51:49,071] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.51 | bwd_microstep: 347.44 | bwd_inner_microstep: 271.31 | bwd_allreduce_microstep: 76.07 | step_microstep: 24.23 +[2025-05-02 01:51:49,073] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2674.89 | bwd: 3993.01 | bwd_inner: 3915.94 | bwd_allreduce: 76.46 | step: 25.24 + 16%|█▌ | 1395/8720 [3:36:22<14:19:37, 7.04s/it] {'loss': 0.7093, 'grad_norm': 14.502824783325195, 'learning_rate': 9.563740216061178e-06, 'epoch': 1.6} + 16%|█▌ | 1395/8720 [3:36:22<14:19:37, 7.04s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:51:49,554] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.80 | bwd_microstep: 271.29 | bwd_inner_microstep: 271.27 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1893 +[2025-05-02 01:51:50,033] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.96 | bwd_microstep: 275.00 | bwd_inner_microstep: 274.99 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 362 +[2025-05-02 01:51:50,238] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 68.81 | bwd_microstep: 122.92 | bwd_inner_microstep: 122.67 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.09 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 337 +[2025-05-02 01:51:50,456] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 84.03 | bwd_microstep: 118.60 | bwd_inner_microstep: 118.34 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-02 01:51:50,931] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.92 | bwd_microstep: 272.85 | bwd_inner_microstep: 272.83 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 01:51:51,408] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.66 | bwd_microstep: 273.04 | bwd_inner_microstep: 273.02 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 840 +[2025-05-02 01:51:51,642] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 92.71 | bwd_microstep: 126.35 | bwd_inner_microstep: 126.23 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.09 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1350 +[2025-05-02 01:51:52,003] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.52 | bwd_microstep: 205.43 | bwd_inner_microstep: 205.35 | bwd_allreduce_microstep: 0.04 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 01:51:52,479] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.78 | bwd_microstep: 272.70 | bwd_inner_microstep: 272.68 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 841 +[2025-05-02 01:51:52,718] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.17 | bwd_microstep: 132.06 | bwd_inner_microstep: 131.94 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 839 +[2025-05-02 01:51:52,956] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 96.54 | bwd_microstep: 126.29 | bwd_inner_microstep: 126.08 | bwd_allreduce_microstep: 0.08 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:51:53,431] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.92 | bwd_microstep: 272.15 | bwd_inner_microstep: 272.13 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 320 +[2025-05-02 01:51:53,635] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 68.82 | bwd_microstep: 121.48 | bwd_inner_microstep: 121.30 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:51:54,110] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.10 | bwd_microstep: 272.33 | bwd_inner_microstep: 272.31 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 834 +[2025-05-02 01:51:54,341] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 91.49 | bwd_microstep: 126.12 | bwd_inner_microstep: 125.85 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:51:54,906] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.20 | optimizer_step: 16.73 +[2025-05-02 01:51:54,906] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.43 | bwd_microstep: 338.23 | bwd_inner_microstep: 271.61 | bwd_allreduce_microstep: 66.57 | step_microstep: 24.01 +[2025-05-02 01:51:54,907] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2238.38 | bwd: 3326.95 | bwd_inner: 3258.84 | bwd_allreduce: 67.20 | step: 25.05 + 16%|█▌ | 1396/8720 [3:36:28<13:35:15, 6.68s/it] {'loss': 0.4611, 'grad_norm': 6.322790145874023, 'learning_rate': 9.562981203738942e-06, 'epoch': 1.6} + 16%|█▌ | 1396/8720 [3:36:28<13:35:15, 6.68s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1927 +[2025-05-02 01:51:55,408] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 194.68 | bwd_microstep: 286.24 | bwd_inner_microstep: 286.22 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1896 +[2025-05-02 01:51:55,888] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.91 | bwd_microstep: 274.77 | bwd_inner_microstep: 274.75 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 01:51:56,365] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.32 | bwd_microstep: 272.74 | bwd_inner_microstep: 272.72 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 855 +[2025-05-02 01:51:56,610] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 96.13 | bwd_microstep: 132.90 | bwd_inner_microstep: 132.65 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 01:51:57,086] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.23 | bwd_microstep: 273.04 | bwd_inner_microstep: 273.02 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 01:51:57,564] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.16 | bwd_microstep: 273.14 | bwd_inner_microstep: 273.12 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 839 +[2025-05-02 01:51:57,798] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 92.86 | bwd_microstep: 125.85 | bwd_inner_microstep: 125.78 | bwd_allreduce_microstep: 0.03 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:51:58,273] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.65 | bwd_microstep: 271.90 | bwd_inner_microstep: 271.88 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 01:51:58,748] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.25 | bwd_microstep: 271.77 | bwd_inner_microstep: 271.75 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 01:51:59,223] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.97 | bwd_microstep: 271.93 | bwd_inner_microstep: 271.91 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:51:59,701] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.73 | bwd_microstep: 272.11 | bwd_inner_microstep: 272.10 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 01:52:00,175] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.58 | bwd_microstep: 271.05 | bwd_inner_microstep: 271.03 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 01:52:00,648] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.78 | bwd_microstep: 270.82 | bwd_inner_microstep: 270.80 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 01:52:01,123] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.65 | bwd_microstep: 270.99 | bwd_inner_microstep: 270.97 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 01:52:01,597] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.84 | bwd_microstep: 270.75 | bwd_inner_microstep: 270.73 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 01:52:02,167] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.18 | optimizer_step: 16.74 +[2025-05-02 01:52:02,167] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.06 | bwd_microstep: 343.72 | bwd_inner_microstep: 270.90 | bwd_allreduce_microstep: 72.78 | step_microstep: 23.96 +[2025-05-02 01:52:02,168] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2826.50 | bwd: 4153.74 | bwd_inner: 4080.36 | bwd_allreduce: 73.01 | step: 24.69 + 16%|█▌ | 1397/8720 [3:36:35<13:56:28, 6.85s/it] {'loss': 0.906, 'grad_norm': 16.79300308227539, 'learning_rate': 9.562221561891591e-06, 'epoch': 1.6} + 16%|█▌ | 1397/8720 [3:36:35<13:56:28, 6.85s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:52:02,646] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.04 | bwd_microstep: 270.23 | bwd_inner_microstep: 270.21 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1899 +[2025-05-02 01:52:03,127] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.83 | bwd_microstep: 275.52 | bwd_inner_microstep: 275.50 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1895 +[2025-05-02 01:52:03,607] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.53 | bwd_microstep: 275.18 | bwd_inner_microstep: 275.16 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1890 +[2025-05-02 01:52:04,090] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.03 | bwd_microstep: 274.53 | bwd_inner_microstep: 274.51 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1890 +[2025-05-02 01:52:04,575] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.61 | bwd_microstep: 274.66 | bwd_inner_microstep: 274.64 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1891 +[2025-05-02 01:52:05,056] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.01 | bwd_microstep: 274.63 | bwd_inner_microstep: 274.61 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-02 01:52:05,538] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.89 | bwd_microstep: 273.77 | bwd_inner_microstep: 273.76 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-02 01:52:06,021] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.43 | bwd_microstep: 273.73 | bwd_inner_microstep: 273.71 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 01:52:06,504] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.94 | bwd_microstep: 273.11 | bwd_inner_microstep: 273.09 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 01:52:06,986] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.55 | bwd_microstep: 273.33 | bwd_inner_microstep: 273.31 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 01:52:07,468] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.75 | bwd_microstep: 272.55 | bwd_inner_microstep: 272.53 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:52:07,945] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.05 | bwd_microstep: 272.46 | bwd_inner_microstep: 272.44 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 01:52:08,426] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.60 | bwd_microstep: 272.12 | bwd_inner_microstep: 272.11 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 318 +[2025-05-02 01:52:08,666] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 90.78 | bwd_microstep: 131.08 | bwd_inner_microstep: 130.91 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1344 +[2025-05-02 01:52:09,028] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 139.87 | bwd_microstep: 204.39 | bwd_inner_microstep: 204.30 | bwd_allreduce_microstep: 0.04 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 01:52:09,606] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.20 | optimizer_step: 16.76 +[2025-05-02 01:52:09,607] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.39 | bwd_microstep: 348.13 | bwd_inner_microstep: 271.27 | bwd_allreduce_microstep: 76.80 | step_microstep: 24.71 +[2025-05-02 01:52:09,608] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2870.90 | bwd: 4239.46 | bwd_inner: 4162.11 | bwd_allreduce: 77.00 | step: 25.59 + 16%|█▌ | 1398/8720 [3:36:43<14:17:53, 7.03s/it] {'loss': 0.7295, 'grad_norm': 6.064123630523682, 'learning_rate': 9.561461290623933e-06, 'epoch': 1.6} + 16%|█▌ | 1398/8720 [3:36:43<14:17:53, 7.03s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1944 +[2025-05-02 01:52:10,116] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.47 | bwd_microstep: 288.49 | bwd_inner_microstep: 288.47 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1906 +[2025-05-02 01:52:10,599] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.31 | bwd_microstep: 275.90 | bwd_inner_microstep: 275.89 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1896 +[2025-05-02 01:52:11,079] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.33 | bwd_microstep: 274.99 | bwd_inner_microstep: 274.97 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1370 +[2025-05-02 01:52:11,444] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.74 | bwd_microstep: 207.43 | bwd_inner_microstep: 207.41 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 01:52:11,921] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.39 | bwd_microstep: 272.87 | bwd_inner_microstep: 272.85 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 01:52:12,399] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.94 | bwd_microstep: 272.93 | bwd_inner_microstep: 272.92 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 01:52:12,875] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.56 | bwd_microstep: 272.74 | bwd_inner_microstep: 272.73 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 842 +[2025-05-02 01:52:13,123] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 100.05 | bwd_microstep: 131.88 | bwd_inner_microstep: 131.63 | bwd_allreduce_microstep: 0.14 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:52:13,601] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.06 | bwd_microstep: 272.48 | bwd_inner_microstep: 272.46 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 01:52:14,082] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.61 | bwd_microstep: 272.49 | bwd_inner_microstep: 272.48 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 01:52:14,564] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.46 | bwd_microstep: 272.54 | bwd_inner_microstep: 272.52 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:52:15,042] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.21 | bwd_microstep: 272.03 | bwd_inner_microstep: 272.01 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:52:15,524] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.01 | bwd_microstep: 272.10 | bwd_inner_microstep: 272.09 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 01:52:16,002] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.54 | bwd_microstep: 271.27 | bwd_inner_microstep: 271.26 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:52:16,480] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.84 | bwd_microstep: 271.18 | bwd_inner_microstep: 271.17 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:52:17,063] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.58 | optimizer_step: 17.01 +[2025-05-02 01:52:17,063] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.60 | bwd_microstep: 349.68 | bwd_inner_microstep: 271.75 | bwd_allreduce_microstep: 77.88 | step_microstep: 25.34 +[2025-05-02 01:52:17,065] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2885.78 | bwd: 4251.05 | bwd_inner: 4172.59 | bwd_allreduce: 78.10 | step: 26.18 + 16%|█▌ | 1399/8720 [3:36:50<14:33:22, 7.16s/it] {'loss': 0.8226, 'grad_norm': 9.676295280456543, 'learning_rate': 9.560700390040856e-06, 'epoch': 1.6} + 16%|█▌ | 1399/8720 [3:36:50<14:33:22, 7.16s/it]dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 987 +[2025-05-02 01:52:17,341] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 104.69 | bwd_microstep: 150.14 | bwd_inner_microstep: 149.86 | bwd_allreduce_microstep: 0.09 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1938 +[2025-05-02 01:52:17,842] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 197.63 | bwd_microstep: 288.00 | bwd_inner_microstep: 287.98 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1903 +[2025-05-02 01:52:18,323] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.77 | bwd_microstep: 275.82 | bwd_inner_microstep: 275.80 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1377 +[2025-05-02 01:52:18,689] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.47 | bwd_microstep: 207.80 | bwd_inner_microstep: 207.78 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-02 01:52:19,165] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.67 | bwd_microstep: 272.71 | bwd_inner_microstep: 272.69 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-02 01:52:19,642] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.11 | bwd_microstep: 273.39 | bwd_inner_microstep: 273.38 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 01:52:20,118] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.40 | bwd_microstep: 272.68 | bwd_inner_microstep: 272.66 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 01:52:20,594] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.83 | bwd_microstep: 272.34 | bwd_inner_microstep: 272.33 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 840 +[2025-05-02 01:52:20,826] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 91.21 | bwd_microstep: 126.18 | bwd_inner_microstep: 125.97 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.23 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 840 +[2025-05-02 01:52:21,059] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 91.03 | bwd_microstep: 126.08 | bwd_inner_microstep: 126.03 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:52:21,536] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.57 | bwd_microstep: 272.93 | bwd_inner_microstep: 272.91 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:52:22,012] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.35 | bwd_microstep: 272.33 | bwd_inner_microstep: 272.31 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:52:22,487] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.82 | bwd_microstep: 271.84 | bwd_inner_microstep: 271.82 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:52:22,960] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.13 | bwd_microstep: 270.83 | bwd_inner_microstep: 270.82 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 319 +[2025-05-02 01:52:23,174] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 80.77 | bwd_microstep: 117.49 | bwd_inner_microstep: 117.18 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.18 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1344 +[2025-05-02 01:52:23,638] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.14 | optimizer_step: 16.59 +[2025-05-02 01:52:23,638] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.39 | bwd_microstep: 281.70 | bwd_inner_microstep: 204.99 | bwd_allreduce_microstep: 76.66 | step_microstep: 24.31 +[2025-05-02 01:52:23,639] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2541.56 | bwd: 3752.35 | bwd_inner: 3674.64 | bwd_allreduce: 77.03 | step: 25.40 + 16%|█▌ | 1400/8720 [3:36:57<14:11:54, 6.98s/it] {'loss': 0.4892, 'grad_norm': 13.362204551696777, 'learning_rate': 9.559938860247338e-06, 'epoch': 1.61} + 16%|█▌ | 1400/8720 [3:36:57<14:11:54, 6.98s/it][INFO|trainer.py:3503] 2025-05-02 01:52:26,097 >> Saving model checkpoint to work_dirs/internvl_chat_v2_5/ak/checkpoint-1400 +[INFO|configuration_utils.py:472] 2025-05-02 01:52:26,099 >> Configuration saved in work_dirs/internvl_chat_v2_5/ak/checkpoint-1400/config.json +[INFO|configuration_utils.py:807] 2025-05-02 01:52:26,100 >> Configuration saved in work_dirs/internvl_chat_v2_5/ak/checkpoint-1400/generation_config.json +[INFO|modeling_utils.py:2755] 2025-05-02 01:52:31,146 >> Model weights saved in work_dirs/internvl_chat_v2_5/ak/checkpoint-1400/model.safetensors +[INFO|tokenization_utils_base.py:2702] 2025-05-02 01:52:31,147 >> tokenizer config file saved in work_dirs/internvl_chat_v2_5/ak/checkpoint-1400/tokenizer_config.json +[INFO|tokenization_utils_base.py:2711] 2025-05-02 01:52:31,147 >> Special tokens file saved in work_dirs/internvl_chat_v2_5/ak/checkpoint-1400/special_tokens_map.json +[INFO|tokenization_utils_base.py:2762] 2025-05-02 01:52:31,147 >> added tokens file saved in work_dirs/internvl_chat_v2_5/ak/checkpoint-1400/added_tokens.json +[2025-05-02 01:52:31,255] [INFO] [logging.py:96:log_dist] [Rank 0] [Torch] Checkpoint global_step1400 is about to be saved! +[2025-05-02 01:52:31,272] [INFO] [logging.py:96:log_dist] [Rank 0] Saving model checkpoint: work_dirs/internvl_chat_v2_5/ak/checkpoint-1400/global_step1400/mp_rank_00_model_states.pt +[2025-05-02 01:52:31,272] [INFO] [torch_checkpoint_engine.py:21:save] [Torch] Saving work_dirs/internvl_chat_v2_5/ak/checkpoint-1400/global_step1400/mp_rank_00_model_states.pt... +[2025-05-02 01:52:35,679] [INFO] [torch_checkpoint_engine.py:23:save] [Torch] Saved work_dirs/internvl_chat_v2_5/ak/checkpoint-1400/global_step1400/mp_rank_00_model_states.pt. +[2025-05-02 01:52:35,680] [INFO] [torch_checkpoint_engine.py:21:save] [Torch] Saving work_dirs/internvl_chat_v2_5/ak/checkpoint-1400/global_step1400/bf16_zero_pp_rank_0_mp_rank_00_optim_states.pt... +[2025-05-02 01:52:35,880] [INFO] [torch_checkpoint_engine.py:23:save] [Torch] Saved work_dirs/internvl_chat_v2_5/ak/checkpoint-1400/global_step1400/bf16_zero_pp_rank_0_mp_rank_00_optim_states.pt. +[2025-05-02 01:52:35,881] [INFO] [engine.py:3536:_save_zero_checkpoint] zero checkpoint saved work_dirs/internvl_chat_v2_5/ak/checkpoint-1400/global_step1400/bf16_zero_pp_rank_0_mp_rank_00_optim_states.pt +[2025-05-02 01:52:35,881] [INFO] [torch_checkpoint_engine.py:33:commit] [Torch] Checkpoint global_step1400 is ready now! +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1342 +[2025-05-02 01:52:36,261] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 139.31 | bwd_microstep: 202.25 | bwd_inner_microstep: 202.23 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1898 +[2025-05-02 01:52:36,737] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.12 | bwd_microstep: 273.19 | bwd_inner_microstep: 273.17 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-02 01:52:37,211] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.42 | bwd_microstep: 271.63 | bwd_inner_microstep: 271.62 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 848 +[2025-05-02 01:52:37,450] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.84 | bwd_microstep: 131.20 | bwd_inner_microstep: 131.14 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 01:52:37,923] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.28 | bwd_microstep: 270.84 | bwd_inner_microstep: 270.82 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 01:52:38,396] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.23 | bwd_microstep: 270.69 | bwd_inner_microstep: 270.68 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 01:52:38,870] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.95 | bwd_microstep: 270.67 | bwd_inner_microstep: 270.65 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 01:52:39,345] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.97 | bwd_microstep: 271.60 | bwd_inner_microstep: 271.59 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:52:39,819] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.07 | bwd_microstep: 270.78 | bwd_inner_microstep: 270.76 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 01:52:40,294] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.74 | bwd_microstep: 271.38 | bwd_inner_microstep: 271.36 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:52:40,772] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.58 | bwd_microstep: 271.14 | bwd_inner_microstep: 271.13 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:52:41,252] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.28 | bwd_microstep: 271.07 | bwd_inner_microstep: 271.06 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:52:41,730] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.42 | bwd_microstep: 271.09 | bwd_inner_microstep: 271.07 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 01:52:42,206] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.69 | bwd_microstep: 270.06 | bwd_inner_microstep: 270.04 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.17 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:52:42,680] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.52 | bwd_microstep: 269.79 | bwd_inner_microstep: 269.77 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 01:52:43,244] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.17 | optimizer_step: 16.57 +[2025-05-02 01:52:43,244] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.51 | bwd_microstep: 336.21 | bwd_inner_microstep: 270.11 | bwd_allreduce_microstep: 66.06 | step_microstep: 23.62 +[2025-05-02 01:52:43,245] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2850.59 | bwd: 4193.63 | bwd_inner: 4127.20 | bwd_allreduce: 66.16 | step: 24.55 + 16%|█▌ | 1401/8720 [3:37:16<21:53:39, 10.77s/it] {'loss': 0.7254, 'grad_norm': 16.236648559570312, 'learning_rate': 9.55917670134844e-06, 'epoch': 1.61} + 16%|█▌ | 1401/8720 [3:37:16<21:53:39, 10.77s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:52:43,722] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.25 | bwd_microstep: 269.60 | bwd_inner_microstep: 269.59 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 1010 +[2025-05-02 01:52:43,989] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 101.74 | bwd_microstep: 151.38 | bwd_inner_microstep: 151.20 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1883 +[2025-05-02 01:52:44,465] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.62 | bwd_microstep: 273.52 | bwd_inner_microstep: 273.50 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 01:52:44,939] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.21 | bwd_microstep: 272.28 | bwd_inner_microstep: 272.26 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 01:52:45,413] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.55 | bwd_microstep: 271.84 | bwd_inner_microstep: 271.82 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1357 +[2025-05-02 01:52:45,776] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 143.58 | bwd_microstep: 204.95 | bwd_inner_microstep: 204.92 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 01:52:46,250] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.97 | bwd_microstep: 271.43 | bwd_inner_microstep: 271.41 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:52:46,723] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.08 | bwd_microstep: 270.84 | bwd_inner_microstep: 270.83 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 01:52:47,194] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 185.92 | bwd_microstep: 270.55 | bwd_inner_microstep: 270.54 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:52:47,668] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.27 | bwd_microstep: 270.98 | bwd_inner_microstep: 270.96 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 01:52:48,141] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.68 | bwd_microstep: 270.75 | bwd_inner_microstep: 270.73 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 01:52:48,612] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 185.51 | bwd_microstep: 269.46 | bwd_inner_microstep: 269.45 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:52:49,084] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.14 | bwd_microstep: 269.75 | bwd_inner_microstep: 269.73 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1084 +[2025-05-02 01:52:49,371] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 113.95 | bwd_microstep: 158.92 | bwd_inner_microstep: 158.86 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:52:49,843] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.99 | bwd_microstep: 269.78 | bwd_inner_microstep: 269.76 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1928 +[2025-05-02 01:52:50,432] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.16 | optimizer_step: 16.53 +[2025-05-02 01:52:50,432] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 193.98 | bwd_microstep: 356.25 | bwd_inner_microstep: 286.58 | bwd_allreduce_microstep: 69.63 | step_microstep: 23.53 +[2025-05-02 01:52:50,433] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2796.15 | bwd: 4122.33 | bwd_inner: 4052.16 | bwd_allreduce: 69.78 | step: 24.32 + 16%|█▌ | 1402/8720 [3:37:24<19:42:27, 9.69s/it] {'loss': 0.761, 'grad_norm': 11.541279792785645, 'learning_rate': 9.558413913449313e-06, 'epoch': 1.61} + 16%|█▌ | 1402/8720 [3:37:24<19:42:27, 9.69s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1887 +[2025-05-02 01:52:50,914] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.46 | bwd_microstep: 273.03 | bwd_inner_microstep: 273.01 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2168 +[2025-05-02 01:52:51,451] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 204.90 | bwd_microstep: 316.12 | bwd_inner_microstep: 316.10 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1966 +[2025-05-02 01:52:51,952] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.97 | bwd_microstep: 289.25 | bwd_inner_microstep: 289.23 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1922 +[2025-05-02 01:52:52,449] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 194.16 | bwd_microstep: 285.56 | bwd_inner_microstep: 285.54 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1887 +[2025-05-02 01:52:52,927] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.63 | bwd_microstep: 273.52 | bwd_inner_microstep: 273.51 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-02 01:52:53,402] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.35 | bwd_microstep: 272.36 | bwd_inner_microstep: 272.34 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-02 01:52:53,877] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.10 | bwd_microstep: 272.88 | bwd_inner_microstep: 272.86 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 01:52:54,352] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.66 | bwd_microstep: 272.29 | bwd_inner_microstep: 272.27 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 01:52:54,828] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.22 | bwd_microstep: 272.09 | bwd_inner_microstep: 272.07 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 01:52:55,305] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.08 | bwd_microstep: 271.99 | bwd_inner_microstep: 271.97 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 321 +[2025-05-02 01:52:55,516] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 79.13 | bwd_microstep: 117.00 | bwd_inner_microstep: 116.82 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 01:52:55,990] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.71 | bwd_microstep: 270.37 | bwd_inner_microstep: 270.35 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.05 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 829 +[2025-05-02 01:52:56,236] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 100.00 | bwd_microstep: 129.29 | bwd_inner_microstep: 129.05 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:52:56,711] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.17 | bwd_microstep: 270.40 | bwd_inner_microstep: 270.38 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 317 +[2025-05-02 01:52:56,922] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 79.08 | bwd_microstep: 116.48 | bwd_inner_microstep: 116.22 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:52:57,492] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.15 | optimizer_step: 16.53 +[2025-05-02 01:52:57,492] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.56 | bwd_microstep: 341.95 | bwd_inner_microstep: 270.91 | bwd_allreduce_microstep: 71.00 | step_microstep: 23.56 +[2025-05-02 01:52:57,493] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2729.89 | bwd: 4044.64 | bwd_inner: 3972.79 | bwd_allreduce: 71.33 | step: 24.48 + 16%|█▌ | 1403/8720 [3:37:31<18:05:53, 8.90s/it] {'loss': 0.6655, 'grad_norm': 13.280330657958984, 'learning_rate': 9.557650496655194e-06, 'epoch': 1.61} + 16%|█▌ | 1403/8720 [3:37:31<18:05:53, 8.90s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2113 +[2025-05-02 01:52:58,027] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 202.69 | bwd_microstep: 311.02 | bwd_inner_microstep: 311.00 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1448 +[2025-05-02 01:52:58,399] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 143.91 | bwd_microstep: 214.45 | bwd_inner_microstep: 214.43 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 353 +[2025-05-02 01:52:58,607] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 71.67 | bwd_microstep: 123.55 | bwd_inner_microstep: 123.43 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1897 +[2025-05-02 01:52:59,086] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.79 | bwd_microstep: 275.04 | bwd_inner_microstep: 275.03 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-02 01:52:59,564] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.59 | bwd_microstep: 273.78 | bwd_inner_microstep: 273.76 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-02 01:53:00,041] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.30 | bwd_microstep: 273.00 | bwd_inner_microstep: 272.99 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 01:53:00,517] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.27 | bwd_microstep: 272.15 | bwd_inner_microstep: 272.13 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 01:53:00,992] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.02 | bwd_microstep: 271.87 | bwd_inner_microstep: 271.86 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:53:01,470] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.02 | bwd_microstep: 272.10 | bwd_inner_microstep: 272.09 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:53:01,950] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.57 | bwd_microstep: 271.98 | bwd_inner_microstep: 271.96 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 325 +[2025-05-02 01:53:02,185] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.93 | bwd_microstep: 121.42 | bwd_inner_microstep: 121.15 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 01:53:02,662] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.93 | bwd_microstep: 271.66 | bwd_inner_microstep: 271.64 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:53:03,139] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.30 | bwd_microstep: 271.75 | bwd_inner_microstep: 271.73 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 01:53:03,612] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.36 | bwd_microstep: 270.66 | bwd_inner_microstep: 270.64 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1883 +[2025-05-02 01:53:04,091] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.99 | bwd_microstep: 273.59 | bwd_inner_microstep: 273.57 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 344 +[2025-05-02 01:53:04,469] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.22 | optimizer_step: 16.63 +[2025-05-02 01:53:04,469] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 98.99 | bwd_microstep: 237.24 | bwd_inner_microstep: 138.47 | bwd_allreduce_microstep: 98.57 | step_microstep: 26.11 +[2025-05-02 01:53:04,471] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2680.99 | bwd: 4005.31 | bwd_inner: 3906.03 | bwd_allreduce: 98.78 | step: 27.08 + 16%|█▌ | 1404/8720 [3:37:38<16:55:21, 8.33s/it] {'loss': 0.6128, 'grad_norm': 5.080214500427246, 'learning_rate': 9.556886451071407e-06, 'epoch': 1.61} + 16%|█▌ | 1404/8720 [3:37:38<16:55:21, 8.33s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 01:53:04,953] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.94 | bwd_microstep: 270.89 | bwd_inner_microstep: 270.87 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1957 +[2025-05-02 01:53:05,456] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 197.82 | bwd_microstep: 288.55 | bwd_inner_microstep: 288.53 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-02 01:53:05,934] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.60 | bwd_microstep: 273.09 | bwd_inner_microstep: 273.07 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 01:53:06,409] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.61 | bwd_microstep: 271.44 | bwd_inner_microstep: 271.43 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 01:53:06,885] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.30 | bwd_microstep: 271.43 | bwd_inner_microstep: 271.41 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 01:53:07,362] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.46 | bwd_microstep: 271.81 | bwd_inner_microstep: 271.79 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 01:53:07,839] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.99 | bwd_microstep: 271.50 | bwd_inner_microstep: 271.48 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 331 +[2025-05-02 01:53:08,075] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 96.24 | bwd_microstep: 124.97 | bwd_inner_microstep: 124.72 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 01:53:08,553] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.98 | bwd_microstep: 271.98 | bwd_inner_microstep: 271.96 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 01:53:09,032] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.32 | bwd_microstep: 272.20 | bwd_inner_microstep: 272.19 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:53:09,511] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.20 | bwd_microstep: 271.57 | bwd_inner_microstep: 271.56 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 01:53:09,990] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.63 | bwd_microstep: 272.35 | bwd_inner_microstep: 272.34 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 01:53:10,469] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.87 | bwd_microstep: 271.47 | bwd_inner_microstep: 271.45 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:53:10,945] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.43 | bwd_microstep: 270.61 | bwd_inner_microstep: 270.60 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.21 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:53:11,422] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.76 | bwd_microstep: 270.71 | bwd_inner_microstep: 270.69 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 01:53:12,007] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.20 | optimizer_step: 16.80 +[2025-05-02 01:53:12,008] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.27 | bwd_microstep: 356.74 | bwd_inner_microstep: 272.11 | bwd_allreduce_microstep: 84.58 | step_microstep: 25.46 +[2025-05-02 01:53:12,009] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2928.05 | bwd: 4301.35 | bwd_inner: 4216.29 | bwd_allreduce: 84.73 | step: 26.59 + 16%|█▌ | 1405/8720 [3:37:45<16:26:16, 8.09s/it] {'loss': 0.7339, 'grad_norm': 10.388213157653809, 'learning_rate': 9.556121776803363e-06, 'epoch': 1.61} + 16%|█▌ | 1405/8720 [3:37:45<16:26:16, 8.09s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:53:12,488] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.65 | bwd_microstep: 269.88 | bwd_inner_microstep: 269.86 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1914 +[2025-05-02 01:53:12,970] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.28 | bwd_microstep: 276.34 | bwd_inner_microstep: 276.32 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1894 +[2025-05-02 01:53:13,450] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.01 | bwd_microstep: 274.25 | bwd_inner_microstep: 274.23 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 867 +[2025-05-02 01:53:13,693] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.46 | bwd_microstep: 133.88 | bwd_inner_microstep: 133.86 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1883 +[2025-05-02 01:53:14,171] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.30 | bwd_microstep: 273.65 | bwd_inner_microstep: 273.63 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 847 +[2025-05-02 01:53:14,414] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.52 | bwd_microstep: 132.47 | bwd_inner_microstep: 132.24 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 01:53:14,890] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.47 | bwd_microstep: 272.16 | bwd_inner_microstep: 272.15 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-02 01:53:15,370] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.08 | bwd_microstep: 273.05 | bwd_inner_microstep: 273.03 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 01:53:15,850] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.98 | bwd_microstep: 272.11 | bwd_inner_microstep: 272.09 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:53:16,329] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.19 | bwd_microstep: 271.70 | bwd_inner_microstep: 271.68 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 01:53:16,807] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.95 | bwd_microstep: 271.72 | bwd_inner_microstep: 271.70 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 01:53:17,286] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.70 | bwd_microstep: 272.36 | bwd_inner_microstep: 272.35 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:53:17,763] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.18 | bwd_microstep: 270.73 | bwd_inner_microstep: 270.71 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:53:18,238] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.14 | bwd_microstep: 270.86 | bwd_inner_microstep: 270.84 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 867 +[2025-05-02 01:53:18,481] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.34 | bwd_microstep: 134.07 | bwd_inner_microstep: 133.98 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1365 +[2025-05-02 01:53:18,942] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.21 | optimizer_step: 16.69 +[2025-05-02 01:53:18,943] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.34 | bwd_microstep: 280.12 | bwd_inner_microstep: 207.19 | bwd_allreduce_microstep: 72.82 | step_microstep: 24.08 +[2025-05-02 01:53:18,944] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2686.27 | bwd: 3949.43 | bwd_inner: 3875.92 | bwd_allreduce: 73.06 | step: 25.20 + 16%|█▌ | 1406/8720 [3:37:52<15:43:54, 7.74s/it] {'loss': 0.8441, 'grad_norm': 10.133315086364746, 'learning_rate': 9.555356473956559e-06, 'epoch': 1.61} + 16%|█▌ | 1406/8720 [3:37:52<15:43:54, 7.74s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 01:53:19,426] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.69 | bwd_microstep: 272.78 | bwd_inner_microstep: 272.76 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2052 +[2025-05-02 01:53:19,943] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 201.20 | bwd_microstep: 300.30 | bwd_inner_microstep: 300.28 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1385 +[2025-05-02 01:53:20,311] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 143.84 | bwd_microstep: 208.08 | bwd_inner_microstep: 207.93 | bwd_allreduce_microstep: 0.08 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-02 01:53:20,788] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.35 | bwd_microstep: 273.08 | bwd_inner_microstep: 273.06 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-02 01:53:21,264] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.23 | bwd_microstep: 272.91 | bwd_inner_microstep: 272.89 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-02 01:53:21,744] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.43 | bwd_microstep: 272.52 | bwd_inner_microstep: 272.50 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:53:22,224] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.22 | bwd_microstep: 271.94 | bwd_inner_microstep: 271.92 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1352 +[2025-05-02 01:53:22,590] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.86 | bwd_microstep: 205.41 | bwd_inner_microstep: 205.38 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:53:23,066] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.93 | bwd_microstep: 271.17 | bwd_inner_microstep: 271.15 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:53:23,546] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.64 | bwd_microstep: 272.03 | bwd_inner_microstep: 272.02 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:53:24,025] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.58 | bwd_microstep: 271.24 | bwd_inner_microstep: 271.22 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 01:53:24,503] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.41 | bwd_microstep: 270.66 | bwd_inner_microstep: 270.64 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:53:24,979] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.98 | bwd_microstep: 270.33 | bwd_inner_microstep: 270.32 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:53:25,456] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.63 | bwd_microstep: 270.51 | bwd_inner_microstep: 270.49 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1995 +[2025-05-02 01:53:25,964] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 196.61 | bwd_microstep: 293.82 | bwd_inner_microstep: 293.80 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1994 +[2025-05-02 01:53:26,572] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.15 | optimizer_step: 16.48 +[2025-05-02 01:53:26,573] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 197.13 | bwd_microstep: 370.03 | bwd_inner_microstep: 293.65 | bwd_allreduce_microstep: 76.33 | step_microstep: 23.74 +[2025-05-02 01:53:26,574] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2945.37 | bwd: 4366.86 | bwd_inner: 4290.04 | bwd_allreduce: 76.53 | step: 24.56 + 16%|█▌ | 1407/8720 [3:38:00<15:39:37, 7.71s/it] {'loss': 0.7311, 'grad_norm': 7.397390842437744, 'learning_rate': 9.554590542636576e-06, 'epoch': 1.61} + 16%|█▌ | 1407/8720 [3:38:00<15:39:37, 7.71s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 352 +[2025-05-02 01:53:26,788] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 72.04 | bwd_microstep: 123.44 | bwd_inner_microstep: 123.12 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1919 +[2025-05-02 01:53:27,269] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.63 | bwd_microstep: 276.34 | bwd_inner_microstep: 276.32 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1925 +[2025-05-02 01:53:27,766] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 194.51 | bwd_microstep: 286.16 | bwd_inner_microstep: 286.15 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1894 +[2025-05-02 01:53:28,245] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.07 | bwd_microstep: 273.80 | bwd_inner_microstep: 273.79 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 01:53:28,725] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.75 | bwd_microstep: 271.86 | bwd_inner_microstep: 271.85 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 01:53:29,203] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.55 | bwd_microstep: 272.42 | bwd_inner_microstep: 272.40 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 01:53:29,682] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.34 | bwd_microstep: 271.66 | bwd_inner_microstep: 271.64 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 838 +[2025-05-02 01:53:29,933] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 105.00 | bwd_microstep: 125.94 | bwd_inner_microstep: 125.69 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:53:30,412] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.68 | bwd_microstep: 272.04 | bwd_inner_microstep: 272.02 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:53:30,888] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 184.16 | bwd_microstep: 272.81 | bwd_inner_microstep: 272.79 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1349 +[2025-05-02 01:53:31,251] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.57 | bwd_microstep: 205.79 | bwd_inner_microstep: 205.69 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.10 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 323 +[2025-05-02 01:53:31,467] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 79.81 | bwd_microstep: 119.76 | bwd_inner_microstep: 119.60 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:53:31,944] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.37 | bwd_microstep: 272.38 | bwd_inner_microstep: 272.36 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:53:32,422] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.26 | bwd_microstep: 272.06 | bwd_inner_microstep: 272.05 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 01:53:32,902] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.51 | bwd_microstep: 272.18 | bwd_inner_microstep: 272.17 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:53:33,484] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.22 | optimizer_step: 16.71 +[2025-05-02 01:53:33,485] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.36 | bwd_microstep: 349.25 | bwd_inner_microstep: 272.60 | bwd_allreduce_microstep: 76.60 | step_microstep: 24.72 +[2025-05-02 01:53:33,486] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2660.22 | bwd: 3938.00 | bwd_inner: 3860.34 | bwd_allreduce: 77.04 | step: 25.77 + 16%|█▌ | 1408/8720 [3:38:07<15:10:25, 7.47s/it] {'loss': 0.6493, 'grad_norm': 5.758459091186523, 'learning_rate': 9.55382398294909e-06, 'epoch': 1.61} + 16%|█▌ | 1408/8720 [3:38:07<15:10:25, 7.47s/it]dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 833 +[2025-05-02 01:53:33,728] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.97 | bwd_microstep: 125.71 | bwd_inner_microstep: 125.46 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.10 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1450 +[2025-05-02 01:53:34,107] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 146.38 | bwd_microstep: 215.42 | bwd_inner_microstep: 215.41 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 371 +[2025-05-02 01:53:34,327] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 80.86 | bwd_microstep: 124.92 | bwd_inner_microstep: 124.55 | bwd_allreduce_microstep: 0.17 | step_microstep: 0.19 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 340 +[2025-05-02 01:53:34,557] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 85.01 | bwd_microstep: 129.96 | bwd_inner_microstep: 129.64 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1883 +[2025-05-02 01:53:35,036] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.95 | bwd_microstep: 274.16 | bwd_inner_microstep: 274.14 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 840 +[2025-05-02 01:53:35,268] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 91.98 | bwd_microstep: 126.25 | bwd_inner_microstep: 125.99 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:53:35,745] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.74 | bwd_microstep: 272.07 | bwd_inner_microstep: 272.05 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:53:36,223] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.92 | bwd_microstep: 272.08 | bwd_inner_microstep: 272.06 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 325 +[2025-05-02 01:53:36,452] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 90.30 | bwd_microstep: 120.17 | bwd_inner_microstep: 120.02 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 01:53:36,929] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.68 | bwd_microstep: 271.89 | bwd_inner_microstep: 271.88 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:53:37,406] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.93 | bwd_microstep: 271.81 | bwd_inner_microstep: 271.79 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:53:37,885] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.61 | bwd_microstep: 270.94 | bwd_inner_microstep: 270.93 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 01:53:38,361] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.16 | bwd_microstep: 270.88 | bwd_inner_microstep: 270.86 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 01:53:38,837] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.96 | bwd_microstep: 271.00 | bwd_inner_microstep: 270.98 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1340 +[2025-05-02 01:53:39,197] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.36 | bwd_microstep: 204.25 | bwd_inner_microstep: 204.23 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1942 +[2025-05-02 01:53:39,789] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.23 | optimizer_step: 16.80 +[2025-05-02 01:53:39,789] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 197.48 | bwd_microstep: 355.77 | bwd_inner_microstep: 288.51 | bwd_allreduce_microstep: 67.21 | step_microstep: 24.24 +[2025-05-02 01:53:39,791] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2428.94 | bwd: 3577.39 | bwd_inner: 3508.71 | bwd_allreduce: 67.84 | step: 25.36 + 16%|█▌ | 1409/8720 [3:38:13<14:27:36, 7.12s/it] {'loss': 0.4894, 'grad_norm': 6.527554512023926, 'learning_rate': 9.553056794999854e-06, 'epoch': 1.62} + 16%|█▌ | 1409/8720 [3:38:13<14:27:36, 7.12s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1920 +[2025-05-02 01:53:40,278] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.04 | bwd_microstep: 276.72 | bwd_inner_microstep: 276.70 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2001 +[2025-05-02 01:53:40,788] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 200.11 | bwd_microstep: 294.47 | bwd_inner_microstep: 294.45 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 388 +[2025-05-02 01:53:40,987] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 68.44 | bwd_microstep: 116.86 | bwd_inner_microstep: 116.56 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1903 +[2025-05-02 01:53:41,467] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.48 | bwd_microstep: 275.47 | bwd_inner_microstep: 275.46 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-02 01:53:41,944] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.77 | bwd_microstep: 273.08 | bwd_inner_microstep: 273.06 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 850 +[2025-05-02 01:53:42,185] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.97 | bwd_microstep: 132.39 | bwd_inner_microstep: 132.37 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 01:53:42,661] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.23 | bwd_microstep: 272.72 | bwd_inner_microstep: 272.70 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:53:43,138] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.79 | bwd_microstep: 272.57 | bwd_inner_microstep: 272.56 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1343 +[2025-05-02 01:53:43,498] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.00 | bwd_microstep: 204.52 | bwd_inner_microstep: 204.50 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:53:43,974] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.53 | bwd_microstep: 272.29 | bwd_inner_microstep: 272.27 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:53:44,450] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.70 | bwd_microstep: 272.33 | bwd_inner_microstep: 272.31 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:53:44,924] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.69 | bwd_microstep: 272.13 | bwd_inner_microstep: 272.11 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:53:45,400] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.12 | bwd_microstep: 272.64 | bwd_inner_microstep: 272.63 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 01:53:45,877] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.98 | bwd_microstep: 272.76 | bwd_inner_microstep: 272.74 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:53:46,351] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.45 | bwd_microstep: 271.18 | bwd_inner_microstep: 271.16 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:53:46,915] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.04 | optimizer_gradients: 2.14 | optimizer_step: 16.54 +[2025-05-02 01:53:46,915] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.72 | bwd_microstep: 337.73 | bwd_inner_microstep: 271.60 | bwd_allreduce_microstep: 66.08 | step_microstep: 23.44 +[2025-05-02 01:53:46,916] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2763.75 | bwd: 4089.88 | bwd_inner: 4023.24 | bwd_allreduce: 66.28 | step: 24.26 + 16%|█▌ | 1410/8720 [3:38:20<14:27:40, 7.12s/it] {'loss': 0.7868, 'grad_norm': 6.0928053855896, 'learning_rate': 9.552288978894712e-06, 'epoch': 1.62} + 16%|█▌ | 1410/8720 [3:38:20<14:27:40, 7.12s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1893 +[2025-05-02 01:53:47,400] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.45 | bwd_microstep: 274.29 | bwd_inner_microstep: 274.27 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1930 +[2025-05-02 01:53:47,898] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.57 | bwd_microstep: 287.90 | bwd_inner_microstep: 287.89 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 898 +[2025-05-02 01:53:48,158] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 101.57 | bwd_microstep: 143.86 | bwd_inner_microstep: 143.74 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.10 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 352 +[2025-05-02 01:53:48,412] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 78.71 | bwd_microstep: 160.67 | bwd_inner_microstep: 160.55 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1883 +[2025-05-02 01:53:48,892] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.25 | bwd_microstep: 274.66 | bwd_inner_microstep: 274.64 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:53:49,372] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.03 | bwd_microstep: 272.83 | bwd_inner_microstep: 272.81 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 01:53:49,851] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.89 | bwd_microstep: 273.06 | bwd_inner_microstep: 273.04 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 01:53:50,334] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.57 | bwd_microstep: 273.86 | bwd_inner_microstep: 273.85 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:53:50,815] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.88 | bwd_microstep: 272.91 | bwd_inner_microstep: 272.89 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:53:51,295] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.91 | bwd_microstep: 272.86 | bwd_inner_microstep: 272.85 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 834 +[2025-05-02 01:53:51,552] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.60 | bwd_microstep: 143.41 | bwd_inner_microstep: 143.18 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 01:53:52,031] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.72 | bwd_microstep: 272.72 | bwd_inner_microstep: 272.70 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:53:52,510] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.93 | bwd_microstep: 272.87 | bwd_inner_microstep: 272.86 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 834 +[2025-05-02 01:53:52,753] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 91.06 | bwd_microstep: 137.80 | bwd_inner_microstep: 137.68 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 01:53:53,229] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.69 | bwd_microstep: 271.72 | bwd_inner_microstep: 271.70 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:53:53,793] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.15 | optimizer_step: 16.54 +[2025-05-02 01:53:53,794] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.79 | bwd_microstep: 338.59 | bwd_inner_microstep: 271.94 | bwd_allreduce_microstep: 66.60 | step_microstep: 23.64 +[2025-05-02 01:53:53,795] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2642.29 | bwd: 3944.07 | bwd_inner: 3876.72 | bwd_allreduce: 66.86 | step: 24.64 + 16%|█▌ | 1411/8720 [3:38:27<14:18:40, 7.05s/it] {'loss': 0.8457, 'grad_norm': 8.222840309143066, 'learning_rate': 9.551520534739597e-06, 'epoch': 1.62} + 16%|█▌ | 1411/8720 [3:38:27<14:18:40, 7.05s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2062 +[2025-05-02 01:53:54,319] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 202.05 | bwd_microstep: 301.89 | bwd_inner_microstep: 301.87 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1953 +[2025-05-02 01:53:54,823] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 198.60 | bwd_microstep: 289.55 | bwd_inner_microstep: 289.53 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1949 +[2025-05-02 01:53:55,323] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.58 | bwd_microstep: 289.07 | bwd_inner_microstep: 289.05 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1417 +[2025-05-02 01:53:55,696] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 145.35 | bwd_microstep: 212.96 | bwd_inner_microstep: 212.94 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 389 +[2025-05-02 01:53:55,936] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 74.10 | bwd_microstep: 152.84 | bwd_inner_microstep: 152.61 | bwd_allreduce_microstep: 0.08 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1934 +[2025-05-02 01:53:56,436] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.68 | bwd_microstep: 287.85 | bwd_inner_microstep: 287.83 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 375 +[2025-05-02 01:53:56,706] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 91.27 | bwd_microstep: 163.34 | bwd_inner_microstep: 163.01 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 01:53:57,184] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.91 | bwd_microstep: 272.67 | bwd_inner_microstep: 272.66 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 338 +[2025-05-02 01:53:57,430] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 75.57 | bwd_microstep: 155.36 | bwd_inner_microstep: 155.17 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 01:53:57,907] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.42 | bwd_microstep: 273.62 | bwd_inner_microstep: 273.61 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:53:58,382] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.00 | bwd_microstep: 272.45 | bwd_inner_microstep: 272.43 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 01:53:58,860] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.71 | bwd_microstep: 272.80 | bwd_inner_microstep: 272.78 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 01:53:59,340] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.28 | bwd_microstep: 273.04 | bwd_inner_microstep: 273.02 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:53:59,817] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.77 | bwd_microstep: 272.20 | bwd_inner_microstep: 272.18 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 01:54:00,294] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.64 | bwd_microstep: 271.71 | bwd_inner_microstep: 271.69 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1930 +[2025-05-02 01:54:00,894] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.04 | optimizer_gradients: 2.11 | optimizer_step: 16.57 +[2025-05-02 01:54:00,895] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.93 | bwd_microstep: 364.29 | bwd_inner_microstep: 288.33 | bwd_allreduce_microstep: 75.87 | step_microstep: 23.41 +[2025-05-02 01:54:00,896] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2689.53 | bwd: 4125.69 | bwd_inner: 4048.94 | bwd_allreduce: 76.16 | step: 24.54 + 16%|█▌ | 1412/8720 [3:38:34<14:20:27, 7.06s/it] {'loss': 1.0014, 'grad_norm': 4.950159072875977, 'learning_rate': 9.550751462640527e-06, 'epoch': 1.62} + 16%|█▌ | 1412/8720 [3:38:34<14:20:27, 7.06s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 389 +[2025-05-02 01:54:01,129] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 67.33 | bwd_microstep: 148.20 | bwd_inner_microstep: 148.07 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1909 +[2025-05-02 01:54:01,610] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.47 | bwd_microstep: 276.30 | bwd_inner_microstep: 276.28 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1893 +[2025-05-02 01:54:02,092] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.10 | bwd_microstep: 275.06 | bwd_inner_microstep: 275.04 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1371 +[2025-05-02 01:54:02,461] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 142.42 | bwd_microstep: 207.84 | bwd_inner_microstep: 207.65 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-02 01:54:02,944] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.24 | bwd_microstep: 273.73 | bwd_inner_microstep: 273.72 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 856 +[2025-05-02 01:54:03,206] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 98.01 | bwd_microstep: 143.01 | bwd_inner_microstep: 142.84 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.10 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 342 +[2025-05-02 01:54:03,477] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 98.37 | bwd_microstep: 153.49 | bwd_inner_microstep: 153.33 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 329 +[2025-05-02 01:54:03,731] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 85.39 | bwd_microstep: 150.71 | bwd_inner_microstep: 150.46 | bwd_allreduce_microstep: 0.09 | step_microstep: 0.10 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 843 +[2025-05-02 01:54:03,985] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 97.74 | bwd_microstep: 140.26 | bwd_inner_microstep: 139.94 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:54:04,463] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.53 | bwd_microstep: 272.24 | bwd_inner_microstep: 272.22 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:54:04,940] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.93 | bwd_microstep: 272.20 | bwd_inner_microstep: 272.19 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 01:54:05,420] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.52 | bwd_microstep: 272.96 | bwd_inner_microstep: 272.94 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:54:05,897] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.64 | bwd_microstep: 271.05 | bwd_inner_microstep: 271.03 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:54:06,375] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.51 | bwd_microstep: 271.10 | bwd_inner_microstep: 271.08 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 01:54:06,854] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.13 | bwd_microstep: 271.15 | bwd_inner_microstep: 271.13 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 01:54:07,432] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.19 | optimizer_step: 16.59 +[2025-05-02 01:54:07,433] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.29 | bwd_microstep: 347.54 | bwd_inner_microstep: 271.66 | bwd_allreduce_microstep: 75.80 | step_microstep: 24.25 +[2025-05-02 01:54:07,434] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2472.22 | bwd: 3746.95 | bwd_inner: 3669.79 | bwd_allreduce: 76.32 | step: 25.38 + 16%|█▌ | 1413/8720 [3:38:41<14:01:10, 6.91s/it] {'loss': 0.7525, 'grad_norm': 6.562392234802246, 'learning_rate': 9.549981762703602e-06, 'epoch': 1.62} + 16%|█▌ | 1413/8720 [3:38:41<14:01:10, 6.91s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1953 +[2025-05-02 01:54:07,942] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.84 | bwd_microstep: 288.76 | bwd_inner_microstep: 288.75 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 388 +[2025-05-02 01:54:08,185] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 80.54 | bwd_microstep: 146.84 | bwd_inner_microstep: 146.57 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1124 +[2025-05-02 01:54:08,482] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 117.79 | bwd_microstep: 163.20 | bwd_inner_microstep: 162.97 | bwd_allreduce_microstep: 0.10 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1896 +[2025-05-02 01:54:08,963] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.28 | bwd_microstep: 275.23 | bwd_inner_microstep: 275.21 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1364 +[2025-05-02 01:54:09,327] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.66 | bwd_microstep: 207.06 | bwd_inner_microstep: 207.05 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-02 01:54:09,807] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.59 | bwd_microstep: 274.21 | bwd_inner_microstep: 274.19 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 01:54:10,286] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.66 | bwd_microstep: 272.97 | bwd_inner_microstep: 272.95 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 01:54:10,768] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.40 | bwd_microstep: 272.99 | bwd_inner_microstep: 272.97 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 01:54:11,249] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.00 | bwd_microstep: 272.53 | bwd_inner_microstep: 272.52 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1354 +[2025-05-02 01:54:11,616] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 143.62 | bwd_microstep: 206.23 | bwd_inner_microstep: 206.22 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 01:54:12,095] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.50 | bwd_microstep: 272.65 | bwd_inner_microstep: 272.64 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 01:54:12,576] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.07 | bwd_microstep: 272.80 | bwd_inner_microstep: 272.78 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 328 +[2025-05-02 01:54:12,801] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 91.94 | bwd_microstep: 115.90 | bwd_inner_microstep: 115.56 | bwd_allreduce_microstep: 0.14 | step_microstep: 0.10 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 320 +[2025-05-02 01:54:13,071] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 80.45 | bwd_microstep: 172.99 | bwd_inner_microstep: 172.74 | bwd_allreduce_microstep: 0.10 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 01:54:13,547] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.37 | bwd_microstep: 271.11 | bwd_inner_microstep: 271.09 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 01:54:14,131] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.17 | optimizer_step: 16.65 +[2025-05-02 01:54:14,131] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.58 | bwd_microstep: 349.65 | bwd_inner_microstep: 271.58 | bwd_allreduce_microstep: 77.94 | step_microstep: 24.56 +[2025-05-02 01:54:14,133] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2547.92 | bwd: 3835.20 | bwd_inner: 3756.04 | bwd_allreduce: 78.37 | step: 25.67 + 16%|█▌ | 1414/8720 [3:38:47<13:53:26, 6.84s/it] {'loss': 0.8261, 'grad_norm': 8.442817687988281, 'learning_rate': 9.549211435035016e-06, 'epoch': 1.62} + 16%|█▌ | 1414/8720 [3:38:47<13:53:26, 6.84s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 01:54:14,613] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.22 | bwd_microstep: 269.97 | bwd_inner_microstep: 269.95 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 911 +[2025-05-02 01:54:14,882] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 105.64 | bwd_microstep: 147.38 | bwd_inner_microstep: 147.12 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-02 01:54:15,362] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.72 | bwd_microstep: 274.37 | bwd_inner_microstep: 274.32 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.17 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-02 01:54:15,844] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.53 | bwd_microstep: 274.17 | bwd_inner_microstep: 274.15 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 01:54:16,324] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.11 | bwd_microstep: 273.26 | bwd_inner_microstep: 273.25 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1357 +[2025-05-02 01:54:16,692] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.55 | bwd_microstep: 206.69 | bwd_inner_microstep: 206.46 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 01:54:17,176] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.25 | bwd_microstep: 272.61 | bwd_inner_microstep: 272.59 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 01:54:17,654] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.77 | bwd_microstep: 272.77 | bwd_inner_microstep: 272.75 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 01:54:18,133] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.39 | bwd_microstep: 272.73 | bwd_inner_microstep: 272.71 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:54:18,613] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.39 | bwd_microstep: 272.42 | bwd_inner_microstep: 272.40 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:54:19,093] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.53 | bwd_microstep: 272.27 | bwd_inner_microstep: 272.25 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:54:19,573] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.41 | bwd_microstep: 272.22 | bwd_inner_microstep: 272.20 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 317 +[2025-05-02 01:54:19,836] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.28 | bwd_microstep: 149.04 | bwd_inner_microstep: 148.87 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 01:54:20,312] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.58 | bwd_microstep: 270.85 | bwd_inner_microstep: 270.83 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:54:20,790] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.00 | bwd_microstep: 271.35 | bwd_inner_microstep: 271.34 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:54:21,369] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.19 | optimizer_step: 16.58 +[2025-05-02 01:54:21,370] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.38 | bwd_microstep: 348.59 | bwd_inner_microstep: 271.99 | bwd_allreduce_microstep: 76.55 | step_microstep: 24.40 +[2025-05-02 01:54:21,371] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2790.35 | bwd: 4120.76 | bwd_inner: 4043.28 | bwd_allreduce: 76.87 | step: 25.71 + 16%|█▌ | 1415/8720 [3:38:55<14:07:43, 6.96s/it] {'loss': 0.9625, 'grad_norm': 18.94839859008789, 'learning_rate': 9.548440479741043e-06, 'epoch': 1.62} + 16%|█▌ | 1415/8720 [3:38:55<14:07:43, 6.96s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:54:21,852] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.28 | bwd_microstep: 270.33 | bwd_inner_microstep: 270.31 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1941 +[2025-05-02 01:54:22,354] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 196.05 | bwd_microstep: 288.77 | bwd_inner_microstep: 288.75 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1893 +[2025-05-02 01:54:22,836] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.61 | bwd_microstep: 275.29 | bwd_inner_microstep: 275.27 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1893 +[2025-05-02 01:54:23,319] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.14 | bwd_microstep: 275.32 | bwd_inner_microstep: 275.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1893 +[2025-05-02 01:54:23,800] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.16 | bwd_microstep: 274.94 | bwd_inner_microstep: 274.93 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1104 +[2025-05-02 01:54:24,095] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 117.24 | bwd_microstep: 161.52 | bwd_inner_microstep: 161.42 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-02 01:54:24,573] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.57 | bwd_microstep: 273.30 | bwd_inner_microstep: 273.29 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 01:54:25,051] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.08 | bwd_microstep: 272.27 | bwd_inner_microstep: 272.25 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 01:54:25,529] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.67 | bwd_microstep: 272.57 | bwd_inner_microstep: 272.55 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:54:26,010] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.18 | bwd_microstep: 272.29 | bwd_inner_microstep: 272.27 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 833 +[2025-05-02 01:54:26,270] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.28 | bwd_microstep: 149.69 | bwd_inner_microstep: 149.52 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1344 +[2025-05-02 01:54:26,633] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.46 | bwd_microstep: 204.69 | bwd_inner_microstep: 204.44 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 01:54:27,108] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.28 | bwd_microstep: 271.12 | bwd_inner_microstep: 271.11 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1850 +[2025-05-02 01:54:27,585] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.05 | bwd_microstep: 270.64 | bwd_inner_microstep: 270.62 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 313 +[2025-05-02 01:54:27,839] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 82.05 | bwd_microstep: 157.20 | bwd_inner_microstep: 157.01 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.11 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 459 +[2025-05-02 01:54:28,212] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.14 | optimizer_step: 16.54 +[2025-05-02 01:54:28,213] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 87.11 | bwd_microstep: 246.46 | bwd_inner_microstep: 170.50 | bwd_allreduce_microstep: 75.86 | step_microstep: 24.18 +[2025-05-02 01:54:28,214] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2598.82 | bwd: 3936.47 | bwd_inner: 3859.68 | bwd_allreduce: 76.21 | step: 25.61 + 16%|█▌ | 1416/8720 [3:39:01<14:03:12, 6.93s/it] {'loss': 0.7515, 'grad_norm': 17.949371337890625, 'learning_rate': 9.54766889692805e-06, 'epoch': 1.62} + 16%|█▌ | 1416/8720 [3:39:01<14:03:12, 6.93s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1913 +[2025-05-02 01:54:28,702] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.74 | bwd_microstep: 276.07 | bwd_inner_microstep: 276.05 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2084 +[2025-05-02 01:54:29,222] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 201.61 | bwd_microstep: 303.37 | bwd_inner_microstep: 303.36 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1921 +[2025-05-02 01:54:29,719] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 194.59 | bwd_microstep: 287.08 | bwd_inner_microstep: 287.06 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1896 +[2025-05-02 01:54:30,198] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.52 | bwd_microstep: 274.71 | bwd_inner_microstep: 274.69 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 866 +[2025-05-02 01:54:30,439] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.52 | bwd_microstep: 134.30 | bwd_inner_microstep: 134.11 | bwd_allreduce_microstep: 0.08 | step_microstep: 0.10 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 338 +[2025-05-02 01:54:30,673] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 67.39 | bwd_microstep: 153.95 | bwd_inner_microstep: 153.82 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 01:54:31,150] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.29 | bwd_microstep: 272.84 | bwd_inner_microstep: 272.82 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-02 01:54:31,628] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.77 | bwd_microstep: 273.26 | bwd_inner_microstep: 273.24 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:54:32,105] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.77 | bwd_microstep: 272.49 | bwd_inner_microstep: 272.47 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 01:54:32,582] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.20 | bwd_microstep: 272.87 | bwd_inner_microstep: 272.86 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 01:54:33,059] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.64 | bwd_microstep: 272.87 | bwd_inner_microstep: 272.85 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:54:33,537] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.94 | bwd_microstep: 272.29 | bwd_inner_microstep: 272.27 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:54:34,014] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.95 | bwd_microstep: 272.59 | bwd_inner_microstep: 272.57 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 01:54:34,490] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.21 | bwd_microstep: 271.10 | bwd_inner_microstep: 271.08 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:54:34,967] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.39 | bwd_microstep: 271.06 | bwd_inner_microstep: 271.04 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1340 +[2025-05-02 01:54:35,442] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.23 | optimizer_step: 26.01 +[2025-05-02 01:54:35,443] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.92 | bwd_microstep: 283.48 | bwd_inner_microstep: 205.04 | bwd_allreduce_microstep: 78.34 | step_microstep: 34.15 +[2025-05-02 01:54:35,444] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2772.19 | bwd: 4164.38 | bwd_inner: 4085.42 | bwd_allreduce: 78.52 | step: 35.36 + 16%|█▋ | 1417/8720 [3:39:09<14:14:11, 7.02s/it] {'loss': 0.6507, 'grad_norm': 8.174848556518555, 'learning_rate': 9.546896686702486e-06, 'epoch': 1.62} + 16%|█▋ | 1417/8720 [3:39:09<14:14:11, 7.02s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1850 +[2025-05-02 01:54:35,926] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.72 | bwd_microstep: 270.26 | bwd_inner_microstep: 270.24 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 451 +[2025-05-02 01:54:36,180] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 83.42 | bwd_microstep: 155.13 | bwd_inner_microstep: 154.87 | bwd_allreduce_microstep: 0.10 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1902 +[2025-05-02 01:54:36,665] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.85 | bwd_microstep: 276.10 | bwd_inner_microstep: 276.08 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1889 +[2025-05-02 01:54:37,148] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.04 | bwd_microstep: 275.08 | bwd_inner_microstep: 275.07 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 853 +[2025-05-02 01:54:37,410] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 99.90 | bwd_microstep: 143.69 | bwd_inner_microstep: 143.55 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-02 01:54:37,891] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.76 | bwd_microstep: 273.60 | bwd_inner_microstep: 273.59 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 337 +[2025-05-02 01:54:38,157] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 91.21 | bwd_microstep: 156.90 | bwd_inner_microstep: 156.59 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 01:54:38,637] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.57 | bwd_microstep: 273.34 | bwd_inner_microstep: 273.32 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 01:54:39,116] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.21 | bwd_microstep: 272.88 | bwd_inner_microstep: 272.86 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 01:54:39,594] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.90 | bwd_microstep: 272.81 | bwd_inner_microstep: 272.79 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 01:54:40,073] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.01 | bwd_microstep: 273.12 | bwd_inner_microstep: 273.11 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:54:40,552] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.29 | bwd_microstep: 272.38 | bwd_inner_microstep: 272.36 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:54:41,034] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.02 | bwd_microstep: 272.82 | bwd_inner_microstep: 272.80 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 322 +[2025-05-02 01:54:41,290] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 86.36 | bwd_microstep: 152.88 | bwd_inner_microstep: 152.69 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:54:41,767] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.89 | bwd_microstep: 271.22 | bwd_inner_microstep: 271.20 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:54:42,356] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.20 | optimizer_step: 27.47 +[2025-05-02 01:54:42,357] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.26 | bwd_microstep: 348.48 | bwd_inner_microstep: 271.58 | bwd_allreduce_microstep: 76.83 | step_microstep: 35.41 +[2025-05-02 01:54:42,358] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2621.03 | bwd: 3960.79 | bwd_inner: 3882.92 | bwd_allreduce: 77.20 | step: 36.56 + 16%|█▋ | 1418/8720 [3:39:16<14:10:12, 6.99s/it] {'loss': 1.0403, 'grad_norm': 7.740389347076416, 'learning_rate': 9.546123849170887e-06, 'epoch': 1.63} + 16%|█▋ | 1418/8720 [3:39:16<14:10:12, 6.99s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1849 +[2025-05-02 01:54:42,837] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.03 | bwd_microstep: 270.26 | bwd_inner_microstep: 270.24 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 924 +[2025-05-02 01:54:43,101] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 103.56 | bwd_microstep: 146.07 | bwd_inner_microstep: 145.77 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 361 +[2025-05-02 01:54:43,351] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 79.42 | bwd_microstep: 158.06 | bwd_inner_microstep: 157.87 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1883 +[2025-05-02 01:54:43,829] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.88 | bwd_microstep: 274.15 | bwd_inner_microstep: 274.13 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-02 01:54:44,308] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.95 | bwd_microstep: 274.35 | bwd_inner_microstep: 274.34 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 01:54:44,788] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.00 | bwd_microstep: 274.20 | bwd_inner_microstep: 274.18 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 01:54:45,265] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.41 | bwd_microstep: 273.43 | bwd_inner_microstep: 273.42 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 836 +[2025-05-02 01:54:45,512] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 91.76 | bwd_microstep: 141.13 | bwd_inner_microstep: 141.00 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-02 01:54:45,989] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.17 | bwd_microstep: 273.63 | bwd_inner_microstep: 273.62 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1089 +[2025-05-02 01:54:46,282] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 115.06 | bwd_microstep: 160.91 | bwd_inner_microstep: 160.66 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 01:54:46,761] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.53 | bwd_microstep: 273.10 | bwd_inner_microstep: 273.08 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 01:54:47,241] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.15 | bwd_microstep: 272.24 | bwd_inner_microstep: 272.22 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:54:47,720] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.68 | bwd_microstep: 272.77 | bwd_inner_microstep: 272.75 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:54:48,199] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.42 | bwd_microstep: 271.25 | bwd_inner_microstep: 271.23 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1343 +[2025-05-02 01:54:48,561] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.57 | bwd_microstep: 204.77 | bwd_inner_microstep: 204.51 | bwd_allreduce_microstep: 0.15 | step_microstep: 0.18 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 828 +[2025-05-02 01:54:48,945] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.07 | optimizer_gradients: 2.20 | optimizer_step: 16.67 +[2025-05-02 01:54:48,945] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 96.53 | bwd_microstep: 245.71 | bwd_inner_microstep: 163.05 | bwd_allreduce_microstep: 82.49 | step_microstep: 24.66 +[2025-05-02 01:54:48,947] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2511.83 | bwd: 3786.15 | bwd_inner: 3702.28 | bwd_allreduce: 82.98 | step: 26.03 + 16%|█▋ | 1419/8720 [3:39:22<13:55:39, 6.87s/it] {'loss': 0.8099, 'grad_norm': 28.238107681274414, 'learning_rate': 9.545350384439877e-06, 'epoch': 1.63} + 16%|█▋ | 1419/8720 [3:39:22<13:55:39, 6.87s/it]dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 884 +[2025-05-02 01:54:49,216] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.96 | bwd_microstep: 151.73 | bwd_inner_microstep: 151.53 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1924 +[2025-05-02 01:54:49,716] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.02 | bwd_microstep: 287.50 | bwd_inner_microstep: 287.48 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1920 +[2025-05-02 01:54:50,205] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.96 | bwd_microstep: 277.46 | bwd_inner_microstep: 277.44 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.11 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 362 +[2025-05-02 01:54:50,470] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 88.21 | bwd_microstep: 158.03 | bwd_inner_microstep: 157.77 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1901 +[2025-05-02 01:54:50,953] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.93 | bwd_microstep: 275.85 | bwd_inner_microstep: 275.83 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-02 01:54:51,433] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.65 | bwd_microstep: 273.77 | bwd_inner_microstep: 273.75 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.21 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 340 +[2025-05-02 01:54:51,683] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 85.71 | bwd_microstep: 148.47 | bwd_inner_microstep: 148.25 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.10 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 841 +[2025-05-02 01:54:51,937] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.92 | bwd_microstep: 141.92 | bwd_inner_microstep: 141.60 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:54:52,417] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.83 | bwd_microstep: 273.04 | bwd_inner_microstep: 273.02 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 01:54:52,894] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.59 | bwd_microstep: 273.60 | bwd_inner_microstep: 273.58 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:54:53,370] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.66 | bwd_microstep: 272.39 | bwd_inner_microstep: 272.37 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 01:54:53,847] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.15 | bwd_microstep: 273.06 | bwd_inner_microstep: 273.04 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:54:54,323] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.08 | bwd_microstep: 272.63 | bwd_inner_microstep: 272.61 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.11 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 829 +[2025-05-02 01:54:54,574] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.96 | bwd_microstep: 141.54 | bwd_inner_microstep: 141.23 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.21 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 01:54:55,050] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.50 | bwd_microstep: 272.10 | bwd_inner_microstep: 272.08 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.19 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 504 +[2025-05-02 01:54:55,438] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.17 | optimizer_step: 16.56 +[2025-05-02 01:54:55,439] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.55 | bwd_microstep: 253.43 | bwd_inner_microstep: 170.32 | bwd_allreduce_microstep: 82.95 | step_microstep: 24.49 +[2025-05-02 01:54:55,440] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2445.36 | bwd: 3746.62 | bwd_inner: 3662.26 | bwd_allreduce: 83.44 | step: 26.07 + 16%|█▋ | 1420/8720 [3:39:29<13:41:53, 6.76s/it] {'loss': 0.7802, 'grad_norm': 9.702366828918457, 'learning_rate': 9.544576292616167e-06, 'epoch': 1.63} + 16%|█▋ | 1420/8720 [3:39:29<13:41:53, 6.76s/it]dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 993 +[2025-05-02 01:54:55,718] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 104.51 | bwd_microstep: 150.57 | bwd_inner_microstep: 150.25 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1921 +[2025-05-02 01:54:56,218] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.36 | bwd_microstep: 286.94 | bwd_inner_microstep: 286.92 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-02 01:54:56,700] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.91 | bwd_microstep: 274.39 | bwd_inner_microstep: 274.37 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 344 +[2025-05-02 01:54:56,958] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 91.43 | bwd_microstep: 150.19 | bwd_inner_microstep: 150.00 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 01:54:57,439] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.18 | bwd_microstep: 273.22 | bwd_inner_microstep: 273.20 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 01:54:57,921] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.93 | bwd_microstep: 273.21 | bwd_inner_microstep: 273.19 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 01:54:58,404] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.20 | bwd_microstep: 273.55 | bwd_inner_microstep: 273.53 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 01:54:58,886] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.63 | bwd_microstep: 273.02 | bwd_inner_microstep: 273.00 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:54:59,366] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.00 | bwd_microstep: 272.52 | bwd_inner_microstep: 272.50 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 01:54:59,846] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.40 | bwd_microstep: 273.08 | bwd_inner_microstep: 273.06 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 01:55:00,327] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.47 | bwd_microstep: 273.19 | bwd_inner_microstep: 273.17 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 326 +[2025-05-02 01:55:00,593] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 97.00 | bwd_microstep: 149.43 | bwd_inner_microstep: 149.25 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.11 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 324 +[2025-05-02 01:55:00,845] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 81.96 | bwd_microstep: 152.69 | bwd_inner_microstep: 152.34 | bwd_allreduce_microstep: 0.15 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:55:01,323] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.83 | bwd_microstep: 272.14 | bwd_inner_microstep: 272.13 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:55:01,802] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.66 | bwd_microstep: 271.80 | bwd_inner_microstep: 271.78 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:55:02,383] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.31 | optimizer_step: 16.78 +[2025-05-02 01:55:02,384] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.47 | bwd_microstep: 349.65 | bwd_inner_microstep: 271.75 | bwd_allreduce_microstep: 77.85 | step_microstep: 24.99 +[2025-05-02 01:55:02,385] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2644.55 | bwd: 3969.70 | bwd_inner: 3890.70 | bwd_allreduce: 78.30 | step: 26.61 + 16%|█▋ | 1421/8720 [3:39:36<13:48:42, 6.81s/it] {'loss': 0.8096, 'grad_norm': 12.97114372253418, 'learning_rate': 9.543801573806552e-06, 'epoch': 1.63} + 16%|█▋ | 1421/8720 [3:39:36<13:48:42, 6.81s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1944 +[2025-05-02 01:55:02,892] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.69 | bwd_microstep: 288.23 | bwd_inner_microstep: 288.21 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 378 +[2025-05-02 01:55:03,146] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 85.47 | bwd_microstep: 150.79 | bwd_inner_microstep: 150.63 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 01:55:03,623] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.80 | bwd_microstep: 273.09 | bwd_inner_microstep: 273.07 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-02 01:55:04,104] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.28 | bwd_microstep: 274.25 | bwd_inner_microstep: 274.23 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.12 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1359 +[2025-05-02 01:55:04,473] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 143.16 | bwd_microstep: 206.99 | bwd_inner_microstep: 206.79 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 01:55:04,954] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.73 | bwd_microstep: 273.26 | bwd_inner_microstep: 273.24 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-02 01:55:05,438] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.67 | bwd_microstep: 273.66 | bwd_inner_microstep: 273.65 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 01:55:05,920] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.00 | bwd_microstep: 273.64 | bwd_inner_microstep: 273.62 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:55:06,399] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.62 | bwd_microstep: 272.86 | bwd_inner_microstep: 272.84 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 01:55:06,879] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.92 | bwd_microstep: 272.81 | bwd_inner_microstep: 272.80 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:55:07,359] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.97 | bwd_microstep: 273.46 | bwd_inner_microstep: 273.44 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 835 +[2025-05-02 01:55:07,623] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 96.12 | bwd_microstep: 148.77 | bwd_inner_microstep: 148.46 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:55:08,101] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.14 | bwd_microstep: 272.44 | bwd_inner_microstep: 272.42 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:55:08,579] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.37 | bwd_microstep: 271.13 | bwd_inner_microstep: 271.12 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:55:09,058] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.73 | bwd_microstep: 271.49 | bwd_inner_microstep: 271.47 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 01:55:09,645] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.17 | optimizer_step: 16.34 +[2025-05-02 01:55:09,645] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.55 | bwd_microstep: 358.05 | bwd_inner_microstep: 271.82 | bwd_allreduce_microstep: 86.18 | step_microstep: 24.04 +[2025-05-02 01:55:09,647] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2784.85 | bwd: 4154.99 | bwd_inner: 4067.92 | bwd_allreduce: 86.54 | step: 25.09 + 16%|█▋ | 1422/8720 [3:39:43<14:04:58, 6.95s/it] {'loss': 0.5936, 'grad_norm': 12.272019386291504, 'learning_rate': 9.543026228117917e-06, 'epoch': 1.63} + 16%|█▋ | 1422/8720 [3:39:43<14:04:58, 6.95s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 338 +[2025-05-02 01:55:09,898] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 79.99 | bwd_microstep: 149.87 | bwd_inner_microstep: 149.55 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1912 +[2025-05-02 01:55:10,385] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 192.49 | bwd_microstep: 276.38 | bwd_inner_microstep: 276.36 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1902 +[2025-05-02 01:55:10,870] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.26 | bwd_microstep: 276.43 | bwd_inner_microstep: 276.41 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1893 +[2025-05-02 01:55:11,353] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.98 | bwd_microstep: 275.14 | bwd_inner_microstep: 275.12 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 01:55:11,835] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.73 | bwd_microstep: 273.68 | bwd_inner_microstep: 273.67 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-02 01:55:12,316] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.75 | bwd_microstep: 273.65 | bwd_inner_microstep: 273.63 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 01:55:12,798] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.20 | bwd_microstep: 273.11 | bwd_inner_microstep: 273.10 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 01:55:13,278] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.80 | bwd_microstep: 273.46 | bwd_inner_microstep: 273.45 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.16 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 01:55:13,760] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.42 | bwd_microstep: 273.72 | bwd_inner_microstep: 273.71 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:55:14,239] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.75 | bwd_microstep: 272.72 | bwd_inner_microstep: 272.70 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:55:14,718] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.12 | bwd_microstep: 272.46 | bwd_inner_microstep: 272.45 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 330 +[2025-05-02 01:55:14,969] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 91.92 | bwd_microstep: 141.22 | bwd_inner_microstep: 141.08 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:55:15,447] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.23 | bwd_microstep: 272.51 | bwd_inner_microstep: 272.49 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 834 +[2025-05-02 01:55:15,702] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.50 | bwd_microstep: 145.06 | bwd_inner_microstep: 144.81 | bwd_allreduce_microstep: 0.10 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:55:16,179] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.66 | bwd_microstep: 271.39 | bwd_inner_microstep: 271.37 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 830 +[2025-05-02 01:55:16,557] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.09 | optimizer_step: 16.41 +[2025-05-02 01:55:16,557] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.51 | bwd_microstep: 243.61 | bwd_inner_microstep: 167.43 | bwd_allreduce_microstep: 76.08 | step_microstep: 23.40 +[2025-05-02 01:55:16,559] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2632.96 | bwd: 3964.48 | bwd_inner: 3887.49 | bwd_allreduce: 76.39 | step: 24.53 + 16%|█▋ | 1423/8720 [3:39:50<14:03:30, 6.94s/it] {'loss': 0.8511, 'grad_norm': 6.029689311981201, 'learning_rate': 9.542250255657229e-06, 'epoch': 1.63} + 16%|█▋ | 1423/8720 [3:39:50<14:03:30, 6.94s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 527 +[2025-05-02 01:55:16,801] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 72.68 | bwd_microstep: 151.98 | bwd_inner_microstep: 151.80 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1892 +[2025-05-02 01:55:17,281] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.99 | bwd_microstep: 275.08 | bwd_inner_microstep: 275.06 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-02 01:55:17,760] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.15 | bwd_microstep: 273.93 | bwd_inner_microstep: 273.92 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-02 01:55:18,239] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.76 | bwd_microstep: 275.11 | bwd_inner_microstep: 275.09 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 01:55:18,719] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.99 | bwd_microstep: 272.98 | bwd_inner_microstep: 272.97 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1356 +[2025-05-02 01:55:19,086] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.59 | bwd_microstep: 206.72 | bwd_inner_microstep: 206.60 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-02 01:55:19,569] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.04 | bwd_microstep: 273.41 | bwd_inner_microstep: 273.39 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 01:55:20,050] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.38 | bwd_microstep: 273.30 | bwd_inner_microstep: 273.28 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 01:55:20,533] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.50 | bwd_microstep: 274.10 | bwd_inner_microstep: 274.09 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:55:21,015] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.30 | bwd_microstep: 273.40 | bwd_inner_microstep: 273.38 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 01:55:21,496] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.26 | bwd_microstep: 273.00 | bwd_inner_microstep: 272.99 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.07 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:55:21,977] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.85 | bwd_microstep: 273.37 | bwd_inner_microstep: 273.35 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:55:22,458] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.47 | bwd_microstep: 272.99 | bwd_inner_microstep: 272.97 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:55:22,935] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.32 | bwd_microstep: 271.77 | bwd_inner_microstep: 271.75 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:55:23,415] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.68 | bwd_microstep: 271.97 | bwd_inner_microstep: 271.95 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:55:23,995] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.14 | optimizer_step: 16.38 +[2025-05-02 01:55:23,995] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.93 | bwd_microstep: 348.58 | bwd_inner_microstep: 271.92 | bwd_allreduce_microstep: 76.61 | step_microstep: 24.11 +[2025-05-02 01:55:23,996] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2860.53 | bwd: 4261.74 | bwd_inner: 4184.57 | bwd_allreduce: 76.81 | step: 25.30 + 16%|█▋ | 1424/8720 [3:39:57<14:21:46, 7.09s/it] {'loss': 0.6677, 'grad_norm': 9.37939167022705, 'learning_rate': 9.541473656531544e-06, 'epoch': 1.63} + 16%|█▋ | 1424/8720 [3:39:57<14:21:46, 7.09s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 01:55:24,478] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.83 | bwd_microstep: 270.78 | bwd_inner_microstep: 270.77 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2140 +[2025-05-02 01:55:25,016] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 204.74 | bwd_microstep: 315.07 | bwd_inner_microstep: 315.06 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1894 +[2025-05-02 01:55:25,499] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.11 | bwd_microstep: 275.33 | bwd_inner_microstep: 275.31 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-02 01:55:25,982] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.20 | bwd_microstep: 274.19 | bwd_inner_microstep: 274.17 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1883 +[2025-05-02 01:55:26,463] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.75 | bwd_microstep: 274.88 | bwd_inner_microstep: 274.86 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.08 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 858 +[2025-05-02 01:55:26,734] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 105.88 | bwd_microstep: 146.63 | bwd_inner_microstep: 146.32 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 01:55:27,217] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.13 | bwd_microstep: 273.47 | bwd_inner_microstep: 273.45 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1364 +[2025-05-02 01:55:27,585] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.86 | bwd_microstep: 207.39 | bwd_inner_microstep: 207.16 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-02 01:55:28,065] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.76 | bwd_microstep: 273.76 | bwd_inner_microstep: 273.74 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 01:55:28,546] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.71 | bwd_microstep: 273.02 | bwd_inner_microstep: 273.00 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 01:55:29,030] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.95 | bwd_microstep: 272.90 | bwd_inner_microstep: 272.88 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:55:29,509] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.07 | bwd_microstep: 272.98 | bwd_inner_microstep: 272.96 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 323 +[2025-05-02 01:55:29,767] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 90.33 | bwd_microstep: 150.05 | bwd_inner_microstep: 149.84 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:55:30,245] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.25 | bwd_microstep: 272.99 | bwd_inner_microstep: 272.97 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:55:30,722] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.71 | bwd_microstep: 271.64 | bwd_inner_microstep: 271.63 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 01:55:31,294] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.17 | optimizer_step: 16.35 +[2025-05-02 01:55:31,295] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.66 | bwd_microstep: 344.71 | bwd_inner_microstep: 271.95 | bwd_allreduce_microstep: 72.70 | step_microstep: 23.40 +[2025-05-02 01:55:31,296] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2803.54 | bwd: 4169.87 | bwd_inner: 4096.22 | bwd_allreduce: 73.07 | step: 24.61 + 16%|█▋ | 1425/8720 [3:40:05<14:29:20, 7.15s/it] {'loss': 0.5634, 'grad_norm': 8.411507606506348, 'learning_rate': 9.540696430848005e-06, 'epoch': 1.63} + 16%|█▋ | 1425/8720 [3:40:05<14:29:20, 7.15s/it]dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 850 +[2025-05-02 01:55:31,540] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.32 | bwd_microstep: 132.77 | bwd_inner_microstep: 132.63 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1949 +[2025-05-02 01:55:32,040] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.13 | bwd_microstep: 289.67 | bwd_inner_microstep: 289.66 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-02 01:55:32,518] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.47 | bwd_microstep: 273.79 | bwd_inner_microstep: 273.77 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 326 +[2025-05-02 01:55:32,757] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 75.86 | bwd_microstep: 149.25 | bwd_inner_microstep: 149.13 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 01:55:33,233] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.80 | bwd_microstep: 272.87 | bwd_inner_microstep: 272.85 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 01:55:33,710] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.82 | bwd_microstep: 272.86 | bwd_inner_microstep: 272.84 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 841 +[2025-05-02 01:55:33,950] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.25 | bwd_microstep: 131.99 | bwd_inner_microstep: 131.88 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 843 +[2025-05-02 01:55:34,193] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.26 | bwd_microstep: 132.57 | bwd_inner_microstep: 132.49 | bwd_allreduce_microstep: 0.03 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 01:55:34,674] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.88 | bwd_microstep: 273.35 | bwd_inner_microstep: 273.34 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:55:35,152] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.35 | bwd_microstep: 273.17 | bwd_inner_microstep: 273.15 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:55:35,627] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.85 | bwd_microstep: 271.93 | bwd_inner_microstep: 271.91 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:55:36,103] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.81 | bwd_microstep: 272.29 | bwd_inner_microstep: 272.27 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:55:36,577] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.65 | bwd_microstep: 271.23 | bwd_inner_microstep: 271.21 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 832 +[2025-05-02 01:55:36,820] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 92.29 | bwd_microstep: 136.64 | bwd_inner_microstep: 136.51 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:55:37,293] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.87 | bwd_microstep: 271.22 | bwd_inner_microstep: 271.21 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 01:55:37,859] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.04 | optimizer_gradients: 2.11 | optimizer_step: 16.37 +[2025-05-02 01:55:37,859] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.07 | bwd_microstep: 339.56 | bwd_inner_microstep: 272.27 | bwd_allreduce_microstep: 67.24 | step_microstep: 23.40 +[2025-05-02 01:55:37,860] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2528.41 | bwd: 3765.24 | bwd_inner: 3697.21 | bwd_allreduce: 67.56 | step: 24.34 + 16%|█▋ | 1426/8720 [3:40:11<14:07:51, 6.97s/it] {'loss': 0.5338, 'grad_norm': 10.124195098876953, 'learning_rate': 9.539918578713842e-06, 'epoch': 1.64} + 16%|█▋ | 1426/8720 [3:40:11<14:07:51, 6.97s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 01:55:38,339] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.86 | bwd_microstep: 271.07 | bwd_inner_microstep: 271.05 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1888 +[2025-05-02 01:55:38,818] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.62 | bwd_microstep: 274.58 | bwd_inner_microstep: 274.56 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1886 +[2025-05-02 01:55:39,297] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.94 | bwd_microstep: 274.41 | bwd_inner_microstep: 274.40 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-02 01:55:39,775] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.51 | bwd_microstep: 273.39 | bwd_inner_microstep: 273.38 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 839 +[2025-05-02 01:55:40,037] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 92.99 | bwd_microstep: 152.11 | bwd_inner_microstep: 151.90 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.09 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1363 +[2025-05-02 01:55:40,400] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.72 | bwd_microstep: 207.00 | bwd_inner_microstep: 206.98 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 839 +[2025-05-02 01:55:40,654] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.89 | bwd_microstep: 143.60 | bwd_inner_microstep: 143.28 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 327 +[2025-05-02 01:55:40,898] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 78.98 | bwd_microstep: 149.48 | bwd_inner_microstep: 149.17 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:55:41,373] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.62 | bwd_microstep: 272.58 | bwd_inner_microstep: 272.56 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:55:41,849] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.50 | bwd_microstep: 272.67 | bwd_inner_microstep: 272.66 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:55:42,328] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.83 | bwd_microstep: 273.40 | bwd_inner_microstep: 273.39 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 01:55:42,806] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.27 | bwd_microstep: 272.51 | bwd_inner_microstep: 272.49 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 01:55:43,285] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.64 | bwd_microstep: 272.03 | bwd_inner_microstep: 272.02 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:55:43,762] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.29 | bwd_microstep: 271.65 | bwd_inner_microstep: 271.63 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:55:44,241] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.77 | bwd_microstep: 271.52 | bwd_inner_microstep: 271.50 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:55:44,820] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.18 | optimizer_step: 16.44 +[2025-05-02 01:55:44,821] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.89 | bwd_microstep: 349.94 | bwd_inner_microstep: 271.77 | bwd_allreduce_microstep: 78.12 | step_microstep: 24.33 +[2025-05-02 01:55:44,822] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2670.02 | bwd: 4002.03 | bwd_inner: 3922.91 | bwd_allreduce: 78.48 | step: 25.63 + 16%|█▋ | 1427/8720 [3:40:18<14:07:21, 6.97s/it] {'loss': 0.4369, 'grad_norm': 6.456092357635498, 'learning_rate': 9.539140100236369e-06, 'epoch': 1.64} + 16%|█▋ | 1427/8720 [3:40:18<14:07:21, 6.97s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1908 +[2025-05-02 01:55:45,311] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.36 | bwd_microstep: 275.49 | bwd_inner_microstep: 275.48 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-02 01:55:45,794] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.11 | bwd_microstep: 274.50 | bwd_inner_microstep: 274.48 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 343 +[2025-05-02 01:55:46,041] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 79.98 | bwd_microstep: 151.19 | bwd_inner_microstep: 150.88 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-02 01:55:46,521] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.90 | bwd_microstep: 273.54 | bwd_inner_microstep: 273.52 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-02 01:55:47,001] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.99 | bwd_microstep: 273.83 | bwd_inner_microstep: 273.81 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 838 +[2025-05-02 01:55:47,250] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 103.89 | bwd_microstep: 125.78 | bwd_inner_microstep: 125.54 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 845 +[2025-05-02 01:55:47,492] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.27 | bwd_microstep: 132.24 | bwd_inner_microstep: 132.05 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.10 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 836 +[2025-05-02 01:55:47,728] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.00 | bwd_microstep: 126.03 | bwd_inner_microstep: 125.91 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 01:55:48,208] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.84 | bwd_microstep: 273.14 | bwd_inner_microstep: 273.13 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:55:48,687] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.04 | bwd_microstep: 272.76 | bwd_inner_microstep: 272.74 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 325 +[2025-05-02 01:55:48,901] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 79.72 | bwd_microstep: 119.18 | bwd_inner_microstep: 118.88 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:55:49,380] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.22 | bwd_microstep: 272.91 | bwd_inner_microstep: 272.89 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1351 +[2025-05-02 01:55:49,744] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.05 | bwd_microstep: 206.08 | bwd_inner_microstep: 205.94 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.13 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:55:50,223] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.81 | bwd_microstep: 272.46 | bwd_inner_microstep: 272.44 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 833 +[2025-05-02 01:55:50,461] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.41 | bwd_microstep: 125.64 | bwd_inner_microstep: 125.63 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 01:55:51,051] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.16 | optimizer_step: 25.17 +[2025-05-02 01:55:51,051] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.07 | bwd_microstep: 351.78 | bwd_inner_microstep: 271.99 | bwd_allreduce_microstep: 79.73 | step_microstep: 32.97 +[2025-05-02 01:55:51,053] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2388.33 | bwd: 3526.67 | bwd_inner: 3445.45 | bwd_allreduce: 80.32 | step: 34.37 + 16%|█▋ | 1428/8720 [3:40:24<13:40:14, 6.75s/it] {'loss': 0.5626, 'grad_norm': 15.892836570739746, 'learning_rate': 9.538360995522989e-06, 'epoch': 1.64} + 16%|█▋ | 1428/8720 [3:40:24<13:40:14, 6.75s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:55:51,535] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.46 | bwd_microstep: 270.69 | bwd_inner_microstep: 270.67 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1144 +[2025-05-02 01:55:51,836] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 118.85 | bwd_microstep: 165.33 | bwd_inner_microstep: 165.25 | bwd_allreduce_microstep: 0.03 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1893 +[2025-05-02 01:55:52,318] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.30 | bwd_microstep: 275.22 | bwd_inner_microstep: 275.20 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-02 01:55:52,801] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.25 | bwd_microstep: 273.78 | bwd_inner_microstep: 273.76 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.15 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-02 01:55:53,283] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.65 | bwd_microstep: 273.48 | bwd_inner_microstep: 273.46 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 847 +[2025-05-02 01:55:53,527] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.04 | bwd_microstep: 133.23 | bwd_inner_microstep: 132.97 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 01:55:54,008] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.55 | bwd_microstep: 273.26 | bwd_inner_microstep: 273.24 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 01:55:54,488] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.42 | bwd_microstep: 272.92 | bwd_inner_microstep: 272.90 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:55:54,967] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.24 | bwd_microstep: 271.87 | bwd_inner_microstep: 271.85 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 01:55:55,446] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.93 | bwd_microstep: 272.66 | bwd_inner_microstep: 272.64 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 01:55:55,926] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.70 | bwd_microstep: 272.55 | bwd_inner_microstep: 272.53 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:55:56,409] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.00 | bwd_microstep: 272.05 | bwd_inner_microstep: 272.03 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 01:55:56,890] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.70 | bwd_microstep: 272.61 | bwd_inner_microstep: 272.59 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 01:55:57,367] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.08 | bwd_microstep: 271.97 | bwd_inner_microstep: 271.95 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:55:57,846] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.64 | bwd_microstep: 272.27 | bwd_inner_microstep: 272.25 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1341 +[2025-05-02 01:55:58,299] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.21 | optimizer_step: 16.49 +[2025-05-02 01:55:58,299] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 142.75 | bwd_microstep: 271.61 | bwd_inner_microstep: 204.90 | bwd_allreduce_microstep: 66.60 | step_microstep: 23.74 +[2025-05-02 01:55:58,300] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2811.21 | bwd: 4115.52 | bwd_inner: 4048.26 | bwd_allreduce: 66.83 | step: 24.74 + 16%|█▋ | 1429/8720 [3:40:32<13:58:14, 6.90s/it] {'loss': 0.8794, 'grad_norm': 12.797378540039062, 'learning_rate': 9.537581264681189e-06, 'epoch': 1.64} + 16%|█▋ | 1429/8720 [3:40:32<13:58:14, 6.90s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 315 +[2025-05-02 01:55:58,506] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 71.73 | bwd_microstep: 115.38 | bwd_inner_microstep: 115.25 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2005 +[2025-05-02 01:55:59,016] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 199.78 | bwd_microstep: 294.75 | bwd_inner_microstep: 294.73 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1926 +[2025-05-02 01:55:59,514] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 194.79 | bwd_microstep: 287.39 | bwd_inner_microstep: 287.37 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1892 +[2025-05-02 01:55:59,993] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.93 | bwd_microstep: 275.07 | bwd_inner_microstep: 275.05 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-02 01:56:00,472] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.49 | bwd_microstep: 273.90 | bwd_inner_microstep: 273.89 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 334 +[2025-05-02 01:56:00,684] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 77.09 | bwd_microstep: 120.63 | bwd_inner_microstep: 120.31 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 01:56:01,163] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.41 | bwd_microstep: 273.50 | bwd_inner_microstep: 273.48 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 01:56:01,862] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 411.12 | bwd_microstep: 272.39 | bwd_inner_microstep: 272.37 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.06 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1352 +[2025-05-02 01:56:02,225] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.26 | bwd_microstep: 206.09 | bwd_inner_microstep: 205.99 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 844 +[2025-05-02 01:56:02,465] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.93 | bwd_microstep: 132.17 | bwd_inner_microstep: 131.93 | bwd_allreduce_microstep: 0.14 | step_microstep: 0.09 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 841 +[2025-05-02 01:56:02,705] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.51 | bwd_microstep: 131.85 | bwd_inner_microstep: 131.70 | bwd_allreduce_microstep: 0.08 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:56:03,181] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.39 | bwd_microstep: 272.51 | bwd_inner_microstep: 272.49 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 01:56:03,658] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.71 | bwd_microstep: 273.25 | bwd_inner_microstep: 273.23 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 01:56:04,135] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.65 | bwd_microstep: 273.10 | bwd_inner_microstep: 273.08 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:56:04,612] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.04 | bwd_microstep: 272.33 | bwd_inner_microstep: 272.32 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:56:05,184] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.22 | optimizer_step: 21.61 +[2025-05-02 01:56:05,184] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.82 | bwd_microstep: 339.12 | bwd_inner_microstep: 272.51 | bwd_allreduce_microstep: 66.57 | step_microstep: 28.95 +[2025-05-02 01:56:05,185] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2790.40 | bwd: 3813.52 | bwd_inner: 3745.79 | bwd_allreduce: 67.08 | step: 29.97 + 16%|█▋ | 1430/8720 [3:40:38<13:57:38, 6.89s/it] {'loss': 0.7671, 'grad_norm': 8.590224266052246, 'learning_rate': 9.536800907818542e-06, 'epoch': 1.64} + 16%|█▋ | 1430/8720 [3:40:38<13:57:38, 6.89s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:56:05,664] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.91 | bwd_microstep: 270.39 | bwd_inner_microstep: 270.37 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1974 +[2025-05-02 01:56:06,168] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 197.42 | bwd_microstep: 291.46 | bwd_inner_microstep: 291.45 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1973 +[2025-05-02 01:56:06,675] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 198.38 | bwd_microstep: 291.54 | bwd_inner_microstep: 291.52 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1939 +[2025-05-02 01:56:07,174] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.27 | bwd_microstep: 288.73 | bwd_inner_microstep: 288.71 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1913 +[2025-05-02 01:56:07,659] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.69 | bwd_microstep: 276.50 | bwd_inner_microstep: 276.48 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1377 +[2025-05-02 01:56:08,028] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 142.38 | bwd_microstep: 208.28 | bwd_inner_microstep: 208.10 | bwd_allreduce_microstep: 0.09 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-02 01:56:08,513] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.34 | bwd_microstep: 274.15 | bwd_inner_microstep: 274.13 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1883 +[2025-05-02 01:56:08,995] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.62 | bwd_microstep: 274.25 | bwd_inner_microstep: 274.23 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 01:56:09,475] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.93 | bwd_microstep: 273.01 | bwd_inner_microstep: 272.99 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-02 01:56:09,955] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.86 | bwd_microstep: 273.24 | bwd_inner_microstep: 273.22 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:56:10,434] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.76 | bwd_microstep: 272.51 | bwd_inner_microstep: 272.49 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:56:10,915] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.43 | bwd_microstep: 272.99 | bwd_inner_microstep: 272.97 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.13 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:56:11,397] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.07 | bwd_microstep: 272.41 | bwd_inner_microstep: 272.40 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 01:56:11,880] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.35 | bwd_microstep: 271.46 | bwd_inner_microstep: 271.44 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:56:12,359] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.96 | bwd_microstep: 271.58 | bwd_inner_microstep: 271.57 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:56:12,940] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.24 | optimizer_step: 16.45 +[2025-05-02 01:56:12,941] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.76 | bwd_microstep: 348.88 | bwd_inner_microstep: 271.93 | bwd_allreduce_microstep: 76.90 | step_microstep: 24.38 +[2025-05-02 01:56:12,942] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2998.78 | bwd: 4431.41 | bwd_inner: 4354.02 | bwd_allreduce: 77.11 | step: 25.42 + 16%|█▋ | 1431/8720 [3:40:46<14:29:02, 7.15s/it] {'loss': 0.8531, 'grad_norm': 13.595519065856934, 'learning_rate': 9.53601992504271e-06, 'epoch': 1.64} + 16%|█▋ | 1431/8720 [3:40:46<14:29:02, 7.15s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 313 +[2025-05-02 01:56:13,166] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 79.50 | bwd_microstep: 123.01 | bwd_inner_microstep: 122.70 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1928 +[2025-05-02 01:56:13,666] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 194.99 | bwd_microstep: 287.41 | bwd_inner_microstep: 287.40 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1907 +[2025-05-02 01:56:14,153] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 191.29 | bwd_microstep: 275.93 | bwd_inner_microstep: 275.91 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1887 +[2025-05-02 01:56:14,637] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.31 | bwd_microstep: 274.60 | bwd_inner_microstep: 274.58 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-02 01:56:15,121] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.36 | bwd_microstep: 273.81 | bwd_inner_microstep: 273.79 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-02 01:56:15,604] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.50 | bwd_microstep: 273.40 | bwd_inner_microstep: 273.38 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1357 +[2025-05-02 01:56:15,974] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.75 | bwd_microstep: 206.67 | bwd_inner_microstep: 206.58 | bwd_allreduce_microstep: 0.04 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 01:56:16,459] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.86 | bwd_microstep: 272.85 | bwd_inner_microstep: 272.83 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 839 +[2025-05-02 01:56:16,700] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 96.53 | bwd_microstep: 126.12 | bwd_inner_microstep: 126.10 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 01:56:17,180] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.13 | bwd_microstep: 272.77 | bwd_inner_microstep: 272.76 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 01:56:17,659] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.17 | bwd_microstep: 272.83 | bwd_inner_microstep: 272.82 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 01:56:18,140] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.58 | bwd_microstep: 273.63 | bwd_inner_microstep: 273.61 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:56:18,619] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.64 | bwd_microstep: 272.27 | bwd_inner_microstep: 272.25 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:56:19,098] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.80 | bwd_microstep: 272.22 | bwd_inner_microstep: 272.20 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:56:19,577] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.45 | bwd_microstep: 272.39 | bwd_inner_microstep: 272.37 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:56:20,155] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.17 | optimizer_step: 16.57 +[2025-05-02 01:56:20,156] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.06 | bwd_microstep: 348.58 | bwd_inner_microstep: 271.99 | bwd_allreduce_microstep: 76.54 | step_microstep: 23.82 +[2025-05-02 01:56:20,157] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2783.54 | bwd: 4098.55 | bwd_inner: 4021.34 | bwd_allreduce: 76.79 | step: 24.75 + 16%|█▋ | 1432/8720 [3:40:53<14:31:04, 7.17s/it] {'loss': 0.7124, 'grad_norm': 18.3519344329834, 'learning_rate': 9.535238316461442e-06, 'epoch': 1.64} + 16%|█▋ | 1432/8720 [3:40:53<14:31:04, 7.17s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 01:56:20,636] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.32 | bwd_microstep: 270.82 | bwd_inner_microstep: 270.81 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1941 +[2025-05-02 01:56:21,137] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 196.44 | bwd_microstep: 288.42 | bwd_inner_microstep: 288.41 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 367 +[2025-05-02 01:56:21,359] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 86.35 | bwd_microstep: 120.25 | bwd_inner_microstep: 120.12 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-02 01:56:21,838] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.05 | bwd_microstep: 273.77 | bwd_inner_microstep: 273.76 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-02 01:56:22,317] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.67 | bwd_microstep: 273.79 | bwd_inner_microstep: 273.77 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-02 01:56:22,798] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.20 | bwd_microstep: 274.12 | bwd_inner_microstep: 274.10 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.13 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-02 01:56:23,281] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.70 | bwd_microstep: 273.93 | bwd_inner_microstep: 273.91 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-02 01:56:23,763] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.12 | bwd_microstep: 273.37 | bwd_inner_microstep: 273.35 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 01:56:24,243] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.09 | bwd_microstep: 272.88 | bwd_inner_microstep: 272.86 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1351 +[2025-05-02 01:56:24,607] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.51 | bwd_microstep: 206.17 | bwd_inner_microstep: 206.00 | bwd_allreduce_microstep: 0.10 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:56:25,088] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.20 | bwd_microstep: 273.06 | bwd_inner_microstep: 273.04 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 01:56:25,570] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.09 | bwd_microstep: 272.89 | bwd_inner_microstep: 272.87 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:56:26,057] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.54 | bwd_microstep: 273.28 | bwd_inner_microstep: 273.26 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 322 +[2025-05-02 01:56:26,274] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 83.51 | bwd_microstep: 117.21 | bwd_inner_microstep: 117.06 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:56:26,751] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.36 | bwd_microstep: 271.45 | bwd_inner_microstep: 271.43 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 01:56:27,336] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.27 | optimizer_step: 16.89 +[2025-05-02 01:56:27,336] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.60 | bwd_microstep: 352.09 | bwd_inner_microstep: 271.59 | bwd_allreduce_microstep: 80.45 | step_microstep: 25.06 +[2025-05-02 01:56:27,337] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2774.37 | bwd: 4087.57 | bwd_inner: 4006.40 | bwd_allreduce: 80.78 | step: 26.06 + 16%|█▋ | 1433/8720 [3:41:01<14:31:21, 7.17s/it] {'loss': 0.8288, 'grad_norm': 8.043546676635742, 'learning_rate': 9.53445608218257e-06, 'epoch': 1.64} + 16%|█▋ | 1433/8720 [3:41:01<14:31:21, 7.17s/it]dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1360 +[2025-05-02 01:56:27,707] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.11 | bwd_microstep: 206.09 | bwd_inner_microstep: 205.86 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.11 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 396 +[2025-05-02 01:56:27,940] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 84.66 | bwd_microstep: 132.55 | bwd_inner_microstep: 132.33 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-02 01:56:28,421] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.65 | bwd_microstep: 274.06 | bwd_inner_microstep: 274.04 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-02 01:56:28,902] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.67 | bwd_microstep: 274.33 | bwd_inner_microstep: 274.31 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 01:56:29,384] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.49 | bwd_microstep: 273.43 | bwd_inner_microstep: 273.41 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.15 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:56:29,867] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.42 | bwd_microstep: 273.24 | bwd_inner_microstep: 273.22 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 842 +[2025-05-02 01:56:30,110] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.53 | bwd_microstep: 132.02 | bwd_inner_microstep: 131.82 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 01:56:30,590] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.97 | bwd_microstep: 273.09 | bwd_inner_microstep: 273.07 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:56:31,068] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.71 | bwd_microstep: 272.40 | bwd_inner_microstep: 272.39 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:56:31,547] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.85 | bwd_microstep: 271.42 | bwd_inner_microstep: 271.41 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:56:32,023] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.10 | bwd_microstep: 271.08 | bwd_inner_microstep: 271.07 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:56:32,503] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.88 | bwd_microstep: 271.72 | bwd_inner_microstep: 271.70 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:56:32,979] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.88 | bwd_microstep: 271.10 | bwd_inner_microstep: 271.08 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 01:56:33,456] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.94 | bwd_microstep: 271.77 | bwd_inner_microstep: 271.75 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1340 +[2025-05-02 01:56:33,820] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.11 | bwd_microstep: 204.45 | bwd_inner_microstep: 204.41 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 01:56:34,401] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.14 | optimizer_step: 16.55 +[2025-05-02 01:56:34,401] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.12 | bwd_microstep: 351.69 | bwd_inner_microstep: 272.28 | bwd_allreduce_microstep: 79.35 | step_microstep: 24.36 +[2025-05-02 01:56:34,403] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2722.72 | bwd: 4024.50 | bwd_inner: 3944.21 | bwd_allreduce: 79.73 | step: 25.66 + 16%|█▋ | 1434/8720 [3:41:08<14:27:14, 7.14s/it] {'loss': 0.5885, 'grad_norm': 9.141556739807129, 'learning_rate': 9.533673222314013e-06, 'epoch': 1.64} + 16%|█▋ | 1434/8720 [3:41:08<14:27:14, 7.14s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1849 +[2025-05-02 01:56:34,885] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.99 | bwd_microstep: 270.83 | bwd_inner_microstep: 270.81 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1889 +[2025-05-02 01:56:35,369] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.43 | bwd_microstep: 275.53 | bwd_inner_microstep: 275.51 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 864 +[2025-05-02 01:56:35,626] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 98.98 | bwd_microstep: 140.75 | bwd_inner_microstep: 140.48 | bwd_allreduce_microstep: 0.14 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1888 +[2025-05-02 01:56:36,108] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.50 | bwd_microstep: 274.77 | bwd_inner_microstep: 274.75 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 343 +[2025-05-02 01:56:36,342] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.05 | bwd_microstep: 121.80 | bwd_inner_microstep: 121.50 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-02 01:56:36,822] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.52 | bwd_microstep: 274.36 | bwd_inner_microstep: 274.35 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 01:56:37,300] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.33 | bwd_microstep: 273.32 | bwd_inner_microstep: 273.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 841 +[2025-05-02 01:56:37,543] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.88 | bwd_microstep: 132.43 | bwd_inner_microstep: 132.26 | bwd_allreduce_microstep: 0.10 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:56:38,021] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.92 | bwd_microstep: 272.44 | bwd_inner_microstep: 272.43 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 01:56:38,502] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.47 | bwd_microstep: 273.19 | bwd_inner_microstep: 273.17 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 01:56:38,983] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.38 | bwd_microstep: 273.28 | bwd_inner_microstep: 273.27 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 01:56:39,467] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.20 | bwd_microstep: 274.02 | bwd_inner_microstep: 274.00 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:56:39,950] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.43 | bwd_microstep: 273.10 | bwd_inner_microstep: 273.08 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 01:56:40,435] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.10 | bwd_microstep: 272.70 | bwd_inner_microstep: 272.68 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 01:56:40,918] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.38 | bwd_microstep: 272.40 | bwd_inner_microstep: 272.38 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.16 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:56:41,502] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.16 | optimizer_step: 21.48 +[2025-05-02 01:56:41,503] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.63 | bwd_microstep: 348.92 | bwd_inner_microstep: 273.47 | bwd_allreduce_microstep: 75.41 | step_microstep: 29.28 +[2025-05-02 01:56:41,504] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2738.74 | bwd: 4023.91 | bwd_inner: 3947.49 | bwd_allreduce: 75.84 | step: 30.46 + 16%|█▋ | 1435/8720 [3:41:15<14:25:39, 7.13s/it] {'loss': 0.6827, 'grad_norm': 6.2712860107421875, 'learning_rate': 9.532889736963777e-06, 'epoch': 1.65} + 16%|█▋ | 1435/8720 [3:41:15<14:25:39, 7.13s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 01:56:41,986] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.46 | bwd_microstep: 271.29 | bwd_inner_microstep: 271.27 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1911 +[2025-05-02 01:56:42,470] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.81 | bwd_microstep: 276.96 | bwd_inner_microstep: 276.94 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-02 01:56:42,950] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.25 | bwd_microstep: 274.26 | bwd_inner_microstep: 274.24 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-02 01:56:43,432] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.03 | bwd_microstep: 274.87 | bwd_inner_microstep: 274.85 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 01:56:43,914] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.30 | bwd_microstep: 272.89 | bwd_inner_microstep: 272.87 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-02 01:56:44,398] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.51 | bwd_microstep: 273.76 | bwd_inner_microstep: 273.74 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 01:56:44,883] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.23 | bwd_microstep: 273.50 | bwd_inner_microstep: 273.48 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 01:56:45,365] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.41 | bwd_microstep: 272.73 | bwd_inner_microstep: 272.71 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:56:45,848] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.95 | bwd_microstep: 272.78 | bwd_inner_microstep: 272.76 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 844 +[2025-05-02 01:56:46,099] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 97.98 | bwd_microstep: 131.97 | bwd_inner_microstep: 131.87 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-02 01:56:46,578] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.18 | bwd_microstep: 273.17 | bwd_inner_microstep: 273.15 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 323 +[2025-05-02 01:56:46,809] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.51 | bwd_microstep: 119.11 | bwd_inner_microstep: 118.79 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 01:56:47,286] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.33 | bwd_microstep: 271.10 | bwd_inner_microstep: 271.08 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:56:47,762] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.10 | bwd_microstep: 271.11 | bwd_inner_microstep: 271.09 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:56:48,241] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.83 | bwd_microstep: 271.20 | bwd_inner_microstep: 271.18 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:56:48,815] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.13 | optimizer_step: 23.55 +[2025-05-02 01:56:48,815] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.64 | bwd_microstep: 339.49 | bwd_inner_microstep: 271.59 | bwd_allreduce_microstep: 67.85 | step_microstep: 30.64 +[2025-05-02 01:56:48,817] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2834.14 | bwd: 4140.23 | bwd_inner: 4071.72 | bwd_allreduce: 68.10 | step: 31.60 + 16%|█▋ | 1436/8720 [3:41:22<14:32:08, 7.18s/it] {'loss': 0.734, 'grad_norm': 11.455995559692383, 'learning_rate': 9.532105626239957e-06, 'epoch': 1.65} + 16%|█▋ | 1436/8720 [3:41:22<14:32:08, 7.18s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 01:56:49,295] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.46 | bwd_microstep: 270.73 | bwd_inner_microstep: 270.71 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1928 +[2025-05-02 01:56:49,793] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.64 | bwd_microstep: 287.54 | bwd_inner_microstep: 287.52 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1893 +[2025-05-02 01:56:50,273] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.96 | bwd_microstep: 275.18 | bwd_inner_microstep: 275.17 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 01:56:50,751] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.48 | bwd_microstep: 273.60 | bwd_inner_microstep: 273.58 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 01:56:51,229] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.65 | bwd_microstep: 273.17 | bwd_inner_microstep: 273.15 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 01:56:51,707] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.67 | bwd_microstep: 273.75 | bwd_inner_microstep: 273.74 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-02 01:56:52,187] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.03 | bwd_microstep: 273.84 | bwd_inner_microstep: 273.82 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 01:56:52,666] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.45 | bwd_microstep: 273.38 | bwd_inner_microstep: 273.36 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 840 +[2025-05-02 01:56:52,898] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 91.65 | bwd_microstep: 126.59 | bwd_inner_microstep: 126.38 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 01:56:53,374] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.60 | bwd_microstep: 273.24 | bwd_inner_microstep: 273.22 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 01:56:53,851] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.86 | bwd_microstep: 273.24 | bwd_inner_microstep: 273.22 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:56:54,330] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.07 | bwd_microstep: 272.68 | bwd_inner_microstep: 272.67 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.16 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 01:56:54,813] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.14 | bwd_microstep: 273.29 | bwd_inner_microstep: 273.27 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:56:55,293] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.03 | bwd_microstep: 272.51 | bwd_inner_microstep: 272.50 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:56:55,770] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.85 | bwd_microstep: 271.19 | bwd_inner_microstep: 271.18 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:56:56,348] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.16 | optimizer_step: 16.39 +[2025-05-02 01:56:56,349] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.82 | bwd_microstep: 348.91 | bwd_inner_microstep: 271.77 | bwd_allreduce_microstep: 77.09 | step_microstep: 24.12 +[2025-05-02 01:56:56,350] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2932.08 | bwd: 4312.87 | bwd_inner: 4235.25 | bwd_allreduce: 77.29 | step: 25.10 + 16%|█▋ | 1437/8720 [3:41:30<14:44:48, 7.29s/it] {'loss': 0.8246, 'grad_norm': 11.417261123657227, 'learning_rate': 9.531320890250731e-06, 'epoch': 1.65} + 16%|█▋ | 1437/8720 [3:41:30<14:44:48, 7.29s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 01:56:56,831] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.76 | bwd_microstep: 270.26 | bwd_inner_microstep: 270.25 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1917 +[2025-05-02 01:56:57,315] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.50 | bwd_microstep: 276.36 | bwd_inner_microstep: 276.34 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1921 +[2025-05-02 01:56:57,813] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 194.83 | bwd_microstep: 287.07 | bwd_inner_microstep: 287.06 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.14 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1377 +[2025-05-02 01:56:58,179] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.85 | bwd_microstep: 208.15 | bwd_inner_microstep: 208.08 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-02 01:56:58,660] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.85 | bwd_microstep: 274.09 | bwd_inner_microstep: 274.07 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 01:56:59,142] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.91 | bwd_microstep: 273.83 | bwd_inner_microstep: 273.81 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 347 +[2025-05-02 01:56:59,370] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 90.79 | bwd_microstep: 118.92 | bwd_inner_microstep: 118.77 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.09 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 326 +[2025-05-02 01:56:59,588] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 82.87 | bwd_microstep: 119.77 | bwd_inner_microstep: 119.53 | bwd_allreduce_microstep: 0.08 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:57:00,067] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.80 | bwd_microstep: 272.63 | bwd_inner_microstep: 272.61 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 01:57:00,548] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.54 | bwd_microstep: 273.11 | bwd_inner_microstep: 273.09 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:57:01,031] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.55 | bwd_microstep: 272.68 | bwd_inner_microstep: 272.66 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 01:57:01,508] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.49 | bwd_microstep: 271.40 | bwd_inner_microstep: 271.38 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:57:01,986] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.76 | bwd_microstep: 271.30 | bwd_inner_microstep: 271.28 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:57:02,464] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.13 | bwd_microstep: 271.23 | bwd_inner_microstep: 271.21 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 01:57:02,942] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.71 | bwd_microstep: 271.16 | bwd_inner_microstep: 271.15 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1849 +[2025-05-02 01:57:03,526] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.12 | optimizer_step: 16.40 +[2025-05-02 01:57:03,527] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.47 | bwd_microstep: 352.58 | bwd_inner_microstep: 271.97 | bwd_allreduce_microstep: 80.55 | step_microstep: 24.03 +[2025-05-02 01:57:03,528] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2776.42 | bwd: 4084.63 | bwd_inner: 4003.38 | bwd_allreduce: 80.76 | step: 25.15 + 16%|█▋ | 1438/8720 [3:41:37<14:40:36, 7.26s/it] {'loss': 0.7363, 'grad_norm': 10.138383865356445, 'learning_rate': 9.53053552910436e-06, 'epoch': 1.65} + 16%|█▋ | 1438/8720 [3:41:37<14:40:36, 7.26s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1939 +[2025-05-02 01:57:04,035] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 196.08 | bwd_microstep: 287.90 | bwd_inner_microstep: 287.89 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2168 +[2025-05-02 01:57:04,576] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 205.02 | bwd_microstep: 317.22 | bwd_inner_microstep: 317.21 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.14 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1905 +[2025-05-02 01:57:05,063] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.99 | bwd_microstep: 276.32 | bwd_inner_microstep: 276.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1894 +[2025-05-02 01:57:05,550] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.00 | bwd_microstep: 275.20 | bwd_inner_microstep: 275.18 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 01:57:06,032] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.49 | bwd_microstep: 273.06 | bwd_inner_microstep: 273.05 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 01:57:06,512] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.55 | bwd_microstep: 272.91 | bwd_inner_microstep: 272.89 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1370 +[2025-05-02 01:57:06,878] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.41 | bwd_microstep: 207.57 | bwd_inner_microstep: 207.41 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 01:57:07,359] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.68 | bwd_microstep: 273.92 | bwd_inner_microstep: 273.91 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 01:57:07,838] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.32 | bwd_microstep: 273.09 | bwd_inner_microstep: 273.07 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 01:57:08,318] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.44 | bwd_microstep: 272.69 | bwd_inner_microstep: 272.67 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:57:08,799] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.58 | bwd_microstep: 273.43 | bwd_inner_microstep: 273.41 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:57:09,278] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.58 | bwd_microstep: 272.22 | bwd_inner_microstep: 272.21 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:57:09,757] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.98 | bwd_microstep: 271.93 | bwd_inner_microstep: 271.92 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:57:10,235] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.19 | bwd_microstep: 272.42 | bwd_inner_microstep: 272.40 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:57:10,711] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.61 | bwd_microstep: 270.98 | bwd_inner_microstep: 270.96 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 01:57:11,279] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.14 | optimizer_step: 16.41 +[2025-05-02 01:57:11,280] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.18 | bwd_microstep: 342.16 | bwd_inner_microstep: 272.36 | bwd_allreduce_microstep: 69.76 | step_microstep: 23.38 +[2025-05-02 01:57:11,281] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2993.70 | bwd: 4433.08 | bwd_inner: 4362.85 | bwd_allreduce: 69.94 | step: 24.80 + 17%|█▋ | 1439/8720 [3:41:45<14:58:31, 7.40s/it] {'loss': 0.7971, 'grad_norm': 7.932753086090088, 'learning_rate': 9.5297495429092e-06, 'epoch': 1.65} + 17%|█▋ | 1439/8720 [3:41:45<14:58:31, 7.40s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 400 +[2025-05-02 01:57:11,483] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 68.63 | bwd_microstep: 116.14 | bwd_inner_microstep: 115.81 | bwd_allreduce_microstep: 0.14 | step_microstep: 0.09 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 437 +[2025-05-02 01:57:11,681] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 71.14 | bwd_microstep: 113.14 | bwd_inner_microstep: 112.83 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1983 +[2025-05-02 01:57:12,185] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 196.58 | bwd_microstep: 292.55 | bwd_inner_microstep: 292.53 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1918 +[2025-05-02 01:57:12,670] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 192.62 | bwd_microstep: 276.78 | bwd_inner_microstep: 276.76 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1915 +[2025-05-02 01:57:13,152] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.43 | bwd_microstep: 276.73 | bwd_inner_microstep: 276.72 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 01:57:13,629] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.42 | bwd_microstep: 273.33 | bwd_inner_microstep: 273.31 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 01:57:14,107] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.00 | bwd_microstep: 272.84 | bwd_inner_microstep: 272.82 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 01:57:14,585] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.22 | bwd_microstep: 273.58 | bwd_inner_microstep: 273.56 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-02 01:57:15,064] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.81 | bwd_microstep: 274.31 | bwd_inner_microstep: 274.29 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.16 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 01:57:15,543] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.67 | bwd_microstep: 273.26 | bwd_inner_microstep: 273.24 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 322 +[2025-05-02 01:57:15,745] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 68.59 | bwd_microstep: 120.56 | bwd_inner_microstep: 120.38 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:57:16,221] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.73 | bwd_microstep: 272.92 | bwd_inner_microstep: 272.90 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:57:16,696] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.56 | bwd_microstep: 271.25 | bwd_inner_microstep: 271.24 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.17 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 01:57:17,171] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.55 | bwd_microstep: 270.85 | bwd_inner_microstep: 270.83 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:57:17,646] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.19 | bwd_microstep: 271.49 | bwd_inner_microstep: 271.48 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 827 +[2025-05-02 01:57:17,973] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.04 | optimizer_gradients: 3.04 | optimizer_step: 16.40 +[2025-05-02 01:57:17,974] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.24 | bwd_microstep: 196.46 | bwd_inner_microstep: 130.24 | bwd_allreduce_microstep: 66.13 | step_microstep: 24.24 +[2025-05-02 01:57:17,975] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2579.10 | bwd: 3846.26 | bwd_inner: 3779.15 | bwd_allreduce: 66.49 | step: 25.43 + 17%|█▋ | 1440/8720 [3:41:51<14:32:32, 7.19s/it] {'loss': 0.9874, 'grad_norm': 6.609742641448975, 'learning_rate': 9.528962931773687e-06, 'epoch': 1.65} + 17%|█▋ | 1440/8720 [3:41:51<14:32:32, 7.19s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1849 +[2025-05-02 01:57:18,452] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.89 | bwd_microstep: 270.12 | bwd_inner_microstep: 270.11 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2136 +[2025-05-02 01:57:18,986] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 204.10 | bwd_microstep: 314.19 | bwd_inner_microstep: 314.17 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1923 +[2025-05-02 01:57:19,487] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 198.06 | bwd_microstep: 287.22 | bwd_inner_microstep: 287.21 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1904 +[2025-05-02 01:57:19,968] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.72 | bwd_microstep: 275.88 | bwd_inner_microstep: 275.86 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-02 01:57:20,446] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.42 | bwd_microstep: 274.01 | bwd_inner_microstep: 273.99 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-02 01:57:20,925] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.19 | bwd_microstep: 273.87 | bwd_inner_microstep: 273.85 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1890 +[2025-05-02 01:57:21,405] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.68 | bwd_microstep: 274.74 | bwd_inner_microstep: 274.73 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 845 +[2025-05-02 01:57:21,648] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.59 | bwd_microstep: 132.67 | bwd_inner_microstep: 132.51 | bwd_allreduce_microstep: 0.09 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 01:57:22,125] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.48 | bwd_microstep: 272.56 | bwd_inner_microstep: 272.54 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 01:57:22,603] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.84 | bwd_microstep: 273.42 | bwd_inner_microstep: 273.40 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-02 01:57:23,082] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.59 | bwd_microstep: 273.41 | bwd_inner_microstep: 273.39 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.17 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 843 +[2025-05-02 01:57:23,325] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.88 | bwd_microstep: 132.62 | bwd_inner_microstep: 132.45 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.10 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 331 +[2025-05-02 01:57:23,544] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 83.85 | bwd_microstep: 120.05 | bwd_inner_microstep: 119.79 | bwd_allreduce_microstep: 0.09 | step_microstep: 0.10 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1094 +[2025-05-02 01:57:23,837] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 114.88 | bwd_microstep: 160.99 | bwd_inner_microstep: 160.90 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:57:24,316] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.10 | bwd_microstep: 272.37 | bwd_inner_microstep: 272.35 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.15 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 01:57:24,899] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.21 | optimizer_step: 16.61 +[2025-05-02 01:57:24,900] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.51 | bwd_microstep: 350.65 | bwd_inner_microstep: 272.76 | bwd_allreduce_microstep: 77.83 | step_microstep: 24.68 +[2025-05-02 01:57:24,901] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2679.50 | bwd: 3958.85 | bwd_inner: 3880.10 | bwd_allreduce: 78.16 | step: 25.84 + 17%|█▋ | 1441/8720 [3:41:58<14:22:51, 7.11s/it] {'loss': 0.8647, 'grad_norm': 13.84591007232666, 'learning_rate': 9.528175695806342e-06, 'epoch': 1.65} + 17%|█▋ | 1441/8720 [3:41:58<14:22:51, 7.11s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:57:25,384] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.25 | bwd_microstep: 271.46 | bwd_inner_microstep: 271.45 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1939 +[2025-05-02 01:57:25,887] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 196.13 | bwd_microstep: 288.34 | bwd_inner_microstep: 288.32 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1906 +[2025-05-02 01:57:26,374] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.33 | bwd_microstep: 276.58 | bwd_inner_microstep: 276.56 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-02 01:57:26,857] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.97 | bwd_microstep: 274.27 | bwd_inner_microstep: 274.26 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 01:57:27,341] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.62 | bwd_microstep: 273.64 | bwd_inner_microstep: 273.62 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 01:57:27,822] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.91 | bwd_microstep: 272.93 | bwd_inner_microstep: 272.91 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 01:57:28,305] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.97 | bwd_microstep: 273.18 | bwd_inner_microstep: 273.16 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 01:57:28,786] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.32 | bwd_microstep: 272.95 | bwd_inner_microstep: 272.93 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 01:57:29,265] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.44 | bwd_microstep: 272.97 | bwd_inner_microstep: 272.96 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:57:29,745] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.26 | bwd_microstep: 272.73 | bwd_inner_microstep: 272.71 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 01:57:30,223] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.51 | bwd_microstep: 271.97 | bwd_inner_microstep: 271.95 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:57:30,701] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.86 | bwd_microstep: 271.17 | bwd_inner_microstep: 271.15 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:57:31,180] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.28 | bwd_microstep: 271.34 | bwd_inner_microstep: 271.32 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 01:57:31,661] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.29 | bwd_microstep: 270.95 | bwd_inner_microstep: 270.93 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 01:57:32,141] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.92 | bwd_microstep: 271.00 | bwd_inner_microstep: 270.98 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 01:57:32,718] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.17 | optimizer_step: 16.43 +[2025-05-02 01:57:32,719] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.09 | bwd_microstep: 348.58 | bwd_inner_microstep: 271.63 | bwd_allreduce_microstep: 76.90 | step_microstep: 24.20 +[2025-05-02 01:57:32,720] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 3023.75 | bwd: 4454.07 | bwd_inner: 4376.84 | bwd_allreduce: 76.99 | step: 25.17 + 17%|█▋ | 1442/8720 [3:42:06<14:48:27, 7.32s/it] {'loss': 0.8928, 'grad_norm': 14.405303955078125, 'learning_rate': 9.52738783511578e-06, 'epoch': 1.65} + 17%|█▋ | 1442/8720 [3:42:06<14:48:27, 7.32s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 01:57:33,203] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.23 | bwd_microstep: 271.77 | bwd_inner_microstep: 271.75 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1904 +[2025-05-02 01:57:33,687] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.80 | bwd_microstep: 275.69 | bwd_inner_microstep: 275.68 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 01:57:34,164] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.39 | bwd_microstep: 273.61 | bwd_inner_microstep: 273.59 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-02 01:57:34,643] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.06 | bwd_microstep: 273.73 | bwd_inner_microstep: 273.71 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 01:57:35,123] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.13 | bwd_microstep: 273.13 | bwd_inner_microstep: 273.11 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 01:57:35,605] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.95 | bwd_microstep: 273.30 | bwd_inner_microstep: 273.28 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 01:57:36,084] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.07 | bwd_microstep: 272.84 | bwd_inner_microstep: 272.82 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-02 01:57:36,565] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.51 | bwd_microstep: 273.02 | bwd_inner_microstep: 273.00 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 01:57:37,046] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.67 | bwd_microstep: 272.86 | bwd_inner_microstep: 272.85 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 01:57:37,525] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.18 | bwd_microstep: 272.55 | bwd_inner_microstep: 272.54 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:57:38,006] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.07 | bwd_microstep: 272.77 | bwd_inner_microstep: 272.75 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.16 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:57:38,484] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.79 | bwd_microstep: 270.96 | bwd_inner_microstep: 270.95 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 01:57:38,963] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.71 | bwd_microstep: 271.01 | bwd_inner_microstep: 270.99 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:57:39,443] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.78 | bwd_microstep: 270.91 | bwd_inner_microstep: 270.89 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 01:57:39,921] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.36 | bwd_microstep: 270.84 | bwd_inner_microstep: 270.82 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 01:57:40,500] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.18 | optimizer_step: 16.58 +[2025-05-02 01:57:40,501] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.32 | bwd_microstep: 349.05 | bwd_inner_microstep: 271.49 | bwd_allreduce_microstep: 77.50 | step_microstep: 24.56 +[2025-05-02 01:57:40,502] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 3013.64 | bwd: 4438.07 | bwd_inner: 4360.23 | bwd_allreduce: 77.58 | step: 25.45 + 17%|█▋ | 1443/8720 [3:42:14<15:04:58, 7.46s/it] {'loss': 0.4834, 'grad_norm': 5.568490028381348, 'learning_rate': 9.526599349810694e-06, 'epoch': 1.65} + 17%|█▋ | 1443/8720 [3:42:14<15:04:58, 7.46s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 01:57:40,984] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.74 | bwd_microstep: 270.46 | bwd_inner_microstep: 270.44 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2114 +[2025-05-02 01:57:41,518] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 203.51 | bwd_microstep: 312.96 | bwd_inner_microstep: 312.94 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-02 01:57:41,999] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.47 | bwd_microstep: 274.90 | bwd_inner_microstep: 274.88 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 01:57:42,479] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.52 | bwd_microstep: 273.53 | bwd_inner_microstep: 273.51 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:57:42,959] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.19 | bwd_microstep: 272.66 | bwd_inner_microstep: 272.64 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 01:57:43,442] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.32 | bwd_microstep: 272.66 | bwd_inner_microstep: 272.64 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.15 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 01:57:43,924] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.17 | bwd_microstep: 273.07 | bwd_inner_microstep: 273.05 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 839 +[2025-05-02 01:57:44,166] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 96.44 | bwd_microstep: 126.41 | bwd_inner_microstep: 126.26 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 01:57:44,645] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.72 | bwd_microstep: 273.06 | bwd_inner_microstep: 273.04 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 01:57:45,124] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.39 | bwd_microstep: 272.79 | bwd_inner_microstep: 272.78 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 01:57:45,605] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.11 | bwd_microstep: 273.36 | bwd_inner_microstep: 273.35 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:57:46,087] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.32 | bwd_microstep: 272.43 | bwd_inner_microstep: 272.41 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:57:46,571] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.92 | bwd_microstep: 272.70 | bwd_inner_microstep: 272.68 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 01:57:47,054] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.47 | bwd_microstep: 272.40 | bwd_inner_microstep: 272.39 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 01:57:47,534] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.67 | bwd_microstep: 271.07 | bwd_inner_microstep: 271.05 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 01:57:48,125] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.29 | optimizer_step: 16.84 +[2025-05-02 01:57:48,126] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.87 | bwd_microstep: 358.35 | bwd_inner_microstep: 271.60 | bwd_allreduce_microstep: 86.71 | step_microstep: 24.85 +[2025-05-02 01:57:48,127] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2941.41 | bwd: 4342.85 | bwd_inner: 4255.69 | bwd_allreduce: 86.85 | step: 25.85 + 17%|█▋ | 1444/8720 [3:42:21<15:10:47, 7.51s/it] {'loss': 0.8608, 'grad_norm': 19.779956817626953, 'learning_rate': 9.525810239999864e-06, 'epoch': 1.66} + 17%|█▋ | 1444/8720 [3:42:21<15:10:47, 7.51s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1891 +[2025-05-02 01:57:48,615] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.18 | bwd_microstep: 274.71 | bwd_inner_microstep: 274.69 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2101 +[2025-05-02 01:57:49,143] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 202.86 | bwd_microstep: 306.27 | bwd_inner_microstep: 306.26 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1914 +[2025-05-02 01:57:49,627] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.67 | bwd_microstep: 276.80 | bwd_inner_microstep: 276.79 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1896 +[2025-05-02 01:57:50,112] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.65 | bwd_microstep: 275.84 | bwd_inner_microstep: 275.82 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-02 01:57:50,597] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.75 | bwd_microstep: 274.44 | bwd_inner_microstep: 274.42 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1890 +[2025-05-02 01:57:51,083] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.32 | bwd_microstep: 275.22 | bwd_inner_microstep: 275.20 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-02 01:57:51,564] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.43 | bwd_microstep: 273.62 | bwd_inner_microstep: 273.60 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 01:57:52,045] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.57 | bwd_microstep: 273.92 | bwd_inner_microstep: 273.90 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-02 01:57:52,525] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.58 | bwd_microstep: 273.84 | bwd_inner_microstep: 273.82 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 01:57:53,005] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.65 | bwd_microstep: 273.85 | bwd_inner_microstep: 273.83 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 840 +[2025-05-02 01:57:53,248] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 97.34 | bwd_microstep: 126.46 | bwd_inner_microstep: 126.36 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 01:57:53,728] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.31 | bwd_microstep: 273.28 | bwd_inner_microstep: 273.26 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:57:54,203] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.92 | bwd_microstep: 271.85 | bwd_inner_microstep: 271.83 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 01:57:54,677] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.61 | bwd_microstep: 271.17 | bwd_inner_microstep: 271.16 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 01:57:55,153] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.93 | bwd_microstep: 271.02 | bwd_inner_microstep: 271.00 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:57:55,732] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.14 | optimizer_step: 16.43 +[2025-05-02 01:57:55,732] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.38 | bwd_microstep: 348.63 | bwd_inner_microstep: 272.50 | bwd_allreduce_microstep: 76.08 | step_microstep: 24.26 +[2025-05-02 01:57:55,734] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2942.74 | bwd: 4340.95 | bwd_inner: 4264.46 | bwd_allreduce: 76.22 | step: 25.19 + 17%|█▋ | 1445/8720 [3:42:29<15:14:08, 7.54s/it] {'loss': 0.6911, 'grad_norm': 7.343807220458984, 'learning_rate': 9.525020505792164e-06, 'epoch': 1.66} + 17%|█▋ | 1445/8720 [3:42:29<15:14:08, 7.54s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:57:56,215] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.53 | bwd_microstep: 270.47 | bwd_inner_microstep: 270.45 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1954 +[2025-05-02 01:57:56,717] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 196.31 | bwd_microstep: 289.82 | bwd_inner_microstep: 289.80 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1912 +[2025-05-02 01:57:57,205] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.38 | bwd_microstep: 277.01 | bwd_inner_microstep: 276.99 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1921 +[2025-05-02 01:57:57,702] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 194.49 | bwd_microstep: 287.12 | bwd_inner_microstep: 287.11 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 358 +[2025-05-02 01:57:57,918] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 79.55 | bwd_microstep: 122.69 | bwd_inner_microstep: 122.37 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-02 01:57:58,396] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.86 | bwd_microstep: 274.76 | bwd_inner_microstep: 274.74 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1886 +[2025-05-02 01:57:58,876] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.49 | bwd_microstep: 275.36 | bwd_inner_microstep: 275.35 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 01:57:59,354] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.89 | bwd_microstep: 273.96 | bwd_inner_microstep: 273.94 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 333 +[2025-05-02 01:57:59,553] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 67.36 | bwd_microstep: 119.12 | bwd_inner_microstep: 118.97 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:58:00,030] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.67 | bwd_microstep: 273.21 | bwd_inner_microstep: 273.19 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 324 +[2025-05-02 01:58:00,236] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 73.83 | bwd_microstep: 118.56 | bwd_inner_microstep: 118.36 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 01:58:00,712] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.74 | bwd_microstep: 272.99 | bwd_inner_microstep: 272.97 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 01:58:01,189] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.25 | bwd_microstep: 272.77 | bwd_inner_microstep: 272.76 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:58:01,665] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.57 | bwd_microstep: 272.62 | bwd_inner_microstep: 272.61 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:58:02,141] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.17 | bwd_microstep: 272.28 | bwd_inner_microstep: 272.26 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:58:02,705] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.14 | optimizer_step: 16.39 +[2025-05-02 01:58:02,705] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.76 | bwd_microstep: 338.83 | bwd_inner_microstep: 272.58 | bwd_allreduce_microstep: 66.21 | step_microstep: 23.41 +[2025-05-02 01:58:02,707] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2687.56 | bwd: 4011.66 | bwd_inner: 3944.63 | bwd_allreduce: 66.50 | step: 24.23 + 17%|█▋ | 1446/8720 [3:42:36<14:53:21, 7.37s/it] {'loss': 0.8476, 'grad_norm': 12.401479721069336, 'learning_rate': 9.524230147296544e-06, 'epoch': 1.66} + 17%|█▋ | 1446/8720 [3:42:36<14:53:21, 7.37s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 323 +[2025-05-02 01:58:02,911] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 67.76 | bwd_microstep: 118.70 | bwd_inner_microstep: 118.57 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1905 +[2025-05-02 01:58:03,393] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.85 | bwd_microstep: 276.72 | bwd_inner_microstep: 276.71 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 01:58:03,872] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.58 | bwd_microstep: 274.12 | bwd_inner_microstep: 274.10 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 01:58:04,350] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.31 | bwd_microstep: 273.19 | bwd_inner_microstep: 273.17 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 01:58:04,829] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.66 | bwd_microstep: 274.08 | bwd_inner_microstep: 274.06 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 01:58:05,310] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.06 | bwd_microstep: 272.72 | bwd_inner_microstep: 272.70 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:58:05,792] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.18 | bwd_microstep: 273.40 | bwd_inner_microstep: 273.38 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 01:58:06,272] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.44 | bwd_microstep: 273.11 | bwd_inner_microstep: 273.09 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 842 +[2025-05-02 01:58:06,517] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.40 | bwd_microstep: 132.13 | bwd_inner_microstep: 132.11 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 01:58:06,996] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.00 | bwd_microstep: 273.43 | bwd_inner_microstep: 273.42 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 839 +[2025-05-02 01:58:07,232] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.84 | bwd_microstep: 126.28 | bwd_inner_microstep: 126.11 | bwd_allreduce_microstep: 0.09 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:58:07,712] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.09 | bwd_microstep: 273.15 | bwd_inner_microstep: 273.14 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:58:08,191] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.77 | bwd_microstep: 273.13 | bwd_inner_microstep: 273.11 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:58:08,669] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.88 | bwd_microstep: 272.54 | bwd_inner_microstep: 272.52 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:58:09,146] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.78 | bwd_microstep: 273.17 | bwd_inner_microstep: 273.15 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.14 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 828 +[2025-05-02 01:58:09,474] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.04 | optimizer_gradients: 2.13 | optimizer_step: 16.41 +[2025-05-02 01:58:09,475] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.19 | bwd_microstep: 196.64 | bwd_inner_microstep: 130.83 | bwd_allreduce_microstep: 65.73 | step_microstep: 23.28 +[2025-05-02 01:58:09,476] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2620.48 | bwd: 3856.55 | bwd_inner: 3790.22 | bwd_allreduce: 65.90 | step: 24.38 + 17%|█▋ | 1447/8720 [3:42:43<14:31:25, 7.19s/it] {'loss': 0.3519, 'grad_norm': 6.401617527008057, 'learning_rate': 9.523439164622045e-06, 'epoch': 1.66} + 17%|█▋ | 1447/8720 [3:42:43<14:31:25, 7.19s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1849 +[2025-05-02 01:58:09,953] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.47 | bwd_microstep: 270.08 | bwd_inner_microstep: 270.06 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1929 +[2025-05-02 01:58:10,452] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.76 | bwd_microstep: 287.87 | bwd_inner_microstep: 287.85 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 843 +[2025-05-02 01:58:10,694] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.29 | bwd_microstep: 132.50 | bwd_inner_microstep: 132.35 | bwd_allreduce_microstep: 0.08 | step_microstep: 0.13 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-02 01:58:11,172] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.52 | bwd_microstep: 274.95 | bwd_inner_microstep: 274.93 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1349 +[2025-05-02 01:58:11,535] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.39 | bwd_microstep: 205.88 | bwd_inner_microstep: 205.86 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 839 +[2025-05-02 01:58:11,766] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 90.91 | bwd_microstep: 126.56 | bwd_inner_microstep: 126.48 | bwd_allreduce_microstep: 0.04 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:58:12,242] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.42 | bwd_microstep: 272.68 | bwd_inner_microstep: 272.67 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 844 +[2025-05-02 01:58:12,484] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 96.09 | bwd_microstep: 132.60 | bwd_inner_microstep: 132.59 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 01:58:12,961] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.38 | bwd_microstep: 273.58 | bwd_inner_microstep: 273.57 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:58:13,437] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.19 | bwd_microstep: 272.96 | bwd_inner_microstep: 272.94 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 01:58:13,912] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.67 | bwd_microstep: 272.73 | bwd_inner_microstep: 272.71 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 01:58:14,388] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.65 | bwd_microstep: 271.56 | bwd_inner_microstep: 271.54 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 320 +[2025-05-02 01:58:14,599] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 76.12 | bwd_microstep: 120.83 | bwd_inner_microstep: 120.51 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:58:15,077] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.95 | bwd_microstep: 272.23 | bwd_inner_microstep: 272.22 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 01:58:15,553] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.66 | bwd_microstep: 270.80 | bwd_inner_microstep: 270.78 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1952 +[2025-05-02 01:58:16,146] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.12 | optimizer_step: 16.40 +[2025-05-02 01:58:16,147] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 196.31 | bwd_microstep: 356.92 | bwd_inner_microstep: 290.08 | bwd_allreduce_microstep: 66.80 | step_microstep: 23.37 +[2025-05-02 01:58:16,148] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2583.50 | bwd: 3814.84 | bwd_inner: 3747.21 | bwd_allreduce: 67.12 | step: 24.43 + 17%|█▋ | 1448/8720 [3:42:49<14:12:30, 7.03s/it] {'loss': 0.6235, 'grad_norm': 15.32612133026123, 'learning_rate': 9.522647557877798e-06, 'epoch': 1.66} + 17%|█▋ | 1448/8720 [3:42:49<14:12:30, 7.03s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 362 +[2025-05-02 01:58:16,363] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 68.29 | bwd_microstep: 128.96 | bwd_inner_microstep: 128.69 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1958 +[2025-05-02 01:58:16,866] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 197.73 | bwd_microstep: 290.31 | bwd_inner_microstep: 290.29 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1903 +[2025-05-02 01:58:17,349] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.51 | bwd_microstep: 276.59 | bwd_inner_microstep: 276.57 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-02 01:58:17,828] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.66 | bwd_microstep: 273.81 | bwd_inner_microstep: 273.79 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.13 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-02 01:58:18,309] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.70 | bwd_microstep: 274.88 | bwd_inner_microstep: 274.86 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1890 +[2025-05-02 01:58:18,790] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.79 | bwd_microstep: 275.48 | bwd_inner_microstep: 275.46 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-02 01:58:19,270] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.64 | bwd_microstep: 274.43 | bwd_inner_microstep: 274.42 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 01:58:19,749] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.16 | bwd_microstep: 273.67 | bwd_inner_microstep: 273.65 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 6, images per sample: 6.0, dynamic token length: 1618 +[2025-05-02 01:58:20,177] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 166.27 | bwd_microstep: 246.06 | bwd_inner_microstep: 246.04 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1353 +[2025-05-02 01:58:20,537] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.13 | bwd_microstep: 206.04 | bwd_inner_microstep: 206.02 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-02 01:58:21,014] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.85 | bwd_microstep: 273.53 | bwd_inner_microstep: 273.52 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1349 +[2025-05-02 01:58:21,376] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.49 | bwd_microstep: 205.97 | bwd_inner_microstep: 205.95 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:58:21,849] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.33 | bwd_microstep: 271.22 | bwd_inner_microstep: 271.20 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 01:58:22,326] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.22 | bwd_microstep: 272.02 | bwd_inner_microstep: 272.00 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:58:22,802] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.76 | bwd_microstep: 272.01 | bwd_inner_microstep: 271.99 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:58:23,369] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.04 | optimizer_gradients: 2.15 | optimizer_step: 16.43 +[2025-05-02 01:58:23,369] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.51 | bwd_microstep: 339.06 | bwd_inner_microstep: 272.87 | bwd_allreduce_microstep: 66.14 | step_microstep: 23.45 +[2025-05-02 01:58:23,370] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2791.74 | bwd: 4154.04 | bwd_inner: 4087.38 | bwd_allreduce: 66.32 | step: 24.46 + 17%|█▋ | 1449/8720 [3:42:57<14:19:14, 7.09s/it] {'loss': 0.9774, 'grad_norm': 7.948238849639893, 'learning_rate': 9.52185532717301e-06, 'epoch': 1.66} + 17%|█▋ | 1449/8720 [3:42:57<14:19:14, 7.09s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:58:23,849] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.60 | bwd_microstep: 271.10 | bwd_inner_microstep: 271.08 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 912 +[2025-05-02 01:58:24,111] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 103.78 | bwd_microstep: 144.94 | bwd_inner_microstep: 144.69 | bwd_allreduce_microstep: 0.14 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1908 +[2025-05-02 01:58:24,592] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.65 | bwd_microstep: 276.28 | bwd_inner_microstep: 276.26 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1888 +[2025-05-02 01:58:25,072] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.26 | bwd_microstep: 274.99 | bwd_inner_microstep: 274.97 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-02 01:58:25,550] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.07 | bwd_microstep: 273.57 | bwd_inner_microstep: 273.55 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-02 01:58:26,028] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.68 | bwd_microstep: 273.89 | bwd_inner_microstep: 273.87 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1361 +[2025-05-02 01:58:26,391] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.64 | bwd_microstep: 206.69 | bwd_inner_microstep: 206.67 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 01:58:26,868] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.21 | bwd_microstep: 273.70 | bwd_inner_microstep: 273.68 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:58:27,347] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.04 | bwd_microstep: 272.80 | bwd_inner_microstep: 272.79 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 01:58:27,825] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.79 | bwd_microstep: 273.04 | bwd_inner_microstep: 273.02 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:58:28,301] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.64 | bwd_microstep: 271.69 | bwd_inner_microstep: 271.67 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 01:58:28,777] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.27 | bwd_microstep: 272.93 | bwd_inner_microstep: 272.91 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 01:58:29,251] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.71 | bwd_microstep: 271.06 | bwd_inner_microstep: 271.04 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 01:58:29,725] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.90 | bwd_microstep: 271.31 | bwd_inner_microstep: 271.29 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 828 +[2025-05-02 01:58:29,962] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.24 | bwd_microstep: 129.83 | bwd_inner_microstep: 129.81 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 01:58:30,526] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.04 | optimizer_gradients: 2.14 | optimizer_step: 16.40 +[2025-05-02 01:58:30,527] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.10 | bwd_microstep: 338.28 | bwd_inner_microstep: 271.91 | bwd_allreduce_microstep: 66.32 | step_microstep: 23.27 +[2025-05-02 01:58:30,528] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2789.30 | bwd: 4096.10 | bwd_inner: 4029.26 | bwd_allreduce: 66.50 | step: 24.07 + 17%|█▋ | 1450/8720 [3:43:04<14:21:33, 7.11s/it] {'loss': 0.7192, 'grad_norm': 8.534299850463867, 'learning_rate': 9.521062472616983e-06, 'epoch': 1.66} + 17%|█▋ | 1450/8720 [3:43:04<14:21:33, 7.11s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 01:58:31,005] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.79 | bwd_microstep: 270.43 | bwd_inner_microstep: 270.41 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1917 +[2025-05-02 01:58:31,488] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.37 | bwd_microstep: 277.24 | bwd_inner_microstep: 277.22 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1896 +[2025-05-02 01:58:31,968] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.63 | bwd_microstep: 275.68 | bwd_inner_microstep: 275.66 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1914 +[2025-05-02 01:58:32,450] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.66 | bwd_microstep: 276.32 | bwd_inner_microstep: 276.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1362 +[2025-05-02 01:58:32,812] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.20 | bwd_microstep: 206.65 | bwd_inner_microstep: 206.59 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1887 +[2025-05-02 01:58:33,292] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.71 | bwd_microstep: 274.52 | bwd_inner_microstep: 274.50 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 339 +[2025-05-02 01:58:33,516] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 90.62 | bwd_microstep: 119.60 | bwd_inner_microstep: 119.45 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 01:58:33,994] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.34 | bwd_microstep: 273.36 | bwd_inner_microstep: 273.34 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 842 +[2025-05-02 01:58:34,239] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.53 | bwd_microstep: 131.89 | bwd_inner_microstep: 131.80 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:58:34,718] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.36 | bwd_microstep: 272.55 | bwd_inner_microstep: 272.53 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 321 +[2025-05-02 01:58:34,936] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 86.29 | bwd_microstep: 116.34 | bwd_inner_microstep: 116.20 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 01:58:35,414] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.13 | bwd_microstep: 272.20 | bwd_inner_microstep: 272.18 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:58:35,891] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.02 | bwd_microstep: 272.30 | bwd_inner_microstep: 272.28 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 01:58:36,371] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.96 | bwd_microstep: 272.49 | bwd_inner_microstep: 272.47 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:58:36,850] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.64 | bwd_microstep: 272.83 | bwd_inner_microstep: 272.81 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 830 +[2025-05-02 01:58:37,192] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.14 | optimizer_step: 16.43 +[2025-05-02 01:58:37,192] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.04 | bwd_microstep: 207.43 | bwd_inner_microstep: 130.84 | bwd_allreduce_microstep: 76.45 | step_microstep: 24.06 +[2025-05-02 01:58:37,194] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2583.00 | bwd: 3791.90 | bwd_inner: 3714.72 | bwd_allreduce: 76.72 | step: 25.07 + 17%|█▋ | 1451/8720 [3:43:10<14:05:21, 6.98s/it] {'loss': 0.5444, 'grad_norm': 5.2039103507995605, 'learning_rate': 9.520268994319104e-06, 'epoch': 1.66} + 17%|█▋ | 1451/8720 [3:43:10<14:05:21, 6.98s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 01:58:37,675] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.43 | bwd_microstep: 270.36 | bwd_inner_microstep: 270.34 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.14 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1910 +[2025-05-02 01:58:38,161] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.85 | bwd_microstep: 276.90 | bwd_inner_microstep: 276.89 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 860 +[2025-05-02 01:58:38,413] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 97.55 | bwd_microstep: 133.99 | bwd_inner_microstep: 133.73 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 864 +[2025-05-02 01:58:38,659] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 96.01 | bwd_microstep: 133.78 | bwd_inner_microstep: 133.52 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-02 01:58:39,140] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.16 | bwd_microstep: 273.83 | bwd_inner_microstep: 273.81 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 01:58:39,623] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.24 | bwd_microstep: 273.04 | bwd_inner_microstep: 273.02 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:58:40,105] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.71 | bwd_microstep: 272.57 | bwd_inner_microstep: 272.56 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1096 +[2025-05-02 01:58:40,401] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 115.46 | bwd_microstep: 161.14 | bwd_inner_microstep: 161.06 | bwd_allreduce_microstep: 0.04 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:58:40,878] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.49 | bwd_microstep: 271.52 | bwd_inner_microstep: 271.50 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:58:41,361] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.47 | bwd_microstep: 272.88 | bwd_inner_microstep: 272.86 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 01:58:41,841] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.14 | bwd_microstep: 273.25 | bwd_inner_microstep: 273.23 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:58:42,320] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.11 | bwd_microstep: 272.69 | bwd_inner_microstep: 272.67 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 324 +[2025-05-02 01:58:42,543] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 89.47 | bwd_microstep: 117.82 | bwd_inner_microstep: 117.65 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:58:43,022] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.71 | bwd_microstep: 273.19 | bwd_inner_microstep: 273.17 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.13 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:58:43,501] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.86 | bwd_microstep: 272.39 | bwd_inner_microstep: 272.37 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 01:58:44,081] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.21 | optimizer_step: 16.58 +[2025-05-02 01:58:44,081] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.10 | bwd_microstep: 347.79 | bwd_inner_microstep: 271.60 | bwd_allreduce_microstep: 76.14 | step_microstep: 24.67 +[2025-05-02 01:58:44,082] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2664.38 | bwd: 3897.23 | bwd_inner: 3820.04 | bwd_allreduce: 76.55 | step: 26.06 + 17%|█▋ | 1452/8720 [3:43:17<14:02:00, 6.95s/it] {'loss': 0.8468, 'grad_norm': 15.877923011779785, 'learning_rate': 9.519474892388839e-06, 'epoch': 1.67} + 17%|█▋ | 1452/8720 [3:43:17<14:02:00, 6.95s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 01:58:44,564] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.48 | bwd_microstep: 270.19 | bwd_inner_microstep: 270.17 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.16 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1930 +[2025-05-02 01:58:45,066] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.68 | bwd_microstep: 287.61 | bwd_inner_microstep: 287.59 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1919 +[2025-05-02 01:58:45,553] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.65 | bwd_microstep: 276.55 | bwd_inner_microstep: 276.53 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 01:58:46,036] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.14 | bwd_microstep: 273.44 | bwd_inner_microstep: 273.43 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1890 +[2025-05-02 01:58:46,521] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.51 | bwd_microstep: 275.26 | bwd_inner_microstep: 275.24 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 333 +[2025-05-02 01:58:46,755] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.60 | bwd_microstep: 121.30 | bwd_inner_microstep: 120.97 | bwd_allreduce_microstep: 0.14 | step_microstep: 0.11 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 339 +[2025-05-02 01:58:47,023] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 97.49 | bwd_microstep: 148.44 | bwd_inner_microstep: 148.28 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 01:58:47,504] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.30 | bwd_microstep: 272.58 | bwd_inner_microstep: 272.56 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 01:58:47,983] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.92 | bwd_microstep: 272.77 | bwd_inner_microstep: 272.75 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 01:58:48,464] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.00 | bwd_microstep: 273.25 | bwd_inner_microstep: 273.23 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.16 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:58:48,942] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.59 | bwd_microstep: 271.98 | bwd_inner_microstep: 271.96 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:58:49,423] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.37 | bwd_microstep: 272.67 | bwd_inner_microstep: 272.65 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:58:49,902] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.80 | bwd_microstep: 272.30 | bwd_inner_microstep: 272.28 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 01:58:50,381] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.72 | bwd_microstep: 271.10 | bwd_inner_microstep: 271.09 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 01:58:50,858] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.10 | bwd_microstep: 271.50 | bwd_inner_microstep: 271.48 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:58:51,438] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.21 | optimizer_step: 16.60 +[2025-05-02 01:58:51,439] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.26 | bwd_microstep: 348.43 | bwd_inner_microstep: 271.74 | bwd_allreduce_microstep: 76.64 | step_microstep: 24.61 +[2025-05-02 01:58:51,440] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2839.20 | bwd: 4179.41 | bwd_inner: 4102.05 | bwd_allreduce: 76.91 | step: 25.79 + 17%|█▋ | 1453/8720 [3:43:25<14:16:39, 7.07s/it] {'loss': 0.8803, 'grad_norm': 13.596282005310059, 'learning_rate': 9.51868016693575e-06, 'epoch': 1.67} + 17%|█▋ | 1453/8720 [3:43:25<14:16:39, 7.07s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 01:58:51,922] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.63 | bwd_microstep: 271.03 | bwd_inner_microstep: 271.01 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1929 +[2025-05-02 01:58:52,421] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 196.10 | bwd_microstep: 287.57 | bwd_inner_microstep: 287.55 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1883 +[2025-05-02 01:58:52,901] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.43 | bwd_microstep: 274.51 | bwd_inner_microstep: 274.50 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-02 01:58:53,379] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.00 | bwd_microstep: 273.61 | bwd_inner_microstep: 273.59 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1366 +[2025-05-02 01:58:53,743] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.75 | bwd_microstep: 207.13 | bwd_inner_microstep: 207.02 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-02 01:58:54,222] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.86 | bwd_microstep: 274.24 | bwd_inner_microstep: 274.22 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 342 +[2025-05-02 01:58:54,422] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 70.92 | bwd_microstep: 115.56 | bwd_inner_microstep: 115.43 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 01:58:54,898] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.21 | bwd_microstep: 272.89 | bwd_inner_microstep: 272.87 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 840 +[2025-05-02 01:58:55,138] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.37 | bwd_microstep: 130.34 | bwd_inner_microstep: 130.07 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 01:58:55,619] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.63 | bwd_microstep: 272.90 | bwd_inner_microstep: 272.88 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:58:56,098] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.49 | bwd_microstep: 272.19 | bwd_inner_microstep: 272.18 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 01:58:56,577] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.85 | bwd_microstep: 271.33 | bwd_inner_microstep: 271.31 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:58:57,058] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.10 | bwd_microstep: 271.04 | bwd_inner_microstep: 271.03 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 01:58:57,539] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.21 | bwd_microstep: 270.99 | bwd_inner_microstep: 270.98 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.22 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 01:58:58,018] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.98 | bwd_microstep: 271.37 | bwd_inner_microstep: 271.35 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.05 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 932 +[2025-05-02 01:58:58,437] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.22 | optimizer_step: 16.72 +[2025-05-02 01:58:58,437] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 117.45 | bwd_microstep: 255.63 | bwd_inner_microstep: 150.61 | bwd_allreduce_microstep: 104.91 | step_microstep: 26.49 +[2025-05-02 01:58:58,439] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2694.65 | bwd: 3992.40 | bwd_inner: 3886.68 | bwd_allreduce: 105.24 | step: 27.74 + 17%|█▋ | 1454/8720 [3:43:32<14:13:52, 7.05s/it] {'loss': 0.6045, 'grad_norm': 11.364599227905273, 'learning_rate': 9.517884818069476e-06, 'epoch': 1.67} + 17%|█▋ | 1454/8720 [3:43:32<14:13:52, 7.05s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 01:58:58,923] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.48 | bwd_microstep: 272.22 | bwd_inner_microstep: 272.21 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1997 +[2025-05-02 01:58:59,437] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 199.75 | bwd_microstep: 294.48 | bwd_inner_microstep: 294.47 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 928 +[2025-05-02 01:58:59,715] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 113.74 | bwd_microstep: 146.01 | bwd_inner_microstep: 145.69 | bwd_allreduce_microstep: 0.14 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1939 +[2025-05-02 01:59:00,217] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 196.38 | bwd_microstep: 288.25 | bwd_inner_microstep: 288.23 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1905 +[2025-05-02 01:59:00,703] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.03 | bwd_microstep: 276.01 | bwd_inner_microstep: 275.99 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1897 +[2025-05-02 01:59:01,184] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.90 | bwd_microstep: 275.26 | bwd_inner_microstep: 275.24 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 856 +[2025-05-02 01:59:01,428] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.51 | bwd_microstep: 132.97 | bwd_inner_microstep: 132.94 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-02 01:59:01,909] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.41 | bwd_microstep: 273.79 | bwd_inner_microstep: 273.77 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-02 01:59:02,390] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.74 | bwd_microstep: 273.17 | bwd_inner_microstep: 273.15 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 01:59:02,875] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.68 | bwd_microstep: 273.62 | bwd_inner_microstep: 273.60 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:59:03,358] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.46 | bwd_microstep: 272.61 | bwd_inner_microstep: 272.59 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:59:03,838] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.11 | bwd_microstep: 272.42 | bwd_inner_microstep: 272.40 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:59:04,316] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.02 | bwd_microstep: 271.07 | bwd_inner_microstep: 271.05 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 830 +[2025-05-02 01:59:04,580] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 115.77 | bwd_microstep: 129.32 | bwd_inner_microstep: 129.11 | bwd_allreduce_microstep: 0.09 | step_microstep: 0.13 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 319 +[2025-05-02 01:59:04,826] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 102.76 | bwd_microstep: 125.06 | bwd_inner_microstep: 124.86 | bwd_allreduce_microstep: 0.08 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 01:59:05,430] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.25 | optimizer_step: 16.63 +[2025-05-02 01:59:05,431] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.31 | bwd_microstep: 370.92 | bwd_inner_microstep: 271.81 | bwd_allreduce_microstep: 99.05 | step_microstep: 26.37 +[2025-05-02 01:59:05,433] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2712.63 | bwd: 3947.25 | bwd_inner: 3847.23 | bwd_allreduce: 99.42 | step: 27.47 + 17%|█▋ | 1455/8720 [3:43:39<14:11:39, 7.03s/it] {'loss': 0.8584, 'grad_norm': 15.723560333251953, 'learning_rate': 9.51708884589975e-06, 'epoch': 1.67} + 17%|█▋ | 1455/8720 [3:43:39<14:11:39, 7.03s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1934 +[2025-05-02 01:59:05,940] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.57 | bwd_microstep: 287.19 | bwd_inner_microstep: 287.17 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.22 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1926 +[2025-05-02 01:59:06,440] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 194.66 | bwd_microstep: 287.09 | bwd_inner_microstep: 287.07 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1910 +[2025-05-02 01:59:06,924] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.77 | bwd_microstep: 275.97 | bwd_inner_microstep: 275.95 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1393 +[2025-05-02 01:59:07,298] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 144.71 | bwd_microstep: 209.89 | bwd_inner_microstep: 209.87 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.12 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 348 +[2025-05-02 01:59:07,547] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 112.76 | bwd_microstep: 117.59 | bwd_inner_microstep: 117.40 | bwd_allreduce_microstep: 0.08 | step_microstep: 0.13 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 01:59:08,030] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.89 | bwd_microstep: 273.94 | bwd_inner_microstep: 273.92 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-02 01:59:08,511] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.89 | bwd_microstep: 273.73 | bwd_inner_microstep: 273.71 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 01:59:08,994] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.69 | bwd_microstep: 273.63 | bwd_inner_microstep: 273.61 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 01:59:09,473] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.28 | bwd_microstep: 273.48 | bwd_inner_microstep: 273.46 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:59:09,952] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.04 | bwd_microstep: 273.32 | bwd_inner_microstep: 273.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 01:59:10,431] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.03 | bwd_microstep: 272.85 | bwd_inner_microstep: 272.83 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:59:10,907] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.16 | bwd_microstep: 271.59 | bwd_inner_microstep: 271.57 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 01:59:11,383] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.81 | bwd_microstep: 271.37 | bwd_inner_microstep: 271.35 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:59:11,858] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.77 | bwd_microstep: 271.59 | bwd_inner_microstep: 271.57 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 01:59:12,333] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.58 | bwd_microstep: 271.36 | bwd_inner_microstep: 271.34 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 01:59:12,921] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.16 | optimizer_step: 16.47 +[2025-05-02 01:59:12,921] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.98 | bwd_microstep: 357.14 | bwd_inner_microstep: 271.96 | bwd_allreduce_microstep: 85.13 | step_microstep: 24.91 +[2025-05-02 01:59:12,922] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2921.22 | bwd: 4261.76 | bwd_inner: 4176.12 | bwd_allreduce: 85.28 | step: 26.15 + 17%|█▋ | 1456/8720 [3:43:46<14:28:02, 7.17s/it] {'loss': 0.6022, 'grad_norm': 6.153566837310791, 'learning_rate': 9.516292250536385e-06, 'epoch': 1.67} + 17%|█▋ | 1456/8720 [3:43:46<14:28:02, 7.17s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 01:59:13,402] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.66 | bwd_microstep: 271.05 | bwd_inner_microstep: 271.04 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1952 +[2025-05-02 01:59:13,903] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.96 | bwd_microstep: 289.46 | bwd_inner_microstep: 289.44 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1950 +[2025-05-02 01:59:14,405] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 197.82 | bwd_microstep: 289.78 | bwd_inner_microstep: 289.77 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1941 +[2025-05-02 01:59:14,905] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.54 | bwd_microstep: 288.73 | bwd_inner_microstep: 288.71 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 860 +[2025-05-02 01:59:15,148] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.78 | bwd_microstep: 133.24 | bwd_inner_microstep: 132.94 | bwd_allreduce_microstep: 0.14 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-02 01:59:15,625] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.06 | bwd_microstep: 274.08 | bwd_inner_microstep: 274.06 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:59:16,101] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.16 | bwd_microstep: 272.42 | bwd_inner_microstep: 272.41 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 01:59:16,577] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.34 | bwd_microstep: 272.77 | bwd_inner_microstep: 272.76 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:59:17,055] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.33 | bwd_microstep: 272.37 | bwd_inner_microstep: 272.35 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:59:17,529] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.98 | bwd_microstep: 271.04 | bwd_inner_microstep: 271.02 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:59:18,004] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.23 | bwd_microstep: 271.11 | bwd_inner_microstep: 271.10 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 01:59:18,478] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.91 | bwd_microstep: 271.22 | bwd_inner_microstep: 271.21 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 01:59:18,952] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.19 | bwd_microstep: 271.01 | bwd_inner_microstep: 271.00 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 01:59:19,429] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.44 | bwd_microstep: 271.96 | bwd_inner_microstep: 271.94 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 316 +[2025-05-02 01:59:19,645] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 81.24 | bwd_microstep: 121.61 | bwd_inner_microstep: 121.30 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 01:59:20,228] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.04 | optimizer_gradients: 2.15 | optimizer_step: 16.44 +[2025-05-02 01:59:20,229] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.83 | bwd_microstep: 355.98 | bwd_inner_microstep: 271.95 | bwd_allreduce_microstep: 83.97 | step_microstep: 24.80 +[2025-05-02 01:59:20,230] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2836.16 | bwd: 4197.88 | bwd_inner: 4113.09 | bwd_allreduce: 84.30 | step: 25.67 + 17%|█▋ | 1457/8720 [3:43:53<14:32:54, 7.21s/it] {'loss': 0.4486, 'grad_norm': 13.569310188293457, 'learning_rate': 9.515495032089284e-06, 'epoch': 1.67} + 17%|█▋ | 1457/8720 [3:43:53<14:32:54, 7.21s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1899 +[2025-05-02 01:59:20,714] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.60 | bwd_microstep: 274.75 | bwd_inner_microstep: 274.73 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 467 +[2025-05-02 01:59:20,942] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 86.03 | bwd_microstep: 127.27 | bwd_inner_microstep: 126.92 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.20 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 380 +[2025-05-02 01:59:21,186] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.28 | bwd_microstep: 135.58 | bwd_inner_microstep: 135.22 | bwd_allreduce_microstep: 0.14 | step_microstep: 0.22 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-02 01:59:21,665] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.09 | bwd_microstep: 273.93 | bwd_inner_microstep: 273.92 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-02 01:59:22,144] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.09 | bwd_microstep: 273.42 | bwd_inner_microstep: 273.40 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-02 01:59:22,626] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.59 | bwd_microstep: 274.32 | bwd_inner_microstep: 274.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.16 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-02 01:59:23,108] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.80 | bwd_microstep: 274.14 | bwd_inner_microstep: 274.12 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 01:59:23,590] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.36 | bwd_microstep: 274.06 | bwd_inner_microstep: 274.04 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.16 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 01:59:24,071] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.30 | bwd_microstep: 273.79 | bwd_inner_microstep: 273.78 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 329 +[2025-05-02 01:59:24,304] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 97.96 | bwd_microstep: 118.71 | bwd_inner_microstep: 118.35 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.14 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:59:24,783] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.99 | bwd_microstep: 272.61 | bwd_inner_microstep: 272.59 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:59:25,264] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.30 | bwd_microstep: 272.55 | bwd_inner_microstep: 272.53 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:59:25,742] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.84 | bwd_microstep: 272.26 | bwd_inner_microstep: 272.24 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 01:59:26,218] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.07 | bwd_microstep: 270.93 | bwd_inner_microstep: 270.91 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 01:59:26,691] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.81 | bwd_microstep: 271.00 | bwd_inner_microstep: 270.98 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1891 +[2025-05-02 01:59:27,290] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.19 | optimizer_step: 16.45 +[2025-05-02 01:59:27,291] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.29 | bwd_microstep: 367.59 | bwd_inner_microstep: 275.70 | bwd_allreduce_microstep: 91.84 | step_microstep: 24.96 +[2025-05-02 01:59:27,292] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2735.05 | bwd: 4027.04 | bwd_inner: 3933.94 | bwd_allreduce: 92.31 | step: 26.52 + 17%|█▋ | 1458/8720 [3:44:01<14:27:22, 7.17s/it] {'loss': 0.9683, 'grad_norm': 9.361430168151855, 'learning_rate': 9.514697190668432e-06, 'epoch': 1.67} + 17%|█▋ | 1458/8720 [3:44:01<14:27:22, 7.17s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 01:59:27,770] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.86 | bwd_microstep: 270.41 | bwd_inner_microstep: 270.39 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 435 +[2025-05-02 01:59:27,993] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 86.92 | bwd_microstep: 121.83 | bwd_inner_microstep: 121.48 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1961 +[2025-05-02 01:59:28,494] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 196.14 | bwd_microstep: 289.66 | bwd_inner_microstep: 289.64 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1919 +[2025-05-02 01:59:28,976] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.32 | bwd_microstep: 276.53 | bwd_inner_microstep: 276.51 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-02 01:59:29,454] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.55 | bwd_microstep: 273.93 | bwd_inner_microstep: 273.92 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 01:59:29,930] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.45 | bwd_microstep: 273.07 | bwd_inner_microstep: 273.06 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 6, images per sample: 6.0, dynamic token length: 1615 +[2025-05-02 01:59:30,355] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 164.31 | bwd_microstep: 245.57 | bwd_inner_microstep: 245.55 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 345 +[2025-05-02 01:59:30,583] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 91.96 | bwd_microstep: 121.52 | bwd_inner_microstep: 121.37 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-02 01:59:31,061] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.08 | bwd_microstep: 274.20 | bwd_inner_microstep: 274.18 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 01:59:31,539] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.42 | bwd_microstep: 273.50 | bwd_inner_microstep: 273.48 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:59:32,016] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.44 | bwd_microstep: 272.45 | bwd_inner_microstep: 272.43 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 01:59:32,493] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.84 | bwd_microstep: 272.64 | bwd_inner_microstep: 272.62 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 01:59:32,970] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.46 | bwd_microstep: 272.81 | bwd_inner_microstep: 272.79 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:59:33,448] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.78 | bwd_microstep: 273.07 | bwd_inner_microstep: 273.06 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 830 +[2025-05-02 01:59:33,690] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 97.91 | bwd_microstep: 129.97 | bwd_inner_microstep: 129.67 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.23 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:59:34,275] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.19 | optimizer_step: 16.40 +[2025-05-02 01:59:34,275] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.23 | bwd_microstep: 356.06 | bwd_inner_microstep: 271.79 | bwd_allreduce_microstep: 84.22 | step_microstep: 25.02 +[2025-05-02 01:59:34,277] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2711.32 | bwd: 3997.32 | bwd_inner: 3912.04 | bwd_allreduce: 84.61 | step: 26.14 + 17%|█▋ | 1459/8720 [3:44:08<14:20:39, 7.11s/it] {'loss': 0.7755, 'grad_norm': 11.247288703918457, 'learning_rate': 9.513898726383902e-06, 'epoch': 1.67} + 17%|█▋ | 1459/8720 [3:44:08<14:20:39, 7.11s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1907 +[2025-05-02 01:59:34,763] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.67 | bwd_microstep: 276.24 | bwd_inner_microstep: 276.22 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 884 +[2025-05-02 01:59:35,017] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 103.09 | bwd_microstep: 135.45 | bwd_inner_microstep: 135.21 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.09 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 351 +[2025-05-02 01:59:35,244] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 97.94 | bwd_microstep: 115.40 | bwd_inner_microstep: 115.25 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-02 01:59:35,723] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.72 | bwd_microstep: 274.09 | bwd_inner_microstep: 274.08 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 345 +[2025-05-02 01:59:35,942] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 82.56 | bwd_microstep: 123.49 | bwd_inner_microstep: 123.30 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.12 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 347 +[2025-05-02 01:59:36,155] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 81.72 | bwd_microstep: 117.91 | bwd_inner_microstep: 117.66 | bwd_allreduce_microstep: 0.09 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 01:59:36,631] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.77 | bwd_microstep: 273.26 | bwd_inner_microstep: 273.24 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-02 01:59:37,111] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.05 | bwd_microstep: 274.72 | bwd_inner_microstep: 274.71 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-02 01:59:37,591] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.56 | bwd_microstep: 274.18 | bwd_inner_microstep: 274.17 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-02 01:59:38,069] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.08 | bwd_microstep: 273.82 | bwd_inner_microstep: 273.81 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 01:59:38,549] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.29 | bwd_microstep: 273.85 | bwd_inner_microstep: 273.83 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 838 +[2025-05-02 01:59:38,801] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 111.13 | bwd_microstep: 125.86 | bwd_inner_microstep: 125.64 | bwd_allreduce_microstep: 0.10 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:59:39,281] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.72 | bwd_microstep: 272.78 | bwd_inner_microstep: 272.77 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:59:39,761] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.29 | bwd_microstep: 272.62 | bwd_inner_microstep: 272.61 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:59:40,243] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.09 | bwd_microstep: 272.53 | bwd_inner_microstep: 272.52 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 316 +[2025-05-02 01:59:40,634] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.18 | optimizer_step: 16.42 +[2025-05-02 01:59:40,635] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 112.23 | bwd_microstep: 234.39 | bwd_inner_microstep: 129.31 | bwd_allreduce_microstep: 104.96 | step_microstep: 25.83 +[2025-05-02 01:59:40,636] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2484.56 | bwd: 3590.76 | bwd_inner: 3484.48 | bwd_allreduce: 105.48 | step: 26.97 + 17%|█▋ | 1460/8720 [3:44:14<13:53:18, 6.89s/it] {'loss': 0.7157, 'grad_norm': 7.41792106628418, 'learning_rate': 9.513099639345853e-06, 'epoch': 1.67} + 17%|█▋ | 1460/8720 [3:44:14<13:53:18, 6.89s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 01:59:41,120] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.60 | bwd_microstep: 270.60 | bwd_inner_microstep: 270.58 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1116 +[2025-05-02 01:59:41,415] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 116.33 | bwd_microstep: 162.87 | bwd_inner_microstep: 162.66 | bwd_allreduce_microstep: 0.16 | step_microstep: 0.11 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1377 +[2025-05-02 01:59:41,781] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.25 | bwd_microstep: 207.35 | bwd_inner_microstep: 207.34 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.12 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 337 +[2025-05-02 01:59:42,021] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 107.41 | bwd_microstep: 115.37 | bwd_inner_microstep: 115.17 | bwd_allreduce_microstep: 0.08 | step_microstep: 0.14 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 345 +[2025-05-02 01:59:42,260] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 105.14 | bwd_microstep: 115.97 | bwd_inner_microstep: 115.70 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-02 01:59:42,741] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.96 | bwd_microstep: 273.16 | bwd_inner_microstep: 273.14 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 01:59:43,220] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.15 | bwd_microstep: 273.00 | bwd_inner_microstep: 272.99 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 01:59:43,698] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.50 | bwd_microstep: 272.56 | bwd_inner_microstep: 272.54 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:59:44,174] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.26 | bwd_microstep: 272.31 | bwd_inner_microstep: 272.29 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 01:59:44,649] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.96 | bwd_microstep: 272.61 | bwd_inner_microstep: 272.59 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 01:59:45,126] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.48 | bwd_microstep: 272.70 | bwd_inner_microstep: 272.68 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 01:59:45,603] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.89 | bwd_microstep: 272.71 | bwd_inner_microstep: 272.69 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:59:46,081] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.65 | bwd_microstep: 272.60 | bwd_inner_microstep: 272.58 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 01:59:46,558] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.66 | bwd_microstep: 272.24 | bwd_inner_microstep: 272.22 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 319 +[2025-05-02 01:59:46,783] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 86.12 | bwd_microstep: 125.07 | bwd_inner_microstep: 124.92 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 01:59:47,368] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.12 | optimizer_step: 16.41 +[2025-05-02 01:59:47,368] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.35 | bwd_microstep: 356.65 | bwd_inner_microstep: 272.01 | bwd_allreduce_microstep: 84.59 | step_microstep: 24.86 +[2025-05-02 01:59:47,369] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2632.38 | bwd: 3807.85 | bwd_inner: 3722.22 | bwd_allreduce: 85.04 | step: 25.99 + 17%|█▋ | 1461/8720 [3:44:21<13:47:32, 6.84s/it] {'loss': 0.5112, 'grad_norm': 5.937987327575684, 'learning_rate': 9.51229992966453e-06, 'epoch': 1.68} + 17%|█▋ | 1461/8720 [3:44:21<13:47:32, 6.84s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 366 +[2025-05-02 01:59:47,616] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 86.25 | bwd_microstep: 142.18 | bwd_inner_microstep: 141.92 | bwd_allreduce_microstep: 0.10 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2113 +[2025-05-02 01:59:48,147] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 203.32 | bwd_microstep: 311.83 | bwd_inner_microstep: 311.81 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 347 +[2025-05-02 01:59:48,375] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 86.04 | bwd_microstep: 128.85 | bwd_inner_microstep: 128.59 | bwd_allreduce_microstep: 0.10 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-02 01:59:48,854] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.66 | bwd_microstep: 273.77 | bwd_inner_microstep: 273.76 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-02 01:59:49,333] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.71 | bwd_microstep: 273.85 | bwd_inner_microstep: 273.83 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-02 01:59:49,810] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.83 | bwd_microstep: 273.62 | bwd_inner_microstep: 273.60 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 01:59:50,290] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.58 | bwd_microstep: 272.99 | bwd_inner_microstep: 272.97 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1364 +[2025-05-02 01:59:50,652] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.70 | bwd_microstep: 206.81 | bwd_inner_microstep: 206.79 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:59:51,127] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.25 | bwd_microstep: 272.33 | bwd_inner_microstep: 272.31 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 01:59:51,602] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.03 | bwd_microstep: 272.53 | bwd_inner_microstep: 272.51 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 01:59:52,082] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.46 | bwd_microstep: 272.47 | bwd_inner_microstep: 272.45 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1353 +[2025-05-02 01:59:52,445] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.82 | bwd_microstep: 206.12 | bwd_inner_microstep: 206.04 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:59:52,922] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.24 | bwd_microstep: 273.39 | bwd_inner_microstep: 273.38 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 01:59:53,399] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.66 | bwd_microstep: 272.60 | bwd_inner_microstep: 272.59 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 01:59:53,879] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.48 | bwd_microstep: 272.34 | bwd_inner_microstep: 272.32 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 01:59:54,444] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.73 | optimizer_step: 16.44 +[2025-05-02 01:59:54,445] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.22 | bwd_microstep: 337.61 | bwd_inner_microstep: 271.60 | bwd_allreduce_microstep: 65.97 | step_microstep: 24.08 +[2025-05-02 01:59:54,446] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2730.95 | bwd: 4063.36 | bwd_inner: 3996.59 | bwd_allreduce: 66.20 | step: 24.97 + 17%|█▋ | 1462/8720 [3:44:28<13:55:59, 6.91s/it] {'loss': 0.5487, 'grad_norm': 12.095837593078613, 'learning_rate': 9.511499597450267e-06, 'epoch': 1.68} + 17%|█▋ | 1462/8720 [3:44:28<13:55:59, 6.91s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 317 +[2025-05-02 01:59:54,649] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 67.11 | bwd_microstep: 118.16 | bwd_inner_microstep: 117.90 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.09 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 435 +[2025-05-02 01:59:54,848] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 67.74 | bwd_microstep: 117.39 | bwd_inner_microstep: 117.09 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.19 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 388 +[2025-05-02 01:59:55,078] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 96.07 | bwd_microstep: 117.36 | bwd_inner_microstep: 117.14 | bwd_allreduce_microstep: 0.08 | step_microstep: 0.08 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 856 +[2025-05-02 01:59:55,318] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.29 | bwd_microstep: 133.54 | bwd_inner_microstep: 133.47 | bwd_allreduce_microstep: 0.03 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-02 01:59:55,796] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.46 | bwd_microstep: 273.59 | bwd_inner_microstep: 273.58 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1357 +[2025-05-02 01:59:56,157] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.85 | bwd_microstep: 205.78 | bwd_inner_microstep: 205.74 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 01:59:56,637] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.65 | bwd_microstep: 272.26 | bwd_inner_microstep: 272.24 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 01:59:57,112] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.11 | bwd_microstep: 272.48 | bwd_inner_microstep: 272.47 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1354 +[2025-05-02 01:59:57,474] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.59 | bwd_microstep: 206.16 | bwd_inner_microstep: 206.14 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 01:59:57,949] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.71 | bwd_microstep: 272.41 | bwd_inner_microstep: 272.39 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 01:59:58,430] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.03 | bwd_microstep: 272.62 | bwd_inner_microstep: 272.60 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 01:59:58,906] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.06 | bwd_microstep: 272.37 | bwd_inner_microstep: 272.36 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 01:59:59,383] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.10 | bwd_microstep: 272.01 | bwd_inner_microstep: 271.99 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1345 +[2025-05-02 01:59:59,743] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.97 | bwd_microstep: 205.11 | bwd_inner_microstep: 205.09 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 02:00:00,222] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.52 | bwd_microstep: 271.54 | bwd_inner_microstep: 271.52 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 02:00:00,785] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.04 | optimizer_gradients: 2.11 | optimizer_step: 16.42 +[2025-05-02 02:00:00,785] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.10 | bwd_microstep: 337.64 | bwd_inner_microstep: 271.65 | bwd_allreduce_microstep: 65.95 | step_microstep: 23.35 +[2025-05-02 02:00:00,786] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2442.09 | bwd: 3620.52 | bwd_inner: 3553.54 | bwd_allreduce: 66.32 | step: 24.35 + 17%|█▋ | 1463/8720 [3:44:34<13:35:11, 6.74s/it] {'loss': 0.7615, 'grad_norm': 10.937847137451172, 'learning_rate': 9.510698642813476e-06, 'epoch': 1.68} + 17%|█▋ | 1463/8720 [3:44:34<13:35:11, 6.74s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 02:00:01,264] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.52 | bwd_microstep: 270.05 | bwd_inner_microstep: 270.03 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2128 +[2025-05-02 02:00:01,796] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 204.25 | bwd_microstep: 313.65 | bwd_inner_microstep: 313.63 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-02 02:00:02,279] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.13 | bwd_microstep: 274.19 | bwd_inner_microstep: 274.18 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 02:00:02,757] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.43 | bwd_microstep: 273.46 | bwd_inner_microstep: 273.45 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-02 02:00:03,237] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.53 | bwd_microstep: 273.70 | bwd_inner_microstep: 273.68 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.51 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 02:00:03,714] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.23 | bwd_microstep: 272.74 | bwd_inner_microstep: 272.72 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 6, images per sample: 6.0, dynamic token length: 1613 +[2025-05-02 02:00:04,145] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 168.69 | bwd_microstep: 243.45 | bwd_inner_microstep: 243.43 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 02:00:04,622] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.83 | bwd_microstep: 272.51 | bwd_inner_microstep: 272.50 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 326 +[2025-05-02 02:00:04,826] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 68.88 | bwd_microstep: 121.63 | bwd_inner_microstep: 121.47 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 02:00:05,301] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.63 | bwd_microstep: 272.37 | bwd_inner_microstep: 272.35 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 02:00:05,776] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.24 | bwd_microstep: 271.23 | bwd_inner_microstep: 271.21 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 02:00:06,255] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.29 | bwd_microstep: 270.97 | bwd_inner_microstep: 270.95 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 02:00:06,734] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.30 | bwd_microstep: 271.13 | bwd_inner_microstep: 271.11 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 02:00:07,213] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.11 | bwd_microstep: 271.56 | bwd_inner_microstep: 271.55 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 02:00:07,691] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.42 | bwd_microstep: 270.98 | bwd_inner_microstep: 270.96 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1849 +[2025-05-02 02:00:08,296] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.07 | optimizer_gradients: 2.24 | optimizer_step: 16.64 +[2025-05-02 02:00:08,297] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.17 | bwd_microstep: 371.74 | bwd_inner_microstep: 271.33 | bwd_allreduce_microstep: 100.35 | step_microstep: 26.43 +[2025-05-02 02:00:08,299] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2895.33 | bwd: 4315.40 | bwd_inner: 4214.62 | bwd_allreduce: 100.48 | step: 27.90 + 17%|█▋ | 1464/8720 [3:44:42<14:03:10, 6.97s/it] {'loss': 0.5476, 'grad_norm': 8.957757949829102, 'learning_rate': 9.509897065864662e-06, 'epoch': 1.68} + 17%|█▋ | 1464/8720 [3:44:42<14:03:10, 6.97s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-02 02:00:08,785] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.91 | bwd_microstep: 273.82 | bwd_inner_microstep: 273.81 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1931 +[2025-05-02 02:00:09,287] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 197.08 | bwd_microstep: 287.92 | bwd_inner_microstep: 287.90 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-02 02:00:09,765] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.51 | bwd_microstep: 273.52 | bwd_inner_microstep: 273.51 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-02 02:00:10,244] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.35 | bwd_microstep: 273.48 | bwd_inner_microstep: 273.46 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 02:00:10,723] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.15 | bwd_microstep: 272.89 | bwd_inner_microstep: 272.87 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 02:00:11,202] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.72 | bwd_microstep: 272.58 | bwd_inner_microstep: 272.56 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1360 +[2025-05-02 02:00:11,568] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.53 | bwd_microstep: 206.71 | bwd_inner_microstep: 206.60 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 02:00:12,053] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.75 | bwd_microstep: 272.96 | bwd_inner_microstep: 272.94 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 847 +[2025-05-02 02:00:12,305] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 101.30 | bwd_microstep: 132.25 | bwd_inner_microstep: 132.02 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.10 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1351 +[2025-05-02 02:00:12,669] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.28 | bwd_microstep: 206.01 | bwd_inner_microstep: 205.99 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 02:00:13,149] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.46 | bwd_microstep: 272.32 | bwd_inner_microstep: 272.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 02:00:13,628] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.98 | bwd_microstep: 272.18 | bwd_inner_microstep: 272.16 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.15 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1090 +[2025-05-02 02:00:13,923] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 117.24 | bwd_microstep: 160.31 | bwd_inner_microstep: 160.16 | bwd_allreduce_microstep: 0.10 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 02:00:14,400] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.62 | bwd_microstep: 272.67 | bwd_inner_microstep: 272.65 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 319 +[2025-05-02 02:00:14,615] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 82.25 | bwd_microstep: 116.53 | bwd_inner_microstep: 116.33 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 02:00:15,183] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.15 | optimizer_step: 16.61 +[2025-05-02 02:00:15,183] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.12 | bwd_microstep: 339.38 | bwd_inner_microstep: 271.65 | bwd_allreduce_microstep: 67.68 | step_microstep: 23.83 +[2025-05-02 02:00:15,185] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2662.88 | bwd: 3905.60 | bwd_inner: 3836.99 | bwd_allreduce: 68.08 | step: 24.99 + 17%|█▋ | 1465/8720 [3:44:48<13:59:51, 6.95s/it] {'loss': 0.8103, 'grad_norm': 10.047516822814941, 'learning_rate': 9.509094866714414e-06, 'epoch': 1.68} + 17%|█▋ | 1465/8720 [3:44:48<13:59:51, 6.95s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 02:00:15,663] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.69 | bwd_microstep: 270.21 | bwd_inner_microstep: 270.19 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 868 +[2025-05-02 02:00:15,910] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 98.92 | bwd_microstep: 134.12 | bwd_inner_microstep: 133.87 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-02 02:00:16,388] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.45 | bwd_microstep: 274.23 | bwd_inner_microstep: 274.21 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1371 +[2025-05-02 02:00:16,750] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.60 | bwd_microstep: 207.49 | bwd_inner_microstep: 207.43 | bwd_allreduce_microstep: 0.03 | step_microstep: 0.09 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 837 +[2025-05-02 02:00:16,983] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 91.51 | bwd_microstep: 125.98 | bwd_inner_microstep: 125.87 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.08 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 337 +[2025-05-02 02:00:17,198] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 67.52 | bwd_microstep: 135.10 | bwd_inner_microstep: 134.97 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1098 +[2025-05-02 02:00:17,490] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 114.64 | bwd_microstep: 160.94 | bwd_inner_microstep: 160.73 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.10 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 847 +[2025-05-02 02:00:17,735] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.37 | bwd_microstep: 132.55 | bwd_inner_microstep: 132.30 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 02:00:18,215] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.34 | bwd_microstep: 272.78 | bwd_inner_microstep: 272.77 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 02:00:18,693] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.69 | bwd_microstep: 272.30 | bwd_inner_microstep: 272.28 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 835 +[2025-05-02 02:00:18,934] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 96.24 | bwd_microstep: 125.96 | bwd_inner_microstep: 125.75 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 02:00:19,414] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.11 | bwd_microstep: 272.34 | bwd_inner_microstep: 272.32 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 02:00:19,894] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.47 | bwd_microstep: 271.34 | bwd_inner_microstep: 271.33 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 02:00:20,371] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.29 | bwd_microstep: 271.40 | bwd_inner_microstep: 271.38 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 02:00:20,848] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.54 | bwd_microstep: 270.93 | bwd_inner_microstep: 270.92 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 907 +[2025-05-02 02:00:21,219] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.24 | optimizer_step: 16.62 +[2025-05-02 02:00:21,219] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 104.53 | bwd_microstep: 222.30 | bwd_inner_microstep: 145.16 | bwd_allreduce_microstep: 77.03 | step_microstep: 25.22 +[2025-05-02 02:00:21,221] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2315.58 | bwd: 3420.11 | bwd_inner: 3341.59 | bwd_allreduce: 77.69 | step: 26.35 + 17%|█▋ | 1466/8720 [3:44:54<13:26:49, 6.67s/it] {'loss': 0.4299, 'grad_norm': 6.018972396850586, 'learning_rate': 9.508292045473404e-06, 'epoch': 1.68} + 17%|█▋ | 1466/8720 [3:44:54<13:26:49, 6.67s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1914 +[2025-05-02 02:00:21,709] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.75 | bwd_microstep: 275.92 | bwd_inner_microstep: 275.91 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 375 +[2025-05-02 02:00:21,921] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 77.71 | bwd_microstep: 118.45 | bwd_inner_microstep: 118.13 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1904 +[2025-05-02 02:00:22,400] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.47 | bwd_microstep: 275.30 | bwd_inner_microstep: 275.28 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-02 02:00:22,878] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.81 | bwd_microstep: 274.10 | bwd_inner_microstep: 274.09 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1886 +[2025-05-02 02:00:23,357] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.11 | bwd_microstep: 274.33 | bwd_inner_microstep: 274.31 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-02 02:00:23,837] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.20 | bwd_microstep: 274.12 | bwd_inner_microstep: 274.10 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 864 +[2025-05-02 02:00:24,080] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.81 | bwd_microstep: 134.17 | bwd_inner_microstep: 133.89 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 02:00:24,559] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.05 | bwd_microstep: 273.11 | bwd_inner_microstep: 273.10 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1356 +[2025-05-02 02:00:24,920] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.70 | bwd_microstep: 205.84 | bwd_inner_microstep: 205.82 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 02:00:25,397] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.67 | bwd_microstep: 272.56 | bwd_inner_microstep: 272.54 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 844 +[2025-05-02 02:00:25,638] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.96 | bwd_microstep: 132.40 | bwd_inner_microstep: 132.36 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.09 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 845 +[2025-05-02 02:00:25,877] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.36 | bwd_microstep: 132.46 | bwd_inner_microstep: 132.43 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 02:00:26,354] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.83 | bwd_microstep: 272.44 | bwd_inner_microstep: 272.42 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 02:00:26,831] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.04 | bwd_microstep: 272.43 | bwd_inner_microstep: 272.41 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 02:00:27,306] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.40 | bwd_microstep: 271.22 | bwd_inner_microstep: 271.21 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 02:00:27,872] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.36 | optimizer_step: 17.16 +[2025-05-02 02:00:27,872] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.78 | bwd_microstep: 338.48 | bwd_inner_microstep: 271.82 | bwd_allreduce_microstep: 66.61 | step_microstep: 24.48 +[2025-05-02 02:00:27,873] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2574.35 | bwd: 3797.41 | bwd_inner: 3729.90 | bwd_allreduce: 66.94 | step: 25.46 + 17%|█▋ | 1467/8720 [3:45:01<13:25:52, 6.67s/it] {'loss': 0.7364, 'grad_norm': 7.761965751647949, 'learning_rate': 9.507488602252395e-06, 'epoch': 1.68} + 17%|█▋ | 1467/8720 [3:45:01<13:25:52, 6.67s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 02:00:28,351] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.54 | bwd_microstep: 270.66 | bwd_inner_microstep: 270.65 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1950 +[2025-05-02 02:00:28,854] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 196.79 | bwd_microstep: 289.49 | bwd_inner_microstep: 289.47 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.12 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1181 +[2025-05-02 02:00:29,166] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 122.66 | bwd_microstep: 172.47 | bwd_inner_microstep: 172.28 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1889 +[2025-05-02 02:00:29,647] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.55 | bwd_microstep: 274.35 | bwd_inner_microstep: 274.33 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-02 02:00:30,129] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.32 | bwd_microstep: 274.21 | bwd_inner_microstep: 274.19 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-02 02:00:30,611] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.06 | bwd_microstep: 273.17 | bwd_inner_microstep: 273.16 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 02:00:31,091] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.20 | bwd_microstep: 272.50 | bwd_inner_microstep: 272.48 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 02:00:31,574] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.06 | bwd_microstep: 272.86 | bwd_inner_microstep: 272.84 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 02:00:32,054] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.44 | bwd_microstep: 272.81 | bwd_inner_microstep: 272.80 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 02:00:32,534] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.83 | bwd_microstep: 272.11 | bwd_inner_microstep: 272.09 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 02:00:33,014] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.36 | bwd_microstep: 272.56 | bwd_inner_microstep: 272.55 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 02:00:33,493] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.78 | bwd_microstep: 272.06 | bwd_inner_microstep: 272.05 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 02:00:33,971] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.13 | bwd_microstep: 270.89 | bwd_inner_microstep: 270.87 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 02:00:34,451] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.17 | bwd_microstep: 271.18 | bwd_inner_microstep: 271.16 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1344 +[2025-05-02 02:00:34,815] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.80 | bwd_microstep: 204.36 | bwd_inner_microstep: 204.32 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 02:00:35,392] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.68 | optimizer_step: 16.82 +[2025-05-02 02:00:35,393] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.32 | bwd_microstep: 347.22 | bwd_inner_microstep: 271.33 | bwd_allreduce_microstep: 75.83 | step_microstep: 25.03 +[2025-05-02 02:00:35,394] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2909.63 | bwd: 4282.95 | bwd_inner: 4206.55 | bwd_allreduce: 76.04 | step: 26.16 + 17%|█▋ | 1468/8720 [3:45:09<13:56:48, 6.92s/it] {'loss': 1.0426, 'grad_norm': 14.417902946472168, 'learning_rate': 9.50668453716223e-06, 'epoch': 1.68} + 17%|█▋ | 1468/8720 [3:45:09<13:56:48, 6.92s/it]dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1343 +[2025-05-02 02:00:35,760] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.18 | bwd_microstep: 203.97 | bwd_inner_microstep: 203.95 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1959 +[2025-05-02 02:00:36,265] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 197.67 | bwd_microstep: 289.97 | bwd_inner_microstep: 289.95 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1930 +[2025-05-02 02:00:36,763] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.19 | bwd_microstep: 287.88 | bwd_inner_microstep: 287.86 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1900 +[2025-05-02 02:00:37,244] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.09 | bwd_microstep: 275.91 | bwd_inner_microstep: 275.90 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1892 +[2025-05-02 02:00:37,722] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.87 | bwd_microstep: 274.53 | bwd_inner_microstep: 274.52 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 02:00:38,201] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.49 | bwd_microstep: 273.20 | bwd_inner_microstep: 273.19 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 02:00:38,680] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.29 | bwd_microstep: 272.61 | bwd_inner_microstep: 272.59 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 02:00:39,160] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.17 | bwd_microstep: 272.97 | bwd_inner_microstep: 272.95 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 02:00:39,637] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.90 | bwd_microstep: 272.25 | bwd_inner_microstep: 272.24 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 02:00:40,114] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.99 | bwd_microstep: 272.51 | bwd_inner_microstep: 272.49 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 02:00:40,593] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.75 | bwd_microstep: 272.21 | bwd_inner_microstep: 272.19 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 02:00:41,071] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.48 | bwd_microstep: 272.43 | bwd_inner_microstep: 272.41 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 02:00:41,549] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.62 | bwd_microstep: 272.27 | bwd_inner_microstep: 272.25 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 02:00:42,028] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.90 | bwd_microstep: 272.39 | bwd_inner_microstep: 272.37 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 02:00:42,504] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.43 | bwd_microstep: 271.27 | bwd_inner_microstep: 271.25 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 02:00:43,068] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.04 | optimizer_gradients: 2.21 | optimizer_step: 16.83 +[2025-05-02 02:00:43,068] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.85 | bwd_microstep: 337.03 | bwd_inner_microstep: 271.41 | bwd_allreduce_microstep: 65.57 | step_microstep: 23.80 +[2025-05-02 02:00:43,069] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2981.55 | bwd: 4393.41 | bwd_inner: 4327.52 | bwd_allreduce: 65.66 | step: 24.55 + 17%|█▋ | 1469/8720 [3:45:16<14:23:53, 7.15s/it] {'loss': 0.4896, 'grad_norm': 7.017140865325928, 'learning_rate': 9.505879850313842e-06, 'epoch': 1.68} + 17%|█▋ | 1469/8720 [3:45:16<14:23:53, 7.15s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2068 +[2025-05-02 02:00:43,593] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 201.25 | bwd_microstep: 302.50 | bwd_inner_microstep: 302.48 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-02 02:00:44,071] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.31 | bwd_microstep: 274.23 | bwd_inner_microstep: 274.21 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 02:00:44,549] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.49 | bwd_microstep: 273.67 | bwd_inner_microstep: 273.65 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 02:00:45,029] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.20 | bwd_microstep: 273.41 | bwd_inner_microstep: 273.39 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 02:00:45,510] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.31 | bwd_microstep: 274.05 | bwd_inner_microstep: 274.04 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 02:00:45,989] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.73 | bwd_microstep: 273.38 | bwd_inner_microstep: 273.36 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 02:00:46,470] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.99 | bwd_microstep: 273.46 | bwd_inner_microstep: 273.45 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 02:00:46,950] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.49 | bwd_microstep: 272.74 | bwd_inner_microstep: 272.72 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 02:00:47,430] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.85 | bwd_microstep: 273.95 | bwd_inner_microstep: 273.93 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 02:00:47,909] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.78 | bwd_microstep: 272.46 | bwd_inner_microstep: 272.44 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 02:00:48,389] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.52 | bwd_microstep: 272.16 | bwd_inner_microstep: 272.14 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 02:00:48,867] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.81 | bwd_microstep: 272.65 | bwd_inner_microstep: 272.63 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 02:00:49,347] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.68 | bwd_microstep: 271.89 | bwd_inner_microstep: 271.87 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 321 +[2025-05-02 02:00:49,566] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 83.20 | bwd_microstep: 119.10 | bwd_inner_microstep: 118.95 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1345 +[2025-05-02 02:00:49,929] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.07 | bwd_microstep: 205.52 | bwd_inner_microstep: 205.47 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 02:00:50,508] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.23 | optimizer_step: 16.85 +[2025-05-02 02:00:50,509] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.93 | bwd_microstep: 347.78 | bwd_inner_microstep: 272.03 | bwd_allreduce_microstep: 75.70 | step_microstep: 24.58 +[2025-05-02 02:00:50,510] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2880.25 | bwd: 4252.99 | bwd_inner: 4176.81 | bwd_allreduce: 75.85 | step: 25.40 + 17%|█▋ | 1470/8720 [3:45:24<14:34:24, 7.24s/it] {'loss': 0.6961, 'grad_norm': 14.432157516479492, 'learning_rate': 9.505074541818247e-06, 'epoch': 1.69} + 17%|█▋ | 1470/8720 [3:45:24<14:34:24, 7.24s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 337 +[2025-05-02 02:00:50,725] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 77.56 | bwd_microstep: 117.14 | bwd_inner_microstep: 117.01 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2008 +[2025-05-02 02:00:51,235] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 200.01 | bwd_microstep: 294.79 | bwd_inner_microstep: 294.77 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 02:00:51,711] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.06 | bwd_microstep: 273.26 | bwd_inner_microstep: 273.24 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-02 02:00:52,188] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.32 | bwd_microstep: 273.21 | bwd_inner_microstep: 273.19 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-02 02:00:52,666] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.76 | bwd_microstep: 273.87 | bwd_inner_microstep: 273.85 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 02:00:53,142] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.25 | bwd_microstep: 272.52 | bwd_inner_microstep: 272.51 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 02:00:53,619] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.82 | bwd_microstep: 272.76 | bwd_inner_microstep: 272.75 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 02:00:54,095] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.31 | bwd_microstep: 273.25 | bwd_inner_microstep: 273.23 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 02:00:54,570] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.82 | bwd_microstep: 272.53 | bwd_inner_microstep: 272.51 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 02:00:55,046] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.21 | bwd_microstep: 272.46 | bwd_inner_microstep: 272.44 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 02:00:55,524] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.63 | bwd_microstep: 272.58 | bwd_inner_microstep: 272.56 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 02:00:56,004] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.35 | bwd_microstep: 273.09 | bwd_inner_microstep: 273.07 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 02:00:56,484] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.40 | bwd_microstep: 272.08 | bwd_inner_microstep: 272.06 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 02:00:56,962] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.17 | bwd_microstep: 271.25 | bwd_inner_microstep: 271.23 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 318 +[2025-05-02 02:00:57,200] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 99.96 | bwd_microstep: 120.04 | bwd_inner_microstep: 119.86 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 02:00:57,784] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.23 | optimizer_step: 16.82 +[2025-05-02 02:00:57,785] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.21 | bwd_microstep: 348.48 | bwd_inner_microstep: 272.21 | bwd_allreduce_microstep: 76.22 | step_microstep: 24.50 +[2025-05-02 02:00:57,786] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2826.50 | bwd: 4153.35 | bwd_inner: 4076.55 | bwd_allreduce: 76.41 | step: 25.28 + 17%|█▋ | 1471/8720 [3:45:31<14:35:43, 7.25s/it] {'loss': 0.8794, 'grad_norm': 8.600227355957031, 'learning_rate': 9.504268611786552e-06, 'epoch': 1.69} + 17%|█▋ | 1471/8720 [3:45:31<14:35:43, 7.25s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1982 +[2025-05-02 02:00:58,299] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 198.12 | bwd_microstep: 291.59 | bwd_inner_microstep: 291.58 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1988 +[2025-05-02 02:00:58,809] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 199.26 | bwd_microstep: 293.45 | bwd_inner_microstep: 293.43 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1904 +[2025-05-02 02:00:59,291] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.49 | bwd_microstep: 276.06 | bwd_inner_microstep: 276.04 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1894 +[2025-05-02 02:00:59,770] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.69 | bwd_microstep: 275.28 | bwd_inner_microstep: 275.26 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-02 02:01:00,248] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.09 | bwd_microstep: 274.03 | bwd_inner_microstep: 274.02 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 02:01:00,724] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.33 | bwd_microstep: 272.72 | bwd_inner_microstep: 272.70 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 02:01:01,200] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.79 | bwd_microstep: 272.65 | bwd_inner_microstep: 272.63 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 02:01:01,677] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.11 | bwd_microstep: 272.74 | bwd_inner_microstep: 272.73 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 02:01:02,153] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.44 | bwd_microstep: 272.69 | bwd_inner_microstep: 272.67 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 02:01:02,629] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.90 | bwd_microstep: 272.60 | bwd_inner_microstep: 272.58 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 02:01:03,103] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.75 | bwd_microstep: 271.21 | bwd_inner_microstep: 271.20 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 02:01:03,579] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.98 | bwd_microstep: 272.29 | bwd_inner_microstep: 272.27 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 02:01:04,054] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.37 | bwd_microstep: 271.42 | bwd_inner_microstep: 271.40 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 829 +[2025-05-02 02:01:04,290] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 92.11 | bwd_microstep: 129.93 | bwd_inner_microstep: 129.91 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 02:01:04,763] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.70 | bwd_microstep: 271.44 | bwd_inner_microstep: 271.43 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 315 +[2025-05-02 02:01:05,080] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.04 | optimizer_gradients: 2.20 | optimizer_step: 16.86 +[2025-05-02 02:01:05,081] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 81.01 | bwd_microstep: 198.09 | bwd_inner_microstep: 132.43 | bwd_allreduce_microstep: 65.55 | step_microstep: 23.85 +[2025-05-02 02:01:05,082] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2832.85 | bwd: 4188.22 | bwd_inner: 4122.34 | bwd_allreduce: 65.62 | step: 24.59 + 17%|█▋ | 1472/8720 [3:45:38<14:37:15, 7.26s/it] {'loss': 0.4769, 'grad_norm': 7.6683244705200195, 'learning_rate': 9.503462060329943e-06, 'epoch': 1.69} + 17%|█▋ | 1472/8720 [3:45:38<14:37:15, 7.26s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1941 +[2025-05-02 02:01:05,585] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.60 | bwd_microstep: 287.96 | bwd_inner_microstep: 287.94 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1913 +[2025-05-02 02:01:06,067] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.41 | bwd_microstep: 276.41 | bwd_inner_microstep: 276.40 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.14 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1923 +[2025-05-02 02:01:06,564] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 194.92 | bwd_microstep: 286.95 | bwd_inner_microstep: 286.94 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1894 +[2025-05-02 02:01:07,043] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.61 | bwd_microstep: 275.08 | bwd_inner_microstep: 275.06 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 359 +[2025-05-02 02:01:07,257] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 78.54 | bwd_microstep: 122.03 | bwd_inner_microstep: 121.90 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-02 02:01:07,733] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.12 | bwd_microstep: 273.10 | bwd_inner_microstep: 273.08 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 02:01:08,210] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.26 | bwd_microstep: 273.59 | bwd_inner_microstep: 273.57 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 02:01:08,684] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.89 | bwd_microstep: 272.25 | bwd_inner_microstep: 272.24 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 02:01:09,161] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.76 | bwd_microstep: 272.98 | bwd_inner_microstep: 272.96 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 02:01:09,640] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.88 | bwd_microstep: 272.86 | bwd_inner_microstep: 272.84 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 02:01:10,119] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.41 | bwd_microstep: 272.58 | bwd_inner_microstep: 272.57 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 02:01:10,599] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.29 | bwd_microstep: 272.90 | bwd_inner_microstep: 272.88 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 02:01:11,079] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.25 | bwd_microstep: 272.84 | bwd_inner_microstep: 272.83 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 02:01:11,560] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.80 | bwd_microstep: 272.40 | bwd_inner_microstep: 272.38 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 02:01:12,040] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.72 | bwd_microstep: 273.39 | bwd_inner_microstep: 273.37 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 02:01:12,627] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.23 | optimizer_step: 16.81 +[2025-05-02 02:01:12,627] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.66 | bwd_microstep: 356.57 | bwd_inner_microstep: 271.51 | bwd_allreduce_microstep: 85.00 | step_microstep: 24.51 +[2025-05-02 02:01:12,629] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2924.82 | bwd: 4333.93 | bwd_inner: 4248.50 | bwd_allreduce: 85.13 | step: 25.36 + 17%|█▋ | 1473/8720 [3:45:46<14:47:31, 7.35s/it] {'loss': 0.5839, 'grad_norm': 9.115434646606445, 'learning_rate': 9.502654887559693e-06, 'epoch': 1.69} + 17%|█▋ | 1473/8720 [3:45:46<14:47:31, 7.35s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1889 +[2025-05-02 02:01:13,115] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.50 | bwd_microstep: 274.16 | bwd_inner_microstep: 274.14 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-02 02:01:13,595] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.47 | bwd_microstep: 273.42 | bwd_inner_microstep: 273.40 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1896 +[2025-05-02 02:01:14,077] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.79 | bwd_microstep: 275.13 | bwd_inner_microstep: 275.11 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1370 +[2025-05-02 02:01:14,442] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 142.31 | bwd_microstep: 207.43 | bwd_inner_microstep: 207.42 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-02 02:01:14,920] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.98 | bwd_microstep: 274.09 | bwd_inner_microstep: 274.07 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-02 02:01:15,399] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.42 | bwd_microstep: 274.10 | bwd_inner_microstep: 274.08 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 02:01:15,878] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.33 | bwd_microstep: 273.51 | bwd_inner_microstep: 273.49 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.12 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 329 +[2025-05-02 02:01:16,076] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 66.91 | bwd_microstep: 118.47 | bwd_inner_microstep: 118.18 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 02:01:16,553] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.72 | bwd_microstep: 273.44 | bwd_inner_microstep: 273.42 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 02:01:17,029] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.30 | bwd_microstep: 272.75 | bwd_inner_microstep: 272.73 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 02:01:17,504] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.53 | bwd_microstep: 272.47 | bwd_inner_microstep: 272.45 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 02:01:17,980] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.39 | bwd_microstep: 272.56 | bwd_inner_microstep: 272.54 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 02:01:18,456] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.01 | bwd_microstep: 272.95 | bwd_inner_microstep: 272.93 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 02:01:18,936] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.31 | bwd_microstep: 272.43 | bwd_inner_microstep: 272.41 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1341 +[2025-05-02 02:01:19,301] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.25 | bwd_microstep: 204.08 | bwd_inner_microstep: 203.97 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 02:01:19,879] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.21 | optimizer_step: 17.35 +[2025-05-02 02:01:19,880] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.82 | bwd_microstep: 347.10 | bwd_inner_microstep: 271.42 | bwd_allreduce_microstep: 75.63 | step_microstep: 25.10 +[2025-05-02 02:01:19,881] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2805.73 | bwd: 4158.12 | bwd_inner: 4081.84 | bwd_allreduce: 75.91 | step: 25.98 + 17%|█▋ | 1474/8720 [3:45:53<14:43:55, 7.32s/it] {'loss': 0.5837, 'grad_norm': 15.386143684387207, 'learning_rate': 9.501847093587167e-06, 'epoch': 1.69} + 17%|█▋ | 1474/8720 [3:45:53<14:43:55, 7.32s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1991 +[2025-05-02 02:01:20,394] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 197.17 | bwd_microstep: 293.66 | bwd_inner_microstep: 293.64 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1408 +[2025-05-02 02:01:20,766] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 144.63 | bwd_microstep: 210.43 | bwd_inner_microstep: 210.41 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1891 +[2025-05-02 02:01:21,244] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.83 | bwd_microstep: 274.70 | bwd_inner_microstep: 274.68 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 355 +[2025-05-02 02:01:21,451] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 71.40 | bwd_microstep: 122.22 | bwd_inner_microstep: 122.09 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-02 02:01:21,928] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.17 | bwd_microstep: 274.86 | bwd_inner_microstep: 274.85 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 02:01:22,404] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.22 | bwd_microstep: 272.92 | bwd_inner_microstep: 272.90 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 02:01:22,881] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.47 | bwd_microstep: 272.96 | bwd_inner_microstep: 272.95 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 02:01:23,358] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.52 | bwd_microstep: 273.41 | bwd_inner_microstep: 273.39 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1353 +[2025-05-02 02:01:23,721] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.23 | bwd_microstep: 206.10 | bwd_inner_microstep: 206.08 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 02:01:24,197] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.30 | bwd_microstep: 272.42 | bwd_inner_microstep: 272.40 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 844 +[2025-05-02 02:01:24,439] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.10 | bwd_microstep: 132.22 | bwd_inner_microstep: 131.93 | bwd_allreduce_microstep: 0.15 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 02:01:24,915] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.14 | bwd_microstep: 272.71 | bwd_inner_microstep: 272.69 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 02:01:25,391] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.50 | bwd_microstep: 271.37 | bwd_inner_microstep: 271.35 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 322 +[2025-05-02 02:01:25,594] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 69.24 | bwd_microstep: 120.11 | bwd_inner_microstep: 119.85 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 02:01:26,072] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.24 | bwd_microstep: 273.05 | bwd_inner_microstep: 273.03 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 02:01:26,638] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.24 | optimizer_step: 16.91 +[2025-05-02 02:01:26,638] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.09 | bwd_microstep: 337.78 | bwd_inner_microstep: 271.82 | bwd_allreduce_microstep: 65.91 | step_microstep: 24.24 +[2025-05-02 02:01:26,639] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2601.98 | bwd: 3880.97 | bwd_inner: 3814.19 | bwd_allreduce: 66.28 | step: 25.08 + 17%|█▋ | 1475/8720 [3:46:00<14:23:26, 7.15s/it] {'loss': 0.7166, 'grad_norm': 7.108105182647705, 'learning_rate': 9.501038678523808e-06, 'epoch': 1.69} + 17%|█▋ | 1475/8720 [3:46:00<14:23:26, 7.15s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1850 +[2025-05-02 02:01:27,117] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.01 | bwd_microstep: 270.07 | bwd_inner_microstep: 270.05 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1918 +[2025-05-02 02:01:27,599] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.54 | bwd_microstep: 276.89 | bwd_inner_microstep: 276.87 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1144 +[2025-05-02 02:01:27,895] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 116.77 | bwd_microstep: 164.96 | bwd_inner_microstep: 164.73 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1893 +[2025-05-02 02:01:28,376] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.42 | bwd_microstep: 275.71 | bwd_inner_microstep: 275.69 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1888 +[2025-05-02 02:01:28,856] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.27 | bwd_microstep: 274.92 | bwd_inner_microstep: 274.91 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 859 +[2025-05-02 02:01:29,102] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 97.79 | bwd_microstep: 133.13 | bwd_inner_microstep: 133.11 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 02:01:29,578] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.90 | bwd_microstep: 272.75 | bwd_inner_microstep: 272.73 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1887 +[2025-05-02 02:01:30,057] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.14 | bwd_microstep: 274.51 | bwd_inner_microstep: 274.49 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 334 +[2025-05-02 02:01:30,276] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 86.63 | bwd_microstep: 116.66 | bwd_inner_microstep: 116.33 | bwd_allreduce_microstep: 0.14 | step_microstep: 0.09 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 849 +[2025-05-02 02:01:30,522] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 97.62 | bwd_microstep: 133.13 | bwd_inner_microstep: 133.11 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 02:01:30,998] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.10 | bwd_microstep: 272.96 | bwd_inner_microstep: 272.94 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 02:01:31,475] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.88 | bwd_microstep: 273.12 | bwd_inner_microstep: 273.11 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 02:01:31,953] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.27 | bwd_microstep: 272.96 | bwd_inner_microstep: 272.94 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 02:01:32,433] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.15 | bwd_microstep: 272.62 | bwd_inner_microstep: 272.60 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 02:01:32,912] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.91 | bwd_microstep: 273.29 | bwd_inner_microstep: 273.27 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 02:01:33,488] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.25 | optimizer_step: 16.91 +[2025-05-02 02:01:33,489] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.45 | bwd_microstep: 345.52 | bwd_inner_microstep: 273.69 | bwd_allreduce_microstep: 71.78 | step_microstep: 24.25 +[2025-05-02 02:01:33,490] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2665.58 | bwd: 3903.23 | bwd_inner: 3830.64 | bwd_allreduce: 72.11 | step: 25.08 + 17%|█▋ | 1476/8720 [3:46:07<14:12:27, 7.06s/it] {'loss': 1.2715, 'grad_norm': 12.6990327835083, 'learning_rate': 9.500229642481148e-06, 'epoch': 1.69} + 17%|█▋ | 1476/8720 [3:46:07<14:12:27, 7.06s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 02:01:33,972] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.94 | bwd_microstep: 271.86 | bwd_inner_microstep: 271.84 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.56 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 464 +[2025-05-02 02:01:34,190] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 78.86 | bwd_microstep: 125.18 | bwd_inner_microstep: 125.04 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1935 +[2025-05-02 02:01:34,690] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.55 | bwd_microstep: 287.94 | bwd_inner_microstep: 287.92 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1909 +[2025-05-02 02:01:35,173] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.99 | bwd_microstep: 276.40 | bwd_inner_microstep: 276.38 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1896 +[2025-05-02 02:01:35,655] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.77 | bwd_microstep: 275.27 | bwd_inner_microstep: 275.25 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-02 02:01:36,136] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.76 | bwd_microstep: 273.66 | bwd_inner_microstep: 273.64 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-02 02:01:36,618] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.12 | bwd_microstep: 273.31 | bwd_inner_microstep: 273.29 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1350 +[2025-05-02 02:01:36,984] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.39 | bwd_microstep: 205.60 | bwd_inner_microstep: 205.59 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 02:01:37,467] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.03 | bwd_microstep: 272.68 | bwd_inner_microstep: 272.67 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 322 +[2025-05-02 02:01:37,690] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 89.85 | bwd_microstep: 115.65 | bwd_inner_microstep: 115.50 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 02:01:38,168] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.55 | bwd_microstep: 272.61 | bwd_inner_microstep: 272.59 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 327 +[2025-05-02 02:01:38,398] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 97.58 | bwd_microstep: 114.89 | bwd_inner_microstep: 114.67 | bwd_allreduce_microstep: 0.08 | step_microstep: 0.10 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 328 +[2025-05-02 02:01:38,628] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 85.73 | bwd_microstep: 126.40 | bwd_inner_microstep: 126.15 | bwd_allreduce_microstep: 0.09 | step_microstep: 0.10 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 836 +[2025-05-02 02:01:38,871] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 101.27 | bwd_microstep: 125.83 | bwd_inner_microstep: 125.77 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 02:01:39,349] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.79 | bwd_microstep: 271.32 | bwd_inner_microstep: 271.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 02:01:39,928] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.26 | optimizer_step: 17.01 +[2025-05-02 02:01:39,928] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.59 | bwd_microstep: 349.24 | bwd_inner_microstep: 271.72 | bwd_allreduce_microstep: 77.47 | step_microstep: 24.38 +[2025-05-02 02:01:39,930] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2490.42 | bwd: 3637.94 | bwd_inner: 3559.53 | bwd_allreduce: 77.79 | step: 25.95 + 17%|█▋ | 1477/8720 [3:46:13<13:49:50, 6.87s/it] {'loss': 0.5398, 'grad_norm': 9.959226608276367, 'learning_rate': 9.499419985570806e-06, 'epoch': 1.69} + 17%|█▋ | 1477/8720 [3:46:13<13:49:50, 6.87s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 02:01:40,408] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.00 | bwd_microstep: 270.90 | bwd_inner_microstep: 270.89 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2027 +[2025-05-02 02:01:40,921] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 200.61 | bwd_microstep: 296.79 | bwd_inner_microstep: 296.78 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 915 +[2025-05-02 02:01:41,183] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 103.04 | bwd_microstep: 145.16 | bwd_inner_microstep: 144.90 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1919 +[2025-05-02 02:01:41,665] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.14 | bwd_microstep: 276.78 | bwd_inner_microstep: 276.76 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 347 +[2025-05-02 02:01:41,864] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 67.49 | bwd_microstep: 118.18 | bwd_inner_microstep: 118.03 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 02:01:42,342] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.32 | bwd_microstep: 273.04 | bwd_inner_microstep: 273.02 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 02:01:42,818] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.00 | bwd_microstep: 272.69 | bwd_inner_microstep: 272.67 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-02 02:01:43,295] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.58 | bwd_microstep: 273.13 | bwd_inner_microstep: 273.11 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 02:01:43,772] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.85 | bwd_microstep: 272.99 | bwd_inner_microstep: 272.98 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 02:01:44,250] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.01 | bwd_microstep: 273.20 | bwd_inner_microstep: 273.18 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.16 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 02:01:44,729] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.45 | bwd_microstep: 273.00 | bwd_inner_microstep: 272.98 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 02:01:45,206] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.62 | bwd_microstep: 272.62 | bwd_inner_microstep: 272.60 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 02:01:45,682] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.15 | bwd_microstep: 272.41 | bwd_inner_microstep: 272.39 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 02:01:46,156] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.58 | bwd_microstep: 271.08 | bwd_inner_microstep: 271.06 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 1105 +[2025-05-02 02:01:46,439] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 107.19 | bwd_microstep: 161.79 | bwd_inner_microstep: 161.70 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1931 +[2025-05-02 02:01:47,028] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.25 | optimizer_step: 16.89 +[2025-05-02 02:01:47,029] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 194.61 | bwd_microstep: 354.16 | bwd_inner_microstep: 288.46 | bwd_allreduce_microstep: 65.65 | step_microstep: 24.22 +[2025-05-02 02:01:47,030] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2746.36 | bwd: 4077.96 | bwd_inner: 4011.56 | bwd_allreduce: 65.95 | step: 25.26 + 17%|█▋ | 1478/8720 [3:46:20<13:57:54, 6.94s/it] {'loss': 0.7212, 'grad_norm': 4.825712203979492, 'learning_rate': 9.498609707904484e-06, 'epoch': 1.69} + 17%|█▋ | 1478/8720 [3:46:20<13:57:54, 6.94s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1889 +[2025-05-02 02:01:47,513] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.70 | bwd_microstep: 273.79 | bwd_inner_microstep: 273.77 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2323 +[2025-05-02 02:01:48,084] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 218.33 | bwd_microstep: 337.53 | bwd_inner_microstep: 337.51 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 02:01:48,561] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.04 | bwd_microstep: 273.69 | bwd_inner_microstep: 273.67 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 02:01:49,039] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.10 | bwd_microstep: 273.22 | bwd_inner_microstep: 273.21 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 852 +[2025-05-02 02:01:49,280] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.40 | bwd_microstep: 133.42 | bwd_inner_microstep: 133.14 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 02:01:49,755] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.30 | bwd_microstep: 272.53 | bwd_inner_microstep: 272.52 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 02:01:50,230] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.28 | bwd_microstep: 272.45 | bwd_inner_microstep: 272.43 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 02:01:50,711] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.57 | bwd_microstep: 272.35 | bwd_inner_microstep: 272.34 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 02:01:51,188] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.63 | bwd_microstep: 272.37 | bwd_inner_microstep: 272.36 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 319 +[2025-05-02 02:01:51,420] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 98.04 | bwd_microstep: 117.37 | bwd_inner_microstep: 117.08 | bwd_allreduce_microstep: 0.15 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 02:01:51,895] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.56 | bwd_microstep: 271.31 | bwd_inner_microstep: 271.30 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 318 +[2025-05-02 02:01:52,117] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 84.71 | bwd_microstep: 118.33 | bwd_inner_microstep: 118.12 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 02:01:52,593] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.11 | bwd_microstep: 271.41 | bwd_inner_microstep: 271.39 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 02:01:53,070] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.69 | bwd_microstep: 271.11 | bwd_inner_microstep: 271.09 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 828 +[2025-05-02 02:01:53,311] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.72 | bwd_microstep: 130.14 | bwd_inner_microstep: 130.03 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 02:01:53,893] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.92 | optimizer_step: 17.07 +[2025-05-02 02:01:53,894] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.88 | bwd_microstep: 350.76 | bwd_inner_microstep: 271.91 | bwd_allreduce_microstep: 78.80 | step_microstep: 26.03 +[2025-05-02 02:01:53,895] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2657.74 | bwd: 3911.86 | bwd_inner: 3831.99 | bwd_allreduce: 79.22 | step: 26.89 + 17%|█▋ | 1479/8720 [3:46:27<13:55:04, 6.92s/it] {'loss': 0.4005, 'grad_norm': 13.75281047821045, 'learning_rate': 9.497798809593973e-06, 'epoch': 1.7} + 17%|█▋ | 1479/8720 [3:46:27<13:55:04, 6.92s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 02:01:54,376] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.99 | bwd_microstep: 270.27 | bwd_inner_microstep: 270.25 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1938 +[2025-05-02 02:01:54,879] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.40 | bwd_microstep: 289.20 | bwd_inner_microstep: 289.18 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1897 +[2025-05-02 02:01:55,361] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.11 | bwd_microstep: 275.54 | bwd_inner_microstep: 275.53 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1894 +[2025-05-02 02:01:55,843] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.54 | bwd_microstep: 275.13 | bwd_inner_microstep: 275.11 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.13 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-02 02:01:56,321] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.83 | bwd_microstep: 273.64 | bwd_inner_microstep: 273.63 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 845 +[2025-05-02 02:01:56,561] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.77 | bwd_microstep: 132.31 | bwd_inner_microstep: 132.10 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 852 +[2025-05-02 02:01:56,801] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.72 | bwd_microstep: 132.70 | bwd_inner_microstep: 132.68 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 02:01:57,278] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.36 | bwd_microstep: 274.19 | bwd_inner_microstep: 274.17 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 02:01:57,755] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.31 | bwd_microstep: 273.01 | bwd_inner_microstep: 272.99 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 02:01:58,232] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.88 | bwd_microstep: 272.74 | bwd_inner_microstep: 272.72 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 02:01:58,708] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.84 | bwd_microstep: 273.12 | bwd_inner_microstep: 273.10 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 834 +[2025-05-02 02:01:58,940] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 92.17 | bwd_microstep: 126.34 | bwd_inner_microstep: 126.07 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 02:01:59,416] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.08 | bwd_microstep: 272.62 | bwd_inner_microstep: 272.61 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 02:01:59,891] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.96 | bwd_microstep: 272.31 | bwd_inner_microstep: 272.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 02:02:00,368] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.90 | bwd_microstep: 273.02 | bwd_inner_microstep: 273.00 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 317 +[2025-05-02 02:02:00,682] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.04 | optimizer_gradients: 2.23 | optimizer_step: 16.83 +[2025-05-02 02:02:00,682] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 75.68 | bwd_microstep: 199.49 | bwd_inner_microstep: 132.86 | bwd_allreduce_microstep: 66.54 | step_microstep: 23.86 +[2025-05-02 02:02:00,684] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2624.26 | bwd: 3885.69 | bwd_inner: 3818.34 | bwd_allreduce: 66.84 | step: 24.87 + 17%|█▋ | 1480/8720 [3:46:34<13:50:08, 6.88s/it] {'loss': 0.5198, 'grad_norm': 5.494067668914795, 'learning_rate': 9.496987290751142e-06, 'epoch': 1.7} + 17%|█▋ | 1480/8720 [3:46:34<13:50:08, 6.88s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-02 02:02:01,167] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.72 | bwd_microstep: 274.06 | bwd_inner_microstep: 274.04 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1917 +[2025-05-02 02:02:01,650] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.56 | bwd_microstep: 276.70 | bwd_inner_microstep: 276.69 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1894 +[2025-05-02 02:02:02,129] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.50 | bwd_microstep: 275.14 | bwd_inner_microstep: 275.12 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1893 +[2025-05-02 02:02:02,609] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.41 | bwd_microstep: 275.20 | bwd_inner_microstep: 275.18 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1886 +[2025-05-02 02:02:03,090] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.83 | bwd_microstep: 275.13 | bwd_inner_microstep: 275.11 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1889 +[2025-05-02 02:02:03,572] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.59 | bwd_microstep: 274.90 | bwd_inner_microstep: 274.88 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1366 +[2025-05-02 02:02:03,940] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.12 | bwd_microstep: 207.70 | bwd_inner_microstep: 207.56 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1891 +[2025-05-02 02:02:04,424] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.07 | bwd_microstep: 275.73 | bwd_inner_microstep: 275.71 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 02:02:04,909] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.84 | bwd_microstep: 273.68 | bwd_inner_microstep: 273.66 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-02 02:02:05,390] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.28 | bwd_microstep: 274.03 | bwd_inner_microstep: 274.01 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 02:02:05,868] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.58 | bwd_microstep: 272.75 | bwd_inner_microstep: 272.73 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 320 +[2025-05-02 02:02:06,106] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 81.86 | bwd_microstep: 139.25 | bwd_inner_microstep: 139.10 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 02:02:06,587] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.22 | bwd_microstep: 273.49 | bwd_inner_microstep: 273.48 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 02:02:07,064] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.81 | bwd_microstep: 270.85 | bwd_inner_microstep: 270.83 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 02:02:07,542] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.06 | bwd_microstep: 271.40 | bwd_inner_microstep: 271.38 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 02:02:08,125] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.21 | optimizer_step: 16.81 +[2025-05-02 02:02:08,126] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.98 | bwd_microstep: 350.29 | bwd_inner_microstep: 271.51 | bwd_allreduce_microstep: 78.74 | step_microstep: 24.45 +[2025-05-02 02:02:08,127] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2873.10 | bwd: 4260.34 | bwd_inner: 4181.02 | bwd_allreduce: 78.96 | step: 25.32 + 17%|█▋ | 1481/8720 [3:46:41<14:10:30, 7.05s/it] {'loss': 0.7685, 'grad_norm': 9.833698272705078, 'learning_rate': 9.496175151487957e-06, 'epoch': 1.7} + 17%|█▋ | 1481/8720 [3:46:41<14:10:30, 7.05s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 02:02:08,613] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.19 | bwd_microstep: 273.12 | bwd_inner_microstep: 273.10 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 404 +[2025-05-02 02:02:08,840] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 89.67 | bwd_microstep: 121.54 | bwd_inner_microstep: 121.21 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 371 +[2025-05-02 02:02:09,066] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 83.87 | bwd_microstep: 125.97 | bwd_inner_microstep: 125.67 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 350 +[2025-05-02 02:02:09,289] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 90.33 | bwd_microstep: 117.11 | bwd_inner_microstep: 116.81 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-02 02:02:09,770] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.38 | bwd_microstep: 274.48 | bwd_inner_microstep: 274.46 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1121 +[2025-05-02 02:02:10,068] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 118.74 | bwd_microstep: 163.25 | bwd_inner_microstep: 163.21 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-02 02:02:10,548] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.94 | bwd_microstep: 274.01 | bwd_inner_microstep: 273.99 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-02 02:02:11,026] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.35 | bwd_microstep: 274.08 | bwd_inner_microstep: 274.06 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-02 02:02:11,506] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.01 | bwd_microstep: 274.39 | bwd_inner_microstep: 274.37 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 02:02:11,984] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.60 | bwd_microstep: 273.04 | bwd_inner_microstep: 273.02 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 02:02:12,463] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.09 | bwd_microstep: 272.63 | bwd_inner_microstep: 272.61 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 02:02:12,945] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.32 | bwd_microstep: 272.99 | bwd_inner_microstep: 272.97 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 322 +[2025-05-02 02:02:13,161] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 81.04 | bwd_microstep: 119.14 | bwd_inner_microstep: 118.93 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 02:02:13,639] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.58 | bwd_microstep: 272.69 | bwd_inner_microstep: 272.67 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 02:02:14,120] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.30 | bwd_microstep: 272.34 | bwd_inner_microstep: 272.32 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 02:02:14,716] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.22 | optimizer_step: 16.81 +[2025-05-02 02:02:14,716] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.60 | bwd_microstep: 360.62 | bwd_inner_microstep: 271.96 | bwd_allreduce_microstep: 88.61 | step_microstep: 25.13 +[2025-05-02 02:02:14,718] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2541.66 | bwd: 3741.48 | bwd_inner: 3651.63 | bwd_allreduce: 89.10 | step: 26.32 + 17%|█▋ | 1482/8720 [3:46:48<13:53:47, 6.91s/it] {'loss': 0.7176, 'grad_norm': 10.152955055236816, 'learning_rate': 9.495362391916458e-06, 'epoch': 1.7} + 17%|█▋ | 1482/8720 [3:46:48<13:53:47, 6.91s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 02:02:15,200] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.63 | bwd_microstep: 270.35 | bwd_inner_microstep: 270.34 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2013 +[2025-05-02 02:02:15,715] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 200.50 | bwd_microstep: 295.73 | bwd_inner_microstep: 295.71 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 434 +[2025-05-02 02:02:15,932] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 82.83 | bwd_microstep: 118.06 | bwd_inner_microstep: 117.91 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1911 +[2025-05-02 02:02:16,416] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.54 | bwd_microstep: 277.47 | bwd_inner_microstep: 277.45 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1899 +[2025-05-02 02:02:16,902] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.14 | bwd_microstep: 276.11 | bwd_inner_microstep: 276.09 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1385 +[2025-05-02 02:02:17,273] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 142.50 | bwd_microstep: 208.76 | bwd_inner_microstep: 208.74 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-02 02:02:17,759] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.25 | bwd_microstep: 274.33 | bwd_inner_microstep: 274.31 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 02:02:18,242] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.38 | bwd_microstep: 274.02 | bwd_inner_microstep: 274.00 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 02:02:18,725] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.56 | bwd_microstep: 273.43 | bwd_inner_microstep: 273.41 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.16 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 02:02:19,209] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.23 | bwd_microstep: 273.26 | bwd_inner_microstep: 273.24 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 332 +[2025-05-02 02:02:19,438] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 91.90 | bwd_microstep: 120.65 | bwd_inner_microstep: 120.35 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 02:02:19,917] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.66 | bwd_microstep: 272.69 | bwd_inner_microstep: 272.67 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 02:02:20,398] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.22 | bwd_microstep: 273.19 | bwd_inner_microstep: 273.18 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 02:02:20,879] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.47 | bwd_microstep: 272.92 | bwd_inner_microstep: 272.91 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 02:02:21,360] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.86 | bwd_microstep: 272.24 | bwd_inner_microstep: 272.23 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 02:02:21,948] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.26 | optimizer_step: 16.86 +[2025-05-02 02:02:21,949] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.20 | bwd_microstep: 357.32 | bwd_inner_microstep: 272.30 | bwd_allreduce_microstep: 84.96 | step_microstep: 24.66 +[2025-05-02 02:02:21,950] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2786.45 | bwd: 4110.60 | bwd_inner: 4024.94 | bwd_allreduce: 85.21 | step: 25.79 + 17%|█▋ | 1483/8720 [3:46:55<14:05:15, 7.01s/it] {'loss': 0.6891, 'grad_norm': 4.453503131866455, 'learning_rate': 9.494549012148781e-06, 'epoch': 1.7} + 17%|█▋ | 1483/8720 [3:46:55<14:05:15, 7.01s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 02:02:22,431] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.07 | bwd_microstep: 270.27 | bwd_inner_microstep: 270.25 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1929 +[2025-05-02 02:02:22,931] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.02 | bwd_microstep: 288.10 | bwd_inner_microstep: 288.08 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 348 +[2025-05-02 02:02:23,150] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 81.91 | bwd_microstep: 120.62 | bwd_inner_microstep: 120.29 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.10 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1118 +[2025-05-02 02:02:23,447] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 117.23 | bwd_microstep: 163.37 | bwd_inner_microstep: 163.23 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.18 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 844 +[2025-05-02 02:02:23,690] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.55 | bwd_microstep: 132.24 | bwd_inner_microstep: 132.02 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 02:02:24,169] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.29 | bwd_microstep: 272.90 | bwd_inner_microstep: 272.88 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 02:02:24,648] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.58 | bwd_microstep: 272.92 | bwd_inner_microstep: 272.90 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 02:02:25,126] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.02 | bwd_microstep: 272.76 | bwd_inner_microstep: 272.74 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 02:02:25,604] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.14 | bwd_microstep: 272.47 | bwd_inner_microstep: 272.45 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 02:02:26,085] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.24 | bwd_microstep: 272.77 | bwd_inner_microstep: 272.76 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 02:02:26,568] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.18 | bwd_microstep: 272.85 | bwd_inner_microstep: 272.83 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 02:02:27,044] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.84 | bwd_microstep: 271.07 | bwd_inner_microstep: 271.05 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 02:02:27,524] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.03 | bwd_microstep: 272.12 | bwd_inner_microstep: 272.10 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 02:02:28,007] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.92 | bwd_microstep: 272.78 | bwd_inner_microstep: 272.76 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 02:02:28,488] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.16 | bwd_microstep: 271.36 | bwd_inner_microstep: 271.34 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 02:02:29,071] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.20 | optimizer_step: 16.87 +[2025-05-02 02:02:29,072] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.33 | bwd_microstep: 348.57 | bwd_inner_microstep: 271.59 | bwd_allreduce_microstep: 76.93 | step_microstep: 24.75 +[2025-05-02 02:02:29,073] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2746.10 | bwd: 4047.25 | bwd_inner: 3969.33 | bwd_allreduce: 77.34 | step: 25.77 + 17%|█▋ | 1484/8720 [3:47:02<14:09:19, 7.04s/it] {'loss': 0.4992, 'grad_norm': 18.152692794799805, 'learning_rate': 9.493735012297142e-06, 'epoch': 1.7} + 17%|█▋ | 1484/8720 [3:47:02<14:09:19, 7.04s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1891 +[2025-05-02 02:02:29,561] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.03 | bwd_microstep: 274.78 | bwd_inner_microstep: 274.77 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1944 +[2025-05-02 02:02:30,063] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.96 | bwd_microstep: 288.92 | bwd_inner_microstep: 288.91 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1914 +[2025-05-02 02:02:30,546] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.02 | bwd_microstep: 276.43 | bwd_inner_microstep: 276.42 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 864 +[2025-05-02 02:02:30,791] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.18 | bwd_microstep: 133.69 | bwd_inner_microstep: 133.51 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 02:02:31,270] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.31 | bwd_microstep: 273.43 | bwd_inner_microstep: 273.42 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-02 02:02:31,750] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.59 | bwd_microstep: 274.23 | bwd_inner_microstep: 274.22 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 02:02:32,229] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.77 | bwd_microstep: 272.92 | bwd_inner_microstep: 272.90 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 02:02:32,707] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.09 | bwd_microstep: 272.69 | bwd_inner_microstep: 272.67 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 839 +[2025-05-02 02:02:32,938] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 90.45 | bwd_microstep: 126.50 | bwd_inner_microstep: 126.34 | bwd_allreduce_microstep: 0.09 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 02:02:33,415] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.27 | bwd_microstep: 273.23 | bwd_inner_microstep: 273.21 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 02:02:33,894] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.06 | bwd_microstep: 273.07 | bwd_inner_microstep: 273.06 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 02:02:34,371] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.64 | bwd_microstep: 272.38 | bwd_inner_microstep: 272.36 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 02:02:34,845] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.65 | bwd_microstep: 271.43 | bwd_inner_microstep: 271.41 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 319 +[2025-05-02 02:02:35,053] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 74.51 | bwd_microstep: 119.72 | bwd_inner_microstep: 119.50 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.09 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 832 +[2025-05-02 02:02:35,290] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 92.21 | bwd_microstep: 130.72 | bwd_inner_microstep: 130.59 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 02:02:35,852] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.04 | optimizer_gradients: 2.22 | optimizer_step: 16.84 +[2025-05-02 02:02:35,853] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.98 | bwd_microstep: 337.48 | bwd_inner_microstep: 271.33 | bwd_allreduce_microstep: 66.11 | step_microstep: 23.82 +[2025-05-02 02:02:35,854] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2623.45 | bwd: 3871.69 | bwd_inner: 3804.73 | bwd_allreduce: 66.40 | step: 24.77 + 17%|█▋ | 1485/8720 [3:47:09<13:59:39, 6.96s/it] {'loss': 0.7517, 'grad_norm': 5.662278652191162, 'learning_rate': 9.492920392473843e-06, 'epoch': 1.7} + 17%|█▋ | 1485/8720 [3:47:09<13:59:39, 6.96s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1850 +[2025-05-02 02:02:36,332] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.14 | bwd_microstep: 270.32 | bwd_inner_microstep: 270.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 464 +[2025-05-02 02:02:36,529] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 68.25 | bwd_microstep: 115.85 | bwd_inner_microstep: 115.73 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 02:02:37,005] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.91 | bwd_microstep: 273.10 | bwd_inner_microstep: 273.08 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 02:02:37,480] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.67 | bwd_microstep: 272.55 | bwd_inner_microstep: 272.53 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 326 +[2025-05-02 02:02:37,693] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 75.86 | bwd_microstep: 123.94 | bwd_inner_microstep: 123.80 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 02:02:38,169] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.56 | bwd_microstep: 272.71 | bwd_inner_microstep: 272.69 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 02:02:38,644] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.90 | bwd_microstep: 272.15 | bwd_inner_microstep: 272.14 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 02:02:39,120] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.17 | bwd_microstep: 272.81 | bwd_inner_microstep: 272.80 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 02:02:39,597] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.25 | bwd_microstep: 273.05 | bwd_inner_microstep: 273.03 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 02:02:40,074] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.30 | bwd_microstep: 272.79 | bwd_inner_microstep: 272.77 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 02:02:40,551] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.80 | bwd_microstep: 272.49 | bwd_inner_microstep: 272.47 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 02:02:41,027] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.57 | bwd_microstep: 272.71 | bwd_inner_microstep: 272.69 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 02:02:41,503] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.76 | bwd_microstep: 272.21 | bwd_inner_microstep: 272.20 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 02:02:41,978] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.20 | bwd_microstep: 272.35 | bwd_inner_microstep: 272.33 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 02:02:42,453] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.09 | bwd_microstep: 271.05 | bwd_inner_microstep: 271.03 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 02:02:43,018] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.04 | optimizer_gradients: 2.27 | optimizer_step: 16.83 +[2025-05-02 02:02:43,018] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.54 | bwd_microstep: 338.10 | bwd_inner_microstep: 271.67 | bwd_allreduce_microstep: 66.38 | step_microstep: 23.85 +[2025-05-02 02:02:43,019] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2779.70 | bwd: 4118.23 | bwd_inner: 4051.31 | bwd_allreduce: 66.56 | step: 24.59 + 17%|█▋ | 1486/8720 [3:47:16<14:06:51, 7.02s/it] {'loss': 0.7574, 'grad_norm': 18.53557014465332, 'learning_rate': 9.49210515279127e-06, 'epoch': 1.7} + 17%|█▋ | 1486/8720 [3:47:16<14:06:51, 7.02s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 02:02:43,496] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.04 | bwd_microstep: 270.05 | bwd_inner_microstep: 270.03 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1990 +[2025-05-02 02:02:44,003] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 197.89 | bwd_microstep: 293.66 | bwd_inner_microstep: 293.64 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1920 +[2025-05-02 02:02:44,484] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.28 | bwd_microstep: 276.61 | bwd_inner_microstep: 276.59 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-02 02:02:44,961] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.33 | bwd_microstep: 273.43 | bwd_inner_microstep: 273.41 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 02:02:45,438] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.57 | bwd_microstep: 273.36 | bwd_inner_microstep: 273.34 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-02 02:02:45,915] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.83 | bwd_microstep: 273.84 | bwd_inner_microstep: 273.82 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-02 02:02:46,395] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.22 | bwd_microstep: 273.92 | bwd_inner_microstep: 273.90 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 02:02:46,873] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.74 | bwd_microstep: 272.71 | bwd_inner_microstep: 272.69 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 02:02:47,356] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.28 | bwd_microstep: 273.34 | bwd_inner_microstep: 273.32 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 02:02:47,835] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.67 | bwd_microstep: 272.80 | bwd_inner_microstep: 272.79 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.16 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 02:02:48,316] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.70 | bwd_microstep: 272.49 | bwd_inner_microstep: 272.48 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 02:02:48,795] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.85 | bwd_microstep: 272.10 | bwd_inner_microstep: 272.09 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1344 +[2025-05-02 02:02:49,157] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.80 | bwd_microstep: 204.43 | bwd_inner_microstep: 204.42 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 02:02:49,634] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.73 | bwd_microstep: 271.17 | bwd_inner_microstep: 271.16 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 02:02:50,109] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.12 | bwd_microstep: 271.35 | bwd_inner_microstep: 271.33 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 02:02:50,677] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.30 | optimizer_step: 17.03 +[2025-05-02 02:02:50,677] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.57 | bwd_microstep: 339.29 | bwd_inner_microstep: 271.99 | bwd_allreduce_microstep: 67.26 | step_microstep: 24.34 +[2025-05-02 02:02:50,678] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2977.31 | bwd: 4384.58 | bwd_inner: 4317.01 | bwd_allreduce: 67.34 | step: 25.20 + 17%|█▋ | 1487/8720 [3:47:24<14:29:43, 7.21s/it] {'loss': 0.6706, 'grad_norm': 11.68614673614502, 'learning_rate': 9.491289293361897e-06, 'epoch': 1.71} + 17%|█▋ | 1487/8720 [3:47:24<14:29:43, 7.21s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 02:02:51,156] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.47 | bwd_microstep: 270.15 | bwd_inner_microstep: 270.13 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 383 +[2025-05-02 02:02:51,370] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 75.87 | bwd_microstep: 123.32 | bwd_inner_microstep: 123.02 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1386 +[2025-05-02 02:02:51,736] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 143.14 | bwd_microstep: 208.34 | bwd_inner_microstep: 208.23 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1889 +[2025-05-02 02:02:52,215] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.88 | bwd_microstep: 275.12 | bwd_inner_microstep: 275.10 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 867 +[2025-05-02 02:02:52,460] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.08 | bwd_microstep: 134.22 | bwd_inner_microstep: 134.20 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-02 02:02:52,939] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.32 | bwd_microstep: 274.32 | bwd_inner_microstep: 274.31 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-02 02:02:53,416] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.00 | bwd_microstep: 273.46 | bwd_inner_microstep: 273.44 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 847 +[2025-05-02 02:02:53,657] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.26 | bwd_microstep: 132.30 | bwd_inner_microstep: 132.15 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 02:02:54,134] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.72 | bwd_microstep: 273.38 | bwd_inner_microstep: 273.36 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 02:02:54,612] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.84 | bwd_microstep: 273.73 | bwd_inner_microstep: 273.71 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1356 +[2025-05-02 02:02:54,975] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.48 | bwd_microstep: 206.09 | bwd_inner_microstep: 206.07 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 320 +[2025-05-02 02:02:55,179] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 72.15 | bwd_microstep: 118.05 | bwd_inner_microstep: 117.86 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 02:02:55,654] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.94 | bwd_microstep: 270.95 | bwd_inner_microstep: 270.93 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 02:02:56,128] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.03 | bwd_microstep: 271.24 | bwd_inner_microstep: 271.22 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 02:02:56,604] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.43 | bwd_microstep: 271.31 | bwd_inner_microstep: 271.30 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 02:02:57,173] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.55 | optimizer_step: 17.06 +[2025-05-02 02:02:57,174] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.82 | bwd_microstep: 340.93 | bwd_inner_microstep: 271.58 | bwd_allreduce_microstep: 69.30 | step_microstep: 24.66 +[2025-05-02 02:02:57,175] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2502.14 | bwd: 3716.98 | bwd_inner: 3646.78 | bwd_allreduce: 69.64 | step: 25.63 + 17%|█▋ | 1488/8720 [3:47:30<14:03:38, 7.00s/it] {'loss': 0.6378, 'grad_norm': 9.623607635498047, 'learning_rate': 9.490472814298283e-06, 'epoch': 1.71} + 17%|█▋ | 1488/8720 [3:47:30<14:03:38, 7.00s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 02:02:57,653] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.47 | bwd_microstep: 270.00 | bwd_inner_microstep: 269.98 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 1092 +[2025-05-02 02:02:57,937] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 107.63 | bwd_microstep: 160.86 | bwd_inner_microstep: 160.79 | bwd_allreduce_microstep: 0.03 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1913 +[2025-05-02 02:02:58,417] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.39 | bwd_microstep: 276.01 | bwd_inner_microstep: 275.99 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1922 +[2025-05-02 02:02:58,914] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 194.57 | bwd_microstep: 287.05 | bwd_inner_microstep: 287.04 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1130 +[2025-05-02 02:02:59,209] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 115.93 | bwd_microstep: 163.80 | bwd_inner_microstep: 163.59 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 342 +[2025-05-02 02:02:59,423] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 78.01 | bwd_microstep: 121.41 | bwd_inner_microstep: 121.28 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 02:02:59,900] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.02 | bwd_microstep: 272.90 | bwd_inner_microstep: 272.88 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 02:03:00,376] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.92 | bwd_microstep: 272.15 | bwd_inner_microstep: 272.13 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.07 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 02:03:00,854] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.07 | bwd_microstep: 272.29 | bwd_inner_microstep: 272.27 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 02:03:01,334] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.16 | bwd_microstep: 272.58 | bwd_inner_microstep: 272.56 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 02:03:01,815] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.87 | bwd_microstep: 272.42 | bwd_inner_microstep: 272.40 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 322 +[2025-05-02 02:03:02,056] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 91.07 | bwd_microstep: 131.22 | bwd_inner_microstep: 130.97 | bwd_allreduce_microstep: 0.08 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 02:03:02,533] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.63 | bwd_microstep: 271.96 | bwd_inner_microstep: 271.94 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 02:03:03,013] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.04 | bwd_microstep: 272.04 | bwd_inner_microstep: 272.02 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 02:03:03,492] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.60 | bwd_microstep: 271.13 | bwd_inner_microstep: 271.11 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 02:03:04,080] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.31 | optimizer_step: 17.15 +[2025-05-02 02:03:04,080] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.32 | bwd_microstep: 355.11 | bwd_inner_microstep: 272.89 | bwd_allreduce_microstep: 82.16 | step_microstep: 25.15 +[2025-05-02 02:03:04,082] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2655.33 | bwd: 3942.99 | bwd_inner: 3859.93 | bwd_allreduce: 82.53 | step: 26.16 + 17%|█▋ | 1489/8720 [3:47:37<14:00:15, 6.97s/it] {'loss': 0.6638, 'grad_norm': 7.821873188018799, 'learning_rate': 9.489655715713076e-06, 'epoch': 1.71} + 17%|█▋ | 1489/8720 [3:47:37<14:00:15, 6.97s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 02:03:04,564] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.36 | bwd_microstep: 270.31 | bwd_inner_microstep: 270.29 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1920 +[2025-05-02 02:03:05,051] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.91 | bwd_microstep: 276.67 | bwd_inner_microstep: 276.66 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1889 +[2025-05-02 02:03:05,534] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.90 | bwd_microstep: 274.34 | bwd_inner_microstep: 274.32 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-02 02:03:06,016] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.55 | bwd_microstep: 273.99 | bwd_inner_microstep: 273.97 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-02 02:03:06,502] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.91 | bwd_microstep: 274.35 | bwd_inner_microstep: 274.33 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-02 02:03:06,988] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.60 | bwd_microstep: 273.69 | bwd_inner_microstep: 273.67 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 02:03:07,470] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.03 | bwd_microstep: 273.96 | bwd_inner_microstep: 273.94 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-02 02:03:07,951] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.73 | bwd_microstep: 273.08 | bwd_inner_microstep: 273.06 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 02:03:08,430] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.89 | bwd_microstep: 273.00 | bwd_inner_microstep: 272.98 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 02:03:08,909] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.60 | bwd_microstep: 272.34 | bwd_inner_microstep: 272.33 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 02:03:09,388] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.65 | bwd_microstep: 272.61 | bwd_inner_microstep: 272.59 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 02:03:09,866] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.34 | bwd_microstep: 271.21 | bwd_inner_microstep: 271.19 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 02:03:10,345] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.60 | bwd_microstep: 271.19 | bwd_inner_microstep: 271.17 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 02:03:10,823] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.07 | bwd_microstep: 271.43 | bwd_inner_microstep: 271.41 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 02:03:11,298] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.15 | bwd_microstep: 271.06 | bwd_inner_microstep: 271.04 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1939 +[2025-05-02 02:03:11,890] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.31 | optimizer_step: 17.26 +[2025-05-02 02:03:11,890] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.24 | bwd_microstep: 355.95 | bwd_inner_microstep: 289.27 | bwd_allreduce_microstep: 66.63 | step_microstep: 25.58 +[2025-05-02 02:03:11,891] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 3028.16 | bwd: 4449.18 | bwd_inner: 4382.23 | bwd_allreduce: 66.72 | step: 26.37 + 17%|█▋ | 1490/8720 [3:47:45<14:30:20, 7.22s/it] {'loss': 0.7852, 'grad_norm': 10.355767250061035, 'learning_rate': 9.488837997719e-06, 'epoch': 1.71} + 17%|█▋ | 1490/8720 [3:47:45<14:30:20, 7.22s/it]dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 888 +[2025-05-02 02:03:12,143] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 97.25 | bwd_microstep: 135.68 | bwd_inner_microstep: 135.46 | bwd_allreduce_microstep: 0.09 | step_microstep: 0.09 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 341 +[2025-05-02 02:03:12,345] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 68.24 | bwd_microstep: 120.11 | bwd_inner_microstep: 119.83 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-02 02:03:12,823] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.10 | bwd_microstep: 274.29 | bwd_inner_microstep: 274.27 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 02:03:13,301] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.48 | bwd_microstep: 273.09 | bwd_inner_microstep: 273.07 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1358 +[2025-05-02 02:03:13,665] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.05 | bwd_microstep: 207.02 | bwd_inner_microstep: 207.00 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 843 +[2025-05-02 02:03:13,905] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.60 | bwd_microstep: 132.33 | bwd_inner_microstep: 132.11 | bwd_allreduce_microstep: 0.08 | step_microstep: 0.09 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 836 +[2025-05-02 02:03:14,138] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 91.89 | bwd_microstep: 126.20 | bwd_inner_microstep: 125.94 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 02:03:14,614] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.57 | bwd_microstep: 272.41 | bwd_inner_microstep: 272.39 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 02:03:15,089] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.74 | bwd_microstep: 272.12 | bwd_inner_microstep: 272.10 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 02:03:15,565] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.25 | bwd_microstep: 272.67 | bwd_inner_microstep: 272.65 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.16 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 02:03:16,043] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.93 | bwd_microstep: 272.34 | bwd_inner_microstep: 272.32 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 02:03:16,519] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.71 | bwd_microstep: 271.38 | bwd_inner_microstep: 271.36 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1345 +[2025-05-02 02:03:16,883] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.88 | bwd_microstep: 205.68 | bwd_inner_microstep: 205.55 | bwd_allreduce_microstep: 0.04 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 02:03:17,361] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.62 | bwd_microstep: 272.68 | bwd_inner_microstep: 272.67 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 02:03:17,841] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.95 | bwd_microstep: 271.22 | bwd_inner_microstep: 271.20 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 02:03:18,417] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.23 | optimizer_step: 16.89 +[2025-05-02 02:03:18,418] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.90 | bwd_microstep: 346.12 | bwd_inner_microstep: 271.65 | bwd_allreduce_microstep: 74.42 | step_microstep: 24.18 +[2025-05-02 02:03:18,419] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2518.88 | bwd: 3725.42 | bwd_inner: 3649.74 | bwd_allreduce: 74.91 | step: 25.40 + 17%|█▋ | 1491/8720 [3:47:52<14:05:05, 7.01s/it] {'loss': 0.6723, 'grad_norm': 18.092496871948242, 'learning_rate': 9.488019660428873e-06, 'epoch': 1.71} + 17%|█▋ | 1491/8720 [3:47:52<14:05:05, 7.01s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 434 +[2025-05-02 02:03:18,619] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 67.99 | bwd_microstep: 113.96 | bwd_inner_microstep: 113.82 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1917 +[2025-05-02 02:03:19,100] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.41 | bwd_microstep: 276.88 | bwd_inner_microstep: 276.87 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 891 +[2025-05-02 02:03:19,350] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 99.08 | bwd_microstep: 135.90 | bwd_inner_microstep: 135.80 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.08 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1128 +[2025-05-02 02:03:19,646] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 118.16 | bwd_microstep: 163.56 | bwd_inner_microstep: 163.49 | bwd_allreduce_microstep: 0.03 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1897 +[2025-05-02 02:03:20,126] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.79 | bwd_microstep: 275.36 | bwd_inner_microstep: 275.35 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 02:03:20,603] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.68 | bwd_microstep: 272.80 | bwd_inner_microstep: 272.78 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-02 02:03:21,082] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.19 | bwd_microstep: 274.32 | bwd_inner_microstep: 274.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1367 +[2025-05-02 02:03:21,449] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 144.33 | bwd_microstep: 207.18 | bwd_inner_microstep: 207.15 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 02:03:21,925] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.54 | bwd_microstep: 273.05 | bwd_inner_microstep: 273.04 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 02:03:22,403] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.48 | bwd_microstep: 272.70 | bwd_inner_microstep: 272.68 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 02:03:22,879] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.09 | bwd_microstep: 272.37 | bwd_inner_microstep: 272.35 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 02:03:23,356] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.92 | bwd_microstep: 272.25 | bwd_inner_microstep: 272.23 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 02:03:23,831] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.02 | bwd_microstep: 272.12 | bwd_inner_microstep: 272.11 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 02:03:24,305] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.71 | bwd_microstep: 271.04 | bwd_inner_microstep: 271.02 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 368 +[2025-05-02 02:03:24,520] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 79.66 | bwd_microstep: 121.11 | bwd_inner_microstep: 120.98 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-02 02:03:25,089] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.04 | optimizer_gradients: 2.19 | optimizer_step: 16.85 +[2025-05-02 02:03:25,089] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.66 | bwd_microstep: 342.17 | bwd_inner_microstep: 273.69 | bwd_allreduce_microstep: 68.44 | step_microstep: 23.80 +[2025-05-02 02:03:25,091] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2586.45 | bwd: 3816.85 | bwd_inner: 3747.71 | bwd_allreduce: 68.70 | step: 24.67 + 17%|█▋ | 1492/8720 [3:47:58<13:52:35, 6.91s/it] {'loss': 0.8627, 'grad_norm': 7.693408966064453, 'learning_rate': 9.487200703955596e-06, 'epoch': 1.71} + 17%|█▋ | 1492/8720 [3:47:58<13:52:35, 6.91s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 02:03:25,570] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.96 | bwd_microstep: 271.73 | bwd_inner_microstep: 271.72 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1947 +[2025-05-02 02:03:26,071] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 197.09 | bwd_microstep: 289.24 | bwd_inner_microstep: 289.22 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 388 +[2025-05-02 02:03:26,273] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 74.15 | bwd_microstep: 115.43 | bwd_inner_microstep: 115.11 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1917 +[2025-05-02 02:03:26,757] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.71 | bwd_microstep: 277.06 | bwd_inner_microstep: 277.05 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-02 02:03:27,236] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.17 | bwd_microstep: 274.31 | bwd_inner_microstep: 274.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-02 02:03:27,715] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.98 | bwd_microstep: 274.53 | bwd_inner_microstep: 274.51 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 02:03:28,193] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.92 | bwd_microstep: 273.35 | bwd_inner_microstep: 273.33 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 02:03:28,669] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.88 | bwd_microstep: 272.56 | bwd_inner_microstep: 272.55 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 02:03:29,146] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.67 | bwd_microstep: 273.31 | bwd_inner_microstep: 273.29 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1355 +[2025-05-02 02:03:29,508] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.03 | bwd_microstep: 206.61 | bwd_inner_microstep: 206.60 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 838 +[2025-05-02 02:03:29,741] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 91.89 | bwd_microstep: 126.75 | bwd_inner_microstep: 126.51 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 02:03:30,219] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.29 | bwd_microstep: 272.72 | bwd_inner_microstep: 272.70 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 02:03:30,696] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.24 | bwd_microstep: 271.72 | bwd_inner_microstep: 271.70 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 02:03:31,172] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.60 | bwd_microstep: 272.52 | bwd_inner_microstep: 272.50 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 02:03:31,647] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.03 | bwd_microstep: 271.43 | bwd_inner_microstep: 271.42 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1911 +[2025-05-02 02:03:32,232] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.29 | optimizer_step: 16.85 +[2025-05-02 02:03:32,232] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.55 | bwd_microstep: 354.05 | bwd_inner_microstep: 277.34 | bwd_allreduce_microstep: 76.65 | step_microstep: 24.69 +[2025-05-02 02:03:32,234] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2770.89 | bwd: 4097.38 | bwd_inner: 4019.92 | bwd_allreduce: 76.97 | step: 25.65 + 17%|█▋ | 1493/8720 [3:48:05<14:00:54, 6.98s/it] {'loss': 0.5256, 'grad_norm': 9.502535820007324, 'learning_rate': 9.486381128412154e-06, 'epoch': 1.71} + 17%|█▋ | 1493/8720 [3:48:05<14:00:54, 6.98s/it]dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 877 +[2025-05-02 02:03:32,488] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 97.95 | bwd_microstep: 135.14 | bwd_inner_microstep: 135.03 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.10 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 860 +[2025-05-02 02:03:32,729] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.62 | bwd_microstep: 133.87 | bwd_inner_microstep: 133.85 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1894 +[2025-05-02 02:03:33,209] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.29 | bwd_microstep: 275.16 | bwd_inner_microstep: 275.15 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1365 +[2025-05-02 02:03:33,571] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.79 | bwd_microstep: 207.24 | bwd_inner_microstep: 207.19 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.09 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 339 +[2025-05-02 02:03:33,780] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 81.25 | bwd_microstep: 114.63 | bwd_inner_microstep: 114.48 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1887 +[2025-05-02 02:03:34,260] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.85 | bwd_microstep: 275.01 | bwd_inner_microstep: 274.99 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1109 +[2025-05-02 02:03:34,556] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 118.96 | bwd_microstep: 162.05 | bwd_inner_microstep: 162.03 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 02:03:35,033] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.50 | bwd_microstep: 273.36 | bwd_inner_microstep: 273.34 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 02:03:35,509] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.45 | bwd_microstep: 272.59 | bwd_inner_microstep: 272.57 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 02:03:35,986] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.20 | bwd_microstep: 272.51 | bwd_inner_microstep: 272.49 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1358 +[2025-05-02 02:03:36,349] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.86 | bwd_microstep: 206.58 | bwd_inner_microstep: 206.54 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 02:03:36,824] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.64 | bwd_microstep: 272.21 | bwd_inner_microstep: 272.20 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 02:03:37,299] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.44 | bwd_microstep: 272.20 | bwd_inner_microstep: 272.18 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 321 +[2025-05-02 02:03:37,534] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 89.02 | bwd_microstep: 129.52 | bwd_inner_microstep: 129.36 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 02:03:38,014] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.60 | bwd_microstep: 272.82 | bwd_inner_microstep: 272.81 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 02:03:38,593] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.22 | optimizer_step: 16.86 +[2025-05-02 02:03:38,594] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.66 | bwd_microstep: 348.90 | bwd_inner_microstep: 271.95 | bwd_allreduce_microstep: 76.89 | step_microstep: 24.56 +[2025-05-02 02:03:38,595] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2459.79 | bwd: 3623.86 | bwd_inner: 3546.25 | bwd_allreduce: 77.16 | step: 25.52 + 17%|█▋ | 1494/8720 [3:48:12<13:38:23, 6.80s/it] {'loss': 0.6741, 'grad_norm': 6.691681385040283, 'learning_rate': 9.48556093391162e-06, 'epoch': 1.71} + 17%|█▋ | 1494/8720 [3:48:12<13:38:23, 6.80s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 02:03:39,077] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.31 | bwd_microstep: 270.55 | bwd_inner_microstep: 270.53 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2084 +[2025-05-02 02:03:39,601] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 202.52 | bwd_microstep: 304.59 | bwd_inner_microstep: 304.57 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1898 +[2025-05-02 02:03:40,082] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.80 | bwd_microstep: 275.64 | bwd_inner_microstep: 275.62 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 875 +[2025-05-02 02:03:40,330] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 98.65 | bwd_microstep: 134.48 | bwd_inner_microstep: 134.36 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-02 02:03:40,808] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.20 | bwd_microstep: 274.61 | bwd_inner_microstep: 274.59 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1890 +[2025-05-02 02:03:41,286] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.99 | bwd_microstep: 274.50 | bwd_inner_microstep: 274.48 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1886 +[2025-05-02 02:03:41,765] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.47 | bwd_microstep: 274.94 | bwd_inner_microstep: 274.92 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 345 +[2025-05-02 02:03:41,970] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 68.36 | bwd_microstep: 123.82 | bwd_inner_microstep: 123.67 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1100 +[2025-05-02 02:03:42,263] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 117.02 | bwd_microstep: 161.59 | bwd_inner_microstep: 161.57 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 02:03:42,741] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.71 | bwd_microstep: 273.36 | bwd_inner_microstep: 273.34 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 839 +[2025-05-02 02:03:42,974] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 92.11 | bwd_microstep: 126.46 | bwd_inner_microstep: 126.44 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 02:03:43,450] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.25 | bwd_microstep: 272.50 | bwd_inner_microstep: 272.49 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 02:03:43,926] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.21 | bwd_microstep: 272.79 | bwd_inner_microstep: 272.77 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 02:03:44,400] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.46 | bwd_microstep: 271.99 | bwd_inner_microstep: 271.97 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 02:03:44,876] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.68 | bwd_microstep: 272.36 | bwd_inner_microstep: 272.34 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 02:03:45,442] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.22 | optimizer_step: 16.84 +[2025-05-02 02:03:45,442] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.58 | bwd_microstep: 338.13 | bwd_inner_microstep: 271.80 | bwd_allreduce_microstep: 66.29 | step_microstep: 23.93 +[2025-05-02 02:03:45,444] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2652.05 | bwd: 3922.34 | bwd_inner: 3855.52 | bwd_allreduce: 66.47 | step: 24.75 + 17%|█▋ | 1495/8720 [3:48:19<13:40:07, 6.81s/it] {'loss': 0.6008, 'grad_norm': 9.87897777557373, 'learning_rate': 9.484740120567151e-06, 'epoch': 1.71} + 17%|█▋ | 1495/8720 [3:48:19<13:40:07, 6.81s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 02:03:45,921] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.63 | bwd_microstep: 270.07 | bwd_inner_microstep: 270.06 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2054 +[2025-05-02 02:03:46,441] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 203.56 | bwd_microstep: 301.99 | bwd_inner_microstep: 301.97 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1883 +[2025-05-02 02:03:46,921] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.18 | bwd_microstep: 274.56 | bwd_inner_microstep: 274.54 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-02 02:03:47,399] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.76 | bwd_microstep: 273.66 | bwd_inner_microstep: 273.64 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-02 02:03:47,877] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.94 | bwd_microstep: 274.21 | bwd_inner_microstep: 274.19 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1359 +[2025-05-02 02:03:48,241] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.69 | bwd_microstep: 206.66 | bwd_inner_microstep: 206.64 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 333 +[2025-05-02 02:03:48,444] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 71.59 | bwd_microstep: 117.17 | bwd_inner_microstep: 116.86 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 02:03:48,919] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.50 | bwd_microstep: 273.19 | bwd_inner_microstep: 273.17 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 837 +[2025-05-02 02:03:49,154] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 92.86 | bwd_microstep: 126.44 | bwd_inner_microstep: 126.26 | bwd_allreduce_microstep: 0.09 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 02:03:49,632] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.22 | bwd_microstep: 272.77 | bwd_inner_microstep: 272.75 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 02:03:50,114] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.03 | bwd_microstep: 272.66 | bwd_inner_microstep: 272.65 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 02:03:50,597] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.10 | bwd_microstep: 273.30 | bwd_inner_microstep: 273.29 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 02:03:51,078] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.78 | bwd_microstep: 271.03 | bwd_inner_microstep: 271.02 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 02:03:51,561] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.15 | bwd_microstep: 272.28 | bwd_inner_microstep: 272.27 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 02:03:52,039] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.49 | bwd_microstep: 270.96 | bwd_inner_microstep: 270.94 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 02:03:52,617] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.22 | optimizer_step: 16.94 +[2025-05-02 02:03:52,617] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.29 | bwd_microstep: 348.17 | bwd_inner_microstep: 271.72 | bwd_allreduce_microstep: 76.40 | step_microstep: 24.67 +[2025-05-02 02:03:52,619] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2770.39 | bwd: 4099.20 | bwd_inner: 4022.01 | bwd_allreduce: 76.72 | step: 25.62 + 17%|█▋ | 1496/8720 [3:48:26<13:53:14, 6.92s/it] {'loss': 0.5497, 'grad_norm': 6.088976860046387, 'learning_rate': 9.483918688491988e-06, 'epoch': 1.72} + 17%|█▋ | 1496/8720 [3:48:26<13:53:14, 6.92s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 02:03:53,099] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.55 | bwd_microstep: 269.96 | bwd_inner_microstep: 269.94 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 462 +[2025-05-02 02:03:53,308] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 74.38 | bwd_microstep: 120.51 | bwd_inner_microstep: 120.38 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1972 +[2025-05-02 02:03:53,811] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 197.73 | bwd_microstep: 291.40 | bwd_inner_microstep: 291.39 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-02 02:03:54,289] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.32 | bwd_microstep: 273.53 | bwd_inner_microstep: 273.51 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 02:03:54,768] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.74 | bwd_microstep: 273.55 | bwd_inner_microstep: 273.53 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 02:03:55,246] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.74 | bwd_microstep: 273.30 | bwd_inner_microstep: 273.28 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 02:03:55,723] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.35 | bwd_microstep: 273.15 | bwd_inner_microstep: 273.13 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 845 +[2025-05-02 02:03:55,962] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.46 | bwd_microstep: 132.12 | bwd_inner_microstep: 132.06 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 02:03:56,437] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.68 | bwd_microstep: 272.73 | bwd_inner_microstep: 272.72 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 02:03:56,914] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.79 | bwd_microstep: 272.75 | bwd_inner_microstep: 272.73 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 02:03:57,391] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.20 | bwd_microstep: 272.69 | bwd_inner_microstep: 272.67 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 02:03:57,870] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.43 | bwd_microstep: 272.51 | bwd_inner_microstep: 272.49 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 02:03:58,351] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.51 | bwd_microstep: 272.61 | bwd_inner_microstep: 272.59 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 02:03:58,833] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.08 | bwd_microstep: 272.80 | bwd_inner_microstep: 272.78 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.15 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 02:03:59,313] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.02 | bwd_microstep: 271.70 | bwd_inner_microstep: 271.68 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 02:03:59,890] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.24 | optimizer_step: 16.88 +[2025-05-02 02:03:59,891] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.30 | bwd_microstep: 347.60 | bwd_inner_microstep: 271.82 | bwd_allreduce_microstep: 75.72 | step_microstep: 24.51 +[2025-05-02 02:03:59,892] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2817.98 | bwd: 4162.94 | bwd_inner: 4086.73 | bwd_allreduce: 75.89 | step: 25.41 + 17%|█▋ | 1497/8720 [3:48:33<14:05:53, 7.03s/it] {'loss': 0.5949, 'grad_norm': 17.140697479248047, 'learning_rate': 9.48309663779946e-06, 'epoch': 1.72} + 17%|█▋ | 1497/8720 [3:48:33<14:05:53, 7.03s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1903 +[2025-05-02 02:04:00,494] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.35 | bwd_microstep: 275.01 | bwd_inner_microstep: 275.00 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1994 +[2025-05-02 02:04:01,002] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 197.99 | bwd_microstep: 293.97 | bwd_inner_microstep: 293.95 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1982 +[2025-05-02 02:04:01,505] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 196.30 | bwd_microstep: 292.13 | bwd_inner_microstep: 292.12 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 342 +[2025-05-02 02:04:01,713] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 77.30 | bwd_microstep: 117.06 | bwd_inner_microstep: 116.75 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-02 02:04:02,191] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.64 | bwd_microstep: 273.72 | bwd_inner_microstep: 273.70 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 02:04:02,672] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.10 | bwd_microstep: 272.82 | bwd_inner_microstep: 272.81 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 02:04:03,153] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.04 | bwd_microstep: 272.92 | bwd_inner_microstep: 272.90 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 330 +[2025-05-02 02:04:03,376] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 86.62 | bwd_microstep: 120.14 | bwd_inner_microstep: 119.99 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 843 +[2025-05-02 02:04:03,620] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.68 | bwd_microstep: 132.43 | bwd_inner_microstep: 132.37 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 02:04:04,099] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.32 | bwd_microstep: 272.95 | bwd_inner_microstep: 272.93 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 02:04:04,579] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.61 | bwd_microstep: 272.44 | bwd_inner_microstep: 272.42 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 322 +[2025-05-02 02:04:04,810] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 86.40 | bwd_microstep: 129.37 | bwd_inner_microstep: 129.10 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 834 +[2025-05-02 02:04:05,050] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 97.53 | bwd_microstep: 125.89 | bwd_inner_microstep: 125.82 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 02:04:05,530] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.34 | bwd_microstep: 272.89 | bwd_inner_microstep: 272.88 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 02:04:06,009] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.77 | bwd_microstep: 271.18 | bwd_inner_microstep: 271.16 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1345 +[2025-05-02 02:04:06,477] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.20 | optimizer_step: 16.90 +[2025-05-02 02:04:06,477] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.10 | bwd_microstep: 281.78 | bwd_inner_microstep: 205.82 | bwd_allreduce_microstep: 75.90 | step_microstep: 24.64 +[2025-05-02 02:04:06,478] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2488.72 | bwd: 3676.79 | bwd_inner: 3599.88 | bwd_allreduce: 76.29 | step: 25.59 + 17%|█▋ | 1498/8720 [3:48:40<13:49:51, 6.89s/it] {'loss': 0.68, 'grad_norm': 22.869447708129883, 'learning_rate': 9.482273968602977e-06, 'epoch': 1.72} + 17%|█▋ | 1498/8720 [3:48:40<13:49:51, 6.89s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 02:04:06,960] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.09 | bwd_microstep: 270.48 | bwd_inner_microstep: 270.46 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1957 +[2025-05-02 02:04:07,463] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.86 | bwd_microstep: 289.90 | bwd_inner_microstep: 289.89 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1930 +[2025-05-02 02:04:07,963] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.46 | bwd_microstep: 287.59 | bwd_inner_microstep: 287.57 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 375 +[2025-05-02 02:04:08,189] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 86.70 | bwd_microstep: 122.62 | bwd_inner_microstep: 122.35 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1380 +[2025-05-02 02:04:08,558] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 142.02 | bwd_microstep: 208.46 | bwd_inner_microstep: 208.30 | bwd_allreduce_microstep: 0.08 | step_microstep: 0.10 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 837 +[2025-05-02 02:04:08,797] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.92 | bwd_microstep: 125.99 | bwd_inner_microstep: 125.89 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-02 02:04:09,276] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.16 | bwd_microstep: 273.18 | bwd_inner_microstep: 273.16 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 02:04:09,756] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.10 | bwd_microstep: 272.65 | bwd_inner_microstep: 272.63 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 02:04:10,235] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.10 | bwd_microstep: 273.16 | bwd_inner_microstep: 273.14 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 02:04:10,715] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.35 | bwd_microstep: 272.83 | bwd_inner_microstep: 272.81 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 02:04:11,198] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.16 | bwd_microstep: 273.02 | bwd_inner_microstep: 273.01 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 02:04:11,677] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.78 | bwd_microstep: 272.53 | bwd_inner_microstep: 272.52 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 02:04:12,155] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.05 | bwd_microstep: 272.27 | bwd_inner_microstep: 272.25 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 02:04:12,635] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.16 | bwd_microstep: 272.53 | bwd_inner_microstep: 272.51 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 02:04:13,114] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.06 | bwd_microstep: 272.12 | bwd_inner_microstep: 272.10 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.17 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 02:04:13,695] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.26 | optimizer_step: 17.06 +[2025-05-02 02:04:13,695] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.15 | bwd_microstep: 350.83 | bwd_inner_microstep: 271.42 | bwd_allreduce_microstep: 79.36 | step_microstep: 25.03 +[2025-05-02 02:04:13,697] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2782.74 | bwd: 4110.21 | bwd_inner: 4030.07 | bwd_allreduce: 79.72 | step: 26.09 + 17%|█▋ | 1499/8720 [3:48:47<14:01:26, 6.99s/it] {'loss': 0.7941, 'grad_norm': 8.939074516296387, 'learning_rate': 9.481450681016042e-06, 'epoch': 1.72} + 17%|█▋ | 1499/8720 [3:48:47<14:01:26, 6.99s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1904 +[2025-05-02 02:04:14,185] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.84 | bwd_microstep: 275.00 | bwd_inner_microstep: 274.98 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-02 02:04:14,667] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.80 | bwd_microstep: 273.65 | bwd_inner_microstep: 273.63 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 02:04:15,150] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.05 | bwd_microstep: 273.45 | bwd_inner_microstep: 273.43 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 02:04:15,630] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.16 | bwd_microstep: 273.05 | bwd_inner_microstep: 273.04 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 328 +[2025-05-02 02:04:15,849] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 82.36 | bwd_microstep: 120.78 | bwd_inner_microstep: 120.58 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 02:04:16,328] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.74 | bwd_microstep: 272.59 | bwd_inner_microstep: 272.57 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-02 02:04:16,808] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.22 | bwd_microstep: 273.43 | bwd_inner_microstep: 273.41 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 02:04:17,288] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.70 | bwd_microstep: 272.36 | bwd_inner_microstep: 272.34 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 02:04:17,767] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.86 | bwd_microstep: 272.65 | bwd_inner_microstep: 272.63 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 02:04:18,248] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.70 | bwd_microstep: 272.83 | bwd_inner_microstep: 272.81 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 02:04:18,731] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.75 | bwd_microstep: 272.11 | bwd_inner_microstep: 272.09 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 02:04:19,211] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.80 | bwd_microstep: 270.94 | bwd_inner_microstep: 270.93 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 833 +[2025-05-02 02:04:19,462] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 102.95 | bwd_microstep: 125.53 | bwd_inner_microstep: 125.39 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 02:04:19,943] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.37 | bwd_microstep: 271.27 | bwd_inner_microstep: 271.26 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1341 +[2025-05-02 02:04:20,306] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.75 | bwd_microstep: 204.35 | bwd_inner_microstep: 204.34 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 02:04:20,886] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.28 | optimizer_step: 16.98 +[2025-05-02 02:04:20,887] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.12 | bwd_microstep: 348.10 | bwd_inner_microstep: 271.72 | bwd_allreduce_microstep: 76.33 | step_microstep: 24.95 +[2025-05-02 02:04:20,888] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2779.74 | bwd: 4072.14 | bwd_inner: 3995.21 | bwd_allreduce: 76.54 | step: 25.83 + 17%|█▋ | 1500/8720 [3:48:54<14:08:32, 7.05s/it] {'loss': 0.3642, 'grad_norm': 7.205230712890625, 'learning_rate': 9.480626775152237e-06, 'epoch': 1.72} + 17%|█▋ | 1500/8720 [3:48:54<14:08:32, 7.05s/it][INFO|trainer.py:3503] 2025-05-02 02:04:23,816 >> Saving model checkpoint to work_dirs/internvl_chat_v2_5/ak/checkpoint-1500 +[INFO|configuration_utils.py:472] 2025-05-02 02:04:23,819 >> Configuration saved in work_dirs/internvl_chat_v2_5/ak/checkpoint-1500/config.json +[INFO|configuration_utils.py:807] 2025-05-02 02:04:23,819 >> Configuration saved in work_dirs/internvl_chat_v2_5/ak/checkpoint-1500/generation_config.json +[INFO|modeling_utils.py:2755] 2025-05-02 02:04:29,672 >> Model weights saved in work_dirs/internvl_chat_v2_5/ak/checkpoint-1500/model.safetensors +[INFO|tokenization_utils_base.py:2702] 2025-05-02 02:04:29,674 >> tokenizer config file saved in work_dirs/internvl_chat_v2_5/ak/checkpoint-1500/tokenizer_config.json +[INFO|tokenization_utils_base.py:2711] 2025-05-02 02:04:29,674 >> Special tokens file saved in work_dirs/internvl_chat_v2_5/ak/checkpoint-1500/special_tokens_map.json +[INFO|tokenization_utils_base.py:2762] 2025-05-02 02:04:29,674 >> added tokens file saved in work_dirs/internvl_chat_v2_5/ak/checkpoint-1500/added_tokens.json +[2025-05-02 02:04:29,802] [INFO] [logging.py:96:log_dist] [Rank 0] [Torch] Checkpoint global_step1500 is about to be saved! +[2025-05-02 02:04:29,822] [INFO] [logging.py:96:log_dist] [Rank 0] Saving model checkpoint: work_dirs/internvl_chat_v2_5/ak/checkpoint-1500/global_step1500/mp_rank_00_model_states.pt +[2025-05-02 02:04:29,822] [INFO] [torch_checkpoint_engine.py:21:save] [Torch] Saving work_dirs/internvl_chat_v2_5/ak/checkpoint-1500/global_step1500/mp_rank_00_model_states.pt... +[2025-05-02 02:04:34,477] [INFO] [torch_checkpoint_engine.py:23:save] [Torch] Saved work_dirs/internvl_chat_v2_5/ak/checkpoint-1500/global_step1500/mp_rank_00_model_states.pt. +[2025-05-02 02:04:34,479] [INFO] [torch_checkpoint_engine.py:21:save] [Torch] Saving work_dirs/internvl_chat_v2_5/ak/checkpoint-1500/global_step1500/bf16_zero_pp_rank_0_mp_rank_00_optim_states.pt... +[2025-05-02 02:04:34,724] [INFO] [torch_checkpoint_engine.py:23:save] [Torch] Saved work_dirs/internvl_chat_v2_5/ak/checkpoint-1500/global_step1500/bf16_zero_pp_rank_0_mp_rank_00_optim_states.pt. +[2025-05-02 02:04:34,724] [INFO] [engine.py:3536:_save_zero_checkpoint] zero checkpoint saved work_dirs/internvl_chat_v2_5/ak/checkpoint-1500/global_step1500/bf16_zero_pp_rank_0_mp_rank_00_optim_states.pt +[2025-05-02 02:04:34,724] [INFO] [torch_checkpoint_engine.py:33:commit] [Torch] Checkpoint global_step1500 is ready now! +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 02:04:35,225] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.35 | bwd_microstep: 267.89 | bwd_inner_microstep: 267.87 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1973 +[2025-05-02 02:04:35,726] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.29 | bwd_microstep: 289.03 | bwd_inner_microstep: 289.01 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1918 +[2025-05-02 02:04:36,206] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.40 | bwd_microstep: 274.16 | bwd_inner_microstep: 274.15 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-02 02:04:36,688] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.41 | bwd_microstep: 271.94 | bwd_inner_microstep: 271.92 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-02 02:04:37,162] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.97 | bwd_microstep: 271.64 | bwd_inner_microstep: 271.62 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1892 +[2025-05-02 02:04:37,639] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.38 | bwd_microstep: 272.71 | bwd_inner_microstep: 272.69 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 02:04:38,113] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.26 | bwd_microstep: 270.88 | bwd_inner_microstep: 270.86 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 02:04:38,592] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.41 | bwd_microstep: 270.95 | bwd_inner_microstep: 270.93 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1099 +[2025-05-02 02:04:38,883] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 116.25 | bwd_microstep: 160.18 | bwd_inner_microstep: 160.02 | bwd_allreduce_microstep: 0.09 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 02:04:39,358] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.32 | bwd_microstep: 270.88 | bwd_inner_microstep: 270.86 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 02:04:39,833] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.64 | bwd_microstep: 271.06 | bwd_inner_microstep: 271.04 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 02:04:40,311] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.76 | bwd_microstep: 270.53 | bwd_inner_microstep: 270.51 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 02:04:40,786] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.12 | bwd_microstep: 271.47 | bwd_inner_microstep: 271.46 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 02:04:41,259] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.16 | bwd_microstep: 270.91 | bwd_inner_microstep: 270.90 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1341 +[2025-05-02 02:04:41,617] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.21 | bwd_microstep: 203.20 | bwd_inner_microstep: 203.03 | bwd_allreduce_microstep: 0.09 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 02:04:42,208] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.07 | optimizer_gradients: 2.28 | optimizer_step: 21.42 +[2025-05-02 02:04:42,209] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.16 | bwd_microstep: 355.64 | bwd_inner_microstep: 270.49 | bwd_allreduce_microstep: 85.10 | step_microstep: 30.22 +[2025-05-02 02:04:42,210] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2890.68 | bwd: 4263.10 | bwd_inner: 4177.36 | bwd_allreduce: 85.36 | step: 31.10 + 17%|█▋ | 1501/8720 [3:49:15<22:43:26, 11.33s/it] {'loss': 0.7484, 'grad_norm': 20.22281265258789, 'learning_rate': 9.479802251125229e-06, 'epoch': 1.72} + 17%|█▋ | 1501/8720 [3:49:15<22:43:26, 11.33s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 02:04:42,688] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.33 | bwd_microstep: 269.68 | bwd_inner_microstep: 269.66 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.09 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 448 +[2025-05-02 02:04:42,909] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 86.14 | bwd_microstep: 121.68 | bwd_inner_microstep: 121.50 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1931 +[2025-05-02 02:04:43,411] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 193.94 | bwd_microstep: 286.44 | bwd_inner_microstep: 286.43 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.07 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1928 +[2025-05-02 02:04:43,906] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 193.44 | bwd_microstep: 286.11 | bwd_inner_microstep: 286.09 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1896 +[2025-05-02 02:04:44,385] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.19 | bwd_microstep: 273.68 | bwd_inner_microstep: 273.66 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1891 +[2025-05-02 02:04:44,862] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.22 | bwd_microstep: 273.56 | bwd_inner_microstep: 273.54 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 02:04:45,337] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.16 | bwd_microstep: 271.78 | bwd_inner_microstep: 271.76 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 860 +[2025-05-02 02:04:45,580] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.04 | bwd_microstep: 132.59 | bwd_inner_microstep: 132.57 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 838 +[2025-05-02 02:04:45,811] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 91.39 | bwd_microstep: 125.66 | bwd_inner_microstep: 125.47 | bwd_allreduce_microstep: 0.10 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 02:04:46,286] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.16 | bwd_microstep: 271.65 | bwd_inner_microstep: 271.63 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 02:04:46,762] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.53 | bwd_microstep: 271.29 | bwd_inner_microstep: 271.27 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 324 +[2025-05-02 02:04:46,984] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 83.11 | bwd_microstep: 122.38 | bwd_inner_microstep: 122.07 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 02:04:47,461] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.50 | bwd_microstep: 271.52 | bwd_inner_microstep: 271.50 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1092 +[2025-05-02 02:04:47,755] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 115.39 | bwd_microstep: 160.19 | bwd_inner_microstep: 160.07 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 02:04:48,233] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.86 | bwd_microstep: 271.67 | bwd_inner_microstep: 271.65 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.16 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 02:04:48,820] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.15 | optimizer_step: 16.41 +[2025-05-02 02:04:48,820] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.97 | bwd_microstep: 354.03 | bwd_inner_microstep: 271.14 | bwd_allreduce_microstep: 82.83 | step_microstep: 24.14 +[2025-05-02 02:04:48,822] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2546.03 | bwd: 3764.03 | bwd_inner: 3680.10 | bwd_allreduce: 83.30 | step: 25.49 + 17%|█▋ | 1502/8720 [3:49:22<19:52:57, 9.92s/it] {'loss': 0.8299, 'grad_norm': 13.104962348937988, 'learning_rate': 9.478977109048772e-06, 'epoch': 1.72} + 17%|█▋ | 1502/8720 [3:49:22<19:52:57, 9.92s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 02:04:49,301] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.97 | bwd_microstep: 269.55 | bwd_inner_microstep: 269.53 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1893 +[2025-05-02 02:04:49,783] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.47 | bwd_microstep: 274.17 | bwd_inner_microstep: 274.16 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1893 +[2025-05-02 02:04:50,264] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.01 | bwd_microstep: 274.18 | bwd_inner_microstep: 274.17 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1883 +[2025-05-02 02:04:50,750] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.05 | bwd_microstep: 273.55 | bwd_inner_microstep: 273.53 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-02 02:04:51,228] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.20 | bwd_microstep: 272.98 | bwd_inner_microstep: 272.96 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-02 02:04:51,705] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.85 | bwd_microstep: 272.79 | bwd_inner_microstep: 272.77 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-02 02:04:52,184] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.10 | bwd_microstep: 272.75 | bwd_inner_microstep: 272.73 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 02:04:52,662] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.62 | bwd_microstep: 271.77 | bwd_inner_microstep: 271.76 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 02:04:53,141] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.72 | bwd_microstep: 272.52 | bwd_inner_microstep: 272.50 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.13 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 02:04:53,618] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.55 | bwd_microstep: 271.87 | bwd_inner_microstep: 271.85 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 02:04:54,096] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.54 | bwd_microstep: 272.31 | bwd_inner_microstep: 272.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 02:04:54,576] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.67 | bwd_microstep: 272.10 | bwd_inner_microstep: 272.08 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 02:04:55,055] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.74 | bwd_microstep: 271.78 | bwd_inner_microstep: 271.77 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.17 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 02:04:55,532] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.74 | bwd_microstep: 271.67 | bwd_inner_microstep: 271.65 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 02:04:56,011] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.35 | bwd_microstep: 270.73 | bwd_inner_microstep: 270.71 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 02:04:56,597] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.16 | optimizer_step: 21.40 +[2025-05-02 02:04:56,597] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.63 | bwd_microstep: 351.99 | bwd_inner_microstep: 270.98 | bwd_allreduce_microstep: 80.96 | step_microstep: 29.20 +[2025-05-02 02:04:56,599] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 3012.83 | bwd: 4436.75 | bwd_inner: 4355.46 | bwd_allreduce: 81.05 | step: 30.36 + 17%|█▋ | 1503/8720 [3:49:30<18:35:34, 9.27s/it] {'loss': 0.5694, 'grad_norm': 29.865419387817383, 'learning_rate': 9.47815134903671e-06, 'epoch': 1.72} + 17%|█▋ | 1503/8720 [3:49:30<18:35:34, 9.27s/it]dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1413 +[2025-05-02 02:04:56,978] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 145.56 | bwd_microstep: 211.19 | bwd_inner_microstep: 211.18 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 907 +[2025-05-02 02:04:57,238] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 99.81 | bwd_microstep: 144.05 | bwd_inner_microstep: 143.92 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 362 +[2025-05-02 02:04:57,466] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 82.68 | bwd_microstep: 129.12 | bwd_inner_microstep: 128.97 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1891 +[2025-05-02 02:04:57,945] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.97 | bwd_microstep: 274.12 | bwd_inner_microstep: 274.10 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1889 +[2025-05-02 02:04:58,425] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.83 | bwd_microstep: 274.02 | bwd_inner_microstep: 274.00 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-02 02:04:58,906] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.20 | bwd_microstep: 273.17 | bwd_inner_microstep: 273.15 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-02 02:04:59,391] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.83 | bwd_microstep: 273.17 | bwd_inner_microstep: 273.16 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 02:04:59,873] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.80 | bwd_microstep: 272.62 | bwd_inner_microstep: 272.61 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 02:05:00,352] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.00 | bwd_microstep: 272.58 | bwd_inner_microstep: 272.56 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-02 02:05:00,834] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.74 | bwd_microstep: 272.82 | bwd_inner_microstep: 272.81 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 02:05:01,313] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.05 | bwd_microstep: 273.04 | bwd_inner_microstep: 273.02 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 02:05:01,793] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.69 | bwd_microstep: 271.66 | bwd_inner_microstep: 271.64 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 333 +[2025-05-02 02:05:02,015] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 81.55 | bwd_microstep: 123.71 | bwd_inner_microstep: 123.48 | bwd_allreduce_microstep: 0.09 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 02:05:02,493] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.53 | bwd_microstep: 272.03 | bwd_inner_microstep: 272.01 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 02:05:02,975] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.77 | bwd_microstep: 272.62 | bwd_inner_microstep: 272.60 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 02:05:03,551] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.14 | optimizer_step: 16.28 +[2025-05-02 02:05:03,552] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.26 | bwd_microstep: 347.56 | bwd_inner_microstep: 271.19 | bwd_allreduce_microstep: 76.32 | step_microstep: 23.95 +[2025-05-02 02:05:03,553] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2672.90 | bwd: 3957.55 | bwd_inner: 3880.49 | bwd_allreduce: 76.57 | step: 24.94 + 17%|█▋ | 1504/8720 [3:49:37<17:11:43, 8.58s/it] {'loss': 0.7162, 'grad_norm': 6.403658866882324, 'learning_rate': 9.477324971202963e-06, 'epoch': 1.72} + 17%|█▋ | 1504/8720 [3:49:37<17:11:43, 8.58s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 316 +[2025-05-02 02:05:03,771] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 78.99 | bwd_microstep: 118.05 | bwd_inner_microstep: 117.88 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1944 +[2025-05-02 02:05:04,271] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.73 | bwd_microstep: 287.51 | bwd_inner_microstep: 287.49 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 389 +[2025-05-02 02:05:04,475] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 72.14 | bwd_microstep: 118.52 | bwd_inner_microstep: 118.39 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1927 +[2025-05-02 02:05:04,971] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 194.82 | bwd_microstep: 286.33 | bwd_inner_microstep: 286.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1907 +[2025-05-02 02:05:05,452] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.45 | bwd_microstep: 275.21 | bwd_inner_microstep: 275.19 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1362 +[2025-05-02 02:05:05,814] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.06 | bwd_microstep: 205.93 | bwd_inner_microstep: 205.91 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 02:05:06,291] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.64 | bwd_microstep: 272.78 | bwd_inner_microstep: 272.76 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 02:05:06,766] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.26 | bwd_microstep: 271.65 | bwd_inner_microstep: 271.64 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 02:05:07,244] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.17 | bwd_microstep: 272.16 | bwd_inner_microstep: 272.14 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 02:05:07,725] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.68 | bwd_microstep: 271.66 | bwd_inner_microstep: 271.64 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 02:05:08,201] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.19 | bwd_microstep: 271.60 | bwd_inner_microstep: 271.58 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 839 +[2025-05-02 02:05:08,437] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.16 | bwd_microstep: 125.56 | bwd_inner_microstep: 125.51 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 02:05:08,914] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.80 | bwd_microstep: 271.48 | bwd_inner_microstep: 271.46 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 02:05:09,393] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.91 | bwd_microstep: 271.19 | bwd_inner_microstep: 271.18 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 02:05:09,873] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.79 | bwd_microstep: 271.23 | bwd_inner_microstep: 271.21 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 02:05:10,450] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.12 | optimizer_step: 16.27 +[2025-05-02 02:05:10,450] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.09 | bwd_microstep: 346.60 | bwd_inner_microstep: 270.72 | bwd_allreduce_microstep: 75.82 | step_microstep: 23.95 +[2025-05-02 02:05:10,452] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2656.54 | bwd: 3937.53 | bwd_inner: 3861.10 | bwd_allreduce: 76.02 | step: 25.00 + 17%|█▋ | 1505/8720 [3:49:44<16:10:57, 8.07s/it] {'loss': 0.7688, 'grad_norm': 9.905653953552246, 'learning_rate': 9.476497975661544e-06, 'epoch': 1.73} + 17%|█▋ | 1505/8720 [3:49:44<16:10:57, 8.07s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 02:05:10,932] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.60 | bwd_microstep: 270.05 | bwd_inner_microstep: 270.03 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1375 +[2025-05-02 02:05:11,300] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 144.07 | bwd_microstep: 207.22 | bwd_inner_microstep: 207.20 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-02 02:05:11,775] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.98 | bwd_microstep: 272.40 | bwd_inner_microstep: 272.38 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 854 +[2025-05-02 02:05:12,018] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 96.53 | bwd_microstep: 132.42 | bwd_inner_microstep: 132.35 | bwd_allreduce_microstep: 0.04 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-02 02:05:12,493] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.57 | bwd_microstep: 272.46 | bwd_inner_microstep: 272.45 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-02 02:05:12,969] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.46 | bwd_microstep: 272.88 | bwd_inner_microstep: 272.86 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 02:05:13,445] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.21 | bwd_microstep: 271.73 | bwd_inner_microstep: 271.71 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 02:05:13,920] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.29 | bwd_microstep: 272.05 | bwd_inner_microstep: 272.03 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 02:05:14,394] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.89 | bwd_microstep: 271.61 | bwd_inner_microstep: 271.59 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 02:05:14,867] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.35 | bwd_microstep: 270.59 | bwd_inner_microstep: 270.57 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 02:05:15,342] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.83 | bwd_microstep: 271.63 | bwd_inner_microstep: 271.61 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 02:05:15,818] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.34 | bwd_microstep: 271.49 | bwd_inner_microstep: 271.47 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 02:05:16,293] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.85 | bwd_microstep: 271.25 | bwd_inner_microstep: 271.23 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 02:05:16,770] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.49 | bwd_microstep: 271.56 | bwd_inner_microstep: 271.54 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 02:05:17,248] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.00 | bwd_microstep: 270.72 | bwd_inner_microstep: 270.70 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 02:05:17,837] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.14 | optimizer_step: 16.26 +[2025-05-02 02:05:17,837] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.49 | bwd_microstep: 355.33 | bwd_inner_microstep: 270.39 | bwd_allreduce_microstep: 84.89 | step_microstep: 23.97 +[2025-05-02 02:05:17,839] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2865.63 | bwd: 4225.41 | bwd_inner: 4140.13 | bwd_allreduce: 85.02 | step: 24.76 + 17%|█▋ | 1506/8720 [3:49:51<15:46:02, 7.87s/it] {'loss': 0.5194, 'grad_norm': 14.37829303741455, 'learning_rate': 9.475670362526548e-06, 'epoch': 1.73} + 17%|█▋ | 1506/8720 [3:49:51<15:46:02, 7.87s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 02:05:18,320] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.22 | bwd_microstep: 269.89 | bwd_inner_microstep: 269.87 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1435 +[2025-05-02 02:05:18,694] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 143.77 | bwd_microstep: 213.73 | bwd_inner_microstep: 213.72 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 349 +[2025-05-02 02:05:18,925] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 76.55 | bwd_microstep: 139.32 | bwd_inner_microstep: 139.01 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-02 02:05:19,401] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.74 | bwd_microstep: 273.01 | bwd_inner_microstep: 272.99 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 856 +[2025-05-02 02:05:19,642] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.13 | bwd_microstep: 132.65 | bwd_inner_microstep: 132.44 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 02:05:20,118] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.94 | bwd_microstep: 272.85 | bwd_inner_microstep: 272.83 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 02:05:20,594] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.14 | bwd_microstep: 273.01 | bwd_inner_microstep: 272.99 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-02 02:05:21,071] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.70 | bwd_microstep: 272.60 | bwd_inner_microstep: 272.58 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 02:05:21,550] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.15 | bwd_microstep: 272.90 | bwd_inner_microstep: 272.88 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 02:05:22,027] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.37 | bwd_microstep: 272.51 | bwd_inner_microstep: 272.49 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 837 +[2025-05-02 02:05:22,268] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 97.35 | bwd_microstep: 126.29 | bwd_inner_microstep: 126.05 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 02:05:22,748] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.17 | bwd_microstep: 272.69 | bwd_inner_microstep: 272.67 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.12 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 318 +[2025-05-02 02:05:22,970] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 88.90 | bwd_microstep: 117.13 | bwd_inner_microstep: 116.86 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 02:05:23,447] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.11 | bwd_microstep: 270.65 | bwd_inner_microstep: 270.64 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 02:05:23,924] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.96 | bwd_microstep: 270.93 | bwd_inner_microstep: 270.91 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 827 +[2025-05-02 02:05:24,271] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.15 | optimizer_step: 16.30 +[2025-05-02 02:05:24,272] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.60 | bwd_microstep: 213.51 | bwd_inner_microstep: 136.32 | bwd_allreduce_microstep: 77.04 | step_microstep: 24.10 +[2025-05-02 02:05:24,273] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2479.50 | bwd: 3663.80 | bwd_inner: 3585.42 | bwd_allreduce: 77.53 | step: 25.30 + 17%|█▋ | 1507/8720 [3:49:58<14:54:10, 7.44s/it] {'loss': 0.6548, 'grad_norm': 11.788830757141113, 'learning_rate': 9.474842131912154e-06, 'epoch': 1.73} + 17%|█▋ | 1507/8720 [3:49:58<14:54:10, 7.44s/it]dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 916 +[2025-05-02 02:05:24,544] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 103.99 | bwd_microstep: 144.91 | bwd_inner_microstep: 144.71 | bwd_allreduce_microstep: 0.09 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1905 +[2025-05-02 02:05:25,027] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.59 | bwd_microstep: 275.75 | bwd_inner_microstep: 275.73 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1893 +[2025-05-02 02:05:25,512] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.94 | bwd_microstep: 275.13 | bwd_inner_microstep: 275.11 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 02:05:25,991] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.65 | bwd_microstep: 272.99 | bwd_inner_microstep: 272.97 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 02:05:26,471] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.81 | bwd_microstep: 272.62 | bwd_inner_microstep: 272.60 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 331 +[2025-05-02 02:05:26,699] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 89.14 | bwd_microstep: 121.38 | bwd_inner_microstep: 121.05 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 02:05:27,177] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.72 | bwd_microstep: 272.36 | bwd_inner_microstep: 272.34 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 02:05:27,655] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.10 | bwd_microstep: 272.81 | bwd_inner_microstep: 272.79 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 02:05:28,134] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.04 | bwd_microstep: 271.83 | bwd_inner_microstep: 271.81 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 844 +[2025-05-02 02:05:28,378] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.32 | bwd_microstep: 132.13 | bwd_inner_microstep: 132.05 | bwd_allreduce_microstep: 0.04 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 02:05:28,856] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.45 | bwd_microstep: 272.61 | bwd_inner_microstep: 272.59 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 833 +[2025-05-02 02:05:29,094] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 96.86 | bwd_microstep: 125.27 | bwd_inner_microstep: 125.23 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 02:05:29,572] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.64 | bwd_microstep: 272.62 | bwd_inner_microstep: 272.60 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1342 +[2025-05-02 02:05:29,933] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.29 | bwd_microstep: 204.83 | bwd_inner_microstep: 204.78 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 02:05:30,412] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.64 | bwd_microstep: 271.74 | bwd_inner_microstep: 271.72 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 317 +[2025-05-02 02:05:30,763] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.20 | optimizer_step: 16.42 +[2025-05-02 02:05:30,764] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 104.17 | bwd_microstep: 203.19 | bwd_inner_microstep: 136.64 | bwd_allreduce_microstep: 66.43 | step_microstep: 23.71 +[2025-05-02 02:05:30,765] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2512.99 | bwd: 3662.24 | bwd_inner: 3594.88 | bwd_allreduce: 66.75 | step: 24.72 + 17%|█▋ | 1508/8720 [3:50:04<14:19:53, 7.15s/it] {'loss': 0.8475, 'grad_norm': 11.35422134399414, 'learning_rate': 9.474013283932628e-06, 'epoch': 1.73} + 17%|█▋ | 1508/8720 [3:50:04<14:19:53, 7.15s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1925 +[2025-05-02 02:05:31,267] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.58 | bwd_microstep: 285.77 | bwd_inner_microstep: 285.75 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2201 +[2025-05-02 02:05:31,811] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 207.68 | bwd_microstep: 321.90 | bwd_inner_microstep: 321.88 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1909 +[2025-05-02 02:05:32,292] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.03 | bwd_microstep: 275.83 | bwd_inner_microstep: 275.81 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 866 +[2025-05-02 02:05:32,550] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 108.18 | bwd_microstep: 132.44 | bwd_inner_microstep: 132.41 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 02:05:33,025] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.86 | bwd_microstep: 272.20 | bwd_inner_microstep: 272.18 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-02 02:05:33,504] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.14 | bwd_microstep: 273.26 | bwd_inner_microstep: 273.24 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 02:05:33,980] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.40 | bwd_microstep: 272.04 | bwd_inner_microstep: 272.02 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1360 +[2025-05-02 02:05:34,345] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.60 | bwd_microstep: 205.77 | bwd_inner_microstep: 205.75 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 02:05:34,821] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.28 | bwd_microstep: 272.11 | bwd_inner_microstep: 272.09 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 02:05:35,295] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.34 | bwd_microstep: 271.92 | bwd_inner_microstep: 271.90 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 02:05:35,769] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.83 | bwd_microstep: 271.12 | bwd_inner_microstep: 271.11 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 02:05:36,247] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.78 | bwd_microstep: 270.97 | bwd_inner_microstep: 270.95 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 02:05:36,722] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.06 | bwd_microstep: 271.75 | bwd_inner_microstep: 271.73 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 02:05:37,197] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.61 | bwd_microstep: 271.01 | bwd_inner_microstep: 271.00 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 02:05:37,670] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.05 | bwd_microstep: 270.67 | bwd_inner_microstep: 270.66 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 02:05:38,238] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.17 | optimizer_step: 16.41 +[2025-05-02 02:05:38,239] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.45 | bwd_microstep: 337.83 | bwd_inner_microstep: 271.19 | bwd_allreduce_microstep: 66.59 | step_microstep: 23.62 +[2025-05-02 02:05:38,240] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2907.59 | bwd: 4276.62 | bwd_inner: 4209.69 | bwd_allreduce: 66.68 | step: 24.55 + 17%|█▋ | 1509/8720 [3:50:11<14:31:20, 7.25s/it] {'loss': 0.8377, 'grad_norm': 11.89579963684082, 'learning_rate': 9.473183818702322e-06, 'epoch': 1.73} + 17%|█▋ | 1509/8720 [3:50:11<14:31:20, 7.25s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 02:05:38,719] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.33 | bwd_microstep: 270.21 | bwd_inner_microstep: 270.20 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1893 +[2025-05-02 02:05:39,198] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.10 | bwd_microstep: 275.10 | bwd_inner_microstep: 275.08 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1887 +[2025-05-02 02:05:39,678] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.95 | bwd_microstep: 274.85 | bwd_inner_microstep: 274.83 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 02:05:40,159] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.69 | bwd_microstep: 272.75 | bwd_inner_microstep: 272.73 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 02:05:40,637] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.45 | bwd_microstep: 273.05 | bwd_inner_microstep: 273.04 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1097 +[2025-05-02 02:05:40,930] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 117.43 | bwd_microstep: 161.11 | bwd_inner_microstep: 161.03 | bwd_allreduce_microstep: 0.04 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 02:05:41,406] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.03 | bwd_microstep: 272.14 | bwd_inner_microstep: 272.12 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 02:05:41,887] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.70 | bwd_microstep: 272.04 | bwd_inner_microstep: 272.02 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 02:05:42,366] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.70 | bwd_microstep: 272.27 | bwd_inner_microstep: 272.25 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 02:05:42,843] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.16 | bwd_microstep: 271.21 | bwd_inner_microstep: 271.19 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 02:05:43,322] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.82 | bwd_microstep: 271.16 | bwd_inner_microstep: 271.14 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 02:05:43,802] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.36 | bwd_microstep: 270.64 | bwd_inner_microstep: 270.62 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 02:05:44,280] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.08 | bwd_microstep: 271.41 | bwd_inner_microstep: 271.40 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 02:05:44,758] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.79 | bwd_microstep: 270.56 | bwd_inner_microstep: 270.55 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 02:05:45,240] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.93 | bwd_microstep: 271.36 | bwd_inner_microstep: 271.34 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 02:05:45,817] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.13 | optimizer_step: 16.35 +[2025-05-02 02:05:45,818] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.46 | bwd_microstep: 345.62 | bwd_inner_microstep: 271.94 | bwd_allreduce_microstep: 73.64 | step_microstep: 23.47 +[2025-05-02 02:05:45,819] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2949.64 | bwd: 4315.52 | bwd_inner: 4241.48 | bwd_allreduce: 73.77 | step: 24.23 + 17%|█▋ | 1510/8720 [3:50:19<14:43:04, 7.35s/it] {'loss': 0.5422, 'grad_norm': 12.613053321838379, 'learning_rate': 9.47235373633567e-06, 'epoch': 1.73} + 17%|█▋ | 1510/8720 [3:50:19<14:43:04, 7.35s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 02:05:46,297] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.47 | bwd_microstep: 270.19 | bwd_inner_microstep: 270.17 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-02 02:05:46,776] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.69 | bwd_microstep: 273.81 | bwd_inner_microstep: 273.79 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 02:05:47,252] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.91 | bwd_microstep: 272.71 | bwd_inner_microstep: 272.70 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 02:05:47,729] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.57 | bwd_microstep: 272.51 | bwd_inner_microstep: 272.50 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.17 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 834 +[2025-05-02 02:05:47,969] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.91 | bwd_microstep: 125.90 | bwd_inner_microstep: 125.68 | bwd_allreduce_microstep: 0.10 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 02:05:48,446] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.87 | bwd_microstep: 272.08 | bwd_inner_microstep: 272.06 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 02:05:48,925] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.63 | bwd_microstep: 272.35 | bwd_inner_microstep: 272.34 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 02:05:49,403] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.39 | bwd_microstep: 272.44 | bwd_inner_microstep: 272.43 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 02:05:49,882] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.47 | bwd_microstep: 271.13 | bwd_inner_microstep: 271.11 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 02:05:50,364] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.04 | bwd_microstep: 272.14 | bwd_inner_microstep: 272.12 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 02:05:50,841] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.75 | bwd_microstep: 271.56 | bwd_inner_microstep: 271.54 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 02:05:51,320] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.94 | bwd_microstep: 271.82 | bwd_inner_microstep: 271.80 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 316 +[2025-05-02 02:05:51,549] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 87.48 | bwd_microstep: 124.33 | bwd_inner_microstep: 124.12 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 316 +[2025-05-02 02:05:51,772] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 84.63 | bwd_microstep: 122.02 | bwd_inner_microstep: 121.82 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1888 +[2025-05-02 02:05:52,252] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.49 | bwd_microstep: 274.33 | bwd_inner_microstep: 274.31 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-02 02:05:52,844] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.20 | optimizer_step: 16.42 +[2025-05-02 02:05:52,844] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.88 | bwd_microstep: 359.09 | bwd_inner_microstep: 274.03 | bwd_allreduce_microstep: 85.01 | step_microstep: 24.49 +[2025-05-02 02:05:52,846] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2714.77 | bwd: 3998.47 | bwd_inner: 3912.67 | bwd_allreduce: 85.27 | step: 25.52 + 17%|█▋ | 1511/8720 [3:50:26<14:31:24, 7.25s/it] {'loss': 0.2229, 'grad_norm': 6.586512088775635, 'learning_rate': 9.471523036947195e-06, 'epoch': 1.73} + 17%|█▋ | 1511/8720 [3:50:26<14:31:24, 7.25s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 02:05:53,330] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.50 | bwd_microstep: 272.21 | bwd_inner_microstep: 272.19 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1908 +[2025-05-02 02:05:53,815] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.72 | bwd_microstep: 276.13 | bwd_inner_microstep: 276.11 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 361 +[2025-05-02 02:05:54,072] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 96.39 | bwd_microstep: 140.84 | bwd_inner_microstep: 140.69 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.11 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 867 +[2025-05-02 02:05:54,333] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.77 | bwd_microstep: 148.63 | bwd_inner_microstep: 148.32 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-02 02:05:54,813] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.64 | bwd_microstep: 273.56 | bwd_inner_microstep: 273.55 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 02:05:55,295] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.14 | bwd_microstep: 273.26 | bwd_inner_microstep: 273.25 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-02 02:05:55,776] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.35 | bwd_microstep: 273.50 | bwd_inner_microstep: 273.48 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 02:05:56,258] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.39 | bwd_microstep: 273.08 | bwd_inner_microstep: 273.06 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 02:05:56,740] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.24 | bwd_microstep: 272.78 | bwd_inner_microstep: 272.76 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 02:05:57,222] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.08 | bwd_microstep: 273.01 | bwd_inner_microstep: 272.99 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 02:05:57,703] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.66 | bwd_microstep: 272.68 | bwd_inner_microstep: 272.66 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 02:05:58,184] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.35 | bwd_microstep: 272.56 | bwd_inner_microstep: 272.54 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.07 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1353 +[2025-05-02 02:05:58,552] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 142.16 | bwd_microstep: 206.40 | bwd_inner_microstep: 206.23 | bwd_allreduce_microstep: 0.08 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 02:05:59,032] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.11 | bwd_microstep: 272.83 | bwd_inner_microstep: 272.81 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 832 +[2025-05-02 02:05:59,291] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 108.22 | bwd_microstep: 129.50 | bwd_inner_microstep: 129.40 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2018 +[2025-05-02 02:05:59,893] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.21 | optimizer_step: 16.48 +[2025-05-02 02:05:59,893] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 199.77 | bwd_microstep: 363.42 | bwd_inner_microstep: 296.56 | bwd_allreduce_microstep: 66.82 | step_microstep: 23.71 +[2025-05-02 02:05:59,894] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2719.07 | bwd: 3994.50 | bwd_inner: 3926.69 | bwd_allreduce: 67.23 | step: 24.83 + 17%|█▋ | 1512/8720 [3:50:33<14:23:52, 7.19s/it] {'loss': 0.838, 'grad_norm': 7.460364818572998, 'learning_rate': 9.4706917206515e-06, 'epoch': 1.73} + 17%|█▋ | 1512/8720 [3:50:33<14:23:52, 7.19s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1981 +[2025-05-02 02:06:00,405] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 199.14 | bwd_microstep: 291.71 | bwd_inner_microstep: 291.69 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1972 +[2025-05-02 02:06:00,909] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 196.55 | bwd_microstep: 291.37 | bwd_inner_microstep: 291.35 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1896 +[2025-05-02 02:06:01,392] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.00 | bwd_microstep: 275.29 | bwd_inner_microstep: 275.27 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-02 02:06:01,871] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.90 | bwd_microstep: 273.69 | bwd_inner_microstep: 273.67 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-02 02:06:02,349] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.78 | bwd_microstep: 273.68 | bwd_inner_microstep: 273.66 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 847 +[2025-05-02 02:06:02,593] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.81 | bwd_microstep: 132.57 | bwd_inner_microstep: 132.35 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 02:06:03,076] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.03 | bwd_microstep: 273.23 | bwd_inner_microstep: 273.21 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-02 02:06:03,555] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.65 | bwd_microstep: 273.95 | bwd_inner_microstep: 273.94 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 02:06:04,032] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.19 | bwd_microstep: 273.00 | bwd_inner_microstep: 272.98 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 02:06:04,509] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.47 | bwd_microstep: 272.84 | bwd_inner_microstep: 272.82 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 02:06:04,987] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.68 | bwd_microstep: 272.34 | bwd_inner_microstep: 272.32 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 839 +[2025-05-02 02:06:05,219] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 92.06 | bwd_microstep: 126.43 | bwd_inner_microstep: 126.29 | bwd_allreduce_microstep: 0.10 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 02:06:05,696] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.86 | bwd_microstep: 273.30 | bwd_inner_microstep: 273.28 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 02:06:06,174] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.41 | bwd_microstep: 273.08 | bwd_inner_microstep: 273.07 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 02:06:06,650] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.61 | bwd_microstep: 272.23 | bwd_inner_microstep: 272.22 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 02:06:07,214] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.04 | optimizer_gradients: 2.12 | optimizer_step: 16.25 +[2025-05-02 02:06:07,214] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.93 | bwd_microstep: 338.10 | bwd_inner_microstep: 271.97 | bwd_allreduce_microstep: 66.09 | step_microstep: 23.23 +[2025-05-02 02:06:07,216] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2849.80 | bwd: 4186.88 | bwd_inner: 4120.09 | bwd_allreduce: 66.37 | step: 24.05 + 17%|█▋ | 1513/8720 [3:50:40<14:28:26, 7.23s/it] {'loss': 0.6325, 'grad_norm': 9.10265064239502, 'learning_rate': 9.469859787563283e-06, 'epoch': 1.73} + 17%|█▋ | 1513/8720 [3:50:40<14:28:26, 7.23s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-02 02:06:07,697] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.88 | bwd_microstep: 273.21 | bwd_inner_microstep: 273.19 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2053 +[2025-05-02 02:06:08,216] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 201.69 | bwd_microstep: 301.45 | bwd_inner_microstep: 301.43 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1901 +[2025-05-02 02:06:08,700] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.51 | bwd_microstep: 275.47 | bwd_inner_microstep: 275.46 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 341 +[2025-05-02 02:06:08,906] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 73.39 | bwd_microstep: 118.43 | bwd_inner_microstep: 118.27 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-02 02:06:09,384] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.07 | bwd_microstep: 274.23 | bwd_inner_microstep: 274.21 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 341 +[2025-05-02 02:06:09,583] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 67.57 | bwd_microstep: 118.32 | bwd_inner_microstep: 118.19 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 02:06:10,064] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.00 | bwd_microstep: 273.87 | bwd_inner_microstep: 273.85 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-02 02:06:10,541] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.60 | bwd_microstep: 273.47 | bwd_inner_microstep: 273.45 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 02:06:11,018] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.64 | bwd_microstep: 273.51 | bwd_inner_microstep: 273.49 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 02:06:11,495] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.61 | bwd_microstep: 272.95 | bwd_inner_microstep: 272.93 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 02:06:11,976] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.57 | bwd_microstep: 272.72 | bwd_inner_microstep: 272.70 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 02:06:12,454] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.25 | bwd_microstep: 273.41 | bwd_inner_microstep: 273.39 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 02:06:12,931] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.13 | bwd_microstep: 272.68 | bwd_inner_microstep: 272.66 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.16 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 02:06:13,407] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.26 | bwd_microstep: 272.84 | bwd_inner_microstep: 272.82 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 02:06:13,883] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.86 | bwd_microstep: 271.72 | bwd_inner_microstep: 271.70 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 02:06:14,461] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.18 | optimizer_step: 16.24 +[2025-05-02 02:06:14,462] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.92 | bwd_microstep: 351.24 | bwd_inner_microstep: 271.53 | bwd_allreduce_microstep: 79.66 | step_microstep: 23.88 +[2025-05-02 02:06:14,463] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2796.67 | bwd: 4169.56 | bwd_inner: 4089.37 | bwd_allreduce: 79.84 | step: 24.76 + 17%|█▋ | 1514/8720 [3:50:48<14:29:00, 7.24s/it] {'loss': 0.6815, 'grad_norm': 7.0227179527282715, 'learning_rate': 9.469027237797315e-06, 'epoch': 1.74} + 17%|█▋ | 1514/8720 [3:50:48<14:29:00, 7.24s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1897 +[2025-05-02 02:06:14,950] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.60 | bwd_microstep: 275.29 | bwd_inner_microstep: 275.27 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1978 +[2025-05-02 02:06:15,459] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 199.22 | bwd_microstep: 291.88 | bwd_inner_microstep: 291.86 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1896 +[2025-05-02 02:06:15,943] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.36 | bwd_microstep: 275.75 | bwd_inner_microstep: 275.73 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-02 02:06:16,428] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.95 | bwd_microstep: 274.20 | bwd_inner_microstep: 274.18 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-02 02:06:16,910] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.64 | bwd_microstep: 274.06 | bwd_inner_microstep: 274.04 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-02 02:06:17,394] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.65 | bwd_microstep: 274.30 | bwd_inner_microstep: 274.28 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 02:06:17,876] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.15 | bwd_microstep: 273.34 | bwd_inner_microstep: 273.33 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 02:06:18,355] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.13 | bwd_microstep: 272.63 | bwd_inner_microstep: 272.61 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 02:06:18,835] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.98 | bwd_microstep: 273.38 | bwd_inner_microstep: 273.36 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 02:06:19,314] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.79 | bwd_microstep: 273.30 | bwd_inner_microstep: 273.28 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.07 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-02 02:06:19,796] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.62 | bwd_microstep: 273.65 | bwd_inner_microstep: 273.63 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 02:06:20,277] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.03 | bwd_microstep: 272.37 | bwd_inner_microstep: 272.36 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 318 +[2025-05-02 02:06:20,504] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 90.91 | bwd_microstep: 118.75 | bwd_inner_microstep: 118.51 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 02:06:20,981] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.90 | bwd_microstep: 272.19 | bwd_inner_microstep: 272.17 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 02:06:21,460] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.92 | bwd_microstep: 271.67 | bwd_inner_microstep: 271.66 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1953 +[2025-05-02 02:06:22,067] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.16 | optimizer_step: 16.20 +[2025-05-02 02:06:22,068] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 196.20 | bwd_microstep: 365.95 | bwd_inner_microstep: 290.41 | bwd_allreduce_microstep: 75.48 | step_microstep: 23.91 +[2025-05-02 02:06:22,069] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2943.70 | bwd: 4332.74 | bwd_inner: 4256.77 | bwd_allreduce: 75.62 | step: 24.85 + 17%|█▋ | 1515/8720 [3:50:55<14:42:13, 7.35s/it] {'loss': 0.7615, 'grad_norm': 9.289323806762695, 'learning_rate': 9.468194071468458e-06, 'epoch': 1.74} + 17%|█▋ | 1515/8720 [3:50:55<14:42:13, 7.35s/it]dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 849 +[2025-05-02 02:06:22,318] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.25 | bwd_microstep: 132.87 | bwd_inner_microstep: 132.75 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 987 +[2025-05-02 02:06:22,587] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 102.71 | bwd_microstep: 150.58 | bwd_inner_microstep: 150.39 | bwd_allreduce_microstep: 0.10 | step_microstep: 0.09 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 418 +[2025-05-02 02:06:22,814] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 89.20 | bwd_microstep: 121.89 | bwd_inner_microstep: 121.57 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 02:06:23,294] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.73 | bwd_microstep: 272.90 | bwd_inner_microstep: 272.89 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 02:06:23,775] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.72 | bwd_microstep: 273.82 | bwd_inner_microstep: 273.80 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 02:06:24,256] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.31 | bwd_microstep: 273.19 | bwd_inner_microstep: 273.18 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 02:06:24,738] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.70 | bwd_microstep: 273.00 | bwd_inner_microstep: 272.99 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 02:06:25,218] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.60 | bwd_microstep: 272.67 | bwd_inner_microstep: 272.66 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 323 +[2025-05-02 02:06:25,459] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.56 | bwd_microstep: 126.21 | bwd_inner_microstep: 126.03 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 02:06:25,937] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.32 | bwd_microstep: 272.75 | bwd_inner_microstep: 272.73 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 832 +[2025-05-02 02:06:26,177] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.19 | bwd_microstep: 130.34 | bwd_inner_microstep: 130.07 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 02:06:26,654] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.11 | bwd_microstep: 271.76 | bwd_inner_microstep: 271.74 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 02:06:27,133] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.21 | bwd_microstep: 272.01 | bwd_inner_microstep: 271.99 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 02:06:27,613] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.82 | bwd_microstep: 271.44 | bwd_inner_microstep: 271.42 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 02:06:28,093] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.77 | bwd_microstep: 271.40 | bwd_inner_microstep: 271.38 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1921 +[2025-05-02 02:06:28,692] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.11 | optimizer_step: 16.23 +[2025-05-02 02:06:28,693] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.21 | bwd_microstep: 363.38 | bwd_inner_microstep: 287.59 | bwd_allreduce_microstep: 75.73 | step_microstep: 23.92 +[2025-05-02 02:06:28,695] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2556.05 | bwd: 3750.33 | bwd_inner: 3673.30 | bwd_allreduce: 76.25 | step: 24.99 + 17%|█▋ | 1516/8720 [3:51:02<14:16:07, 7.13s/it] {'loss': 0.6979, 'grad_norm': 21.331331253051758, 'learning_rate': 9.467360288691658e-06, 'epoch': 1.74} + 17%|█▋ | 1516/8720 [3:51:02<14:16:07, 7.13s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1894 +[2025-05-02 02:06:29,181] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.19 | bwd_microstep: 275.00 | bwd_inner_microstep: 274.98 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2041 +[2025-05-02 02:06:29,698] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 200.84 | bwd_microstep: 298.34 | bwd_inner_microstep: 298.33 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1897 +[2025-05-02 02:06:30,178] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.60 | bwd_microstep: 275.65 | bwd_inner_microstep: 275.64 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1899 +[2025-05-02 02:06:30,657] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.07 | bwd_microstep: 275.28 | bwd_inner_microstep: 275.26 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1893 +[2025-05-02 02:06:31,137] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.28 | bwd_microstep: 275.48 | bwd_inner_microstep: 275.46 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1887 +[2025-05-02 02:06:31,618] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.95 | bwd_microstep: 275.02 | bwd_inner_microstep: 275.01 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1886 +[2025-05-02 02:06:32,099] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.52 | bwd_microstep: 274.44 | bwd_inner_microstep: 274.42 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-02 02:06:32,580] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.28 | bwd_microstep: 274.27 | bwd_inner_microstep: 274.25 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 345 +[2025-05-02 02:06:32,809] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.00 | bwd_microstep: 117.40 | bwd_inner_microstep: 117.11 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 02:06:33,290] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.42 | bwd_microstep: 272.79 | bwd_inner_microstep: 272.77 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 02:06:33,770] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.30 | bwd_microstep: 273.32 | bwd_inner_microstep: 273.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 02:06:34,247] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.83 | bwd_microstep: 272.50 | bwd_inner_microstep: 272.49 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 02:06:34,730] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.16 | bwd_microstep: 272.18 | bwd_inner_microstep: 272.16 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 02:06:35,208] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.73 | bwd_microstep: 273.02 | bwd_inner_microstep: 273.00 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 02:06:35,682] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.69 | bwd_microstep: 271.41 | bwd_inner_microstep: 271.39 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 439 +[2025-05-02 02:06:36,002] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.15 | optimizer_step: 16.23 +[2025-05-02 02:06:36,002] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 79.92 | bwd_microstep: 202.76 | bwd_inner_microstep: 135.54 | bwd_allreduce_microstep: 67.06 | step_microstep: 23.36 +[2025-05-02 02:06:36,003] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2828.43 | bwd: 4178.88 | bwd_inner: 4111.25 | bwd_allreduce: 67.20 | step: 24.18 + 17%|█▋ | 1517/8720 [3:51:09<14:22:22, 7.18s/it] {'loss': 0.9988, 'grad_norm': 6.746757984161377, 'learning_rate': 9.46652588958195e-06, 'epoch': 1.74} + 17%|█▋ | 1517/8720 [3:51:09<14:22:22, 7.18s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-02 02:06:36,486] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.27 | bwd_microstep: 273.37 | bwd_inner_microstep: 273.36 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2116 +[2025-05-02 02:06:37,019] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 206.04 | bwd_microstep: 312.43 | bwd_inner_microstep: 312.41 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1935 +[2025-05-02 02:06:37,519] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 194.96 | bwd_microstep: 288.21 | bwd_inner_microstep: 288.19 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1888 +[2025-05-02 02:06:38,001] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.20 | bwd_microstep: 274.90 | bwd_inner_microstep: 274.88 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1886 +[2025-05-02 02:06:38,484] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.32 | bwd_microstep: 274.29 | bwd_inner_microstep: 274.28 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-02 02:06:38,965] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.51 | bwd_microstep: 274.04 | bwd_inner_microstep: 274.03 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 02:06:39,445] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.41 | bwd_microstep: 272.91 | bwd_inner_microstep: 272.90 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 02:06:39,927] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.88 | bwd_microstep: 273.63 | bwd_inner_microstep: 273.61 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-02 02:06:40,411] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.12 | bwd_microstep: 272.92 | bwd_inner_microstep: 272.90 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 02:06:40,889] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.64 | bwd_microstep: 272.65 | bwd_inner_microstep: 272.63 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 02:06:41,368] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.31 | bwd_microstep: 272.24 | bwd_inner_microstep: 272.23 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 02:06:41,847] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.91 | bwd_microstep: 272.52 | bwd_inner_microstep: 272.50 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 02:06:42,326] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.03 | bwd_microstep: 271.29 | bwd_inner_microstep: 271.27 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 02:06:42,804] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.19 | bwd_microstep: 271.31 | bwd_inner_microstep: 271.29 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 02:06:43,284] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.11 | bwd_microstep: 271.25 | bwd_inner_microstep: 271.24 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1948 +[2025-05-02 02:06:43,891] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.11 | optimizer_step: 16.27 +[2025-05-02 02:06:43,891] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 197.81 | bwd_microstep: 364.95 | bwd_inner_microstep: 289.49 | bwd_allreduce_microstep: 75.40 | step_microstep: 23.92 +[2025-05-02 02:06:43,892] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 3052.33 | bwd: 4512.94 | bwd_inner: 4437.20 | bwd_allreduce: 75.48 | step: 24.78 + 17%|█▋ | 1518/8720 [3:51:17<14:47:43, 7.40s/it] {'loss': 0.8209, 'grad_norm': 6.173440933227539, 'learning_rate': 9.465690874254447e-06, 'epoch': 1.74} + 17%|█▋ | 1518/8720 [3:51:17<14:47:43, 7.40s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1917 +[2025-05-02 02:06:44,381] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.11 | bwd_microstep: 275.89 | bwd_inner_microstep: 275.87 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 388 +[2025-05-02 02:06:44,606] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 85.93 | bwd_microstep: 122.11 | bwd_inner_microstep: 121.79 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.08 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1370 +[2025-05-02 02:06:44,969] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.36 | bwd_microstep: 207.40 | bwd_inner_microstep: 207.38 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 851 +[2025-05-02 02:06:45,212] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 96.20 | bwd_microstep: 132.95 | bwd_inner_microstep: 132.84 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-02 02:06:45,688] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.16 | bwd_microstep: 273.24 | bwd_inner_microstep: 273.22 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 02:06:46,165] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.06 | bwd_microstep: 273.39 | bwd_inner_microstep: 273.38 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 02:06:46,641] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.92 | bwd_microstep: 272.68 | bwd_inner_microstep: 272.66 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 02:06:47,120] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.17 | bwd_microstep: 272.84 | bwd_inner_microstep: 272.82 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1093 +[2025-05-02 02:06:47,418] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 119.97 | bwd_microstep: 160.99 | bwd_inner_microstep: 160.97 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 02:06:47,896] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.18 | bwd_microstep: 272.62 | bwd_inner_microstep: 272.61 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 02:06:48,376] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.30 | bwd_microstep: 272.39 | bwd_inner_microstep: 272.37 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 02:06:48,855] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.33 | bwd_microstep: 272.86 | bwd_inner_microstep: 272.84 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 02:06:49,333] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.33 | bwd_microstep: 271.28 | bwd_inner_microstep: 271.27 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 02:06:49,812] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.84 | bwd_microstep: 271.77 | bwd_inner_microstep: 271.75 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 830 +[2025-05-02 02:06:50,070] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 106.42 | bwd_microstep: 129.77 | bwd_inner_microstep: 129.62 | bwd_allreduce_microstep: 0.10 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 02:06:50,647] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.14 | optimizer_step: 16.36 +[2025-05-02 02:06:50,648] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.29 | bwd_microstep: 348.36 | bwd_inner_microstep: 271.43 | bwd_allreduce_microstep: 76.88 | step_microstep: 24.11 +[2025-05-02 02:06:50,649] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2623.22 | bwd: 3830.60 | bwd_inner: 3752.89 | bwd_allreduce: 77.21 | step: 24.98 + 17%|█▋ | 1519/8720 [3:51:24<14:24:35, 7.20s/it] {'loss': 0.4886, 'grad_norm': 5.219083309173584, 'learning_rate': 9.464855242824354e-06, 'epoch': 1.74} + 17%|█▋ | 1519/8720 [3:51:24<14:24:35, 7.20s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-02 02:06:51,135] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.83 | bwd_microstep: 273.73 | bwd_inner_microstep: 273.72 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 900 +[2025-05-02 02:06:51,401] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 104.06 | bwd_microstep: 144.56 | bwd_inner_microstep: 144.44 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1898 +[2025-05-02 02:06:51,885] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.52 | bwd_microstep: 275.72 | bwd_inner_microstep: 275.71 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1373 +[2025-05-02 02:06:52,255] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 144.51 | bwd_microstep: 207.98 | bwd_inner_microstep: 207.86 | bwd_allreduce_microstep: 0.04 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-02 02:06:52,735] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.95 | bwd_microstep: 274.36 | bwd_inner_microstep: 274.34 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 02:06:53,216] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.87 | bwd_microstep: 273.02 | bwd_inner_microstep: 273.00 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-02 02:06:53,696] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.65 | bwd_microstep: 273.61 | bwd_inner_microstep: 273.59 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 332 +[2025-05-02 02:06:53,903] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 69.00 | bwd_microstep: 122.10 | bwd_inner_microstep: 121.86 | bwd_allreduce_microstep: 0.10 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 02:06:54,379] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.47 | bwd_microstep: 272.59 | bwd_inner_microstep: 272.58 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 02:06:54,855] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.47 | bwd_microstep: 272.41 | bwd_inner_microstep: 272.39 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 02:06:55,331] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.89 | bwd_microstep: 272.24 | bwd_inner_microstep: 272.22 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 02:06:55,806] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.34 | bwd_microstep: 272.30 | bwd_inner_microstep: 272.28 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 02:06:56,282] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.44 | bwd_microstep: 272.26 | bwd_inner_microstep: 272.24 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 02:06:56,758] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.07 | bwd_microstep: 271.23 | bwd_inner_microstep: 271.22 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 02:06:57,232] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.88 | bwd_microstep: 271.29 | bwd_inner_microstep: 271.27 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 315 +[2025-05-02 02:06:57,542] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.15 | optimizer_step: 16.42 +[2025-05-02 02:06:57,543] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 70.44 | bwd_microstep: 202.86 | bwd_inner_microstep: 136.29 | bwd_allreduce_microstep: 66.43 | step_microstep: 23.53 +[2025-05-02 02:06:57,544] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2651.07 | bwd: 3952.33 | bwd_inner: 3885.12 | bwd_allreduce: 66.67 | step: 24.50 + 17%|█▋ | 1520/8720 [3:51:31<14:13:17, 7.11s/it] {'loss': 0.8161, 'grad_norm': 14.804104804992676, 'learning_rate': 9.464018995406957e-06, 'epoch': 1.74} + 17%|█▋ | 1520/8720 [3:51:31<14:13:17, 7.11s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 02:06:58,022] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.77 | bwd_microstep: 270.14 | bwd_inner_microstep: 270.12 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1953 +[2025-05-02 02:06:58,524] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 196.72 | bwd_microstep: 289.59 | bwd_inner_microstep: 289.57 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1906 +[2025-05-02 02:06:59,006] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.94 | bwd_microstep: 276.51 | bwd_inner_microstep: 276.49 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1899 +[2025-05-02 02:06:59,487] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.93 | bwd_microstep: 275.67 | bwd_inner_microstep: 275.65 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1893 +[2025-05-02 02:06:59,967] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.16 | bwd_microstep: 275.66 | bwd_inner_microstep: 275.64 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1891 +[2025-05-02 02:07:00,447] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.99 | bwd_microstep: 275.31 | bwd_inner_microstep: 275.29 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-02 02:07:00,925] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.34 | bwd_microstep: 273.74 | bwd_inner_microstep: 273.73 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1883 +[2025-05-02 02:07:01,404] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.07 | bwd_microstep: 274.25 | bwd_inner_microstep: 274.23 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 02:07:01,883] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.62 | bwd_microstep: 273.28 | bwd_inner_microstep: 273.26 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-02 02:07:02,361] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.98 | bwd_microstep: 273.57 | bwd_inner_microstep: 273.55 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 02:07:02,839] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.34 | bwd_microstep: 272.91 | bwd_inner_microstep: 272.89 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 02:07:03,317] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.37 | bwd_microstep: 273.04 | bwd_inner_microstep: 273.03 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 02:07:03,795] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.11 | bwd_microstep: 272.94 | bwd_inner_microstep: 272.92 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 02:07:04,271] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.24 | bwd_microstep: 272.38 | bwd_inner_microstep: 272.36 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 326 +[2025-05-02 02:07:04,486] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 79.21 | bwd_microstep: 120.78 | bwd_inner_microstep: 120.51 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 831 +[2025-05-02 02:07:04,817] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.16 | optimizer_step: 16.38 +[2025-05-02 02:07:04,818] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.39 | bwd_microstep: 198.81 | bwd_inner_microstep: 132.88 | bwd_allreduce_microstep: 65.77 | step_microstep: 23.51 +[2025-05-02 02:07:04,819] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2827.91 | bwd: 4168.60 | bwd_inner: 4102.26 | bwd_allreduce: 65.91 | step: 24.21 + 17%|█▋ | 1521/8720 [3:51:38<14:19:04, 7.16s/it] {'loss': 1.5227, 'grad_norm': 15.822820663452148, 'learning_rate': 9.463182132117624e-06, 'epoch': 1.74} + 17%|█▋ | 1521/8720 [3:51:38<14:19:04, 7.16s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 02:07:05,299] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.24 | bwd_microstep: 272.29 | bwd_inner_microstep: 272.27 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.13 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1944 +[2025-05-02 02:07:05,800] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 196.30 | bwd_microstep: 288.58 | bwd_inner_microstep: 288.56 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1914 +[2025-05-02 02:07:06,283] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.38 | bwd_microstep: 276.82 | bwd_inner_microstep: 276.81 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1896 +[2025-05-02 02:07:06,763] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.06 | bwd_microstep: 275.20 | bwd_inner_microstep: 275.19 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1105 +[2025-05-02 02:07:07,055] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 115.37 | bwd_microstep: 161.73 | bwd_inner_microstep: 161.71 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-02 02:07:07,533] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.60 | bwd_microstep: 274.00 | bwd_inner_microstep: 273.98 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 02:07:08,010] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.26 | bwd_microstep: 273.24 | bwd_inner_microstep: 273.23 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-02 02:07:08,487] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.59 | bwd_microstep: 273.56 | bwd_inner_microstep: 273.55 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 02:07:08,963] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.79 | bwd_microstep: 273.51 | bwd_inner_microstep: 273.49 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 02:07:09,440] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.15 | bwd_microstep: 272.46 | bwd_inner_microstep: 272.44 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.11 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 852 +[2025-05-02 02:07:09,682] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.70 | bwd_microstep: 133.11 | bwd_inner_microstep: 133.00 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 02:07:10,162] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.46 | bwd_microstep: 273.06 | bwd_inner_microstep: 273.04 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 02:07:10,643] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.34 | bwd_microstep: 273.01 | bwd_inner_microstep: 272.99 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.06 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 840 +[2025-05-02 02:07:10,893] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 102.58 | bwd_microstep: 126.04 | bwd_inner_microstep: 125.92 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 02:07:11,379] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.86 | bwd_microstep: 272.67 | bwd_inner_microstep: 272.65 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 02:07:11,969] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.17 | optimizer_step: 16.54 +[2025-05-02 02:07:11,969] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.73 | bwd_microstep: 355.18 | bwd_inner_microstep: 271.50 | bwd_allreduce_microstep: 83.63 | step_microstep: 24.52 +[2025-05-02 02:07:11,971] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2772.05 | bwd: 4074.52 | bwd_inner: 3990.34 | bwd_allreduce: 83.84 | step: 25.56 + 17%|█▋ | 1522/8720 [3:51:45<14:18:44, 7.16s/it] {'loss': 0.7041, 'grad_norm': 19.038780212402344, 'learning_rate': 9.462344653071816e-06, 'epoch': 1.75} + 17%|█▋ | 1522/8720 [3:51:45<14:18:44, 7.16s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 02:07:12,453] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.53 | bwd_microstep: 270.92 | bwd_inner_microstep: 270.91 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2116 +[2025-05-02 02:07:12,991] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 204.46 | bwd_microstep: 313.59 | bwd_inner_microstep: 313.57 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-02 02:07:13,478] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.09 | bwd_microstep: 275.40 | bwd_inner_microstep: 275.38 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-02 02:07:13,961] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.37 | bwd_microstep: 274.52 | bwd_inner_microstep: 274.50 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 02:07:14,441] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.46 | bwd_microstep: 273.40 | bwd_inner_microstep: 273.38 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 02:07:14,923] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.58 | bwd_microstep: 273.40 | bwd_inner_microstep: 273.38 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 02:07:15,404] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.03 | bwd_microstep: 273.83 | bwd_inner_microstep: 273.81 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 02:07:15,883] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.66 | bwd_microstep: 273.17 | bwd_inner_microstep: 273.16 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 02:07:16,362] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.41 | bwd_microstep: 273.00 | bwd_inner_microstep: 272.98 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 02:07:16,841] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.03 | bwd_microstep: 274.07 | bwd_inner_microstep: 274.06 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-02 02:07:17,320] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.35 | bwd_microstep: 274.34 | bwd_inner_microstep: 274.33 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 844 +[2025-05-02 02:07:17,562] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.44 | bwd_microstep: 132.83 | bwd_inner_microstep: 132.56 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 02:07:18,037] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.38 | bwd_microstep: 271.57 | bwd_inner_microstep: 271.55 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 02:07:18,517] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.52 | bwd_microstep: 273.64 | bwd_inner_microstep: 273.62 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 831 +[2025-05-02 02:07:18,760] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.47 | bwd_microstep: 130.83 | bwd_inner_microstep: 130.55 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 02:07:19,339] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.19 | optimizer_step: 16.39 +[2025-05-02 02:07:19,340] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.36 | bwd_microstep: 349.09 | bwd_inner_microstep: 272.07 | bwd_allreduce_microstep: 76.98 | step_microstep: 24.32 +[2025-05-02 02:07:19,341] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2851.75 | bwd: 4207.64 | bwd_inner: 4129.87 | bwd_allreduce: 77.30 | step: 25.20 + 17%|█▋ | 1523/8720 [3:51:53<14:26:15, 7.22s/it] {'loss': 0.9721, 'grad_norm': 23.956768035888672, 'learning_rate': 9.461506558385072e-06, 'epoch': 1.75} + 17%|█▋ | 1523/8720 [3:51:53<14:26:15, 7.22s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-02 02:07:19,827] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.60 | bwd_microstep: 273.87 | bwd_inner_microstep: 273.85 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1889 +[2025-05-02 02:07:20,308] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.26 | bwd_microstep: 275.32 | bwd_inner_microstep: 275.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1889 +[2025-05-02 02:07:20,789] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.50 | bwd_microstep: 275.12 | bwd_inner_microstep: 275.10 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1883 +[2025-05-02 02:07:21,274] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 191.11 | bwd_microstep: 274.30 | bwd_inner_microstep: 274.28 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1358 +[2025-05-02 02:07:21,641] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.89 | bwd_microstep: 206.56 | bwd_inner_microstep: 206.54 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 02:07:22,121] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.35 | bwd_microstep: 273.91 | bwd_inner_microstep: 273.89 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 02:07:22,603] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.24 | bwd_microstep: 273.26 | bwd_inner_microstep: 273.25 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-02 02:07:23,085] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.73 | bwd_microstep: 274.29 | bwd_inner_microstep: 274.27 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 02:07:23,566] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.60 | bwd_microstep: 272.99 | bwd_inner_microstep: 272.98 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 835 +[2025-05-02 02:07:23,804] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.55 | bwd_microstep: 126.23 | bwd_inner_microstep: 126.07 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 02:07:24,284] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.32 | bwd_microstep: 272.95 | bwd_inner_microstep: 272.93 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 02:07:24,765] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.57 | bwd_microstep: 272.44 | bwd_inner_microstep: 272.42 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 833 +[2025-05-02 02:07:25,005] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.69 | bwd_microstep: 125.85 | bwd_inner_microstep: 125.63 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 325 +[2025-05-02 02:07:25,219] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 79.98 | bwd_microstep: 118.82 | bwd_inner_microstep: 118.52 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 02:07:25,696] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.66 | bwd_microstep: 271.14 | bwd_inner_microstep: 271.12 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.14 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 02:07:26,275] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.16 | optimizer_step: 16.23 +[2025-05-02 02:07:26,275] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.75 | bwd_microstep: 349.90 | bwd_inner_microstep: 271.56 | bwd_allreduce_microstep: 78.29 | step_microstep: 23.93 +[2025-05-02 02:07:26,277] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2677.45 | bwd: 3937.01 | bwd_inner: 3857.78 | bwd_allreduce: 78.66 | step: 25.30 + 17%|█▋ | 1524/8720 [3:52:00<14:15:49, 7.14s/it] {'loss': 0.7977, 'grad_norm': 7.614800453186035, 'learning_rate': 9.46066784817302e-06, 'epoch': 1.75} + 17%|█▋ | 1524/8720 [3:52:00<14:15:49, 7.14s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1893 +[2025-05-02 02:07:26,763] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.15 | bwd_microstep: 274.87 | bwd_inner_microstep: 274.85 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1181 +[2025-05-02 02:07:27,074] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 119.89 | bwd_microstep: 172.64 | bwd_inner_microstep: 172.44 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1922 +[2025-05-02 02:07:27,573] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.33 | bwd_microstep: 287.11 | bwd_inner_microstep: 287.09 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-02 02:07:28,054] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.36 | bwd_microstep: 274.06 | bwd_inner_microstep: 274.04 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 02:07:28,535] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.77 | bwd_microstep: 273.49 | bwd_inner_microstep: 273.47 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-02 02:07:29,016] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.60 | bwd_microstep: 274.35 | bwd_inner_microstep: 274.33 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-02 02:07:29,497] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.10 | bwd_microstep: 273.60 | bwd_inner_microstep: 273.58 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-02 02:07:29,978] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.01 | bwd_microstep: 274.02 | bwd_inner_microstep: 274.00 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 02:07:30,457] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.58 | bwd_microstep: 273.47 | bwd_inner_microstep: 273.45 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 02:07:30,935] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.53 | bwd_microstep: 272.58 | bwd_inner_microstep: 272.57 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 02:07:31,413] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.91 | bwd_microstep: 273.14 | bwd_inner_microstep: 273.12 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1348 +[2025-05-02 02:07:31,777] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 143.68 | bwd_microstep: 206.28 | bwd_inner_microstep: 206.22 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.09 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 833 +[2025-05-02 02:07:32,008] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 91.19 | bwd_microstep: 126.10 | bwd_inner_microstep: 125.88 | bwd_allreduce_microstep: 0.08 | step_microstep: 0.09 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 829 +[2025-05-02 02:07:32,246] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.31 | bwd_microstep: 130.03 | bwd_inner_microstep: 129.85 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 02:07:32,721] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.89 | bwd_microstep: 271.88 | bwd_inner_microstep: 271.86 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1926 +[2025-05-02 02:07:33,307] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.13 | optimizer_step: 16.23 +[2025-05-02 02:07:33,308] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 194.76 | bwd_microstep: 354.17 | bwd_inner_microstep: 288.08 | bwd_allreduce_microstep: 66.04 | step_microstep: 23.19 +[2025-05-02 02:07:33,309] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2727.72 | bwd: 4011.83 | bwd_inner: 3944.91 | bwd_allreduce: 66.36 | step: 24.06 + 17%|█▋ | 1525/8720 [3:52:07<14:11:55, 7.10s/it] {'loss': 0.7281, 'grad_norm': 5.608772277832031, 'learning_rate': 9.459828522551371e-06, 'epoch': 1.75} + 17%|█▋ | 1525/8720 [3:52:07<14:11:55, 7.10s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 02:07:33,789] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.54 | bwd_microstep: 272.24 | bwd_inner_microstep: 272.22 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1914 +[2025-05-02 02:07:34,272] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.78 | bwd_microstep: 276.94 | bwd_inner_microstep: 276.93 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1928 +[2025-05-02 02:07:34,772] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.77 | bwd_microstep: 287.54 | bwd_inner_microstep: 287.52 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-02 02:07:35,253] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.61 | bwd_microstep: 274.53 | bwd_inner_microstep: 274.51 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 02:07:35,733] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.44 | bwd_microstep: 274.11 | bwd_inner_microstep: 274.09 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-02 02:07:36,212] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.57 | bwd_microstep: 274.74 | bwd_inner_microstep: 274.72 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1883 +[2025-05-02 02:07:36,693] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.95 | bwd_microstep: 274.37 | bwd_inner_microstep: 274.35 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 02:07:37,170] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.05 | bwd_microstep: 272.97 | bwd_inner_microstep: 272.95 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 02:07:37,646] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.28 | bwd_microstep: 272.62 | bwd_inner_microstep: 272.60 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 02:07:38,123] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.47 | bwd_microstep: 273.03 | bwd_inner_microstep: 273.01 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 02:07:38,599] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.48 | bwd_microstep: 273.00 | bwd_inner_microstep: 272.98 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 02:07:39,075] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.55 | bwd_microstep: 272.68 | bwd_inner_microstep: 272.66 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 02:07:39,550] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.96 | bwd_microstep: 272.01 | bwd_inner_microstep: 271.99 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1341 +[2025-05-02 02:07:39,911] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.26 | bwd_microstep: 204.31 | bwd_inner_microstep: 204.29 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 02:07:40,387] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.35 | bwd_microstep: 271.22 | bwd_inner_microstep: 271.20 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 02:07:40,953] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.15 | optimizer_step: 16.37 +[2025-05-02 02:07:40,954] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.63 | bwd_microstep: 339.21 | bwd_inner_microstep: 272.44 | bwd_allreduce_microstep: 66.72 | step_microstep: 23.48 +[2025-05-02 02:07:40,955] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2983.40 | bwd: 4385.55 | bwd_inner: 4318.49 | bwd_allreduce: 66.80 | step: 24.21 + 18%|█▊ | 1526/8720 [3:52:14<14:31:16, 7.27s/it] {'loss': 0.9287, 'grad_norm': 12.193320274353027, 'learning_rate': 9.458988581635921e-06, 'epoch': 1.75} + 18%|█▊ | 1526/8720 [3:52:14<14:31:16, 7.27s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 02:07:41,433] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.52 | bwd_microstep: 270.68 | bwd_inner_microstep: 270.66 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2067 +[2025-05-02 02:07:41,955] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 204.21 | bwd_microstep: 303.22 | bwd_inner_microstep: 303.21 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1904 +[2025-05-02 02:07:42,436] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.73 | bwd_microstep: 276.46 | bwd_inner_microstep: 276.44 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1888 +[2025-05-02 02:07:42,915] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.13 | bwd_microstep: 274.47 | bwd_inner_microstep: 274.45 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-02 02:07:43,393] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.13 | bwd_microstep: 274.10 | bwd_inner_microstep: 274.08 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 02:07:43,870] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.05 | bwd_microstep: 273.44 | bwd_inner_microstep: 273.43 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-02 02:07:44,350] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.81 | bwd_microstep: 274.57 | bwd_inner_microstep: 274.55 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 02:07:44,828] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.58 | bwd_microstep: 274.10 | bwd_inner_microstep: 274.09 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.15 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 02:07:45,306] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.45 | bwd_microstep: 272.91 | bwd_inner_microstep: 272.90 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 02:07:45,783] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.35 | bwd_microstep: 273.41 | bwd_inner_microstep: 273.39 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 02:07:46,261] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.75 | bwd_microstep: 273.01 | bwd_inner_microstep: 272.99 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 02:07:46,736] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.67 | bwd_microstep: 272.22 | bwd_inner_microstep: 272.21 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 02:07:47,213] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.51 | bwd_microstep: 272.00 | bwd_inner_microstep: 271.98 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 02:07:47,688] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.26 | bwd_microstep: 271.37 | bwd_inner_microstep: 271.35 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 02:07:48,168] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.07 | bwd_microstep: 271.18 | bwd_inner_microstep: 271.16 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 02:07:48,751] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.16 | optimizer_step: 16.29 +[2025-05-02 02:07:48,752] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.47 | bwd_microstep: 353.73 | bwd_inner_microstep: 271.82 | bwd_allreduce_microstep: 81.86 | step_microstep: 24.00 +[2025-05-02 02:07:48,753] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 3036.44 | bwd: 4480.89 | bwd_inner: 4398.70 | bwd_allreduce: 81.95 | step: 24.94 + 18%|█▊ | 1527/8720 [3:52:22<14:50:21, 7.43s/it] {'loss': 0.7825, 'grad_norm': 15.728638648986816, 'learning_rate': 9.458148025542553e-06, 'epoch': 1.75} + 18%|█▊ | 1527/8720 [3:52:22<14:50:21, 7.43s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 02:07:49,235] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.94 | bwd_microstep: 270.95 | bwd_inner_microstep: 270.93 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 864 +[2025-05-02 02:07:49,486] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 99.32 | bwd_microstep: 133.54 | bwd_inner_microstep: 133.49 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-02 02:07:49,968] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.50 | bwd_microstep: 275.12 | bwd_inner_microstep: 275.10 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 02:07:50,449] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.13 | bwd_microstep: 272.75 | bwd_inner_microstep: 272.73 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 02:07:50,930] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.81 | bwd_microstep: 273.35 | bwd_inner_microstep: 273.33 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 02:07:51,409] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.02 | bwd_microstep: 273.22 | bwd_inner_microstep: 273.20 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 02:07:51,888] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.03 | bwd_microstep: 272.81 | bwd_inner_microstep: 272.80 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 339 +[2025-05-02 02:07:52,088] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 69.21 | bwd_microstep: 117.74 | bwd_inner_microstep: 117.61 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 02:07:52,564] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.42 | bwd_microstep: 272.43 | bwd_inner_microstep: 272.41 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 02:07:53,040] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.18 | bwd_microstep: 272.80 | bwd_inner_microstep: 272.78 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 02:07:53,518] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.19 | bwd_microstep: 273.13 | bwd_inner_microstep: 273.12 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 02:07:53,998] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.57 | bwd_microstep: 273.11 | bwd_inner_microstep: 273.09 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 02:07:54,475] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.18 | bwd_microstep: 271.67 | bwd_inner_microstep: 271.65 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 318 +[2025-05-02 02:07:54,687] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 81.64 | bwd_microstep: 114.51 | bwd_inner_microstep: 114.19 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 02:07:55,163] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.31 | bwd_microstep: 271.22 | bwd_inner_microstep: 271.20 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 02:07:55,728] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.04 | optimizer_gradients: 2.13 | optimizer_step: 16.25 +[2025-05-02 02:07:55,728] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.44 | bwd_microstep: 337.76 | bwd_inner_microstep: 271.70 | bwd_allreduce_microstep: 66.01 | step_microstep: 23.20 +[2025-05-02 02:07:55,730] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2703.55 | bwd: 3976.17 | bwd_inner: 3909.44 | bwd_allreduce: 66.27 | step: 24.07 + 18%|█▊ | 1528/8720 [3:52:29<14:33:57, 7.29s/it] {'loss': 0.6585, 'grad_norm': 10.300775527954102, 'learning_rate': 9.45730685438723e-06, 'epoch': 1.75} + 18%|█▊ | 1528/8720 [3:52:29<14:33:57, 7.29s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2013 +[2025-05-02 02:07:56,243] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 198.14 | bwd_microstep: 295.41 | bwd_inner_microstep: 295.39 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 967 +[2025-05-02 02:07:56,514] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 106.08 | bwd_microstep: 150.65 | bwd_inner_microstep: 150.41 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1893 +[2025-05-02 02:07:56,993] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.42 | bwd_microstep: 275.38 | bwd_inner_microstep: 275.37 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1886 +[2025-05-02 02:07:57,472] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.80 | bwd_microstep: 274.91 | bwd_inner_microstep: 274.89 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-02 02:07:57,952] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.62 | bwd_microstep: 274.30 | bwd_inner_microstep: 274.29 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-02 02:07:58,430] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.10 | bwd_microstep: 274.24 | bwd_inner_microstep: 274.22 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 337 +[2025-05-02 02:07:58,643] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 81.26 | bwd_microstep: 118.02 | bwd_inner_microstep: 117.84 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 02:07:59,120] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.73 | bwd_microstep: 273.65 | bwd_inner_microstep: 273.64 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 339 +[2025-05-02 02:07:59,351] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 82.15 | bwd_microstep: 132.31 | bwd_inner_microstep: 132.00 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 02:07:59,829] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.95 | bwd_microstep: 272.68 | bwd_inner_microstep: 272.66 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1099 +[2025-05-02 02:08:00,123] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 115.40 | bwd_microstep: 161.40 | bwd_inner_microstep: 161.21 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.10 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 330 +[2025-05-02 02:08:00,339] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 82.38 | bwd_microstep: 118.93 | bwd_inner_microstep: 118.78 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.12 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1356 +[2025-05-02 02:08:00,704] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.06 | bwd_microstep: 206.47 | bwd_inner_microstep: 206.40 | bwd_allreduce_microstep: 0.03 | step_microstep: 0.10 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1345 +[2025-05-02 02:08:01,069] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.56 | bwd_microstep: 205.65 | bwd_inner_microstep: 205.55 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 02:08:01,545] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.96 | bwd_microstep: 271.23 | bwd_inner_microstep: 271.21 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 02:08:02,122] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.14 | optimizer_step: 16.21 +[2025-05-02 02:08:02,123] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.12 | bwd_microstep: 348.19 | bwd_inner_microstep: 271.74 | bwd_allreduce_microstep: 76.40 | step_microstep: 23.89 +[2025-05-02 02:08:02,124] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2454.41 | bwd: 3653.60 | bwd_inner: 3575.75 | bwd_allreduce: 77.04 | step: 25.19 + 18%|█▊ | 1529/8720 [3:52:35<14:01:40, 7.02s/it] {'loss': 0.8442, 'grad_norm': 10.928874969482422, 'learning_rate': 9.456465068286005e-06, 'epoch': 1.75} + 18%|█▊ | 1529/8720 [3:52:35<14:01:40, 7.02s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 02:08:02,605] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.55 | bwd_microstep: 270.35 | bwd_inner_microstep: 270.33 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1915 +[2025-05-02 02:08:03,088] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.33 | bwd_microstep: 277.32 | bwd_inner_microstep: 277.30 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1904 +[2025-05-02 02:08:03,569] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.46 | bwd_microstep: 276.03 | bwd_inner_microstep: 276.01 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1901 +[2025-05-02 02:08:04,049] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.61 | bwd_microstep: 276.24 | bwd_inner_microstep: 276.22 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 02:08:04,525] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.49 | bwd_microstep: 272.88 | bwd_inner_microstep: 272.86 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 02:08:05,003] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.03 | bwd_microstep: 273.95 | bwd_inner_microstep: 273.93 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1091 +[2025-05-02 02:08:05,296] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 117.76 | bwd_microstep: 161.09 | bwd_inner_microstep: 160.99 | bwd_allreduce_microstep: 0.03 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 02:08:05,772] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.21 | bwd_microstep: 272.86 | bwd_inner_microstep: 272.84 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1351 +[2025-05-02 02:08:06,133] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.34 | bwd_microstep: 205.77 | bwd_inner_microstep: 205.76 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 02:08:06,608] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.70 | bwd_microstep: 272.65 | bwd_inner_microstep: 272.63 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 02:08:07,084] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.14 | bwd_microstep: 273.08 | bwd_inner_microstep: 273.07 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 321 +[2025-05-02 02:08:07,307] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 76.53 | bwd_microstep: 133.45 | bwd_inner_microstep: 133.30 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.09 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1344 +[2025-05-02 02:08:07,667] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.20 | bwd_microstep: 204.10 | bwd_inner_microstep: 204.08 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 02:08:08,142] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.00 | bwd_microstep: 271.24 | bwd_inner_microstep: 271.22 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 02:08:08,620] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.68 | bwd_microstep: 271.23 | bwd_inner_microstep: 271.22 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1084 +[2025-05-02 02:08:09,013] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.11 | optimizer_step: 16.24 +[2025-05-02 02:08:09,014] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 115.81 | bwd_microstep: 237.88 | bwd_inner_microstep: 160.01 | bwd_allreduce_microstep: 77.72 | step_microstep: 23.71 +[2025-05-02 02:08:09,015] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2664.54 | bwd: 3950.15 | bwd_inner: 3871.85 | bwd_allreduce: 77.90 | step: 24.48 + 18%|█▊ | 1530/8720 [3:52:42<13:56:43, 6.98s/it] {'loss': 0.7446, 'grad_norm': 10.35707950592041, 'learning_rate': 9.455622667355013e-06, 'epoch': 1.75} + 18%|█▊ | 1530/8720 [3:52:42<13:56:43, 6.98s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 02:08:09,493] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.35 | bwd_microstep: 270.47 | bwd_inner_microstep: 270.45 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2116 +[2025-05-02 02:08:10,024] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 203.30 | bwd_microstep: 312.93 | bwd_inner_microstep: 312.91 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1908 +[2025-05-02 02:08:10,506] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.53 | bwd_microstep: 276.04 | bwd_inner_microstep: 276.03 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1892 +[2025-05-02 02:08:10,985] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.39 | bwd_microstep: 274.80 | bwd_inner_microstep: 274.78 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1892 +[2025-05-02 02:08:11,464] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.01 | bwd_microstep: 274.67 | bwd_inner_microstep: 274.65 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.16 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-02 02:08:11,942] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.13 | bwd_microstep: 273.35 | bwd_inner_microstep: 273.33 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1888 +[2025-05-02 02:08:12,422] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.60 | bwd_microstep: 274.66 | bwd_inner_microstep: 274.64 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 344 +[2025-05-02 02:08:12,621] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 71.06 | bwd_microstep: 114.78 | bwd_inner_microstep: 114.65 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 02:08:13,097] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.46 | bwd_microstep: 273.28 | bwd_inner_microstep: 273.26 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 02:08:13,577] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.13 | bwd_microstep: 273.38 | bwd_inner_microstep: 273.37 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-02 02:08:14,056] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.62 | bwd_microstep: 273.60 | bwd_inner_microstep: 273.58 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 02:08:14,535] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.04 | bwd_microstep: 273.13 | bwd_inner_microstep: 273.11 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 02:08:15,015] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.56 | bwd_microstep: 273.07 | bwd_inner_microstep: 273.05 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 834 +[2025-05-02 02:08:15,256] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 96.85 | bwd_microstep: 125.73 | bwd_inner_microstep: 125.62 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 321 +[2025-05-02 02:08:15,479] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 85.80 | bwd_microstep: 120.58 | bwd_inner_microstep: 120.42 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 02:08:16,063] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.15 | optimizer_step: 16.33 +[2025-05-02 02:08:16,064] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.91 | bwd_microstep: 353.13 | bwd_inner_microstep: 272.90 | bwd_allreduce_microstep: 80.18 | step_microstep: 24.37 +[2025-05-02 02:08:16,065] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2727.45 | bwd: 4037.65 | bwd_inner: 3956.81 | bwd_allreduce: 80.43 | step: 25.40 + 18%|█▊ | 1531/8720 [3:52:49<13:59:08, 7.00s/it] {'loss': 0.9247, 'grad_norm': 7.227096080780029, 'learning_rate': 9.454779651710476e-06, 'epoch': 1.76} + 18%|█▊ | 1531/8720 [3:52:49<13:59:08, 7.00s/it]dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 899 +[2025-05-02 02:08:16,335] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 103.24 | bwd_microstep: 143.90 | bwd_inner_microstep: 143.68 | bwd_allreduce_microstep: 0.08 | step_microstep: 0.10 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 527 +[2025-05-02 02:08:16,553] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 82.94 | bwd_microstep: 118.69 | bwd_inner_microstep: 118.54 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 458 +[2025-05-02 02:08:16,780] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 91.86 | bwd_microstep: 119.62 | bwd_inner_microstep: 119.34 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1952 +[2025-05-02 02:08:17,284] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.74 | bwd_microstep: 289.12 | bwd_inner_microstep: 289.10 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 365 +[2025-05-02 02:08:17,527] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 96.77 | bwd_microstep: 127.25 | bwd_inner_microstep: 127.04 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1889 +[2025-05-02 02:08:18,009] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.19 | bwd_microstep: 275.18 | bwd_inner_microstep: 275.16 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.15 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-02 02:08:18,492] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.01 | bwd_microstep: 274.20 | bwd_inner_microstep: 274.18 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-02 02:08:18,974] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.30 | bwd_microstep: 273.72 | bwd_inner_microstep: 273.70 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 02:08:19,456] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.11 | bwd_microstep: 273.08 | bwd_inner_microstep: 273.06 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 02:08:19,941] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.46 | bwd_microstep: 272.89 | bwd_inner_microstep: 272.88 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 02:08:20,422] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.77 | bwd_microstep: 271.93 | bwd_inner_microstep: 271.91 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1109 +[2025-05-02 02:08:20,717] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 115.69 | bwd_microstep: 161.82 | bwd_inner_microstep: 161.72 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 02:08:21,195] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.57 | bwd_microstep: 272.71 | bwd_inner_microstep: 272.69 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 02:08:21,677] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.04 | bwd_microstep: 272.74 | bwd_inner_microstep: 272.72 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 02:08:22,158] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.21 | bwd_microstep: 272.34 | bwd_inner_microstep: 272.32 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 02:08:22,741] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.19 | optimizer_step: 16.37 +[2025-05-02 02:08:22,742] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.02 | bwd_microstep: 349.12 | bwd_inner_microstep: 272.60 | bwd_allreduce_microstep: 76.47 | step_microstep: 23.94 +[2025-05-02 02:08:22,743] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2573.48 | bwd: 3768.40 | bwd_inner: 3690.84 | bwd_allreduce: 76.88 | step: 25.10 + 18%|█▊ | 1532/8720 [3:52:56<13:47:14, 6.91s/it] {'loss': 0.8791, 'grad_norm': 3.753875970840454, 'learning_rate': 9.453936021468697e-06, 'epoch': 1.76} + 18%|█▊ | 1532/8720 [3:52:56<13:47:14, 6.91s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 02:08:23,222] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.45 | bwd_microstep: 270.31 | bwd_inner_microstep: 270.29 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1957 +[2025-05-02 02:08:23,725] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.91 | bwd_microstep: 289.93 | bwd_inner_microstep: 289.92 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-02 02:08:24,203] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.22 | bwd_microstep: 273.20 | bwd_inner_microstep: 273.18 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 345 +[2025-05-02 02:08:24,412] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 74.41 | bwd_microstep: 120.60 | bwd_inner_microstep: 120.47 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-02 02:08:24,890] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.74 | bwd_microstep: 274.13 | bwd_inner_microstep: 274.11 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-02 02:08:25,372] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.38 | bwd_microstep: 274.17 | bwd_inner_microstep: 274.15 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 02:08:25,849] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.64 | bwd_microstep: 272.80 | bwd_inner_microstep: 272.78 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 02:08:26,325] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.45 | bwd_microstep: 272.89 | bwd_inner_microstep: 272.88 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 330 +[2025-05-02 02:08:26,529] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 69.93 | bwd_microstep: 120.22 | bwd_inner_microstep: 119.93 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.09 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 328 +[2025-05-02 02:08:26,732] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 69.33 | bwd_microstep: 120.24 | bwd_inner_microstep: 119.95 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 837 +[2025-05-02 02:08:26,966] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 91.73 | bwd_microstep: 126.45 | bwd_inner_microstep: 126.39 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.09 +dynamic ViT batch size: 6, images per sample: 6.0, dynamic token length: 1603 +[2025-05-02 02:08:27,389] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 164.69 | bwd_microstep: 243.52 | bwd_inner_microstep: 243.51 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 02:08:27,863] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.43 | bwd_microstep: 271.46 | bwd_inner_microstep: 271.44 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 02:08:28,337] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.26 | bwd_microstep: 270.99 | bwd_inner_microstep: 270.97 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 828 +[2025-05-02 02:08:28,573] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.21 | bwd_microstep: 129.75 | bwd_inner_microstep: 129.72 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1899 +[2025-05-02 02:08:29,145] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.11 | optimizer_step: 16.22 +[2025-05-02 02:08:29,145] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.66 | bwd_microstep: 343.68 | bwd_inner_microstep: 276.54 | bwd_allreduce_microstep: 67.09 | step_microstep: 23.37 +[2025-05-02 02:08:29,146] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2454.15 | bwd: 3674.44 | bwd_inner: 3606.37 | bwd_allreduce: 67.47 | step: 24.25 + 18%|█▊ | 1533/8720 [3:53:02<13:29:05, 6.75s/it] {'loss': 0.4132, 'grad_norm': 13.784008979797363, 'learning_rate': 9.453091776746068e-06, 'epoch': 1.76} + 18%|█▊ | 1533/8720 [3:53:02<13:29:05, 6.75s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1849 +[2025-05-02 02:08:29,624] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.68 | bwd_microstep: 270.49 | bwd_inner_microstep: 270.47 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1910 +[2025-05-02 02:08:30,105] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.53 | bwd_microstep: 276.06 | bwd_inner_microstep: 276.05 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1895 +[2025-05-02 02:08:30,587] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.59 | bwd_microstep: 275.52 | bwd_inner_microstep: 275.50 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-02 02:08:31,066] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.00 | bwd_microstep: 274.55 | bwd_inner_microstep: 274.53 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 346 +[2025-05-02 02:08:31,287] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 86.93 | bwd_microstep: 119.98 | bwd_inner_microstep: 119.83 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 02:08:31,763] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.21 | bwd_microstep: 273.10 | bwd_inner_microstep: 273.08 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 02:08:32,241] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.23 | bwd_microstep: 272.90 | bwd_inner_microstep: 272.88 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 02:08:32,720] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.21 | bwd_microstep: 272.49 | bwd_inner_microstep: 272.48 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 02:08:33,199] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.07 | bwd_microstep: 272.61 | bwd_inner_microstep: 272.59 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 02:08:33,677] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.44 | bwd_microstep: 272.22 | bwd_inner_microstep: 272.20 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 02:08:34,156] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.79 | bwd_microstep: 272.66 | bwd_inner_microstep: 272.64 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1351 +[2025-05-02 02:08:34,521] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 142.04 | bwd_microstep: 206.13 | bwd_inner_microstep: 206.05 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 02:08:34,997] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.31 | bwd_microstep: 271.27 | bwd_inner_microstep: 271.25 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 321 +[2025-05-02 02:08:35,215] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 77.89 | bwd_microstep: 125.89 | bwd_inner_microstep: 125.59 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1850 +[2025-05-02 02:08:35,689] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.95 | bwd_microstep: 270.93 | bwd_inner_microstep: 270.91 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1214 +[2025-05-02 02:08:36,093] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.14 | optimizer_step: 16.34 +[2025-05-02 02:08:36,094] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 123.41 | bwd_microstep: 242.88 | bwd_inner_microstep: 175.85 | bwd_allreduce_microstep: 66.92 | step_microstep: 23.55 +[2025-05-02 02:08:36,095] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2691.99 | bwd: 3969.73 | bwd_inner: 3902.06 | bwd_allreduce: 67.19 | step: 24.38 + 18%|█▊ | 1534/8720 [3:53:09<13:35:57, 6.81s/it] {'loss': 0.4561, 'grad_norm': 14.577839851379395, 'learning_rate': 9.452246917659064e-06, 'epoch': 1.76} + 18%|█▊ | 1534/8720 [3:53:09<13:35:57, 6.81s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1908 +[2025-05-02 02:08:36,580] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.71 | bwd_microstep: 275.29 | bwd_inner_microstep: 275.27 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1919 +[2025-05-02 02:08:37,061] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.47 | bwd_microstep: 276.77 | bwd_inner_microstep: 276.76 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1893 +[2025-05-02 02:08:37,541] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.85 | bwd_microstep: 275.28 | bwd_inner_microstep: 275.26 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1896 +[2025-05-02 02:08:38,020] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.83 | bwd_microstep: 274.97 | bwd_inner_microstep: 274.95 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 862 +[2025-05-02 02:08:38,271] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 101.59 | bwd_microstep: 132.94 | bwd_inner_microstep: 132.86 | bwd_allreduce_microstep: 0.03 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-02 02:08:38,755] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.05 | bwd_microstep: 273.70 | bwd_inner_microstep: 273.68 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1362 +[2025-05-02 02:08:39,122] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.53 | bwd_microstep: 207.18 | bwd_inner_microstep: 207.16 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 02:08:39,601] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.72 | bwd_microstep: 273.17 | bwd_inner_microstep: 273.15 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1103 +[2025-05-02 02:08:39,898] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 118.03 | bwd_microstep: 162.03 | bwd_inner_microstep: 161.90 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 02:08:40,380] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.67 | bwd_microstep: 273.47 | bwd_inner_microstep: 273.45 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 02:08:40,861] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.49 | bwd_microstep: 273.18 | bwd_inner_microstep: 273.17 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 02:08:41,342] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.68 | bwd_microstep: 273.66 | bwd_inner_microstep: 273.65 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 02:08:41,821] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.72 | bwd_microstep: 273.01 | bwd_inner_microstep: 272.99 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1346 +[2025-05-02 02:08:42,188] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 143.05 | bwd_microstep: 205.79 | bwd_inner_microstep: 205.77 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 6, images per sample: 6.0, dynamic token length: 1603 +[2025-05-02 02:08:42,616] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 164.19 | bwd_microstep: 243.86 | bwd_inner_microstep: 243.85 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 02:08:43,197] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.24 | optimizer_step: 16.65 +[2025-05-02 02:08:43,198] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.92 | bwd_microstep: 348.64 | bwd_inner_microstep: 271.89 | bwd_allreduce_microstep: 76.70 | step_microstep: 24.60 +[2025-05-02 02:08:43,199] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2745.15 | bwd: 4043.01 | bwd_inner: 3965.78 | bwd_allreduce: 76.89 | step: 25.60 + 18%|█▊ | 1535/8720 [3:53:16<13:46:21, 6.90s/it] {'loss': 0.7327, 'grad_norm': 7.774493217468262, 'learning_rate': 9.451401444324245e-06, 'epoch': 1.76} + 18%|█▊ | 1535/8720 [3:53:16<13:46:21, 6.90s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 02:08:43,681] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.35 | bwd_microstep: 270.31 | bwd_inner_microstep: 270.29 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2124 +[2025-05-02 02:08:44,218] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 205.78 | bwd_microstep: 313.41 | bwd_inner_microstep: 313.39 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1944 +[2025-05-02 02:08:44,723] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.37 | bwd_microstep: 289.19 | bwd_inner_microstep: 289.18 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 360 +[2025-05-02 02:08:44,969] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 107.86 | bwd_microstep: 120.65 | bwd_inner_microstep: 120.50 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 02:08:45,449] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.70 | bwd_microstep: 273.15 | bwd_inner_microstep: 273.13 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1354 +[2025-05-02 02:08:45,815] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 142.29 | bwd_microstep: 206.71 | bwd_inner_microstep: 206.56 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 02:08:46,294] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.93 | bwd_microstep: 273.03 | bwd_inner_microstep: 273.02 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 02:08:46,774] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.29 | bwd_microstep: 273.37 | bwd_inner_microstep: 273.35 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 02:08:47,252] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.97 | bwd_microstep: 272.45 | bwd_inner_microstep: 272.43 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 02:08:47,729] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.40 | bwd_microstep: 272.97 | bwd_inner_microstep: 272.95 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 02:08:48,206] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.37 | bwd_microstep: 272.69 | bwd_inner_microstep: 272.67 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 02:08:48,685] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.52 | bwd_microstep: 273.01 | bwd_inner_microstep: 272.99 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 317 +[2025-05-02 02:08:48,883] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 67.64 | bwd_microstep: 117.66 | bwd_inner_microstep: 117.35 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 317 +[2025-05-02 02:08:49,087] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 73.02 | bwd_microstep: 117.46 | bwd_inner_microstep: 117.26 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2103 +[2025-05-02 02:08:49,618] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 205.19 | bwd_microstep: 310.08 | bwd_inner_microstep: 310.06 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1967 +[2025-05-02 02:08:50,211] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.04 | optimizer_gradients: 2.08 | optimizer_step: 16.21 +[2025-05-02 02:08:50,211] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 197.64 | bwd_microstep: 357.36 | bwd_inner_microstep: 291.12 | bwd_allreduce_microstep: 66.18 | step_microstep: 23.16 +[2025-05-02 02:08:50,212] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2707.00 | bwd: 4013.56 | bwd_inner: 3946.42 | bwd_allreduce: 66.58 | step: 24.12 + 18%|█▊ | 1536/8720 [3:53:23<13:50:13, 6.93s/it] {'loss': 1.0236, 'grad_norm': 16.88024139404297, 'learning_rate': 9.450555356858253e-06, 'epoch': 1.76} + 18%|█▊ | 1536/8720 [3:53:23<13:50:13, 6.93s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 02:08:50,695] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.88 | bwd_microstep: 273.85 | bwd_inner_microstep: 273.83 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1888 +[2025-05-02 02:08:51,175] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.13 | bwd_microstep: 274.98 | bwd_inner_microstep: 274.97 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-02 02:08:51,654] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.73 | bwd_microstep: 274.45 | bwd_inner_microstep: 274.43 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1892 +[2025-05-02 02:08:52,136] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.11 | bwd_microstep: 275.92 | bwd_inner_microstep: 275.91 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-02 02:08:52,615] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.53 | bwd_microstep: 274.34 | bwd_inner_microstep: 274.32 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 02:08:53,093] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.63 | bwd_microstep: 273.43 | bwd_inner_microstep: 273.41 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1352 +[2025-05-02 02:08:53,456] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.56 | bwd_microstep: 206.33 | bwd_inner_microstep: 206.31 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 02:08:53,932] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.21 | bwd_microstep: 272.84 | bwd_inner_microstep: 272.83 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 02:08:54,410] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.40 | bwd_microstep: 273.35 | bwd_inner_microstep: 273.34 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 02:08:54,888] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.74 | bwd_microstep: 273.20 | bwd_inner_microstep: 273.18 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 02:08:55,369] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.74 | bwd_microstep: 273.70 | bwd_inner_microstep: 273.68 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 02:08:55,847] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.62 | bwd_microstep: 273.07 | bwd_inner_microstep: 273.06 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1347 +[2025-05-02 02:08:56,210] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 143.67 | bwd_microstep: 205.78 | bwd_inner_microstep: 205.75 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 02:08:56,687] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.04 | bwd_microstep: 272.78 | bwd_inner_microstep: 272.76 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 02:08:57,167] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.68 | bwd_microstep: 271.33 | bwd_inner_microstep: 271.31 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 02:08:57,757] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.12 | optimizer_step: 16.21 +[2025-05-02 02:08:57,757] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.47 | bwd_microstep: 358.28 | bwd_inner_microstep: 271.85 | bwd_allreduce_microstep: 86.38 | step_microstep: 23.93 +[2025-05-02 02:08:57,759] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2934.85 | bwd: 4327.67 | bwd_inner: 4240.94 | bwd_allreduce: 86.46 | step: 24.70 + 18%|█▊ | 1537/8720 [3:53:31<14:12:10, 7.12s/it] {'loss': 0.6409, 'grad_norm': 6.086698532104492, 'learning_rate': 9.44970865537782e-06, 'epoch': 1.76} + 18%|█▊ | 1537/8720 [3:53:31<14:12:10, 7.12s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 02:08:58,240] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.28 | bwd_microstep: 270.56 | bwd_inner_microstep: 270.54 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1966 +[2025-05-02 02:08:58,747] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 198.53 | bwd_microstep: 290.69 | bwd_inner_microstep: 290.67 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1927 +[2025-05-02 02:08:59,249] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.52 | bwd_microstep: 287.53 | bwd_inner_microstep: 287.51 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1924 +[2025-05-02 02:08:59,749] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.31 | bwd_microstep: 287.22 | bwd_inner_microstep: 287.20 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1908 +[2025-05-02 02:09:00,232] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.62 | bwd_microstep: 276.24 | bwd_inner_microstep: 276.22 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 360 +[2025-05-02 02:09:00,444] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 79.59 | bwd_microstep: 116.80 | bwd_inner_microstep: 116.54 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-02 02:09:00,925] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.30 | bwd_microstep: 274.10 | bwd_inner_microstep: 274.08 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-02 02:09:01,407] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.22 | bwd_microstep: 274.34 | bwd_inner_microstep: 274.32 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 02:09:01,888] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.05 | bwd_microstep: 273.35 | bwd_inner_microstep: 273.34 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 334 +[2025-05-02 02:09:02,117] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 96.05 | bwd_microstep: 114.97 | bwd_inner_microstep: 114.66 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 02:09:02,602] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.98 | bwd_microstep: 273.09 | bwd_inner_microstep: 273.07 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 840 +[2025-05-02 02:09:02,839] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.63 | bwd_microstep: 126.28 | bwd_inner_microstep: 126.27 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.07 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 02:09:03,317] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.14 | bwd_microstep: 272.46 | bwd_inner_microstep: 272.44 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 836 +[2025-05-02 02:09:03,553] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.87 | bwd_microstep: 125.98 | bwd_inner_microstep: 125.93 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 02:09:04,031] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.85 | bwd_microstep: 272.59 | bwd_inner_microstep: 272.58 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 02:09:04,611] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.12 | optimizer_step: 16.19 +[2025-05-02 02:09:04,612] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.25 | bwd_microstep: 350.83 | bwd_inner_microstep: 272.98 | bwd_allreduce_microstep: 77.80 | step_microstep: 23.83 +[2025-05-02 02:09:04,613] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2651.85 | bwd: 3887.11 | bwd_inner: 3808.46 | bwd_allreduce: 78.10 | step: 25.00 + 18%|█▊ | 1538/8720 [3:53:38<14:02:34, 7.04s/it] {'loss': 1.0327, 'grad_norm': 10.361868858337402, 'learning_rate': 9.44886133999976e-06, 'epoch': 1.76} + 18%|█▊ | 1538/8720 [3:53:38<14:02:34, 7.04s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1935 +[2025-05-02 02:09:05,119] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 196.24 | bwd_microstep: 287.57 | bwd_inner_microstep: 287.56 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1903 +[2025-05-02 02:09:05,602] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.71 | bwd_microstep: 276.28 | bwd_inner_microstep: 276.26 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1377 +[2025-05-02 02:09:05,970] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 142.54 | bwd_microstep: 208.16 | bwd_inner_microstep: 208.14 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 851 +[2025-05-02 02:09:06,214] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.41 | bwd_microstep: 133.08 | bwd_inner_microstep: 133.01 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 02:09:06,693] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.22 | bwd_microstep: 272.90 | bwd_inner_microstep: 272.88 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 329 +[2025-05-02 02:09:06,925] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.60 | bwd_microstep: 120.08 | bwd_inner_microstep: 119.76 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 02:09:07,404] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.92 | bwd_microstep: 273.08 | bwd_inner_microstep: 273.06 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 328 +[2025-05-02 02:09:07,626] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 90.92 | bwd_microstep: 115.26 | bwd_inner_microstep: 115.11 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 02:09:08,103] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.74 | bwd_microstep: 272.20 | bwd_inner_microstep: 272.18 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 02:09:08,581] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.79 | bwd_microstep: 272.39 | bwd_inner_microstep: 272.37 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 02:09:09,059] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.02 | bwd_microstep: 272.18 | bwd_inner_microstep: 272.16 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 02:09:09,536] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.60 | bwd_microstep: 271.25 | bwd_inner_microstep: 271.24 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 02:09:10,018] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.12 | bwd_microstep: 272.60 | bwd_inner_microstep: 272.58 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 02:09:10,502] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.04 | bwd_microstep: 272.38 | bwd_inner_microstep: 272.37 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 02:09:10,983] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.57 | bwd_microstep: 271.28 | bwd_inner_microstep: 271.26 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 02:09:11,563] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.11 | optimizer_step: 16.20 +[2025-05-02 02:09:11,564] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.92 | bwd_microstep: 347.82 | bwd_inner_microstep: 271.35 | bwd_allreduce_microstep: 76.42 | step_microstep: 23.73 +[2025-05-02 02:09:11,565] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2692.96 | bwd: 3938.58 | bwd_inner: 3861.40 | bwd_allreduce: 76.70 | step: 24.68 + 18%|█▊ | 1539/8720 [3:53:45<13:59:19, 7.01s/it] {'loss': 0.5584, 'grad_norm': 26.571760177612305, 'learning_rate': 9.44801341084097e-06, 'epoch': 1.76} + 18%|█▊ | 1539/8720 [3:53:45<13:59:19, 7.01s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 314 +[2025-05-02 02:09:11,794] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 83.61 | bwd_microstep: 125.11 | bwd_inner_microstep: 124.92 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 459 +[2025-05-02 02:09:12,016] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 85.23 | bwd_microstep: 121.27 | bwd_inner_microstep: 120.95 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.10 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 435 +[2025-05-02 02:09:12,241] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 86.44 | bwd_microstep: 122.79 | bwd_inner_microstep: 122.49 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1911 +[2025-05-02 02:09:12,726] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.21 | bwd_microstep: 277.04 | bwd_inner_microstep: 277.02 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-02 02:09:13,208] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.81 | bwd_microstep: 273.28 | bwd_inner_microstep: 273.27 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1894 +[2025-05-02 02:09:13,694] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.08 | bwd_microstep: 274.71 | bwd_inner_microstep: 274.69 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 02:09:14,174] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.18 | bwd_microstep: 272.47 | bwd_inner_microstep: 272.45 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 02:09:14,652] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.21 | bwd_microstep: 272.54 | bwd_inner_microstep: 272.52 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 842 +[2025-05-02 02:09:14,896] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.13 | bwd_microstep: 132.11 | bwd_inner_microstep: 131.85 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 02:09:15,374] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.27 | bwd_microstep: 272.50 | bwd_inner_microstep: 272.49 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 02:09:15,853] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.67 | bwd_microstep: 273.03 | bwd_inner_microstep: 273.01 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 02:09:16,333] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.13 | bwd_microstep: 273.32 | bwd_inner_microstep: 273.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 02:09:16,810] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.98 | bwd_microstep: 272.43 | bwd_inner_microstep: 272.42 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 02:09:17,288] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.00 | bwd_microstep: 272.15 | bwd_inner_microstep: 272.14 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 02:09:17,766] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.02 | bwd_microstep: 271.92 | bwd_inner_microstep: 271.90 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 835 +[2025-05-02 02:09:18,122] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.13 | optimizer_step: 16.20 +[2025-05-02 02:09:18,123] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.78 | bwd_microstep: 219.46 | bwd_inner_microstep: 142.72 | bwd_allreduce_microstep: 76.58 | step_microstep: 23.87 +[2025-05-02 02:09:18,124] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2519.38 | bwd: 3726.22 | bwd_inner: 3648.39 | bwd_allreduce: 77.05 | step: 24.84 + 18%|█▊ | 1540/8720 [3:53:51<13:42:55, 6.88s/it] {'loss': 0.5061, 'grad_norm': 4.0236406326293945, 'learning_rate': 9.447164868018434e-06, 'epoch': 1.77} + 18%|█▊ | 1540/8720 [3:53:51<13:42:55, 6.88s/it]dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 829 +[2025-05-02 02:09:18,368] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 92.64 | bwd_microstep: 129.78 | bwd_inner_microstep: 129.71 | bwd_allreduce_microstep: 0.03 | step_microstep: 0.11 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 517 +[2025-05-02 02:09:18,589] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 86.81 | bwd_microstep: 118.41 | bwd_inner_microstep: 118.26 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1910 +[2025-05-02 02:09:19,073] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.35 | bwd_microstep: 276.79 | bwd_inner_microstep: 276.77 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1897 +[2025-05-02 02:09:19,555] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.95 | bwd_microstep: 275.68 | bwd_inner_microstep: 275.66 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 844 +[2025-05-02 02:09:19,800] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 96.08 | bwd_microstep: 132.00 | bwd_inner_microstep: 131.98 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 845 +[2025-05-02 02:09:20,044] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.99 | bwd_microstep: 132.61 | bwd_inner_microstep: 132.52 | bwd_allreduce_microstep: 0.04 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 02:09:20,523] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.12 | bwd_microstep: 272.53 | bwd_inner_microstep: 272.52 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 02:09:21,002] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.77 | bwd_microstep: 273.01 | bwd_inner_microstep: 272.99 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 02:09:21,484] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.12 | bwd_microstep: 272.10 | bwd_inner_microstep: 272.09 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 02:09:21,965] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.25 | bwd_microstep: 272.33 | bwd_inner_microstep: 272.31 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 02:09:22,446] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.16 | bwd_microstep: 272.58 | bwd_inner_microstep: 272.56 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 02:09:22,924] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.43 | bwd_microstep: 272.61 | bwd_inner_microstep: 272.60 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 02:09:23,402] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.52 | bwd_microstep: 272.72 | bwd_inner_microstep: 272.70 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 02:09:23,878] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.58 | bwd_microstep: 272.44 | bwd_inner_microstep: 272.42 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 02:09:24,354] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.79 | bwd_microstep: 271.40 | bwd_inner_microstep: 271.39 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 830 +[2025-05-02 02:09:24,681] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.06 | optimizer_step: 16.18 +[2025-05-02 02:09:24,682] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 92.76 | bwd_microstep: 197.95 | bwd_inner_microstep: 130.53 | bwd_allreduce_microstep: 67.26 | step_microstep: 23.24 +[2025-05-02 02:09:24,683] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2537.98 | bwd: 3715.03 | bwd_inner: 3647.10 | bwd_allreduce: 67.45 | step: 24.33 + 18%|█▊ | 1541/8720 [3:53:58<13:31:20, 6.78s/it] {'loss': 0.5139, 'grad_norm': 11.77314567565918, 'learning_rate': 9.446315711649222e-06, 'epoch': 1.77} + 18%|█▊ | 1541/8720 [3:53:58<13:31:20, 6.78s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2141 +[2025-05-02 02:09:25,223] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 205.77 | bwd_microstep: 314.17 | bwd_inner_microstep: 314.16 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1920 +[2025-05-02 02:09:25,705] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.22 | bwd_microstep: 276.47 | bwd_inner_microstep: 276.45 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1908 +[2025-05-02 02:09:26,185] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.63 | bwd_microstep: 275.99 | bwd_inner_microstep: 275.97 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1886 +[2025-05-02 02:09:26,664] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.57 | bwd_microstep: 274.33 | bwd_inner_microstep: 274.32 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1891 +[2025-05-02 02:09:27,145] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.47 | bwd_microstep: 275.00 | bwd_inner_microstep: 274.99 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 327 +[2025-05-02 02:09:27,369] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 89.82 | bwd_microstep: 117.52 | bwd_inner_microstep: 117.37 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 02:09:27,846] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.94 | bwd_microstep: 272.64 | bwd_inner_microstep: 272.62 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 02:09:28,324] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.26 | bwd_microstep: 272.67 | bwd_inner_microstep: 272.65 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 02:09:28,800] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.86 | bwd_microstep: 272.51 | bwd_inner_microstep: 272.50 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 02:09:29,280] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.40 | bwd_microstep: 272.29 | bwd_inner_microstep: 272.27 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1092 +[2025-05-02 02:09:29,570] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 114.84 | bwd_microstep: 160.90 | bwd_inner_microstep: 160.85 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 02:09:30,045] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.66 | bwd_microstep: 271.13 | bwd_inner_microstep: 271.12 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 02:09:30,519] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.40 | bwd_microstep: 270.92 | bwd_inner_microstep: 270.90 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 02:09:30,998] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.27 | bwd_microstep: 271.28 | bwd_inner_microstep: 271.26 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 02:09:31,477] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.98 | bwd_microstep: 271.35 | bwd_inner_microstep: 271.34 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 02:09:32,063] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.07 | optimizer_gradients: 2.10 | optimizer_step: 16.25 +[2025-05-02 02:09:32,063] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.29 | bwd_microstep: 355.29 | bwd_inner_microstep: 271.43 | bwd_allreduce_microstep: 83.80 | step_microstep: 23.99 +[2025-05-02 02:09:32,065] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2861.07 | bwd: 4224.51 | bwd_inner: 4140.21 | bwd_allreduce: 83.96 | step: 24.78 + 18%|█▊ | 1542/8720 [3:54:05<13:52:50, 6.96s/it] {'loss': 0.7053, 'grad_norm': 17.963096618652344, 'learning_rate': 9.445465941850482e-06, 'epoch': 1.77} + 18%|█▊ | 1542/8720 [3:54:05<13:52:50, 6.96s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 02:09:32,544] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.12 | bwd_microstep: 270.23 | bwd_inner_microstep: 270.21 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1413 +[2025-05-02 02:09:32,917] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 143.35 | bwd_microstep: 212.69 | bwd_inner_microstep: 212.67 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1893 +[2025-05-02 02:09:33,399] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.48 | bwd_microstep: 275.04 | bwd_inner_microstep: 275.02 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1896 +[2025-05-02 02:09:33,881] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.67 | bwd_microstep: 275.16 | bwd_inner_microstep: 275.15 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1889 +[2025-05-02 02:09:34,361] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.67 | bwd_microstep: 274.73 | bwd_inner_microstep: 274.72 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 02:09:34,837] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.44 | bwd_microstep: 272.96 | bwd_inner_microstep: 272.94 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 02:09:35,313] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.95 | bwd_microstep: 272.78 | bwd_inner_microstep: 272.76 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 02:09:35,791] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.95 | bwd_microstep: 272.40 | bwd_inner_microstep: 272.38 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 02:09:36,270] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.87 | bwd_microstep: 272.67 | bwd_inner_microstep: 272.65 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 327 +[2025-05-02 02:09:36,489] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 87.37 | bwd_microstep: 116.17 | bwd_inner_microstep: 115.88 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 02:09:36,967] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.06 | bwd_microstep: 272.29 | bwd_inner_microstep: 272.27 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 02:09:37,446] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.94 | bwd_microstep: 271.37 | bwd_inner_microstep: 271.35 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 02:09:37,925] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.26 | bwd_microstep: 272.16 | bwd_inner_microstep: 272.14 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 829 +[2025-05-02 02:09:38,167] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.28 | bwd_microstep: 129.87 | bwd_inner_microstep: 129.64 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.19 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 829 +[2025-05-02 02:09:38,409] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.62 | bwd_microstep: 129.66 | bwd_inner_microstep: 129.64 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 02:09:38,990] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.15 | optimizer_step: 16.95 +[2025-05-02 02:09:38,991] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.73 | bwd_microstep: 348.94 | bwd_inner_microstep: 271.61 | bwd_allreduce_microstep: 77.28 | step_microstep: 24.90 +[2025-05-02 02:09:38,992] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2682.42 | bwd: 3939.18 | bwd_inner: 3861.10 | bwd_allreduce: 77.58 | step: 26.09 + 18%|█▊ | 1543/8720 [3:54:12<13:51:30, 6.95s/it] {'loss': 0.5806, 'grad_norm': 12.733270645141602, 'learning_rate': 9.444615558739456e-06, 'epoch': 1.77} + 18%|█▊ | 1543/8720 [3:54:12<13:51:30, 6.95s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-02 02:09:39,478] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.52 | bwd_microstep: 273.57 | bwd_inner_microstep: 273.55 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1893 +[2025-05-02 02:09:39,957] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.44 | bwd_microstep: 274.76 | bwd_inner_microstep: 274.75 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 852 +[2025-05-02 02:09:40,199] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.07 | bwd_microstep: 132.85 | bwd_inner_microstep: 132.58 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 02:09:40,676] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.47 | bwd_microstep: 273.15 | bwd_inner_microstep: 273.14 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 02:09:41,153] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.91 | bwd_microstep: 272.76 | bwd_inner_microstep: 272.74 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 02:09:41,629] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.90 | bwd_microstep: 272.71 | bwd_inner_microstep: 272.69 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 02:09:42,107] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.63 | bwd_microstep: 272.96 | bwd_inner_microstep: 272.94 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-02 02:09:42,584] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.47 | bwd_microstep: 273.16 | bwd_inner_microstep: 273.15 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 843 +[2025-05-02 02:09:42,824] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.43 | bwd_microstep: 132.10 | bwd_inner_microstep: 132.03 | bwd_allreduce_microstep: 0.03 | step_microstep: 0.10 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 330 +[2025-05-02 02:09:43,034] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 69.34 | bwd_microstep: 126.57 | bwd_inner_microstep: 126.39 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1351 +[2025-05-02 02:09:43,396] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.99 | bwd_microstep: 205.84 | bwd_inner_microstep: 205.82 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 02:09:43,874] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.36 | bwd_microstep: 272.80 | bwd_inner_microstep: 272.78 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 02:09:44,353] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.27 | bwd_microstep: 272.67 | bwd_inner_microstep: 272.65 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 836 +[2025-05-02 02:09:44,585] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 91.91 | bwd_microstep: 126.34 | bwd_inner_microstep: 126.12 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 02:09:45,061] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.18 | bwd_microstep: 272.45 | bwd_inner_microstep: 272.44 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 02:09:45,628] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.16 | optimizer_step: 16.58 +[2025-05-02 02:09:45,629] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.91 | bwd_microstep: 339.53 | bwd_inner_microstep: 271.92 | bwd_allreduce_microstep: 67.57 | step_microstep: 23.86 +[2025-05-02 02:09:45,630] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2565.52 | bwd: 3794.30 | bwd_inner: 3725.80 | bwd_allreduce: 67.93 | step: 24.77 + 18%|█▊ | 1544/8720 [3:54:19<13:40:04, 6.86s/it] {'loss': 0.5344, 'grad_norm': 9.308890342712402, 'learning_rate': 9.443764562433464e-06, 'epoch': 1.77} + 18%|█▊ | 1544/8720 [3:54:19<13:40:04, 6.86s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 02:09:46,109] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.43 | bwd_microstep: 270.70 | bwd_inner_microstep: 270.68 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1966 +[2025-05-02 02:09:46,612] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 197.08 | bwd_microstep: 290.16 | bwd_inner_microstep: 290.14 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1396 +[2025-05-02 02:09:46,980] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 144.46 | bwd_microstep: 209.47 | bwd_inner_microstep: 209.45 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1131 +[2025-05-02 02:09:47,278] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 117.89 | bwd_microstep: 163.78 | bwd_inner_microstep: 163.57 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1896 +[2025-05-02 02:09:47,759] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.64 | bwd_microstep: 274.40 | bwd_inner_microstep: 274.38 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1896 +[2025-05-02 02:09:48,244] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.04 | bwd_microstep: 274.96 | bwd_inner_microstep: 274.94 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-02 02:09:48,726] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.70 | bwd_microstep: 273.30 | bwd_inner_microstep: 273.28 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-02 02:09:49,206] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.59 | bwd_microstep: 273.46 | bwd_inner_microstep: 273.45 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 02:09:49,688] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.99 | bwd_microstep: 273.07 | bwd_inner_microstep: 273.05 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 02:09:50,170] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.56 | bwd_microstep: 273.04 | bwd_inner_microstep: 273.02 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 847 +[2025-05-02 02:09:50,421] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 98.25 | bwd_microstep: 132.26 | bwd_inner_microstep: 132.07 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 324 +[2025-05-02 02:09:50,644] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 88.26 | bwd_microstep: 118.77 | bwd_inner_microstep: 118.52 | bwd_allreduce_microstep: 0.10 | step_microstep: 0.11 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1349 +[2025-05-02 02:09:51,008] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.59 | bwd_microstep: 205.93 | bwd_inner_microstep: 205.76 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 02:09:51,485] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.88 | bwd_microstep: 271.07 | bwd_inner_microstep: 271.06 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 02:09:51,962] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.90 | bwd_microstep: 271.15 | bwd_inner_microstep: 271.13 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 02:09:52,531] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.25 | optimizer_step: 16.58 +[2025-05-02 02:09:52,531] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.36 | bwd_microstep: 340.28 | bwd_inner_microstep: 271.35 | bwd_allreduce_microstep: 68.88 | step_microstep: 23.90 +[2025-05-02 02:09:52,533] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2671.26 | bwd: 3915.86 | bwd_inner: 3845.94 | bwd_allreduce: 69.32 | step: 24.87 + 18%|█▊ | 1545/8720 [3:54:26<13:41:36, 6.87s/it] {'loss': 0.6156, 'grad_norm': 5.085261821746826, 'learning_rate': 9.44291295304991e-06, 'epoch': 1.77} + 18%|█▊ | 1545/8720 [3:54:26<13:41:36, 6.87s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1924 +[2025-05-02 02:09:53,034] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 194.53 | bwd_microstep: 286.56 | bwd_inner_microstep: 286.54 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1898 +[2025-05-02 02:09:53,515] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.45 | bwd_microstep: 275.93 | bwd_inner_microstep: 275.92 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1892 +[2025-05-02 02:09:53,995] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.42 | bwd_microstep: 274.79 | bwd_inner_microstep: 274.77 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-02 02:09:54,473] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.83 | bwd_microstep: 273.64 | bwd_inner_microstep: 273.62 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1887 +[2025-05-02 02:09:54,952] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.33 | bwd_microstep: 274.67 | bwd_inner_microstep: 274.65 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 02:09:55,429] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.76 | bwd_microstep: 272.82 | bwd_inner_microstep: 272.81 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 02:09:55,907] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.98 | bwd_microstep: 272.97 | bwd_inner_microstep: 272.96 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 02:09:56,383] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.58 | bwd_microstep: 272.40 | bwd_inner_microstep: 272.38 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 02:09:56,861] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.25 | bwd_microstep: 273.31 | bwd_inner_microstep: 273.29 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 02:09:57,336] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.77 | bwd_microstep: 272.08 | bwd_inner_microstep: 272.06 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 02:09:57,812] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.07 | bwd_microstep: 271.93 | bwd_inner_microstep: 271.91 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1089 +[2025-05-02 02:09:58,105] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 117.99 | bwd_microstep: 160.88 | bwd_inner_microstep: 160.67 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 02:09:58,581] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.04 | bwd_microstep: 273.22 | bwd_inner_microstep: 273.20 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 02:09:59,056] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.72 | bwd_microstep: 271.28 | bwd_inner_microstep: 271.26 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 322 +[2025-05-02 02:09:59,271] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 76.96 | bwd_microstep: 123.53 | bwd_inner_microstep: 123.20 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 02:09:59,837] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.19 | optimizer_step: 16.55 +[2025-05-02 02:09:59,837] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.00 | bwd_microstep: 338.37 | bwd_inner_microstep: 272.03 | bwd_allreduce_microstep: 66.30 | step_microstep: 23.82 +[2025-05-02 02:09:59,838] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2840.42 | bwd: 4188.43 | bwd_inner: 4121.33 | bwd_allreduce: 66.61 | step: 24.58 + 18%|█▊ | 1546/8720 [3:54:33<13:57:06, 7.00s/it] {'loss': 1.0917, 'grad_norm': 21.37537384033203, 'learning_rate': 9.44206073070629e-06, 'epoch': 1.77} + 18%|█▊ | 1546/8720 [3:54:33<13:57:06, 7.00s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2067 +[2025-05-02 02:10:00,362] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 201.41 | bwd_microstep: 301.82 | bwd_inner_microstep: 301.80 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1896 +[2025-05-02 02:10:00,841] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.84 | bwd_microstep: 275.32 | bwd_inner_microstep: 275.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1888 +[2025-05-02 02:10:01,320] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.10 | bwd_microstep: 274.17 | bwd_inner_microstep: 274.16 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1366 +[2025-05-02 02:10:01,684] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.99 | bwd_microstep: 207.01 | bwd_inner_microstep: 206.94 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 02:10:02,164] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.13 | bwd_microstep: 273.80 | bwd_inner_microstep: 273.78 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-02 02:10:02,645] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.59 | bwd_microstep: 273.44 | bwd_inner_microstep: 273.42 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 02:10:03,126] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.41 | bwd_microstep: 273.05 | bwd_inner_microstep: 273.04 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-02 02:10:03,607] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.91 | bwd_microstep: 273.80 | bwd_inner_microstep: 273.78 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 02:10:04,086] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.39 | bwd_microstep: 272.56 | bwd_inner_microstep: 272.54 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 02:10:04,564] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.52 | bwd_microstep: 273.35 | bwd_inner_microstep: 273.33 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 02:10:05,041] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.14 | bwd_microstep: 272.79 | bwd_inner_microstep: 272.77 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 843 +[2025-05-02 02:10:05,281] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.75 | bwd_microstep: 132.01 | bwd_inner_microstep: 131.95 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 02:10:05,757] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.89 | bwd_microstep: 272.54 | bwd_inner_microstep: 272.52 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 02:10:06,233] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.93 | bwd_microstep: 272.58 | bwd_inner_microstep: 272.57 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 02:10:06,710] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.11 | bwd_microstep: 272.29 | bwd_inner_microstep: 272.27 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.14 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 02:10:07,288] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.20 | optimizer_step: 16.51 +[2025-05-02 02:10:07,289] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.15 | bwd_microstep: 350.14 | bwd_inner_microstep: 271.75 | bwd_allreduce_microstep: 78.34 | step_microstep: 24.54 +[2025-05-02 02:10:07,290] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2890.95 | bwd: 4270.72 | bwd_inner: 4191.93 | bwd_allreduce: 78.50 | step: 25.42 + 18%|█▊ | 1547/8720 [3:54:41<14:13:12, 7.14s/it] {'loss': 0.5334, 'grad_norm': 6.201137542724609, 'learning_rate': 9.441207895520176e-06, 'epoch': 1.77} + 18%|█▊ | 1547/8720 [3:54:41<14:13:12, 7.14s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 02:10:07,771] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.31 | bwd_microstep: 270.79 | bwd_inner_microstep: 270.77 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1894 +[2025-05-02 02:10:08,251] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.50 | bwd_microstep: 274.85 | bwd_inner_microstep: 274.83 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-02 02:10:08,730] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.68 | bwd_microstep: 273.99 | bwd_inner_microstep: 273.97 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-02 02:10:09,210] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.22 | bwd_microstep: 273.72 | bwd_inner_microstep: 273.70 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 02:10:09,692] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.04 | bwd_microstep: 273.50 | bwd_inner_microstep: 273.49 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-02 02:10:10,176] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.34 | bwd_microstep: 273.85 | bwd_inner_microstep: 273.84 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 02:10:10,660] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.15 | bwd_microstep: 273.55 | bwd_inner_microstep: 273.53 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 326 +[2025-05-02 02:10:10,877] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 82.09 | bwd_microstep: 118.39 | bwd_inner_microstep: 118.13 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 02:10:11,356] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.14 | bwd_microstep: 273.77 | bwd_inner_microstep: 273.76 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 847 +[2025-05-02 02:10:11,599] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.06 | bwd_microstep: 132.51 | bwd_inner_microstep: 132.29 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 02:10:12,078] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.15 | bwd_microstep: 272.62 | bwd_inner_microstep: 272.60 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 326 +[2025-05-02 02:10:12,311] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.75 | bwd_microstep: 117.53 | bwd_inner_microstep: 117.27 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 02:10:12,796] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.32 | bwd_microstep: 272.51 | bwd_inner_microstep: 272.49 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 02:10:13,272] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.49 | bwd_microstep: 271.62 | bwd_inner_microstep: 271.60 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 02:10:13,748] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.47 | bwd_microstep: 270.89 | bwd_inner_microstep: 270.88 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 827 +[2025-05-02 02:10:14,105] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.17 | optimizer_step: 16.50 +[2025-05-02 02:10:14,105] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.95 | bwd_microstep: 220.96 | bwd_inner_microstep: 144.30 | bwd_allreduce_microstep: 76.50 | step_microstep: 24.20 +[2025-05-02 02:10:14,107] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2627.27 | bwd: 3865.15 | bwd_inner: 3787.65 | bwd_allreduce: 76.82 | step: 25.21 + 18%|█▊ | 1548/8720 [3:54:47<14:01:35, 7.04s/it] {'loss': 0.5256, 'grad_norm': 8.927276611328125, 'learning_rate': 9.440354447609227e-06, 'epoch': 1.78} + 18%|█▊ | 1548/8720 [3:54:47<14:01:35, 7.04s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1931 +[2025-05-02 02:10:14,612] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.51 | bwd_microstep: 287.09 | bwd_inner_microstep: 287.07 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 458 +[2025-05-02 02:10:14,839] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 88.31 | bwd_microstep: 121.54 | bwd_inner_microstep: 121.24 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1935 +[2025-05-02 02:10:15,341] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.55 | bwd_microstep: 287.78 | bwd_inner_microstep: 287.76 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1917 +[2025-05-02 02:10:15,826] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.58 | bwd_microstep: 276.38 | bwd_inner_microstep: 276.36 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1386 +[2025-05-02 02:10:16,199] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.70 | bwd_microstep: 209.08 | bwd_inner_microstep: 208.96 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.11 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1124 +[2025-05-02 02:10:16,504] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 119.25 | bwd_microstep: 163.41 | bwd_inner_microstep: 163.29 | bwd_allreduce_microstep: 0.08 | step_microstep: 0.09 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 345 +[2025-05-02 02:10:16,732] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 82.80 | bwd_microstep: 129.55 | bwd_inner_microstep: 129.39 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1368 +[2025-05-02 02:10:17,099] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 142.20 | bwd_microstep: 207.49 | bwd_inner_microstep: 207.47 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1883 +[2025-05-02 02:10:17,584] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.74 | bwd_microstep: 274.61 | bwd_inner_microstep: 274.59 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 02:10:18,064] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.37 | bwd_microstep: 272.84 | bwd_inner_microstep: 272.82 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 02:10:18,544] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.50 | bwd_microstep: 272.81 | bwd_inner_microstep: 272.79 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 02:10:19,026] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.96 | bwd_microstep: 272.81 | bwd_inner_microstep: 272.80 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 02:10:19,507] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.44 | bwd_microstep: 272.90 | bwd_inner_microstep: 272.88 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 02:10:19,987] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.18 | bwd_microstep: 271.47 | bwd_inner_microstep: 271.46 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 02:10:20,469] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.08 | bwd_microstep: 272.26 | bwd_inner_microstep: 272.24 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 02:10:21,049] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.21 | optimizer_step: 16.43 +[2025-05-02 02:10:21,050] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.17 | bwd_microstep: 351.10 | bwd_inner_microstep: 271.78 | bwd_allreduce_microstep: 79.27 | step_microstep: 24.30 +[2025-05-02 02:10:21,051] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2666.93 | bwd: 3943.20 | bwd_inner: 3862.98 | bwd_allreduce: 79.69 | step: 25.51 + 18%|█▊ | 1549/8720 [3:54:54<13:58:02, 7.01s/it] {'loss': 0.9914, 'grad_norm': 21.06898307800293, 'learning_rate': 9.439500387091192e-06, 'epoch': 1.78} + 18%|█▊ | 1549/8720 [3:54:54<13:58:02, 7.01s/it]dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 872 +[2025-05-02 02:10:21,311] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 97.79 | bwd_microstep: 140.00 | bwd_inner_microstep: 139.93 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.10 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 367 +[2025-05-02 02:10:21,539] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 80.51 | bwd_microstep: 131.98 | bwd_inner_microstep: 131.83 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 364 +[2025-05-02 02:10:21,770] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.21 | bwd_microstep: 121.05 | bwd_inner_microstep: 120.80 | bwd_allreduce_microstep: 0.08 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1897 +[2025-05-02 02:10:22,252] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.52 | bwd_microstep: 275.45 | bwd_inner_microstep: 275.43 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 354 +[2025-05-02 02:10:22,486] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 96.25 | bwd_microstep: 120.05 | bwd_inner_microstep: 119.75 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1888 +[2025-05-02 02:10:22,968] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.05 | bwd_microstep: 274.70 | bwd_inner_microstep: 274.68 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1893 +[2025-05-02 02:10:23,456] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.98 | bwd_microstep: 275.46 | bwd_inner_microstep: 275.44 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 349 +[2025-05-02 02:10:23,684] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.65 | bwd_microstep: 115.73 | bwd_inner_microstep: 115.58 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 02:10:24,163] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.85 | bwd_microstep: 273.81 | bwd_inner_microstep: 273.80 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 02:10:24,644] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.27 | bwd_microstep: 272.71 | bwd_inner_microstep: 272.69 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 02:10:25,125] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.81 | bwd_microstep: 273.00 | bwd_inner_microstep: 272.98 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 327 +[2025-05-02 02:10:25,341] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 81.85 | bwd_microstep: 118.21 | bwd_inner_microstep: 118.03 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 02:10:25,819] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.95 | bwd_microstep: 272.05 | bwd_inner_microstep: 272.04 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 837 +[2025-05-02 02:10:26,061] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 96.66 | bwd_microstep: 126.01 | bwd_inner_microstep: 125.74 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 02:10:26,538] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.83 | bwd_microstep: 271.91 | bwd_inner_microstep: 271.90 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 02:10:27,116] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.14 | optimizer_step: 16.38 +[2025-05-02 02:10:27,116] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.44 | bwd_microstep: 348.13 | bwd_inner_microstep: 271.33 | bwd_allreduce_microstep: 76.74 | step_microstep: 24.10 +[2025-05-02 02:10:27,118] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2342.23 | bwd: 3410.39 | bwd_inner: 3332.18 | bwd_allreduce: 77.32 | step: 25.24 + 18%|█▊ | 1550/8720 [3:55:00<13:24:01, 6.73s/it] {'loss': 0.8429, 'grad_norm': 14.2042818069458, 'learning_rate': 9.438645714083899e-06, 'epoch': 1.78} + 18%|█▊ | 1550/8720 [3:55:00<13:24:01, 6.73s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 315 +[2025-05-02 02:10:27,334] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 78.88 | bwd_microstep: 116.16 | bwd_inner_microstep: 115.85 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1988 +[2025-05-02 02:10:27,841] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 197.26 | bwd_microstep: 293.25 | bwd_inner_microstep: 293.23 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1893 +[2025-05-02 02:10:28,323] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.43 | bwd_microstep: 275.28 | bwd_inner_microstep: 275.26 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.14 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 348 +[2025-05-02 02:10:28,540] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 81.77 | bwd_microstep: 119.00 | bwd_inner_microstep: 118.83 | bwd_allreduce_microstep: 0.08 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1891 +[2025-05-02 02:10:29,021] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.65 | bwd_microstep: 275.30 | bwd_inner_microstep: 275.28 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 02:10:29,503] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.20 | bwd_microstep: 273.77 | bwd_inner_microstep: 273.75 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1898 +[2025-05-02 02:10:29,987] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.02 | bwd_microstep: 275.46 | bwd_inner_microstep: 275.45 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.11 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 337 +[2025-05-02 02:10:30,202] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 80.20 | bwd_microstep: 118.63 | bwd_inner_microstep: 118.31 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-02 02:10:30,681] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.44 | bwd_microstep: 273.21 | bwd_inner_microstep: 273.20 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 02:10:31,160] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.11 | bwd_microstep: 272.70 | bwd_inner_microstep: 272.68 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 02:10:31,640] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.12 | bwd_microstep: 272.59 | bwd_inner_microstep: 272.58 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1352 +[2025-05-02 02:10:32,004] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.69 | bwd_microstep: 206.14 | bwd_inner_microstep: 206.12 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 02:10:32,483] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.38 | bwd_microstep: 272.39 | bwd_inner_microstep: 272.37 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 02:10:32,961] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.16 | bwd_microstep: 272.11 | bwd_inner_microstep: 272.09 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 02:10:33,443] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.08 | bwd_microstep: 272.41 | bwd_inner_microstep: 272.39 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 02:10:34,022] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.21 | optimizer_step: 16.42 +[2025-05-02 02:10:34,023] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.40 | bwd_microstep: 349.63 | bwd_inner_microstep: 272.50 | bwd_allreduce_microstep: 77.08 | step_microstep: 24.35 +[2025-05-02 02:10:34,024] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2655.44 | bwd: 3938.09 | bwd_inner: 3860.04 | bwd_allreduce: 77.46 | step: 25.51 + 18%|█▊ | 1551/8720 [3:55:07<13:30:17, 6.78s/it] {'loss': 0.7275, 'grad_norm': 8.443130493164062, 'learning_rate': 9.43779042870526e-06, 'epoch': 1.78} + 18%|█▊ | 1551/8720 [3:55:07<13:30:17, 6.78s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 02:10:34,505] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.75 | bwd_microstep: 270.56 | bwd_inner_microstep: 270.54 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2053 +[2025-05-02 02:10:35,024] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 200.48 | bwd_microstep: 302.08 | bwd_inner_microstep: 302.06 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1417 +[2025-05-02 02:10:35,400] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 145.46 | bwd_microstep: 213.36 | bwd_inner_microstep: 213.34 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 368 +[2025-05-02 02:10:35,637] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.82 | bwd_microstep: 122.73 | bwd_inner_microstep: 122.56 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.11 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 353 +[2025-05-02 02:10:35,892] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 89.38 | bwd_microstep: 147.57 | bwd_inner_microstep: 147.32 | bwd_allreduce_microstep: 0.10 | step_microstep: 0.10 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1359 +[2025-05-02 02:10:36,256] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.31 | bwd_microstep: 206.65 | bwd_inner_microstep: 206.63 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.07 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 02:10:36,738] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.02 | bwd_microstep: 272.96 | bwd_inner_microstep: 272.94 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 324 +[2025-05-02 02:10:36,957] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 79.78 | bwd_microstep: 123.73 | bwd_inner_microstep: 123.48 | bwd_allreduce_microstep: 0.10 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 02:10:37,436] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.91 | bwd_microstep: 272.82 | bwd_inner_microstep: 272.81 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1094 +[2025-05-02 02:10:37,730] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 116.28 | bwd_microstep: 161.04 | bwd_inner_microstep: 160.82 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 02:10:38,211] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.32 | bwd_microstep: 272.95 | bwd_inner_microstep: 272.93 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 02:10:38,690] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.43 | bwd_microstep: 272.34 | bwd_inner_microstep: 272.33 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 02:10:39,168] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.15 | bwd_microstep: 272.62 | bwd_inner_microstep: 272.60 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 02:10:39,645] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.72 | bwd_microstep: 271.43 | bwd_inner_microstep: 271.42 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 02:10:40,124] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.05 | bwd_microstep: 272.00 | bwd_inner_microstep: 271.99 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1341 +[2025-05-02 02:10:40,603] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.19 | optimizer_step: 16.40 +[2025-05-02 02:10:40,603] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.18 | bwd_microstep: 294.28 | bwd_inner_microstep: 204.90 | bwd_allreduce_microstep: 89.28 | step_microstep: 24.16 +[2025-05-02 02:10:40,605] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2513.65 | bwd: 3749.19 | bwd_inner: 3658.82 | bwd_allreduce: 89.68 | step: 25.18 + 18%|█▊ | 1552/8720 [3:55:14<13:22:58, 6.72s/it] {'loss': 0.5412, 'grad_norm': 7.248950004577637, 'learning_rate': 9.436934531073274e-06, 'epoch': 1.78} + 18%|█▊ | 1552/8720 [3:55:14<13:22:58, 6.72s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 02:10:41,085] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.96 | bwd_microstep: 270.12 | bwd_inner_microstep: 270.11 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 967 +[2025-05-02 02:10:41,363] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 108.90 | bwd_microstep: 150.10 | bwd_inner_microstep: 149.90 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.09 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1413 +[2025-05-02 02:10:41,735] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 143.04 | bwd_microstep: 212.98 | bwd_inner_microstep: 212.89 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-02 02:10:42,215] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.12 | bwd_microstep: 273.64 | bwd_inner_microstep: 273.62 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-02 02:10:42,699] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.30 | bwd_microstep: 274.20 | bwd_inner_microstep: 274.18 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 847 +[2025-05-02 02:10:42,948] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 96.92 | bwd_microstep: 132.46 | bwd_inner_microstep: 132.23 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-02 02:10:43,428] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.22 | bwd_microstep: 273.12 | bwd_inner_microstep: 273.10 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 02:10:43,906] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.43 | bwd_microstep: 272.69 | bwd_inner_microstep: 272.68 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 02:10:44,383] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.89 | bwd_microstep: 272.49 | bwd_inner_microstep: 272.47 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 02:10:44,858] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.50 | bwd_microstep: 272.70 | bwd_inner_microstep: 272.68 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 326 +[2025-05-02 02:10:45,068] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 75.71 | bwd_microstep: 120.42 | bwd_inner_microstep: 120.23 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 02:10:45,545] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.26 | bwd_microstep: 272.38 | bwd_inner_microstep: 272.36 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 02:10:46,020] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.91 | bwd_microstep: 272.23 | bwd_inner_microstep: 272.22 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 02:10:46,495] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.65 | bwd_microstep: 272.35 | bwd_inner_microstep: 272.34 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 02:10:46,970] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.52 | bwd_microstep: 271.16 | bwd_inner_microstep: 271.14 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 02:10:47,535] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.04 | optimizer_gradients: 2.16 | optimizer_step: 16.37 +[2025-05-02 02:10:47,535] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.82 | bwd_microstep: 338.21 | bwd_inner_microstep: 271.67 | bwd_allreduce_microstep: 66.50 | step_microstep: 23.40 +[2025-05-02 02:10:47,536] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2682.85 | bwd: 3951.31 | bwd_inner: 3883.88 | bwd_allreduce: 66.88 | step: 24.41 + 18%|█▊ | 1553/8720 [3:55:21<13:30:19, 6.78s/it] {'loss': 0.8154, 'grad_norm': 9.339883804321289, 'learning_rate': 9.436078021306022e-06, 'epoch': 1.78} + 18%|█▊ | 1553/8720 [3:55:21<13:30:19, 6.78s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 02:10:48,013] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.27 | bwd_microstep: 270.06 | bwd_inner_microstep: 270.05 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1886 +[2025-05-02 02:10:48,492] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.81 | bwd_microstep: 274.47 | bwd_inner_microstep: 274.45 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 334 +[2025-05-02 02:10:48,701] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 73.63 | bwd_microstep: 121.98 | bwd_inner_microstep: 121.71 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 02:10:49,177] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.90 | bwd_microstep: 273.09 | bwd_inner_microstep: 273.08 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 02:10:49,653] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.49 | bwd_microstep: 272.24 | bwd_inner_microstep: 272.22 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 02:10:50,131] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.55 | bwd_microstep: 272.86 | bwd_inner_microstep: 272.84 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 328 +[2025-05-02 02:10:50,344] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 75.52 | bwd_microstep: 122.75 | bwd_inner_microstep: 122.62 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 02:10:50,819] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.42 | bwd_microstep: 272.36 | bwd_inner_microstep: 272.34 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 02:10:51,293] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.24 | bwd_microstep: 271.08 | bwd_inner_microstep: 271.07 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 02:10:51,768] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.45 | bwd_microstep: 271.33 | bwd_inner_microstep: 271.31 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 02:10:52,242] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.88 | bwd_microstep: 271.17 | bwd_inner_microstep: 271.16 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 02:10:52,719] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.66 | bwd_microstep: 270.97 | bwd_inner_microstep: 270.95 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 02:10:53,199] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.75 | bwd_microstep: 271.10 | bwd_inner_microstep: 271.08 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 02:10:53,677] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.65 | bwd_microstep: 271.04 | bwd_inner_microstep: 271.02 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 02:10:54,154] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.45 | bwd_microstep: 270.73 | bwd_inner_microstep: 270.72 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 02:10:54,731] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.04 | optimizer_gradients: 2.23 | optimizer_step: 16.42 +[2025-05-02 02:10:54,732] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.07 | bwd_microstep: 348.16 | bwd_inner_microstep: 271.39 | bwd_allreduce_microstep: 76.71 | step_microstep: 23.86 +[2025-05-02 02:10:54,733] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2782.42 | bwd: 4125.42 | bwd_inner: 4048.08 | bwd_allreduce: 76.95 | step: 24.64 + 18%|█▊ | 1554/8720 [3:55:28<13:45:00, 6.91s/it] {'loss': 0.6822, 'grad_norm': 16.200199127197266, 'learning_rate': 9.435220899521675e-06, 'epoch': 1.78} + 18%|█▊ | 1554/8720 [3:55:28<13:45:00, 6.91s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 02:10:55,210] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.47 | bwd_microstep: 270.31 | bwd_inner_microstep: 270.29 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2053 +[2025-05-02 02:10:55,727] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 201.08 | bwd_microstep: 300.99 | bwd_inner_microstep: 300.97 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1915 +[2025-05-02 02:10:56,209] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.66 | bwd_microstep: 276.31 | bwd_inner_microstep: 276.29 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 02:10:56,687] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.04 | bwd_microstep: 272.64 | bwd_inner_microstep: 272.63 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1356 +[2025-05-02 02:10:57,049] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.11 | bwd_microstep: 206.22 | bwd_inner_microstep: 206.09 | bwd_allreduce_microstep: 0.04 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 02:10:57,527] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.74 | bwd_microstep: 273.39 | bwd_inner_microstep: 273.37 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 02:10:58,004] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.45 | bwd_microstep: 272.49 | bwd_inner_microstep: 272.47 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 02:10:58,479] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.75 | bwd_microstep: 272.57 | bwd_inner_microstep: 272.55 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 02:10:58,956] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.94 | bwd_microstep: 272.64 | bwd_inner_microstep: 272.62 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 02:10:59,435] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.75 | bwd_microstep: 272.66 | bwd_inner_microstep: 272.65 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 02:10:59,912] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.69 | bwd_microstep: 272.66 | bwd_inner_microstep: 272.64 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 02:11:00,387] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.61 | bwd_microstep: 271.29 | bwd_inner_microstep: 271.27 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 02:11:00,864] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.36 | bwd_microstep: 271.30 | bwd_inner_microstep: 271.28 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 02:11:01,337] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.59 | bwd_microstep: 270.82 | bwd_inner_microstep: 270.80 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1850 +[2025-05-02 02:11:01,811] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.51 | bwd_microstep: 270.71 | bwd_inner_microstep: 270.69 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1911 +[2025-05-02 02:11:02,384] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.19 | optimizer_step: 16.51 +[2025-05-02 02:11:02,385] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.16 | bwd_microstep: 344.47 | bwd_inner_microstep: 277.70 | bwd_allreduce_microstep: 66.72 | step_microstep: 23.77 +[2025-05-02 02:11:02,386] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2979.63 | bwd: 4391.52 | bwd_inner: 4324.33 | bwd_allreduce: 66.88 | step: 24.71 + 18%|█▊ | 1555/8720 [3:55:36<14:11:35, 7.13s/it] {'loss': 0.8249, 'grad_norm': 10.225411415100098, 'learning_rate': 9.434363165838481e-06, 'epoch': 1.78} + 18%|█▊ | 1555/8720 [3:55:36<14:11:35, 7.13s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1883 +[2025-05-02 02:11:02,869] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.37 | bwd_microstep: 273.53 | bwd_inner_microstep: 273.51 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1891 +[2025-05-02 02:11:03,349] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.86 | bwd_microstep: 274.82 | bwd_inner_microstep: 274.80 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-02 02:11:03,829] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.37 | bwd_microstep: 273.25 | bwd_inner_microstep: 273.23 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-02 02:11:04,308] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.28 | bwd_microstep: 273.71 | bwd_inner_microstep: 273.69 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1364 +[2025-05-02 02:11:04,671] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.75 | bwd_microstep: 206.80 | bwd_inner_microstep: 206.78 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 02:11:05,148] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.09 | bwd_microstep: 272.50 | bwd_inner_microstep: 272.48 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 02:11:05,626] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.19 | bwd_microstep: 273.03 | bwd_inner_microstep: 273.02 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 320 +[2025-05-02 02:11:05,846] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 83.39 | bwd_microstep: 122.43 | bwd_inner_microstep: 122.23 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 02:11:06,322] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.02 | bwd_microstep: 271.21 | bwd_inner_microstep: 271.19 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1086 +[2025-05-02 02:11:06,615] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 117.47 | bwd_microstep: 159.59 | bwd_inner_microstep: 159.43 | bwd_allreduce_microstep: 0.10 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 02:11:07,092] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.47 | bwd_microstep: 271.01 | bwd_inner_microstep: 270.99 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 02:11:07,569] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.98 | bwd_microstep: 271.08 | bwd_inner_microstep: 271.06 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 02:11:08,048] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.77 | bwd_microstep: 270.83 | bwd_inner_microstep: 270.82 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 02:11:08,525] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.97 | bwd_microstep: 271.14 | bwd_inner_microstep: 271.12 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 02:11:09,003] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.68 | bwd_microstep: 271.21 | bwd_inner_microstep: 271.19 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 02:11:09,590] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.23 | optimizer_step: 16.53 +[2025-05-02 02:11:09,590] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.55 | bwd_microstep: 355.23 | bwd_inner_microstep: 271.56 | bwd_allreduce_microstep: 83.62 | step_microstep: 24.50 +[2025-05-02 02:11:09,592] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2793.88 | bwd: 4111.41 | bwd_inner: 4027.17 | bwd_allreduce: 83.83 | step: 25.33 + 18%|█▊ | 1556/8720 [3:55:43<14:14:13, 7.15s/it] {'loss': 0.5236, 'grad_norm': 27.5929012298584, 'learning_rate': 9.433504820374779e-06, 'epoch': 1.78} + 18%|█▊ | 1556/8720 [3:55:43<14:14:13, 7.15s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2001 +[2025-05-02 02:11:10,108] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 198.98 | bwd_microstep: 293.77 | bwd_inner_microstep: 293.75 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1930 +[2025-05-02 02:11:10,610] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.76 | bwd_microstep: 288.11 | bwd_inner_microstep: 288.09 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1898 +[2025-05-02 02:11:11,093] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.89 | bwd_microstep: 275.51 | bwd_inner_microstep: 275.49 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1894 +[2025-05-02 02:11:11,577] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.52 | bwd_microstep: 275.16 | bwd_inner_microstep: 275.14 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1883 +[2025-05-02 02:11:12,059] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.10 | bwd_microstep: 274.43 | bwd_inner_microstep: 274.41 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 345 +[2025-05-02 02:11:12,303] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 89.29 | bwd_microstep: 136.87 | bwd_inner_microstep: 136.58 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 848 +[2025-05-02 02:11:12,560] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 97.13 | bwd_microstep: 143.18 | bwd_inner_microstep: 142.98 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 02:11:13,039] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.18 | bwd_microstep: 273.16 | bwd_inner_microstep: 273.14 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-02 02:11:13,519] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.13 | bwd_microstep: 273.52 | bwd_inner_microstep: 273.51 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 02:11:14,002] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.04 | bwd_microstep: 273.90 | bwd_inner_microstep: 273.89 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1351 +[2025-05-02 02:11:14,367] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.39 | bwd_microstep: 206.06 | bwd_inner_microstep: 206.04 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 02:11:14,845] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.51 | bwd_microstep: 272.40 | bwd_inner_microstep: 272.38 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1344 +[2025-05-02 02:11:15,208] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.67 | bwd_microstep: 204.39 | bwd_inner_microstep: 204.37 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 02:11:15,685] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.97 | bwd_microstep: 271.15 | bwd_inner_microstep: 271.13 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 02:11:16,163] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.39 | bwd_microstep: 271.14 | bwd_inner_microstep: 271.13 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1990 +[2025-05-02 02:11:16,777] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.24 | optimizer_step: 16.58 +[2025-05-02 02:11:16,777] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 199.09 | bwd_microstep: 371.34 | bwd_inner_microstep: 294.11 | bwd_allreduce_microstep: 77.18 | step_microstep: 24.61 +[2025-05-02 02:11:16,779] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2761.66 | bwd: 4104.18 | bwd_inner: 4026.20 | bwd_allreduce: 77.49 | step: 25.65 + 18%|█▊ | 1557/8720 [3:55:50<14:15:16, 7.16s/it] {'loss': 0.8379, 'grad_norm': 7.829466819763184, 'learning_rate': 9.432645863248986e-06, 'epoch': 1.79} + 18%|█▊ | 1557/8720 [3:55:50<14:15:16, 7.16s/it]dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 922 +[2025-05-02 02:11:17,050] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 104.18 | bwd_microstep: 145.56 | bwd_inner_microstep: 145.46 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1912 +[2025-05-02 02:11:17,532] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.32 | bwd_microstep: 276.23 | bwd_inner_microstep: 276.22 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1390 +[2025-05-02 02:11:17,901] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 143.70 | bwd_microstep: 209.06 | bwd_inner_microstep: 208.92 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1897 +[2025-05-02 02:11:18,380] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.74 | bwd_microstep: 274.91 | bwd_inner_microstep: 274.89 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-02 02:11:18,858] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.29 | bwd_microstep: 273.55 | bwd_inner_microstep: 273.53 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 337 +[2025-05-02 02:11:19,066] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 69.26 | bwd_microstep: 125.65 | bwd_inner_microstep: 125.32 | bwd_allreduce_microstep: 0.14 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 02:11:19,544] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.98 | bwd_microstep: 273.06 | bwd_inner_microstep: 273.05 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-02 02:11:20,024] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.30 | bwd_microstep: 273.39 | bwd_inner_microstep: 273.38 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 843 +[2025-05-02 02:11:20,269] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.86 | bwd_microstep: 132.42 | bwd_inner_microstep: 132.35 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 02:11:20,748] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.08 | bwd_microstep: 272.65 | bwd_inner_microstep: 272.63 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.17 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 02:11:21,228] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.97 | bwd_microstep: 272.68 | bwd_inner_microstep: 272.66 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.16 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 02:11:21,707] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.44 | bwd_microstep: 272.04 | bwd_inner_microstep: 272.02 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 02:11:22,184] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.83 | bwd_microstep: 271.08 | bwd_inner_microstep: 271.07 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 322 +[2025-05-02 02:11:22,420] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 90.48 | bwd_microstep: 129.42 | bwd_inner_microstep: 129.27 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 02:11:22,896] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.71 | bwd_microstep: 270.90 | bwd_inner_microstep: 270.88 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 02:11:23,462] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.20 | optimizer_step: 16.49 +[2025-05-02 02:11:23,462] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.45 | bwd_microstep: 337.80 | bwd_inner_microstep: 271.39 | bwd_allreduce_microstep: 66.36 | step_microstep: 23.72 +[2025-05-02 02:11:23,463] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2573.27 | bwd: 3810.49 | bwd_inner: 3743.14 | bwd_allreduce: 66.77 | step: 25.06 + 18%|█▊ | 1558/8720 [3:55:57<13:57:55, 7.02s/it] {'loss': 0.7421, 'grad_norm': 12.972987174987793, 'learning_rate': 9.43178629457961e-06, 'epoch': 1.79} + 18%|█▊ | 1558/8720 [3:55:57<13:57:55, 7.02s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 02:11:23,942] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.84 | bwd_microstep: 270.31 | bwd_inner_microstep: 270.29 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 429 +[2025-05-02 02:11:24,150] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 73.13 | bwd_microstep: 121.99 | bwd_inner_microstep: 121.86 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1893 +[2025-05-02 02:11:24,629] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.77 | bwd_microstep: 274.72 | bwd_inner_microstep: 274.70 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1892 +[2025-05-02 02:11:25,109] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.13 | bwd_microstep: 274.91 | bwd_inner_microstep: 274.89 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 357 +[2025-05-02 02:11:25,333] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 74.80 | bwd_microstep: 134.70 | bwd_inner_microstep: 134.57 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 02:11:25,810] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.88 | bwd_microstep: 273.30 | bwd_inner_microstep: 273.28 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 334 +[2025-05-02 02:11:26,013] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 68.93 | bwd_microstep: 120.68 | bwd_inner_microstep: 120.36 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 333 +[2025-05-02 02:11:26,217] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 68.79 | bwd_microstep: 122.23 | bwd_inner_microstep: 122.04 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1358 +[2025-05-02 02:11:26,579] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.75 | bwd_microstep: 205.93 | bwd_inner_microstep: 205.92 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 02:11:27,056] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.94 | bwd_microstep: 272.46 | bwd_inner_microstep: 272.45 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1344 +[2025-05-02 02:11:27,415] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.27 | bwd_microstep: 204.11 | bwd_inner_microstep: 204.10 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 02:11:27,891] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.95 | bwd_microstep: 272.53 | bwd_inner_microstep: 272.52 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 02:11:28,365] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.50 | bwd_microstep: 271.62 | bwd_inner_microstep: 271.60 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 02:11:28,840] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.98 | bwd_microstep: 271.36 | bwd_inner_microstep: 271.34 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1344 +[2025-05-02 02:11:29,200] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.89 | bwd_microstep: 204.14 | bwd_inner_microstep: 204.00 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 02:11:29,765] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.29 | optimizer_step: 16.68 +[2025-05-02 02:11:29,766] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.94 | bwd_microstep: 338.46 | bwd_inner_microstep: 271.67 | bwd_allreduce_microstep: 66.75 | step_microstep: 24.14 +[2025-05-02 02:11:29,767] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2400.23 | bwd: 3633.58 | bwd_inner: 3565.77 | bwd_allreduce: 67.18 | step: 25.23 + 18%|█▊ | 1559/8720 [3:56:03<13:32:10, 6.80s/it] {'loss': 0.9753, 'grad_norm': 20.770233154296875, 'learning_rate': 9.430926114485238e-06, 'epoch': 1.79} + 18%|█▊ | 1559/8720 [3:56:03<13:32:10, 6.80s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 02:11:30,245] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.33 | bwd_microstep: 269.99 | bwd_inner_microstep: 269.98 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1933 +[2025-05-02 02:11:30,746] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 197.85 | bwd_microstep: 287.72 | bwd_inner_microstep: 287.70 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1422 +[2025-05-02 02:11:31,120] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 145.70 | bwd_microstep: 213.37 | bwd_inner_microstep: 213.31 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1903 +[2025-05-02 02:11:31,600] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.59 | bwd_microstep: 275.48 | bwd_inner_microstep: 275.46 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1901 +[2025-05-02 02:11:32,082] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.83 | bwd_microstep: 275.40 | bwd_inner_microstep: 275.38 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1893 +[2025-05-02 02:11:32,561] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.18 | bwd_microstep: 274.69 | bwd_inner_microstep: 274.68 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1894 +[2025-05-02 02:11:33,041] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.84 | bwd_microstep: 274.81 | bwd_inner_microstep: 274.79 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 02:11:33,519] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.15 | bwd_microstep: 273.12 | bwd_inner_microstep: 273.10 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 02:11:33,999] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.16 | bwd_microstep: 272.51 | bwd_inner_microstep: 272.49 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 02:11:34,479] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.51 | bwd_microstep: 272.39 | bwd_inner_microstep: 272.37 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 02:11:34,957] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.57 | bwd_microstep: 272.45 | bwd_inner_microstep: 272.43 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 02:11:35,436] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.98 | bwd_microstep: 272.60 | bwd_inner_microstep: 272.58 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 02:11:35,917] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.77 | bwd_microstep: 272.30 | bwd_inner_microstep: 272.28 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 02:11:36,396] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.16 | bwd_microstep: 272.19 | bwd_inner_microstep: 272.17 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1346 +[2025-05-02 02:11:36,759] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.79 | bwd_microstep: 205.40 | bwd_inner_microstep: 205.38 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 02:11:37,337] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.19 | optimizer_step: 16.41 +[2025-05-02 02:11:37,338] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.69 | bwd_microstep: 349.24 | bwd_inner_microstep: 271.79 | bwd_allreduce_microstep: 77.39 | step_microstep: 24.04 +[2025-05-02 02:11:37,339] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2940.77 | bwd: 4333.67 | bwd_inner: 4255.91 | bwd_allreduce: 77.51 | step: 25.00 + 18%|█▊ | 1560/8720 [3:56:11<13:59:34, 7.04s/it] {'loss': 0.5152, 'grad_norm': 5.177057266235352, 'learning_rate': 9.430065323084545e-06, 'epoch': 1.79} + 18%|█▊ | 1560/8720 [3:56:11<13:59:34, 7.04s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 02:11:37,820] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.14 | bwd_microstep: 270.32 | bwd_inner_microstep: 270.31 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1935 +[2025-05-02 02:11:38,324] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 196.31 | bwd_microstep: 288.62 | bwd_inner_microstep: 288.61 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1897 +[2025-05-02 02:11:38,810] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.27 | bwd_microstep: 275.46 | bwd_inner_microstep: 275.44 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 859 +[2025-05-02 02:11:39,054] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.03 | bwd_microstep: 133.54 | bwd_inner_microstep: 133.37 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 02:11:39,534] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.97 | bwd_microstep: 273.48 | bwd_inner_microstep: 273.46 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 02:11:40,016] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.62 | bwd_microstep: 273.64 | bwd_inner_microstep: 273.62 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 02:11:40,497] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.89 | bwd_microstep: 273.53 | bwd_inner_microstep: 273.51 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 02:11:40,977] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.47 | bwd_microstep: 273.09 | bwd_inner_microstep: 273.08 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 02:11:41,457] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.87 | bwd_microstep: 273.04 | bwd_inner_microstep: 273.02 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 02:11:41,936] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.68 | bwd_microstep: 272.86 | bwd_inner_microstep: 272.84 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 02:11:42,415] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.15 | bwd_microstep: 272.81 | bwd_inner_microstep: 272.80 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 835 +[2025-05-02 02:11:42,648] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 92.80 | bwd_microstep: 126.48 | bwd_inner_microstep: 126.46 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 02:11:43,122] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.88 | bwd_microstep: 271.33 | bwd_inner_microstep: 271.31 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 02:11:43,600] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.15 | bwd_microstep: 273.60 | bwd_inner_microstep: 273.58 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 832 +[2025-05-02 02:11:43,840] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.09 | bwd_microstep: 130.82 | bwd_inner_microstep: 130.63 | bwd_allreduce_microstep: 0.10 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 02:11:44,419] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.19 | optimizer_step: 16.37 +[2025-05-02 02:11:44,420] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.41 | bwd_microstep: 349.96 | bwd_inner_microstep: 271.99 | bwd_allreduce_microstep: 77.92 | step_microstep: 24.00 +[2025-05-02 02:11:44,421] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2748.40 | bwd: 4032.63 | bwd_inner: 3954.04 | bwd_allreduce: 78.19 | step: 24.96 + 18%|█▊ | 1561/8720 [3:56:18<14:01:07, 7.05s/it] {'loss': 0.741, 'grad_norm': 17.461061477661133, 'learning_rate': 9.429203920496287e-06, 'epoch': 1.79} + 18%|█▊ | 1561/8720 [3:56:18<14:01:07, 7.05s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 318 +[2025-05-02 02:11:44,638] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 78.72 | bwd_microstep: 117.39 | bwd_inner_microstep: 117.16 | bwd_allreduce_microstep: 0.09 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1917 +[2025-05-02 02:11:45,123] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.68 | bwd_microstep: 276.77 | bwd_inner_microstep: 276.76 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 369 +[2025-05-02 02:11:45,357] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.32 | bwd_microstep: 121.50 | bwd_inner_microstep: 121.20 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.20 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1387 +[2025-05-02 02:11:45,729] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 144.47 | bwd_microstep: 209.32 | bwd_inner_microstep: 209.20 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 02:11:46,214] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.15 | bwd_microstep: 273.61 | bwd_inner_microstep: 273.59 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1353 +[2025-05-02 02:11:46,582] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 142.24 | bwd_microstep: 206.21 | bwd_inner_microstep: 206.20 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 02:11:47,061] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.94 | bwd_microstep: 272.20 | bwd_inner_microstep: 272.18 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 326 +[2025-05-02 02:11:47,272] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 80.21 | bwd_microstep: 115.77 | bwd_inner_microstep: 115.57 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 02:11:47,750] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.03 | bwd_microstep: 272.37 | bwd_inner_microstep: 272.36 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 02:11:48,229] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.59 | bwd_microstep: 272.67 | bwd_inner_microstep: 272.66 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 02:11:48,708] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.41 | bwd_microstep: 272.64 | bwd_inner_microstep: 272.63 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 02:11:49,186] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.24 | bwd_microstep: 271.98 | bwd_inner_microstep: 271.96 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 02:11:49,667] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.97 | bwd_microstep: 271.36 | bwd_inner_microstep: 271.34 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 02:11:50,149] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.52 | bwd_microstep: 270.89 | bwd_inner_microstep: 270.87 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 317 +[2025-05-02 02:11:50,381] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 98.89 | bwd_microstep: 115.51 | bwd_inner_microstep: 115.21 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.17 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 02:11:50,956] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.19 | optimizer_step: 16.39 +[2025-05-02 02:11:50,956] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.83 | bwd_microstep: 347.46 | bwd_inner_microstep: 271.23 | bwd_allreduce_microstep: 76.17 | step_microstep: 24.08 +[2025-05-02 02:11:50,957] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2522.80 | bwd: 3687.83 | bwd_inner: 3610.34 | bwd_allreduce: 76.65 | step: 25.54 + 18%|█▊ | 1562/8720 [3:56:24<13:42:37, 6.90s/it] {'loss': 0.4617, 'grad_norm': 7.357646465301514, 'learning_rate': 9.428341906839309e-06, 'epoch': 1.79} + 18%|█▊ | 1562/8720 [3:56:24<13:42:37, 6.90s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 634 +[2025-05-02 02:11:51,180] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 86.07 | bwd_microstep: 115.62 | bwd_inner_microstep: 115.40 | bwd_allreduce_microstep: 0.08 | step_microstep: 0.12 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 362 +[2025-05-02 02:11:51,398] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 81.69 | bwd_microstep: 120.15 | bwd_inner_microstep: 119.85 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1372 +[2025-05-02 02:11:51,765] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 143.29 | bwd_microstep: 207.63 | bwd_inner_microstep: 207.61 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-02 02:11:52,245] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.25 | bwd_microstep: 273.86 | bwd_inner_microstep: 273.84 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-02 02:11:52,729] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.76 | bwd_microstep: 273.36 | bwd_inner_microstep: 273.34 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-02 02:11:53,211] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.94 | bwd_microstep: 273.28 | bwd_inner_microstep: 273.26 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-02 02:11:53,695] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.26 | bwd_microstep: 273.25 | bwd_inner_microstep: 273.23 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 337 +[2025-05-02 02:11:53,941] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 92.10 | bwd_microstep: 135.01 | bwd_inner_microstep: 134.84 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.10 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 334 +[2025-05-02 02:11:54,166] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 82.95 | bwd_microstep: 126.47 | bwd_inner_microstep: 126.31 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 345 +[2025-05-02 02:11:54,379] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 81.38 | bwd_microstep: 116.92 | bwd_inner_microstep: 116.62 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 02:11:54,856] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.25 | bwd_microstep: 272.11 | bwd_inner_microstep: 272.10 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 02:11:55,335] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.80 | bwd_microstep: 272.33 | bwd_inner_microstep: 272.32 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 02:11:55,817] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.31 | bwd_microstep: 272.13 | bwd_inner_microstep: 272.11 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 02:11:56,295] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.38 | bwd_microstep: 272.18 | bwd_inner_microstep: 272.16 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 02:11:56,776] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.20 | bwd_microstep: 272.02 | bwd_inner_microstep: 272.01 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 02:11:57,353] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.18 | optimizer_step: 16.38 +[2025-05-02 02:11:57,354] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.80 | bwd_microstep: 347.38 | bwd_inner_microstep: 271.59 | bwd_allreduce_microstep: 75.75 | step_microstep: 23.97 +[2025-05-02 02:11:57,355] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2451.02 | bwd: 3623.82 | bwd_inner: 3546.82 | bwd_allreduce: 76.23 | step: 25.22 + 18%|█▊ | 1563/8720 [3:56:31<13:24:42, 6.75s/it] {'loss': 0.6461, 'grad_norm': 5.783836841583252, 'learning_rate': 9.427479282232535e-06, 'epoch': 1.79} + 18%|█▊ | 1563/8720 [3:56:31<13:24:42, 6.75s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 02:11:57,835] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.32 | bwd_microstep: 270.11 | bwd_inner_microstep: 270.09 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1921 +[2025-05-02 02:11:58,334] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.19 | bwd_microstep: 286.90 | bwd_inner_microstep: 286.88 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 870 +[2025-05-02 02:11:58,580] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 97.85 | bwd_microstep: 134.36 | bwd_inner_microstep: 134.10 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 876 +[2025-05-02 02:11:58,825] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 96.88 | bwd_microstep: 134.69 | bwd_inner_microstep: 134.58 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-02 02:11:59,304] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.71 | bwd_microstep: 274.60 | bwd_inner_microstep: 274.58 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1900 +[2025-05-02 02:11:59,787] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.72 | bwd_microstep: 275.80 | bwd_inner_microstep: 275.78 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 02:12:00,269] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.40 | bwd_microstep: 273.87 | bwd_inner_microstep: 273.85 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 02:12:00,750] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.74 | bwd_microstep: 273.29 | bwd_inner_microstep: 273.28 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 333 +[2025-05-02 02:12:00,965] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 80.36 | bwd_microstep: 118.13 | bwd_inner_microstep: 117.78 | bwd_allreduce_microstep: 0.14 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 02:12:01,443] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.40 | bwd_microstep: 272.82 | bwd_inner_microstep: 272.80 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 02:12:01,922] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.49 | bwd_microstep: 273.13 | bwd_inner_microstep: 273.11 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 02:12:02,401] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.58 | bwd_microstep: 272.58 | bwd_inner_microstep: 272.56 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 02:12:02,877] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.70 | bwd_microstep: 271.08 | bwd_inner_microstep: 271.07 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 02:12:03,354] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.48 | bwd_microstep: 271.36 | bwd_inner_microstep: 271.34 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 02:12:03,831] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.60 | bwd_microstep: 271.40 | bwd_inner_microstep: 271.38 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 924 +[2025-05-02 02:12:04,188] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.04 | optimizer_gradients: 2.18 | optimizer_step: 16.40 +[2025-05-02 02:12:04,189] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 105.05 | bwd_microstep: 215.74 | bwd_inner_microstep: 147.17 | bwd_allreduce_microstep: 68.42 | step_microstep: 23.39 +[2025-05-02 02:12:04,190] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2650.16 | bwd: 3889.93 | bwd_inner: 3820.50 | bwd_allreduce: 68.78 | step: 24.39 + 18%|█▊ | 1564/8720 [3:56:37<13:27:41, 6.77s/it] {'loss': 1.0271, 'grad_norm': 7.797766208648682, 'learning_rate': 9.426616046794975e-06, 'epoch': 1.79} + 18%|█▊ | 1564/8720 [3:56:37<13:27:41, 6.77s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1906 +[2025-05-02 02:12:04,675] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.16 | bwd_microstep: 275.50 | bwd_inner_microstep: 275.49 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 02:12:05,153] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.39 | bwd_microstep: 273.71 | bwd_inner_microstep: 273.69 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1889 +[2025-05-02 02:12:05,633] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.90 | bwd_microstep: 275.02 | bwd_inner_microstep: 275.00 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1366 +[2025-05-02 02:12:05,996] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 142.09 | bwd_microstep: 206.89 | bwd_inner_microstep: 206.88 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1356 +[2025-05-02 02:12:06,358] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.65 | bwd_microstep: 206.00 | bwd_inner_microstep: 205.98 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 838 +[2025-05-02 02:12:06,593] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 91.32 | bwd_microstep: 129.81 | bwd_inner_microstep: 129.60 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.08 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 833 +[2025-05-02 02:12:06,823] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 90.87 | bwd_microstep: 125.66 | bwd_inner_microstep: 125.59 | bwd_allreduce_microstep: 0.03 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 02:12:07,297] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.85 | bwd_microstep: 272.21 | bwd_inner_microstep: 272.19 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 323 +[2025-05-02 02:12:07,503] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 76.88 | bwd_microstep: 115.42 | bwd_inner_microstep: 115.11 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 02:12:07,977] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.21 | bwd_microstep: 272.21 | bwd_inner_microstep: 272.19 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 02:12:08,452] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.85 | bwd_microstep: 271.98 | bwd_inner_microstep: 271.96 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 02:12:08,926] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.51 | bwd_microstep: 271.15 | bwd_inner_microstep: 271.13 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 02:12:09,401] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.05 | bwd_microstep: 272.05 | bwd_inner_microstep: 272.03 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 02:12:09,874] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.44 | bwd_microstep: 270.84 | bwd_inner_microstep: 270.82 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 02:12:10,347] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.82 | bwd_microstep: 270.88 | bwd_inner_microstep: 270.86 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 462 +[2025-05-02 02:12:10,648] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.04 | optimizer_gradients: 2.16 | optimizer_step: 16.38 +[2025-05-02 02:12:10,648] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 67.47 | bwd_microstep: 197.56 | bwd_inner_microstep: 131.42 | bwd_allreduce_microstep: 65.96 | step_microstep: 23.36 +[2025-05-02 02:12:10,650] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2493.21 | bwd: 3706.95 | bwd_inner: 3640.07 | bwd_allreduce: 66.27 | step: 24.25 + 18%|█▊ | 1565/8720 [3:56:44<13:16:24, 6.68s/it] {'loss': 0.3663, 'grad_norm': 16.735408782958984, 'learning_rate': 9.425752200645726e-06, 'epoch': 1.79} + 18%|█▊ | 1565/8720 [3:56:44<13:16:24, 6.68s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1917 +[2025-05-02 02:12:11,134] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.66 | bwd_microstep: 275.59 | bwd_inner_microstep: 275.57 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 404 +[2025-05-02 02:12:11,341] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 75.76 | bwd_microstep: 117.07 | bwd_inner_microstep: 116.83 | bwd_allreduce_microstep: 0.10 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1924 +[2025-05-02 02:12:11,836] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 193.88 | bwd_microstep: 286.94 | bwd_inner_microstep: 286.92 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1928 +[2025-05-02 02:12:12,334] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 194.64 | bwd_microstep: 287.47 | bwd_inner_microstep: 287.45 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1362 +[2025-05-02 02:12:12,699] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.15 | bwd_microstep: 206.71 | bwd_inner_microstep: 206.70 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1888 +[2025-05-02 02:12:13,176] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.33 | bwd_microstep: 274.19 | bwd_inner_microstep: 274.18 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 02:12:13,653] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.66 | bwd_microstep: 272.79 | bwd_inner_microstep: 272.77 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 02:12:14,132] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.61 | bwd_microstep: 273.21 | bwd_inner_microstep: 273.19 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1883 +[2025-05-02 02:12:14,614] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.10 | bwd_microstep: 273.88 | bwd_inner_microstep: 273.86 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 330 +[2025-05-02 02:12:14,829] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 81.33 | bwd_microstep: 118.40 | bwd_inner_microstep: 118.25 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 02:12:15,308] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.71 | bwd_microstep: 272.93 | bwd_inner_microstep: 272.91 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 02:12:15,790] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.49 | bwd_microstep: 272.58 | bwd_inner_microstep: 272.57 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 02:12:16,272] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.21 | bwd_microstep: 272.16 | bwd_inner_microstep: 272.14 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 02:12:16,754] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.14 | bwd_microstep: 272.61 | bwd_inner_microstep: 272.59 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1343 +[2025-05-02 02:12:17,121] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.52 | bwd_microstep: 204.39 | bwd_inner_microstep: 204.37 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 02:12:17,698] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.18 | optimizer_step: 16.41 +[2025-05-02 02:12:17,698] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.29 | bwd_microstep: 347.71 | bwd_inner_microstep: 271.63 | bwd_allreduce_microstep: 76.02 | step_microstep: 24.14 +[2025-05-02 02:12:17,699] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2710.09 | bwd: 4028.67 | bwd_inner: 3952.03 | bwd_allreduce: 76.23 | step: 25.02 + 18%|█▊ | 1566/8720 [3:56:51<13:29:39, 6.79s/it] {'loss': 0.8446, 'grad_norm': 7.423483848571777, 'learning_rate': 9.424887743903968e-06, 'epoch': 1.8} + 18%|█▊ | 1566/8720 [3:56:51<13:29:39, 6.79s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 02:12:18,183] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.85 | bwd_microstep: 271.81 | bwd_inner_microstep: 271.79 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 1008 +[2025-05-02 02:12:18,460] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 106.36 | bwd_microstep: 152.25 | bwd_inner_microstep: 152.11 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1962 +[2025-05-02 02:12:18,966] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 197.48 | bwd_microstep: 290.15 | bwd_inner_microstep: 290.13 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 02:12:19,445] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.84 | bwd_microstep: 273.52 | bwd_inner_microstep: 273.51 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-02 02:12:19,925] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.16 | bwd_microstep: 273.80 | bwd_inner_microstep: 273.78 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-02 02:12:20,402] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.72 | bwd_microstep: 273.37 | bwd_inner_microstep: 273.36 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 02:12:20,878] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.12 | bwd_microstep: 272.96 | bwd_inner_microstep: 272.94 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 328 +[2025-05-02 02:12:21,093] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 77.41 | bwd_microstep: 123.14 | bwd_inner_microstep: 122.95 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 329 +[2025-05-02 02:12:21,305] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 80.33 | bwd_microstep: 118.47 | bwd_inner_microstep: 118.33 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 02:12:21,782] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.19 | bwd_microstep: 272.30 | bwd_inner_microstep: 272.29 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 02:12:22,261] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.47 | bwd_microstep: 272.15 | bwd_inner_microstep: 272.13 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 02:12:22,739] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.24 | bwd_microstep: 272.12 | bwd_inner_microstep: 272.11 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 322 +[2025-05-02 02:12:22,972] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 92.35 | bwd_microstep: 122.05 | bwd_inner_microstep: 121.90 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 02:12:23,448] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.38 | bwd_microstep: 271.71 | bwd_inner_microstep: 271.69 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 02:12:23,926] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.26 | bwd_microstep: 272.05 | bwd_inner_microstep: 272.03 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 318 +[2025-05-02 02:12:24,234] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.20 | optimizer_step: 16.48 +[2025-05-02 02:12:24,235] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 71.25 | bwd_microstep: 200.20 | bwd_inner_microstep: 134.06 | bwd_allreduce_microstep: 66.02 | step_microstep: 23.68 +[2025-05-02 02:12:24,236] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2509.07 | bwd: 3732.13 | bwd_inner: 3665.30 | bwd_allreduce: 66.30 | step: 24.72 + 18%|█▊ | 1567/8720 [3:56:57<13:20:22, 6.71s/it] {'loss': 0.7654, 'grad_norm': 8.723426818847656, 'learning_rate': 9.424022676688962e-06, 'epoch': 1.8} + 18%|█▊ | 1567/8720 [3:56:57<13:20:22, 6.71s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1907 +[2025-05-02 02:12:24,721] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.54 | bwd_microstep: 275.37 | bwd_inner_microstep: 275.35 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 907 +[2025-05-02 02:12:24,980] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 100.64 | bwd_microstep: 144.28 | bwd_inner_microstep: 144.27 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 897 +[2025-05-02 02:12:25,241] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 102.69 | bwd_microstep: 143.31 | bwd_inner_microstep: 143.29 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1912 +[2025-05-02 02:12:25,722] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.31 | bwd_microstep: 276.42 | bwd_inner_microstep: 276.40 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-02 02:12:26,202] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.11 | bwd_microstep: 274.05 | bwd_inner_microstep: 274.03 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 02:12:26,683] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.81 | bwd_microstep: 273.01 | bwd_inner_microstep: 272.99 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-02 02:12:27,167] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.61 | bwd_microstep: 273.16 | bwd_inner_microstep: 273.15 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 02:12:27,649] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.98 | bwd_microstep: 272.56 | bwd_inner_microstep: 272.54 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 836 +[2025-05-02 02:12:27,895] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 99.47 | bwd_microstep: 125.78 | bwd_inner_microstep: 125.73 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 02:12:28,373] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.83 | bwd_microstep: 272.31 | bwd_inner_microstep: 272.29 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 02:12:28,851] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.96 | bwd_microstep: 272.24 | bwd_inner_microstep: 272.22 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 322 +[2025-05-02 02:12:29,084] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 92.42 | bwd_microstep: 122.18 | bwd_inner_microstep: 121.95 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 02:12:29,561] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.84 | bwd_microstep: 271.25 | bwd_inner_microstep: 271.23 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 02:12:30,038] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.32 | bwd_microstep: 271.15 | bwd_inner_microstep: 271.13 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 02:12:30,516] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.00 | bwd_microstep: 270.96 | bwd_inner_microstep: 270.94 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 02:12:31,094] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.24 | optimizer_step: 16.52 +[2025-05-02 02:12:31,094] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.51 | bwd_microstep: 348.71 | bwd_inner_microstep: 271.12 | bwd_allreduce_microstep: 77.54 | step_microstep: 24.55 +[2025-05-02 02:12:31,096] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2655.68 | bwd: 3886.77 | bwd_inner: 3808.71 | bwd_allreduce: 77.69 | step: 25.55 + 18%|█▊ | 1568/8720 [3:57:04<13:25:34, 6.76s/it] {'loss': 0.6185, 'grad_norm': 14.819649696350098, 'learning_rate': 9.423156999120057e-06, 'epoch': 1.8} + 18%|█▊ | 1568/8720 [3:57:04<13:25:34, 6.76s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 02:12:31,578] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.54 | bwd_microstep: 270.28 | bwd_inner_microstep: 270.26 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1949 +[2025-05-02 02:12:32,080] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 197.22 | bwd_microstep: 289.56 | bwd_inner_microstep: 289.54 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1934 +[2025-05-02 02:12:32,579] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.62 | bwd_microstep: 287.73 | bwd_inner_microstep: 287.71 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-02 02:12:33,059] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.18 | bwd_microstep: 274.15 | bwd_inner_microstep: 274.14 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-02 02:12:33,539] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.95 | bwd_microstep: 274.11 | bwd_inner_microstep: 274.10 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 861 +[2025-05-02 02:12:33,791] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 100.93 | bwd_microstep: 133.15 | bwd_inner_microstep: 133.11 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 02:12:34,269] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.07 | bwd_microstep: 273.03 | bwd_inner_microstep: 273.02 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 337 +[2025-05-02 02:12:34,495] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 90.32 | bwd_microstep: 119.30 | bwd_inner_microstep: 119.02 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 847 +[2025-05-02 02:12:34,738] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.89 | bwd_microstep: 132.56 | bwd_inner_microstep: 132.28 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 02:12:35,216] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.24 | bwd_microstep: 272.31 | bwd_inner_microstep: 272.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 02:12:35,693] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.99 | bwd_microstep: 272.29 | bwd_inner_microstep: 272.28 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1354 +[2025-05-02 02:12:36,057] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.81 | bwd_microstep: 205.76 | bwd_inner_microstep: 205.68 | bwd_allreduce_microstep: 0.04 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 02:12:36,532] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.79 | bwd_microstep: 272.53 | bwd_inner_microstep: 272.51 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 02:12:37,008] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.75 | bwd_microstep: 272.05 | bwd_inner_microstep: 272.04 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1090 +[2025-05-02 02:12:37,300] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 114.77 | bwd_microstep: 160.35 | bwd_inner_microstep: 160.26 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 02:12:37,873] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.24 | optimizer_step: 16.52 +[2025-05-02 02:12:37,873] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.23 | bwd_microstep: 345.20 | bwd_inner_microstep: 271.60 | bwd_allreduce_microstep: 73.55 | step_microstep: 23.73 +[2025-05-02 02:12:37,874] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2627.96 | bwd: 3854.45 | bwd_inner: 3779.91 | bwd_allreduce: 73.96 | step: 24.69 + 18%|█▊ | 1569/8720 [3:57:11<13:26:07, 6.76s/it] {'loss': 0.5436, 'grad_norm': 13.214858055114746, 'learning_rate': 9.422290711316686e-06, 'epoch': 1.8} + 18%|█▊ | 1569/8720 [3:57:11<13:26:07, 6.76s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1849 +[2025-05-02 02:12:38,352] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.84 | bwd_microstep: 270.11 | bwd_inner_microstep: 270.10 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1906 +[2025-05-02 02:12:38,833] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.97 | bwd_microstep: 275.71 | bwd_inner_microstep: 275.69 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1926 +[2025-05-02 02:12:39,329] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 194.32 | bwd_microstep: 286.91 | bwd_inner_microstep: 286.89 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 02:12:39,806] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.84 | bwd_microstep: 273.15 | bwd_inner_microstep: 273.14 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 02:12:40,283] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.92 | bwd_microstep: 273.33 | bwd_inner_microstep: 273.32 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 837 +[2025-05-02 02:12:40,518] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 92.45 | bwd_microstep: 126.19 | bwd_inner_microstep: 125.98 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 02:12:40,996] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.83 | bwd_microstep: 273.35 | bwd_inner_microstep: 273.33 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-02 02:12:41,476] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.09 | bwd_microstep: 273.51 | bwd_inner_microstep: 273.50 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 02:12:41,958] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.49 | bwd_microstep: 273.33 | bwd_inner_microstep: 273.31 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-02 02:12:42,443] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.36 | bwd_microstep: 273.12 | bwd_inner_microstep: 273.10 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 02:12:42,923] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.11 | bwd_microstep: 272.38 | bwd_inner_microstep: 272.36 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 02:12:43,402] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.37 | bwd_microstep: 272.54 | bwd_inner_microstep: 272.53 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 02:12:43,882] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.32 | bwd_microstep: 272.43 | bwd_inner_microstep: 272.41 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 02:12:44,363] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.66 | bwd_microstep: 272.41 | bwd_inner_microstep: 272.40 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 02:12:44,843] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.79 | bwd_microstep: 271.99 | bwd_inner_microstep: 271.98 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1342 +[2025-05-02 02:12:45,307] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.20 | optimizer_step: 16.53 +[2025-05-02 02:12:45,307] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.30 | bwd_microstep: 281.54 | bwd_inner_microstep: 204.74 | bwd_allreduce_microstep: 76.65 | step_microstep: 24.50 +[2025-05-02 02:12:45,309] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2878.29 | bwd: 4242.07 | bwd_inner: 4164.83 | bwd_allreduce: 76.83 | step: 25.40 + 18%|█▊ | 1570/8720 [3:57:19<13:50:02, 6.97s/it] {'loss': 0.5688, 'grad_norm': 17.404428482055664, 'learning_rate': 9.421423813398366e-06, 'epoch': 1.8} + 18%|█▊ | 1570/8720 [3:57:19<13:50:02, 6.97s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 02:12:45,790] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.09 | bwd_microstep: 270.24 | bwd_inner_microstep: 270.23 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1925 +[2025-05-02 02:12:46,293] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.18 | bwd_microstep: 286.82 | bwd_inner_microstep: 286.80 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1921 +[2025-05-02 02:12:46,794] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.30 | bwd_microstep: 287.03 | bwd_inner_microstep: 287.01 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 335 +[2025-05-02 02:12:47,038] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 98.45 | bwd_microstep: 124.79 | bwd_inner_microstep: 124.60 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-02 02:12:47,518] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.07 | bwd_microstep: 273.24 | bwd_inner_microstep: 273.22 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 02:12:47,998] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.25 | bwd_microstep: 273.15 | bwd_inner_microstep: 273.13 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 02:12:48,478] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.00 | bwd_microstep: 273.01 | bwd_inner_microstep: 272.99 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 850 +[2025-05-02 02:12:48,722] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 97.44 | bwd_microstep: 132.31 | bwd_inner_microstep: 132.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 02:12:49,199] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.19 | bwd_microstep: 273.04 | bwd_inner_microstep: 273.03 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 02:12:49,675] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.71 | bwd_microstep: 272.76 | bwd_inner_microstep: 272.74 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 02:12:50,151] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.35 | bwd_microstep: 272.19 | bwd_inner_microstep: 272.18 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 02:12:50,627] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.07 | bwd_microstep: 271.93 | bwd_inner_microstep: 271.91 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 02:12:51,103] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.82 | bwd_microstep: 272.08 | bwd_inner_microstep: 272.06 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 02:12:51,578] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.23 | bwd_microstep: 272.04 | bwd_inner_microstep: 272.03 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1345 +[2025-05-02 02:12:51,940] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.17 | bwd_microstep: 205.16 | bwd_inner_microstep: 205.06 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 02:12:52,507] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.21 | optimizer_step: 16.65 +[2025-05-02 02:12:52,507] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.63 | bwd_microstep: 339.25 | bwd_inner_microstep: 271.46 | bwd_allreduce_microstep: 67.74 | step_microstep: 23.90 +[2025-05-02 02:12:52,508] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2799.63 | bwd: 4099.10 | bwd_inner: 4030.81 | bwd_allreduce: 67.96 | step: 24.92 + 18%|█▊ | 1571/8720 [3:57:26<13:58:14, 7.04s/it] {'loss': 0.8591, 'grad_norm': 17.58738899230957, 'learning_rate': 9.420556305484691e-06, 'epoch': 1.8} + 18%|█▊ | 1571/8720 [3:57:26<13:58:14, 7.04s/it]dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1130 +[2025-05-02 02:12:52,807] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 115.80 | bwd_microstep: 163.49 | bwd_inner_microstep: 163.37 | bwd_allreduce_microstep: 0.08 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-02 02:12:53,283] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.01 | bwd_microstep: 273.12 | bwd_inner_microstep: 273.10 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-02 02:12:53,761] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.76 | bwd_microstep: 274.10 | bwd_inner_microstep: 274.09 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 344 +[2025-05-02 02:12:53,961] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 67.93 | bwd_microstep: 119.35 | bwd_inner_microstep: 119.22 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 02:12:54,438] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.06 | bwd_microstep: 273.01 | bwd_inner_microstep: 272.99 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 02:12:54,915] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.24 | bwd_microstep: 272.92 | bwd_inner_microstep: 272.90 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 02:12:55,392] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.15 | bwd_microstep: 272.74 | bwd_inner_microstep: 272.72 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 02:12:55,866] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.76 | bwd_microstep: 271.20 | bwd_inner_microstep: 271.19 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 02:12:56,340] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.18 | bwd_microstep: 271.97 | bwd_inner_microstep: 271.96 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 02:12:56,816] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.36 | bwd_microstep: 272.29 | bwd_inner_microstep: 272.27 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 02:12:57,292] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.74 | bwd_microstep: 272.20 | bwd_inner_microstep: 272.18 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 02:12:57,767] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.06 | bwd_microstep: 272.12 | bwd_inner_microstep: 272.10 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 02:12:58,241] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.58 | bwd_microstep: 270.97 | bwd_inner_microstep: 270.95 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 02:12:58,716] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.52 | bwd_microstep: 271.27 | bwd_inner_microstep: 271.25 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 02:12:59,191] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.38 | bwd_microstep: 271.17 | bwd_inner_microstep: 271.16 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 02:12:59,756] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.04 | optimizer_gradients: 2.21 | optimizer_step: 16.38 +[2025-05-02 02:12:59,756] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.99 | bwd_microstep: 337.61 | bwd_inner_microstep: 271.43 | bwd_allreduce_microstep: 66.13 | step_microstep: 23.45 +[2025-05-02 02:12:59,758] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2818.24 | bwd: 4159.57 | bwd_inner: 4092.90 | bwd_allreduce: 66.32 | step: 24.20 + 18%|█▊ | 1572/8720 [3:57:33<14:05:45, 7.10s/it] {'loss': 0.4919, 'grad_norm': 14.393190383911133, 'learning_rate': 9.419688187695353e-06, 'epoch': 1.8} + 18%|█▊ | 1572/8720 [3:57:33<14:05:45, 7.10s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-02 02:13:00,238] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.52 | bwd_microstep: 272.75 | bwd_inner_microstep: 272.73 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 866 +[2025-05-02 02:13:00,481] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.82 | bwd_microstep: 133.88 | bwd_inner_microstep: 133.70 | bwd_allreduce_microstep: 0.10 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-02 02:13:00,959] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.04 | bwd_microstep: 274.28 | bwd_inner_microstep: 274.26 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1370 +[2025-05-02 02:13:01,324] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 142.01 | bwd_microstep: 207.49 | bwd_inner_microstep: 207.33 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-02 02:13:01,801] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.47 | bwd_microstep: 273.46 | bwd_inner_microstep: 273.44 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-02 02:13:02,278] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.70 | bwd_microstep: 274.10 | bwd_inner_microstep: 274.08 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1366 +[2025-05-02 02:13:02,642] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.37 | bwd_microstep: 207.09 | bwd_inner_microstep: 206.99 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 02:13:03,117] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.87 | bwd_microstep: 272.26 | bwd_inner_microstep: 272.24 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 02:13:03,595] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.52 | bwd_microstep: 272.57 | bwd_inner_microstep: 272.55 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1349 +[2025-05-02 02:13:03,957] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.50 | bwd_microstep: 205.71 | bwd_inner_microstep: 205.70 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 02:13:04,433] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.73 | bwd_microstep: 272.92 | bwd_inner_microstep: 272.90 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 02:13:04,911] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.34 | bwd_microstep: 273.11 | bwd_inner_microstep: 273.09 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 02:13:05,387] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.96 | bwd_microstep: 271.62 | bwd_inner_microstep: 271.60 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 02:13:05,862] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.09 | bwd_microstep: 272.49 | bwd_inner_microstep: 272.48 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 02:13:06,336] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.47 | bwd_microstep: 271.28 | bwd_inner_microstep: 271.27 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 02:13:06,900] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.04 | optimizer_gradients: 2.20 | optimizer_step: 16.37 +[2025-05-02 02:13:06,901] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.68 | bwd_microstep: 338.04 | bwd_inner_microstep: 271.95 | bwd_allreduce_microstep: 66.05 | step_microstep: 23.40 +[2025-05-02 02:13:06,902] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2780.80 | bwd: 4093.12 | bwd_inner: 4026.31 | bwd_allreduce: 66.35 | step: 24.36 + 18%|█▊ | 1573/8720 [3:57:40<14:07:15, 7.11s/it] {'loss': 0.6671, 'grad_norm': 9.843683242797852, 'learning_rate': 9.418819460150117e-06, 'epoch': 1.8} + 18%|█▊ | 1573/8720 [3:57:40<14:07:15, 7.11s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 02:13:07,380] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.81 | bwd_microstep: 270.58 | bwd_inner_microstep: 270.56 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1948 +[2025-05-02 02:13:07,880] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 196.35 | bwd_microstep: 289.03 | bwd_inner_microstep: 289.01 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1899 +[2025-05-02 02:13:08,359] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.04 | bwd_microstep: 275.15 | bwd_inner_microstep: 275.13 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 02:13:08,835] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.76 | bwd_microstep: 273.04 | bwd_inner_microstep: 273.03 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 02:13:09,312] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.80 | bwd_microstep: 273.32 | bwd_inner_microstep: 273.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 02:13:09,790] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.18 | bwd_microstep: 273.11 | bwd_inner_microstep: 273.09 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 842 +[2025-05-02 02:13:10,033] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 97.05 | bwd_microstep: 131.95 | bwd_inner_microstep: 131.82 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 02:13:10,513] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.26 | bwd_microstep: 273.20 | bwd_inner_microstep: 273.18 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 843 +[2025-05-02 02:13:10,759] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 97.21 | bwd_microstep: 131.73 | bwd_inner_microstep: 131.72 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.22 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 327 +[2025-05-02 02:13:10,977] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 81.79 | bwd_microstep: 120.04 | bwd_inner_microstep: 119.78 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 02:13:11,454] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.99 | bwd_microstep: 272.59 | bwd_inner_microstep: 272.57 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 02:13:11,932] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.51 | bwd_microstep: 272.13 | bwd_inner_microstep: 272.11 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 02:13:12,410] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.33 | bwd_microstep: 271.29 | bwd_inner_microstep: 271.27 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 02:13:12,889] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.27 | bwd_microstep: 271.39 | bwd_inner_microstep: 271.38 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 02:13:13,371] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.18 | bwd_microstep: 271.05 | bwd_inner_microstep: 271.03 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 827 +[2025-05-02 02:13:13,723] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.20 | optimizer_step: 16.36 +[2025-05-02 02:13:13,724] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 99.60 | bwd_microstep: 209.62 | bwd_inner_microstep: 133.02 | bwd_allreduce_microstep: 76.44 | step_microstep: 24.19 +[2025-05-02 02:13:13,725] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2644.78 | bwd: 3879.29 | bwd_inner: 3802.13 | bwd_allreduce: 76.64 | step: 25.17 + 18%|█▊ | 1574/8720 [3:57:47<13:56:51, 7.03s/it] {'loss': 0.6338, 'grad_norm': 7.664860248565674, 'learning_rate': 9.417950122968837e-06, 'epoch': 1.8} + 18%|█▊ | 1574/8720 [3:57:47<13:56:51, 7.03s/it]dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 1092 +[2025-05-02 02:13:14,015] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 107.37 | bwd_microstep: 160.86 | bwd_inner_microstep: 160.55 | bwd_allreduce_microstep: 0.14 | step_microstep: 0.11 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1384 +[2025-05-02 02:13:14,384] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 143.28 | bwd_microstep: 208.09 | bwd_inner_microstep: 208.08 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1899 +[2025-05-02 02:13:14,867] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.05 | bwd_microstep: 276.25 | bwd_inner_microstep: 276.24 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1893 +[2025-05-02 02:13:15,348] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.59 | bwd_microstep: 274.97 | bwd_inner_microstep: 274.96 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1886 +[2025-05-02 02:13:15,832] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.76 | bwd_microstep: 274.64 | bwd_inner_microstep: 274.62 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 02:13:16,315] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.41 | bwd_microstep: 273.01 | bwd_inner_microstep: 273.00 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 02:13:16,798] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.76 | bwd_microstep: 272.29 | bwd_inner_microstep: 272.27 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 02:13:17,277] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.43 | bwd_microstep: 272.89 | bwd_inner_microstep: 272.87 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 02:13:17,755] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.27 | bwd_microstep: 272.45 | bwd_inner_microstep: 272.44 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 325 +[2025-05-02 02:13:17,980] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 90.15 | bwd_microstep: 116.82 | bwd_inner_microstep: 116.58 | bwd_allreduce_microstep: 0.10 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 02:13:18,458] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.91 | bwd_microstep: 272.31 | bwd_inner_microstep: 272.29 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 832 +[2025-05-02 02:13:18,697] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 92.45 | bwd_microstep: 130.10 | bwd_inner_microstep: 129.99 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 02:13:19,172] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.12 | bwd_microstep: 271.13 | bwd_inner_microstep: 271.11 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 02:13:19,648] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.42 | bwd_microstep: 271.44 | bwd_inner_microstep: 271.43 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 02:13:20,125] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.76 | bwd_microstep: 271.29 | bwd_inner_microstep: 271.27 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 826 +[2025-05-02 02:13:20,475] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.19 | optimizer_step: 22.84 +[2025-05-02 02:13:20,476] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 97.42 | bwd_microstep: 206.37 | bwd_inner_microstep: 130.17 | bwd_allreduce_microstep: 76.07 | step_microstep: 30.78 +[2025-05-02 02:13:20,477] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2603.78 | bwd: 3825.00 | bwd_inner: 3748.03 | bwd_allreduce: 76.41 | step: 31.80 + 18%|█▊ | 1575/8720 [3:57:54<13:46:55, 6.94s/it] {'loss': 0.7216, 'grad_norm': 10.3098783493042, 'learning_rate': 9.417080176271448e-06, 'epoch': 1.81} + 18%|█▊ | 1575/8720 [3:57:54<13:46:55, 6.94s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2116 +[2025-05-02 02:13:21,016] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 203.80 | bwd_microstep: 311.94 | bwd_inner_microstep: 311.92 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1991 +[2025-05-02 02:13:21,526] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 197.13 | bwd_microstep: 294.04 | bwd_inner_microstep: 294.02 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1924 +[2025-05-02 02:13:22,029] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.88 | bwd_microstep: 286.99 | bwd_inner_microstep: 286.97 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1902 +[2025-05-02 02:13:22,518] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 191.54 | bwd_microstep: 275.47 | bwd_inner_microstep: 275.45 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 867 +[2025-05-02 02:13:22,773] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 98.34 | bwd_microstep: 136.21 | bwd_inner_microstep: 135.94 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.10 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 346 +[2025-05-02 02:13:23,014] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 83.45 | bwd_microstep: 141.50 | bwd_inner_microstep: 141.22 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-02 02:13:23,494] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.86 | bwd_microstep: 273.52 | bwd_inner_microstep: 273.51 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 02:13:23,975] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.52 | bwd_microstep: 273.01 | bwd_inner_microstep: 272.99 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 02:13:24,456] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.38 | bwd_microstep: 272.74 | bwd_inner_microstep: 272.72 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1355 +[2025-05-02 02:13:24,821] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.36 | bwd_microstep: 206.44 | bwd_inner_microstep: 206.42 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 02:13:25,299] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.14 | bwd_microstep: 272.44 | bwd_inner_microstep: 272.42 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 02:13:25,782] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.52 | bwd_microstep: 272.73 | bwd_inner_microstep: 272.71 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 02:13:26,260] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.23 | bwd_microstep: 272.62 | bwd_inner_microstep: 272.61 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 02:13:26,737] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.10 | bwd_microstep: 272.34 | bwd_inner_microstep: 272.32 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 02:13:27,217] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.24 | bwd_microstep: 272.30 | bwd_inner_microstep: 272.28 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 02:13:27,809] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.14 | optimizer_step: 20.41 +[2025-05-02 02:13:27,810] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.80 | bwd_microstep: 356.79 | bwd_inner_microstep: 271.68 | bwd_allreduce_microstep: 85.05 | step_microstep: 28.25 +[2025-05-02 02:13:27,811] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2803.89 | bwd: 4191.12 | bwd_inner: 4105.25 | bwd_allreduce: 85.36 | step: 29.39 + 18%|█▊ | 1576/8720 [3:58:01<14:00:44, 7.06s/it] {'loss': 0.7356, 'grad_norm': 12.36601734161377, 'learning_rate': 9.416209620177972e-06, 'epoch': 1.81} + 18%|█▊ | 1576/8720 [3:58:01<14:00:44, 7.06s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 02:13:28,291] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.27 | bwd_microstep: 270.04 | bwd_inner_microstep: 270.02 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2092 +[2025-05-02 02:13:28,817] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 203.99 | bwd_microstep: 304.65 | bwd_inner_microstep: 304.63 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 367 +[2025-05-02 02:13:29,049] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 91.04 | bwd_microstep: 123.26 | bwd_inner_microstep: 123.06 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-02 02:13:29,529] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.59 | bwd_microstep: 273.59 | bwd_inner_microstep: 273.58 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 334 +[2025-05-02 02:13:29,760] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 98.07 | bwd_microstep: 116.13 | bwd_inner_microstep: 115.85 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 845 +[2025-05-02 02:13:30,003] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.75 | bwd_microstep: 132.99 | bwd_inner_microstep: 132.72 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 02:13:30,480] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.13 | bwd_microstep: 272.30 | bwd_inner_microstep: 272.28 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 02:13:30,959] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.43 | bwd_microstep: 272.77 | bwd_inner_microstep: 272.75 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 02:13:31,434] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.02 | bwd_microstep: 272.58 | bwd_inner_microstep: 272.56 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 325 +[2025-05-02 02:13:31,633] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 67.27 | bwd_microstep: 118.97 | bwd_inner_microstep: 118.82 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 02:13:32,108] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.05 | bwd_microstep: 272.32 | bwd_inner_microstep: 272.31 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 02:13:32,584] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.31 | bwd_microstep: 272.13 | bwd_inner_microstep: 272.11 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 02:13:33,060] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.86 | bwd_microstep: 272.61 | bwd_inner_microstep: 272.59 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 322 +[2025-05-02 02:13:33,272] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 80.78 | bwd_microstep: 116.58 | bwd_inner_microstep: 116.44 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 02:13:33,746] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.73 | bwd_microstep: 270.95 | bwd_inner_microstep: 270.94 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 02:13:34,309] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.04 | optimizer_gradients: 2.15 | optimizer_step: 16.27 +[2025-05-02 02:13:34,309] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.81 | bwd_microstep: 336.95 | bwd_inner_microstep: 271.37 | bwd_allreduce_microstep: 65.53 | step_microstep: 23.23 +[2025-05-02 02:13:34,310] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2513.79 | bwd: 3698.90 | bwd_inner: 3632.21 | bwd_allreduce: 65.99 | step: 24.17 + 18%|█▊ | 1577/8720 [3:58:08<13:40:29, 6.89s/it] {'loss': 0.3881, 'grad_norm': 6.828419208526611, 'learning_rate': 9.415338454808515e-06, 'epoch': 1.81} + 18%|█▊ | 1577/8720 [3:58:08<13:40:29, 6.89s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 02:13:34,787] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.30 | bwd_microstep: 269.89 | bwd_inner_microstep: 269.87 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1921 +[2025-05-02 02:13:35,284] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.69 | bwd_microstep: 286.66 | bwd_inner_microstep: 286.64 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1886 +[2025-05-02 02:13:35,763] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.58 | bwd_microstep: 274.43 | bwd_inner_microstep: 274.41 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 860 +[2025-05-02 02:13:36,005] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.85 | bwd_microstep: 133.65 | bwd_inner_microstep: 133.40 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-02 02:13:36,484] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.90 | bwd_microstep: 274.19 | bwd_inner_microstep: 274.17 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1367 +[2025-05-02 02:13:36,847] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.80 | bwd_microstep: 207.18 | bwd_inner_microstep: 206.99 | bwd_allreduce_microstep: 0.08 | step_microstep: 0.10 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1366 +[2025-05-02 02:13:37,209] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.79 | bwd_microstep: 206.65 | bwd_inner_microstep: 206.64 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 02:13:37,684] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.15 | bwd_microstep: 272.48 | bwd_inner_microstep: 272.46 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 329 +[2025-05-02 02:13:37,883] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 67.30 | bwd_microstep: 117.88 | bwd_inner_microstep: 117.62 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 02:13:38,358] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.10 | bwd_microstep: 272.44 | bwd_inner_microstep: 272.42 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 02:13:38,834] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.05 | bwd_microstep: 272.51 | bwd_inner_microstep: 272.49 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 02:13:39,309] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.75 | bwd_microstep: 272.10 | bwd_inner_microstep: 272.08 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 834 +[2025-05-02 02:13:39,540] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 91.38 | bwd_microstep: 125.60 | bwd_inner_microstep: 125.51 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 02:13:40,016] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.02 | bwd_microstep: 272.34 | bwd_inner_microstep: 272.32 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 02:13:40,492] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.13 | bwd_microstep: 272.34 | bwd_inner_microstep: 272.32 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 02:13:41,056] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.15 | optimizer_step: 16.33 +[2025-05-02 02:13:41,056] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.47 | bwd_microstep: 336.97 | bwd_inner_microstep: 271.33 | bwd_allreduce_microstep: 65.60 | step_microstep: 23.45 +[2025-05-02 02:13:41,058] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2612.97 | bwd: 3867.34 | bwd_inner: 3800.74 | bwd_allreduce: 66.04 | step: 24.30 + 18%|█▊ | 1578/8720 [3:58:14<13:35:12, 6.85s/it] {'loss': 0.6053, 'grad_norm': 20.753854751586914, 'learning_rate': 9.414466680283264e-06, 'epoch': 1.81} + 18%|█▊ | 1578/8720 [3:58:14<13:35:12, 6.85s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 02:13:41,536] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.04 | bwd_microstep: 270.40 | bwd_inner_microstep: 270.27 | bwd_allreduce_microstep: 0.04 | step_microstep: 0.24 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2016 +[2025-05-02 02:13:42,047] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 199.59 | bwd_microstep: 295.53 | bwd_inner_microstep: 295.51 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 867 +[2025-05-02 02:13:42,289] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.25 | bwd_microstep: 134.07 | bwd_inner_microstep: 133.80 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-02 02:13:42,766] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.95 | bwd_microstep: 273.30 | bwd_inner_microstep: 273.28 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-02 02:13:43,246] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.67 | bwd_microstep: 273.53 | bwd_inner_microstep: 273.51 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-02 02:13:43,724] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.26 | bwd_microstep: 272.92 | bwd_inner_microstep: 272.90 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 02:13:44,204] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.84 | bwd_microstep: 273.16 | bwd_inner_microstep: 273.14 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 02:13:44,686] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.40 | bwd_microstep: 272.77 | bwd_inner_microstep: 272.75 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 02:13:45,164] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.13 | bwd_microstep: 272.88 | bwd_inner_microstep: 272.86 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 02:13:45,643] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.54 | bwd_microstep: 272.49 | bwd_inner_microstep: 272.47 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 02:13:46,125] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.48 | bwd_microstep: 272.36 | bwd_inner_microstep: 272.34 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.16 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 02:13:46,603] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.20 | bwd_microstep: 272.18 | bwd_inner_microstep: 272.16 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 02:13:47,082] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.72 | bwd_microstep: 273.13 | bwd_inner_microstep: 273.11 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 02:13:47,559] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.73 | bwd_microstep: 272.37 | bwd_inner_microstep: 272.36 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 316 +[2025-05-02 02:13:47,772] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 77.43 | bwd_microstep: 120.96 | bwd_inner_microstep: 120.71 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 02:13:48,336] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.18 | optimizer_step: 16.41 +[2025-05-02 02:13:48,337] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.21 | bwd_microstep: 337.61 | bwd_inner_microstep: 271.28 | bwd_allreduce_microstep: 66.29 | step_microstep: 23.63 +[2025-05-02 02:13:48,338] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2819.13 | bwd: 4159.72 | bwd_inner: 4092.53 | bwd_allreduce: 66.62 | step: 24.82 + 18%|█▊ | 1579/8720 [3:58:22<13:50:30, 6.98s/it] {'loss': 0.5552, 'grad_norm': 13.033891677856445, 'learning_rate': 9.413594296722495e-06, 'epoch': 1.81} + 18%|█▊ | 1579/8720 [3:58:22<13:50:30, 6.98s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 02:13:48,816] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.92 | bwd_microstep: 270.30 | bwd_inner_microstep: 270.28 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 460 +[2025-05-02 02:13:49,039] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 78.01 | bwd_microstep: 130.49 | bwd_inner_microstep: 130.26 | bwd_allreduce_microstep: 0.09 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1904 +[2025-05-02 02:13:49,519] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.38 | bwd_microstep: 275.70 | bwd_inner_microstep: 275.68 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 362 +[2025-05-02 02:13:49,734] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 78.62 | bwd_microstep: 121.07 | bwd_inner_microstep: 120.94 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-02 02:13:50,211] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.12 | bwd_microstep: 274.06 | bwd_inner_microstep: 274.04 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1372 +[2025-05-02 02:13:50,575] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.18 | bwd_microstep: 207.35 | bwd_inner_microstep: 207.33 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 02:13:51,052] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.11 | bwd_microstep: 273.11 | bwd_inner_microstep: 273.10 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 02:13:51,530] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.20 | bwd_microstep: 273.27 | bwd_inner_microstep: 273.25 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 02:13:52,006] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.80 | bwd_microstep: 272.36 | bwd_inner_microstep: 272.34 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 839 +[2025-05-02 02:13:52,241] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 92.03 | bwd_microstep: 126.33 | bwd_inner_microstep: 126.08 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 02:13:52,718] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.45 | bwd_microstep: 272.41 | bwd_inner_microstep: 272.40 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 02:13:53,200] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.79 | bwd_microstep: 272.73 | bwd_inner_microstep: 272.71 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 02:13:53,680] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.73 | bwd_microstep: 272.51 | bwd_inner_microstep: 272.49 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 02:13:54,158] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.43 | bwd_microstep: 272.10 | bwd_inner_microstep: 272.08 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 02:13:54,638] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.43 | bwd_microstep: 271.13 | bwd_inner_microstep: 271.11 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 02:13:55,219] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.22 | optimizer_step: 16.49 +[2025-05-02 02:13:55,220] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.98 | bwd_microstep: 348.81 | bwd_inner_microstep: 271.66 | bwd_allreduce_microstep: 77.09 | step_microstep: 24.55 +[2025-05-02 02:13:55,221] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2649.86 | bwd: 3933.80 | bwd_inner: 3855.84 | bwd_allreduce: 77.40 | step: 25.52 + 18%|█▊ | 1580/8720 [3:58:28<13:47:04, 6.95s/it] {'loss': 0.739, 'grad_norm': 10.392534255981445, 'learning_rate': 9.412721304246564e-06, 'epoch': 1.81} + 18%|█▊ | 1580/8720 [3:58:28<13:47:04, 6.95s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 02:13:55,702] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.42 | bwd_microstep: 269.75 | bwd_inner_microstep: 269.73 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1889 +[2025-05-02 02:13:56,183] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.02 | bwd_microstep: 274.41 | bwd_inner_microstep: 274.39 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1888 +[2025-05-02 02:13:56,661] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.02 | bwd_microstep: 274.34 | bwd_inner_microstep: 274.32 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-02 02:13:57,140] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.10 | bwd_microstep: 273.96 | bwd_inner_microstep: 273.94 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1364 +[2025-05-02 02:13:57,506] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.74 | bwd_microstep: 206.46 | bwd_inner_microstep: 206.44 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 02:13:57,989] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.95 | bwd_microstep: 272.55 | bwd_inner_microstep: 272.53 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-02 02:13:58,474] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.80 | bwd_microstep: 273.30 | bwd_inner_microstep: 273.29 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 02:13:58,958] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.21 | bwd_microstep: 274.01 | bwd_inner_microstep: 273.99 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 325 +[2025-05-02 02:13:59,180] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 84.97 | bwd_microstep: 118.90 | bwd_inner_microstep: 118.75 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 326 +[2025-05-02 02:13:59,407] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 79.71 | bwd_microstep: 131.40 | bwd_inner_microstep: 131.09 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 02:13:59,884] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.24 | bwd_microstep: 271.91 | bwd_inner_microstep: 271.89 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 02:14:00,360] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.57 | bwd_microstep: 271.82 | bwd_inner_microstep: 271.81 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 02:14:00,840] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.01 | bwd_microstep: 271.89 | bwd_inner_microstep: 271.88 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.16 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 02:14:01,321] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.37 | bwd_microstep: 271.01 | bwd_inner_microstep: 270.99 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 02:14:01,797] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.93 | bwd_microstep: 271.19 | bwd_inner_microstep: 271.17 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 02:14:02,381] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.22 | optimizer_step: 16.47 +[2025-05-02 02:14:02,381] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.11 | bwd_microstep: 351.87 | bwd_inner_microstep: 271.67 | bwd_allreduce_microstep: 80.15 | step_microstep: 24.51 +[2025-05-02 02:14:02,383] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2752.78 | bwd: 4078.81 | bwd_inner: 3998.00 | bwd_allreduce: 80.39 | step: 25.79 + 18%|█▊ | 1581/8720 [3:58:36<13:54:30, 7.01s/it] {'loss': 0.5356, 'grad_norm': 13.895511627197266, 'learning_rate': 9.41184770297591e-06, 'epoch': 1.81} + 18%|█▊ | 1581/8720 [3:58:36<13:54:30, 7.01s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 02:14:02,864] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.75 | bwd_microstep: 270.24 | bwd_inner_microstep: 270.22 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2201 +[2025-05-02 02:14:03,412] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 207.06 | bwd_microstep: 321.91 | bwd_inner_microstep: 321.89 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 02:14:03,892] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.07 | bwd_microstep: 272.98 | bwd_inner_microstep: 272.96 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 02:14:04,376] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.39 | bwd_microstep: 273.33 | bwd_inner_microstep: 273.31 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-02 02:14:04,856] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.45 | bwd_microstep: 273.03 | bwd_inner_microstep: 273.01 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-02 02:14:05,336] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.11 | bwd_microstep: 273.63 | bwd_inner_microstep: 273.61 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 334 +[2025-05-02 02:14:05,570] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 96.94 | bwd_microstep: 119.29 | bwd_inner_microstep: 119.03 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 02:14:06,050] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.34 | bwd_microstep: 273.12 | bwd_inner_microstep: 273.10 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 02:14:06,529] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.68 | bwd_microstep: 272.57 | bwd_inner_microstep: 272.55 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 02:14:07,008] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.30 | bwd_microstep: 272.25 | bwd_inner_microstep: 272.24 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 02:14:07,488] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.24 | bwd_microstep: 272.25 | bwd_inner_microstep: 272.23 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 02:14:07,969] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.19 | bwd_microstep: 271.16 | bwd_inner_microstep: 271.14 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 02:14:08,446] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.10 | bwd_microstep: 271.18 | bwd_inner_microstep: 271.16 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 317 +[2025-05-02 02:14:08,690] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.03 | bwd_microstep: 133.48 | bwd_inner_microstep: 133.33 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 02:14:09,168] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.26 | bwd_microstep: 270.60 | bwd_inner_microstep: 270.58 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 962 +[2025-05-02 02:14:09,562] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.25 | optimizer_step: 28.72 +[2025-05-02 02:14:09,563] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 106.92 | bwd_microstep: 232.18 | bwd_inner_microstep: 150.19 | bwd_allreduce_microstep: 81.88 | step_microstep: 36.86 +[2025-05-02 02:14:09,564] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2767.43 | bwd: 4073.24 | bwd_inner: 3990.69 | bwd_allreduce: 82.09 | step: 37.78 + 18%|█▊ | 1582/8720 [3:58:43<14:00:22, 7.06s/it] {'loss': 0.5528, 'grad_norm': 16.83113670349121, 'learning_rate': 9.41097349303106e-06, 'epoch': 1.81} + 18%|█▊ | 1582/8720 [3:58:43<14:00:22, 7.06s/it]dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1120 +[2025-05-02 02:14:09,868] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 118.72 | bwd_microstep: 162.44 | bwd_inner_microstep: 162.36 | bwd_allreduce_microstep: 0.03 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1897 +[2025-05-02 02:14:10,350] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.13 | bwd_microstep: 275.22 | bwd_inner_microstep: 275.20 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-02 02:14:10,832] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.54 | bwd_microstep: 273.53 | bwd_inner_microstep: 273.51 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-02 02:14:11,315] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.07 | bwd_microstep: 273.69 | bwd_inner_microstep: 273.67 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1360 +[2025-05-02 02:14:11,681] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.60 | bwd_microstep: 206.43 | bwd_inner_microstep: 206.42 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 02:14:12,159] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.00 | bwd_microstep: 272.85 | bwd_inner_microstep: 272.83 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 02:14:12,642] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.14 | bwd_microstep: 272.79 | bwd_inner_microstep: 272.77 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 02:14:13,125] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.30 | bwd_microstep: 272.71 | bwd_inner_microstep: 272.70 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.05 +dynamic ViT batch size: 6, images per sample: 6.0, dynamic token length: 1613 +[2025-05-02 02:14:13,556] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 164.24 | bwd_microstep: 243.57 | bwd_inner_microstep: 243.56 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 02:14:14,037] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.38 | bwd_microstep: 272.40 | bwd_inner_microstep: 272.38 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 02:14:14,519] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.82 | bwd_microstep: 272.27 | bwd_inner_microstep: 272.25 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.17 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 02:14:14,997] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.63 | bwd_microstep: 272.18 | bwd_inner_microstep: 272.17 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 839 +[2025-05-02 02:14:15,239] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 96.89 | bwd_microstep: 126.00 | bwd_inner_microstep: 125.93 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 02:14:15,717] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.87 | bwd_microstep: 272.63 | bwd_inner_microstep: 272.61 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 02:14:16,195] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.11 | bwd_microstep: 272.23 | bwd_inner_microstep: 272.22 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 02:14:16,780] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.19 | optimizer_step: 16.39 +[2025-05-02 02:14:16,780] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.18 | bwd_microstep: 354.35 | bwd_inner_microstep: 272.76 | bwd_allreduce_microstep: 81.54 | step_microstep: 24.17 +[2025-05-02 02:14:16,782] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2781.19 | bwd: 4095.34 | bwd_inner: 4013.33 | bwd_allreduce: 81.70 | step: 25.35 + 18%|█▊ | 1583/8720 [3:58:50<14:05:43, 7.11s/it] {'loss': 0.8671, 'grad_norm': 6.960371017456055, 'learning_rate': 9.410098674532622e-06, 'epoch': 1.82} + 18%|█▊ | 1583/8720 [3:58:50<14:05:43, 7.11s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-02 02:14:17,267] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.18 | bwd_microstep: 273.56 | bwd_inner_microstep: 273.54 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 882 +[2025-05-02 02:14:17,526] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 105.72 | bwd_microstep: 134.86 | bwd_inner_microstep: 134.79 | bwd_allreduce_microstep: 0.03 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1897 +[2025-05-02 02:14:18,009] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.32 | bwd_microstep: 275.11 | bwd_inner_microstep: 275.10 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1893 +[2025-05-02 02:14:18,490] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.68 | bwd_microstep: 274.97 | bwd_inner_microstep: 274.96 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-02 02:14:18,972] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.65 | bwd_microstep: 273.44 | bwd_inner_microstep: 273.42 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-02 02:14:19,451] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.19 | bwd_microstep: 273.62 | bwd_inner_microstep: 273.60 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1349 +[2025-05-02 02:14:19,817] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.56 | bwd_microstep: 205.51 | bwd_inner_microstep: 205.49 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 02:14:20,301] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.00 | bwd_microstep: 273.50 | bwd_inner_microstep: 273.48 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 02:14:20,784] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.41 | bwd_microstep: 272.64 | bwd_inner_microstep: 272.62 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 02:14:21,263] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.17 | bwd_microstep: 272.21 | bwd_inner_microstep: 272.19 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 839 +[2025-05-02 02:14:21,524] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 96.49 | bwd_microstep: 144.51 | bwd_inner_microstep: 144.25 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 321 +[2025-05-02 02:14:21,743] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 80.06 | bwd_microstep: 123.50 | bwd_inner_microstep: 123.19 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 02:14:22,220] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.85 | bwd_microstep: 272.11 | bwd_inner_microstep: 272.09 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 830 +[2025-05-02 02:14:22,463] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.22 | bwd_microstep: 129.99 | bwd_inner_microstep: 129.76 | bwd_allreduce_microstep: 0.16 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 02:14:22,939] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.33 | bwd_microstep: 270.83 | bwd_inner_microstep: 270.82 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 02:14:23,512] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.17 | optimizer_step: 16.35 +[2025-05-02 02:14:23,512] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.42 | bwd_microstep: 345.35 | bwd_inner_microstep: 271.37 | bwd_allreduce_microstep: 73.93 | step_microstep: 23.37 +[2025-05-02 02:14:23,513] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2591.88 | bwd: 3815.80 | bwd_inner: 3740.74 | bwd_allreduce: 74.44 | step: 24.46 + 18%|█▊ | 1584/8720 [3:58:57<13:52:03, 7.00s/it] {'loss': 0.7097, 'grad_norm': 15.022171974182129, 'learning_rate': 9.40922324760129e-06, 'epoch': 1.82} + 18%|█▊ | 1584/8720 [3:58:57<13:52:03, 7.00s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2033 +[2025-05-02 02:14:24,030] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 200.65 | bwd_microstep: 296.86 | bwd_inner_microstep: 296.84 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 02:14:24,508] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.79 | bwd_microstep: 272.88 | bwd_inner_microstep: 272.86 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-02 02:14:24,985] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.11 | bwd_microstep: 273.53 | bwd_inner_microstep: 273.51 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 02:14:25,462] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.50 | bwd_microstep: 272.79 | bwd_inner_microstep: 272.77 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-02 02:14:25,937] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.16 | bwd_microstep: 273.04 | bwd_inner_microstep: 273.02 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1361 +[2025-05-02 02:14:26,302] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 142.73 | bwd_microstep: 206.35 | bwd_inner_microstep: 206.21 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 02:14:26,781] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.99 | bwd_microstep: 272.45 | bwd_inner_microstep: 272.44 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 02:14:27,259] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.14 | bwd_microstep: 272.67 | bwd_inner_microstep: 272.65 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 02:14:27,737] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.29 | bwd_microstep: 272.48 | bwd_inner_microstep: 272.46 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 02:14:28,216] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.88 | bwd_microstep: 272.16 | bwd_inner_microstep: 272.15 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 02:14:28,699] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.10 | bwd_microstep: 272.53 | bwd_inner_microstep: 272.51 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 02:14:29,182] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.38 | bwd_microstep: 272.47 | bwd_inner_microstep: 272.45 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.07 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 02:14:29,666] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.64 | bwd_microstep: 272.36 | bwd_inner_microstep: 272.34 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.13 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1346 +[2025-05-02 02:14:30,031] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.22 | bwd_microstep: 205.23 | bwd_inner_microstep: 205.15 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 02:14:30,508] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.21 | bwd_microstep: 270.85 | bwd_inner_microstep: 270.83 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 02:14:31,088] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.18 | optimizer_step: 16.40 +[2025-05-02 02:14:31,089] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.83 | bwd_microstep: 348.92 | bwd_inner_microstep: 271.44 | bwd_allreduce_microstep: 77.43 | step_microstep: 24.25 +[2025-05-02 02:14:31,090] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2931.26 | bwd: 4327.62 | bwd_inner: 4249.64 | bwd_allreduce: 77.65 | step: 25.22 + 18%|█▊ | 1585/8720 [3:59:04<14:12:42, 7.17s/it] {'loss': 0.6889, 'grad_norm': 10.178923606872559, 'learning_rate': 9.408347212357843e-06, 'epoch': 1.82} + 18%|█▊ | 1585/8720 [3:59:04<14:12:42, 7.17s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 314 +[2025-05-02 02:14:31,312] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 79.35 | bwd_microstep: 121.34 | bwd_inner_microstep: 120.99 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1759 +[2025-05-02 02:14:31,747] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 163.38 | bwd_microstep: 255.58 | bwd_inner_microstep: 255.56 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1999 +[2025-05-02 02:14:32,258] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 200.11 | bwd_microstep: 293.84 | bwd_inner_microstep: 293.83 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1899 +[2025-05-02 02:14:32,738] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.85 | bwd_microstep: 274.90 | bwd_inner_microstep: 274.88 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 02:14:33,214] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.21 | bwd_microstep: 272.91 | bwd_inner_microstep: 272.89 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 02:14:33,689] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.91 | bwd_microstep: 272.39 | bwd_inner_microstep: 272.38 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 02:14:34,171] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.83 | bwd_microstep: 272.53 | bwd_inner_microstep: 272.51 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 02:14:34,653] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.92 | bwd_microstep: 272.78 | bwd_inner_microstep: 272.76 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 842 +[2025-05-02 02:14:34,901] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 96.11 | bwd_microstep: 131.66 | bwd_inner_microstep: 131.64 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 02:14:35,380] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.55 | bwd_microstep: 272.50 | bwd_inner_microstep: 272.49 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1091 +[2025-05-02 02:14:35,673] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 115.68 | bwd_microstep: 160.41 | bwd_inner_microstep: 160.22 | bwd_allreduce_microstep: 0.09 | step_microstep: 0.09 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 835 +[2025-05-02 02:14:35,908] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.90 | bwd_microstep: 125.69 | bwd_inner_microstep: 125.46 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 02:14:36,387] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.44 | bwd_microstep: 272.47 | bwd_inner_microstep: 272.45 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 02:14:36,864] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.32 | bwd_microstep: 271.84 | bwd_inner_microstep: 271.82 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 02:14:37,340] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.22 | bwd_microstep: 271.08 | bwd_inner_microstep: 271.06 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 02:14:37,902] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.14 | optimizer_step: 16.30 +[2025-05-02 02:14:37,903] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.52 | bwd_microstep: 336.95 | bwd_inner_microstep: 271.26 | bwd_allreduce_microstep: 65.64 | step_microstep: 23.23 +[2025-05-02 02:14:37,904] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2629.97 | bwd: 3878.95 | bwd_inner: 3812.31 | bwd_allreduce: 66.08 | step: 24.32 + 18%|█▊ | 1586/8720 [3:59:11<13:59:48, 7.06s/it] {'loss': 0.5077, 'grad_norm': 19.117204666137695, 'learning_rate': 9.407470568923139e-06, 'epoch': 1.82} + 18%|█▊ | 1586/8720 [3:59:11<13:59:48, 7.06s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 02:14:38,382] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.06 | bwd_microstep: 270.23 | bwd_inner_microstep: 270.22 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1912 +[2025-05-02 02:14:38,864] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.94 | bwd_microstep: 276.47 | bwd_inner_microstep: 276.45 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1893 +[2025-05-02 02:14:39,343] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.50 | bwd_microstep: 274.92 | bwd_inner_microstep: 274.91 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 864 +[2025-05-02 02:14:39,585] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.65 | bwd_microstep: 133.72 | bwd_inner_microstep: 133.52 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1883 +[2025-05-02 02:14:40,064] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.21 | bwd_microstep: 274.28 | bwd_inner_microstep: 274.27 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 02:14:40,541] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.11 | bwd_microstep: 272.96 | bwd_inner_microstep: 272.95 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 02:14:41,017] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.23 | bwd_microstep: 272.50 | bwd_inner_microstep: 272.48 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 02:14:41,492] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.92 | bwd_microstep: 272.49 | bwd_inner_microstep: 272.48 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 02:14:41,968] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.18 | bwd_microstep: 272.71 | bwd_inner_microstep: 272.69 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 02:14:42,446] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.97 | bwd_microstep: 273.26 | bwd_inner_microstep: 273.24 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 02:14:42,923] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.95 | bwd_microstep: 272.61 | bwd_inner_microstep: 272.59 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 02:14:43,402] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.01 | bwd_microstep: 272.19 | bwd_inner_microstep: 272.17 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 02:14:43,879] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.85 | bwd_microstep: 271.32 | bwd_inner_microstep: 271.30 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1086 +[2025-05-02 02:14:44,170] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 115.08 | bwd_microstep: 159.43 | bwd_inner_microstep: 159.42 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 02:14:44,646] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.74 | bwd_microstep: 270.95 | bwd_inner_microstep: 270.93 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 827 +[2025-05-02 02:14:44,985] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.15 | optimizer_step: 16.34 +[2025-05-02 02:14:44,985] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.36 | bwd_microstep: 206.95 | bwd_inner_microstep: 130.26 | bwd_allreduce_microstep: 76.53 | step_microstep: 23.75 +[2025-05-02 02:14:44,987] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2755.47 | bwd: 4047.05 | bwd_inner: 3969.93 | bwd_allreduce: 76.69 | step: 24.63 + 18%|█▊ | 1587/8720 [3:59:18<14:00:22, 7.07s/it] {'loss': 0.7063, 'grad_norm': 11.223892211914062, 'learning_rate': 9.406593317418123e-06, 'epoch': 1.82} + 18%|█▊ | 1587/8720 [3:59:18<14:00:22, 7.07s/it]dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 827 +[2025-05-02 02:14:45,227] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 92.25 | bwd_microstep: 129.65 | bwd_inner_microstep: 129.55 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1895 +[2025-05-02 02:14:45,706] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.92 | bwd_microstep: 275.00 | bwd_inner_microstep: 274.99 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1883 +[2025-05-02 02:14:46,185] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.56 | bwd_microstep: 274.17 | bwd_inner_microstep: 274.15 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-02 02:14:46,663] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.00 | bwd_microstep: 273.68 | bwd_inner_microstep: 273.67 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 833 +[2025-05-02 02:14:46,895] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 92.52 | bwd_microstep: 126.07 | bwd_inner_microstep: 125.80 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 02:14:47,372] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.91 | bwd_microstep: 272.42 | bwd_inner_microstep: 272.40 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 02:14:47,846] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.39 | bwd_microstep: 272.09 | bwd_inner_microstep: 272.07 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 839 +[2025-05-02 02:14:48,078] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 91.96 | bwd_microstep: 126.41 | bwd_inner_microstep: 126.23 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 02:14:48,554] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.18 | bwd_microstep: 272.66 | bwd_inner_microstep: 272.64 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 02:14:49,029] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.20 | bwd_microstep: 272.75 | bwd_inner_microstep: 272.74 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 02:14:49,505] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.18 | bwd_microstep: 272.07 | bwd_inner_microstep: 272.05 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 02:14:49,979] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.37 | bwd_microstep: 271.10 | bwd_inner_microstep: 271.08 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 02:14:50,455] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.21 | bwd_microstep: 272.22 | bwd_inner_microstep: 272.20 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 02:14:50,930] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.72 | bwd_microstep: 271.16 | bwd_inner_microstep: 271.14 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 02:14:51,407] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.66 | bwd_microstep: 271.10 | bwd_inner_microstep: 271.08 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 317 +[2025-05-02 02:14:51,765] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.18 | optimizer_step: 16.37 +[2025-05-02 02:14:51,766] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 91.78 | bwd_microstep: 224.74 | bwd_inner_microstep: 148.63 | bwd_allreduce_microstep: 75.97 | step_microstep: 24.02 +[2025-05-02 02:14:51,767] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2626.51 | bwd: 3877.37 | bwd_inner: 3800.50 | bwd_allreduce: 76.29 | step: 24.96 + 18%|█▊ | 1588/8720 [3:59:25<13:50:02, 6.98s/it] {'loss': 0.3992, 'grad_norm': 6.939387798309326, 'learning_rate': 9.405715457963824e-06, 'epoch': 1.82} + 18%|█▊ | 1588/8720 [3:59:25<13:50:02, 6.98s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 02:14:52,248] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.89 | bwd_microstep: 270.43 | bwd_inner_microstep: 270.41 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1982 +[2025-05-02 02:14:52,755] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 196.36 | bwd_microstep: 291.97 | bwd_inner_microstep: 291.95 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1948 +[2025-05-02 02:14:53,259] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 196.20 | bwd_microstep: 288.97 | bwd_inner_microstep: 288.95 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1920 +[2025-05-02 02:14:53,745] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.09 | bwd_microstep: 276.57 | bwd_inner_microstep: 276.55 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1903 +[2025-05-02 02:14:54,230] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.26 | bwd_microstep: 275.57 | bwd_inner_microstep: 275.56 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1899 +[2025-05-02 02:14:54,716] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.20 | bwd_microstep: 275.65 | bwd_inner_microstep: 275.63 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1890 +[2025-05-02 02:14:55,198] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.34 | bwd_microstep: 274.72 | bwd_inner_microstep: 274.70 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 02:14:55,679] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.37 | bwd_microstep: 273.11 | bwd_inner_microstep: 273.09 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 02:14:56,159] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.67 | bwd_microstep: 273.33 | bwd_inner_microstep: 273.31 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 02:14:56,638] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.84 | bwd_microstep: 272.58 | bwd_inner_microstep: 272.56 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1095 +[2025-05-02 02:14:56,930] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 117.79 | bwd_microstep: 161.01 | bwd_inner_microstep: 160.99 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 02:14:57,405] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.48 | bwd_microstep: 272.34 | bwd_inner_microstep: 272.32 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 02:14:57,881] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.61 | bwd_microstep: 272.85 | bwd_inner_microstep: 272.84 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 02:14:58,357] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.71 | bwd_microstep: 272.55 | bwd_inner_microstep: 272.53 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 831 +[2025-05-02 02:14:58,597] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.66 | bwd_microstep: 130.24 | bwd_inner_microstep: 129.92 | bwd_allreduce_microstep: 0.18 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 02:14:59,178] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.19 | optimizer_step: 16.39 +[2025-05-02 02:14:59,179] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.11 | bwd_microstep: 351.54 | bwd_inner_microstep: 271.62 | bwd_allreduce_microstep: 79.86 | step_microstep: 24.14 +[2025-05-02 02:14:59,180] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2870.21 | bwd: 4233.44 | bwd_inner: 4152.96 | bwd_allreduce: 80.10 | step: 24.93 + 18%|█▊ | 1589/8720 [3:59:32<14:05:16, 7.11s/it] {'loss': 0.6036, 'grad_norm': 7.0938401222229, 'learning_rate': 9.404836990681355e-06, 'epoch': 1.82} + 18%|█▊ | 1589/8720 [3:59:32<14:05:16, 7.11s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 02:14:59,661] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.63 | bwd_microstep: 270.02 | bwd_inner_microstep: 270.01 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1903 +[2025-05-02 02:15:00,145] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.00 | bwd_microstep: 275.78 | bwd_inner_microstep: 275.76 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-02 02:15:00,625] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.00 | bwd_microstep: 273.94 | bwd_inner_microstep: 273.92 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-02 02:15:01,107] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.49 | bwd_microstep: 273.38 | bwd_inner_microstep: 273.36 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-02 02:15:01,589] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.49 | bwd_microstep: 273.55 | bwd_inner_microstep: 273.53 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 02:15:02,070] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.24 | bwd_microstep: 273.26 | bwd_inner_microstep: 273.25 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 02:15:02,549] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.40 | bwd_microstep: 273.12 | bwd_inner_microstep: 273.10 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 02:15:03,030] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.55 | bwd_microstep: 273.14 | bwd_inner_microstep: 273.13 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 02:15:03,512] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.63 | bwd_microstep: 272.27 | bwd_inner_microstep: 272.26 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1358 +[2025-05-02 02:15:03,881] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.60 | bwd_microstep: 206.56 | bwd_inner_microstep: 206.54 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 837 +[2025-05-02 02:15:04,119] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.71 | bwd_microstep: 126.02 | bwd_inner_microstep: 125.94 | bwd_allreduce_microstep: 0.03 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 02:15:04,598] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.75 | bwd_microstep: 272.46 | bwd_inner_microstep: 272.44 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 02:15:05,077] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.12 | bwd_microstep: 272.61 | bwd_inner_microstep: 272.59 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 02:15:05,558] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.59 | bwd_microstep: 272.44 | bwd_inner_microstep: 272.42 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 326 +[2025-05-02 02:15:05,799] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 102.33 | bwd_microstep: 117.83 | bwd_inner_microstep: 117.68 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 02:15:06,378] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.20 | optimizer_step: 16.46 +[2025-05-02 02:15:06,378] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.09 | bwd_microstep: 349.08 | bwd_inner_microstep: 271.78 | bwd_allreduce_microstep: 77.25 | step_microstep: 24.46 +[2025-05-02 02:15:06,380] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2790.19 | bwd: 4075.50 | bwd_inner: 3997.74 | bwd_allreduce: 77.43 | step: 25.40 + 18%|█▊ | 1590/8720 [3:59:40<14:08:16, 7.14s/it] {'loss': 1.0395, 'grad_norm': 9.886592864990234, 'learning_rate': 9.403957915691914e-06, 'epoch': 1.82} + 18%|█▊ | 1590/8720 [3:59:40<14:08:16, 7.14s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 02:15:06,861] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.17 | bwd_microstep: 270.18 | bwd_inner_microstep: 270.17 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1921 +[2025-05-02 02:15:07,359] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.14 | bwd_microstep: 286.52 | bwd_inner_microstep: 286.50 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1893 +[2025-05-02 02:15:07,838] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.45 | bwd_microstep: 274.99 | bwd_inner_microstep: 274.97 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1896 +[2025-05-02 02:15:08,318] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.47 | bwd_microstep: 275.01 | bwd_inner_microstep: 274.99 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1911 +[2025-05-02 02:15:08,802] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.15 | bwd_microstep: 276.29 | bwd_inner_microstep: 276.28 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-02 02:15:09,281] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.24 | bwd_microstep: 273.07 | bwd_inner_microstep: 273.05 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 02:15:09,760] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.42 | bwd_microstep: 272.98 | bwd_inner_microstep: 272.97 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 329 +[2025-05-02 02:15:10,011] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.81 | bwd_microstep: 137.52 | bwd_inner_microstep: 137.34 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1357 +[2025-05-02 02:15:10,379] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 142.91 | bwd_microstep: 206.61 | bwd_inner_microstep: 206.60 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 02:15:10,858] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.92 | bwd_microstep: 272.38 | bwd_inner_microstep: 272.36 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 02:15:11,338] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.40 | bwd_microstep: 272.50 | bwd_inner_microstep: 272.48 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 02:15:11,816] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.41 | bwd_microstep: 272.17 | bwd_inner_microstep: 272.15 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 02:15:12,295] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.39 | bwd_microstep: 271.96 | bwd_inner_microstep: 271.94 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1094 +[2025-05-02 02:15:12,591] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 115.59 | bwd_microstep: 160.89 | bwd_inner_microstep: 160.67 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 02:15:13,068] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.90 | bwd_microstep: 271.16 | bwd_inner_microstep: 271.14 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 02:15:13,647] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.20 | optimizer_step: 16.44 +[2025-05-02 02:15:13,648] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.66 | bwd_microstep: 347.69 | bwd_inner_microstep: 271.38 | bwd_allreduce_microstep: 76.26 | step_microstep: 24.41 +[2025-05-02 02:15:13,649] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2808.65 | bwd: 4141.98 | bwd_inner: 4065.04 | bwd_allreduce: 76.51 | step: 25.27 + 18%|█▊ | 1591/8720 [3:59:47<14:12:49, 7.18s/it] {'loss': 0.6252, 'grad_norm': 11.53496265411377, 'learning_rate': 9.403078233116779e-06, 'epoch': 1.82} + 18%|█▊ | 1591/8720 [3:59:47<14:12:49, 7.18s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 02:15:14,131] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.31 | bwd_microstep: 270.24 | bwd_inner_microstep: 270.22 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1974 +[2025-05-02 02:15:14,639] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 198.58 | bwd_microstep: 290.78 | bwd_inner_microstep: 290.77 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1905 +[2025-05-02 02:15:15,123] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.33 | bwd_microstep: 275.76 | bwd_inner_microstep: 275.74 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 354 +[2025-05-02 02:15:15,375] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.74 | bwd_microstep: 138.41 | bwd_inner_microstep: 138.16 | bwd_allreduce_microstep: 0.10 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-02 02:15:15,856] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.38 | bwd_microstep: 273.63 | bwd_inner_microstep: 273.61 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 02:15:16,339] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.43 | bwd_microstep: 272.96 | bwd_inner_microstep: 272.95 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-02 02:15:16,821] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.44 | bwd_microstep: 273.18 | bwd_inner_microstep: 273.16 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-02 02:15:17,304] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.62 | bwd_microstep: 274.11 | bwd_inner_microstep: 274.09 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1109 +[2025-05-02 02:15:17,598] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 115.08 | bwd_microstep: 162.51 | bwd_inner_microstep: 162.35 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 02:15:18,077] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.14 | bwd_microstep: 272.72 | bwd_inner_microstep: 272.70 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 02:15:18,556] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.43 | bwd_microstep: 272.65 | bwd_inner_microstep: 272.63 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 02:15:19,034] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.40 | bwd_microstep: 272.48 | bwd_inner_microstep: 272.46 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 02:15:19,511] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.77 | bwd_microstep: 272.97 | bwd_inner_microstep: 272.96 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 02:15:19,987] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.49 | bwd_microstep: 272.25 | bwd_inner_microstep: 272.23 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 02:15:20,461] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.55 | bwd_microstep: 271.09 | bwd_inner_microstep: 271.07 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 02:15:21,025] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.21 | optimizer_step: 16.47 +[2025-05-02 02:15:21,025] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.33 | bwd_microstep: 338.24 | bwd_inner_microstep: 271.36 | bwd_allreduce_microstep: 66.83 | step_microstep: 23.71 +[2025-05-02 02:15:21,026] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2855.65 | bwd: 4204.04 | bwd_inner: 4136.54 | bwd_allreduce: 67.08 | step: 24.62 + 18%|█▊ | 1592/8720 [3:59:54<14:19:44, 7.24s/it] {'loss': 0.7256, 'grad_norm': 6.14448881149292, 'learning_rate': 9.402197943077315e-06, 'epoch': 1.83} + 18%|█▊ | 1592/8720 [3:59:54<14:19:44, 7.24s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 02:15:21,504] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.96 | bwd_microstep: 270.26 | bwd_inner_microstep: 270.25 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1894 +[2025-05-02 02:15:21,984] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.69 | bwd_microstep: 274.80 | bwd_inner_microstep: 274.78 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1883 +[2025-05-02 02:15:22,462] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.35 | bwd_microstep: 273.94 | bwd_inner_microstep: 273.92 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-02 02:15:22,938] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.80 | bwd_microstep: 272.82 | bwd_inner_microstep: 272.80 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 02:15:23,415] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.75 | bwd_microstep: 273.35 | bwd_inner_microstep: 273.33 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 02:15:23,895] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.56 | bwd_microstep: 272.98 | bwd_inner_microstep: 272.96 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-02 02:15:24,375] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.22 | bwd_microstep: 273.51 | bwd_inner_microstep: 273.49 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 02:15:24,856] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.47 | bwd_microstep: 273.55 | bwd_inner_microstep: 273.53 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 02:15:25,336] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.47 | bwd_microstep: 272.37 | bwd_inner_microstep: 272.36 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 02:15:25,816] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.52 | bwd_microstep: 272.78 | bwd_inner_microstep: 272.76 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 02:15:26,294] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.02 | bwd_microstep: 272.35 | bwd_inner_microstep: 272.34 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 323 +[2025-05-02 02:15:26,513] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 84.00 | bwd_microstep: 117.89 | bwd_inner_microstep: 117.54 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 02:15:26,991] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.70 | bwd_microstep: 272.14 | bwd_inner_microstep: 272.12 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 02:15:27,468] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.34 | bwd_microstep: 271.07 | bwd_inner_microstep: 271.05 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 02:15:27,948] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.50 | bwd_microstep: 271.12 | bwd_inner_microstep: 271.10 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 02:15:28,526] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.17 | optimizer_step: 16.49 +[2025-05-02 02:15:28,527] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.43 | bwd_microstep: 349.11 | bwd_inner_microstep: 271.73 | bwd_allreduce_microstep: 77.34 | step_microstep: 23.76 +[2025-05-02 02:15:28,528] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2909.46 | bwd: 4284.08 | bwd_inner: 4206.12 | bwd_allreduce: 77.53 | step: 24.64 + 18%|█▊ | 1593/8720 [4:00:02<14:29:03, 7.32s/it] {'loss': 0.9184, 'grad_norm': 9.600091934204102, 'learning_rate': 9.401317045694968e-06, 'epoch': 1.83} + 18%|█▊ | 1593/8720 [4:00:02<14:29:03, 7.32s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 02:15:29,007] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.13 | bwd_microstep: 270.24 | bwd_inner_microstep: 270.22 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 371 +[2025-05-02 02:15:29,221] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 76.93 | bwd_microstep: 122.41 | bwd_inner_microstep: 122.10 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 881 +[2025-05-02 02:15:29,469] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 97.30 | bwd_microstep: 135.11 | bwd_inner_microstep: 135.01 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1883 +[2025-05-02 02:15:29,948] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.00 | bwd_microstep: 274.25 | bwd_inner_microstep: 274.23 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 860 +[2025-05-02 02:15:30,191] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.65 | bwd_microstep: 133.49 | bwd_inner_microstep: 133.28 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.13 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-02 02:15:30,670] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.16 | bwd_microstep: 273.44 | bwd_inner_microstep: 273.43 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.13 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 02:15:31,151] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.93 | bwd_microstep: 272.97 | bwd_inner_microstep: 272.96 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 02:15:31,633] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.10 | bwd_microstep: 272.98 | bwd_inner_microstep: 272.97 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1351 +[2025-05-02 02:15:32,001] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.12 | bwd_microstep: 206.24 | bwd_inner_microstep: 206.16 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 02:15:32,479] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.93 | bwd_microstep: 272.39 | bwd_inner_microstep: 272.37 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 02:15:32,961] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.45 | bwd_microstep: 272.40 | bwd_inner_microstep: 272.38 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 02:15:33,446] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.30 | bwd_microstep: 272.35 | bwd_inner_microstep: 272.34 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 02:15:33,925] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.65 | bwd_microstep: 272.54 | bwd_inner_microstep: 272.53 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.14 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 02:15:34,406] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.67 | bwd_microstep: 272.46 | bwd_inner_microstep: 272.44 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 02:15:34,884] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.68 | bwd_microstep: 271.32 | bwd_inner_microstep: 271.30 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 02:15:35,467] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.27 | optimizer_step: 16.46 +[2025-05-02 02:15:35,468] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.78 | bwd_microstep: 348.92 | bwd_inner_microstep: 271.61 | bwd_allreduce_microstep: 77.26 | step_microstep: 24.50 +[2025-05-02 02:15:35,469] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2674.38 | bwd: 3943.65 | bwd_inner: 3865.39 | bwd_allreduce: 77.66 | step: 25.94 + 18%|█▊ | 1594/8720 [4:00:09<14:15:38, 7.20s/it] {'loss': 0.5077, 'grad_norm': 8.744040489196777, 'learning_rate': 9.400435541091275e-06, 'epoch': 1.83} + 18%|█▊ | 1594/8720 [4:00:09<14:15:38, 7.20s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 02:15:35,951] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.83 | bwd_microstep: 270.26 | bwd_inner_microstep: 270.24 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 375 +[2025-05-02 02:15:36,180] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 90.47 | bwd_microstep: 120.85 | bwd_inner_microstep: 120.70 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 02:15:36,660] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.62 | bwd_microstep: 273.25 | bwd_inner_microstep: 273.23 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1894 +[2025-05-02 02:15:37,141] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.04 | bwd_microstep: 274.71 | bwd_inner_microstep: 274.69 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-02 02:15:37,623] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.61 | bwd_microstep: 272.98 | bwd_inner_microstep: 272.96 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1362 +[2025-05-02 02:15:37,991] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.80 | bwd_microstep: 206.55 | bwd_inner_microstep: 206.53 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.11 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 333 +[2025-05-02 02:15:38,235] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 92.04 | bwd_microstep: 133.75 | bwd_inner_microstep: 133.60 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 02:15:38,713] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.12 | bwd_microstep: 272.55 | bwd_inner_microstep: 272.53 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 02:15:39,191] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.49 | bwd_microstep: 272.65 | bwd_inner_microstep: 272.63 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 02:15:39,671] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.58 | bwd_microstep: 272.19 | bwd_inner_microstep: 272.18 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 02:15:40,149] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.93 | bwd_microstep: 271.20 | bwd_inner_microstep: 271.18 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 02:15:40,629] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.36 | bwd_microstep: 272.10 | bwd_inner_microstep: 272.08 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 02:15:41,106] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.84 | bwd_microstep: 271.31 | bwd_inner_microstep: 271.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 02:15:41,585] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.65 | bwd_microstep: 272.50 | bwd_inner_microstep: 272.48 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 02:15:42,062] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.18 | bwd_microstep: 271.31 | bwd_inner_microstep: 271.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 02:15:42,638] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 3.15 | optimizer_step: 16.37 +[2025-05-02 02:15:42,639] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.01 | bwd_microstep: 347.48 | bwd_inner_microstep: 271.51 | bwd_allreduce_microstep: 75.93 | step_microstep: 24.43 +[2025-05-02 02:15:42,640] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2770.18 | bwd: 4075.69 | bwd_inner: 3999.20 | bwd_allreduce: 76.12 | step: 25.33 + 18%|█▊ | 1595/8720 [4:00:16<14:14:14, 7.19s/it] {'loss': 0.7014, 'grad_norm': 22.243438720703125, 'learning_rate': 9.399553429387847e-06, 'epoch': 1.83} + 18%|█▊ | 1595/8720 [4:00:16<14:14:14, 7.19s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 448 +[2025-05-02 02:15:42,841] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 67.83 | bwd_microstep: 115.03 | bwd_inner_microstep: 114.90 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1966 +[2025-05-02 02:15:43,342] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.65 | bwd_microstep: 290.55 | bwd_inner_microstep: 290.54 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 02:15:43,818] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.33 | bwd_microstep: 273.24 | bwd_inner_microstep: 273.22 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 02:15:44,294] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.93 | bwd_microstep: 272.55 | bwd_inner_microstep: 272.53 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-02 02:15:44,770] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.08 | bwd_microstep: 272.95 | bwd_inner_microstep: 272.93 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 846 +[2025-05-02 02:15:45,012] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 96.95 | bwd_microstep: 131.89 | bwd_inner_microstep: 131.84 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.08 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1109 +[2025-05-02 02:15:45,303] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 115.14 | bwd_microstep: 161.96 | bwd_inner_microstep: 161.77 | bwd_allreduce_microstep: 0.10 | step_microstep: 0.20 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 333 +[2025-05-02 02:15:45,512] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 75.62 | bwd_microstep: 119.80 | bwd_inner_microstep: 119.67 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 02:15:45,988] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.95 | bwd_microstep: 272.50 | bwd_inner_microstep: 272.49 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 02:15:46,465] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.05 | bwd_microstep: 273.17 | bwd_inner_microstep: 273.16 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 02:15:46,941] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.15 | bwd_microstep: 272.59 | bwd_inner_microstep: 272.57 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 02:15:47,418] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.63 | bwd_microstep: 272.97 | bwd_inner_microstep: 272.95 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 02:15:47,893] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.86 | bwd_microstep: 272.35 | bwd_inner_microstep: 272.33 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 319 +[2025-05-02 02:15:48,105] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 76.89 | bwd_microstep: 120.71 | bwd_inner_microstep: 120.42 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 02:15:48,579] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.96 | bwd_microstep: 271.30 | bwd_inner_microstep: 271.28 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 02:15:49,142] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.15 | optimizer_step: 16.31 +[2025-05-02 02:15:49,143] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.70 | bwd_microstep: 337.76 | bwd_inner_microstep: 271.41 | bwd_allreduce_microstep: 66.31 | step_microstep: 23.35 +[2025-05-02 02:15:49,144] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2510.45 | bwd: 3731.44 | bwd_inner: 3664.13 | bwd_allreduce: 66.75 | step: 24.34 + 18%|█▊ | 1596/8720 [4:00:22<13:49:33, 6.99s/it] {'loss': 0.6188, 'grad_norm': 11.48967456817627, 'learning_rate': 9.398670710706384e-06, 'epoch': 1.83} + 18%|█▊ | 1596/8720 [4:00:22<13:49:33, 6.99s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 02:15:49,622] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.18 | bwd_microstep: 269.96 | bwd_inner_microstep: 269.94 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2067 +[2025-05-02 02:15:50,140] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 201.18 | bwd_microstep: 302.76 | bwd_inner_microstep: 302.74 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2054 +[2025-05-02 02:15:50,659] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 201.11 | bwd_microstep: 301.42 | bwd_inner_microstep: 301.40 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1909 +[2025-05-02 02:15:51,140] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.43 | bwd_microstep: 276.31 | bwd_inner_microstep: 276.29 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1370 +[2025-05-02 02:15:51,503] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.66 | bwd_microstep: 206.97 | bwd_inner_microstep: 206.95 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 02:15:51,980] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.67 | bwd_microstep: 272.91 | bwd_inner_microstep: 272.90 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-02 02:15:52,457] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.62 | bwd_microstep: 273.05 | bwd_inner_microstep: 273.03 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 02:15:52,932] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.73 | bwd_microstep: 272.36 | bwd_inner_microstep: 272.34 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 02:15:53,406] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.86 | bwd_microstep: 272.17 | bwd_inner_microstep: 272.16 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 02:15:53,882] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.00 | bwd_microstep: 271.82 | bwd_inner_microstep: 271.80 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 02:15:54,358] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.38 | bwd_microstep: 271.31 | bwd_inner_microstep: 271.30 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 02:15:54,835] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.32 | bwd_microstep: 272.21 | bwd_inner_microstep: 272.19 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 322 +[2025-05-02 02:15:55,068] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 91.16 | bwd_microstep: 123.86 | bwd_inner_microstep: 123.70 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 02:15:55,546] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.96 | bwd_microstep: 272.31 | bwd_inner_microstep: 272.29 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 02:15:56,023] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.44 | bwd_microstep: 272.01 | bwd_inner_microstep: 271.99 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 02:15:56,590] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.04 | optimizer_gradients: 3.39 | optimizer_step: 16.34 +[2025-05-02 02:15:56,590] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.82 | bwd_microstep: 338.36 | bwd_inner_microstep: 271.95 | bwd_allreduce_microstep: 66.37 | step_microstep: 24.55 +[2025-05-02 02:15:56,591] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2896.21 | bwd: 4269.80 | bwd_inner: 4202.99 | bwd_allreduce: 66.51 | step: 25.27 + 18%|█▊ | 1597/8720 [4:00:30<14:05:51, 7.13s/it] {'loss': 0.6582, 'grad_norm': 5.761222839355469, 'learning_rate': 9.39778738516867e-06, 'epoch': 1.83} + 18%|█▊ | 1597/8720 [4:00:30<14:05:51, 7.13s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 02:15:57,069] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.42 | bwd_microstep: 270.24 | bwd_inner_microstep: 270.22 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 993 +[2025-05-02 02:15:57,338] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 103.88 | bwd_microstep: 150.72 | bwd_inner_microstep: 150.58 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.08 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1393 +[2025-05-02 02:15:57,706] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 143.53 | bwd_microstep: 209.55 | bwd_inner_microstep: 209.46 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1894 +[2025-05-02 02:15:58,185] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.33 | bwd_microstep: 274.73 | bwd_inner_microstep: 274.72 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1892 +[2025-05-02 02:15:58,665] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.60 | bwd_microstep: 274.88 | bwd_inner_microstep: 274.86 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 02:15:59,142] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.05 | bwd_microstep: 273.47 | bwd_inner_microstep: 273.45 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-02 02:15:59,621] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.58 | bwd_microstep: 274.20 | bwd_inner_microstep: 274.18 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-02 02:16:00,100] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.79 | bwd_microstep: 273.84 | bwd_inner_microstep: 273.83 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-02 02:16:00,578] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.36 | bwd_microstep: 273.78 | bwd_inner_microstep: 273.76 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 02:16:01,056] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.74 | bwd_microstep: 272.56 | bwd_inner_microstep: 272.54 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 328 +[2025-05-02 02:16:01,258] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 70.73 | bwd_microstep: 117.85 | bwd_inner_microstep: 117.72 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 02:16:01,735] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.32 | bwd_microstep: 272.20 | bwd_inner_microstep: 272.19 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 02:16:02,211] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.95 | bwd_microstep: 272.16 | bwd_inner_microstep: 272.15 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 831 +[2025-05-02 02:16:02,448] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 92.33 | bwd_microstep: 130.22 | bwd_inner_microstep: 129.97 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 02:16:02,922] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.63 | bwd_microstep: 270.99 | bwd_inner_microstep: 270.97 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 02:16:03,486] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.04 | optimizer_gradients: 2.18 | optimizer_step: 16.33 +[2025-05-02 02:16:03,486] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.91 | bwd_microstep: 338.03 | bwd_inner_microstep: 271.73 | bwd_allreduce_microstep: 66.26 | step_microstep: 23.33 +[2025-05-02 02:16:03,487] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2674.88 | bwd: 3949.51 | bwd_inner: 3882.36 | bwd_allreduce: 66.56 | step: 24.24 + 18%|█▊ | 1598/8720 [4:00:37<13:57:34, 7.06s/it] {'loss': 0.7518, 'grad_norm': 12.77051830291748, 'learning_rate': 9.39690345289657e-06, 'epoch': 1.83} + 18%|█▊ | 1598/8720 [4:00:37<13:57:34, 7.06s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 02:16:03,964] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.07 | bwd_microstep: 270.21 | bwd_inner_microstep: 270.19 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1928 +[2025-05-02 02:16:04,462] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.54 | bwd_microstep: 287.33 | bwd_inner_microstep: 287.31 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 360 +[2025-05-02 02:16:04,664] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 70.44 | bwd_microstep: 117.24 | bwd_inner_microstep: 116.92 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 02:16:05,140] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.19 | bwd_microstep: 273.10 | bwd_inner_microstep: 273.08 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 02:16:05,618] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.28 | bwd_microstep: 273.14 | bwd_inner_microstep: 273.12 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1109 +[2025-05-02 02:16:05,910] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 115.48 | bwd_microstep: 162.22 | bwd_inner_microstep: 162.15 | bwd_allreduce_microstep: 0.04 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1883 +[2025-05-02 02:16:06,387] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.27 | bwd_microstep: 274.00 | bwd_inner_microstep: 273.98 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 02:16:06,863] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.56 | bwd_microstep: 272.72 | bwd_inner_microstep: 272.70 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 328 +[2025-05-02 02:16:07,068] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 75.72 | bwd_microstep: 115.90 | bwd_inner_microstep: 115.60 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 02:16:07,543] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.42 | bwd_microstep: 272.32 | bwd_inner_microstep: 272.31 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 02:16:08,020] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.21 | bwd_microstep: 272.42 | bwd_inner_microstep: 272.40 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 02:16:08,496] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.65 | bwd_microstep: 272.17 | bwd_inner_microstep: 272.15 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 02:16:08,970] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.79 | bwd_microstep: 271.29 | bwd_inner_microstep: 271.27 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 02:16:09,443] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.03 | bwd_microstep: 270.96 | bwd_inner_microstep: 270.94 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 835 +[2025-05-02 02:16:09,674] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 91.07 | bwd_microstep: 126.19 | bwd_inner_microstep: 126.02 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 02:16:10,238] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.17 | optimizer_step: 16.33 +[2025-05-02 02:16:10,238] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.65 | bwd_microstep: 337.85 | bwd_inner_microstep: 271.60 | bwd_allreduce_microstep: 66.20 | step_microstep: 23.43 +[2025-05-02 02:16:10,239] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2617.14 | bwd: 3869.16 | bwd_inner: 3801.86 | bwd_allreduce: 66.64 | step: 24.34 + 18%|█▊ | 1599/8720 [4:00:43<13:46:37, 6.97s/it] {'loss': 0.4867, 'grad_norm': 7.208169460296631, 'learning_rate': 9.396018914012037e-06, 'epoch': 1.83} + 18%|█▊ | 1599/8720 [4:00:43<13:46:37, 6.97s/it]dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1337 +[2025-05-02 02:16:10,604] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 142.20 | bwd_microstep: 203.53 | bwd_inner_microstep: 203.50 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 350 +[2025-05-02 02:16:10,809] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 76.06 | bwd_microstep: 115.76 | bwd_inner_microstep: 115.62 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 02:16:11,284] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.52 | bwd_microstep: 272.47 | bwd_inner_microstep: 272.45 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 02:16:11,760] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.40 | bwd_microstep: 272.83 | bwd_inner_microstep: 272.81 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1351 +[2025-05-02 02:16:12,123] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.57 | bwd_microstep: 206.04 | bwd_inner_microstep: 206.02 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 02:16:12,600] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.73 | bwd_microstep: 272.47 | bwd_inner_microstep: 272.46 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 321 +[2025-05-02 02:16:12,820] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 81.25 | bwd_microstep: 123.87 | bwd_inner_microstep: 123.53 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 02:16:13,300] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.71 | bwd_microstep: 272.85 | bwd_inner_microstep: 272.83 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1353 +[2025-05-02 02:16:13,668] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.70 | bwd_microstep: 206.21 | bwd_inner_microstep: 206.19 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 02:16:14,145] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.71 | bwd_microstep: 272.43 | bwd_inner_microstep: 272.42 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 322 +[2025-05-02 02:16:14,355] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 79.39 | bwd_microstep: 116.87 | bwd_inner_microstep: 116.54 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.08 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1351 +[2025-05-02 02:16:14,716] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.68 | bwd_microstep: 205.94 | bwd_inner_microstep: 205.85 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 02:16:15,190] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.37 | bwd_microstep: 271.14 | bwd_inner_microstep: 271.13 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 02:16:15,664] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.24 | bwd_microstep: 270.99 | bwd_inner_microstep: 270.97 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 315 +[2025-05-02 02:16:15,862] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 66.83 | bwd_microstep: 118.39 | bwd_inner_microstep: 118.24 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1974 +[2025-05-02 02:16:16,455] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.18 | optimizer_step: 16.43 +[2025-05-02 02:16:16,455] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 196.16 | bwd_microstep: 357.47 | bwd_inner_microstep: 291.90 | bwd_allreduce_microstep: 65.52 | step_microstep: 23.49 +[2025-05-02 02:16:16,457] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2381.20 | bwd: 3559.36 | bwd_inner: 3492.61 | bwd_allreduce: 66.00 | step: 24.49 + 18%|█▊ | 1600/8720 [4:00:50<13:19:53, 6.74s/it] {'loss': 0.5816, 'grad_norm': 8.619322776794434, 'learning_rate': 9.395133768637103e-06, 'epoch': 1.83} + 18%|█▊ | 1600/8720 [4:00:50<13:19:53, 6.74s/it][INFO|trainer.py:3503] 2025-05-02 02:16:18,913 >> Saving model checkpoint to work_dirs/internvl_chat_v2_5/ak/checkpoint-1600 +[INFO|configuration_utils.py:472] 2025-05-02 02:16:18,916 >> Configuration saved in work_dirs/internvl_chat_v2_5/ak/checkpoint-1600/config.json +[INFO|configuration_utils.py:807] 2025-05-02 02:16:18,916 >> Configuration saved in work_dirs/internvl_chat_v2_5/ak/checkpoint-1600/generation_config.json +[INFO|modeling_utils.py:2755] 2025-05-02 02:16:24,001 >> Model weights saved in work_dirs/internvl_chat_v2_5/ak/checkpoint-1600/model.safetensors +[INFO|tokenization_utils_base.py:2702] 2025-05-02 02:16:24,002 >> tokenizer config file saved in work_dirs/internvl_chat_v2_5/ak/checkpoint-1600/tokenizer_config.json +[INFO|tokenization_utils_base.py:2711] 2025-05-02 02:16:24,003 >> Special tokens file saved in work_dirs/internvl_chat_v2_5/ak/checkpoint-1600/special_tokens_map.json +[INFO|tokenization_utils_base.py:2762] 2025-05-02 02:16:24,003 >> added tokens file saved in work_dirs/internvl_chat_v2_5/ak/checkpoint-1600/added_tokens.json +[2025-05-02 02:16:24,133] [INFO] [logging.py:96:log_dist] [Rank 0] [Torch] Checkpoint global_step1600 is about to be saved! +[2025-05-02 02:16:24,150] [INFO] [logging.py:96:log_dist] [Rank 0] Saving model checkpoint: work_dirs/internvl_chat_v2_5/ak/checkpoint-1600/global_step1600/mp_rank_00_model_states.pt +[2025-05-02 02:16:24,150] [INFO] [torch_checkpoint_engine.py:21:save] [Torch] Saving work_dirs/internvl_chat_v2_5/ak/checkpoint-1600/global_step1600/mp_rank_00_model_states.pt... +[2025-05-02 02:16:28,598] [INFO] [torch_checkpoint_engine.py:23:save] [Torch] Saved work_dirs/internvl_chat_v2_5/ak/checkpoint-1600/global_step1600/mp_rank_00_model_states.pt. +[2025-05-02 02:16:28,599] [INFO] [torch_checkpoint_engine.py:21:save] [Torch] Saving work_dirs/internvl_chat_v2_5/ak/checkpoint-1600/global_step1600/bf16_zero_pp_rank_0_mp_rank_00_optim_states.pt... +[2025-05-02 02:16:28,801] [INFO] [torch_checkpoint_engine.py:23:save] [Torch] Saved work_dirs/internvl_chat_v2_5/ak/checkpoint-1600/global_step1600/bf16_zero_pp_rank_0_mp_rank_00_optim_states.pt. +[2025-05-02 02:16:28,801] [INFO] [engine.py:3536:_save_zero_checkpoint] zero checkpoint saved work_dirs/internvl_chat_v2_5/ak/checkpoint-1600/global_step1600/bf16_zero_pp_rank_0_mp_rank_00_optim_states.pt +[2025-05-02 02:16:28,801] [INFO] [torch_checkpoint_engine.py:33:commit] [Torch] Checkpoint global_step1600 is ready now! +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1933 +[2025-05-02 02:16:29,325] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 194.45 | bwd_microstep: 285.51 | bwd_inner_microstep: 285.50 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2092 +[2025-05-02 02:16:29,842] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 199.41 | bwd_microstep: 301.78 | bwd_inner_microstep: 301.76 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1936 +[2025-05-02 02:16:30,338] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 194.11 | bwd_microstep: 285.72 | bwd_inner_microstep: 285.71 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 877 +[2025-05-02 02:16:30,581] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.01 | bwd_microstep: 133.39 | bwd_inner_microstep: 133.26 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 02:16:31,054] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 185.57 | bwd_microstep: 270.77 | bwd_inner_microstep: 270.75 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-02 02:16:31,528] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.93 | bwd_microstep: 271.02 | bwd_inner_microstep: 271.00 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 346 +[2025-05-02 02:16:31,749] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 81.44 | bwd_microstep: 124.29 | bwd_inner_microstep: 124.16 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1883 +[2025-05-02 02:16:32,226] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.10 | bwd_microstep: 273.05 | bwd_inner_microstep: 273.03 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 02:16:32,701] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.75 | bwd_microstep: 272.16 | bwd_inner_microstep: 272.14 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 02:16:33,176] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.43 | bwd_microstep: 271.77 | bwd_inner_microstep: 271.75 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1354 +[2025-05-02 02:16:33,538] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.66 | bwd_microstep: 205.96 | bwd_inner_microstep: 205.68 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1089 +[2025-05-02 02:16:33,833] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 114.49 | bwd_microstep: 165.51 | bwd_inner_microstep: 165.23 | bwd_allreduce_microstep: 0.10 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 02:16:34,304] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 185.73 | bwd_microstep: 269.09 | bwd_inner_microstep: 269.07 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 02:16:34,779] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.33 | bwd_microstep: 269.99 | bwd_inner_microstep: 269.98 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.11 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1344 +[2025-05-02 02:16:35,139] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 138.06 | bwd_microstep: 203.09 | bwd_inner_microstep: 202.89 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 02:16:35,716] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.07 | optimizer_gradients: 2.26 | optimizer_step: 16.58 +[2025-05-02 02:16:35,716] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 185.33 | bwd_microstep: 348.73 | bwd_inner_microstep: 270.40 | bwd_allreduce_microstep: 78.20 | step_microstep: 24.67 +[2025-05-02 02:16:35,718] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2649.48 | bwd: 3951.92 | bwd_inner: 3872.57 | bwd_allreduce: 78.59 | step: 25.71 + 18%|█▊ | 1601/8720 [4:01:09<20:45:31, 10.50s/it] {'loss': 0.7995, 'grad_norm': 9.346505165100098, 'learning_rate': 9.394248016893886e-06, 'epoch': 1.84} + 18%|█▊ | 1601/8720 [4:01:09<20:45:31, 10.50s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 02:16:36,196] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.02 | bwd_microstep: 267.95 | bwd_inner_microstep: 267.90 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 435 +[2025-05-02 02:16:36,449] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 84.80 | bwd_microstep: 152.69 | bwd_inner_microstep: 152.53 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1919 +[2025-05-02 02:16:36,933] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.54 | bwd_microstep: 275.66 | bwd_inner_microstep: 275.65 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1923 +[2025-05-02 02:16:37,430] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 194.53 | bwd_microstep: 284.85 | bwd_inner_microstep: 284.84 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1904 +[2025-05-02 02:16:37,912] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.22 | bwd_microstep: 274.29 | bwd_inner_microstep: 274.27 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-02 02:16:38,391] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.96 | bwd_microstep: 273.23 | bwd_inner_microstep: 273.21 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 02:16:38,869] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.78 | bwd_microstep: 272.54 | bwd_inner_microstep: 272.52 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1362 +[2025-05-02 02:16:39,233] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.05 | bwd_microstep: 205.66 | bwd_inner_microstep: 205.60 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 02:16:39,711] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.25 | bwd_microstep: 272.26 | bwd_inner_microstep: 272.24 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 337 +[2025-05-02 02:16:39,973] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 90.71 | bwd_microstep: 153.92 | bwd_inner_microstep: 153.61 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 02:16:40,451] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.22 | bwd_microstep: 271.96 | bwd_inner_microstep: 271.94 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 326 +[2025-05-02 02:16:40,695] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 78.96 | bwd_microstep: 150.36 | bwd_inner_microstep: 150.15 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 02:16:41,171] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.06 | bwd_microstep: 271.84 | bwd_inner_microstep: 271.82 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 02:16:41,646] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.50 | bwd_microstep: 270.60 | bwd_inner_microstep: 270.58 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 831 +[2025-05-02 02:16:41,892] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 92.86 | bwd_microstep: 139.12 | bwd_inner_microstep: 138.99 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 828 +[2025-05-02 02:16:42,246] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.25 | optimizer_step: 16.54 +[2025-05-02 02:16:42,247] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 91.94 | bwd_microstep: 224.35 | bwd_inner_microstep: 158.01 | bwd_allreduce_microstep: 66.25 | step_microstep: 23.75 +[2025-05-02 02:16:42,248] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2464.07 | bwd: 3761.37 | bwd_inner: 3694.03 | bwd_allreduce: 66.64 | step: 24.79 + 18%|█▊ | 1602/8720 [4:01:15<18:24:04, 9.31s/it] {'loss': 0.8005, 'grad_norm': 10.382501602172852, 'learning_rate': 9.393361658904589e-06, 'epoch': 1.84} + 18%|█▊ | 1602/8720 [4:01:15<18:24:04, 9.31s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 02:16:42,725] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.54 | bwd_microstep: 269.72 | bwd_inner_microstep: 269.71 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1899 +[2025-05-02 02:16:43,204] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.52 | bwd_microstep: 274.85 | bwd_inner_microstep: 274.83 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-02 02:16:43,682] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.31 | bwd_microstep: 273.77 | bwd_inner_microstep: 273.76 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 348 +[2025-05-02 02:16:43,918] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 67.84 | bwd_microstep: 154.85 | bwd_inner_microstep: 154.59 | bwd_allreduce_microstep: 0.10 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-02 02:16:44,395] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.33 | bwd_microstep: 273.30 | bwd_inner_microstep: 273.28 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1359 +[2025-05-02 02:16:44,758] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.19 | bwd_microstep: 205.87 | bwd_inner_microstep: 205.72 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 02:16:45,234] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.75 | bwd_microstep: 271.49 | bwd_inner_microstep: 271.47 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 02:16:45,712] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.15 | bwd_microstep: 271.74 | bwd_inner_microstep: 271.72 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 02:16:46,189] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.43 | bwd_microstep: 271.31 | bwd_inner_microstep: 271.29 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 02:16:46,667] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.12 | bwd_microstep: 271.48 | bwd_inner_microstep: 271.46 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 02:16:47,144] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.49 | bwd_microstep: 271.43 | bwd_inner_microstep: 271.41 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 02:16:47,621] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.80 | bwd_microstep: 271.67 | bwd_inner_microstep: 271.65 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 02:16:48,098] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.78 | bwd_microstep: 269.97 | bwd_inner_microstep: 269.95 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 02:16:48,572] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.34 | bwd_microstep: 269.53 | bwd_inner_microstep: 269.51 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 02:16:49,049] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.02 | bwd_microstep: 269.78 | bwd_inner_microstep: 269.76 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.14 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 02:16:49,625] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.07 | optimizer_gradients: 2.19 | optimizer_step: 16.49 +[2025-05-02 02:16:49,626] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.80 | bwd_microstep: 347.00 | bwd_inner_microstep: 270.46 | bwd_allreduce_microstep: 76.48 | step_microstep: 24.42 +[2025-05-02 02:16:49,627] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2829.06 | bwd: 4237.81 | bwd_inner: 4160.65 | bwd_allreduce: 76.74 | step: 25.67 + 18%|█▊ | 1603/8720 [4:01:23<17:15:24, 8.73s/it] {'loss': 0.6282, 'grad_norm': 8.315180778503418, 'learning_rate': 9.392474694791497e-06, 'epoch': 1.84} + 18%|█▊ | 1603/8720 [4:01:23<17:15:24, 8.73s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 02:16:50,109] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.71 | bwd_microstep: 271.17 | bwd_inner_microstep: 271.15 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1925 +[2025-05-02 02:16:50,608] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 194.36 | bwd_microstep: 286.22 | bwd_inner_microstep: 286.20 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 360 +[2025-05-02 02:16:50,815] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 69.71 | bwd_microstep: 123.23 | bwd_inner_microstep: 122.93 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1887 +[2025-05-02 02:16:51,293] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.68 | bwd_microstep: 273.72 | bwd_inner_microstep: 273.70 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 02:16:51,769] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.77 | bwd_microstep: 272.11 | bwd_inner_microstep: 272.10 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 02:16:52,245] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.64 | bwd_microstep: 272.58 | bwd_inner_microstep: 272.57 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 02:16:52,721] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.32 | bwd_microstep: 272.13 | bwd_inner_microstep: 272.11 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 324 +[2025-05-02 02:16:52,935] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 75.62 | bwd_microstep: 124.20 | bwd_inner_microstep: 123.88 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 838 +[2025-05-02 02:16:53,165] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 89.62 | bwd_microstep: 126.14 | bwd_inner_microstep: 125.98 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 02:16:53,641] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.53 | bwd_microstep: 272.15 | bwd_inner_microstep: 272.13 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 843 +[2025-05-02 02:16:53,880] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.40 | bwd_microstep: 131.65 | bwd_inner_microstep: 131.48 | bwd_allreduce_microstep: 0.09 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 02:16:54,355] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.29 | bwd_microstep: 271.87 | bwd_inner_microstep: 271.85 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 02:16:54,830] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.55 | bwd_microstep: 271.96 | bwd_inner_microstep: 271.94 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 02:16:55,307] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.42 | bwd_microstep: 272.53 | bwd_inner_microstep: 272.51 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 02:16:55,784] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.40 | bwd_microstep: 271.71 | bwd_inner_microstep: 271.69 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 02:16:56,349] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.25 | optimizer_step: 16.64 +[2025-05-02 02:16:56,349] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.03 | bwd_microstep: 337.68 | bwd_inner_microstep: 271.13 | bwd_allreduce_microstep: 66.51 | step_microstep: 23.91 +[2025-05-02 02:16:56,351] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2590.76 | bwd: 3851.12 | bwd_inner: 3783.53 | bwd_allreduce: 66.93 | step: 24.78 + 18%|█▊ | 1604/8720 [4:01:30<16:03:50, 8.13s/it] {'loss': 0.5046, 'grad_norm': 8.203904151916504, 'learning_rate': 9.391587124676974e-06, 'epoch': 1.84} + 18%|█▊ | 1604/8720 [4:01:30<16:03:50, 8.13s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 02:16:56,827] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.01 | bwd_microstep: 269.68 | bwd_inner_microstep: 269.67 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1895 +[2025-05-02 02:16:57,307] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.37 | bwd_microstep: 274.70 | bwd_inner_microstep: 274.68 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1896 +[2025-05-02 02:16:57,786] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.58 | bwd_microstep: 274.67 | bwd_inner_microstep: 274.65 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 02:16:58,264] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.08 | bwd_microstep: 273.24 | bwd_inner_microstep: 273.22 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-02 02:16:58,741] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.87 | bwd_microstep: 272.70 | bwd_inner_microstep: 272.68 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 02:16:59,219] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.19 | bwd_microstep: 272.61 | bwd_inner_microstep: 272.59 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1361 +[2025-05-02 02:16:59,582] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.33 | bwd_microstep: 205.77 | bwd_inner_microstep: 205.75 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 02:17:00,057] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.57 | bwd_microstep: 271.51 | bwd_inner_microstep: 271.49 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 02:17:00,532] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.93 | bwd_microstep: 271.60 | bwd_inner_microstep: 271.58 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-02 02:17:01,007] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.59 | bwd_microstep: 272.49 | bwd_inner_microstep: 272.47 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 836 +[2025-05-02 02:17:01,237] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 90.92 | bwd_microstep: 125.52 | bwd_inner_microstep: 125.41 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 02:17:01,710] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.05 | bwd_microstep: 271.26 | bwd_inner_microstep: 271.24 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 02:17:02,184] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.57 | bwd_microstep: 271.54 | bwd_inner_microstep: 271.52 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 02:17:02,659] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.19 | bwd_microstep: 271.27 | bwd_inner_microstep: 271.25 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 02:17:03,133] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.33 | bwd_microstep: 271.25 | bwd_inner_microstep: 271.23 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 02:17:03,695] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.20 | optimizer_step: 16.41 +[2025-05-02 02:17:03,696] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.66 | bwd_microstep: 337.06 | bwd_inner_microstep: 270.60 | bwd_allreduce_microstep: 66.42 | step_microstep: 23.48 +[2025-05-02 02:17:03,697] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2863.96 | bwd: 4206.90 | bwd_inner: 4140.07 | bwd_allreduce: 66.55 | step: 24.22 + 18%|█▊ | 1605/8720 [4:01:37<15:35:55, 7.89s/it] {'loss': 0.5723, 'grad_norm': 15.871417999267578, 'learning_rate': 9.390698948683482e-06, 'epoch': 1.84} + 18%|█▊ | 1605/8720 [4:01:37<15:35:55, 7.89s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 02:17:04,176] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.45 | bwd_microstep: 270.02 | bwd_inner_microstep: 270.00 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 366 +[2025-05-02 02:17:04,392] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 77.52 | bwd_microstep: 124.13 | bwd_inner_microstep: 123.80 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.08 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 899 +[2025-05-02 02:17:04,652] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 101.03 | bwd_microstep: 144.07 | bwd_inner_microstep: 143.87 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.09 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 358 +[2025-05-02 02:17:04,876] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 84.16 | bwd_microstep: 125.99 | bwd_inner_microstep: 125.74 | bwd_allreduce_microstep: 0.10 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1893 +[2025-05-02 02:17:05,356] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.75 | bwd_microstep: 274.39 | bwd_inner_microstep: 274.37 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-02 02:17:05,837] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.91 | bwd_microstep: 273.98 | bwd_inner_microstep: 273.96 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-02 02:17:06,317] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.02 | bwd_microstep: 273.86 | bwd_inner_microstep: 273.84 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.13 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-02 02:17:06,799] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.99 | bwd_microstep: 272.89 | bwd_inner_microstep: 272.87 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1358 +[2025-05-02 02:17:07,164] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 142.01 | bwd_microstep: 205.67 | bwd_inner_microstep: 205.65 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1357 +[2025-05-02 02:17:07,529] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.18 | bwd_microstep: 205.62 | bwd_inner_microstep: 205.60 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 833 +[2025-05-02 02:17:07,765] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.01 | bwd_microstep: 125.14 | bwd_inner_microstep: 125.10 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 832 +[2025-05-02 02:17:08,005] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.84 | bwd_microstep: 129.90 | bwd_inner_microstep: 129.66 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 02:17:08,482] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.53 | bwd_microstep: 271.44 | bwd_inner_microstep: 271.43 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 319 +[2025-05-02 02:17:08,711] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 92.33 | bwd_microstep: 118.01 | bwd_inner_microstep: 117.86 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 02:17:09,188] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.56 | bwd_microstep: 271.72 | bwd_inner_microstep: 271.70 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 02:17:09,767] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.18 | optimizer_step: 16.39 +[2025-05-02 02:17:09,767] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.19 | bwd_microstep: 347.75 | bwd_inner_microstep: 271.04 | bwd_allreduce_microstep: 76.65 | step_microstep: 24.03 +[2025-05-02 02:17:09,769] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2331.12 | bwd: 3434.71 | bwd_inner: 3356.70 | bwd_allreduce: 77.18 | step: 25.37 + 18%|█▊ | 1606/8720 [4:01:43<14:31:05, 7.35s/it] {'loss': 1.0454, 'grad_norm': 10.564047813415527, 'learning_rate': 9.389810166933546e-06, 'epoch': 1.84} + 18%|█▊ | 1606/8720 [4:01:43<14:31:05, 7.35s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 02:17:10,250] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.02 | bwd_microstep: 270.14 | bwd_inner_microstep: 270.12 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1390 +[2025-05-02 02:17:10,619] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.48 | bwd_microstep: 208.58 | bwd_inner_microstep: 208.50 | bwd_allreduce_microstep: 0.04 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 02:17:11,102] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.01 | bwd_microstep: 273.16 | bwd_inner_microstep: 273.14 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-02 02:17:11,583] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.77 | bwd_microstep: 273.89 | bwd_inner_microstep: 273.88 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-02 02:17:12,062] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.93 | bwd_microstep: 273.29 | bwd_inner_microstep: 273.27 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-02 02:17:12,541] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.00 | bwd_microstep: 273.40 | bwd_inner_microstep: 273.39 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 02:17:13,019] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.49 | bwd_microstep: 272.87 | bwd_inner_microstep: 272.85 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.15 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 02:17:13,496] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.03 | bwd_microstep: 272.54 | bwd_inner_microstep: 272.52 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 331 +[2025-05-02 02:17:13,696] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 67.38 | bwd_microstep: 118.90 | bwd_inner_microstep: 118.77 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 02:17:14,171] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.93 | bwd_microstep: 272.95 | bwd_inner_microstep: 272.93 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 02:17:14,647] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.80 | bwd_microstep: 271.99 | bwd_inner_microstep: 271.97 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 832 +[2025-05-02 02:17:14,883] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 91.77 | bwd_microstep: 130.19 | bwd_inner_microstep: 129.98 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 02:17:15,360] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.23 | bwd_microstep: 272.37 | bwd_inner_microstep: 272.36 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 322 +[2025-05-02 02:17:15,571] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 79.51 | bwd_microstep: 118.32 | bwd_inner_microstep: 118.10 | bwd_allreduce_microstep: 0.10 | step_microstep: 0.09 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 833 +[2025-05-02 02:17:15,801] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 90.59 | bwd_microstep: 125.80 | bwd_inner_microstep: 125.78 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 02:17:16,366] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.04 | optimizer_gradients: 2.20 | optimizer_step: 16.39 +[2025-05-02 02:17:16,366] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.56 | bwd_microstep: 338.97 | bwd_inner_microstep: 272.81 | bwd_allreduce_microstep: 66.11 | step_microstep: 23.37 +[2025-05-02 02:17:16,367] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2547.21 | bwd: 3767.47 | bwd_inner: 3700.45 | bwd_allreduce: 66.49 | step: 24.72 + 18%|█▊ | 1607/8720 [4:01:50<14:04:18, 7.12s/it] {'loss': 0.6767, 'grad_norm': 21.762645721435547, 'learning_rate': 9.388920779549792e-06, 'epoch': 1.84} + 18%|█▊ | 1607/8720 [4:01:50<14:04:18, 7.12s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 02:17:16,844] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.17 | bwd_microstep: 270.32 | bwd_inner_microstep: 270.31 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-02 02:17:17,322] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.52 | bwd_microstep: 273.77 | bwd_inner_microstep: 273.75 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1887 +[2025-05-02 02:17:17,802] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.51 | bwd_microstep: 274.14 | bwd_inner_microstep: 274.12 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 02:17:18,280] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.47 | bwd_microstep: 273.57 | bwd_inner_microstep: 273.56 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 02:17:18,757] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.53 | bwd_microstep: 272.55 | bwd_inner_microstep: 272.53 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 02:17:19,234] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.83 | bwd_microstep: 272.21 | bwd_inner_microstep: 272.19 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 02:17:19,711] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.61 | bwd_microstep: 272.54 | bwd_inner_microstep: 272.52 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1096 +[2025-05-02 02:17:20,004] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 117.37 | bwd_microstep: 160.54 | bwd_inner_microstep: 160.52 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 836 +[2025-05-02 02:17:20,234] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 90.02 | bwd_microstep: 125.93 | bwd_inner_microstep: 125.68 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 02:17:20,708] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.23 | bwd_microstep: 272.19 | bwd_inner_microstep: 272.17 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1351 +[2025-05-02 02:17:21,068] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 139.58 | bwd_microstep: 205.62 | bwd_inner_microstep: 205.57 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 02:17:21,543] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.31 | bwd_microstep: 272.22 | bwd_inner_microstep: 272.21 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1342 +[2025-05-02 02:17:21,902] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.47 | bwd_microstep: 204.14 | bwd_inner_microstep: 204.09 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 02:17:22,375] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.84 | bwd_microstep: 270.54 | bwd_inner_microstep: 270.52 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 02:17:22,849] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.16 | bwd_microstep: 270.53 | bwd_inner_microstep: 270.51 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1926 +[2025-05-02 02:17:23,433] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.04 | optimizer_gradients: 2.19 | optimizer_step: 16.36 +[2025-05-02 02:17:23,433] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 193.99 | bwd_microstep: 352.77 | bwd_inner_microstep: 287.02 | bwd_allreduce_microstep: 65.71 | step_microstep: 23.33 +[2025-05-02 02:17:23,435] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2754.34 | bwd: 4043.63 | bwd_inner: 3977.28 | bwd_allreduce: 65.94 | step: 24.15 + 18%|█▊ | 1608/8720 [4:01:57<14:02:13, 7.11s/it] {'loss': 0.499, 'grad_norm': 13.42253589630127, 'learning_rate': 9.388030786654922e-06, 'epoch': 1.84} + 18%|█▊ | 1608/8720 [4:01:57<14:02:13, 7.11s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-02 02:17:23,916] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.42 | bwd_microstep: 273.10 | bwd_inner_microstep: 273.08 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1972 +[2025-05-02 02:17:24,419] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 196.95 | bwd_microstep: 290.44 | bwd_inner_microstep: 290.42 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1970 +[2025-05-02 02:17:24,922] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 197.97 | bwd_microstep: 290.35 | bwd_inner_microstep: 290.33 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-02 02:17:25,398] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.75 | bwd_microstep: 272.79 | bwd_inner_microstep: 272.77 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-02 02:17:25,877] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.28 | bwd_microstep: 273.20 | bwd_inner_microstep: 273.18 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 02:17:26,358] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.19 | bwd_microstep: 273.11 | bwd_inner_microstep: 273.09 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 02:17:26,838] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.61 | bwd_microstep: 271.94 | bwd_inner_microstep: 271.92 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 02:17:27,316] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.44 | bwd_microstep: 271.97 | bwd_inner_microstep: 271.95 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 327 +[2025-05-02 02:17:27,541] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 91.37 | bwd_microstep: 116.45 | bwd_inner_microstep: 116.15 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 02:17:28,018] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.83 | bwd_microstep: 271.88 | bwd_inner_microstep: 271.86 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1349 +[2025-05-02 02:17:28,383] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.22 | bwd_microstep: 205.37 | bwd_inner_microstep: 205.25 | bwd_allreduce_microstep: 0.04 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 02:17:28,865] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.62 | bwd_microstep: 272.51 | bwd_inner_microstep: 272.49 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 325 +[2025-05-02 02:17:29,092] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 88.65 | bwd_microstep: 122.39 | bwd_inner_microstep: 122.23 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1345 +[2025-05-02 02:17:29,455] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.83 | bwd_microstep: 204.96 | bwd_inner_microstep: 204.92 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 02:17:29,934] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.71 | bwd_microstep: 271.48 | bwd_inner_microstep: 271.47 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1086 +[2025-05-02 02:17:30,325] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.15 | optimizer_step: 16.31 +[2025-05-02 02:17:30,326] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 115.18 | bwd_microstep: 236.82 | bwd_inner_microstep: 159.97 | bwd_allreduce_microstep: 76.69 | step_microstep: 24.04 +[2025-05-02 02:17:30,327] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2667.65 | bwd: 3918.86 | bwd_inner: 3841.25 | bwd_allreduce: 76.98 | step: 25.08 + 18%|█▊ | 1609/8720 [4:02:04<13:54:36, 7.04s/it] {'loss': 0.6093, 'grad_norm': 10.227964401245117, 'learning_rate': 9.387140188371723e-06, 'epoch': 1.85} + 18%|█▊ | 1609/8720 [4:02:04<13:54:36, 7.04s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2053 +[2025-05-02 02:17:30,851] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 201.48 | bwd_microstep: 299.83 | bwd_inner_microstep: 299.81 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1104 +[2025-05-02 02:17:31,146] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 117.56 | bwd_microstep: 161.00 | bwd_inner_microstep: 160.89 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 02:17:31,622] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.97 | bwd_microstep: 271.47 | bwd_inner_microstep: 271.46 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 02:17:32,100] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.03 | bwd_microstep: 271.81 | bwd_inner_microstep: 271.79 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 328 +[2025-05-02 02:17:32,337] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.60 | bwd_microstep: 122.79 | bwd_inner_microstep: 122.60 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 02:17:32,815] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.80 | bwd_microstep: 272.56 | bwd_inner_microstep: 272.55 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 02:17:33,295] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.34 | bwd_microstep: 272.94 | bwd_inner_microstep: 272.93 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 324 +[2025-05-02 02:17:33,527] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 87.23 | bwd_microstep: 127.73 | bwd_inner_microstep: 127.39 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 323 +[2025-05-02 02:17:33,746] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 83.98 | bwd_microstep: 119.16 | bwd_inner_microstep: 118.99 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.09 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 323 +[2025-05-02 02:17:33,965] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 87.94 | bwd_microstep: 115.34 | bwd_inner_microstep: 115.19 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 02:17:34,441] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.42 | bwd_microstep: 271.60 | bwd_inner_microstep: 271.58 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 02:17:34,915] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.73 | bwd_microstep: 270.97 | bwd_inner_microstep: 270.96 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 02:17:35,393] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.35 | bwd_microstep: 270.75 | bwd_inner_microstep: 270.74 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2092 +[2025-05-02 02:17:35,918] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 202.92 | bwd_microstep: 304.15 | bwd_inner_microstep: 304.13 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1988 +[2025-05-02 02:17:36,430] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 196.77 | bwd_microstep: 292.76 | bwd_inner_microstep: 292.74 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1408 +[2025-05-02 02:17:36,888] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.04 | optimizer_gradients: 2.14 | optimizer_step: 16.25 +[2025-05-02 02:17:36,889] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 144.18 | bwd_microstep: 276.50 | bwd_inner_microstep: 210.24 | bwd_allreduce_microstep: 66.14 | step_microstep: 23.17 +[2025-05-02 02:17:36,890] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2530.92 | bwd: 3721.47 | bwd_inner: 3654.28 | bwd_allreduce: 66.54 | step: 24.20 + 18%|█▊ | 1610/8720 [4:02:10<13:37:23, 6.90s/it] {'loss': 0.5236, 'grad_norm': 28.993425369262695, 'learning_rate': 9.386248984823063e-06, 'epoch': 1.85} + 18%|█▊ | 1610/8720 [4:02:10<13:37:23, 6.90s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-02 02:17:37,372] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.45 | bwd_microstep: 273.20 | bwd_inner_microstep: 273.18 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1988 +[2025-05-02 02:17:37,877] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 197.86 | bwd_microstep: 292.30 | bwd_inner_microstep: 292.28 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 350 +[2025-05-02 02:17:38,080] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 69.70 | bwd_microstep: 119.97 | bwd_inner_microstep: 119.70 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1888 +[2025-05-02 02:17:38,558] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.71 | bwd_microstep: 274.00 | bwd_inner_microstep: 273.98 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 02:17:39,034] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.99 | bwd_microstep: 272.63 | bwd_inner_microstep: 272.61 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-02 02:17:39,514] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.91 | bwd_microstep: 274.41 | bwd_inner_microstep: 274.39 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.17 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 02:17:39,993] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.48 | bwd_microstep: 273.77 | bwd_inner_microstep: 273.76 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-02 02:17:40,472] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.87 | bwd_microstep: 273.66 | bwd_inner_microstep: 273.65 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 02:17:40,951] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.55 | bwd_microstep: 273.10 | bwd_inner_microstep: 273.08 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 02:17:41,430] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.46 | bwd_microstep: 272.50 | bwd_inner_microstep: 272.49 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 02:17:41,909] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.22 | bwd_microstep: 272.46 | bwd_inner_microstep: 272.44 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 02:17:42,388] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.21 | bwd_microstep: 272.52 | bwd_inner_microstep: 272.50 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 837 +[2025-05-02 02:17:42,629] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.99 | bwd_microstep: 125.75 | bwd_inner_microstep: 125.61 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 02:17:43,108] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.35 | bwd_microstep: 271.91 | bwd_inner_microstep: 271.89 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 02:17:43,591] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.09 | bwd_microstep: 272.85 | bwd_inner_microstep: 272.83 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 02:17:44,184] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.16 | optimizer_step: 16.35 +[2025-05-02 02:17:44,184] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.11 | bwd_microstep: 360.47 | bwd_inner_microstep: 272.91 | bwd_allreduce_microstep: 87.50 | step_microstep: 24.16 +[2025-05-02 02:17:44,186] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2823.61 | bwd: 4175.53 | bwd_inner: 4087.37 | bwd_allreduce: 87.73 | step: 25.14 + 18%|█▊ | 1611/8720 [4:02:17<13:51:29, 7.02s/it] {'loss': 0.6271, 'grad_norm': 5.944077014923096, 'learning_rate': 9.385357176131898e-06, 'epoch': 1.85} + 18%|█▊ | 1611/8720 [4:02:17<13:51:29, 7.02s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 02:17:44,667] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.35 | bwd_microstep: 270.26 | bwd_inner_microstep: 270.24 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1893 +[2025-05-02 02:17:45,149] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.82 | bwd_microstep: 274.67 | bwd_inner_microstep: 274.65 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1892 +[2025-05-02 02:17:45,631] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.11 | bwd_microstep: 274.95 | bwd_inner_microstep: 274.93 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1886 +[2025-05-02 02:17:46,112] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.07 | bwd_microstep: 274.72 | bwd_inner_microstep: 274.70 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-02 02:17:46,593] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.37 | bwd_microstep: 272.70 | bwd_inner_microstep: 272.68 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 02:17:47,073] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.34 | bwd_microstep: 272.05 | bwd_inner_microstep: 272.03 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 02:17:47,555] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.98 | bwd_microstep: 272.30 | bwd_inner_microstep: 272.28 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 02:17:48,035] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.01 | bwd_microstep: 272.21 | bwd_inner_microstep: 272.19 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 02:17:48,516] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.34 | bwd_microstep: 272.38 | bwd_inner_microstep: 272.36 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 02:17:48,998] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.13 | bwd_microstep: 272.68 | bwd_inner_microstep: 272.67 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 02:17:49,476] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.88 | bwd_microstep: 272.32 | bwd_inner_microstep: 272.31 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 02:17:49,955] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.83 | bwd_microstep: 272.53 | bwd_inner_microstep: 272.51 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 02:17:50,432] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.80 | bwd_microstep: 271.47 | bwd_inner_microstep: 271.45 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 02:17:50,910] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.48 | bwd_microstep: 271.08 | bwd_inner_microstep: 271.07 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 02:17:51,389] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.55 | bwd_microstep: 270.72 | bwd_inner_microstep: 270.70 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 02:17:51,971] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.18 | optimizer_step: 16.39 +[2025-05-02 02:17:51,972] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.63 | bwd_microstep: 348.78 | bwd_inner_microstep: 271.44 | bwd_allreduce_microstep: 77.29 | step_microstep: 24.37 +[2025-05-02 02:17:51,973] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 3017.28 | bwd: 4435.83 | bwd_inner: 4358.21 | bwd_allreduce: 77.38 | step: 25.11 + 18%|█▊ | 1612/8720 [4:02:25<14:18:43, 7.25s/it] {'loss': 0.3804, 'grad_norm': 18.235506057739258, 'learning_rate': 9.384464762421264e-06, 'epoch': 1.85} + 18%|█▊ | 1612/8720 [4:02:25<14:18:43, 7.25s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1902 +[2025-05-02 02:17:52,461] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.31 | bwd_microstep: 275.37 | bwd_inner_microstep: 275.35 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1952 +[2025-05-02 02:17:52,962] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.31 | bwd_microstep: 288.62 | bwd_inner_microstep: 288.60 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1931 +[2025-05-02 02:17:53,459] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 194.38 | bwd_microstep: 287.29 | bwd_inner_microstep: 287.27 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-02 02:17:53,936] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.41 | bwd_microstep: 272.96 | bwd_inner_microstep: 272.94 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 02:17:54,412] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.55 | bwd_microstep: 272.28 | bwd_inner_microstep: 272.26 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 02:17:54,888] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.70 | bwd_microstep: 272.55 | bwd_inner_microstep: 272.54 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.13 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 02:17:55,365] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.40 | bwd_microstep: 272.35 | bwd_inner_microstep: 272.33 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 02:17:55,841] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.88 | bwd_microstep: 272.17 | bwd_inner_microstep: 272.15 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1358 +[2025-05-02 02:17:56,203] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.60 | bwd_microstep: 205.79 | bwd_inner_microstep: 205.74 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 02:17:56,678] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.45 | bwd_microstep: 271.57 | bwd_inner_microstep: 271.55 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 835 +[2025-05-02 02:17:56,939] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 99.33 | bwd_microstep: 144.55 | bwd_inner_microstep: 144.21 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1345 +[2025-05-02 02:17:57,301] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.33 | bwd_microstep: 205.25 | bwd_inner_microstep: 205.19 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 02:17:57,777] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.34 | bwd_microstep: 270.85 | bwd_inner_microstep: 270.84 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 02:17:58,253] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.07 | bwd_microstep: 271.20 | bwd_inner_microstep: 271.18 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 02:17:58,728] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.25 | bwd_microstep: 270.62 | bwd_inner_microstep: 270.60 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-02 02:17:59,310] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.21 | optimizer_step: 16.39 +[2025-05-02 02:17:59,311] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.63 | bwd_microstep: 351.53 | bwd_inner_microstep: 274.11 | bwd_allreduce_microstep: 77.29 | step_microstep: 24.36 +[2025-05-02 02:17:59,312] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2835.60 | bwd: 4204.99 | bwd_inner: 4126.97 | bwd_allreduce: 77.52 | step: 25.37 + 18%|█▊ | 1613/8720 [4:02:33<14:21:49, 7.28s/it] {'loss': 0.6655, 'grad_norm': 13.170933723449707, 'learning_rate': 9.38357174381428e-06, 'epoch': 1.85} + 18%|█▊ | 1613/8720 [4:02:33<14:21:49, 7.28s/it]dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1353 +[2025-05-02 02:17:59,682] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.96 | bwd_microstep: 205.53 | bwd_inner_microstep: 205.35 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1931 +[2025-05-02 02:18:00,181] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.31 | bwd_microstep: 287.80 | bwd_inner_microstep: 287.78 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.21 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1912 +[2025-05-02 02:18:00,665] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.76 | bwd_microstep: 276.24 | bwd_inner_microstep: 276.22 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 380 +[2025-05-02 02:18:00,929] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 86.74 | bwd_microstep: 162.41 | bwd_inner_microstep: 162.11 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1889 +[2025-05-02 02:18:01,410] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.97 | bwd_microstep: 274.41 | bwd_inner_microstep: 274.40 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1894 +[2025-05-02 02:18:01,894] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.94 | bwd_microstep: 274.97 | bwd_inner_microstep: 274.96 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 852 +[2025-05-02 02:18:02,152] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.79 | bwd_microstep: 146.77 | bwd_inner_microstep: 146.55 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 02:18:02,630] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.63 | bwd_microstep: 272.92 | bwd_inner_microstep: 272.90 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 02:18:03,111] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.40 | bwd_microstep: 272.99 | bwd_inner_microstep: 272.97 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 02:18:03,589] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.61 | bwd_microstep: 272.63 | bwd_inner_microstep: 272.62 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 02:18:04,065] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.66 | bwd_microstep: 272.83 | bwd_inner_microstep: 272.81 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 02:18:04,542] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.63 | bwd_microstep: 272.38 | bwd_inner_microstep: 272.36 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 02:18:05,019] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.69 | bwd_microstep: 272.39 | bwd_inner_microstep: 272.37 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.07 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 02:18:05,496] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.94 | bwd_microstep: 271.44 | bwd_inner_microstep: 271.42 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 319 +[2025-05-02 02:18:05,751] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 80.19 | bwd_microstep: 158.92 | bwd_inner_microstep: 158.61 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 02:18:06,330] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.24 | optimizer_step: 16.44 +[2025-05-02 02:18:06,330] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.61 | bwd_microstep: 349.07 | bwd_inner_microstep: 271.72 | bwd_allreduce_microstep: 77.24 | step_microstep: 24.33 +[2025-05-02 02:18:06,331] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2670.48 | bwd: 4043.78 | bwd_inner: 3965.39 | bwd_allreduce: 77.65 | step: 25.65 + 19%|█▊ | 1614/8720 [4:02:40<14:12:34, 7.20s/it] {'loss': 0.6707, 'grad_norm': 12.447585105895996, 'learning_rate': 9.382678120434154e-06, 'epoch': 1.85} + 19%|█▊ | 1614/8720 [4:02:40<14:12:34, 7.20s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2000 +[2025-05-02 02:18:06,847] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 199.30 | bwd_microstep: 293.45 | bwd_inner_microstep: 293.43 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2101 +[2025-05-02 02:18:07,372] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 204.25 | bwd_microstep: 305.79 | bwd_inner_microstep: 305.77 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1430 +[2025-05-02 02:18:07,747] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 145.17 | bwd_microstep: 214.36 | bwd_inner_microstep: 214.23 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-02 02:18:08,226] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.19 | bwd_microstep: 274.41 | bwd_inner_microstep: 274.39 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-02 02:18:08,706] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.92 | bwd_microstep: 273.54 | bwd_inner_microstep: 273.52 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-02 02:18:09,185] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.19 | bwd_microstep: 274.72 | bwd_inner_microstep: 274.70 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 333 +[2025-05-02 02:18:09,440] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 85.92 | bwd_microstep: 154.44 | bwd_inner_microstep: 154.22 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 02:18:09,920] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.44 | bwd_microstep: 273.40 | bwd_inner_microstep: 273.38 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.07 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 02:18:10,403] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.25 | bwd_microstep: 273.30 | bwd_inner_microstep: 273.28 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 02:18:10,883] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.56 | bwd_microstep: 272.90 | bwd_inner_microstep: 272.88 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 02:18:11,363] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.66 | bwd_microstep: 273.03 | bwd_inner_microstep: 273.01 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 02:18:11,842] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.62 | bwd_microstep: 272.76 | bwd_inner_microstep: 272.74 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 839 +[2025-05-02 02:18:12,110] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.00 | bwd_microstep: 160.50 | bwd_inner_microstep: 160.35 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 02:18:12,586] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.96 | bwd_microstep: 272.48 | bwd_inner_microstep: 272.46 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 02:18:13,064] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.32 | bwd_microstep: 273.25 | bwd_inner_microstep: 273.24 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 02:18:13,630] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.13 | optimizer_step: 16.39 +[2025-05-02 02:18:13,630] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.21 | bwd_microstep: 338.89 | bwd_inner_microstep: 271.95 | bwd_allreduce_microstep: 66.79 | step_microstep: 23.59 +[2025-05-02 02:18:13,631] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2804.65 | bwd: 4201.30 | bwd_inner: 4133.73 | bwd_allreduce: 67.00 | step: 24.91 + 19%|█▊ | 1615/8720 [4:02:47<14:15:59, 7.23s/it] {'loss': 0.5767, 'grad_norm': 7.687130928039551, 'learning_rate': 9.381783892404168e-06, 'epoch': 1.85} + 19%|█▊ | 1615/8720 [4:02:47<14:15:59, 7.23s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 02:18:14,110] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.73 | bwd_microstep: 270.64 | bwd_inner_microstep: 270.56 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1922 +[2025-05-02 02:18:14,607] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 194.59 | bwd_microstep: 287.39 | bwd_inner_microstep: 287.37 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1907 +[2025-05-02 02:18:15,090] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.13 | bwd_microstep: 276.26 | bwd_inner_microstep: 276.24 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1904 +[2025-05-02 02:18:15,571] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.39 | bwd_microstep: 275.92 | bwd_inner_microstep: 275.90 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 02:18:16,047] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.21 | bwd_microstep: 272.80 | bwd_inner_microstep: 272.79 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 02:18:16,524] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.72 | bwd_microstep: 272.89 | bwd_inner_microstep: 272.87 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 02:18:17,002] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.13 | bwd_microstep: 273.56 | bwd_inner_microstep: 273.54 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 02:18:17,480] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.36 | bwd_microstep: 273.57 | bwd_inner_microstep: 273.56 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 02:18:17,958] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.87 | bwd_microstep: 273.29 | bwd_inner_microstep: 273.27 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 02:18:18,435] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.73 | bwd_microstep: 273.22 | bwd_inner_microstep: 273.20 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 02:18:18,912] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.99 | bwd_microstep: 272.27 | bwd_inner_microstep: 272.26 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 02:18:19,390] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.42 | bwd_microstep: 272.84 | bwd_inner_microstep: 272.82 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 02:18:19,867] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.73 | bwd_microstep: 271.49 | bwd_inner_microstep: 271.47 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 02:18:20,348] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.63 | bwd_microstep: 271.78 | bwd_inner_microstep: 271.76 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1949 +[2025-05-02 02:18:20,851] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.30 | bwd_microstep: 289.77 | bwd_inner_microstep: 289.75 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-02 02:18:21,429] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.04 | optimizer_gradients: 2.11 | optimizer_step: 16.28 +[2025-05-02 02:18:21,430] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.27 | bwd_microstep: 348.99 | bwd_inner_microstep: 274.98 | bwd_allreduce_microstep: 73.97 | step_microstep: 23.26 +[2025-05-02 02:18:21,431] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 3030.90 | bwd: 4476.73 | bwd_inner: 4402.35 | bwd_allreduce: 74.08 | step: 24.31 + 19%|█▊ | 1616/8720 [4:02:55<14:36:08, 7.40s/it] {'loss': 0.5801, 'grad_norm': 9.471400260925293, 'learning_rate': 9.380889059847698e-06, 'epoch': 1.85} + 19%|█▊ | 1616/8720 [4:02:55<14:36:08, 7.40s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 02:18:21,911] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.60 | bwd_microstep: 272.23 | bwd_inner_microstep: 272.21 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 378 +[2025-05-02 02:18:22,158] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 77.06 | bwd_microstep: 156.07 | bwd_inner_microstep: 155.76 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 348 +[2025-05-02 02:18:22,404] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 80.14 | bwd_microstep: 150.57 | bwd_inner_microstep: 150.42 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.09 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1367 +[2025-05-02 02:18:22,770] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.34 | bwd_microstep: 207.47 | bwd_inner_microstep: 207.29 | bwd_allreduce_microstep: 0.09 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 02:18:23,252] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.63 | bwd_microstep: 272.59 | bwd_inner_microstep: 272.57 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 02:18:23,736] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.83 | bwd_microstep: 273.47 | bwd_inner_microstep: 273.46 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 834 +[2025-05-02 02:18:23,996] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 96.65 | bwd_microstep: 144.81 | bwd_inner_microstep: 144.49 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 837 +[2025-05-02 02:18:24,255] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.94 | bwd_microstep: 147.66 | bwd_inner_microstep: 147.50 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 02:18:24,734] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.53 | bwd_microstep: 272.71 | bwd_inner_microstep: 272.70 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 02:18:25,213] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.62 | bwd_microstep: 272.88 | bwd_inner_microstep: 272.86 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 02:18:25,695] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.97 | bwd_microstep: 271.52 | bwd_inner_microstep: 271.50 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 02:18:26,174] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.84 | bwd_microstep: 271.47 | bwd_inner_microstep: 271.46 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 02:18:26,655] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.51 | bwd_microstep: 271.35 | bwd_inner_microstep: 271.33 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 02:18:27,132] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.68 | bwd_microstep: 271.34 | bwd_inner_microstep: 271.32 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 02:18:27,609] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.15 | bwd_microstep: 271.28 | bwd_inner_microstep: 271.26 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 02:18:28,193] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.14 | optimizer_step: 16.34 +[2025-05-02 02:18:28,194] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.91 | bwd_microstep: 354.18 | bwd_inner_microstep: 271.77 | bwd_allreduce_microstep: 82.36 | step_microstep: 24.14 +[2025-05-02 02:18:28,195] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2564.02 | bwd: 3881.71 | bwd_inner: 3798.08 | bwd_allreduce: 82.91 | step: 25.36 + 19%|█▊ | 1617/8720 [4:03:01<14:13:31, 7.21s/it] {'loss': 0.4774, 'grad_norm': 9.144631385803223, 'learning_rate': 9.379993622888196e-06, 'epoch': 1.85} + 19%|█▊ | 1617/8720 [4:03:01<14:13:31, 7.21s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1919 +[2025-05-02 02:18:28,684] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.85 | bwd_microstep: 276.52 | bwd_inner_microstep: 276.50 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 377 +[2025-05-02 02:18:28,943] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 84.20 | bwd_microstep: 158.94 | bwd_inner_microstep: 158.79 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1896 +[2025-05-02 02:18:29,424] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.62 | bwd_microstep: 275.65 | bwd_inner_microstep: 275.63 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1883 +[2025-05-02 02:18:29,903] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.70 | bwd_microstep: 274.49 | bwd_inner_microstep: 274.48 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 02:18:30,381] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.68 | bwd_microstep: 273.03 | bwd_inner_microstep: 273.01 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.09 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 344 +[2025-05-02 02:18:30,614] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 69.58 | bwd_microstep: 150.40 | bwd_inner_microstep: 150.09 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-02 02:18:31,092] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.79 | bwd_microstep: 274.09 | bwd_inner_microstep: 274.07 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1361 +[2025-05-02 02:18:31,455] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.23 | bwd_microstep: 207.04 | bwd_inner_microstep: 206.84 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 02:18:31,933] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.13 | bwd_microstep: 273.92 | bwd_inner_microstep: 273.90 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 326 +[2025-05-02 02:18:32,166] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 69.07 | bwd_microstep: 150.30 | bwd_inner_microstep: 150.16 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 02:18:32,641] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.36 | bwd_microstep: 272.90 | bwd_inner_microstep: 272.89 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 02:18:33,119] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.39 | bwd_microstep: 273.73 | bwd_inner_microstep: 273.71 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1356 +[2025-05-02 02:18:33,482] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.57 | bwd_microstep: 206.67 | bwd_inner_microstep: 206.50 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 02:18:33,959] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.22 | bwd_microstep: 273.26 | bwd_inner_microstep: 273.24 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 02:18:34,435] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.72 | bwd_microstep: 272.68 | bwd_inner_microstep: 272.66 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 02:18:35,002] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.12 | optimizer_step: 16.26 +[2025-05-02 02:18:35,002] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.85 | bwd_microstep: 339.26 | bwd_inner_microstep: 272.14 | bwd_allreduce_microstep: 67.08 | step_microstep: 23.23 +[2025-05-02 02:18:35,004] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2581.69 | bwd: 3952.96 | bwd_inner: 3884.76 | bwd_allreduce: 67.55 | step: 24.26 + 19%|█▊ | 1618/8720 [4:03:08<13:59:04, 7.09s/it] {'loss': 0.7636, 'grad_norm': 7.447063446044922, 'learning_rate': 9.379097581649198e-06, 'epoch': 1.86} + 19%|█▊ | 1618/8720 [4:03:08<13:59:04, 7.09s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1850 +[2025-05-02 02:18:35,481] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.36 | bwd_microstep: 270.04 | bwd_inner_microstep: 270.02 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 1105 +[2025-05-02 02:18:35,764] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 107.14 | bwd_microstep: 161.81 | bwd_inner_microstep: 161.61 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1952 +[2025-05-02 02:18:36,264] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.51 | bwd_microstep: 289.75 | bwd_inner_microstep: 289.73 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1396 +[2025-05-02 02:18:36,630] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.86 | bwd_microstep: 209.63 | bwd_inner_microstep: 209.56 | bwd_allreduce_microstep: 0.03 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-02 02:18:37,108] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.76 | bwd_microstep: 274.05 | bwd_inner_microstep: 274.03 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 02:18:37,586] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.57 | bwd_microstep: 274.18 | bwd_inner_microstep: 274.16 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 02:18:38,064] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.28 | bwd_microstep: 273.62 | bwd_inner_microstep: 273.61 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 334 +[2025-05-02 02:18:38,299] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 70.69 | bwd_microstep: 151.15 | bwd_inner_microstep: 150.88 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.09 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1356 +[2025-05-02 02:18:38,662] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.81 | bwd_microstep: 206.49 | bwd_inner_microstep: 206.24 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1093 +[2025-05-02 02:18:38,956] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 116.21 | bwd_microstep: 161.29 | bwd_inner_microstep: 160.98 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.19 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 327 +[2025-05-02 02:18:39,202] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 80.32 | bwd_microstep: 150.93 | bwd_inner_microstep: 150.77 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1091 +[2025-05-02 02:18:39,495] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 114.58 | bwd_microstep: 161.53 | bwd_inner_microstep: 161.29 | bwd_allreduce_microstep: 0.10 | step_microstep: 0.15 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 02:18:39,973] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.51 | bwd_microstep: 273.12 | bwd_inner_microstep: 273.11 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 842 +[2025-05-02 02:18:40,222] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.92 | bwd_microstep: 140.03 | bwd_inner_microstep: 139.72 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 02:18:40,698] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.52 | bwd_microstep: 272.23 | bwd_inner_microstep: 272.21 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 02:18:41,274] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.05 | optimizer_step: 16.27 +[2025-05-02 02:18:41,274] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.43 | bwd_microstep: 348.93 | bwd_inner_microstep: 271.99 | bwd_allreduce_microstep: 76.87 | step_microstep: 23.93 +[2025-05-02 02:18:41,276] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2380.22 | bwd: 3618.96 | bwd_inner: 3540.22 | bwd_allreduce: 77.62 | step: 25.30 + 19%|█▊ | 1619/8720 [4:03:15<13:30:00, 6.84s/it] {'loss': 0.913, 'grad_norm': 12.389643669128418, 'learning_rate': 9.37820093625433e-06, 'epoch': 1.86} + 19%|█▊ | 1619/8720 [4:03:15<13:30:00, 6.84s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 02:18:41,756] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.43 | bwd_microstep: 270.43 | bwd_inner_microstep: 270.41 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2001 +[2025-05-02 02:18:42,264] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 198.30 | bwd_microstep: 294.71 | bwd_inner_microstep: 294.69 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 993 +[2025-05-02 02:18:42,531] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 101.96 | bwd_microstep: 150.91 | bwd_inner_microstep: 150.78 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1935 +[2025-05-02 02:18:43,030] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.53 | bwd_microstep: 287.87 | bwd_inner_microstep: 287.86 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-02 02:18:43,508] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.87 | bwd_microstep: 273.90 | bwd_inner_microstep: 273.88 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.16 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-02 02:18:43,986] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.72 | bwd_microstep: 274.20 | bwd_inner_microstep: 274.19 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 02:18:44,462] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.84 | bwd_microstep: 272.75 | bwd_inner_microstep: 272.74 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 02:18:44,937] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.77 | bwd_microstep: 272.35 | bwd_inner_microstep: 272.33 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 02:18:45,414] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.25 | bwd_microstep: 273.65 | bwd_inner_microstep: 273.63 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 02:18:45,891] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.34 | bwd_microstep: 273.00 | bwd_inner_microstep: 272.99 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 02:18:46,367] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.65 | bwd_microstep: 272.48 | bwd_inner_microstep: 272.46 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 02:18:46,843] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.07 | bwd_microstep: 272.54 | bwd_inner_microstep: 272.52 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 326 +[2025-05-02 02:18:47,077] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 69.18 | bwd_microstep: 150.73 | bwd_inner_microstep: 150.59 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1351 +[2025-05-02 02:18:47,440] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.76 | bwd_microstep: 206.21 | bwd_inner_microstep: 206.12 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 02:18:47,914] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.52 | bwd_microstep: 271.87 | bwd_inner_microstep: 271.86 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 6, images per sample: 6.0, dynamic token length: 1603 +[2025-05-02 02:18:48,428] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.07 | optimizer_step: 18.30 +[2025-05-02 02:18:48,429] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 163.46 | bwd_microstep: 310.31 | bwd_inner_microstep: 243.93 | bwd_allreduce_microstep: 66.33 | step_microstep: 25.33 +[2025-05-02 02:18:48,430] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2751.39 | bwd: 4127.96 | bwd_inner: 4061.01 | bwd_allreduce: 66.55 | step: 26.31 + 19%|█▊ | 1620/8720 [4:03:22<13:40:50, 6.94s/it] {'loss': 0.4822, 'grad_norm': 4.788912773132324, 'learning_rate': 9.377303686827293e-06, 'epoch': 1.86} + 19%|█▊ | 1620/8720 [4:03:22<13:40:50, 6.94s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1887 +[2025-05-02 02:18:48,914] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.63 | bwd_microstep: 274.86 | bwd_inner_microstep: 274.85 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 435 +[2025-05-02 02:18:49,153] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 75.31 | bwd_microstep: 149.90 | bwd_inner_microstep: 149.63 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1905 +[2025-05-02 02:18:49,635] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.80 | bwd_microstep: 276.80 | bwd_inner_microstep: 276.78 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1897 +[2025-05-02 02:18:50,116] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.87 | bwd_microstep: 275.83 | bwd_inner_microstep: 275.81 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1886 +[2025-05-02 02:18:50,595] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.14 | bwd_microstep: 275.05 | bwd_inner_microstep: 275.03 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1887 +[2025-05-02 02:18:51,075] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.82 | bwd_microstep: 274.69 | bwd_inner_microstep: 274.67 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1886 +[2025-05-02 02:18:51,555] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.45 | bwd_microstep: 274.48 | bwd_inner_microstep: 274.46 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 02:18:52,033] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.58 | bwd_microstep: 273.59 | bwd_inner_microstep: 273.57 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 841 +[2025-05-02 02:18:52,281] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 102.66 | bwd_microstep: 131.90 | bwd_inner_microstep: 131.86 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 842 +[2025-05-02 02:18:52,523] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.90 | bwd_microstep: 132.05 | bwd_inner_microstep: 131.96 | bwd_allreduce_microstep: 0.04 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 02:18:53,001] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.13 | bwd_microstep: 272.15 | bwd_inner_microstep: 272.13 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 02:18:53,479] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.19 | bwd_microstep: 273.12 | bwd_inner_microstep: 273.10 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 02:18:53,959] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.88 | bwd_microstep: 272.43 | bwd_inner_microstep: 272.41 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 02:18:54,437] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.72 | bwd_microstep: 271.09 | bwd_inner_microstep: 271.08 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 02:18:54,917] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.91 | bwd_microstep: 272.69 | bwd_inner_microstep: 272.67 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 02:18:55,506] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.11 | optimizer_step: 17.90 +[2025-05-02 02:18:55,507] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.81 | bwd_microstep: 356.63 | bwd_inner_microstep: 271.67 | bwd_allreduce_microstep: 84.91 | step_microstep: 25.68 +[2025-05-02 02:18:55,508] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2725.47 | bwd: 4057.33 | bwd_inner: 3971.78 | bwd_allreduce: 85.13 | step: 26.60 + 19%|█▊ | 1621/8720 [4:03:29<13:45:48, 6.98s/it] {'loss': 0.8024, 'grad_norm': 7.843785285949707, 'learning_rate': 9.376405833491873e-06, 'epoch': 1.86} + 19%|█▊ | 1621/8720 [4:03:29<13:45:48, 6.98s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 02:18:55,990] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.91 | bwd_microstep: 270.98 | bwd_inner_microstep: 270.96 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 897 +[2025-05-02 02:18:56,267] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 101.34 | bwd_microstep: 158.58 | bwd_inner_microstep: 158.43 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1911 +[2025-05-02 02:18:56,753] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.40 | bwd_microstep: 276.85 | bwd_inner_microstep: 276.84 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 888 +[2025-05-02 02:18:57,012] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.76 | bwd_microstep: 146.87 | bwd_inner_microstep: 146.66 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1888 +[2025-05-02 02:18:57,493] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.92 | bwd_microstep: 274.54 | bwd_inner_microstep: 274.52 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-02 02:18:57,975] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.38 | bwd_microstep: 274.84 | bwd_inner_microstep: 274.83 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-02 02:18:58,456] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.85 | bwd_microstep: 274.88 | bwd_inner_microstep: 274.87 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1883 +[2025-05-02 02:18:58,934] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.39 | bwd_microstep: 274.39 | bwd_inner_microstep: 274.38 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-02 02:18:59,413] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.16 | bwd_microstep: 274.42 | bwd_inner_microstep: 274.41 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-02 02:18:59,891] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.34 | bwd_microstep: 273.90 | bwd_inner_microstep: 273.88 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 02:19:00,368] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.75 | bwd_microstep: 272.55 | bwd_inner_microstep: 272.54 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 02:19:00,846] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.25 | bwd_microstep: 273.05 | bwd_inner_microstep: 273.03 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 02:19:01,325] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.38 | bwd_microstep: 272.47 | bwd_inner_microstep: 272.45 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 319 +[2025-05-02 02:19:01,578] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 91.38 | bwd_microstep: 145.85 | bwd_inner_microstep: 145.69 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 02:19:02,054] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.66 | bwd_microstep: 271.24 | bwd_inner_microstep: 271.22 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 02:19:02,632] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.12 | optimizer_step: 16.30 +[2025-05-02 02:19:02,633] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.76 | bwd_microstep: 349.43 | bwd_inner_microstep: 271.59 | bwd_allreduce_microstep: 77.79 | step_microstep: 24.08 +[2025-05-02 02:19:02,634] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2744.31 | bwd: 4084.95 | bwd_inner: 4006.44 | bwd_allreduce: 78.05 | step: 25.11 + 19%|█▊ | 1622/8720 [4:03:36<13:50:53, 7.02s/it] {'loss': 0.7834, 'grad_norm': 19.376129150390625, 'learning_rate': 9.375507376371944e-06, 'epoch': 1.86} + 19%|█▊ | 1622/8720 [4:03:36<13:50:53, 7.02s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 02:19:03,116] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.87 | bwd_microstep: 270.83 | bwd_inner_microstep: 270.71 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 451 +[2025-05-02 02:19:03,386] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.16 | bwd_microstep: 157.95 | bwd_inner_microstep: 157.71 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1893 +[2025-05-02 02:19:03,870] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.11 | bwd_microstep: 275.20 | bwd_inner_microstep: 275.18 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1360 +[2025-05-02 02:19:04,238] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.16 | bwd_microstep: 207.00 | bwd_inner_microstep: 206.90 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-02 02:19:04,726] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.22 | bwd_microstep: 274.80 | bwd_inner_microstep: 274.79 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 850 +[2025-05-02 02:19:04,997] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 99.51 | bwd_microstep: 149.47 | bwd_inner_microstep: 149.32 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 848 +[2025-05-02 02:19:05,260] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.00 | bwd_microstep: 152.07 | bwd_inner_microstep: 151.95 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-02 02:19:05,741] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.21 | bwd_microstep: 274.76 | bwd_inner_microstep: 274.74 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1356 +[2025-05-02 02:19:06,106] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.95 | bwd_microstep: 206.87 | bwd_inner_microstep: 206.70 | bwd_allreduce_microstep: 0.10 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 02:19:06,586] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.13 | bwd_microstep: 273.23 | bwd_inner_microstep: 273.21 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 02:19:07,068] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.56 | bwd_microstep: 273.68 | bwd_inner_microstep: 273.67 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 02:19:07,551] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.77 | bwd_microstep: 272.75 | bwd_inner_microstep: 272.74 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 02:19:08,030] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.62 | bwd_microstep: 272.47 | bwd_inner_microstep: 272.45 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 02:19:08,509] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.20 | bwd_microstep: 272.60 | bwd_inner_microstep: 272.58 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 02:19:08,988] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.72 | bwd_microstep: 272.49 | bwd_inner_microstep: 272.47 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 02:19:09,556] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.04 | optimizer_gradients: 2.09 | optimizer_step: 16.29 +[2025-05-02 02:19:09,557] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.84 | bwd_microstep: 339.64 | bwd_inner_microstep: 273.57 | bwd_allreduce_microstep: 66.00 | step_microstep: 23.29 +[2025-05-02 02:19:09,558] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2650.66 | bwd: 3945.95 | bwd_inner: 3878.80 | bwd_allreduce: 66.41 | step: 24.57 + 19%|█▊ | 1623/8720 [4:03:43<13:47:10, 6.99s/it] {'loss': 0.3884, 'grad_norm': 7.320853233337402, 'learning_rate': 9.374608315591461e-06, 'epoch': 1.86} + 19%|█▊ | 1623/8720 [4:03:43<13:47:10, 6.99s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 02:19:10,037] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.79 | bwd_microstep: 270.92 | bwd_inner_microstep: 270.90 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 360 +[2025-05-02 02:19:10,270] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 70.24 | bwd_microstep: 149.49 | bwd_inner_microstep: 149.36 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1893 +[2025-05-02 02:19:10,751] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.24 | bwd_microstep: 275.32 | bwd_inner_microstep: 275.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1887 +[2025-05-02 02:19:11,231] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.54 | bwd_microstep: 274.83 | bwd_inner_microstep: 274.81 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-02 02:19:11,711] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.76 | bwd_microstep: 274.63 | bwd_inner_microstep: 274.61 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-02 02:19:12,190] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.04 | bwd_microstep: 273.72 | bwd_inner_microstep: 273.70 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-02 02:19:12,670] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.16 | bwd_microstep: 273.82 | bwd_inner_microstep: 273.81 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 335 +[2025-05-02 02:19:12,910] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 72.87 | bwd_microstep: 153.09 | bwd_inner_microstep: 152.76 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 02:19:13,388] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.28 | bwd_microstep: 273.41 | bwd_inner_microstep: 273.39 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 02:19:13,868] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.17 | bwd_microstep: 273.25 | bwd_inner_microstep: 273.23 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.23 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 02:19:14,352] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.55 | bwd_microstep: 273.01 | bwd_inner_microstep: 272.99 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 02:19:14,834] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.43 | bwd_microstep: 272.79 | bwd_inner_microstep: 272.78 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 02:19:15,318] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.64 | bwd_microstep: 273.06 | bwd_inner_microstep: 273.04 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 02:19:15,798] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.79 | bwd_microstep: 272.97 | bwd_inner_microstep: 272.94 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.18 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1349 +[2025-05-02 02:19:16,164] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.53 | bwd_microstep: 206.30 | bwd_inner_microstep: 206.17 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 02:19:16,748] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.15 | optimizer_step: 16.41 +[2025-05-02 02:19:16,749] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.60 | bwd_microstep: 353.65 | bwd_inner_microstep: 272.02 | bwd_allreduce_microstep: 81.57 | step_microstep: 24.35 +[2025-05-02 02:19:16,750] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2740.29 | bwd: 4144.37 | bwd_inner: 4061.91 | bwd_allreduce: 81.89 | step: 25.82 + 19%|█▊ | 1624/8720 [4:03:50<13:54:12, 7.05s/it] {'loss': 0.6461, 'grad_norm': 6.32720422744751, 'learning_rate': 9.373708651274456e-06, 'epoch': 1.86} + 19%|█▊ | 1624/8720 [4:03:50<13:54:12, 7.05s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1907 +[2025-05-02 02:19:17,240] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.36 | bwd_microstep: 275.85 | bwd_inner_microstep: 275.83 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1889 +[2025-05-02 02:19:17,726] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.54 | bwd_microstep: 275.09 | bwd_inner_microstep: 275.07 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 02:19:18,206] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.32 | bwd_microstep: 273.42 | bwd_inner_microstep: 273.40 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-02 02:19:18,688] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.50 | bwd_microstep: 273.70 | bwd_inner_microstep: 273.69 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 02:19:19,169] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.77 | bwd_microstep: 273.09 | bwd_inner_microstep: 273.07 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 329 +[2025-05-02 02:19:19,429] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 87.58 | bwd_microstep: 155.00 | bwd_inner_microstep: 154.70 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 02:19:19,909] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.31 | bwd_microstep: 273.01 | bwd_inner_microstep: 272.99 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 02:19:20,390] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.35 | bwd_microstep: 273.07 | bwd_inner_microstep: 273.06 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 02:19:20,869] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.45 | bwd_microstep: 272.46 | bwd_inner_microstep: 272.44 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 02:19:21,348] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.12 | bwd_microstep: 271.87 | bwd_inner_microstep: 271.86 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 02:19:21,829] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.14 | bwd_microstep: 271.67 | bwd_inner_microstep: 271.66 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 02:19:22,308] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.14 | bwd_microstep: 271.50 | bwd_inner_microstep: 271.49 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 02:19:22,787] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.05 | bwd_microstep: 271.36 | bwd_inner_microstep: 271.34 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 02:19:23,269] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.95 | bwd_microstep: 271.55 | bwd_inner_microstep: 271.53 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 02:19:23,748] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.96 | bwd_microstep: 271.39 | bwd_inner_microstep: 271.37 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 02:19:24,334] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.13 | optimizer_step: 16.44 +[2025-05-02 02:19:24,335] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.04 | bwd_microstep: 353.81 | bwd_inner_microstep: 272.13 | bwd_allreduce_microstep: 81.63 | step_microstep: 24.40 +[2025-05-02 02:19:24,336] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2917.19 | bwd: 4327.88 | bwd_inner: 4245.68 | bwd_allreduce: 81.81 | step: 25.48 + 19%|█▊ | 1625/8720 [4:03:58<14:12:58, 7.21s/it] {'loss': 0.6664, 'grad_norm': 14.7278470993042, 'learning_rate': 9.372808383545058e-06, 'epoch': 1.86} + 19%|█▊ | 1625/8720 [4:03:58<14:12:58, 7.21s/it]dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 828 +[2025-05-02 02:19:24,607] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.13 | bwd_microstep: 153.96 | bwd_inner_microstep: 153.63 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1894 +[2025-05-02 02:19:25,088] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.61 | bwd_microstep: 274.76 | bwd_inner_microstep: 274.74 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-02 02:19:25,568] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.75 | bwd_microstep: 273.53 | bwd_inner_microstep: 273.51 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 02:19:26,049] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.26 | bwd_microstep: 272.84 | bwd_inner_microstep: 272.82 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 02:19:26,531] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.22 | bwd_microstep: 272.97 | bwd_inner_microstep: 272.96 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 02:19:27,011] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.28 | bwd_microstep: 273.43 | bwd_inner_microstep: 273.41 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 02:19:27,489] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.23 | bwd_microstep: 272.81 | bwd_inner_microstep: 272.79 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 02:19:27,967] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.97 | bwd_microstep: 272.20 | bwd_inner_microstep: 272.18 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 02:19:28,445] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.85 | bwd_microstep: 272.47 | bwd_inner_microstep: 272.45 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 02:19:28,922] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.06 | bwd_microstep: 272.55 | bwd_inner_microstep: 272.54 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 02:19:29,399] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.39 | bwd_microstep: 272.51 | bwd_inner_microstep: 272.50 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 02:19:29,879] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.70 | bwd_microstep: 272.38 | bwd_inner_microstep: 272.36 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 02:19:30,357] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.91 | bwd_microstep: 271.43 | bwd_inner_microstep: 271.42 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 830 +[2025-05-02 02:19:30,620] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.07 | bwd_microstep: 150.91 | bwd_inner_microstep: 150.76 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.11 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 828 +[2025-05-02 02:19:30,892] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.28 | bwd_microstep: 160.19 | bwd_inner_microstep: 160.03 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1896 +[2025-05-02 02:19:31,475] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.15 | optimizer_step: 16.40 +[2025-05-02 02:19:31,476] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.02 | bwd_microstep: 352.95 | bwd_inner_microstep: 276.07 | bwd_allreduce_microstep: 76.83 | step_microstep: 24.39 +[2025-05-02 02:19:31,477] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2732.37 | bwd: 4091.96 | bwd_inner: 4014.28 | bwd_allreduce: 77.14 | step: 25.45 + 19%|█▊ | 1626/8720 [4:04:05<14:10:17, 7.19s/it] {'loss': 0.7633, 'grad_norm': 11.682133674621582, 'learning_rate': 9.371907512527465e-06, 'epoch': 1.86} + 19%|█▊ | 1626/8720 [4:04:05<14:10:17, 7.19s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 02:19:31,962] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.68 | bwd_microstep: 272.32 | bwd_inner_microstep: 272.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 348 +[2025-05-02 02:19:32,202] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 70.04 | bwd_microstep: 156.37 | bwd_inner_microstep: 156.06 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1897 +[2025-05-02 02:19:32,684] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.87 | bwd_microstep: 275.32 | bwd_inner_microstep: 275.31 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-02 02:19:33,164] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.73 | bwd_microstep: 273.38 | bwd_inner_microstep: 273.36 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 329 +[2025-05-02 02:19:33,432] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.55 | bwd_microstep: 154.49 | bwd_inner_microstep: 154.16 | bwd_allreduce_microstep: 0.14 | step_microstep: 0.10 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1110 +[2025-05-02 02:19:33,730] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 118.15 | bwd_microstep: 162.68 | bwd_inner_microstep: 162.37 | bwd_allreduce_microstep: 0.14 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 02:19:34,209] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.95 | bwd_microstep: 273.10 | bwd_inner_microstep: 273.08 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 02:19:34,689] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.45 | bwd_microstep: 273.14 | bwd_inner_microstep: 273.12 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 02:19:35,165] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.98 | bwd_microstep: 272.56 | bwd_inner_microstep: 272.54 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 839 +[2025-05-02 02:19:35,417] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 91.65 | bwd_microstep: 144.98 | bwd_inner_microstep: 144.88 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 02:19:35,895] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.04 | bwd_microstep: 272.75 | bwd_inner_microstep: 272.73 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 02:19:36,372] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.08 | bwd_microstep: 272.61 | bwd_inner_microstep: 272.60 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 02:19:36,850] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.71 | bwd_microstep: 272.67 | bwd_inner_microstep: 272.66 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 02:19:37,329] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.41 | bwd_microstep: 272.57 | bwd_inner_microstep: 272.55 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 02:19:37,809] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.02 | bwd_microstep: 272.49 | bwd_inner_microstep: 272.47 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 833 +[2025-05-02 02:19:38,193] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.23 | optimizer_step: 16.69 +[2025-05-02 02:19:38,194] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.35 | bwd_microstep: 248.10 | bwd_inner_microstep: 169.52 | bwd_allreduce_microstep: 78.47 | step_microstep: 24.75 +[2025-05-02 02:19:38,195] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2544.33 | bwd: 3869.64 | bwd_inner: 3789.92 | bwd_allreduce: 78.95 | step: 26.09 + 19%|█▊ | 1627/8720 [4:04:11<13:53:21, 7.05s/it] {'loss': 0.7219, 'grad_norm': 8.009764671325684, 'learning_rate': 9.371006038345966e-06, 'epoch': 1.87} + 19%|█▊ | 1627/8720 [4:04:11<13:53:21, 7.05s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 02:19:38,677] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.85 | bwd_microstep: 270.62 | bwd_inner_microstep: 270.60 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1903 +[2025-05-02 02:19:39,163] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.43 | bwd_microstep: 275.89 | bwd_inner_microstep: 275.87 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-02 02:19:39,645] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.21 | bwd_microstep: 273.57 | bwd_inner_microstep: 273.55 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1887 +[2025-05-02 02:19:40,126] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.94 | bwd_microstep: 274.57 | bwd_inner_microstep: 274.56 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 02:19:40,607] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.59 | bwd_microstep: 273.16 | bwd_inner_microstep: 273.15 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.25 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-02 02:19:41,090] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.10 | bwd_microstep: 273.69 | bwd_inner_microstep: 273.67 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-02 02:19:41,571] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.96 | bwd_microstep: 273.39 | bwd_inner_microstep: 273.38 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 329 +[2025-05-02 02:19:41,815] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 75.65 | bwd_microstep: 152.73 | bwd_inner_microstep: 152.60 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 02:19:42,291] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.58 | bwd_microstep: 272.88 | bwd_inner_microstep: 272.86 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 02:19:42,770] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.38 | bwd_microstep: 273.82 | bwd_inner_microstep: 273.81 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 02:19:43,247] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.40 | bwd_microstep: 272.77 | bwd_inner_microstep: 272.75 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 322 +[2025-05-02 02:19:43,495] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 85.91 | bwd_microstep: 147.56 | bwd_inner_microstep: 147.44 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.08 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1343 +[2025-05-02 02:19:43,854] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.47 | bwd_microstep: 204.70 | bwd_inner_microstep: 204.52 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 02:19:44,331] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.28 | bwd_microstep: 272.34 | bwd_inner_microstep: 272.32 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 02:19:44,805] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.88 | bwd_microstep: 271.51 | bwd_inner_microstep: 271.49 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 02:19:45,369] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.06 | optimizer_step: 16.28 +[2025-05-02 02:19:45,370] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.64 | bwd_microstep: 337.90 | bwd_inner_microstep: 271.59 | bwd_allreduce_microstep: 66.27 | step_microstep: 23.23 +[2025-05-02 02:19:45,371] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2752.95 | bwd: 4121.16 | bwd_inner: 4054.21 | bwd_allreduce: 66.57 | step: 24.37 + 19%|█▊ | 1628/8720 [4:04:19<13:57:38, 7.09s/it] {'loss': 0.4131, 'grad_norm': 13.974860191345215, 'learning_rate': 9.370103961124933e-06, 'epoch': 1.87} + 19%|█▊ | 1628/8720 [4:04:19<13:57:38, 7.09s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1979 +[2025-05-02 02:19:45,881] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 199.32 | bwd_microstep: 291.42 | bwd_inner_microstep: 291.40 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2052 +[2025-05-02 02:19:46,401] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 203.14 | bwd_microstep: 302.02 | bwd_inner_microstep: 302.00 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1897 +[2025-05-02 02:19:46,881] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.58 | bwd_microstep: 275.26 | bwd_inner_microstep: 275.25 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-02 02:19:47,360] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.21 | bwd_microstep: 274.17 | bwd_inner_microstep: 274.16 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 351 +[2025-05-02 02:19:47,608] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 72.77 | bwd_microstep: 162.03 | bwd_inner_microstep: 161.78 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-02 02:19:48,086] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.57 | bwd_microstep: 274.78 | bwd_inner_microstep: 274.76 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 860 +[2025-05-02 02:19:48,329] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.25 | bwd_microstep: 134.28 | bwd_inner_microstep: 134.04 | bwd_allreduce_microstep: 0.10 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-02 02:19:48,806] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.36 | bwd_microstep: 273.78 | bwd_inner_microstep: 273.76 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 02:19:49,285] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.46 | bwd_microstep: 274.04 | bwd_inner_microstep: 274.03 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 02:19:49,764] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.87 | bwd_microstep: 272.86 | bwd_inner_microstep: 272.84 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 02:19:50,242] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.38 | bwd_microstep: 273.43 | bwd_inner_microstep: 273.41 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 02:19:50,722] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.34 | bwd_microstep: 273.04 | bwd_inner_microstep: 273.03 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.17 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 02:19:51,200] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.60 | bwd_microstep: 272.27 | bwd_inner_microstep: 272.25 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 02:19:51,678] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.60 | bwd_microstep: 272.45 | bwd_inner_microstep: 272.43 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 02:19:52,157] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.88 | bwd_microstep: 273.14 | bwd_inner_microstep: 273.13 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 02:19:52,740] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.13 | optimizer_step: 16.23 +[2025-05-02 02:19:52,741] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.31 | bwd_microstep: 352.92 | bwd_inner_microstep: 271.83 | bwd_allreduce_microstep: 81.04 | step_microstep: 23.83 +[2025-05-02 02:19:52,742] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2830.33 | bwd: 4251.93 | bwd_inner: 4170.21 | bwd_allreduce: 81.28 | step: 24.87 + 19%|█▊ | 1629/8720 [4:04:26<14:07:40, 7.17s/it] {'loss': 0.8581, 'grad_norm': 4.6645379066467285, 'learning_rate': 9.369201280988819e-06, 'epoch': 1.87} + 19%|█▊ | 1629/8720 [4:04:26<14:07:40, 7.17s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 02:19:53,224] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.16 | bwd_microstep: 270.51 | bwd_inner_microstep: 270.49 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1894 +[2025-05-02 02:19:53,707] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.52 | bwd_microstep: 275.56 | bwd_inner_microstep: 275.55 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 347 +[2025-05-02 02:19:53,973] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 99.23 | bwd_microstep: 151.42 | bwd_inner_microstep: 151.09 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 844 +[2025-05-02 02:19:54,228] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.23 | bwd_microstep: 144.99 | bwd_inner_microstep: 144.83 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1098 +[2025-05-02 02:19:54,523] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 117.29 | bwd_microstep: 161.07 | bwd_inner_microstep: 160.90 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 330 +[2025-05-02 02:19:54,777] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 82.46 | bwd_microstep: 155.57 | bwd_inner_microstep: 155.42 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 323 +[2025-05-02 02:19:55,031] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 89.04 | bwd_microstep: 149.46 | bwd_inner_microstep: 149.13 | bwd_allreduce_microstep: 0.14 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 02:19:55,512] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.00 | bwd_microstep: 273.26 | bwd_inner_microstep: 273.25 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 02:19:55,992] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.67 | bwd_microstep: 272.91 | bwd_inner_microstep: 272.89 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1348 +[2025-05-02 02:19:56,357] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.51 | bwd_microstep: 205.94 | bwd_inner_microstep: 205.85 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 02:19:56,837] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.89 | bwd_microstep: 272.35 | bwd_inner_microstep: 272.33 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 320 +[2025-05-02 02:19:57,095] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 89.45 | bwd_microstep: 150.20 | bwd_inner_microstep: 150.05 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 02:19:57,572] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.93 | bwd_microstep: 271.14 | bwd_inner_microstep: 271.12 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 02:19:58,052] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.40 | bwd_microstep: 271.20 | bwd_inner_microstep: 271.18 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 02:19:58,531] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.27 | bwd_microstep: 271.21 | bwd_inner_microstep: 271.19 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 02:19:59,108] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.04 | optimizer_gradients: 2.10 | optimizer_step: 16.23 +[2025-05-02 02:19:59,108] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.70 | bwd_microstep: 348.01 | bwd_inner_microstep: 271.63 | bwd_allreduce_microstep: 76.34 | step_microstep: 23.41 +[2025-05-02 02:19:59,110] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2409.36 | bwd: 3644.92 | bwd_inner: 3567.15 | bwd_allreduce: 76.93 | step: 24.56 + 19%|█▊ | 1630/8720 [4:04:32<13:38:58, 6.93s/it] {'loss': 0.6125, 'grad_norm': 14.544693946838379, 'learning_rate': 9.36829799806216e-06, 'epoch': 1.87} + 19%|█▊ | 1630/8720 [4:04:32<13:38:58, 6.93s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 02:19:59,588] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.04 | bwd_microstep: 270.38 | bwd_inner_microstep: 270.36 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1911 +[2025-05-02 02:20:00,070] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.69 | bwd_microstep: 276.53 | bwd_inner_microstep: 276.51 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1897 +[2025-05-02 02:20:00,552] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.50 | bwd_microstep: 275.47 | bwd_inner_microstep: 275.45 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-02 02:20:01,031] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.81 | bwd_microstep: 273.93 | bwd_inner_microstep: 273.91 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 02:20:01,509] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.58 | bwd_microstep: 273.43 | bwd_inner_microstep: 273.42 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-02 02:20:01,988] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.66 | bwd_microstep: 273.99 | bwd_inner_microstep: 273.97 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 02:20:02,466] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.18 | bwd_microstep: 272.93 | bwd_inner_microstep: 272.92 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 02:20:02,945] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.24 | bwd_microstep: 272.92 | bwd_inner_microstep: 272.90 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1349 +[2025-05-02 02:20:03,312] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.71 | bwd_microstep: 206.15 | bwd_inner_microstep: 205.97 | bwd_allreduce_microstep: 0.10 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 02:20:03,790] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.16 | bwd_microstep: 272.83 | bwd_inner_microstep: 272.81 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 02:20:04,269] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.27 | bwd_microstep: 273.02 | bwd_inner_microstep: 273.00 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 02:20:04,748] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.31 | bwd_microstep: 272.67 | bwd_inner_microstep: 272.66 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 02:20:05,228] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.38 | bwd_microstep: 271.47 | bwd_inner_microstep: 271.45 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 02:20:05,707] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.08 | bwd_microstep: 271.32 | bwd_inner_microstep: 271.31 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 02:20:06,185] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.91 | bwd_microstep: 271.42 | bwd_inner_microstep: 271.40 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 02:20:06,765] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.11 | optimizer_step: 16.27 +[2025-05-02 02:20:06,766] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.59 | bwd_microstep: 350.04 | bwd_inner_microstep: 271.94 | bwd_allreduce_microstep: 78.01 | step_microstep: 23.86 +[2025-05-02 02:20:06,767] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2978.78 | bwd: 4378.52 | bwd_inner: 4299.97 | bwd_allreduce: 78.18 | step: 24.98 + 19%|█▊ | 1631/8720 [4:04:40<14:04:39, 7.15s/it] {'loss': 0.7527, 'grad_norm': 8.092804908752441, 'learning_rate': 9.367394112469578e-06, 'epoch': 1.87} + 19%|█▊ | 1631/8720 [4:04:40<14:04:39, 7.15s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1850 +[2025-05-02 02:20:07,248] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.24 | bwd_microstep: 270.84 | bwd_inner_microstep: 270.82 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1900 +[2025-05-02 02:20:07,731] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.35 | bwd_microstep: 275.57 | bwd_inner_microstep: 275.55 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.16 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 359 +[2025-05-02 02:20:07,979] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 72.47 | bwd_microstep: 161.61 | bwd_inner_microstep: 161.28 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1131 +[2025-05-02 02:20:08,273] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 115.39 | bwd_microstep: 164.16 | bwd_inner_microstep: 163.94 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 02:20:08,750] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.30 | bwd_microstep: 272.79 | bwd_inner_microstep: 272.78 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1365 +[2025-05-02 02:20:09,114] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.69 | bwd_microstep: 207.70 | bwd_inner_microstep: 207.44 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 02:20:09,591] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.63 | bwd_microstep: 274.06 | bwd_inner_microstep: 274.04 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 02:20:10,071] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.81 | bwd_microstep: 272.99 | bwd_inner_microstep: 272.97 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 02:20:10,549] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.46 | bwd_microstep: 272.65 | bwd_inner_microstep: 272.63 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 835 +[2025-05-02 02:20:10,808] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.71 | bwd_microstep: 147.82 | bwd_inner_microstep: 147.67 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1355 +[2025-05-02 02:20:11,173] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.51 | bwd_microstep: 206.41 | bwd_inner_microstep: 206.37 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 02:20:11,654] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.92 | bwd_microstep: 272.36 | bwd_inner_microstep: 272.34 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 02:20:12,137] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.13 | bwd_microstep: 272.44 | bwd_inner_microstep: 272.42 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 02:20:12,615] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.79 | bwd_microstep: 271.18 | bwd_inner_microstep: 271.16 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 02:20:13,097] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.52 | bwd_microstep: 272.22 | bwd_inner_microstep: 272.20 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 02:20:13,676] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.11 | optimizer_step: 16.25 +[2025-05-02 02:20:13,677] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.05 | bwd_microstep: 348.76 | bwd_inner_microstep: 271.84 | bwd_allreduce_microstep: 76.85 | step_microstep: 23.84 +[2025-05-02 02:20:13,678] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2637.62 | bwd: 3963.67 | bwd_inner: 3885.63 | bwd_allreduce: 77.28 | step: 25.42 + 19%|█▊ | 1632/8720 [4:04:47<13:56:06, 7.08s/it] {'loss': 0.9435, 'grad_norm': 16.536928176879883, 'learning_rate': 9.366489624335774e-06, 'epoch': 1.87} + 19%|█▊ | 1632/8720 [4:04:47<13:56:06, 7.08s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 02:20:14,160] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.59 | bwd_microstep: 270.69 | bwd_inner_microstep: 270.67 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1983 +[2025-05-02 02:20:14,669] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 198.84 | bwd_microstep: 292.36 | bwd_inner_microstep: 292.34 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 02:20:15,149] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.81 | bwd_microstep: 273.54 | bwd_inner_microstep: 273.52 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-02 02:20:15,631] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.82 | bwd_microstep: 273.53 | bwd_inner_microstep: 273.51 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 02:20:16,113] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.38 | bwd_microstep: 273.04 | bwd_inner_microstep: 272.96 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.30 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 02:20:16,594] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.03 | bwd_microstep: 272.86 | bwd_inner_microstep: 272.84 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 02:20:17,076] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.15 | bwd_microstep: 273.38 | bwd_inner_microstep: 273.36 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 02:20:17,555] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.39 | bwd_microstep: 272.80 | bwd_inner_microstep: 272.78 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 02:20:18,034] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.28 | bwd_microstep: 272.65 | bwd_inner_microstep: 272.64 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 02:20:18,513] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.55 | bwd_microstep: 272.56 | bwd_inner_microstep: 272.54 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 02:20:18,992] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.15 | bwd_microstep: 272.21 | bwd_inner_microstep: 272.20 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 02:20:19,472] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.77 | bwd_microstep: 270.87 | bwd_inner_microstep: 270.86 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 02:20:19,952] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.75 | bwd_microstep: 271.14 | bwd_inner_microstep: 271.12 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 02:20:20,431] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.67 | bwd_microstep: 271.02 | bwd_inner_microstep: 271.00 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 02:20:20,908] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.64 | bwd_microstep: 271.10 | bwd_inner_microstep: 271.08 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 829 +[2025-05-02 02:20:21,266] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.12 | optimizer_step: 16.23 +[2025-05-02 02:20:21,267] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 108.39 | bwd_microstep: 207.29 | bwd_inner_microstep: 130.23 | bwd_allreduce_microstep: 76.90 | step_microstep: 23.89 +[2025-05-02 02:20:21,268] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2941.77 | bwd: 4311.13 | bwd_inner: 4233.72 | bwd_allreduce: 76.95 | step: 25.08 + 19%|█▊ | 1633/8720 [4:04:55<14:14:08, 7.23s/it] {'loss': 0.5228, 'grad_norm': 7.362147331237793, 'learning_rate': 9.365584533785535e-06, 'epoch': 1.87} + 19%|█▊ | 1633/8720 [4:04:55<14:14:08, 7.23s/it]dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1387 +[2025-05-02 02:20:21,640] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.37 | bwd_microstep: 208.49 | bwd_inner_microstep: 208.28 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1955 +[2025-05-02 02:20:22,147] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 197.96 | bwd_microstep: 289.78 | bwd_inner_microstep: 289.77 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.21 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-02 02:20:22,627] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.12 | bwd_microstep: 273.54 | bwd_inner_microstep: 273.52 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1886 +[2025-05-02 02:20:23,110] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.68 | bwd_microstep: 274.87 | bwd_inner_microstep: 274.85 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 02:20:23,594] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.68 | bwd_microstep: 272.68 | bwd_inner_microstep: 272.66 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 02:20:24,078] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.78 | bwd_microstep: 273.82 | bwd_inner_microstep: 273.81 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 02:20:24,559] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.24 | bwd_microstep: 273.15 | bwd_inner_microstep: 273.13 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 02:20:25,040] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.28 | bwd_microstep: 273.02 | bwd_inner_microstep: 273.00 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 844 +[2025-05-02 02:20:25,290] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 98.14 | bwd_microstep: 131.91 | bwd_inner_microstep: 131.79 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 330 +[2025-05-02 02:20:25,518] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 84.38 | bwd_microstep: 127.26 | bwd_inner_microstep: 127.11 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 840 +[2025-05-02 02:20:25,755] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.55 | bwd_microstep: 126.73 | bwd_inner_microstep: 126.47 | bwd_allreduce_microstep: 0.14 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 02:20:26,234] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.12 | bwd_microstep: 272.59 | bwd_inner_microstep: 272.57 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 02:20:26,712] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.41 | bwd_microstep: 272.35 | bwd_inner_microstep: 272.34 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 02:20:27,189] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.72 | bwd_microstep: 272.12 | bwd_inner_microstep: 272.11 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 02:20:27,664] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.25 | bwd_microstep: 271.16 | bwd_inner_microstep: 271.14 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 02:20:28,247] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.64 | optimizer_step: 16.26 +[2025-05-02 02:20:28,247] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.30 | bwd_microstep: 353.02 | bwd_inner_microstep: 271.69 | bwd_allreduce_microstep: 81.27 | step_microstep: 24.44 +[2025-05-02 02:20:28,249] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2690.59 | bwd: 3966.60 | bwd_inner: 3884.27 | bwd_allreduce: 81.74 | step: 25.70 + 19%|█▊ | 1634/8720 [4:05:01<14:05:08, 7.16s/it] {'loss': 1.0859, 'grad_norm': 11.527323722839355, 'learning_rate': 9.364678840943733e-06, 'epoch': 1.87} + 19%|█▊ | 1634/8720 [4:05:01<14:05:08, 7.16s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 02:20:28,730] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.86 | bwd_microstep: 270.66 | bwd_inner_microstep: 270.64 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2016 +[2025-05-02 02:20:29,240] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 197.88 | bwd_microstep: 295.56 | bwd_inner_microstep: 295.54 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1897 +[2025-05-02 02:20:29,724] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.62 | bwd_microstep: 275.00 | bwd_inner_microstep: 274.98 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1890 +[2025-05-02 02:20:30,207] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.87 | bwd_microstep: 274.29 | bwd_inner_microstep: 274.27 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 858 +[2025-05-02 02:20:30,457] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 98.33 | bwd_microstep: 133.03 | bwd_inner_microstep: 132.93 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 02:20:30,936] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.25 | bwd_microstep: 272.90 | bwd_inner_microstep: 272.88 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-02 02:20:31,416] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.45 | bwd_microstep: 273.34 | bwd_inner_microstep: 273.33 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-02 02:20:31,898] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.21 | bwd_microstep: 273.53 | bwd_inner_microstep: 273.51 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 02:20:32,379] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.65 | bwd_microstep: 272.67 | bwd_inner_microstep: 272.66 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1345 +[2025-05-02 02:20:32,744] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.52 | bwd_microstep: 205.31 | bwd_inner_microstep: 205.29 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 02:20:33,223] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.00 | bwd_microstep: 271.91 | bwd_inner_microstep: 271.89 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 02:20:33,704] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.50 | bwd_microstep: 271.84 | bwd_inner_microstep: 271.82 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.05 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1345 +[2025-05-02 02:20:34,070] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.49 | bwd_microstep: 205.15 | bwd_inner_microstep: 205.11 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 02:20:34,548] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.82 | bwd_microstep: 270.85 | bwd_inner_microstep: 270.83 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 02:20:35,027] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.35 | bwd_microstep: 270.66 | bwd_inner_microstep: 270.64 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 02:20:35,605] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.16 | optimizer_step: 16.49 +[2025-05-02 02:20:35,606] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.97 | bwd_microstep: 348.53 | bwd_inner_microstep: 271.19 | bwd_allreduce_microstep: 77.28 | step_microstep: 24.48 +[2025-05-02 02:20:35,607] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2836.34 | bwd: 4185.29 | bwd_inner: 4107.53 | bwd_allreduce: 77.43 | step: 25.47 + 19%|█▉ | 1635/8720 [4:05:09<14:12:12, 7.22s/it] {'loss': 0.6859, 'grad_norm': 11.6160888671875, 'learning_rate': 9.363772545935317e-06, 'epoch': 1.87} + 19%|█▉ | 1635/8720 [4:05:09<14:12:12, 7.22s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1850 +[2025-05-02 02:20:36,089] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.07 | bwd_microstep: 270.11 | bwd_inner_microstep: 270.09 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1968 +[2025-05-02 02:20:36,596] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 197.82 | bwd_microstep: 291.23 | bwd_inner_microstep: 291.21 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1922 +[2025-05-02 02:20:37,095] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.74 | bwd_microstep: 287.01 | bwd_inner_microstep: 286.99 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1902 +[2025-05-02 02:20:37,576] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.88 | bwd_microstep: 275.83 | bwd_inner_microstep: 275.82 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-02 02:20:38,055] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.67 | bwd_microstep: 274.49 | bwd_inner_microstep: 274.48 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 847 +[2025-05-02 02:20:38,324] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.97 | bwd_microstep: 160.45 | bwd_inner_microstep: 160.14 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 02:20:38,801] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.64 | bwd_microstep: 272.77 | bwd_inner_microstep: 272.75 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-02 02:20:39,282] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.29 | bwd_microstep: 273.74 | bwd_inner_microstep: 273.72 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 02:20:39,761] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.43 | bwd_microstep: 272.79 | bwd_inner_microstep: 272.77 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 02:20:40,242] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.65 | bwd_microstep: 272.87 | bwd_inner_microstep: 272.85 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 02:20:40,723] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.24 | bwd_microstep: 272.03 | bwd_inner_microstep: 272.02 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 02:20:41,208] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.18 | bwd_microstep: 273.27 | bwd_inner_microstep: 273.25 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 02:20:41,692] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.14 | bwd_microstep: 273.08 | bwd_inner_microstep: 273.06 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 835 +[2025-05-02 02:20:41,944] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 100.35 | bwd_microstep: 129.72 | bwd_inner_microstep: 129.47 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 02:20:42,423] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.05 | bwd_microstep: 272.48 | bwd_inner_microstep: 272.46 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 02:20:43,005] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.15 | optimizer_step: 16.37 +[2025-05-02 02:20:43,006] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.97 | bwd_microstep: 347.97 | bwd_inner_microstep: 271.53 | bwd_allreduce_microstep: 76.38 | step_microstep: 24.18 +[2025-05-02 02:20:43,007] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2850.71 | bwd: 4219.88 | bwd_inner: 4142.67 | bwd_allreduce: 76.72 | step: 25.27 + 19%|█▉ | 1636/8720 [4:05:16<14:18:34, 7.27s/it] {'loss': 0.8141, 'grad_norm': 17.288436889648438, 'learning_rate': 9.362865648885326e-06, 'epoch': 1.88} + 19%|█▉ | 1636/8720 [4:05:16<14:18:34, 7.27s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 02:20:43,489] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.02 | bwd_microstep: 270.52 | bwd_inner_microstep: 270.50 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2084 +[2025-05-02 02:20:44,013] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 203.05 | bwd_microstep: 303.73 | bwd_inner_microstep: 303.72 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1929 +[2025-05-02 02:20:44,514] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 197.14 | bwd_microstep: 287.95 | bwd_inner_microstep: 287.93 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-02 02:20:44,994] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.41 | bwd_microstep: 274.22 | bwd_inner_microstep: 274.20 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-02 02:20:45,472] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.11 | bwd_microstep: 273.71 | bwd_inner_microstep: 273.70 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 02:20:45,951] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.68 | bwd_microstep: 272.84 | bwd_inner_microstep: 272.83 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 02:20:46,430] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.48 | bwd_microstep: 272.68 | bwd_inner_microstep: 272.66 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 02:20:46,909] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.36 | bwd_microstep: 272.28 | bwd_inner_microstep: 272.27 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 02:20:47,390] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.34 | bwd_microstep: 273.07 | bwd_inner_microstep: 273.05 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 318 +[2025-05-02 02:20:47,620] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 91.40 | bwd_microstep: 119.07 | bwd_inner_microstep: 118.91 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 318 +[2025-05-02 02:20:47,840] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 83.13 | bwd_microstep: 119.86 | bwd_inner_microstep: 119.59 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 02:20:48,318] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.76 | bwd_microstep: 272.05 | bwd_inner_microstep: 272.03 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1085 +[2025-05-02 02:20:48,614] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 117.86 | bwd_microstep: 159.66 | bwd_inner_microstep: 159.60 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 02:20:49,095] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.97 | bwd_microstep: 271.15 | bwd_inner_microstep: 271.13 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 02:20:49,578] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.01 | bwd_microstep: 270.95 | bwd_inner_microstep: 270.93 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 02:20:50,158] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.21 | optimizer_step: 16.40 +[2025-05-02 02:20:50,158] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.11 | bwd_microstep: 349.88 | bwd_inner_microstep: 271.74 | bwd_allreduce_microstep: 78.09 | step_microstep: 24.48 +[2025-05-02 02:20:50,160] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2764.48 | bwd: 4063.68 | bwd_inner: 3984.89 | bwd_allreduce: 78.34 | step: 25.41 + 19%|█▉ | 1637/8720 [4:05:23<14:14:12, 7.24s/it] {'loss': 0.5003, 'grad_norm': 9.220575332641602, 'learning_rate': 9.361958149918875e-06, 'epoch': 1.88} + 19%|█▉ | 1637/8720 [4:05:23<14:14:12, 7.24s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 02:20:50,641] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.72 | bwd_microstep: 270.28 | bwd_inner_microstep: 270.27 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1974 +[2025-05-02 02:20:51,148] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 196.24 | bwd_microstep: 291.53 | bwd_inner_microstep: 291.51 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1912 +[2025-05-02 02:20:51,635] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.31 | bwd_microstep: 277.07 | bwd_inner_microstep: 277.05 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1909 +[2025-05-02 02:20:52,123] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.27 | bwd_microstep: 276.79 | bwd_inner_microstep: 276.77 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1385 +[2025-05-02 02:20:52,492] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 143.14 | bwd_microstep: 208.31 | bwd_inner_microstep: 208.22 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1897 +[2025-05-02 02:20:52,976] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.97 | bwd_microstep: 275.56 | bwd_inner_microstep: 275.54 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1897 +[2025-05-02 02:20:53,462] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.53 | bwd_microstep: 275.57 | bwd_inner_microstep: 275.55 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 348 +[2025-05-02 02:20:53,689] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 82.61 | bwd_microstep: 127.72 | bwd_inner_microstep: 127.41 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1893 +[2025-05-02 02:20:54,172] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.40 | bwd_microstep: 275.73 | bwd_inner_microstep: 275.71 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-02 02:20:54,655] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.24 | bwd_microstep: 274.25 | bwd_inner_microstep: 274.23 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 856 +[2025-05-02 02:20:54,906] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 98.62 | bwd_microstep: 132.87 | bwd_inner_microstep: 132.65 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 02:20:55,391] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.19 | bwd_microstep: 272.84 | bwd_inner_microstep: 272.83 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 845 +[2025-05-02 02:20:55,646] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 103.12 | bwd_microstep: 132.00 | bwd_inner_microstep: 131.92 | bwd_allreduce_microstep: 0.04 | step_microstep: 0.10 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 325 +[2025-05-02 02:20:55,865] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 87.22 | bwd_microstep: 115.57 | bwd_inner_microstep: 115.42 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 02:20:56,343] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.83 | bwd_microstep: 272.41 | bwd_inner_microstep: 272.40 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 02:20:56,920] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.13 | optimizer_step: 16.39 +[2025-05-02 02:20:56,920] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.50 | bwd_microstep: 348.42 | bwd_inner_microstep: 271.73 | bwd_allreduce_microstep: 76.64 | step_microstep: 24.24 +[2025-05-02 02:20:56,922] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2601.51 | bwd: 3827.05 | bwd_inner: 3749.30 | bwd_allreduce: 77.09 | step: 25.48 + 19%|█▉ | 1638/8720 [4:05:30<13:57:18, 7.09s/it] {'loss': 0.8522, 'grad_norm': 5.801365852355957, 'learning_rate': 9.36105004916117e-06, 'epoch': 1.88} + 19%|█▉ | 1638/8720 [4:05:30<13:57:18, 7.09s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 02:20:57,403] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.80 | bwd_microstep: 270.34 | bwd_inner_microstep: 270.32 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2054 +[2025-05-02 02:20:57,922] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 200.61 | bwd_microstep: 301.92 | bwd_inner_microstep: 301.91 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1974 +[2025-05-02 02:20:58,426] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 196.30 | bwd_microstep: 291.55 | bwd_inner_microstep: 291.53 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1917 +[2025-05-02 02:20:58,911] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.27 | bwd_microstep: 276.83 | bwd_inner_microstep: 276.81 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-02 02:20:59,394] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.81 | bwd_microstep: 274.24 | bwd_inner_microstep: 274.22 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1883 +[2025-05-02 02:20:59,878] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.50 | bwd_microstep: 274.21 | bwd_inner_microstep: 274.20 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.08 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 338 +[2025-05-02 02:21:00,104] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 86.48 | bwd_microstep: 123.04 | bwd_inner_microstep: 122.70 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.20 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1096 +[2025-05-02 02:21:00,399] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 114.83 | bwd_microstep: 161.67 | bwd_inner_microstep: 161.46 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.12 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1349 +[2025-05-02 02:21:00,762] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.22 | bwd_microstep: 205.94 | bwd_inner_microstep: 205.89 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.10 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1355 +[2025-05-02 02:21:01,126] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.64 | bwd_microstep: 206.37 | bwd_inner_microstep: 206.31 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 02:21:01,609] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.25 | bwd_microstep: 273.43 | bwd_inner_microstep: 273.41 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 02:21:02,091] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.57 | bwd_microstep: 273.23 | bwd_inner_microstep: 273.21 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 02:21:02,571] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.22 | bwd_microstep: 272.66 | bwd_inner_microstep: 272.64 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 02:21:03,050] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.37 | bwd_microstep: 272.60 | bwd_inner_microstep: 272.58 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 02:21:03,529] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.92 | bwd_microstep: 271.33 | bwd_inner_microstep: 271.31 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 02:21:04,119] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 3.32 | optimizer_step: 16.62 +[2025-05-02 02:21:04,120] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.65 | bwd_microstep: 355.25 | bwd_inner_microstep: 271.67 | bwd_allreduce_microstep: 83.53 | step_microstep: 25.74 +[2025-05-02 02:21:04,121] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2771.05 | bwd: 4104.72 | bwd_inner: 4020.27 | bwd_allreduce: 83.89 | step: 27.03 + 19%|█▉ | 1639/8720 [4:05:37<14:00:56, 7.13s/it] {'loss': 0.6515, 'grad_norm': 11.47527027130127, 'learning_rate': 9.360141346737491e-06, 'epoch': 1.88} + 19%|█▉ | 1639/8720 [4:05:37<14:00:56, 7.13s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1850 +[2025-05-02 02:21:04,604] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.45 | bwd_microstep: 270.23 | bwd_inner_microstep: 270.21 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 845 +[2025-05-02 02:21:04,847] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.34 | bwd_microstep: 132.86 | bwd_inner_microstep: 132.58 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 02:21:05,326] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.34 | bwd_microstep: 272.97 | bwd_inner_microstep: 272.95 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 02:21:05,803] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.89 | bwd_microstep: 272.99 | bwd_inner_microstep: 272.97 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 02:21:06,282] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.64 | bwd_microstep: 273.30 | bwd_inner_microstep: 273.28 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 02:21:06,766] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.35 | bwd_microstep: 273.17 | bwd_inner_microstep: 273.15 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 02:21:07,246] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.43 | bwd_microstep: 273.12 | bwd_inner_microstep: 273.11 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.13 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 02:21:07,729] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.30 | bwd_microstep: 272.88 | bwd_inner_microstep: 272.87 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.14 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 02:21:08,209] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.48 | bwd_microstep: 273.41 | bwd_inner_microstep: 273.39 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 02:21:08,689] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.76 | bwd_microstep: 272.89 | bwd_inner_microstep: 272.87 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 02:21:09,169] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.86 | bwd_microstep: 272.73 | bwd_inner_microstep: 272.72 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.15 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 02:21:09,650] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.25 | bwd_microstep: 272.61 | bwd_inner_microstep: 272.59 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.14 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 02:21:10,130] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.14 | bwd_microstep: 271.81 | bwd_inner_microstep: 271.80 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 02:21:10,613] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.10 | bwd_microstep: 272.52 | bwd_inner_microstep: 272.50 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 321 +[2025-05-02 02:21:10,850] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 96.48 | bwd_microstep: 118.88 | bwd_inner_microstep: 118.57 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 02:21:11,432] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.09 | optimizer_step: 16.20 +[2025-05-02 02:21:11,432] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.30 | bwd_microstep: 351.72 | bwd_inner_microstep: 271.86 | bwd_allreduce_microstep: 79.80 | step_microstep: 23.89 +[2025-05-02 02:21:11,434] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2835.71 | bwd: 4148.15 | bwd_inner: 4067.50 | bwd_allreduce: 80.12 | step: 25.35 + 19%|█▉ | 1640/8720 [4:05:45<14:07:24, 7.18s/it] {'loss': 0.51, 'grad_norm': 8.967557907104492, 'learning_rate': 9.35923204277321e-06, 'epoch': 1.88} + 19%|█▉ | 1640/8720 [4:05:45<14:07:24, 7.18s/it]dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 868 +[2025-05-02 02:21:11,691] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 97.23 | bwd_microstep: 138.62 | bwd_inner_microstep: 138.53 | bwd_allreduce_microstep: 0.04 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2053 +[2025-05-02 02:21:12,211] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 201.03 | bwd_microstep: 301.96 | bwd_inner_microstep: 301.94 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1988 +[2025-05-02 02:21:12,722] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 197.62 | bwd_microstep: 293.46 | bwd_inner_microstep: 293.45 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.11 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 383 +[2025-05-02 02:21:12,965] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 100.54 | bwd_microstep: 121.32 | bwd_inner_microstep: 120.95 | bwd_allreduce_microstep: 0.15 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-02 02:21:13,454] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.03 | bwd_microstep: 274.58 | bwd_inner_microstep: 274.57 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-02 02:21:13,937] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.49 | bwd_microstep: 272.98 | bwd_inner_microstep: 272.96 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 02:21:14,423] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.25 | bwd_microstep: 273.25 | bwd_inner_microstep: 273.23 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 02:21:14,901] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.65 | bwd_microstep: 272.60 | bwd_inner_microstep: 272.58 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 02:21:15,384] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.09 | bwd_microstep: 273.72 | bwd_inner_microstep: 273.70 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 02:21:15,865] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.09 | bwd_microstep: 272.90 | bwd_inner_microstep: 272.89 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 02:21:16,347] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.40 | bwd_microstep: 272.69 | bwd_inner_microstep: 272.67 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 02:21:16,825] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.99 | bwd_microstep: 271.68 | bwd_inner_microstep: 271.66 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 02:21:17,304] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.87 | bwd_microstep: 271.25 | bwd_inner_microstep: 271.23 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 02:21:17,785] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.78 | bwd_microstep: 271.32 | bwd_inner_microstep: 271.31 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 02:21:18,266] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.30 | bwd_microstep: 271.64 | bwd_inner_microstep: 271.63 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 02:21:18,843] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.07 | optimizer_step: 16.22 +[2025-05-02 02:21:18,843] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.64 | bwd_microstep: 347.61 | bwd_inner_microstep: 271.69 | bwd_allreduce_microstep: 75.87 | step_microstep: 23.84 +[2025-05-02 02:21:18,845] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2862.59 | bwd: 4201.63 | bwd_inner: 4125.04 | bwd_allreduce: 76.17 | step: 24.85 + 19%|█▉ | 1641/8720 [4:05:52<14:15:25, 7.25s/it] {'loss': 0.4814, 'grad_norm': 4.109318733215332, 'learning_rate': 9.358322137393777e-06, 'epoch': 1.88} + 19%|█▉ | 1641/8720 [4:05:52<14:15:25, 7.25s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2628 +[2025-05-02 02:21:19,468] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 230.98 | bwd_microstep: 370.10 | bwd_inner_microstep: 370.08 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1887 +[2025-05-02 02:21:19,949] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.23 | bwd_microstep: 274.52 | bwd_inner_microstep: 274.50 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 02:21:20,428] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.45 | bwd_microstep: 274.24 | bwd_inner_microstep: 274.23 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 02:21:20,906] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.97 | bwd_microstep: 273.49 | bwd_inner_microstep: 273.47 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 02:21:21,383] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.23 | bwd_microstep: 272.84 | bwd_inner_microstep: 272.82 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 02:21:21,861] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.77 | bwd_microstep: 273.48 | bwd_inner_microstep: 273.46 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-02 02:21:22,340] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.81 | bwd_microstep: 274.43 | bwd_inner_microstep: 274.41 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 332 +[2025-05-02 02:21:22,551] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 77.80 | bwd_microstep: 119.97 | bwd_inner_microstep: 119.71 | bwd_allreduce_microstep: 0.09 | step_microstep: 0.08 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 333 +[2025-05-02 02:21:22,752] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 68.33 | bwd_microstep: 119.70 | bwd_inner_microstep: 119.38 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 02:21:23,229] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.84 | bwd_microstep: 272.87 | bwd_inner_microstep: 272.86 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 847 +[2025-05-02 02:21:23,472] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.43 | bwd_microstep: 132.29 | bwd_inner_microstep: 132.08 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 02:21:23,950] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.86 | bwd_microstep: 272.19 | bwd_inner_microstep: 272.17 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 02:21:24,430] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.24 | bwd_microstep: 272.28 | bwd_inner_microstep: 272.26 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 02:21:24,909] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.18 | bwd_microstep: 272.17 | bwd_inner_microstep: 272.15 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 02:21:25,387] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.62 | bwd_microstep: 271.16 | bwd_inner_microstep: 271.14 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 02:21:25,979] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.10 | optimizer_step: 16.21 +[2025-05-02 02:21:25,979] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.03 | bwd_microstep: 358.42 | bwd_inner_microstep: 271.50 | bwd_allreduce_microstep: 86.86 | step_microstep: 23.75 +[2025-05-02 02:21:25,981] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2733.44 | bwd: 4104.19 | bwd_inner: 4016.35 | bwd_allreduce: 87.23 | step: 24.66 + 19%|█▉ | 1642/8720 [4:05:59<14:11:14, 7.22s/it] {'loss': 0.3508, 'grad_norm': 7.254936218261719, 'learning_rate': 9.357411630724724e-06, 'epoch': 1.88} + 19%|█▉ | 1642/8720 [4:05:59<14:11:14, 7.22s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 02:21:26,462] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.23 | bwd_microstep: 270.59 | bwd_inner_microstep: 270.57 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1890 +[2025-05-02 02:21:26,946] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.16 | bwd_microstep: 274.62 | bwd_inner_microstep: 274.60 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1888 +[2025-05-02 02:21:27,431] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.22 | bwd_microstep: 274.33 | bwd_inner_microstep: 274.32 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1356 +[2025-05-02 02:21:27,800] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.24 | bwd_microstep: 206.48 | bwd_inner_microstep: 206.35 | bwd_allreduce_microstep: 0.04 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 02:21:28,287] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.91 | bwd_microstep: 273.40 | bwd_inner_microstep: 273.38 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-02 02:21:28,768] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.08 | bwd_microstep: 273.32 | bwd_inner_microstep: 273.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 02:21:29,248] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.80 | bwd_microstep: 273.34 | bwd_inner_microstep: 273.33 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 02:21:29,728] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.43 | bwd_microstep: 272.50 | bwd_inner_microstep: 272.48 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 02:21:30,209] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.16 | bwd_microstep: 272.59 | bwd_inner_microstep: 272.57 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 02:21:30,688] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.02 | bwd_microstep: 271.11 | bwd_inner_microstep: 271.09 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 02:21:31,166] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.90 | bwd_microstep: 271.10 | bwd_inner_microstep: 271.08 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 02:21:31,646] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.16 | bwd_microstep: 270.98 | bwd_inner_microstep: 270.96 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 02:21:32,125] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.96 | bwd_microstep: 270.92 | bwd_inner_microstep: 270.90 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 315 +[2025-05-02 02:21:32,354] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 90.98 | bwd_microstep: 119.32 | bwd_inner_microstep: 119.14 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 02:21:32,831] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.82 | bwd_microstep: 271.03 | bwd_inner_microstep: 271.01 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1850 +[2025-05-02 02:21:33,412] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.04 | optimizer_step: 16.26 +[2025-05-02 02:21:33,412] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.63 | bwd_microstep: 350.84 | bwd_inner_microstep: 271.24 | bwd_allreduce_microstep: 79.55 | step_microstep: 24.13 +[2025-05-02 02:21:33,414] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2870.24 | bwd: 4216.52 | bwd_inner: 4136.39 | bwd_allreduce: 79.76 | step: 25.06 + 19%|█▉ | 1643/8720 [4:06:07<14:18:48, 7.28s/it] {'loss': 0.6423, 'grad_norm': 14.662691116333008, 'learning_rate': 9.356500522891669e-06, 'epoch': 1.88} + 19%|█▉ | 1643/8720 [4:06:07<14:18:48, 7.28s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 02:21:33,895] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.16 | bwd_microstep: 270.43 | bwd_inner_microstep: 270.41 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1894 +[2025-05-02 02:21:34,378] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.28 | bwd_microstep: 275.16 | bwd_inner_microstep: 275.14 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1883 +[2025-05-02 02:21:34,860] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.33 | bwd_microstep: 274.70 | bwd_inner_microstep: 274.69 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 02:21:35,340] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.72 | bwd_microstep: 272.87 | bwd_inner_microstep: 272.86 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-02 02:21:35,825] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.27 | bwd_microstep: 274.45 | bwd_inner_microstep: 274.43 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 02:21:36,303] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.77 | bwd_microstep: 272.24 | bwd_inner_microstep: 272.22 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 02:21:36,783] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.80 | bwd_microstep: 272.59 | bwd_inner_microstep: 272.57 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 02:21:37,262] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.24 | bwd_microstep: 272.24 | bwd_inner_microstep: 272.23 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 02:21:37,743] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.96 | bwd_microstep: 272.46 | bwd_inner_microstep: 272.44 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1346 +[2025-05-02 02:21:38,107] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.24 | bwd_microstep: 205.46 | bwd_inner_microstep: 205.30 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 02:21:38,584] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.47 | bwd_microstep: 271.99 | bwd_inner_microstep: 271.97 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 317 +[2025-05-02 02:21:38,798] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 81.50 | bwd_microstep: 117.32 | bwd_inner_microstep: 117.06 | bwd_allreduce_microstep: 0.10 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 02:21:39,276] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.35 | bwd_microstep: 271.70 | bwd_inner_microstep: 271.69 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1849 +[2025-05-02 02:21:39,755] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.19 | bwd_microstep: 270.87 | bwd_inner_microstep: 270.85 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2140 +[2025-05-02 02:21:40,293] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 206.56 | bwd_microstep: 314.32 | bwd_inner_microstep: 314.30 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1974 +[2025-05-02 02:21:40,907] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.66 | optimizer_step: 16.21 +[2025-05-02 02:21:40,908] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 196.75 | bwd_microstep: 374.50 | bwd_inner_microstep: 291.53 | bwd_allreduce_microstep: 82.91 | step_microstep: 24.45 +[2025-05-02 02:21:40,909] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2891.23 | bwd: 4283.34 | bwd_inner: 4199.74 | bwd_allreduce: 83.19 | step: 25.42 + 19%|█▉ | 1644/8720 [4:06:14<14:26:16, 7.35s/it] {'loss': 0.4059, 'grad_norm': 3.9441134929656982, 'learning_rate': 9.355588814020312e-06, 'epoch': 1.89} + 19%|█▉ | 1644/8720 [4:06:14<14:26:16, 7.35s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 02:21:41,392] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.43 | bwd_microstep: 271.91 | bwd_inner_microstep: 271.89 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 1008 +[2025-05-02 02:21:41,665] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 103.23 | bwd_microstep: 151.84 | bwd_inner_microstep: 151.70 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-02 02:21:42,144] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.41 | bwd_microstep: 273.12 | bwd_inner_microstep: 273.10 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 02:21:42,624] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.27 | bwd_microstep: 273.13 | bwd_inner_microstep: 273.11 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 02:21:43,104] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.55 | bwd_microstep: 272.81 | bwd_inner_microstep: 272.79 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 02:21:43,583] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.72 | bwd_microstep: 272.62 | bwd_inner_microstep: 272.60 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1091 +[2025-05-02 02:21:43,877] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 115.14 | bwd_microstep: 160.81 | bwd_inner_microstep: 160.79 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 02:21:44,356] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.74 | bwd_microstep: 272.65 | bwd_inner_microstep: 272.63 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 02:21:44,835] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.04 | bwd_microstep: 273.17 | bwd_inner_microstep: 273.15 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1349 +[2025-05-02 02:21:45,200] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.34 | bwd_microstep: 205.95 | bwd_inner_microstep: 205.79 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 02:21:45,680] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.05 | bwd_microstep: 272.08 | bwd_inner_microstep: 272.06 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 842 +[2025-05-02 02:21:45,932] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 101.59 | bwd_microstep: 131.49 | bwd_inner_microstep: 131.43 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.14 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 02:21:46,417] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.92 | bwd_microstep: 271.90 | bwd_inner_microstep: 271.89 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 02:21:46,898] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.30 | bwd_microstep: 271.24 | bwd_inner_microstep: 271.22 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 02:21:47,373] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.01 | bwd_microstep: 270.73 | bwd_inner_microstep: 270.71 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 02:21:47,952] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.08 | optimizer_step: 16.25 +[2025-05-02 02:21:47,952] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.85 | bwd_microstep: 348.05 | bwd_inner_microstep: 271.38 | bwd_allreduce_microstep: 76.63 | step_microstep: 23.79 +[2025-05-02 02:21:47,954] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2722.16 | bwd: 3993.57 | bwd_inner: 3916.27 | bwd_allreduce: 76.90 | step: 24.85 + 19%|█▉ | 1645/8720 [4:06:21<14:15:30, 7.26s/it] {'loss': 0.55, 'grad_norm': 6.943203449249268, 'learning_rate': 9.354676504236435e-06, 'epoch': 1.89} + 19%|█▉ | 1645/8720 [4:06:21<14:15:30, 7.26s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1892 +[2025-05-02 02:21:48,440] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.45 | bwd_microstep: 274.90 | bwd_inner_microstep: 274.88 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 855 +[2025-05-02 02:21:48,686] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 98.09 | bwd_microstep: 133.34 | bwd_inner_microstep: 133.14 | bwd_allreduce_microstep: 0.09 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 02:21:49,163] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.70 | bwd_microstep: 272.88 | bwd_inner_microstep: 272.87 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.13 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-02 02:21:49,641] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.07 | bwd_microstep: 274.23 | bwd_inner_microstep: 274.22 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 02:21:50,118] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.35 | bwd_microstep: 272.41 | bwd_inner_microstep: 272.39 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 02:21:50,596] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.56 | bwd_microstep: 273.03 | bwd_inner_microstep: 273.01 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1347 +[2025-05-02 02:21:50,957] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.24 | bwd_microstep: 205.16 | bwd_inner_microstep: 205.15 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 02:21:51,434] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.91 | bwd_microstep: 272.83 | bwd_inner_microstep: 272.82 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 838 +[2025-05-02 02:21:51,665] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 91.16 | bwd_microstep: 126.28 | bwd_inner_microstep: 126.02 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 02:21:52,141] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.29 | bwd_microstep: 273.00 | bwd_inner_microstep: 272.99 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 02:21:52,617] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.64 | bwd_microstep: 272.62 | bwd_inner_microstep: 272.60 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1091 +[2025-05-02 02:21:52,907] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 115.55 | bwd_microstep: 160.77 | bwd_inner_microstep: 160.63 | bwd_allreduce_microstep: 0.10 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 02:21:53,383] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.58 | bwd_microstep: 272.63 | bwd_inner_microstep: 272.62 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 02:21:53,857] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.77 | bwd_microstep: 271.18 | bwd_inner_microstep: 271.17 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 02:21:54,332] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.81 | bwd_microstep: 271.07 | bwd_inner_microstep: 271.05 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 02:21:54,896] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.11 | optimizer_step: 16.19 +[2025-05-02 02:21:54,897] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.00 | bwd_microstep: 337.71 | bwd_inner_microstep: 271.54 | bwd_allreduce_microstep: 66.12 | step_microstep: 23.19 +[2025-05-02 02:21:54,898] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2708.91 | bwd: 3964.10 | bwd_inner: 3897.10 | bwd_allreduce: 66.46 | step: 24.17 + 19%|█▉ | 1646/8720 [4:06:28<14:04:19, 7.16s/it] {'loss': 0.566, 'grad_norm': 13.279613494873047, 'learning_rate': 9.353763593665903e-06, 'epoch': 1.89} + 19%|█▉ | 1646/8720 [4:06:28<14:04:19, 7.16s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 02:21:55,377] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.77 | bwd_microstep: 272.03 | bwd_inner_microstep: 272.01 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 420 +[2025-05-02 02:21:55,588] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 73.77 | bwd_microstep: 123.58 | bwd_inner_microstep: 123.32 | bwd_allreduce_microstep: 0.10 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 02:21:56,065] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.96 | bwd_microstep: 272.60 | bwd_inner_microstep: 272.58 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 02:21:56,540] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.84 | bwd_microstep: 272.25 | bwd_inner_microstep: 272.23 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 02:21:57,017] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.20 | bwd_microstep: 272.63 | bwd_inner_microstep: 272.61 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 02:21:57,495] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.40 | bwd_microstep: 272.48 | bwd_inner_microstep: 272.47 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 02:21:57,974] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.77 | bwd_microstep: 272.83 | bwd_inner_microstep: 272.81 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 02:21:58,453] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.28 | bwd_microstep: 272.41 | bwd_inner_microstep: 272.40 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 02:21:58,935] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.90 | bwd_microstep: 273.01 | bwd_inner_microstep: 273.00 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 02:21:59,417] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.13 | bwd_microstep: 272.68 | bwd_inner_microstep: 272.66 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 02:21:59,897] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.09 | bwd_microstep: 272.18 | bwd_inner_microstep: 272.16 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 02:22:00,381] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.85 | bwd_microstep: 272.02 | bwd_inner_microstep: 272.00 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 02:22:00,857] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.52 | bwd_microstep: 271.03 | bwd_inner_microstep: 271.02 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 02:22:01,335] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.98 | bwd_microstep: 271.17 | bwd_inner_microstep: 271.15 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 02:22:01,813] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.28 | bwd_microstep: 271.29 | bwd_inner_microstep: 271.27 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 830 +[2025-05-02 02:22:02,158] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 1.99 | optimizer_step: 16.59 +[2025-05-02 02:22:02,159] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 97.39 | bwd_microstep: 206.99 | bwd_inner_microstep: 130.18 | bwd_allreduce_microstep: 76.69 | step_microstep: 24.95 +[2025-05-02 02:22:02,160] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2806.74 | bwd: 4141.20 | bwd_inner: 4063.95 | bwd_allreduce: 76.84 | step: 25.71 + 19%|█▉ | 1647/8720 [4:06:35<14:07:51, 7.19s/it] {'loss': 0.7139, 'grad_norm': 21.05886459350586, 'learning_rate': 9.352850082434666e-06, 'epoch': 1.89} + 19%|█▉ | 1647/8720 [4:06:35<14:07:51, 7.19s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 02:22:02,642] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.91 | bwd_microstep: 270.15 | bwd_inner_microstep: 270.14 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1911 +[2025-05-02 02:22:03,128] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.51 | bwd_microstep: 276.67 | bwd_inner_microstep: 276.65 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1902 +[2025-05-02 02:22:03,615] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.36 | bwd_microstep: 276.46 | bwd_inner_microstep: 276.44 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1897 +[2025-05-02 02:22:04,098] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.01 | bwd_microstep: 275.46 | bwd_inner_microstep: 275.44 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-02 02:22:04,579] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.08 | bwd_microstep: 274.06 | bwd_inner_microstep: 274.05 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 02:22:05,057] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.65 | bwd_microstep: 272.83 | bwd_inner_microstep: 272.82 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1353 +[2025-05-02 02:22:05,421] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.94 | bwd_microstep: 206.02 | bwd_inner_microstep: 205.84 | bwd_allreduce_microstep: 0.08 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 02:22:05,897] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.62 | bwd_microstep: 272.43 | bwd_inner_microstep: 272.41 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 838 +[2025-05-02 02:22:06,132] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 92.97 | bwd_microstep: 126.59 | bwd_inner_microstep: 126.58 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 02:22:06,611] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.14 | bwd_microstep: 272.52 | bwd_inner_microstep: 272.50 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 02:22:07,088] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.09 | bwd_microstep: 272.70 | bwd_inner_microstep: 272.68 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 02:22:07,565] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.30 | bwd_microstep: 272.27 | bwd_inner_microstep: 272.25 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 02:22:08,041] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.82 | bwd_microstep: 272.53 | bwd_inner_microstep: 272.51 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 02:22:08,516] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.55 | bwd_microstep: 270.97 | bwd_inner_microstep: 270.95 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 02:22:08,990] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.14 | bwd_microstep: 271.31 | bwd_inner_microstep: 271.29 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 02:22:09,556] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.04 | optimizer_gradients: 2.08 | optimizer_step: 16.20 +[2025-05-02 02:22:09,556] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.57 | bwd_microstep: 338.59 | bwd_inner_microstep: 271.77 | bwd_allreduce_microstep: 66.77 | step_microstep: 23.07 +[2025-05-02 02:22:09,557] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2874.36 | bwd: 4221.59 | bwd_inner: 4154.33 | bwd_allreduce: 66.97 | step: 24.13 + 19%|█▉ | 1648/8720 [4:06:43<14:14:53, 7.25s/it] {'loss': 0.8136, 'grad_norm': 19.42058563232422, 'learning_rate': 9.351935970668753e-06, 'epoch': 1.89} + 19%|█▉ | 1648/8720 [4:06:43<14:14:53, 7.25s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 02:22:10,036] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.65 | bwd_microstep: 270.20 | bwd_inner_microstep: 270.18 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1903 +[2025-05-02 02:22:10,516] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.09 | bwd_microstep: 275.95 | bwd_inner_microstep: 275.93 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1921 +[2025-05-02 02:22:11,014] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.30 | bwd_microstep: 286.86 | bwd_inner_microstep: 286.84 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-02 02:22:11,495] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.47 | bwd_microstep: 274.21 | bwd_inner_microstep: 274.19 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.13 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1886 +[2025-05-02 02:22:11,978] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.88 | bwd_microstep: 274.17 | bwd_inner_microstep: 274.15 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 347 +[2025-05-02 02:22:12,212] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.75 | bwd_microstep: 122.02 | bwd_inner_microstep: 121.71 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-02 02:22:12,692] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.99 | bwd_microstep: 273.26 | bwd_inner_microstep: 273.24 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 02:22:13,173] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.81 | bwd_microstep: 272.43 | bwd_inner_microstep: 272.41 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 02:22:13,655] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.71 | bwd_microstep: 272.68 | bwd_inner_microstep: 272.67 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.13 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 845 +[2025-05-02 02:22:13,908] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 99.32 | bwd_microstep: 132.13 | bwd_inner_microstep: 131.92 | bwd_allreduce_microstep: 0.10 | step_microstep: 0.10 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1354 +[2025-05-02 02:22:14,273] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.38 | bwd_microstep: 206.13 | bwd_inner_microstep: 206.11 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 02:22:14,754] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.63 | bwd_microstep: 272.93 | bwd_inner_microstep: 272.91 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 02:22:15,234] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.40 | bwd_microstep: 272.17 | bwd_inner_microstep: 272.15 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 02:22:15,716] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.56 | bwd_microstep: 271.15 | bwd_inner_microstep: 271.13 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 02:22:16,195] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.50 | bwd_microstep: 270.95 | bwd_inner_microstep: 270.93 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 02:22:16,774] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.12 | optimizer_step: 16.39 +[2025-05-02 02:22:16,774] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.27 | bwd_microstep: 349.82 | bwd_inner_microstep: 271.43 | bwd_allreduce_microstep: 78.34 | step_microstep: 24.24 +[2025-05-02 02:22:16,776] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2791.30 | bwd: 4097.14 | bwd_inner: 4017.99 | bwd_allreduce: 78.61 | step: 25.39 + 19%|█▉ | 1649/8720 [4:06:50<14:13:37, 7.24s/it] {'loss': 0.4534, 'grad_norm': 8.113813400268555, 'learning_rate': 9.35102125849428e-06, 'epoch': 1.89} + 19%|█▉ | 1649/8720 [4:06:50<14:13:37, 7.24s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 02:22:17,257] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.49 | bwd_microstep: 270.10 | bwd_inner_microstep: 270.08 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1889 +[2025-05-02 02:22:17,739] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.91 | bwd_microstep: 274.84 | bwd_inner_microstep: 274.82 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 02:22:18,221] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.62 | bwd_microstep: 273.48 | bwd_inner_microstep: 273.46 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1887 +[2025-05-02 02:22:18,706] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.15 | bwd_microstep: 275.34 | bwd_inner_microstep: 275.32 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 02:22:19,190] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.08 | bwd_microstep: 273.59 | bwd_inner_microstep: 273.57 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 02:22:19,673] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.14 | bwd_microstep: 272.82 | bwd_inner_microstep: 272.80 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 02:22:20,153] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.85 | bwd_microstep: 273.21 | bwd_inner_microstep: 273.20 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.13 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 845 +[2025-05-02 02:22:20,397] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.48 | bwd_microstep: 132.70 | bwd_inner_microstep: 132.47 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 02:22:20,874] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.58 | bwd_microstep: 272.20 | bwd_inner_microstep: 272.18 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 325 +[2025-05-02 02:22:21,109] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 88.34 | bwd_microstep: 129.89 | bwd_inner_microstep: 129.63 | bwd_allreduce_microstep: 0.09 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 02:22:21,585] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.66 | bwd_microstep: 272.29 | bwd_inner_microstep: 272.27 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 02:22:22,061] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.18 | bwd_microstep: 272.29 | bwd_inner_microstep: 272.27 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 02:22:22,536] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.07 | bwd_microstep: 272.66 | bwd_inner_microstep: 272.64 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 02:22:23,012] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.99 | bwd_microstep: 272.38 | bwd_inner_microstep: 272.36 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1344 +[2025-05-02 02:22:23,372] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.58 | bwd_microstep: 204.75 | bwd_inner_microstep: 204.67 | bwd_allreduce_microstep: 0.04 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 02:22:23,937] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.20 | optimizer_step: 16.44 +[2025-05-02 02:22:23,937] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.93 | bwd_microstep: 338.08 | bwd_inner_microstep: 271.77 | bwd_allreduce_microstep: 66.26 | step_microstep: 23.73 +[2025-05-02 02:22:23,938] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2770.71 | bwd: 4080.66 | bwd_inner: 4013.60 | bwd_allreduce: 66.56 | step: 24.73 + 19%|█▉ | 1650/8720 [4:06:57<14:10:34, 7.22s/it] {'loss': 0.3751, 'grad_norm': 6.787440299987793, 'learning_rate': 9.350105946037444e-06, 'epoch': 1.89} + 19%|█▉ | 1650/8720 [4:06:57<14:10:34, 7.22s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 02:22:24,417] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.85 | bwd_microstep: 270.61 | bwd_inner_microstep: 270.60 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1895 +[2025-05-02 02:22:24,896] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.99 | bwd_microstep: 274.99 | bwd_inner_microstep: 274.98 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1893 +[2025-05-02 02:22:25,375] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.96 | bwd_microstep: 275.18 | bwd_inner_microstep: 275.16 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 861 +[2025-05-02 02:22:25,618] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.80 | bwd_microstep: 133.91 | bwd_inner_microstep: 133.76 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1887 +[2025-05-02 02:22:26,098] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.78 | bwd_microstep: 274.48 | bwd_inner_microstep: 274.46 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-02 02:22:26,575] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.63 | bwd_microstep: 273.38 | bwd_inner_microstep: 273.36 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 02:22:27,051] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.08 | bwd_microstep: 272.89 | bwd_inner_microstep: 272.87 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-02 02:22:27,528] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.68 | bwd_microstep: 273.22 | bwd_inner_microstep: 273.20 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 02:22:28,006] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.38 | bwd_microstep: 273.29 | bwd_inner_microstep: 273.27 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 02:22:28,483] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.46 | bwd_microstep: 273.35 | bwd_inner_microstep: 273.33 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 02:22:28,962] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.31 | bwd_microstep: 273.00 | bwd_inner_microstep: 272.98 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 841 +[2025-05-02 02:22:29,209] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 97.52 | bwd_microstep: 131.87 | bwd_inner_microstep: 131.66 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.18 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 326 +[2025-05-02 02:22:29,456] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 91.63 | bwd_microstep: 136.40 | bwd_inner_microstep: 136.24 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.11 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 835 +[2025-05-02 02:22:29,708] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 98.19 | bwd_microstep: 136.92 | bwd_inner_microstep: 136.67 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 02:22:30,187] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.50 | bwd_microstep: 273.02 | bwd_inner_microstep: 273.00 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 02:22:30,764] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.04 | optimizer_gradients: 2.04 | optimizer_step: 17.08 +[2025-05-02 02:22:30,765] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.26 | bwd_microstep: 348.02 | bwd_inner_microstep: 271.90 | bwd_allreduce_microstep: 76.06 | step_microstep: 24.28 +[2025-05-02 02:22:30,766] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2645.72 | bwd: 3894.61 | bwd_inner: 3817.51 | bwd_allreduce: 76.49 | step: 25.28 + 19%|█▉ | 1651/8720 [4:07:04<13:56:37, 7.10s/it] {'loss': 0.5428, 'grad_norm': 5.2202229499816895, 'learning_rate': 9.349190033424523e-06, 'epoch': 1.89} + 19%|█▉ | 1651/8720 [4:07:04<13:56:37, 7.10s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 02:22:31,244] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.91 | bwd_microstep: 271.13 | bwd_inner_microstep: 271.11 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 435 +[2025-05-02 02:22:31,452] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 81.60 | bwd_microstep: 112.41 | bwd_inner_microstep: 112.16 | bwd_allreduce_microstep: 0.10 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1905 +[2025-05-02 02:22:31,931] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.85 | bwd_microstep: 275.94 | bwd_inner_microstep: 275.92 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-02 02:22:32,408] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.73 | bwd_microstep: 273.53 | bwd_inner_microstep: 273.52 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1364 +[2025-05-02 02:22:32,772] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.88 | bwd_microstep: 206.94 | bwd_inner_microstep: 206.93 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-02 02:22:33,250] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.53 | bwd_microstep: 274.25 | bwd_inner_microstep: 274.23 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 02:22:33,727] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.70 | bwd_microstep: 272.80 | bwd_inner_microstep: 272.78 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 334 +[2025-05-02 02:22:33,933] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 78.51 | bwd_microstep: 114.43 | bwd_inner_microstep: 114.26 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.10 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 331 +[2025-05-02 02:22:34,146] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 80.72 | bwd_microstep: 116.80 | bwd_inner_microstep: 116.47 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 02:22:34,624] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.72 | bwd_microstep: 272.71 | bwd_inner_microstep: 272.69 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 324 +[2025-05-02 02:22:34,829] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 73.98 | bwd_microstep: 117.19 | bwd_inner_microstep: 117.06 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 321 +[2025-05-02 02:22:35,037] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 80.49 | bwd_microstep: 114.94 | bwd_inner_microstep: 114.69 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 02:22:35,512] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.91 | bwd_microstep: 272.29 | bwd_inner_microstep: 272.27 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 02:22:35,988] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.86 | bwd_microstep: 272.21 | bwd_inner_microstep: 272.20 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 02:22:36,463] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.14 | bwd_microstep: 271.45 | bwd_inner_microstep: 271.43 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 02:22:37,030] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.04 | optimizer_gradients: 2.08 | optimizer_step: 16.19 +[2025-05-02 02:22:37,031] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.79 | bwd_microstep: 340.15 | bwd_inner_microstep: 272.94 | bwd_allreduce_microstep: 67.17 | step_microstep: 23.00 +[2025-05-02 02:22:37,032] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2421.03 | bwd: 3579.24 | bwd_inner: 3510.92 | bwd_allreduce: 67.63 | step: 23.92 + 19%|█▉ | 1652/8720 [4:07:10<13:26:59, 6.85s/it] {'loss': 0.4553, 'grad_norm': 6.228435516357422, 'learning_rate': 9.348273520781881e-06, 'epoch': 1.89} + 19%|█▉ | 1652/8720 [4:07:10<13:26:59, 6.85s/it]dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 827 +[2025-05-02 02:22:37,272] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 91.58 | bwd_microstep: 130.14 | bwd_inner_microstep: 129.89 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.08 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1386 +[2025-05-02 02:22:37,636] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.10 | bwd_microstep: 208.59 | bwd_inner_microstep: 208.52 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 02:22:38,113] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.35 | bwd_microstep: 273.76 | bwd_inner_microstep: 273.74 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-02 02:22:38,591] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.47 | bwd_microstep: 273.44 | bwd_inner_microstep: 273.42 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 847 +[2025-05-02 02:22:38,831] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.45 | bwd_microstep: 132.86 | bwd_inner_microstep: 132.59 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-02 02:22:39,308] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.34 | bwd_microstep: 273.34 | bwd_inner_microstep: 273.32 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 02:22:39,784] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.56 | bwd_microstep: 273.14 | bwd_inner_microstep: 273.12 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 02:22:40,261] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.85 | bwd_microstep: 273.17 | bwd_inner_microstep: 273.15 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 02:22:40,738] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.96 | bwd_microstep: 272.39 | bwd_inner_microstep: 272.37 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 02:22:41,214] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.14 | bwd_microstep: 272.39 | bwd_inner_microstep: 272.37 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 02:22:41,691] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.85 | bwd_microstep: 272.89 | bwd_inner_microstep: 272.87 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 02:22:42,168] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.07 | bwd_microstep: 272.73 | bwd_inner_microstep: 272.71 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 02:22:42,645] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.17 | bwd_microstep: 272.00 | bwd_inner_microstep: 271.98 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 02:22:43,122] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.07 | bwd_microstep: 271.23 | bwd_inner_microstep: 271.21 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 02:22:43,602] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.12 | bwd_microstep: 271.70 | bwd_inner_microstep: 271.68 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 02:22:44,177] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.04 | optimizer_gradients: 2.10 | optimizer_step: 16.58 +[2025-05-02 02:22:44,178] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.67 | bwd_microstep: 346.72 | bwd_inner_microstep: 271.49 | bwd_allreduce_microstep: 75.18 | step_microstep: 23.58 +[2025-05-02 02:22:44,179] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2774.44 | bwd: 4090.55 | bwd_inner: 4014.50 | bwd_allreduce: 75.49 | step: 24.54 + 19%|█▉ | 1653/8720 [4:07:17<13:37:21, 6.94s/it] {'loss': 0.6271, 'grad_norm': 13.615897178649902, 'learning_rate': 9.347356408235963e-06, 'epoch': 1.9} + 19%|█▉ | 1653/8720 [4:07:17<13:37:21, 6.94s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 02:22:44,657] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.16 | bwd_microstep: 270.31 | bwd_inner_microstep: 270.29 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1934 +[2025-05-02 02:22:45,155] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.30 | bwd_microstep: 288.42 | bwd_inner_microstep: 288.40 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 877 +[2025-05-02 02:22:45,398] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.45 | bwd_microstep: 134.88 | bwd_inner_microstep: 134.69 | bwd_allreduce_microstep: 0.10 | step_microstep: 0.08 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 357 +[2025-05-02 02:22:45,604] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 75.74 | bwd_microstep: 116.65 | bwd_inner_microstep: 116.33 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1893 +[2025-05-02 02:22:46,083] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.69 | bwd_microstep: 275.14 | bwd_inner_microstep: 275.12 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-02 02:22:46,561] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.63 | bwd_microstep: 274.35 | bwd_inner_microstep: 274.33 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1892 +[2025-05-02 02:22:47,041] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.32 | bwd_microstep: 275.04 | bwd_inner_microstep: 275.02 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 852 +[2025-05-02 02:22:47,283] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.64 | bwd_microstep: 133.15 | bwd_inner_microstep: 133.05 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 02:22:47,760] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.77 | bwd_microstep: 273.11 | bwd_inner_microstep: 273.09 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 02:22:48,239] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.54 | bwd_microstep: 273.44 | bwd_inner_microstep: 273.42 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 329 +[2025-05-02 02:22:48,460] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 85.79 | bwd_microstep: 120.47 | bwd_inner_microstep: 120.20 | bwd_allreduce_microstep: 0.10 | step_microstep: 0.09 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 331 +[2025-05-02 02:22:48,677] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 86.94 | bwd_microstep: 114.86 | bwd_inner_microstep: 114.54 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 02:22:49,155] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.30 | bwd_microstep: 272.69 | bwd_inner_microstep: 272.67 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 839 +[2025-05-02 02:22:49,396] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.24 | bwd_microstep: 129.61 | bwd_inner_microstep: 129.38 | bwd_allreduce_microstep: 0.14 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 02:22:49,875] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.77 | bwd_microstep: 272.42 | bwd_inner_microstep: 272.41 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 02:22:50,451] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.08 | optimizer_step: 16.27 +[2025-05-02 02:22:50,452] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.30 | bwd_microstep: 348.42 | bwd_inner_microstep: 272.82 | bwd_allreduce_microstep: 75.56 | step_microstep: 23.19 +[2025-05-02 02:22:50,453] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2428.29 | bwd: 3573.11 | bwd_inner: 3495.95 | bwd_allreduce: 76.20 | step: 24.24 + 19%|█▉ | 1654/8720 [4:07:24<13:13:44, 6.74s/it] {'loss': 0.8113, 'grad_norm': 9.161611557006836, 'learning_rate': 9.346438695913297e-06, 'epoch': 1.9} + 19%|█▉ | 1654/8720 [4:07:24<13:13:44, 6.74s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1925 +[2025-05-02 02:22:50,954] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.15 | bwd_microstep: 286.38 | bwd_inner_microstep: 286.36 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1931 +[2025-05-02 02:22:51,453] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.39 | bwd_microstep: 288.16 | bwd_inner_microstep: 288.14 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1908 +[2025-05-02 02:22:51,934] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.54 | bwd_microstep: 276.32 | bwd_inner_microstep: 276.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1889 +[2025-05-02 02:22:52,414] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.42 | bwd_microstep: 275.12 | bwd_inner_microstep: 275.11 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 345 +[2025-05-02 02:22:52,636] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 87.64 | bwd_microstep: 117.88 | bwd_inner_microstep: 117.62 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1896 +[2025-05-02 02:22:53,118] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.58 | bwd_microstep: 275.09 | bwd_inner_microstep: 275.08 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 02:22:53,596] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.89 | bwd_microstep: 272.94 | bwd_inner_microstep: 272.93 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 02:22:54,076] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.50 | bwd_microstep: 272.83 | bwd_inner_microstep: 272.81 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 02:22:54,555] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.30 | bwd_microstep: 273.57 | bwd_inner_microstep: 273.55 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 02:22:55,035] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.01 | bwd_microstep: 272.97 | bwd_inner_microstep: 272.95 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 02:22:55,512] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.98 | bwd_microstep: 272.31 | bwd_inner_microstep: 272.29 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 02:22:55,987] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.03 | bwd_microstep: 272.65 | bwd_inner_microstep: 272.63 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 02:22:56,463] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.78 | bwd_microstep: 271.30 | bwd_inner_microstep: 271.28 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 02:22:56,944] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.84 | bwd_microstep: 272.12 | bwd_inner_microstep: 272.11 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 02:22:57,426] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.80 | bwd_microstep: 271.05 | bwd_inner_microstep: 271.03 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 829 +[2025-05-02 02:22:57,773] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.11 | optimizer_step: 16.28 +[2025-05-02 02:22:57,774] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 97.40 | bwd_microstep: 206.15 | bwd_inner_microstep: 130.45 | bwd_allreduce_microstep: 75.56 | step_microstep: 23.86 +[2025-05-02 02:22:57,775] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2840.90 | bwd: 4176.87 | bwd_inner: 4100.75 | bwd_allreduce: 75.71 | step: 24.60 + 19%|█▉ | 1655/8720 [4:07:31<13:34:14, 6.92s/it] {'loss': 0.5393, 'grad_norm': 6.5904459953308105, 'learning_rate': 9.345520383940494e-06, 'epoch': 1.9} + 19%|█▉ | 1655/8720 [4:07:31<13:34:14, 6.92s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 02:22:58,256] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.02 | bwd_microstep: 270.50 | bwd_inner_microstep: 270.48 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1941 +[2025-05-02 02:22:58,762] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 198.17 | bwd_microstep: 288.62 | bwd_inner_microstep: 288.61 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 02:22:59,241] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.77 | bwd_microstep: 273.43 | bwd_inner_microstep: 273.41 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 02:22:59,719] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.35 | bwd_microstep: 272.96 | bwd_inner_microstep: 272.94 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 02:23:00,197] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.83 | bwd_microstep: 273.61 | bwd_inner_microstep: 273.59 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 02:23:00,676] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.72 | bwd_microstep: 272.94 | bwd_inner_microstep: 272.92 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 02:23:01,154] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.40 | bwd_microstep: 272.64 | bwd_inner_microstep: 272.63 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 02:23:01,635] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.75 | bwd_microstep: 272.44 | bwd_inner_microstep: 272.43 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 02:23:02,115] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.22 | bwd_microstep: 272.86 | bwd_inner_microstep: 272.84 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 02:23:02,594] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.19 | bwd_microstep: 273.17 | bwd_inner_microstep: 273.15 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 02:23:03,070] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.49 | bwd_microstep: 272.71 | bwd_inner_microstep: 272.69 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 02:23:03,545] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.14 | bwd_microstep: 272.53 | bwd_inner_microstep: 272.51 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 02:23:04,021] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.47 | bwd_microstep: 271.41 | bwd_inner_microstep: 271.39 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 02:23:04,497] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.90 | bwd_microstep: 272.70 | bwd_inner_microstep: 272.69 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 02:23:04,975] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.47 | bwd_microstep: 272.40 | bwd_inner_microstep: 272.39 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 02:23:05,555] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.08 | optimizer_step: 16.25 +[2025-05-02 02:23:05,555] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.44 | bwd_microstep: 349.05 | bwd_inner_microstep: 273.11 | bwd_allreduce_microstep: 75.89 | step_microstep: 23.84 +[2025-05-02 02:23:05,557] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 3026.01 | bwd: 4454.01 | bwd_inner: 4377.79 | bwd_allreduce: 75.98 | step: 24.66 + 19%|█▉ | 1656/8720 [4:07:39<14:04:44, 7.18s/it] {'loss': 0.4138, 'grad_norm': 7.445685386657715, 'learning_rate': 9.344601472444247e-06, 'epoch': 1.9} + 19%|█▉ | 1656/8720 [4:07:39<14:04:44, 7.18s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 315 +[2025-05-02 02:23:05,772] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 78.78 | bwd_microstep: 115.72 | bwd_inner_microstep: 115.40 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1974 +[2025-05-02 02:23:06,277] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 196.95 | bwd_microstep: 291.16 | bwd_inner_microstep: 291.14 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 419 +[2025-05-02 02:23:06,526] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.31 | bwd_microstep: 136.32 | bwd_inner_microstep: 136.07 | bwd_allreduce_microstep: 0.09 | step_microstep: 0.10 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 874 +[2025-05-02 02:23:06,776] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 99.43 | bwd_microstep: 134.68 | bwd_inner_microstep: 134.42 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-02 02:23:07,255] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.86 | bwd_microstep: 273.15 | bwd_inner_microstep: 273.13 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-02 02:23:07,738] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.53 | bwd_microstep: 273.47 | bwd_inner_microstep: 273.45 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 338 +[2025-05-02 02:23:07,967] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 84.86 | bwd_microstep: 128.17 | bwd_inner_microstep: 128.02 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 02:23:08,446] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.43 | bwd_microstep: 272.66 | bwd_inner_microstep: 272.64 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 333 +[2025-05-02 02:23:08,673] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.36 | bwd_microstep: 117.41 | bwd_inner_microstep: 117.19 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 02:23:09,153] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.62 | bwd_microstep: 273.22 | bwd_inner_microstep: 273.20 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 02:23:09,633] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.44 | bwd_microstep: 273.03 | bwd_inner_microstep: 273.01 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 02:23:10,112] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.38 | bwd_microstep: 271.19 | bwd_inner_microstep: 271.17 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 321 +[2025-05-02 02:23:10,345] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 82.00 | bwd_microstep: 135.34 | bwd_inner_microstep: 135.16 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 02:23:10,824] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.24 | bwd_microstep: 272.80 | bwd_inner_microstep: 272.78 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 832 +[2025-05-02 02:23:11,064] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.77 | bwd_microstep: 130.24 | bwd_inner_microstep: 130.07 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 02:23:11,641] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.12 | optimizer_step: 16.25 +[2025-05-02 02:23:11,641] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.53 | bwd_microstep: 347.55 | bwd_inner_microstep: 271.68 | bwd_allreduce_microstep: 75.82 | step_microstep: 23.89 +[2025-05-02 02:23:11,643] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2332.11 | bwd: 3446.20 | bwd_inner: 3368.84 | bwd_allreduce: 76.46 | step: 25.12 + 19%|█▉ | 1657/8720 [4:07:45<13:26:10, 6.85s/it] {'loss': 0.7423, 'grad_norm': 24.88728904724121, 'learning_rate': 9.343681961551332e-06, 'epoch': 1.9} + 19%|█▉ | 1657/8720 [4:07:45<13:26:10, 6.85s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1902 +[2025-05-02 02:23:12,131] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.74 | bwd_microstep: 275.29 | bwd_inner_microstep: 275.27 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1909 +[2025-05-02 02:23:12,616] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.66 | bwd_microstep: 276.24 | bwd_inner_microstep: 276.22 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1906 +[2025-05-02 02:23:13,101] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.37 | bwd_microstep: 275.82 | bwd_inner_microstep: 275.80 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1907 +[2025-05-02 02:23:13,585] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.17 | bwd_microstep: 275.91 | bwd_inner_microstep: 275.90 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1913 +[2025-05-02 02:23:14,070] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 191.37 | bwd_microstep: 276.47 | bwd_inner_microstep: 276.46 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1887 +[2025-05-02 02:23:14,553] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.63 | bwd_microstep: 274.57 | bwd_inner_microstep: 274.56 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1118 +[2025-05-02 02:23:14,854] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 120.64 | bwd_microstep: 162.55 | bwd_inner_microstep: 162.53 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-02 02:23:15,333] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.68 | bwd_microstep: 273.25 | bwd_inner_microstep: 273.23 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 02:23:15,813] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.97 | bwd_microstep: 272.23 | bwd_inner_microstep: 272.21 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 02:23:16,292] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.79 | bwd_microstep: 272.80 | bwd_inner_microstep: 272.79 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 02:23:16,774] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.22 | bwd_microstep: 272.33 | bwd_inner_microstep: 272.31 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 02:23:17,253] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.57 | bwd_microstep: 272.49 | bwd_inner_microstep: 272.47 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 837 +[2025-05-02 02:23:17,491] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.09 | bwd_microstep: 127.11 | bwd_inner_microstep: 126.94 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 02:23:17,969] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.43 | bwd_microstep: 271.37 | bwd_inner_microstep: 271.35 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 02:23:18,449] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.10 | bwd_microstep: 270.95 | bwd_inner_microstep: 270.93 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 828 +[2025-05-02 02:23:18,811] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.14 | optimizer_step: 16.38 +[2025-05-02 02:23:18,812] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 97.22 | bwd_microstep: 221.92 | bwd_inner_microstep: 145.56 | bwd_allreduce_microstep: 76.26 | step_microstep: 24.27 +[2025-05-02 02:23:18,813] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2772.24 | bwd: 4071.33 | bwd_inner: 3994.58 | bwd_allreduce: 76.39 | step: 25.15 + 19%|█▉ | 1658/8720 [4:07:52<13:37:26, 6.95s/it] {'loss': 0.624, 'grad_norm': 13.492278099060059, 'learning_rate': 9.34276185138861e-06, 'epoch': 1.9} + 19%|█▉ | 1658/8720 [4:07:52<13:37:26, 6.95s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1901 +[2025-05-02 02:23:19,301] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.18 | bwd_microstep: 275.03 | bwd_inner_microstep: 275.01 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 362 +[2025-05-02 02:23:19,527] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 79.21 | bwd_microstep: 130.81 | bwd_inner_microstep: 130.50 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1892 +[2025-05-02 02:23:20,006] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.00 | bwd_microstep: 274.74 | bwd_inner_microstep: 274.72 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 343 +[2025-05-02 02:23:20,224] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 72.25 | bwd_microstep: 132.25 | bwd_inner_microstep: 131.94 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.19 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1365 +[2025-05-02 02:23:20,587] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.78 | bwd_microstep: 206.53 | bwd_inner_microstep: 206.51 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-02 02:23:21,065] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.44 | bwd_microstep: 273.76 | bwd_inner_microstep: 273.74 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 848 +[2025-05-02 02:23:21,311] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 96.64 | bwd_microstep: 133.54 | bwd_inner_microstep: 133.43 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 02:23:21,790] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.27 | bwd_microstep: 272.73 | bwd_inner_microstep: 272.71 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 02:23:22,270] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.02 | bwd_microstep: 272.99 | bwd_inner_microstep: 272.97 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 834 +[2025-05-02 02:23:22,515] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 100.73 | bwd_microstep: 125.94 | bwd_inner_microstep: 125.69 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.10 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 835 +[2025-05-02 02:23:22,751] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.50 | bwd_microstep: 125.93 | bwd_inner_microstep: 125.67 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 321 +[2025-05-02 02:23:22,986] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 83.36 | bwd_microstep: 134.92 | bwd_inner_microstep: 134.61 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 02:23:23,464] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.18 | bwd_microstep: 271.21 | bwd_inner_microstep: 271.19 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 02:23:23,944] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.57 | bwd_microstep: 271.31 | bwd_inner_microstep: 271.29 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 02:23:24,427] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.14 | bwd_microstep: 270.95 | bwd_inner_microstep: 270.93 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 02:23:25,010] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.14 | optimizer_step: 16.40 +[2025-05-02 02:23:25,010] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.15 | bwd_microstep: 349.40 | bwd_inner_microstep: 271.32 | bwd_allreduce_microstep: 78.03 | step_microstep: 24.36 +[2025-05-02 02:23:25,012] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2364.04 | bwd: 3522.17 | bwd_inner: 3442.42 | bwd_allreduce: 78.77 | step: 25.55 + 19%|█▉ | 1659/8720 [4:07:58<13:10:57, 6.72s/it] {'loss': 0.626, 'grad_norm': 6.713804721832275, 'learning_rate': 9.341841142083022e-06, 'epoch': 1.9} + 19%|█▉ | 1659/8720 [4:07:58<13:10:57, 6.72s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 02:23:25,494] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.87 | bwd_microstep: 270.30 | bwd_inner_microstep: 270.28 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1935 +[2025-05-02 02:23:25,996] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 194.87 | bwd_microstep: 288.18 | bwd_inner_microstep: 288.16 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 378 +[2025-05-02 02:23:26,234] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 100.00 | bwd_microstep: 118.53 | bwd_inner_microstep: 118.38 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-02 02:23:26,715] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.77 | bwd_microstep: 273.48 | bwd_inner_microstep: 273.46 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 02:23:27,197] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.07 | bwd_microstep: 272.63 | bwd_inner_microstep: 272.61 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 02:23:27,679] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.33 | bwd_microstep: 273.00 | bwd_inner_microstep: 272.98 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 02:23:28,160] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.23 | bwd_microstep: 272.85 | bwd_inner_microstep: 272.83 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 02:23:28,637] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.18 | bwd_microstep: 272.18 | bwd_inner_microstep: 272.16 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 02:23:29,117] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.06 | bwd_microstep: 272.20 | bwd_inner_microstep: 272.19 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 02:23:29,595] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.76 | bwd_microstep: 271.97 | bwd_inner_microstep: 271.96 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 02:23:30,072] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.93 | bwd_microstep: 271.97 | bwd_inner_microstep: 271.95 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 831 +[2025-05-02 02:23:30,311] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 92.93 | bwd_microstep: 130.47 | bwd_inner_microstep: 130.37 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 02:23:30,789] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.79 | bwd_microstep: 270.90 | bwd_inner_microstep: 270.88 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 02:23:31,263] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.31 | bwd_microstep: 271.19 | bwd_inner_microstep: 271.17 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1342 +[2025-05-02 02:23:31,625] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.62 | bwd_microstep: 204.30 | bwd_inner_microstep: 204.28 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 828 +[2025-05-02 02:23:31,965] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.11 | optimizer_step: 16.20 +[2025-05-02 02:23:31,966] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 96.16 | bwd_microstep: 206.01 | bwd_inner_microstep: 130.39 | bwd_allreduce_microstep: 75.52 | step_microstep: 23.74 +[2025-05-02 02:23:31,967] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2693.49 | bwd: 3940.19 | bwd_inner: 3864.11 | bwd_allreduce: 75.70 | step: 24.67 + 19%|█▉ | 1660/8720 [4:08:05<13:19:05, 6.79s/it] {'loss': 0.3845, 'grad_norm': 4.991039276123047, 'learning_rate': 9.340919833761592e-06, 'epoch': 1.9} + 19%|█▉ | 1660/8720 [4:08:05<13:19:05, 6.79s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 02:23:32,447] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.62 | bwd_microstep: 270.10 | bwd_inner_microstep: 270.09 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1946 +[2025-05-02 02:23:32,952] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 198.39 | bwd_microstep: 288.92 | bwd_inner_microstep: 288.91 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.15 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1925 +[2025-05-02 02:23:33,451] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 194.92 | bwd_microstep: 287.11 | bwd_inner_microstep: 287.10 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1907 +[2025-05-02 02:23:33,934] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.75 | bwd_microstep: 276.14 | bwd_inner_microstep: 276.12 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1112 +[2025-05-02 02:23:34,231] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 117.94 | bwd_microstep: 162.12 | bwd_inner_microstep: 161.96 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.11 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1371 +[2025-05-02 02:23:34,598] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 142.83 | bwd_microstep: 207.12 | bwd_inner_microstep: 207.11 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 02:23:35,077] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.30 | bwd_microstep: 272.91 | bwd_inner_microstep: 272.89 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 02:23:35,556] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.26 | bwd_microstep: 272.78 | bwd_inner_microstep: 272.76 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 841 +[2025-05-02 02:23:35,797] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 92.98 | bwd_microstep: 131.97 | bwd_inner_microstep: 131.88 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 326 +[2025-05-02 02:23:36,008] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 76.47 | bwd_microstep: 120.03 | bwd_inner_microstep: 119.72 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 02:23:36,485] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.20 | bwd_microstep: 272.99 | bwd_inner_microstep: 272.97 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 02:23:36,960] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.59 | bwd_microstep: 271.13 | bwd_inner_microstep: 271.11 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 02:23:37,435] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.73 | bwd_microstep: 271.14 | bwd_inner_microstep: 271.13 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 02:23:37,910] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.59 | bwd_microstep: 270.70 | bwd_inner_microstep: 270.69 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 02:23:38,387] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.13 | bwd_microstep: 271.12 | bwd_inner_microstep: 271.10 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 02:23:38,965] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.13 | optimizer_step: 16.34 +[2025-05-02 02:23:38,965] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.65 | bwd_microstep: 347.80 | bwd_inner_microstep: 271.43 | bwd_allreduce_microstep: 76.31 | step_microstep: 24.22 +[2025-05-02 02:23:38,967] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2704.04 | bwd: 3994.14 | bwd_inner: 3917.01 | bwd_allreduce: 76.66 | step: 25.35 + 19%|█▉ | 1661/8720 [4:08:12<13:26:21, 6.85s/it] {'loss': 0.6428, 'grad_norm': 23.983627319335938, 'learning_rate': 9.339997926551425e-06, 'epoch': 1.9} + 19%|█▉ | 1661/8720 [4:08:12<13:26:21, 6.85s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 369 +[2025-05-02 02:23:39,195] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 80.54 | bwd_microstep: 126.00 | bwd_inner_microstep: 125.85 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-02 02:23:39,676] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.25 | bwd_microstep: 273.54 | bwd_inner_microstep: 273.52 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1893 +[2025-05-02 02:23:40,162] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.58 | bwd_microstep: 275.44 | bwd_inner_microstep: 275.42 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-02 02:23:40,644] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.75 | bwd_microstep: 273.42 | bwd_inner_microstep: 273.40 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.13 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-02 02:23:41,126] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.22 | bwd_microstep: 273.55 | bwd_inner_microstep: 273.53 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 02:23:41,607] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.80 | bwd_microstep: 272.41 | bwd_inner_microstep: 272.39 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 02:23:42,086] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.53 | bwd_microstep: 272.25 | bwd_inner_microstep: 272.23 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 02:23:42,564] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.64 | bwd_microstep: 272.28 | bwd_inner_microstep: 272.26 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 02:23:43,041] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.74 | bwd_microstep: 272.77 | bwd_inner_microstep: 272.76 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 02:23:43,517] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.53 | bwd_microstep: 272.56 | bwd_inner_microstep: 272.55 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 02:23:43,993] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.17 | bwd_microstep: 272.62 | bwd_inner_microstep: 272.61 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 834 +[2025-05-02 02:23:44,226] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 91.66 | bwd_microstep: 125.93 | bwd_inner_microstep: 125.66 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 02:23:44,700] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.41 | bwd_microstep: 271.14 | bwd_inner_microstep: 271.13 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 02:23:45,176] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.34 | bwd_microstep: 271.41 | bwd_inner_microstep: 271.40 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.16 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 02:23:45,651] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.52 | bwd_microstep: 271.00 | bwd_inner_microstep: 270.98 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 02:23:46,215] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.21 | optimizer_step: 16.64 +[2025-05-02 02:23:46,216] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.01 | bwd_microstep: 338.32 | bwd_inner_microstep: 271.23 | bwd_allreduce_microstep: 67.04 | step_microstep: 24.03 +[2025-05-02 02:23:46,217] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2812.36 | bwd: 4134.69 | bwd_inner: 4066.97 | bwd_allreduce: 67.29 | step: 25.11 + 19%|█▉ | 1662/8720 [4:08:19<13:40:09, 6.97s/it] {'loss': 0.5702, 'grad_norm': 19.40492820739746, 'learning_rate': 9.339075420579714e-06, 'epoch': 1.91} + 19%|█▉ | 1662/8720 [4:08:19<13:40:09, 6.97s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 3522 +[2025-05-02 02:23:47,032] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 291.64 | bwd_microstep: 503.37 | bwd_inner_microstep: 503.35 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2018 +[2025-05-02 02:23:47,545] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 200.90 | bwd_microstep: 295.88 | bwd_inner_microstep: 295.87 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1917 +[2025-05-02 02:23:48,027] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.30 | bwd_microstep: 276.53 | bwd_inner_microstep: 276.51 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1928 +[2025-05-02 02:23:48,527] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.01 | bwd_microstep: 287.45 | bwd_inner_microstep: 287.43 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1910 +[2025-05-02 02:23:49,011] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.85 | bwd_microstep: 276.48 | bwd_inner_microstep: 276.46 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1934 +[2025-05-02 02:23:49,515] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.37 | bwd_microstep: 288.30 | bwd_inner_microstep: 288.28 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1887 +[2025-05-02 02:23:49,999] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.42 | bwd_microstep: 274.52 | bwd_inner_microstep: 274.51 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-02 02:23:50,483] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.44 | bwd_microstep: 273.71 | bwd_inner_microstep: 273.69 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-02 02:23:50,967] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.78 | bwd_microstep: 273.44 | bwd_inner_microstep: 273.42 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 02:23:51,453] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.64 | bwd_microstep: 273.04 | bwd_inner_microstep: 273.03 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 02:23:51,936] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.10 | bwd_microstep: 273.17 | bwd_inner_microstep: 273.15 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 02:23:52,416] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.93 | bwd_microstep: 273.19 | bwd_inner_microstep: 273.17 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 02:23:52,898] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.09 | bwd_microstep: 272.89 | bwd_inner_microstep: 272.87 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 02:23:53,379] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.97 | bwd_microstep: 272.37 | bwd_inner_microstep: 272.35 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 02:23:53,861] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.15 | bwd_microstep: 271.08 | bwd_inner_microstep: 271.06 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 02:23:54,443] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.09 | optimizer_step: 16.28 +[2025-05-02 02:23:54,444] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.49 | bwd_microstep: 347.44 | bwd_inner_microstep: 271.35 | bwd_allreduce_microstep: 76.03 | step_microstep: 23.85 +[2025-05-02 02:23:54,445] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 3150.65 | bwd: 4732.87 | bwd_inner: 4656.51 | bwd_allreduce: 76.12 | step: 24.70 + 19%|█▉ | 1663/8720 [4:08:28<14:24:25, 7.35s/it] {'loss': 0.8008, 'grad_norm': 6.7441792488098145, 'learning_rate': 9.338152315973728e-06, 'epoch': 1.91} + 19%|█▉ | 1663/8720 [4:08:28<14:24:25, 7.35s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2084 +[2025-05-02 02:23:54,973] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 201.75 | bwd_microstep: 303.49 | bwd_inner_microstep: 303.47 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2067 +[2025-05-02 02:23:55,496] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 201.40 | bwd_microstep: 303.02 | bwd_inner_microstep: 303.01 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1903 +[2025-05-02 02:23:55,983] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.38 | bwd_microstep: 275.89 | bwd_inner_microstep: 275.88 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-02 02:23:56,467] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.82 | bwd_microstep: 274.28 | bwd_inner_microstep: 274.26 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1888 +[2025-05-02 02:23:56,951] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.90 | bwd_microstep: 274.39 | bwd_inner_microstep: 274.37 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-02 02:23:57,440] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.65 | bwd_microstep: 274.27 | bwd_inner_microstep: 274.25 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 02:23:57,925] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.54 | bwd_microstep: 273.01 | bwd_inner_microstep: 272.99 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 02:23:58,404] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.96 | bwd_microstep: 272.67 | bwd_inner_microstep: 272.66 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 842 +[2025-05-02 02:23:58,649] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 97.12 | bwd_microstep: 131.58 | bwd_inner_microstep: 131.31 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 02:23:59,130] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.20 | bwd_microstep: 272.55 | bwd_inner_microstep: 272.53 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 02:23:59,611] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.31 | bwd_microstep: 272.60 | bwd_inner_microstep: 272.58 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 02:24:00,090] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.43 | bwd_microstep: 272.34 | bwd_inner_microstep: 272.33 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 02:24:00,569] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.90 | bwd_microstep: 272.78 | bwd_inner_microstep: 272.77 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 02:24:01,047] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.10 | bwd_microstep: 272.71 | bwd_inner_microstep: 272.69 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 02:24:01,522] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.00 | bwd_microstep: 271.27 | bwd_inner_microstep: 271.25 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 02:24:02,101] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.08 | optimizer_step: 16.28 +[2025-05-02 02:24:02,101] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.19 | bwd_microstep: 348.10 | bwd_inner_microstep: 271.57 | bwd_allreduce_microstep: 76.47 | step_microstep: 24.02 +[2025-05-02 02:24:02,103] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2950.22 | bwd: 4365.01 | bwd_inner: 4287.93 | bwd_allreduce: 76.67 | step: 24.86 + 19%|█▉ | 1664/8720 [4:08:35<14:35:10, 7.44s/it] {'loss': 0.623, 'grad_norm': 22.228418350219727, 'learning_rate': 9.337228612860825e-06, 'epoch': 1.91} + 19%|█▉ | 1664/8720 [4:08:35<14:35:10, 7.44s/it]dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 827 +[2025-05-02 02:24:02,347] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 92.67 | bwd_microstep: 130.10 | bwd_inner_microstep: 129.78 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.08 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1403 +[2025-05-02 02:24:02,715] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 143.26 | bwd_microstep: 210.14 | bwd_inner_microstep: 210.12 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1902 +[2025-05-02 02:24:03,197] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.92 | bwd_microstep: 276.15 | bwd_inner_microstep: 276.13 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-02 02:24:03,677] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.59 | bwd_microstep: 274.21 | bwd_inner_microstep: 274.20 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 02:24:04,157] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.84 | bwd_microstep: 273.53 | bwd_inner_microstep: 273.52 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 333 +[2025-05-02 02:24:04,392] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 88.28 | bwd_microstep: 129.03 | bwd_inner_microstep: 128.79 | bwd_allreduce_microstep: 0.09 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 02:24:04,872] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.66 | bwd_microstep: 272.91 | bwd_inner_microstep: 272.90 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.14 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 02:24:05,351] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.51 | bwd_microstep: 272.60 | bwd_inner_microstep: 272.58 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 02:24:05,835] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.02 | bwd_microstep: 272.39 | bwd_inner_microstep: 272.38 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 02:24:06,317] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.02 | bwd_microstep: 272.35 | bwd_inner_microstep: 272.33 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 02:24:06,801] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.55 | bwd_microstep: 272.71 | bwd_inner_microstep: 272.69 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 02:24:07,287] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.16 | bwd_microstep: 272.84 | bwd_inner_microstep: 272.82 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 02:24:07,764] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.00 | bwd_microstep: 272.50 | bwd_inner_microstep: 272.49 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 02:24:08,239] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.48 | bwd_microstep: 272.44 | bwd_inner_microstep: 272.42 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 02:24:08,716] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.63 | bwd_microstep: 272.79 | bwd_inner_microstep: 272.77 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 02:24:09,283] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.09 | optimizer_step: 16.34 +[2025-05-02 02:24:09,284] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.09 | bwd_microstep: 339.83 | bwd_inner_microstep: 272.74 | bwd_allreduce_microstep: 67.04 | step_microstep: 23.29 +[2025-05-02 02:24:09,285] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2780.31 | bwd: 4086.56 | bwd_inner: 4018.77 | bwd_allreduce: 67.30 | step: 24.21 + 19%|█▉ | 1665/8720 [4:08:43<14:25:49, 7.36s/it] {'loss': 0.6605, 'grad_norm': 13.568042755126953, 'learning_rate': 9.33630431136844e-06, 'epoch': 1.91} + 19%|█▉ | 1665/8720 [4:08:43<14:25:49, 7.36s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1954 +[2025-05-02 02:24:09,791] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 197.27 | bwd_microstep: 289.26 | bwd_inner_microstep: 289.24 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-02 02:24:10,268] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.76 | bwd_microstep: 273.71 | bwd_inner_microstep: 273.70 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-02 02:24:10,745] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.27 | bwd_microstep: 273.59 | bwd_inner_microstep: 273.57 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 02:24:11,222] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.22 | bwd_microstep: 273.03 | bwd_inner_microstep: 273.02 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 02:24:11,703] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.31 | bwd_microstep: 272.81 | bwd_inner_microstep: 272.79 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1361 +[2025-05-02 02:24:12,068] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.81 | bwd_microstep: 207.07 | bwd_inner_microstep: 206.96 | bwd_allreduce_microstep: 0.03 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 02:24:12,547] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.88 | bwd_microstep: 273.00 | bwd_inner_microstep: 272.99 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 02:24:13,025] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.28 | bwd_microstep: 272.48 | bwd_inner_microstep: 272.47 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 02:24:13,503] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.12 | bwd_microstep: 272.85 | bwd_inner_microstep: 272.83 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 834 +[2025-05-02 02:24:13,735] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 91.44 | bwd_microstep: 126.02 | bwd_inner_microstep: 125.93 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 02:24:14,212] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.93 | bwd_microstep: 273.11 | bwd_inner_microstep: 273.09 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 02:24:14,688] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.66 | bwd_microstep: 271.34 | bwd_inner_microstep: 271.33 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 02:24:15,165] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.60 | bwd_microstep: 271.78 | bwd_inner_microstep: 271.76 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.11 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1345 +[2025-05-02 02:24:15,526] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.30 | bwd_microstep: 205.56 | bwd_inner_microstep: 205.51 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.09 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 318 +[2025-05-02 02:24:15,743] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 82.54 | bwd_microstep: 118.89 | bwd_inner_microstep: 118.55 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 02:24:16,320] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.15 | optimizer_step: 16.27 +[2025-05-02 02:24:16,320] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.32 | bwd_microstep: 348.00 | bwd_inner_microstep: 271.70 | bwd_allreduce_microstep: 76.24 | step_microstep: 23.96 +[2025-05-02 02:24:16,321] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2723.43 | bwd: 4022.60 | bwd_inner: 3945.50 | bwd_allreduce: 76.57 | step: 24.87 + 19%|█▉ | 1666/8720 [4:08:50<14:14:13, 7.27s/it] {'loss': 0.6518, 'grad_norm': 7.467089653015137, 'learning_rate': 9.335379411624093e-06, 'epoch': 1.91} + 19%|█▉ | 1666/8720 [4:08:50<14:14:13, 7.27s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1849 +[2025-05-02 02:24:16,803] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.01 | bwd_microstep: 270.79 | bwd_inner_microstep: 270.77 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1954 +[2025-05-02 02:24:17,303] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.57 | bwd_microstep: 289.53 | bwd_inner_microstep: 289.51 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1923 +[2025-05-02 02:24:17,799] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 194.44 | bwd_microstep: 287.05 | bwd_inner_microstep: 287.03 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1918 +[2025-05-02 02:24:18,283] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 191.73 | bwd_microstep: 276.98 | bwd_inner_microstep: 276.96 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1892 +[2025-05-02 02:24:18,762] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.08 | bwd_microstep: 274.57 | bwd_inner_microstep: 274.55 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 340 +[2025-05-02 02:24:18,970] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 72.13 | bwd_microstep: 123.52 | bwd_inner_microstep: 123.30 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1887 +[2025-05-02 02:24:19,449] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.07 | bwd_microstep: 274.60 | bwd_inner_microstep: 274.58 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1368 +[2025-05-02 02:24:19,812] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.51 | bwd_microstep: 207.28 | bwd_inner_microstep: 207.23 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 02:24:20,289] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.04 | bwd_microstep: 273.45 | bwd_inner_microstep: 273.44 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 844 +[2025-05-02 02:24:20,529] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.69 | bwd_microstep: 132.10 | bwd_inner_microstep: 132.01 | bwd_allreduce_microstep: 0.03 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 02:24:21,005] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.16 | bwd_microstep: 272.82 | bwd_inner_microstep: 272.80 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 02:24:21,481] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.16 | bwd_microstep: 273.04 | bwd_inner_microstep: 273.03 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 02:24:21,954] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.44 | bwd_microstep: 270.87 | bwd_inner_microstep: 270.85 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 02:24:22,429] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.56 | bwd_microstep: 271.52 | bwd_inner_microstep: 271.50 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 02:24:22,906] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.66 | bwd_microstep: 271.06 | bwd_inner_microstep: 271.04 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.18 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1340 +[2025-05-02 02:24:23,372] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.13 | optimizer_step: 16.23 +[2025-05-02 02:24:23,373] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 142.73 | bwd_microstep: 280.82 | bwd_inner_microstep: 204.64 | bwd_allreduce_microstep: 76.02 | step_microstep: 23.82 +[2025-05-02 02:24:23,374] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2727.69 | bwd: 4050.05 | bwd_inner: 3973.37 | bwd_allreduce: 76.20 | step: 24.75 + 19%|█▉ | 1667/8720 [4:08:57<14:06:35, 7.20s/it] {'loss': 0.9054, 'grad_norm': 20.427148818969727, 'learning_rate': 9.334453913755388e-06, 'epoch': 1.91} + 19%|█▉ | 1667/8720 [4:08:57<14:06:35, 7.20s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1921 +[2025-05-02 02:24:23,877] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 194.44 | bwd_microstep: 285.98 | bwd_inner_microstep: 285.96 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2113 +[2025-05-02 02:24:24,413] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 204.45 | bwd_microstep: 312.41 | bwd_inner_microstep: 312.39 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1970 +[2025-05-02 02:24:24,919] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 197.10 | bwd_microstep: 291.07 | bwd_inner_microstep: 291.05 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1901 +[2025-05-02 02:24:25,401] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.27 | bwd_microstep: 275.46 | bwd_inner_microstep: 275.44 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-02 02:24:25,881] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.83 | bwd_microstep: 274.23 | bwd_inner_microstep: 274.21 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-02 02:24:26,360] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.12 | bwd_microstep: 273.04 | bwd_inner_microstep: 273.03 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 02:24:26,838] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.09 | bwd_microstep: 272.26 | bwd_inner_microstep: 272.24 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 02:24:27,317] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.71 | bwd_microstep: 272.09 | bwd_inner_microstep: 272.08 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 02:24:27,795] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.20 | bwd_microstep: 270.95 | bwd_inner_microstep: 270.93 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 02:24:28,272] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.33 | bwd_microstep: 272.07 | bwd_inner_microstep: 272.05 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 02:24:28,750] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.70 | bwd_microstep: 271.20 | bwd_inner_microstep: 271.18 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 02:24:29,227] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.93 | bwd_microstep: 271.09 | bwd_inner_microstep: 271.07 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 02:24:29,705] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.42 | bwd_microstep: 271.58 | bwd_inner_microstep: 271.56 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 02:24:30,183] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.12 | bwd_microstep: 271.06 | bwd_inner_microstep: 271.04 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 02:24:30,660] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.95 | bwd_microstep: 271.06 | bwd_inner_microstep: 271.04 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 02:24:31,236] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.15 | optimizer_step: 16.27 +[2025-05-02 02:24:31,236] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.64 | bwd_microstep: 348.01 | bwd_inner_microstep: 271.53 | bwd_allreduce_microstep: 76.43 | step_microstep: 23.59 +[2025-05-02 02:24:31,238] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 3040.95 | bwd: 4503.56 | bwd_inner: 4426.81 | bwd_allreduce: 76.52 | step: 24.53 + 19%|█▉ | 1668/8720 [4:09:04<14:29:43, 7.40s/it] {'loss': 0.5187, 'grad_norm': 12.02083969116211, 'learning_rate': 9.33352781789001e-06, 'epoch': 1.91} + 19%|█▉ | 1668/8720 [4:09:04<14:29:43, 7.40s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2014 +[2025-05-02 02:24:31,752] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 199.68 | bwd_microstep: 294.94 | bwd_inner_microstep: 294.92 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 457 +[2025-05-02 02:24:31,962] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 81.04 | bwd_microstep: 116.58 | bwd_inner_microstep: 116.37 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1883 +[2025-05-02 02:24:32,439] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.21 | bwd_microstep: 274.06 | bwd_inner_microstep: 274.04 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1359 +[2025-05-02 02:24:32,800] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.10 | bwd_microstep: 206.30 | bwd_inner_microstep: 206.28 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.07 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 844 +[2025-05-02 02:24:33,040] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.77 | bwd_microstep: 132.06 | bwd_inner_microstep: 132.04 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 02:24:33,516] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.49 | bwd_microstep: 272.60 | bwd_inner_microstep: 272.58 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 834 +[2025-05-02 02:24:33,747] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 91.14 | bwd_microstep: 125.87 | bwd_inner_microstep: 125.82 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 02:24:34,224] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.80 | bwd_microstep: 272.27 | bwd_inner_microstep: 272.26 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 02:24:34,701] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.36 | bwd_microstep: 272.48 | bwd_inner_microstep: 272.47 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 02:24:35,179] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.36 | bwd_microstep: 272.61 | bwd_inner_microstep: 272.59 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 320 +[2025-05-02 02:24:35,410] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 97.75 | bwd_microstep: 114.85 | bwd_inner_microstep: 114.71 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 02:24:35,887] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.81 | bwd_microstep: 271.13 | bwd_inner_microstep: 271.11 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 834 +[2025-05-02 02:24:36,125] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.87 | bwd_microstep: 125.95 | bwd_inner_microstep: 125.66 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 02:24:36,604] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.80 | bwd_microstep: 272.35 | bwd_inner_microstep: 272.33 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.14 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1344 +[2025-05-02 02:24:36,965] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.02 | bwd_microstep: 204.25 | bwd_inner_microstep: 204.19 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 02:24:37,543] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.12 | optimizer_step: 16.28 +[2025-05-02 02:24:37,544] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.56 | bwd_microstep: 348.24 | bwd_inner_microstep: 271.67 | bwd_allreduce_microstep: 76.52 | step_microstep: 23.89 +[2025-05-02 02:24:37,545] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2445.47 | bwd: 3576.64 | bwd_inner: 3499.17 | bwd_allreduce: 76.85 | step: 25.11 + 19%|█▉ | 1669/8720 [4:09:11<13:51:09, 7.07s/it] {'loss': 0.3685, 'grad_norm': 11.674808502197266, 'learning_rate': 9.332601124155723e-06, 'epoch': 1.91} + 19%|█▉ | 1669/8720 [4:09:11<13:51:09, 7.07s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 02:24:38,026] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.76 | bwd_microstep: 270.77 | bwd_inner_microstep: 270.75 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 429 +[2025-05-02 02:24:38,225] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 67.95 | bwd_microstep: 117.54 | bwd_inner_microstep: 117.41 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1916 +[2025-05-02 02:24:38,708] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 191.11 | bwd_microstep: 276.37 | bwd_inner_microstep: 276.36 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 362 +[2025-05-02 02:24:38,915] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 74.82 | bwd_microstep: 118.37 | bwd_inner_microstep: 118.22 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-02 02:24:39,392] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.89 | bwd_microstep: 273.46 | bwd_inner_microstep: 273.44 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 02:24:39,871] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.84 | bwd_microstep: 273.13 | bwd_inner_microstep: 273.11 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1361 +[2025-05-02 02:24:40,236] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.11 | bwd_microstep: 206.82 | bwd_inner_microstep: 206.79 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 02:24:40,716] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.11 | bwd_microstep: 272.83 | bwd_inner_microstep: 272.82 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 02:24:41,194] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.89 | bwd_microstep: 272.23 | bwd_inner_microstep: 272.21 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 02:24:41,671] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.71 | bwd_microstep: 272.34 | bwd_inner_microstep: 272.32 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 02:24:42,149] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.68 | bwd_microstep: 272.29 | bwd_inner_microstep: 272.27 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 325 +[2025-05-02 02:24:42,385] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.34 | bwd_microstep: 123.94 | bwd_inner_microstep: 123.67 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 02:24:42,864] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.08 | bwd_microstep: 272.36 | bwd_inner_microstep: 272.34 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 02:24:43,342] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.47 | bwd_microstep: 270.94 | bwd_inner_microstep: 270.92 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 317 +[2025-05-02 02:24:43,569] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 84.89 | bwd_microstep: 123.44 | bwd_inner_microstep: 123.28 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1953 +[2025-05-02 02:24:44,175] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.07 | optimizer_gradients: 2.15 | optimizer_step: 16.45 +[2025-05-02 02:24:44,176] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 197.71 | bwd_microstep: 367.39 | bwd_inner_microstep: 290.31 | bwd_allreduce_microstep: 77.03 | step_microstep: 24.59 +[2025-05-02 02:24:44,177] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2542.01 | bwd: 3784.29 | bwd_inner: 3706.38 | bwd_allreduce: 77.36 | step: 25.56 + 19%|█▉ | 1670/8720 [4:09:17<13:35:30, 6.94s/it] {'loss': 0.6478, 'grad_norm': 20.905658721923828, 'learning_rate': 9.33167383268038e-06, 'epoch': 1.92} + 19%|█▉ | 1670/8720 [4:09:17<13:35:30, 6.94s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1895 +[2025-05-02 02:24:44,663] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.53 | bwd_microstep: 274.33 | bwd_inner_microstep: 274.32 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2053 +[2025-05-02 02:24:45,180] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 201.10 | bwd_microstep: 300.83 | bwd_inner_microstep: 300.82 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 899 +[2025-05-02 02:24:45,440] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 100.52 | bwd_microstep: 143.98 | bwd_inner_microstep: 143.96 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1899 +[2025-05-02 02:24:45,921] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.88 | bwd_microstep: 275.09 | bwd_inner_microstep: 275.08 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1899 +[2025-05-02 02:24:46,403] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.37 | bwd_microstep: 275.11 | bwd_inner_microstep: 275.09 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-02 02:24:46,882] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.65 | bwd_microstep: 272.95 | bwd_inner_microstep: 272.94 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 02:24:47,364] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.46 | bwd_microstep: 272.69 | bwd_inner_microstep: 272.67 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 02:24:47,845] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.34 | bwd_microstep: 272.44 | bwd_inner_microstep: 272.42 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 02:24:48,323] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.34 | bwd_microstep: 272.24 | bwd_inner_microstep: 272.22 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1351 +[2025-05-02 02:24:48,691] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.25 | bwd_microstep: 205.70 | bwd_inner_microstep: 205.55 | bwd_allreduce_microstep: 0.10 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 02:24:49,172] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.11 | bwd_microstep: 270.80 | bwd_inner_microstep: 270.79 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 02:24:49,649] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.31 | bwd_microstep: 270.82 | bwd_inner_microstep: 270.81 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 02:24:50,127] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.34 | bwd_microstep: 270.59 | bwd_inner_microstep: 270.57 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 02:24:50,604] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.43 | bwd_microstep: 270.59 | bwd_inner_microstep: 270.57 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 02:24:51,084] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.22 | bwd_microstep: 270.69 | bwd_inner_microstep: 270.67 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 02:24:51,659] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.11 | optimizer_step: 16.33 +[2025-05-02 02:24:51,660] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.85 | bwd_microstep: 347.13 | bwd_inner_microstep: 271.00 | bwd_allreduce_microstep: 76.08 | step_microstep: 23.53 +[2025-05-02 02:24:51,661] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2888.30 | bwd: 4266.03 | bwd_inner: 4189.48 | bwd_allreduce: 76.26 | step: 24.51 + 19%|█▉ | 1671/8720 [4:09:25<13:54:29, 7.10s/it] {'loss': 0.6049, 'grad_norm': 17.767772674560547, 'learning_rate': 9.330745943591915e-06, 'epoch': 1.92} + 19%|█▉ | 1671/8720 [4:09:25<13:54:29, 7.10s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 02:24:52,140] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.92 | bwd_microstep: 270.50 | bwd_inner_microstep: 270.49 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2053 +[2025-05-02 02:24:52,657] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 201.52 | bwd_microstep: 300.58 | bwd_inner_microstep: 300.57 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1905 +[2025-05-02 02:24:53,137] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.08 | bwd_microstep: 275.97 | bwd_inner_microstep: 275.95 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1134 +[2025-05-02 02:24:53,435] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 118.37 | bwd_microstep: 163.54 | bwd_inner_microstep: 163.40 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1883 +[2025-05-02 02:24:53,912] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.32 | bwd_microstep: 273.83 | bwd_inner_microstep: 273.81 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-02 02:24:54,390] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.69 | bwd_microstep: 273.98 | bwd_inner_microstep: 273.97 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-02 02:24:54,868] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.40 | bwd_microstep: 273.63 | bwd_inner_microstep: 273.62 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 852 +[2025-05-02 02:24:55,112] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.62 | bwd_microstep: 132.45 | bwd_inner_microstep: 132.38 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 02:24:55,589] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.88 | bwd_microstep: 272.36 | bwd_inner_microstep: 272.35 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 02:24:56,067] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.33 | bwd_microstep: 272.20 | bwd_inner_microstep: 272.19 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 02:24:56,547] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.51 | bwd_microstep: 272.06 | bwd_inner_microstep: 272.04 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 02:24:57,025] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.06 | bwd_microstep: 272.57 | bwd_inner_microstep: 272.55 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 02:24:57,504] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.40 | bwd_microstep: 272.41 | bwd_inner_microstep: 272.39 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 02:24:57,980] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.73 | bwd_microstep: 270.91 | bwd_inner_microstep: 270.89 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 02:24:58,458] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.36 | bwd_microstep: 270.91 | bwd_inner_microstep: 270.90 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1344 +[2025-05-02 02:24:58,932] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.16 | optimizer_step: 16.35 +[2025-05-02 02:24:58,933] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.99 | bwd_microstep: 289.85 | bwd_inner_microstep: 204.70 | bwd_allreduce_microstep: 85.04 | step_microstep: 24.26 +[2025-05-02 02:24:58,934] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2810.86 | bwd: 4157.83 | bwd_inner: 4072.21 | bwd_allreduce: 85.24 | step: 25.25 + 19%|█▉ | 1672/8720 [4:09:32<14:00:26, 7.15s/it] {'loss': 0.6701, 'grad_norm': 7.367943286895752, 'learning_rate': 9.32981745701834e-06, 'epoch': 1.92} + 19%|█▉ | 1672/8720 [4:09:32<14:00:26, 7.15s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 02:24:59,416] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.44 | bwd_microstep: 270.23 | bwd_inner_microstep: 270.21 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 907 +[2025-05-02 02:24:59,681] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 101.74 | bwd_microstep: 144.46 | bwd_inner_microstep: 144.32 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1902 +[2025-05-02 02:25:00,165] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.26 | bwd_microstep: 275.65 | bwd_inner_microstep: 275.63 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 845 +[2025-05-02 02:25:00,432] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 114.76 | bwd_microstep: 131.05 | bwd_inner_microstep: 131.03 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1369 +[2025-05-02 02:25:00,802] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 145.68 | bwd_microstep: 207.34 | bwd_inner_microstep: 207.32 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 342 +[2025-05-02 02:25:01,015] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 73.03 | bwd_microstep: 126.01 | bwd_inner_microstep: 125.89 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 02:25:01,490] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.43 | bwd_microstep: 272.46 | bwd_inner_microstep: 272.45 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 02:25:01,965] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.79 | bwd_microstep: 272.87 | bwd_inner_microstep: 272.85 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1357 +[2025-05-02 02:25:02,328] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.43 | bwd_microstep: 206.05 | bwd_inner_microstep: 205.94 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 02:25:02,806] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.70 | bwd_microstep: 272.40 | bwd_inner_microstep: 272.38 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 02:25:03,285] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.07 | bwd_microstep: 272.18 | bwd_inner_microstep: 272.16 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 323 +[2025-05-02 02:25:03,528] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 104.70 | bwd_microstep: 117.56 | bwd_inner_microstep: 117.35 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 02:25:04,005] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.30 | bwd_microstep: 271.88 | bwd_inner_microstep: 271.86 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 02:25:04,482] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.41 | bwd_microstep: 272.08 | bwd_inner_microstep: 272.06 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 02:25:04,962] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.95 | bwd_microstep: 271.19 | bwd_inner_microstep: 271.17 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 02:25:05,544] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.21 | optimizer_step: 16.58 +[2025-05-02 02:25:05,545] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.85 | bwd_microstep: 349.61 | bwd_inner_microstep: 272.20 | bwd_allreduce_microstep: 77.36 | step_microstep: 24.53 +[2025-05-02 02:25:05,546] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2560.16 | bwd: 3733.07 | bwd_inner: 3654.92 | bwd_allreduce: 77.64 | step: 25.48 + 19%|█▉ | 1673/8720 [4:09:39<13:41:11, 6.99s/it] {'loss': 0.5651, 'grad_norm': 20.72933578491211, 'learning_rate': 9.328888373087754e-06, 'epoch': 1.92} + 19%|█▉ | 1673/8720 [4:09:39<13:41:11, 6.99s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 02:25:06,028] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.23 | bwd_microstep: 271.08 | bwd_inner_microstep: 271.06 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2141 +[2025-05-02 02:25:06,565] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 203.95 | bwd_microstep: 314.61 | bwd_inner_microstep: 314.60 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1919 +[2025-05-02 02:25:07,047] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.06 | bwd_microstep: 277.04 | bwd_inner_microstep: 277.02 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1906 +[2025-05-02 02:25:07,527] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.82 | bwd_microstep: 275.91 | bwd_inner_microstep: 275.89 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 381 +[2025-05-02 02:25:07,754] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 83.45 | bwd_microstep: 128.17 | bwd_inner_microstep: 127.86 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 344 +[2025-05-02 02:25:07,975] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 83.90 | bwd_microstep: 121.62 | bwd_inner_microstep: 121.46 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1356 +[2025-05-02 02:25:08,340] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.30 | bwd_microstep: 206.43 | bwd_inner_microstep: 206.33 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-02 02:25:08,819] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.56 | bwd_microstep: 273.08 | bwd_inner_microstep: 273.06 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 846 +[2025-05-02 02:25:09,064] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.59 | bwd_microstep: 132.17 | bwd_inner_microstep: 132.04 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 02:25:09,543] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.87 | bwd_microstep: 273.08 | bwd_inner_microstep: 273.07 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 02:25:10,023] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.40 | bwd_microstep: 272.61 | bwd_inner_microstep: 272.60 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 02:25:10,501] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.76 | bwd_microstep: 272.38 | bwd_inner_microstep: 272.37 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 02:25:10,980] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.66 | bwd_microstep: 272.59 | bwd_inner_microstep: 272.57 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 02:25:11,459] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.95 | bwd_microstep: 272.80 | bwd_inner_microstep: 272.78 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 02:25:11,939] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.45 | bwd_microstep: 272.30 | bwd_inner_microstep: 272.28 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 830 +[2025-05-02 02:25:12,286] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.14 | optimizer_step: 16.25 +[2025-05-02 02:25:12,287] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.04 | bwd_microstep: 213.29 | bwd_inner_microstep: 137.15 | bwd_allreduce_microstep: 76.04 | step_microstep: 23.89 +[2025-05-02 02:25:12,288] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2587.66 | bwd: 3849.27 | bwd_inner: 3772.26 | bwd_allreduce: 76.39 | step: 24.81 + 19%|█▉ | 1674/8720 [4:09:46<13:32:15, 6.92s/it] {'loss': 0.7339, 'grad_norm': 8.358673095703125, 'learning_rate': 9.327958691928334e-06, 'epoch': 1.92} + 19%|█▉ | 1674/8720 [4:09:46<13:32:15, 6.92s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1908 +[2025-05-02 02:25:12,777] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.21 | bwd_microstep: 275.91 | bwd_inner_microstep: 275.90 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1904 +[2025-05-02 02:25:13,262] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.11 | bwd_microstep: 275.90 | bwd_inner_microstep: 275.88 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-02 02:25:13,746] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.08 | bwd_microstep: 274.29 | bwd_inner_microstep: 274.27 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-02 02:25:14,226] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.70 | bwd_microstep: 273.64 | bwd_inner_microstep: 273.62 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 843 +[2025-05-02 02:25:14,499] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.01 | bwd_microstep: 159.80 | bwd_inner_microstep: 159.49 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 02:25:14,978] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.22 | bwd_microstep: 272.80 | bwd_inner_microstep: 272.79 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 02:25:15,459] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.63 | bwd_microstep: 272.20 | bwd_inner_microstep: 272.19 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 02:25:15,940] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.65 | bwd_microstep: 272.39 | bwd_inner_microstep: 272.37 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 02:25:16,418] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.21 | bwd_microstep: 272.58 | bwd_inner_microstep: 272.57 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 02:25:16,896] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.61 | bwd_microstep: 272.67 | bwd_inner_microstep: 272.65 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 02:25:17,372] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.00 | bwd_microstep: 272.47 | bwd_inner_microstep: 272.46 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 831 +[2025-05-02 02:25:17,621] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.05 | bwd_microstep: 141.33 | bwd_inner_microstep: 141.01 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 02:25:18,096] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.92 | bwd_microstep: 272.48 | bwd_inner_microstep: 272.46 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 02:25:18,573] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.95 | bwd_microstep: 272.30 | bwd_inner_microstep: 272.28 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 02:25:19,048] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.74 | bwd_microstep: 271.22 | bwd_inner_microstep: 271.20 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 02:25:19,624] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.14 | optimizer_step: 16.27 +[2025-05-02 02:25:19,624] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.09 | bwd_microstep: 347.06 | bwd_inner_microstep: 271.60 | bwd_allreduce_microstep: 75.41 | step_microstep: 23.87 +[2025-05-02 02:25:19,626] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2829.82 | bwd: 4199.13 | bwd_inner: 4122.85 | bwd_allreduce: 75.73 | step: 24.95 + 19%|█▉ | 1675/8720 [4:09:53<13:46:58, 7.04s/it] {'loss': 0.2922, 'grad_norm': 6.7699384689331055, 'learning_rate': 9.327028413668344e-06, 'epoch': 1.92} + 19%|█▉ | 1675/8720 [4:09:53<13:46:58, 7.04s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 02:25:20,107] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.19 | bwd_microstep: 270.52 | bwd_inner_microstep: 270.51 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 916 +[2025-05-02 02:25:20,370] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 103.07 | bwd_microstep: 145.28 | bwd_inner_microstep: 145.15 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.08 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 891 +[2025-05-02 02:25:20,624] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 97.45 | bwd_microstep: 141.79 | bwd_inner_microstep: 141.46 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1886 +[2025-05-02 02:25:21,101] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.30 | bwd_microstep: 274.39 | bwd_inner_microstep: 274.37 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-02 02:25:21,581] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.41 | bwd_microstep: 274.01 | bwd_inner_microstep: 273.99 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-02 02:25:22,059] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.50 | bwd_microstep: 274.45 | bwd_inner_microstep: 274.44 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-02 02:25:22,540] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.62 | bwd_microstep: 273.27 | bwd_inner_microstep: 273.25 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-02 02:25:23,019] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.38 | bwd_microstep: 273.93 | bwd_inner_microstep: 273.91 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 02:25:23,500] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.32 | bwd_microstep: 272.97 | bwd_inner_microstep: 272.96 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 02:25:23,984] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.13 | bwd_microstep: 273.18 | bwd_inner_microstep: 273.16 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 02:25:24,465] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.11 | bwd_microstep: 272.61 | bwd_inner_microstep: 272.59 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 02:25:24,942] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.15 | bwd_microstep: 272.54 | bwd_inner_microstep: 272.52 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 02:25:25,422] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.27 | bwd_microstep: 272.40 | bwd_inner_microstep: 272.38 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1093 +[2025-05-02 02:25:25,714] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 114.58 | bwd_microstep: 161.21 | bwd_inner_microstep: 161.07 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 02:25:26,192] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.26 | bwd_microstep: 271.92 | bwd_inner_microstep: 271.90 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 317 +[2025-05-02 02:25:26,561] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.08 | optimizer_step: 16.26 +[2025-05-02 02:25:26,562] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 89.29 | bwd_microstep: 241.09 | bwd_inner_microstep: 164.79 | bwd_allreduce_microstep: 76.14 | step_microstep: 23.77 +[2025-05-02 02:25:26,563] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2664.67 | bwd: 3965.64 | bwd_inner: 3888.61 | bwd_allreduce: 76.41 | step: 25.07 + 19%|█▉ | 1676/8720 [4:10:00<13:43:08, 7.01s/it] {'loss': 0.8053, 'grad_norm': 6.412970066070557, 'learning_rate': 9.32609753843613e-06, 'epoch': 1.92} + 19%|█▉ | 1676/8720 [4:10:00<13:43:08, 7.01s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1850 +[2025-05-02 02:25:27,044] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.97 | bwd_microstep: 270.46 | bwd_inner_microstep: 270.43 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1921 +[2025-05-02 02:25:27,545] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 194.87 | bwd_microstep: 287.37 | bwd_inner_microstep: 287.35 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1403 +[2025-05-02 02:25:27,914] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 142.40 | bwd_microstep: 210.21 | bwd_inner_microstep: 210.19 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 381 +[2025-05-02 02:25:28,171] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 82.64 | bwd_microstep: 157.73 | bwd_inner_microstep: 157.57 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1922 +[2025-05-02 02:25:28,670] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.17 | bwd_microstep: 286.61 | bwd_inner_microstep: 286.59 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1358 +[2025-05-02 02:25:29,032] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.24 | bwd_microstep: 206.13 | bwd_inner_microstep: 205.93 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 02:25:29,509] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.63 | bwd_microstep: 272.82 | bwd_inner_microstep: 272.80 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 846 +[2025-05-02 02:25:29,767] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.82 | bwd_microstep: 149.85 | bwd_inner_microstep: 149.59 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.10 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 837 +[2025-05-02 02:25:30,025] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 96.23 | bwd_microstep: 144.88 | bwd_inner_microstep: 144.62 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 02:25:30,503] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.24 | bwd_microstep: 272.66 | bwd_inner_microstep: 272.65 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 835 +[2025-05-02 02:25:30,759] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 96.59 | bwd_microstep: 142.79 | bwd_inner_microstep: 142.63 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 02:25:31,237] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.41 | bwd_microstep: 271.30 | bwd_inner_microstep: 271.28 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 02:25:31,716] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.61 | bwd_microstep: 270.96 | bwd_inner_microstep: 270.94 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 02:25:32,196] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.68 | bwd_microstep: 271.11 | bwd_inner_microstep: 271.09 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 02:25:32,678] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.53 | bwd_microstep: 271.04 | bwd_inner_microstep: 271.02 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 02:25:33,263] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.13 | optimizer_step: 16.31 +[2025-05-02 02:25:33,264] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.52 | bwd_microstep: 353.42 | bwd_inner_microstep: 271.46 | bwd_allreduce_microstep: 81.90 | step_microstep: 24.04 +[2025-05-02 02:25:33,265] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2546.21 | bwd: 3839.41 | bwd_inner: 3756.32 | bwd_allreduce: 82.39 | step: 25.24 + 19%|█▉ | 1677/8720 [4:10:07<13:32:07, 6.92s/it] {'loss': 0.7251, 'grad_norm': 6.491570949554443, 'learning_rate': 9.325166066360116e-06, 'epoch': 1.92} + 19%|█▉ | 1677/8720 [4:10:07<13:32:07, 6.92s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1931 +[2025-05-02 02:25:33,771] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.82 | bwd_microstep: 287.43 | bwd_inner_microstep: 287.41 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2089 +[2025-05-02 02:25:34,301] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 205.14 | bwd_microstep: 304.95 | bwd_inner_microstep: 304.93 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1921 +[2025-05-02 02:25:34,805] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.38 | bwd_microstep: 287.23 | bwd_inner_microstep: 287.22 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1362 +[2025-05-02 02:25:35,171] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.50 | bwd_microstep: 206.53 | bwd_inner_microstep: 206.41 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 02:25:35,651] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.84 | bwd_microstep: 273.53 | bwd_inner_microstep: 273.52 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 02:25:36,130] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.27 | bwd_microstep: 272.81 | bwd_inner_microstep: 272.79 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 02:25:36,610] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.80 | bwd_microstep: 273.30 | bwd_inner_microstep: 273.28 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 02:25:37,090] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.82 | bwd_microstep: 272.94 | bwd_inner_microstep: 272.92 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 02:25:37,571] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.52 | bwd_microstep: 272.76 | bwd_inner_microstep: 272.75 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 02:25:38,050] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.74 | bwd_microstep: 272.68 | bwd_inner_microstep: 272.66 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 02:25:38,532] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.58 | bwd_microstep: 272.53 | bwd_inner_microstep: 272.51 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1353 +[2025-05-02 02:25:38,896] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.05 | bwd_microstep: 206.41 | bwd_inner_microstep: 206.23 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.12 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 832 +[2025-05-02 02:25:39,136] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.38 | bwd_microstep: 130.57 | bwd_inner_microstep: 130.35 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 02:25:39,611] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.32 | bwd_microstep: 270.87 | bwd_inner_microstep: 270.85 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 02:25:40,088] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.36 | bwd_microstep: 271.16 | bwd_inner_microstep: 271.15 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 02:25:40,672] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.11 | optimizer_step: 16.26 +[2025-05-02 02:25:40,672] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.32 | bwd_microstep: 354.23 | bwd_inner_microstep: 271.79 | bwd_allreduce_microstep: 82.39 | step_microstep: 23.78 +[2025-05-02 02:25:40,674] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2857.49 | bwd: 4229.99 | bwd_inner: 4146.78 | bwd_allreduce: 82.74 | step: 24.89 + 19%|█▉ | 1678/8720 [4:10:14<13:49:15, 7.07s/it] {'loss': 0.3715, 'grad_norm': 17.032575607299805, 'learning_rate': 9.324233997568813e-06, 'epoch': 1.92} + 19%|█▉ | 1678/8720 [4:10:14<13:49:15, 7.07s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1850 +[2025-05-02 02:25:41,154] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.65 | bwd_microstep: 270.15 | bwd_inner_microstep: 270.14 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 879 +[2025-05-02 02:25:41,405] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 98.11 | bwd_microstep: 134.98 | bwd_inner_microstep: 134.90 | bwd_allreduce_microstep: 0.04 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1915 +[2025-05-02 02:25:41,888] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.72 | bwd_microstep: 276.80 | bwd_inner_microstep: 276.78 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 847 +[2025-05-02 02:25:42,132] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.84 | bwd_microstep: 132.84 | bwd_inner_microstep: 132.60 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 341 +[2025-05-02 02:25:42,358] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 89.65 | bwd_microstep: 120.28 | bwd_inner_microstep: 120.03 | bwd_allreduce_microstep: 0.09 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 02:25:42,837] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.29 | bwd_microstep: 272.96 | bwd_inner_microstep: 272.95 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 02:25:43,316] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.15 | bwd_microstep: 272.70 | bwd_inner_microstep: 272.69 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 02:25:43,794] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.29 | bwd_microstep: 272.72 | bwd_inner_microstep: 272.70 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 02:25:44,275] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.83 | bwd_microstep: 273.04 | bwd_inner_microstep: 273.02 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 02:25:44,754] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.14 | bwd_microstep: 272.29 | bwd_inner_microstep: 272.27 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 02:25:45,232] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.51 | bwd_microstep: 272.65 | bwd_inner_microstep: 272.63 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 319 +[2025-05-02 02:25:45,434] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 73.52 | bwd_microstep: 115.50 | bwd_inner_microstep: 115.37 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 02:25:45,909] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.27 | bwd_microstep: 271.62 | bwd_inner_microstep: 271.59 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1286 +[2025-05-02 02:25:46,259] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 135.69 | bwd_microstep: 199.89 | bwd_inner_microstep: 199.79 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1940 +[2025-05-02 02:25:46,759] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 197.05 | bwd_microstep: 288.91 | bwd_inner_microstep: 288.89 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1907 +[2025-05-02 02:25:47,328] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.04 | optimizer_gradients: 2.14 | optimizer_step: 16.28 +[2025-05-02 02:25:47,329] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.58 | bwd_microstep: 342.09 | bwd_inner_microstep: 276.74 | bwd_allreduce_microstep: 65.30 | step_microstep: 23.22 +[2025-05-02 02:25:47,330] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2571.97 | bwd: 3789.51 | bwd_inner: 3723.19 | bwd_allreduce: 65.74 | step: 24.24 + 19%|█▉ | 1679/8720 [4:10:21<13:34:40, 6.94s/it] {'loss': 0.7021, 'grad_norm': 6.196946144104004, 'learning_rate': 9.323301332190811e-06, 'epoch': 1.93} + 19%|█▉ | 1679/8720 [4:10:21<13:34:40, 6.94s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 02:25:47,811] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.52 | bwd_microstep: 272.68 | bwd_inner_microstep: 272.66 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 419 +[2025-05-02 02:25:48,016] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 75.17 | bwd_microstep: 116.15 | bwd_inner_microstep: 115.90 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1916 +[2025-05-02 02:25:48,497] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.85 | bwd_microstep: 276.70 | bwd_inner_microstep: 276.68 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-02 02:25:48,977] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.77 | bwd_microstep: 274.12 | bwd_inner_microstep: 274.10 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 347 +[2025-05-02 02:25:49,196] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 86.92 | bwd_microstep: 116.39 | bwd_inner_microstep: 116.23 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.10 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 352 +[2025-05-02 02:25:49,440] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 88.77 | bwd_microstep: 138.79 | bwd_inner_microstep: 138.46 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-02 02:25:49,920] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.93 | bwd_microstep: 273.53 | bwd_inner_microstep: 273.51 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-02 02:25:50,400] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.02 | bwd_microstep: 273.87 | bwd_inner_microstep: 273.85 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 02:25:50,880] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.68 | bwd_microstep: 272.91 | bwd_inner_microstep: 272.89 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 02:25:51,362] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.05 | bwd_microstep: 272.44 | bwd_inner_microstep: 272.42 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 02:25:51,841] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.12 | bwd_microstep: 272.55 | bwd_inner_microstep: 272.53 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 02:25:52,324] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.95 | bwd_microstep: 272.58 | bwd_inner_microstep: 272.56 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 02:25:52,805] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.78 | bwd_microstep: 272.33 | bwd_inner_microstep: 272.31 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 835 +[2025-05-02 02:25:53,040] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.74 | bwd_microstep: 126.17 | bwd_inner_microstep: 126.02 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.09 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1345 +[2025-05-02 02:25:53,404] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.91 | bwd_microstep: 205.46 | bwd_inner_microstep: 205.30 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 02:25:53,985] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.12 | optimizer_step: 16.34 +[2025-05-02 02:25:53,985] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.32 | bwd_microstep: 351.51 | bwd_inner_microstep: 271.61 | bwd_allreduce_microstep: 79.85 | step_microstep: 24.08 +[2025-05-02 02:25:53,987] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2562.14 | bwd: 3788.28 | bwd_inner: 3707.20 | bwd_allreduce: 80.35 | step: 25.13 + 19%|█▉ | 1680/8720 [4:10:27<13:24:34, 6.86s/it] {'loss': 0.6217, 'grad_norm': 6.020155906677246, 'learning_rate': 9.322368070354787e-06, 'epoch': 1.93} + 19%|█▉ | 1680/8720 [4:10:27<13:24:34, 6.86s/it]dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1341 +[2025-05-02 02:25:54,354] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.32 | bwd_microstep: 204.08 | bwd_inner_microstep: 203.85 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1906 +[2025-05-02 02:25:54,836] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.47 | bwd_microstep: 276.10 | bwd_inner_microstep: 276.08 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1894 +[2025-05-02 02:25:55,321] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.32 | bwd_microstep: 275.00 | bwd_inner_microstep: 274.98 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 02:25:55,805] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.75 | bwd_microstep: 272.89 | bwd_inner_microstep: 272.88 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 02:25:56,286] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.51 | bwd_microstep: 272.97 | bwd_inner_microstep: 272.95 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 02:25:56,766] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.50 | bwd_microstep: 272.74 | bwd_inner_microstep: 272.72 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 328 +[2025-05-02 02:25:56,981] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 82.06 | bwd_microstep: 118.16 | bwd_inner_microstep: 118.00 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 02:25:57,460] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.95 | bwd_microstep: 273.18 | bwd_inner_microstep: 273.16 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 02:25:57,940] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.15 | bwd_microstep: 272.28 | bwd_inner_microstep: 272.26 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 02:25:58,421] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.22 | bwd_microstep: 272.86 | bwd_inner_microstep: 272.85 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 02:25:58,899] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.60 | bwd_microstep: 272.74 | bwd_inner_microstep: 272.72 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 02:25:59,378] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.14 | bwd_microstep: 272.44 | bwd_inner_microstep: 272.42 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 02:25:59,856] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.54 | bwd_microstep: 272.17 | bwd_inner_microstep: 272.15 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 02:26:00,334] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.12 | bwd_microstep: 272.62 | bwd_inner_microstep: 272.60 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1086 +[2025-05-02 02:26:00,622] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 114.46 | bwd_microstep: 159.88 | bwd_inner_microstep: 159.84 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 02:26:01,187] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.15 | optimizer_step: 16.38 +[2025-05-02 02:26:01,188] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.28 | bwd_microstep: 338.35 | bwd_inner_microstep: 271.67 | bwd_allreduce_microstep: 66.63 | step_microstep: 23.85 +[2025-05-02 02:26:01,189] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2792.03 | bwd: 4098.51 | bwd_inner: 4031.19 | bwd_allreduce: 66.89 | step: 24.77 + 19%|█▉ | 1681/8720 [4:10:34<13:36:34, 6.96s/it] {'loss': 0.8566, 'grad_norm': 25.541332244873047, 'learning_rate': 9.321434212189493e-06, 'epoch': 1.93} + 19%|█▉ | 1681/8720 [4:10:34<13:36:34, 6.96s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 02:26:01,668] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.37 | bwd_microstep: 270.59 | bwd_inner_microstep: 270.57 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1371 +[2025-05-02 02:26:02,032] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.81 | bwd_microstep: 207.90 | bwd_inner_microstep: 207.88 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-02 02:26:02,510] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.33 | bwd_microstep: 273.38 | bwd_inner_microstep: 273.37 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 336 +[2025-05-02 02:26:02,739] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 87.97 | bwd_microstep: 125.32 | bwd_inner_microstep: 125.10 | bwd_allreduce_microstep: 0.08 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-02 02:26:03,218] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.18 | bwd_microstep: 274.14 | bwd_inner_microstep: 274.13 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-02 02:26:03,700] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.75 | bwd_microstep: 274.27 | bwd_inner_microstep: 274.26 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.11 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 840 +[2025-05-02 02:26:03,949] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.83 | bwd_microstep: 136.53 | bwd_inner_microstep: 136.40 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 02:26:04,428] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.58 | bwd_microstep: 272.84 | bwd_inner_microstep: 272.83 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 02:26:04,907] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.47 | bwd_microstep: 272.76 | bwd_inner_microstep: 272.75 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 02:26:05,386] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.62 | bwd_microstep: 273.01 | bwd_inner_microstep: 272.99 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 02:26:05,864] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.91 | bwd_microstep: 272.85 | bwd_inner_microstep: 272.83 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 02:26:06,341] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.79 | bwd_microstep: 271.89 | bwd_inner_microstep: 271.87 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 02:26:06,817] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.70 | bwd_microstep: 272.09 | bwd_inner_microstep: 272.08 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 02:26:07,292] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.60 | bwd_microstep: 271.13 | bwd_inner_microstep: 271.11 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 831 +[2025-05-02 02:26:07,532] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.92 | bwd_microstep: 130.03 | bwd_inner_microstep: 129.74 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 02:26:08,097] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.13 | optimizer_step: 16.38 +[2025-05-02 02:26:08,098] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.18 | bwd_microstep: 337.69 | bwd_inner_microstep: 271.07 | bwd_allreduce_microstep: 66.57 | step_microstep: 23.52 +[2025-05-02 02:26:08,099] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2679.68 | bwd: 3936.49 | bwd_inner: 3869.08 | bwd_allreduce: 66.87 | step: 24.63 + 19%|█▉ | 1682/8720 [4:10:41<13:34:39, 6.95s/it] {'loss': 0.3923, 'grad_norm': 6.526767253875732, 'learning_rate': 9.320499757823772e-06, 'epoch': 1.93} + 19%|█▉ | 1682/8720 [4:10:41<13:34:39, 6.95s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 02:26:08,578] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.89 | bwd_microstep: 270.71 | bwd_inner_microstep: 270.69 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1978 +[2025-05-02 02:26:09,084] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 199.34 | bwd_microstep: 291.63 | bwd_inner_microstep: 291.61 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1911 +[2025-05-02 02:26:09,566] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.80 | bwd_microstep: 276.71 | bwd_inner_microstep: 276.70 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1116 +[2025-05-02 02:26:09,862] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 118.30 | bwd_microstep: 162.65 | bwd_inner_microstep: 162.58 | bwd_allreduce_microstep: 0.03 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 02:26:10,341] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.65 | bwd_microstep: 273.19 | bwd_inner_microstep: 273.17 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 02:26:10,821] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.06 | bwd_microstep: 272.50 | bwd_inner_microstep: 272.48 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 324 +[2025-05-02 02:26:11,043] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 81.28 | bwd_microstep: 124.65 | bwd_inner_microstep: 124.37 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 02:26:11,521] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.89 | bwd_microstep: 272.85 | bwd_inner_microstep: 272.83 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 02:26:12,000] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.36 | bwd_microstep: 272.59 | bwd_inner_microstep: 272.57 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 02:26:12,480] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.67 | bwd_microstep: 272.59 | bwd_inner_microstep: 272.57 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 02:26:12,959] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.30 | bwd_microstep: 271.02 | bwd_inner_microstep: 271.00 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 02:26:13,437] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.26 | bwd_microstep: 271.41 | bwd_inner_microstep: 271.40 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1346 +[2025-05-02 02:26:13,801] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.58 | bwd_microstep: 205.20 | bwd_inner_microstep: 205.03 | bwd_allreduce_microstep: 0.08 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 02:26:14,277] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.60 | bwd_microstep: 270.88 | bwd_inner_microstep: 270.86 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 02:26:14,755] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.09 | bwd_microstep: 271.08 | bwd_inner_microstep: 271.06 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 02:26:15,337] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.12 | optimizer_step: 16.30 +[2025-05-02 02:26:15,338] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.78 | bwd_microstep: 348.38 | bwd_inner_microstep: 271.30 | bwd_allreduce_microstep: 77.03 | step_microstep: 23.99 +[2025-05-02 02:26:15,339] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2802.51 | bwd: 4128.08 | bwd_inner: 4050.29 | bwd_allreduce: 77.35 | step: 24.87 + 19%|█▉ | 1683/8720 [4:10:49<13:45:00, 7.03s/it] {'loss': 0.4351, 'grad_norm': 15.722221374511719, 'learning_rate': 9.31956470738654e-06, 'epoch': 1.93} + 19%|█▉ | 1683/8720 [4:10:49<13:45:00, 7.03s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1949 +[2025-05-02 02:26:15,847] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.54 | bwd_microstep: 288.54 | bwd_inner_microstep: 288.52 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2128 +[2025-05-02 02:26:16,384] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 205.38 | bwd_microstep: 313.60 | bwd_inner_microstep: 313.58 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1903 +[2025-05-02 02:26:16,871] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.34 | bwd_microstep: 276.38 | bwd_inner_microstep: 276.37 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 357 +[2025-05-02 02:26:17,087] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 80.46 | bwd_microstep: 120.29 | bwd_inner_microstep: 120.09 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-02 02:26:17,568] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.19 | bwd_microstep: 275.00 | bwd_inner_microstep: 274.98 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 344 +[2025-05-02 02:26:17,796] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 84.57 | bwd_microstep: 129.01 | bwd_inner_microstep: 128.84 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 02:26:18,274] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.45 | bwd_microstep: 272.58 | bwd_inner_microstep: 272.56 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 02:26:18,754] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.33 | bwd_microstep: 273.01 | bwd_inner_microstep: 273.00 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1097 +[2025-05-02 02:26:19,053] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 118.97 | bwd_microstep: 161.34 | bwd_inner_microstep: 161.14 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 02:26:19,533] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.81 | bwd_microstep: 272.74 | bwd_inner_microstep: 272.73 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 02:26:20,015] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.16 | bwd_microstep: 272.49 | bwd_inner_microstep: 272.47 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1349 +[2025-05-02 02:26:20,382] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.35 | bwd_microstep: 205.90 | bwd_inner_microstep: 205.84 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 02:26:20,861] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.15 | bwd_microstep: 272.57 | bwd_inner_microstep: 272.56 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 02:26:21,341] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.14 | bwd_microstep: 272.42 | bwd_inner_microstep: 272.40 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 02:26:21,818] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.09 | bwd_microstep: 271.20 | bwd_inner_microstep: 271.18 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 318 +[2025-05-02 02:26:22,168] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.14 | optimizer_step: 16.42 +[2025-05-02 02:26:22,169] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.09 | bwd_microstep: 213.80 | bwd_inner_microstep: 136.68 | bwd_allreduce_microstep: 76.97 | step_microstep: 24.34 +[2025-05-02 02:26:22,170] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2618.62 | bwd: 3890.94 | bwd_inner: 3813.12 | bwd_allreduce: 77.28 | step: 25.35 + 19%|█▉ | 1684/8720 [4:10:55<13:37:42, 6.97s/it] {'loss': 0.5879, 'grad_norm': 8.877652168273926, 'learning_rate': 9.318629061006803e-06, 'epoch': 1.93} + 19%|█▉ | 1684/8720 [4:10:55<13:37:42, 6.97s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 02:26:22,653] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.26 | bwd_microstep: 270.47 | bwd_inner_microstep: 270.46 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1902 +[2025-05-02 02:26:23,138] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.50 | bwd_microstep: 275.96 | bwd_inner_microstep: 275.95 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 02:26:23,618] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.81 | bwd_microstep: 273.06 | bwd_inner_microstep: 273.04 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 02:26:24,096] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.54 | bwd_microstep: 272.72 | bwd_inner_microstep: 272.70 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 840 +[2025-05-02 02:26:24,341] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 91.88 | bwd_microstep: 139.00 | bwd_inner_microstep: 138.72 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 02:26:24,818] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.95 | bwd_microstep: 272.75 | bwd_inner_microstep: 272.73 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1349 +[2025-05-02 02:26:25,182] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.81 | bwd_microstep: 205.95 | bwd_inner_microstep: 205.69 | bwd_allreduce_microstep: 0.14 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 02:26:25,664] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.85 | bwd_microstep: 272.62 | bwd_inner_microstep: 272.60 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 02:26:26,145] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.29 | bwd_microstep: 272.26 | bwd_inner_microstep: 272.24 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-02 02:26:26,632] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.26 | bwd_microstep: 273.52 | bwd_inner_microstep: 273.51 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 02:26:27,110] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.72 | bwd_microstep: 271.65 | bwd_inner_microstep: 271.64 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 02:26:27,589] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.65 | bwd_microstep: 272.39 | bwd_inner_microstep: 272.37 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 02:26:28,068] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.02 | bwd_microstep: 271.54 | bwd_inner_microstep: 271.52 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 316 +[2025-05-02 02:26:28,299] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 83.21 | bwd_microstep: 131.11 | bwd_inner_microstep: 130.77 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 02:26:28,775] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.30 | bwd_microstep: 271.08 | bwd_inner_microstep: 271.06 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 02:26:29,355] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.15 | optimizer_step: 16.52 +[2025-05-02 02:26:29,356] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.95 | bwd_microstep: 348.99 | bwd_inner_microstep: 271.65 | bwd_allreduce_microstep: 77.28 | step_microstep: 24.40 +[2025-05-02 02:26:29,357] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2765.64 | bwd: 4095.17 | bwd_inner: 4016.78 | bwd_allreduce: 77.77 | step: 25.81 + 19%|█▉ | 1685/8720 [4:11:03<13:45:07, 7.04s/it] {'loss': 0.392, 'grad_norm': 23.519620895385742, 'learning_rate': 9.317692818813643e-06, 'epoch': 1.93} + 19%|█▉ | 1685/8720 [4:11:03<13:45:07, 7.04s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 02:26:29,838] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.71 | bwd_microstep: 270.23 | bwd_inner_microstep: 270.21 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1935 +[2025-05-02 02:26:30,339] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.39 | bwd_microstep: 288.00 | bwd_inner_microstep: 287.98 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1894 +[2025-05-02 02:26:30,822] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.89 | bwd_microstep: 274.53 | bwd_inner_microstep: 274.51 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-02 02:26:31,305] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.53 | bwd_microstep: 273.95 | bwd_inner_microstep: 273.94 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 02:26:31,784] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.30 | bwd_microstep: 271.91 | bwd_inner_microstep: 271.89 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 332 +[2025-05-02 02:26:32,020] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.38 | bwd_microstep: 123.17 | bwd_inner_microstep: 122.96 | bwd_allreduce_microstep: 0.08 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 02:26:32,503] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.26 | bwd_microstep: 272.73 | bwd_inner_microstep: 272.71 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 02:26:32,985] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.33 | bwd_microstep: 272.49 | bwd_inner_microstep: 272.48 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 02:26:33,467] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.54 | bwd_microstep: 272.40 | bwd_inner_microstep: 272.38 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 02:26:33,946] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.58 | bwd_microstep: 272.88 | bwd_inner_microstep: 272.86 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 02:26:34,427] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.82 | bwd_microstep: 272.50 | bwd_inner_microstep: 272.49 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 02:26:34,906] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.55 | bwd_microstep: 272.47 | bwd_inner_microstep: 272.45 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.14 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 02:26:35,387] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.48 | bwd_microstep: 272.47 | bwd_inner_microstep: 272.45 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 02:26:35,867] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.01 | bwd_microstep: 272.15 | bwd_inner_microstep: 272.13 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 02:26:36,349] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.96 | bwd_microstep: 272.58 | bwd_inner_microstep: 272.57 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 02:26:36,933] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.51 | optimizer_step: 16.28 +[2025-05-02 02:26:36,934] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.05 | bwd_microstep: 353.94 | bwd_inner_microstep: 272.82 | bwd_allreduce_microstep: 81.07 | step_microstep: 24.31 +[2025-05-02 02:26:36,935] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2929.35 | bwd: 4308.44 | bwd_inner: 4226.86 | bwd_allreduce: 81.24 | step: 25.32 + 19%|█▉ | 1686/8720 [4:11:10<14:04:00, 7.20s/it] {'loss': 0.6201, 'grad_norm': 9.744917869567871, 'learning_rate': 9.316755980936231e-06, 'epoch': 1.93} + 19%|█▉ | 1686/8720 [4:11:10<14:04:00, 7.20s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1935 +[2025-05-02 02:26:37,440] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 194.80 | bwd_microstep: 287.41 | bwd_inner_microstep: 287.40 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 459 +[2025-05-02 02:26:37,673] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 84.89 | bwd_microstep: 132.34 | bwd_inner_microstep: 132.19 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1953 +[2025-05-02 02:26:38,175] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.99 | bwd_microstep: 289.22 | bwd_inner_microstep: 289.20 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 388 +[2025-05-02 02:26:38,430] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 97.66 | bwd_microstep: 140.56 | bwd_inner_microstep: 140.41 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1911 +[2025-05-02 02:26:38,915] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.42 | bwd_microstep: 277.24 | bwd_inner_microstep: 277.23 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1928 +[2025-05-02 02:26:39,415] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.48 | bwd_microstep: 287.53 | bwd_inner_microstep: 287.51 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 02:26:39,896] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.52 | bwd_microstep: 273.59 | bwd_inner_microstep: 273.57 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1352 +[2025-05-02 02:26:40,262] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.68 | bwd_microstep: 206.07 | bwd_inner_microstep: 205.92 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 02:26:40,745] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.82 | bwd_microstep: 273.08 | bwd_inner_microstep: 273.06 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 330 +[2025-05-02 02:26:40,979] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 96.30 | bwd_microstep: 117.74 | bwd_inner_microstep: 117.42 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.12 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1349 +[2025-05-02 02:26:41,349] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.37 | bwd_microstep: 205.79 | bwd_inner_microstep: 205.76 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.12 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1354 +[2025-05-02 02:26:41,720] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.95 | bwd_microstep: 206.14 | bwd_inner_microstep: 206.07 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 02:26:42,207] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.91 | bwd_microstep: 273.04 | bwd_inner_microstep: 273.03 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 320 +[2025-05-02 02:26:42,420] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 79.79 | bwd_microstep: 117.80 | bwd_inner_microstep: 117.64 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 02:26:42,899] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.92 | bwd_microstep: 272.65 | bwd_inner_microstep: 272.64 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 02:26:43,481] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.11 | optimizer_step: 16.28 +[2025-05-02 02:26:43,482] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.36 | bwd_microstep: 350.21 | bwd_inner_microstep: 272.74 | bwd_allreduce_microstep: 77.43 | step_microstep: 23.89 +[2025-05-02 02:26:43,483] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2500.44 | bwd: 3710.55 | bwd_inner: 3631.92 | bwd_allreduce: 77.92 | step: 25.04 + 19%|█▉ | 1687/8720 [4:11:17<13:40:59, 7.00s/it] {'loss': 0.6267, 'grad_norm': 10.45308780670166, 'learning_rate': 9.315818547503814e-06, 'epoch': 1.93} + 19%|█▉ | 1687/8720 [4:11:17<13:40:59, 7.00s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 02:26:43,965] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.21 | bwd_microstep: 270.58 | bwd_inner_microstep: 270.57 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2005 +[2025-05-02 02:26:44,476] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 199.50 | bwd_microstep: 294.99 | bwd_inner_microstep: 294.98 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1905 +[2025-05-02 02:26:44,959] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.43 | bwd_microstep: 275.73 | bwd_inner_microstep: 275.71 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-02 02:26:45,442] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.93 | bwd_microstep: 274.10 | bwd_inner_microstep: 274.08 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-02 02:26:45,927] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.39 | bwd_microstep: 274.11 | bwd_inner_microstep: 274.10 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 02:26:46,408] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.06 | bwd_microstep: 273.37 | bwd_inner_microstep: 273.35 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1366 +[2025-05-02 02:26:46,776] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.70 | bwd_microstep: 206.87 | bwd_inner_microstep: 206.86 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-02 02:26:47,261] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.85 | bwd_microstep: 273.33 | bwd_inner_microstep: 273.31 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 02:26:47,742] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.64 | bwd_microstep: 272.79 | bwd_inner_microstep: 272.78 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 02:26:48,223] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.76 | bwd_microstep: 272.84 | bwd_inner_microstep: 272.83 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 328 +[2025-05-02 02:26:48,455] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.06 | bwd_microstep: 119.34 | bwd_inner_microstep: 119.09 | bwd_allreduce_microstep: 0.10 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 02:26:48,934] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.77 | bwd_microstep: 272.62 | bwd_inner_microstep: 272.61 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 02:26:49,413] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.56 | bwd_microstep: 272.09 | bwd_inner_microstep: 272.08 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 02:26:49,891] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.78 | bwd_microstep: 272.46 | bwd_inner_microstep: 272.44 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 02:26:50,368] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.05 | bwd_microstep: 271.25 | bwd_inner_microstep: 271.24 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 02:26:50,956] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.11 | optimizer_step: 16.29 +[2025-05-02 02:26:50,957] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.47 | bwd_microstep: 356.92 | bwd_inner_microstep: 271.59 | bwd_allreduce_microstep: 85.28 | step_microstep: 23.98 +[2025-05-02 02:26:50,958] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2885.72 | bwd: 4253.44 | bwd_inner: 4167.65 | bwd_allreduce: 85.43 | step: 24.85 + 19%|█▉ | 1688/8720 [4:11:24<13:57:25, 7.15s/it] {'loss': 0.5648, 'grad_norm': 25.245004653930664, 'learning_rate': 9.314880518645726e-06, 'epoch': 1.94} + 19%|█▉ | 1688/8720 [4:11:24<13:57:25, 7.15s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 02:26:51,439] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.11 | bwd_microstep: 270.35 | bwd_inner_microstep: 270.34 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1893 +[2025-05-02 02:26:51,921] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.16 | bwd_microstep: 275.67 | bwd_inner_microstep: 275.65 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1895 +[2025-05-02 02:26:52,401] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.34 | bwd_microstep: 275.80 | bwd_inner_microstep: 275.78 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1889 +[2025-05-02 02:26:52,881] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.13 | bwd_microstep: 275.64 | bwd_inner_microstep: 275.62 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 02:26:53,357] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.28 | bwd_microstep: 272.81 | bwd_inner_microstep: 272.79 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 347 +[2025-05-02 02:26:53,566] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 77.26 | bwd_microstep: 118.74 | bwd_inner_microstep: 118.52 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-02 02:26:54,042] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.68 | bwd_microstep: 273.37 | bwd_inner_microstep: 273.35 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-02 02:26:54,521] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.98 | bwd_microstep: 273.76 | bwd_inner_microstep: 273.74 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-02 02:26:54,998] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.53 | bwd_microstep: 273.93 | bwd_inner_microstep: 273.91 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 834 +[2025-05-02 02:26:55,232] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.18 | bwd_microstep: 125.89 | bwd_inner_microstep: 125.69 | bwd_allreduce_microstep: 0.10 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 02:26:55,710] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.85 | bwd_microstep: 272.27 | bwd_inner_microstep: 272.25 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 02:26:56,189] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.63 | bwd_microstep: 272.56 | bwd_inner_microstep: 272.54 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 02:26:56,669] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.92 | bwd_microstep: 272.67 | bwd_inner_microstep: 272.66 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 02:26:57,149] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.17 | bwd_microstep: 272.96 | bwd_inner_microstep: 272.94 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 02:26:57,630] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.64 | bwd_microstep: 271.12 | bwd_inner_microstep: 271.10 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 02:26:58,212] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.09 | optimizer_step: 16.29 +[2025-05-02 02:26:58,212] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.34 | bwd_microstep: 352.24 | bwd_inner_microstep: 271.64 | bwd_allreduce_microstep: 80.55 | step_microstep: 24.09 +[2025-05-02 02:26:58,214] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2808.87 | bwd: 4149.80 | bwd_inner: 4068.58 | bwd_allreduce: 80.76 | step: 24.89 + 19%|█▉ | 1689/8720 [4:11:31<14:01:11, 7.18s/it] {'loss': 0.6054, 'grad_norm': 13.269583702087402, 'learning_rate': 9.313941894491378e-06, 'epoch': 1.94} + 19%|█▉ | 1689/8720 [4:11:31<14:01:11, 7.18s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 02:26:58,695] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.06 | bwd_microstep: 270.70 | bwd_inner_microstep: 270.69 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 356 +[2025-05-02 02:26:58,923] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 83.66 | bwd_microstep: 128.75 | bwd_inner_microstep: 128.60 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-02 02:26:59,403] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.90 | bwd_microstep: 274.14 | bwd_inner_microstep: 274.12 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-02 02:26:59,883] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.55 | bwd_microstep: 274.44 | bwd_inner_microstep: 274.42 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 845 +[2025-05-02 02:27:00,125] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.40 | bwd_microstep: 132.38 | bwd_inner_microstep: 132.31 | bwd_allreduce_microstep: 0.03 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 02:27:00,602] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.87 | bwd_microstep: 272.92 | bwd_inner_microstep: 272.91 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 02:27:01,080] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.21 | bwd_microstep: 273.57 | bwd_inner_microstep: 273.55 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.16 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 02:27:01,561] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.16 | bwd_microstep: 273.18 | bwd_inner_microstep: 273.16 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 02:27:02,043] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.02 | bwd_microstep: 272.70 | bwd_inner_microstep: 272.68 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 02:27:02,524] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.11 | bwd_microstep: 272.45 | bwd_inner_microstep: 272.43 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 02:27:03,004] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.10 | bwd_microstep: 273.21 | bwd_inner_microstep: 273.19 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 321 +[2025-05-02 02:27:03,225] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 85.49 | bwd_microstep: 119.50 | bwd_inner_microstep: 119.19 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 02:27:03,703] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.72 | bwd_microstep: 271.49 | bwd_inner_microstep: 271.47 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 319 +[2025-05-02 02:27:03,923] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 85.22 | bwd_microstep: 117.27 | bwd_inner_microstep: 117.12 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1343 +[2025-05-02 02:27:04,285] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.12 | bwd_microstep: 204.46 | bwd_inner_microstep: 204.44 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 02:27:04,868] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.11 | optimizer_step: 16.23 +[2025-05-02 02:27:04,869] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.60 | bwd_microstep: 351.14 | bwd_inner_microstep: 271.82 | bwd_allreduce_microstep: 79.27 | step_microstep: 23.98 +[2025-05-02 02:27:04,870] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2566.82 | bwd: 3782.37 | bwd_inner: 3702.22 | bwd_allreduce: 79.61 | step: 25.28 + 19%|█▉ | 1690/8720 [4:11:38<13:42:44, 7.02s/it] {'loss': 0.425, 'grad_norm': 6.511429786682129, 'learning_rate': 9.313002675170266e-06, 'epoch': 1.94} + 19%|█▉ | 1690/8720 [4:11:38<13:42:44, 7.02s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1849 +[2025-05-02 02:27:05,352] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.12 | bwd_microstep: 270.17 | bwd_inner_microstep: 270.15 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1958 +[2025-05-02 02:27:05,857] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 197.73 | bwd_microstep: 290.07 | bwd_inner_microstep: 290.05 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1387 +[2025-05-02 02:27:06,225] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 142.05 | bwd_microstep: 208.68 | bwd_inner_microstep: 208.50 | bwd_allreduce_microstep: 0.09 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1894 +[2025-05-02 02:27:06,708] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.15 | bwd_microstep: 275.02 | bwd_inner_microstep: 275.01 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-02 02:27:07,193] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.29 | bwd_microstep: 274.42 | bwd_inner_microstep: 274.41 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 6, images per sample: 6.0, dynamic token length: 1615 +[2025-05-02 02:27:07,622] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 165.58 | bwd_microstep: 245.89 | bwd_inner_microstep: 245.87 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 02:27:08,100] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.65 | bwd_microstep: 273.76 | bwd_inner_microstep: 273.74 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-02 02:27:08,580] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.07 | bwd_microstep: 273.95 | bwd_inner_microstep: 273.93 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 02:27:09,058] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.66 | bwd_microstep: 273.96 | bwd_inner_microstep: 273.94 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 02:27:09,539] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.77 | bwd_microstep: 273.23 | bwd_inner_microstep: 273.21 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 02:27:10,021] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.79 | bwd_microstep: 273.50 | bwd_inner_microstep: 273.48 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 02:27:10,501] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.68 | bwd_microstep: 273.19 | bwd_inner_microstep: 273.17 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 02:27:10,979] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.09 | bwd_microstep: 271.73 | bwd_inner_microstep: 271.71 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 02:27:11,458] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.41 | bwd_microstep: 271.77 | bwd_inner_microstep: 271.75 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1343 +[2025-05-02 02:27:11,822] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.54 | bwd_microstep: 204.89 | bwd_inner_microstep: 204.75 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 02:27:12,411] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.11 | optimizer_step: 16.29 +[2025-05-02 02:27:12,412] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.31 | bwd_microstep: 355.98 | bwd_inner_microstep: 271.82 | bwd_allreduce_microstep: 84.11 | step_microstep: 23.92 +[2025-05-02 02:27:12,413] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2918.54 | bwd: 4310.25 | bwd_inner: 4225.49 | bwd_allreduce: 84.40 | step: 24.87 + 19%|█▉ | 1691/8720 [4:11:46<14:00:54, 7.18s/it] {'loss': 0.8262, 'grad_norm': 11.938481330871582, 'learning_rate': 9.312062860811972e-06, 'epoch': 1.94} + 19%|█▉ | 1691/8720 [4:11:46<14:00:54, 7.18s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 02:27:12,895] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.85 | bwd_microstep: 270.67 | bwd_inner_microstep: 270.65 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1927 +[2025-05-02 02:27:13,398] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 197.41 | bwd_microstep: 287.71 | bwd_inner_microstep: 287.69 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1905 +[2025-05-02 02:27:13,883] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 191.01 | bwd_microstep: 276.33 | bwd_inner_microstep: 276.31 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 880 +[2025-05-02 02:27:14,138] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 102.26 | bwd_microstep: 134.67 | bwd_inner_microstep: 134.65 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 860 +[2025-05-02 02:27:14,391] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 98.65 | bwd_microstep: 134.22 | bwd_inner_microstep: 134.17 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1891 +[2025-05-02 02:27:14,878] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.12 | bwd_microstep: 275.11 | bwd_inner_microstep: 275.09 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1886 +[2025-05-02 02:27:15,366] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.11 | bwd_microstep: 274.58 | bwd_inner_microstep: 274.56 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-02 02:27:15,850] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.06 | bwd_microstep: 274.53 | bwd_inner_microstep: 274.51 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 02:27:16,331] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.06 | bwd_microstep: 273.72 | bwd_inner_microstep: 273.71 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 02:27:16,815] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.32 | bwd_microstep: 273.91 | bwd_inner_microstep: 273.89 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 02:27:17,295] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.39 | bwd_microstep: 273.49 | bwd_inner_microstep: 273.47 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 02:27:17,776] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.54 | bwd_microstep: 273.87 | bwd_inner_microstep: 273.86 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 02:27:18,256] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.76 | bwd_microstep: 272.83 | bwd_inner_microstep: 272.82 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 02:27:18,736] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.86 | bwd_microstep: 273.20 | bwd_inner_microstep: 273.18 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 02:27:19,218] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.70 | bwd_microstep: 273.17 | bwd_inner_microstep: 273.16 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 02:27:19,789] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.09 | optimizer_step: 16.25 +[2025-05-02 02:27:19,790] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.86 | bwd_microstep: 340.87 | bwd_inner_microstep: 272.21 | bwd_allreduce_microstep: 68.62 | step_microstep: 23.18 +[2025-05-02 02:27:19,791] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2864.58 | bwd: 4182.94 | bwd_inner: 4113.94 | bwd_allreduce: 68.71 | step: 24.12 + 19%|█▉ | 1692/8720 [4:11:53<14:07:44, 7.24s/it] {'loss': 0.6828, 'grad_norm': 6.344645977020264, 'learning_rate': 9.311122451546152e-06, 'epoch': 1.94} + 19%|█▉ | 1692/8720 [4:11:53<14:07:44, 7.24s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 02:27:20,270] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.18 | bwd_microstep: 270.98 | bwd_inner_microstep: 270.97 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1905 +[2025-05-02 02:27:20,751] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.62 | bwd_microstep: 276.26 | bwd_inner_microstep: 276.24 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 859 +[2025-05-02 02:27:20,996] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.25 | bwd_microstep: 133.53 | bwd_inner_microstep: 133.39 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 343 +[2025-05-02 02:27:21,201] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 71.73 | bwd_microstep: 120.49 | bwd_inner_microstep: 120.18 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-02 02:27:21,683] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.18 | bwd_microstep: 274.79 | bwd_inner_microstep: 274.77 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1887 +[2025-05-02 02:27:22,163] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.38 | bwd_microstep: 274.87 | bwd_inner_microstep: 274.85 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 02:27:22,640] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.11 | bwd_microstep: 273.03 | bwd_inner_microstep: 273.01 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.14 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1091 +[2025-05-02 02:27:22,931] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 115.69 | bwd_microstep: 160.67 | bwd_inner_microstep: 160.65 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.09 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 839 +[2025-05-02 02:27:23,163] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 91.66 | bwd_microstep: 126.65 | bwd_inner_microstep: 126.41 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 02:27:23,641] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.85 | bwd_microstep: 272.84 | bwd_inner_microstep: 272.82 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 02:27:24,117] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.25 | bwd_microstep: 272.54 | bwd_inner_microstep: 272.52 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 02:27:24,594] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.07 | bwd_microstep: 272.91 | bwd_inner_microstep: 272.89 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 02:27:25,070] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.47 | bwd_microstep: 272.56 | bwd_inner_microstep: 272.55 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 02:27:25,547] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.92 | bwd_microstep: 272.18 | bwd_inner_microstep: 272.16 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 02:27:26,021] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.29 | bwd_microstep: 271.27 | bwd_inner_microstep: 271.25 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 02:27:26,601] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.15 | optimizer_step: 16.42 +[2025-05-02 02:27:26,602] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.18 | bwd_microstep: 350.19 | bwd_inner_microstep: 271.80 | bwd_allreduce_microstep: 78.33 | step_microstep: 24.33 +[2025-05-02 02:27:26,603] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2638.54 | bwd: 3895.83 | bwd_inner: 3816.59 | bwd_allreduce: 78.70 | step: 25.29 + 19%|█▉ | 1693/8720 [4:12:00<13:52:45, 7.11s/it] {'loss': 0.5944, 'grad_norm': 17.169822692871094, 'learning_rate': 9.310181447502548e-06, 'epoch': 1.94} + 19%|█▉ | 1693/8720 [4:12:00<13:52:45, 7.11s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 02:27:27,087] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.59 | bwd_microstep: 272.44 | bwd_inner_microstep: 272.42 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 389 +[2025-05-02 02:27:27,318] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 84.65 | bwd_microstep: 132.60 | bwd_inner_microstep: 132.28 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1890 +[2025-05-02 02:27:27,798] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.98 | bwd_microstep: 274.65 | bwd_inner_microstep: 274.64 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1365 +[2025-05-02 02:27:28,163] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.57 | bwd_microstep: 207.02 | bwd_inner_microstep: 207.00 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-02 02:27:28,642] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.52 | bwd_microstep: 273.90 | bwd_inner_microstep: 273.88 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 02:27:29,121] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.11 | bwd_microstep: 272.87 | bwd_inner_microstep: 272.86 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 339 +[2025-05-02 02:27:29,367] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 104.98 | bwd_microstep: 122.19 | bwd_inner_microstep: 121.89 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.13 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 331 +[2025-05-02 02:27:29,607] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 98.45 | bwd_microstep: 118.34 | bwd_inner_microstep: 118.03 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 02:27:30,094] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.76 | bwd_microstep: 272.70 | bwd_inner_microstep: 272.68 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 02:27:30,575] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.87 | bwd_microstep: 272.54 | bwd_inner_microstep: 272.52 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 02:27:31,055] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.05 | bwd_microstep: 271.54 | bwd_inner_microstep: 271.53 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 02:27:31,535] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.21 | bwd_microstep: 271.81 | bwd_inner_microstep: 271.79 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 02:27:32,013] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.16 | bwd_microstep: 271.20 | bwd_inner_microstep: 271.18 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 02:27:32,492] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.62 | bwd_microstep: 271.23 | bwd_inner_microstep: 271.22 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 02:27:32,974] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.16 | bwd_microstep: 271.60 | bwd_inner_microstep: 271.59 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 02:27:33,554] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.12 | optimizer_step: 16.40 +[2025-05-02 02:27:33,555] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.86 | bwd_microstep: 347.51 | bwd_inner_microstep: 271.40 | bwd_allreduce_microstep: 76.06 | step_microstep: 24.21 +[2025-05-02 02:27:33,556] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2690.14 | bwd: 3924.24 | bwd_inner: 3847.08 | bwd_allreduce: 76.48 | step: 25.40 + 19%|█▉ | 1694/8720 [4:12:07<13:47:06, 7.06s/it] {'loss': 0.5603, 'grad_norm': 15.928895950317383, 'learning_rate': 9.309239848810989e-06, 'epoch': 1.94} + 19%|█▉ | 1694/8720 [4:12:07<13:47:06, 7.06s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-02 02:27:34,041] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.45 | bwd_microstep: 273.47 | bwd_inner_microstep: 273.46 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1900 +[2025-05-02 02:27:34,523] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.51 | bwd_microstep: 275.63 | bwd_inner_microstep: 275.62 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1904 +[2025-05-02 02:27:35,005] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.16 | bwd_microstep: 276.13 | bwd_inner_microstep: 276.11 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1900 +[2025-05-02 02:27:35,486] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.15 | bwd_microstep: 275.76 | bwd_inner_microstep: 275.74 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 362 +[2025-05-02 02:27:35,703] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 80.44 | bwd_microstep: 121.81 | bwd_inner_microstep: 121.49 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-02 02:27:36,181] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.21 | bwd_microstep: 273.57 | bwd_inner_microstep: 273.54 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-02 02:27:36,659] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.22 | bwd_microstep: 273.59 | bwd_inner_microstep: 273.57 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-02 02:27:37,137] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.36 | bwd_microstep: 274.59 | bwd_inner_microstep: 274.58 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.06 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 864 +[2025-05-02 02:27:37,380] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.18 | bwd_microstep: 133.84 | bwd_inner_microstep: 133.83 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-02 02:27:37,856] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.20 | bwd_microstep: 273.43 | bwd_inner_microstep: 273.41 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-02 02:27:38,333] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.95 | bwd_microstep: 273.66 | bwd_inner_microstep: 273.64 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 02:27:38,813] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.15 | bwd_microstep: 273.21 | bwd_inner_microstep: 273.20 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 02:27:39,294] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.63 | bwd_microstep: 273.54 | bwd_inner_microstep: 273.52 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 02:27:39,775] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.61 | bwd_microstep: 272.97 | bwd_inner_microstep: 272.95 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 02:27:40,254] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.48 | bwd_microstep: 272.60 | bwd_inner_microstep: 272.58 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 02:27:40,832] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.19 | optimizer_step: 16.46 +[2025-05-02 02:27:40,832] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.29 | bwd_microstep: 348.33 | bwd_inner_microstep: 272.11 | bwd_allreduce_microstep: 76.15 | step_microstep: 24.35 +[2025-05-02 02:27:40,834] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2816.67 | bwd: 4166.17 | bwd_inner: 4089.40 | bwd_allreduce: 76.36 | step: 25.24 + 19%|█▉ | 1695/8720 [4:12:14<13:54:31, 7.13s/it] {'loss': 0.8433, 'grad_norm': 5.730443954467773, 'learning_rate': 9.308297655601377e-06, 'epoch': 1.94} + 19%|█▉ | 1695/8720 [4:12:14<13:54:31, 7.13s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-02 02:27:41,319] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.43 | bwd_microstep: 273.56 | bwd_inner_microstep: 273.54 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 358 +[2025-05-02 02:27:41,520] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 67.14 | bwd_microstep: 120.07 | bwd_inner_microstep: 119.75 | bwd_allreduce_microstep: 0.14 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-02 02:27:41,998] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.13 | bwd_microstep: 274.33 | bwd_inner_microstep: 274.31 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 02:27:42,475] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.87 | bwd_microstep: 273.23 | bwd_inner_microstep: 273.21 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 02:27:42,954] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.86 | bwd_microstep: 273.44 | bwd_inner_microstep: 273.42 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 02:27:43,431] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.19 | bwd_microstep: 272.38 | bwd_inner_microstep: 272.36 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 328 +[2025-05-02 02:27:43,644] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 77.04 | bwd_microstep: 122.00 | bwd_inner_microstep: 121.69 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 02:27:44,120] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.83 | bwd_microstep: 272.29 | bwd_inner_microstep: 272.27 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 02:27:44,594] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.20 | bwd_microstep: 271.06 | bwd_inner_microstep: 271.04 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 02:27:45,071] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.51 | bwd_microstep: 272.47 | bwd_inner_microstep: 272.45 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.13 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 02:27:45,548] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.47 | bwd_microstep: 271.38 | bwd_inner_microstep: 271.36 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 02:27:46,026] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.57 | bwd_microstep: 271.26 | bwd_inner_microstep: 271.24 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 02:27:46,504] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.30 | bwd_microstep: 271.34 | bwd_inner_microstep: 271.32 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 02:27:46,983] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.09 | bwd_microstep: 271.06 | bwd_inner_microstep: 271.04 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 02:27:47,462] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.81 | bwd_microstep: 271.15 | bwd_inner_microstep: 271.14 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 02:27:48,043] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.16 | optimizer_step: 16.42 +[2025-05-02 02:27:48,044] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.29 | bwd_microstep: 347.85 | bwd_inner_microstep: 271.75 | bwd_allreduce_microstep: 76.04 | step_microstep: 24.26 +[2025-05-02 02:27:48,045] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2780.41 | bwd: 4128.93 | bwd_inner: 4052.02 | bwd_allreduce: 76.37 | step: 25.40 + 19%|█▉ | 1696/8720 [4:12:21<13:57:21, 7.15s/it] {'loss': 0.5093, 'grad_norm': 31.540578842163086, 'learning_rate': 9.3073548680037e-06, 'epoch': 1.94} + 19%|█▉ | 1696/8720 [4:12:21<13:57:21, 7.15s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-02 02:27:48,531] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.99 | bwd_microstep: 273.18 | bwd_inner_microstep: 273.16 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1759 +[2025-05-02 02:27:48,967] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 162.35 | bwd_microstep: 255.97 | bwd_inner_microstep: 255.95 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1891 +[2025-05-02 02:27:49,453] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.79 | bwd_microstep: 275.14 | bwd_inner_microstep: 275.13 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1894 +[2025-05-02 02:27:49,937] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.63 | bwd_microstep: 275.53 | bwd_inner_microstep: 275.51 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-02 02:27:50,418] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.84 | bwd_microstep: 274.79 | bwd_inner_microstep: 274.77 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-02 02:27:50,900] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.91 | bwd_microstep: 273.93 | bwd_inner_microstep: 273.91 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1358 +[2025-05-02 02:27:51,266] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.09 | bwd_microstep: 206.39 | bwd_inner_microstep: 206.25 | bwd_allreduce_microstep: 0.09 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 02:27:51,749] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.15 | bwd_microstep: 273.88 | bwd_inner_microstep: 273.87 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 334 +[2025-05-02 02:27:51,981] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 92.79 | bwd_microstep: 119.88 | bwd_inner_microstep: 119.63 | bwd_allreduce_microstep: 0.09 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 02:27:52,461] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.26 | bwd_microstep: 273.31 | bwd_inner_microstep: 273.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1353 +[2025-05-02 02:27:52,829] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.74 | bwd_microstep: 206.37 | bwd_inner_microstep: 206.18 | bwd_allreduce_microstep: 0.10 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 02:27:53,310] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.02 | bwd_microstep: 273.54 | bwd_inner_microstep: 273.52 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 02:27:53,791] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.08 | bwd_microstep: 273.27 | bwd_inner_microstep: 273.25 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 02:27:54,270] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.42 | bwd_microstep: 273.12 | bwd_inner_microstep: 273.10 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 02:27:54,750] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.49 | bwd_microstep: 271.99 | bwd_inner_microstep: 271.97 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 02:27:55,327] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.14 | optimizer_step: 16.27 +[2025-05-02 02:27:55,328] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.19 | bwd_microstep: 347.86 | bwd_inner_microstep: 271.81 | bwd_allreduce_microstep: 76.00 | step_microstep: 23.90 +[2025-05-02 02:27:55,329] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2804.37 | bwd: 4148.23 | bwd_inner: 4071.39 | bwd_allreduce: 76.36 | step: 24.96 + 19%|█▉ | 1697/8720 [4:12:29<14:01:49, 7.19s/it] {'loss': 0.5519, 'grad_norm': 5.613767623901367, 'learning_rate': 9.30641148614803e-06, 'epoch': 1.95} + 19%|█▉ | 1697/8720 [4:12:29<14:01:49, 7.19s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 02:27:55,810] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.70 | bwd_microstep: 270.79 | bwd_inner_microstep: 270.77 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1896 +[2025-05-02 02:27:56,291] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.62 | bwd_microstep: 275.56 | bwd_inner_microstep: 275.54 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-02 02:27:56,769] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.62 | bwd_microstep: 274.19 | bwd_inner_microstep: 274.17 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 02:27:57,247] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.56 | bwd_microstep: 273.51 | bwd_inner_microstep: 273.49 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 02:27:57,726] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.92 | bwd_microstep: 272.99 | bwd_inner_microstep: 272.97 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 02:27:58,203] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.03 | bwd_microstep: 273.08 | bwd_inner_microstep: 273.06 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1357 +[2025-05-02 02:27:58,566] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.33 | bwd_microstep: 206.38 | bwd_inner_microstep: 206.36 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 02:27:59,042] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.87 | bwd_microstep: 272.90 | bwd_inner_microstep: 272.88 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 840 +[2025-05-02 02:27:59,321] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 91.08 | bwd_microstep: 174.06 | bwd_inner_microstep: 173.95 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 02:27:59,796] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.65 | bwd_microstep: 272.66 | bwd_inner_microstep: 272.64 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 02:28:00,272] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.98 | bwd_microstep: 272.83 | bwd_inner_microstep: 272.81 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 02:28:00,748] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.12 | bwd_microstep: 272.34 | bwd_inner_microstep: 272.32 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 02:28:01,224] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.44 | bwd_microstep: 272.16 | bwd_inner_microstep: 272.15 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 02:28:01,701] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.81 | bwd_microstep: 272.55 | bwd_inner_microstep: 272.53 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 02:28:02,176] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.88 | bwd_microstep: 271.53 | bwd_inner_microstep: 271.51 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 02:28:02,750] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.15 | optimizer_step: 16.20 +[2025-05-02 02:28:02,751] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.43 | bwd_microstep: 347.46 | bwd_inner_microstep: 271.74 | bwd_allreduce_microstep: 75.67 | step_microstep: 23.72 +[2025-05-02 02:28:02,752] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2872.77 | bwd: 4275.01 | bwd_inner: 4198.91 | bwd_allreduce: 75.81 | step: 24.68 + 19%|█▉ | 1698/8720 [4:12:36<14:09:48, 7.26s/it] {'loss': 0.3127, 'grad_norm': 9.757328033447266, 'learning_rate': 9.305467510164521e-06, 'epoch': 1.95} + 19%|█▉ | 1698/8720 [4:12:36<14:09:48, 7.26s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2201 +[2025-05-02 02:28:03,304] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 207.25 | bwd_microstep: 322.24 | bwd_inner_microstep: 322.21 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1886 +[2025-05-02 02:28:03,787] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.97 | bwd_microstep: 275.20 | bwd_inner_microstep: 275.19 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 866 +[2025-05-02 02:28:04,031] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.05 | bwd_microstep: 134.65 | bwd_inner_microstep: 134.41 | bwd_allreduce_microstep: 0.10 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 02:28:04,508] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.53 | bwd_microstep: 274.17 | bwd_inner_microstep: 274.15 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 843 +[2025-05-02 02:28:04,764] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.33 | bwd_microstep: 147.07 | bwd_inner_microstep: 146.93 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 02:28:05,242] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.72 | bwd_microstep: 273.40 | bwd_inner_microstep: 273.39 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 842 +[2025-05-02 02:28:05,488] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.09 | bwd_microstep: 138.20 | bwd_inner_microstep: 138.05 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.08 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1350 +[2025-05-02 02:28:05,852] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 142.63 | bwd_microstep: 206.35 | bwd_inner_microstep: 206.09 | bwd_allreduce_microstep: 0.14 | step_microstep: 0.09 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 324 +[2025-05-02 02:28:06,089] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 76.29 | bwd_microstep: 147.75 | bwd_inner_microstep: 147.63 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 02:28:06,564] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.97 | bwd_microstep: 272.14 | bwd_inner_microstep: 272.12 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 02:28:07,040] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.08 | bwd_microstep: 272.66 | bwd_inner_microstep: 272.65 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 322 +[2025-05-02 02:28:07,287] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 80.53 | bwd_microstep: 150.92 | bwd_inner_microstep: 150.79 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.10 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 318 +[2025-05-02 02:28:07,520] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 70.93 | bwd_microstep: 149.26 | bwd_inner_microstep: 149.02 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 02:28:07,995] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.58 | bwd_microstep: 272.06 | bwd_inner_microstep: 272.05 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 02:28:08,469] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.67 | bwd_microstep: 271.29 | bwd_inner_microstep: 271.27 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 02:28:09,034] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.08 | optimizer_step: 16.25 +[2025-05-02 02:28:09,035] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.10 | bwd_microstep: 338.47 | bwd_inner_microstep: 271.95 | bwd_allreduce_microstep: 66.47 | step_microstep: 23.18 +[2025-05-02 02:28:09,036] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2368.44 | bwd: 3645.97 | bwd_inner: 3578.14 | bwd_allreduce: 67.00 | step: 24.42 + 19%|█▉ | 1699/8720 [4:12:42<13:35:18, 6.97s/it] {'loss': 0.3682, 'grad_norm': 7.675639629364014, 'learning_rate': 9.304522940183404e-06, 'epoch': 1.95} + 19%|█▉ | 1699/8720 [4:12:42<13:35:18, 6.97s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 02:28:09,514] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.84 | bwd_microstep: 271.17 | bwd_inner_microstep: 271.16 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 353 +[2025-05-02 02:28:09,763] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 82.74 | bwd_microstep: 151.68 | bwd_inner_microstep: 151.50 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-02 02:28:10,241] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.98 | bwd_microstep: 274.48 | bwd_inner_microstep: 274.46 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-02 02:28:10,722] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.78 | bwd_microstep: 275.10 | bwd_inner_microstep: 275.09 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 02:28:11,200] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.17 | bwd_microstep: 273.57 | bwd_inner_microstep: 273.56 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 02:28:11,677] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.84 | bwd_microstep: 273.29 | bwd_inner_microstep: 273.27 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1109 +[2025-05-02 02:28:11,968] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 114.84 | bwd_microstep: 162.59 | bwd_inner_microstep: 162.28 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 02:28:12,444] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.62 | bwd_microstep: 272.72 | bwd_inner_microstep: 272.71 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 02:28:12,921] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.75 | bwd_microstep: 272.92 | bwd_inner_microstep: 272.91 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 02:28:13,398] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.72 | bwd_microstep: 273.19 | bwd_inner_microstep: 273.17 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 837 +[2025-05-02 02:28:13,643] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 92.00 | bwd_microstep: 138.30 | bwd_inner_microstep: 138.19 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 02:28:14,118] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.54 | bwd_microstep: 273.01 | bwd_inner_microstep: 272.99 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 02:28:14,595] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.47 | bwd_microstep: 273.10 | bwd_inner_microstep: 273.09 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 02:28:15,069] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.94 | bwd_microstep: 272.25 | bwd_inner_microstep: 272.23 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 02:28:15,544] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.69 | bwd_microstep: 271.97 | bwd_inner_microstep: 271.95 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 488 +[2025-05-02 02:28:15,896] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.07 | optimizer_step: 16.19 +[2025-05-02 02:28:15,896] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 80.48 | bwd_microstep: 234.36 | bwd_inner_microstep: 168.56 | bwd_allreduce_microstep: 65.65 | step_microstep: 23.13 +[2025-05-02 02:28:15,897] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2633.12 | bwd: 3963.77 | bwd_inner: 3897.29 | bwd_allreduce: 65.92 | step: 24.11 + 19%|█▉ | 1700/8720 [4:12:49<13:31:28, 6.94s/it] {'loss': 0.4487, 'grad_norm': 7.033843994140625, 'learning_rate': 9.303577776334997e-06, 'epoch': 1.95} + 19%|█▉ | 1700/8720 [4:12:49<13:31:28, 6.94s/it][INFO|trainer.py:3503] 2025-05-02 02:28:18,333 >> Saving model checkpoint to work_dirs/internvl_chat_v2_5/ak/checkpoint-1700 +[INFO|configuration_utils.py:472] 2025-05-02 02:28:18,336 >> Configuration saved in work_dirs/internvl_chat_v2_5/ak/checkpoint-1700/config.json +[INFO|configuration_utils.py:807] 2025-05-02 02:28:18,336 >> Configuration saved in work_dirs/internvl_chat_v2_5/ak/checkpoint-1700/generation_config.json +[INFO|modeling_utils.py:2755] 2025-05-02 02:28:23,402 >> Model weights saved in work_dirs/internvl_chat_v2_5/ak/checkpoint-1700/model.safetensors +[INFO|tokenization_utils_base.py:2702] 2025-05-02 02:28:23,404 >> tokenizer config file saved in work_dirs/internvl_chat_v2_5/ak/checkpoint-1700/tokenizer_config.json +[INFO|tokenization_utils_base.py:2711] 2025-05-02 02:28:23,404 >> Special tokens file saved in work_dirs/internvl_chat_v2_5/ak/checkpoint-1700/special_tokens_map.json +[INFO|tokenization_utils_base.py:2762] 2025-05-02 02:28:23,404 >> added tokens file saved in work_dirs/internvl_chat_v2_5/ak/checkpoint-1700/added_tokens.json +[2025-05-02 02:28:23,512] [INFO] [logging.py:96:log_dist] [Rank 0] [Torch] Checkpoint global_step1700 is about to be saved! +[2025-05-02 02:28:23,528] [INFO] [logging.py:96:log_dist] [Rank 0] Saving model checkpoint: work_dirs/internvl_chat_v2_5/ak/checkpoint-1700/global_step1700/mp_rank_00_model_states.pt +[2025-05-02 02:28:23,528] [INFO] [torch_checkpoint_engine.py:21:save] [Torch] Saving work_dirs/internvl_chat_v2_5/ak/checkpoint-1700/global_step1700/mp_rank_00_model_states.pt... +[2025-05-02 02:28:27,990] [INFO] [torch_checkpoint_engine.py:23:save] [Torch] Saved work_dirs/internvl_chat_v2_5/ak/checkpoint-1700/global_step1700/mp_rank_00_model_states.pt. +[2025-05-02 02:28:27,991] [INFO] [torch_checkpoint_engine.py:21:save] [Torch] Saving work_dirs/internvl_chat_v2_5/ak/checkpoint-1700/global_step1700/bf16_zero_pp_rank_0_mp_rank_00_optim_states.pt... +[2025-05-02 02:28:28,191] [INFO] [torch_checkpoint_engine.py:23:save] [Torch] Saved work_dirs/internvl_chat_v2_5/ak/checkpoint-1700/global_step1700/bf16_zero_pp_rank_0_mp_rank_00_optim_states.pt. +[2025-05-02 02:28:28,192] [INFO] [engine.py:3536:_save_zero_checkpoint] zero checkpoint saved work_dirs/internvl_chat_v2_5/ak/checkpoint-1700/global_step1700/bf16_zero_pp_rank_0_mp_rank_00_optim_states.pt +[2025-05-02 02:28:28,192] [INFO] [torch_checkpoint_engine.py:33:commit] [Torch] Checkpoint global_step1700 is ready now! +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 879 +[2025-05-02 02:28:28,475] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.63 | bwd_microstep: 142.92 | bwd_inner_microstep: 142.57 | bwd_allreduce_microstep: 0.15 | step_microstep: 0.20 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 987 +[2025-05-02 02:28:28,741] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 102.30 | bwd_microstep: 149.07 | bwd_inner_microstep: 148.94 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.08 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 378 +[2025-05-02 02:28:28,989] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 77.01 | bwd_microstep: 156.58 | bwd_inner_microstep: 156.31 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.08 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 359 +[2025-05-02 02:28:29,237] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 80.88 | bwd_microstep: 152.67 | bwd_inner_microstep: 152.36 | bwd_allreduce_microstep: 0.14 | step_microstep: 0.09 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 356 +[2025-05-02 02:28:29,473] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 72.22 | bwd_microstep: 150.81 | bwd_inner_microstep: 150.48 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1367 +[2025-05-02 02:28:29,836] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.71 | bwd_microstep: 206.44 | bwd_inner_microstep: 206.27 | bwd_allreduce_microstep: 0.10 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1889 +[2025-05-02 02:28:30,315] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.75 | bwd_microstep: 273.78 | bwd_inner_microstep: 273.76 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.21 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-02 02:28:30,793] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.07 | bwd_microstep: 272.81 | bwd_inner_microstep: 272.79 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 02:28:31,273] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.65 | bwd_microstep: 272.31 | bwd_inner_microstep: 272.29 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.22 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 841 +[2025-05-02 02:28:31,542] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.00 | bwd_microstep: 156.06 | bwd_inner_microstep: 155.76 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1352 +[2025-05-02 02:28:31,905] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 139.53 | bwd_microstep: 205.49 | bwd_inner_microstep: 205.26 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 02:28:32,380] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.96 | bwd_microstep: 271.05 | bwd_inner_microstep: 271.03 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 02:28:32,857] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.76 | bwd_microstep: 270.40 | bwd_inner_microstep: 270.38 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 02:28:33,336] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.48 | bwd_microstep: 270.53 | bwd_inner_microstep: 270.51 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 02:28:33,816] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.28 | bwd_microstep: 270.81 | bwd_inner_microstep: 270.79 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 02:28:34,394] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.10 | optimizer_step: 16.31 +[2025-05-02 02:28:34,394] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.16 | bwd_microstep: 349.40 | bwd_inner_microstep: 270.87 | bwd_allreduce_microstep: 78.46 | step_microstep: 23.41 +[2025-05-02 02:28:34,396] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2307.01 | bwd: 3571.27 | bwd_inner: 3490.73 | bwd_allreduce: 79.31 | step: 24.95 + 20%|█▉ | 1701/8720 [4:13:08<20:17:09, 10.40s/it] {'loss': 0.6628, 'grad_norm': 6.266927242279053, 'learning_rate': 9.302632018749698e-06, 'epoch': 1.95} + 20%|█▉ | 1701/8720 [4:13:08<20:17:09, 10.40s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 02:28:34,873] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.61 | bwd_microstep: 269.62 | bwd_inner_microstep: 269.60 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1364 +[2025-05-02 02:28:35,236] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.94 | bwd_microstep: 206.23 | bwd_inner_microstep: 206.18 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-02 02:28:35,713] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.97 | bwd_microstep: 272.96 | bwd_inner_microstep: 272.94 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 02:28:36,189] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.40 | bwd_microstep: 272.20 | bwd_inner_microstep: 272.18 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1351 +[2025-05-02 02:28:36,551] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.59 | bwd_microstep: 204.75 | bwd_inner_microstep: 204.60 | bwd_allreduce_microstep: 0.09 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 02:28:37,026] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.27 | bwd_microstep: 271.88 | bwd_inner_microstep: 271.86 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 323 +[2025-05-02 02:28:37,288] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 92.02 | bwd_microstep: 151.10 | bwd_inner_microstep: 150.75 | bwd_allreduce_microstep: 0.18 | step_microstep: 0.10 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 842 +[2025-05-02 02:28:37,556] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.80 | bwd_microstep: 157.17 | bwd_inner_microstep: 156.86 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 02:28:38,037] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.40 | bwd_microstep: 272.44 | bwd_inner_microstep: 272.42 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 02:28:38,516] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.16 | bwd_microstep: 272.82 | bwd_inner_microstep: 272.80 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 333 +[2025-05-02 02:28:38,775] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 90.29 | bwd_microstep: 150.59 | bwd_inner_microstep: 150.43 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 02:28:39,255] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.76 | bwd_microstep: 272.68 | bwd_inner_microstep: 272.67 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 02:28:39,734] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.04 | bwd_microstep: 272.30 | bwd_inner_microstep: 272.29 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 02:28:40,212] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.68 | bwd_microstep: 271.35 | bwd_inner_microstep: 271.33 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 02:28:40,692] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.54 | bwd_microstep: 270.00 | bwd_inner_microstep: 269.98 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 02:28:41,267] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.11 | optimizer_step: 16.23 +[2025-05-02 02:28:41,268] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.44 | bwd_microstep: 346.95 | bwd_inner_microstep: 270.35 | bwd_allreduce_microstep: 76.55 | step_microstep: 24.04 +[2025-05-02 02:28:41,269] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2630.53 | bwd: 3935.15 | bwd_inner: 3857.39 | bwd_allreduce: 77.06 | step: 25.27 + 20%|█▉ | 1702/8720 [4:13:15<18:13:08, 9.35s/it] {'loss': 0.6668, 'grad_norm': 30.7100887298584, 'learning_rate': 9.301685667557987e-06, 'epoch': 1.95} + 20%|█▉ | 1702/8720 [4:13:15<18:13:08, 9.35s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1973 +[2025-05-02 02:28:41,780] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 198.36 | bwd_microstep: 289.46 | bwd_inner_microstep: 289.44 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1924 +[2025-05-02 02:28:42,276] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 193.62 | bwd_microstep: 286.13 | bwd_inner_microstep: 286.11 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-02 02:28:42,757] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.17 | bwd_microstep: 273.24 | bwd_inner_microstep: 273.22 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1372 +[2025-05-02 02:28:43,125] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.55 | bwd_microstep: 206.81 | bwd_inner_microstep: 206.78 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-02 02:28:43,603] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.48 | bwd_microstep: 273.25 | bwd_inner_microstep: 273.23 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 02:28:44,079] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.18 | bwd_microstep: 272.07 | bwd_inner_microstep: 272.05 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 02:28:44,555] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.25 | bwd_microstep: 271.60 | bwd_inner_microstep: 271.58 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 842 +[2025-05-02 02:28:44,803] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.47 | bwd_microstep: 138.69 | bwd_inner_microstep: 138.36 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 02:28:45,277] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.62 | bwd_microstep: 271.72 | bwd_inner_microstep: 271.70 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 02:28:45,754] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.01 | bwd_microstep: 271.29 | bwd_inner_microstep: 271.27 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 02:28:46,232] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.20 | bwd_microstep: 271.24 | bwd_inner_microstep: 271.22 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 02:28:46,710] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.11 | bwd_microstep: 271.91 | bwd_inner_microstep: 271.90 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 322 +[2025-05-02 02:28:46,962] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 83.75 | bwd_microstep: 151.40 | bwd_inner_microstep: 151.24 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 02:28:47,437] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.72 | bwd_microstep: 270.39 | bwd_inner_microstep: 270.38 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 02:28:47,915] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.61 | bwd_microstep: 270.66 | bwd_inner_microstep: 270.65 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1891 +[2025-05-02 02:28:48,496] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.05 | optimizer_step: 16.36 +[2025-05-02 02:28:48,497] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.95 | bwd_microstep: 351.46 | bwd_inner_microstep: 274.65 | bwd_allreduce_microstep: 76.70 | step_microstep: 24.01 +[2025-05-02 02:28:48,498] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2773.69 | bwd: 4141.38 | bwd_inner: 4063.90 | bwd_allreduce: 76.94 | step: 25.27 + 20%|█▉ | 1703/8720 [4:13:22<16:58:40, 8.71s/it] {'loss': 0.7044, 'grad_norm': 4.081421852111816, 'learning_rate': 9.300738722890426e-06, 'epoch': 1.95} + 20%|█▉ | 1703/8720 [4:13:22<16:58:40, 8.71s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1889 +[2025-05-02 02:28:48,981] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.38 | bwd_microstep: 273.27 | bwd_inner_microstep: 273.25 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1958 +[2025-05-02 02:28:49,479] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 194.66 | bwd_microstep: 288.68 | bwd_inner_microstep: 288.67 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-02 02:28:49,953] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.63 | bwd_microstep: 271.72 | bwd_inner_microstep: 271.70 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-02 02:28:50,431] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.30 | bwd_microstep: 273.11 | bwd_inner_microstep: 273.09 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.22 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 02:28:50,909] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.27 | bwd_microstep: 272.13 | bwd_inner_microstep: 272.11 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.09 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 836 +[2025-05-02 02:28:51,173] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 91.73 | bwd_microstep: 158.46 | bwd_inner_microstep: 158.22 | bwd_allreduce_microstep: 0.10 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 02:28:51,648] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.86 | bwd_microstep: 271.31 | bwd_inner_microstep: 271.29 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 02:28:52,122] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.58 | bwd_microstep: 271.39 | bwd_inner_microstep: 271.37 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 02:28:52,595] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.48 | bwd_microstep: 271.16 | bwd_inner_microstep: 271.14 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 02:28:53,069] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.58 | bwd_microstep: 271.30 | bwd_inner_microstep: 271.28 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 836 +[2025-05-02 02:28:53,325] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.47 | bwd_microstep: 147.36 | bwd_inner_microstep: 147.05 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 02:28:53,799] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.27 | bwd_microstep: 272.06 | bwd_inner_microstep: 272.04 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 02:28:54,273] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.14 | bwd_microstep: 270.86 | bwd_inner_microstep: 270.84 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 02:28:54,747] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.97 | bwd_microstep: 271.49 | bwd_inner_microstep: 271.48 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 02:28:55,222] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.13 | bwd_microstep: 270.81 | bwd_inner_microstep: 270.79 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 02:28:55,785] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.10 | optimizer_step: 16.28 +[2025-05-02 02:28:55,786] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.09 | bwd_microstep: 337.14 | bwd_inner_microstep: 270.95 | bwd_allreduce_microstep: 66.13 | step_microstep: 23.46 +[2025-05-02 02:28:55,787] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2817.27 | bwd: 4192.28 | bwd_inner: 4125.39 | bwd_allreduce: 66.39 | step: 24.63 + 20%|█▉ | 1704/8720 [4:13:29<16:08:39, 8.28s/it] {'loss': 0.3705, 'grad_norm': 5.575202465057373, 'learning_rate': 9.299791184877657e-06, 'epoch': 1.95} + 20%|█▉ | 1704/8720 [4:13:29<16:08:39, 8.28s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 316 +[2025-05-02 02:28:56,025] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 71.33 | bwd_microstep: 148.46 | bwd_inner_microstep: 148.23 | bwd_allreduce_microstep: 0.08 | step_microstep: 0.09 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 439 +[2025-05-02 02:28:56,275] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 73.29 | bwd_microstep: 162.44 | bwd_inner_microstep: 162.21 | bwd_allreduce_microstep: 0.09 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-02 02:28:56,753] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.36 | bwd_microstep: 273.75 | bwd_inner_microstep: 273.73 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-02 02:28:57,234] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.60 | bwd_microstep: 273.77 | bwd_inner_microstep: 273.75 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 854 +[2025-05-02 02:28:57,490] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 96.74 | bwd_microstep: 145.55 | bwd_inner_microstep: 145.42 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 845 +[2025-05-02 02:28:57,740] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.48 | bwd_microstep: 141.68 | bwd_inner_microstep: 141.58 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.08 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1357 +[2025-05-02 02:28:58,101] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 139.72 | bwd_microstep: 206.52 | bwd_inner_microstep: 206.34 | bwd_allreduce_microstep: 0.09 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 02:28:58,576] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.57 | bwd_microstep: 272.20 | bwd_inner_microstep: 272.18 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1356 +[2025-05-02 02:28:58,937] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.11 | bwd_microstep: 205.95 | bwd_inner_microstep: 205.86 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.08 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 841 +[2025-05-02 02:28:59,176] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.29 | bwd_microstep: 131.74 | bwd_inner_microstep: 131.67 | bwd_allreduce_microstep: 0.03 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 02:28:59,657] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.91 | bwd_microstep: 272.21 | bwd_inner_microstep: 272.19 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 02:29:00,140] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.32 | bwd_microstep: 272.40 | bwd_inner_microstep: 272.39 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 02:29:00,630] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.64 | bwd_microstep: 271.81 | bwd_inner_microstep: 271.79 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 02:29:01,109] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.80 | bwd_microstep: 271.80 | bwd_inner_microstep: 271.78 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.50 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 02:29:01,589] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.19 | bwd_microstep: 270.83 | bwd_inner_microstep: 270.81 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 02:29:02,169] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.08 | optimizer_gradients: 2.15 | optimizer_step: 16.46 +[2025-05-02 02:29:02,169] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.76 | bwd_microstep: 349.42 | bwd_inner_microstep: 271.45 | bwd_allreduce_microstep: 77.92 | step_microstep: 24.48 +[2025-05-02 02:29:02,171] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2402.77 | bwd: 3670.63 | bwd_inner: 3591.54 | bwd_allreduce: 78.35 | step: 26.04 + 20%|█▉ | 1705/8720 [4:13:35<15:01:56, 7.71s/it] {'loss': 0.8009, 'grad_norm': 7.158106327056885, 'learning_rate': 9.298843053650409e-06, 'epoch': 1.96} + 20%|█▉ | 1705/8720 [4:13:35<15:01:56, 7.71s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 02:29:02,651] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.46 | bwd_microstep: 269.83 | bwd_inner_microstep: 269.82 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 517 +[2025-05-02 02:29:02,875] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 81.63 | bwd_microstep: 127.01 | bwd_inner_microstep: 126.78 | bwd_allreduce_microstep: 0.09 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1896 +[2025-05-02 02:29:03,354] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.14 | bwd_microstep: 274.55 | bwd_inner_microstep: 274.53 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1891 +[2025-05-02 02:29:03,832] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.89 | bwd_microstep: 274.37 | bwd_inner_microstep: 274.36 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1893 +[2025-05-02 02:29:04,312] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.07 | bwd_microstep: 275.11 | bwd_inner_microstep: 275.09 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 351 +[2025-05-02 02:29:04,520] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 75.94 | bwd_microstep: 118.98 | bwd_inner_microstep: 118.66 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1361 +[2025-05-02 02:29:04,883] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.45 | bwd_microstep: 206.44 | bwd_inner_microstep: 206.31 | bwd_allreduce_microstep: 0.04 | step_microstep: 0.09 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1103 +[2025-05-02 02:29:05,176] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 116.87 | bwd_microstep: 161.52 | bwd_inner_microstep: 161.43 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1352 +[2025-05-02 02:29:05,537] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.41 | bwd_microstep: 205.47 | bwd_inner_microstep: 205.46 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 02:29:06,011] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.58 | bwd_microstep: 271.92 | bwd_inner_microstep: 271.90 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 02:29:06,486] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.64 | bwd_microstep: 272.06 | bwd_inner_microstep: 272.05 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 02:29:06,961] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.81 | bwd_microstep: 270.35 | bwd_inner_microstep: 270.33 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 02:29:07,434] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.83 | bwd_microstep: 270.39 | bwd_inner_microstep: 270.37 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1343 +[2025-05-02 02:29:07,796] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.39 | bwd_microstep: 203.92 | bwd_inner_microstep: 203.84 | bwd_allreduce_microstep: 0.03 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 02:29:08,273] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.71 | bwd_microstep: 270.78 | bwd_inner_microstep: 270.76 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 02:29:08,849] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.12 | optimizer_step: 16.32 +[2025-05-02 02:29:08,850] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.59 | bwd_microstep: 347.95 | bwd_inner_microstep: 270.63 | bwd_allreduce_microstep: 77.27 | step_microstep: 24.32 +[2025-05-02 02:29:08,851] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2572.10 | bwd: 3820.73 | bwd_inner: 3742.44 | bwd_allreduce: 77.69 | step: 25.41 + 20%|█▉ | 1706/8720 [4:13:42<14:25:33, 7.40s/it] {'loss': 0.4417, 'grad_norm': 5.536677837371826, 'learning_rate': 9.297894329339488e-06, 'epoch': 1.96} + 20%|█▉ | 1706/8720 [4:13:42<14:25:33, 7.40s/it]dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 987 +[2025-05-02 02:29:09,126] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 102.09 | bwd_microstep: 150.37 | bwd_inner_microstep: 150.22 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1928 +[2025-05-02 02:29:09,625] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.18 | bwd_microstep: 286.21 | bwd_inner_microstep: 286.19 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 388 +[2025-05-02 02:29:09,826] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 71.05 | bwd_microstep: 115.81 | bwd_inner_microstep: 115.64 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.11 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 368 +[2025-05-02 02:29:10,054] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 92.64 | bwd_microstep: 121.98 | bwd_inner_microstep: 121.78 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1904 +[2025-05-02 02:29:10,533] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.74 | bwd_microstep: 275.67 | bwd_inner_microstep: 275.66 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1903 +[2025-05-02 02:29:11,014] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.27 | bwd_microstep: 275.90 | bwd_inner_microstep: 275.89 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 866 +[2025-05-02 02:29:11,256] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.60 | bwd_microstep: 134.08 | bwd_inner_microstep: 133.95 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 353 +[2025-05-02 02:29:11,491] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 97.51 | bwd_microstep: 120.38 | bwd_inner_microstep: 120.16 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.09 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 344 +[2025-05-02 02:29:11,748] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 75.71 | bwd_microstep: 167.22 | bwd_inner_microstep: 167.09 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 02:29:12,226] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.77 | bwd_microstep: 272.90 | bwd_inner_microstep: 272.88 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 02:29:12,705] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.62 | bwd_microstep: 273.02 | bwd_inner_microstep: 273.00 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 332 +[2025-05-02 02:29:12,972] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 86.88 | bwd_microstep: 165.22 | bwd_inner_microstep: 164.96 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.09 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 832 +[2025-05-02 02:29:13,237] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 92.12 | bwd_microstep: 157.75 | bwd_inner_microstep: 157.61 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 02:29:13,713] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.63 | bwd_microstep: 272.27 | bwd_inner_microstep: 272.25 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 02:29:14,188] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.54 | bwd_microstep: 270.99 | bwd_inner_microstep: 270.98 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 02:29:14,779] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.11 | optimizer_step: 39.81 +[2025-05-02 02:29:14,779] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.03 | bwd_microstep: 338.55 | bwd_inner_microstep: 271.21 | bwd_allreduce_microstep: 67.22 | step_microstep: 47.38 +[2025-05-02 02:29:14,780] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2226.05 | bwd: 3398.45 | bwd_inner: 3329.81 | bwd_allreduce: 67.75 | step: 48.62 + 20%|█▉ | 1707/8720 [4:13:48<13:33:39, 6.96s/it] {'loss': 1.0133, 'grad_norm': 5.716560363769531, 'learning_rate': 9.296945012075782e-06, 'epoch': 1.96} + 20%|█▉ | 1707/8720 [4:13:48<13:33:39, 6.96s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 02:29:15,260] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.64 | bwd_microstep: 270.36 | bwd_inner_microstep: 270.33 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2103 +[2025-05-02 02:29:15,790] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 204.58 | bwd_microstep: 309.29 | bwd_inner_microstep: 309.27 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1997 +[2025-05-02 02:29:16,299] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 198.54 | bwd_microstep: 294.32 | bwd_inner_microstep: 294.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-02 02:29:16,777] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.10 | bwd_microstep: 273.27 | bwd_inner_microstep: 273.26 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 02:29:17,253] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.00 | bwd_microstep: 272.70 | bwd_inner_microstep: 272.68 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 02:29:17,728] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.31 | bwd_microstep: 272.02 | bwd_inner_microstep: 272.00 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 02:29:18,205] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.98 | bwd_microstep: 272.41 | bwd_inner_microstep: 272.39 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 02:29:18,682] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.98 | bwd_microstep: 272.62 | bwd_inner_microstep: 272.60 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 839 +[2025-05-02 02:29:18,935] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 112.56 | bwd_microstep: 125.63 | bwd_inner_microstep: 125.47 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 02:29:19,411] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.32 | bwd_microstep: 272.22 | bwd_inner_microstep: 272.20 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 02:29:19,887] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.51 | bwd_microstep: 272.04 | bwd_inner_microstep: 272.02 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 02:29:20,362] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.55 | bwd_microstep: 272.10 | bwd_inner_microstep: 272.08 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 02:29:20,839] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.11 | bwd_microstep: 271.87 | bwd_inner_microstep: 271.85 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 02:29:21,314] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.28 | bwd_microstep: 271.91 | bwd_inner_microstep: 271.89 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 02:29:21,789] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.87 | bwd_microstep: 272.01 | bwd_inner_microstep: 271.99 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 02:29:22,373] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.11 | optimizer_step: 16.42 +[2025-05-02 02:29:22,374] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.63 | bwd_microstep: 355.64 | bwd_inner_microstep: 271.34 | bwd_allreduce_microstep: 84.26 | step_microstep: 24.84 +[2025-05-02 02:29:22,375] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2960.66 | bwd: 4350.45 | bwd_inner: 4265.72 | bwd_allreduce: 84.40 | step: 25.88 + 20%|█▉ | 1708/8720 [4:13:56<13:55:43, 7.15s/it] {'loss': 0.3696, 'grad_norm': 5.800665855407715, 'learning_rate': 9.295995101990263e-06, 'epoch': 1.96} + 20%|█▉ | 1708/8720 [4:13:56<13:55:43, 7.15s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 02:29:22,854] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.60 | bwd_microstep: 270.48 | bwd_inner_microstep: 270.47 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1982 +[2025-05-02 02:29:23,358] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 196.61 | bwd_microstep: 292.05 | bwd_inner_microstep: 292.03 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 911 +[2025-05-02 02:29:23,621] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 103.37 | bwd_microstep: 144.58 | bwd_inner_microstep: 144.29 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 02:29:24,101] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.23 | bwd_microstep: 272.48 | bwd_inner_microstep: 272.46 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1117 +[2025-05-02 02:29:24,400] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 118.51 | bwd_microstep: 162.31 | bwd_inner_microstep: 162.13 | bwd_allreduce_microstep: 0.08 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-02 02:29:24,882] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.29 | bwd_microstep: 272.92 | bwd_inner_microstep: 272.90 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 02:29:25,362] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.75 | bwd_microstep: 272.79 | bwd_inner_microstep: 272.77 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 02:29:25,842] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.55 | bwd_microstep: 272.33 | bwd_inner_microstep: 272.32 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 02:29:26,321] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.18 | bwd_microstep: 272.36 | bwd_inner_microstep: 272.35 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 02:29:26,800] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.93 | bwd_microstep: 272.26 | bwd_inner_microstep: 272.24 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 02:29:27,278] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.06 | bwd_microstep: 272.31 | bwd_inner_microstep: 272.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 02:29:27,757] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.02 | bwd_microstep: 272.22 | bwd_inner_microstep: 272.21 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 02:29:28,238] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.77 | bwd_microstep: 272.01 | bwd_inner_microstep: 271.99 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 02:29:28,715] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.51 | bwd_microstep: 270.90 | bwd_inner_microstep: 270.89 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 02:29:29,191] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.30 | bwd_microstep: 270.49 | bwd_inner_microstep: 270.47 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 02:29:29,794] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.13 | optimizer_step: 16.46 +[2025-05-02 02:29:29,795] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.10 | bwd_microstep: 371.14 | bwd_inner_microstep: 271.24 | bwd_allreduce_microstep: 99.84 | step_microstep: 25.94 +[2025-05-02 02:29:29,796] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2870.40 | bwd: 4233.70 | bwd_inner: 4133.09 | bwd_allreduce: 100.16 | step: 26.99 + 20%|█▉ | 1709/8720 [4:14:03<14:05:07, 7.23s/it] {'loss': 0.6605, 'grad_norm': 11.046699523925781, 'learning_rate': 9.295044599213987e-06, 'epoch': 1.96} + 20%|█▉ | 1709/8720 [4:14:03<14:05:07, 7.23s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 02:29:30,278] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.95 | bwd_microstep: 269.84 | bwd_inner_microstep: 269.82 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.12 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 928 +[2025-05-02 02:29:30,547] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 107.90 | bwd_microstep: 146.00 | bwd_inner_microstep: 145.97 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1926 +[2025-05-02 02:29:31,047] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.24 | bwd_microstep: 287.14 | bwd_inner_microstep: 287.12 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 355 +[2025-05-02 02:29:31,289] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 100.68 | bwd_microstep: 122.04 | bwd_inner_microstep: 121.87 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-02 02:29:31,771] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.82 | bwd_microstep: 274.11 | bwd_inner_microstep: 274.10 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1357 +[2025-05-02 02:29:32,138] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.26 | bwd_microstep: 206.14 | bwd_inner_microstep: 206.02 | bwd_allreduce_microstep: 0.03 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 02:29:32,622] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.17 | bwd_microstep: 272.31 | bwd_inner_microstep: 272.29 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1350 +[2025-05-02 02:29:32,985] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.46 | bwd_microstep: 205.76 | bwd_inner_microstep: 205.75 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.15 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 02:29:33,462] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.79 | bwd_microstep: 272.06 | bwd_inner_microstep: 272.05 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 02:29:33,942] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.01 | bwd_microstep: 272.63 | bwd_inner_microstep: 272.61 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 02:29:34,420] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.02 | bwd_microstep: 272.35 | bwd_inner_microstep: 272.33 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 02:29:34,897] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.38 | bwd_microstep: 271.12 | bwd_inner_microstep: 271.11 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1345 +[2025-05-02 02:29:35,262] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.10 | bwd_microstep: 205.75 | bwd_inner_microstep: 205.63 | bwd_allreduce_microstep: 0.04 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 02:29:35,740] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.54 | bwd_microstep: 271.11 | bwd_inner_microstep: 271.09 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 02:29:36,217] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.44 | bwd_microstep: 271.08 | bwd_inner_microstep: 271.06 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 02:29:36,793] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.07 | optimizer_gradients: 2.12 | optimizer_step: 16.44 +[2025-05-02 02:29:36,794] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.53 | bwd_microstep: 348.30 | bwd_inner_microstep: 272.03 | bwd_allreduce_microstep: 76.23 | step_microstep: 23.56 +[2025-05-02 02:29:36,795] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2707.90 | bwd: 3967.87 | bwd_inner: 3890.89 | bwd_allreduce: 76.50 | step: 25.03 + 20%|█▉ | 1710/8720 [4:14:10<13:56:45, 7.16s/it] {'loss': 0.4829, 'grad_norm': 9.65456485748291, 'learning_rate': 9.294093503878085e-06, 'epoch': 1.96} + 20%|█▉ | 1710/8720 [4:14:10<13:56:45, 7.16s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1896 +[2025-05-02 02:29:37,280] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.57 | bwd_microstep: 274.66 | bwd_inner_microstep: 274.64 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2068 +[2025-05-02 02:29:37,802] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 203.82 | bwd_microstep: 303.26 | bwd_inner_microstep: 303.24 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1214 +[2025-05-02 02:29:38,114] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 122.79 | bwd_microstep: 175.51 | bwd_inner_microstep: 175.49 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1931 +[2025-05-02 02:29:38,613] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.96 | bwd_microstep: 288.05 | bwd_inner_microstep: 288.04 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.13 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1890 +[2025-05-02 02:29:39,093] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.18 | bwd_microstep: 274.87 | bwd_inner_microstep: 274.86 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-02 02:29:39,572] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.82 | bwd_microstep: 273.26 | bwd_inner_microstep: 273.24 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 331 +[2025-05-02 02:29:39,804] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 87.51 | bwd_microstep: 127.69 | bwd_inner_microstep: 127.37 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 02:29:40,280] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.13 | bwd_microstep: 271.07 | bwd_inner_microstep: 271.05 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 02:29:40,759] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.83 | bwd_microstep: 272.79 | bwd_inner_microstep: 272.77 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 02:29:41,240] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.39 | bwd_microstep: 272.73 | bwd_inner_microstep: 272.71 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.09 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1356 +[2025-05-02 02:29:41,604] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.08 | bwd_microstep: 205.94 | bwd_inner_microstep: 205.92 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 02:29:42,083] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.82 | bwd_microstep: 272.76 | bwd_inner_microstep: 272.74 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 02:29:42,561] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.91 | bwd_microstep: 272.20 | bwd_inner_microstep: 272.19 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 02:29:43,040] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.44 | bwd_microstep: 272.30 | bwd_inner_microstep: 272.28 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1346 +[2025-05-02 02:29:43,405] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.48 | bwd_microstep: 205.75 | bwd_inner_microstep: 205.56 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 02:29:43,997] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.12 | optimizer_step: 23.88 +[2025-05-02 02:29:43,998] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.80 | bwd_microstep: 354.64 | bwd_inner_microstep: 271.75 | bwd_allreduce_microstep: 82.83 | step_microstep: 31.72 +[2025-05-02 02:29:43,999] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2775.18 | bwd: 4117.51 | bwd_inner: 4033.95 | bwd_allreduce: 83.09 | step: 32.82 + 20%|█▉ | 1711/8720 [4:14:17<13:58:11, 7.18s/it] {'loss': 0.6515, 'grad_norm': 7.211212635040283, 'learning_rate': 9.293141816113776e-06, 'epoch': 1.96} + 20%|█▉ | 1711/8720 [4:14:17<13:58:11, 7.18s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 02:29:44,480] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.66 | bwd_microstep: 270.17 | bwd_inner_microstep: 270.15 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.14 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1911 +[2025-05-02 02:29:44,965] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.95 | bwd_microstep: 277.16 | bwd_inner_microstep: 277.14 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 859 +[2025-05-02 02:29:45,210] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.45 | bwd_microstep: 133.49 | bwd_inner_microstep: 133.22 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 02:29:45,689] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.28 | bwd_microstep: 273.58 | bwd_inner_microstep: 273.56 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-02 02:29:46,170] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.17 | bwd_microstep: 273.64 | bwd_inner_microstep: 273.62 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1117 +[2025-05-02 02:29:46,472] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 123.40 | bwd_microstep: 162.46 | bwd_inner_microstep: 162.37 | bwd_allreduce_microstep: 0.04 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 02:29:46,954] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.43 | bwd_microstep: 274.12 | bwd_inner_microstep: 274.10 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 02:29:47,435] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.58 | bwd_microstep: 272.82 | bwd_inner_microstep: 272.80 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 02:29:47,917] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.10 | bwd_microstep: 273.19 | bwd_inner_microstep: 273.17 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-02 02:29:48,398] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.44 | bwd_microstep: 273.82 | bwd_inner_microstep: 273.80 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 02:29:48,877] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.24 | bwd_microstep: 273.11 | bwd_inner_microstep: 273.09 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 02:29:49,358] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.57 | bwd_microstep: 272.87 | bwd_inner_microstep: 272.86 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.22 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 834 +[2025-05-02 02:29:49,614] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 111.61 | bwd_microstep: 125.14 | bwd_inner_microstep: 124.90 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.12 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 839 +[2025-05-02 02:29:49,884] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 123.10 | bwd_microstep: 125.72 | bwd_inner_microstep: 125.52 | bwd_allreduce_microstep: 0.08 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 02:29:50,362] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.37 | bwd_microstep: 272.23 | bwd_inner_microstep: 272.21 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 02:29:50,973] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.12 | optimizer_step: 24.48 +[2025-05-02 02:29:50,973] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.84 | bwd_microstep: 370.17 | bwd_inner_microstep: 271.78 | bwd_allreduce_microstep: 98.33 | step_microstep: 34.64 +[2025-05-02 02:29:50,975] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2719.77 | bwd: 3923.80 | bwd_inner: 3824.36 | bwd_allreduce: 98.79 | step: 35.95 + 20%|█▉ | 1712/8720 [4:14:24<13:51:04, 7.12s/it] {'loss': 0.5806, 'grad_norm': 7.01940393447876, 'learning_rate': 9.292189536052353e-06, 'epoch': 1.96} + 20%|█▉ | 1712/8720 [4:14:24<13:51:04, 7.12s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 02:29:51,458] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.56 | bwd_microstep: 270.72 | bwd_inner_microstep: 270.70 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1904 +[2025-05-02 02:29:51,942] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.14 | bwd_microstep: 276.03 | bwd_inner_microstep: 276.01 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1131 +[2025-05-02 02:29:52,240] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 116.21 | bwd_microstep: 164.46 | bwd_inner_microstep: 164.22 | bwd_allreduce_microstep: 0.08 | step_microstep: 0.14 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 02:29:52,720] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.86 | bwd_microstep: 273.82 | bwd_inner_microstep: 273.80 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 02:29:53,202] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.98 | bwd_microstep: 273.29 | bwd_inner_microstep: 273.27 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 02:29:53,683] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.97 | bwd_microstep: 273.40 | bwd_inner_microstep: 273.38 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 328 +[2025-05-02 02:29:53,905] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 83.61 | bwd_microstep: 122.75 | bwd_inner_microstep: 122.43 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 02:29:54,384] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.77 | bwd_microstep: 273.04 | bwd_inner_microstep: 273.03 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 02:29:54,865] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.55 | bwd_microstep: 273.12 | bwd_inner_microstep: 273.10 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 02:29:55,345] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.74 | bwd_microstep: 272.84 | bwd_inner_microstep: 272.82 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 02:29:55,824] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.90 | bwd_microstep: 272.91 | bwd_inner_microstep: 272.90 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 02:29:56,304] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.79 | bwd_microstep: 272.67 | bwd_inner_microstep: 272.65 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 02:29:56,787] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.63 | bwd_microstep: 273.17 | bwd_inner_microstep: 273.15 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 835 +[2025-05-02 02:29:57,025] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.96 | bwd_microstep: 126.38 | bwd_inner_microstep: 126.09 | bwd_allreduce_microstep: 0.15 | step_microstep: 0.20 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 831 +[2025-05-02 02:29:57,267] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.31 | bwd_microstep: 130.44 | bwd_inner_microstep: 130.14 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 02:29:57,845] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.09 | optimizer_step: 16.48 +[2025-05-02 02:29:57,845] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.50 | bwd_microstep: 348.91 | bwd_inner_microstep: 272.23 | bwd_allreduce_microstep: 76.63 | step_microstep: 24.17 +[2025-05-02 02:29:57,847] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2660.13 | bwd: 3898.04 | bwd_inner: 3820.10 | bwd_allreduce: 77.17 | step: 25.28 + 20%|█▉ | 1713/8720 [4:14:31<13:42:25, 7.04s/it] {'loss': 0.6733, 'grad_norm': 13.374833106994629, 'learning_rate': 9.291236663825205e-06, 'epoch': 1.96} + 20%|█▉ | 1713/8720 [4:14:31<13:42:25, 7.04s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 02:29:58,328] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.42 | bwd_microstep: 270.49 | bwd_inner_microstep: 270.47 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 924 +[2025-05-02 02:29:58,595] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 105.15 | bwd_microstep: 146.31 | bwd_inner_microstep: 146.10 | bwd_allreduce_microstep: 0.10 | step_microstep: 0.09 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 895 +[2025-05-02 02:29:58,843] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 98.16 | bwd_microstep: 136.19 | bwd_inner_microstep: 136.10 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1386 +[2025-05-02 02:29:59,208] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.12 | bwd_microstep: 208.79 | bwd_inner_microstep: 208.78 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-02 02:29:59,686] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.86 | bwd_microstep: 274.45 | bwd_inner_microstep: 274.43 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1359 +[2025-05-02 02:30:00,048] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.11 | bwd_microstep: 206.49 | bwd_inner_microstep: 206.47 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 02:30:00,524] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.36 | bwd_microstep: 273.03 | bwd_inner_microstep: 273.02 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 02:30:01,002] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.69 | bwd_microstep: 273.45 | bwd_inner_microstep: 273.43 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 340 +[2025-05-02 02:30:01,231] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.77 | bwd_microstep: 116.83 | bwd_inner_microstep: 116.52 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 02:30:01,712] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.27 | bwd_microstep: 273.32 | bwd_inner_microstep: 273.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.13 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 02:30:02,196] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.52 | bwd_microstep: 272.81 | bwd_inner_microstep: 272.79 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 02:30:02,681] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.90 | bwd_microstep: 272.84 | bwd_inner_microstep: 272.82 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 02:30:03,166] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.23 | bwd_microstep: 272.80 | bwd_inner_microstep: 272.78 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 02:30:03,646] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.15 | bwd_microstep: 273.23 | bwd_inner_microstep: 273.22 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 02:30:04,127] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.84 | bwd_microstep: 271.39 | bwd_inner_microstep: 271.37 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 02:30:04,712] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.07 | optimizer_gradients: 2.08 | optimizer_step: 16.48 +[2025-05-02 02:30:04,713] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.80 | bwd_microstep: 352.36 | bwd_inner_microstep: 271.97 | bwd_allreduce_microstep: 80.31 | step_microstep: 24.17 +[2025-05-02 02:30:04,714] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2655.95 | bwd: 3894.86 | bwd_inner: 3813.66 | bwd_allreduce: 80.59 | step: 25.29 + 20%|█▉ | 1714/8720 [4:14:38<13:36:09, 6.99s/it] {'loss': 0.5087, 'grad_norm': 9.235331535339355, 'learning_rate': 9.290283199563785e-06, 'epoch': 1.97} + 20%|█▉ | 1714/8720 [4:14:38<13:36:09, 6.99s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 02:30:05,196] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.91 | bwd_microstep: 271.00 | bwd_inner_microstep: 270.99 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 875 +[2025-05-02 02:30:05,475] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 98.89 | bwd_microstep: 162.19 | bwd_inner_microstep: 161.87 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1889 +[2025-05-02 02:30:05,956] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.51 | bwd_microstep: 275.02 | bwd_inner_microstep: 275.00 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1893 +[2025-05-02 02:30:06,438] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.32 | bwd_microstep: 275.06 | bwd_inner_microstep: 275.04 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1892 +[2025-05-02 02:30:06,921] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.06 | bwd_microstep: 274.78 | bwd_inner_microstep: 274.76 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 02:30:07,405] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.09 | bwd_microstep: 273.48 | bwd_inner_microstep: 273.46 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-02 02:30:07,889] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.56 | bwd_microstep: 273.86 | bwd_inner_microstep: 273.84 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 02:30:08,369] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.97 | bwd_microstep: 273.32 | bwd_inner_microstep: 273.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 02:30:08,848] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.56 | bwd_microstep: 273.13 | bwd_inner_microstep: 273.12 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 02:30:09,328] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.18 | bwd_microstep: 272.89 | bwd_inner_microstep: 272.87 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 02:30:09,810] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.35 | bwd_microstep: 273.15 | bwd_inner_microstep: 273.13 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 02:30:10,292] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.88 | bwd_microstep: 273.23 | bwd_inner_microstep: 273.21 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 02:30:10,773] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.69 | bwd_microstep: 273.48 | bwd_inner_microstep: 273.47 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 02:30:11,255] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.07 | bwd_microstep: 273.01 | bwd_inner_microstep: 272.99 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 02:30:11,737] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.07 | bwd_microstep: 271.35 | bwd_inner_microstep: 271.33 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 02:30:12,321] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.13 | optimizer_step: 16.66 +[2025-05-02 02:30:12,322] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.59 | bwd_microstep: 353.31 | bwd_inner_microstep: 272.30 | bwd_allreduce_microstep: 80.87 | step_microstep: 24.67 +[2025-05-02 02:30:12,323] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2929.28 | bwd: 4342.27 | bwd_inner: 4260.77 | bwd_allreduce: 81.05 | step: 25.71 + 20%|█▉ | 1715/8720 [4:14:46<13:57:45, 7.18s/it] {'loss': 0.676, 'grad_norm': 6.810021877288818, 'learning_rate': 9.28932914339964e-06, 'epoch': 1.97} + 20%|█▉ | 1715/8720 [4:14:46<13:57:45, 7.18s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 315 +[2025-05-02 02:30:12,579] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 81.81 | bwd_microstep: 151.69 | bwd_inner_microstep: 151.45 | bwd_allreduce_microstep: 0.10 | step_microstep: 0.10 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 460 +[2025-05-02 02:30:12,842] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 90.76 | bwd_microstep: 156.59 | bwd_inner_microstep: 156.27 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1436 +[2025-05-02 02:30:13,221] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 146.61 | bwd_microstep: 214.69 | bwd_inner_microstep: 214.68 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1888 +[2025-05-02 02:30:13,703] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.51 | bwd_microstep: 275.54 | bwd_inner_microstep: 275.52 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-02 02:30:14,185] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.79 | bwd_microstep: 274.63 | bwd_inner_microstep: 274.62 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.07 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-02 02:30:14,667] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.62 | bwd_microstep: 273.57 | bwd_inner_microstep: 273.54 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-02 02:30:15,147] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.15 | bwd_microstep: 273.27 | bwd_inner_microstep: 273.26 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.05 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1098 +[2025-05-02 02:30:15,443] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 116.15 | bwd_microstep: 161.17 | bwd_inner_microstep: 161.09 | bwd_allreduce_microstep: 0.04 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 02:30:15,924] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.09 | bwd_microstep: 273.05 | bwd_inner_microstep: 273.04 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 02:30:16,406] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.12 | bwd_microstep: 272.92 | bwd_inner_microstep: 272.90 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 02:30:16,888] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.15 | bwd_microstep: 272.75 | bwd_inner_microstep: 272.73 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 02:30:17,366] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.63 | bwd_microstep: 272.15 | bwd_inner_microstep: 272.13 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 322 +[2025-05-02 02:30:17,638] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 90.09 | bwd_microstep: 163.35 | bwd_inner_microstep: 163.04 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 02:30:18,115] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.79 | bwd_microstep: 271.56 | bwd_inner_microstep: 271.54 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 02:30:18,594] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.84 | bwd_microstep: 271.25 | bwd_inner_microstep: 271.24 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 02:30:19,178] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.14 | optimizer_step: 16.67 +[2025-05-02 02:30:19,178] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.14 | bwd_microstep: 349.05 | bwd_inner_microstep: 272.14 | bwd_allreduce_microstep: 76.81 | step_microstep: 24.63 +[2025-05-02 02:30:19,180] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2601.87 | bwd: 3927.34 | bwd_inner: 3849.36 | bwd_allreduce: 77.21 | step: 25.83 + 20%|█▉ | 1716/8720 [4:14:52<13:46:27, 7.08s/it] {'loss': 0.4986, 'grad_norm': 7.401495933532715, 'learning_rate': 9.288374495464397e-06, 'epoch': 1.97} + 20%|█▉ | 1716/8720 [4:14:52<13:46:27, 7.08s/it]dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1131 +[2025-05-02 02:30:19,483] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 116.79 | bwd_microstep: 163.80 | bwd_inner_microstep: 163.51 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2124 +[2025-05-02 02:30:20,022] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 206.18 | bwd_microstep: 313.75 | bwd_inner_microstep: 313.74 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2041 +[2025-05-02 02:30:20,540] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 201.66 | bwd_microstep: 298.32 | bwd_inner_microstep: 298.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1919 +[2025-05-02 02:30:21,023] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.10 | bwd_microstep: 277.35 | bwd_inner_microstep: 277.33 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1892 +[2025-05-02 02:30:21,505] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.67 | bwd_microstep: 275.55 | bwd_inner_microstep: 275.53 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-02 02:30:21,985] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.24 | bwd_microstep: 274.33 | bwd_inner_microstep: 274.31 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1891 +[2025-05-02 02:30:22,465] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.14 | bwd_microstep: 274.94 | bwd_inner_microstep: 274.93 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-02 02:30:22,945] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.59 | bwd_microstep: 274.57 | bwd_inner_microstep: 274.55 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 342 +[2025-05-02 02:30:23,191] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 75.79 | bwd_microstep: 155.38 | bwd_inner_microstep: 155.25 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 02:30:23,666] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.72 | bwd_microstep: 272.78 | bwd_inner_microstep: 272.77 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 838 +[2025-05-02 02:30:23,926] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.42 | bwd_microstep: 147.54 | bwd_inner_microstep: 147.39 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 02:30:24,406] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.80 | bwd_microstep: 273.00 | bwd_inner_microstep: 272.98 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 834 +[2025-05-02 02:30:24,663] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.96 | bwd_microstep: 145.59 | bwd_inner_microstep: 145.30 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 02:30:25,142] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.77 | bwd_microstep: 272.89 | bwd_inner_microstep: 272.85 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 02:30:25,622] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.54 | bwd_microstep: 271.33 | bwd_inner_microstep: 271.31 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 02:30:26,200] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.09 | optimizer_step: 16.61 +[2025-05-02 02:30:26,201] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.85 | bwd_microstep: 348.09 | bwd_inner_microstep: 272.44 | bwd_allreduce_microstep: 75.60 | step_microstep: 23.77 +[2025-05-02 02:30:26,202] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2681.90 | bwd: 4039.34 | bwd_inner: 3962.66 | bwd_allreduce: 76.02 | step: 24.99 + 20%|█▉ | 1717/8720 [4:14:59<13:44:15, 7.06s/it] {'loss': 0.8618, 'grad_norm': 6.162452220916748, 'learning_rate': 9.28741925588976e-06, 'epoch': 1.97} + 20%|█▉ | 1717/8720 [4:14:59<13:44:15, 7.06s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1914 +[2025-05-02 02:30:26,690] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 192.06 | bwd_microstep: 276.06 | bwd_inner_microstep: 276.04 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1911 +[2025-05-02 02:30:27,173] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.74 | bwd_microstep: 277.11 | bwd_inner_microstep: 277.10 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1910 +[2025-05-02 02:30:27,656] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.65 | bwd_microstep: 277.05 | bwd_inner_microstep: 277.04 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1894 +[2025-05-02 02:30:28,136] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.22 | bwd_microstep: 275.52 | bwd_inner_microstep: 275.50 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-02 02:30:28,615] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.75 | bwd_microstep: 273.86 | bwd_inner_microstep: 273.84 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 02:30:29,093] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.52 | bwd_microstep: 273.40 | bwd_inner_microstep: 273.38 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 02:30:29,570] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.09 | bwd_microstep: 273.61 | bwd_inner_microstep: 273.59 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-02 02:30:30,049] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.40 | bwd_microstep: 273.94 | bwd_inner_microstep: 273.92 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 02:30:30,526] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.64 | bwd_microstep: 272.77 | bwd_inner_microstep: 272.75 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 02:30:31,003] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.57 | bwd_microstep: 273.91 | bwd_inner_microstep: 273.89 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-02 02:30:31,482] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.16 | bwd_microstep: 274.25 | bwd_inner_microstep: 274.24 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 02:30:31,961] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.03 | bwd_microstep: 273.43 | bwd_inner_microstep: 273.41 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 02:30:32,438] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.31 | bwd_microstep: 272.84 | bwd_inner_microstep: 272.82 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 02:30:32,916] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.09 | bwd_microstep: 273.09 | bwd_inner_microstep: 273.07 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 02:30:33,394] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.28 | bwd_microstep: 272.87 | bwd_inner_microstep: 272.86 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 322 +[2025-05-02 02:30:33,744] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.23 | optimizer_step: 16.81 +[2025-05-02 02:30:33,744] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 76.24 | bwd_microstep: 235.42 | bwd_inner_microstep: 168.39 | bwd_allreduce_microstep: 66.85 | step_microstep: 24.13 +[2025-05-02 02:30:33,745] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2912.48 | bwd: 4349.16 | bwd_inner: 4281.91 | bwd_allreduce: 66.89 | step: 25.03 + 20%|█▉ | 1718/8720 [4:15:07<14:00:59, 7.21s/it] {'loss': 0.6869, 'grad_norm': 7.664870262145996, 'learning_rate': 9.286463424807517e-06, 'epoch': 1.97} + 20%|█▉ | 1718/8720 [4:15:07<14:00:59, 7.21s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 02:30:34,224] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.17 | bwd_microstep: 270.91 | bwd_inner_microstep: 270.89 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1988 +[2025-05-02 02:30:34,732] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 198.13 | bwd_microstep: 293.71 | bwd_inner_microstep: 293.69 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1941 +[2025-05-02 02:30:35,232] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.39 | bwd_microstep: 289.39 | bwd_inner_microstep: 289.37 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-02 02:30:35,714] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.07 | bwd_microstep: 274.85 | bwd_inner_microstep: 274.83 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1370 +[2025-05-02 02:30:36,078] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.48 | bwd_microstep: 207.73 | bwd_inner_microstep: 207.46 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-02 02:30:36,555] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.63 | bwd_microstep: 273.33 | bwd_inner_microstep: 273.31 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 02:30:37,032] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.34 | bwd_microstep: 272.50 | bwd_inner_microstep: 272.48 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 02:30:37,511] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.25 | bwd_microstep: 273.78 | bwd_inner_microstep: 273.77 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 02:30:37,991] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.69 | bwd_microstep: 273.22 | bwd_inner_microstep: 273.20 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 02:30:38,471] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.91 | bwd_microstep: 273.12 | bwd_inner_microstep: 273.10 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 02:30:38,950] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.65 | bwd_microstep: 273.25 | bwd_inner_microstep: 273.23 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 02:30:39,429] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.10 | bwd_microstep: 273.26 | bwd_inner_microstep: 273.24 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 02:30:39,906] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.93 | bwd_microstep: 272.00 | bwd_inner_microstep: 271.98 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 02:30:40,386] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.80 | bwd_microstep: 271.69 | bwd_inner_microstep: 271.67 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 02:30:40,869] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.26 | bwd_microstep: 272.10 | bwd_inner_microstep: 272.08 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1948 +[2025-05-02 02:30:41,476] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.09 | optimizer_step: 16.55 +[2025-05-02 02:30:41,477] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.81 | bwd_microstep: 366.61 | bwd_inner_microstep: 290.08 | bwd_allreduce_microstep: 76.48 | step_microstep: 24.29 +[2025-05-02 02:30:41,478] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2989.26 | bwd: 4431.50 | bwd_inner: 4354.40 | bwd_allreduce: 76.68 | step: 25.30 + 20%|█▉ | 1719/8720 [4:15:15<14:19:21, 7.36s/it] {'loss': 0.5756, 'grad_norm': 10.881269454956055, 'learning_rate': 9.28550700234954e-06, 'epoch': 1.97} + 20%|█▉ | 1719/8720 [4:15:15<14:19:21, 7.36s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 391 +[2025-05-02 02:30:41,740] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 83.88 | bwd_microstep: 156.29 | bwd_inner_microstep: 155.99 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1927 +[2025-05-02 02:30:42,239] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 194.72 | bwd_microstep: 287.81 | bwd_inner_microstep: 287.79 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 359 +[2025-05-02 02:30:42,486] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 79.36 | bwd_microstep: 150.75 | bwd_inner_microstep: 150.43 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-02 02:30:42,967] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.59 | bwd_microstep: 274.30 | bwd_inner_microstep: 274.28 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 845 +[2025-05-02 02:30:43,222] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.20 | bwd_microstep: 143.45 | bwd_inner_microstep: 143.19 | bwd_allreduce_microstep: 0.09 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-02 02:30:43,701] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.66 | bwd_microstep: 273.58 | bwd_inner_microstep: 273.56 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 02:30:44,182] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.72 | bwd_microstep: 273.40 | bwd_inner_microstep: 273.38 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 02:30:44,662] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.60 | bwd_microstep: 272.38 | bwd_inner_microstep: 272.36 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.06 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 323 +[2025-05-02 02:30:44,937] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 106.90 | bwd_microstep: 148.22 | bwd_inner_microstep: 147.92 | bwd_allreduce_microstep: 0.14 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 02:30:45,418] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.75 | bwd_microstep: 273.25 | bwd_inner_microstep: 273.23 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 324 +[2025-05-02 02:30:45,675] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 83.66 | bwd_microstep: 156.64 | bwd_inner_microstep: 156.43 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 02:30:46,154] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.82 | bwd_microstep: 273.43 | bwd_inner_microstep: 273.41 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 02:30:46,635] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.65 | bwd_microstep: 272.90 | bwd_inner_microstep: 272.89 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 02:30:47,113] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.57 | bwd_microstep: 271.61 | bwd_inner_microstep: 271.59 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 02:30:47,593] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.94 | bwd_microstep: 271.34 | bwd_inner_microstep: 271.32 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 02:30:48,172] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.08 | optimizer_step: 16.47 +[2025-05-02 02:30:48,172] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.47 | bwd_microstep: 348.87 | bwd_inner_microstep: 272.34 | bwd_allreduce_microstep: 76.48 | step_microstep: 23.98 +[2025-05-02 02:30:48,174] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2529.11 | bwd: 3848.34 | bwd_inner: 3770.42 | bwd_allreduce: 77.03 | step: 25.20 + 20%|█▉ | 1720/8720 [4:15:21<13:55:47, 7.16s/it] {'loss': 0.8406, 'grad_norm': 9.6709623336792, 'learning_rate': 9.284549988647776e-06, 'epoch': 1.97} + 20%|█▉ | 1720/8720 [4:15:21<13:55:47, 7.16s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 02:30:48,655] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.84 | bwd_microstep: 271.29 | bwd_inner_microstep: 271.27 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 889 +[2025-05-02 02:30:48,909] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 99.01 | bwd_microstep: 138.63 | bwd_inner_microstep: 138.34 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.19 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 378 +[2025-05-02 02:30:49,140] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 67.42 | bwd_microstep: 149.63 | bwd_inner_microstep: 149.31 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-02 02:30:49,619] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.76 | bwd_microstep: 274.73 | bwd_inner_microstep: 274.71 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 02:30:50,100] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.01 | bwd_microstep: 273.39 | bwd_inner_microstep: 273.38 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 329 +[2025-05-02 02:30:50,348] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 81.29 | bwd_microstep: 150.24 | bwd_inner_microstep: 150.01 | bwd_allreduce_microstep: 0.08 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 02:30:50,828] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.69 | bwd_microstep: 273.48 | bwd_inner_microstep: 273.46 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-02 02:30:51,309] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.45 | bwd_microstep: 274.13 | bwd_inner_microstep: 274.11 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 333 +[2025-05-02 02:30:51,581] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 89.08 | bwd_microstep: 165.94 | bwd_inner_microstep: 165.63 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.19 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1096 +[2025-05-02 02:30:51,874] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 115.11 | bwd_microstep: 161.56 | bwd_inner_microstep: 161.24 | bwd_allreduce_microstep: 0.14 | step_microstep: 0.10 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 328 +[2025-05-02 02:30:52,123] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 82.68 | bwd_microstep: 150.17 | bwd_inner_microstep: 150.03 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 02:30:52,602] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.91 | bwd_microstep: 272.87 | bwd_inner_microstep: 272.86 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 02:30:53,080] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.58 | bwd_microstep: 272.31 | bwd_inner_microstep: 272.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 02:30:53,558] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.34 | bwd_microstep: 272.26 | bwd_inner_microstep: 272.24 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 02:30:54,036] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.91 | bwd_microstep: 272.48 | bwd_inner_microstep: 272.46 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1349 +[2025-05-02 02:30:54,501] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.04 | optimizer_gradients: 2.05 | optimizer_step: 16.49 +[2025-05-02 02:30:54,501] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.22 | bwd_microstep: 283.25 | bwd_inner_microstep: 206.65 | bwd_allreduce_microstep: 76.46 | step_microstep: 24.12 +[2025-05-02 02:30:54,503] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2369.97 | bwd: 3656.52 | bwd_inner: 3578.36 | bwd_allreduce: 77.14 | step: 25.55 + 20%|█▉ | 1721/8720 [4:15:28<13:26:28, 6.91s/it] {'loss': 0.5554, 'grad_norm': 7.24700927734375, 'learning_rate': 9.283592383834263e-06, 'epoch': 1.97} + 20%|█▉ | 1721/8720 [4:15:28<13:26:28, 6.91s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 321 +[2025-05-02 02:30:54,752] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 79.15 | bwd_microstep: 148.50 | bwd_inner_microstep: 148.19 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1898 +[2025-05-02 02:30:55,237] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 191.90 | bwd_microstep: 275.43 | bwd_inner_microstep: 275.42 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 02:30:55,717] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.85 | bwd_microstep: 273.47 | bwd_inner_microstep: 273.45 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 02:30:56,195] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.10 | bwd_microstep: 274.18 | bwd_inner_microstep: 274.16 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 02:30:56,672] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.45 | bwd_microstep: 273.14 | bwd_inner_microstep: 273.12 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 845 +[2025-05-02 02:30:56,922] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.91 | bwd_microstep: 140.34 | bwd_inner_microstep: 140.18 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 02:30:57,396] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.48 | bwd_microstep: 272.37 | bwd_inner_microstep: 272.35 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 324 +[2025-05-02 02:30:57,629] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 74.96 | bwd_microstep: 144.29 | bwd_inner_microstep: 144.11 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 02:30:58,104] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.05 | bwd_microstep: 272.22 | bwd_inner_microstep: 272.20 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 02:30:58,578] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.64 | bwd_microstep: 271.05 | bwd_inner_microstep: 271.03 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 02:30:59,053] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.28 | bwd_microstep: 271.89 | bwd_inner_microstep: 271.87 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 02:30:59,528] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.51 | bwd_microstep: 271.75 | bwd_inner_microstep: 271.73 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 02:31:00,001] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.47 | bwd_microstep: 270.98 | bwd_inner_microstep: 270.96 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 02:31:00,474] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.17 | bwd_microstep: 271.46 | bwd_inner_microstep: 271.44 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 02:31:00,950] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.48 | bwd_microstep: 271.39 | bwd_inner_microstep: 271.37 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 418 +[2025-05-02 02:31:01,260] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.04 | optimizer_gradients: 2.04 | optimizer_step: 16.52 +[2025-05-02 02:31:01,260] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 73.47 | bwd_microstep: 201.06 | bwd_inner_microstep: 135.37 | bwd_allreduce_microstep: 65.61 | step_microstep: 23.34 +[2025-05-02 02:31:01,262] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2584.60 | bwd: 3903.56 | bwd_inner: 3837.17 | bwd_allreduce: 65.89 | step: 24.25 + 20%|█▉ | 1722/8720 [4:15:35<13:20:52, 6.87s/it] {'loss': 0.6581, 'grad_norm': 14.183053016662598, 'learning_rate': 9.282634188041112e-06, 'epoch': 1.97} + 20%|█▉ | 1722/8720 [4:15:35<13:20:52, 6.87s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1889 +[2025-05-02 02:31:01,744] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.94 | bwd_microstep: 273.94 | bwd_inner_microstep: 273.92 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1898 +[2025-05-02 02:31:02,224] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.03 | bwd_microstep: 275.22 | bwd_inner_microstep: 275.20 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 02:31:02,700] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.45 | bwd_microstep: 273.52 | bwd_inner_microstep: 273.50 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 02:31:03,179] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.42 | bwd_microstep: 273.89 | bwd_inner_microstep: 273.88 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 844 +[2025-05-02 02:31:03,418] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.97 | bwd_microstep: 131.93 | bwd_inner_microstep: 131.84 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 02:31:03,894] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.18 | bwd_microstep: 272.84 | bwd_inner_microstep: 272.83 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 02:31:04,372] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.81 | bwd_microstep: 273.49 | bwd_inner_microstep: 273.47 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1349 +[2025-05-02 02:31:04,733] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.46 | bwd_microstep: 205.93 | bwd_inner_microstep: 205.91 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 02:31:05,209] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.59 | bwd_microstep: 272.90 | bwd_inner_microstep: 272.88 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 02:31:05,686] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.75 | bwd_microstep: 272.63 | bwd_inner_microstep: 272.61 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 02:31:06,161] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.04 | bwd_microstep: 272.43 | bwd_inner_microstep: 272.41 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 02:31:06,637] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.00 | bwd_microstep: 272.58 | bwd_inner_microstep: 272.56 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 02:31:07,112] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.10 | bwd_microstep: 271.27 | bwd_inner_microstep: 271.26 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 02:31:07,588] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.15 | bwd_microstep: 271.36 | bwd_inner_microstep: 271.34 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 02:31:08,064] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.56 | bwd_microstep: 271.50 | bwd_inner_microstep: 271.48 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1981 +[2025-05-02 02:31:08,659] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.04 | optimizer_gradients: 2.08 | optimizer_step: 16.49 +[2025-05-02 02:31:08,659] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 198.58 | bwd_microstep: 358.68 | bwd_inner_microstep: 293.01 | bwd_allreduce_microstep: 65.62 | step_microstep: 23.44 +[2025-05-02 02:31:08,660] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2883.74 | bwd: 4244.13 | bwd_inner: 4178.10 | bwd_allreduce: 65.75 | step: 24.11 + 20%|█▉ | 1723/8720 [4:15:42<13:39:22, 7.03s/it] {'loss': 0.474, 'grad_norm': 9.107953071594238, 'learning_rate': 9.281675401400523e-06, 'epoch': 1.98} + 20%|█▉ | 1723/8720 [4:15:42<13:39:22, 7.03s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 366 +[2025-05-02 02:31:08,912] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 68.51 | bwd_microstep: 165.28 | bwd_inner_microstep: 164.97 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2005 +[2025-05-02 02:31:09,420] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 198.06 | bwd_microstep: 295.32 | bwd_inner_microstep: 295.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 361 +[2025-05-02 02:31:09,659] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 71.59 | bwd_microstep: 153.99 | bwd_inner_microstep: 153.86 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 342 +[2025-05-02 02:31:09,895] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 72.13 | bwd_microstep: 150.21 | bwd_inner_microstep: 150.01 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-02 02:31:10,373] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.38 | bwd_microstep: 273.31 | bwd_inner_microstep: 273.29 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-02 02:31:10,852] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.23 | bwd_microstep: 274.49 | bwd_inner_microstep: 274.47 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 02:31:11,328] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.91 | bwd_microstep: 272.80 | bwd_inner_microstep: 272.79 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-02 02:31:11,807] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.36 | bwd_microstep: 273.77 | bwd_inner_microstep: 273.75 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.14 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 02:31:12,285] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.85 | bwd_microstep: 273.33 | bwd_inner_microstep: 273.31 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 02:31:12,761] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.23 | bwd_microstep: 272.39 | bwd_inner_microstep: 272.37 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1346 +[2025-05-02 02:31:13,121] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.00 | bwd_microstep: 205.72 | bwd_inner_microstep: 205.71 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 02:31:13,596] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.39 | bwd_microstep: 272.82 | bwd_inner_microstep: 272.80 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 02:31:14,070] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.13 | bwd_microstep: 271.30 | bwd_inner_microstep: 271.27 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 02:31:14,547] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.06 | bwd_microstep: 272.46 | bwd_inner_microstep: 272.44 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 02:31:15,022] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.48 | bwd_microstep: 271.02 | bwd_inner_microstep: 271.00 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-02 02:31:15,588] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.05 | optimizer_step: 16.46 +[2025-05-02 02:31:15,589] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.37 | bwd_microstep: 340.17 | bwd_inner_microstep: 274.14 | bwd_allreduce_microstep: 65.98 | step_microstep: 23.39 +[2025-05-02 02:31:15,590] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2624.40 | bwd: 4038.44 | bwd_inner: 3971.63 | bwd_allreduce: 66.28 | step: 24.45 + 20%|█▉ | 1724/8720 [4:15:49<13:35:52, 7.00s/it] {'loss': 0.8879, 'grad_norm': 10.740958213806152, 'learning_rate': 9.280716024044771e-06, 'epoch': 1.98} + 20%|█▉ | 1724/8720 [4:15:49<13:35:52, 7.00s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 02:31:16,067] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.47 | bwd_microstep: 270.57 | bwd_inner_microstep: 270.56 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 962 +[2025-05-02 02:31:16,337] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 105.83 | bwd_microstep: 149.78 | bwd_inner_microstep: 149.67 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 433 +[2025-05-02 02:31:16,556] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 84.11 | bwd_microstep: 120.71 | bwd_inner_microstep: 120.47 | bwd_allreduce_microstep: 0.10 | step_microstep: 0.08 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 405 +[2025-05-02 02:31:16,769] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 75.64 | bwd_microstep: 123.96 | bwd_inner_microstep: 123.84 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 362 +[2025-05-02 02:31:16,972] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 72.05 | bwd_microstep: 117.58 | bwd_inner_microstep: 117.45 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1892 +[2025-05-02 02:31:17,451] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.68 | bwd_microstep: 274.76 | bwd_inner_microstep: 274.74 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-02 02:31:17,930] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.81 | bwd_microstep: 274.07 | bwd_inner_microstep: 274.05 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-02 02:31:18,408] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.17 | bwd_microstep: 273.79 | bwd_inner_microstep: 273.77 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 02:31:18,887] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.67 | bwd_microstep: 272.19 | bwd_inner_microstep: 272.17 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 02:31:19,369] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.61 | bwd_microstep: 272.48 | bwd_inner_microstep: 272.46 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 02:31:19,851] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.83 | bwd_microstep: 272.48 | bwd_inner_microstep: 272.46 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 02:31:20,335] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.11 | bwd_microstep: 272.28 | bwd_inner_microstep: 272.26 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 02:31:20,815] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.02 | bwd_microstep: 272.71 | bwd_inner_microstep: 272.69 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 02:31:21,294] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.01 | bwd_microstep: 272.27 | bwd_inner_microstep: 272.25 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 02:31:21,773] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.32 | bwd_microstep: 270.97 | bwd_inner_microstep: 270.95 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 02:31:22,350] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.09 | optimizer_step: 16.49 +[2025-05-02 02:31:22,351] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.71 | bwd_microstep: 348.51 | bwd_inner_microstep: 271.50 | bwd_allreduce_microstep: 76.96 | step_microstep: 24.22 +[2025-05-02 02:31:22,352] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2595.69 | bwd: 3859.17 | bwd_inner: 3781.40 | bwd_allreduce: 77.26 | step: 25.13 + 20%|█▉ | 1725/8720 [4:15:56<13:27:36, 6.93s/it] {'loss': 0.6202, 'grad_norm': 11.883797645568848, 'learning_rate': 9.279756056106216e-06, 'epoch': 1.98} + 20%|█▉ | 1725/8720 [4:15:56<13:27:36, 6.93s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 02:31:22,833] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.79 | bwd_microstep: 270.17 | bwd_inner_microstep: 270.16 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1971 +[2025-05-02 02:31:23,338] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 197.54 | bwd_microstep: 291.44 | bwd_inner_microstep: 291.42 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1902 +[2025-05-02 02:31:23,819] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.33 | bwd_microstep: 275.59 | bwd_inner_microstep: 275.57 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1895 +[2025-05-02 02:31:24,303] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.53 | bwd_microstep: 275.29 | bwd_inner_microstep: 275.27 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1895 +[2025-05-02 02:31:24,788] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.70 | bwd_microstep: 275.13 | bwd_inner_microstep: 275.11 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1893 +[2025-05-02 02:31:25,269] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.95 | bwd_microstep: 275.21 | bwd_inner_microstep: 275.19 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1892 +[2025-05-02 02:31:25,750] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.99 | bwd_microstep: 274.67 | bwd_inner_microstep: 274.66 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 845 +[2025-05-02 02:31:25,993] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.99 | bwd_microstep: 132.62 | bwd_inner_microstep: 132.44 | bwd_allreduce_microstep: 0.10 | step_microstep: 0.17 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 02:31:26,468] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.37 | bwd_microstep: 272.62 | bwd_inner_microstep: 272.60 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 02:31:26,945] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.85 | bwd_microstep: 272.83 | bwd_inner_microstep: 272.81 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 324 +[2025-05-02 02:31:27,153] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 75.26 | bwd_microstep: 118.90 | bwd_inner_microstep: 118.77 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 02:31:27,627] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.95 | bwd_microstep: 272.16 | bwd_inner_microstep: 272.15 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 02:31:28,103] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.48 | bwd_microstep: 272.92 | bwd_inner_microstep: 272.90 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 835 +[2025-05-02 02:31:28,335] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 91.32 | bwd_microstep: 126.07 | bwd_inner_microstep: 126.01 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.08 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 318 +[2025-05-02 02:31:28,537] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 68.19 | bwd_microstep: 120.92 | bwd_inner_microstep: 120.79 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 316 +[2025-05-02 02:31:28,846] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.08 | optimizer_step: 16.58 +[2025-05-02 02:31:28,847] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 68.88 | bwd_microstep: 203.69 | bwd_inner_microstep: 136.84 | bwd_allreduce_microstep: 66.77 | step_microstep: 23.80 +[2025-05-02 02:31:28,848] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2482.84 | bwd: 3730.31 | bwd_inner: 3662.76 | bwd_allreduce: 67.08 | step: 24.78 + 20%|█▉ | 1726/8720 [4:16:02<13:12:20, 6.80s/it] {'loss': 0.7689, 'grad_norm': 6.915977478027344, 'learning_rate': 9.278795497717295e-06, 'epoch': 1.98} + 20%|█▉ | 1726/8720 [4:16:02<13:12:20, 6.80s/it]dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 898 +[2025-05-02 02:31:29,136] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 101.84 | bwd_microstep: 167.33 | bwd_inner_microstep: 167.00 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1895 +[2025-05-02 02:31:29,615] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.30 | bwd_microstep: 275.01 | bwd_inner_microstep: 274.99 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.21 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1894 +[2025-05-02 02:31:30,095] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.61 | bwd_microstep: 275.02 | bwd_inner_microstep: 275.00 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-02 02:31:30,573] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.46 | bwd_microstep: 273.63 | bwd_inner_microstep: 273.61 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 02:31:31,052] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.32 | bwd_microstep: 272.81 | bwd_inner_microstep: 272.79 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 842 +[2025-05-02 02:31:31,317] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.90 | bwd_microstep: 150.65 | bwd_inner_microstep: 150.50 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 329 +[2025-05-02 02:31:31,575] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 88.69 | bwd_microstep: 153.41 | bwd_inner_microstep: 153.16 | bwd_allreduce_microstep: 0.09 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 02:31:32,054] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.33 | bwd_microstep: 272.68 | bwd_inner_microstep: 272.66 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 02:31:32,534] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.27 | bwd_microstep: 272.90 | bwd_inner_microstep: 272.89 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 02:31:33,015] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.45 | bwd_microstep: 272.85 | bwd_inner_microstep: 272.83 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 830 +[2025-05-02 02:31:33,275] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.88 | bwd_microstep: 147.85 | bwd_inner_microstep: 147.59 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 02:31:33,752] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.54 | bwd_microstep: 271.29 | bwd_inner_microstep: 271.27 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 02:31:34,228] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.33 | bwd_microstep: 271.04 | bwd_inner_microstep: 271.03 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 02:31:34,702] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.14 | bwd_microstep: 270.74 | bwd_inner_microstep: 270.73 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 02:31:35,177] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.25 | bwd_microstep: 271.05 | bwd_inner_microstep: 271.03 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1988 +[2025-05-02 02:31:35,781] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.12 | optimizer_step: 16.60 +[2025-05-02 02:31:35,782] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 197.63 | bwd_microstep: 367.36 | bwd_inner_microstep: 293.96 | bwd_allreduce_microstep: 73.33 | step_microstep: 23.85 +[2025-05-02 02:31:35,783] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2647.62 | bwd: 3985.69 | bwd_inner: 3911.24 | bwd_allreduce: 73.76 | step: 25.18 + 20%|█▉ | 1727/8720 [4:16:09<13:17:03, 6.84s/it] {'loss': 0.568, 'grad_norm': 26.249189376831055, 'learning_rate': 9.277834349010535e-06, 'epoch': 1.98} + 20%|█▉ | 1727/8720 [4:16:09<13:17:03, 6.84s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 02:31:36,262] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.57 | bwd_microstep: 270.57 | bwd_inner_microstep: 270.46 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.14 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1988 +[2025-05-02 02:31:36,772] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 197.96 | bwd_microstep: 293.67 | bwd_inner_microstep: 293.65 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1926 +[2025-05-02 02:31:37,273] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 194.97 | bwd_microstep: 287.55 | bwd_inner_microstep: 287.53 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1887 +[2025-05-02 02:31:37,760] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.51 | bwd_microstep: 274.75 | bwd_inner_microstep: 274.74 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 02:31:38,243] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.28 | bwd_microstep: 273.48 | bwd_inner_microstep: 273.46 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 02:31:38,724] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.73 | bwd_microstep: 273.53 | bwd_inner_microstep: 273.51 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 02:31:39,203] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.45 | bwd_microstep: 273.00 | bwd_inner_microstep: 272.98 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.21 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 02:31:39,684] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.94 | bwd_microstep: 273.66 | bwd_inner_microstep: 273.64 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 02:31:40,166] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.51 | bwd_microstep: 272.77 | bwd_inner_microstep: 272.75 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 02:31:40,649] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.18 | bwd_microstep: 272.62 | bwd_inner_microstep: 272.61 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 02:31:41,135] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.08 | bwd_microstep: 272.96 | bwd_inner_microstep: 272.94 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 02:31:41,616] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.00 | bwd_microstep: 272.69 | bwd_inner_microstep: 272.68 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 02:31:42,098] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.75 | bwd_microstep: 272.34 | bwd_inner_microstep: 272.33 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 02:31:42,576] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.02 | bwd_microstep: 272.52 | bwd_inner_microstep: 272.50 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 835 +[2025-05-02 02:31:42,847] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.98 | bwd_microstep: 154.94 | bwd_inner_microstep: 154.74 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1346 +[2025-05-02 02:31:43,312] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.13 | optimizer_step: 16.68 +[2025-05-02 02:31:43,312] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 139.71 | bwd_microstep: 284.05 | bwd_inner_microstep: 206.35 | bwd_allreduce_microstep: 77.57 | step_microstep: 24.72 +[2025-05-02 02:31:43,314] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2893.21 | bwd: 4295.16 | bwd_inner: 4217.01 | bwd_allreduce: 77.76 | step: 26.11 + 20%|█▉ | 1728/8720 [4:16:17<13:41:11, 7.05s/it] {'loss': 0.5309, 'grad_norm': 17.3670597076416, 'learning_rate': 9.276872610118538e-06, 'epoch': 1.98} + 20%|█▉ | 1728/8720 [4:16:17<13:41:11, 7.05s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 02:31:43,796] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.23 | bwd_microstep: 270.58 | bwd_inner_microstep: 270.57 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1942 +[2025-05-02 02:31:44,301] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 198.04 | bwd_microstep: 288.61 | bwd_inner_microstep: 288.59 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-02 02:31:44,781] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.46 | bwd_microstep: 274.30 | bwd_inner_microstep: 274.28 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1888 +[2025-05-02 02:31:45,260] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.37 | bwd_microstep: 274.65 | bwd_inner_microstep: 274.64 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 02:31:45,740] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.17 | bwd_microstep: 273.28 | bwd_inner_microstep: 273.27 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 02:31:46,222] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.86 | bwd_microstep: 273.47 | bwd_inner_microstep: 273.45 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 02:31:46,705] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.39 | bwd_microstep: 273.14 | bwd_inner_microstep: 273.12 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 02:31:47,187] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.27 | bwd_microstep: 273.06 | bwd_inner_microstep: 273.04 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-02 02:31:47,667] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.25 | bwd_microstep: 273.05 | bwd_inner_microstep: 273.04 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1349 +[2025-05-02 02:31:48,031] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.41 | bwd_microstep: 206.27 | bwd_inner_microstep: 206.08 | bwd_allreduce_microstep: 0.09 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 02:31:48,510] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.37 | bwd_microstep: 272.46 | bwd_inner_microstep: 272.44 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 02:31:48,992] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.48 | bwd_microstep: 272.82 | bwd_inner_microstep: 272.80 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 325 +[2025-05-02 02:31:49,252] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 86.90 | bwd_microstep: 154.69 | bwd_inner_microstep: 154.53 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 02:31:49,732] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.46 | bwd_microstep: 272.50 | bwd_inner_microstep: 272.48 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 02:31:50,212] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.51 | bwd_microstep: 272.54 | bwd_inner_microstep: 272.52 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 02:31:50,804] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.15 | optimizer_step: 16.62 +[2025-05-02 02:31:50,805] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.32 | bwd_microstep: 357.11 | bwd_inner_microstep: 271.61 | bwd_allreduce_microstep: 85.45 | step_microstep: 24.55 +[2025-05-02 02:31:50,806] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2877.12 | bwd: 4282.61 | bwd_inner: 4196.49 | bwd_allreduce: 85.63 | step: 25.79 + 20%|█▉ | 1729/8720 [4:16:24<13:56:38, 7.18s/it] {'loss': 0.6351, 'grad_norm': 17.590484619140625, 'learning_rate': 9.275910281173987e-06, 'epoch': 1.98} + 20%|█▉ | 1729/8720 [4:16:24<13:56:38, 7.18s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1903 +[2025-05-02 02:31:51,295] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.32 | bwd_microstep: 275.65 | bwd_inner_microstep: 275.63 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 891 +[2025-05-02 02:31:51,561] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 96.35 | bwd_microstep: 153.00 | bwd_inner_microstep: 152.80 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-02 02:31:52,043] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.20 | bwd_microstep: 274.79 | bwd_inner_microstep: 274.77 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-02 02:31:52,526] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.83 | bwd_microstep: 273.92 | bwd_inner_microstep: 273.90 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 02:31:53,013] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.52 | bwd_microstep: 273.67 | bwd_inner_microstep: 273.65 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 02:31:53,495] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.78 | bwd_microstep: 273.35 | bwd_inner_microstep: 273.33 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 02:31:53,976] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.51 | bwd_microstep: 273.93 | bwd_inner_microstep: 273.91 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 02:31:54,457] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.73 | bwd_microstep: 273.43 | bwd_inner_microstep: 273.41 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 02:31:54,938] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.34 | bwd_microstep: 272.52 | bwd_inner_microstep: 272.44 | bwd_allreduce_microstep: 0.03 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 02:31:55,421] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.01 | bwd_microstep: 272.34 | bwd_inner_microstep: 272.32 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 02:31:55,908] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.81 | bwd_microstep: 272.96 | bwd_inner_microstep: 272.94 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 02:31:56,394] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.51 | bwd_microstep: 272.63 | bwd_inner_microstep: 272.62 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 02:31:56,874] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.47 | bwd_microstep: 272.60 | bwd_inner_microstep: 272.58 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 02:31:57,355] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.04 | bwd_microstep: 272.99 | bwd_inner_microstep: 272.97 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 02:31:57,833] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.47 | bwd_microstep: 271.74 | bwd_inner_microstep: 271.72 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.12 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 827 +[2025-05-02 02:31:58,218] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.19 | optimizer_step: 16.76 +[2025-05-02 02:31:58,219] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 104.58 | bwd_microstep: 238.08 | bwd_inner_microstep: 160.74 | bwd_allreduce_microstep: 77.18 | step_microstep: 24.82 +[2025-05-02 02:31:58,220] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2849.07 | bwd: 4217.64 | bwd_inner: 4139.86 | bwd_allreduce: 77.34 | step: 26.14 + 20%|█▉ | 1730/8720 [4:16:31<14:04:41, 7.25s/it] {'loss': 0.7171, 'grad_norm': 11.175262451171875, 'learning_rate': 9.274947362309651e-06, 'epoch': 1.98} + 20%|█▉ | 1730/8720 [4:16:31<14:04:41, 7.25s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1891 +[2025-05-02 02:31:58,707] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.33 | bwd_microstep: 274.19 | bwd_inner_microstep: 274.17 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1893 +[2025-05-02 02:31:59,192] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.47 | bwd_microstep: 275.20 | bwd_inner_microstep: 275.15 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1892 +[2025-05-02 02:31:59,678] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.04 | bwd_microstep: 274.77 | bwd_inner_microstep: 274.75 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1887 +[2025-05-02 02:32:00,160] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.00 | bwd_microstep: 274.57 | bwd_inner_microstep: 274.55 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.08 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 338 +[2025-05-02 02:32:00,410] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 81.67 | bwd_microstep: 152.23 | bwd_inner_microstep: 151.93 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 02:32:00,891] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.03 | bwd_microstep: 273.68 | bwd_inner_microstep: 273.66 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.08 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1353 +[2025-05-02 02:32:01,259] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 142.28 | bwd_microstep: 207.18 | bwd_inner_microstep: 206.93 | bwd_allreduce_microstep: 0.17 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 02:32:01,744] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.21 | bwd_microstep: 272.22 | bwd_inner_microstep: 272.20 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 834 +[2025-05-02 02:32:02,002] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.99 | bwd_microstep: 146.91 | bwd_inner_microstep: 146.66 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 02:32:02,479] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.18 | bwd_microstep: 272.09 | bwd_inner_microstep: 272.07 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 02:32:02,957] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.88 | bwd_microstep: 272.27 | bwd_inner_microstep: 272.25 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 02:32:03,434] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.07 | bwd_microstep: 271.19 | bwd_inner_microstep: 271.17 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.22 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 827 +[2025-05-02 02:32:03,690] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.29 | bwd_microstep: 143.85 | bwd_inner_microstep: 143.69 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 02:32:04,168] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.17 | bwd_microstep: 271.34 | bwd_inner_microstep: 271.33 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 02:32:04,645] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.15 | bwd_microstep: 271.30 | bwd_inner_microstep: 271.29 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 02:32:05,229] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.08 | optimizer_step: 19.70 +[2025-05-02 02:32:05,230] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.74 | bwd_microstep: 351.67 | bwd_inner_microstep: 271.63 | bwd_allreduce_microstep: 79.98 | step_microstep: 27.55 +[2025-05-02 02:32:05,231] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2675.11 | bwd: 4004.77 | bwd_inner: 3923.59 | bwd_allreduce: 80.51 | step: 28.97 + 20%|█▉ | 1731/8720 [4:16:38<13:56:11, 7.18s/it] {'loss': 0.464, 'grad_norm': 11.47154712677002, 'learning_rate': 9.273983853658378e-06, 'epoch': 1.98} + 20%|█▉ | 1731/8720 [4:16:38<13:56:11, 7.18s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 02:32:05,712] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.71 | bwd_microstep: 270.61 | bwd_inner_microstep: 270.59 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 3522 +[2025-05-02 02:32:06,524] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 290.92 | bwd_microstep: 503.94 | bwd_inner_microstep: 503.92 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 987 +[2025-05-02 02:32:06,791] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 101.90 | bwd_microstep: 150.53 | bwd_inner_microstep: 150.20 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 344 +[2025-05-02 02:32:07,037] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 80.97 | bwd_microstep: 151.15 | bwd_inner_microstep: 150.91 | bwd_allreduce_microstep: 0.10 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 02:32:07,514] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.73 | bwd_microstep: 273.46 | bwd_inner_microstep: 273.44 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 02:32:07,991] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.23 | bwd_microstep: 272.64 | bwd_inner_microstep: 272.62 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 02:32:08,467] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.70 | bwd_microstep: 272.84 | bwd_inner_microstep: 272.83 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 02:32:08,945] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.54 | bwd_microstep: 272.87 | bwd_inner_microstep: 272.86 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 02:32:09,421] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.94 | bwd_microstep: 273.18 | bwd_inner_microstep: 273.17 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 02:32:09,896] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.96 | bwd_microstep: 272.67 | bwd_inner_microstep: 272.65 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.07 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1089 +[2025-05-02 02:32:10,186] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 114.97 | bwd_microstep: 160.46 | bwd_inner_microstep: 160.35 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 02:32:10,660] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.43 | bwd_microstep: 271.22 | bwd_inner_microstep: 271.20 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 02:32:11,134] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.38 | bwd_microstep: 271.32 | bwd_inner_microstep: 271.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.16 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 02:32:11,609] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.28 | bwd_microstep: 271.22 | bwd_inner_microstep: 271.20 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 02:32:12,084] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.28 | bwd_microstep: 271.24 | bwd_inner_microstep: 271.22 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1911 +[2025-05-02 02:32:12,655] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.04 | optimizer_gradients: 2.08 | optimizer_step: 16.44 +[2025-05-02 02:32:12,656] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.45 | bwd_microstep: 344.34 | bwd_inner_microstep: 277.75 | bwd_allreduce_microstep: 66.54 | step_microstep: 23.39 +[2025-05-02 02:32:12,657] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2848.13 | bwd: 4303.73 | bwd_inner: 4236.34 | bwd_allreduce: 66.86 | step: 24.63 + 20%|█▉ | 1732/8720 [4:16:46<14:04:38, 7.25s/it] {'loss': 0.4831, 'grad_norm': 12.078719139099121, 'learning_rate': 9.273019755353092e-06, 'epoch': 1.99} + 20%|█▉ | 1732/8720 [4:16:46<14:04:38, 7.25s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 02:32:13,137] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.35 | bwd_microstep: 272.45 | bwd_inner_microstep: 272.43 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 347 +[2025-05-02 02:32:13,371] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 68.72 | bwd_microstep: 151.21 | bwd_inner_microstep: 150.91 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1889 +[2025-05-02 02:32:13,850] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.23 | bwd_microstep: 275.28 | bwd_inner_microstep: 275.26 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1886 +[2025-05-02 02:32:14,330] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.84 | bwd_microstep: 274.79 | bwd_inner_microstep: 274.77 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 02:32:14,809] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.45 | bwd_microstep: 273.93 | bwd_inner_microstep: 273.92 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1356 +[2025-05-02 02:32:15,172] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.90 | bwd_microstep: 206.52 | bwd_inner_microstep: 206.50 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 02:32:15,650] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.88 | bwd_microstep: 273.35 | bwd_inner_microstep: 273.33 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 02:32:16,129] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.09 | bwd_microstep: 273.02 | bwd_inner_microstep: 273.01 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 323 +[2025-05-02 02:32:16,361] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 67.87 | bwd_microstep: 151.73 | bwd_inner_microstep: 151.56 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 02:32:16,837] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.90 | bwd_microstep: 272.73 | bwd_inner_microstep: 272.71 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 02:32:17,313] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.30 | bwd_microstep: 272.61 | bwd_inner_microstep: 272.59 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 333 +[2025-05-02 02:32:17,524] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 68.35 | bwd_microstep: 128.96 | bwd_inner_microstep: 128.63 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 02:32:18,002] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.34 | bwd_microstep: 273.14 | bwd_inner_microstep: 273.13 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 02:32:18,477] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.74 | bwd_microstep: 271.59 | bwd_inner_microstep: 271.58 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 02:32:18,951] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.33 | bwd_microstep: 271.14 | bwd_inner_microstep: 271.12 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 02:32:19,518] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.01 | optimizer_step: 19.24 +[2025-05-02 02:32:19,519] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.59 | bwd_microstep: 338.51 | bwd_inner_microstep: 271.69 | bwd_allreduce_microstep: 66.78 | step_microstep: 26.31 +[2025-05-02 02:32:19,520] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2609.63 | bwd: 3981.06 | bwd_inner: 3913.29 | bwd_allreduce: 67.16 | step: 27.44 + 20%|█▉ | 1733/8720 [4:16:53<13:50:56, 7.14s/it] {'loss': 0.8181, 'grad_norm': 7.026237487792969, 'learning_rate': 9.272055067526809e-06, 'epoch': 1.99} + 20%|█▉ | 1733/8720 [4:16:53<13:50:56, 7.14s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 464 +[2025-05-02 02:32:19,762] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 75.99 | bwd_microstep: 147.74 | bwd_inner_microstep: 147.61 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1920 +[2025-05-02 02:32:20,245] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 191.18 | bwd_microstep: 277.04 | bwd_inner_microstep: 277.02 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-02 02:32:20,723] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.15 | bwd_microstep: 273.93 | bwd_inner_microstep: 273.91 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 02:32:21,200] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.43 | bwd_microstep: 272.88 | bwd_inner_microstep: 272.86 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 02:32:21,679] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.56 | bwd_microstep: 273.40 | bwd_inner_microstep: 273.38 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 853 +[2025-05-02 02:32:21,934] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 98.91 | bwd_microstep: 142.06 | bwd_inner_microstep: 141.91 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1353 +[2025-05-02 02:32:22,295] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.24 | bwd_microstep: 206.16 | bwd_inner_microstep: 206.14 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 02:32:22,771] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.79 | bwd_microstep: 272.82 | bwd_inner_microstep: 272.80 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 02:32:23,247] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.53 | bwd_microstep: 272.46 | bwd_inner_microstep: 272.44 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1094 +[2025-05-02 02:32:23,539] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 117.13 | bwd_microstep: 160.68 | bwd_inner_microstep: 160.63 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 02:32:24,014] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.84 | bwd_microstep: 272.53 | bwd_inner_microstep: 272.52 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 02:32:24,489] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.19 | bwd_microstep: 272.21 | bwd_inner_microstep: 272.19 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1346 +[2025-05-02 02:32:24,851] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.20 | bwd_microstep: 205.74 | bwd_inner_microstep: 205.56 | bwd_allreduce_microstep: 0.09 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 02:32:25,327] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.16 | bwd_microstep: 272.80 | bwd_inner_microstep: 272.79 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.06 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 832 +[2025-05-02 02:32:25,575] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.14 | bwd_microstep: 139.58 | bwd_inner_microstep: 139.34 | bwd_allreduce_microstep: 0.10 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 02:32:26,140] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.07 | optimizer_step: 16.42 +[2025-05-02 02:32:26,140] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.05 | bwd_microstep: 338.53 | bwd_inner_microstep: 271.67 | bwd_allreduce_microstep: 66.81 | step_microstep: 23.54 +[2025-05-02 02:32:26,141] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2552.21 | bwd: 3800.62 | bwd_inner: 3732.89 | bwd_allreduce: 67.15 | step: 24.57 + 20%|█▉ | 1734/8720 [4:16:59<13:32:51, 6.98s/it] {'loss': 0.5139, 'grad_norm': 11.344401359558105, 'learning_rate': 9.27108979031262e-06, 'epoch': 1.99} + 20%|█▉ | 1734/8720 [4:16:59<13:32:51, 6.98s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 365 +[2025-05-02 02:32:26,380] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 73.41 | bwd_microstep: 146.91 | bwd_inner_microstep: 146.60 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1909 +[2025-05-02 02:32:26,861] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.27 | bwd_microstep: 276.37 | bwd_inner_microstep: 276.36 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 357 +[2025-05-02 02:32:27,061] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 70.18 | bwd_microstep: 117.21 | bwd_inner_microstep: 116.95 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1889 +[2025-05-02 02:32:27,542] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.23 | bwd_microstep: 274.66 | bwd_inner_microstep: 274.64 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 02:32:28,019] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.60 | bwd_microstep: 273.20 | bwd_inner_microstep: 273.19 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 846 +[2025-05-02 02:32:28,259] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.51 | bwd_microstep: 132.46 | bwd_inner_microstep: 132.19 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.08 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1350 +[2025-05-02 02:32:28,619] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.16 | bwd_microstep: 206.22 | bwd_inner_microstep: 206.10 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 02:32:29,095] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.80 | bwd_microstep: 272.87 | bwd_inner_microstep: 272.85 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 02:32:29,570] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.62 | bwd_microstep: 272.17 | bwd_inner_microstep: 272.15 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 02:32:30,047] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.84 | bwd_microstep: 273.52 | bwd_inner_microstep: 273.51 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 02:32:30,525] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.87 | bwd_microstep: 272.69 | bwd_inner_microstep: 272.67 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 02:32:31,001] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.53 | bwd_microstep: 272.66 | bwd_inner_microstep: 272.64 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 02:32:31,477] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.58 | bwd_microstep: 272.41 | bwd_inner_microstep: 272.40 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 02:32:31,952] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.94 | bwd_microstep: 272.31 | bwd_inner_microstep: 272.29 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 02:32:32,426] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.54 | bwd_microstep: 271.27 | bwd_inner_microstep: 271.26 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 02:32:32,996] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.08 | optimizer_step: 16.39 +[2025-05-02 02:32:32,996] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.18 | bwd_microstep: 341.33 | bwd_inner_microstep: 271.58 | bwd_allreduce_microstep: 69.70 | step_microstep: 23.28 +[2025-05-02 02:32:32,997] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2637.98 | bwd: 3948.35 | bwd_inner: 3877.52 | bwd_allreduce: 70.19 | step: 24.11 + 20%|█▉ | 1735/8720 [4:17:06<13:28:20, 6.94s/it] {'loss': 0.5771, 'grad_norm': 10.136025428771973, 'learning_rate': 9.270123923843693e-06, 'epoch': 1.99} + 20%|█▉ | 1735/8720 [4:17:06<13:28:20, 6.94s/it]dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 829 +[2025-05-02 02:32:33,239] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 92.53 | bwd_microstep: 130.15 | bwd_inner_microstep: 129.83 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-02 02:32:33,716] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.41 | bwd_microstep: 273.52 | bwd_inner_microstep: 273.51 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-02 02:32:34,195] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.54 | bwd_microstep: 274.18 | bwd_inner_microstep: 274.16 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 02:32:34,670] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.01 | bwd_microstep: 272.72 | bwd_inner_microstep: 272.71 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 02:32:35,148] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.16 | bwd_microstep: 272.92 | bwd_inner_microstep: 272.90 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 02:32:35,625] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.90 | bwd_microstep: 273.03 | bwd_inner_microstep: 273.02 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 842 +[2025-05-02 02:32:35,867] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.84 | bwd_microstep: 132.48 | bwd_inner_microstep: 132.22 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 02:32:36,342] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.19 | bwd_microstep: 272.79 | bwd_inner_microstep: 272.77 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 02:32:36,819] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.11 | bwd_microstep: 272.45 | bwd_inner_microstep: 272.43 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 02:32:37,295] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.30 | bwd_microstep: 272.47 | bwd_inner_microstep: 272.45 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 02:32:37,771] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.30 | bwd_microstep: 272.13 | bwd_inner_microstep: 272.11 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 326 +[2025-05-02 02:32:37,997] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 87.19 | bwd_microstep: 124.05 | bwd_inner_microstep: 123.90 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.11 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1349 +[2025-05-02 02:32:38,361] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.78 | bwd_microstep: 205.91 | bwd_inner_microstep: 205.86 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 02:32:38,841] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.16 | bwd_microstep: 272.55 | bwd_inner_microstep: 272.54 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 02:32:39,319] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.77 | bwd_microstep: 272.26 | bwd_inner_microstep: 272.24 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.17 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 320 +[2025-05-02 02:32:39,656] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.07 | optimizer_step: 16.51 +[2025-05-02 02:32:39,656] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 83.17 | bwd_microstep: 212.93 | bwd_inner_microstep: 136.12 | bwd_allreduce_microstep: 76.65 | step_microstep: 24.14 +[2025-05-02 02:32:39,658] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2572.03 | bwd: 3806.63 | bwd_inner: 3728.90 | bwd_allreduce: 77.01 | step: 25.41 + 20%|█▉ | 1736/8720 [4:17:13<13:18:24, 6.86s/it] {'loss': 0.4316, 'grad_norm': 7.154569149017334, 'learning_rate': 9.26915746825329e-06, 'epoch': 1.99} + 20%|█▉ | 1736/8720 [4:17:13<13:18:24, 6.86s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 02:32:40,139] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.00 | bwd_microstep: 270.67 | bwd_inner_microstep: 270.66 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1935 +[2025-05-02 02:32:40,640] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 196.01 | bwd_microstep: 287.74 | bwd_inner_microstep: 287.73 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1935 +[2025-05-02 02:32:41,138] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.58 | bwd_microstep: 287.90 | bwd_inner_microstep: 287.88 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1911 +[2025-05-02 02:32:41,620] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.01 | bwd_microstep: 276.52 | bwd_inner_microstep: 276.50 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1903 +[2025-05-02 02:32:42,103] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.47 | bwd_microstep: 275.81 | bwd_inner_microstep: 275.79 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 346 +[2025-05-02 02:32:42,339] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.46 | bwd_microstep: 123.45 | bwd_inner_microstep: 123.30 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-02 02:32:42,819] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.68 | bwd_microstep: 273.68 | bwd_inner_microstep: 273.66 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 329 +[2025-05-02 02:32:43,044] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.27 | bwd_microstep: 115.11 | bwd_inner_microstep: 114.81 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 02:32:43,521] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.77 | bwd_microstep: 272.14 | bwd_inner_microstep: 272.13 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 323 +[2025-05-02 02:32:43,743] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 87.76 | bwd_microstep: 117.83 | bwd_inner_microstep: 117.66 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 02:32:44,222] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.78 | bwd_microstep: 272.82 | bwd_inner_microstep: 272.80 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 02:32:44,701] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.90 | bwd_microstep: 272.79 | bwd_inner_microstep: 272.77 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 02:32:45,180] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.11 | bwd_microstep: 272.88 | bwd_inner_microstep: 272.87 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 02:32:45,659] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.65 | bwd_microstep: 272.46 | bwd_inner_microstep: 272.44 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 02:32:46,135] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.24 | bwd_microstep: 271.13 | bwd_inner_microstep: 271.12 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 316 +[2025-05-02 02:32:46,446] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.03 | optimizer_step: 16.50 +[2025-05-02 02:32:46,446] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 67.94 | bwd_microstep: 205.22 | bwd_inner_microstep: 138.66 | bwd_allreduce_microstep: 66.46 | step_microstep: 23.43 +[2025-05-02 02:32:46,447] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2622.28 | bwd: 3868.23 | bwd_inner: 3800.93 | bwd_allreduce: 66.74 | step: 24.29 + 20%|█▉ | 1737/8720 [4:17:20<13:15:48, 6.84s/it] {'loss': 0.6302, 'grad_norm': 12.756253242492676, 'learning_rate': 9.268190423674742e-06, 'epoch': 1.99} + 20%|█▉ | 1737/8720 [4:17:20<13:15:48, 6.84s/it]dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 827 +[2025-05-02 02:32:46,687] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 91.59 | bwd_microstep: 129.98 | bwd_inner_microstep: 129.82 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2033 +[2025-05-02 02:32:47,200] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 200.06 | bwd_microstep: 297.20 | bwd_inner_microstep: 297.19 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1936 +[2025-05-02 02:32:47,701] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 198.07 | bwd_microstep: 287.77 | bwd_inner_microstep: 287.76 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1890 +[2025-05-02 02:32:48,180] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.15 | bwd_microstep: 274.55 | bwd_inner_microstep: 274.53 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-02 02:32:48,659] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.56 | bwd_microstep: 273.96 | bwd_inner_microstep: 273.94 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 02:32:49,136] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.05 | bwd_microstep: 273.52 | bwd_inner_microstep: 273.50 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 02:32:49,613] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.57 | bwd_microstep: 272.79 | bwd_inner_microstep: 272.78 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 845 +[2025-05-02 02:32:49,865] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 101.63 | bwd_microstep: 131.93 | bwd_inner_microstep: 131.91 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 6, images per sample: 6.0, dynamic token length: 1607 +[2025-05-02 02:32:50,290] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 165.10 | bwd_microstep: 243.59 | bwd_inner_microstep: 243.58 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 02:32:50,768] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.55 | bwd_microstep: 272.74 | bwd_inner_microstep: 272.72 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 02:32:51,244] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.65 | bwd_microstep: 272.40 | bwd_inner_microstep: 272.39 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 02:32:51,720] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.20 | bwd_microstep: 272.50 | bwd_inner_microstep: 272.48 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 02:32:52,197] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.66 | bwd_microstep: 272.24 | bwd_inner_microstep: 272.22 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 02:32:52,674] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.62 | bwd_microstep: 272.30 | bwd_inner_microstep: 272.28 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 316 +[2025-05-02 02:32:52,922] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 78.12 | bwd_microstep: 155.50 | bwd_inner_microstep: 155.33 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 02:32:53,487] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.11 | optimizer_step: 16.70 +[2025-05-02 02:32:53,488] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.80 | bwd_microstep: 338.79 | bwd_inner_microstep: 271.60 | bwd_allreduce_microstep: 67.14 | step_microstep: 23.90 +[2025-05-02 02:32:53,489] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2719.09 | bwd: 4041.82 | bwd_inner: 3974.16 | bwd_allreduce: 67.32 | step: 24.87 + 20%|█▉ | 1738/8720 [4:17:27<13:22:49, 6.90s/it] {'loss': 0.57, 'grad_norm': 27.923402786254883, 'learning_rate': 9.267222790241465e-06, 'epoch': 1.99} + 20%|█▉ | 1738/8720 [4:17:27<13:22:49, 6.90s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 460 +[2025-05-02 02:32:53,728] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 70.10 | bwd_microstep: 150.17 | bwd_inner_microstep: 149.96 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2323 +[2025-05-02 02:32:54,299] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 217.27 | bwd_microstep: 337.70 | bwd_inner_microstep: 337.64 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 360 +[2025-05-02 02:32:54,549] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 79.21 | bwd_microstep: 155.18 | bwd_inner_microstep: 154.89 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1893 +[2025-05-02 02:32:55,030] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.03 | bwd_microstep: 274.88 | bwd_inner_microstep: 274.86 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1361 +[2025-05-02 02:32:55,396] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.15 | bwd_microstep: 206.69 | bwd_inner_microstep: 206.67 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 02:32:55,879] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.41 | bwd_microstep: 272.97 | bwd_inner_microstep: 272.95 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 02:32:56,359] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.99 | bwd_microstep: 273.00 | bwd_inner_microstep: 272.99 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 02:32:56,839] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.09 | bwd_microstep: 272.52 | bwd_inner_microstep: 272.51 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 02:32:57,322] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.96 | bwd_microstep: 272.72 | bwd_inner_microstep: 272.70 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.15 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 02:32:57,805] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.00 | bwd_microstep: 272.79 | bwd_inner_microstep: 272.77 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 02:32:58,286] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.88 | bwd_microstep: 272.31 | bwd_inner_microstep: 272.29 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 02:32:58,768] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.47 | bwd_microstep: 272.36 | bwd_inner_microstep: 272.35 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1343 +[2025-05-02 02:32:59,130] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.26 | bwd_microstep: 204.60 | bwd_inner_microstep: 204.51 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 02:32:59,607] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.70 | bwd_microstep: 271.17 | bwd_inner_microstep: 271.15 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 02:33:00,087] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.89 | bwd_microstep: 271.31 | bwd_inner_microstep: 271.29 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 02:33:00,671] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.15 | optimizer_step: 16.64 +[2025-05-02 02:33:00,672] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.55 | bwd_microstep: 353.63 | bwd_inner_microstep: 271.34 | bwd_allreduce_microstep: 82.16 | step_microstep: 24.56 +[2025-05-02 02:33:00,673] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2717.57 | bwd: 4134.11 | bwd_inner: 4051.05 | bwd_allreduce: 82.42 | step: 25.87 + 20%|█▉ | 1739/8720 [4:17:34<13:32:43, 6.99s/it] {'loss': 0.6442, 'grad_norm': 9.853355407714844, 'learning_rate': 9.26625456808696e-06, 'epoch': 1.99} + 20%|█▉ | 1739/8720 [4:17:34<13:32:43, 6.99s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1972 +[2025-05-02 02:33:01,186] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 198.93 | bwd_microstep: 290.01 | bwd_inner_microstep: 289.99 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-02 02:33:01,665] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.10 | bwd_microstep: 273.61 | bwd_inner_microstep: 273.59 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.07 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 02:33:02,144] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.09 | bwd_microstep: 273.29 | bwd_inner_microstep: 273.27 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 02:33:02,622] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.74 | bwd_microstep: 272.15 | bwd_inner_microstep: 272.13 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 02:33:03,100] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.50 | bwd_microstep: 272.91 | bwd_inner_microstep: 272.89 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1355 +[2025-05-02 02:33:03,462] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.77 | bwd_microstep: 206.36 | bwd_inner_microstep: 206.22 | bwd_allreduce_microstep: 0.10 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 02:33:03,937] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.74 | bwd_microstep: 272.63 | bwd_inner_microstep: 272.61 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 02:33:04,412] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.88 | bwd_microstep: 272.15 | bwd_inner_microstep: 272.13 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 02:33:04,889] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.55 | bwd_microstep: 272.62 | bwd_inner_microstep: 272.60 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 844 +[2025-05-02 02:33:05,143] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.11 | bwd_microstep: 144.19 | bwd_inner_microstep: 144.05 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1354 +[2025-05-02 02:33:05,505] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 139.52 | bwd_microstep: 206.27 | bwd_inner_microstep: 206.06 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 02:33:05,984] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.22 | bwd_microstep: 272.67 | bwd_inner_microstep: 272.65 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 02:33:06,462] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.23 | bwd_microstep: 272.25 | bwd_inner_microstep: 272.24 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 832 +[2025-05-02 02:33:06,720] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.66 | bwd_microstep: 145.11 | bwd_inner_microstep: 144.95 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 02:33:07,197] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.23 | bwd_microstep: 272.22 | bwd_inner_microstep: 272.20 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 02:33:07,776] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.19 | optimizer_step: 16.97 +[2025-05-02 02:33:07,777] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.96 | bwd_microstep: 348.90 | bwd_inner_microstep: 271.70 | bwd_allreduce_microstep: 77.12 | step_microstep: 24.97 +[2025-05-02 02:33:07,778] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2735.92 | bwd: 4067.38 | bwd_inner: 3989.35 | bwd_allreduce: 77.49 | step: 26.15 + 20%|█▉ | 1740/8720 [4:17:41<13:36:46, 7.02s/it] {'loss': 0.8257, 'grad_norm': 12.911438941955566, 'learning_rate': 9.265285757344806e-06, 'epoch': 2.0} + 20%|█▉ | 1740/8720 [4:17:41<13:36:46, 7.02s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 315 +[2025-05-02 02:33:08,021] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 75.69 | bwd_microstep: 146.27 | bwd_inner_microstep: 145.95 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1904 +[2025-05-02 02:33:08,501] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.20 | bwd_microstep: 275.60 | bwd_inner_microstep: 275.58 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 02:33:08,979] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.30 | bwd_microstep: 272.83 | bwd_inner_microstep: 272.81 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.21 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 344 +[2025-05-02 02:33:09,235] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 87.15 | bwd_microstep: 152.27 | bwd_inner_microstep: 152.11 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-02 02:33:09,716] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.26 | bwd_microstep: 273.64 | bwd_inner_microstep: 273.62 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1359 +[2025-05-02 02:33:10,081] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.32 | bwd_microstep: 206.42 | bwd_inner_microstep: 206.28 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-02 02:33:10,559] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.77 | bwd_microstep: 273.08 | bwd_inner_microstep: 273.06 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1370 +[2025-05-02 02:33:10,925] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.81 | bwd_microstep: 207.67 | bwd_inner_microstep: 207.41 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-02 02:33:11,405] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.44 | bwd_microstep: 273.18 | bwd_inner_microstep: 273.17 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 841 +[2025-05-02 02:33:11,667] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 99.17 | bwd_microstep: 144.99 | bwd_inner_microstep: 144.89 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 02:33:12,147] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.68 | bwd_microstep: 273.30 | bwd_inner_microstep: 273.29 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 02:33:12,625] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.51 | bwd_microstep: 272.63 | bwd_inner_microstep: 272.61 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 02:33:13,102] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.36 | bwd_microstep: 272.28 | bwd_inner_microstep: 272.26 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 02:33:13,578] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.00 | bwd_microstep: 271.27 | bwd_inner_microstep: 271.26 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 02:33:14,055] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.87 | bwd_microstep: 272.16 | bwd_inner_microstep: 272.14 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 319 +[2025-05-02 02:33:14,425] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.13 | optimizer_step: 16.61 +[2025-05-02 02:33:14,426] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 81.53 | bwd_microstep: 248.82 | bwd_inner_microstep: 171.42 | bwd_allreduce_microstep: 77.25 | step_microstep: 24.52 +[2025-05-02 02:33:14,427] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2509.74 | bwd: 3836.56 | bwd_inner: 3758.03 | bwd_allreduce: 77.71 | step: 25.85 + 20%|█▉ | 1741/8720 [4:17:48<13:23:41, 6.91s/it] {'loss': 0.5926, 'grad_norm': 7.238270282745361, 'learning_rate': 9.264316358148662e-06, 'epoch': 2.0} + 20%|█▉ | 1741/8720 [4:17:48<13:23:41, 6.91s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 315 +[2025-05-02 02:33:14,684] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 80.39 | bwd_microstep: 154.88 | bwd_inner_microstep: 154.69 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1940 +[2025-05-02 02:33:15,186] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.15 | bwd_microstep: 288.69 | bwd_inner_microstep: 288.67 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.12 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 368 +[2025-05-02 02:33:15,417] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 84.08 | bwd_microstep: 130.80 | bwd_inner_microstep: 130.49 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1893 +[2025-05-02 02:33:15,897] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.81 | bwd_microstep: 274.64 | bwd_inner_microstep: 274.63 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-02 02:33:16,380] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.91 | bwd_microstep: 274.21 | bwd_inner_microstep: 274.19 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1887 +[2025-05-02 02:33:16,864] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.77 | bwd_microstep: 274.41 | bwd_inner_microstep: 274.40 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1365 +[2025-05-02 02:33:17,235] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 142.17 | bwd_microstep: 207.07 | bwd_inner_microstep: 207.04 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.12 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 853 +[2025-05-02 02:33:17,498] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 107.53 | bwd_microstep: 132.26 | bwd_inner_microstep: 132.15 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-02 02:33:17,978] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.84 | bwd_microstep: 272.85 | bwd_inner_microstep: 272.83 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 02:33:18,456] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.73 | bwd_microstep: 272.38 | bwd_inner_microstep: 272.36 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 02:33:18,938] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.26 | bwd_microstep: 272.67 | bwd_inner_microstep: 272.66 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 842 +[2025-05-02 02:33:19,188] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 98.80 | bwd_microstep: 131.78 | bwd_inner_microstep: 131.68 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1350 +[2025-05-02 02:33:19,553] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.17 | bwd_microstep: 205.76 | bwd_inner_microstep: 205.75 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 02:33:20,031] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.31 | bwd_microstep: 272.60 | bwd_inner_microstep: 272.58 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 02:33:20,508] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.77 | bwd_microstep: 271.30 | bwd_inner_microstep: 271.28 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1988 +[2025-05-02 02:33:21,113] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.19 | optimizer_step: 23.64 +[2025-05-02 02:33:21,114] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 198.12 | bwd_microstep: 360.76 | bwd_inner_microstep: 293.69 | bwd_allreduce_microstep: 67.02 | step_microstep: 31.10 +[2025-05-02 02:33:21,115] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2553.42 | bwd: 3797.20 | bwd_inner: 3729.19 | bwd_allreduce: 67.41 | step: 32.53 + 20%|█▉ | 1742/8720 [4:17:54<13:15:46, 6.84s/it] {'loss': 0.6056, 'grad_norm': 5.7946648597717285, 'learning_rate': 9.26334637063227e-06, 'epoch': 2.0} + 20%|█▉ | 1742/8720 [4:17:54<13:15:46, 6.84s/it]dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1450 +[2025-05-02 02:33:21,497] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 146.65 | bwd_microstep: 215.78 | bwd_inner_microstep: 215.67 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.09 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 895 +[2025-05-02 02:33:21,751] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.99 | bwd_microstep: 143.94 | bwd_inner_microstep: 143.81 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1901 +[2025-05-02 02:33:22,233] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.85 | bwd_microstep: 276.05 | bwd_inner_microstep: 276.03 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1892 +[2025-05-02 02:33:22,713] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.18 | bwd_microstep: 275.23 | bwd_inner_microstep: 275.21 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1899 +[2025-05-02 02:33:23,195] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.19 | bwd_microstep: 276.00 | bwd_inner_microstep: 275.99 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1370 +[2025-05-02 02:33:23,559] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.64 | bwd_microstep: 207.85 | bwd_inner_microstep: 207.77 | bwd_allreduce_microstep: 0.03 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1887 +[2025-05-02 02:33:24,038] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.75 | bwd_microstep: 274.86 | bwd_inner_microstep: 274.84 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.08 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 326 +[2025-05-02 02:33:24,281] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 77.15 | bwd_microstep: 151.79 | bwd_inner_microstep: 151.66 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 02:33:24,758] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.23 | bwd_microstep: 272.68 | bwd_inner_microstep: 272.66 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 02:33:25,234] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.99 | bwd_microstep: 272.72 | bwd_inner_microstep: 272.70 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 02:33:25,710] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.00 | bwd_microstep: 272.31 | bwd_inner_microstep: 272.29 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 02:33:26,186] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.73 | bwd_microstep: 272.41 | bwd_inner_microstep: 272.39 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 02:33:26,662] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.54 | bwd_microstep: 271.40 | bwd_inner_microstep: 271.38 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 828 +[2025-05-02 02:33:26,898] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 92.31 | bwd_microstep: 130.05 | bwd_inner_microstep: 129.77 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 02:33:27,372] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.75 | bwd_microstep: 270.92 | bwd_inner_microstep: 270.91 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 833 +[2025-05-02 02:33:27,698] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.04 | optimizer_gradients: 2.03 | optimizer_step: 16.48 +[2025-05-02 02:33:27,698] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 91.18 | bwd_microstep: 197.93 | bwd_inner_microstep: 131.39 | bwd_allreduce_microstep: 66.46 | step_microstep: 23.35 +[2025-05-02 02:33:27,699] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2532.85 | bwd: 3782.00 | bwd_inner: 3714.59 | bwd_allreduce: 66.83 | step: 24.30 + 20%|█▉ | 1743/8720 [4:18:01<13:06:38, 6.76s/it] {'loss': 0.5663, 'grad_norm': 5.548950672149658, 'learning_rate': 9.262375794929455e-06, 'epoch': 2.0} + 20%|█▉ | 1743/8720 [4:18:01<13:06:38, 6.76s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 02:33:28,177] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.68 | bwd_microstep: 270.33 | bwd_inner_microstep: 270.31 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 02:33:28,653] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.02 | bwd_microstep: 273.45 | bwd_inner_microstep: 273.43 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1894 +[2025-05-02 02:33:29,133] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.21 | bwd_microstep: 275.20 | bwd_inner_microstep: 275.18 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-02 02:33:29,611] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.88 | bwd_microstep: 274.23 | bwd_inner_microstep: 274.21 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-02 02:33:30,089] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.09 | bwd_microstep: 274.23 | bwd_inner_microstep: 274.22 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 02:33:30,567] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.69 | bwd_microstep: 273.32 | bwd_inner_microstep: 273.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 02:33:31,045] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.17 | bwd_microstep: 272.89 | bwd_inner_microstep: 272.87 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 02:33:31,525] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.30 | bwd_microstep: 273.14 | bwd_inner_microstep: 273.12 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 02:33:32,006] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.98 | bwd_microstep: 272.86 | bwd_inner_microstep: 272.84 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 02:33:32,486] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.52 | bwd_microstep: 273.26 | bwd_inner_microstep: 273.24 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 847 +[2025-05-02 02:33:32,735] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.26 | bwd_microstep: 138.94 | bwd_inner_microstep: 138.64 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 02:33:33,211] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.31 | bwd_microstep: 272.81 | bwd_inner_microstep: 272.79 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 02:33:33,687] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.46 | bwd_microstep: 272.91 | bwd_inner_microstep: 272.90 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 02:33:34,163] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.55 | bwd_microstep: 272.85 | bwd_inner_microstep: 272.83 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 02:33:34,636] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.94 | bwd_microstep: 271.35 | bwd_inner_microstep: 271.33 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 02:33:35,206] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.04 | optimizer_step: 22.93 +[2025-05-02 02:33:35,206] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.95 | bwd_microstep: 338.21 | bwd_inner_microstep: 271.83 | bwd_allreduce_microstep: 66.34 | step_microstep: 29.92 +[2025-05-02 02:33:35,207] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2920.72 | bwd: 4300.02 | bwd_inner: 4233.09 | bwd_allreduce: 66.53 | step: 30.91 + 20%|██ | 1744/8720 [4:18:08<13:32:26, 6.99s/it] {'loss': 0.4907, 'grad_norm': 5.218378067016602, 'learning_rate': 9.26140463117412e-06, 'epoch': 2.0} + 20%|██ | 1744/8720 [4:18:08<13:32:26, 6.99s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1911 +[2025-05-02 02:33:35,692] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.50 | bwd_microstep: 275.66 | bwd_inner_microstep: 275.65 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.06 +petrel_client is not installed. If you read data locally instead of from ceph, ignore it. +petrel_client is not installed. Using PIL to load images. +petrel_client is not installed. If you read data locally instead of from ceph, ignore it. +petrel_client is not installed. Using PIL to load images. +petrel_client is not installed. If you read data locally instead of from ceph, ignore it. +petrel_client is not installed. Using PIL to load images. +petrel_client is not installed. If you read data locally instead of from ceph, ignore it. +petrel_client is not installed. Using PIL to load images. +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1911 +[2025-05-02 02:33:38,175] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.72 | bwd_microstep: 275.68 | bwd_inner_microstep: 275.67 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +[2025-05-02 02:33:40,288] [INFO] [real_accelerator.py:203:get_accelerator] Setting ds_accelerator to cuda (auto detect) +/home1/gmh/anaconda3/envs/promptbench/lib/python3.9/site-packages/timm/models/layers/__init__.py:48: FutureWarning: Importing from timm.models.layers is deprecated, please import via timm.layers + warnings.warn(f"Importing from {__name__} is deprecated, please import via timm.layers", FutureWarning) +[2025-05-02 02:33:46,464] [INFO] [real_accelerator.py:203:get_accelerator] Setting ds_accelerator to cuda (auto detect) +/home1/gmh/anaconda3/envs/promptbench/lib/python3.9/site-packages/timm/models/layers/__init__.py:48: FutureWarning: Importing from timm.models.layers is deprecated, please import via timm.layers + warnings.warn(f"Importing from {__name__} is deprecated, please import via timm.layers", FutureWarning) +[2025-05-02 02:33:52,556] [INFO] [real_accelerator.py:203:get_accelerator] Setting ds_accelerator to cuda (auto detect) +/home1/gmh/anaconda3/envs/promptbench/lib/python3.9/site-packages/timm/models/layers/__init__.py:48: FutureWarning: Importing from timm.models.layers is deprecated, please import via timm.layers + warnings.warn(f"Importing from {__name__} is deprecated, please import via timm.layers", FutureWarning) +[2025-05-02 02:33:58,664] [INFO] [real_accelerator.py:203:get_accelerator] Setting ds_accelerator to cuda (auto detect) +/home1/gmh/anaconda3/envs/promptbench/lib/python3.9/site-packages/timm/models/layers/__init__.py:48: FutureWarning: Importing from timm.models.layers is deprecated, please import via timm.layers + warnings.warn(f"Importing from {__name__} is deprecated, please import via timm.layers", FutureWarning) +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2293 +[2025-05-02 02:34:03,476] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 217.71 | bwd_microstep: 320.97 | bwd_inner_microstep: 320.95 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1949 +[2025-05-02 02:34:03,971] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 191.85 | bwd_microstep: 288.10 | bwd_inner_microstep: 288.09 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1941 +[2025-05-02 02:34:04,464] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 194.00 | bwd_microstep: 284.45 | bwd_inner_microstep: 284.44 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1098 +[2025-05-02 02:34:04,750] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 112.91 | bwd_microstep: 158.68 | bwd_inner_microstep: 158.66 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 02:34:05,222] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.35 | bwd_microstep: 270.87 | bwd_inner_microstep: 270.85 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 02:34:05,691] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 185.77 | bwd_microstep: 269.28 | bwd_inner_microstep: 269.27 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 843 +[2025-05-02 02:34:05,943] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.39 | bwd_microstep: 143.82 | bwd_inner_microstep: 143.75 | bwd_allreduce_microstep: 0.03 | step_microstep: 0.10 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 843 +[2025-05-02 02:34:06,194] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.91 | bwd_microstep: 140.84 | bwd_inner_microstep: 140.76 | bwd_allreduce_microstep: 0.04 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 02:34:06,662] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 184.99 | bwd_microstep: 269.09 | bwd_inner_microstep: 269.08 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 326 +[2025-05-02 02:34:06,906] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 81.22 | bwd_microstep: 149.54 | bwd_inner_microstep: 149.38 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.10 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 324 +[2025-05-02 02:34:07,150] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 81.41 | bwd_microstep: 149.47 | bwd_inner_microstep: 149.32 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 02:34:07,620] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 185.36 | bwd_microstep: 269.07 | bwd_inner_microstep: 269.05 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 02:34:08,093] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 185.78 | bwd_microstep: 269.91 | bwd_inner_microstep: 269.89 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 02:34:08,682] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.14 | optimizer_step: 30.13 +[2025-05-02 02:34:08,683] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 185.77 | bwd_microstep: 349.18 | bwd_inner_microstep: 268.83 | bwd_allreduce_microstep: 80.30 | step_microstep: 38.04 +[2025-05-02 02:34:08,684] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2563.27 | bwd: 3884.70 | bwd_inner: 3803.68 | bwd_allreduce: 80.59 | step: 39.10 + 20%|██ | 1745/8720 [4:18:42<28:56:12, 14.94s/it] {'loss': 0.4257, 'grad_norm': 5.149142742156982, 'learning_rate': 9.26043287950025e-06, 'epoch': 2.0} + 20%|██ | 1745/8720 [4:18:42<28:56:12, 14.94s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 02:34:09,163] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.91 | bwd_microstep: 269.00 | bwd_inner_microstep: 268.99 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 02:34:09,639] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.53 | bwd_microstep: 269.43 | bwd_inner_microstep: 269.41 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 928 +[2025-05-02 02:34:09,906] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 105.04 | bwd_microstep: 144.92 | bwd_inner_microstep: 144.86 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1952 +[2025-05-02 02:34:10,404] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 194.41 | bwd_microstep: 286.36 | bwd_inner_microstep: 286.35 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1895 +[2025-05-02 02:34:10,886] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.90 | bwd_microstep: 272.44 | bwd_inner_microstep: 272.42 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1893 +[2025-05-02 02:34:11,366] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.85 | bwd_microstep: 272.36 | bwd_inner_microstep: 272.34 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.16 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1888 +[2025-05-02 02:34:11,846] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.29 | bwd_microstep: 271.91 | bwd_inner_microstep: 271.90 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 860 +[2025-05-02 02:34:12,089] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.10 | bwd_microstep: 132.18 | bwd_inner_microstep: 131.91 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-02 02:34:12,566] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.62 | bwd_microstep: 271.24 | bwd_inner_microstep: 271.22 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 02:34:13,041] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 185.92 | bwd_microstep: 270.26 | bwd_inner_microstep: 270.24 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.23 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1356 +[2025-05-02 02:34:13,406] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 138.79 | bwd_microstep: 204.73 | bwd_inner_microstep: 204.51 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.11 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 847 +[2025-05-02 02:34:13,664] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.32 | bwd_microstep: 147.21 | bwd_inner_microstep: 147.05 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 02:34:14,137] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 185.53 | bwd_microstep: 269.77 | bwd_inner_microstep: 269.76 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 02:34:14,613] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 185.89 | bwd_microstep: 269.84 | bwd_inner_microstep: 269.82 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 02:34:15,090] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.37 | bwd_microstep: 270.07 | bwd_inner_microstep: 270.05 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 02:34:15,666] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.12 | optimizer_step: 16.73 +[2025-05-02 02:34:15,667] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.73 | bwd_microstep: 347.42 | bwd_inner_microstep: 270.19 | bwd_allreduce_microstep: 77.15 | step_microstep: 24.67 +[2025-05-02 02:34:15,668] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2677.77 | bwd: 3969.29 | bwd_inner: 3891.05 | bwd_allreduce: 77.51 | step: 26.17 + 20%|██ | 1746/8720 [4:18:49<24:18:42, 12.55s/it] {'loss': 0.74, 'grad_norm': 12.676887512207031, 'learning_rate': 9.259460540041909e-06, 'epoch': 2.0} + 20%|██ | 1746/8720 [4:18:49<24:18:42, 12.55s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 318 +[2025-05-02 02:34:15,921] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 80.74 | bwd_microstep: 150.63 | bwd_inner_microstep: 150.48 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 02:34:16,395] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.48 | bwd_microstep: 269.71 | bwd_inner_microstep: 269.69 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2001 +[2025-05-02 02:34:16,902] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 196.72 | bwd_microstep: 292.48 | bwd_inner_microstep: 292.46 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1961 +[2025-05-02 02:34:17,404] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.73 | bwd_microstep: 288.37 | bwd_inner_microstep: 288.35 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1952 +[2025-05-02 02:34:17,902] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 193.33 | bwd_microstep: 287.22 | bwd_inner_microstep: 287.20 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1905 +[2025-05-02 02:34:18,379] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.41 | bwd_microstep: 274.04 | bwd_inner_microstep: 274.03 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-02 02:34:18,852] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.61 | bwd_microstep: 271.62 | bwd_inner_microstep: 271.60 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1370 +[2025-05-02 02:34:19,214] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.78 | bwd_microstep: 206.24 | bwd_inner_microstep: 205.97 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-02 02:34:19,689] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.95 | bwd_microstep: 271.49 | bwd_inner_microstep: 271.47 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 02:34:20,162] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.90 | bwd_microstep: 270.67 | bwd_inner_microstep: 270.66 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 02:34:20,633] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 185.79 | bwd_microstep: 270.22 | bwd_inner_microstep: 270.20 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 02:34:21,110] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.15 | bwd_microstep: 270.70 | bwd_inner_microstep: 270.68 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 02:34:21,588] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.02 | bwd_microstep: 270.63 | bwd_inner_microstep: 270.58 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 02:34:22,067] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.88 | bwd_microstep: 270.55 | bwd_inner_microstep: 270.53 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 02:34:22,547] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.52 | bwd_microstep: 270.73 | bwd_inner_microstep: 270.72 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 02:34:23,136] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.12 | optimizer_step: 16.69 +[2025-05-02 02:34:23,136] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.10 | bwd_microstep: 354.44 | bwd_inner_microstep: 271.64 | bwd_allreduce_microstep: 82.62 | step_microstep: 24.58 +[2025-05-02 02:34:23,138] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2861.75 | bwd: 4289.81 | bwd_inner: 4206.42 | bwd_allreduce: 82.85 | step: 25.85 + 20%|██ | 1747/8720 [4:18:56<21:21:22, 11.03s/it] {'loss': 0.5496, 'grad_norm': 5.26962423324585, 'learning_rate': 9.258487612933248e-06, 'epoch': 2.0} + 20%|██ | 1747/8720 [4:18:56<21:21:22, 11.03s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 02:34:23,621] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.96 | bwd_microstep: 271.46 | bwd_inner_microstep: 271.44 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 02:34:24,095] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.19 | bwd_microstep: 270.08 | bwd_inner_microstep: 270.07 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2116 +[2025-05-02 02:34:24,630] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 204.10 | bwd_microstep: 310.74 | bwd_inner_microstep: 310.72 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1898 +[2025-05-02 02:34:25,111] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.62 | bwd_microstep: 273.88 | bwd_inner_microstep: 273.87 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1895 +[2025-05-02 02:34:25,592] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.09 | bwd_microstep: 273.68 | bwd_inner_microstep: 273.66 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-02 02:34:26,071] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.59 | bwd_microstep: 272.48 | bwd_inner_microstep: 272.44 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 02:34:26,549] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.34 | bwd_microstep: 272.01 | bwd_inner_microstep: 271.99 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 02:34:27,025] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.52 | bwd_microstep: 271.51 | bwd_inner_microstep: 271.50 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 02:34:27,499] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.70 | bwd_microstep: 270.96 | bwd_inner_microstep: 270.94 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 326 +[2025-05-02 02:34:27,747] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 111.34 | bwd_microstep: 117.22 | bwd_inner_microstep: 117.05 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 02:34:28,223] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.51 | bwd_microstep: 271.48 | bwd_inner_microstep: 271.47 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 02:34:28,700] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.55 | bwd_microstep: 271.57 | bwd_inner_microstep: 271.56 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.23 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 02:34:29,176] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.83 | bwd_microstep: 270.54 | bwd_inner_microstep: 270.52 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 02:34:29,652] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.47 | bwd_microstep: 270.25 | bwd_inner_microstep: 270.23 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1346 +[2025-05-02 02:34:30,015] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.52 | bwd_microstep: 205.12 | bwd_inner_microstep: 204.94 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 02:34:30,617] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.21 | optimizer_step: 16.70 +[2025-05-02 02:34:30,618] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.60 | bwd_microstep: 370.75 | bwd_inner_microstep: 270.50 | bwd_allreduce_microstep: 100.18 | step_microstep: 26.42 +[2025-05-02 02:34:30,620] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2892.55 | bwd: 4263.80 | bwd_inner: 4162.92 | bwd_allreduce: 100.46 | step: 27.61 + 20%|██ | 1748/8720 [4:19:04<19:17:38, 9.96s/it] {'loss': 0.529, 'grad_norm': 9.71983528137207, 'learning_rate': 9.257514098308493e-06, 'epoch': 2.0} + 20%|██ | 1748/8720 [4:19:04<19:17:38, 9.96s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 02:34:31,100] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.72 | bwd_microstep: 269.66 | bwd_inner_microstep: 269.65 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 02:34:31,572] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.63 | bwd_microstep: 270.18 | bwd_inner_microstep: 270.17 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 435 +[2025-05-02 02:34:31,801] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 90.35 | bwd_microstep: 123.83 | bwd_inner_microstep: 123.69 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 02:34:32,278] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.94 | bwd_microstep: 272.21 | bwd_inner_microstep: 272.20 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 339 +[2025-05-02 02:34:32,510] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 84.66 | bwd_microstep: 133.03 | bwd_inner_microstep: 132.88 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 02:34:32,987] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.31 | bwd_microstep: 271.57 | bwd_inner_microstep: 271.55 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 339 +[2025-05-02 02:34:33,223] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 103.28 | bwd_microstep: 117.94 | bwd_inner_microstep: 117.62 | bwd_allreduce_microstep: 0.14 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 02:34:33,698] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.86 | bwd_microstep: 271.96 | bwd_inner_microstep: 271.94 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 02:34:34,174] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.47 | bwd_microstep: 272.15 | bwd_inner_microstep: 272.13 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1349 +[2025-05-02 02:34:34,535] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.24 | bwd_microstep: 205.05 | bwd_inner_microstep: 204.97 | bwd_allreduce_microstep: 0.03 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 02:34:35,010] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.19 | bwd_microstep: 271.73 | bwd_inner_microstep: 271.71 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 02:34:35,486] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.83 | bwd_microstep: 272.36 | bwd_inner_microstep: 272.35 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 02:34:35,963] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.86 | bwd_microstep: 272.14 | bwd_inner_microstep: 272.12 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-02 02:34:36,439] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.25 | bwd_microstep: 272.70 | bwd_inner_microstep: 272.68 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 02:34:36,914] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.48 | bwd_microstep: 271.85 | bwd_inner_microstep: 271.83 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 321 +[2025-05-02 02:34:37,290] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.09 | optimizer_step: 16.56 +[2025-05-02 02:34:37,291] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 85.56 | bwd_microstep: 252.89 | bwd_inner_microstep: 168.81 | bwd_allreduce_microstep: 83.98 | step_microstep: 24.97 +[2025-05-02 02:34:37,292] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2570.30 | bwd: 3821.33 | bwd_inner: 3736.44 | bwd_allreduce: 84.33 | step: 25.89 + 20%|██ | 1749/8720 [4:19:11<17:22:44, 8.98s/it] {'loss': 0.51, 'grad_norm': 6.118220806121826, 'learning_rate': 9.256539996301957e-06, 'epoch': 2.01} + 20%|██ | 1749/8720 [4:19:11<17:22:44, 8.98s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 02:34:37,771] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.71 | bwd_microstep: 271.14 | bwd_inner_microstep: 271.12 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1959 +[2025-05-02 02:34:38,274] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 198.35 | bwd_microstep: 288.70 | bwd_inner_microstep: 288.68 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1907 +[2025-05-02 02:34:38,752] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.33 | bwd_microstep: 274.69 | bwd_inner_microstep: 274.67 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1893 +[2025-05-02 02:34:39,230] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.16 | bwd_microstep: 273.67 | bwd_inner_microstep: 273.65 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-02 02:34:39,705] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.22 | bwd_microstep: 272.49 | bwd_inner_microstep: 272.47 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1896 +[2025-05-02 02:34:40,183] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.69 | bwd_microstep: 273.91 | bwd_inner_microstep: 273.89 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 02:34:40,659] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.78 | bwd_microstep: 272.20 | bwd_inner_microstep: 272.18 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 02:34:41,133] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.22 | bwd_microstep: 271.55 | bwd_inner_microstep: 271.54 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 02:34:41,607] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.28 | bwd_microstep: 271.35 | bwd_inner_microstep: 271.33 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 02:34:42,082] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.62 | bwd_microstep: 271.59 | bwd_inner_microstep: 271.58 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 02:34:42,553] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.51 | bwd_microstep: 270.09 | bwd_inner_microstep: 270.07 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 02:34:43,026] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.53 | bwd_microstep: 270.82 | bwd_inner_microstep: 270.80 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1345 +[2025-05-02 02:34:43,386] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.79 | bwd_microstep: 204.73 | bwd_inner_microstep: 204.71 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 02:34:43,862] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.08 | bwd_microstep: 271.17 | bwd_inner_microstep: 271.15 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 318 +[2025-05-02 02:34:44,104] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 80.09 | bwd_microstep: 148.78 | bwd_inner_microstep: 148.65 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 02:34:44,685] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.08 | optimizer_step: 16.56 +[2025-05-02 02:34:44,686] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.36 | bwd_microstep: 355.33 | bwd_inner_microstep: 271.09 | bwd_allreduce_microstep: 84.19 | step_microstep: 24.95 +[2025-05-02 02:34:44,687] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2859.43 | bwd: 4262.23 | bwd_inner: 4177.61 | bwd_allreduce: 84.32 | step: 25.79 + 20%|██ | 1750/8720 [4:19:18<16:27:32, 8.50s/it] {'loss': 0.468, 'grad_norm': 4.36456823348999, 'learning_rate': 9.255565307048026e-06, 'epoch': 2.01} + 20%|██ | 1750/8720 [4:19:18<16:27:32, 8.50s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 02:34:45,165] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.60 | bwd_microstep: 269.85 | bwd_inner_microstep: 269.82 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 02:34:45,639] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.46 | bwd_microstep: 270.62 | bwd_inner_microstep: 270.61 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1929 +[2025-05-02 02:34:46,135] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 194.58 | bwd_microstep: 287.00 | bwd_inner_microstep: 286.98 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 02:34:46,609] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.43 | bwd_microstep: 271.96 | bwd_inner_microstep: 271.94 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 02:34:47,084] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.23 | bwd_microstep: 271.90 | bwd_inner_microstep: 271.88 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 02:34:47,559] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.13 | bwd_microstep: 271.72 | bwd_inner_microstep: 271.70 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1095 +[2025-05-02 02:34:47,851] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 117.90 | bwd_microstep: 160.49 | bwd_inner_microstep: 160.47 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 02:34:48,323] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.39 | bwd_microstep: 271.27 | bwd_inner_microstep: 271.25 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1346 +[2025-05-02 02:34:48,683] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.29 | bwd_microstep: 204.70 | bwd_inner_microstep: 204.69 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 02:34:49,157] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.97 | bwd_microstep: 271.71 | bwd_inner_microstep: 271.69 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 02:34:49,630] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.76 | bwd_microstep: 271.79 | bwd_inner_microstep: 271.77 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 02:34:50,104] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.35 | bwd_microstep: 271.38 | bwd_inner_microstep: 271.36 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 02:34:50,579] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.21 | bwd_microstep: 271.67 | bwd_inner_microstep: 271.65 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 02:34:51,052] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.35 | bwd_microstep: 271.15 | bwd_inner_microstep: 271.13 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 02:34:51,525] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.46 | bwd_microstep: 271.27 | bwd_inner_microstep: 271.25 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 827 +[2025-05-02 02:34:51,903] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.08 | optimizer_step: 16.55 +[2025-05-02 02:34:51,903] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 96.14 | bwd_microstep: 243.73 | bwd_inner_microstep: 160.10 | bwd_allreduce_microstep: 83.54 | step_microstep: 24.90 +[2025-05-02 02:34:51,904] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2798.98 | bwd: 4152.22 | bwd_inner: 4068.34 | bwd_allreduce: 83.61 | step: 25.64 + 20%|██ | 1751/8720 [4:19:25<15:42:39, 8.12s/it] {'loss': 0.3631, 'grad_norm': 6.25006628036499, 'learning_rate': 9.254590030681174e-06, 'epoch': 2.01} + 20%|██ | 1751/8720 [4:19:25<15:42:39, 8.12s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 315 +[2025-05-02 02:34:52,150] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 81.15 | bwd_microstep: 146.60 | bwd_inner_microstep: 146.46 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.09 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 850 +[2025-05-02 02:34:52,402] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.51 | bwd_microstep: 143.18 | bwd_inner_microstep: 143.10 | bwd_allreduce_microstep: 0.04 | step_microstep: 0.09 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1358 +[2025-05-02 02:34:52,762] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.36 | bwd_microstep: 205.78 | bwd_inner_microstep: 205.76 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1371 +[2025-05-02 02:34:53,124] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.17 | bwd_microstep: 207.17 | bwd_inner_microstep: 207.15 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-02 02:34:53,600] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.21 | bwd_microstep: 272.22 | bwd_inner_microstep: 272.20 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 02:34:54,077] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.77 | bwd_microstep: 273.07 | bwd_inner_microstep: 273.06 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 02:34:54,551] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.39 | bwd_microstep: 271.56 | bwd_inner_microstep: 271.53 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 02:34:55,025] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.24 | bwd_microstep: 272.05 | bwd_inner_microstep: 272.03 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 02:34:55,501] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.36 | bwd_microstep: 272.60 | bwd_inner_microstep: 272.58 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 02:34:55,977] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.67 | bwd_microstep: 272.36 | bwd_inner_microstep: 272.34 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 02:34:56,450] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.33 | bwd_microstep: 271.22 | bwd_inner_microstep: 271.21 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 02:34:56,923] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.79 | bwd_microstep: 271.37 | bwd_inner_microstep: 271.35 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 02:34:57,398] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.41 | bwd_microstep: 271.83 | bwd_inner_microstep: 271.81 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 02:34:57,872] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.68 | bwd_microstep: 270.73 | bwd_inner_microstep: 270.71 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 02:34:58,347] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.78 | bwd_microstep: 270.92 | bwd_inner_microstep: 270.90 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 02:34:58,923] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.12 | optimizer_step: 16.49 +[2025-05-02 02:34:58,924] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.06 | bwd_microstep: 348.86 | bwd_inner_microstep: 270.91 | bwd_allreduce_microstep: 77.90 | step_microstep: 24.09 +[2025-05-02 02:34:58,925] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2709.62 | bwd: 4041.57 | bwd_inner: 3963.14 | bwd_allreduce: 78.07 | step: 24.93 + 20%|██ | 1752/8720 [4:19:32<15:04:25, 7.79s/it] {'loss': 0.4254, 'grad_norm': 33.776676177978516, 'learning_rate': 9.253614167335954e-06, 'epoch': 2.01} + 20%|██ | 1752/8720 [4:19:32<15:04:25, 7.79s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 02:34:59,405] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.43 | bwd_microstep: 269.71 | bwd_inner_microstep: 269.70 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 02:34:59,880] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.63 | bwd_microstep: 270.64 | bwd_inner_microstep: 270.62 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2053 +[2025-05-02 02:35:00,399] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 201.38 | bwd_microstep: 301.15 | bwd_inner_microstep: 301.13 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.20 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 389 +[2025-05-02 02:35:00,631] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 92.61 | bwd_microstep: 124.93 | bwd_inner_microstep: 124.67 | bwd_allreduce_microstep: 0.10 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1918 +[2025-05-02 02:35:01,112] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.56 | bwd_microstep: 275.91 | bwd_inner_microstep: 275.89 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1370 +[2025-05-02 02:35:01,477] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.47 | bwd_microstep: 207.18 | bwd_inner_microstep: 206.96 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-02 02:35:01,958] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.11 | bwd_microstep: 273.28 | bwd_inner_microstep: 273.26 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 02:35:02,438] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.84 | bwd_microstep: 272.99 | bwd_inner_microstep: 272.98 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 02:35:02,920] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.78 | bwd_microstep: 272.58 | bwd_inner_microstep: 272.56 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 02:35:03,401] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.38 | bwd_microstep: 272.46 | bwd_inner_microstep: 272.44 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 840 +[2025-05-02 02:35:03,657] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 112.12 | bwd_microstep: 125.29 | bwd_inner_microstep: 125.20 | bwd_allreduce_microstep: 0.03 | step_microstep: 0.11 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1344 +[2025-05-02 02:35:04,020] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.39 | bwd_microstep: 204.19 | bwd_inner_microstep: 204.12 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 02:35:04,498] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.53 | bwd_microstep: 270.82 | bwd_inner_microstep: 270.80 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 834 +[2025-05-02 02:35:04,752] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 106.28 | bwd_microstep: 130.96 | bwd_inner_microstep: 130.84 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 02:35:05,228] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.92 | bwd_microstep: 270.82 | bwd_inner_microstep: 270.80 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 317 +[2025-05-02 02:35:05,607] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.11 | optimizer_step: 16.55 +[2025-05-02 02:35:05,608] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 110.73 | bwd_microstep: 228.08 | bwd_inner_microstep: 129.79 | bwd_allreduce_microstep: 98.17 | step_microstep: 25.97 +[2025-05-02 02:35:05,610] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2604.77 | bwd: 3771.09 | bwd_inner: 3671.86 | bwd_allreduce: 98.55 | step: 27.23 + 20%|██ | 1753/8720 [4:19:39<14:25:52, 7.46s/it] {'loss': 0.5778, 'grad_norm': 5.13577938079834, 'learning_rate': 9.252637717146999e-06, 'epoch': 2.01} + 20%|██ | 1753/8720 [4:19:39<14:25:52, 7.46s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 02:35:06,092] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.96 | bwd_microstep: 269.94 | bwd_inner_microstep: 269.92 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1901 +[2025-05-02 02:35:06,575] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.69 | bwd_microstep: 275.21 | bwd_inner_microstep: 275.19 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1894 +[2025-05-02 02:35:07,057] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.78 | bwd_microstep: 274.51 | bwd_inner_microstep: 274.50 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1892 +[2025-05-02 02:35:07,538] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.87 | bwd_microstep: 274.74 | bwd_inner_microstep: 274.72 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1888 +[2025-05-02 02:35:08,017] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.87 | bwd_microstep: 274.06 | bwd_inner_microstep: 274.04 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-02 02:35:08,496] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.57 | bwd_microstep: 273.43 | bwd_inner_microstep: 273.42 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-02 02:35:08,973] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.85 | bwd_microstep: 273.27 | bwd_inner_microstep: 273.25 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 02:35:09,450] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.41 | bwd_microstep: 272.26 | bwd_inner_microstep: 272.24 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.20 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 837 +[2025-05-02 02:35:09,696] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 105.45 | bwd_microstep: 125.75 | bwd_inner_microstep: 125.51 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 02:35:10,175] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.35 | bwd_microstep: 271.92 | bwd_inner_microstep: 271.90 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 02:35:10,653] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.98 | bwd_microstep: 271.81 | bwd_inner_microstep: 271.79 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 02:35:11,130] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.55 | bwd_microstep: 270.92 | bwd_inner_microstep: 270.90 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 02:35:11,609] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.36 | bwd_microstep: 271.71 | bwd_inner_microstep: 271.69 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.20 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 318 +[2025-05-02 02:35:11,848] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 104.12 | bwd_microstep: 117.84 | bwd_inner_microstep: 117.67 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.11 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1341 +[2025-05-02 02:35:12,209] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 139.49 | bwd_microstep: 203.99 | bwd_inner_microstep: 203.91 | bwd_allreduce_microstep: 0.03 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 02:35:12,809] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.11 | optimizer_step: 16.58 +[2025-05-02 02:35:12,810] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.29 | bwd_microstep: 369.73 | bwd_inner_microstep: 271.30 | bwd_allreduce_microstep: 98.38 | step_microstep: 26.00 +[2025-05-02 02:35:12,811] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2807.21 | bwd: 4091.16 | bwd_inner: 3992.01 | bwd_allreduce: 98.66 | step: 27.44 + 20%|██ | 1754/8720 [4:19:46<14:16:51, 7.38s/it] {'loss': 0.3329, 'grad_norm': 3.0913736820220947, 'learning_rate': 9.251660680249023e-06, 'epoch': 2.01} + 20%|██ | 1754/8720 [4:19:46<14:16:51, 7.38s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 316 +[2025-05-02 02:35:13,039] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 90.12 | bwd_microstep: 116.54 | bwd_inner_microstep: 116.25 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1850 +[2025-05-02 02:35:13,514] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.08 | bwd_microstep: 270.42 | bwd_inner_microstep: 270.40 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2201 +[2025-05-02 02:35:14,059] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 207.55 | bwd_microstep: 321.72 | bwd_inner_microstep: 321.70 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1893 +[2025-05-02 02:35:14,538] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.32 | bwd_microstep: 274.09 | bwd_inner_microstep: 274.07 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1895 +[2025-05-02 02:35:15,019] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.84 | bwd_microstep: 274.23 | bwd_inner_microstep: 274.22 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1371 +[2025-05-02 02:35:15,385] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.74 | bwd_microstep: 206.98 | bwd_inner_microstep: 206.80 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.23 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-02 02:35:15,864] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.76 | bwd_microstep: 272.36 | bwd_inner_microstep: 272.35 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 02:35:16,345] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.34 | bwd_microstep: 272.87 | bwd_inner_microstep: 272.86 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.22 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1357 +[2025-05-02 02:35:16,711] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.97 | bwd_microstep: 205.77 | bwd_inner_microstep: 205.67 | bwd_allreduce_microstep: 0.04 | step_microstep: 0.13 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 02:35:17,195] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.86 | bwd_microstep: 272.87 | bwd_inner_microstep: 272.85 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-02 02:35:17,674] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.56 | bwd_microstep: 273.32 | bwd_inner_microstep: 273.31 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 848 +[2025-05-02 02:35:17,936] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 96.24 | bwd_microstep: 147.65 | bwd_inner_microstep: 147.34 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.11 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 838 +[2025-05-02 02:35:18,196] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.95 | bwd_microstep: 149.43 | bwd_inner_microstep: 149.11 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 02:35:18,674] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.44 | bwd_microstep: 272.26 | bwd_inner_microstep: 272.24 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 02:35:19,151] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.41 | bwd_microstep: 271.72 | bwd_inner_microstep: 271.70 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 02:35:19,732] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.05 | optimizer_step: 16.54 +[2025-05-02 02:35:19,732] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.23 | bwd_microstep: 348.68 | bwd_inner_microstep: 271.12 | bwd_allreduce_microstep: 77.49 | step_microstep: 24.22 +[2025-05-02 02:35:19,734] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2656.01 | bwd: 3951.04 | bwd_inner: 3872.17 | bwd_allreduce: 78.03 | step: 25.60 + 20%|██ | 1755/8720 [4:19:53<14:00:46, 7.24s/it] {'loss': 0.964, 'grad_norm': 8.29026985168457, 'learning_rate': 9.250683056776821e-06, 'epoch': 2.01} + 20%|██ | 1755/8720 [4:19:53<14:00:46, 7.24s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 02:35:20,216] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.31 | bwd_microstep: 271.22 | bwd_inner_microstep: 271.20 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 02:35:20,696] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.86 | bwd_microstep: 270.86 | bwd_inner_microstep: 270.84 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1919 +[2025-05-02 02:35:21,181] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.25 | bwd_microstep: 276.22 | bwd_inner_microstep: 276.20 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1922 +[2025-05-02 02:35:21,682] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 193.97 | bwd_microstep: 286.09 | bwd_inner_microstep: 286.07 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-02 02:35:22,166] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.54 | bwd_microstep: 273.09 | bwd_inner_microstep: 273.07 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1891 +[2025-05-02 02:35:22,650] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.84 | bwd_microstep: 274.12 | bwd_inner_microstep: 274.10 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 02:35:23,128] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.72 | bwd_microstep: 272.04 | bwd_inner_microstep: 272.02 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 02:35:23,605] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.42 | bwd_microstep: 272.79 | bwd_inner_microstep: 272.77 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 843 +[2025-05-02 02:35:23,859] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.63 | bwd_microstep: 143.47 | bwd_inner_microstep: 143.19 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 02:35:24,335] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.75 | bwd_microstep: 271.77 | bwd_inner_microstep: 271.75 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 02:35:24,813] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.96 | bwd_microstep: 271.52 | bwd_inner_microstep: 271.51 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 02:35:25,293] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.14 | bwd_microstep: 272.48 | bwd_inner_microstep: 272.46 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 02:35:25,771] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.06 | bwd_microstep: 271.67 | bwd_inner_microstep: 271.66 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 02:35:26,248] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.16 | bwd_microstep: 271.29 | bwd_inner_microstep: 271.27 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 02:35:26,726] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.31 | bwd_microstep: 271.50 | bwd_inner_microstep: 271.48 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 02:35:27,307] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.08 | optimizer_step: 16.52 +[2025-05-02 02:35:27,307] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.30 | bwd_microstep: 350.78 | bwd_inner_microstep: 270.54 | bwd_allreduce_microstep: 80.19 | step_microstep: 24.10 +[2025-05-02 02:35:27,309] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2919.78 | bwd: 4320.95 | bwd_inner: 4240.21 | bwd_allreduce: 80.39 | step: 25.43 + 20%|██ | 1756/8720 [4:20:01<14:12:15, 7.34s/it] {'loss': 0.5742, 'grad_norm': 7.653007507324219, 'learning_rate': 9.249704846865274e-06, 'epoch': 2.01} + 20%|██ | 1756/8720 [4:20:01<14:12:15, 7.34s/it]dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 1010 +[2025-05-02 02:35:27,589] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 105.54 | bwd_microstep: 151.75 | bwd_inner_microstep: 151.60 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1911 +[2025-05-02 02:35:28,072] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.98 | bwd_microstep: 276.09 | bwd_inner_microstep: 276.07 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1940 +[2025-05-02 02:35:28,575] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.41 | bwd_microstep: 287.46 | bwd_inner_microstep: 287.44 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1934 +[2025-05-02 02:35:29,078] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 194.00 | bwd_microstep: 287.61 | bwd_inner_microstep: 287.59 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 866 +[2025-05-02 02:35:29,323] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.23 | bwd_microstep: 134.03 | bwd_inner_microstep: 133.75 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 381 +[2025-05-02 02:35:29,536] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 79.98 | bwd_microstep: 117.78 | bwd_inner_microstep: 117.63 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-02 02:35:30,015] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.95 | bwd_microstep: 273.09 | bwd_inner_microstep: 273.08 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-02 02:35:30,494] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.06 | bwd_microstep: 272.96 | bwd_inner_microstep: 272.94 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 02:35:30,971] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.15 | bwd_microstep: 272.90 | bwd_inner_microstep: 272.88 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 02:35:31,448] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.16 | bwd_microstep: 273.47 | bwd_inner_microstep: 273.45 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 02:35:31,923] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.24 | bwd_microstep: 271.97 | bwd_inner_microstep: 271.96 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-02 02:35:32,399] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.14 | bwd_microstep: 273.14 | bwd_inner_microstep: 273.12 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.17 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 02:35:32,874] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.86 | bwd_microstep: 271.93 | bwd_inner_microstep: 271.92 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 02:35:33,352] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.51 | bwd_microstep: 272.52 | bwd_inner_microstep: 272.50 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 02:35:33,827] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.62 | bwd_microstep: 272.19 | bwd_inner_microstep: 272.17 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 321 +[2025-05-02 02:35:34,135] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.09 | optimizer_step: 16.66 +[2025-05-02 02:35:34,135] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 68.71 | bwd_microstep: 202.64 | bwd_inner_microstep: 135.82 | bwd_allreduce_microstep: 66.74 | step_microstep: 23.85 +[2025-05-02 02:35:34,136] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2625.23 | bwd: 3911.58 | bwd_inner: 3844.02 | bwd_allreduce: 67.04 | step: 24.84 + 20%|██ | 1757/8720 [4:20:07<13:54:06, 7.19s/it] {'loss': 0.89, 'grad_norm': 5.924834728240967, 'learning_rate': 9.24872605064933e-06, 'epoch': 2.01} + 20%|██ | 1757/8720 [4:20:07<13:54:06, 7.19s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 02:35:34,616] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.71 | bwd_microstep: 271.46 | bwd_inner_microstep: 271.45 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 319 +[2025-05-02 02:35:34,824] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 77.51 | bwd_microstep: 117.17 | bwd_inner_microstep: 117.04 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1955 +[2025-05-02 02:35:35,323] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 194.67 | bwd_microstep: 288.96 | bwd_inner_microstep: 288.94 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 371 +[2025-05-02 02:35:35,535] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 73.21 | bwd_microstep: 124.86 | bwd_inner_microstep: 124.55 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.22 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 341 +[2025-05-02 02:35:35,748] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 78.23 | bwd_microstep: 120.58 | bwd_inner_microstep: 120.30 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-02 02:35:36,226] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.79 | bwd_microstep: 273.61 | bwd_inner_microstep: 273.59 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1366 +[2025-05-02 02:35:36,589] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.07 | bwd_microstep: 206.78 | bwd_inner_microstep: 206.63 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 02:35:37,066] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.81 | bwd_microstep: 272.36 | bwd_inner_microstep: 272.35 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-02 02:35:37,543] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.83 | bwd_microstep: 273.02 | bwd_inner_microstep: 273.00 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 02:35:38,021] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.36 | bwd_microstep: 273.18 | bwd_inner_microstep: 273.16 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 334 +[2025-05-02 02:35:38,235] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 78.50 | bwd_microstep: 122.00 | bwd_inner_microstep: 121.87 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 02:35:38,712] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.99 | bwd_microstep: 272.32 | bwd_inner_microstep: 272.31 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 02:35:39,193] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.12 | bwd_microstep: 272.01 | bwd_inner_microstep: 271.99 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 02:35:39,673] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.89 | bwd_microstep: 272.12 | bwd_inner_microstep: 272.11 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1345 +[2025-05-02 02:35:40,038] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 139.71 | bwd_microstep: 204.69 | bwd_inner_microstep: 204.67 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 02:35:40,614] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.07 | optimizer_gradients: 2.14 | optimizer_step: 16.69 +[2025-05-02 02:35:40,614] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.92 | bwd_microstep: 346.79 | bwd_inner_microstep: 270.43 | bwd_allreduce_microstep: 76.31 | step_microstep: 24.61 +[2025-05-02 02:35:40,616] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2475.99 | bwd: 3712.02 | bwd_inner: 3634.55 | bwd_allreduce: 76.82 | step: 25.68 + 20%|██ | 1758/8720 [4:20:14<13:29:25, 6.98s/it] {'loss': 0.5088, 'grad_norm': 6.359701633453369, 'learning_rate': 9.247746668264037e-06, 'epoch': 2.02} + 20%|██ | 1758/8720 [4:20:14<13:29:25, 6.98s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 02:35:41,098] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.19 | bwd_microstep: 270.10 | bwd_inner_microstep: 270.08 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 02:35:41,575] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.28 | bwd_microstep: 271.68 | bwd_inner_microstep: 271.66 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1995 +[2025-05-02 02:35:42,083] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 198.41 | bwd_microstep: 293.34 | bwd_inner_microstep: 293.32 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1893 +[2025-05-02 02:35:42,563] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.72 | bwd_microstep: 274.12 | bwd_inner_microstep: 274.11 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1889 +[2025-05-02 02:35:43,046] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.94 | bwd_microstep: 273.82 | bwd_inner_microstep: 273.80 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-02 02:35:43,528] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.62 | bwd_microstep: 273.27 | bwd_inner_microstep: 273.25 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 02:35:44,008] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.95 | bwd_microstep: 272.02 | bwd_inner_microstep: 272.01 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 02:35:44,490] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.40 | bwd_microstep: 272.25 | bwd_inner_microstep: 272.24 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 02:35:44,970] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.41 | bwd_microstep: 271.91 | bwd_inner_microstep: 271.89 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.16 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 02:35:45,449] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.24 | bwd_microstep: 272.31 | bwd_inner_microstep: 272.29 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 842 +[2025-05-02 02:35:45,692] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.01 | bwd_microstep: 131.81 | bwd_inner_microstep: 131.59 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 324 +[2025-05-02 02:35:45,918] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 85.26 | bwd_microstep: 124.62 | bwd_inner_microstep: 124.31 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 02:35:46,396] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.73 | bwd_microstep: 272.66 | bwd_inner_microstep: 272.65 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 02:35:46,874] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.70 | bwd_microstep: 271.46 | bwd_inner_microstep: 271.44 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 02:35:47,353] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.75 | bwd_microstep: 271.78 | bwd_inner_microstep: 271.77 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 02:35:47,932] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.16 | optimizer_step: 16.83 +[2025-05-02 02:35:47,934] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.40 | bwd_microstep: 349.18 | bwd_inner_microstep: 271.40 | bwd_allreduce_microstep: 77.72 | step_microstep: 24.96 +[2025-05-02 02:35:47,935] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2819.60 | bwd: 4166.38 | bwd_inner: 4087.86 | bwd_allreduce: 78.04 | step: 25.97 + 20%|██ | 1759/8720 [4:20:21<13:41:14, 7.08s/it] {'loss': 0.495, 'grad_norm': 13.180047035217285, 'learning_rate': 9.24676669984451e-06, 'epoch': 2.02} + 20%|██ | 1759/8720 [4:20:21<13:41:14, 7.08s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 02:35:48,417] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.34 | bwd_microstep: 270.30 | bwd_inner_microstep: 270.28 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 02:35:48,893] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.53 | bwd_microstep: 271.01 | bwd_inner_microstep: 270.99 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 366 +[2025-05-02 02:35:49,119] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 89.31 | bwd_microstep: 120.55 | bwd_inner_microstep: 120.39 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1896 +[2025-05-02 02:35:49,600] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.90 | bwd_microstep: 274.76 | bwd_inner_microstep: 274.75 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.15 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1893 +[2025-05-02 02:35:50,085] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.15 | bwd_microstep: 275.12 | bwd_inner_microstep: 275.11 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-02 02:35:50,568] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.87 | bwd_microstep: 275.08 | bwd_inner_microstep: 275.06 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-02 02:35:51,049] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.60 | bwd_microstep: 273.23 | bwd_inner_microstep: 273.21 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-02 02:35:51,531] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.54 | bwd_microstep: 273.18 | bwd_inner_microstep: 273.16 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-02 02:35:52,015] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.30 | bwd_microstep: 273.56 | bwd_inner_microstep: 273.54 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-02 02:35:52,494] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.30 | bwd_microstep: 273.42 | bwd_inner_microstep: 273.40 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 02:35:52,974] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.18 | bwd_microstep: 273.16 | bwd_inner_microstep: 273.14 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 02:35:53,451] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.85 | bwd_microstep: 272.15 | bwd_inner_microstep: 272.13 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 02:35:53,932] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.06 | bwd_microstep: 272.42 | bwd_inner_microstep: 272.40 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 321 +[2025-05-02 02:35:54,156] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 84.44 | bwd_microstep: 123.62 | bwd_inner_microstep: 123.34 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 02:35:54,634] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.45 | bwd_microstep: 272.46 | bwd_inner_microstep: 272.44 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 02:35:55,212] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.09 | optimizer_step: 16.68 +[2025-05-02 02:35:55,213] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.38 | bwd_microstep: 348.53 | bwd_inner_microstep: 271.53 | bwd_allreduce_microstep: 76.95 | step_microstep: 24.47 +[2025-05-02 02:35:55,214] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2810.83 | bwd: 4142.59 | bwd_inner: 4064.97 | bwd_allreduce: 77.20 | step: 25.51 + 20%|██ | 1760/8720 [4:20:28<13:48:05, 7.14s/it] {'loss': 0.459, 'grad_norm': 4.629913330078125, 'learning_rate': 9.245786145525948e-06, 'epoch': 2.02} + 20%|██ | 1760/8720 [4:20:28<13:48:05, 7.14s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1982 +[2025-05-02 02:35:55,725] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 197.28 | bwd_microstep: 290.31 | bwd_inner_microstep: 290.29 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1962 +[2025-05-02 02:35:56,232] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 197.34 | bwd_microstep: 289.40 | bwd_inner_microstep: 289.38 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1214 +[2025-05-02 02:35:56,544] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 119.95 | bwd_microstep: 175.20 | bwd_inner_microstep: 175.04 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1962 +[2025-05-02 02:35:57,047] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.96 | bwd_microstep: 289.92 | bwd_inner_microstep: 289.90 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-02 02:35:57,525] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.42 | bwd_microstep: 272.69 | bwd_inner_microstep: 272.67 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 330 +[2025-05-02 02:35:57,770] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 74.84 | bwd_microstep: 156.20 | bwd_inner_microstep: 155.94 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 02:35:58,247] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.33 | bwd_microstep: 272.54 | bwd_inner_microstep: 272.53 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 02:35:58,724] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.53 | bwd_microstep: 272.49 | bwd_inner_microstep: 272.47 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 330 +[2025-05-02 02:35:58,963] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 69.56 | bwd_microstep: 155.45 | bwd_inner_microstep: 155.15 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 02:35:59,439] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.64 | bwd_microstep: 272.48 | bwd_inner_microstep: 272.46 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 02:35:59,915] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.86 | bwd_microstep: 272.31 | bwd_inner_microstep: 272.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 02:36:00,389] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.62 | bwd_microstep: 272.07 | bwd_inner_microstep: 272.05 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 02:36:00,865] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.19 | bwd_microstep: 271.85 | bwd_inner_microstep: 271.83 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1344 +[2025-05-02 02:36:01,224] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.57 | bwd_microstep: 204.07 | bwd_inner_microstep: 203.97 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 02:36:01,698] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.92 | bwd_microstep: 270.65 | bwd_inner_microstep: 270.64 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 02:36:02,263] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.19 | optimizer_step: 17.00 +[2025-05-02 02:36:02,264] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.08 | bwd_microstep: 338.76 | bwd_inner_microstep: 270.86 | bwd_allreduce_microstep: 67.85 | step_microstep: 24.31 +[2025-05-02 02:36:02,265] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2685.78 | bwd: 4076.45 | bwd_inner: 4007.64 | bwd_allreduce: 68.25 | step: 25.41 + 20%|██ | 1761/8720 [4:20:36<13:44:51, 7.11s/it] {'loss': 0.42, 'grad_norm': 4.740091323852539, 'learning_rate': 9.244805005443632e-06, 'epoch': 2.02} + 20%|██ | 1761/8720 [4:20:36<13:44:51, 7.11s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 02:36:02,743] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.44 | bwd_microstep: 270.36 | bwd_inner_microstep: 270.34 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1890 +[2025-05-02 02:36:03,224] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.10 | bwd_microstep: 274.82 | bwd_inner_microstep: 274.80 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1921 +[2025-05-02 02:36:03,721] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 194.88 | bwd_microstep: 286.68 | bwd_inner_microstep: 286.66 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1891 +[2025-05-02 02:36:04,202] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.92 | bwd_microstep: 275.16 | bwd_inner_microstep: 275.14 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 345 +[2025-05-02 02:36:04,439] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 71.18 | bwd_microstep: 151.90 | bwd_inner_microstep: 151.76 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-02 02:36:04,920] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.93 | bwd_microstep: 274.78 | bwd_inner_microstep: 274.77 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 02:36:05,402] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.52 | bwd_microstep: 273.87 | bwd_inner_microstep: 273.85 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 02:36:05,883] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.64 | bwd_microstep: 273.54 | bwd_inner_microstep: 273.53 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 02:36:06,364] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.49 | bwd_microstep: 272.48 | bwd_inner_microstep: 272.47 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 02:36:06,844] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.13 | bwd_microstep: 273.14 | bwd_inner_microstep: 273.12 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 02:36:07,324] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.61 | bwd_microstep: 273.52 | bwd_inner_microstep: 273.51 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 02:36:07,802] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.96 | bwd_microstep: 272.72 | bwd_inner_microstep: 272.70 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 02:36:08,283] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.69 | bwd_microstep: 272.65 | bwd_inner_microstep: 272.63 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 02:36:08,765] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.25 | bwd_microstep: 272.67 | bwd_inner_microstep: 272.65 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 02:36:09,247] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.61 | bwd_microstep: 272.57 | bwd_inner_microstep: 272.55 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.05 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 832 +[2025-05-02 02:36:09,630] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.08 | optimizer_step: 16.54 +[2025-05-02 02:36:09,631] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 101.29 | bwd_microstep: 236.19 | bwd_inner_microstep: 159.72 | bwd_allreduce_microstep: 76.37 | step_microstep: 24.08 +[2025-05-02 02:36:09,632] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2823.26 | bwd: 4227.08 | bwd_inner: 4150.26 | bwd_allreduce: 76.49 | step: 25.34 + 20%|██ | 1762/8720 [4:20:43<13:53:40, 7.19s/it] {'loss': 0.6881, 'grad_norm': 6.137080192565918, 'learning_rate': 9.243823279732925e-06, 'epoch': 2.02} + 20%|██ | 1762/8720 [4:20:43<13:53:40, 7.19s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 02:36:10,114] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.65 | bwd_microstep: 270.41 | bwd_inner_microstep: 270.39 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1377 +[2025-05-02 02:36:10,481] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 143.21 | bwd_microstep: 207.92 | bwd_inner_microstep: 207.83 | bwd_allreduce_microstep: 0.04 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1946 +[2025-05-02 02:36:10,983] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.40 | bwd_microstep: 288.21 | bwd_inner_microstep: 288.19 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 852 +[2025-05-02 02:36:11,234] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 96.70 | bwd_microstep: 134.52 | bwd_inner_microstep: 134.46 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 02:36:11,711] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.48 | bwd_microstep: 272.17 | bwd_inner_microstep: 272.15 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1886 +[2025-05-02 02:36:12,192] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.87 | bwd_microstep: 274.66 | bwd_inner_microstep: 274.65 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-02 02:36:12,673] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.54 | bwd_microstep: 272.86 | bwd_inner_microstep: 272.84 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 02:36:13,150] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.07 | bwd_microstep: 272.07 | bwd_inner_microstep: 272.06 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 02:36:13,630] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.55 | bwd_microstep: 272.23 | bwd_inner_microstep: 272.21 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1360 +[2025-05-02 02:36:13,999] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.15 | bwd_microstep: 205.90 | bwd_inner_microstep: 205.88 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 326 +[2025-05-02 02:36:14,220] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 82.67 | bwd_microstep: 121.93 | bwd_inner_microstep: 121.75 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 02:36:14,698] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.34 | bwd_microstep: 272.94 | bwd_inner_microstep: 272.93 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 02:36:15,177] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.58 | bwd_microstep: 272.86 | bwd_inner_microstep: 272.84 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 317 +[2025-05-02 02:36:15,389] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 77.96 | bwd_microstep: 118.53 | bwd_inner_microstep: 118.26 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 02:36:15,865] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.88 | bwd_microstep: 271.26 | bwd_inner_microstep: 271.25 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 02:36:16,453] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.07 | optimizer_step: 16.52 +[2025-05-02 02:36:16,453] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.85 | bwd_microstep: 356.65 | bwd_inner_microstep: 271.72 | bwd_allreduce_microstep: 84.87 | step_microstep: 24.08 +[2025-05-02 02:36:16,455] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2619.53 | bwd: 3885.20 | bwd_inner: 3799.52 | bwd_allreduce: 85.19 | step: 25.20 + 20%|██ | 1763/8720 [4:20:50<13:40:48, 7.08s/it] {'loss': 0.8019, 'grad_norm': 7.050351142883301, 'learning_rate': 9.242840968529268e-06, 'epoch': 2.02} + 20%|██ | 1763/8720 [4:20:50<13:40:48, 7.08s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 02:36:16,935] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.45 | bwd_microstep: 270.47 | bwd_inner_microstep: 270.45 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1926 +[2025-05-02 02:36:17,434] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.61 | bwd_microstep: 286.43 | bwd_inner_microstep: 286.42 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.15 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1759 +[2025-05-02 02:36:17,870] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 161.68 | bwd_microstep: 254.91 | bwd_inner_microstep: 254.89 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1893 +[2025-05-02 02:36:18,351] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.99 | bwd_microstep: 275.33 | bwd_inner_microstep: 274.87 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 354 +[2025-05-02 02:36:18,577] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 87.57 | bwd_microstep: 122.22 | bwd_inner_microstep: 121.91 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 02:36:19,058] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.07 | bwd_microstep: 273.72 | bwd_inner_microstep: 273.70 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 02:36:19,537] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.84 | bwd_microstep: 273.34 | bwd_inner_microstep: 273.32 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 02:36:20,019] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.36 | bwd_microstep: 273.36 | bwd_inner_microstep: 273.34 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 02:36:20,501] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.00 | bwd_microstep: 273.08 | bwd_inner_microstep: 273.06 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 837 +[2025-05-02 02:36:20,740] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.09 | bwd_microstep: 126.26 | bwd_inner_microstep: 126.07 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.10 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 834 +[2025-05-02 02:36:20,979] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.14 | bwd_microstep: 129.99 | bwd_inner_microstep: 129.77 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 02:36:21,457] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.88 | bwd_microstep: 272.98 | bwd_inner_microstep: 272.96 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1092 +[2025-05-02 02:36:21,752] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 117.96 | bwd_microstep: 160.66 | bwd_inner_microstep: 160.62 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 02:36:22,231] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.69 | bwd_microstep: 272.57 | bwd_inner_microstep: 272.56 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 02:36:22,709] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.70 | bwd_microstep: 271.61 | bwd_inner_microstep: 271.60 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 02:36:23,285] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.10 | optimizer_step: 16.52 +[2025-05-02 02:36:23,286] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.45 | bwd_microstep: 348.16 | bwd_inner_microstep: 272.12 | bwd_allreduce_microstep: 75.99 | step_microstep: 24.07 +[2025-05-02 02:36:23,287] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2637.13 | bwd: 3885.20 | bwd_inner: 3807.72 | bwd_allreduce: 76.85 | step: 25.38 + 20%|██ | 1764/8720 [4:20:57<13:32:07, 7.01s/it] {'loss': 0.4429, 'grad_norm': 4.3267388343811035, 'learning_rate': 9.241858071968185e-06, 'epoch': 2.02} + 20%|██ | 1764/8720 [4:20:57<13:32:07, 7.01s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 02:36:23,770] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.91 | bwd_microstep: 270.94 | bwd_inner_microstep: 270.92 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 314 +[2025-05-02 02:36:23,988] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 85.81 | bwd_microstep: 118.35 | bwd_inner_microstep: 118.19 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2053 +[2025-05-02 02:36:24,505] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 200.72 | bwd_microstep: 301.58 | bwd_inner_microstep: 301.56 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 02:36:24,982] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.20 | bwd_microstep: 273.41 | bwd_inner_microstep: 273.39 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 847 +[2025-05-02 02:36:25,224] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.58 | bwd_microstep: 132.83 | bwd_inner_microstep: 132.60 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-02 02:36:25,701] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.98 | bwd_microstep: 272.83 | bwd_inner_microstep: 272.82 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 840 +[2025-05-02 02:36:25,937] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.64 | bwd_microstep: 126.31 | bwd_inner_microstep: 126.07 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.19 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1096 +[2025-05-02 02:36:26,230] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 115.76 | bwd_microstep: 161.18 | bwd_inner_microstep: 161.16 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 6, images per sample: 6.0, dynamic token length: 1618 +[2025-05-02 02:36:26,660] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 165.85 | bwd_microstep: 246.00 | bwd_inner_microstep: 245.98 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 02:36:27,140] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.01 | bwd_microstep: 272.85 | bwd_inner_microstep: 272.84 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.18 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 333 +[2025-05-02 02:36:27,368] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 91.06 | bwd_microstep: 118.19 | bwd_inner_microstep: 117.96 | bwd_allreduce_microstep: 0.08 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 02:36:27,847] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.54 | bwd_microstep: 272.85 | bwd_inner_microstep: 272.83 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1094 +[2025-05-02 02:36:28,140] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 115.12 | bwd_microstep: 160.86 | bwd_inner_microstep: 160.83 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 02:36:28,617] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.96 | bwd_microstep: 272.20 | bwd_inner_microstep: 272.18 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 02:36:29,096] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.44 | bwd_microstep: 271.16 | bwd_inner_microstep: 271.14 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1345 +[2025-05-02 02:36:29,563] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.08 | optimizer_step: 16.51 +[2025-05-02 02:36:29,564] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.81 | bwd_microstep: 285.08 | bwd_inner_microstep: 205.75 | bwd_allreduce_microstep: 79.25 | step_microstep: 24.03 +[2025-05-02 02:36:29,565] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2420.04 | bwd: 3556.73 | bwd_inner: 3476.32 | bwd_allreduce: 79.66 | step: 25.40 + 20%|██ | 1765/8720 [4:21:03<13:06:43, 6.79s/it] {'loss': 0.9355, 'grad_norm': 7.359152793884277, 'learning_rate': 9.24087459018528e-06, 'epoch': 2.02} + 20%|██ | 1765/8720 [4:21:03<13:06:43, 6.79s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1966 +[2025-05-02 02:36:30,077] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 198.57 | bwd_microstep: 290.01 | bwd_inner_microstep: 289.99 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 02:36:30,556] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.81 | bwd_microstep: 273.12 | bwd_inner_microstep: 273.11 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-02 02:36:31,036] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.70 | bwd_microstep: 274.01 | bwd_inner_microstep: 274.00 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1889 +[2025-05-02 02:36:31,517] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.53 | bwd_microstep: 275.08 | bwd_inner_microstep: 275.06 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1889 +[2025-05-02 02:36:31,996] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.46 | bwd_microstep: 274.80 | bwd_inner_microstep: 274.79 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-02 02:36:32,475] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.30 | bwd_microstep: 274.38 | bwd_inner_microstep: 274.36 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-02 02:36:32,952] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.09 | bwd_microstep: 273.77 | bwd_inner_microstep: 273.76 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-02 02:36:33,430] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.20 | bwd_microstep: 273.41 | bwd_inner_microstep: 273.39 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-02 02:36:33,909] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.63 | bwd_microstep: 274.19 | bwd_inner_microstep: 274.18 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-02 02:36:34,390] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.58 | bwd_microstep: 273.99 | bwd_inner_microstep: 273.97 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 02:36:34,873] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.59 | bwd_microstep: 273.26 | bwd_inner_microstep: 273.24 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1355 +[2025-05-02 02:36:35,239] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.89 | bwd_microstep: 206.28 | bwd_inner_microstep: 206.26 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.11 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 838 +[2025-05-02 02:36:35,487] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 100.37 | bwd_microstep: 126.04 | bwd_inner_microstep: 126.02 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 02:36:35,966] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.64 | bwd_microstep: 272.86 | bwd_inner_microstep: 272.84 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 02:36:36,444] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.28 | bwd_microstep: 272.59 | bwd_inner_microstep: 272.57 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 02:36:37,025] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.06 | optimizer_step: 16.72 +[2025-05-02 02:36:37,025] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.36 | bwd_microstep: 350.76 | bwd_inner_microstep: 273.12 | bwd_allreduce_microstep: 77.58 | step_microstep: 24.26 +[2025-05-02 02:36:37,027] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2897.65 | bwd: 4258.57 | bwd_inner: 4180.66 | bwd_allreduce: 77.67 | step: 25.17 + 20%|██ | 1766/8720 [4:21:10<13:30:03, 6.99s/it] {'loss': 0.6959, 'grad_norm': 7.954008102416992, 'learning_rate': 9.239890523316237e-06, 'epoch': 2.03} + 20%|██ | 1766/8720 [4:21:10<13:30:03, 6.99s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 02:36:37,508] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.19 | bwd_microstep: 270.35 | bwd_inner_microstep: 270.33 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 02:36:37,985] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.67 | bwd_microstep: 270.97 | bwd_inner_microstep: 270.95 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1929 +[2025-05-02 02:36:38,486] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.57 | bwd_microstep: 287.68 | bwd_inner_microstep: 287.67 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 881 +[2025-05-02 02:36:38,744] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 103.74 | bwd_microstep: 135.12 | bwd_inner_microstep: 135.03 | bwd_allreduce_microstep: 0.04 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1908 +[2025-05-02 02:36:39,229] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.01 | bwd_microstep: 276.28 | bwd_inner_microstep: 276.26 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 02:36:39,711] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.79 | bwd_microstep: 274.27 | bwd_inner_microstep: 274.26 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1889 +[2025-05-02 02:36:40,192] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.57 | bwd_microstep: 274.90 | bwd_inner_microstep: 274.88 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 02:36:40,671] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.11 | bwd_microstep: 273.43 | bwd_inner_microstep: 273.41 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-02 02:36:41,158] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.55 | bwd_microstep: 273.61 | bwd_inner_microstep: 273.59 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 02:36:41,636] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.42 | bwd_microstep: 272.89 | bwd_inner_microstep: 272.88 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 02:36:42,116] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.78 | bwd_microstep: 272.92 | bwd_inner_microstep: 272.90 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 02:36:42,594] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.52 | bwd_microstep: 272.81 | bwd_inner_microstep: 272.79 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.13 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 02:36:43,074] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.39 | bwd_microstep: 272.71 | bwd_inner_microstep: 272.70 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1091 +[2025-05-02 02:36:43,366] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 115.21 | bwd_microstep: 160.82 | bwd_inner_microstep: 160.81 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 02:36:43,844] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.99 | bwd_microstep: 272.29 | bwd_inner_microstep: 272.27 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 02:36:44,429] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.07 | optimizer_step: 16.48 +[2025-05-02 02:36:44,429] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.70 | bwd_microstep: 353.00 | bwd_inner_microstep: 272.82 | bwd_allreduce_microstep: 80.12 | step_microstep: 24.08 +[2025-05-02 02:36:44,431] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2866.82 | bwd: 4214.08 | bwd_inner: 4133.55 | bwd_allreduce: 80.26 | step: 25.13 + 20%|██ | 1767/8720 [4:21:18<13:44:21, 7.11s/it] {'loss': 0.6807, 'grad_norm': 6.347464561462402, 'learning_rate': 9.238905871496823e-06, 'epoch': 2.03} + 20%|██ | 1767/8720 [4:21:18<13:44:21, 7.11s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 02:36:44,911] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.33 | bwd_microstep: 270.24 | bwd_inner_microstep: 270.22 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2062 +[2025-05-02 02:36:45,434] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 203.59 | bwd_microstep: 302.40 | bwd_inner_microstep: 302.38 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1958 +[2025-05-02 02:36:45,937] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.85 | bwd_microstep: 289.86 | bwd_inner_microstep: 289.85 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1948 +[2025-05-02 02:36:46,440] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.57 | bwd_microstep: 289.27 | bwd_inner_microstep: 289.25 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1922 +[2025-05-02 02:36:46,944] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.17 | bwd_microstep: 287.05 | bwd_inner_microstep: 287.04 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 362 +[2025-05-02 02:36:47,187] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 105.17 | bwd_microstep: 115.64 | bwd_inner_microstep: 115.38 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1899 +[2025-05-02 02:36:47,668] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.24 | bwd_microstep: 275.41 | bwd_inner_microstep: 275.39 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1897 +[2025-05-02 02:36:48,151] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.56 | bwd_microstep: 275.43 | bwd_inner_microstep: 275.41 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-02 02:36:48,632] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.69 | bwd_microstep: 273.91 | bwd_inner_microstep: 273.89 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 02:36:49,113] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.39 | bwd_microstep: 272.78 | bwd_inner_microstep: 272.76 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-02 02:36:49,593] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.85 | bwd_microstep: 273.81 | bwd_inner_microstep: 273.80 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 02:36:50,071] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.73 | bwd_microstep: 272.62 | bwd_inner_microstep: 272.61 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 02:36:50,549] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.48 | bwd_microstep: 273.08 | bwd_inner_microstep: 273.06 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 02:36:51,029] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.07 | bwd_microstep: 273.01 | bwd_inner_microstep: 273.00 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 328 +[2025-05-02 02:36:51,242] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 79.19 | bwd_microstep: 118.21 | bwd_inner_microstep: 117.91 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.09 +dynamic ViT batch size: 6, images per sample: 6.0, dynamic token length: 1603 +[2025-05-02 02:36:51,767] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.05 | optimizer_step: 16.46 +[2025-05-02 02:36:51,768] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 165.11 | bwd_microstep: 320.84 | bwd_inner_microstep: 243.80 | bwd_allreduce_microstep: 76.98 | step_microstep: 24.13 +[2025-05-02 02:36:51,769] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2836.63 | bwd: 4183.61 | bwd_inner: 4105.86 | bwd_allreduce: 77.28 | step: 24.99 + 20%|██ | 1768/8720 [4:21:25<13:52:02, 7.18s/it] {'loss': 0.9576, 'grad_norm': 6.709996700286865, 'learning_rate': 9.237920634862881e-06, 'epoch': 2.03} + 20%|██ | 1768/8720 [4:21:25<13:52:02, 7.18s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 321 +[2025-05-02 02:36:51,986] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 80.13 | bwd_microstep: 116.29 | bwd_inner_microstep: 116.14 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 02:36:52,464] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.45 | bwd_microstep: 271.38 | bwd_inner_microstep: 271.37 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1389 +[2025-05-02 02:36:52,836] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 144.85 | bwd_microstep: 208.55 | bwd_inner_microstep: 208.54 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 355 +[2025-05-02 02:36:53,050] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 80.14 | bwd_microstep: 118.74 | bwd_inner_microstep: 118.50 | bwd_allreduce_microstep: 0.09 | step_microstep: 0.15 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 344 +[2025-05-02 02:36:53,271] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 84.03 | bwd_microstep: 120.20 | bwd_inner_microstep: 120.02 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 346 +[2025-05-02 02:36:53,497] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 92.95 | bwd_microstep: 117.25 | bwd_inner_microstep: 117.05 | bwd_allreduce_microstep: 0.09 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 02:36:53,981] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.61 | bwd_microstep: 273.24 | bwd_inner_microstep: 273.22 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-02 02:36:54,461] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.88 | bwd_microstep: 273.60 | bwd_inner_microstep: 273.58 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 02:36:54,941] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.43 | bwd_microstep: 272.28 | bwd_inner_microstep: 272.26 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 02:36:55,424] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.84 | bwd_microstep: 272.60 | bwd_inner_microstep: 272.58 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 02:36:55,906] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.14 | bwd_microstep: 272.54 | bwd_inner_microstep: 272.53 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 02:36:56,389] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.52 | bwd_microstep: 272.59 | bwd_inner_microstep: 272.57 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 02:36:56,876] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.23 | bwd_microstep: 272.72 | bwd_inner_microstep: 272.70 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 02:36:57,355] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.95 | bwd_microstep: 271.23 | bwd_inner_microstep: 271.21 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.18 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1343 +[2025-05-02 02:36:57,717] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 139.70 | bwd_microstep: 204.89 | bwd_inner_microstep: 204.87 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 318 +[2025-05-02 02:36:58,053] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.13 | optimizer_step: 16.69 +[2025-05-02 02:36:58,053] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 85.71 | bwd_microstep: 209.79 | bwd_inner_microstep: 132.62 | bwd_allreduce_microstep: 77.07 | step_microstep: 24.51 +[2025-05-02 02:36:58,055] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2404.11 | bwd: 3548.01 | bwd_inner: 3469.95 | bwd_allreduce: 77.42 | step: 25.83 + 20%|██ | 1769/8720 [4:21:31<13:20:48, 6.91s/it] {'loss': 0.4731, 'grad_norm': 6.758031845092773, 'learning_rate': 9.23693481355034e-06, 'epoch': 2.03} + 20%|██ | 1769/8720 [4:21:31<13:20:48, 6.91s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 02:36:58,536] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.03 | bwd_microstep: 270.51 | bwd_inner_microstep: 270.49 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-02 02:36:59,019] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.98 | bwd_microstep: 274.23 | bwd_inner_microstep: 274.22 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1953 +[2025-05-02 02:36:59,523] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 196.17 | bwd_microstep: 289.27 | bwd_inner_microstep: 289.25 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1934 +[2025-05-02 02:37:00,025] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 196.14 | bwd_microstep: 287.78 | bwd_inner_microstep: 287.76 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1905 +[2025-05-02 02:37:00,510] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.57 | bwd_microstep: 275.76 | bwd_inner_microstep: 275.74 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-02 02:37:00,992] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.50 | bwd_microstep: 273.54 | bwd_inner_microstep: 273.52 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 02:37:01,475] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.14 | bwd_microstep: 273.47 | bwd_inner_microstep: 273.45 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-02 02:37:01,954] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.23 | bwd_microstep: 273.21 | bwd_inner_microstep: 273.19 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 838 +[2025-05-02 02:37:02,193] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.67 | bwd_microstep: 126.49 | bwd_inner_microstep: 126.26 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 02:37:02,673] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.08 | bwd_microstep: 272.92 | bwd_inner_microstep: 272.90 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 02:37:03,154] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.79 | bwd_microstep: 272.55 | bwd_inner_microstep: 272.53 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 325 +[2025-05-02 02:37:03,391] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 98.04 | bwd_microstep: 119.17 | bwd_inner_microstep: 118.95 | bwd_allreduce_microstep: 0.10 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 02:37:03,877] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.69 | bwd_microstep: 272.74 | bwd_inner_microstep: 272.72 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 02:37:04,361] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.34 | bwd_microstep: 272.25 | bwd_inner_microstep: 272.23 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 02:37:04,838] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.87 | bwd_microstep: 271.12 | bwd_inner_microstep: 271.11 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.12 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 318 +[2025-05-02 02:37:05,197] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.14 | optimizer_step: 16.71 +[2025-05-02 02:37:05,197] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.16 | bwd_microstep: 220.53 | bwd_inner_microstep: 143.32 | bwd_allreduce_microstep: 77.05 | step_microstep: 24.55 +[2025-05-02 02:37:05,199] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2751.97 | bwd: 4045.62 | bwd_inner: 3967.76 | bwd_allreduce: 77.32 | step: 25.68 + 20%|██ | 1770/8720 [4:21:38<13:28:45, 6.98s/it] {'loss': 0.4708, 'grad_norm': 4.5615997314453125, 'learning_rate': 9.235948407695208e-06, 'epoch': 2.03} + 20%|██ | 1770/8720 [4:21:38<13:28:45, 6.98s/it]dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 828 +[2025-05-02 02:37:05,447] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.75 | bwd_microstep: 129.98 | bwd_inner_microstep: 129.61 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 435 +[2025-05-02 02:37:05,667] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 80.85 | bwd_microstep: 124.25 | bwd_inner_microstep: 123.97 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1915 +[2025-05-02 02:37:06,150] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.65 | bwd_microstep: 276.08 | bwd_inner_microstep: 276.07 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 02:37:06,629] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.47 | bwd_microstep: 272.71 | bwd_inner_microstep: 272.69 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1362 +[2025-05-02 02:37:06,997] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.98 | bwd_microstep: 206.90 | bwd_inner_microstep: 206.82 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 02:37:07,479] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.17 | bwd_microstep: 272.52 | bwd_inner_microstep: 272.50 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 332 +[2025-05-02 02:37:07,698] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 82.20 | bwd_microstep: 120.03 | bwd_inner_microstep: 119.73 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 02:37:08,176] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.43 | bwd_microstep: 272.66 | bwd_inner_microstep: 272.64 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 02:37:08,658] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.05 | bwd_microstep: 272.72 | bwd_inner_microstep: 272.70 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 839 +[2025-05-02 02:37:08,899] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 96.27 | bwd_microstep: 126.22 | bwd_inner_microstep: 126.12 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 02:37:09,379] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.63 | bwd_microstep: 272.83 | bwd_inner_microstep: 272.82 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 02:37:09,863] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.66 | bwd_microstep: 272.28 | bwd_inner_microstep: 272.26 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 02:37:10,342] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.42 | bwd_microstep: 272.28 | bwd_inner_microstep: 272.26 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 02:37:10,820] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.45 | bwd_microstep: 272.19 | bwd_inner_microstep: 272.17 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 318 +[2025-05-02 02:37:11,040] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 79.66 | bwd_microstep: 124.75 | bwd_inner_microstep: 124.39 | bwd_allreduce_microstep: 0.14 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 02:37:11,623] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.13 | optimizer_step: 16.79 +[2025-05-02 02:37:11,624] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.10 | bwd_microstep: 352.93 | bwd_inner_microstep: 271.95 | bwd_allreduce_microstep: 80.92 | step_microstep: 24.64 +[2025-05-02 02:37:11,625] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2460.33 | bwd: 3641.45 | bwd_inner: 3558.97 | bwd_allreduce: 81.58 | step: 25.91 + 20%|██ | 1771/8720 [4:21:45<13:09:20, 6.82s/it] {'loss': 0.4093, 'grad_norm': 12.290578842163086, 'learning_rate': 9.23496141743357e-06, 'epoch': 2.03} + 20%|██ | 1771/8720 [4:21:45<13:09:20, 6.82s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 02:37:12,106] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.62 | bwd_microstep: 270.29 | bwd_inner_microstep: 270.27 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 02:37:12,582] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.21 | bwd_microstep: 270.83 | bwd_inner_microstep: 270.81 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1380 +[2025-05-02 02:37:12,952] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 143.73 | bwd_microstep: 208.08 | bwd_inner_microstep: 208.06 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1387 +[2025-05-02 02:37:13,320] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.88 | bwd_microstep: 208.78 | bwd_inner_microstep: 208.64 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.10 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 345 +[2025-05-02 02:37:13,532] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 74.89 | bwd_microstep: 121.47 | bwd_inner_microstep: 121.33 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1364 +[2025-05-02 02:37:13,894] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.57 | bwd_microstep: 206.74 | bwd_inner_microstep: 206.65 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-02 02:37:14,372] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.91 | bwd_microstep: 274.08 | bwd_inner_microstep: 274.06 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-02 02:37:14,852] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.62 | bwd_microstep: 273.71 | bwd_inner_microstep: 273.69 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 02:37:15,333] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.23 | bwd_microstep: 272.95 | bwd_inner_microstep: 272.93 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1353 +[2025-05-02 02:37:15,697] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.44 | bwd_microstep: 206.06 | bwd_inner_microstep: 205.99 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1350 +[2025-05-02 02:37:16,061] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.12 | bwd_microstep: 205.63 | bwd_inner_microstep: 205.62 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1349 +[2025-05-02 02:37:16,425] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.04 | bwd_microstep: 206.00 | bwd_inner_microstep: 205.85 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.21 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 02:37:16,904] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.31 | bwd_microstep: 272.56 | bwd_inner_microstep: 272.54 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 02:37:17,382] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.79 | bwd_microstep: 272.32 | bwd_inner_microstep: 272.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 02:37:17,859] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.99 | bwd_microstep: 272.28 | bwd_inner_microstep: 272.26 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 02:37:18,440] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.08 | optimizer_step: 16.69 +[2025-05-02 02:37:18,441] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.28 | bwd_microstep: 351.74 | bwd_inner_microstep: 271.67 | bwd_allreduce_microstep: 80.02 | step_microstep: 24.54 +[2025-05-02 02:37:18,442] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2615.31 | bwd: 3893.62 | bwd_inner: 3812.72 | bwd_allreduce: 80.41 | step: 25.76 + 20%|██ | 1772/8720 [4:21:52<13:09:15, 6.82s/it] {'loss': 0.8295, 'grad_norm': 11.84283447265625, 'learning_rate': 9.233973842901598e-06, 'epoch': 2.03} + 20%|██ | 1772/8720 [4:21:52<13:09:15, 6.82s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 02:37:18,925] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.95 | bwd_microstep: 271.57 | bwd_inner_microstep: 271.55 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 827 +[2025-05-02 02:37:19,165] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.21 | bwd_microstep: 129.76 | bwd_inner_microstep: 129.55 | bwd_allreduce_microstep: 0.10 | step_microstep: 0.10 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 375 +[2025-05-02 02:37:19,380] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 73.38 | bwd_microstep: 125.94 | bwd_inner_microstep: 125.81 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1970 +[2025-05-02 02:37:19,883] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 196.52 | bwd_microstep: 290.97 | bwd_inner_microstep: 290.95 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 337 +[2025-05-02 02:37:20,110] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 82.36 | bwd_microstep: 130.26 | bwd_inner_microstep: 130.10 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 02:37:20,588] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.15 | bwd_microstep: 272.85 | bwd_inner_microstep: 272.83 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 02:37:21,067] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.78 | bwd_microstep: 272.63 | bwd_inner_microstep: 272.61 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 02:37:21,546] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.23 | bwd_microstep: 272.68 | bwd_inner_microstep: 272.66 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 02:37:22,026] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.37 | bwd_microstep: 272.95 | bwd_inner_microstep: 272.93 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 836 +[2025-05-02 02:37:22,267] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.75 | bwd_microstep: 129.40 | bwd_inner_microstep: 129.24 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 02:37:22,746] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.97 | bwd_microstep: 272.84 | bwd_inner_microstep: 272.82 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 02:37:23,223] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.37 | bwd_microstep: 272.20 | bwd_inner_microstep: 272.19 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 02:37:23,699] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.23 | bwd_microstep: 271.44 | bwd_inner_microstep: 271.42 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 02:37:24,177] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.14 | bwd_microstep: 272.00 | bwd_inner_microstep: 271.98 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 02:37:24,654] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.27 | bwd_microstep: 271.22 | bwd_inner_microstep: 271.20 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 02:37:25,244] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.18 | optimizer_step: 16.82 +[2025-05-02 02:37:25,245] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.03 | bwd_microstep: 356.25 | bwd_inner_microstep: 271.77 | bwd_allreduce_microstep: 84.43 | step_microstep: 24.72 +[2025-05-02 02:37:25,246] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2609.35 | bwd: 3885.02 | bwd_inner: 3799.73 | bwd_allreduce: 84.77 | step: 25.67 + 20%|██ | 1773/8720 [4:21:58<13:08:44, 6.81s/it] {'loss': 0.3073, 'grad_norm': 11.598796844482422, 'learning_rate': 9.23298568423554e-06, 'epoch': 2.03} + 20%|██ | 1773/8720 [4:21:58<13:08:44, 6.81s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 02:37:25,728] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.37 | bwd_microstep: 270.79 | bwd_inner_microstep: 270.77 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 02:37:26,210] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.42 | bwd_microstep: 274.38 | bwd_inner_microstep: 274.36 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1963 +[2025-05-02 02:37:26,716] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 198.56 | bwd_microstep: 290.34 | bwd_inner_microstep: 290.33 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1944 +[2025-05-02 02:37:27,222] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 198.33 | bwd_microstep: 288.79 | bwd_inner_microstep: 288.78 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 378 +[2025-05-02 02:37:27,449] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 87.37 | bwd_microstep: 120.98 | bwd_inner_microstep: 120.68 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1893 +[2025-05-02 02:37:27,929] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.90 | bwd_microstep: 275.60 | bwd_inner_microstep: 275.58 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 334 +[2025-05-02 02:37:28,145] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 80.46 | bwd_microstep: 119.46 | bwd_inner_microstep: 119.25 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 02:37:28,624] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.23 | bwd_microstep: 273.63 | bwd_inner_microstep: 273.61 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 02:37:29,103] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.42 | bwd_microstep: 272.96 | bwd_inner_microstep: 272.95 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 333 +[2025-05-02 02:37:29,328] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 92.42 | bwd_microstep: 115.95 | bwd_inner_microstep: 115.71 | bwd_allreduce_microstep: 0.09 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 02:37:29,807] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.00 | bwd_microstep: 273.09 | bwd_inner_microstep: 273.07 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 02:37:30,285] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.36 | bwd_microstep: 273.27 | bwd_inner_microstep: 273.25 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 02:37:30,768] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.57 | bwd_microstep: 272.58 | bwd_inner_microstep: 272.57 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 02:37:31,251] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.91 | bwd_microstep: 272.39 | bwd_inner_microstep: 272.37 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 02:37:31,734] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.78 | bwd_microstep: 272.29 | bwd_inner_microstep: 272.27 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 02:37:32,315] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.05 | optimizer_step: 16.47 +[2025-05-02 02:37:32,316] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.88 | bwd_microstep: 348.54 | bwd_inner_microstep: 271.85 | bwd_allreduce_microstep: 76.64 | step_microstep: 24.04 +[2025-05-02 02:37:32,317] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2730.57 | bwd: 4015.09 | bwd_inner: 3937.58 | bwd_allreduce: 76.96 | step: 25.02 + 20%|██ | 1774/8720 [4:22:06<13:17:37, 6.89s/it] {'loss': 0.8983, 'grad_norm': 16.826143264770508, 'learning_rate': 9.231996941571724e-06, 'epoch': 2.03} + 20%|██ | 1774/8720 [4:22:06<13:17:37, 6.89s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 02:37:32,798] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.78 | bwd_microstep: 270.57 | bwd_inner_microstep: 270.55 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1085 +[2025-05-02 02:37:33,094] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 117.47 | bwd_microstep: 159.67 | bwd_inner_microstep: 159.60 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.10 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 993 +[2025-05-02 02:37:33,366] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 104.96 | bwd_microstep: 150.74 | bwd_inner_microstep: 150.66 | bwd_allreduce_microstep: 0.04 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1955 +[2025-05-02 02:37:33,869] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.52 | bwd_microstep: 290.08 | bwd_inner_microstep: 290.07 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1905 +[2025-05-02 02:37:34,356] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.44 | bwd_microstep: 276.09 | bwd_inner_microstep: 276.07 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-02 02:37:34,839] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.36 | bwd_microstep: 274.12 | bwd_inner_microstep: 274.10 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-02 02:37:35,321] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.21 | bwd_microstep: 273.96 | bwd_inner_microstep: 273.94 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 02:37:35,805] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.84 | bwd_microstep: 273.47 | bwd_inner_microstep: 273.46 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 847 +[2025-05-02 02:37:36,059] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 99.04 | bwd_microstep: 132.14 | bwd_inner_microstep: 132.00 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-02 02:37:36,543] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.27 | bwd_microstep: 274.18 | bwd_inner_microstep: 274.16 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 02:37:37,028] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.58 | bwd_microstep: 273.30 | bwd_inner_microstep: 273.29 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 02:37:37,509] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.19 | bwd_microstep: 273.18 | bwd_inner_microstep: 273.17 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 02:37:37,992] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.95 | bwd_microstep: 272.88 | bwd_inner_microstep: 272.87 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 02:37:38,475] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.45 | bwd_microstep: 272.68 | bwd_inner_microstep: 272.66 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.21 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 02:37:38,956] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.60 | bwd_microstep: 272.14 | bwd_inner_microstep: 272.13 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 02:37:39,550] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.16 | optimizer_step: 16.72 +[2025-05-02 02:37:39,550] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.55 | bwd_microstep: 358.89 | bwd_inner_microstep: 271.70 | bwd_allreduce_microstep: 87.14 | step_microstep: 25.18 +[2025-05-02 02:37:39,552] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2780.80 | bwd: 4098.20 | bwd_inner: 4010.42 | bwd_allreduce: 87.37 | step: 26.28 + 20%|██ | 1775/8720 [4:22:13<13:29:30, 6.99s/it] {'loss': 0.5692, 'grad_norm': 11.704590797424316, 'learning_rate': 9.231007615046564e-06, 'epoch': 2.04} + 20%|██ | 1775/8720 [4:22:13<13:29:30, 6.99s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 02:37:40,035] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.49 | bwd_microstep: 270.41 | bwd_inner_microstep: 270.39 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 02:37:40,512] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.58 | bwd_microstep: 270.98 | bwd_inner_microstep: 270.96 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1889 +[2025-05-02 02:37:40,999] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.91 | bwd_microstep: 274.80 | bwd_inner_microstep: 274.79 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 349 +[2025-05-02 02:37:41,231] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 87.98 | bwd_microstep: 126.07 | bwd_inner_microstep: 125.91 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1883 +[2025-05-02 02:37:41,712] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.68 | bwd_microstep: 274.34 | bwd_inner_microstep: 274.32 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1368 +[2025-05-02 02:37:42,080] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.92 | bwd_microstep: 207.42 | bwd_inner_microstep: 207.31 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.13 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 855 +[2025-05-02 02:37:42,326] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.42 | bwd_microstep: 133.20 | bwd_inner_microstep: 132.98 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.13 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-02 02:37:42,805] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.58 | bwd_microstep: 273.57 | bwd_inner_microstep: 273.55 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 02:37:43,286] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.79 | bwd_microstep: 272.83 | bwd_inner_microstep: 272.81 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 02:37:43,768] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.19 | bwd_microstep: 272.91 | bwd_inner_microstep: 272.89 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.11 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1357 +[2025-05-02 02:37:44,139] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.82 | bwd_microstep: 206.54 | bwd_inner_microstep: 206.32 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 02:37:44,624] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.46 | bwd_microstep: 273.48 | bwd_inner_microstep: 273.46 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.21 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 02:37:45,104] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.31 | bwd_microstep: 272.84 | bwd_inner_microstep: 272.83 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 02:37:45,586] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.43 | bwd_microstep: 272.48 | bwd_inner_microstep: 272.46 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 02:37:46,066] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.74 | bwd_microstep: 271.64 | bwd_inner_microstep: 271.62 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 02:37:46,646] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.12 | optimizer_step: 16.75 +[2025-05-02 02:37:46,646] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.18 | bwd_microstep: 349.39 | bwd_inner_microstep: 272.12 | bwd_allreduce_microstep: 77.21 | step_microstep: 24.01 +[2025-05-02 02:37:46,647] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2727.12 | bwd: 4022.99 | bwd_inner: 3944.84 | bwd_allreduce: 77.62 | step: 25.49 + 20%|██ | 1776/8720 [4:22:20<13:32:52, 7.02s/it] {'loss': 0.6887, 'grad_norm': 18.487741470336914, 'learning_rate': 9.230017704796549e-06, 'epoch': 2.04} + 20%|██ | 1776/8720 [4:22:20<13:32:52, 7.02s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 02:37:47,127] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.88 | bwd_microstep: 270.53 | bwd_inner_microstep: 270.51 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 02:37:47,605] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.20 | bwd_microstep: 271.44 | bwd_inner_microstep: 271.42 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1925 +[2025-05-02 02:37:48,106] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.56 | bwd_microstep: 287.19 | bwd_inner_microstep: 287.17 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-02 02:37:48,591] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.43 | bwd_microstep: 275.08 | bwd_inner_microstep: 275.06 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-02 02:37:49,075] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.81 | bwd_microstep: 274.15 | bwd_inner_microstep: 274.14 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-02 02:37:49,560] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.29 | bwd_microstep: 273.84 | bwd_inner_microstep: 273.83 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 846 +[2025-05-02 02:37:49,809] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 96.39 | bwd_microstep: 132.46 | bwd_inner_microstep: 132.23 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.14 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1347 +[2025-05-02 02:37:50,175] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.63 | bwd_microstep: 205.85 | bwd_inner_microstep: 205.71 | bwd_allreduce_microstep: 0.09 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 02:37:50,658] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.38 | bwd_microstep: 272.94 | bwd_inner_microstep: 272.92 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.22 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 02:37:51,143] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.83 | bwd_microstep: 272.79 | bwd_inner_microstep: 272.77 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 02:37:51,625] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.10 | bwd_microstep: 272.57 | bwd_inner_microstep: 272.55 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 02:37:52,110] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.55 | bwd_microstep: 272.77 | bwd_inner_microstep: 272.76 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 02:37:52,593] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.39 | bwd_microstep: 272.46 | bwd_inner_microstep: 272.45 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 02:37:53,074] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.54 | bwd_microstep: 272.00 | bwd_inner_microstep: 271.98 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 02:37:53,556] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.66 | bwd_microstep: 271.26 | bwd_inner_microstep: 271.24 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 02:37:54,146] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.15 | optimizer_step: 16.76 +[2025-05-02 02:37:54,147] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.23 | bwd_microstep: 354.34 | bwd_inner_microstep: 271.77 | bwd_allreduce_microstep: 82.51 | step_microstep: 24.78 +[2025-05-02 02:37:54,148] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2881.44 | bwd: 4251.73 | bwd_inner: 4168.57 | bwd_allreduce: 82.76 | step: 26.23 + 20%|██ | 1777/8720 [4:22:27<13:49:22, 7.17s/it] {'loss': 0.446, 'grad_norm': 17.622499465942383, 'learning_rate': 9.22902721095825e-06, 'epoch': 2.04} + 20%|██ | 1777/8720 [4:22:27<13:49:22, 7.17s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 02:37:54,631] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.52 | bwd_microstep: 270.33 | bwd_inner_microstep: 270.31 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 02:37:55,113] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.09 | bwd_microstep: 273.39 | bwd_inner_microstep: 273.37 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2116 +[2025-05-02 02:37:55,649] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 203.44 | bwd_microstep: 312.74 | bwd_inner_microstep: 312.73 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1979 +[2025-05-02 02:37:56,160] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 199.38 | bwd_microstep: 292.11 | bwd_inner_microstep: 292.09 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1941 +[2025-05-02 02:37:56,662] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.56 | bwd_microstep: 289.06 | bwd_inner_microstep: 289.05 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-02 02:37:57,145] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.13 | bwd_microstep: 274.40 | bwd_inner_microstep: 274.38 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-02 02:37:57,626] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.81 | bwd_microstep: 273.83 | bwd_inner_microstep: 273.81 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-02 02:37:58,110] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.67 | bwd_microstep: 274.59 | bwd_inner_microstep: 274.57 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.21 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1353 +[2025-05-02 02:37:58,474] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.61 | bwd_microstep: 206.18 | bwd_inner_microstep: 206.01 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 02:37:58,951] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.04 | bwd_microstep: 272.66 | bwd_inner_microstep: 272.64 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 02:37:59,428] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.42 | bwd_microstep: 272.36 | bwd_inner_microstep: 272.34 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 837 +[2025-05-02 02:37:59,664] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.07 | bwd_microstep: 126.26 | bwd_inner_microstep: 125.99 | bwd_allreduce_microstep: 0.14 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 02:38:00,141] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.26 | bwd_microstep: 272.35 | bwd_inner_microstep: 272.32 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 02:38:00,617] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.99 | bwd_microstep: 271.26 | bwd_inner_microstep: 271.24 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 02:38:01,095] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.92 | bwd_microstep: 270.92 | bwd_inner_microstep: 270.91 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 02:38:01,684] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.13 | optimizer_step: 16.80 +[2025-05-02 02:38:01,685] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.42 | bwd_microstep: 356.66 | bwd_inner_microstep: 271.49 | bwd_allreduce_microstep: 85.12 | step_microstep: 24.74 +[2025-05-02 02:38:01,686] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2905.00 | bwd: 4309.17 | bwd_inner: 4223.26 | bwd_allreduce: 85.42 | step: 26.04 + 20%|██ | 1778/8720 [4:22:35<14:02:07, 7.28s/it] {'loss': 0.5593, 'grad_norm': 8.823213577270508, 'learning_rate': 9.228036133668322e-06, 'epoch': 2.04} + 20%|██ | 1778/8720 [4:22:35<14:02:07, 7.28s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 02:38:02,169] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.91 | bwd_microstep: 270.53 | bwd_inner_microstep: 270.52 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 02:38:02,647] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.50 | bwd_microstep: 271.30 | bwd_inner_microstep: 271.29 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 362 +[2025-05-02 02:38:02,873] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 86.81 | bwd_microstep: 119.12 | bwd_inner_microstep: 118.86 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1893 +[2025-05-02 02:38:03,355] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.89 | bwd_microstep: 275.30 | bwd_inner_microstep: 275.28 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.24 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 351 +[2025-05-02 02:38:03,559] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 68.73 | bwd_microstep: 120.65 | bwd_inner_microstep: 120.51 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-02 02:38:04,039] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.96 | bwd_microstep: 274.69 | bwd_inner_microstep: 274.67 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.22 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-02 02:38:04,521] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.48 | bwd_microstep: 273.51 | bwd_inner_microstep: 273.49 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.21 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 02:38:05,003] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.59 | bwd_microstep: 273.42 | bwd_inner_microstep: 273.40 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 02:38:05,486] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.48 | bwd_microstep: 273.37 | bwd_inner_microstep: 273.36 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 02:38:05,967] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.44 | bwd_microstep: 272.98 | bwd_inner_microstep: 272.96 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 02:38:06,450] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.90 | bwd_microstep: 273.00 | bwd_inner_microstep: 272.99 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 02:38:06,934] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.62 | bwd_microstep: 272.82 | bwd_inner_microstep: 272.80 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 02:38:07,420] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.34 | bwd_microstep: 272.53 | bwd_inner_microstep: 272.51 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 02:38:07,904] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.91 | bwd_microstep: 272.31 | bwd_inner_microstep: 272.29 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 02:38:08,385] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.39 | bwd_microstep: 271.11 | bwd_inner_microstep: 271.09 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 02:38:08,970] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.11 | optimizer_step: 16.64 +[2025-05-02 02:38:08,971] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.74 | bwd_microstep: 354.59 | bwd_inner_microstep: 271.80 | bwd_allreduce_microstep: 82.75 | step_microstep: 24.36 +[2025-05-02 02:38:08,972] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2800.32 | bwd: 4141.29 | bwd_inner: 4057.91 | bwd_allreduce: 82.96 | step: 26.06 + 20%|██ | 1779/8720 [4:22:42<14:02:13, 7.28s/it] {'loss': 0.3828, 'grad_norm': 7.418478965759277, 'learning_rate': 9.227044473063492e-06, 'epoch': 2.04} + 20%|██ | 1779/8720 [4:22:42<14:02:13, 7.28s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1850 +[2025-05-02 02:38:09,456] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.23 | bwd_microstep: 270.14 | bwd_inner_microstep: 270.13 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 365 +[2025-05-02 02:38:09,686] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.45 | bwd_microstep: 117.28 | bwd_inner_microstep: 117.11 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1991 +[2025-05-02 02:38:10,197] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 199.61 | bwd_microstep: 294.03 | bwd_inner_microstep: 294.01 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1974 +[2025-05-02 02:38:10,707] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 197.19 | bwd_microstep: 291.32 | bwd_inner_microstep: 291.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1913 +[2025-05-02 02:38:11,191] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.25 | bwd_microstep: 275.98 | bwd_inner_microstep: 275.96 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1893 +[2025-05-02 02:38:11,676] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.88 | bwd_microstep: 275.09 | bwd_inner_microstep: 275.07 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1890 +[2025-05-02 02:38:12,159] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.53 | bwd_microstep: 274.74 | bwd_inner_microstep: 274.73 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1886 +[2025-05-02 02:38:12,645] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.73 | bwd_microstep: 274.69 | bwd_inner_microstep: 274.67 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.13 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 02:38:13,129] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.24 | bwd_microstep: 273.12 | bwd_inner_microstep: 273.11 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.21 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 02:38:13,611] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.95 | bwd_microstep: 272.74 | bwd_inner_microstep: 272.72 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.13 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 322 +[2025-05-02 02:38:13,835] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 85.91 | bwd_microstep: 119.94 | bwd_inner_microstep: 119.76 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.13 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 02:38:14,318] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.00 | bwd_microstep: 273.21 | bwd_inner_microstep: 273.20 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 834 +[2025-05-02 02:38:14,559] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.32 | bwd_microstep: 128.09 | bwd_inner_microstep: 127.90 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 02:38:15,039] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.62 | bwd_microstep: 272.76 | bwd_inner_microstep: 272.74 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 02:38:15,519] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.60 | bwd_microstep: 272.65 | bwd_inner_microstep: 272.63 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 02:38:16,102] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.12 | optimizer_step: 16.73 +[2025-05-02 02:38:16,102] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.82 | bwd_microstep: 350.79 | bwd_inner_microstep: 272.75 | bwd_allreduce_microstep: 77.99 | step_microstep: 24.61 +[2025-05-02 02:38:16,104] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2749.96 | bwd: 4036.67 | bwd_inner: 3957.93 | bwd_allreduce: 78.26 | step: 25.97 + 20%|██ | 1780/8720 [4:22:49<13:56:58, 7.24s/it] {'loss': 0.8572, 'grad_norm': 6.208500385284424, 'learning_rate': 9.226052229280579e-06, 'epoch': 2.04} + 20%|██ | 1780/8720 [4:22:49<13:56:58, 7.24s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 02:38:16,586] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.19 | bwd_microstep: 270.19 | bwd_inner_microstep: 270.17 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 02:38:17,061] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.29 | bwd_microstep: 271.31 | bwd_inner_microstep: 271.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 358 +[2025-05-02 02:38:17,269] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 77.22 | bwd_microstep: 116.39 | bwd_inner_microstep: 116.24 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1894 +[2025-05-02 02:38:17,748] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.95 | bwd_microstep: 274.72 | bwd_inner_microstep: 274.70 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.13 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1364 +[2025-05-02 02:38:18,113] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.24 | bwd_microstep: 206.88 | bwd_inner_microstep: 206.74 | bwd_allreduce_microstep: 0.10 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-02 02:38:18,592] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.85 | bwd_microstep: 273.36 | bwd_inner_microstep: 273.34 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-02 02:38:19,073] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.06 | bwd_microstep: 273.12 | bwd_inner_microstep: 273.10 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 841 +[2025-05-02 02:38:19,318] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.29 | bwd_microstep: 132.43 | bwd_inner_microstep: 132.20 | bwd_allreduce_microstep: 0.10 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 02:38:19,796] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.37 | bwd_microstep: 272.28 | bwd_inner_microstep: 272.27 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 02:38:20,278] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.75 | bwd_microstep: 273.22 | bwd_inner_microstep: 273.20 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.20 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 325 +[2025-05-02 02:38:20,510] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.04 | bwd_microstep: 120.05 | bwd_inner_microstep: 119.86 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.12 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 321 +[2025-05-02 02:38:20,733] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 85.68 | bwd_microstep: 120.16 | bwd_inner_microstep: 119.98 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 02:38:21,210] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.41 | bwd_microstep: 271.55 | bwd_inner_microstep: 271.53 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 02:38:21,686] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.09 | bwd_microstep: 271.24 | bwd_inner_microstep: 271.22 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 02:38:22,161] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.34 | bwd_microstep: 271.05 | bwd_inner_microstep: 271.04 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 02:38:22,730] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.15 | optimizer_step: 16.97 +[2025-05-02 02:38:22,730] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.93 | bwd_microstep: 339.64 | bwd_inner_microstep: 271.66 | bwd_allreduce_microstep: 67.93 | step_microstep: 24.57 +[2025-05-02 02:38:22,732] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2557.39 | bwd: 3757.69 | bwd_inner: 3688.75 | bwd_allreduce: 68.34 | step: 26.03 + 20%|██ | 1781/8720 [4:22:56<13:35:41, 7.05s/it] {'loss': 0.5707, 'grad_norm': 11.760065078735352, 'learning_rate': 9.225059402456474e-06, 'epoch': 2.04} + 20%|██ | 1781/8720 [4:22:56<13:35:41, 7.05s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2116 +[2025-05-02 02:38:23,270] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 204.04 | bwd_microstep: 312.24 | bwd_inner_microstep: 312.20 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.13 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1911 +[2025-05-02 02:38:23,753] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.33 | bwd_microstep: 276.46 | bwd_inner_microstep: 276.45 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1921 +[2025-05-02 02:38:24,252] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 194.92 | bwd_microstep: 286.92 | bwd_inner_microstep: 286.91 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 348 +[2025-05-02 02:38:24,478] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 79.17 | bwd_microstep: 130.24 | bwd_inner_microstep: 129.96 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.11 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 856 +[2025-05-02 02:38:24,725] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 96.96 | bwd_microstep: 133.83 | bwd_inner_microstep: 133.56 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.16 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 02:38:25,202] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.80 | bwd_microstep: 272.29 | bwd_inner_microstep: 272.27 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 02:38:25,679] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.41 | bwd_microstep: 272.46 | bwd_inner_microstep: 272.45 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 848 +[2025-05-02 02:38:25,924] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.19 | bwd_microstep: 132.80 | bwd_inner_microstep: 132.68 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 02:38:26,401] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.98 | bwd_microstep: 272.84 | bwd_inner_microstep: 272.82 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 02:38:26,879] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.55 | bwd_microstep: 273.01 | bwd_inner_microstep: 272.99 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 839 +[2025-05-02 02:38:27,115] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 92.79 | bwd_microstep: 126.65 | bwd_inner_microstep: 126.41 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 02:38:27,594] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.70 | bwd_microstep: 272.65 | bwd_inner_microstep: 272.63 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 02:38:28,073] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.71 | bwd_microstep: 272.82 | bwd_inner_microstep: 272.80 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 02:38:28,552] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.99 | bwd_microstep: 273.16 | bwd_inner_microstep: 273.14 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 842 +[2025-05-02 02:38:28,794] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.97 | bwd_microstep: 132.59 | bwd_inner_microstep: 132.43 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 02:38:29,365] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.13 | optimizer_step: 16.95 +[2025-05-02 02:38:29,365] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.97 | bwd_microstep: 340.71 | bwd_inner_microstep: 272.69 | bwd_allreduce_microstep: 67.97 | step_microstep: 24.42 +[2025-05-02 02:38:29,366] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2553.19 | bwd: 3781.78 | bwd_inner: 3712.58 | bwd_allreduce: 68.45 | step: 25.67 + 20%|██ | 1782/8720 [4:23:03<13:21:03, 6.93s/it] {'loss': 0.6881, 'grad_norm': 8.291945457458496, 'learning_rate': 9.224065992728148e-06, 'epoch': 2.04} + 20%|██ | 1782/8720 [4:23:03<13:21:03, 6.93s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 322 +[2025-05-02 02:38:29,587] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 68.67 | bwd_microstep: 131.57 | bwd_inner_microstep: 131.27 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1898 +[2025-05-02 02:38:30,067] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.81 | bwd_microstep: 275.01 | bwd_inner_microstep: 274.99 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1905 +[2025-05-02 02:38:30,548] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.36 | bwd_microstep: 275.67 | bwd_inner_microstep: 275.65 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1380 +[2025-05-02 02:38:30,916] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 142.60 | bwd_microstep: 208.11 | bwd_inner_microstep: 208.10 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-02 02:38:31,396] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.01 | bwd_microstep: 274.42 | bwd_inner_microstep: 274.40 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1888 +[2025-05-02 02:38:31,878] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.16 | bwd_microstep: 274.43 | bwd_inner_microstep: 274.41 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-02 02:38:32,360] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.34 | bwd_microstep: 273.96 | bwd_inner_microstep: 273.94 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 02:38:32,840] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.95 | bwd_microstep: 272.82 | bwd_inner_microstep: 272.80 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 837 +[2025-05-02 02:38:33,083] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 96.73 | bwd_microstep: 126.12 | bwd_inner_microstep: 125.86 | bwd_allreduce_microstep: 0.08 | step_microstep: 0.13 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1097 +[2025-05-02 02:38:33,378] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 114.64 | bwd_microstep: 161.52 | bwd_inner_microstep: 161.32 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.13 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1092 +[2025-05-02 02:38:33,673] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 114.79 | bwd_microstep: 160.98 | bwd_inner_microstep: 160.71 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.14 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 02:38:34,154] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.81 | bwd_microstep: 272.58 | bwd_inner_microstep: 272.56 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.25 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 834 +[2025-05-02 02:38:34,394] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.07 | bwd_microstep: 125.80 | bwd_inner_microstep: 125.67 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 02:38:34,875] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.89 | bwd_microstep: 272.88 | bwd_inner_microstep: 272.86 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 02:38:35,357] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.62 | bwd_microstep: 273.08 | bwd_inner_microstep: 273.04 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 02:38:35,940] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.17 | optimizer_step: 17.00 +[2025-05-02 02:38:35,941] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.51 | bwd_microstep: 351.39 | bwd_inner_microstep: 272.66 | bwd_allreduce_microstep: 78.67 | step_microstep: 24.89 +[2025-05-02 02:38:35,942] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2520.62 | bwd: 3730.46 | bwd_inner: 3650.47 | bwd_allreduce: 79.18 | step: 26.39 + 20%|██ | 1783/8720 [4:23:09<13:08:48, 6.82s/it] {'loss': 0.7057, 'grad_norm': 9.280548095703125, 'learning_rate': 9.223072000232661e-06, 'epoch': 2.04} + 20%|██ | 1783/8720 [4:23:09<13:08:48, 6.82s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 02:38:36,425] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.63 | bwd_microstep: 270.49 | bwd_inner_microstep: 270.47 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 02:38:36,899] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.97 | bwd_microstep: 270.83 | bwd_inner_microstep: 270.81 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2140 +[2025-05-02 02:38:37,439] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 206.32 | bwd_microstep: 314.42 | bwd_inner_microstep: 314.40 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-02 02:38:37,919] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.39 | bwd_microstep: 273.98 | bwd_inner_microstep: 273.97 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 02:38:38,398] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.17 | bwd_microstep: 273.34 | bwd_inner_microstep: 273.33 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1352 +[2025-05-02 02:38:38,762] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.87 | bwd_microstep: 205.87 | bwd_inner_microstep: 205.84 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.13 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1354 +[2025-05-02 02:38:39,126] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.36 | bwd_microstep: 206.22 | bwd_inner_microstep: 206.00 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.12 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 843 +[2025-05-02 02:38:39,367] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 92.94 | bwd_microstep: 132.31 | bwd_inner_microstep: 132.14 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.10 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 330 +[2025-05-02 02:38:39,577] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 70.89 | bwd_microstep: 124.21 | bwd_inner_microstep: 123.89 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 02:38:40,053] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.61 | bwd_microstep: 272.42 | bwd_inner_microstep: 272.40 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 02:38:40,531] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.22 | bwd_microstep: 272.71 | bwd_inner_microstep: 272.69 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 02:38:41,008] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.67 | bwd_microstep: 272.30 | bwd_inner_microstep: 272.29 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 02:38:41,483] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.56 | bwd_microstep: 271.27 | bwd_inner_microstep: 271.25 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 02:38:41,959] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.31 | bwd_microstep: 271.16 | bwd_inner_microstep: 271.14 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 02:38:42,435] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.66 | bwd_microstep: 270.95 | bwd_inner_microstep: 270.93 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 02:38:43,003] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.14 | optimizer_step: 16.92 +[2025-05-02 02:38:43,004] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.28 | bwd_microstep: 339.30 | bwd_inner_microstep: 271.73 | bwd_allreduce_microstep: 67.51 | step_microstep: 24.11 +[2025-05-02 02:38:43,005] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2719.60 | bwd: 4041.86 | bwd_inner: 3973.41 | bwd_allreduce: 67.87 | step: 25.28 + 20%|██ | 1784/8720 [4:23:16<13:16:57, 6.89s/it] {'loss': 0.3766, 'grad_norm': 9.319002151489258, 'learning_rate': 9.222077425107144e-06, 'epoch': 2.05} + 20%|██ | 1784/8720 [4:23:16<13:16:57, 6.89s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 02:38:43,485] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.17 | bwd_microstep: 270.37 | bwd_inner_microstep: 270.35 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.14 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1903 +[2025-05-02 02:38:43,967] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.92 | bwd_microstep: 275.77 | bwd_inner_microstep: 275.75 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1947 +[2025-05-02 02:38:44,472] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 197.61 | bwd_microstep: 288.97 | bwd_inner_microstep: 288.96 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1911 +[2025-05-02 02:38:44,956] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.39 | bwd_microstep: 276.54 | bwd_inner_microstep: 276.52 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.17 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-02 02:38:45,436] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.74 | bwd_microstep: 274.24 | bwd_inner_microstep: 274.22 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 02:38:45,917] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.36 | bwd_microstep: 272.64 | bwd_inner_microstep: 272.62 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 02:38:46,397] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.81 | bwd_microstep: 272.90 | bwd_inner_microstep: 272.88 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 02:38:46,878] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.85 | bwd_microstep: 272.60 | bwd_inner_microstep: 272.58 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 02:38:47,360] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.93 | bwd_microstep: 272.66 | bwd_inner_microstep: 272.65 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.14 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 838 +[2025-05-02 02:38:47,604] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 97.45 | bwd_microstep: 125.94 | bwd_inner_microstep: 125.88 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 02:38:48,083] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.91 | bwd_microstep: 272.25 | bwd_inner_microstep: 272.23 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 323 +[2025-05-02 02:38:48,309] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 82.44 | bwd_microstep: 126.21 | bwd_inner_microstep: 125.92 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.15 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 02:38:48,791] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.85 | bwd_microstep: 273.34 | bwd_inner_microstep: 273.32 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 322 +[2025-05-02 02:38:49,020] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 87.43 | bwd_microstep: 123.41 | bwd_inner_microstep: 123.24 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.10 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 319 +[2025-05-02 02:38:49,245] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 83.56 | bwd_microstep: 124.15 | bwd_inner_microstep: 123.97 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.13 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 02:38:49,828] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.19 | optimizer_step: 17.02 +[2025-05-02 02:38:49,829] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.07 | bwd_microstep: 351.20 | bwd_inner_microstep: 272.01 | bwd_allreduce_microstep: 79.13 | step_microstep: 25.01 +[2025-05-02 02:38:49,830] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2622.14 | bwd: 3873.28 | bwd_inner: 3793.23 | bwd_allreduce: 79.50 | step: 26.44 + 20%|██ | 1785/8720 [4:23:23<13:14:32, 6.87s/it] {'loss': 0.4379, 'grad_norm': 17.171613693237305, 'learning_rate': 9.221082267488813e-06, 'epoch': 2.05} + 20%|██ | 1785/8720 [4:23:23<13:14:32, 6.87s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 02:38:50,313] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.38 | bwd_microstep: 270.35 | bwd_inner_microstep: 270.34 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 02:38:50,787] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.81 | bwd_microstep: 270.97 | bwd_inner_microstep: 270.95 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1913 +[2025-05-02 02:38:51,271] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.14 | bwd_microstep: 276.64 | bwd_inner_microstep: 276.62 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 346 +[2025-05-02 02:38:51,477] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 68.27 | bwd_microstep: 122.75 | bwd_inner_microstep: 122.62 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-02 02:38:51,954] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.72 | bwd_microstep: 273.50 | bwd_inner_microstep: 273.48 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-02 02:38:52,432] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.87 | bwd_microstep: 273.19 | bwd_inner_microstep: 273.17 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 02:38:52,911] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.85 | bwd_microstep: 272.73 | bwd_inner_microstep: 272.71 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 02:38:53,393] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.82 | bwd_microstep: 273.33 | bwd_inner_microstep: 273.31 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.21 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 02:38:53,875] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.72 | bwd_microstep: 272.39 | bwd_inner_microstep: 272.38 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 02:38:54,358] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.22 | bwd_microstep: 273.19 | bwd_inner_microstep: 273.17 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.13 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 02:38:54,844] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.92 | bwd_microstep: 273.04 | bwd_inner_microstep: 273.02 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 331 +[2025-05-02 02:38:55,073] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 83.95 | bwd_microstep: 127.09 | bwd_inner_microstep: 126.78 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 02:38:55,551] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.78 | bwd_microstep: 272.97 | bwd_inner_microstep: 272.96 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 02:38:56,031] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.45 | bwd_microstep: 272.92 | bwd_inner_microstep: 272.91 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 02:38:56,509] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.48 | bwd_microstep: 272.30 | bwd_inner_microstep: 272.28 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 02:38:57,077] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.07 | optimizer_step: 16.76 +[2025-05-02 02:38:57,078] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.52 | bwd_microstep: 338.53 | bwd_inner_microstep: 271.98 | bwd_allreduce_microstep: 66.51 | step_microstep: 23.78 +[2025-05-02 02:38:57,079] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2790.58 | bwd: 4136.00 | bwd_inner: 4068.77 | bwd_allreduce: 66.75 | step: 24.90 + 20%|██ | 1786/8720 [4:23:30<13:27:18, 6.99s/it] {'loss': 0.4082, 'grad_norm': 15.43290901184082, 'learning_rate': 9.220086527514964e-06, 'epoch': 2.05} + 20%|██ | 1786/8720 [4:23:30<13:27:18, 6.99s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 02:38:57,558] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.58 | bwd_microstep: 270.41 | bwd_inner_microstep: 270.39 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2052 +[2025-05-02 02:38:58,078] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 202.14 | bwd_microstep: 301.04 | bwd_inner_microstep: 301.03 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1948 +[2025-05-02 02:38:58,578] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.09 | bwd_microstep: 288.95 | bwd_inner_microstep: 288.93 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1422 +[2025-05-02 02:38:58,956] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 145.49 | bwd_microstep: 213.41 | bwd_inner_microstep: 213.26 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.15 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1370 +[2025-05-02 02:38:59,326] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.87 | bwd_microstep: 207.20 | bwd_inner_microstep: 207.18 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.12 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1360 +[2025-05-02 02:38:59,696] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.21 | bwd_microstep: 207.13 | bwd_inner_microstep: 206.92 | bwd_allreduce_microstep: 0.08 | step_microstep: 0.14 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 346 +[2025-05-02 02:38:59,926] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 89.79 | bwd_microstep: 120.76 | bwd_inner_microstep: 120.50 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.15 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-02 02:39:00,409] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.38 | bwd_microstep: 273.52 | bwd_inner_microstep: 273.50 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.11 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1368 +[2025-05-02 02:39:00,776] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.18 | bwd_microstep: 207.16 | bwd_inner_microstep: 207.02 | bwd_allreduce_microstep: 0.10 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 02:39:01,258] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.88 | bwd_microstep: 272.40 | bwd_inner_microstep: 272.38 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 852 +[2025-05-02 02:39:01,513] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 101.22 | bwd_microstep: 132.36 | bwd_inner_microstep: 132.25 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.13 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 02:39:01,992] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.53 | bwd_microstep: 272.32 | bwd_inner_microstep: 272.31 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 02:39:02,471] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.62 | bwd_microstep: 272.40 | bwd_inner_microstep: 272.38 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 02:39:02,952] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.19 | bwd_microstep: 272.72 | bwd_inner_microstep: 272.70 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 02:39:03,430] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.73 | bwd_microstep: 271.17 | bwd_inner_microstep: 271.15 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 02:39:04,014] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.12 | optimizer_step: 16.78 +[2025-05-02 02:39:04,015] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.50 | bwd_microstep: 351.39 | bwd_inner_microstep: 271.53 | bwd_allreduce_microstep: 79.81 | step_microstep: 25.01 +[2025-05-02 02:39:04,017] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2660.06 | bwd: 3934.51 | bwd_inner: 3853.52 | bwd_allreduce: 80.34 | step: 26.41 + 20%|██ | 1787/8720 [4:23:37<13:25:36, 6.97s/it] {'loss': 0.6452, 'grad_norm': 5.471256732940674, 'learning_rate': 9.21909020532297e-06, 'epoch': 2.05} + 20%|██ | 1787/8720 [4:23:37<13:25:36, 6.97s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 02:39:04,501] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.17 | bwd_microstep: 271.22 | bwd_inner_microstep: 271.20 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 02:39:04,981] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.47 | bwd_microstep: 271.03 | bwd_inner_microstep: 271.01 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-02 02:39:05,468] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.02 | bwd_microstep: 274.57 | bwd_inner_microstep: 274.56 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.21 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-02 02:39:05,952] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.13 | bwd_microstep: 274.15 | bwd_inner_microstep: 274.13 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-02 02:39:06,436] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.21 | bwd_microstep: 273.54 | bwd_inner_microstep: 273.52 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-02 02:39:06,922] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.19 | bwd_microstep: 273.28 | bwd_inner_microstep: 273.26 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 02:39:07,407] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.80 | bwd_microstep: 273.52 | bwd_inner_microstep: 273.50 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 02:39:07,889] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.77 | bwd_microstep: 272.90 | bwd_inner_microstep: 272.89 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 326 +[2025-05-02 02:39:08,111] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 83.90 | bwd_microstep: 120.37 | bwd_inner_microstep: 120.21 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-02 02:39:08,591] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.08 | bwd_microstep: 273.59 | bwd_inner_microstep: 273.57 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 02:39:09,073] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.51 | bwd_microstep: 272.52 | bwd_inner_microstep: 272.51 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 02:39:09,559] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.03 | bwd_microstep: 272.97 | bwd_inner_microstep: 272.96 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 02:39:10,042] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.88 | bwd_microstep: 272.70 | bwd_inner_microstep: 272.69 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 02:39:10,526] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.61 | bwd_microstep: 272.79 | bwd_inner_microstep: 272.77 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 02:39:11,008] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.87 | bwd_microstep: 272.56 | bwd_inner_microstep: 272.55 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 02:39:11,596] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.10 | optimizer_step: 17.01 +[2025-05-02 02:39:11,597] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.64 | bwd_microstep: 352.66 | bwd_inner_microstep: 271.56 | bwd_allreduce_microstep: 81.04 | step_microstep: 24.97 +[2025-05-02 02:39:11,598] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2914.86 | bwd: 4294.41 | bwd_inner: 4212.92 | bwd_allreduce: 81.18 | step: 26.17 + 21%|██ | 1788/8720 [4:23:45<13:46:37, 7.15s/it] {'loss': 0.8796, 'grad_norm': 17.80327033996582, 'learning_rate': 9.218093301050293e-06, 'epoch': 2.05} + 21%|██ | 1788/8720 [4:23:45<13:46:37, 7.15s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 02:39:12,082] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.09 | bwd_microstep: 270.69 | bwd_inner_microstep: 270.67 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 02:39:12,561] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.06 | bwd_microstep: 271.09 | bwd_inner_microstep: 271.07 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1887 +[2025-05-02 02:39:13,046] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.08 | bwd_microstep: 274.64 | bwd_inner_microstep: 274.63 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 02:39:13,526] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.58 | bwd_microstep: 273.40 | bwd_inner_microstep: 273.38 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 02:39:14,009] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.21 | bwd_microstep: 273.28 | bwd_inner_microstep: 272.96 | bwd_allreduce_microstep: 0.23 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 02:39:14,491] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.11 | bwd_microstep: 272.70 | bwd_inner_microstep: 272.68 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 02:39:14,971] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.48 | bwd_microstep: 273.16 | bwd_inner_microstep: 273.14 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 02:39:15,451] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.60 | bwd_microstep: 272.87 | bwd_inner_microstep: 272.85 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 02:39:15,929] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.93 | bwd_microstep: 272.58 | bwd_inner_microstep: 272.56 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 02:39:16,409] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.78 | bwd_microstep: 272.60 | bwd_inner_microstep: 272.58 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1095 +[2025-05-02 02:39:16,705] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 115.24 | bwd_microstep: 161.29 | bwd_inner_microstep: 161.27 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.12 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 841 +[2025-05-02 02:39:16,950] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.85 | bwd_microstep: 131.83 | bwd_inner_microstep: 131.57 | bwd_allreduce_microstep: 0.14 | step_microstep: 0.22 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 02:39:17,429] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.37 | bwd_microstep: 272.28 | bwd_inner_microstep: 272.26 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1345 +[2025-05-02 02:39:17,796] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.31 | bwd_microstep: 205.83 | bwd_inner_microstep: 205.70 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.12 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 836 +[2025-05-02 02:39:18,036] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 96.79 | bwd_microstep: 125.94 | bwd_inner_microstep: 125.81 | bwd_allreduce_microstep: 0.08 | step_microstep: 0.13 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 02:39:18,620] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.16 | optimizer_step: 16.77 +[2025-05-02 02:39:18,621] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.15 | bwd_microstep: 351.93 | bwd_inner_microstep: 272.10 | bwd_allreduce_microstep: 79.78 | step_microstep: 24.77 +[2025-05-02 02:39:18,622] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2705.27 | bwd: 3976.23 | bwd_inner: 3895.26 | bwd_allreduce: 80.44 | step: 26.07 + 21%|██ | 1789/8720 [4:23:52<13:41:58, 7.12s/it] {'loss': 0.5781, 'grad_norm': 29.471542358398438, 'learning_rate': 9.217095814834465e-06, 'epoch': 2.05} + 21%|██ | 1789/8720 [4:23:52<13:41:58, 7.12s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 02:39:19,105] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.39 | bwd_microstep: 271.02 | bwd_inner_microstep: 271.00 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 02:39:19,584] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.06 | bwd_microstep: 271.59 | bwd_inner_microstep: 271.57 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1936 +[2025-05-02 02:39:20,087] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.90 | bwd_microstep: 288.09 | bwd_inner_microstep: 288.07 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1919 +[2025-05-02 02:39:20,575] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.65 | bwd_microstep: 277.19 | bwd_inner_microstep: 277.18 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 02:39:21,058] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.60 | bwd_microstep: 273.11 | bwd_inner_microstep: 273.09 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 02:39:21,541] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.31 | bwd_microstep: 273.36 | bwd_inner_microstep: 273.34 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 02:39:22,025] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.84 | bwd_microstep: 272.52 | bwd_inner_microstep: 272.51 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 02:39:22,510] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.78 | bwd_microstep: 272.31 | bwd_inner_microstep: 272.29 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 02:39:22,992] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.13 | bwd_microstep: 272.48 | bwd_inner_microstep: 272.47 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 02:39:23,471] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.84 | bwd_microstep: 272.79 | bwd_inner_microstep: 272.78 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 02:39:23,951] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.26 | bwd_microstep: 272.18 | bwd_inner_microstep: 272.17 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 02:39:24,433] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.37 | bwd_microstep: 272.19 | bwd_inner_microstep: 272.17 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 02:39:24,915] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.47 | bwd_microstep: 272.10 | bwd_inner_microstep: 272.08 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 02:39:25,399] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.41 | bwd_microstep: 271.48 | bwd_inner_microstep: 271.46 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 02:39:25,883] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.64 | bwd_microstep: 271.00 | bwd_inner_microstep: 270.98 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 02:39:26,469] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.13 | optimizer_step: 16.79 +[2025-05-02 02:39:26,470] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.36 | bwd_microstep: 351.17 | bwd_inner_microstep: 271.99 | bwd_allreduce_microstep: 79.12 | step_microstep: 24.80 +[2025-05-02 02:39:26,471] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 3020.54 | bwd: 4454.59 | bwd_inner: 4375.15 | bwd_allreduce: 79.20 | step: 25.78 + 21%|██ | 1790/8720 [4:24:00<14:07:14, 7.34s/it] {'loss': 0.2547, 'grad_norm': 4.71461820602417, 'learning_rate': 9.216097746813103e-06, 'epoch': 2.05} + 21%|██ | 1790/8720 [4:24:00<14:07:14, 7.34s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1903 +[2025-05-02 02:39:26,961] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.54 | bwd_microstep: 275.08 | bwd_inner_microstep: 275.07 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-02 02:39:27,443] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.40 | bwd_microstep: 273.69 | bwd_inner_microstep: 273.67 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-02 02:39:27,927] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.47 | bwd_microstep: 274.89 | bwd_inner_microstep: 274.87 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 02:39:28,410] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.40 | bwd_microstep: 273.37 | bwd_inner_microstep: 273.35 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-02 02:39:28,894] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.89 | bwd_microstep: 273.85 | bwd_inner_microstep: 273.84 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 02:39:29,375] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.75 | bwd_microstep: 272.87 | bwd_inner_microstep: 272.85 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 02:39:29,858] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.43 | bwd_microstep: 272.60 | bwd_inner_microstep: 272.58 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 02:39:30,336] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.03 | bwd_microstep: 272.37 | bwd_inner_microstep: 272.35 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 02:39:30,815] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.13 | bwd_microstep: 272.91 | bwd_inner_microstep: 272.89 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 02:39:31,292] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.23 | bwd_microstep: 272.36 | bwd_inner_microstep: 272.33 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 02:39:31,771] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.89 | bwd_microstep: 273.02 | bwd_inner_microstep: 273.00 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 02:39:32,249] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.99 | bwd_microstep: 272.36 | bwd_inner_microstep: 272.34 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.16 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 02:39:32,727] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.67 | bwd_microstep: 272.52 | bwd_inner_microstep: 272.50 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.21 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 02:39:33,206] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.56 | bwd_microstep: 272.66 | bwd_inner_microstep: 272.65 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 02:39:33,685] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.27 | bwd_microstep: 272.20 | bwd_inner_microstep: 272.19 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 02:39:34,269] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.11 | optimizer_step: 16.76 +[2025-05-02 02:39:34,269] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.72 | bwd_microstep: 351.79 | bwd_inner_microstep: 272.78 | bwd_allreduce_microstep: 78.96 | step_microstep: 24.75 +[2025-05-02 02:39:34,271] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 3019.04 | bwd: 4448.55 | bwd_inner: 4369.26 | bwd_allreduce: 79.02 | step: 25.96 + 21%|██ | 1791/8720 [4:24:08<14:23:13, 7.47s/it] {'loss': 0.5466, 'grad_norm': 7.211980819702148, 'learning_rate': 9.215099097123904e-06, 'epoch': 2.05} + 21%|██ | 1791/8720 [4:24:08<14:23:13, 7.47s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 02:39:34,756] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.86 | bwd_microstep: 270.94 | bwd_inner_microstep: 270.92 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 02:39:35,235] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.00 | bwd_microstep: 271.67 | bwd_inner_microstep: 271.65 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1983 +[2025-05-02 02:39:35,745] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 200.35 | bwd_microstep: 292.42 | bwd_inner_microstep: 292.40 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1895 +[2025-05-02 02:39:36,226] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.65 | bwd_microstep: 275.10 | bwd_inner_microstep: 275.09 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1893 +[2025-05-02 02:39:36,707] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.81 | bwd_microstep: 274.75 | bwd_inner_microstep: 274.74 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-02 02:39:37,187] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.53 | bwd_microstep: 274.68 | bwd_inner_microstep: 274.66 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1360 +[2025-05-02 02:39:37,556] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.72 | bwd_microstep: 206.49 | bwd_inner_microstep: 206.42 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.13 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 02:39:38,037] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.53 | bwd_microstep: 272.80 | bwd_inner_microstep: 272.79 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 02:39:38,516] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.56 | bwd_microstep: 272.29 | bwd_inner_microstep: 272.27 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-02 02:39:38,999] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.18 | bwd_microstep: 273.24 | bwd_inner_microstep: 273.22 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 02:39:39,479] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.72 | bwd_microstep: 272.21 | bwd_inner_microstep: 272.19 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 833 +[2025-05-02 02:39:39,726] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 99.61 | bwd_microstep: 125.71 | bwd_inner_microstep: 125.59 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 02:39:40,206] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.85 | bwd_microstep: 272.50 | bwd_inner_microstep: 272.48 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 318 +[2025-05-02 02:39:40,449] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 92.77 | bwd_microstep: 130.03 | bwd_inner_microstep: 129.78 | bwd_allreduce_microstep: 0.10 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 02:39:40,930] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.82 | bwd_microstep: 272.58 | bwd_inner_microstep: 272.56 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 02:39:41,520] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.19 | optimizer_step: 16.95 +[2025-05-02 02:39:41,521] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.21 | bwd_microstep: 357.14 | bwd_inner_microstep: 271.81 | bwd_allreduce_microstep: 85.26 | step_microstep: 24.99 +[2025-05-02 02:39:41,522] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2798.79 | bwd: 4114.63 | bwd_inner: 4028.63 | bwd_allreduce: 85.47 | step: 26.05 + 21%|██ | 1792/8720 [4:24:15<14:15:21, 7.41s/it] {'loss': 0.6396, 'grad_norm': 13.575328826904297, 'learning_rate': 9.21409986590465e-06, 'epoch': 2.05} + 21%|██ | 1792/8720 [4:24:15<14:15:21, 7.41s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 02:39:42,005] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.61 | bwd_microstep: 270.36 | bwd_inner_microstep: 270.35 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1909 +[2025-05-02 02:39:42,491] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.44 | bwd_microstep: 276.62 | bwd_inner_microstep: 276.60 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 932 +[2025-05-02 02:39:42,764] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 105.78 | bwd_microstep: 146.53 | bwd_inner_microstep: 146.38 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.13 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1911 +[2025-05-02 02:39:43,249] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.06 | bwd_microstep: 276.57 | bwd_inner_microstep: 276.56 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1899 +[2025-05-02 02:39:43,732] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.16 | bwd_microstep: 275.50 | bwd_inner_microstep: 275.48 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1894 +[2025-05-02 02:39:44,216] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.87 | bwd_microstep: 275.03 | bwd_inner_microstep: 275.01 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1887 +[2025-05-02 02:39:44,702] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.46 | bwd_microstep: 274.42 | bwd_inner_microstep: 274.41 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 02:39:45,185] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.32 | bwd_microstep: 273.25 | bwd_inner_microstep: 273.24 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-02 02:39:45,668] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.73 | bwd_microstep: 273.80 | bwd_inner_microstep: 273.79 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 02:39:46,149] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.80 | bwd_microstep: 273.12 | bwd_inner_microstep: 273.10 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.13 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1356 +[2025-05-02 02:39:46,516] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.56 | bwd_microstep: 206.23 | bwd_inner_microstep: 206.16 | bwd_allreduce_microstep: 0.03 | step_microstep: 0.14 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 02:39:46,996] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.61 | bwd_microstep: 272.55 | bwd_inner_microstep: 272.53 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 319 +[2025-05-02 02:39:47,228] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.62 | bwd_microstep: 119.28 | bwd_inner_microstep: 119.12 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 02:39:47,705] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.57 | bwd_microstep: 271.33 | bwd_inner_microstep: 271.31 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 02:39:48,184] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.02 | bwd_microstep: 270.96 | bwd_inner_microstep: 270.94 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.14 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 02:39:48,780] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.07 | optimizer_gradients: 2.16 | optimizer_step: 16.98 +[2025-05-02 02:39:48,780] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.12 | bwd_microstep: 359.79 | bwd_inner_microstep: 271.67 | bwd_allreduce_microstep: 88.05 | step_microstep: 25.02 +[2025-05-02 02:39:48,782] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2794.34 | bwd: 4115.43 | bwd_inner: 4026.69 | bwd_allreduce: 88.28 | step: 26.47 + 21%|██ | 1793/8720 [4:24:22<14:10:05, 7.36s/it] {'loss': 0.666, 'grad_norm': 7.005762577056885, 'learning_rate': 9.213100053293189e-06, 'epoch': 2.06} + 21%|██ | 1793/8720 [4:24:22<14:10:05, 7.36s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 02:39:49,266] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.87 | bwd_microstep: 270.90 | bwd_inner_microstep: 270.89 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 354 +[2025-05-02 02:39:49,490] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 80.21 | bwd_microstep: 126.85 | bwd_inner_microstep: 126.69 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.11 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 434 +[2025-05-02 02:39:49,721] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 91.95 | bwd_microstep: 122.00 | bwd_inner_microstep: 121.67 | bwd_allreduce_microstep: 0.14 | step_microstep: 0.22 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1922 +[2025-05-02 02:39:50,224] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 194.89 | bwd_microstep: 287.64 | bwd_inner_microstep: 287.62 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1377 +[2025-05-02 02:39:50,594] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.60 | bwd_microstep: 207.84 | bwd_inner_microstep: 207.70 | bwd_allreduce_microstep: 0.08 | step_microstep: 0.13 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 337 +[2025-05-02 02:39:50,818] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 83.49 | bwd_microstep: 123.45 | bwd_inner_microstep: 123.29 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-02 02:39:51,298] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.70 | bwd_microstep: 273.84 | bwd_inner_microstep: 273.83 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 02:39:51,780] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.76 | bwd_microstep: 273.73 | bwd_inner_microstep: 273.71 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-02 02:39:52,260] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.16 | bwd_microstep: 272.81 | bwd_inner_microstep: 272.79 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 330 +[2025-05-02 02:39:52,484] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 82.06 | bwd_microstep: 124.90 | bwd_inner_microstep: 124.56 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-02 02:39:52,966] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.45 | bwd_microstep: 273.48 | bwd_inner_microstep: 273.47 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 844 +[2025-05-02 02:39:53,212] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.59 | bwd_microstep: 132.63 | bwd_inner_microstep: 132.33 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 02:39:53,691] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.66 | bwd_microstep: 272.39 | bwd_inner_microstep: 272.37 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.14 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 02:39:54,174] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.74 | bwd_microstep: 272.71 | bwd_inner_microstep: 272.69 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 02:39:54,657] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.91 | bwd_microstep: 271.07 | bwd_inner_microstep: 271.05 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 02:39:55,247] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.13 | optimizer_step: 17.06 +[2025-05-02 02:39:55,247] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.72 | bwd_microstep: 354.26 | bwd_inner_microstep: 271.44 | bwd_allreduce_microstep: 82.76 | step_microstep: 25.23 +[2025-05-02 02:39:55,249] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2465.39 | bwd: 3660.64 | bwd_inner: 3576.33 | bwd_allreduce: 83.42 | step: 26.72 + 21%|██ | 1794/8720 [4:24:28<13:38:55, 7.09s/it] {'loss': 0.5701, 'grad_norm': 14.958683967590332, 'learning_rate': 9.212099659427467e-06, 'epoch': 2.06} + 21%|██ | 1794/8720 [4:24:29<13:38:55, 7.09s/it]dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1342 +[2025-05-02 02:39:55,620] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 142.39 | bwd_microstep: 203.99 | bwd_inner_microstep: 203.69 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1897 +[2025-05-02 02:39:56,103] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.53 | bwd_microstep: 275.31 | bwd_inner_microstep: 275.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1984 +[2025-05-02 02:39:56,616] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 199.54 | bwd_microstep: 291.76 | bwd_inner_microstep: 291.74 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1902 +[2025-05-02 02:39:57,104] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.97 | bwd_microstep: 275.38 | bwd_inner_microstep: 275.37 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1892 +[2025-05-02 02:39:57,589] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.52 | bwd_microstep: 274.70 | bwd_inner_microstep: 274.68 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-02 02:39:58,073] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.61 | bwd_microstep: 273.91 | bwd_inner_microstep: 273.89 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-02 02:39:58,554] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.72 | bwd_microstep: 273.38 | bwd_inner_microstep: 273.36 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-02 02:39:59,036] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.79 | bwd_microstep: 272.80 | bwd_inner_microstep: 272.78 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 02:39:59,517] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.81 | bwd_microstep: 272.89 | bwd_inner_microstep: 272.87 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 02:39:59,997] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.44 | bwd_microstep: 272.08 | bwd_inner_microstep: 272.07 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 02:40:00,481] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.51 | bwd_microstep: 272.52 | bwd_inner_microstep: 272.51 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 02:40:00,964] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.38 | bwd_microstep: 272.44 | bwd_inner_microstep: 272.42 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 02:40:01,444] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.37 | bwd_microstep: 272.50 | bwd_inner_microstep: 272.49 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.14 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 02:40:01,926] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.41 | bwd_microstep: 272.23 | bwd_inner_microstep: 272.22 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1351 +[2025-05-02 02:40:02,292] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.29 | bwd_microstep: 206.15 | bwd_inner_microstep: 205.94 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.13 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 02:40:02,876] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.18 | optimizer_step: 16.92 +[2025-05-02 02:40:02,877] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.66 | bwd_microstep: 352.79 | bwd_inner_microstep: 272.64 | bwd_allreduce_microstep: 80.10 | step_microstep: 24.87 +[2025-05-02 02:40:02,878] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2931.54 | bwd: 4334.92 | bwd_inner: 4254.01 | bwd_allreduce: 80.40 | step: 26.29 + 21%|██ | 1795/8720 [4:24:36<13:57:20, 7.25s/it] {'loss': 0.6719, 'grad_norm': 34.42676544189453, 'learning_rate': 9.211098684445498e-06, 'epoch': 2.06} + 21%|██ | 1795/8720 [4:24:36<13:57:20, 7.25s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 02:40:03,362] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.28 | bwd_microstep: 270.62 | bwd_inner_microstep: 270.61 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1340 +[2025-05-02 02:40:03,725] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 139.97 | bwd_microstep: 204.12 | bwd_inner_microstep: 204.00 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2013 +[2025-05-02 02:40:04,237] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 199.97 | bwd_microstep: 295.77 | bwd_inner_microstep: 295.75 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.07 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1997 +[2025-05-02 02:40:04,746] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 196.85 | bwd_microstep: 294.53 | bwd_inner_microstep: 294.51 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 411 +[2025-05-02 02:40:04,970] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 71.89 | bwd_microstep: 137.08 | bwd_inner_microstep: 136.91 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.15 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-02 02:40:05,451] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.31 | bwd_microstep: 273.78 | bwd_inner_microstep: 273.77 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-02 02:40:05,931] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.96 | bwd_microstep: 273.50 | bwd_inner_microstep: 273.48 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-02 02:40:06,411] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.28 | bwd_microstep: 273.09 | bwd_inner_microstep: 273.08 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-02 02:40:06,892] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.84 | bwd_microstep: 272.81 | bwd_inner_microstep: 272.79 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 327 +[2025-05-02 02:40:07,157] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 96.31 | bwd_microstep: 148.59 | bwd_inner_microstep: 148.25 | bwd_allreduce_microstep: 0.17 | step_microstep: 0.11 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1093 +[2025-05-02 02:40:07,451] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 114.39 | bwd_microstep: 161.33 | bwd_inner_microstep: 161.19 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.14 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-02 02:40:07,931] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.93 | bwd_microstep: 272.54 | bwd_inner_microstep: 272.52 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.12 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 837 +[2025-05-02 02:40:08,174] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 98.71 | bwd_microstep: 126.26 | bwd_inner_microstep: 125.98 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 02:40:08,654] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.74 | bwd_microstep: 273.12 | bwd_inner_microstep: 273.11 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 02:40:09,134] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.20 | bwd_microstep: 272.25 | bwd_inner_microstep: 272.23 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.15 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 02:40:09,721] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.29 | optimizer_step: 17.20 +[2025-05-02 02:40:09,722] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.50 | bwd_microstep: 353.69 | bwd_inner_microstep: 271.48 | bwd_allreduce_microstep: 82.14 | step_microstep: 25.36 +[2025-05-02 02:40:09,723] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2611.80 | bwd: 3903.17 | bwd_inner: 3819.82 | bwd_allreduce: 82.63 | step: 26.88 + 21%|██ | 1796/8720 [4:24:43<13:43:01, 7.13s/it] {'loss': 0.6908, 'grad_norm': 6.589293003082275, 'learning_rate': 9.210097128485383e-06, 'epoch': 2.06} + 21%|██ | 1796/8720 [4:24:43<13:43:01, 7.13s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 02:40:10,206] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.80 | bwd_microstep: 270.64 | bwd_inner_microstep: 270.63 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.14 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 02:40:10,687] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.22 | bwd_microstep: 271.31 | bwd_inner_microstep: 271.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-02 02:40:11,171] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.23 | bwd_microstep: 273.59 | bwd_inner_microstep: 273.58 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.14 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-02 02:40:11,651] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.97 | bwd_microstep: 272.81 | bwd_inner_microstep: 272.80 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.13 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 02:40:12,136] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.35 | bwd_microstep: 274.06 | bwd_inner_microstep: 274.04 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 847 +[2025-05-02 02:40:12,393] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 99.56 | bwd_microstep: 132.85 | bwd_inner_microstep: 132.62 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.11 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1101 +[2025-05-02 02:40:12,690] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 117.32 | bwd_microstep: 161.58 | bwd_inner_microstep: 161.34 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.15 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 02:40:13,170] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.56 | bwd_microstep: 272.72 | bwd_inner_microstep: 272.70 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-02 02:40:13,650] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.69 | bwd_microstep: 271.92 | bwd_inner_microstep: 271.90 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 02:40:14,133] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.61 | bwd_microstep: 272.32 | bwd_inner_microstep: 272.31 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 02:40:14,618] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.05 | bwd_microstep: 271.96 | bwd_inner_microstep: 271.94 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 832 +[2025-05-02 02:40:14,874] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 99.17 | bwd_microstep: 132.85 | bwd_inner_microstep: 132.71 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 02:40:15,350] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.78 | bwd_microstep: 270.80 | bwd_inner_microstep: 270.78 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.13 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 02:40:15,832] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.45 | bwd_microstep: 271.28 | bwd_inner_microstep: 271.26 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 02:40:16,309] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.38 | bwd_microstep: 270.87 | bwd_inner_microstep: 270.86 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-02 02:40:16,891] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.16 | optimizer_step: 16.83 +[2025-05-02 02:40:16,891] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.47 | bwd_microstep: 349.48 | bwd_inner_microstep: 271.29 | bwd_allreduce_microstep: 78.11 | step_microstep: 25.16 +[2025-05-02 02:40:16,893] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2758.19 | bwd: 4041.13 | bwd_inner: 3962.15 | bwd_allreduce: 78.45 | step: 26.77 + 21%|██ | 1797/8720 [4:24:50<13:44:12, 7.14s/it] {'loss': 0.3998, 'grad_norm': 6.867987155914307, 'learning_rate': 9.209094991685297e-06, 'epoch': 2.06} + 21%|██ | 1797/8720 [4:24:50<13:44:12, 7.14s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 02:40:17,376] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.15 | bwd_microstep: 270.51 | bwd_inner_microstep: 270.50 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 02:40:17,854] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.94 | bwd_microstep: 272.82 | bwd_inner_microstep: 272.80 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2101 +[2025-05-02 02:40:18,381] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 203.89 | bwd_microstep: 306.28 | bwd_inner_microstep: 306.16 | bwd_allreduce_microstep: 0.03 | step_microstep: 0.21 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1905 +[2025-05-02 02:40:18,865] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.89 | bwd_microstep: 276.28 | bwd_inner_microstep: 276.26 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1886 +[2025-05-02 02:40:19,346] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.57 | bwd_microstep: 274.50 | bwd_inner_microstep: 274.48 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 02:40:19,824] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.99 | bwd_microstep: 273.19 | bwd_inner_microstep: 273.17 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 02:40:20,304] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.38 | bwd_microstep: 273.63 | bwd_inner_microstep: 273.61 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1353 +[2025-05-02 02:40:20,671] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.52 | bwd_microstep: 206.20 | bwd_inner_microstep: 206.09 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.13 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1348 +[2025-05-02 02:40:21,037] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 142.40 | bwd_microstep: 205.74 | bwd_inner_microstep: 205.72 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 02:40:21,519] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.58 | bwd_microstep: 272.49 | bwd_inner_microstep: 272.47 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 02:40:21,997] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.36 | bwd_microstep: 271.17 | bwd_inner_microstep: 271.15 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 321 +[2025-05-02 02:40:22,228] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 85.23 | bwd_microstep: 128.54 | bwd_inner_microstep: 128.36 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-02 02:40:22,706] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.18 | bwd_microstep: 271.05 | bwd_inner_microstep: 271.03 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 02:40:23,188] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.83 | bwd_microstep: 271.27 | bwd_inner_microstep: 271.26 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 02:40:23,665] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.35 | bwd_microstep: 270.81 | bwd_inner_microstep: 270.79 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 02:40:24,251] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.09 | optimizer_step: 16.78 +[2025-05-02 02:40:24,252] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.59 | bwd_microstep: 352.73 | bwd_inner_microstep: 271.25 | bwd_allreduce_microstep: 81.43 | step_microstep: 24.66 +[2025-05-02 02:40:24,253] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2834.53 | bwd: 4197.31 | bwd_inner: 4115.16 | bwd_allreduce: 81.72 | step: 25.91 + 21%|██ | 1798/8720 [4:24:58<13:51:36, 7.21s/it] {'loss': 0.2924, 'grad_norm': 8.769898414611816, 'learning_rate': 9.208092274183498e-06, 'epoch': 2.06} + 21%|██ | 1798/8720 [4:24:58<13:51:36, 7.21s/it]dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 866 +[2025-05-02 02:40:24,506] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.77 | bwd_microstep: 134.29 | bwd_inner_microstep: 134.13 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.11 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1365 +[2025-05-02 02:40:24,872] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.06 | bwd_microstep: 207.28 | bwd_inner_microstep: 207.22 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.10 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 634 +[2025-05-02 02:40:25,102] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.82 | bwd_microstep: 120.29 | bwd_inner_microstep: 120.13 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.11 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 888 +[2025-05-02 02:40:25,353] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 97.44 | bwd_microstep: 136.10 | bwd_inner_microstep: 136.02 | bwd_allreduce_microstep: 0.03 | step_microstep: 0.10 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1393 +[2025-05-02 02:40:25,722] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 142.83 | bwd_microstep: 209.38 | bwd_inner_microstep: 209.33 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.13 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-02 02:40:26,201] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.62 | bwd_microstep: 273.61 | bwd_inner_microstep: 273.59 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 852 +[2025-05-02 02:40:26,444] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.66 | bwd_microstep: 132.84 | bwd_inner_microstep: 132.60 | bwd_allreduce_microstep: 0.09 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-02 02:40:26,925] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.85 | bwd_microstep: 275.20 | bwd_inner_microstep: 275.18 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-02 02:40:27,406] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.92 | bwd_microstep: 273.26 | bwd_inner_microstep: 273.20 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.22 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-02 02:40:27,885] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.22 | bwd_microstep: 272.81 | bwd_inner_microstep: 272.79 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 02:40:28,362] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.85 | bwd_microstep: 272.27 | bwd_inner_microstep: 272.25 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 321 +[2025-05-02 02:40:28,577] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 81.53 | bwd_microstep: 118.39 | bwd_inner_microstep: 118.10 | bwd_allreduce_microstep: 0.14 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-02 02:40:29,053] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.72 | bwd_microstep: 271.38 | bwd_inner_microstep: 271.36 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-02 02:40:29,533] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.09 | bwd_microstep: 272.57 | bwd_inner_microstep: 272.56 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.13 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 835 +[2025-05-02 02:40:29,777] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 97.44 | bwd_microstep: 126.10 | bwd_inner_microstep: 125.81 | bwd_allreduce_microstep: 0.14 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-02 02:40:30,362] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.13 | optimizer_step: 16.78 +[2025-05-02 02:40:30,362] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.46 | bwd_microstep: 352.89 | bwd_inner_microstep: 272.35 | bwd_allreduce_microstep: 80.48 | step_microstep: 24.79 +[2025-05-02 02:40:30,364] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2350.95 | bwd: 3448.82 | bwd_inner: 3366.87 | bwd_allreduce: 81.06 | step: 26.30 + 21%|██ | 1799/8720 [4:25:04<13:13:29, 6.88s/it] {'loss': 0.4647, 'grad_norm': 4.391622066497803, 'learning_rate': 9.207088976118328e-06, 'epoch': 2.06} + 21%|██ | 1799/8720 [4:25:04<13:13:29, 6.88s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 02:40:30,847] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.46 | bwd_microstep: 270.70 | bwd_inner_microstep: 270.68 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1851 +[2025-05-02 02:40:31,326] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.29 | bwd_microstep: 270.79 | bwd_inner_microstep: 270.77 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 345 +[2025-05-02 02:40:31,584] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 112.35 | bwd_microstep: 123.85 | bwd_inner_microstep: 123.68 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-02 02:40:32,063] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.65 | bwd_microstep: 273.82 | bwd_inner_microstep: 273.80 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 334 +[2025-05-02 02:40:32,277] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 77.77 | bwd_microstep: 119.73 | bwd_inner_microstep: 119.40 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.21 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-02 02:40:32,756] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.73 | bwd_microstep: 273.20 | bwd_inner_microstep: 273.18 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1353 +[2025-05-02 02:40:33,119] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.18 | bwd_microstep: 205.98 | bwd_inner_microstep: 205.92 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.13 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-02 02:40:33,600] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.53 | bwd_microstep: 273.22 | bwd_inner_microstep: 273.21 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 02:40:34,080] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.98 | bwd_microstep: 273.47 | bwd_inner_microstep: 273.44 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-02 02:40:34,560] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.32 | bwd_microstep: 273.58 | bwd_inner_microstep: 273.56 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-02 02:40:35,039] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.74 | bwd_microstep: 272.96 | bwd_inner_microstep: 272.94 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-02 02:40:35,519] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.25 | bwd_microstep: 273.48 | bwd_inner_microstep: 273.46 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-02 02:40:35,997] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.10 | bwd_microstep: 272.58 | bwd_inner_microstep: 272.56 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-02 02:40:36,475] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.66 | bwd_microstep: 272.39 | bwd_inner_microstep: 272.38 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 828 +[2025-05-02 02:40:36,713] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.07 | bwd_microstep: 129.94 | bwd_inner_microstep: 129.79 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-02 02:40:37,280] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.10 | optimizer_step: 16.74 +[2025-05-02 02:40:37,280] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.73 | bwd_microstep: 338.80 | bwd_inner_microstep: 271.76 | bwd_allreduce_microstep: 67.00 | step_microstep: 23.87 +[2025-05-02 02:40:37,281] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2686.51 | bwd: 3918.59 | bwd_inner: 3850.66 | bwd_allreduce: 67.35 | step: 25.03 + 21%|██ | 1800/8720 [4:25:11<13:14:38, 6.89s/it] {'loss': 0.2398, 'grad_norm': 7.123698711395264, 'learning_rate': 9.206085097628203e-06, 'epoch': 2.06} + 21%|██ | 1800/8720 [4:25:11<13:14:38, 6.89s/it][INFO|trainer.py:3503] 2025-05-02 02:40:41,172 >> Saving model checkpoint to work_dirs/internvl_chat_v2_5/ak/checkpoint-1800 +[INFO|configuration_utils.py:472] 2025-05-02 02:40:41,177 >> Configuration saved in work_dirs/internvl_chat_v2_5/ak/checkpoint-1800/config.json +[INFO|configuration_utils.py:807] 2025-05-02 02:40:41,177 >> Configuration saved in work_dirs/internvl_chat_v2_5/ak/checkpoint-1800/generation_config.json +[INFO|modeling_utils.py:2755] 2025-05-02 02:40:46,514 >> Model weights saved in work_dirs/internvl_chat_v2_5/ak/checkpoint-1800/model.safetensors +[INFO|tokenization_utils_base.py:2702] 2025-05-02 02:40:46,516 >> tokenizer config file saved in work_dirs/internvl_chat_v2_5/ak/checkpoint-1800/tokenizer_config.json +[INFO|tokenization_utils_base.py:2711] 2025-05-02 02:40:46,516 >> Special tokens file saved in work_dirs/internvl_chat_v2_5/ak/checkpoint-1800/special_tokens_map.json +[INFO|tokenization_utils_base.py:2762] 2025-05-02 02:40:46,517 >> added tokens file saved in work_dirs/internvl_chat_v2_5/ak/checkpoint-1800/added_tokens.json +[2025-05-02 02:40:46,723] [INFO] [logging.py:96:log_dist] [Rank 0] [Torch] Checkpoint global_step1800 is about to be saved! +[2025-05-02 02:40:46,745] [INFO] [logging.py:96:log_dist] [Rank 0] Saving model checkpoint: work_dirs/internvl_chat_v2_5/ak/checkpoint-1800/global_step1800/mp_rank_00_model_states.pt +[2025-05-02 02:40:46,745] [INFO] [torch_checkpoint_engine.py:21:save] [Torch] Saving work_dirs/internvl_chat_v2_5/ak/checkpoint-1800/global_step1800/mp_rank_00_model_states.pt... +petrel_client is not installed. If you read data locally instead of from ceph, ignore it. +petrel_client is not installed. Using PIL to load images. +petrel_client is not installed. If you read data locally instead of from ceph, ignore it. +petrel_client is not installed. Using PIL to load images. +petrel_client is not installed. If you read data locally instead of from ceph, ignore it. +petrel_client is not installed. Using PIL to load images. +petrel_client is not installed. If you read data locally instead of from ceph, ignore it. +petrel_client is not installed. Using PIL to load images. +Error in atexit._run_exitfuncs: +Traceback (most recent call last): + File "/home1/gmh/anaconda3/envs/promptbench/lib/python3.9/site-packages/deepspeed/ops/transformer/inference/triton/matmul_ext.py", line 101, in put + pickle.dump(table, handle) +OSError: [Errno 28] No space left on device +Error in atexit._run_exitfuncs: +Traceback (most recent call last): + Fi \ No newline at end of file diff --git a/InternVL-main/internvl_chat/work_dirs/internvl_chat_v2_5/mmvet/100/added_tokens.json b/InternVL-main/internvl_chat/work_dirs/internvl_chat_v2_5/mmvet/100/added_tokens.json new file mode 100644 index 0000000000000000000000000000000000000000..35f5893c8e29d6102945a953529819a2d56c62a9 --- /dev/null +++ b/InternVL-main/internvl_chat/work_dirs/internvl_chat_v2_5/mmvet/100/added_tokens.json @@ -0,0 +1,11 @@ +{ + "": 92552, + "": 92545, + "": 92548, + "": 92550, + "": 92546, + "": 92551, + "": 92544, + "": 92547, + "": 92549 +} diff --git a/InternVL-main/internvl_chat/work_dirs/internvl_chat_v2_5/mmvet/100/config.json b/InternVL-main/internvl_chat/work_dirs/internvl_chat_v2_5/mmvet/100/config.json new file mode 100644 index 0000000000000000000000000000000000000000..5cf57c2817b8fdf49abd1d3bd4efc4fea8513978 --- /dev/null +++ b/InternVL-main/internvl_chat/work_dirs/internvl_chat_v2_5/mmvet/100/config.json @@ -0,0 +1,204 @@ +{ + "_commit_hash": null, + "_name_or_path": "/home1/gmh/InternVL-main/internvl_chat/work_dirs/internvl_chat_v2_5/mmvet/checkpoint-100", + "architectures": [ + "InternVLChatModel" + ], + "auto_map": { + "AutoConfig": "configuration_internvl_chat.InternVLChatConfig", + "AutoModel": "modeling_internvl_chat.InternVLChatModel", + "AutoModelForCausalLM": "modeling_internvl_chat.InternVLChatModel" + }, + "downsample_ratio": 0.5, + "dynamic_image_size": true, + "force_image_size": 448, + "hidden_size": 2048, + "llm_config": { + "_name_or_path": "internlm/internlm2_5-1_8b-chat", + "add_cross_attention": false, + "architectures": [ + "InternLM2ForCausalLM" + ], + "attn_implementation": "flash_attention_2", + "auto_map": { + "AutoConfig": "configuration_internlm2.InternLM2Config", + "AutoModel": "modeling_internlm2.InternLM2ForCausalLM", + "AutoModelForCausalLM": "modeling_internlm2.InternLM2ForCausalLM", + "AutoModelForSequenceClassification": "modeling_internlm2.InternLM2ForSequenceClassification" + }, + "bad_words_ids": null, + "begin_suppress_tokens": null, + "bias": false, + "bos_token_id": 1, + "chunk_size_feed_forward": 0, + "cross_attention_hidden_size": null, + "decoder_start_token_id": null, + "diversity_penalty": 0.0, + "do_sample": false, + "early_stopping": false, + "encoder_no_repeat_ngram_size": 0, + "eos_token_id": 2, + "exponential_decay_length_penalty": null, + "finetuning_task": null, + "forced_bos_token_id": null, + "forced_eos_token_id": null, + "hidden_act": "silu", + "hidden_size": 2048, + "id2label": { + "0": "LABEL_0", + "1": "LABEL_1" + }, + "initializer_range": 0.02, + "intermediate_size": 8192, + "is_decoder": false, + "is_encoder_decoder": false, + "label2id": { + "LABEL_0": 0, + "LABEL_1": 1 + }, + "length_penalty": 1.0, + "max_length": 20, + "max_position_embeddings": 32768, + "min_length": 0, + "model_type": "internlm2", + "no_repeat_ngram_size": 0, + "num_attention_heads": 16, + "num_beam_groups": 1, + "num_beams": 1, + "num_hidden_layers": 24, + "num_key_value_heads": 8, + "num_return_sequences": 1, + "output_attentions": false, + "output_hidden_states": false, + "output_scores": false, + "pad_token_id": 2, + "prefix": null, + "pretraining_tp": 1, + "problem_type": null, + "pruned_heads": {}, + "remove_invalid_values": false, + "repetition_penalty": 1.0, + "return_dict": true, + "return_dict_in_generate": false, + "rms_norm_eps": 1e-05, + "rope_scaling": { + "factor": 2.0, + "type": "dynamic" + }, + "rope_theta": 1000000, + "sep_token_id": null, + "suppress_tokens": null, + "task_specific_params": null, + "temperature": 1.0, + "tf_legacy_loss": false, + "tie_encoder_decoder": false, + "tie_word_embeddings": false, + "tokenizer_class": null, + "top_k": 50, + "top_p": 1.0, + "torch_dtype": "bfloat16", + "torchscript": false, + "transformers_version": "4.43.2", + "typical_p": 1.0, + "use_bfloat16": true, + "use_cache": false, + "vocab_size": 92553 + }, + "max_dynamic_patch": 6, + "min_dynamic_patch": 1, + "model_type": "internvl_chat", + "pad2square": false, + "ps_version": "v2", + "select_layer": -1, + "template": "internvl2_5", + "tie_word_embeddings": false, + "torch_dtype": "bfloat16", + "transformers_version": null, + "use_backbone_lora": 0, + "use_llm_lora": 0, + "use_thumbnail": true, + "vision_config": { + "_name_or_path": "", + "add_cross_attention": false, + "architectures": [ + "InternVisionModel" + ], + "attention_dropout": 0.0, + "bad_words_ids": null, + "begin_suppress_tokens": null, + "bos_token_id": null, + "chunk_size_feed_forward": 0, + "cross_attention_hidden_size": null, + "decoder_start_token_id": null, + "diversity_penalty": 0.0, + "do_sample": false, + "drop_path_rate": 0.0, + "dropout": 0.0, + "early_stopping": false, + "encoder_no_repeat_ngram_size": 0, + "eos_token_id": null, + "exponential_decay_length_penalty": null, + "finetuning_task": null, + "forced_bos_token_id": null, + "forced_eos_token_id": null, + "hidden_act": "gelu", + "hidden_size": 1024, + "id2label": { + "0": "LABEL_0", + "1": "LABEL_1" + }, + "image_size": 448, + "initializer_factor": 1.0, + "initializer_range": 0.02, + "intermediate_size": 4096, + "is_decoder": false, + "is_encoder_decoder": false, + "label2id": { + "LABEL_0": 0, + "LABEL_1": 1 + }, + "layer_norm_eps": 1e-06, + "length_penalty": 1.0, + "max_length": 20, + "min_length": 0, + "model_type": "intern_vit_6b", + "no_repeat_ngram_size": 0, + "norm_type": "layer_norm", + "num_attention_heads": 16, + "num_beam_groups": 1, + "num_beams": 1, + "num_channels": 3, + "num_hidden_layers": 24, + "num_return_sequences": 1, + "output_attentions": false, + "output_hidden_states": false, + "output_scores": false, + "pad_token_id": null, + "patch_size": 14, + "prefix": null, + "problem_type": null, + "pruned_heads": {}, + "qk_normalization": false, + "qkv_bias": true, + "remove_invalid_values": false, + "repetition_penalty": 1.0, + "return_dict": true, + "return_dict_in_generate": false, + "sep_token_id": null, + "suppress_tokens": null, + "task_specific_params": null, + "temperature": 1.0, + "tf_legacy_loss": false, + "tie_encoder_decoder": false, + "tie_word_embeddings": true, + "tokenizer_class": null, + "top_k": 50, + "top_p": 1.0, + "torch_dtype": "bfloat16", + "torchscript": false, + "transformers_version": "4.43.2", + "typical_p": 1.0, + "use_bfloat16": true, + "use_flash_attn": true + } +} diff --git a/InternVL-main/internvl_chat/work_dirs/internvl_chat_v2_5/mmvet/100/configuration_intern_vit.py b/InternVL-main/internvl_chat/work_dirs/internvl_chat_v2_5/mmvet/100/configuration_intern_vit.py new file mode 100644 index 0000000000000000000000000000000000000000..7e630c456eb9cf350e55bf850c3ff72f445a7e17 --- /dev/null +++ b/InternVL-main/internvl_chat/work_dirs/internvl_chat_v2_5/mmvet/100/configuration_intern_vit.py @@ -0,0 +1,120 @@ +# -------------------------------------------------------- +# InternVL +# Copyright (c) 2024 OpenGVLab +# Licensed under The MIT License [see LICENSE for details] +# -------------------------------------------------------- + +import os +from typing import Union + +from transformers.configuration_utils import PretrainedConfig +from transformers.utils import logging + +logger = logging.get_logger(__name__) + + +class InternVisionConfig(PretrainedConfig): + r""" + This is the configuration class to store the configuration of a [`InternVisionModel`]. It is used to + instantiate a vision encoder according to the specified arguments, defining the model architecture. + + Configuration objects inherit from [`PretrainedConfig`] and can be used to control the model outputs. Read the + documentation from [`PretrainedConfig`] for more information. + + Args: + num_channels (`int`, *optional*, defaults to 3): + Number of color channels in the input images (e.g., 3 for RGB). + patch_size (`int`, *optional*, defaults to 14): + The size (resolution) of each patch. + image_size (`int`, *optional*, defaults to 224): + The size (resolution) of each image. + qkv_bias (`bool`, *optional*, defaults to `False`): + Whether to add a bias to the queries and values in the self-attention layers. + hidden_size (`int`, *optional*, defaults to 3200): + Dimensionality of the encoder layers and the pooler layer. + num_attention_heads (`int`, *optional*, defaults to 25): + Number of attention heads for each attention layer in the Transformer encoder. + intermediate_size (`int`, *optional*, defaults to 12800): + Dimensionality of the "intermediate" (i.e., feed-forward) layer in the Transformer encoder. + qk_normalization (`bool`, *optional*, defaults to `True`): + Whether to normalize the queries and keys in the self-attention layers. + num_hidden_layers (`int`, *optional*, defaults to 48): + Number of hidden layers in the Transformer encoder. + use_flash_attn (`bool`, *optional*, defaults to `True`): + Whether to use flash attention mechanism. + hidden_act (`str` or `function`, *optional*, defaults to `"gelu"`): + The non-linear activation function (function or string) in the encoder and pooler. If string, `"gelu"`, + `"relu"`, `"selu"` and `"gelu_new"` ``"gelu"` are supported. + layer_norm_eps (`float`, *optional*, defaults to 1e-6): + The epsilon used by the layer normalization layers. + dropout (`float`, *optional*, defaults to 0.0): + The dropout probability for all fully connected layers in the embeddings, encoder, and pooler. + drop_path_rate (`float`, *optional*, defaults to 0.0): + Dropout rate for stochastic depth. + attention_dropout (`float`, *optional*, defaults to 0.0): + The dropout ratio for the attention probabilities. + initializer_range (`float`, *optional*, defaults to 0.02): + The standard deviation of the truncated_normal_initializer for initializing all weight matrices. + initializer_factor (`float`, *optional*, defaults to 0.1): + A factor for layer scale. + """ + + model_type = 'intern_vit_6b' + + def __init__( + self, + num_channels=3, + patch_size=14, + image_size=224, + qkv_bias=False, + hidden_size=3200, + num_attention_heads=25, + intermediate_size=12800, + qk_normalization=True, + num_hidden_layers=48, + use_flash_attn=True, + hidden_act='gelu', + norm_type='rms_norm', + layer_norm_eps=1e-6, + dropout=0.0, + drop_path_rate=0.0, + attention_dropout=0.0, + initializer_range=0.02, + initializer_factor=0.1, + **kwargs, + ): + super().__init__(**kwargs) + + self.hidden_size = hidden_size + self.intermediate_size = intermediate_size + self.dropout = dropout + self.drop_path_rate = drop_path_rate + self.num_hidden_layers = num_hidden_layers + self.num_attention_heads = num_attention_heads + self.num_channels = num_channels + self.patch_size = patch_size + self.image_size = image_size + self.initializer_range = initializer_range + self.initializer_factor = initializer_factor + self.attention_dropout = attention_dropout + self.layer_norm_eps = layer_norm_eps + self.hidden_act = hidden_act + self.norm_type = norm_type + self.qkv_bias = qkv_bias + self.qk_normalization = qk_normalization + self.use_flash_attn = use_flash_attn + + @classmethod + def from_pretrained(cls, pretrained_model_name_or_path: Union[str, os.PathLike], **kwargs) -> 'PretrainedConfig': + config_dict, kwargs = cls.get_config_dict(pretrained_model_name_or_path, **kwargs) + + if 'vision_config' in config_dict: + config_dict = config_dict['vision_config'] + + if 'model_type' in config_dict and hasattr(cls, 'model_type') and config_dict['model_type'] != cls.model_type: + logger.warning( + f"You are using a model of type {config_dict['model_type']} to instantiate a model of type " + f'{cls.model_type}. This is not supported for all configurations of models and can yield errors.' + ) + + return cls.from_dict(config_dict, **kwargs) diff --git a/InternVL-main/internvl_chat/work_dirs/internvl_chat_v2_5/mmvet/100/configuration_internlm2.py b/InternVL-main/internvl_chat/work_dirs/internvl_chat_v2_5/mmvet/100/configuration_internlm2.py new file mode 100644 index 0000000000000000000000000000000000000000..282b13b1e2066ecc074ecae87b35a19d251f0ed7 --- /dev/null +++ b/InternVL-main/internvl_chat/work_dirs/internvl_chat_v2_5/mmvet/100/configuration_internlm2.py @@ -0,0 +1,150 @@ +# Copyright (c) The InternLM team and The HuggingFace Inc. team. All rights reserved. +# +# This code is based on transformers/src/transformers/models/llama/configuration_llama.py +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +""" InternLM2 model configuration""" + +from transformers.configuration_utils import PretrainedConfig +from transformers.utils import logging + +logger = logging.get_logger(__name__) + +INTERNLM2_PRETRAINED_CONFIG_ARCHIVE_MAP = {} + + +# Modified from transformers.model.llama.configuration_llama.LlamaConfig +class InternLM2Config(PretrainedConfig): + r""" + This is the configuration class to store the configuration of a [`InternLM2Model`]. It is used to instantiate + an InternLM2 model according to the specified arguments, defining the model architecture. Instantiating a + configuration with the defaults will yield a similar configuration to that of the InternLM2-7B. + + Configuration objects inherit from [`PretrainedConfig`] and can be used to control the model outputs. Read the + documentation from [`PretrainedConfig`] for more information. + + + Args: + vocab_size (`int`, *optional*, defaults to 32000): + Vocabulary size of the InternLM2 model. Defines the number of different tokens that can be represented by the + `inputs_ids` passed when calling [`InternLM2Model`] + hidden_size (`int`, *optional*, defaults to 4096): + Dimension of the hidden representations. + intermediate_size (`int`, *optional*, defaults to 11008): + Dimension of the MLP representations. + num_hidden_layers (`int`, *optional*, defaults to 32): + Number of hidden layers in the Transformer encoder. + num_attention_heads (`int`, *optional*, defaults to 32): + Number of attention heads for each attention layer in the Transformer encoder. + num_key_value_heads (`int`, *optional*): + This is the number of key_value heads that should be used to implement Grouped Query Attention. If + `num_key_value_heads=num_attention_heads`, the model will use Multi Head Attention (MHA), if + `num_key_value_heads=1 the model will use Multi Query Attention (MQA) otherwise GQA is used. When + converting a multi-head checkpoint to a GQA checkpoint, each group key and value head should be constructed + by meanpooling all the original heads within that group. For more details checkout [this + paper](https://arxiv.org/pdf/2305.13245.pdf). If it is not specified, will default to + `num_attention_heads`. + hidden_act (`str` or `function`, *optional*, defaults to `"silu"`): + The non-linear activation function (function or string) in the decoder. + max_position_embeddings (`int`, *optional*, defaults to 2048): + The maximum sequence length that this model might ever be used with. Typically set this to something large + just in case (e.g., 512 or 1024 or 2048). + initializer_range (`float`, *optional*, defaults to 0.02): + The standard deviation of the truncated_normal_initializer for initializing all weight matrices. + rms_norm_eps (`float`, *optional*, defaults to 1e-12): + The epsilon used by the rms normalization layers. + use_cache (`bool`, *optional*, defaults to `True`): + Whether or not the model should return the last key/values attentions (not used by all models). Only + relevant if `config.is_decoder=True`. + tie_word_embeddings(`bool`, *optional*, defaults to `False`): + Whether to tie weight embeddings + Example: + + """ + model_type = 'internlm2' + _auto_class = 'AutoConfig' + + def __init__( # pylint: disable=W0102 + self, + vocab_size=103168, + hidden_size=4096, + intermediate_size=11008, + num_hidden_layers=32, + num_attention_heads=32, + num_key_value_heads=None, + hidden_act='silu', + max_position_embeddings=2048, + initializer_range=0.02, + rms_norm_eps=1e-6, + use_cache=True, + pad_token_id=0, + bos_token_id=1, + eos_token_id=2, + tie_word_embeddings=False, + bias=True, + rope_theta=10000, + rope_scaling=None, + attn_implementation='eager', + **kwargs, + ): + self.vocab_size = vocab_size + self.max_position_embeddings = max_position_embeddings + self.hidden_size = hidden_size + self.intermediate_size = intermediate_size + self.num_hidden_layers = num_hidden_layers + self.num_attention_heads = num_attention_heads + self.bias = bias + + if num_key_value_heads is None: + num_key_value_heads = num_attention_heads + self.num_key_value_heads = num_key_value_heads + + self.hidden_act = hidden_act + self.initializer_range = initializer_range + self.rms_norm_eps = rms_norm_eps + self.use_cache = use_cache + self.rope_theta = rope_theta + self.rope_scaling = rope_scaling + self._rope_scaling_validation() + + self.attn_implementation = attn_implementation + if self.attn_implementation is None: + self.attn_implementation = 'eager' + super().__init__( + pad_token_id=pad_token_id, + bos_token_id=bos_token_id, + eos_token_id=eos_token_id, + tie_word_embeddings=tie_word_embeddings, + **kwargs, + ) + + def _rope_scaling_validation(self): + """ + Validate the `rope_scaling` configuration. + """ + if self.rope_scaling is None: + return + + if not isinstance(self.rope_scaling, dict) or len(self.rope_scaling) != 2: + raise ValueError( + '`rope_scaling` must be a dictionary with with two fields, `type` and `factor`, ' + f'got {self.rope_scaling}' + ) + rope_scaling_type = self.rope_scaling.get('type', None) + rope_scaling_factor = self.rope_scaling.get('factor', None) + if rope_scaling_type is None or rope_scaling_type not in ['linear', 'dynamic']: + raise ValueError( + f"`rope_scaling`'s type field must be one of ['linear', 'dynamic'], got {rope_scaling_type}" + ) + if rope_scaling_factor is None or not isinstance(rope_scaling_factor, float) or rope_scaling_factor < 1.0: + raise ValueError(f"`rope_scaling`'s factor field must be a float >= 1, got {rope_scaling_factor}") diff --git a/InternVL-main/internvl_chat/work_dirs/internvl_chat_v2_5/mmvet/100/configuration_internvl_chat.py b/InternVL-main/internvl_chat/work_dirs/internvl_chat_v2_5/mmvet/100/configuration_internvl_chat.py new file mode 100644 index 0000000000000000000000000000000000000000..56c628e15a646dfbb2618c90e0577b7037901b6b --- /dev/null +++ b/InternVL-main/internvl_chat/work_dirs/internvl_chat_v2_5/mmvet/100/configuration_internvl_chat.py @@ -0,0 +1,96 @@ +# -------------------------------------------------------- +# InternVL +# Copyright (c) 2024 OpenGVLab +# Licensed under The MIT License [see LICENSE for details] +# -------------------------------------------------------- + +import copy + +from transformers import AutoConfig, LlamaConfig +from transformers.configuration_utils import PretrainedConfig +from transformers.utils import logging + +from .configuration_intern_vit import InternVisionConfig +from .configuration_internlm2 import InternLM2Config + +logger = logging.get_logger(__name__) + + +class InternVLChatConfig(PretrainedConfig): + model_type = 'internvl_chat' + is_composition = True + + def __init__( + self, + vision_config=None, + llm_config=None, + use_backbone_lora=0, + use_llm_lora=0, + select_layer=-1, + force_image_size=None, + downsample_ratio=0.5, + template=None, + dynamic_image_size=False, + use_thumbnail=False, + ps_version='v1', + min_dynamic_patch=1, + max_dynamic_patch=6, + **kwargs): + super().__init__(**kwargs) + + if vision_config is None: + vision_config = {'architectures': ['InternVisionModel']} + logger.info('vision_config is None. Initializing the InternVisionConfig with default values.') + + if llm_config is None: + llm_config = {'architectures': ['InternLM2ForCausalLM']} + logger.info('llm_config is None. Initializing the LlamaConfig config with default values (`LlamaConfig`).') + + self.vision_config = InternVisionConfig(**vision_config) + if llm_config.get('architectures')[0] == 'LlamaForCausalLM': + self.llm_config = LlamaConfig(**llm_config) + elif llm_config.get('architectures')[0] == 'InternLM2ForCausalLM': + self.llm_config = InternLM2Config(**llm_config) + else: + raise ValueError('Unsupported architecture: {}'.format(llm_config.get('architectures')[0])) + self.use_backbone_lora = use_backbone_lora + self.use_llm_lora = use_llm_lora + self.select_layer = select_layer + self.force_image_size = force_image_size + self.downsample_ratio = downsample_ratio + self.template = template + self.dynamic_image_size = dynamic_image_size + self.use_thumbnail = use_thumbnail + self.ps_version = ps_version # pixel shuffle version + self.min_dynamic_patch = min_dynamic_patch + self.max_dynamic_patch = max_dynamic_patch + + logger.info(f'vision_select_layer: {self.select_layer}') + logger.info(f'ps_version: {self.ps_version}') + logger.info(f'min_dynamic_patch: {self.min_dynamic_patch}') + logger.info(f'max_dynamic_patch: {self.max_dynamic_patch}') + + def to_dict(self): + """ + Serializes this instance to a Python dictionary. Override the default [`~PretrainedConfig.to_dict`]. + + Returns: + `Dict[str, any]`: Dictionary of all the attributes that make up this configuration instance, + """ + output = copy.deepcopy(self.__dict__) + output['vision_config'] = self.vision_config.to_dict() + output['llm_config'] = self.llm_config.to_dict() + output['model_type'] = self.__class__.model_type + output['use_backbone_lora'] = self.use_backbone_lora + output['use_llm_lora'] = self.use_llm_lora + output['select_layer'] = self.select_layer + output['force_image_size'] = self.force_image_size + output['downsample_ratio'] = self.downsample_ratio + output['template'] = self.template + output['dynamic_image_size'] = self.dynamic_image_size + output['use_thumbnail'] = self.use_thumbnail + output['ps_version'] = self.ps_version + output['min_dynamic_patch'] = self.min_dynamic_patch + output['max_dynamic_patch'] = self.max_dynamic_patch + + return output diff --git a/InternVL-main/internvl_chat/work_dirs/internvl_chat_v2_5/mmvet/100/conversation.py b/InternVL-main/internvl_chat/work_dirs/internvl_chat_v2_5/mmvet/100/conversation.py new file mode 100644 index 0000000000000000000000000000000000000000..5a771766f21ce3aeeb99b286fb8d188b0038a547 --- /dev/null +++ b/InternVL-main/internvl_chat/work_dirs/internvl_chat_v2_5/mmvet/100/conversation.py @@ -0,0 +1,391 @@ +""" +Conversation prompt templates. + +We kindly request that you import fastchat instead of copying this file if you wish to use it. +If you have changes in mind, please contribute back so the community can benefit collectively and continue to maintain these valuable templates. + +Modified from https://github.com/lm-sys/FastChat/blob/main/fastchat/conversation.py +""" + +import dataclasses +from enum import IntEnum, auto +from typing import Dict, List, Tuple, Union + + +class SeparatorStyle(IntEnum): + """Separator styles.""" + + ADD_COLON_SINGLE = auto() + ADD_COLON_TWO = auto() + ADD_COLON_SPACE_SINGLE = auto() + NO_COLON_SINGLE = auto() + NO_COLON_TWO = auto() + ADD_NEW_LINE_SINGLE = auto() + LLAMA2 = auto() + CHATGLM = auto() + CHATML = auto() + CHATINTERN = auto() + DOLLY = auto() + RWKV = auto() + PHOENIX = auto() + ROBIN = auto() + FALCON_CHAT = auto() + CHATGLM3 = auto() + INTERNVL_ZH = auto() + MPT = auto() + + +@dataclasses.dataclass +class Conversation: + """A class that manages prompt templates and keeps all conversation history.""" + + # The name of this template + name: str + # The template of the system prompt + system_template: str = '{system_message}' + # The system message + system_message: str = '' + # The names of two roles + roles: Tuple[str] = ('USER', 'ASSISTANT') + # All messages. Each item is (role, message). + messages: List[List[str]] = () + # The number of few shot examples + offset: int = 0 + # The separator style and configurations + sep_style: SeparatorStyle = SeparatorStyle.ADD_COLON_SINGLE + sep: str = '\n' + sep2: str = None + # Stop criteria (the default one is EOS token) + stop_str: Union[str, List[str]] = None + # Stops generation if meeting any token in this list + stop_token_ids: List[int] = None + + def get_prompt(self) -> str: + """Get the prompt for generation.""" + system_prompt = self.system_template.format(system_message=self.system_message) + if self.sep_style == SeparatorStyle.ADD_COLON_SINGLE: + ret = system_prompt + self.sep + for role, message in self.messages: + if message: + ret += role + ': ' + message + self.sep + else: + ret += role + ':' + return ret + elif self.sep_style == SeparatorStyle.ADD_COLON_TWO: + seps = [self.sep, self.sep2] + ret = system_prompt + seps[0] + for i, (role, message) in enumerate(self.messages): + if message: + ret += role + ': ' + message + seps[i % 2] + else: + ret += role + ':' + return ret + elif self.sep_style == SeparatorStyle.ADD_COLON_SPACE_SINGLE: + ret = system_prompt + self.sep + for role, message in self.messages: + if message: + ret += role + ': ' + message + self.sep + else: + ret += role + ': ' # must be end with a space + return ret + elif self.sep_style == SeparatorStyle.ADD_NEW_LINE_SINGLE: + ret = '' if system_prompt == '' else system_prompt + self.sep + for role, message in self.messages: + if message: + ret += role + '\n' + message + self.sep + else: + ret += role + '\n' + return ret + elif self.sep_style == SeparatorStyle.NO_COLON_SINGLE: + ret = system_prompt + for role, message in self.messages: + if message: + ret += role + message + self.sep + else: + ret += role + return ret + elif self.sep_style == SeparatorStyle.NO_COLON_TWO: + seps = [self.sep, self.sep2] + ret = system_prompt + for i, (role, message) in enumerate(self.messages): + if message: + ret += role + message + seps[i % 2] + else: + ret += role + return ret + elif self.sep_style == SeparatorStyle.RWKV: + ret = system_prompt + for i, (role, message) in enumerate(self.messages): + if message: + ret += ( + role + + ': ' + + message.replace('\r\n', '\n').replace('\n\n', '\n') + ) + ret += '\n\n' + else: + ret += role + ':' + return ret + elif self.sep_style == SeparatorStyle.LLAMA2: + seps = [self.sep, self.sep2] + if self.system_message: + ret = system_prompt + else: + ret = '[INST] ' + for i, (role, message) in enumerate(self.messages): + tag = self.roles[i % 2] + if message: + if i == 0: + ret += message + ' ' + else: + ret += tag + ' ' + message + seps[i % 2] + else: + ret += tag + return ret + elif self.sep_style == SeparatorStyle.CHATGLM: + # source: https://huggingface.co/THUDM/chatglm-6b/blob/1d240ba371910e9282298d4592532d7f0f3e9f3e/modeling_chatglm.py#L1302-L1308 + # source2: https://huggingface.co/THUDM/chatglm2-6b/blob/e186c891cf64310ac66ef10a87e6635fa6c2a579/modeling_chatglm.py#L926 + round_add_n = 1 if self.name == 'chatglm2' else 0 + if system_prompt: + ret = system_prompt + self.sep + else: + ret = '' + + for i, (role, message) in enumerate(self.messages): + if i % 2 == 0: + ret += f'[Round {i//2 + round_add_n}]{self.sep}' + + if message: + ret += f'{role}：{message}{self.sep}' + else: + ret += f'{role}：' + return ret + elif self.sep_style == SeparatorStyle.CHATML: + ret = '' if system_prompt == '' else system_prompt + self.sep + '\n' + for role, message in self.messages: + if message: + ret += role + '\n' + message + self.sep + '\n' + else: + ret += role + '\n' + return ret + elif self.sep_style == SeparatorStyle.CHATGLM3: + ret = '' + if self.system_message: + ret += system_prompt + for role, message in self.messages: + if message: + ret += role + '\n' + ' ' + message + else: + ret += role + return ret + elif self.sep_style == SeparatorStyle.CHATINTERN: + # source: https://huggingface.co/internlm/internlm-chat-7b-8k/blob/bd546fa984b4b0b86958f56bf37f94aa75ab8831/modeling_internlm.py#L771 + seps = [self.sep, self.sep2] + ret = system_prompt + for i, (role, message) in enumerate(self.messages): + # if i % 2 == 0: + # ret += "" + if message: + ret += role + ':' + message + seps[i % 2] + '\n' + else: + ret += role + ':' + return ret + elif self.sep_style == SeparatorStyle.DOLLY: + seps = [self.sep, self.sep2] + ret = system_prompt + for i, (role, message) in enumerate(self.messages): + if message: + ret += role + ':\n' + message + seps[i % 2] + if i % 2 == 1: + ret += '\n\n' + else: + ret += role + ':\n' + return ret + elif self.sep_style == SeparatorStyle.PHOENIX: + ret = system_prompt + for role, message in self.messages: + if message: + ret += role + ': ' + '' + message + '' + else: + ret += role + ': ' + '' + return ret + elif self.sep_style == SeparatorStyle.ROBIN: + ret = system_prompt + self.sep + for role, message in self.messages: + if message: + ret += role + ':\n' + message + self.sep + else: + ret += role + ':\n' + return ret + elif self.sep_style == SeparatorStyle.FALCON_CHAT: + ret = '' + if self.system_message: + ret += system_prompt + self.sep + for role, message in self.messages: + if message: + ret += role + ': ' + message + self.sep + else: + ret += role + ':' + + return ret + elif self.sep_style == SeparatorStyle.INTERNVL_ZH: + seps = [self.sep, self.sep2] + ret = self.system_message + seps[0] + for i, (role, message) in enumerate(self.messages): + if message: + ret += role + ': ' + message + seps[i % 2] + else: + ret += role + ':' + return ret + elif self.sep_style == SeparatorStyle.MPT: + ret = system_prompt + self.sep + for role, message in self.messages: + if message: + if type(message) is tuple: + message, _, _ = message + ret += role + message + self.sep + else: + ret += role + return ret + else: + raise ValueError(f'Invalid style: {self.sep_style}') + + def set_system_message(self, system_message: str): + """Set the system message.""" + self.system_message = system_message + + def append_message(self, role: str, message: str): + """Append a new message.""" + self.messages.append([role, message]) + + def update_last_message(self, message: str): + """Update the last output. + + The last message is typically set to be None when constructing the prompt, + so we need to update it in-place after getting the response from a model. + """ + self.messages[-1][1] = message + + def to_gradio_chatbot(self): + """Convert the conversation to gradio chatbot format.""" + ret = [] + for i, (role, msg) in enumerate(self.messages[self.offset :]): + if i % 2 == 0: + ret.append([msg, None]) + else: + ret[-1][-1] = msg + return ret + + def to_openai_api_messages(self): + """Convert the conversation to OpenAI chat completion format.""" + ret = [{'role': 'system', 'content': self.system_message}] + + for i, (_, msg) in enumerate(self.messages[self.offset :]): + if i % 2 == 0: + ret.append({'role': 'user', 'content': msg}) + else: + if msg is not None: + ret.append({'role': 'assistant', 'content': msg}) + return ret + + def copy(self): + return Conversation( + name=self.name, + system_template=self.system_template, + system_message=self.system_message, + roles=self.roles, + messages=[[x, y] for x, y in self.messages], + offset=self.offset, + sep_style=self.sep_style, + sep=self.sep, + sep2=self.sep2, + stop_str=self.stop_str, + stop_token_ids=self.stop_token_ids, + ) + + def dict(self): + return { + 'template_name': self.name, + 'system_message': self.system_message, + 'roles': self.roles, + 'messages': self.messages, + 'offset': self.offset, + } + + +# A global registry for all conversation templates +conv_templates: Dict[str, Conversation] = {} + + +def register_conv_template(template: Conversation, override: bool = False): + """Register a new conversation template.""" + if not override: + assert ( + template.name not in conv_templates + ), f'{template.name} has been registered.' + + conv_templates[template.name] = template + + +def get_conv_template(name: str) -> Conversation: + """Get a conversation template.""" + return conv_templates[name].copy() + + +# Both Hermes-2 and internlm2-chat are chatml-format conversation templates. The difference +# is that during training, the preprocessing function for the Hermes-2 template doesn't add +# at the beginning of the tokenized sequence, while the internlm2-chat template does. +# Therefore, they are completely equivalent during inference. +register_conv_template( + Conversation( + name='Hermes-2', + system_template='<|im_start|>system\n{system_message}', + # note: The new system prompt was not used here to avoid changes in benchmark performance. + # system_message='我是书生·万象，英文名是InternVL，是由上海人工智能实验室、清华大学及多家合作单位联合开发的多模态大语言模型。', + system_message='你是由上海人工智能实验室联合商汤科技开发的书生多模态大模型，英文名叫InternVL, 是一个有用无害的人工智能助手。', + roles=('<|im_start|>user\n', '<|im_start|>assistant\n'), + sep_style=SeparatorStyle.MPT, + sep='<|im_end|>', + stop_str='<|endoftext|>', + ) +) + + +register_conv_template( + Conversation( + name='internlm2-chat', + system_template='<|im_start|>system\n{system_message}', + # note: The new system prompt was not used here to avoid changes in benchmark performance. + # system_message='我是书生·万象，英文名是InternVL，是由上海人工智能实验室、清华大学及多家合作单位联合开发的多模态大语言模型。', + system_message='你是由上海人工智能实验室联合商汤科技开发的书生多模态大模型，英文名叫InternVL, 是一个有用无害的人工智能助手。', + roles=('<|im_start|>user\n', '<|im_start|>assistant\n'), + sep_style=SeparatorStyle.MPT, + sep='<|im_end|>', + ) +) + + +register_conv_template( + Conversation( + name='phi3-chat', + system_template='<|system|>\n{system_message}', + # note: The new system prompt was not used here to avoid changes in benchmark performance. + # system_message='我是书生·万象，英文名是InternVL，是由上海人工智能实验室、清华大学及多家合作单位联合开发的多模态大语言模型。', + system_message='你是由上海人工智能实验室联合商汤科技开发的书生多模态大模型，英文名叫InternVL, 是一个有用无害的人工智能助手。', + roles=('<|user|>\n', '<|assistant|>\n'), + sep_style=SeparatorStyle.MPT, + sep='<|end|>', + ) +) + + +register_conv_template( + Conversation( + name='internvl2_5', + system_template='<|im_start|>system\n{system_message}', + system_message='你是书生·万象，英文名是InternVL，是由上海人工智能实验室、清华大学及多家合作单位联合开发的多模态大语言模型。', + roles=('<|im_start|>user\n', '<|im_start|>assistant\n'), + sep_style=SeparatorStyle.MPT, + sep='<|im_end|>\n', + ) +) diff --git a/InternVL-main/internvl_chat/work_dirs/internvl_chat_v2_5/mmvet/100/generation_config.json b/InternVL-main/internvl_chat/work_dirs/internvl_chat_v2_5/mmvet/100/generation_config.json new file mode 100644 index 0000000000000000000000000000000000000000..918fe50c5a6fd362e537376348091b2bc5f51820 --- /dev/null +++ b/InternVL-main/internvl_chat/work_dirs/internvl_chat_v2_5/mmvet/100/generation_config.json @@ -0,0 +1,8 @@ +{ + "_from_model_config": true, + "eos_token_id": [ + 92542, + 92543 + ], + "transformers_version": "4.43.2" +} diff --git a/InternVL-main/internvl_chat/work_dirs/internvl_chat_v2_5/mmvet/100/modeling_intern_vit.py b/InternVL-main/internvl_chat/work_dirs/internvl_chat_v2_5/mmvet/100/modeling_intern_vit.py new file mode 100644 index 0000000000000000000000000000000000000000..1c5c043a4b860720b3b6e55107e8e6ecf0c573de --- /dev/null +++ b/InternVL-main/internvl_chat/work_dirs/internvl_chat_v2_5/mmvet/100/modeling_intern_vit.py @@ -0,0 +1,430 @@ +# -------------------------------------------------------- +# InternVL +# Copyright (c) 2024 OpenGVLab +# Licensed under The MIT License [see LICENSE for details] +# -------------------------------------------------------- + +from typing import Optional, Tuple, Union + +import torch +import torch.nn.functional as F +import torch.utils.checkpoint +from einops import rearrange +from timm.models.layers import DropPath +from torch import nn +from transformers.activations import ACT2FN +from transformers.modeling_outputs import (BaseModelOutput, + BaseModelOutputWithPooling) +from transformers.modeling_utils import PreTrainedModel +from transformers.utils import logging + +from .configuration_intern_vit import InternVisionConfig + +try: + from flash_attn.bert_padding import pad_input, unpad_input + from flash_attn.flash_attn_interface import \ + flash_attn_varlen_qkvpacked_func + has_flash_attn = True +except: + print('FlashAttention2 is not installed.') + has_flash_attn = False + +logger = logging.get_logger(__name__) + + +class FlashAttention(nn.Module): + """Implement the scaled dot product attention with softmax. + Arguments + --------- + softmax_scale: The temperature to use for the softmax attention. + (default: 1/sqrt(d_keys) where d_keys is computed at + runtime) + attention_dropout: The dropout rate to apply to the attention + (default: 0.0) + """ + + def __init__(self, softmax_scale=None, attention_dropout=0.0, device=None, dtype=None): + super().__init__() + self.softmax_scale = softmax_scale + self.dropout_p = attention_dropout + + def forward(self, qkv, key_padding_mask=None, causal=False, cu_seqlens=None, + max_s=None, need_weights=False): + """Implements the multihead softmax attention. + Arguments + --------- + qkv: The tensor containing the query, key, and value. (B, S, 3, H, D) if key_padding_mask is None + if unpadded: (nnz, 3, h, d) + key_padding_mask: a bool tensor of shape (B, S) + """ + assert not need_weights + assert qkv.dtype in [torch.float16, torch.bfloat16] + assert qkv.is_cuda + + if cu_seqlens is None: + batch_size = qkv.shape[0] + seqlen = qkv.shape[1] + if key_padding_mask is None: + qkv = rearrange(qkv, 'b s ... -> (b s) ...') + max_s = seqlen + cu_seqlens = torch.arange(0, (batch_size + 1) * seqlen, step=seqlen, dtype=torch.int32, + device=qkv.device) + output = flash_attn_varlen_qkvpacked_func( + qkv, cu_seqlens, max_s, self.dropout_p if self.training else 0.0, + softmax_scale=self.softmax_scale, causal=causal + ) + output = rearrange(output, '(b s) ... -> b s ...', b=batch_size) + else: + nheads = qkv.shape[-2] + x = rearrange(qkv, 'b s three h d -> b s (three h d)') + x_unpad, indices, cu_seqlens, max_s = unpad_input(x, key_padding_mask) + x_unpad = rearrange(x_unpad, 'nnz (three h d) -> nnz three h d', three=3, h=nheads) + output_unpad = flash_attn_varlen_qkvpacked_func( + x_unpad, cu_seqlens, max_s, self.dropout_p if self.training else 0.0, + softmax_scale=self.softmax_scale, causal=causal + ) + output = rearrange(pad_input(rearrange(output_unpad, 'nnz h d -> nnz (h d)'), + indices, batch_size, seqlen), + 'b s (h d) -> b s h d', h=nheads) + else: + assert max_s is not None + output = flash_attn_varlen_qkvpacked_func( + qkv, cu_seqlens, max_s, self.dropout_p if self.training else 0.0, + softmax_scale=self.softmax_scale, causal=causal + ) + + return output, None + + +class InternRMSNorm(nn.Module): + def __init__(self, hidden_size, eps=1e-6): + super().__init__() + self.weight = nn.Parameter(torch.ones(hidden_size)) + self.variance_epsilon = eps + + def forward(self, hidden_states): + input_dtype = hidden_states.dtype + hidden_states = hidden_states.to(torch.float32) + variance = hidden_states.pow(2).mean(-1, keepdim=True) + hidden_states = hidden_states * torch.rsqrt(variance + self.variance_epsilon) + return self.weight * hidden_states.to(input_dtype) + + +try: + from apex.normalization import FusedRMSNorm + + InternRMSNorm = FusedRMSNorm # noqa + + logger.info('Discovered apex.normalization.FusedRMSNorm - will use it instead of InternRMSNorm') +except ImportError: + # using the normal InternRMSNorm + pass +except Exception: + logger.warning('discovered apex but it failed to load, falling back to InternRMSNorm') + pass + + +NORM2FN = { + 'rms_norm': InternRMSNorm, + 'layer_norm': nn.LayerNorm, +} + + +class InternVisionEmbeddings(nn.Module): + def __init__(self, config: InternVisionConfig): + super().__init__() + self.config = config + self.embed_dim = config.hidden_size + self.image_size = config.image_size + self.patch_size = config.patch_size + + self.class_embedding = nn.Parameter( + torch.randn(1, 1, self.embed_dim), + ) + + self.patch_embedding = nn.Conv2d( + in_channels=3, out_channels=self.embed_dim, kernel_size=self.patch_size, stride=self.patch_size + ) + + self.num_patches = (self.image_size // self.patch_size) ** 2 + self.num_positions = self.num_patches + 1 + + self.position_embedding = nn.Parameter(torch.randn(1, self.num_positions, self.embed_dim)) + + def _get_pos_embed(self, pos_embed, H, W): + target_dtype = pos_embed.dtype + pos_embed = pos_embed.float().reshape( + 1, self.image_size // self.patch_size, self.image_size // self.patch_size, -1).permute(0, 3, 1, 2) + pos_embed = F.interpolate(pos_embed, size=(H, W), mode='bicubic', align_corners=False). \ + reshape(1, -1, H * W).permute(0, 2, 1).to(target_dtype) + return pos_embed + + def forward(self, pixel_values: torch.FloatTensor) -> torch.Tensor: + target_dtype = self.patch_embedding.weight.dtype + patch_embeds = self.patch_embedding(pixel_values) # shape = [*, channel, width, height] + batch_size, _, height, width = patch_embeds.shape + patch_embeds = patch_embeds.flatten(2).transpose(1, 2) + class_embeds = self.class_embedding.expand(batch_size, 1, -1).to(target_dtype) + embeddings = torch.cat([class_embeds, patch_embeds], dim=1) + position_embedding = torch.cat([ + self.position_embedding[:, :1, :], + self._get_pos_embed(self.position_embedding[:, 1:, :], height, width) + ], dim=1) + embeddings = embeddings + position_embedding.to(target_dtype) + return embeddings + + +class InternAttention(nn.Module): + """Multi-headed attention from 'Attention Is All You Need' paper""" + + def __init__(self, config: InternVisionConfig): + super().__init__() + self.config = config + self.embed_dim = config.hidden_size + self.num_heads = config.num_attention_heads + self.use_flash_attn = config.use_flash_attn and has_flash_attn + if config.use_flash_attn and not has_flash_attn: + print('Warning: Flash Attention is not available, use_flash_attn is set to False.') + self.head_dim = self.embed_dim // self.num_heads + if self.head_dim * self.num_heads != self.embed_dim: + raise ValueError( + f'embed_dim must be divisible by num_heads (got `embed_dim`: {self.embed_dim} and `num_heads`:' + f' {self.num_heads}).' + ) + + self.scale = self.head_dim ** -0.5 + self.qkv = nn.Linear(self.embed_dim, 3 * self.embed_dim, bias=config.qkv_bias) + self.attn_drop = nn.Dropout(config.attention_dropout) + self.proj_drop = nn.Dropout(config.dropout) + + self.qk_normalization = config.qk_normalization + + if self.qk_normalization: + self.q_norm = InternRMSNorm(self.embed_dim, eps=config.layer_norm_eps) + self.k_norm = InternRMSNorm(self.embed_dim, eps=config.layer_norm_eps) + + if self.use_flash_attn: + self.inner_attn = FlashAttention(attention_dropout=config.attention_dropout) + self.proj = nn.Linear(self.embed_dim, self.embed_dim) + + def _naive_attn(self, x): + B, N, C = x.shape + qkv = self.qkv(x).reshape(B, N, 3, self.num_heads, C // self.num_heads).permute(2, 0, 3, 1, 4) + q, k, v = qkv.unbind(0) # make torchscript happy (cannot use tensor as tuple) + + if self.qk_normalization: + B_, H_, N_, D_ = q.shape + q = self.q_norm(q.transpose(1, 2).flatten(-2, -1)).view(B_, N_, H_, D_).transpose(1, 2) + k = self.k_norm(k.transpose(1, 2).flatten(-2, -1)).view(B_, N_, H_, D_).transpose(1, 2) + + attn = ((q * self.scale) @ k.transpose(-2, -1)) + attn = attn.softmax(dim=-1) + attn = self.attn_drop(attn) + + x = (attn @ v).transpose(1, 2).reshape(B, N, C) + x = self.proj(x) + x = self.proj_drop(x) + return x + + def _flash_attn(self, x, key_padding_mask=None, need_weights=False): + qkv = self.qkv(x) + qkv = rearrange(qkv, 'b s (three h d) -> b s three h d', three=3, h=self.num_heads) + + if self.qk_normalization: + q, k, v = qkv.unbind(2) + q = self.q_norm(q.flatten(-2, -1)).view(q.shape) + k = self.k_norm(k.flatten(-2, -1)).view(k.shape) + qkv = torch.stack([q, k, v], dim=2) + + context, _ = self.inner_attn( + qkv, key_padding_mask=key_padding_mask, need_weights=need_weights, causal=False + ) + outs = self.proj(rearrange(context, 'b s h d -> b s (h d)')) + outs = self.proj_drop(outs) + return outs + + def forward(self, hidden_states: torch.Tensor) -> torch.Tensor: + x = self._naive_attn(hidden_states) if not self.use_flash_attn else self._flash_attn(hidden_states) + return x + + +class InternMLP(nn.Module): + def __init__(self, config: InternVisionConfig): + super().__init__() + self.config = config + self.act = ACT2FN[config.hidden_act] + self.fc1 = nn.Linear(config.hidden_size, config.intermediate_size) + self.fc2 = nn.Linear(config.intermediate_size, config.hidden_size) + + def forward(self, hidden_states: torch.Tensor) -> torch.Tensor: + hidden_states = self.fc1(hidden_states) + hidden_states = self.act(hidden_states) + hidden_states = self.fc2(hidden_states) + return hidden_states + + +class InternVisionEncoderLayer(nn.Module): + def __init__(self, config: InternVisionConfig, drop_path_rate: float): + super().__init__() + self.embed_dim = config.hidden_size + self.intermediate_size = config.intermediate_size + self.norm_type = config.norm_type + + self.attn = InternAttention(config) + self.mlp = InternMLP(config) + self.norm1 = NORM2FN[self.norm_type](self.embed_dim, eps=config.layer_norm_eps) + self.norm2 = NORM2FN[self.norm_type](self.embed_dim, eps=config.layer_norm_eps) + + self.ls1 = nn.Parameter(config.initializer_factor * torch.ones(self.embed_dim)) + self.ls2 = nn.Parameter(config.initializer_factor * torch.ones(self.embed_dim)) + self.drop_path1 = DropPath(drop_path_rate) if drop_path_rate > 0. else nn.Identity() + self.drop_path2 = DropPath(drop_path_rate) if drop_path_rate > 0. else nn.Identity() + + def forward( + self, + hidden_states: torch.Tensor, + ) -> Tuple[torch.FloatTensor, Optional[torch.FloatTensor], Optional[Tuple[torch.FloatTensor]]]: + """ + Args: + hidden_states (`Tuple[torch.FloatTensor, Optional[torch.FloatTensor]]`): input to the layer of shape `(batch, seq_len, embed_dim)` + """ + hidden_states = hidden_states + self.drop_path1(self.attn(self.norm1(hidden_states).to(hidden_states.dtype)) * self.ls1) + + hidden_states = hidden_states + self.drop_path2(self.mlp(self.norm2(hidden_states).to(hidden_states.dtype)) * self.ls2) + + return hidden_states + + +class InternVisionEncoder(nn.Module): + """ + Transformer encoder consisting of `config.num_hidden_layers` self attention layers. Each layer is a + [`InternEncoderLayer`]. + + Args: + config (`InternConfig`): + The corresponding vision configuration for the `InternEncoder`. + """ + + def __init__(self, config: InternVisionConfig): + super().__init__() + self.config = config + # stochastic depth decay rule + dpr = [x.item() for x in torch.linspace(0, config.drop_path_rate, config.num_hidden_layers)] + self.layers = nn.ModuleList([ + InternVisionEncoderLayer(config, dpr[idx]) for idx in range(config.num_hidden_layers)]) + self.gradient_checkpointing = True + + def forward( + self, + inputs_embeds, + output_hidden_states: Optional[bool] = None, + return_dict: Optional[bool] = None, + ) -> Union[Tuple, BaseModelOutput]: + r""" + Args: + inputs_embeds (`torch.FloatTensor` of shape `(batch_size, sequence_length, hidden_size)`): + Embedded representation of the inputs. Should be float, not int tokens. + output_hidden_states (`bool`, *optional*): + Whether or not to return the hidden states of all layers. See `hidden_states` under returned tensors + for more detail. + return_dict (`bool`, *optional*): + Whether or not to return a [`~utils.ModelOutput`] instead of a plain tuple. + """ + output_hidden_states = ( + output_hidden_states if output_hidden_states is not None else self.config.output_hidden_states + ) + return_dict = return_dict if return_dict is not None else self.config.use_return_dict + + encoder_states = () if output_hidden_states else None + hidden_states = inputs_embeds + + for idx, encoder_layer in enumerate(self.layers): + if output_hidden_states: + encoder_states = encoder_states + (hidden_states,) + if self.gradient_checkpointing and self.training: + layer_outputs = torch.utils.checkpoint.checkpoint( + encoder_layer, + hidden_states) + else: + layer_outputs = encoder_layer( + hidden_states, + ) + hidden_states = layer_outputs + + if output_hidden_states: + encoder_states = encoder_states + (hidden_states,) + + if not return_dict: + return tuple(v for v in [hidden_states, encoder_states] if v is not None) + return BaseModelOutput( + last_hidden_state=hidden_states, hidden_states=encoder_states + ) + + +class InternVisionModel(PreTrainedModel): + main_input_name = 'pixel_values' + _supports_flash_attn_2 = True + config_class = InternVisionConfig + _no_split_modules = ['InternVisionEncoderLayer'] + + def __init__(self, config: InternVisionConfig): + super().__init__(config) + self.config = config + + self.embeddings = InternVisionEmbeddings(config) + self.encoder = InternVisionEncoder(config) + + def resize_pos_embeddings(self, old_size, new_size, patch_size): + pos_emb = self.embeddings.position_embedding + _, num_positions, embed_dim = pos_emb.shape + cls_emb = pos_emb[:, :1, :] + pos_emb = pos_emb[:, 1:, :].reshape(1, old_size // patch_size, old_size // patch_size, -1).permute(0, 3, 1, 2) + pos_emb = F.interpolate(pos_emb.float(), size=new_size // patch_size, mode='bicubic', align_corners=False) + pos_emb = pos_emb.to(cls_emb.dtype).reshape(1, embed_dim, -1).permute(0, 2, 1) + pos_emb = torch.cat([cls_emb, pos_emb], dim=1) + self.embeddings.position_embedding = nn.Parameter(pos_emb) + self.embeddings.image_size = new_size + logger.info('Resized position embeddings from {} to {}'.format(old_size, new_size)) + + def get_input_embeddings(self): + return self.embeddings + + def forward( + self, + pixel_values: Optional[torch.FloatTensor] = None, + output_hidden_states: Optional[bool] = None, + return_dict: Optional[bool] = None, + pixel_embeds: Optional[torch.FloatTensor] = None, + ) -> Union[Tuple, BaseModelOutputWithPooling]: + output_hidden_states = ( + output_hidden_states if output_hidden_states is not None else self.config.output_hidden_states + ) + return_dict = return_dict if return_dict is not None else self.config.use_return_dict + + if pixel_values is None and pixel_embeds is None: + raise ValueError('You have to specify pixel_values or pixel_embeds') + + if pixel_embeds is not None: + hidden_states = pixel_embeds + else: + if len(pixel_values.shape) == 4: + hidden_states = self.embeddings(pixel_values) + else: + raise ValueError(f'wrong pixel_values size: {pixel_values.shape}') + encoder_outputs = self.encoder( + inputs_embeds=hidden_states, + output_hidden_states=output_hidden_states, + return_dict=return_dict, + ) + last_hidden_state = encoder_outputs.last_hidden_state + pooled_output = last_hidden_state[:, 0, :] + + if not return_dict: + return (last_hidden_state, pooled_output) + encoder_outputs[1:] + + return BaseModelOutputWithPooling( + last_hidden_state=last_hidden_state, + pooler_output=pooled_output, + hidden_states=encoder_outputs.hidden_states, + attentions=encoder_outputs.attentions, + ) diff --git a/InternVL-main/internvl_chat/work_dirs/internvl_chat_v2_5/mmvet/100/modeling_internlm2.py b/InternVL-main/internvl_chat/work_dirs/internvl_chat_v2_5/mmvet/100/modeling_internlm2.py new file mode 100644 index 0000000000000000000000000000000000000000..7c8c24d873f6ecd152d00fd65371e23ead981e1d --- /dev/null +++ b/InternVL-main/internvl_chat/work_dirs/internvl_chat_v2_5/mmvet/100/modeling_internlm2.py @@ -0,0 +1,1415 @@ +# Copyright (c) The InternLM team and The HuggingFace Inc. team. All rights reserved. +# +# This code is based on transformers/src/transformers/models/llama/modeling_llama.py +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +""" PyTorch InternLM2 model.""" +import math +import queue +import threading +import warnings +from typing import List, Optional, Tuple, Union + +import torch +import torch.nn.functional as F +import torch.utils.checkpoint +from einops import rearrange +from torch import nn +from torch.nn import BCEWithLogitsLoss, CrossEntropyLoss, MSELoss +from transformers.activations import ACT2FN +from transformers.modeling_outputs import (BaseModelOutputWithPast, + CausalLMOutputWithPast, + SequenceClassifierOutputWithPast) +from transformers.modeling_utils import PreTrainedModel +from transformers.utils import (add_start_docstrings, + add_start_docstrings_to_model_forward, logging, + replace_return_docstrings) + +try: + from transformers.generation.streamers import BaseStreamer +except: # noqa # pylint: disable=bare-except + BaseStreamer = None + +from .configuration_internlm2 import InternLM2Config + +logger = logging.get_logger(__name__) + +_CONFIG_FOR_DOC = 'InternLM2Config' + +flash_attn_func, flash_attn_varlen_func = None, None +pad_input, index_first_axis, unpad_input = None, None, None +try: + from flash_attn import flash_attn_func as _flash_attn_func + from flash_attn import flash_attn_varlen_func as _flash_attn_varlen_func + from flash_attn.bert_padding import index_first_axis as _index_first_axis + from flash_attn.bert_padding import pad_input as _pad_input + from flash_attn.bert_padding import unpad_input as _unpad_input + + flash_attn_func, flash_attn_varlen_func = _flash_attn_func, _flash_attn_varlen_func + pad_input, index_first_axis, unpad_input = _pad_input, _index_first_axis, _unpad_input + has_flash_attn = True +except: + has_flash_attn = False + + +def _import_flash_attn(): + global flash_attn_func, flash_attn_varlen_func + global pad_input, index_first_axis, unpad_input + try: + from flash_attn import flash_attn_func as _flash_attn_func + from flash_attn import \ + flash_attn_varlen_func as _flash_attn_varlen_func + from flash_attn.bert_padding import \ + index_first_axis as _index_first_axis + from flash_attn.bert_padding import pad_input as _pad_input + from flash_attn.bert_padding import unpad_input as _unpad_input + flash_attn_func, flash_attn_varlen_func = _flash_attn_func, _flash_attn_varlen_func + pad_input, index_first_axis, unpad_input = _pad_input, _index_first_axis, _unpad_input + except ImportError: + raise ImportError('flash_attn is not installed.') + + +# Copied from transformers.models.llama.modeling_llama._get_unpad_data +def _get_unpad_data(attention_mask): + seqlens_in_batch = attention_mask.sum(dim=-1, dtype=torch.int32) + indices = torch.nonzero(attention_mask.flatten(), as_tuple=False).flatten() + max_seqlen_in_batch = seqlens_in_batch.max().item() + cu_seqlens = F.pad(torch.cumsum(seqlens_in_batch, dim=0, dtype=torch.torch.int32), (1, 0)) + return ( + indices, + cu_seqlens, + max_seqlen_in_batch, + ) + + +# Copied from transformers.models.bart.modeling_bart._make_causal_mask +def _make_causal_mask( + input_ids_shape: torch.Size, dtype: torch.dtype, device: torch.device, past_key_values_length: int = 0 +): + """ + Make causal mask used for bi-directional self-attention. + """ + bsz, tgt_len = input_ids_shape + mask = torch.full((tgt_len, tgt_len), torch.tensor(torch.finfo(dtype).min, device=device), device=device) + mask_cond = torch.arange(mask.size(-1), device=device) + mask.masked_fill_(mask_cond < (mask_cond + 1).view(mask.size(-1), 1), 0) + mask = mask.to(dtype) + + if past_key_values_length > 0: + mask = torch.cat([torch.zeros(tgt_len, past_key_values_length, dtype=dtype, device=device), mask], dim=-1) + return mask[None, None, :, :].expand(bsz, 1, tgt_len, tgt_len + past_key_values_length) + + +# Copied from transformers.models.bart.modeling_bart._expand_mask +def _expand_mask(mask: torch.Tensor, dtype: torch.dtype, tgt_len: Optional[int] = None): + """ + Expands attention_mask from `[bsz, seq_len]` to `[bsz, 1, tgt_seq_len, src_seq_len]`. + """ + bsz, src_len = mask.size() + tgt_len = tgt_len if tgt_len is not None else src_len + + expanded_mask = mask[:, None, None, :].expand(bsz, 1, tgt_len, src_len).to(dtype) + + inverted_mask = 1.0 - expanded_mask + + return inverted_mask.masked_fill(inverted_mask.to(torch.bool), torch.finfo(dtype).min) + + +# Copied from transformers.models.llama.modeling_llama.LlamaRMSNorm with Llama->InternLM2 +class InternLM2RMSNorm(nn.Module): + def __init__(self, hidden_size, eps=1e-6): + """ + InternLM2RMSNorm is equivalent to T5LayerNorm + """ + super().__init__() + self.weight = nn.Parameter(torch.ones(hidden_size)) + self.variance_epsilon = eps + + def forward(self, hidden_states): + input_dtype = hidden_states.dtype + hidden_states = hidden_states.to(torch.float32) + variance = hidden_states.pow(2).mean(-1, keepdim=True) + hidden_states = hidden_states * torch.rsqrt(variance + self.variance_epsilon) + return self.weight * hidden_states.to(input_dtype) + + +# Copied from transformers.model.llama.modeling_llama.LlamaRotaryEmbedding with Llama->InternLM2 +class InternLM2RotaryEmbedding(nn.Module): + def __init__(self, dim, max_position_embeddings=2048, base=10000, device=None): + super().__init__() + + self.dim = dim + self.max_position_embeddings = max_position_embeddings + self.base = base + inv_freq = 1.0 / (self.base ** (torch.arange(0, self.dim, 2).float().to(device) / self.dim)) + self.register_buffer('inv_freq', inv_freq, persistent=False) + + # Build here to make `torch.jit.trace` work. + self._set_cos_sin_cache( + seq_len=max_position_embeddings, device=self.inv_freq.device, dtype=torch.get_default_dtype() + ) + + def _set_cos_sin_cache(self, seq_len, device, dtype): + self.max_seq_len_cached = seq_len + t = torch.arange(self.max_seq_len_cached, device=device).to(dtype=self.inv_freq.dtype) + + freqs = torch.einsum('i,j->ij', t, self.inv_freq) + # Different from paper, but it uses a different permutation in order to obtain the same calculation + emb = torch.cat((freqs, freqs), dim=-1) + self.register_buffer('cos_cached', emb.cos().to(dtype), persistent=False) + self.register_buffer('sin_cached', emb.sin().to(dtype), persistent=False) + + def forward(self, x, seq_len=None): + # x: [bs, num_attention_heads, seq_len, head_size] + if seq_len > self.max_seq_len_cached: + self._set_cos_sin_cache(seq_len=seq_len, device=x.device, dtype=torch.float32) + + return ( + self.cos_cached[:seq_len].to(dtype=x.dtype), + self.sin_cached[:seq_len].to(dtype=x.dtype), + ) + + +# Copied from transformers.model.llama.modeling_llama.LlamaLinearScalingRotaryEmbedding with Llama->InternLM2 +class InternLM2LinearScalingRotaryEmbedding(InternLM2RotaryEmbedding): + """InternLM2RotaryEmbedding extended with linear scaling. Credits to the Reddit user /u/kaiokendev""" + + def __init__(self, dim, max_position_embeddings=2048, base=10000, device=None, scaling_factor=1.0): + self.scaling_factor = scaling_factor + super().__init__(dim, max_position_embeddings, base, device) + + def _set_cos_sin_cache(self, seq_len, device, dtype): + self.max_seq_len_cached = seq_len + t = torch.arange(self.max_seq_len_cached, device=device).to(dtype=self.inv_freq.dtype) + t = t / self.scaling_factor + + freqs = torch.einsum('i,j->ij', t, self.inv_freq) + # Different from paper, but it uses a different permutation in order to obtain the same calculation + emb = torch.cat((freqs, freqs), dim=-1) + self.register_buffer('cos_cached', emb.cos().to(dtype), persistent=False) + self.register_buffer('sin_cached', emb.sin().to(dtype), persistent=False) + + +# Copied from transformers.model.llama.modeling_llama.LlamaDynamicNTKScalingRotaryEmbedding with Llama->InternLM2 +class InternLM2DynamicNTKScalingRotaryEmbedding(InternLM2RotaryEmbedding): + """InternLM2RotaryEmbedding extended with Dynamic NTK scaling. + Credits to the Reddit users /u/bloc97 and /u/emozilla. + """ + + def __init__(self, dim, max_position_embeddings=2048, base=10000, device=None, scaling_factor=1.0): + self.scaling_factor = scaling_factor + super().__init__(dim, max_position_embeddings, base, device) + + def _set_cos_sin_cache(self, seq_len, device, dtype): + self.max_seq_len_cached = seq_len + + if seq_len > self.max_position_embeddings: + base = self.base * ( + (self.scaling_factor * seq_len / self.max_position_embeddings) - (self.scaling_factor - 1) + ) ** (self.dim / (self.dim - 2)) + inv_freq = 1.0 / (base ** (torch.arange(0, self.dim, 2).float().to(device) / self.dim)) + self.register_buffer('inv_freq', inv_freq, persistent=False) + + t = torch.arange(self.max_seq_len_cached, device=device).to(dtype=self.inv_freq.dtype) + + freqs = torch.einsum('i,j->ij', t, self.inv_freq) + # Different from paper, but it uses a different permutation in order to obtain the same calculation + emb = torch.cat((freqs, freqs), dim=-1) + self.register_buffer('cos_cached', emb.cos().to(dtype), persistent=False) + self.register_buffer('sin_cached', emb.sin().to(dtype), persistent=False) + + +# Copied from transformers.model.llama.modeling_llama.rotate_half +def rotate_half(x): + """Rotates half the hidden dims of the input.""" + x1 = x[..., : x.shape[-1] // 2] + x2 = x[..., x.shape[-1] // 2 :] + return torch.cat((-x2, x1), dim=-1) + + +# Copied from transformers.model.llama.modeling_llama.apply_rotary_pos_emb +def apply_rotary_pos_emb(q, k, cos, sin, position_ids, unsqueeze_dim=1): + """Applies Rotary Position Embedding to the query and key tensors.""" + cos = cos[position_ids].unsqueeze(unsqueeze_dim) + sin = sin[position_ids].unsqueeze(unsqueeze_dim) + q_embed = (q * cos) + (rotate_half(q) * sin) + k_embed = (k * cos) + (rotate_half(k) * sin) + return q_embed, k_embed + + +class InternLM2MLP(nn.Module): + def __init__(self, config): + super().__init__() + self.config = config + self.hidden_size = config.hidden_size + self.intermediate_size = config.intermediate_size + self.w1 = nn.Linear(self.hidden_size, self.intermediate_size, bias=False) + self.w3 = nn.Linear(self.hidden_size, self.intermediate_size, bias=False) + self.w2 = nn.Linear(self.intermediate_size, self.hidden_size, bias=False) + self.act_fn = ACT2FN[config.hidden_act] + + def forward(self, x): + down_proj = self.w2(self.act_fn(self.w1(x)) * self.w3(x)) + + return down_proj + + +# Copied from transformers.model.llama.modeling_llama.repeat_kv +def repeat_kv(hidden_states: torch.Tensor, n_rep: int) -> torch.Tensor: + """ + This is the equivalent of torch.repeat_interleave(x, dim=1, repeats=n_rep). The hidden states go from (batch, + num_key_value_heads, seqlen, head_dim) to (batch, num_attention_heads, seqlen, head_dim) + """ + batch, num_key_value_heads, slen, head_dim = hidden_states.shape + if n_rep == 1: + return hidden_states + hidden_states = hidden_states[:, :, None, :, :].expand(batch, num_key_value_heads, n_rep, slen, head_dim) + return hidden_states.reshape(batch, num_key_value_heads * n_rep, slen, head_dim) + + +# Modified from transformers.model.llama.modeling_llama.LlamaAttention +class InternLM2Attention(nn.Module): + """Multi-headed attention from 'Attention Is All You Need' paper""" + + def __init__(self, config: InternLM2Config): + super().__init__() + self.config = config + self.hidden_size = config.hidden_size + self.num_heads = config.num_attention_heads + self.head_dim = self.hidden_size // self.num_heads + self.num_key_value_heads = config.num_key_value_heads + self.num_key_value_groups = self.num_heads // self.num_key_value_heads + self.max_position_embeddings = config.max_position_embeddings + self.is_causal = True + + if (self.head_dim * self.num_heads) != self.hidden_size: + raise ValueError( + f'hidden_size must be divisible by num_heads (got `hidden_size`: {self.hidden_size}' + f' and `num_heads`: {self.num_heads}).' + ) + + self.wqkv = nn.Linear( + self.hidden_size, + (self.num_heads + 2 * self.num_key_value_heads) * self.head_dim, + bias=config.bias, + ) + + self.wo = nn.Linear(self.num_heads * self.head_dim, self.hidden_size, bias=config.bias) + self._init_rope() + + def _init_rope(self): + if self.config.rope_scaling is None: + self.rotary_emb = InternLM2RotaryEmbedding( + self.head_dim, + max_position_embeddings=self.max_position_embeddings, + base=self.config.rope_theta, + ) + else: + scaling_type = self.config.rope_scaling['type'] + scaling_factor = self.config.rope_scaling['factor'] + if scaling_type == 'dynamic': + self.rotary_emb = InternLM2DynamicNTKScalingRotaryEmbedding( + self.head_dim, + max_position_embeddings=self.max_position_embeddings, + base=self.config.rope_theta, + scaling_factor=scaling_factor, + ) + elif scaling_type == 'linear': + self.rotary_emb = InternLM2LinearScalingRotaryEmbedding( + self.head_dim, + max_position_embeddings=self.max_position_embeddings, + base=self.config.rope_theta, + scaling_factor=scaling_factor, + ) + else: + raise ValueError("Currently we only support rotary embedding's type being 'dynamic' or 'linear'.") + return self.rotary_emb + + def _shape(self, tensor: torch.Tensor, seq_len: int, bsz: int): + return tensor.view(bsz, seq_len, self.num_heads, self.head_dim).transpose(1, 2).contiguous() + + def forward( + self, + hidden_states: torch.Tensor, + attention_mask: Optional[torch.Tensor] = None, + position_ids: Optional[torch.LongTensor] = None, + past_key_value: Optional[Tuple[torch.Tensor]] = None, + output_attentions: bool = False, + use_cache: bool = False, + **kwargs, + ) -> Tuple[torch.Tensor, Optional[torch.Tensor], Optional[Tuple[torch.Tensor]]]: + if 'padding_mask' in kwargs: + warnings.warn( + 'Passing `padding_mask` is deprecated and will be removed in v4.37. ' + 'Please make sure use `attention_mask` instead.`' + ) + + bsz, q_len, _ = hidden_states.size() + + qkv_states = self.wqkv(hidden_states) + + qkv_states = rearrange( + qkv_states, + 'b q (h gs d) -> b q h gs d', + gs=2 + self.num_key_value_groups, + d=self.head_dim, + ) + + query_states = qkv_states[..., : self.num_key_value_groups, :] + query_states = rearrange(query_states, 'b q h gs d -> b q (h gs) d') + key_states = qkv_states[..., -2, :] + value_states = qkv_states[..., -1, :] + + query_states = query_states.transpose(1, 2) + key_states = key_states.transpose(1, 2) + value_states = value_states.transpose(1, 2) + + kv_seq_len = key_states.shape[-2] + if past_key_value is not None: + kv_seq_len += past_key_value[0].shape[-2] + cos, sin = self.rotary_emb(value_states, seq_len=kv_seq_len) + query_states, key_states = apply_rotary_pos_emb(query_states, key_states, cos, sin, position_ids) + + if past_key_value is not None: + # reuse k, v, self_attention + key_states = torch.cat([past_key_value[0], key_states], dim=2) + value_states = torch.cat([past_key_value[1], value_states], dim=2) + + past_key_value = (key_states, value_states) if use_cache else None + + key_states = repeat_kv(key_states, self.num_key_value_groups) + value_states = repeat_kv(value_states, self.num_key_value_groups) + + attn_weights = torch.matmul(query_states, key_states.transpose(2, 3)) / math.sqrt(self.head_dim) + + if attn_weights.size() != (bsz, self.num_heads, q_len, kv_seq_len): + raise ValueError( + f'Attention weights should be of size {(bsz, self.num_heads, q_len, kv_seq_len)}, but is' + f' {attn_weights.size()}' + ) + + if attention_mask is not None: + if attention_mask.size() != (bsz, 1, q_len, kv_seq_len): + raise ValueError( + f'Attention mask should be of size {(bsz, 1, q_len, kv_seq_len)}, but is {attention_mask.size()}' + ) + attn_weights = attn_weights + attention_mask + + # upcast attention to fp32 + attn_weights = nn.functional.softmax(attn_weights, dim=-1, dtype=torch.float32).to(query_states.dtype) + attn_output = torch.matmul(attn_weights, value_states) + + if attn_output.size() != (bsz, self.num_heads, q_len, self.head_dim): + raise ValueError( + f'`attn_output` should be of size {(bsz, self.num_heads, q_len, self.head_dim)}, but is' + f' {attn_output.size()}' + ) + + attn_output = attn_output.transpose(1, 2).contiguous() + attn_output = attn_output.reshape(bsz, q_len, self.hidden_size) + + attn_output = self.wo(attn_output) + + if not output_attentions: + attn_weights = None + + return attn_output, attn_weights, past_key_value + + +# Modified from transformers.model.llama.modeling_llama.InternLM2FlashAttention2 +class InternLM2FlashAttention2(InternLM2Attention): + """ + InternLM2 flash attention module. This module inherits from `InternLM2Attention` as the weights of the module stays + untouched. The only required change would be on the forward pass where it needs to correctly call the public API of + flash attention and deal with padding tokens in case the input contains any of them. + """ + + def forward( + self, + hidden_states: torch.Tensor, + attention_mask: Optional[torch.LongTensor] = None, + position_ids: Optional[torch.LongTensor] = None, + past_key_value: Optional[Tuple[torch.Tensor]] = None, + output_attentions: bool = False, + use_cache: bool = False, + **kwargs, + ) -> Tuple[torch.Tensor, Optional[torch.Tensor], Optional[Tuple[torch.Tensor]]]: + # InternLM2FlashAttention2 attention does not support output_attentions + if 'padding_mask' in kwargs: + warnings.warn( + 'Passing `padding_mask` is deprecated and will be removed in v4.37. ' + 'Please make sure use `attention_mask` instead.`' + ) + + # overwrite attention_mask with padding_mask + attention_mask = kwargs.pop('padding_mask') + + output_attentions = False + + bsz, q_len, _ = hidden_states.size() + + qkv_states = self.wqkv(hidden_states) + + qkv_states = rearrange( + qkv_states, + 'b q (h gs d) -> b q h gs d', + gs=2 + self.num_key_value_groups, + d=self.head_dim, + ) + + query_states = qkv_states[..., : self.num_key_value_groups, :] + query_states = rearrange(query_states, 'b q h gs d -> b q (h gs) d') + key_states = qkv_states[..., -2, :] + value_states = qkv_states[..., -1, :] + + query_states = query_states.transpose(1, 2) + key_states = key_states.transpose(1, 2) + value_states = value_states.transpose(1, 2) + + kv_seq_len = key_states.shape[-2] + if past_key_value is not None: + kv_seq_len += past_key_value[0].shape[-2] + + cos, sin = self.rotary_emb(value_states, seq_len=kv_seq_len) + + query_states, key_states = apply_rotary_pos_emb(query_states, key_states, cos, sin, position_ids) + + if past_key_value is not None: + # reuse k, v, self_attention + key_states = torch.cat([past_key_value[0], key_states], dim=2) + value_states = torch.cat([past_key_value[1], value_states], dim=2) + + past_key_value = (key_states, value_states) if use_cache else None + + query_states = query_states.transpose(1, 2) + key_states = key_states.transpose(1, 2) + value_states = value_states.transpose(1, 2) + + attn_output = self._flash_attention_forward( + query_states, key_states, value_states, attention_mask, q_len + ) + attn_output = attn_output.reshape(bsz, q_len, self.hidden_size).contiguous() + attn_output = self.wo(attn_output) + + if not output_attentions: + attn_weights = None + + return attn_output, attn_weights, past_key_value + + def _flash_attention_forward( + self, query_states, key_states, value_states, attention_mask, query_length, dropout=0.0, softmax_scale=None + ): + """ + Calls the forward method of Flash Attention - if the input hidden states contain at least one padding token + first unpad the input, then computes the attention scores and pad the final attention scores. + + Args: + query_states (`torch.Tensor`): + Input query states to be passed to Flash Attention API + key_states (`torch.Tensor`): + Input key states to be passed to Flash Attention API + value_states (`torch.Tensor`): + Input value states to be passed to Flash Attention API + attention_mask (`torch.Tensor`): + The padding mask - corresponds to a tensor of size `(batch_size, seq_len)` where 0 stands for the + position of padding tokens and 1 for the position of non-padding tokens. + dropout (`int`, *optional*): + Attention dropout + softmax_scale (`float`, *optional*): + The scaling of QK^T before applying softmax. Default to 1 / sqrt(head_dim) + """ + # Contains at least one padding token in the sequence + causal = self.is_causal and query_length != 1 + if attention_mask is not None: + batch_size = query_states.shape[0] + query_states, key_states, value_states, indices_q, cu_seq_lens, max_seq_lens = self._unpad_input( + query_states, key_states, value_states, attention_mask, query_length + ) + + cu_seqlens_q, cu_seqlens_k = cu_seq_lens + max_seqlen_in_batch_q, max_seqlen_in_batch_k = max_seq_lens + + attn_output_unpad = flash_attn_varlen_func( + query_states, + key_states, + value_states, + cu_seqlens_q=cu_seqlens_q, + cu_seqlens_k=cu_seqlens_k, + max_seqlen_q=max_seqlen_in_batch_q, + max_seqlen_k=max_seqlen_in_batch_k, + dropout_p=dropout, + softmax_scale=softmax_scale, + causal=causal, + ) + + attn_output = pad_input(attn_output_unpad, indices_q, batch_size, query_length) + else: + attn_output = flash_attn_func( + query_states, key_states, value_states, dropout, softmax_scale=softmax_scale, causal=causal + ) + + return attn_output + + def _unpad_input(self, query_layer, key_layer, value_layer, attention_mask, query_length): + indices_k, cu_seqlens_k, max_seqlen_in_batch_k = _get_unpad_data(attention_mask) + batch_size, kv_seq_len, num_key_value_heads, head_dim = key_layer.shape + + key_layer = index_first_axis( + key_layer.reshape(batch_size * kv_seq_len, num_key_value_heads, head_dim), indices_k + ) + value_layer = index_first_axis( + value_layer.reshape(batch_size * kv_seq_len, num_key_value_heads, head_dim), indices_k + ) + + if query_length == kv_seq_len: + query_layer = index_first_axis( + query_layer.reshape(batch_size * kv_seq_len, self.num_heads, head_dim), indices_k + ) + cu_seqlens_q = cu_seqlens_k + max_seqlen_in_batch_q = max_seqlen_in_batch_k + indices_q = indices_k + elif query_length == 1: + max_seqlen_in_batch_q = 1 + cu_seqlens_q = torch.arange( + batch_size + 1, dtype=torch.int32, device=query_layer.device + ) # There is a memcpy here, that is very bad. + indices_q = cu_seqlens_q[:-1] + query_layer = query_layer.squeeze(1) + else: + # The -q_len: slice assumes left padding. + attention_mask = attention_mask[:, -query_length:] + query_layer, indices_q, cu_seqlens_q, max_seqlen_in_batch_q = unpad_input(query_layer, attention_mask) + + return ( + query_layer, + key_layer, + value_layer, + indices_q.to(torch.int64), + (cu_seqlens_q, cu_seqlens_k), + (max_seqlen_in_batch_q, max_seqlen_in_batch_k), + ) + + +INTERNLM2_ATTENTION_CLASSES = { + 'eager': InternLM2Attention, + 'flash_attention_2': InternLM2FlashAttention2, +} + + +# Modified from transformers.model.llama.modeling_llama.LlamaDecoderLayer +class InternLM2DecoderLayer(nn.Module): + def __init__(self, config: InternLM2Config): + super().__init__() + self.hidden_size = config.hidden_size + + self.attention = INTERNLM2_ATTENTION_CLASSES[config.attn_implementation](config=config) + + self.feed_forward = InternLM2MLP(config) + self.attention_norm = InternLM2RMSNorm(config.hidden_size, eps=config.rms_norm_eps) + self.ffn_norm = InternLM2RMSNorm(config.hidden_size, eps=config.rms_norm_eps) + + def forward( + self, + hidden_states: torch.Tensor, + attention_mask: Optional[torch.Tensor] = None, + position_ids: Optional[torch.LongTensor] = None, + past_key_value: Optional[Tuple[torch.Tensor]] = None, + output_attentions: Optional[bool] = False, + use_cache: Optional[bool] = False, + **kwargs, + ) -> Tuple[torch.FloatTensor, Optional[Tuple[torch.FloatTensor, torch.FloatTensor]]]: + """ + Args: + hidden_states (`torch.FloatTensor`): input to the layer of shape `(batch, seq_len, embed_dim)` + attention_mask (`torch.FloatTensor`, *optional*): + attention mask of size `(batch_size, sequence_length)` if flash attention is used or `(batch_size, 1, + query_sequence_length, key_sequence_length)` if default attention is used. + output_attentions (`bool`, *optional*): + Whether or not to return the attentions tensors of all attention layers. See `attentions` under + returned tensors for more detail. + use_cache (`bool`, *optional*): + If set to `True`, `past_key_values` key value states are returned and can be used to speed up decoding + (see `past_key_values`). + past_key_value (`Tuple(torch.FloatTensor)`, *optional*): cached past key and value projection states + """ + if 'padding_mask' in kwargs: + warnings.warn( + 'Passing `padding_mask` is deprecated and will be removed in v4.37. ' + 'Please make sure use `attention_mask` instead.`' + ) + + residual = hidden_states + + hidden_states = self.attention_norm(hidden_states) + + # Self Attention + hidden_states, self_attn_weights, present_key_value = self.attention( + hidden_states=hidden_states, + attention_mask=attention_mask, + position_ids=position_ids, + past_key_value=past_key_value, + output_attentions=output_attentions, + use_cache=use_cache, + **kwargs, + ) + hidden_states = residual + hidden_states + + # Fully Connected + residual = hidden_states + hidden_states = self.ffn_norm(hidden_states) + hidden_states = self.feed_forward(hidden_states) + hidden_states = residual + hidden_states + + outputs = (hidden_states,) + + if output_attentions: + outputs += (self_attn_weights,) + + if use_cache: + outputs += (present_key_value,) + + return outputs + + +InternLM2_START_DOCSTRING = r""" + This model inherits from [`PreTrainedModel`]. Check the superclass documentation for the generic methods the + library implements for all its model (such as downloading or saving, resizing the input embeddings, pruning heads + etc.) + + This model is also a PyTorch [torch.nn.Module](https://pytorch.org/docs/stable/nn.html#torch.nn.Module) subclass. + Use it as a regular PyTorch Module and refer to the PyTorch documentation for all matter related to general usage + and behavior. + + Parameters: + config ([`InternLM2Config`]): + Model configuration class with all the parameters of the model. Initializing with a config file does not + load the weights associated with the model, only the configuration. Check out the + [`~PreTrainedModel.from_pretrained`] method to load the model weights. +""" + + +# Copied from transformers.models.llama.modeling_llama.LlamaPreTrainedModel with Llama->InternLM2 +@add_start_docstrings( + 'The bare InternLM2 Model outputting raw hidden-states without any specific head on top.', + InternLM2_START_DOCSTRING, +) +class InternLM2PreTrainedModel(PreTrainedModel): + config_class = InternLM2Config + base_model_prefix = 'model' + supports_gradient_checkpointing = True + _no_split_modules = ['InternLM2DecoderLayer'] + _skip_keys_device_placement = 'past_key_values' + _supports_flash_attn_2 = True + + def _init_weights(self, module): + std = self.config.initializer_range + if isinstance(module, nn.Linear): + module.weight.data.normal_(mean=0.0, std=std) + if module.bias is not None: + module.bias.data.zero_() + elif isinstance(module, nn.Embedding): + module.weight.data.normal_(mean=0.0, std=std) + if module.padding_idx is not None: + module.weight.data[module.padding_idx].zero_() + + +InternLM2_INPUTS_DOCSTRING = r""" + Args: + input_ids (`torch.LongTensor` of shape `(batch_size, sequence_length)`): + Indices of input sequence tokens in the vocabulary. Padding will be ignored by default should you provide + it. + + Indices can be obtained using [`AutoTokenizer`]. See [`PreTrainedTokenizer.encode`] and + [`PreTrainedTokenizer.__call__`] for details. + + [What are input IDs?](../glossary#input-ids) + attention_mask (`torch.Tensor` of shape `(batch_size, sequence_length)`, *optional*): + Mask to avoid performing attention on padding token indices. Mask values selected in `[0, 1]`: + + - 1 for tokens that are **not masked**, + - 0 for tokens that are **masked**. + + [What are attention masks?](../glossary#attention-mask) + + Indices can be obtained using [`AutoTokenizer`]. See [`PreTrainedTokenizer.encode`] and + [`PreTrainedTokenizer.__call__`] for details. + + If `past_key_values` is used, optionally only the last `input_ids` have to be input (see + `past_key_values`). + + If you want to change padding behavior, you should read [`modeling_opt._prepare_decoder_attention_mask`] + and modify to your needs. See diagram 1 in [the paper](https://arxiv.org/abs/1910.13461) for more + information on the default strategy. + + - 1 indicates the head is **not masked**, + - 0 indicates the head is **masked**. + position_ids (`torch.LongTensor` of shape `(batch_size, sequence_length)`, *optional*): + Indices of positions of each input sequence tokens in the position embeddings. Selected in the range `[0, + config.n_positions - 1]`. + + [What are position IDs?](../glossary#position-ids) + past_key_values (`tuple(tuple(torch.FloatTensor))`, *optional*, returned when `use_cache=True` is passed or + when `config.use_cache=True`): + Tuple of `tuple(torch.FloatTensor)` of length `config.n_layers`, with each tuple having 2 tensors of shape + `(batch_size, num_heads, sequence_length, embed_size_per_head)`) and 2 additional tensors of shape + `(batch_size, num_heads, decoder_sequence_length, embed_size_per_head)`. + + Contains pre-computed hidden-states (key and values in the self-attention blocks and in the cross-attention + blocks) that can be used (see `past_key_values` input) to speed up sequential decoding. + + If `past_key_values` are used, the user can optionally input only the last `input_ids` (those that don't + have their past key value states given to this model) of shape `(batch_size, 1)` instead of all `input_ids` + of shape `(batch_size, sequence_length)`. + inputs_embeds (`torch.FloatTensor` of shape `(batch_size, sequence_length, hidden_size)`, *optional*): + Optionally, instead of passing `input_ids` you can choose to directly pass an embedded representation. This + is useful if you want more control over how to convert `input_ids` indices into associated vectors than the + model's internal embedding lookup matrix. + use_cache (`bool`, *optional*): + If set to `True`, `past_key_values` key value states are returned and can be used to speed up decoding (see + `past_key_values`). + output_attentions (`bool`, *optional*): + Whether or not to return the attentions tensors of all attention layers. See `attentions` under returned + tensors for more detail. + output_hidden_states (`bool`, *optional*): + Whether or not to return the hidden states of all layers. See `hidden_states` under returned tensors for + more detail. + return_dict (`bool`, *optional*): + Whether or not to return a [`~utils.ModelOutput`] instead of a plain tuple. +""" + + +# Modified from transformers.model.llama.modeling_llama.LlamaModel +@add_start_docstrings( + 'The bare InternLM2 Model outputting raw hidden-states without any specific head on top.', + InternLM2_START_DOCSTRING, +) +class InternLM2Model(InternLM2PreTrainedModel): + """ + Transformer decoder consisting of *config.num_hidden_layers* layers. Each layer is a [`InternLM2DecoderLayer`] + + Args: + config: InternLM2Config + """ + + _auto_class = 'AutoModel' + + def __init__(self, config: InternLM2Config): + super().__init__(config) + self.padding_idx = config.pad_token_id + self.vocab_size = config.vocab_size + self.config = config + if not has_flash_attn: + self.config.attn_implementation = 'eager' + print('Warning: Flash attention is not available, using eager attention instead.') + + self.tok_embeddings = nn.Embedding(config.vocab_size, config.hidden_size, self.padding_idx) + + self.layers = nn.ModuleList([InternLM2DecoderLayer(config) for _ in range(config.num_hidden_layers)]) + self.norm = InternLM2RMSNorm(config.hidden_size, eps=config.rms_norm_eps) + + self.gradient_checkpointing = False + # Initialize weights and apply final processing + self.post_init() + + def get_input_embeddings(self): + return self.tok_embeddings + + def set_input_embeddings(self, value): + self.tok_embeddings = value + + def _prepare_decoder_attention_mask(self, attention_mask, input_shape, inputs_embeds, past_key_values_length): + # create causal mask + # [bsz, seq_len] -> [bsz, 1, tgt_seq_len, src_seq_len] + combined_attention_mask = None + if input_shape[-1] > 1: + combined_attention_mask = _make_causal_mask( + input_shape, + inputs_embeds.dtype, + device=inputs_embeds.device, + past_key_values_length=past_key_values_length, + ) + + if attention_mask is not None: + # [bsz, seq_len] -> [bsz, 1, tgt_seq_len, src_seq_len] + expanded_attn_mask = _expand_mask(attention_mask, inputs_embeds.dtype, tgt_len=input_shape[-1]).to( + inputs_embeds.device + ) + combined_attention_mask = ( + expanded_attn_mask if combined_attention_mask is None else expanded_attn_mask + combined_attention_mask + ) + + return combined_attention_mask + + @add_start_docstrings_to_model_forward(InternLM2_INPUTS_DOCSTRING) + def forward( + self, + input_ids: torch.LongTensor = None, + attention_mask: Optional[torch.Tensor] = None, + position_ids: Optional[torch.LongTensor] = None, + past_key_values: Optional[List[torch.FloatTensor]] = None, + inputs_embeds: Optional[torch.FloatTensor] = None, + use_cache: Optional[bool] = None, + output_attentions: Optional[bool] = None, + output_hidden_states: Optional[bool] = None, + return_dict: Optional[bool] = None, + ) -> Union[Tuple, BaseModelOutputWithPast]: + output_attentions = output_attentions if output_attentions is not None else self.config.output_attentions + output_hidden_states = ( + output_hidden_states if output_hidden_states is not None else self.config.output_hidden_states + ) + use_cache = use_cache if use_cache is not None else self.config.use_cache + + return_dict = return_dict if return_dict is not None else self.config.use_return_dict + + if self.config.attn_implementation == 'flash_attention_2': + _import_flash_attn() + + # retrieve input_ids and inputs_embeds + if input_ids is not None and inputs_embeds is not None: + raise ValueError('You cannot specify both input_ids and inputs_embeds at the same time') + elif input_ids is not None: + batch_size, seq_length = input_ids.shape[:2] + elif inputs_embeds is not None: + batch_size, seq_length = inputs_embeds.shape[:2] + else: + raise ValueError('You have to specify either input_ids or inputs_embeds') + + seq_length_with_past = seq_length + past_key_values_length = 0 + if past_key_values is not None: + past_key_values_length = past_key_values[0][0].shape[2] + seq_length_with_past = seq_length_with_past + past_key_values_length + + if position_ids is None: + device = input_ids.device if input_ids is not None else inputs_embeds.device + position_ids = torch.arange( + past_key_values_length, seq_length + past_key_values_length, dtype=torch.long, device=device + ) + position_ids = position_ids.unsqueeze(0) + + if inputs_embeds is None: + inputs_embeds = self.tok_embeddings(input_ids) + + if self.config.attn_implementation == 'flash_attention_2': + # 2d mask is passed through the layers + attention_mask = attention_mask if (attention_mask is not None and 0 in attention_mask) else None + else: + if attention_mask is None: + attention_mask = torch.ones( + (batch_size, seq_length_with_past), dtype=torch.bool, device=inputs_embeds.device + ) + attention_mask = self._prepare_decoder_attention_mask( + attention_mask, (batch_size, seq_length), inputs_embeds, past_key_values_length + ) + + # embed positions + hidden_states = inputs_embeds + + if self.gradient_checkpointing and self.training: + if use_cache: + logger.warning_once( + '`use_cache=True` is incompatible with gradient checkpointing. Setting `use_cache=False`...' + ) + use_cache = False + + # decoder layers + all_hidden_states = () if output_hidden_states else None + all_self_attns = () if output_attentions else None + next_decoder_cache = () if use_cache else None + + for idx, decoder_layer in enumerate(self.layers): + if output_hidden_states: + all_hidden_states += (hidden_states,) + + past_key_value = past_key_values[idx] if past_key_values is not None else None + + if self.gradient_checkpointing and self.training: + + def create_custom_forward(module): + def custom_forward(*inputs): + # None for past_key_value + return module(*inputs, output_attentions, None) + + return custom_forward + + layer_outputs = torch.utils.checkpoint.checkpoint( + create_custom_forward(decoder_layer), + hidden_states, + attention_mask, + position_ids, + None, + ) + else: + layer_outputs = decoder_layer( + hidden_states, + attention_mask=attention_mask, + position_ids=position_ids, + past_key_value=past_key_value, + output_attentions=output_attentions, + use_cache=use_cache, + ) + + hidden_states = layer_outputs[0] + + if use_cache: + next_decoder_cache += (layer_outputs[2 if output_attentions else 1],) + + if output_attentions: + all_self_attns += (layer_outputs[1],) + + hidden_states = self.norm(hidden_states) + + # add hidden states from the last decoder layer + if output_hidden_states: + all_hidden_states += (hidden_states,) + + next_cache = next_decoder_cache if use_cache else None + if not return_dict: + return tuple(v for v in [hidden_states, next_cache, all_hidden_states, all_self_attns] if v is not None) + return BaseModelOutputWithPast( + last_hidden_state=hidden_states, + past_key_values=next_cache, + hidden_states=all_hidden_states, + attentions=all_self_attns, + ) + + +# Modified from transformers.model.llama.modeling_llama.LlamaForCausalLM +class InternLM2ForCausalLM(InternLM2PreTrainedModel): + _auto_class = 'AutoModelForCausalLM' + + _tied_weights_keys = ['output.weight'] + + def __init__(self, config): + super().__init__(config) + self.model = InternLM2Model(config) + self.vocab_size = config.vocab_size + self.output = nn.Linear(config.hidden_size, config.vocab_size, bias=False) + + # Initialize weights and apply final processing + self.post_init() + + def get_input_embeddings(self): + return self.model.tok_embeddings + + def set_input_embeddings(self, value): + self.model.tok_embeddings = value + + def get_output_embeddings(self): + return self.output + + def set_output_embeddings(self, new_embeddings): + self.output = new_embeddings + + def set_decoder(self, decoder): + self.model = decoder + + def get_decoder(self): + return self.model + + @add_start_docstrings_to_model_forward(InternLM2_INPUTS_DOCSTRING) + @replace_return_docstrings(output_type=CausalLMOutputWithPast, config_class=_CONFIG_FOR_DOC) + def forward( + self, + input_ids: torch.LongTensor = None, + attention_mask: Optional[torch.Tensor] = None, + position_ids: Optional[torch.LongTensor] = None, + past_key_values: Optional[List[torch.FloatTensor]] = None, + inputs_embeds: Optional[torch.FloatTensor] = None, + labels: Optional[torch.LongTensor] = None, + use_cache: Optional[bool] = None, + output_attentions: Optional[bool] = None, + output_hidden_states: Optional[bool] = None, + return_dict: Optional[bool] = None, + ) -> Union[Tuple, CausalLMOutputWithPast]: + r""" + Args: + labels (`torch.LongTensor` of shape `(batch_size, sequence_length)`, *optional*): + Labels for computing the masked language modeling loss. Indices should either be in `[0, ..., + config.vocab_size]` or -100 (see `input_ids` docstring). Tokens with indices set to `-100` are ignored + (masked), the loss is only computed for the tokens with labels in `[0, ..., config.vocab_size]`. + + Returns: + + Example: + + ```python + >>> from transformers import AutoTokenizer, InternLM2ForCausalLM + + >>> model = InternLM2ForCausalLM.from_pretrained(PATH_TO_CONVERTED_WEIGHTS) + >>> tokenizer = AutoTokenizer.from_pretrained(PATH_TO_CONVERTED_TOKENIZER) + + >>> prompt = "Hey, are you conscious? Can you talk to me?" + >>> inputs = tokenizer(prompt, return_tensors="pt") + + >>> # Generate + >>> generate_ids = model.generate(inputs.input_ids, max_length=30) + >>> tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0] + "Hey, are you conscious? Can you talk to me?\nI'm not conscious, but I can talk to you." + ```""" + + output_attentions = output_attentions if output_attentions is not None else self.config.output_attentions + output_hidden_states = ( + output_hidden_states if output_hidden_states is not None else self.config.output_hidden_states + ) + return_dict = return_dict if return_dict is not None else self.config.use_return_dict + + # decoder outputs consists of (dec_features, layer_state, dec_hidden, dec_attn) + outputs = self.model( + input_ids=input_ids, + attention_mask=attention_mask, + position_ids=position_ids, + past_key_values=past_key_values, + inputs_embeds=inputs_embeds, + use_cache=use_cache, + output_attentions=output_attentions, + output_hidden_states=output_hidden_states, + return_dict=return_dict, + ) + + hidden_states = outputs[0] + logits = self.output(hidden_states) + logits = logits.float() + + loss = None + if labels is not None: + # Shift so that tokens < n predict n + shift_logits = logits[..., :-1, :].contiguous() + shift_labels = labels[..., 1:].contiguous() + # Flatten the tokens + loss_fct = CrossEntropyLoss() + shift_logits = shift_logits.view(-1, self.config.vocab_size) + shift_labels = shift_labels.view(-1) + # Enable model parallelism + shift_labels = shift_labels.to(shift_logits.device) + loss = loss_fct(shift_logits, shift_labels) + + if not return_dict: + output = (logits,) + outputs[1:] + return (loss,) + output if loss is not None else output + + device = input_ids.device if input_ids is not None else inputs_embeds.device + output = CausalLMOutputWithPast( + loss=loss, + logits=logits, + past_key_values=outputs.past_key_values, + hidden_states=outputs.hidden_states, + attentions=outputs.attentions, + ) + output['logits'] = output['logits'].to(device) + return output + + def prepare_inputs_for_generation( + self, input_ids, past_key_values=None, attention_mask=None, inputs_embeds=None, **kwargs + ): + if past_key_values is not None: + past_length = past_key_values[0][0].shape[2] + + # Some generation methods already pass only the last input ID + if input_ids.shape[1] > past_length: + remove_prefix_length = past_length + else: + # Default to old behavior: keep only final ID + remove_prefix_length = input_ids.shape[1] - 1 + + input_ids = input_ids[:, remove_prefix_length:] + + position_ids = kwargs.get('position_ids', None) + if attention_mask is not None and position_ids is None: + # create position_ids on the fly for batch generation + position_ids = attention_mask.long().cumsum(-1) - 1 + position_ids.masked_fill_(attention_mask == 0, 1) + if past_key_values: + position_ids = position_ids[:, -input_ids.shape[1] :] + + # if `inputs_embeds` are passed, we only want to use them in the 1st generation step + if inputs_embeds is not None and past_key_values is None: + model_inputs = {'inputs_embeds': inputs_embeds} + else: + model_inputs = {'input_ids': input_ids} + + model_inputs.update( + { + 'position_ids': position_ids, + 'past_key_values': past_key_values, + 'use_cache': kwargs.get('use_cache'), + 'attention_mask': attention_mask, + } + ) + return model_inputs + + @staticmethod + def _reorder_cache(past_key_values, beam_idx): + reordered_past = () + for layer_past in past_key_values: + reordered_past += ( + tuple(past_state.index_select(0, beam_idx.to(past_state.device)) for past_state in layer_past), + ) + return reordered_past + + def build_inputs(self, tokenizer, query: str, history: List[Tuple[str, str]] = [], meta_instruction=''): + if tokenizer.add_bos_token: + prompt = '' + else: + prompt = tokenizer.bos_token + if meta_instruction: + prompt += f"""<|im_start|>system\n{meta_instruction}<|im_end|>\n""" + for record in history: + prompt += f"""<|im_start|>user\n{record[0]}<|im_end|>\n<|im_start|>assistant\n{record[1]}<|im_end|>\n""" + prompt += f"""<|im_start|>user\n{query}<|im_end|>\n<|im_start|>assistant\n""" + return tokenizer([prompt], return_tensors='pt') + + @torch.no_grad() + def chat( + self, + tokenizer, + query: str, + history: List[Tuple[str, str]] = [], + streamer: Optional[BaseStreamer] = None, + max_new_tokens: int = 1024, + do_sample: bool = True, + temperature: float = 0.8, + top_p: float = 0.8, + meta_instruction: str = 'You are an AI assistant whose name is InternLM (书生·浦语).\n' + '- InternLM (书生·浦语) is a conversational language model that is developed by Shanghai AI Laboratory (上海人工智能实验室). It is designed to be helpful, honest, and harmless.\n' + '- InternLM (书生·浦语) can understand and communicate fluently in the language chosen by the user such as English and 中文.', + **kwargs, + ): + inputs = self.build_inputs(tokenizer, query, history, meta_instruction) + inputs = {k: v.to(self.device) for k, v in inputs.items() if torch.is_tensor(v)} + # also add end-of-assistant token in eos token id to avoid unnecessary generation + eos_token_id = [tokenizer.eos_token_id, tokenizer.convert_tokens_to_ids(['<|im_end|>'])[0]] + outputs = self.generate( + **inputs, + streamer=streamer, + max_new_tokens=max_new_tokens, + do_sample=do_sample, + temperature=temperature, + top_p=top_p, + eos_token_id=eos_token_id, + **kwargs, + ) + outputs = outputs[0].cpu().tolist()[len(inputs['input_ids'][0]) :] + response = tokenizer.decode(outputs, skip_special_tokens=True) + response = response.split('<|im_end|>')[0] + history = history + [(query, response)] + return response, history + + @torch.no_grad() + def stream_chat( + self, + tokenizer, + query: str, + history: List[Tuple[str, str]] = [], + max_new_tokens: int = 1024, + do_sample: bool = True, + temperature: float = 0.8, + top_p: float = 0.8, + **kwargs, + ): + """ + Return a generator in format: (response, history) + Eg. + ('你好，有什么可以帮助您的吗', [('你好', '你好，有什么可以帮助您的吗')]) + ('你好，有什么可以帮助您的吗？', [('你好', '你好，有什么可以帮助您的吗？')]) + """ + if BaseStreamer is None: + raise ModuleNotFoundError( + 'The version of `transformers` is too low. Please make sure ' + 'that you have installed `transformers>=4.28.0`.' + ) + + response_queue = queue.Queue(maxsize=20) + + class ChatStreamer(BaseStreamer): + def __init__(self, tokenizer) -> None: + super().__init__() + self.tokenizer = tokenizer + self.queue = response_queue + self.query = query + self.history = history + self.response = '' + self.cache = [] + self.received_inputs = False + self.queue.put((self.response, history + [(self.query, self.response)])) + + def put(self, value): + if len(value.shape) > 1 and value.shape[0] > 1: + raise ValueError('ChatStreamer only supports batch size 1') + elif len(value.shape) > 1: + value = value[0] + + if not self.received_inputs: + # The first received value is input_ids, ignore here + self.received_inputs = True + return + + self.cache.extend(value.tolist()) + token = self.tokenizer.decode(self.cache, skip_special_tokens=True) + if token.strip() != '<|im_end|>': + self.response = self.response + token + history = self.history + [(self.query, self.response)] + self.queue.put((self.response, history)) + self.cache = [] + else: + self.end() + + def end(self): + self.queue.put(None) + + def stream_producer(): + return self.chat( + tokenizer=tokenizer, + query=query, + streamer=ChatStreamer(tokenizer=tokenizer), + history=history, + max_new_tokens=max_new_tokens, + do_sample=do_sample, + temperature=temperature, + top_p=top_p, + **kwargs, + ) + + def consumer(): + producer = threading.Thread(target=stream_producer) + producer.start() + while True: + res = response_queue.get() + if res is None: + return + yield res + + return consumer() + + +# Copied from transformers.model.llama.modeling_llama.LlamaForSequenceClassification with Llama->InternLM2 +@add_start_docstrings( + """ + The InternLM2 Model transformer with a sequence classification head on top (linear layer). + + [`InternLM2ForSequenceClassification`] uses the last token in order to do the classification, + as other causal models (e.g. GPT-2) do. + + Since it does classification on the last token, it requires to know the position of the last token. If a + `pad_token_id` is defined in the configuration, it finds the last token that is not a padding token in each row. If + no `pad_token_id` is defined, it simply takes the last value in each row of the batch. Since it cannot guess the + padding tokens when `inputs_embeds` are passed instead of `input_ids`, it does the same (take the last value in + each row of the batch). + """, + InternLM2_START_DOCSTRING, +) +class InternLM2ForSequenceClassification(InternLM2PreTrainedModel): + def __init__(self, config): + super().__init__(config) + self.num_labels = config.num_labels + self.model = InternLM2Model(config) + self.score = nn.Linear(config.hidden_size, self.num_labels, bias=False) + + # Initialize weights and apply final processing + self.post_init() + + def get_input_embeddings(self): + return self.model.tok_embeddings + + def set_input_embeddings(self, value): + self.model.tok_embeddings = value + + @add_start_docstrings_to_model_forward(InternLM2_INPUTS_DOCSTRING) + def forward( + self, + input_ids: torch.LongTensor = None, + attention_mask: Optional[torch.Tensor] = None, + position_ids: Optional[torch.LongTensor] = None, + past_key_values: Optional[List[torch.FloatTensor]] = None, + inputs_embeds: Optional[torch.FloatTensor] = None, + labels: Optional[torch.LongTensor] = None, + use_cache: Optional[bool] = None, + output_attentions: Optional[bool] = None, + output_hidden_states: Optional[bool] = None, + return_dict: Optional[bool] = None, + ) -> Union[Tuple, SequenceClassifierOutputWithPast]: + r""" + labels (`torch.LongTensor` of shape `(batch_size,)`, *optional*): + Labels for computing the sequence classification/regression loss. Indices should be in `[0, ..., + config.num_labels - 1]`. If `config.num_labels == 1` a regression loss is computed (Mean-Square loss), If + `config.num_labels > 1` a classification loss is computed (Cross-Entropy). + """ + return_dict = return_dict if return_dict is not None else self.config.use_return_dict + + transformer_outputs = self.model( + input_ids, + attention_mask=attention_mask, + position_ids=position_ids, + past_key_values=past_key_values, + inputs_embeds=inputs_embeds, + use_cache=use_cache, + output_attentions=output_attentions, + output_hidden_states=output_hidden_states, + return_dict=return_dict, + ) + hidden_states = transformer_outputs[0] + logits = self.score(hidden_states) + + if input_ids is not None: + batch_size = input_ids.shape[0] + else: + batch_size = inputs_embeds.shape[0] + + if self.config.pad_token_id is None and batch_size != 1: + raise ValueError('Cannot handle batch sizes > 1 if no padding token is defined.') + if self.config.pad_token_id is None: + sequence_lengths = -1 + else: + if input_ids is not None: + sequence_lengths = (torch.eq(input_ids, self.config.pad_token_id).int().argmax(-1) - 1).to( + logits.device + ) + else: + sequence_lengths = -1 + + pooled_logits = logits[torch.arange(batch_size, device=logits.device), sequence_lengths] + + loss = None + if labels is not None: + labels = labels.to(logits.device) + if self.config.problem_type is None: + if self.num_labels == 1: + self.config.problem_type = 'regression' + elif self.num_labels > 1 and (labels.dtype == torch.long or labels.dtype == torch.int): + self.config.problem_type = 'single_label_classification' + else: + self.config.problem_type = 'multi_label_classification' + + if self.config.problem_type == 'regression': + loss_fct = MSELoss() + if self.num_labels == 1: + loss = loss_fct(pooled_logits.squeeze(), labels.squeeze()) + else: + loss = loss_fct(pooled_logits, labels) + elif self.config.problem_type == 'single_label_classification': + loss_fct = CrossEntropyLoss() + loss = loss_fct(pooled_logits.view(-1, self.num_labels), labels.view(-1)) + elif self.config.problem_type == 'multi_label_classification': + loss_fct = BCEWithLogitsLoss() + loss = loss_fct(pooled_logits, labels) + if not return_dict: + output = (pooled_logits,) + transformer_outputs[1:] + return ((loss,) + output) if loss is not None else output + + return SequenceClassifierOutputWithPast( + loss=loss, + logits=pooled_logits, + past_key_values=transformer_outputs.past_key_values, + hidden_states=transformer_outputs.hidden_states, + attentions=transformer_outputs.attentions, + ) diff --git a/InternVL-main/internvl_chat/work_dirs/internvl_chat_v2_5/mmvet/100/modeling_internvl_chat.py b/InternVL-main/internvl_chat/work_dirs/internvl_chat_v2_5/mmvet/100/modeling_internvl_chat.py new file mode 100644 index 0000000000000000000000000000000000000000..c4014b13f436084268a6ba6d332afcd850c4e82c --- /dev/null +++ b/InternVL-main/internvl_chat/work_dirs/internvl_chat_v2_5/mmvet/100/modeling_internvl_chat.py @@ -0,0 +1,349 @@ +# -------------------------------------------------------- +# InternVL +# Copyright (c) 2024 OpenGVLab +# Licensed under The MIT License [see LICENSE for details] +# -------------------------------------------------------- + +import warnings +from typing import List, Optional, Tuple, Union + +import torch.utils.checkpoint +import transformers +from torch import nn +from torch.nn import CrossEntropyLoss +from transformers import (AutoModel, GenerationConfig, LlamaForCausalLM, + LlamaTokenizer) +from transformers.modeling_outputs import CausalLMOutputWithPast +from transformers.modeling_utils import PreTrainedModel +from transformers.utils import ModelOutput, logging + +from .configuration_internvl_chat import InternVLChatConfig +from .conversation import get_conv_template +from .modeling_intern_vit import InternVisionModel, has_flash_attn +from .modeling_internlm2 import InternLM2ForCausalLM + +logger = logging.get_logger(__name__) + + +def version_cmp(v1, v2, op='eq'): + import operator + + from packaging import version + op_func = getattr(operator, op) + return op_func(version.parse(v1), version.parse(v2)) + + +class InternVLChatModel(PreTrainedModel): + config_class = InternVLChatConfig + main_input_name = 'pixel_values' + base_model_prefix = 'language_model' + _supports_flash_attn_2 = True + _no_split_modules = ['InternVisionModel', 'LlamaDecoderLayer', 'InternLM2DecoderLayer'] + + def __init__(self, config: InternVLChatConfig, vision_model=None, language_model=None, use_flash_attn=True): + super().__init__(config) + + assert version_cmp(transformers.__version__, '4.37.0', 'ge') + image_size = config.force_image_size or config.vision_config.image_size + patch_size = config.vision_config.patch_size + self.patch_size = patch_size + self.select_layer = config.select_layer + self.template = config.template + self.num_image_token = int((image_size // patch_size) ** 2 * (config.downsample_ratio ** 2)) + self.downsample_ratio = config.downsample_ratio + self.ps_version = config.ps_version + use_flash_attn = use_flash_attn if has_flash_attn else False + config.vision_config.use_flash_attn = True if use_flash_attn else False + config.llm_config.attn_implementation = 'flash_attention_2' if use_flash_attn else 'eager' + + logger.info(f'num_image_token: {self.num_image_token}') + logger.info(f'ps_version: {self.ps_version}') + if vision_model is not None: + self.vision_model = vision_model + else: + self.vision_model = InternVisionModel(config.vision_config) + if language_model is not None: + self.language_model = language_model + else: + if config.llm_config.architectures[0] == 'LlamaForCausalLM': + self.language_model = LlamaForCausalLM(config.llm_config) + elif config.llm_config.architectures[0] == 'InternLM2ForCausalLM': + self.language_model = InternLM2ForCausalLM(config.llm_config) + else: + raise NotImplementedError(f'{config.llm_config.architectures[0]} is not implemented.') + + vit_hidden_size = config.vision_config.hidden_size + llm_hidden_size = config.llm_config.hidden_size + + self.mlp1 = nn.Sequential( + nn.LayerNorm(vit_hidden_size * int(1 / self.downsample_ratio) ** 2), + nn.Linear(vit_hidden_size * int(1 / self.downsample_ratio) ** 2, llm_hidden_size), + nn.GELU(), + nn.Linear(llm_hidden_size, llm_hidden_size) + ) + + self.img_context_token_id = None + self.conv_template = get_conv_template(self.template) + self.system_message = self.conv_template.system_message + + def forward( + self, + pixel_values: torch.FloatTensor, + input_ids: torch.LongTensor = None, + attention_mask: Optional[torch.Tensor] = None, + position_ids: Optional[torch.LongTensor] = None, + image_flags: Optional[torch.LongTensor] = None, + past_key_values: Optional[List[torch.FloatTensor]] = None, + labels: Optional[torch.LongTensor] = None, + use_cache: Optional[bool] = None, + output_attentions: Optional[bool] = None, + output_hidden_states: Optional[bool] = None, + return_dict: Optional[bool] = None, + ) -> Union[Tuple, CausalLMOutputWithPast]: + return_dict = return_dict if return_dict is not None else self.config.use_return_dict + + image_flags = image_flags.squeeze(-1) + input_embeds = self.language_model.get_input_embeddings()(input_ids).clone() + + vit_embeds = self.extract_feature(pixel_values) + vit_embeds = vit_embeds[image_flags == 1] + vit_batch_size = pixel_values.shape[0] + + B, N, C = input_embeds.shape + input_embeds = input_embeds.reshape(B * N, C) + + if torch.distributed.is_initialized() and torch.distributed.get_rank() == 0: + print(f'dynamic ViT batch size: {vit_batch_size}, images per sample: {vit_batch_size / B}, dynamic token length: {N}') + + input_ids = input_ids.reshape(B * N) + selected = (input_ids == self.img_context_token_id) + try: + input_embeds[selected] = input_embeds[selected] * 0.0 + vit_embeds.reshape(-1, C) + except Exception as e: + vit_embeds = vit_embeds.reshape(-1, C) + print(f'warning: {e}, input_embeds[selected].shape={input_embeds[selected].shape}, ' + f'vit_embeds.shape={vit_embeds.shape}') + n_token = selected.sum() + input_embeds[selected] = input_embeds[selected] * 0.0 + vit_embeds[:n_token] + + input_embeds = input_embeds.reshape(B, N, C) + + outputs = self.language_model( + inputs_embeds=input_embeds, + attention_mask=attention_mask, + position_ids=position_ids, + past_key_values=past_key_values, + use_cache=use_cache, + output_attentions=output_attentions, + output_hidden_states=output_hidden_states, + return_dict=return_dict, + ) + logits = outputs.logits + + loss = None + if labels is not None: + # Shift so that tokens < n predict n + shift_logits = logits[..., :-1, :].contiguous() + shift_labels = labels[..., 1:].contiguous() + # Flatten the tokens + loss_fct = CrossEntropyLoss() + shift_logits = shift_logits.view(-1, self.language_model.config.vocab_size) + shift_labels = shift_labels.view(-1) + # Enable model parallelism + shift_labels = shift_labels.to(shift_logits.device) + loss = loss_fct(shift_logits, shift_labels) + + if not return_dict: + output = (logits,) + outputs[1:] + return (loss,) + output if loss is not None else output + + return CausalLMOutputWithPast( + loss=loss, + logits=logits, + past_key_values=outputs.past_key_values, + hidden_states=outputs.hidden_states, + attentions=outputs.attentions, + ) + + def pixel_shuffle(self, x, scale_factor=0.5): + n, w, h, c = x.size() + # N, W, H, C --> N, W, H * scale, C // scale + x = x.view(n, w, int(h * scale_factor), int(c / scale_factor)) + # N, W, H * scale, C // scale --> N, H * scale, W, C // scale + x = x.permute(0, 2, 1, 3).contiguous() + # N, H * scale, W, C // scale --> N, H * scale, W * scale, C // (scale ** 2) + x = x.view(n, int(h * scale_factor), int(w * scale_factor), + int(c / (scale_factor * scale_factor))) + if self.ps_version == 'v1': + warnings.warn("In ps_version 'v1', the height and width have not been swapped back, " + 'which results in a transposed image.') + else: + x = x.permute(0, 2, 1, 3).contiguous() + return x + + def extract_feature(self, pixel_values): + if self.select_layer == -1: + vit_embeds = self.vision_model( + pixel_values=pixel_values, + output_hidden_states=False, + return_dict=True).last_hidden_state + else: + vit_embeds = self.vision_model( + pixel_values=pixel_values, + output_hidden_states=True, + return_dict=True).hidden_states[self.select_layer] + vit_embeds = vit_embeds[:, 1:, :] + + h = w = int(vit_embeds.shape[1] ** 0.5) + vit_embeds = vit_embeds.reshape(vit_embeds.shape[0], h, w, -1) + vit_embeds = self.pixel_shuffle(vit_embeds, scale_factor=self.downsample_ratio) + vit_embeds = vit_embeds.reshape(vit_embeds.shape[0], -1, vit_embeds.shape[-1]) + vit_embeds = self.mlp1(vit_embeds) + return vit_embeds + + def batch_chat(self, tokenizer, pixel_values, questions, generation_config, num_patches_list=None, + history=None, return_history=False, IMG_START_TOKEN='', IMG_END_TOKEN='', + IMG_CONTEXT_TOKEN='', verbose=False, image_counts=None): + if history is not None or return_history: + print('Now multi-turn chat is not supported in batch_chat.') + raise NotImplementedError + + if image_counts is not None: + num_patches_list = image_counts + print('Warning: `image_counts` is deprecated. Please use `num_patches_list` instead.') + + img_context_token_id = tokenizer.convert_tokens_to_ids(IMG_CONTEXT_TOKEN) + self.img_context_token_id = img_context_token_id + + if verbose and pixel_values is not None: + image_bs = pixel_values.shape[0] + print(f'dynamic ViT batch size: {image_bs}') + + queries = [] + for idx, num_patches in enumerate(num_patches_list): + question = questions[idx] + if pixel_values is not None and '' not in question: + question = '\n' + question + template = get_conv_template(self.template) + template.system_message = self.system_message + template.append_message(template.roles[0], question) + template.append_message(template.roles[1], None) + query = template.get_prompt() + + image_tokens = IMG_START_TOKEN + IMG_CONTEXT_TOKEN * self.num_image_token * num_patches + IMG_END_TOKEN + query = query.replace('', image_tokens, 1) + queries.append(query) + + tokenizer.padding_side = 'left' + model_inputs = tokenizer(queries, return_tensors='pt', padding=True) + input_ids = model_inputs['input_ids'].to(self.device) + attention_mask = model_inputs['attention_mask'].to(self.device) + eos_token_id = tokenizer.convert_tokens_to_ids(template.sep.strip()) + generation_config['eos_token_id'] = eos_token_id + generation_output = self.generate( + pixel_values=pixel_values, + input_ids=input_ids, + attention_mask=attention_mask, + **generation_config + ) + responses = tokenizer.batch_decode(generation_output, skip_special_tokens=True) + responses = [response.split(template.sep.strip())[0].strip() for response in responses] + return responses + + def chat(self, tokenizer, pixel_values, question, generation_config, history=None, return_history=False, + num_patches_list=None, IMG_START_TOKEN='', IMG_END_TOKEN='', IMG_CONTEXT_TOKEN='', + verbose=False): + + if history is None and pixel_values is not None and '' not in question: + question = '\n' + question + + if num_patches_list is None: + num_patches_list = [pixel_values.shape[0]] if pixel_values is not None else [] + assert pixel_values is None or len(pixel_values) == sum(num_patches_list) + + img_context_token_id = tokenizer.convert_tokens_to_ids(IMG_CONTEXT_TOKEN) + self.img_context_token_id = img_context_token_id + + template = get_conv_template(self.template) + template.system_message = self.system_message + eos_token_id = tokenizer.convert_tokens_to_ids(template.sep.strip()) + + history = [] if history is None else history + for (old_question, old_answer) in history: + template.append_message(template.roles[0], old_question) + template.append_message(template.roles[1], old_answer) + template.append_message(template.roles[0], question) + template.append_message(template.roles[1], None) + query = template.get_prompt() + + if verbose and pixel_values is not None: + image_bs = pixel_values.shape[0] + print(f'dynamic ViT batch size: {image_bs}') + + for num_patches in num_patches_list: + image_tokens = IMG_START_TOKEN + IMG_CONTEXT_TOKEN * self.num_image_token * num_patches + IMG_END_TOKEN + query = query.replace('', image_tokens, 1) + + model_inputs = tokenizer(query, return_tensors='pt') + input_ids = model_inputs['input_ids'].to(self.device) + attention_mask = model_inputs['attention_mask'].to(self.device) + generation_config['eos_token_id'] = eos_token_id + generation_output = self.generate( + pixel_values=pixel_values, + input_ids=input_ids, + attention_mask=attention_mask, + **generation_config + ) + response = tokenizer.batch_decode(generation_output, skip_special_tokens=True)[0] + response = response.split(template.sep.strip())[0].strip() + history.append((question, response)) + if return_history: + return response, history + else: + query_to_print = query.replace(IMG_CONTEXT_TOKEN, '') + query_to_print = query_to_print.replace(f'{IMG_START_TOKEN}{IMG_END_TOKEN}', '') + if verbose: + print(query_to_print, response) + return response + + @torch.no_grad() + def generate( + self, + pixel_values: Optional[torch.FloatTensor] = None, + input_ids: Optional[torch.FloatTensor] = None, + attention_mask: Optional[torch.LongTensor] = None, + visual_features: Optional[torch.FloatTensor] = None, + generation_config: Optional[GenerationConfig] = None, + output_hidden_states: Optional[bool] = None, + **generate_kwargs, + ) -> torch.LongTensor: + + assert self.img_context_token_id is not None + if pixel_values is not None: + if visual_features is not None: + vit_embeds = visual_features + else: + vit_embeds = self.extract_feature(pixel_values) + input_embeds = self.language_model.get_input_embeddings()(input_ids) + B, N, C = input_embeds.shape + input_embeds = input_embeds.reshape(B * N, C) + + input_ids = input_ids.reshape(B * N) + selected = (input_ids == self.img_context_token_id) + assert selected.sum() != 0 + input_embeds[selected] = vit_embeds.reshape(-1, C).to(input_embeds.device) + + input_embeds = input_embeds.reshape(B, N, C) + else: + input_embeds = self.language_model.get_input_embeddings()(input_ids) + + outputs = self.language_model.generate( + inputs_embeds=input_embeds, + attention_mask=attention_mask, + generation_config=generation_config, + output_hidden_states=output_hidden_states, + use_cache=True, + **generate_kwargs, + ) + + return outputs diff --git a/InternVL-main/internvl_chat/work_dirs/internvl_chat_v2_5/mmvet/100/special_tokens_map.json b/InternVL-main/internvl_chat/work_dirs/internvl_chat_v2_5/mmvet/100/special_tokens_map.json new file mode 100644 index 0000000000000000000000000000000000000000..cbf34a50d27c43ed8d1e2823b800b4e6f66e637a --- /dev/null +++ b/InternVL-main/internvl_chat/work_dirs/internvl_chat_v2_5/mmvet/100/special_tokens_map.json @@ -0,0 +1,47 @@ +{ + "additional_special_tokens": [ + "<|im_start|>", + "<|im_end|>", + "<|action_start|>", + "<|action_end|>", + "<|interpreter|>", + "<|plugin|>", + "", + "", + "", + "", + "", + "", + "", + "", + "" + ], + "bos_token": { + "content": "", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false + }, + "eos_token": { + "content": "", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false + }, + "pad_token": { + "content": "", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false + }, + "unk_token": { + "content": "", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false + } +} diff --git a/InternVL-main/internvl_chat/work_dirs/internvl_chat_v2_5/mmvet/100/tokenization_internlm2.py b/InternVL-main/internvl_chat/work_dirs/internvl_chat_v2_5/mmvet/100/tokenization_internlm2.py new file mode 100644 index 0000000000000000000000000000000000000000..1be581da37ef678de65f2737493fc0ed7160446e --- /dev/null +++ b/InternVL-main/internvl_chat/work_dirs/internvl_chat_v2_5/mmvet/100/tokenization_internlm2.py @@ -0,0 +1,235 @@ +# Copyright (c) The InternLM team and The HuggingFace Inc. team. All rights reserved. +# +# This code is based on transformers/src/transformers/models/llama/tokenization_llama.py +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +"""Tokenization classes for InternLM.""" +import os +from shutil import copyfile +from typing import Any, Dict, List, Optional, Tuple + +import sentencepiece as spm +from transformers.tokenization_utils import PreTrainedTokenizer +from transformers.utils import logging + +logger = logging.get_logger(__name__) + +VOCAB_FILES_NAMES = {'vocab_file': './tokenizer.model'} + +PRETRAINED_VOCAB_FILES_MAP = {} + + +# Modified from transformers.model.llama.tokenization_llama.LlamaTokenizer +class InternLM2Tokenizer(PreTrainedTokenizer): + """ + Construct a InternLM2 tokenizer. Based on byte-level Byte-Pair-Encoding. + + Args: + vocab_file (`str`): + Path to the vocabulary file. + """ + + vocab_files_names = VOCAB_FILES_NAMES + pretrained_vocab_files_map = PRETRAINED_VOCAB_FILES_MAP + model_input_names = ['input_ids', 'attention_mask'] + _auto_class = 'AutoTokenizer' + + def __init__( + self, + vocab_file, + unk_token='', + bos_token='', + eos_token='', + pad_token='', + sp_model_kwargs: Optional[Dict[str, Any]] = None, + add_bos_token=True, + add_eos_token=False, + decode_with_prefix_space=False, + clean_up_tokenization_spaces=False, + **kwargs, + ): + self.sp_model_kwargs = {} if sp_model_kwargs is None else sp_model_kwargs + self.vocab_file = vocab_file + self.add_bos_token = add_bos_token + self.add_eos_token = add_eos_token + self.decode_with_prefix_space = decode_with_prefix_space + self.sp_model = spm.SentencePieceProcessor(**self.sp_model_kwargs) + self.sp_model.Load(vocab_file) + self._no_prefix_space_tokens = None + super().__init__( + bos_token=bos_token, + eos_token=eos_token, + unk_token=unk_token, + pad_token=pad_token, + clean_up_tokenization_spaces=clean_up_tokenization_spaces, + **kwargs, + ) + + @property + def no_prefix_space_tokens(self): + if self._no_prefix_space_tokens is None: + vocab = self.convert_ids_to_tokens(list(range(self.vocab_size))) + self._no_prefix_space_tokens = {i for i, tok in enumerate(vocab) if not tok.startswith('▁')} + return self._no_prefix_space_tokens + + @property + def vocab_size(self): + """Returns vocab size""" + return self.sp_model.get_piece_size() + + @property + def bos_token_id(self) -> Optional[int]: + return self.sp_model.bos_id() + + @property + def eos_token_id(self) -> Optional[int]: + return self.sp_model.eos_id() + + def get_vocab(self): + """Returns vocab as a dict""" + vocab = {self.convert_ids_to_tokens(i): i for i in range(self.vocab_size)} + vocab.update(self.added_tokens_encoder) + return vocab + + def _tokenize(self, text): + """Returns a tokenized string.""" + return self.sp_model.encode(text, out_type=str) + + def _convert_token_to_id(self, token): + """Converts a token (str) in an id using the vocab.""" + return self.sp_model.piece_to_id(token) + + def _convert_id_to_token(self, index): + """Converts an index (integer) in a token (str) using the vocab.""" + token = self.sp_model.IdToPiece(index) + return token + + def _maybe_add_prefix_space(self, tokens, decoded): + if tokens and tokens[0] not in self.no_prefix_space_tokens: + return ' ' + decoded + else: + return decoded + + def convert_tokens_to_string(self, tokens): + """Converts a sequence of tokens (string) in a single string.""" + current_sub_tokens = [] + out_string = '' + prev_is_special = False + for token in tokens: + # make sure that special tokens are not decoded using sentencepiece model + if token in self.all_special_tokens: + if not prev_is_special: + out_string += ' ' + out_string += self.sp_model.decode(current_sub_tokens) + token + prev_is_special = True + current_sub_tokens = [] + else: + current_sub_tokens.append(token) + prev_is_special = False + out_string += self.sp_model.decode(current_sub_tokens) + out_string = self.clean_up_tokenization(out_string) + out_string = self._maybe_add_prefix_space(tokens=tokens, decoded=out_string) + return out_string[1:] + + def save_vocabulary(self, save_directory, filename_prefix: Optional[str] = None) -> Tuple[str]: + """ + Save the vocabulary and special tokens file to a directory. + + Args: + save_directory (`str`): + The directory in which to save the vocabulary. + + Returns: + `Tuple(str)`: Paths to the files saved. + """ + if not os.path.isdir(save_directory): + logger.error(f'Vocabulary path ({save_directory}) should be a directory') + return + out_vocab_file = os.path.join( + save_directory, (filename_prefix + '-' if filename_prefix else '') + VOCAB_FILES_NAMES['vocab_file'] + ) + + if os.path.abspath(self.vocab_file) != os.path.abspath(out_vocab_file) and os.path.isfile(self.vocab_file): + copyfile(self.vocab_file, out_vocab_file) + elif not os.path.isfile(self.vocab_file): + with open(out_vocab_file, 'wb') as fi: + content_spiece_model = self.sp_model.serialized_model_proto() + fi.write(content_spiece_model) + + return (out_vocab_file,) + + def build_inputs_with_special_tokens(self, token_ids_0, token_ids_1=None): + if self.add_bos_token: + bos_token_ids = [self.bos_token_id] + else: + bos_token_ids = [] + + output = bos_token_ids + token_ids_0 + + if token_ids_1 is not None: + output = output + token_ids_1 + + if self.add_eos_token: + output = output + [self.eos_token_id] + + return output + + def get_special_tokens_mask( + self, token_ids_0: List[int], token_ids_1: Optional[List[int]] = None, already_has_special_tokens: bool = False + ) -> List[int]: + """ + Retrieve sequence ids from a token list that has no special tokens added. This method is called when adding + special tokens using the tokenizer `prepare_for_model` method. + + Args: + token_ids_0 (`List[int]`): + List of IDs. + token_ids_1 (`List[int]`, *optional*): + Optional second list of IDs for sequence pairs. + already_has_special_tokens (`bool`, *optional*, defaults to `False`): + Whether or not the token list is already formatted with special tokens for the model. + + Returns: + `List[int]`: A list of integers in the range [0, 1]: 1 for a special token, 0 for a sequence token. + """ + if already_has_special_tokens: + return super().get_special_tokens_mask( + token_ids_0=token_ids_0, token_ids_1=token_ids_1, already_has_special_tokens=True + ) + + if token_ids_1 is None: + return [1] + ([0] * len(token_ids_0)) + [1] + return [1] + ([0] * len(token_ids_0)) + [1, 1] + ([0] * len(token_ids_1)) + [1] + + def create_token_type_ids_from_sequences( + self, token_ids_0: List[int], token_ids_1: Optional[List[int]] = None + ) -> List[int]: + """ + Create a mask from the two sequences passed to be used in a sequence-pair classification task. T5 does not make + use of token type ids, therefore a list of zeros is returned. + + Args: + token_ids_0 (`List[int]`): + List of IDs. + token_ids_1 (`List[int]`, *optional*): + Optional second list of IDs for sequence pairs. + + Returns: + `List[int]`: List of zeros. + """ + eos = [self.eos_token_id] + + if token_ids_1 is None: + return len(token_ids_0 + eos) * [0] + return len(token_ids_0 + eos + token_ids_1 + eos) * [0] diff --git a/InternVL-main/internvl_chat/work_dirs/internvl_chat_v2_5/mmvet/100/tokenization_internlm2_fast.py b/InternVL-main/internvl_chat/work_dirs/internvl_chat_v2_5/mmvet/100/tokenization_internlm2_fast.py new file mode 100644 index 0000000000000000000000000000000000000000..aa0fccbd0f1d029d79e19821f2edcb01b594537c --- /dev/null +++ b/InternVL-main/internvl_chat/work_dirs/internvl_chat_v2_5/mmvet/100/tokenization_internlm2_fast.py @@ -0,0 +1,211 @@ +# Copyright (c) The InternLM team and The HuggingFace Inc. team. All rights reserved. +# +# This code is based on transformers/src/transformers/models/llama/tokenization_llama_fast.py +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +"""Tokenization Fast class for InternLM.""" +import os +from shutil import copyfile +from typing import Any, Dict, Optional, Tuple + +from tokenizers import Tokenizer, decoders, normalizers, processors +from tokenizers.models import BPE +from transformers.convert_slow_tokenizer import (SLOW_TO_FAST_CONVERTERS, + SentencePieceExtractor, + SpmConverter) +from transformers.tokenization_utils_fast import PreTrainedTokenizerFast +from transformers.utils import logging + +from .tokenization_internlm2 import InternLM2Tokenizer + +logger = logging.get_logger(__name__) + +VOCAB_FILES_NAMES = {'vocab_file': './tokenizer.model'} + + +# Modified from transformers.convert_slow_tokenizer.LlamaConverter +class InternLM2Converter(SpmConverter): + handle_byte_fallback = True + + def vocab(self, proto): + vocab = [ + ('', 0.0), + ('', 0.0), + ('', 0.0), + ] + vocab += [(piece.piece, piece.score) for piece in proto.pieces[3:]] + return vocab + + def unk_id(self, proto): + unk_id = 0 + return unk_id + + def decoder(self, replacement, add_prefix_space): + return decoders.Sequence( + [ + decoders.Replace('▁', ' '), + decoders.ByteFallback(), + decoders.Fuse(), + decoders.Strip(content=' ', left=1), + ] + ) + + def tokenizer(self, proto): + model_type = proto.trainer_spec.model_type + vocab_scores = self.vocab(proto) + # special tokens + added_tokens = self.original_tokenizer.added_tokens_decoder + for i in range(len(vocab_scores)): + piece, score = vocab_scores[i] + if i in added_tokens: + vocab_scores[i] = (added_tokens[i].content, score) + if model_type == 1: + raise RuntimeError('InternLM2 is supposed to be a BPE model!') + + elif model_type == 2: + _, merges = SentencePieceExtractor(self.original_tokenizer.vocab_file).extract(vocab_scores) + bpe_vocab = {word: i for i, (word, _score) in enumerate(vocab_scores)} + tokenizer = Tokenizer( + BPE(bpe_vocab, merges, unk_token=proto.trainer_spec.unk_piece, fuse_unk=True, byte_fallback=True) + ) + tokenizer.add_special_tokens( + [ added_token for index, added_token in added_tokens.items()] + ) + else: + raise Exception( + "You're trying to run a `Unigram` model but you're file was trained with a different algorithm" + ) + + return tokenizer + + def normalizer(self, proto): + normalizers_list = [] + if proto.normalizer_spec.add_dummy_prefix: + normalizers_list.append(normalizers.Prepend(prepend='▁')) + normalizers_list.append(normalizers.Replace(pattern=' ', content='▁')) + return normalizers.Sequence(normalizers_list) + + def pre_tokenizer(self, replacement, add_prefix_space): + return None + + +SLOW_TO_FAST_CONVERTERS['InternLM2Tokenizer'] = InternLM2Converter + + +# Modified from transformers.model.llama.tokenization_llama_fast.LlamaTokenizerFast -> InternLM2TokenizerFast +class InternLM2TokenizerFast(PreTrainedTokenizerFast): + vocab_files_names = VOCAB_FILES_NAMES + slow_tokenizer_class = InternLM2Tokenizer + padding_side = 'left' + model_input_names = ['input_ids', 'attention_mask'] + _auto_class = 'AutoTokenizer' + + def __init__( + self, + vocab_file, + unk_token='', + bos_token='', + eos_token='', + pad_token='', + sp_model_kwargs: Optional[Dict[str, Any]] = None, + add_bos_token=True, + add_eos_token=False, + decode_with_prefix_space=False, + clean_up_tokenization_spaces=False, + **kwargs, + ): + super().__init__( + vocab_file=vocab_file, + unk_token=unk_token, + bos_token=bos_token, + eos_token=eos_token, + pad_token=pad_token, + sp_model_kwargs=sp_model_kwargs, + add_bos_token=add_bos_token, + add_eos_token=add_eos_token, + decode_with_prefix_space=decode_with_prefix_space, + clean_up_tokenization_spaces=clean_up_tokenization_spaces, + **kwargs, + ) + self._add_bos_token = add_bos_token + self._add_eos_token = add_eos_token + self.update_post_processor() + self.vocab_file = vocab_file + + @property + def can_save_slow_tokenizer(self) -> bool: + return os.path.isfile(self.vocab_file) if self.vocab_file else False + + def update_post_processor(self): + """ + Updates the underlying post processor with the current `bos_token` and `eos_token`. + """ + bos = self.bos_token + bos_token_id = self.bos_token_id + if bos is None and self.add_bos_token: + raise ValueError('add_bos_token = True but bos_token = None') + + eos = self.eos_token + eos_token_id = self.eos_token_id + if eos is None and self.add_eos_token: + raise ValueError('add_eos_token = True but eos_token = None') + + single = f"{(bos+':0 ') if self.add_bos_token else ''}$A:0{(' '+eos+':0') if self.add_eos_token else ''}" + pair = f"{single}{(' '+bos+':1') if self.add_bos_token else ''} $B:1{(' '+eos+':1') if self.add_eos_token else ''}" + + special_tokens = [] + if self.add_bos_token: + special_tokens.append((bos, bos_token_id)) + if self.add_eos_token: + special_tokens.append((eos, eos_token_id)) + self._tokenizer.post_processor = processors.TemplateProcessing( + single=single, pair=pair, special_tokens=special_tokens + ) + + @property + def add_eos_token(self): + return self._add_eos_token + + @property + def add_bos_token(self): + return self._add_bos_token + + @add_eos_token.setter + def add_eos_token(self, value): + self._add_eos_token = value + self.update_post_processor() + + @add_bos_token.setter + def add_bos_token(self, value): + self._add_bos_token = value + self.update_post_processor() + + def save_vocabulary(self, save_directory: str, filename_prefix: Optional[str] = None) -> Tuple[str]: + if not self.can_save_slow_tokenizer: + raise ValueError( + 'Your fast tokenizer does not have the necessary information to save the vocabulary for a slow ' + 'tokenizer.' + ) + + if not os.path.isdir(save_directory): + logger.error(f'Vocabulary path ({save_directory}) should be a directory') + return + out_vocab_file = os.path.join( + save_directory, (filename_prefix + '-' if filename_prefix else '') + VOCAB_FILES_NAMES['vocab_file'] + ) + + if os.path.abspath(self.vocab_file) != os.path.abspath(out_vocab_file): + copyfile(self.vocab_file, out_vocab_file) + + return (out_vocab_file,) diff --git a/InternVL-main/internvl_chat/work_dirs/internvl_chat_v2_5/mmvet/100/tokenizer_config.json b/InternVL-main/internvl_chat/work_dirs/internvl_chat_v2_5/mmvet/100/tokenizer_config.json new file mode 100644 index 0000000000000000000000000000000000000000..1f32946df0f56d92ddbc1df79cabb4477b622480 --- /dev/null +++ b/InternVL-main/internvl_chat/work_dirs/internvl_chat_v2_5/mmvet/100/tokenizer_config.json @@ -0,0 +1,179 @@ +{ + "added_tokens_decoder": { + "0": { + "content": "", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "1": { + "content": "", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "2": { + "content": "", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "92538": { + "content": "<|plugin|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "92539": { + "content": "<|interpreter|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "92540": { + "content": "<|action_end|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "92541": { + "content": "<|action_start|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "92542": { + "content": "<|im_end|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "92543": { + "content": "<|im_start|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "92544": { + "content": "", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "92545": { + "content": "", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "92546": { + "content": "", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "92547": { + "content": "", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "92548": { + "content": "", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "92549": { + "content": "", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "92550": { + "content": "", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "92551": { + "content": "", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "92552": { + "content": "", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + } + }, + "additional_special_tokens": [ + "<|im_start|>", + "<|im_end|>", + "<|action_start|>", + "<|action_end|>", + "<|interpreter|>", + "<|plugin|>", + "", + "", + "", + "", + "", + "", + "", + "", + "" + ], + "auto_map": { + "AutoTokenizer": [ + "tokenization_internlm2.InternLM2Tokenizer", + null + ] + }, + "bos_token": "", + "chat_template": "{{ bos_token }}{% for message in messages %}{{'<|im_start|>' + message['role'] + '\n' + message['content'] + '<|im_end|>' + '\n'}}{% endfor %}{% if add_generation_prompt %}{{ '<|im_start|>assistant\n' }}{% endif %}", + "clean_up_tokenization_spaces": false, + "eos_token": "", + "model_max_length": 8192, + "pad_token": "", + "tokenizer_class": "InternLM2Tokenizer", + "unk_token": "" +} diff --git a/InternVL-main/internvl_chat/work_dirs/internvl_chat_v2_5/mmvet/200/added_tokens.json b/InternVL-main/internvl_chat/work_dirs/internvl_chat_v2_5/mmvet/200/added_tokens.json new file mode 100644 index 0000000000000000000000000000000000000000..35f5893c8e29d6102945a953529819a2d56c62a9 --- /dev/null +++ b/InternVL-main/internvl_chat/work_dirs/internvl_chat_v2_5/mmvet/200/added_tokens.json @@ -0,0 +1,11 @@ +{ + "": 92552, + "": 92545, + "": 92548, + "": 92550, + "": 92546, + "": 92551, + "": 92544, + "": 92547, + "": 92549 +} diff --git a/InternVL-main/internvl_chat/work_dirs/internvl_chat_v2_5/mmvet/200/config.json b/InternVL-main/internvl_chat/work_dirs/internvl_chat_v2_5/mmvet/200/config.json new file mode 100644 index 0000000000000000000000000000000000000000..8af9ae1bdee0c6804bbe7fcd93c34e0aa9912890 --- /dev/null +++ b/InternVL-main/internvl_chat/work_dirs/internvl_chat_v2_5/mmvet/200/config.json @@ -0,0 +1,204 @@ +{ + "_commit_hash": null, + "_name_or_path": "/home1/gmh/InternVL-main/internvl_chat/work_dirs/internvl_chat_v2_5/mmvet/checkpoint-200", + "architectures": [ + "InternVLChatModel" + ], + "auto_map": { + "AutoConfig": "configuration_internvl_chat.InternVLChatConfig", + "AutoModel": "modeling_internvl_chat.InternVLChatModel", + "AutoModelForCausalLM": "modeling_internvl_chat.InternVLChatModel" + }, + "downsample_ratio": 0.5, + "dynamic_image_size": true, + "force_image_size": 448, + "hidden_size": 2048, + "llm_config": { + "_name_or_path": "internlm/internlm2_5-1_8b-chat", + "add_cross_attention": false, + "architectures": [ + "InternLM2ForCausalLM" + ], + "attn_implementation": "flash_attention_2", + "auto_map": { + "AutoConfig": "configuration_internlm2.InternLM2Config", + "AutoModel": "modeling_internlm2.InternLM2ForCausalLM", + "AutoModelForCausalLM": "modeling_internlm2.InternLM2ForCausalLM", + "AutoModelForSequenceClassification": "modeling_internlm2.InternLM2ForSequenceClassification" + }, + "bad_words_ids": null, + "begin_suppress_tokens": null, + "bias": false, + "bos_token_id": 1, + "chunk_size_feed_forward": 0, + "cross_attention_hidden_size": null, + "decoder_start_token_id": null, + "diversity_penalty": 0.0, + "do_sample": false, + "early_stopping": false, + "encoder_no_repeat_ngram_size": 0, + "eos_token_id": 2, + "exponential_decay_length_penalty": null, + "finetuning_task": null, + "forced_bos_token_id": null, + "forced_eos_token_id": null, + "hidden_act": "silu", + "hidden_size": 2048, + "id2label": { + "0": "LABEL_0", + "1": "LABEL_1" + }, + "initializer_range": 0.02, + "intermediate_size": 8192, + "is_decoder": false, + "is_encoder_decoder": false, + "label2id": { + "LABEL_0": 0, + "LABEL_1": 1 + }, + "length_penalty": 1.0, + "max_length": 20, + "max_position_embeddings": 32768, + "min_length": 0, + "model_type": "internlm2", + "no_repeat_ngram_size": 0, + "num_attention_heads": 16, + "num_beam_groups": 1, + "num_beams": 1, + "num_hidden_layers": 24, + "num_key_value_heads": 8, + "num_return_sequences": 1, + "output_attentions": false, + "output_hidden_states": false, + "output_scores": false, + "pad_token_id": 2, + "prefix": null, + "pretraining_tp": 1, + "problem_type": null, + "pruned_heads": {}, + "remove_invalid_values": false, + "repetition_penalty": 1.0, + "return_dict": true, + "return_dict_in_generate": false, + "rms_norm_eps": 1e-05, + "rope_scaling": { + "factor": 2.0, + "type": "dynamic" + }, + "rope_theta": 1000000, + "sep_token_id": null, + "suppress_tokens": null, + "task_specific_params": null, + "temperature": 1.0, + "tf_legacy_loss": false, + "tie_encoder_decoder": false, + "tie_word_embeddings": false, + "tokenizer_class": null, + "top_k": 50, + "top_p": 1.0, + "torch_dtype": "bfloat16", + "torchscript": false, + "transformers_version": "4.43.2", + "typical_p": 1.0, + "use_bfloat16": true, + "use_cache": false, + "vocab_size": 92553 + }, + "max_dynamic_patch": 6, + "min_dynamic_patch": 1, + "model_type": "internvl_chat", + "pad2square": false, + "ps_version": "v2", + "select_layer": -1, + "template": "internvl2_5", + "tie_word_embeddings": false, + "torch_dtype": "bfloat16", + "transformers_version": null, + "use_backbone_lora": 0, + "use_llm_lora": 0, + "use_thumbnail": true, + "vision_config": { + "_name_or_path": "", + "add_cross_attention": false, + "architectures": [ + "InternVisionModel" + ], + "attention_dropout": 0.0, + "bad_words_ids": null, + "begin_suppress_tokens": null, + "bos_token_id": null, + "chunk_size_feed_forward": 0, + "cross_attention_hidden_size": null, + "decoder_start_token_id": null, + "diversity_penalty": 0.0, + "do_sample": false, + "drop_path_rate": 0.0, + "dropout": 0.0, + "early_stopping": false, + "encoder_no_repeat_ngram_size": 0, + "eos_token_id": null, + "exponential_decay_length_penalty": null, + "finetuning_task": null, + "forced_bos_token_id": null, + "forced_eos_token_id": null, + "hidden_act": "gelu", + "hidden_size": 1024, + "id2label": { + "0": "LABEL_0", + "1": "LABEL_1" + }, + "image_size": 448, + "initializer_factor": 1.0, + "initializer_range": 0.02, + "intermediate_size": 4096, + "is_decoder": false, + "is_encoder_decoder": false, + "label2id": { + "LABEL_0": 0, + "LABEL_1": 1 + }, + "layer_norm_eps": 1e-06, + "length_penalty": 1.0, + "max_length": 20, + "min_length": 0, + "model_type": "intern_vit_6b", + "no_repeat_ngram_size": 0, + "norm_type": "layer_norm", + "num_attention_heads": 16, + "num_beam_groups": 1, + "num_beams": 1, + "num_channels": 3, + "num_hidden_layers": 24, + "num_return_sequences": 1, + "output_attentions": false, + "output_hidden_states": false, + "output_scores": false, + "pad_token_id": null, + "patch_size": 14, + "prefix": null, + "problem_type": null, + "pruned_heads": {}, + "qk_normalization": false, + "qkv_bias": true, + "remove_invalid_values": false, + "repetition_penalty": 1.0, + "return_dict": true, + "return_dict_in_generate": false, + "sep_token_id": null, + "suppress_tokens": null, + "task_specific_params": null, + "temperature": 1.0, + "tf_legacy_loss": false, + "tie_encoder_decoder": false, + "tie_word_embeddings": true, + "tokenizer_class": null, + "top_k": 50, + "top_p": 1.0, + "torch_dtype": "bfloat16", + "torchscript": false, + "transformers_version": "4.43.2", + "typical_p": 1.0, + "use_bfloat16": true, + "use_flash_attn": true + } +} diff --git a/InternVL-main/internvl_chat/work_dirs/internvl_chat_v2_5/mmvet/200/configuration_intern_vit.py b/InternVL-main/internvl_chat/work_dirs/internvl_chat_v2_5/mmvet/200/configuration_intern_vit.py new file mode 100644 index 0000000000000000000000000000000000000000..7e630c456eb9cf350e55bf850c3ff72f445a7e17 --- /dev/null +++ b/InternVL-main/internvl_chat/work_dirs/internvl_chat_v2_5/mmvet/200/configuration_intern_vit.py @@ -0,0 +1,120 @@ +# -------------------------------------------------------- +# InternVL +# Copyright (c) 2024 OpenGVLab +# Licensed under The MIT License [see LICENSE for details] +# -------------------------------------------------------- + +import os +from typing import Union + +from transformers.configuration_utils import PretrainedConfig +from transformers.utils import logging + +logger = logging.get_logger(__name__) + + +class InternVisionConfig(PretrainedConfig): + r""" + This is the configuration class to store the configuration of a [`InternVisionModel`]. It is used to + instantiate a vision encoder according to the specified arguments, defining the model architecture. + + Configuration objects inherit from [`PretrainedConfig`] and can be used to control the model outputs. Read the + documentation from [`PretrainedConfig`] for more information. + + Args: + num_channels (`int`, *optional*, defaults to 3): + Number of color channels in the input images (e.g., 3 for RGB). + patch_size (`int`, *optional*, defaults to 14): + The size (resolution) of each patch. + image_size (`int`, *optional*, defaults to 224): + The size (resolution) of each image. + qkv_bias (`bool`, *optional*, defaults to `False`): + Whether to add a bias to the queries and values in the self-attention layers. + hidden_size (`int`, *optional*, defaults to 3200): + Dimensionality of the encoder layers and the pooler layer. + num_attention_heads (`int`, *optional*, defaults to 25): + Number of attention heads for each attention layer in the Transformer encoder. + intermediate_size (`int`, *optional*, defaults to 12800): + Dimensionality of the "intermediate" (i.e., feed-forward) layer in the Transformer encoder. + qk_normalization (`bool`, *optional*, defaults to `True`): + Whether to normalize the queries and keys in the self-attention layers. + num_hidden_layers (`int`, *optional*, defaults to 48): + Number of hidden layers in the Transformer encoder. + use_flash_attn (`bool`, *optional*, defaults to `True`): + Whether to use flash attention mechanism. + hidden_act (`str` or `function`, *optional*, defaults to `"gelu"`): + The non-linear activation function (function or string) in the encoder and pooler. If string, `"gelu"`, + `"relu"`, `"selu"` and `"gelu_new"` ``"gelu"` are supported. + layer_norm_eps (`float`, *optional*, defaults to 1e-6): + The epsilon used by the layer normalization layers. + dropout (`float`, *optional*, defaults to 0.0): + The dropout probability for all fully connected layers in the embeddings, encoder, and pooler. + drop_path_rate (`float`, *optional*, defaults to 0.0): + Dropout rate for stochastic depth. + attention_dropout (`float`, *optional*, defaults to 0.0): + The dropout ratio for the attention probabilities. + initializer_range (`float`, *optional*, defaults to 0.02): + The standard deviation of the truncated_normal_initializer for initializing all weight matrices. + initializer_factor (`float`, *optional*, defaults to 0.1): + A factor for layer scale. + """ + + model_type = 'intern_vit_6b' + + def __init__( + self, + num_channels=3, + patch_size=14, + image_size=224, + qkv_bias=False, + hidden_size=3200, + num_attention_heads=25, + intermediate_size=12800, + qk_normalization=True, + num_hidden_layers=48, + use_flash_attn=True, + hidden_act='gelu', + norm_type='rms_norm', + layer_norm_eps=1e-6, + dropout=0.0, + drop_path_rate=0.0, + attention_dropout=0.0, + initializer_range=0.02, + initializer_factor=0.1, + **kwargs, + ): + super().__init__(**kwargs) + + self.hidden_size = hidden_size + self.intermediate_size = intermediate_size + self.dropout = dropout + self.drop_path_rate = drop_path_rate + self.num_hidden_layers = num_hidden_layers + self.num_attention_heads = num_attention_heads + self.num_channels = num_channels + self.patch_size = patch_size + self.image_size = image_size + self.initializer_range = initializer_range + self.initializer_factor = initializer_factor + self.attention_dropout = attention_dropout + self.layer_norm_eps = layer_norm_eps + self.hidden_act = hidden_act + self.norm_type = norm_type + self.qkv_bias = qkv_bias + self.qk_normalization = qk_normalization + self.use_flash_attn = use_flash_attn + + @classmethod + def from_pretrained(cls, pretrained_model_name_or_path: Union[str, os.PathLike], **kwargs) -> 'PretrainedConfig': + config_dict, kwargs = cls.get_config_dict(pretrained_model_name_or_path, **kwargs) + + if 'vision_config' in config_dict: + config_dict = config_dict['vision_config'] + + if 'model_type' in config_dict and hasattr(cls, 'model_type') and config_dict['model_type'] != cls.model_type: + logger.warning( + f"You are using a model of type {config_dict['model_type']} to instantiate a model of type " + f'{cls.model_type}. This is not supported for all configurations of models and can yield errors.' + ) + + return cls.from_dict(config_dict, **kwargs) diff --git a/InternVL-main/internvl_chat/work_dirs/internvl_chat_v2_5/mmvet/200/configuration_internlm2.py b/InternVL-main/internvl_chat/work_dirs/internvl_chat_v2_5/mmvet/200/configuration_internlm2.py new file mode 100644 index 0000000000000000000000000000000000000000..282b13b1e2066ecc074ecae87b35a19d251f0ed7 --- /dev/null +++ b/InternVL-main/internvl_chat/work_dirs/internvl_chat_v2_5/mmvet/200/configuration_internlm2.py @@ -0,0 +1,150 @@ +# Copyright (c) The InternLM team and The HuggingFace Inc. team. All rights reserved. +# +# This code is based on transformers/src/transformers/models/llama/configuration_llama.py +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +""" InternLM2 model configuration""" + +from transformers.configuration_utils import PretrainedConfig +from transformers.utils import logging + +logger = logging.get_logger(__name__) + +INTERNLM2_PRETRAINED_CONFIG_ARCHIVE_MAP = {} + + +# Modified from transformers.model.llama.configuration_llama.LlamaConfig +class InternLM2Config(PretrainedConfig): + r""" + This is the configuration class to store the configuration of a [`InternLM2Model`]. It is used to instantiate + an InternLM2 model according to the specified arguments, defining the model architecture. Instantiating a + configuration with the defaults will yield a similar configuration to that of the InternLM2-7B. + + Configuration objects inherit from [`PretrainedConfig`] and can be used to control the model outputs. Read the + documentation from [`PretrainedConfig`] for more information. + + + Args: + vocab_size (`int`, *optional*, defaults to 32000): + Vocabulary size of the InternLM2 model. Defines the number of different tokens that can be represented by the + `inputs_ids` passed when calling [`InternLM2Model`] + hidden_size (`int`, *optional*, defaults to 4096): + Dimension of the hidden representations. + intermediate_size (`int`, *optional*, defaults to 11008): + Dimension of the MLP representations. + num_hidden_layers (`int`, *optional*, defaults to 32): + Number of hidden layers in the Transformer encoder. + num_attention_heads (`int`, *optional*, defaults to 32): + Number of attention heads for each attention layer in the Transformer encoder. + num_key_value_heads (`int`, *optional*): + This is the number of key_value heads that should be used to implement Grouped Query Attention. If + `num_key_value_heads=num_attention_heads`, the model will use Multi Head Attention (MHA), if + `num_key_value_heads=1 the model will use Multi Query Attention (MQA) otherwise GQA is used. When + converting a multi-head checkpoint to a GQA checkpoint, each group key and value head should be constructed + by meanpooling all the original heads within that group. For more details checkout [this + paper](https://arxiv.org/pdf/2305.13245.pdf). If it is not specified, will default to + `num_attention_heads`. + hidden_act (`str` or `function`, *optional*, defaults to `"silu"`): + The non-linear activation function (function or string) in the decoder. + max_position_embeddings (`int`, *optional*, defaults to 2048): + The maximum sequence length that this model might ever be used with. Typically set this to something large + just in case (e.g., 512 or 1024 or 2048). + initializer_range (`float`, *optional*, defaults to 0.02): + The standard deviation of the truncated_normal_initializer for initializing all weight matrices. + rms_norm_eps (`float`, *optional*, defaults to 1e-12): + The epsilon used by the rms normalization layers. + use_cache (`bool`, *optional*, defaults to `True`): + Whether or not the model should return the last key/values attentions (not used by all models). Only + relevant if `config.is_decoder=True`. + tie_word_embeddings(`bool`, *optional*, defaults to `False`): + Whether to tie weight embeddings + Example: + + """ + model_type = 'internlm2' + _auto_class = 'AutoConfig' + + def __init__( # pylint: disable=W0102 + self, + vocab_size=103168, + hidden_size=4096, + intermediate_size=11008, + num_hidden_layers=32, + num_attention_heads=32, + num_key_value_heads=None, + hidden_act='silu', + max_position_embeddings=2048, + initializer_range=0.02, + rms_norm_eps=1e-6, + use_cache=True, + pad_token_id=0, + bos_token_id=1, + eos_token_id=2, + tie_word_embeddings=False, + bias=True, + rope_theta=10000, + rope_scaling=None, + attn_implementation='eager', + **kwargs, + ): + self.vocab_size = vocab_size + self.max_position_embeddings = max_position_embeddings + self.hidden_size = hidden_size + self.intermediate_size = intermediate_size + self.num_hidden_layers = num_hidden_layers + self.num_attention_heads = num_attention_heads + self.bias = bias + + if num_key_value_heads is None: + num_key_value_heads = num_attention_heads + self.num_key_value_heads = num_key_value_heads + + self.hidden_act = hidden_act + self.initializer_range = initializer_range + self.rms_norm_eps = rms_norm_eps + self.use_cache = use_cache + self.rope_theta = rope_theta + self.rope_scaling = rope_scaling + self._rope_scaling_validation() + + self.attn_implementation = attn_implementation + if self.attn_implementation is None: + self.attn_implementation = 'eager' + super().__init__( + pad_token_id=pad_token_id, + bos_token_id=bos_token_id, + eos_token_id=eos_token_id, + tie_word_embeddings=tie_word_embeddings, + **kwargs, + ) + + def _rope_scaling_validation(self): + """ + Validate the `rope_scaling` configuration. + """ + if self.rope_scaling is None: + return + + if not isinstance(self.rope_scaling, dict) or len(self.rope_scaling) != 2: + raise ValueError( + '`rope_scaling` must be a dictionary with with two fields, `type` and `factor`, ' + f'got {self.rope_scaling}' + ) + rope_scaling_type = self.rope_scaling.get('type', None) + rope_scaling_factor = self.rope_scaling.get('factor', None) + if rope_scaling_type is None or rope_scaling_type not in ['linear', 'dynamic']: + raise ValueError( + f"`rope_scaling`'s type field must be one of ['linear', 'dynamic'], got {rope_scaling_type}" + ) + if rope_scaling_factor is None or not isinstance(rope_scaling_factor, float) or rope_scaling_factor < 1.0: + raise ValueError(f"`rope_scaling`'s factor field must be a float >= 1, got {rope_scaling_factor}") diff --git a/InternVL-main/internvl_chat/work_dirs/internvl_chat_v2_5/mmvet/200/configuration_internvl_chat.py b/InternVL-main/internvl_chat/work_dirs/internvl_chat_v2_5/mmvet/200/configuration_internvl_chat.py new file mode 100644 index 0000000000000000000000000000000000000000..56c628e15a646dfbb2618c90e0577b7037901b6b --- /dev/null +++ b/InternVL-main/internvl_chat/work_dirs/internvl_chat_v2_5/mmvet/200/configuration_internvl_chat.py @@ -0,0 +1,96 @@ +# -------------------------------------------------------- +# InternVL +# Copyright (c) 2024 OpenGVLab +# Licensed under The MIT License [see LICENSE for details] +# -------------------------------------------------------- + +import copy + +from transformers import AutoConfig, LlamaConfig +from transformers.configuration_utils import PretrainedConfig +from transformers.utils import logging + +from .configuration_intern_vit import InternVisionConfig +from .configuration_internlm2 import InternLM2Config + +logger = logging.get_logger(__name__) + + +class InternVLChatConfig(PretrainedConfig): + model_type = 'internvl_chat' + is_composition = True + + def __init__( + self, + vision_config=None, + llm_config=None, + use_backbone_lora=0, + use_llm_lora=0, + select_layer=-1, + force_image_size=None, + downsample_ratio=0.5, + template=None, + dynamic_image_size=False, + use_thumbnail=False, + ps_version='v1', + min_dynamic_patch=1, + max_dynamic_patch=6, + **kwargs): + super().__init__(**kwargs) + + if vision_config is None: + vision_config = {'architectures': ['InternVisionModel']} + logger.info('vision_config is None. Initializing the InternVisionConfig with default values.') + + if llm_config is None: + llm_config = {'architectures': ['InternLM2ForCausalLM']} + logger.info('llm_config is None. Initializing the LlamaConfig config with default values (`LlamaConfig`).') + + self.vision_config = InternVisionConfig(**vision_config) + if llm_config.get('architectures')[0] == 'LlamaForCausalLM': + self.llm_config = LlamaConfig(**llm_config) + elif llm_config.get('architectures')[0] == 'InternLM2ForCausalLM': + self.llm_config = InternLM2Config(**llm_config) + else: + raise ValueError('Unsupported architecture: {}'.format(llm_config.get('architectures')[0])) + self.use_backbone_lora = use_backbone_lora + self.use_llm_lora = use_llm_lora + self.select_layer = select_layer + self.force_image_size = force_image_size + self.downsample_ratio = downsample_ratio + self.template = template + self.dynamic_image_size = dynamic_image_size + self.use_thumbnail = use_thumbnail + self.ps_version = ps_version # pixel shuffle version + self.min_dynamic_patch = min_dynamic_patch + self.max_dynamic_patch = max_dynamic_patch + + logger.info(f'vision_select_layer: {self.select_layer}') + logger.info(f'ps_version: {self.ps_version}') + logger.info(f'min_dynamic_patch: {self.min_dynamic_patch}') + logger.info(f'max_dynamic_patch: {self.max_dynamic_patch}') + + def to_dict(self): + """ + Serializes this instance to a Python dictionary. Override the default [`~PretrainedConfig.to_dict`]. + + Returns: + `Dict[str, any]`: Dictionary of all the attributes that make up this configuration instance, + """ + output = copy.deepcopy(self.__dict__) + output['vision_config'] = self.vision_config.to_dict() + output['llm_config'] = self.llm_config.to_dict() + output['model_type'] = self.__class__.model_type + output['use_backbone_lora'] = self.use_backbone_lora + output['use_llm_lora'] = self.use_llm_lora + output['select_layer'] = self.select_layer + output['force_image_size'] = self.force_image_size + output['downsample_ratio'] = self.downsample_ratio + output['template'] = self.template + output['dynamic_image_size'] = self.dynamic_image_size + output['use_thumbnail'] = self.use_thumbnail + output['ps_version'] = self.ps_version + output['min_dynamic_patch'] = self.min_dynamic_patch + output['max_dynamic_patch'] = self.max_dynamic_patch + + return output diff --git a/InternVL-main/internvl_chat/work_dirs/internvl_chat_v2_5/mmvet/200/conversation.py b/InternVL-main/internvl_chat/work_dirs/internvl_chat_v2_5/mmvet/200/conversation.py new file mode 100644 index 0000000000000000000000000000000000000000..5a771766f21ce3aeeb99b286fb8d188b0038a547 --- /dev/null +++ b/InternVL-main/internvl_chat/work_dirs/internvl_chat_v2_5/mmvet/200/conversation.py @@ -0,0 +1,391 @@ +""" +Conversation prompt templates. + +We kindly request that you import fastchat instead of copying this file if you wish to use it. +If you have changes in mind, please contribute back so the community can benefit collectively and continue to maintain these valuable templates. + +Modified from https://github.com/lm-sys/FastChat/blob/main/fastchat/conversation.py +""" + +import dataclasses +from enum import IntEnum, auto +from typing import Dict, List, Tuple, Union + + +class SeparatorStyle(IntEnum): + """Separator styles.""" + + ADD_COLON_SINGLE = auto() + ADD_COLON_TWO = auto() + ADD_COLON_SPACE_SINGLE = auto() + NO_COLON_SINGLE = auto() + NO_COLON_TWO = auto() + ADD_NEW_LINE_SINGLE = auto() + LLAMA2 = auto() + CHATGLM = auto() + CHATML = auto() + CHATINTERN = auto() + DOLLY = auto() + RWKV = auto() + PHOENIX = auto() + ROBIN = auto() + FALCON_CHAT = auto() + CHATGLM3 = auto() + INTERNVL_ZH = auto() + MPT = auto() + + +@dataclasses.dataclass +class Conversation: + """A class that manages prompt templates and keeps all conversation history.""" + + # The name of this template + name: str + # The template of the system prompt + system_template: str = '{system_message}' + # The system message + system_message: str = '' + # The names of two roles + roles: Tuple[str] = ('USER', 'ASSISTANT') + # All messages. Each item is (role, message). + messages: List[List[str]] = () + # The number of few shot examples + offset: int = 0 + # The separator style and configurations + sep_style: SeparatorStyle = SeparatorStyle.ADD_COLON_SINGLE + sep: str = '\n' + sep2: str = None + # Stop criteria (the default one is EOS token) + stop_str: Union[str, List[str]] = None + # Stops generation if meeting any token in this list + stop_token_ids: List[int] = None + + def get_prompt(self) -> str: + """Get the prompt for generation.""" + system_prompt = self.system_template.format(system_message=self.system_message) + if self.sep_style == SeparatorStyle.ADD_COLON_SINGLE: + ret = system_prompt + self.sep + for role, message in self.messages: + if message: + ret += role + ': ' + message + self.sep + else: + ret += role + ':' + return ret + elif self.sep_style == SeparatorStyle.ADD_COLON_TWO: + seps = [self.sep, self.sep2] + ret = system_prompt + seps[0] + for i, (role, message) in enumerate(self.messages): + if message: + ret += role + ': ' + message + seps[i % 2] + else: + ret += role + ':' + return ret + elif self.sep_style == SeparatorStyle.ADD_COLON_SPACE_SINGLE: + ret = system_prompt + self.sep + for role, message in self.messages: + if message: + ret += role + ': ' + message + self.sep + else: + ret += role + ': ' # must be end with a space + return ret + elif self.sep_style == SeparatorStyle.ADD_NEW_LINE_SINGLE: + ret = '' if system_prompt == '' else system_prompt + self.sep + for role, message in self.messages: + if message: + ret += role + '\n' + message + self.sep + else: + ret += role + '\n' + return ret + elif self.sep_style == SeparatorStyle.NO_COLON_SINGLE: + ret = system_prompt + for role, message in self.messages: + if message: + ret += role + message + self.sep + else: + ret += role + return ret + elif self.sep_style == SeparatorStyle.NO_COLON_TWO: + seps = [self.sep, self.sep2] + ret = system_prompt + for i, (role, message) in enumerate(self.messages): + if message: + ret += role + message + seps[i % 2] + else: + ret += role + return ret + elif self.sep_style == SeparatorStyle.RWKV: + ret = system_prompt + for i, (role, message) in enumerate(self.messages): + if message: + ret += ( + role + + ': ' + + message.replace('\r\n', '\n').replace('\n\n', '\n') + ) + ret += '\n\n' + else: + ret += role + ':' + return ret + elif self.sep_style == SeparatorStyle.LLAMA2: + seps = [self.sep, self.sep2] + if self.system_message: + ret = system_prompt + else: + ret = '[INST] ' + for i, (role, message) in enumerate(self.messages): + tag = self.roles[i % 2] + if message: + if i == 0: + ret += message + ' ' + else: + ret += tag + ' ' + message + seps[i % 2] + else: + ret += tag + return ret + elif self.sep_style == SeparatorStyle.CHATGLM: + # source: https://huggingface.co/THUDM/chatglm-6b/blob/1d240ba371910e9282298d4592532d7f0f3e9f3e/modeling_chatglm.py#L1302-L1308 + # source2: https://huggingface.co/THUDM/chatglm2-6b/blob/e186c891cf64310ac66ef10a87e6635fa6c2a579/modeling_chatglm.py#L926 + round_add_n = 1 if self.name == 'chatglm2' else 0 + if system_prompt: + ret = system_prompt + self.sep + else: + ret = '' + + for i, (role, message) in enumerate(self.messages): + if i % 2 == 0: + ret += f'[Round {i//2 + round_add_n}]{self.sep}' + + if message: + ret += f'{role}：{message}{self.sep}' + else: + ret += f'{role}：' + return ret + elif self.sep_style == SeparatorStyle.CHATML: + ret = '' if system_prompt == '' else system_prompt + self.sep + '\n' + for role, message in self.messages: + if message: + ret += role + '\n' + message + self.sep + '\n' + else: + ret += role + '\n' + return ret + elif self.sep_style == SeparatorStyle.CHATGLM3: + ret = '' + if self.system_message: + ret += system_prompt + for role, message in self.messages: + if message: + ret += role + '\n' + ' ' + message + else: + ret += role + return ret + elif self.sep_style == SeparatorStyle.CHATINTERN: + # source: https://huggingface.co/internlm/internlm-chat-7b-8k/blob/bd546fa984b4b0b86958f56bf37f94aa75ab8831/modeling_internlm.py#L771 + seps = [self.sep, self.sep2] + ret = system_prompt + for i, (role, message) in enumerate(self.messages): + # if i % 2 == 0: + # ret += "" + if message: + ret += role + ':' + message + seps[i % 2] + '\n' + else: + ret += role + ':' + return ret + elif self.sep_style == SeparatorStyle.DOLLY: + seps = [self.sep, self.sep2] + ret = system_prompt + for i, (role, message) in enumerate(self.messages): + if message: + ret += role + ':\n' + message + seps[i % 2] + if i % 2 == 1: + ret += '\n\n' + else: + ret += role + ':\n' + return ret + elif self.sep_style == SeparatorStyle.PHOENIX: + ret = system_prompt + for role, message in self.messages: + if message: + ret += role + ': ' + '' + message + '' + else: + ret += role + ': ' + '' + return ret + elif self.sep_style == SeparatorStyle.ROBIN: + ret = system_prompt + self.sep + for role, message in self.messages: + if message: + ret += role + ':\n' + message + self.sep + else: + ret += role + ':\n' + return ret + elif self.sep_style == SeparatorStyle.FALCON_CHAT: + ret = '' + if self.system_message: + ret += system_prompt + self.sep + for role, message in self.messages: + if message: + ret += role + ': ' + message + self.sep + else: + ret += role + ':' + + return ret + elif self.sep_style == SeparatorStyle.INTERNVL_ZH: + seps = [self.sep, self.sep2] + ret = self.system_message + seps[0] + for i, (role, message) in enumerate(self.messages): + if message: + ret += role + ': ' + message + seps[i % 2] + else: + ret += role + ':' + return ret + elif self.sep_style == SeparatorStyle.MPT: + ret = system_prompt + self.sep + for role, message in self.messages: + if message: + if type(message) is tuple: + message, _, _ = message + ret += role + message + self.sep + else: + ret += role + return ret + else: + raise ValueError(f'Invalid style: {self.sep_style}') + + def set_system_message(self, system_message: str): + """Set the system message.""" + self.system_message = system_message + + def append_message(self, role: str, message: str): + """Append a new message.""" + self.messages.append([role, message]) + + def update_last_message(self, message: str): + """Update the last output. + + The last message is typically set to be None when constructing the prompt, + so we need to update it in-place after getting the response from a model. + """ + self.messages[-1][1] = message + + def to_gradio_chatbot(self): + """Convert the conversation to gradio chatbot format.""" + ret = [] + for i, (role, msg) in enumerate(self.messages[self.offset :]): + if i % 2 == 0: + ret.append([msg, None]) + else: + ret[-1][-1] = msg + return ret + + def to_openai_api_messages(self): + """Convert the conversation to OpenAI chat completion format.""" + ret = [{'role': 'system', 'content': self.system_message}] + + for i, (_, msg) in enumerate(self.messages[self.offset :]): + if i % 2 == 0: + ret.append({'role': 'user', 'content': msg}) + else: + if msg is not None: + ret.append({'role': 'assistant', 'content': msg}) + return ret + + def copy(self): + return Conversation( + name=self.name, + system_template=self.system_template, + system_message=self.system_message, + roles=self.roles, + messages=[[x, y] for x, y in self.messages], + offset=self.offset, + sep_style=self.sep_style, + sep=self.sep, + sep2=self.sep2, + stop_str=self.stop_str, + stop_token_ids=self.stop_token_ids, + ) + + def dict(self): + return { + 'template_name': self.name, + 'system_message': self.system_message, + 'roles': self.roles, + 'messages': self.messages, + 'offset': self.offset, + } + + +# A global registry for all conversation templates +conv_templates: Dict[str, Conversation] = {} + + +def register_conv_template(template: Conversation, override: bool = False): + """Register a new conversation template.""" + if not override: + assert ( + template.name not in conv_templates + ), f'{template.name} has been registered.' + + conv_templates[template.name] = template + + +def get_conv_template(name: str) -> Conversation: + """Get a conversation template.""" + return conv_templates[name].copy() + + +# Both Hermes-2 and internlm2-chat are chatml-format conversation templates. The difference +# is that during training, the preprocessing function for the Hermes-2 template doesn't add +# at the beginning of the tokenized sequence, while the internlm2-chat template does. +# Therefore, they are completely equivalent during inference. +register_conv_template( + Conversation( + name='Hermes-2', + system_template='<|im_start|>system\n{system_message}', + # note: The new system prompt was not used here to avoid changes in benchmark performance. + # system_message='我是书生·万象，英文名是InternVL，是由上海人工智能实验室、清华大学及多家合作单位联合开发的多模态大语言模型。', + system_message='你是由上海人工智能实验室联合商汤科技开发的书生多模态大模型，英文名叫InternVL, 是一个有用无害的人工智能助手。', + roles=('<|im_start|>user\n', '<|im_start|>assistant\n'), + sep_style=SeparatorStyle.MPT, + sep='<|im_end|>', + stop_str='<|endoftext|>', + ) +) + + +register_conv_template( + Conversation( + name='internlm2-chat', + system_template='<|im_start|>system\n{system_message}', + # note: The new system prompt was not used here to avoid changes in benchmark performance. + # system_message='我是书生·万象，英文名是InternVL，是由上海人工智能实验室、清华大学及多家合作单位联合开发的多模态大语言模型。', + system_message='你是由上海人工智能实验室联合商汤科技开发的书生多模态大模型，英文名叫InternVL, 是一个有用无害的人工智能助手。', + roles=('<|im_start|>user\n', '<|im_start|>assistant\n'), + sep_style=SeparatorStyle.MPT, + sep='<|im_end|>', + ) +) + + +register_conv_template( + Conversation( + name='phi3-chat', + system_template='<|system|>\n{system_message}', + # note: The new system prompt was not used here to avoid changes in benchmark performance. + # system_message='我是书生·万象，英文名是InternVL，是由上海人工智能实验室、清华大学及多家合作单位联合开发的多模态大语言模型。', + system_message='你是由上海人工智能实验室联合商汤科技开发的书生多模态大模型，英文名叫InternVL, 是一个有用无害的人工智能助手。', + roles=('<|user|>\n', '<|assistant|>\n'), + sep_style=SeparatorStyle.MPT, + sep='<|end|>', + ) +) + + +register_conv_template( + Conversation( + name='internvl2_5', + system_template='<|im_start|>system\n{system_message}', + system_message='你是书生·万象，英文名是InternVL，是由上海人工智能实验室、清华大学及多家合作单位联合开发的多模态大语言模型。', + roles=('<|im_start|>user\n', '<|im_start|>assistant\n'), + sep_style=SeparatorStyle.MPT, + sep='<|im_end|>\n', + ) +) diff --git a/InternVL-main/internvl_chat/work_dirs/internvl_chat_v2_5/mmvet/200/generation_config.json b/InternVL-main/internvl_chat/work_dirs/internvl_chat_v2_5/mmvet/200/generation_config.json new file mode 100644 index 0000000000000000000000000000000000000000..918fe50c5a6fd362e537376348091b2bc5f51820 --- /dev/null +++ b/InternVL-main/internvl_chat/work_dirs/internvl_chat_v2_5/mmvet/200/generation_config.json @@ -0,0 +1,8 @@ +{ + "_from_model_config": true, + "eos_token_id": [ + 92542, + 92543 + ], + "transformers_version": "4.43.2" +} diff --git a/InternVL-main/internvl_chat/work_dirs/internvl_chat_v2_5/mmvet/200/modeling_intern_vit.py b/InternVL-main/internvl_chat/work_dirs/internvl_chat_v2_5/mmvet/200/modeling_intern_vit.py new file mode 100644 index 0000000000000000000000000000000000000000..1c5c043a4b860720b3b6e55107e8e6ecf0c573de --- /dev/null +++ b/InternVL-main/internvl_chat/work_dirs/internvl_chat_v2_5/mmvet/200/modeling_intern_vit.py @@ -0,0 +1,430 @@ +# -------------------------------------------------------- +# InternVL +# Copyright (c) 2024 OpenGVLab +# Licensed under The MIT License [see LICENSE for details] +# -------------------------------------------------------- + +from typing import Optional, Tuple, Union + +import torch +import torch.nn.functional as F +import torch.utils.checkpoint +from einops import rearrange +from timm.models.layers import DropPath +from torch import nn +from transformers.activations import ACT2FN +from transformers.modeling_outputs import (BaseModelOutput, + BaseModelOutputWithPooling) +from transformers.modeling_utils import PreTrainedModel +from transformers.utils import logging + +from .configuration_intern_vit import InternVisionConfig + +try: + from flash_attn.bert_padding import pad_input, unpad_input + from flash_attn.flash_attn_interface import \ + flash_attn_varlen_qkvpacked_func + has_flash_attn = True +except: + print('FlashAttention2 is not installed.') + has_flash_attn = False + +logger = logging.get_logger(__name__) + + +class FlashAttention(nn.Module): + """Implement the scaled dot product attention with softmax. + Arguments + --------- + softmax_scale: The temperature to use for the softmax attention. + (default: 1/sqrt(d_keys) where d_keys is computed at + runtime) + attention_dropout: The dropout rate to apply to the attention + (default: 0.0) + """ + + def __init__(self, softmax_scale=None, attention_dropout=0.0, device=None, dtype=None): + super().__init__() + self.softmax_scale = softmax_scale + self.dropout_p = attention_dropout + + def forward(self, qkv, key_padding_mask=None, causal=False, cu_seqlens=None, + max_s=None, need_weights=False): + """Implements the multihead softmax attention. + Arguments + --------- + qkv: The tensor containing the query, key, and value. (B, S, 3, H, D) if key_padding_mask is None + if unpadded: (nnz, 3, h, d) + key_padding_mask: a bool tensor of shape (B, S) + """ + assert not need_weights + assert qkv.dtype in [torch.float16, torch.bfloat16] + assert qkv.is_cuda + + if cu_seqlens is None: + batch_size = qkv.shape[0] + seqlen = qkv.shape[1] + if key_padding_mask is None: + qkv = rearrange(qkv, 'b s ... -> (b s) ...') + max_s = seqlen + cu_seqlens = torch.arange(0, (batch_size + 1) * seqlen, step=seqlen, dtype=torch.int32, + device=qkv.device) + output = flash_attn_varlen_qkvpacked_func( + qkv, cu_seqlens, max_s, self.dropout_p if self.training else 0.0, + softmax_scale=self.softmax_scale, causal=causal + ) + output = rearrange(output, '(b s) ... -> b s ...', b=batch_size) + else: + nheads = qkv.shape[-2] + x = rearrange(qkv, 'b s three h d -> b s (three h d)') + x_unpad, indices, cu_seqlens, max_s = unpad_input(x, key_padding_mask) + x_unpad = rearrange(x_unpad, 'nnz (three h d) -> nnz three h d', three=3, h=nheads) + output_unpad = flash_attn_varlen_qkvpacked_func( + x_unpad, cu_seqlens, max_s, self.dropout_p if self.training else 0.0, + softmax_scale=self.softmax_scale, causal=causal + ) + output = rearrange(pad_input(rearrange(output_unpad, 'nnz h d -> nnz (h d)'), + indices, batch_size, seqlen), + 'b s (h d) -> b s h d', h=nheads) + else: + assert max_s is not None + output = flash_attn_varlen_qkvpacked_func( + qkv, cu_seqlens, max_s, self.dropout_p if self.training else 0.0, + softmax_scale=self.softmax_scale, causal=causal + ) + + return output, None + + +class InternRMSNorm(nn.Module): + def __init__(self, hidden_size, eps=1e-6): + super().__init__() + self.weight = nn.Parameter(torch.ones(hidden_size)) + self.variance_epsilon = eps + + def forward(self, hidden_states): + input_dtype = hidden_states.dtype + hidden_states = hidden_states.to(torch.float32) + variance = hidden_states.pow(2).mean(-1, keepdim=True) + hidden_states = hidden_states * torch.rsqrt(variance + self.variance_epsilon) + return self.weight * hidden_states.to(input_dtype) + + +try: + from apex.normalization import FusedRMSNorm + + InternRMSNorm = FusedRMSNorm # noqa + + logger.info('Discovered apex.normalization.FusedRMSNorm - will use it instead of InternRMSNorm') +except ImportError: + # using the normal InternRMSNorm + pass +except Exception: + logger.warning('discovered apex but it failed to load, falling back to InternRMSNorm') + pass + + +NORM2FN = { + 'rms_norm': InternRMSNorm, + 'layer_norm': nn.LayerNorm, +} + + +class InternVisionEmbeddings(nn.Module): + def __init__(self, config: InternVisionConfig): + super().__init__() + self.config = config + self.embed_dim = config.hidden_size + self.image_size = config.image_size + self.patch_size = config.patch_size + + self.class_embedding = nn.Parameter( + torch.randn(1, 1, self.embed_dim), + ) + + self.patch_embedding = nn.Conv2d( + in_channels=3, out_channels=self.embed_dim, kernel_size=self.patch_size, stride=self.patch_size + ) + + self.num_patches = (self.image_size // self.patch_size) ** 2 + self.num_positions = self.num_patches + 1 + + self.position_embedding = nn.Parameter(torch.randn(1, self.num_positions, self.embed_dim)) + + def _get_pos_embed(self, pos_embed, H, W): + target_dtype = pos_embed.dtype + pos_embed = pos_embed.float().reshape( + 1, self.image_size // self.patch_size, self.image_size // self.patch_size, -1).permute(0, 3, 1, 2) + pos_embed = F.interpolate(pos_embed, size=(H, W), mode='bicubic', align_corners=False). \ + reshape(1, -1, H * W).permute(0, 2, 1).to(target_dtype) + return pos_embed + + def forward(self, pixel_values: torch.FloatTensor) -> torch.Tensor: + target_dtype = self.patch_embedding.weight.dtype + patch_embeds = self.patch_embedding(pixel_values) # shape = [*, channel, width, height] + batch_size, _, height, width = patch_embeds.shape + patch_embeds = patch_embeds.flatten(2).transpose(1, 2) + class_embeds = self.class_embedding.expand(batch_size, 1, -1).to(target_dtype) + embeddings = torch.cat([class_embeds, patch_embeds], dim=1) + position_embedding = torch.cat([ + self.position_embedding[:, :1, :], + self._get_pos_embed(self.position_embedding[:, 1:, :], height, width) + ], dim=1) + embeddings = embeddings + position_embedding.to(target_dtype) + return embeddings + + +class InternAttention(nn.Module): + """Multi-headed attention from 'Attention Is All You Need' paper""" + + def __init__(self, config: InternVisionConfig): + super().__init__() + self.config = config + self.embed_dim = config.hidden_size + self.num_heads = config.num_attention_heads + self.use_flash_attn = config.use_flash_attn and has_flash_attn + if config.use_flash_attn and not has_flash_attn: + print('Warning: Flash Attention is not available, use_flash_attn is set to False.') + self.head_dim = self.embed_dim // self.num_heads + if self.head_dim * self.num_heads != self.embed_dim: + raise ValueError( + f'embed_dim must be divisible by num_heads (got `embed_dim`: {self.embed_dim} and `num_heads`:' + f' {self.num_heads}).' + ) + + self.scale = self.head_dim ** -0.5 + self.qkv = nn.Linear(self.embed_dim, 3 * self.embed_dim, bias=config.qkv_bias) + self.attn_drop = nn.Dropout(config.attention_dropout) + self.proj_drop = nn.Dropout(config.dropout) + + self.qk_normalization = config.qk_normalization + + if self.qk_normalization: + self.q_norm = InternRMSNorm(self.embed_dim, eps=config.layer_norm_eps) + self.k_norm = InternRMSNorm(self.embed_dim, eps=config.layer_norm_eps) + + if self.use_flash_attn: + self.inner_attn = FlashAttention(attention_dropout=config.attention_dropout) + self.proj = nn.Linear(self.embed_dim, self.embed_dim) + + def _naive_attn(self, x): + B, N, C = x.shape + qkv = self.qkv(x).reshape(B, N, 3, self.num_heads, C // self.num_heads).permute(2, 0, 3, 1, 4) + q, k, v = qkv.unbind(0) # make torchscript happy (cannot use tensor as tuple) + + if self.qk_normalization: + B_, H_, N_, D_ = q.shape + q = self.q_norm(q.transpose(1, 2).flatten(-2, -1)).view(B_, N_, H_, D_).transpose(1, 2) + k = self.k_norm(k.transpose(1, 2).flatten(-2, -1)).view(B_, N_, H_, D_).transpose(1, 2) + + attn = ((q * self.scale) @ k.transpose(-2, -1)) + attn = attn.softmax(dim=-1) + attn = self.attn_drop(attn) + + x = (attn @ v).transpose(1, 2).reshape(B, N, C) + x = self.proj(x) + x = self.proj_drop(x) + return x + + def _flash_attn(self, x, key_padding_mask=None, need_weights=False): + qkv = self.qkv(x) + qkv = rearrange(qkv, 'b s (three h d) -> b s three h d', three=3, h=self.num_heads) + + if self.qk_normalization: + q, k, v = qkv.unbind(2) + q = self.q_norm(q.flatten(-2, -1)).view(q.shape) + k = self.k_norm(k.flatten(-2, -1)).view(k.shape) + qkv = torch.stack([q, k, v], dim=2) + + context, _ = self.inner_attn( + qkv, key_padding_mask=key_padding_mask, need_weights=need_weights, causal=False + ) + outs = self.proj(rearrange(context, 'b s h d -> b s (h d)')) + outs = self.proj_drop(outs) + return outs + + def forward(self, hidden_states: torch.Tensor) -> torch.Tensor: + x = self._naive_attn(hidden_states) if not self.use_flash_attn else self._flash_attn(hidden_states) + return x + + +class InternMLP(nn.Module): + def __init__(self, config: InternVisionConfig): + super().__init__() + self.config = config + self.act = ACT2FN[config.hidden_act] + self.fc1 = nn.Linear(config.hidden_size, config.intermediate_size) + self.fc2 = nn.Linear(config.intermediate_size, config.hidden_size) + + def forward(self, hidden_states: torch.Tensor) -> torch.Tensor: + hidden_states = self.fc1(hidden_states) + hidden_states = self.act(hidden_states) + hidden_states = self.fc2(hidden_states) + return hidden_states + + +class InternVisionEncoderLayer(nn.Module): + def __init__(self, config: InternVisionConfig, drop_path_rate: float): + super().__init__() + self.embed_dim = config.hidden_size + self.intermediate_size = config.intermediate_size + self.norm_type = config.norm_type + + self.attn = InternAttention(config) + self.mlp = InternMLP(config) + self.norm1 = NORM2FN[self.norm_type](self.embed_dim, eps=config.layer_norm_eps) + self.norm2 = NORM2FN[self.norm_type](self.embed_dim, eps=config.layer_norm_eps) + + self.ls1 = nn.Parameter(config.initializer_factor * torch.ones(self.embed_dim)) + self.ls2 = nn.Parameter(config.initializer_factor * torch.ones(self.embed_dim)) + self.drop_path1 = DropPath(drop_path_rate) if drop_path_rate > 0. else nn.Identity() + self.drop_path2 = DropPath(drop_path_rate) if drop_path_rate > 0. else nn.Identity() + + def forward( + self, + hidden_states: torch.Tensor, + ) -> Tuple[torch.FloatTensor, Optional[torch.FloatTensor], Optional[Tuple[torch.FloatTensor]]]: + """ + Args: + hidden_states (`Tuple[torch.FloatTensor, Optional[torch.FloatTensor]]`): input to the layer of shape `(batch, seq_len, embed_dim)` + """ + hidden_states = hidden_states + self.drop_path1(self.attn(self.norm1(hidden_states).to(hidden_states.dtype)) * self.ls1) + + hidden_states = hidden_states + self.drop_path2(self.mlp(self.norm2(hidden_states).to(hidden_states.dtype)) * self.ls2) + + return hidden_states + + +class InternVisionEncoder(nn.Module): + """ + Transformer encoder consisting of `config.num_hidden_layers` self attention layers. Each layer is a + [`InternEncoderLayer`]. + + Args: + config (`InternConfig`): + The corresponding vision configuration for the `InternEncoder`. + """ + + def __init__(self, config: InternVisionConfig): + super().__init__() + self.config = config + # stochastic depth decay rule + dpr = [x.item() for x in torch.linspace(0, config.drop_path_rate, config.num_hidden_layers)] + self.layers = nn.ModuleList([ + InternVisionEncoderLayer(config, dpr[idx]) for idx in range(config.num_hidden_layers)]) + self.gradient_checkpointing = True + + def forward( + self, + inputs_embeds, + output_hidden_states: Optional[bool] = None, + return_dict: Optional[bool] = None, + ) -> Union[Tuple, BaseModelOutput]: + r""" + Args: + inputs_embeds (`torch.FloatTensor` of shape `(batch_size, sequence_length, hidden_size)`): + Embedded representation of the inputs. Should be float, not int tokens. + output_hidden_states (`bool`, *optional*): + Whether or not to return the hidden states of all layers. See `hidden_states` under returned tensors + for more detail. + return_dict (`bool`, *optional*): + Whether or not to return a [`~utils.ModelOutput`] instead of a plain tuple. + """ + output_hidden_states = ( + output_hidden_states if output_hidden_states is not None else self.config.output_hidden_states + ) + return_dict = return_dict if return_dict is not None else self.config.use_return_dict + + encoder_states = () if output_hidden_states else None + hidden_states = inputs_embeds + + for idx, encoder_layer in enumerate(self.layers): + if output_hidden_states: + encoder_states = encoder_states + (hidden_states,) + if self.gradient_checkpointing and self.training: + layer_outputs = torch.utils.checkpoint.checkpoint( + encoder_layer, + hidden_states) + else: + layer_outputs = encoder_layer( + hidden_states, + ) + hidden_states = layer_outputs + + if output_hidden_states: + encoder_states = encoder_states + (hidden_states,) + + if not return_dict: + return tuple(v for v in [hidden_states, encoder_states] if v is not None) + return BaseModelOutput( + last_hidden_state=hidden_states, hidden_states=encoder_states + ) + + +class InternVisionModel(PreTrainedModel): + main_input_name = 'pixel_values' + _supports_flash_attn_2 = True + config_class = InternVisionConfig + _no_split_modules = ['InternVisionEncoderLayer'] + + def __init__(self, config: InternVisionConfig): + super().__init__(config) + self.config = config + + self.embeddings = InternVisionEmbeddings(config) + self.encoder = InternVisionEncoder(config) + + def resize_pos_embeddings(self, old_size, new_size, patch_size): + pos_emb = self.embeddings.position_embedding + _, num_positions, embed_dim = pos_emb.shape + cls_emb = pos_emb[:, :1, :] + pos_emb = pos_emb[:, 1:, :].reshape(1, old_size // patch_size, old_size // patch_size, -1).permute(0, 3, 1, 2) + pos_emb = F.interpolate(pos_emb.float(), size=new_size // patch_size, mode='bicubic', align_corners=False) + pos_emb = pos_emb.to(cls_emb.dtype).reshape(1, embed_dim, -1).permute(0, 2, 1) + pos_emb = torch.cat([cls_emb, pos_emb], dim=1) + self.embeddings.position_embedding = nn.Parameter(pos_emb) + self.embeddings.image_size = new_size + logger.info('Resized position embeddings from {} to {}'.format(old_size, new_size)) + + def get_input_embeddings(self): + return self.embeddings + + def forward( + self, + pixel_values: Optional[torch.FloatTensor] = None, + output_hidden_states: Optional[bool] = None, + return_dict: Optional[bool] = None, + pixel_embeds: Optional[torch.FloatTensor] = None, + ) -> Union[Tuple, BaseModelOutputWithPooling]: + output_hidden_states = ( + output_hidden_states if output_hidden_states is not None else self.config.output_hidden_states + ) + return_dict = return_dict if return_dict is not None else self.config.use_return_dict + + if pixel_values is None and pixel_embeds is None: + raise ValueError('You have to specify pixel_values or pixel_embeds') + + if pixel_embeds is not None: + hidden_states = pixel_embeds + else: + if len(pixel_values.shape) == 4: + hidden_states = self.embeddings(pixel_values) + else: + raise ValueError(f'wrong pixel_values size: {pixel_values.shape}') + encoder_outputs = self.encoder( + inputs_embeds=hidden_states, + output_hidden_states=output_hidden_states, + return_dict=return_dict, + ) + last_hidden_state = encoder_outputs.last_hidden_state + pooled_output = last_hidden_state[:, 0, :] + + if not return_dict: + return (last_hidden_state, pooled_output) + encoder_outputs[1:] + + return BaseModelOutputWithPooling( + last_hidden_state=last_hidden_state, + pooler_output=pooled_output, + hidden_states=encoder_outputs.hidden_states, + attentions=encoder_outputs.attentions, + ) diff --git a/InternVL-main/internvl_chat/work_dirs/internvl_chat_v2_5/mmvet/200/modeling_internlm2.py b/InternVL-main/internvl_chat/work_dirs/internvl_chat_v2_5/mmvet/200/modeling_internlm2.py new file mode 100644 index 0000000000000000000000000000000000000000..7c8c24d873f6ecd152d00fd65371e23ead981e1d --- /dev/null +++ b/InternVL-main/internvl_chat/work_dirs/internvl_chat_v2_5/mmvet/200/modeling_internlm2.py @@ -0,0 +1,1415 @@ +# Copyright (c) The InternLM team and The HuggingFace Inc. team. All rights reserved. +# +# This code is based on transformers/src/transformers/models/llama/modeling_llama.py +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +""" PyTorch InternLM2 model.""" +import math +import queue +import threading +import warnings +from typing import List, Optional, Tuple, Union + +import torch +import torch.nn.functional as F +import torch.utils.checkpoint +from einops import rearrange +from torch import nn +from torch.nn import BCEWithLogitsLoss, CrossEntropyLoss, MSELoss +from transformers.activations import ACT2FN +from transformers.modeling_outputs import (BaseModelOutputWithPast, + CausalLMOutputWithPast, + SequenceClassifierOutputWithPast) +from transformers.modeling_utils import PreTrainedModel +from transformers.utils import (add_start_docstrings, + add_start_docstrings_to_model_forward, logging, + replace_return_docstrings) + +try: + from transformers.generation.streamers import BaseStreamer +except: # noqa # pylint: disable=bare-except + BaseStreamer = None + +from .configuration_internlm2 import InternLM2Config + +logger = logging.get_logger(__name__) + +_CONFIG_FOR_DOC = 'InternLM2Config' + +flash_attn_func, flash_attn_varlen_func = None, None +pad_input, index_first_axis, unpad_input = None, None, None +try: + from flash_attn import flash_attn_func as _flash_attn_func + from flash_attn import flash_attn_varlen_func as _flash_attn_varlen_func + from flash_attn.bert_padding import index_first_axis as _index_first_axis + from flash_attn.bert_padding import pad_input as _pad_input + from flash_attn.bert_padding import unpad_input as _unpad_input + + flash_attn_func, flash_attn_varlen_func = _flash_attn_func, _flash_attn_varlen_func + pad_input, index_first_axis, unpad_input = _pad_input, _index_first_axis, _unpad_input + has_flash_attn = True +except: + has_flash_attn = False + + +def _import_flash_attn(): + global flash_attn_func, flash_attn_varlen_func + global pad_input, index_first_axis, unpad_input + try: + from flash_attn import flash_attn_func as _flash_attn_func + from flash_attn import \ + flash_attn_varlen_func as _flash_attn_varlen_func + from flash_attn.bert_padding import \ + index_first_axis as _index_first_axis + from flash_attn.bert_padding import pad_input as _pad_input + from flash_attn.bert_padding import unpad_input as _unpad_input + flash_attn_func, flash_attn_varlen_func = _flash_attn_func, _flash_attn_varlen_func + pad_input, index_first_axis, unpad_input = _pad_input, _index_first_axis, _unpad_input + except ImportError: + raise ImportError('flash_attn is not installed.') + + +# Copied from transformers.models.llama.modeling_llama._get_unpad_data +def _get_unpad_data(attention_mask): + seqlens_in_batch = attention_mask.sum(dim=-1, dtype=torch.int32) + indices = torch.nonzero(attention_mask.flatten(), as_tuple=False).flatten() + max_seqlen_in_batch = seqlens_in_batch.max().item() + cu_seqlens = F.pad(torch.cumsum(seqlens_in_batch, dim=0, dtype=torch.torch.int32), (1, 0)) + return ( + indices, + cu_seqlens, + max_seqlen_in_batch, + ) + + +# Copied from transformers.models.bart.modeling_bart._make_causal_mask +def _make_causal_mask( + input_ids_shape: torch.Size, dtype: torch.dtype, device: torch.device, past_key_values_length: int = 0 +): + """ + Make causal mask used for bi-directional self-attention. + """ + bsz, tgt_len = input_ids_shape + mask = torch.full((tgt_len, tgt_len), torch.tensor(torch.finfo(dtype).min, device=device), device=device) + mask_cond = torch.arange(mask.size(-1), device=device) + mask.masked_fill_(mask_cond < (mask_cond + 1).view(mask.size(-1), 1), 0) + mask = mask.to(dtype) + + if past_key_values_length > 0: + mask = torch.cat([torch.zeros(tgt_len, past_key_values_length, dtype=dtype, device=device), mask], dim=-1) + return mask[None, None, :, :].expand(bsz, 1, tgt_len, tgt_len + past_key_values_length) + + +# Copied from transformers.models.bart.modeling_bart._expand_mask +def _expand_mask(mask: torch.Tensor, dtype: torch.dtype, tgt_len: Optional[int] = None): + """ + Expands attention_mask from `[bsz, seq_len]` to `[bsz, 1, tgt_seq_len, src_seq_len]`. + """ + bsz, src_len = mask.size() + tgt_len = tgt_len if tgt_len is not None else src_len + + expanded_mask = mask[:, None, None, :].expand(bsz, 1, tgt_len, src_len).to(dtype) + + inverted_mask = 1.0 - expanded_mask + + return inverted_mask.masked_fill(inverted_mask.to(torch.bool), torch.finfo(dtype).min) + + +# Copied from transformers.models.llama.modeling_llama.LlamaRMSNorm with Llama->InternLM2 +class InternLM2RMSNorm(nn.Module): + def __init__(self, hidden_size, eps=1e-6): + """ + InternLM2RMSNorm is equivalent to T5LayerNorm + """ + super().__init__() + self.weight = nn.Parameter(torch.ones(hidden_size)) + self.variance_epsilon = eps + + def forward(self, hidden_states): + input_dtype = hidden_states.dtype + hidden_states = hidden_states.to(torch.float32) + variance = hidden_states.pow(2).mean(-1, keepdim=True) + hidden_states = hidden_states * torch.rsqrt(variance + self.variance_epsilon) + return self.weight * hidden_states.to(input_dtype) + + +# Copied from transformers.model.llama.modeling_llama.LlamaRotaryEmbedding with Llama->InternLM2 +class InternLM2RotaryEmbedding(nn.Module): + def __init__(self, dim, max_position_embeddings=2048, base=10000, device=None): + super().__init__() + + self.dim = dim + self.max_position_embeddings = max_position_embeddings + self.base = base + inv_freq = 1.0 / (self.base ** (torch.arange(0, self.dim, 2).float().to(device) / self.dim)) + self.register_buffer('inv_freq', inv_freq, persistent=False) + + # Build here to make `torch.jit.trace` work. + self._set_cos_sin_cache( + seq_len=max_position_embeddings, device=self.inv_freq.device, dtype=torch.get_default_dtype() + ) + + def _set_cos_sin_cache(self, seq_len, device, dtype): + self.max_seq_len_cached = seq_len + t = torch.arange(self.max_seq_len_cached, device=device).to(dtype=self.inv_freq.dtype) + + freqs = torch.einsum('i,j->ij', t, self.inv_freq) + # Different from paper, but it uses a different permutation in order to obtain the same calculation + emb = torch.cat((freqs, freqs), dim=-1) + self.register_buffer('cos_cached', emb.cos().to(dtype), persistent=False) + self.register_buffer('sin_cached', emb.sin().to(dtype), persistent=False) + + def forward(self, x, seq_len=None): + # x: [bs, num_attention_heads, seq_len, head_size] + if seq_len > self.max_seq_len_cached: + self._set_cos_sin_cache(seq_len=seq_len, device=x.device, dtype=torch.float32) + + return ( + self.cos_cached[:seq_len].to(dtype=x.dtype), + self.sin_cached[:seq_len].to(dtype=x.dtype), + ) + + +# Copied from transformers.model.llama.modeling_llama.LlamaLinearScalingRotaryEmbedding with Llama->InternLM2 +class InternLM2LinearScalingRotaryEmbedding(InternLM2RotaryEmbedding): + """InternLM2RotaryEmbedding extended with linear scaling. Credits to the Reddit user /u/kaiokendev""" + + def __init__(self, dim, max_position_embeddings=2048, base=10000, device=None, scaling_factor=1.0): + self.scaling_factor = scaling_factor + super().__init__(dim, max_position_embeddings, base, device) + + def _set_cos_sin_cache(self, seq_len, device, dtype): + self.max_seq_len_cached = seq_len + t = torch.arange(self.max_seq_len_cached, device=device).to(dtype=self.inv_freq.dtype) + t = t / self.scaling_factor + + freqs = torch.einsum('i,j->ij', t, self.inv_freq) + # Different from paper, but it uses a different permutation in order to obtain the same calculation + emb = torch.cat((freqs, freqs), dim=-1) + self.register_buffer('cos_cached', emb.cos().to(dtype), persistent=False) + self.register_buffer('sin_cached', emb.sin().to(dtype), persistent=False) + + +# Copied from transformers.model.llama.modeling_llama.LlamaDynamicNTKScalingRotaryEmbedding with Llama->InternLM2 +class InternLM2DynamicNTKScalingRotaryEmbedding(InternLM2RotaryEmbedding): + """InternLM2RotaryEmbedding extended with Dynamic NTK scaling. + Credits to the Reddit users /u/bloc97 and /u/emozilla. + """ + + def __init__(self, dim, max_position_embeddings=2048, base=10000, device=None, scaling_factor=1.0): + self.scaling_factor = scaling_factor + super().__init__(dim, max_position_embeddings, base, device) + + def _set_cos_sin_cache(self, seq_len, device, dtype): + self.max_seq_len_cached = seq_len + + if seq_len > self.max_position_embeddings: + base = self.base * ( + (self.scaling_factor * seq_len / self.max_position_embeddings) - (self.scaling_factor - 1) + ) ** (self.dim / (self.dim - 2)) + inv_freq = 1.0 / (base ** (torch.arange(0, self.dim, 2).float().to(device) / self.dim)) + self.register_buffer('inv_freq', inv_freq, persistent=False) + + t = torch.arange(self.max_seq_len_cached, device=device).to(dtype=self.inv_freq.dtype) + + freqs = torch.einsum('i,j->ij', t, self.inv_freq) + # Different from paper, but it uses a different permutation in order to obtain the same calculation + emb = torch.cat((freqs, freqs), dim=-1) + self.register_buffer('cos_cached', emb.cos().to(dtype), persistent=False) + self.register_buffer('sin_cached', emb.sin().to(dtype), persistent=False) + + +# Copied from transformers.model.llama.modeling_llama.rotate_half +def rotate_half(x): + """Rotates half the hidden dims of the input.""" + x1 = x[..., : x.shape[-1] // 2] + x2 = x[..., x.shape[-1] // 2 :] + return torch.cat((-x2, x1), dim=-1) + + +# Copied from transformers.model.llama.modeling_llama.apply_rotary_pos_emb +def apply_rotary_pos_emb(q, k, cos, sin, position_ids, unsqueeze_dim=1): + """Applies Rotary Position Embedding to the query and key tensors.""" + cos = cos[position_ids].unsqueeze(unsqueeze_dim) + sin = sin[position_ids].unsqueeze(unsqueeze_dim) + q_embed = (q * cos) + (rotate_half(q) * sin) + k_embed = (k * cos) + (rotate_half(k) * sin) + return q_embed, k_embed + + +class InternLM2MLP(nn.Module): + def __init__(self, config): + super().__init__() + self.config = config + self.hidden_size = config.hidden_size + self.intermediate_size = config.intermediate_size + self.w1 = nn.Linear(self.hidden_size, self.intermediate_size, bias=False) + self.w3 = nn.Linear(self.hidden_size, self.intermediate_size, bias=False) + self.w2 = nn.Linear(self.intermediate_size, self.hidden_size, bias=False) + self.act_fn = ACT2FN[config.hidden_act] + + def forward(self, x): + down_proj = self.w2(self.act_fn(self.w1(x)) * self.w3(x)) + + return down_proj + + +# Copied from transformers.model.llama.modeling_llama.repeat_kv +def repeat_kv(hidden_states: torch.Tensor, n_rep: int) -> torch.Tensor: + """ + This is the equivalent of torch.repeat_interleave(x, dim=1, repeats=n_rep). The hidden states go from (batch, + num_key_value_heads, seqlen, head_dim) to (batch, num_attention_heads, seqlen, head_dim) + """ + batch, num_key_value_heads, slen, head_dim = hidden_states.shape + if n_rep == 1: + return hidden_states + hidden_states = hidden_states[:, :, None, :, :].expand(batch, num_key_value_heads, n_rep, slen, head_dim) + return hidden_states.reshape(batch, num_key_value_heads * n_rep, slen, head_dim) + + +# Modified from transformers.model.llama.modeling_llama.LlamaAttention +class InternLM2Attention(nn.Module): + """Multi-headed attention from 'Attention Is All You Need' paper""" + + def __init__(self, config: InternLM2Config): + super().__init__() + self.config = config + self.hidden_size = config.hidden_size + self.num_heads = config.num_attention_heads + self.head_dim = self.hidden_size // self.num_heads + self.num_key_value_heads = config.num_key_value_heads + self.num_key_value_groups = self.num_heads // self.num_key_value_heads + self.max_position_embeddings = config.max_position_embeddings + self.is_causal = True + + if (self.head_dim * self.num_heads) != self.hidden_size: + raise ValueError( + f'hidden_size must be divisible by num_heads (got `hidden_size`: {self.hidden_size}' + f' and `num_heads`: {self.num_heads}).' + ) + + self.wqkv = nn.Linear( + self.hidden_size, + (self.num_heads + 2 * self.num_key_value_heads) * self.head_dim, + bias=config.bias, + ) + + self.wo = nn.Linear(self.num_heads * self.head_dim, self.hidden_size, bias=config.bias) + self._init_rope() + + def _init_rope(self): + if self.config.rope_scaling is None: + self.rotary_emb = InternLM2RotaryEmbedding( + self.head_dim, + max_position_embeddings=self.max_position_embeddings, + base=self.config.rope_theta, + ) + else: + scaling_type = self.config.rope_scaling['type'] + scaling_factor = self.config.rope_scaling['factor'] + if scaling_type == 'dynamic': + self.rotary_emb = InternLM2DynamicNTKScalingRotaryEmbedding( + self.head_dim, + max_position_embeddings=self.max_position_embeddings, + base=self.config.rope_theta, + scaling_factor=scaling_factor, + ) + elif scaling_type == 'linear': + self.rotary_emb = InternLM2LinearScalingRotaryEmbedding( + self.head_dim, + max_position_embeddings=self.max_position_embeddings, + base=self.config.rope_theta, + scaling_factor=scaling_factor, + ) + else: + raise ValueError("Currently we only support rotary embedding's type being 'dynamic' or 'linear'.") + return self.rotary_emb + + def _shape(self, tensor: torch.Tensor, seq_len: int, bsz: int): + return tensor.view(bsz, seq_len, self.num_heads, self.head_dim).transpose(1, 2).contiguous() + + def forward( + self, + hidden_states: torch.Tensor, + attention_mask: Optional[torch.Tensor] = None, + position_ids: Optional[torch.LongTensor] = None, + past_key_value: Optional[Tuple[torch.Tensor]] = None, + output_attentions: bool = False, + use_cache: bool = False, + **kwargs, + ) -> Tuple[torch.Tensor, Optional[torch.Tensor], Optional[Tuple[torch.Tensor]]]: + if 'padding_mask' in kwargs: + warnings.warn( + 'Passing `padding_mask` is deprecated and will be removed in v4.37. ' + 'Please make sure use `attention_mask` instead.`' + ) + + bsz, q_len, _ = hidden_states.size() + + qkv_states = self.wqkv(hidden_states) + + qkv_states = rearrange( + qkv_states, + 'b q (h gs d) -> b q h gs d', + gs=2 + self.num_key_value_groups, + d=self.head_dim, + ) + + query_states = qkv_states[..., : self.num_key_value_groups, :] + query_states = rearrange(query_states, 'b q h gs d -> b q (h gs) d') + key_states = qkv_states[..., -2, :] + value_states = qkv_states[..., -1, :] + + query_states = query_states.transpose(1, 2) + key_states = key_states.transpose(1, 2) + value_states = value_states.transpose(1, 2) + + kv_seq_len = key_states.shape[-2] + if past_key_value is not None: + kv_seq_len += past_key_value[0].shape[-2] + cos, sin = self.rotary_emb(value_states, seq_len=kv_seq_len) + query_states, key_states = apply_rotary_pos_emb(query_states, key_states, cos, sin, position_ids) + + if past_key_value is not None: + # reuse k, v, self_attention + key_states = torch.cat([past_key_value[0], key_states], dim=2) + value_states = torch.cat([past_key_value[1], value_states], dim=2) + + past_key_value = (key_states, value_states) if use_cache else None + + key_states = repeat_kv(key_states, self.num_key_value_groups) + value_states = repeat_kv(value_states, self.num_key_value_groups) + + attn_weights = torch.matmul(query_states, key_states.transpose(2, 3)) / math.sqrt(self.head_dim) + + if attn_weights.size() != (bsz, self.num_heads, q_len, kv_seq_len): + raise ValueError( + f'Attention weights should be of size {(bsz, self.num_heads, q_len, kv_seq_len)}, but is' + f' {attn_weights.size()}' + ) + + if attention_mask is not None: + if attention_mask.size() != (bsz, 1, q_len, kv_seq_len): + raise ValueError( + f'Attention mask should be of size {(bsz, 1, q_len, kv_seq_len)}, but is {attention_mask.size()}' + ) + attn_weights = attn_weights + attention_mask + + # upcast attention to fp32 + attn_weights = nn.functional.softmax(attn_weights, dim=-1, dtype=torch.float32).to(query_states.dtype) + attn_output = torch.matmul(attn_weights, value_states) + + if attn_output.size() != (bsz, self.num_heads, q_len, self.head_dim): + raise ValueError( + f'`attn_output` should be of size {(bsz, self.num_heads, q_len, self.head_dim)}, but is' + f' {attn_output.size()}' + ) + + attn_output = attn_output.transpose(1, 2).contiguous() + attn_output = attn_output.reshape(bsz, q_len, self.hidden_size) + + attn_output = self.wo(attn_output) + + if not output_attentions: + attn_weights = None + + return attn_output, attn_weights, past_key_value + + +# Modified from transformers.model.llama.modeling_llama.InternLM2FlashAttention2 +class InternLM2FlashAttention2(InternLM2Attention): + """ + InternLM2 flash attention module. This module inherits from `InternLM2Attention` as the weights of the module stays + untouched. The only required change would be on the forward pass where it needs to correctly call the public API of + flash attention and deal with padding tokens in case the input contains any of them. + """ + + def forward( + self, + hidden_states: torch.Tensor, + attention_mask: Optional[torch.LongTensor] = None, + position_ids: Optional[torch.LongTensor] = None, + past_key_value: Optional[Tuple[torch.Tensor]] = None, + output_attentions: bool = False, + use_cache: bool = False, + **kwargs, + ) -> Tuple[torch.Tensor, Optional[torch.Tensor], Optional[Tuple[torch.Tensor]]]: + # InternLM2FlashAttention2 attention does not support output_attentions + if 'padding_mask' in kwargs: + warnings.warn( + 'Passing `padding_mask` is deprecated and will be removed in v4.37. ' + 'Please make sure use `attention_mask` instead.`' + ) + + # overwrite attention_mask with padding_mask + attention_mask = kwargs.pop('padding_mask') + + output_attentions = False + + bsz, q_len, _ = hidden_states.size() + + qkv_states = self.wqkv(hidden_states) + + qkv_states = rearrange( + qkv_states, + 'b q (h gs d) -> b q h gs d', + gs=2 + self.num_key_value_groups, + d=self.head_dim, + ) + + query_states = qkv_states[..., : self.num_key_value_groups, :] + query_states = rearrange(query_states, 'b q h gs d -> b q (h gs) d') + key_states = qkv_states[..., -2, :] + value_states = qkv_states[..., -1, :] + + query_states = query_states.transpose(1, 2) + key_states = key_states.transpose(1, 2) + value_states = value_states.transpose(1, 2) + + kv_seq_len = key_states.shape[-2] + if past_key_value is not None: + kv_seq_len += past_key_value[0].shape[-2] + + cos, sin = self.rotary_emb(value_states, seq_len=kv_seq_len) + + query_states, key_states = apply_rotary_pos_emb(query_states, key_states, cos, sin, position_ids) + + if past_key_value is not None: + # reuse k, v, self_attention + key_states = torch.cat([past_key_value[0], key_states], dim=2) + value_states = torch.cat([past_key_value[1], value_states], dim=2) + + past_key_value = (key_states, value_states) if use_cache else None + + query_states = query_states.transpose(1, 2) + key_states = key_states.transpose(1, 2) + value_states = value_states.transpose(1, 2) + + attn_output = self._flash_attention_forward( + query_states, key_states, value_states, attention_mask, q_len + ) + attn_output = attn_output.reshape(bsz, q_len, self.hidden_size).contiguous() + attn_output = self.wo(attn_output) + + if not output_attentions: + attn_weights = None + + return attn_output, attn_weights, past_key_value + + def _flash_attention_forward( + self, query_states, key_states, value_states, attention_mask, query_length, dropout=0.0, softmax_scale=None + ): + """ + Calls the forward method of Flash Attention - if the input hidden states contain at least one padding token + first unpad the input, then computes the attention scores and pad the final attention scores. + + Args: + query_states (`torch.Tensor`): + Input query states to be passed to Flash Attention API + key_states (`torch.Tensor`): + Input key states to be passed to Flash Attention API + value_states (`torch.Tensor`): + Input value states to be passed to Flash Attention API + attention_mask (`torch.Tensor`): + The padding mask - corresponds to a tensor of size `(batch_size, seq_len)` where 0 stands for the + position of padding tokens and 1 for the position of non-padding tokens. + dropout (`int`, *optional*): + Attention dropout + softmax_scale (`float`, *optional*): + The scaling of QK^T before applying softmax. Default to 1 / sqrt(head_dim) + """ + # Contains at least one padding token in the sequence + causal = self.is_causal and query_length != 1 + if attention_mask is not None: + batch_size = query_states.shape[0] + query_states, key_states, value_states, indices_q, cu_seq_lens, max_seq_lens = self._unpad_input( + query_states, key_states, value_states, attention_mask, query_length + ) + + cu_seqlens_q, cu_seqlens_k = cu_seq_lens + max_seqlen_in_batch_q, max_seqlen_in_batch_k = max_seq_lens + + attn_output_unpad = flash_attn_varlen_func( + query_states, + key_states, + value_states, + cu_seqlens_q=cu_seqlens_q, + cu_seqlens_k=cu_seqlens_k, + max_seqlen_q=max_seqlen_in_batch_q, + max_seqlen_k=max_seqlen_in_batch_k, + dropout_p=dropout, + softmax_scale=softmax_scale, + causal=causal, + ) + + attn_output = pad_input(attn_output_unpad, indices_q, batch_size, query_length) + else: + attn_output = flash_attn_func( + query_states, key_states, value_states, dropout, softmax_scale=softmax_scale, causal=causal + ) + + return attn_output + + def _unpad_input(self, query_layer, key_layer, value_layer, attention_mask, query_length): + indices_k, cu_seqlens_k, max_seqlen_in_batch_k = _get_unpad_data(attention_mask) + batch_size, kv_seq_len, num_key_value_heads, head_dim = key_layer.shape + + key_layer = index_first_axis( + key_layer.reshape(batch_size * kv_seq_len, num_key_value_heads, head_dim), indices_k + ) + value_layer = index_first_axis( + value_layer.reshape(batch_size * kv_seq_len, num_key_value_heads, head_dim), indices_k + ) + + if query_length == kv_seq_len: + query_layer = index_first_axis( + query_layer.reshape(batch_size * kv_seq_len, self.num_heads, head_dim), indices_k + ) + cu_seqlens_q = cu_seqlens_k + max_seqlen_in_batch_q = max_seqlen_in_batch_k + indices_q = indices_k + elif query_length == 1: + max_seqlen_in_batch_q = 1 + cu_seqlens_q = torch.arange( + batch_size + 1, dtype=torch.int32, device=query_layer.device + ) # There is a memcpy here, that is very bad. + indices_q = cu_seqlens_q[:-1] + query_layer = query_layer.squeeze(1) + else: + # The -q_len: slice assumes left padding. + attention_mask = attention_mask[:, -query_length:] + query_layer, indices_q, cu_seqlens_q, max_seqlen_in_batch_q = unpad_input(query_layer, attention_mask) + + return ( + query_layer, + key_layer, + value_layer, + indices_q.to(torch.int64), + (cu_seqlens_q, cu_seqlens_k), + (max_seqlen_in_batch_q, max_seqlen_in_batch_k), + ) + + +INTERNLM2_ATTENTION_CLASSES = { + 'eager': InternLM2Attention, + 'flash_attention_2': InternLM2FlashAttention2, +} + + +# Modified from transformers.model.llama.modeling_llama.LlamaDecoderLayer +class InternLM2DecoderLayer(nn.Module): + def __init__(self, config: InternLM2Config): + super().__init__() + self.hidden_size = config.hidden_size + + self.attention = INTERNLM2_ATTENTION_CLASSES[config.attn_implementation](config=config) + + self.feed_forward = InternLM2MLP(config) + self.attention_norm = InternLM2RMSNorm(config.hidden_size, eps=config.rms_norm_eps) + self.ffn_norm = InternLM2RMSNorm(config.hidden_size, eps=config.rms_norm_eps) + + def forward( + self, + hidden_states: torch.Tensor, + attention_mask: Optional[torch.Tensor] = None, + position_ids: Optional[torch.LongTensor] = None, + past_key_value: Optional[Tuple[torch.Tensor]] = None, + output_attentions: Optional[bool] = False, + use_cache: Optional[bool] = False, + **kwargs, + ) -> Tuple[torch.FloatTensor, Optional[Tuple[torch.FloatTensor, torch.FloatTensor]]]: + """ + Args: + hidden_states (`torch.FloatTensor`): input to the layer of shape `(batch, seq_len, embed_dim)` + attention_mask (`torch.FloatTensor`, *optional*): + attention mask of size `(batch_size, sequence_length)` if flash attention is used or `(batch_size, 1, + query_sequence_length, key_sequence_length)` if default attention is used. + output_attentions (`bool`, *optional*): + Whether or not to return the attentions tensors of all attention layers. See `attentions` under + returned tensors for more detail. + use_cache (`bool`, *optional*): + If set to `True`, `past_key_values` key value states are returned and can be used to speed up decoding + (see `past_key_values`). + past_key_value (`Tuple(torch.FloatTensor)`, *optional*): cached past key and value projection states + """ + if 'padding_mask' in kwargs: + warnings.warn( + 'Passing `padding_mask` is deprecated and will be removed in v4.37. ' + 'Please make sure use `attention_mask` instead.`' + ) + + residual = hidden_states + + hidden_states = self.attention_norm(hidden_states) + + # Self Attention + hidden_states, self_attn_weights, present_key_value = self.attention( + hidden_states=hidden_states, + attention_mask=attention_mask, + position_ids=position_ids, + past_key_value=past_key_value, + output_attentions=output_attentions, + use_cache=use_cache, + **kwargs, + ) + hidden_states = residual + hidden_states + + # Fully Connected + residual = hidden_states + hidden_states = self.ffn_norm(hidden_states) + hidden_states = self.feed_forward(hidden_states) + hidden_states = residual + hidden_states + + outputs = (hidden_states,) + + if output_attentions: + outputs += (self_attn_weights,) + + if use_cache: + outputs += (present_key_value,) + + return outputs + + +InternLM2_START_DOCSTRING = r""" + This model inherits from [`PreTrainedModel`]. Check the superclass documentation for the generic methods the + library implements for all its model (such as downloading or saving, resizing the input embeddings, pruning heads + etc.) + + This model is also a PyTorch [torch.nn.Module](https://pytorch.org/docs/stable/nn.html#torch.nn.Module) subclass. + Use it as a regular PyTorch Module and refer to the PyTorch documentation for all matter related to general usage + and behavior. + + Parameters: + config ([`InternLM2Config`]): + Model configuration class with all the parameters of the model. Initializing with a config file does not + load the weights associated with the model, only the configuration. Check out the + [`~PreTrainedModel.from_pretrained`] method to load the model weights. +""" + + +# Copied from transformers.models.llama.modeling_llama.LlamaPreTrainedModel with Llama->InternLM2 +@add_start_docstrings( + 'The bare InternLM2 Model outputting raw hidden-states without any specific head on top.', + InternLM2_START_DOCSTRING, +) +class InternLM2PreTrainedModel(PreTrainedModel): + config_class = InternLM2Config + base_model_prefix = 'model' + supports_gradient_checkpointing = True + _no_split_modules = ['InternLM2DecoderLayer'] + _skip_keys_device_placement = 'past_key_values' + _supports_flash_attn_2 = True + + def _init_weights(self, module): + std = self.config.initializer_range + if isinstance(module, nn.Linear): + module.weight.data.normal_(mean=0.0, std=std) + if module.bias is not None: + module.bias.data.zero_() + elif isinstance(module, nn.Embedding): + module.weight.data.normal_(mean=0.0, std=std) + if module.padding_idx is not None: + module.weight.data[module.padding_idx].zero_() + + +InternLM2_INPUTS_DOCSTRING = r""" + Args: + input_ids (`torch.LongTensor` of shape `(batch_size, sequence_length)`): + Indices of input sequence tokens in the vocabulary. Padding will be ignored by default should you provide + it. + + Indices can be obtained using [`AutoTokenizer`]. See [`PreTrainedTokenizer.encode`] and + [`PreTrainedTokenizer.__call__`] for details. + + [What are input IDs?](../glossary#input-ids) + attention_mask (`torch.Tensor` of shape `(batch_size, sequence_length)`, *optional*): + Mask to avoid performing attention on padding token indices. Mask values selected in `[0, 1]`: + + - 1 for tokens that are **not masked**, + - 0 for tokens that are **masked**. + + [What are attention masks?](../glossary#attention-mask) + + Indices can be obtained using [`AutoTokenizer`]. See [`PreTrainedTokenizer.encode`] and + [`PreTrainedTokenizer.__call__`] for details. + + If `past_key_values` is used, optionally only the last `input_ids` have to be input (see + `past_key_values`). + + If you want to change padding behavior, you should read [`modeling_opt._prepare_decoder_attention_mask`] + and modify to your needs. See diagram 1 in [the paper](https://arxiv.org/abs/1910.13461) for more + information on the default strategy. + + - 1 indicates the head is **not masked**, + - 0 indicates the head is **masked**. + position_ids (`torch.LongTensor` of shape `(batch_size, sequence_length)`, *optional*): + Indices of positions of each input sequence tokens in the position embeddings. Selected in the range `[0, + config.n_positions - 1]`. + + [What are position IDs?](../glossary#position-ids) + past_key_values (`tuple(tuple(torch.FloatTensor))`, *optional*, returned when `use_cache=True` is passed or + when `config.use_cache=True`): + Tuple of `tuple(torch.FloatTensor)` of length `config.n_layers`, with each tuple having 2 tensors of shape + `(batch_size, num_heads, sequence_length, embed_size_per_head)`) and 2 additional tensors of shape + `(batch_size, num_heads, decoder_sequence_length, embed_size_per_head)`. + + Contains pre-computed hidden-states (key and values in the self-attention blocks and in the cross-attention + blocks) that can be used (see `past_key_values` input) to speed up sequential decoding. + + If `past_key_values` are used, the user can optionally input only the last `input_ids` (those that don't + have their past key value states given to this model) of shape `(batch_size, 1)` instead of all `input_ids` + of shape `(batch_size, sequence_length)`. + inputs_embeds (`torch.FloatTensor` of shape `(batch_size, sequence_length, hidden_size)`, *optional*): + Optionally, instead of passing `input_ids` you can choose to directly pass an embedded representation. This + is useful if you want more control over how to convert `input_ids` indices into associated vectors than the + model's internal embedding lookup matrix. + use_cache (`bool`, *optional*): + If set to `True`, `past_key_values` key value states are returned and can be used to speed up decoding (see + `past_key_values`). + output_attentions (`bool`, *optional*): + Whether or not to return the attentions tensors of all attention layers. See `attentions` under returned + tensors for more detail. + output_hidden_states (`bool`, *optional*): + Whether or not to return the hidden states of all layers. See `hidden_states` under returned tensors for + more detail. + return_dict (`bool`, *optional*): + Whether or not to return a [`~utils.ModelOutput`] instead of a plain tuple. +""" + + +# Modified from transformers.model.llama.modeling_llama.LlamaModel +@add_start_docstrings( + 'The bare InternLM2 Model outputting raw hidden-states without any specific head on top.', + InternLM2_START_DOCSTRING, +) +class InternLM2Model(InternLM2PreTrainedModel): + """ + Transformer decoder consisting of *config.num_hidden_layers* layers. Each layer is a [`InternLM2DecoderLayer`] + + Args: + config: InternLM2Config + """ + + _auto_class = 'AutoModel' + + def __init__(self, config: InternLM2Config): + super().__init__(config) + self.padding_idx = config.pad_token_id + self.vocab_size = config.vocab_size + self.config = config + if not has_flash_attn: + self.config.attn_implementation = 'eager' + print('Warning: Flash attention is not available, using eager attention instead.') + + self.tok_embeddings = nn.Embedding(config.vocab_size, config.hidden_size, self.padding_idx) + + self.layers = nn.ModuleList([InternLM2DecoderLayer(config) for _ in range(config.num_hidden_layers)]) + self.norm = InternLM2RMSNorm(config.hidden_size, eps=config.rms_norm_eps) + + self.gradient_checkpointing = False + # Initialize weights and apply final processing + self.post_init() + + def get_input_embeddings(self): + return self.tok_embeddings + + def set_input_embeddings(self, value): + self.tok_embeddings = value + + def _prepare_decoder_attention_mask(self, attention_mask, input_shape, inputs_embeds, past_key_values_length): + # create causal mask + # [bsz, seq_len] -> [bsz, 1, tgt_seq_len, src_seq_len] + combined_attention_mask = None + if input_shape[-1] > 1: + combined_attention_mask = _make_causal_mask( + input_shape, + inputs_embeds.dtype, + device=inputs_embeds.device, + past_key_values_length=past_key_values_length, + ) + + if attention_mask is not None: + # [bsz, seq_len] -> [bsz, 1, tgt_seq_len, src_seq_len] + expanded_attn_mask = _expand_mask(attention_mask, inputs_embeds.dtype, tgt_len=input_shape[-1]).to( + inputs_embeds.device + ) + combined_attention_mask = ( + expanded_attn_mask if combined_attention_mask is None else expanded_attn_mask + combined_attention_mask + ) + + return combined_attention_mask + + @add_start_docstrings_to_model_forward(InternLM2_INPUTS_DOCSTRING) + def forward( + self, + input_ids: torch.LongTensor = None, + attention_mask: Optional[torch.Tensor] = None, + position_ids: Optional[torch.LongTensor] = None, + past_key_values: Optional[List[torch.FloatTensor]] = None, + inputs_embeds: Optional[torch.FloatTensor] = None, + use_cache: Optional[bool] = None, + output_attentions: Optional[bool] = None, + output_hidden_states: Optional[bool] = None, + return_dict: Optional[bool] = None, + ) -> Union[Tuple, BaseModelOutputWithPast]: + output_attentions = output_attentions if output_attentions is not None else self.config.output_attentions + output_hidden_states = ( + output_hidden_states if output_hidden_states is not None else self.config.output_hidden_states + ) + use_cache = use_cache if use_cache is not None else self.config.use_cache + + return_dict = return_dict if return_dict is not None else self.config.use_return_dict + + if self.config.attn_implementation == 'flash_attention_2': + _import_flash_attn() + + # retrieve input_ids and inputs_embeds + if input_ids is not None and inputs_embeds is not None: + raise ValueError('You cannot specify both input_ids and inputs_embeds at the same time') + elif input_ids is not None: + batch_size, seq_length = input_ids.shape[:2] + elif inputs_embeds is not None: + batch_size, seq_length = inputs_embeds.shape[:2] + else: + raise ValueError('You have to specify either input_ids or inputs_embeds') + + seq_length_with_past = seq_length + past_key_values_length = 0 + if past_key_values is not None: + past_key_values_length = past_key_values[0][0].shape[2] + seq_length_with_past = seq_length_with_past + past_key_values_length + + if position_ids is None: + device = input_ids.device if input_ids is not None else inputs_embeds.device + position_ids = torch.arange( + past_key_values_length, seq_length + past_key_values_length, dtype=torch.long, device=device + ) + position_ids = position_ids.unsqueeze(0) + + if inputs_embeds is None: + inputs_embeds = self.tok_embeddings(input_ids) + + if self.config.attn_implementation == 'flash_attention_2': + # 2d mask is passed through the layers + attention_mask = attention_mask if (attention_mask is not None and 0 in attention_mask) else None + else: + if attention_mask is None: + attention_mask = torch.ones( + (batch_size, seq_length_with_past), dtype=torch.bool, device=inputs_embeds.device + ) + attention_mask = self._prepare_decoder_attention_mask( + attention_mask, (batch_size, seq_length), inputs_embeds, past_key_values_length + ) + + # embed positions + hidden_states = inputs_embeds + + if self.gradient_checkpointing and self.training: + if use_cache: + logger.warning_once( + '`use_cache=True` is incompatible with gradient checkpointing. Setting `use_cache=False`...' + ) + use_cache = False + + # decoder layers + all_hidden_states = () if output_hidden_states else None + all_self_attns = () if output_attentions else None + next_decoder_cache = () if use_cache else None + + for idx, decoder_layer in enumerate(self.layers): + if output_hidden_states: + all_hidden_states += (hidden_states,) + + past_key_value = past_key_values[idx] if past_key_values is not None else None + + if self.gradient_checkpointing and self.training: + + def create_custom_forward(module): + def custom_forward(*inputs): + # None for past_key_value + return module(*inputs, output_attentions, None) + + return custom_forward + + layer_outputs = torch.utils.checkpoint.checkpoint( + create_custom_forward(decoder_layer), + hidden_states, + attention_mask, + position_ids, + None, + ) + else: + layer_outputs = decoder_layer( + hidden_states, + attention_mask=attention_mask, + position_ids=position_ids, + past_key_value=past_key_value, + output_attentions=output_attentions, + use_cache=use_cache, + ) + + hidden_states = layer_outputs[0] + + if use_cache: + next_decoder_cache += (layer_outputs[2 if output_attentions else 1],) + + if output_attentions: + all_self_attns += (layer_outputs[1],) + + hidden_states = self.norm(hidden_states) + + # add hidden states from the last decoder layer + if output_hidden_states: + all_hidden_states += (hidden_states,) + + next_cache = next_decoder_cache if use_cache else None + if not return_dict: + return tuple(v for v in [hidden_states, next_cache, all_hidden_states, all_self_attns] if v is not None) + return BaseModelOutputWithPast( + last_hidden_state=hidden_states, + past_key_values=next_cache, + hidden_states=all_hidden_states, + attentions=all_self_attns, + ) + + +# Modified from transformers.model.llama.modeling_llama.LlamaForCausalLM +class InternLM2ForCausalLM(InternLM2PreTrainedModel): + _auto_class = 'AutoModelForCausalLM' + + _tied_weights_keys = ['output.weight'] + + def __init__(self, config): + super().__init__(config) + self.model = InternLM2Model(config) + self.vocab_size = config.vocab_size + self.output = nn.Linear(config.hidden_size, config.vocab_size, bias=False) + + # Initialize weights and apply final processing + self.post_init() + + def get_input_embeddings(self): + return self.model.tok_embeddings + + def set_input_embeddings(self, value): + self.model.tok_embeddings = value + + def get_output_embeddings(self): + return self.output + + def set_output_embeddings(self, new_embeddings): + self.output = new_embeddings + + def set_decoder(self, decoder): + self.model = decoder + + def get_decoder(self): + return self.model + + @add_start_docstrings_to_model_forward(InternLM2_INPUTS_DOCSTRING) + @replace_return_docstrings(output_type=CausalLMOutputWithPast, config_class=_CONFIG_FOR_DOC) + def forward( + self, + input_ids: torch.LongTensor = None, + attention_mask: Optional[torch.Tensor] = None, + position_ids: Optional[torch.LongTensor] = None, + past_key_values: Optional[List[torch.FloatTensor]] = None, + inputs_embeds: Optional[torch.FloatTensor] = None, + labels: Optional[torch.LongTensor] = None, + use_cache: Optional[bool] = None, + output_attentions: Optional[bool] = None, + output_hidden_states: Optional[bool] = None, + return_dict: Optional[bool] = None, + ) -> Union[Tuple, CausalLMOutputWithPast]: + r""" + Args: + labels (`torch.LongTensor` of shape `(batch_size, sequence_length)`, *optional*): + Labels for computing the masked language modeling loss. Indices should either be in `[0, ..., + config.vocab_size]` or -100 (see `input_ids` docstring). Tokens with indices set to `-100` are ignored + (masked), the loss is only computed for the tokens with labels in `[0, ..., config.vocab_size]`. + + Returns: + + Example: + + ```python + >>> from transformers import AutoTokenizer, InternLM2ForCausalLM + + >>> model = InternLM2ForCausalLM.from_pretrained(PATH_TO_CONVERTED_WEIGHTS) + >>> tokenizer = AutoTokenizer.from_pretrained(PATH_TO_CONVERTED_TOKENIZER) + + >>> prompt = "Hey, are you conscious? Can you talk to me?" + >>> inputs = tokenizer(prompt, return_tensors="pt") + + >>> # Generate + >>> generate_ids = model.generate(inputs.input_ids, max_length=30) + >>> tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0] + "Hey, are you conscious? Can you talk to me?\nI'm not conscious, but I can talk to you." + ```""" + + output_attentions = output_attentions if output_attentions is not None else self.config.output_attentions + output_hidden_states = ( + output_hidden_states if output_hidden_states is not None else self.config.output_hidden_states + ) + return_dict = return_dict if return_dict is not None else self.config.use_return_dict + + # decoder outputs consists of (dec_features, layer_state, dec_hidden, dec_attn) + outputs = self.model( + input_ids=input_ids, + attention_mask=attention_mask, + position_ids=position_ids, + past_key_values=past_key_values, + inputs_embeds=inputs_embeds, + use_cache=use_cache, + output_attentions=output_attentions, + output_hidden_states=output_hidden_states, + return_dict=return_dict, + ) + + hidden_states = outputs[0] + logits = self.output(hidden_states) + logits = logits.float() + + loss = None + if labels is not None: + # Shift so that tokens < n predict n + shift_logits = logits[..., :-1, :].contiguous() + shift_labels = labels[..., 1:].contiguous() + # Flatten the tokens + loss_fct = CrossEntropyLoss() + shift_logits = shift_logits.view(-1, self.config.vocab_size) + shift_labels = shift_labels.view(-1) + # Enable model parallelism + shift_labels = shift_labels.to(shift_logits.device) + loss = loss_fct(shift_logits, shift_labels) + + if not return_dict: + output = (logits,) + outputs[1:] + return (loss,) + output if loss is not None else output + + device = input_ids.device if input_ids is not None else inputs_embeds.device + output = CausalLMOutputWithPast( + loss=loss, + logits=logits, + past_key_values=outputs.past_key_values, + hidden_states=outputs.hidden_states, + attentions=outputs.attentions, + ) + output['logits'] = output['logits'].to(device) + return output + + def prepare_inputs_for_generation( + self, input_ids, past_key_values=None, attention_mask=None, inputs_embeds=None, **kwargs + ): + if past_key_values is not None: + past_length = past_key_values[0][0].shape[2] + + # Some generation methods already pass only the last input ID + if input_ids.shape[1] > past_length: + remove_prefix_length = past_length + else: + # Default to old behavior: keep only final ID + remove_prefix_length = input_ids.shape[1] - 1 + + input_ids = input_ids[:, remove_prefix_length:] + + position_ids = kwargs.get('position_ids', None) + if attention_mask is not None and position_ids is None: + # create position_ids on the fly for batch generation + position_ids = attention_mask.long().cumsum(-1) - 1 + position_ids.masked_fill_(attention_mask == 0, 1) + if past_key_values: + position_ids = position_ids[:, -input_ids.shape[1] :] + + # if `inputs_embeds` are passed, we only want to use them in the 1st generation step + if inputs_embeds is not None and past_key_values is None: + model_inputs = {'inputs_embeds': inputs_embeds} + else: + model_inputs = {'input_ids': input_ids} + + model_inputs.update( + { + 'position_ids': position_ids, + 'past_key_values': past_key_values, + 'use_cache': kwargs.get('use_cache'), + 'attention_mask': attention_mask, + } + ) + return model_inputs + + @staticmethod + def _reorder_cache(past_key_values, beam_idx): + reordered_past = () + for layer_past in past_key_values: + reordered_past += ( + tuple(past_state.index_select(0, beam_idx.to(past_state.device)) for past_state in layer_past), + ) + return reordered_past + + def build_inputs(self, tokenizer, query: str, history: List[Tuple[str, str]] = [], meta_instruction=''): + if tokenizer.add_bos_token: + prompt = '' + else: + prompt = tokenizer.bos_token + if meta_instruction: + prompt += f"""<|im_start|>system\n{meta_instruction}<|im_end|>\n""" + for record in history: + prompt += f"""<|im_start|>user\n{record[0]}<|im_end|>\n<|im_start|>assistant\n{record[1]}<|im_end|>\n""" + prompt += f"""<|im_start|>user\n{query}<|im_end|>\n<|im_start|>assistant\n""" + return tokenizer([prompt], return_tensors='pt') + + @torch.no_grad() + def chat( + self, + tokenizer, + query: str, + history: List[Tuple[str, str]] = [], + streamer: Optional[BaseStreamer] = None, + max_new_tokens: int = 1024, + do_sample: bool = True, + temperature: float = 0.8, + top_p: float = 0.8, + meta_instruction: str = 'You are an AI assistant whose name is InternLM (书生·浦语).\n' + '- InternLM (书生·浦语) is a conversational language model that is developed by Shanghai AI Laboratory (上海人工智能实验室). It is designed to be helpful, honest, and harmless.\n' + '- InternLM (书生·浦语) can understand and communicate fluently in the language chosen by the user such as English and 中文.', + **kwargs, + ): + inputs = self.build_inputs(tokenizer, query, history, meta_instruction) + inputs = {k: v.to(self.device) for k, v in inputs.items() if torch.is_tensor(v)} + # also add end-of-assistant token in eos token id to avoid unnecessary generation + eos_token_id = [tokenizer.eos_token_id, tokenizer.convert_tokens_to_ids(['<|im_end|>'])[0]] + outputs = self.generate( + **inputs, + streamer=streamer, + max_new_tokens=max_new_tokens, + do_sample=do_sample, + temperature=temperature, + top_p=top_p, + eos_token_id=eos_token_id, + **kwargs, + ) + outputs = outputs[0].cpu().tolist()[len(inputs['input_ids'][0]) :] + response = tokenizer.decode(outputs, skip_special_tokens=True) + response = response.split('<|im_end|>')[0] + history = history + [(query, response)] + return response, history + + @torch.no_grad() + def stream_chat( + self, + tokenizer, + query: str, + history: List[Tuple[str, str]] = [], + max_new_tokens: int = 1024, + do_sample: bool = True, + temperature: float = 0.8, + top_p: float = 0.8, + **kwargs, + ): + """ + Return a generator in format: (response, history) + Eg. + ('你好，有什么可以帮助您的吗', [('你好', '你好，有什么可以帮助您的吗')]) + ('你好，有什么可以帮助您的吗？', [('你好', '你好，有什么可以帮助您的吗？')]) + """ + if BaseStreamer is None: + raise ModuleNotFoundError( + 'The version of `transformers` is too low. Please make sure ' + 'that you have installed `transformers>=4.28.0`.' + ) + + response_queue = queue.Queue(maxsize=20) + + class ChatStreamer(BaseStreamer): + def __init__(self, tokenizer) -> None: + super().__init__() + self.tokenizer = tokenizer + self.queue = response_queue + self.query = query + self.history = history + self.response = '' + self.cache = [] + self.received_inputs = False + self.queue.put((self.response, history + [(self.query, self.response)])) + + def put(self, value): + if len(value.shape) > 1 and value.shape[0] > 1: + raise ValueError('ChatStreamer only supports batch size 1') + elif len(value.shape) > 1: + value = value[0] + + if not self.received_inputs: + # The first received value is input_ids, ignore here + self.received_inputs = True + return + + self.cache.extend(value.tolist()) + token = self.tokenizer.decode(self.cache, skip_special_tokens=True) + if token.strip() != '<|im_end|>': + self.response = self.response + token + history = self.history + [(self.query, self.response)] + self.queue.put((self.response, history)) + self.cache = [] + else: + self.end() + + def end(self): + self.queue.put(None) + + def stream_producer(): + return self.chat( + tokenizer=tokenizer, + query=query, + streamer=ChatStreamer(tokenizer=tokenizer), + history=history, + max_new_tokens=max_new_tokens, + do_sample=do_sample, + temperature=temperature, + top_p=top_p, + **kwargs, + ) + + def consumer(): + producer = threading.Thread(target=stream_producer) + producer.start() + while True: + res = response_queue.get() + if res is None: + return + yield res + + return consumer() + + +# Copied from transformers.model.llama.modeling_llama.LlamaForSequenceClassification with Llama->InternLM2 +@add_start_docstrings( + """ + The InternLM2 Model transformer with a sequence classification head on top (linear layer). + + [`InternLM2ForSequenceClassification`] uses the last token in order to do the classification, + as other causal models (e.g. GPT-2) do. + + Since it does classification on the last token, it requires to know the position of the last token. If a + `pad_token_id` is defined in the configuration, it finds the last token that is not a padding token in each row. If + no `pad_token_id` is defined, it simply takes the last value in each row of the batch. Since it cannot guess the + padding tokens when `inputs_embeds` are passed instead of `input_ids`, it does the same (take the last value in + each row of the batch). + """, + InternLM2_START_DOCSTRING, +) +class InternLM2ForSequenceClassification(InternLM2PreTrainedModel): + def __init__(self, config): + super().__init__(config) + self.num_labels = config.num_labels + self.model = InternLM2Model(config) + self.score = nn.Linear(config.hidden_size, self.num_labels, bias=False) + + # Initialize weights and apply final processing + self.post_init() + + def get_input_embeddings(self): + return self.model.tok_embeddings + + def set_input_embeddings(self, value): + self.model.tok_embeddings = value + + @add_start_docstrings_to_model_forward(InternLM2_INPUTS_DOCSTRING) + def forward( + self, + input_ids: torch.LongTensor = None, + attention_mask: Optional[torch.Tensor] = None, + position_ids: Optional[torch.LongTensor] = None, + past_key_values: Optional[List[torch.FloatTensor]] = None, + inputs_embeds: Optional[torch.FloatTensor] = None, + labels: Optional[torch.LongTensor] = None, + use_cache: Optional[bool] = None, + output_attentions: Optional[bool] = None, + output_hidden_states: Optional[bool] = None, + return_dict: Optional[bool] = None, + ) -> Union[Tuple, SequenceClassifierOutputWithPast]: + r""" + labels (`torch.LongTensor` of shape `(batch_size,)`, *optional*): + Labels for computing the sequence classification/regression loss. Indices should be in `[0, ..., + config.num_labels - 1]`. If `config.num_labels == 1` a regression loss is computed (Mean-Square loss), If + `config.num_labels > 1` a classification loss is computed (Cross-Entropy). + """ + return_dict = return_dict if return_dict is not None else self.config.use_return_dict + + transformer_outputs = self.model( + input_ids, + attention_mask=attention_mask, + position_ids=position_ids, + past_key_values=past_key_values, + inputs_embeds=inputs_embeds, + use_cache=use_cache, + output_attentions=output_attentions, + output_hidden_states=output_hidden_states, + return_dict=return_dict, + ) + hidden_states = transformer_outputs[0] + logits = self.score(hidden_states) + + if input_ids is not None: + batch_size = input_ids.shape[0] + else: + batch_size = inputs_embeds.shape[0] + + if self.config.pad_token_id is None and batch_size != 1: + raise ValueError('Cannot handle batch sizes > 1 if no padding token is defined.') + if self.config.pad_token_id is None: + sequence_lengths = -1 + else: + if input_ids is not None: + sequence_lengths = (torch.eq(input_ids, self.config.pad_token_id).int().argmax(-1) - 1).to( + logits.device + ) + else: + sequence_lengths = -1 + + pooled_logits = logits[torch.arange(batch_size, device=logits.device), sequence_lengths] + + loss = None + if labels is not None: + labels = labels.to(logits.device) + if self.config.problem_type is None: + if self.num_labels == 1: + self.config.problem_type = 'regression' + elif self.num_labels > 1 and (labels.dtype == torch.long or labels.dtype == torch.int): + self.config.problem_type = 'single_label_classification' + else: + self.config.problem_type = 'multi_label_classification' + + if self.config.problem_type == 'regression': + loss_fct = MSELoss() + if self.num_labels == 1: + loss = loss_fct(pooled_logits.squeeze(), labels.squeeze()) + else: + loss = loss_fct(pooled_logits, labels) + elif self.config.problem_type == 'single_label_classification': + loss_fct = CrossEntropyLoss() + loss = loss_fct(pooled_logits.view(-1, self.num_labels), labels.view(-1)) + elif self.config.problem_type == 'multi_label_classification': + loss_fct = BCEWithLogitsLoss() + loss = loss_fct(pooled_logits, labels) + if not return_dict: + output = (pooled_logits,) + transformer_outputs[1:] + return ((loss,) + output) if loss is not None else output + + return SequenceClassifierOutputWithPast( + loss=loss, + logits=pooled_logits, + past_key_values=transformer_outputs.past_key_values, + hidden_states=transformer_outputs.hidden_states, + attentions=transformer_outputs.attentions, + ) diff --git a/InternVL-main/internvl_chat/work_dirs/internvl_chat_v2_5/mmvet/200/modeling_internvl_chat.py b/InternVL-main/internvl_chat/work_dirs/internvl_chat_v2_5/mmvet/200/modeling_internvl_chat.py new file mode 100644 index 0000000000000000000000000000000000000000..c4014b13f436084268a6ba6d332afcd850c4e82c --- /dev/null +++ b/InternVL-main/internvl_chat/work_dirs/internvl_chat_v2_5/mmvet/200/modeling_internvl_chat.py @@ -0,0 +1,349 @@ +# -------------------------------------------------------- +# InternVL +# Copyright (c) 2024 OpenGVLab +# Licensed under The MIT License [see LICENSE for details] +# -------------------------------------------------------- + +import warnings +from typing import List, Optional, Tuple, Union + +import torch.utils.checkpoint +import transformers +from torch import nn +from torch.nn import CrossEntropyLoss +from transformers import (AutoModel, GenerationConfig, LlamaForCausalLM, + LlamaTokenizer) +from transformers.modeling_outputs import CausalLMOutputWithPast +from transformers.modeling_utils import PreTrainedModel +from transformers.utils import ModelOutput, logging + +from .configuration_internvl_chat import InternVLChatConfig +from .conversation import get_conv_template +from .modeling_intern_vit import InternVisionModel, has_flash_attn +from .modeling_internlm2 import InternLM2ForCausalLM + +logger = logging.get_logger(__name__) + + +def version_cmp(v1, v2, op='eq'): + import operator + + from packaging import version + op_func = getattr(operator, op) + return op_func(version.parse(v1), version.parse(v2)) + + +class InternVLChatModel(PreTrainedModel): + config_class = InternVLChatConfig + main_input_name = 'pixel_values' + base_model_prefix = 'language_model' + _supports_flash_attn_2 = True + _no_split_modules = ['InternVisionModel', 'LlamaDecoderLayer', 'InternLM2DecoderLayer'] + + def __init__(self, config: InternVLChatConfig, vision_model=None, language_model=None, use_flash_attn=True): + super().__init__(config) + + assert version_cmp(transformers.__version__, '4.37.0', 'ge') + image_size = config.force_image_size or config.vision_config.image_size + patch_size = config.vision_config.patch_size + self.patch_size = patch_size + self.select_layer = config.select_layer + self.template = config.template + self.num_image_token = int((image_size // patch_size) ** 2 * (config.downsample_ratio ** 2)) + self.downsample_ratio = config.downsample_ratio + self.ps_version = config.ps_version + use_flash_attn = use_flash_attn if has_flash_attn else False + config.vision_config.use_flash_attn = True if use_flash_attn else False + config.llm_config.attn_implementation = 'flash_attention_2' if use_flash_attn else 'eager' + + logger.info(f'num_image_token: {self.num_image_token}') + logger.info(f'ps_version: {self.ps_version}') + if vision_model is not None: + self.vision_model = vision_model + else: + self.vision_model = InternVisionModel(config.vision_config) + if language_model is not None: + self.language_model = language_model + else: + if config.llm_config.architectures[0] == 'LlamaForCausalLM': + self.language_model = LlamaForCausalLM(config.llm_config) + elif config.llm_config.architectures[0] == 'InternLM2ForCausalLM': + self.language_model = InternLM2ForCausalLM(config.llm_config) + else: + raise NotImplementedError(f'{config.llm_config.architectures[0]} is not implemented.') + + vit_hidden_size = config.vision_config.hidden_size + llm_hidden_size = config.llm_config.hidden_size + + self.mlp1 = nn.Sequential( + nn.LayerNorm(vit_hidden_size * int(1 / self.downsample_ratio) ** 2), + nn.Linear(vit_hidden_size * int(1 / self.downsample_ratio) ** 2, llm_hidden_size), + nn.GELU(), + nn.Linear(llm_hidden_size, llm_hidden_size) + ) + + self.img_context_token_id = None + self.conv_template = get_conv_template(self.template) + self.system_message = self.conv_template.system_message + + def forward( + self, + pixel_values: torch.FloatTensor, + input_ids: torch.LongTensor = None, + attention_mask: Optional[torch.Tensor] = None, + position_ids: Optional[torch.LongTensor] = None, + image_flags: Optional[torch.LongTensor] = None, + past_key_values: Optional[List[torch.FloatTensor]] = None, + labels: Optional[torch.LongTensor] = None, + use_cache: Optional[bool] = None, + output_attentions: Optional[bool] = None, + output_hidden_states: Optional[bool] = None, + return_dict: Optional[bool] = None, + ) -> Union[Tuple, CausalLMOutputWithPast]: + return_dict = return_dict if return_dict is not None else self.config.use_return_dict + + image_flags = image_flags.squeeze(-1) + input_embeds = self.language_model.get_input_embeddings()(input_ids).clone() + + vit_embeds = self.extract_feature(pixel_values) + vit_embeds = vit_embeds[image_flags == 1] + vit_batch_size = pixel_values.shape[0] + + B, N, C = input_embeds.shape + input_embeds = input_embeds.reshape(B * N, C) + + if torch.distributed.is_initialized() and torch.distributed.get_rank() == 0: + print(f'dynamic ViT batch size: {vit_batch_size}, images per sample: {vit_batch_size / B}, dynamic token length: {N}') + + input_ids = input_ids.reshape(B * N) + selected = (input_ids == self.img_context_token_id) + try: + input_embeds[selected] = input_embeds[selected] * 0.0 + vit_embeds.reshape(-1, C) + except Exception as e: + vit_embeds = vit_embeds.reshape(-1, C) + print(f'warning: {e}, input_embeds[selected].shape={input_embeds[selected].shape}, ' + f'vit_embeds.shape={vit_embeds.shape}') + n_token = selected.sum() + input_embeds[selected] = input_embeds[selected] * 0.0 + vit_embeds[:n_token] + + input_embeds = input_embeds.reshape(B, N, C) + + outputs = self.language_model( + inputs_embeds=input_embeds, + attention_mask=attention_mask, + position_ids=position_ids, + past_key_values=past_key_values, + use_cache=use_cache, + output_attentions=output_attentions, + output_hidden_states=output_hidden_states, + return_dict=return_dict, + ) + logits = outputs.logits + + loss = None + if labels is not None: + # Shift so that tokens < n predict n + shift_logits = logits[..., :-1, :].contiguous() + shift_labels = labels[..., 1:].contiguous() + # Flatten the tokens + loss_fct = CrossEntropyLoss() + shift_logits = shift_logits.view(-1, self.language_model.config.vocab_size) + shift_labels = shift_labels.view(-1) + # Enable model parallelism + shift_labels = shift_labels.to(shift_logits.device) + loss = loss_fct(shift_logits, shift_labels) + + if not return_dict: + output = (logits,) + outputs[1:] + return (loss,) + output if loss is not None else output + + return CausalLMOutputWithPast( + loss=loss, + logits=logits, + past_key_values=outputs.past_key_values, + hidden_states=outputs.hidden_states, + attentions=outputs.attentions, + ) + + def pixel_shuffle(self, x, scale_factor=0.5): + n, w, h, c = x.size() + # N, W, H, C --> N, W, H * scale, C // scale + x = x.view(n, w, int(h * scale_factor), int(c / scale_factor)) + # N, W, H * scale, C // scale --> N, H * scale, W, C // scale + x = x.permute(0, 2, 1, 3).contiguous() + # N, H * scale, W, C // scale --> N, H * scale, W * scale, C // (scale ** 2) + x = x.view(n, int(h * scale_factor), int(w * scale_factor), + int(c / (scale_factor * scale_factor))) + if self.ps_version == 'v1': + warnings.warn("In ps_version 'v1', the height and width have not been swapped back, " + 'which results in a transposed image.') + else: + x = x.permute(0, 2, 1, 3).contiguous() + return x + + def extract_feature(self, pixel_values): + if self.select_layer == -1: + vit_embeds = self.vision_model( + pixel_values=pixel_values, + output_hidden_states=False, + return_dict=True).last_hidden_state + else: + vit_embeds = self.vision_model( + pixel_values=pixel_values, + output_hidden_states=True, + return_dict=True).hidden_states[self.select_layer] + vit_embeds = vit_embeds[:, 1:, :] + + h = w = int(vit_embeds.shape[1] ** 0.5) + vit_embeds = vit_embeds.reshape(vit_embeds.shape[0], h, w, -1) + vit_embeds = self.pixel_shuffle(vit_embeds, scale_factor=self.downsample_ratio) + vit_embeds = vit_embeds.reshape(vit_embeds.shape[0], -1, vit_embeds.shape[-1]) + vit_embeds = self.mlp1(vit_embeds) + return vit_embeds + + def batch_chat(self, tokenizer, pixel_values, questions, generation_config, num_patches_list=None, + history=None, return_history=False, IMG_START_TOKEN='', IMG_END_TOKEN='', + IMG_CONTEXT_TOKEN='', verbose=False, image_counts=None): + if history is not None or return_history: + print('Now multi-turn chat is not supported in batch_chat.') + raise NotImplementedError + + if image_counts is not None: + num_patches_list = image_counts + print('Warning: `image_counts` is deprecated. Please use `num_patches_list` instead.') + + img_context_token_id = tokenizer.convert_tokens_to_ids(IMG_CONTEXT_TOKEN) + self.img_context_token_id = img_context_token_id + + if verbose and pixel_values is not None: + image_bs = pixel_values.shape[0] + print(f'dynamic ViT batch size: {image_bs}') + + queries = [] + for idx, num_patches in enumerate(num_patches_list): + question = questions[idx] + if pixel_values is not None and '' not in question: + question = '\n' + question + template = get_conv_template(self.template) + template.system_message = self.system_message + template.append_message(template.roles[0], question) + template.append_message(template.roles[1], None) + query = template.get_prompt() + + image_tokens = IMG_START_TOKEN + IMG_CONTEXT_TOKEN * self.num_image_token * num_patches + IMG_END_TOKEN + query = query.replace('', image_tokens, 1) + queries.append(query) + + tokenizer.padding_side = 'left' + model_inputs = tokenizer(queries, return_tensors='pt', padding=True) + input_ids = model_inputs['input_ids'].to(self.device) + attention_mask = model_inputs['attention_mask'].to(self.device) + eos_token_id = tokenizer.convert_tokens_to_ids(template.sep.strip()) + generation_config['eos_token_id'] = eos_token_id + generation_output = self.generate( + pixel_values=pixel_values, + input_ids=input_ids, + attention_mask=attention_mask, + **generation_config + ) + responses = tokenizer.batch_decode(generation_output, skip_special_tokens=True) + responses = [response.split(template.sep.strip())[0].strip() for response in responses] + return responses + + def chat(self, tokenizer, pixel_values, question, generation_config, history=None, return_history=False, + num_patches_list=None, IMG_START_TOKEN='', IMG_END_TOKEN='', IMG_CONTEXT_TOKEN='', + verbose=False): + + if history is None and pixel_values is not None and '' not in question: + question = '\n' + question + + if num_patches_list is None: + num_patches_list = [pixel_values.shape[0]] if pixel_values is not None else [] + assert pixel_values is None or len(pixel_values) == sum(num_patches_list) + + img_context_token_id = tokenizer.convert_tokens_to_ids(IMG_CONTEXT_TOKEN) + self.img_context_token_id = img_context_token_id + + template = get_conv_template(self.template) + template.system_message = self.system_message + eos_token_id = tokenizer.convert_tokens_to_ids(template.sep.strip()) + + history = [] if history is None else history + for (old_question, old_answer) in history: + template.append_message(template.roles[0], old_question) + template.append_message(template.roles[1], old_answer) + template.append_message(template.roles[0], question) + template.append_message(template.roles[1], None) + query = template.get_prompt() + + if verbose and pixel_values is not None: + image_bs = pixel_values.shape[0] + print(f'dynamic ViT batch size: {image_bs}') + + for num_patches in num_patches_list: + image_tokens = IMG_START_TOKEN + IMG_CONTEXT_TOKEN * self.num_image_token * num_patches + IMG_END_TOKEN + query = query.replace('', image_tokens, 1) + + model_inputs = tokenizer(query, return_tensors='pt') + input_ids = model_inputs['input_ids'].to(self.device) + attention_mask = model_inputs['attention_mask'].to(self.device) + generation_config['eos_token_id'] = eos_token_id + generation_output = self.generate( + pixel_values=pixel_values, + input_ids=input_ids, + attention_mask=attention_mask, + **generation_config + ) + response = tokenizer.batch_decode(generation_output, skip_special_tokens=True)[0] + response = response.split(template.sep.strip())[0].strip() + history.append((question, response)) + if return_history: + return response, history + else: + query_to_print = query.replace(IMG_CONTEXT_TOKEN, '') + query_to_print = query_to_print.replace(f'{IMG_START_TOKEN}{IMG_END_TOKEN}', '') + if verbose: + print(query_to_print, response) + return response + + @torch.no_grad() + def generate( + self, + pixel_values: Optional[torch.FloatTensor] = None, + input_ids: Optional[torch.FloatTensor] = None, + attention_mask: Optional[torch.LongTensor] = None, + visual_features: Optional[torch.FloatTensor] = None, + generation_config: Optional[GenerationConfig] = None, + output_hidden_states: Optional[bool] = None, + **generate_kwargs, + ) -> torch.LongTensor: + + assert self.img_context_token_id is not None + if pixel_values is not None: + if visual_features is not None: + vit_embeds = visual_features + else: + vit_embeds = self.extract_feature(pixel_values) + input_embeds = self.language_model.get_input_embeddings()(input_ids) + B, N, C = input_embeds.shape + input_embeds = input_embeds.reshape(B * N, C) + + input_ids = input_ids.reshape(B * N) + selected = (input_ids == self.img_context_token_id) + assert selected.sum() != 0 + input_embeds[selected] = vit_embeds.reshape(-1, C).to(input_embeds.device) + + input_embeds = input_embeds.reshape(B, N, C) + else: + input_embeds = self.language_model.get_input_embeddings()(input_ids) + + outputs = self.language_model.generate( + inputs_embeds=input_embeds, + attention_mask=attention_mask, + generation_config=generation_config, + output_hidden_states=output_hidden_states, + use_cache=True, + **generate_kwargs, + ) + + return outputs diff --git a/InternVL-main/internvl_chat/work_dirs/internvl_chat_v2_5/mmvet/200/special_tokens_map.json b/InternVL-main/internvl_chat/work_dirs/internvl_chat_v2_5/mmvet/200/special_tokens_map.json new file mode 100644 index 0000000000000000000000000000000000000000..cbf34a50d27c43ed8d1e2823b800b4e6f66e637a --- /dev/null +++ b/InternVL-main/internvl_chat/work_dirs/internvl_chat_v2_5/mmvet/200/special_tokens_map.json @@ -0,0 +1,47 @@ +{ + "additional_special_tokens": [ + "<|im_start|>", + "<|im_end|>", + "<|action_start|>", + "<|action_end|>", + "<|interpreter|>", + "<|plugin|>", + "", + "", + "", + "", + "", + "", + "", + "", + "" + ], + "bos_token": { + "content": "", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false + }, + "eos_token": { + "content": "", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false + }, + "pad_token": { + "content": "", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false + }, + "unk_token": { + "content": "", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false + } +} diff --git a/InternVL-main/internvl_chat/work_dirs/internvl_chat_v2_5/mmvet/200/tokenization_internlm2.py b/InternVL-main/internvl_chat/work_dirs/internvl_chat_v2_5/mmvet/200/tokenization_internlm2.py new file mode 100644 index 0000000000000000000000000000000000000000..1be581da37ef678de65f2737493fc0ed7160446e --- /dev/null +++ b/InternVL-main/internvl_chat/work_dirs/internvl_chat_v2_5/mmvet/200/tokenization_internlm2.py @@ -0,0 +1,235 @@ +# Copyright (c) The InternLM team and The HuggingFace Inc. team. All rights reserved. +# +# This code is based on transformers/src/transformers/models/llama/tokenization_llama.py +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +"""Tokenization classes for InternLM.""" +import os +from shutil import copyfile +from typing import Any, Dict, List, Optional, Tuple + +import sentencepiece as spm +from transformers.tokenization_utils import PreTrainedTokenizer +from transformers.utils import logging + +logger = logging.get_logger(__name__) + +VOCAB_FILES_NAMES = {'vocab_file': './tokenizer.model'} + +PRETRAINED_VOCAB_FILES_MAP = {} + + +# Modified from transformers.model.llama.tokenization_llama.LlamaTokenizer +class InternLM2Tokenizer(PreTrainedTokenizer): + """ + Construct a InternLM2 tokenizer. Based on byte-level Byte-Pair-Encoding. + + Args: + vocab_file (`str`): + Path to the vocabulary file. + """ + + vocab_files_names = VOCAB_FILES_NAMES + pretrained_vocab_files_map = PRETRAINED_VOCAB_FILES_MAP + model_input_names = ['input_ids', 'attention_mask'] + _auto_class = 'AutoTokenizer' + + def __init__( + self, + vocab_file, + unk_token='', + bos_token='', + eos_token='', + pad_token='', + sp_model_kwargs: Optional[Dict[str, Any]] = None, + add_bos_token=True, + add_eos_token=False, + decode_with_prefix_space=False, + clean_up_tokenization_spaces=False, + **kwargs, + ): + self.sp_model_kwargs = {} if sp_model_kwargs is None else sp_model_kwargs + self.vocab_file = vocab_file + self.add_bos_token = add_bos_token + self.add_eos_token = add_eos_token + self.decode_with_prefix_space = decode_with_prefix_space + self.sp_model = spm.SentencePieceProcessor(**self.sp_model_kwargs) + self.sp_model.Load(vocab_file) + self._no_prefix_space_tokens = None + super().__init__( + bos_token=bos_token, + eos_token=eos_token, + unk_token=unk_token, + pad_token=pad_token, + clean_up_tokenization_spaces=clean_up_tokenization_spaces, + **kwargs, + ) + + @property + def no_prefix_space_tokens(self): + if self._no_prefix_space_tokens is None: + vocab = self.convert_ids_to_tokens(list(range(self.vocab_size))) + self._no_prefix_space_tokens = {i for i, tok in enumerate(vocab) if not tok.startswith('▁')} + return self._no_prefix_space_tokens + + @property + def vocab_size(self): + """Returns vocab size""" + return self.sp_model.get_piece_size() + + @property + def bos_token_id(self) -> Optional[int]: + return self.sp_model.bos_id() + + @property + def eos_token_id(self) -> Optional[int]: + return self.sp_model.eos_id() + + def get_vocab(self): + """Returns vocab as a dict""" + vocab = {self.convert_ids_to_tokens(i): i for i in range(self.vocab_size)} + vocab.update(self.added_tokens_encoder) + return vocab + + def _tokenize(self, text): + """Returns a tokenized string.""" + return self.sp_model.encode(text, out_type=str) + + def _convert_token_to_id(self, token): + """Converts a token (str) in an id using the vocab.""" + return self.sp_model.piece_to_id(token) + + def _convert_id_to_token(self, index): + """Converts an index (integer) in a token (str) using the vocab.""" + token = self.sp_model.IdToPiece(index) + return token + + def _maybe_add_prefix_space(self, tokens, decoded): + if tokens and tokens[0] not in self.no_prefix_space_tokens: + return ' ' + decoded + else: + return decoded + + def convert_tokens_to_string(self, tokens): + """Converts a sequence of tokens (string) in a single string.""" + current_sub_tokens = [] + out_string = '' + prev_is_special = False + for token in tokens: + # make sure that special tokens are not decoded using sentencepiece model + if token in self.all_special_tokens: + if not prev_is_special: + out_string += ' ' + out_string += self.sp_model.decode(current_sub_tokens) + token + prev_is_special = True + current_sub_tokens = [] + else: + current_sub_tokens.append(token) + prev_is_special = False + out_string += self.sp_model.decode(current_sub_tokens) + out_string = self.clean_up_tokenization(out_string) + out_string = self._maybe_add_prefix_space(tokens=tokens, decoded=out_string) + return out_string[1:] + + def save_vocabulary(self, save_directory, filename_prefix: Optional[str] = None) -> Tuple[str]: + """ + Save the vocabulary and special tokens file to a directory. + + Args: + save_directory (`str`): + The directory in which to save the vocabulary. + + Returns: + `Tuple(str)`: Paths to the files saved. + """ + if not os.path.isdir(save_directory): + logger.error(f'Vocabulary path ({save_directory}) should be a directory') + return + out_vocab_file = os.path.join( + save_directory, (filename_prefix + '-' if filename_prefix else '') + VOCAB_FILES_NAMES['vocab_file'] + ) + + if os.path.abspath(self.vocab_file) != os.path.abspath(out_vocab_file) and os.path.isfile(self.vocab_file): + copyfile(self.vocab_file, out_vocab_file) + elif not os.path.isfile(self.vocab_file): + with open(out_vocab_file, 'wb') as fi: + content_spiece_model = self.sp_model.serialized_model_proto() + fi.write(content_spiece_model) + + return (out_vocab_file,) + + def build_inputs_with_special_tokens(self, token_ids_0, token_ids_1=None): + if self.add_bos_token: + bos_token_ids = [self.bos_token_id] + else: + bos_token_ids = [] + + output = bos_token_ids + token_ids_0 + + if token_ids_1 is not None: + output = output + token_ids_1 + + if self.add_eos_token: + output = output + [self.eos_token_id] + + return output + + def get_special_tokens_mask( + self, token_ids_0: List[int], token_ids_1: Optional[List[int]] = None, already_has_special_tokens: bool = False + ) -> List[int]: + """ + Retrieve sequence ids from a token list that has no special tokens added. This method is called when adding + special tokens using the tokenizer `prepare_for_model` method. + + Args: + token_ids_0 (`List[int]`): + List of IDs. + token_ids_1 (`List[int]`, *optional*): + Optional second list of IDs for sequence pairs. + already_has_special_tokens (`bool`, *optional*, defaults to `False`): + Whether or not the token list is already formatted with special tokens for the model. + + Returns: + `List[int]`: A list of integers in the range [0, 1]: 1 for a special token, 0 for a sequence token. + """ + if already_has_special_tokens: + return super().get_special_tokens_mask( + token_ids_0=token_ids_0, token_ids_1=token_ids_1, already_has_special_tokens=True + ) + + if token_ids_1 is None: + return [1] + ([0] * len(token_ids_0)) + [1] + return [1] + ([0] * len(token_ids_0)) + [1, 1] + ([0] * len(token_ids_1)) + [1] + + def create_token_type_ids_from_sequences( + self, token_ids_0: List[int], token_ids_1: Optional[List[int]] = None + ) -> List[int]: + """ + Create a mask from the two sequences passed to be used in a sequence-pair classification task. T5 does not make + use of token type ids, therefore a list of zeros is returned. + + Args: + token_ids_0 (`List[int]`): + List of IDs. + token_ids_1 (`List[int]`, *optional*): + Optional second list of IDs for sequence pairs. + + Returns: + `List[int]`: List of zeros. + """ + eos = [self.eos_token_id] + + if token_ids_1 is None: + return len(token_ids_0 + eos) * [0] + return len(token_ids_0 + eos + token_ids_1 + eos) * [0] diff --git a/InternVL-main/internvl_chat/work_dirs/internvl_chat_v2_5/mmvet/200/tokenization_internlm2_fast.py b/InternVL-main/internvl_chat/work_dirs/internvl_chat_v2_5/mmvet/200/tokenization_internlm2_fast.py new file mode 100644 index 0000000000000000000000000000000000000000..aa0fccbd0f1d029d79e19821f2edcb01b594537c --- /dev/null +++ b/InternVL-main/internvl_chat/work_dirs/internvl_chat_v2_5/mmvet/200/tokenization_internlm2_fast.py @@ -0,0 +1,211 @@ +# Copyright (c) The InternLM team and The HuggingFace Inc. team. All rights reserved. +# +# This code is based on transformers/src/transformers/models/llama/tokenization_llama_fast.py +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +"""Tokenization Fast class for InternLM.""" +import os +from shutil import copyfile +from typing import Any, Dict, Optional, Tuple + +from tokenizers import Tokenizer, decoders, normalizers, processors +from tokenizers.models import BPE +from transformers.convert_slow_tokenizer import (SLOW_TO_FAST_CONVERTERS, + SentencePieceExtractor, + SpmConverter) +from transformers.tokenization_utils_fast import PreTrainedTokenizerFast +from transformers.utils import logging + +from .tokenization_internlm2 import InternLM2Tokenizer + +logger = logging.get_logger(__name__) + +VOCAB_FILES_NAMES = {'vocab_file': './tokenizer.model'} + + +# Modified from transformers.convert_slow_tokenizer.LlamaConverter +class InternLM2Converter(SpmConverter): + handle_byte_fallback = True + + def vocab(self, proto): + vocab = [ + ('', 0.0), + ('', 0.0), + ('', 0.0), + ] + vocab += [(piece.piece, piece.score) for piece in proto.pieces[3:]] + return vocab + + def unk_id(self, proto): + unk_id = 0 + return unk_id + + def decoder(self, replacement, add_prefix_space): + return decoders.Sequence( + [ + decoders.Replace('▁', ' '), + decoders.ByteFallback(), + decoders.Fuse(), + decoders.Strip(content=' ', left=1), + ] + ) + + def tokenizer(self, proto): + model_type = proto.trainer_spec.model_type + vocab_scores = self.vocab(proto) + # special tokens + added_tokens = self.original_tokenizer.added_tokens_decoder + for i in range(len(vocab_scores)): + piece, score = vocab_scores[i] + if i in added_tokens: + vocab_scores[i] = (added_tokens[i].content, score) + if model_type == 1: + raise RuntimeError('InternLM2 is supposed to be a BPE model!') + + elif model_type == 2: + _, merges = SentencePieceExtractor(self.original_tokenizer.vocab_file).extract(vocab_scores) + bpe_vocab = {word: i for i, (word, _score) in enumerate(vocab_scores)} + tokenizer = Tokenizer( + BPE(bpe_vocab, merges, unk_token=proto.trainer_spec.unk_piece, fuse_unk=True, byte_fallback=True) + ) + tokenizer.add_special_tokens( + [ added_token for index, added_token in added_tokens.items()] + ) + else: + raise Exception( + "You're trying to run a `Unigram` model but you're file was trained with a different algorithm" + ) + + return tokenizer + + def normalizer(self, proto): + normalizers_list = [] + if proto.normalizer_spec.add_dummy_prefix: + normalizers_list.append(normalizers.Prepend(prepend='▁')) + normalizers_list.append(normalizers.Replace(pattern=' ', content='▁')) + return normalizers.Sequence(normalizers_list) + + def pre_tokenizer(self, replacement, add_prefix_space): + return None + + +SLOW_TO_FAST_CONVERTERS['InternLM2Tokenizer'] = InternLM2Converter + + +# Modified from transformers.model.llama.tokenization_llama_fast.LlamaTokenizerFast -> InternLM2TokenizerFast +class InternLM2TokenizerFast(PreTrainedTokenizerFast): + vocab_files_names = VOCAB_FILES_NAMES + slow_tokenizer_class = InternLM2Tokenizer + padding_side = 'left' + model_input_names = ['input_ids', 'attention_mask'] + _auto_class = 'AutoTokenizer' + + def __init__( + self, + vocab_file, + unk_token='', + bos_token='', + eos_token='', + pad_token='', + sp_model_kwargs: Optional[Dict[str, Any]] = None, + add_bos_token=True, + add_eos_token=False, + decode_with_prefix_space=False, + clean_up_tokenization_spaces=False, + **kwargs, + ): + super().__init__( + vocab_file=vocab_file, + unk_token=unk_token, + bos_token=bos_token, + eos_token=eos_token, + pad_token=pad_token, + sp_model_kwargs=sp_model_kwargs, + add_bos_token=add_bos_token, + add_eos_token=add_eos_token, + decode_with_prefix_space=decode_with_prefix_space, + clean_up_tokenization_spaces=clean_up_tokenization_spaces, + **kwargs, + ) + self._add_bos_token = add_bos_token + self._add_eos_token = add_eos_token + self.update_post_processor() + self.vocab_file = vocab_file + + @property + def can_save_slow_tokenizer(self) -> bool: + return os.path.isfile(self.vocab_file) if self.vocab_file else False + + def update_post_processor(self): + """ + Updates the underlying post processor with the current `bos_token` and `eos_token`. + """ + bos = self.bos_token + bos_token_id = self.bos_token_id + if bos is None and self.add_bos_token: + raise ValueError('add_bos_token = True but bos_token = None') + + eos = self.eos_token + eos_token_id = self.eos_token_id + if eos is None and self.add_eos_token: + raise ValueError('add_eos_token = True but eos_token = None') + + single = f"{(bos+':0 ') if self.add_bos_token else ''}$A:0{(' '+eos+':0') if self.add_eos_token else ''}" + pair = f"{single}{(' '+bos+':1') if self.add_bos_token else ''} $B:1{(' '+eos+':1') if self.add_eos_token else ''}" + + special_tokens = [] + if self.add_bos_token: + special_tokens.append((bos, bos_token_id)) + if self.add_eos_token: + special_tokens.append((eos, eos_token_id)) + self._tokenizer.post_processor = processors.TemplateProcessing( + single=single, pair=pair, special_tokens=special_tokens + ) + + @property + def add_eos_token(self): + return self._add_eos_token + + @property + def add_bos_token(self): + return self._add_bos_token + + @add_eos_token.setter + def add_eos_token(self, value): + self._add_eos_token = value + self.update_post_processor() + + @add_bos_token.setter + def add_bos_token(self, value): + self._add_bos_token = value + self.update_post_processor() + + def save_vocabulary(self, save_directory: str, filename_prefix: Optional[str] = None) -> Tuple[str]: + if not self.can_save_slow_tokenizer: + raise ValueError( + 'Your fast tokenizer does not have the necessary information to save the vocabulary for a slow ' + 'tokenizer.' + ) + + if not os.path.isdir(save_directory): + logger.error(f'Vocabulary path ({save_directory}) should be a directory') + return + out_vocab_file = os.path.join( + save_directory, (filename_prefix + '-' if filename_prefix else '') + VOCAB_FILES_NAMES['vocab_file'] + ) + + if os.path.abspath(self.vocab_file) != os.path.abspath(out_vocab_file): + copyfile(self.vocab_file, out_vocab_file) + + return (out_vocab_file,) diff --git a/InternVL-main/internvl_chat/work_dirs/internvl_chat_v2_5/mmvet/200/tokenizer_config.json b/InternVL-main/internvl_chat/work_dirs/internvl_chat_v2_5/mmvet/200/tokenizer_config.json new file mode 100644 index 0000000000000000000000000000000000000000..1f32946df0f56d92ddbc1df79cabb4477b622480 --- /dev/null +++ b/InternVL-main/internvl_chat/work_dirs/internvl_chat_v2_5/mmvet/200/tokenizer_config.json @@ -0,0 +1,179 @@ +{ + "added_tokens_decoder": { + "0": { + "content": "", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "1": { + "content": "", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "2": { + "content": "", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "92538": { + "content": "<|plugin|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "92539": { + "content": "<|interpreter|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "92540": { + "content": "<|action_end|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "92541": { + "content": "<|action_start|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "92542": { + "content": "<|im_end|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "92543": { + "content": "<|im_start|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "92544": { + "content": "", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "92545": { + "content": "", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "92546": { + "content": "", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "92547": { + "content": "", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "92548": { + "content": "", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "92549": { + "content": "", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "92550": { + "content": "", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "92551": { + "content": "", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "92552": { + "content": "", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + } + }, + "additional_special_tokens": [ + "<|im_start|>", + "<|im_end|>", + "<|action_start|>", + "<|action_end|>", + "<|interpreter|>", + "<|plugin|>", + "", + "", + "", + "", + "", + "", + "", + "", + "" + ], + "auto_map": { + "AutoTokenizer": [ + "tokenization_internlm2.InternLM2Tokenizer", + null + ] + }, + "bos_token": "", + "chat_template": "{{ bos_token }}{% for message in messages %}{{'<|im_start|>' + message['role'] + '\n' + message['content'] + '<|im_end|>' + '\n'}}{% endfor %}{% if add_generation_prompt %}{{ '<|im_start|>assistant\n' }}{% endif %}", + "clean_up_tokenization_spaces": false, + "eos_token": "", + "model_max_length": 8192, + "pad_token": "", + "tokenizer_class": "InternLM2Tokenizer", + "unk_token": "" +} diff --git a/InternVL-main/internvl_chat/work_dirs/internvl_chat_v2_5/mmvet/added_tokens.json b/InternVL-main/internvl_chat/work_dirs/internvl_chat_v2_5/mmvet/added_tokens.json new file mode 100644 index 0000000000000000000000000000000000000000..35f5893c8e29d6102945a953529819a2d56c62a9 --- /dev/null +++ b/InternVL-main/internvl_chat/work_dirs/internvl_chat_v2_5/mmvet/added_tokens.json @@ -0,0 +1,11 @@ +{ + "": 92552, + "": 92545, + "": 92548, + "": 92550, + "": 92546, + "": 92551, + "": 92544, + "": 92547, + "": 92549 +} diff --git a/InternVL-main/internvl_chat/work_dirs/internvl_chat_v2_5/mmvet/all_results.json b/InternVL-main/internvl_chat/work_dirs/internvl_chat_v2_5/mmvet/all_results.json new file mode 100644 index 0000000000000000000000000000000000000000..270e4a822e3818e7c5a365e1397a583b903d3e28 --- /dev/null +++ b/InternVL-main/internvl_chat/work_dirs/internvl_chat_v2_5/mmvet/all_results.json @@ -0,0 +1,9 @@ +{ + "epoch": 0.300121016538927, + "total_flos": 1.9913151490885996e+20, + "train_loss": 5.00184802257032, + "train_runtime": 3870.6705, + "train_samples": 14874, + "train_samples_per_second": 1.153, + "train_steps_per_second": 0.144 +} \ No newline at end of file diff --git a/InternVL-main/internvl_chat/work_dirs/internvl_chat_v2_5/mmvet/checkpoint-558/special_tokens_map.json b/InternVL-main/internvl_chat/work_dirs/internvl_chat_v2_5/mmvet/checkpoint-558/special_tokens_map.json new file mode 100644 index 0000000000000000000000000000000000000000..cbf34a50d27c43ed8d1e2823b800b4e6f66e637a --- /dev/null +++ b/InternVL-main/internvl_chat/work_dirs/internvl_chat_v2_5/mmvet/checkpoint-558/special_tokens_map.json @@ -0,0 +1,47 @@ +{ + "additional_special_tokens": [ + "<|im_start|>", + "<|im_end|>", + "<|action_start|>", + "<|action_end|>", + "<|interpreter|>", + "<|plugin|>", + "", + "", + "", + "", + "", + "", + "", + "", + "" + ], + "bos_token": { + "content": "", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false + }, + "eos_token": { + "content": "", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false + }, + "pad_token": { + "content": "", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false + }, + "unk_token": { + "content": "", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false + } +} diff --git a/InternVL-main/internvl_chat/work_dirs/internvl_chat_v2_5/mmvet/checkpoint-558/tokenization_internlm2.py b/InternVL-main/internvl_chat/work_dirs/internvl_chat_v2_5/mmvet/checkpoint-558/tokenization_internlm2.py new file mode 100644 index 0000000000000000000000000000000000000000..1be581da37ef678de65f2737493fc0ed7160446e --- /dev/null +++ b/InternVL-main/internvl_chat/work_dirs/internvl_chat_v2_5/mmvet/checkpoint-558/tokenization_internlm2.py @@ -0,0 +1,235 @@ +# Copyright (c) The InternLM team and The HuggingFace Inc. team. All rights reserved. +# +# This code is based on transformers/src/transformers/models/llama/tokenization_llama.py +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +"""Tokenization classes for InternLM.""" +import os +from shutil import copyfile +from typing import Any, Dict, List, Optional, Tuple + +import sentencepiece as spm +from transformers.tokenization_utils import PreTrainedTokenizer +from transformers.utils import logging + +logger = logging.get_logger(__name__) + +VOCAB_FILES_NAMES = {'vocab_file': './tokenizer.model'} + +PRETRAINED_VOCAB_FILES_MAP = {} + + +# Modified from transformers.model.llama.tokenization_llama.LlamaTokenizer +class InternLM2Tokenizer(PreTrainedTokenizer): + """ + Construct a InternLM2 tokenizer. Based on byte-level Byte-Pair-Encoding. + + Args: + vocab_file (`str`): + Path to the vocabulary file. + """ + + vocab_files_names = VOCAB_FILES_NAMES + pretrained_vocab_files_map = PRETRAINED_VOCAB_FILES_MAP + model_input_names = ['input_ids', 'attention_mask'] + _auto_class = 'AutoTokenizer' + + def __init__( + self, + vocab_file, + unk_token='', + bos_token='', + eos_token='', + pad_token='', + sp_model_kwargs: Optional[Dict[str, Any]] = None, + add_bos_token=True, + add_eos_token=False, + decode_with_prefix_space=False, + clean_up_tokenization_spaces=False, + **kwargs, + ): + self.sp_model_kwargs = {} if sp_model_kwargs is None else sp_model_kwargs + self.vocab_file = vocab_file + self.add_bos_token = add_bos_token + self.add_eos_token = add_eos_token + self.decode_with_prefix_space = decode_with_prefix_space + self.sp_model = spm.SentencePieceProcessor(**self.sp_model_kwargs) + self.sp_model.Load(vocab_file) + self._no_prefix_space_tokens = None + super().__init__( + bos_token=bos_token, + eos_token=eos_token, + unk_token=unk_token, + pad_token=pad_token, + clean_up_tokenization_spaces=clean_up_tokenization_spaces, + **kwargs, + ) + + @property + def no_prefix_space_tokens(self): + if self._no_prefix_space_tokens is None: + vocab = self.convert_ids_to_tokens(list(range(self.vocab_size))) + self._no_prefix_space_tokens = {i for i, tok in enumerate(vocab) if not tok.startswith('▁')} + return self._no_prefix_space_tokens + + @property + def vocab_size(self): + """Returns vocab size""" + return self.sp_model.get_piece_size() + + @property + def bos_token_id(self) -> Optional[int]: + return self.sp_model.bos_id() + + @property + def eos_token_id(self) -> Optional[int]: + return self.sp_model.eos_id() + + def get_vocab(self): + """Returns vocab as a dict""" + vocab = {self.convert_ids_to_tokens(i): i for i in range(self.vocab_size)} + vocab.update(self.added_tokens_encoder) + return vocab + + def _tokenize(self, text): + """Returns a tokenized string.""" + return self.sp_model.encode(text, out_type=str) + + def _convert_token_to_id(self, token): + """Converts a token (str) in an id using the vocab.""" + return self.sp_model.piece_to_id(token) + + def _convert_id_to_token(self, index): + """Converts an index (integer) in a token (str) using the vocab.""" + token = self.sp_model.IdToPiece(index) + return token + + def _maybe_add_prefix_space(self, tokens, decoded): + if tokens and tokens[0] not in self.no_prefix_space_tokens: + return ' ' + decoded + else: + return decoded + + def convert_tokens_to_string(self, tokens): + """Converts a sequence of tokens (string) in a single string.""" + current_sub_tokens = [] + out_string = '' + prev_is_special = False + for token in tokens: + # make sure that special tokens are not decoded using sentencepiece model + if token in self.all_special_tokens: + if not prev_is_special: + out_string += ' ' + out_string += self.sp_model.decode(current_sub_tokens) + token + prev_is_special = True + current_sub_tokens = [] + else: + current_sub_tokens.append(token) + prev_is_special = False + out_string += self.sp_model.decode(current_sub_tokens) + out_string = self.clean_up_tokenization(out_string) + out_string = self._maybe_add_prefix_space(tokens=tokens, decoded=out_string) + return out_string[1:] + + def save_vocabulary(self, save_directory, filename_prefix: Optional[str] = None) -> Tuple[str]: + """ + Save the vocabulary and special tokens file to a directory. + + Args: + save_directory (`str`): + The directory in which to save the vocabulary. + + Returns: + `Tuple(str)`: Paths to the files saved. + """ + if not os.path.isdir(save_directory): + logger.error(f'Vocabulary path ({save_directory}) should be a directory') + return + out_vocab_file = os.path.join( + save_directory, (filename_prefix + '-' if filename_prefix else '') + VOCAB_FILES_NAMES['vocab_file'] + ) + + if os.path.abspath(self.vocab_file) != os.path.abspath(out_vocab_file) and os.path.isfile(self.vocab_file): + copyfile(self.vocab_file, out_vocab_file) + elif not os.path.isfile(self.vocab_file): + with open(out_vocab_file, 'wb') as fi: + content_spiece_model = self.sp_model.serialized_model_proto() + fi.write(content_spiece_model) + + return (out_vocab_file,) + + def build_inputs_with_special_tokens(self, token_ids_0, token_ids_1=None): + if self.add_bos_token: + bos_token_ids = [self.bos_token_id] + else: + bos_token_ids = [] + + output = bos_token_ids + token_ids_0 + + if token_ids_1 is not None: + output = output + token_ids_1 + + if self.add_eos_token: + output = output + [self.eos_token_id] + + return output + + def get_special_tokens_mask( + self, token_ids_0: List[int], token_ids_1: Optional[List[int]] = None, already_has_special_tokens: bool = False + ) -> List[int]: + """ + Retrieve sequence ids from a token list that has no special tokens added. This method is called when adding + special tokens using the tokenizer `prepare_for_model` method. + + Args: + token_ids_0 (`List[int]`): + List of IDs. + token_ids_1 (`List[int]`, *optional*): + Optional second list of IDs for sequence pairs. + already_has_special_tokens (`bool`, *optional*, defaults to `False`): + Whether or not the token list is already formatted with special tokens for the model. + + Returns: + `List[int]`: A list of integers in the range [0, 1]: 1 for a special token, 0 for a sequence token. + """ + if already_has_special_tokens: + return super().get_special_tokens_mask( + token_ids_0=token_ids_0, token_ids_1=token_ids_1, already_has_special_tokens=True + ) + + if token_ids_1 is None: + return [1] + ([0] * len(token_ids_0)) + [1] + return [1] + ([0] * len(token_ids_0)) + [1, 1] + ([0] * len(token_ids_1)) + [1] + + def create_token_type_ids_from_sequences( + self, token_ids_0: List[int], token_ids_1: Optional[List[int]] = None + ) -> List[int]: + """ + Create a mask from the two sequences passed to be used in a sequence-pair classification task. T5 does not make + use of token type ids, therefore a list of zeros is returned. + + Args: + token_ids_0 (`List[int]`): + List of IDs. + token_ids_1 (`List[int]`, *optional*): + Optional second list of IDs for sequence pairs. + + Returns: + `List[int]`: List of zeros. + """ + eos = [self.eos_token_id] + + if token_ids_1 is None: + return len(token_ids_0 + eos) * [0] + return len(token_ids_0 + eos + token_ids_1 + eos) * [0] diff --git a/InternVL-main/internvl_chat/work_dirs/internvl_chat_v2_5/mmvet/checkpoint-558/zero_to_fp32.py b/InternVL-main/internvl_chat/work_dirs/internvl_chat_v2_5/mmvet/checkpoint-558/zero_to_fp32.py new file mode 100644 index 0000000000000000000000000000000000000000..24cc342e78d1a006c782b3a4cd68d9ce786d8fd8 --- /dev/null +++ b/InternVL-main/internvl_chat/work_dirs/internvl_chat_v2_5/mmvet/checkpoint-558/zero_to_fp32.py @@ -0,0 +1,604 @@ +#!/usr/bin/env python + +# Copyright (c) Microsoft Corporation. +# SPDX-License-Identifier: Apache-2.0 + +# DeepSpeed Team + +# This script extracts fp32 consolidated weights from a zero 1, 2 and 3 DeepSpeed checkpoints. It gets +# copied into the top level checkpoint dir, so the user can easily do the conversion at any point in +# the future. Once extracted, the weights don't require DeepSpeed and can be used in any +# application. +# +# example: python zero_to_fp32.py . pytorch_model.bin + +import argparse +import torch +import glob +import math +import os +import re +from collections import OrderedDict +from dataclasses import dataclass + +# while this script doesn't use deepspeed to recover data, since the checkpoints are pickled with +# DeepSpeed data structures it has to be available in the current python environment. +from deepspeed.utils import logger +from deepspeed.checkpoint.constants import (DS_VERSION, OPTIMIZER_STATE_DICT, SINGLE_PARTITION_OF_FP32_GROUPS, + FP32_FLAT_GROUPS, ZERO_STAGE, PARTITION_COUNT, PARAM_SHAPES, BUFFER_NAMES, + FROZEN_PARAM_SHAPES, FROZEN_PARAM_FRAGMENTS) + + +@dataclass +class zero_model_state: + buffers: dict() + param_shapes: dict() + shared_params: list + ds_version: int + frozen_param_shapes: dict() + frozen_param_fragments: dict() + + +debug = 0 + +# load to cpu +device = torch.device('cpu') + + +def atoi(text): + return int(text) if text.isdigit() else text + + +def natural_keys(text): + ''' + alist.sort(key=natural_keys) sorts in human order + http://nedbatchelder.com/blog/200712/human_sorting.html + (See Toothy's implementation in the comments) + ''' + return [atoi(c) for c in re.split(r'(\d+)', text)] + + +def get_model_state_file(checkpoint_dir, zero_stage): + if not os.path.isdir(checkpoint_dir): + raise FileNotFoundError(f"Directory '{checkpoint_dir}' doesn't exist") + + # there should be only one file + if zero_stage <= 2: + file = os.path.join(checkpoint_dir, "mp_rank_00_model_states.pt") + elif zero_stage == 3: + file = os.path.join(checkpoint_dir, "zero_pp_rank_0_mp_rank_00_model_states.pt") + + if not os.path.exists(file): + raise FileNotFoundError(f"can't find model states file at '{file}'") + + return file + + +def get_checkpoint_files(checkpoint_dir, glob_pattern): + # XXX: need to test that this simple glob rule works for multi-node setup too + ckpt_files = sorted(glob.glob(os.path.join(checkpoint_dir, glob_pattern)), key=natural_keys) + + if len(ckpt_files) == 0: + raise FileNotFoundError(f"can't find {glob_pattern} files in directory '{checkpoint_dir}'") + + return ckpt_files + + +def get_optim_files(checkpoint_dir): + return get_checkpoint_files(checkpoint_dir, "*_optim_states.pt") + + +def get_model_state_files(checkpoint_dir): + return get_checkpoint_files(checkpoint_dir, "*_model_states.pt") + + +def parse_model_states(files): + zero_model_states = [] + for file in files: + state_dict = torch.load(file, map_location=device) + + if BUFFER_NAMES not in state_dict: + raise ValueError(f"{file} is not a model state checkpoint") + buffer_names = state_dict[BUFFER_NAMES] + if debug: + print("Found buffers:", buffer_names) + + # recover just the buffers while restoring them to fp32 if they were saved in fp16 + buffers = {k: v.float() for k, v in state_dict["module"].items() if k in buffer_names} + param_shapes = state_dict[PARAM_SHAPES] + + # collect parameters that are included in param_shapes + param_names = [] + for s in param_shapes: + for name in s.keys(): + param_names.append(name) + + # update with frozen parameters + frozen_param_shapes = state_dict.get(FROZEN_PARAM_SHAPES, None) + if frozen_param_shapes is not None: + if debug: + print(f"Found frozen_param_shapes: {frozen_param_shapes}") + param_names += list(frozen_param_shapes.keys()) + + # handle shared params + shared_params = [[k, v] for k, v in state_dict["shared_params"].items()] + + ds_version = state_dict.get(DS_VERSION, None) + + frozen_param_fragments = state_dict.get(FROZEN_PARAM_FRAGMENTS, None) + + z_model_state = zero_model_state(buffers=buffers, + param_shapes=param_shapes, + shared_params=shared_params, + ds_version=ds_version, + frozen_param_shapes=frozen_param_shapes, + frozen_param_fragments=frozen_param_fragments) + zero_model_states.append(z_model_state) + + return zero_model_states + + +def parse_optim_states(files, ds_checkpoint_dir): + + total_files = len(files) + state_dicts = [] + for f in files: + state_dict = torch.load(f, map_location=device) + # immediately discard the potentially huge 2 optimizer states as we only care for fp32 master weights + # and also handle the case where it was already removed by another helper script + state_dict["optimizer_state_dict"].pop("optimizer_state_dict", None) + state_dicts.append(state_dict) + + if not ZERO_STAGE in state_dicts[0][OPTIMIZER_STATE_DICT]: + raise ValueError(f"{files[0]} is not a zero checkpoint") + zero_stage = state_dicts[0][OPTIMIZER_STATE_DICT][ZERO_STAGE] + world_size = state_dicts[0][OPTIMIZER_STATE_DICT][PARTITION_COUNT] + + # For ZeRO-2 each param group can have different partition_count as data parallelism for expert + # parameters can be different from data parallelism for non-expert parameters. So we can just + # use the max of the partition_count to get the dp world_size. + + if type(world_size) is list: + world_size = max(world_size) + + if world_size != total_files: + raise ValueError( + f"Expected {world_size} of '*_optim_states.pt' under '{ds_checkpoint_dir}' but found {total_files} files. " + "Possibly due to an overwrite of an old checkpoint, or a checkpoint didn't get saved by one or more processes." + ) + + # the groups are named differently in each stage + if zero_stage <= 2: + fp32_groups_key = SINGLE_PARTITION_OF_FP32_GROUPS + elif zero_stage == 3: + fp32_groups_key = FP32_FLAT_GROUPS + else: + raise ValueError(f"unknown zero stage {zero_stage}") + + if zero_stage <= 2: + fp32_flat_groups = [state_dicts[i][OPTIMIZER_STATE_DICT][fp32_groups_key] for i in range(len(state_dicts))] + elif zero_stage == 3: + # if there is more than one param group, there will be multiple flattened tensors - one + # flattened tensor per group - for simplicity merge them into a single tensor + # + # XXX: could make the script more memory efficient for when there are multiple groups - it + # will require matching the sub-lists of param_shapes for each param group flattened tensor + + fp32_flat_groups = [ + torch.cat(state_dicts[i][OPTIMIZER_STATE_DICT][fp32_groups_key], 0) for i in range(len(state_dicts)) + ] + + return zero_stage, world_size, fp32_flat_groups + + +def _get_fp32_state_dict_from_zero_checkpoint(ds_checkpoint_dir, exclude_frozen_parameters): + """ + Returns fp32 state_dict reconstructed from ds checkpoint + + Args: + - ``ds_checkpoint_dir``: path to the deepspeed checkpoint folder (where the optimizer files are) + + """ + print(f"Processing zero checkpoint '{ds_checkpoint_dir}'") + + optim_files = get_optim_files(ds_checkpoint_dir) + zero_stage, world_size, fp32_flat_groups = parse_optim_states(optim_files, ds_checkpoint_dir) + print(f"Detected checkpoint of type zero stage {zero_stage}, world_size: {world_size}") + + model_files = get_model_state_files(ds_checkpoint_dir) + + zero_model_states = parse_model_states(model_files) + print(f'Parsing checkpoint created by deepspeed=={zero_model_states[0].ds_version}') + + if zero_stage <= 2: + return _get_fp32_state_dict_from_zero2_checkpoint(world_size, fp32_flat_groups, zero_model_states, + exclude_frozen_parameters) + elif zero_stage == 3: + return _get_fp32_state_dict_from_zero3_checkpoint(world_size, fp32_flat_groups, zero_model_states, + exclude_frozen_parameters) + + +def _zero2_merge_frozen_params(state_dict, zero_model_states): + if zero_model_states[0].frozen_param_shapes is None or len(zero_model_states[0].frozen_param_shapes) == 0: + return + + frozen_param_shapes = zero_model_states[0].frozen_param_shapes + frozen_param_fragments = zero_model_states[0].frozen_param_fragments + + if debug: + num_elem = sum(s.numel() for s in frozen_param_shapes.values()) + print(f'rank 0: {FROZEN_PARAM_SHAPES}.numel = {num_elem}') + + wanted_params = len(frozen_param_shapes) + wanted_numel = sum(s.numel() for s in frozen_param_shapes.values()) + avail_numel = sum([p.numel() for p in frozen_param_fragments.values()]) + print(f'Frozen params: Have {avail_numel} numels to process.') + print(f'Frozen params: Need {wanted_numel} numels in {wanted_params} params') + + total_params = 0 + total_numel = 0 + for name, shape in frozen_param_shapes.items(): + total_params += 1 + unpartitioned_numel = shape.numel() + total_numel += unpartitioned_numel + + state_dict[name] = frozen_param_fragments[name] + + if debug: + print(f"{name} full shape: {shape} unpartitioned numel {unpartitioned_numel} ") + + print(f"Reconstructed Frozen fp32 state dict with {total_params} params {total_numel} elements") + + +def _has_callable(obj, fn): + attr = getattr(obj, fn, None) + return callable(attr) + + +def _zero2_merge_trainable_params(state_dict, world_size, fp32_flat_groups, zero_model_states): + param_shapes = zero_model_states[0].param_shapes + + # Reconstruction protocol: + # + # XXX: document this + + if debug: + for i in range(world_size): + for j in range(len(fp32_flat_groups[0])): + print(f"{FP32_FLAT_GROUPS}[{i}][{j}].shape={fp32_flat_groups[i][j].shape}") + + # XXX: memory usage doubles here (zero2) + num_param_groups = len(fp32_flat_groups[0]) + merged_single_partition_of_fp32_groups = [] + for i in range(num_param_groups): + merged_partitions = [sd[i] for sd in fp32_flat_groups] + full_single_fp32_vector = torch.cat(merged_partitions, 0) + merged_single_partition_of_fp32_groups.append(full_single_fp32_vector) + avail_numel = sum( + [full_single_fp32_vector.numel() for full_single_fp32_vector in merged_single_partition_of_fp32_groups]) + + if debug: + wanted_params = sum([len(shapes) for shapes in param_shapes]) + wanted_numel = sum([sum(shape.numel() for shape in shapes.values()) for shapes in param_shapes]) + # not asserting if there is a mismatch due to possible padding + print(f"Have {avail_numel} numels to process.") + print(f"Need {wanted_numel} numels in {wanted_params} params.") + + # params + # XXX: for huge models that can't fit into the host's RAM we will have to recode this to support + # out-of-core computing solution + total_numel = 0 + total_params = 0 + for shapes, full_single_fp32_vector in zip(param_shapes, merged_single_partition_of_fp32_groups): + offset = 0 + avail_numel = full_single_fp32_vector.numel() + for name, shape in shapes.items(): + + unpartitioned_numel = shape.numel() if _has_callable(shape, 'numel') else math.prod(shape) + total_numel += unpartitioned_numel + total_params += 1 + + if debug: + print(f"{name} full shape: {shape} unpartitioned numel {unpartitioned_numel} ") + state_dict[name] = full_single_fp32_vector.narrow(0, offset, unpartitioned_numel).view(shape) + offset += unpartitioned_numel + + # Z2 started to align to 2*world_size to improve nccl performance. Therefore both offset and + # avail_numel can differ by anywhere between 0..2*world_size. Due to two unrelated complex + # paddings performed in the code it's almost impossible to predict the exact numbers w/o the + # live optimizer object, so we are checking that the numbers are within the right range + align_to = 2 * world_size + + def zero2_align(x): + return align_to * math.ceil(x / align_to) + + if debug: + print(f"original offset={offset}, avail_numel={avail_numel}") + + offset = zero2_align(offset) + avail_numel = zero2_align(avail_numel) + + if debug: + print(f"aligned offset={offset}, avail_numel={avail_numel}") + + # Sanity check + if offset != avail_numel: + raise ValueError(f"consumed {offset} numels out of {avail_numel} - something is wrong") + + print(f"Reconstructed fp32 state dict with {total_params} params {total_numel} elements") + + +def _get_fp32_state_dict_from_zero2_checkpoint(world_size, fp32_flat_groups, zero_model_states, + exclude_frozen_parameters): + state_dict = OrderedDict() + + # buffers + buffers = zero_model_states[0].buffers + state_dict.update(buffers) + if debug: + print(f"added {len(buffers)} buffers") + + if not exclude_frozen_parameters: + _zero2_merge_frozen_params(state_dict, zero_model_states) + + _zero2_merge_trainable_params(state_dict, world_size, fp32_flat_groups, zero_model_states) + + # recover shared parameters + for pair in zero_model_states[0].shared_params: + if pair[1] in state_dict: + state_dict[pair[0]] = state_dict[pair[1]] + + return state_dict + + +def zero3_partitioned_param_info(unpartitioned_numel, world_size): + remainder = unpartitioned_numel % world_size + padding_numel = (world_size - remainder) if remainder else 0 + partitioned_numel = math.ceil(unpartitioned_numel / world_size) + return partitioned_numel, padding_numel + + +def _zero3_merge_frozen_params(state_dict, world_size, zero_model_states): + if zero_model_states[0].frozen_param_shapes is None or len(zero_model_states[0].frozen_param_shapes) == 0: + return + + if debug: + for i in range(world_size): + num_elem = sum(s.numel() for s in zero_model_states[i].frozen_param_fragments.values()) + print(f'rank {i}: {FROZEN_PARAM_SHAPES}.numel = {num_elem}') + + frozen_param_shapes = zero_model_states[0].frozen_param_shapes + wanted_params = len(frozen_param_shapes) + wanted_numel = sum(s.numel() for s in frozen_param_shapes.values()) + avail_numel = sum([p.numel() for p in zero_model_states[0].frozen_param_fragments.values()]) * world_size + print(f'Frozen params: Have {avail_numel} numels to process.') + print(f'Frozen params: Need {wanted_numel} numels in {wanted_params} params') + + total_params = 0 + total_numel = 0 + for name, shape in zero_model_states[0].frozen_param_shapes.items(): + total_params += 1 + unpartitioned_numel = shape.numel() + total_numel += unpartitioned_numel + + param_frags = tuple(model_state.frozen_param_fragments[name] for model_state in zero_model_states) + state_dict[name] = torch.cat(param_frags, 0).narrow(0, 0, unpartitioned_numel).view(shape) + + partitioned_numel, partitioned_padding_numel = zero3_partitioned_param_info(unpartitioned_numel, world_size) + + if debug: + print( + f"Frozen params: {total_params} {name} full shape: {shape} partition0 numel={partitioned_numel} partitioned_padding_numel={partitioned_padding_numel}" + ) + + print(f"Reconstructed Frozen fp32 state dict with {total_params} params {total_numel} elements") + + +def _zero3_merge_trainable_params(state_dict, world_size, fp32_flat_groups, zero_model_states): + param_shapes = zero_model_states[0].param_shapes + avail_numel = fp32_flat_groups[0].numel() * world_size + # Reconstruction protocol: For zero3 we need to zip the partitions together at boundary of each + # param, re-consolidating each param, while dealing with padding if any + + # merge list of dicts, preserving order + param_shapes = {k: v for d in param_shapes for k, v in d.items()} + + if debug: + for i in range(world_size): + print(f"{FP32_FLAT_GROUPS}[{i}].shape={fp32_flat_groups[i].shape}") + + wanted_params = len(param_shapes) + wanted_numel = sum(shape.numel() for shape in param_shapes.values()) + # not asserting if there is a mismatch due to possible padding + avail_numel = fp32_flat_groups[0].numel() * world_size + print(f"Trainable params: Have {avail_numel} numels to process.") + print(f"Trainable params: Need {wanted_numel} numels in {wanted_params} params.") + + # params + # XXX: for huge models that can't fit into the host's RAM we will have to recode this to support + # out-of-core computing solution + offset = 0 + total_numel = 0 + total_params = 0 + for name, shape in param_shapes.items(): + + unpartitioned_numel = shape.numel() + total_numel += unpartitioned_numel + total_params += 1 + + partitioned_numel, partitioned_padding_numel = zero3_partitioned_param_info(unpartitioned_numel, world_size) + + if debug: + print( + f"Trainable params: {total_params} {name} full shape: {shape} partition0 numel={partitioned_numel} partitioned_padding_numel={partitioned_padding_numel}" + ) + + # XXX: memory usage doubles here + state_dict[name] = torch.cat( + tuple(fp32_flat_groups[i].narrow(0, offset, partitioned_numel) for i in range(world_size)), + 0).narrow(0, 0, unpartitioned_numel).view(shape) + offset += partitioned_numel + + offset *= world_size + + # Sanity check + if offset != avail_numel: + raise ValueError(f"consumed {offset} numels out of {avail_numel} - something is wrong") + + print(f"Reconstructed Trainable fp32 state dict with {total_params} params {total_numel} elements") + + +def _get_fp32_state_dict_from_zero3_checkpoint(world_size, fp32_flat_groups, zero_model_states, + exclude_frozen_parameters): + state_dict = OrderedDict() + + # buffers + buffers = zero_model_states[0].buffers + state_dict.update(buffers) + if debug: + print(f"added {len(buffers)} buffers") + + if not exclude_frozen_parameters: + _zero3_merge_frozen_params(state_dict, world_size, zero_model_states) + + _zero3_merge_trainable_params(state_dict, world_size, fp32_flat_groups, zero_model_states) + + # recover shared parameters + for pair in zero_model_states[0].shared_params: + if pair[1] in state_dict: + state_dict[pair[0]] = state_dict[pair[1]] + + return state_dict + + +def get_fp32_state_dict_from_zero_checkpoint(checkpoint_dir, tag=None, exclude_frozen_parameters=False): + """ + Convert ZeRO 2 or 3 checkpoint into a single fp32 consolidated state_dict that can be loaded with + ``load_state_dict()`` and used for training without DeepSpeed or shared with others, for example + via a model hub. + + Args: + - ``checkpoint_dir``: path to the desired checkpoint folder + - ``tag``: checkpoint tag used as a unique identifier for checkpoint. If not provided will attempt to load tag in 'latest' file. e.g., ``global_step14`` + - ``exclude_frozen_parameters``: exclude frozen parameters + + Returns: + - pytorch ``state_dict`` + + Note: this approach may not work if your application doesn't have sufficient free CPU memory and + you may need to use the offline approach using the ``zero_to_fp32.py`` script that is saved with + the checkpoint. + + A typical usage might be :: + + from deepspeed.utils.zero_to_fp32 import get_fp32_state_dict_from_zero_checkpoint + # do the training and checkpoint saving + state_dict = get_fp32_state_dict_from_zero_checkpoint(checkpoint_dir) # already on cpu + model = model.cpu() # move to cpu + model.load_state_dict(state_dict) + # submit to model hub or save the model to share with others + + In this example the ``model`` will no longer be usable in the deepspeed context of the same + application. i.e. you will need to re-initialize the deepspeed engine, since + ``model.load_state_dict(state_dict)`` will remove all the deepspeed magic from it. + + If you want it all done for you, use ``load_state_dict_from_zero_checkpoint`` instead. + + """ + if tag is None: + latest_path = os.path.join(checkpoint_dir, 'latest') + if os.path.isfile(latest_path): + with open(latest_path, 'r') as fd: + tag = fd.read().strip() + else: + raise ValueError(f"Unable to find 'latest' file at {latest_path}") + + ds_checkpoint_dir = os.path.join(checkpoint_dir, tag) + + if not os.path.isdir(ds_checkpoint_dir): + raise FileNotFoundError(f"Directory '{ds_checkpoint_dir}' doesn't exist") + + return _get_fp32_state_dict_from_zero_checkpoint(ds_checkpoint_dir, exclude_frozen_parameters) + + +def convert_zero_checkpoint_to_fp32_state_dict(checkpoint_dir, output_file, tag=None, exclude_frozen_parameters=False): + """ + Convert ZeRO 2 or 3 checkpoint into a single fp32 consolidated ``state_dict`` file that can be + loaded with ``torch.load(file)`` + ``load_state_dict()`` and used for training without DeepSpeed. + + Args: + - ``checkpoint_dir``: path to the desired checkpoint folder. (one that contains the tag-folder, like ``global_step14``) + - ``output_file``: path to the pytorch fp32 state_dict output file (e.g. path/pytorch_model.bin) + - ``tag``: checkpoint tag used as a unique identifier for checkpoint. If not provided will attempt to load tag in the file named ``latest`` in the checkpoint folder, e.g., ``global_step14`` + - ``exclude_frozen_parameters``: exclude frozen parameters + """ + + state_dict = get_fp32_state_dict_from_zero_checkpoint(checkpoint_dir, tag, exclude_frozen_parameters) + print(f"Saving fp32 state dict to {output_file}") + torch.save(state_dict, output_file) + + +def load_state_dict_from_zero_checkpoint(model, checkpoint_dir, tag=None): + """ + 1. Put the provided model to cpu + 2. Convert ZeRO 2 or 3 checkpoint into a single fp32 consolidated ``state_dict`` + 3. Load it into the provided model + + Args: + - ``model``: the model object to update + - ``checkpoint_dir``: path to the desired checkpoint folder. (one that contains the tag-folder, like ``global_step14``) + - ``tag``: checkpoint tag used as a unique identifier for checkpoint. If not provided will attempt to load tag in the file named ``latest`` in the checkpoint folder, e.g., ``global_step14`` + + Returns: + - ``model`: modified model + + Make sure you have plenty of CPU memory available before you call this function. If you don't + have enough use the ``zero_to_fp32.py`` utility to do the conversion. You will find it + conveniently placed for you in the checkpoint folder. + + A typical usage might be :: + + from deepspeed.utils.zero_to_fp32 import load_state_dict_from_zero_checkpoint + model = load_state_dict_from_zero_checkpoint(trainer.model, checkpoint_dir) + # submit to model hub or save the model to share with others + + Note, that once this was run, the ``model`` will no longer be usable in the deepspeed context + of the same application. i.e. you will need to re-initialize the deepspeed engine, since + ``model.load_state_dict(state_dict)`` will remove all the deepspeed magic from it. + + """ + logger.info(f"Extracting fp32 weights") + state_dict = get_fp32_state_dict_from_zero_checkpoint(checkpoint_dir, tag) + + logger.info(f"Overwriting model with fp32 weights") + model = model.cpu() + model.load_state_dict(state_dict, strict=False) + + return model + + +if __name__ == "__main__": + + parser = argparse.ArgumentParser() + parser.add_argument("checkpoint_dir", + type=str, + help="path to the desired checkpoint folder, e.g., path/checkpoint-12") + parser.add_argument( + "output_file", + type=str, + help="path to the pytorch fp32 state_dict output file (e.g. path/checkpoint-12/pytorch_model.bin)") + parser.add_argument("-t", + "--tag", + type=str, + default=None, + help="checkpoint tag used as a unique identifier for checkpoint. e.g., global_step1") + parser.add_argument("--exclude_frozen_parameters", action='store_true', help="exclude frozen parameters") + parser.add_argument("-d", "--debug", action='store_true', help="enable debug") + args = parser.parse_args() + + debug = args.debug + + convert_zero_checkpoint_to_fp32_state_dict(args.checkpoint_dir, + args.output_file, + tag=args.tag, + exclude_frozen_parameters=args.exclude_frozen_parameters) diff --git a/InternVL-main/internvl_chat/work_dirs/internvl_chat_v2_5/mmvet/config.json b/InternVL-main/internvl_chat/work_dirs/internvl_chat_v2_5/mmvet/config.json new file mode 100644 index 0000000000000000000000000000000000000000..158971cad1ae787acc2978b8a91808af019905fc --- /dev/null +++ b/InternVL-main/internvl_chat/work_dirs/internvl_chat_v2_5/mmvet/config.json @@ -0,0 +1,204 @@ +{ + "_commit_hash": null, + "_name_or_path": "/home1/gmh/InternVL/InternVL_2_5", + "architectures": [ + "InternVLChatModel" + ], + "auto_map": { + "AutoConfig": "configuration_internvl_chat.InternVLChatConfig", + "AutoModel": "modeling_internvl_chat.InternVLChatModel", + "AutoModelForCausalLM": "modeling_internvl_chat.InternVLChatModel" + }, + "downsample_ratio": 0.5, + "dynamic_image_size": true, + "force_image_size": 448, + "hidden_size": 2048, + "llm_config": { + "_name_or_path": "internlm/internlm2_5-1_8b-chat", + "add_cross_attention": false, + "architectures": [ + "InternLM2ForCausalLM" + ], + "attn_implementation": "flash_attention_2", + "auto_map": { + "AutoConfig": "configuration_internlm2.InternLM2Config", + "AutoModel": "modeling_internlm2.InternLM2ForCausalLM", + "AutoModelForCausalLM": "modeling_internlm2.InternLM2ForCausalLM", + "AutoModelForSequenceClassification": "modeling_internlm2.InternLM2ForSequenceClassification" + }, + "bad_words_ids": null, + "begin_suppress_tokens": null, + "bias": false, + "bos_token_id": 1, + "chunk_size_feed_forward": 0, + "cross_attention_hidden_size": null, + "decoder_start_token_id": null, + "diversity_penalty": 0.0, + "do_sample": false, + "early_stopping": false, + "encoder_no_repeat_ngram_size": 0, + "eos_token_id": 2, + "exponential_decay_length_penalty": null, + "finetuning_task": null, + "forced_bos_token_id": null, + "forced_eos_token_id": null, + "hidden_act": "silu", + "hidden_size": 2048, + "id2label": { + "0": "LABEL_0", + "1": "LABEL_1" + }, + "initializer_range": 0.02, + "intermediate_size": 8192, + "is_decoder": false, + "is_encoder_decoder": false, + "label2id": { + "LABEL_0": 0, + "LABEL_1": 1 + }, + "length_penalty": 1.0, + "max_length": 20, + "max_position_embeddings": 32768, + "min_length": 0, + "model_type": "internlm2", + "no_repeat_ngram_size": 0, + "num_attention_heads": 16, + "num_beam_groups": 1, + "num_beams": 1, + "num_hidden_layers": 24, + "num_key_value_heads": 8, + "num_return_sequences": 1, + "output_attentions": false, + "output_hidden_states": false, + "output_scores": false, + "pad_token_id": 2, + "prefix": null, + "pretraining_tp": 1, + "problem_type": null, + "pruned_heads": {}, + "remove_invalid_values": false, + "repetition_penalty": 1.0, + "return_dict": true, + "return_dict_in_generate": false, + "rms_norm_eps": 1e-05, + "rope_scaling": { + "factor": 2.0, + "type": "dynamic" + }, + "rope_theta": 1000000, + "sep_token_id": null, + "suppress_tokens": null, + "task_specific_params": null, + "temperature": 1.0, + "tf_legacy_loss": false, + "tie_encoder_decoder": false, + "tie_word_embeddings": false, + "tokenizer_class": null, + "top_k": 50, + "top_p": 1.0, + "torch_dtype": "bfloat16", + "torchscript": false, + "transformers_version": "4.43.2", + "typical_p": 1.0, + "use_bfloat16": true, + "use_cache": false, + "vocab_size": 92553 + }, + "max_dynamic_patch": 6, + "min_dynamic_patch": 1, + "model_type": "internvl_chat", + "pad2square": false, + "ps_version": "v2", + "select_layer": -1, + "template": "internvl2_5", + "tie_word_embeddings": false, + "torch_dtype": "bfloat16", + "transformers_version": null, + "use_backbone_lora": 0, + "use_llm_lora": 16, + "use_thumbnail": true, + "vision_config": { + "_name_or_path": "", + "add_cross_attention": false, + "architectures": [ + "InternVisionModel" + ], + "attention_dropout": 0.0, + "bad_words_ids": null, + "begin_suppress_tokens": null, + "bos_token_id": null, + "chunk_size_feed_forward": 0, + "cross_attention_hidden_size": null, + "decoder_start_token_id": null, + "diversity_penalty": 0.0, + "do_sample": false, + "drop_path_rate": 0.0, + "dropout": 0.0, + "early_stopping": false, + "encoder_no_repeat_ngram_size": 0, + "eos_token_id": null, + "exponential_decay_length_penalty": null, + "finetuning_task": null, + "forced_bos_token_id": null, + "forced_eos_token_id": null, + "hidden_act": "gelu", + "hidden_size": 1024, + "id2label": { + "0": "LABEL_0", + "1": "LABEL_1" + }, + "image_size": 448, + "initializer_factor": 1.0, + "initializer_range": 0.02, + "intermediate_size": 4096, + "is_decoder": false, + "is_encoder_decoder": false, + "label2id": { + "LABEL_0": 0, + "LABEL_1": 1 + }, + "layer_norm_eps": 1e-06, + "length_penalty": 1.0, + "max_length": 20, + "min_length": 0, + "model_type": "intern_vit_6b", + "no_repeat_ngram_size": 0, + "norm_type": "layer_norm", + "num_attention_heads": 16, + "num_beam_groups": 1, + "num_beams": 1, + "num_channels": 3, + "num_hidden_layers": 24, + "num_return_sequences": 1, + "output_attentions": false, + "output_hidden_states": false, + "output_scores": false, + "pad_token_id": null, + "patch_size": 14, + "prefix": null, + "problem_type": null, + "pruned_heads": {}, + "qk_normalization": false, + "qkv_bias": true, + "remove_invalid_values": false, + "repetition_penalty": 1.0, + "return_dict": true, + "return_dict_in_generate": false, + "sep_token_id": null, + "suppress_tokens": null, + "task_specific_params": null, + "temperature": 1.0, + "tf_legacy_loss": false, + "tie_encoder_decoder": false, + "tie_word_embeddings": true, + "tokenizer_class": null, + "top_k": 50, + "top_p": 1.0, + "torch_dtype": "bfloat16", + "torchscript": false, + "transformers_version": "4.43.2", + "typical_p": 1.0, + "use_bfloat16": true, + "use_flash_attn": true + } +} diff --git a/InternVL-main/internvl_chat/work_dirs/internvl_chat_v2_5/mmvet/generation_config.json b/InternVL-main/internvl_chat/work_dirs/internvl_chat_v2_5/mmvet/generation_config.json new file mode 100644 index 0000000000000000000000000000000000000000..918fe50c5a6fd362e537376348091b2bc5f51820 --- /dev/null +++ b/InternVL-main/internvl_chat/work_dirs/internvl_chat_v2_5/mmvet/generation_config.json @@ -0,0 +1,8 @@ +{ + "_from_model_config": true, + "eos_token_id": [ + 92542, + 92543 + ], + "transformers_version": "4.43.2" +} diff --git a/InternVL-main/internvl_chat/work_dirs/internvl_chat_v2_5/mmvet/special_tokens_map.json b/InternVL-main/internvl_chat/work_dirs/internvl_chat_v2_5/mmvet/special_tokens_map.json new file mode 100644 index 0000000000000000000000000000000000000000..cbf34a50d27c43ed8d1e2823b800b4e6f66e637a --- /dev/null +++ b/InternVL-main/internvl_chat/work_dirs/internvl_chat_v2_5/mmvet/special_tokens_map.json @@ -0,0 +1,47 @@ +{ + "additional_special_tokens": [ + "<|im_start|>", + "<|im_end|>", + "<|action_start|>", + "<|action_end|>", + "<|interpreter|>", + "<|plugin|>", + "", + "", + "", + "", + "", + "", + "", + "", + "" + ], + "bos_token": { + "content": "", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false + }, + "eos_token": { + "content": "", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false + }, + "pad_token": { + "content": "", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false + }, + "unk_token": { + "content": "", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false + } +} diff --git a/InternVL-main/internvl_chat/work_dirs/internvl_chat_v2_5/mmvet/tokenization_internlm2.py b/InternVL-main/internvl_chat/work_dirs/internvl_chat_v2_5/mmvet/tokenization_internlm2.py new file mode 100644 index 0000000000000000000000000000000000000000..1be581da37ef678de65f2737493fc0ed7160446e --- /dev/null +++ b/InternVL-main/internvl_chat/work_dirs/internvl_chat_v2_5/mmvet/tokenization_internlm2.py @@ -0,0 +1,235 @@ +# Copyright (c) The InternLM team and The HuggingFace Inc. team. All rights reserved. +# +# This code is based on transformers/src/transformers/models/llama/tokenization_llama.py +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +"""Tokenization classes for InternLM.""" +import os +from shutil import copyfile +from typing import Any, Dict, List, Optional, Tuple + +import sentencepiece as spm +from transformers.tokenization_utils import PreTrainedTokenizer +from transformers.utils import logging + +logger = logging.get_logger(__name__) + +VOCAB_FILES_NAMES = {'vocab_file': './tokenizer.model'} + +PRETRAINED_VOCAB_FILES_MAP = {} + + +# Modified from transformers.model.llama.tokenization_llama.LlamaTokenizer +class InternLM2Tokenizer(PreTrainedTokenizer): + """ + Construct a InternLM2 tokenizer. Based on byte-level Byte-Pair-Encoding. + + Args: + vocab_file (`str`): + Path to the vocabulary file. + """ + + vocab_files_names = VOCAB_FILES_NAMES + pretrained_vocab_files_map = PRETRAINED_VOCAB_FILES_MAP + model_input_names = ['input_ids', 'attention_mask'] + _auto_class = 'AutoTokenizer' + + def __init__( + self, + vocab_file, + unk_token='', + bos_token='', + eos_token='', + pad_token='', + sp_model_kwargs: Optional[Dict[str, Any]] = None, + add_bos_token=True, + add_eos_token=False, + decode_with_prefix_space=False, + clean_up_tokenization_spaces=False, + **kwargs, + ): + self.sp_model_kwargs = {} if sp_model_kwargs is None else sp_model_kwargs + self.vocab_file = vocab_file + self.add_bos_token = add_bos_token + self.add_eos_token = add_eos_token + self.decode_with_prefix_space = decode_with_prefix_space + self.sp_model = spm.SentencePieceProcessor(**self.sp_model_kwargs) + self.sp_model.Load(vocab_file) + self._no_prefix_space_tokens = None + super().__init__( + bos_token=bos_token, + eos_token=eos_token, + unk_token=unk_token, + pad_token=pad_token, + clean_up_tokenization_spaces=clean_up_tokenization_spaces, + **kwargs, + ) + + @property + def no_prefix_space_tokens(self): + if self._no_prefix_space_tokens is None: + vocab = self.convert_ids_to_tokens(list(range(self.vocab_size))) + self._no_prefix_space_tokens = {i for i, tok in enumerate(vocab) if not tok.startswith('▁')} + return self._no_prefix_space_tokens + + @property + def vocab_size(self): + """Returns vocab size""" + return self.sp_model.get_piece_size() + + @property + def bos_token_id(self) -> Optional[int]: + return self.sp_model.bos_id() + + @property + def eos_token_id(self) -> Optional[int]: + return self.sp_model.eos_id() + + def get_vocab(self): + """Returns vocab as a dict""" + vocab = {self.convert_ids_to_tokens(i): i for i in range(self.vocab_size)} + vocab.update(self.added_tokens_encoder) + return vocab + + def _tokenize(self, text): + """Returns a tokenized string.""" + return self.sp_model.encode(text, out_type=str) + + def _convert_token_to_id(self, token): + """Converts a token (str) in an id using the vocab.""" + return self.sp_model.piece_to_id(token) + + def _convert_id_to_token(self, index): + """Converts an index (integer) in a token (str) using the vocab.""" + token = self.sp_model.IdToPiece(index) + return token + + def _maybe_add_prefix_space(self, tokens, decoded): + if tokens and tokens[0] not in self.no_prefix_space_tokens: + return ' ' + decoded + else: + return decoded + + def convert_tokens_to_string(self, tokens): + """Converts a sequence of tokens (string) in a single string.""" + current_sub_tokens = [] + out_string = '' + prev_is_special = False + for token in tokens: + # make sure that special tokens are not decoded using sentencepiece model + if token in self.all_special_tokens: + if not prev_is_special: + out_string += ' ' + out_string += self.sp_model.decode(current_sub_tokens) + token + prev_is_special = True + current_sub_tokens = [] + else: + current_sub_tokens.append(token) + prev_is_special = False + out_string += self.sp_model.decode(current_sub_tokens) + out_string = self.clean_up_tokenization(out_string) + out_string = self._maybe_add_prefix_space(tokens=tokens, decoded=out_string) + return out_string[1:] + + def save_vocabulary(self, save_directory, filename_prefix: Optional[str] = None) -> Tuple[str]: + """ + Save the vocabulary and special tokens file to a directory. + + Args: + save_directory (`str`): + The directory in which to save the vocabulary. + + Returns: + `Tuple(str)`: Paths to the files saved. + """ + if not os.path.isdir(save_directory): + logger.error(f'Vocabulary path ({save_directory}) should be a directory') + return + out_vocab_file = os.path.join( + save_directory, (filename_prefix + '-' if filename_prefix else '') + VOCAB_FILES_NAMES['vocab_file'] + ) + + if os.path.abspath(self.vocab_file) != os.path.abspath(out_vocab_file) and os.path.isfile(self.vocab_file): + copyfile(self.vocab_file, out_vocab_file) + elif not os.path.isfile(self.vocab_file): + with open(out_vocab_file, 'wb') as fi: + content_spiece_model = self.sp_model.serialized_model_proto() + fi.write(content_spiece_model) + + return (out_vocab_file,) + + def build_inputs_with_special_tokens(self, token_ids_0, token_ids_1=None): + if self.add_bos_token: + bos_token_ids = [self.bos_token_id] + else: + bos_token_ids = [] + + output = bos_token_ids + token_ids_0 + + if token_ids_1 is not None: + output = output + token_ids_1 + + if self.add_eos_token: + output = output + [self.eos_token_id] + + return output + + def get_special_tokens_mask( + self, token_ids_0: List[int], token_ids_1: Optional[List[int]] = None, already_has_special_tokens: bool = False + ) -> List[int]: + """ + Retrieve sequence ids from a token list that has no special tokens added. This method is called when adding + special tokens using the tokenizer `prepare_for_model` method. + + Args: + token_ids_0 (`List[int]`): + List of IDs. + token_ids_1 (`List[int]`, *optional*): + Optional second list of IDs for sequence pairs. + already_has_special_tokens (`bool`, *optional*, defaults to `False`): + Whether or not the token list is already formatted with special tokens for the model. + + Returns: + `List[int]`: A list of integers in the range [0, 1]: 1 for a special token, 0 for a sequence token. + """ + if already_has_special_tokens: + return super().get_special_tokens_mask( + token_ids_0=token_ids_0, token_ids_1=token_ids_1, already_has_special_tokens=True + ) + + if token_ids_1 is None: + return [1] + ([0] * len(token_ids_0)) + [1] + return [1] + ([0] * len(token_ids_0)) + [1, 1] + ([0] * len(token_ids_1)) + [1] + + def create_token_type_ids_from_sequences( + self, token_ids_0: List[int], token_ids_1: Optional[List[int]] = None + ) -> List[int]: + """ + Create a mask from the two sequences passed to be used in a sequence-pair classification task. T5 does not make + use of token type ids, therefore a list of zeros is returned. + + Args: + token_ids_0 (`List[int]`): + List of IDs. + token_ids_1 (`List[int]`, *optional*): + Optional second list of IDs for sequence pairs. + + Returns: + `List[int]`: List of zeros. + """ + eos = [self.eos_token_id] + + if token_ids_1 is None: + return len(token_ids_0 + eos) * [0] + return len(token_ids_0 + eos + token_ids_1 + eos) * [0] diff --git a/InternVL-main/internvl_chat/work_dirs/internvl_chat_v2_5/mmvet/tokenizer_config.json b/InternVL-main/internvl_chat/work_dirs/internvl_chat_v2_5/mmvet/tokenizer_config.json new file mode 100644 index 0000000000000000000000000000000000000000..1f32946df0f56d92ddbc1df79cabb4477b622480 --- /dev/null +++ b/InternVL-main/internvl_chat/work_dirs/internvl_chat_v2_5/mmvet/tokenizer_config.json @@ -0,0 +1,179 @@ +{ + "added_tokens_decoder": { + "0": { + "content": "", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "1": { + "content": "", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "2": { + "content": "", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "92538": { + "content": "<|plugin|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "92539": { + "content": "<|interpreter|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "92540": { + "content": "<|action_end|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "92541": { + "content": "<|action_start|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "92542": { + "content": "<|im_end|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "92543": { + "content": "<|im_start|>", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "92544": { + "content": "", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "92545": { + "content": "", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "92546": { + "content": "", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "92547": { + "content": "", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "92548": { + "content": "", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "92549": { + "content": "", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "92550": { + "content": "", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "92551": { + "content": "", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "92552": { + "content": "", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + } + }, + "additional_special_tokens": [ + "<|im_start|>", + "<|im_end|>", + "<|action_start|>", + "<|action_end|>", + "<|interpreter|>", + "<|plugin|>", + "", + "", + "", + "", + "", + "", + "", + "", + "" + ], + "auto_map": { + "AutoTokenizer": [ + "tokenization_internlm2.InternLM2Tokenizer", + null + ] + }, + "bos_token": "", + "chat_template": "{{ bos_token }}{% for message in messages %}{{'<|im_start|>' + message['role'] + '\n' + message['content'] + '<|im_end|>' + '\n'}}{% endfor %}{% if add_generation_prompt %}{{ '<|im_start|>assistant\n' }}{% endif %}", 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a/InternVL-main/internvl_chat/work_dirs/internvl_chat_v2_5/mmvet/training_log.txt b/InternVL-main/internvl_chat/work_dirs/internvl_chat_v2_5/mmvet/training_log.txt new file mode 100644 index 0000000000000000000000000000000000000000..d19343606222eefe5ea6aa13d1075d2726d78e8f --- /dev/null +++ b/InternVL-main/internvl_chat/work_dirs/internvl_chat_v2_5/mmvet/training_log.txt @@ -0,0 +1,17131 @@ +[2025-05-14 21:25:53,333] [INFO] [real_accelerator.py:203:get_accelerator] Setting ds_accelerator to cuda (auto detect) +/home1/gmh/anaconda3/envs/promptbench/lib/python3.9/site-packages/timm/models/layers/__init__.py:48: FutureWarning: Importing from timm.models.layers is deprecated, please import via timm.layers + warnings.warn(f"Importing from {__name__} is deprecated, please import via timm.layers", FutureWarning) +petrel_client is not installed. If you read data locally instead of from ceph, ignore it. +petrel_client is not installed. Using PIL to load images. +[2025-05-14 21:25:57,164] [INFO] [comm.py:652:init_distributed] cdb=None +[2025-05-14 21:25:57,164] [INFO] [comm.py:683:init_distributed] Initializing TorchBackend in DeepSpeed with backend nccl +05/14/2025 21:25:57 - WARNING - __main__ - Process rank: 0, device: cuda:0, n_gpu: 1distributed training: True, 16-bits training: False +05/14/2025 21:25:57 - INFO - __main__ - Training/evaluation parameters TrainingArguments( +_n_gpu=1, +accelerator_config={'split_batches': False, 'dispatch_batches': None, 'even_batches': True, 'use_seedable_sampler': True, 'non_blocking': False, 'gradient_accumulation_kwargs': None, 'use_configured_state': False}, +adafactor=False, +adam_beta1=0.9, +adam_beta2=0.999, +adam_epsilon=1e-08, +auto_find_batch_size=False, +batch_eval_metrics=False, +bf16=True, +bf16_full_eval=False, +data_seed=None, +dataloader_drop_last=False, +dataloader_num_workers=4, +dataloader_persistent_workers=False, +dataloader_pin_memory=True, +dataloader_prefetch_factor=None, +ddp_backend=None, +ddp_broadcast_buffers=None, +ddp_bucket_cap_mb=None, +ddp_find_unused_parameters=None, +ddp_timeout=1800, +debug=[], +deepspeed=zero_stage1_config.json, +disable_tqdm=False, +dispatch_batches=None, +do_eval=False, +do_predict=False, +do_train=True, +eval_accumulation_steps=None, +eval_delay=0, +eval_do_concat_batches=True, +eval_on_start=False, +eval_steps=None, +eval_strategy=no, +eval_use_gather_object=False, +evaluation_strategy=no, +fp16=False, +fp16_backend=auto, +fp16_full_eval=False, +fp16_opt_level=O1, +fsdp=[], +fsdp_config={'min_num_params': 0, 'xla': False, 'xla_fsdp_v2': False, 'xla_fsdp_grad_ckpt': False}, +fsdp_min_num_params=0, +fsdp_transformer_layer_cls_to_wrap=None, +full_determinism=False, +gradient_accumulation_steps=8, +gradient_checkpointing=False, +gradient_checkpointing_kwargs=None, +greater_is_better=None, +group_by_length=True, +half_precision_backend=auto, +hub_always_push=False, +hub_model_id=None, +hub_private_repo=False, +hub_strategy=every_save, +hub_token=, +ignore_data_skip=False, +include_inputs_for_metrics=False, +include_num_input_tokens_seen=False, +include_tokens_per_second=False, +jit_mode_eval=False, +label_names=None, +label_smoothing_factor=0.0, +learning_rate=1e-10, +length_column_name=length, +load_best_model_at_end=False, +local_rank=0, +log_level=passive, +log_level_replica=warning, +log_on_each_node=True, +logging_dir=work_dirs/internvl_chat_v2_5/mmvet/runs/May14_21-25-57_9007, +logging_first_step=False, +logging_nan_inf_filter=True, +logging_steps=1.0, +logging_strategy=steps, +lr_scheduler_kwargs={}, +lr_scheduler_type=cosine, +max_grad_norm=1.0, +max_steps=-1, +metric_for_best_model=None, +mp_parameters=, +neftune_noise_alpha=None, +no_cuda=False, +num_train_epochs=1.0, +optim=adamw_torch, +optim_args=None, +optim_target_modules=None, +output_dir=work_dirs/internvl_chat_v2_5/mmvet, +overwrite_output_dir=True, +past_index=-1, +per_device_eval_batch_size=8, +per_device_train_batch_size=1, +prediction_loss_only=False, +push_to_hub=False, +push_to_hub_model_id=None, +push_to_hub_organization=None, +push_to_hub_token=, +ray_scope=last, +remove_unused_columns=True, +report_to=['tensorboard'], +restore_callback_states_from_checkpoint=False, +resume_from_checkpoint=None, +run_name=work_dirs/internvl_chat_v2_5/mmvet, +save_on_each_node=False, +save_only_model=False, +save_safetensors=True, +save_steps=100, +save_strategy=steps, +save_total_limit=100, +seed=42, +skip_memory_metrics=True, +split_batches=None, +tf32=None, +torch_compile=False, +torch_compile_backend=None, +torch_compile_mode=None, +torch_empty_cache_steps=None, +torchdynamo=None, +tpu_metrics_debug=False, +tpu_num_cores=None, +use_cpu=False, +use_ipex=False, +use_legacy_prediction_loop=False, +use_mps_device=False, +warmup_ratio=0.03, +warmup_steps=0, +weight_decay=0.01, +) +05/14/2025 21:25:57 - INFO - __main__ - Loading Tokenizer: /home1/gmh/InternVL/InternVL_2_5 +[INFO|tokenization_utils_base.py:2287] 2025-05-14 21:25:57,287 >> loading file ./tokenizer.model +[INFO|tokenization_utils_base.py:2287] 2025-05-14 21:25:57,287 >> loading file added_tokens.json +[INFO|tokenization_utils_base.py:2287] 2025-05-14 21:25:57,287 >> loading file special_tokens_map.json +[INFO|tokenization_utils_base.py:2287] 2025-05-14 21:25:57,287 >> loading file tokenizer_config.json +[INFO|tokenization_utils_base.py:2287] 2025-05-14 21:25:57,287 >> loading file tokenizer.json +[INFO|tokenization_utils_base.py:2533] 2025-05-14 21:25:57,481 >> Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained. +05/14/2025 21:25:57 - INFO - __main__ - Loading InternVLChatModel... +[INFO|configuration_utils.py:731] 2025-05-14 21:25:57,626 >> loading configuration file /home1/gmh/InternVL/InternVL_2_5/config.json +[INFO|configuration_utils.py:800] 2025-05-14 21:25:57,628 >> Model config InternVLChatConfig { + "_commit_hash": null, + "architectures": [ + "InternVLChatModel" + ], + "auto_map": { + "AutoConfig": "configuration_internvl_chat.InternVLChatConfig", + "AutoModel": "modeling_internvl_chat.InternVLChatModel", + "AutoModelForCausalLM": "modeling_internvl_chat.InternVLChatModel" + }, + "downsample_ratio": 0.5, + "dynamic_image_size": true, + "force_image_size": 448, + "hidden_size": 2048, + "llm_config": { + "_name_or_path": "internlm/internlm2_5-1_8b-chat", + "add_cross_attention": false, + "architectures": [ + "InternLM2ForCausalLM" + ], + "attn_implementation": "flash_attention_2", + "auto_map": { + "AutoConfig": "configuration_internlm2.InternLM2Config", + "AutoModel": "modeling_internlm2.InternLM2ForCausalLM", + "AutoModelForCausalLM": "modeling_internlm2.InternLM2ForCausalLM", + "AutoModelForSequenceClassification": "modeling_internlm2.InternLM2ForSequenceClassification" + }, + "bad_words_ids": null, + "begin_suppress_tokens": null, + "bias": false, + "bos_token_id": 1, + "chunk_size_feed_forward": 0, + "cross_attention_hidden_size": null, + "decoder_start_token_id": null, + "diversity_penalty": 0.0, + "do_sample": false, + "early_stopping": false, + "encoder_no_repeat_ngram_size": 0, + "eos_token_id": 2, + "exponential_decay_length_penalty": null, + "finetuning_task": null, + "forced_bos_token_id": null, + "forced_eos_token_id": null, + "hidden_act": "silu", + "hidden_size": 2048, + "id2label": { + "0": "LABEL_0", + "1": "LABEL_1" + }, + "initializer_range": 0.02, + "intermediate_size": 8192, + "is_decoder": false, + "is_encoder_decoder": false, + "label2id": { + "LABEL_0": 0, + "LABEL_1": 1 + }, + "length_penalty": 1.0, + "max_length": 20, + "max_position_embeddings": 32768, + "min_length": 0, + "model_type": "internlm2", + "no_repeat_ngram_size": 0, + "num_attention_heads": 16, + "num_beam_groups": 1, + "num_beams": 1, + "num_hidden_layers": 24, + "num_key_value_heads": 8, + "num_return_sequences": 1, + "output_attentions": false, + "output_hidden_states": false, + "output_scores": false, + "pad_token_id": 2, + "prefix": null, + "pretraining_tp": 1, + "problem_type": null, + "pruned_heads": {}, + "remove_invalid_values": false, + "repetition_penalty": 1.0, + "return_dict": true, + "return_dict_in_generate": false, + "rms_norm_eps": 1e-05, + "rope_scaling": { + "factor": 2.0, + "type": "dynamic" + }, + "rope_theta": 1000000, + "sep_token_id": null, + "suppress_tokens": null, + "task_specific_params": null, + "temperature": 1.0, + "tf_legacy_loss": false, + "tie_encoder_decoder": false, + "tie_word_embeddings": false, + "tokenizer_class": null, + "top_k": 50, + "top_p": 1.0, + "torch_dtype": "bfloat16", + "torchscript": false, + "transformers_version": "4.43.2", + "typical_p": 1.0, + "use_bfloat16": true, + "use_cache": true, + "vocab_size": 92553 + }, + "max_dynamic_patch": 12, + "min_dynamic_patch": 1, + "model_type": "internvl_chat", + "pad2square": false, + "ps_version": "v2", + "select_layer": -1, + "template": "internvl2_5", + "tie_word_embeddings": false, + "torch_dtype": "bfloat16", + "transformers_version": null, + "use_backbone_lora": 0, + "use_llm_lora": 0, + "use_thumbnail": true, + "vision_config": { + "_name_or_path": "", + "add_cross_attention": false, + "architectures": [ + "InternVisionModel" + ], + "attention_dropout": 0.0, + "bad_words_ids": null, + "begin_suppress_tokens": null, + "bos_token_id": null, + "chunk_size_feed_forward": 0, + "cross_attention_hidden_size": null, + "decoder_start_token_id": null, + "diversity_penalty": 0.0, + "do_sample": false, + "drop_path_rate": 0.0, + "dropout": 0.0, + "early_stopping": false, + "encoder_no_repeat_ngram_size": 0, + "eos_token_id": null, + "exponential_decay_length_penalty": null, + "finetuning_task": null, + "forced_bos_token_id": null, + "forced_eos_token_id": null, + "hidden_act": "gelu", + "hidden_size": 1024, + "id2label": { + "0": "LABEL_0", + "1": "LABEL_1" + }, + "image_size": 448, + "initializer_factor": 1.0, + "initializer_range": 0.02, + "intermediate_size": 4096, + "is_decoder": false, + "is_encoder_decoder": false, + "label2id": { + "LABEL_0": 0, + "LABEL_1": 1 + }, + "layer_norm_eps": 1e-06, + "length_penalty": 1.0, + "max_length": 20, + "min_length": 0, + "model_type": "intern_vit_6b", + "no_repeat_ngram_size": 0, + "norm_type": "layer_norm", + "num_attention_heads": 16, + "num_beam_groups": 1, + "num_beams": 1, + "num_channels": 3, + "num_hidden_layers": 24, + "num_return_sequences": 1, + "output_attentions": false, + "output_hidden_states": false, + "output_scores": false, + "pad_token_id": null, + "patch_size": 14, + "prefix": null, + "problem_type": null, + "pruned_heads": {}, + "qk_normalization": false, + "qkv_bias": true, + "remove_invalid_values": false, + "repetition_penalty": 1.0, + "return_dict": true, + "return_dict_in_generate": false, + "sep_token_id": null, + "suppress_tokens": null, + "task_specific_params": null, + "temperature": 1.0, + "tf_legacy_loss": false, + "tie_encoder_decoder": false, + "tie_word_embeddings": true, + "tokenizer_class": null, + "top_k": 50, + "top_p": 1.0, + "torch_dtype": "bfloat16", + "torchscript": false, + "transformers_version": "4.43.2", + "typical_p": 1.0, + "use_bfloat16": true, + "use_flash_attn": true + } +} + +05/14/2025 21:25:57 - INFO - __main__ - Using flash_attention_2 for InternLM +[INFO|modeling_utils.py:3631] 2025-05-14 21:25:57,628 >> loading weights file /home1/gmh/InternVL/InternVL_2_5/model.safetensors +[INFO|modeling_utils.py:1572] 2025-05-14 21:25:58,036 >> Instantiating InternVLChatModel model under default dtype torch.bfloat16. +[INFO|configuration_utils.py:1038] 2025-05-14 21:25:58,040 >> Generate config GenerationConfig {} + +[INFO|configuration_utils.py:1038] 2025-05-14 21:25:58,123 >> Generate config GenerationConfig { + "bos_token_id": 1, + "eos_token_id": 2, + "pad_token_id": 2 +} + +[INFO|modeling_utils.py:4463] 2025-05-14 21:25:58,456 >> All model checkpoint weights were used when initializing InternVLChatModel. + +[INFO|modeling_utils.py:4471] 2025-05-14 21:25:58,456 >> All the weights of InternVLChatModel were initialized from the model checkpoint at /home1/gmh/InternVL/InternVL_2_5. +If your task is similar to the task the model of the checkpoint was trained on, you can already use InternVLChatModel for predictions without further training. +[INFO|configuration_utils.py:991] 2025-05-14 21:25:58,466 >> loading configuration file /home1/gmh/InternVL/InternVL_2_5/generation_config.json +[INFO|configuration_utils.py:1038] 2025-05-14 21:25:58,467 >> Generate config GenerationConfig { + "eos_token_id": [ + 92542, + 92543 + ] +} + +05/14/2025 21:25:58 - INFO - __main__ - Finished +05/14/2025 21:25:58 - INFO - __main__ - model.config.force_image_size: 448 +05/14/2025 21:25:58 - INFO - __main__ - data_args.force_image_size: 448 +05/14/2025 21:25:58 - INFO - __main__ - model.config.vision_config.image_size: 448 +05/14/2025 21:25:58 - INFO - __main__ - [Dataset] num_image_token: 256 +05/14/2025 21:25:58 - INFO - __main__ - [Dataset] dynamic_image_size: True +05/14/2025 21:25:58 - INFO - __main__ - [Dataset] use_thumbnail: True +05/14/2025 21:25:58 - INFO - __main__ - [Dataset] min_dynamic_patch: 1, max_dynamic_patch: 6 +05/14/2025 21:25:58 - INFO - __main__ - Formatting inputs...Skip in lazy mode +05/14/2025 21:25:59 - INFO - __main__ - Add dataset: extend2 with length: 14874 +trainable params: 15,728,640 || all params: 1,904,875,520 || trainable%: 0.8257 +05/14/2025 21:25:59 - INFO - __main__ - language_model.base_model.model.model.layers.0.attention.wqkv.lora_A.default.weight +05/14/2025 21:25:59 - INFO - __main__ - language_model.base_model.model.model.layers.0.attention.wqkv.lora_B.default.weight +05/14/2025 21:25:59 - INFO - __main__ - language_model.base_model.model.model.layers.0.attention.wo.lora_A.default.weight +05/14/2025 21:25:59 - INFO - __main__ - language_model.base_model.model.model.layers.0.attention.wo.lora_B.default.weight 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__main__ - language_model.base_model.model.model.layers.23.feed_forward.w2.lora_B.default.weight +[INFO|trainer.py:648] 2025-05-14 21:25:59,834 >> Using auto half precision backend +[2025-05-14 21:26:00,299] [INFO] [logging.py:96:log_dist] [Rank 0] DeepSpeed info: version=0.15.1, git-hash=unknown, git-branch=unknown +[2025-05-14 21:26:00,299] [INFO] [config.py:733:__init__] Config mesh_device None world_size = 1 +[2025-05-14 21:26:12,956] [INFO] [logging.py:96:log_dist] [Rank 0] DeepSpeed Flops Profiler Enabled: False +Using /home1/gmh/.cache/torch_extensions/py39_cu121 as PyTorch extensions root... +Emitting ninja build file /home1/gmh/.cache/torch_extensions/py39_cu121/cpu_adam/build.ninja... +Building extension module cpu_adam... +Allowing ninja to set a default number of workers... (overridable by setting the environment variable MAX_JOBS=N) +[1/3] c++ -MMD -MF cpu_adam.o.d -DTORCH_EXTENSION_NAME=cpu_adam -DTORCH_API_INCLUDE_EXTENSION_H -DPYBIND11_COMPILER_TYPE=\"_gcc\" -DPYBIND11_STDLIB=\"_libstdcpp\" -DPYBIND11_BUILD_ABI=\"_cxxabi1011\" -I/home1/gmh/anaconda3/envs/promptbench/lib/python3.9/site-packages/deepspeed/ops/csrc/includes -isystem /home1/gmh/anaconda3/envs/promptbench/lib/python3.9/site-packages/torch/include -isystem /home1/gmh/anaconda3/envs/promptbench/lib/python3.9/site-packages/torch/include/torch/csrc/api/include -isystem /home1/gmh/anaconda3/envs/promptbench/lib/python3.9/site-packages/torch/include/TH -isystem /home1/gmh/anaconda3/envs/promptbench/lib/python3.9/site-packages/torch/include/THC -isystem /home1/gmh/anaconda3/envs/promptbench/include/python3.9 -D_GLIBCXX_USE_CXX11_ABI=0 -fPIC -std=c++17 -O3 -std=c++17 -g -Wno-reorder -L/usr/local/cuda-12.1/lib64 -lcudart -lcublas -g -march=native -fopenmp -D__AVX512__ -D__ENABLE_CUDA__ -DBF16_AVAILABLE -c /home1/gmh/anaconda3/envs/promptbench/lib/python3.9/site-packages/deepspeed/ops/csrc/adam/cpu_adam.cpp -o cpu_adam.o +[2/3] c++ -MMD -MF cpu_adam_impl.o.d -DTORCH_EXTENSION_NAME=cpu_adam -DTORCH_API_INCLUDE_EXTENSION_H -DPYBIND11_COMPILER_TYPE=\"_gcc\" -DPYBIND11_STDLIB=\"_libstdcpp\" -DPYBIND11_BUILD_ABI=\"_cxxabi1011\" -I/home1/gmh/anaconda3/envs/promptbench/lib/python3.9/site-packages/deepspeed/ops/csrc/includes -isystem /home1/gmh/anaconda3/envs/promptbench/lib/python3.9/site-packages/torch/include -isystem /home1/gmh/anaconda3/envs/promptbench/lib/python3.9/site-packages/torch/include/torch/csrc/api/include -isystem /home1/gmh/anaconda3/envs/promptbench/lib/python3.9/site-packages/torch/include/TH -isystem /home1/gmh/anaconda3/envs/promptbench/lib/python3.9/site-packages/torch/include/THC -isystem /home1/gmh/anaconda3/envs/promptbench/include/python3.9 -D_GLIBCXX_USE_CXX11_ABI=0 -fPIC -std=c++17 -O3 -std=c++17 -g -Wno-reorder -L/usr/local/cuda-12.1/lib64 -lcudart -lcublas -g -march=native -fopenmp -D__AVX512__ -D__ENABLE_CUDA__ -DBF16_AVAILABLE -c /home1/gmh/anaconda3/envs/promptbench/lib/python3.9/site-packages/deepspeed/ops/csrc/adam/cpu_adam_impl.cpp -o cpu_adam_impl.o +[3/3] c++ cpu_adam.o cpu_adam_impl.o -shared -lcurand -L/usr/local/cuda-12.1/lib64 -L/home1/gmh/anaconda3/envs/promptbench/lib/python3.9/site-packages/torch/lib -lc10 -ltorch_cpu -ltorch -ltorch_python -o cpu_adam.so +Loading extension module cpu_adam... +Time to load cpu_adam op: 34.46602940559387 seconds +Adam Optimizer #0 is created with AVX512 arithmetic capability. +Config: alpha=0.000000, betas=(0.900000, 0.999000), weight_decay=0.010000, adam_w=1 +[2025-05-14 21:26:48,707] [INFO] [logging.py:96:log_dist] [Rank 0] Using DeepSpeed Optimizer param name adamw as basic optimizer +[2025-05-14 21:26:48,707] [INFO] [logging.py:96:log_dist] [Rank 0] Removing param_group that has no 'params' in the basic Optimizer +[2025-05-14 21:26:48,746] [INFO] [logging.py:96:log_dist] [Rank 0] DeepSpeed Basic Optimizer = DeepSpeedCPUAdam +[2025-05-14 21:26:48,747] [INFO] [utils.py:59:is_zero_supported_optimizer] Checking ZeRO support for optimizer=DeepSpeedCPUAdam type= +[2025-05-14 21:26:48,747] [INFO] [logging.py:96:log_dist] [Rank 0] Creating torch.bfloat16 ZeRO stage 1 optimizer +[2025-05-14 21:26:48,747] [INFO] [stage_1_and_2.py:148:__init__] Reduce bucket size 1000000000 +[2025-05-14 21:26:48,747] [INFO] [stage_1_and_2.py:149:__init__] Allgather bucket size 1000000000 +[2025-05-14 21:26:48,747] [INFO] [stage_1_and_2.py:150:__init__] CPU Offload: True +[2025-05-14 21:26:48,747] [INFO] [stage_1_and_2.py:151:__init__] Round robin gradient partitioning: False +[2025-05-14 21:26:49,203] [INFO] [utils.py:781:see_memory_usage] Before initializing optimizer states +[2025-05-14 21:26:49,203] [INFO] [utils.py:782:see_memory_usage] MA 4.51 GB Max_MA 4.51 GB CA 4.7 GB Max_CA 5 GB +[2025-05-14 21:26:49,204] [INFO] [utils.py:789:see_memory_usage] CPU Virtual Memory: used = 352.59 GB, percent = 46.7% +[2025-05-14 21:26:49,452] [INFO] [utils.py:781:see_memory_usage] After initializing optimizer states +[2025-05-14 21:26:49,453] [INFO] [utils.py:782:see_memory_usage] MA 4.51 GB Max_MA 4.51 GB CA 4.7 GB Max_CA 5 GB +[2025-05-14 21:26:49,453] [INFO] [utils.py:789:see_memory_usage] CPU Virtual Memory: used = 352.64 GB, percent = 46.7% +[2025-05-14 21:26:49,453] [INFO] [stage_1_and_2.py:543:__init__] optimizer state initialized +[2025-05-14 21:26:49,667] [INFO] [utils.py:781:see_memory_usage] After initializing ZeRO optimizer +[2025-05-14 21:26:49,668] [INFO] [utils.py:782:see_memory_usage] MA 4.51 GB Max_MA 4.51 GB CA 4.7 GB Max_CA 5 GB +[2025-05-14 21:26:49,668] [INFO] [utils.py:789:see_memory_usage] CPU Virtual Memory: used = 352.64 GB, percent = 46.7% +[2025-05-14 21:26:49,677] [INFO] [logging.py:96:log_dist] [Rank 0] DeepSpeed Final Optimizer = DeepSpeedZeroOptimizer +[2025-05-14 21:26:49,677] [INFO] [logging.py:96:log_dist] [Rank 0] DeepSpeed using client callable to create LR scheduler +[2025-05-14 21:26:49,678] [INFO] [logging.py:96:log_dist] [Rank 0] DeepSpeed LR Scheduler = +[2025-05-14 21:26:49,678] [INFO] [logging.py:96:log_dist] [Rank 0] step=0, skipped=0, lr=[0.0], mom=[[0.9, 0.999]] +[2025-05-14 21:26:49,683] [INFO] [config.py:999:print] DeepSpeedEngine configuration: +[2025-05-14 21:26:49,684] [INFO] [config.py:1003:print] activation_checkpointing_config { + "partition_activations": false, + "contiguous_memory_optimization": false, + "cpu_checkpointing": false, + "number_checkpoints": null, + "synchronize_checkpoint_boundary": false, + "profile": false +} +[2025-05-14 21:26:49,684] [INFO] [config.py:1003:print] aio_config ................... {'block_size': 1048576, 'queue_depth': 8, 'thread_count': 1, 'single_submit': False, 'overlap_events': True, 'use_gds': False} +[2025-05-14 21:26:49,684] [INFO] [config.py:1003:print] amp_enabled .................. False +[2025-05-14 21:26:49,684] [INFO] [config.py:1003:print] amp_params ................... False +[2025-05-14 21:26:49,684] [INFO] [config.py:1003:print] autotuning_config ............ { + "enabled": false, + "start_step": null, + "end_step": null, + "metric_path": null, + "arg_mappings": null, + "metric": "throughput", + "model_info": null, + "results_dir": "autotuning_results", + "exps_dir": "autotuning_exps", + "overwrite": true, + "fast": true, + "start_profile_step": 3, + "end_profile_step": 5, + "tuner_type": "gridsearch", + "tuner_early_stopping": 5, + "tuner_num_trials": 50, + "model_info_path": null, + "mp_size": 1, + "max_train_batch_size": null, + "min_train_batch_size": 1, + "max_train_micro_batch_size_per_gpu": 1.024000e+03, + "min_train_micro_batch_size_per_gpu": 1, + "num_tuning_micro_batch_sizes": 3 +} +[2025-05-14 21:26:49,684] [INFO] [config.py:1003:print] bfloat16_enabled ............. True +[2025-05-14 21:26:49,684] [INFO] [config.py:1003:print] bfloat16_immediate_grad_update False +[2025-05-14 21:26:49,684] [INFO] [config.py:1003:print] checkpoint_parallel_write_pipeline False +[2025-05-14 21:26:49,684] [INFO] [config.py:1003:print] checkpoint_tag_validation_enabled True +[2025-05-14 21:26:49,684] [INFO] [config.py:1003:print] checkpoint_tag_validation_fail False +[2025-05-14 21:26:49,684] [INFO] [config.py:1003:print] comms_config ................. +[2025-05-14 21:26:49,684] [INFO] [config.py:1003:print] communication_data_type ...... None +[2025-05-14 21:26:49,684] [INFO] [config.py:1003:print] compression_config ........... {'weight_quantization': {'shared_parameters': {'enabled': False, 'quantizer_kernel': False, 'schedule_offset': 0, 'quantize_groups': 1, 'quantize_verbose': False, 'quantization_type': 'symmetric', 'quantize_weight_in_forward': False, 'rounding': 'nearest', 'fp16_mixed_quantize': False, 'quantize_change_ratio': 0.001}, 'different_groups': {}}, 'activation_quantization': {'shared_parameters': {'enabled': False, 'quantization_type': 'symmetric', 'range_calibration': 'dynamic', 'schedule_offset': 1000}, 'different_groups': {}}, 'sparse_pruning': {'shared_parameters': {'enabled': False, 'method': 'l1', 'schedule_offset': 1000}, 'different_groups': {}}, 'row_pruning': {'shared_parameters': {'enabled': False, 'method': 'l1', 'schedule_offset': 1000}, 'different_groups': {}}, 'head_pruning': {'shared_parameters': {'enabled': False, 'method': 'topk', 'schedule_offset': 1000}, 'different_groups': {}}, 'channel_pruning': {'shared_parameters': {'enabled': False, 'method': 'l1', 'schedule_offset': 1000}, 'different_groups': {}}, 'layer_reduction': {'enabled': False}} +[2025-05-14 21:26:49,684] [INFO] [config.py:1003:print] curriculum_enabled_legacy .... False +[2025-05-14 21:26:49,684] [INFO] [config.py:1003:print] curriculum_params_legacy ..... False +[2025-05-14 21:26:49,684] [INFO] [config.py:1003:print] data_efficiency_config ....... {'enabled': False, 'seed': 1234, 'data_sampling': {'enabled': False, 'num_epochs': 1000, 'num_workers': 0, 'curriculum_learning': {'enabled': False}}, 'data_routing': {'enabled': False, 'random_ltd': {'enabled': False, 'layer_token_lr_schedule': {'enabled': False}}}} +[2025-05-14 21:26:49,684] [INFO] [config.py:1003:print] data_efficiency_enabled ...... False +[2025-05-14 21:26:49,684] [INFO] [config.py:1003:print] dataloader_drop_last ......... False +[2025-05-14 21:26:49,684] [INFO] [config.py:1003:print] disable_allgather ............ False +[2025-05-14 21:26:49,684] [INFO] [config.py:1003:print] dump_state ................... False +[2025-05-14 21:26:49,685] [INFO] [config.py:1003:print] dynamic_loss_scale_args ...... None +[2025-05-14 21:26:49,685] [INFO] [config.py:1003:print] eigenvalue_enabled ........... False +[2025-05-14 21:26:49,685] [INFO] [config.py:1003:print] eigenvalue_gas_boundary_resolution 1 +[2025-05-14 21:26:49,685] [INFO] [config.py:1003:print] eigenvalue_layer_name ........ bert.encoder.layer +[2025-05-14 21:26:49,685] [INFO] [config.py:1003:print] eigenvalue_layer_num ......... 0 +[2025-05-14 21:26:49,685] [INFO] [config.py:1003:print] eigenvalue_max_iter .......... 100 +[2025-05-14 21:26:49,685] [INFO] [config.py:1003:print] eigenvalue_stability ......... 1e-06 +[2025-05-14 21:26:49,685] [INFO] [config.py:1003:print] eigenvalue_tol ............... 0.01 +[2025-05-14 21:26:49,685] [INFO] [config.py:1003:print] eigenvalue_verbose ........... False +[2025-05-14 21:26:49,685] [INFO] [config.py:1003:print] elasticity_enabled ........... False +[2025-05-14 21:26:49,685] [INFO] [config.py:1003:print] flops_profiler_config ........ { + "enabled": false, + "recompute_fwd_factor": 0.0, + "profile_step": 1, + "module_depth": -1, + "top_modules": 1, + "detailed": true, + "output_file": null +} +[2025-05-14 21:26:49,685] [INFO] [config.py:1003:print] fp16_auto_cast ............... None +[2025-05-14 21:26:49,685] [INFO] [config.py:1003:print] fp16_enabled ................. False +[2025-05-14 21:26:49,685] [INFO] [config.py:1003:print] fp16_master_weights_and_gradients False +[2025-05-14 21:26:49,685] [INFO] [config.py:1003:print] global_rank .................. 0 +[2025-05-14 21:26:49,685] [INFO] [config.py:1003:print] grad_accum_dtype ............. None +[2025-05-14 21:26:49,685] [INFO] [config.py:1003:print] gradient_accumulation_steps .. 8 +[2025-05-14 21:26:49,685] [INFO] [config.py:1003:print] gradient_clipping ............ 1.0 +[2025-05-14 21:26:49,685] [INFO] [config.py:1003:print] gradient_predivide_factor .... 1.0 +[2025-05-14 21:26:49,685] [INFO] [config.py:1003:print] graph_harvesting ............. False +[2025-05-14 21:26:49,685] [INFO] [config.py:1003:print] hybrid_engine ................ enabled=False max_out_tokens=512 inference_tp_size=1 release_inference_cache=False pin_parameters=True tp_gather_partition_size=8 +[2025-05-14 21:26:49,685] [INFO] [config.py:1003:print] initial_dynamic_scale ........ 1 +[2025-05-14 21:26:49,685] [INFO] [config.py:1003:print] load_universal_checkpoint .... False +[2025-05-14 21:26:49,685] [INFO] [config.py:1003:print] loss_scale ................... 1.0 +[2025-05-14 21:26:49,685] [INFO] [config.py:1003:print] memory_breakdown ............. False +[2025-05-14 21:26:49,685] [INFO] [config.py:1003:print] mics_hierarchial_params_gather False +[2025-05-14 21:26:49,685] [INFO] [config.py:1003:print] mics_shard_size .............. -1 +[2025-05-14 21:26:49,685] [INFO] [config.py:1003:print] monitor_config ............... tensorboard=TensorBoardConfig(enabled=False, output_path='', job_name='DeepSpeedJobName') comet=CometConfig(enabled=False, samples_log_interval=100, project=None, workspace=None, api_key=None, experiment_name=None, experiment_key=None, online=None, mode=None) wandb=WandbConfig(enabled=False, group=None, team=None, project='deepspeed') csv_monitor=CSVConfig(enabled=False, output_path='', job_name='DeepSpeedJobName') +[2025-05-14 21:26:49,685] [INFO] [config.py:1003:print] nebula_config ................ { + "enabled": false, + "persistent_storage_path": null, + "persistent_time_interval": 100, + "num_of_version_in_retention": 2, + "enable_nebula_load": true, + "load_path": null +} +[2025-05-14 21:26:49,685] [INFO] [config.py:1003:print] optimizer_legacy_fusion ...... False +[2025-05-14 21:26:49,685] [INFO] [config.py:1003:print] optimizer_name ............... adamw +[2025-05-14 21:26:49,685] [INFO] [config.py:1003:print] optimizer_params ............. {'lr': 1e-10, 'betas': [0.9, 0.999], 'eps': 1e-08, 'weight_decay': 0.01} +[2025-05-14 21:26:49,685] [INFO] [config.py:1003:print] pipeline ..................... {'stages': 'auto', 'partition': 'best', 'seed_layers': False, 'activation_checkpoint_interval': 0, 'pipe_partitioned': True, 'grad_partitioned': True} +[2025-05-14 21:26:49,686] [INFO] [config.py:1003:print] pld_enabled .................. False +[2025-05-14 21:26:49,686] [INFO] [config.py:1003:print] pld_params ................... False +[2025-05-14 21:26:49,686] [INFO] [config.py:1003:print] prescale_gradients ........... False +[2025-05-14 21:26:49,686] [INFO] [config.py:1003:print] scheduler_name ............... None +[2025-05-14 21:26:49,686] [INFO] [config.py:1003:print] scheduler_params ............. None +[2025-05-14 21:26:49,686] [INFO] [config.py:1003:print] seq_parallel_communication_data_type torch.float32 +[2025-05-14 21:26:49,686] [INFO] [config.py:1003:print] sparse_attention ............. None +[2025-05-14 21:26:49,686] [INFO] [config.py:1003:print] sparse_gradients_enabled ..... False +[2025-05-14 21:26:49,686] [INFO] [config.py:1003:print] steps_per_print .............. inf +[2025-05-14 21:26:49,686] [INFO] [config.py:1003:print] timers_config ................ enabled=True synchronized=True +[2025-05-14 21:26:49,686] [INFO] [config.py:1003:print] train_batch_size ............. 8 +[2025-05-14 21:26:49,686] [INFO] [config.py:1003:print] train_micro_batch_size_per_gpu 1 +[2025-05-14 21:26:49,686] [INFO] [config.py:1003:print] use_data_before_expert_parallel_ False +[2025-05-14 21:26:49,686] [INFO] [config.py:1003:print] use_node_local_storage ....... False +[2025-05-14 21:26:49,686] [INFO] [config.py:1003:print] wall_clock_breakdown ......... True +[2025-05-14 21:26:49,686] [INFO] [config.py:1003:print] weight_quantization_config ... None +[2025-05-14 21:26:49,686] [INFO] [config.py:1003:print] world_size ................... 1 +[2025-05-14 21:26:49,686] [INFO] [config.py:1003:print] zero_allow_untested_optimizer False +[2025-05-14 21:26:49,686] [INFO] [config.py:1003:print] zero_config .................. stage=1 contiguous_gradients=True reduce_scatter=True reduce_bucket_size=1000000000 use_multi_rank_bucket_allreduce=True allgather_partitions=True allgather_bucket_size=1000000000 overlap_comm=True load_from_fp32_weights=True elastic_checkpoint=False offload_param=DeepSpeedZeroOffloadParamConfig(device='cpu', nvme_path=None, buffer_count=5, buffer_size=100000000, max_in_cpu=1000000000, pin_memory=True) offload_optimizer=DeepSpeedZeroOffloadOptimizerConfig(device='cpu', nvme_path=None, buffer_count=4, pin_memory=True, pipeline_read=False, pipeline_write=False, fast_init=False, ratio=1.0) sub_group_size=1000000000 cpu_offload_param=None cpu_offload_use_pin_memory=None cpu_offload=None prefetch_bucket_size=50000000 param_persistence_threshold=100000 model_persistence_threshold=9223372036854775807 max_live_parameters=1000000000 max_reuse_distance=1000000000 gather_16bit_weights_on_model_save=False use_all_reduce_for_fetch_params=False stage3_gather_fp16_weights_on_model_save=False ignore_unused_parameters=True legacy_stage1=False round_robin_gradients=False zero_hpz_partition_size=1 zero_quantized_weights=False zero_quantized_nontrainable_weights=False zero_quantized_gradients=False mics_shard_size=-1 mics_hierarchical_params_gather=False memory_efficient_linear=True pipeline_loading_checkpoint=False override_module_apply=True +[2025-05-14 21:26:49,686] [INFO] [config.py:1003:print] zero_enabled ................. True +[2025-05-14 21:26:49,686] [INFO] [config.py:1003:print] zero_force_ds_cpu_optimizer .. True +[2025-05-14 21:26:49,686] [INFO] [config.py:1003:print] zero_optimization_stage ...... 1 +[2025-05-14 21:26:49,686] [INFO] [config.py:989:print_user_config] json = { + "zero_optimization": { + "stage": 1, + "allgather_partitions": true, + "allgather_bucket_size": 1.000000e+09, + "overlap_comm": true, + "reduce_scatter": true, + "reduce_bucket_size": 1.000000e+09, + "contiguous_gradients": true, + "offload_param": { + "device": "cpu", + "pin_memory": true + }, + "offload_optimizer": { + "device": "cpu", + "pin_memory": true + } + }, + "fp16": { + "enabled": false, + "auto_cast": true, + "loss_scale": 0, + "initial_scale_power": 32, + "loss_scale_window": 1000, + "hysteresis": 2, + "min_loss_scale": 1 + }, + "bf16": { + "enabled": true + }, + "optimizer": { + "type": "AdamW", + "params": { + "lr": 1e-10, + "betas": [0.9, 0.999], + "eps": 1e-08, + "weight_decay": 0.01 + } + }, + "gradient_accumulation_steps": 8, + "gradient_clipping": 1.0, + "steps_per_print": inf, + "train_batch_size": 8, + "train_micro_batch_size_per_gpu": 1, + "wall_clock_breakdown": true +} +[INFO|trainer.py:2134] 2025-05-14 21:26:49,687 >> ***** Running training ***** +[INFO|trainer.py:2135] 2025-05-14 21:26:49,687 >> Num examples = 14,874 +[INFO|trainer.py:2136] 2025-05-14 21:26:49,687 >> Num Epochs = 1 +[INFO|trainer.py:2137] 2025-05-14 21:26:49,687 >> Instantaneous batch size per device = 1 +[INFO|trainer.py:2140] 2025-05-14 21:26:49,687 >> Total train batch size (w. parallel, distributed & accumulation) = 8 +[INFO|trainer.py:2141] 2025-05-14 21:26:49,687 >> Gradient Accumulation steps = 8 +[INFO|trainer.py:2142] 2025-05-14 21:26:49,687 >> Total optimization steps = 1,859 +[INFO|trainer.py:2143] 2025-05-14 21:26:49,691 >> Number of trainable parameters = 15,728,640 + 0%| | 0/1859 [00:00> Saving model checkpoint to work_dirs/internvl_chat_v2_5/mmvet/checkpoint-100 +[INFO|configuration_utils.py:472] 2025-05-14 21:35:50,216 >> Configuration saved in work_dirs/internvl_chat_v2_5/mmvet/checkpoint-100/config.json +[INFO|configuration_utils.py:807] 2025-05-14 21:35:50,216 >> Configuration saved in work_dirs/internvl_chat_v2_5/mmvet/checkpoint-100/generation_config.json +[INFO|modeling_utils.py:2755] 2025-05-14 21:35:55,471 >> Model weights saved in work_dirs/internvl_chat_v2_5/mmvet/checkpoint-100/model.safetensors +[INFO|tokenization_utils_base.py:2702] 2025-05-14 21:35:55,473 >> tokenizer config file saved in work_dirs/internvl_chat_v2_5/mmvet/checkpoint-100/tokenizer_config.json +[INFO|tokenization_utils_base.py:2711] 2025-05-14 21:35:55,473 >> Special tokens file saved in work_dirs/internvl_chat_v2_5/mmvet/checkpoint-100/special_tokens_map.json +[INFO|tokenization_utils_base.py:2762] 2025-05-14 21:35:55,473 >> added tokens file saved in work_dirs/internvl_chat_v2_5/mmvet/checkpoint-100/added_tokens.json +[2025-05-14 21:35:55,640] [INFO] [logging.py:96:log_dist] [Rank 0] [Torch] Checkpoint global_step100 is about to be saved! +[2025-05-14 21:35:55,659] [INFO] [logging.py:96:log_dist] [Rank 0] Saving model checkpoint: work_dirs/internvl_chat_v2_5/mmvet/checkpoint-100/global_step100/mp_rank_00_model_states.pt +[2025-05-14 21:35:55,659] [INFO] [torch_checkpoint_engine.py:21:save] [Torch] Saving work_dirs/internvl_chat_v2_5/mmvet/checkpoint-100/global_step100/mp_rank_00_model_states.pt... +[2025-05-14 21:36:00,383] [INFO] [torch_checkpoint_engine.py:23:save] [Torch] Saved work_dirs/internvl_chat_v2_5/mmvet/checkpoint-100/global_step100/mp_rank_00_model_states.pt. +[2025-05-14 21:36:00,385] [INFO] [torch_checkpoint_engine.py:21:save] [Torch] Saving work_dirs/internvl_chat_v2_5/mmvet/checkpoint-100/global_step100/bf16_zero_pp_rank_0_mp_rank_00_optim_states.pt... +[2025-05-14 21:36:00,543] [INFO] [torch_checkpoint_engine.py:23:save] [Torch] Saved work_dirs/internvl_chat_v2_5/mmvet/checkpoint-100/global_step100/bf16_zero_pp_rank_0_mp_rank_00_optim_states.pt. +[2025-05-14 21:36:00,544] [INFO] [engine.py:3536:_save_zero_checkpoint] zero checkpoint saved work_dirs/internvl_chat_v2_5/mmvet/checkpoint-100/global_step100/bf16_zero_pp_rank_0_mp_rank_00_optim_states.pt +[2025-05-14 21:36:00,544] [INFO] [torch_checkpoint_engine.py:33:commit] [Torch] Checkpoint global_step100 is ready now! +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2023 +[2025-05-14 21:36:01,055] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 199.22 | bwd_microstep: 296.11 | bwd_inner_microstep: 295.89 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1894 +[2025-05-14 21:36:01,536] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.53 | bwd_microstep: 275.18 | bwd_inner_microstep: 274.87 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-14 21:36:02,015] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.93 | bwd_microstep: 273.20 | bwd_inner_microstep: 272.88 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.11 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 327 +[2025-05-14 21:36:02,267] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 77.10 | bwd_microstep: 159.88 | bwd_inner_microstep: 159.68 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-14 21:36:02,746] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.05 | bwd_microstep: 272.86 | bwd_inner_microstep: 272.61 | bwd_allreduce_microstep: 0.10 | step_microstep: 0.11 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 844 +[2025-05-14 21:36:02,993] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.00 | bwd_microstep: 134.53 | bwd_inner_microstep: 134.37 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-14 21:36:03,469] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.86 | bwd_microstep: 272.84 | bwd_inner_microstep: 272.67 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.10 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 320 +[2025-05-14 21:36:03,810] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.13 | optimizer_step: 18.42 +[2025-05-14 21:36:03,811] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 78.32 | bwd_microstep: 221.32 | bwd_inner_microstep: 159.68 | bwd_allreduce_microstep: 61.52 | step_microstep: 26.78 +[2025-05-14 21:36:03,811] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 1199.89 | bwd: 1906.00 | bwd_inner: 1843.03 | bwd_allreduce: 62.11 | step: 27.50 + 5%|▌ | 101/1859 [09:14<3:41:13, 7.55s/it] {'loss': 6.7344, 'grad_norm': 17.423341751098633, 'learning_rate': 9.984637892017597e-11, 'epoch': 0.05} + 5%|▌ | 101/1859 [09:14<3:41:13, 7.55s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1941 +[2025-05-14 21:36:04,320] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 196.09 | bwd_microstep: 288.58 | bwd_inner_microstep: 288.27 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-14 21:36:04,800] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.31 | bwd_microstep: 273.84 | bwd_inner_microstep: 273.69 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-14 21:36:05,277] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.53 | bwd_microstep: 272.34 | bwd_inner_microstep: 272.19 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.09 +dynamic ViT batch size: 2, images per sample: 2.0, dynamic token length: 584 +[2025-05-14 21:36:05,519] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 80.29 | bwd_microstep: 146.80 | bwd_inner_microstep: 146.54 | bwd_allreduce_microstep: 0.09 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-14 21:36:05,999] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.49 | bwd_microstep: 273.27 | bwd_inner_microstep: 272.93 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-14 21:36:06,477] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.24 | bwd_microstep: 272.24 | bwd_inner_microstep: 272.08 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-14 21:36:06,955] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.42 | bwd_microstep: 272.30 | bwd_inner_microstep: 271.98 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 829 +[2025-05-14 21:36:07,310] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.19 | optimizer_step: 18.03 +[2025-05-14 21:36:07,311] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 96.11 | bwd_microstep: 216.54 | bwd_inner_microstep: 154.89 | bwd_allreduce_microstep: 61.53 | step_microstep: 26.34 +[2025-05-14 21:36:07,312] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 1311.37 | bwd: 2016.01 | bwd_inner: 1952.93 | bwd_allreduce: 62.14 | step: 27.17 + 5%|▌ | 102/1859 [09:17<3:05:31, 6.34s/it] {'loss': 7.2009, 'grad_norm': 72.84622192382812, 'learning_rate': 9.983947915052343e-11, 'epoch': 0.05} + 5%|▌ | 102/1859 [09:17<3:05:31, 6.34s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1886 +[2025-05-14 21:36:07,799] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.06 | bwd_microstep: 274.08 | bwd_inner_microstep: 273.94 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-14 21:36:08,279] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.53 | bwd_microstep: 273.82 | bwd_inner_microstep: 273.61 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 858 +[2025-05-14 21:36:08,527] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.98 | bwd_microstep: 137.45 | bwd_inner_microstep: 137.31 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-14 21:36:09,007] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.29 | bwd_microstep: 273.82 | bwd_inner_microstep: 273.48 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-14 21:36:09,487] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.93 | bwd_microstep: 273.52 | bwd_inner_microstep: 273.35 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-14 21:36:09,966] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.75 | bwd_microstep: 273.25 | bwd_inner_microstep: 273.01 | bwd_allreduce_microstep: 0.08 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-14 21:36:10,442] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.01 | bwd_microstep: 269.93 | bwd_inner_microstep: 269.60 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1996 +[2025-05-14 21:36:11,044] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.01 | optimizer_gradients: 2.07 | optimizer_step: 18.49 +[2025-05-14 21:36:11,044] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 197.05 | bwd_microstep: 359.13 | bwd_inner_microstep: 295.61 | bwd_allreduce_microstep: 63.35 | step_microstep: 27.05 +[2025-05-14 21:36:11,045] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 1420.49 | bwd: 2135.12 | bwd_inner: 2070.30 | bwd_allreduce: 63.86 | step: 27.90 + 6%|▌ | 103/1859 [09:21<2:42:34, 5.55s/it] {'loss': 4.8091, 'grad_norm': 39.036720275878906, 'learning_rate': 9.983242806597719e-11, 'epoch': 0.06} + 6%|▌ | 103/1859 [09:21<2:42:34, 5.55s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1887 +[2025-05-14 21:36:11,536] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.93 | bwd_microstep: 275.68 | bwd_inner_microstep: 275.48 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1888 +[2025-05-14 21:36:12,021] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.73 | bwd_microstep: 276.29 | bwd_inner_microstep: 276.14 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-14 21:36:12,504] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.86 | bwd_microstep: 275.00 | bwd_inner_microstep: 274.86 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-14 21:36:12,986] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.12 | bwd_microstep: 274.47 | bwd_inner_microstep: 274.31 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-14 21:36:13,468] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.40 | bwd_microstep: 274.87 | bwd_inner_microstep: 274.57 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-14 21:36:13,949] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.58 | bwd_microstep: 274.77 | bwd_inner_microstep: 274.40 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.10 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 321 +[2025-05-14 21:36:14,200] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 85.30 | bwd_microstep: 149.02 | bwd_inner_microstep: 148.82 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-14 21:36:14,769] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.07 | optimizer_gradients: 2.09 | optimizer_step: 18.25 +[2025-05-14 21:36:14,770] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.08 | bwd_microstep: 336.05 | bwd_inner_microstep: 274.39 | bwd_allreduce_microstep: 61.47 | step_microstep: 26.72 +[2025-05-14 21:36:14,771] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 1413.88 | bwd: 2136.26 | bwd_inner: 2073.37 | bwd_allreduce: 61.98 | step: 27.41 + 6%|▌ | 104/1859 [09:25<2:26:25, 5.01s/it] {'loss': 5.0874, 'grad_norm': 18.151918411254883, 'learning_rate': 9.982522568794464e-11, 'epoch': 0.06} + 6%|▌ | 104/1859 [09:25<2:26:25, 5.01s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1909 +[2025-05-14 21:36:15,265] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 191.76 | bwd_microstep: 278.25 | bwd_inner_microstep: 277.93 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1904 +[2025-05-14 21:36:15,752] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.36 | bwd_microstep: 278.01 | bwd_inner_microstep: 277.82 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1892 +[2025-05-14 21:36:16,238] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 191.19 | bwd_microstep: 276.91 | bwd_inner_microstep: 276.77 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-14 21:36:16,720] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.70 | bwd_microstep: 274.65 | bwd_inner_microstep: 274.49 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-14 21:36:17,203] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.73 | bwd_microstep: 275.11 | bwd_inner_microstep: 274.97 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-14 21:36:17,683] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.55 | bwd_microstep: 273.97 | bwd_inner_microstep: 273.82 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-14 21:36:18,162] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.69 | bwd_microstep: 272.63 | bwd_inner_microstep: 272.50 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-14 21:36:18,726] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.16 | optimizer_step: 18.22 +[2025-05-14 21:36:18,727] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.56 | bwd_microstep: 333.74 | bwd_inner_microstep: 273.37 | bwd_allreduce_microstep: 60.19 | step_microstep: 26.57 +[2025-05-14 21:36:18,727] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 1518.44 | bwd: 2263.37 | bwd_inner: 2201.96 | bwd_allreduce: 60.66 | step: 27.25 + 6%|▌ | 105/1859 [09:28<2:17:08, 4.69s/it] {'loss': 5.6229, 'grad_norm': 21.740598678588867, 'learning_rate': 9.981787203829254e-11, 'epoch': 0.06} + 6%|▌ | 105/1859 [09:28<2:17:08, 4.69s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-14 21:36:19,219] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.96 | bwd_microstep: 276.12 | bwd_inner_microstep: 275.81 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-14 21:36:19,703] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.99 | bwd_microstep: 276.36 | bwd_inner_microstep: 276.16 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 351 +[2025-05-14 21:36:19,950] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 92.77 | bwd_microstep: 138.21 | bwd_inner_microstep: 137.87 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-14 21:36:20,433] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.34 | bwd_microstep: 275.39 | bwd_inner_microstep: 275.19 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-14 21:36:20,917] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.77 | bwd_microstep: 275.47 | bwd_inner_microstep: 275.29 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.12 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 329 +[2025-05-14 21:36:21,172] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 92.91 | bwd_microstep: 144.48 | bwd_inner_microstep: 144.15 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.13 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-14 21:36:21,658] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.95 | bwd_microstep: 274.51 | bwd_inner_microstep: 274.15 | bwd_allreduce_microstep: 0.14 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-14 21:36:22,246] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.07 | optimizer_gradients: 2.17 | optimizer_step: 18.41 +[2025-05-14 21:36:22,246] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.77 | bwd_microstep: 349.80 | bwd_inner_microstep: 275.05 | bwd_allreduce_microstep: 74.58 | step_microstep: 27.27 +[2025-05-14 21:36:22,247] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 1327.36 | bwd: 2010.49 | bwd_inner: 1934.16 | bwd_allreduce: 75.24 | step: 28.22 + 6%|▌ | 106/1859 [09:32<2:06:48, 4.34s/it] {'loss': 6.1477, 'grad_norm': 22.655757904052734, 'learning_rate': 9.981036713934687e-11, 'epoch': 0.06} + 6%|▌ | 106/1859 [09:32<2:06:48, 4.34s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1953 +[2025-05-14 21:36:22,763] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 197.93 | bwd_microstep: 291.06 | bwd_inner_microstep: 290.90 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-14 21:36:23,247] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.63 | bwd_microstep: 275.73 | bwd_inner_microstep: 275.34 | bwd_allreduce_microstep: 0.15 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-14 21:36:23,730] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.34 | bwd_microstep: 274.49 | bwd_inner_microstep: 274.23 | bwd_allreduce_microstep: 0.09 | step_microstep: 0.11 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 836 +[2025-05-14 21:36:23,979] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 99.29 | bwd_microstep: 133.84 | bwd_inner_microstep: 133.60 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1353 +[2025-05-14 21:36:24,345] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.52 | bwd_microstep: 207.79 | bwd_inner_microstep: 207.63 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-14 21:36:24,825] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.30 | bwd_microstep: 273.97 | bwd_inner_microstep: 273.82 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-14 21:36:25,307] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.78 | bwd_microstep: 274.06 | bwd_inner_microstep: 273.91 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1354 +[2025-05-14 21:36:25,763] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.14 | optimizer_step: 18.34 +[2025-05-14 21:36:25,764] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.71 | bwd_microstep: 270.85 | bwd_inner_microstep: 208.61 | bwd_allreduce_microstep: 62.14 | step_microstep: 26.90 +[2025-05-14 21:36:25,764] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 1334.38 | bwd: 2001.89 | bwd_inner: 1938.35 | bwd_allreduce: 62.66 | step: 27.72 + 6%|▌ | 107/1859 [09:36<1:59:30, 4.09s/it] {'loss': 6.6329, 'grad_norm': 26.272512435913086, 'learning_rate': 9.980271101389286e-11, 'epoch': 0.06} + 6%|▌ | 107/1859 [09:36<1:59:30, 4.09s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1901 +[2025-05-14 21:36:26,258] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 191.33 | bwd_microstep: 277.57 | bwd_inner_microstep: 277.38 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.14 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-14 21:36:26,753] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 191.85 | bwd_microstep: 276.53 | bwd_inner_microstep: 276.38 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-14 21:36:27,289] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 202.81 | bwd_microstep: 314.90 | bwd_inner_microstep: 314.56 | bwd_allreduce_microstep: 0.14 | step_microstep: 0.21 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-14 21:36:27,827] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 217.93 | bwd_microstep: 299.77 | bwd_inner_microstep: 299.62 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 856 +[2025-05-14 21:36:28,089] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 99.39 | bwd_microstep: 145.58 | bwd_inner_microstep: 145.27 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-14 21:36:28,595] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 197.41 | bwd_microstep: 290.79 | bwd_inner_microstep: 290.48 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-14 21:36:29,094] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 197.36 | bwd_microstep: 281.71 | bwd_inner_microstep: 281.54 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-14 21:36:29,912] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.16 | optimizer_step: 18.49 +[2025-05-14 21:36:29,913] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 212.53 | bwd_microstep: 560.56 | bwd_inner_microstep: 452.62 | bwd_allreduce_microstep: 107.89 | step_microstep: 27.10 +[2025-05-14 21:36:29,914] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 1510.50 | bwd: 2447.53 | bwd_inner: 2338.11 | bwd_allreduce: 108.54 | step: 28.11 + 6%|▌ | 108/1859 [09:40<1:59:56, 4.11s/it] {'loss': 4.9384, 'grad_norm': 14.417268753051758, 'learning_rate': 9.979490368517485e-11, 'epoch': 0.06} + 6%|▌ | 108/1859 [09:40<1:59:56, 4.11s/it]dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 858 +[2025-05-14 21:36:30,202] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.64 | bwd_microstep: 170.33 | bwd_inner_microstep: 170.27 | bwd_allreduce_microstep: 0.02 | step_microstep: 2.36 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 360 +[2025-05-14 21:36:30,471] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 97.29 | bwd_microstep: 141.67 | bwd_inner_microstep: 141.38 | bwd_allreduce_microstep: 0.25 | step_microstep: 0.22 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-14 21:36:31,277] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 283.73 | bwd_microstep: 501.51 | bwd_inner_microstep: 501.47 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1383 +[2025-05-14 21:36:31,959] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 225.86 | bwd_microstep: 424.30 | bwd_inner_microstep: 423.99 | bwd_allreduce_microstep: 0.16 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-14 21:36:32,824] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 353.88 | bwd_microstep: 488.26 | bwd_inner_microstep: 488.22 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.32 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-14 21:36:33,637] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 289.67 | bwd_microstep: 491.45 | bwd_inner_microstep: 491.36 | bwd_allreduce_microstep: 0.03 | step_microstep: 0.10 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 840 +[2025-05-14 21:36:34,047] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.59 | bwd_microstep: 190.03 | bwd_inner_microstep: 189.99 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 926 +[2025-05-14 21:36:34,752] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.07 | optimizer_step: 18.02 +[2025-05-14 21:36:34,752] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 222.49 | bwd_microstep: 433.45 | bwd_inner_microstep: 217.07 | bwd_allreduce_microstep: 216.33 | step_microstep: 26.43 +[2025-05-14 21:36:34,753] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 1758.11 | bwd: 2841.03 | bwd_inner: 2623.82 | bwd_allreduce: 216.81 | step: 36.25 + 6%|▌ | 109/1859 [09:45<2:06:15, 4.33s/it] {'loss': 4.4807, 'grad_norm': 23.257627487182617, 'learning_rate': 9.978694517689624e-11, 'epoch': 0.06} + 6%|▌ | 109/1859 [09:45<2:06:15, 4.33s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1897 +[2025-05-14 21:36:35,463] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 399.10 | bwd_microstep: 286.67 | bwd_inner_microstep: 286.52 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1902 +[2025-05-14 21:36:36,378] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 398.53 | bwd_microstep: 497.37 | bwd_inner_microstep: 497.34 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.21 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1377 +[2025-05-14 21:36:36,965] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 215.47 | bwd_microstep: 352.72 | bwd_inner_microstep: 352.54 | bwd_allreduce_microstep: 0.08 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-14 21:36:37,877] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 393.75 | bwd_microstep: 496.22 | bwd_inner_microstep: 495.99 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-14 21:36:38,764] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 343.18 | bwd_microstep: 520.60 | bwd_inner_microstep: 520.55 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.32 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-14 21:36:39,588] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 292.78 | bwd_microstep: 498.40 | bwd_inner_microstep: 498.37 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-14 21:36:40,397] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 279.15 | bwd_microstep: 492.97 | bwd_inner_microstep: 492.95 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.56 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 864 +[2025-05-14 21:36:41,148] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 4.10 | optimizer_step: 24.26 +[2025-05-14 21:36:41,148] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 210.58 | bwd_microstep: 472.74 | bwd_inner_microstep: 187.84 | bwd_allreduce_microstep: 284.71 | step_microstep: 35.52 +[2025-05-14 21:36:41,149] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2532.49 | bwd: 3617.75 | bwd_inner: 3332.27 | bwd_allreduce: 284.92 | step: 43.29 + 6%|▌ | 110/1859 [09:51<2:24:15, 4.95s/it] {'loss': 4.4414, 'grad_norm': 27.526134490966797, 'learning_rate': 9.977883551321943e-11, 'epoch': 0.06} + 6%|▌ | 110/1859 [09:51<2:24:15, 4.95s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1900 +[2025-05-14 21:36:42,052] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 362.39 | bwd_microstep: 500.25 | bwd_inner_microstep: 499.91 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.20 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1364 +[2025-05-14 21:36:42,681] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 268.59 | bwd_microstep: 342.13 | bwd_inner_microstep: 342.11 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-14 21:36:43,412] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 217.25 | bwd_microstep: 480.18 | bwd_inner_microstep: 480.14 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.28 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-14 21:36:44,242] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 299.83 | bwd_microstep: 493.78 | bwd_inner_microstep: 493.75 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.37 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1095 +[2025-05-14 21:36:44,772] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 247.61 | bwd_microstep: 251.71 | bwd_inner_microstep: 251.44 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.28 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-14 21:36:45,586] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 302.14 | bwd_microstep: 477.89 | bwd_inner_microstep: 477.84 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-14 21:36:46,478] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 362.15 | bwd_microstep: 497.19 | bwd_inner_microstep: 497.04 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-14 21:36:47,521] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.01 | optimizer_gradients: 2.53 | optimizer_step: 19.25 +[2025-05-14 21:36:47,523] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 378.15 | bwd_microstep: 619.01 | bwd_inner_microstep: 501.72 | bwd_allreduce_microstep: 117.23 | step_microstep: 30.74 +[2025-05-14 21:36:47,524] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2438.05 | bwd: 3662.23 | bwd_inner: 3544.04 | bwd_allreduce: 117.60 | step: 40.65 + 6%|▌ | 111/1859 [09:57<2:36:40, 5.38s/it] {'loss': 6.8167, 'grad_norm': 27.770854949951172, 'learning_rate': 9.977057471876568e-11, 'epoch': 0.06} + 6%|▌ | 111/1859 [09:57<2:36:40, 5.38s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1906 +[2025-05-14 21:36:48,406] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 344.69 | bwd_microstep: 494.28 | bwd_inner_microstep: 493.97 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1897 +[2025-05-14 21:36:49,231] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 401.81 | bwd_microstep: 404.07 | bwd_inner_microstep: 403.92 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-14 21:36:50,129] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 376.12 | bwd_microstep: 492.68 | bwd_inner_microstep: 492.35 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.16 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-14 21:36:50,936] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 302.52 | bwd_microstep: 480.82 | bwd_inner_microstep: 480.77 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.37 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-14 21:36:51,681] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 317.00 | bwd_microstep: 394.23 | bwd_inner_microstep: 393.88 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-14 21:36:52,586] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 399.84 | bwd_microstep: 482.32 | bwd_inner_microstep: 482.27 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.26 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-14 21:36:53,392] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 292.30 | bwd_microstep: 492.17 | bwd_inner_microstep: 492.14 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-14 21:36:54,484] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.01 | optimizer_gradients: 2.24 | optimizer_step: 20.26 +[2025-05-14 21:36:54,485] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 293.06 | bwd_microstep: 739.61 | bwd_inner_microstep: 480.26 | bwd_allreduce_microstep: 259.27 | step_microstep: 28.94 +[2025-05-14 21:36:54,486] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2727.28 | bwd: 3980.29 | bwd_inner: 3719.77 | bwd_allreduce: 259.76 | step: 34.45 + 6%|▌ | 112/1859 [10:04<2:50:25, 5.85s/it] {'loss': 4.6787, 'grad_norm': 19.638137817382812, 'learning_rate': 9.976216281861518e-11, 'epoch': 0.06} + 6%|▌ | 112/1859 [10:04<2:50:25, 5.85s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1899 +[2025-05-14 21:36:55,358] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 333.90 | bwd_microstep: 494.79 | bwd_inner_microstep: 494.65 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1893 +[2025-05-14 21:36:56,270] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 397.77 | bwd_microstep: 496.40 | bwd_inner_microstep: 496.36 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.23 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1886 +[2025-05-14 21:36:57,093] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 303.87 | bwd_microstep: 497.53 | bwd_inner_microstep: 497.50 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.28 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-14 21:36:57,902] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 299.99 | bwd_microstep: 472.16 | bwd_inner_microstep: 472.12 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-14 21:36:58,759] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 344.45 | bwd_microstep: 478.12 | bwd_inner_microstep: 478.07 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.37 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1356 +[2025-05-14 21:36:59,284] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 284.10 | bwd_microstep: 209.14 | bwd_inner_microstep: 209.00 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-14 21:37:00,139] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 358.37 | bwd_microstep: 479.12 | bwd_inner_microstep: 479.06 | bwd_allreduce_microstep: 0.02 | step_microstep: 2.55 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1346 +[2025-05-14 21:37:00,864] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.01 | optimizer_gradients: 2.25 | optimizer_step: 23.02 +[2025-05-14 21:37:00,866] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 174.76 | bwd_microstep: 486.54 | bwd_inner_microstep: 416.80 | bwd_allreduce_microstep: 69.64 | step_microstep: 33.46 +[2025-05-14 21:37:00,866] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2497.16 | bwd: 3614.03 | bwd_inner: 3543.60 | bwd_allreduce: 69.80 | step: 43.43 + 6%|▌ | 113/1859 [10:11<2:54:55, 6.01s/it] {'loss': 5.6492, 'grad_norm': 20.223373413085938, 'learning_rate': 9.975359983830681e-11, 'epoch': 0.06} + 6%|▌ | 113/1859 [10:11<2:54:55, 6.01s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1921 +[2025-05-14 21:37:01,758] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 330.56 | bwd_microstep: 514.40 | bwd_inner_microstep: 514.36 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.37 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1915 +[2025-05-14 21:37:02,652] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 358.74 | bwd_microstep: 503.10 | bwd_inner_microstep: 502.95 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.14 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 357 +[2025-05-14 21:37:02,909] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.75 | bwd_microstep: 145.37 | bwd_inner_microstep: 145.33 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.28 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1886 +[2025-05-14 21:37:03,726] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 290.21 | bwd_microstep: 492.63 | bwd_inner_microstep: 492.60 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.31 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-14 21:37:04,576] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 325.16 | bwd_microstep: 492.94 | bwd_inner_microstep: 492.78 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-14 21:37:05,489] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 385.36 | bwd_microstep: 510.22 | bwd_inner_microstep: 510.19 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-14 21:37:06,303] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 301.19 | bwd_microstep: 491.45 | bwd_inner_microstep: 491.40 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.57 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-14 21:37:07,404] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.07 | optimizer_gradients: 2.12 | optimizer_step: 23.13 +[2025-05-14 21:37:07,405] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 290.65 | bwd_microstep: 746.64 | bwd_inner_microstep: 493.76 | bwd_allreduce_microstep: 252.82 | step_microstep: 32.31 +[2025-05-14 21:37:07,406] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2375.56 | bwd: 3896.78 | bwd_inner: 3643.41 | bwd_allreduce: 253.01 | step: 42.44 + 6%|▌ | 114/1859 [10:17<2:59:25, 6.17s/it] {'loss': 3.6794, 'grad_norm': 8.176952362060547, 'learning_rate': 9.974488580383816e-11, 'epoch': 0.06} + 6%|▌ | 114/1859 [10:17<2:59:25, 6.17s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1907 +[2025-05-14 21:37:08,336] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 403.43 | bwd_microstep: 498.23 | bwd_inner_microstep: 498.18 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.41 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 366 +[2025-05-14 21:37:08,580] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 79.04 | bwd_microstep: 148.66 | bwd_inner_microstep: 148.61 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.10 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1368 +[2025-05-14 21:37:09,263] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 232.52 | bwd_microstep: 416.16 | bwd_inner_microstep: 416.13 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.40 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-14 21:37:10,106] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 312.64 | bwd_microstep: 509.09 | bwd_inner_microstep: 509.04 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.58 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-14 21:37:10,937] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 301.60 | bwd_microstep: 496.03 | bwd_inner_microstep: 495.98 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.37 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 322 +[2025-05-14 21:37:11,210] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 106.72 | bwd_microstep: 137.02 | bwd_inner_microstep: 136.87 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-14 21:37:12,114] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 396.66 | bwd_microstep: 484.98 | bwd_inner_microstep: 484.94 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-14 21:37:13,169] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.01 | optimizer_gradients: 7.97 | optimizer_step: 20.48 +[2025-05-14 21:37:13,171] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 321.64 | bwd_microstep: 679.72 | bwd_inner_microstep: 507.58 | bwd_allreduce_microstep: 172.08 | step_microstep: 34.93 +[2025-05-14 21:37:13,172] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2151.61 | bwd: 3369.92 | bwd_inner: 3197.36 | bwd_allreduce: 172.21 | step: 43.24 + 6%|▌ | 115/1859 [10:23<2:55:48, 6.05s/it] {'loss': 3.8572, 'grad_norm': 31.4202938079834, 'learning_rate': 9.973602074166545e-11, 'epoch': 0.06} + 6%|▌ | 115/1859 [10:23<2:55:48, 6.05s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1934 +[2025-05-14 21:37:14,079] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 348.85 | bwd_microstep: 515.84 | bwd_inner_microstep: 515.80 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1394 +[2025-05-14 21:37:14,745] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 209.06 | bwd_microstep: 424.89 | bwd_inner_microstep: 424.68 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1899 +[2025-05-14 21:37:15,544] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 351.55 | bwd_microstep: 422.62 | bwd_inner_microstep: 422.58 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-14 21:37:16,374] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 295.37 | bwd_microstep: 500.73 | bwd_inner_microstep: 500.68 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.37 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-14 21:37:17,242] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 341.61 | bwd_microstep: 493.80 | bwd_inner_microstep: 493.62 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-14 21:37:18,149] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 395.68 | bwd_microstep: 490.88 | bwd_inner_microstep: 490.59 | bwd_allreduce_microstep: 0.26 | step_microstep: 0.21 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-14 21:37:18,965] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 301.99 | bwd_microstep: 492.23 | bwd_inner_microstep: 492.20 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.55 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1943 +[2025-05-14 21:37:20,110] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.01 | optimizer_gradients: 9.90 | optimizer_step: 19.59 +[2025-05-14 21:37:20,112] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 323.36 | bwd_microstep: 753.98 | bwd_inner_microstep: 533.61 | bwd_allreduce_microstep: 220.29 | step_microstep: 37.48 +[2025-05-14 21:37:20,112] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2567.45 | bwd: 4095.00 | bwd_inner: 3873.87 | bwd_allreduce: 220.73 | step: 47.51 + 6%|▌ | 116/1859 [10:30<3:03:29, 6.32s/it] {'loss': 6.7472, 'grad_norm': 30.727859497070312, 'learning_rate': 9.972700467870339e-11, 'epoch': 0.06} + 6%|▌ | 116/1859 [10:30<3:03:29, 6.32s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1927 +[2025-05-14 21:37:21,017] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 348.82 | bwd_microstep: 513.07 | bwd_inner_microstep: 512.91 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1887 +[2025-05-14 21:37:21,954] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 411.14 | bwd_microstep: 500.56 | bwd_inner_microstep: 500.40 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-14 21:37:22,819] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 324.71 | bwd_microstep: 517.57 | bwd_inner_microstep: 517.52 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.29 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 346 +[2025-05-14 21:37:23,058] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 83.09 | bwd_microstep: 125.03 | bwd_inner_microstep: 124.76 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-14 21:37:23,868] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 294.20 | bwd_microstep: 497.64 | bwd_inner_microstep: 497.59 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.46 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-14 21:37:24,682] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 281.38 | bwd_microstep: 496.56 | bwd_inner_microstep: 496.50 | bwd_allreduce_microstep: 0.02 | step_microstep: 2.37 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-14 21:37:25,545] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 335.82 | bwd_microstep: 494.69 | bwd_inner_microstep: 494.53 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-14 21:37:26,575] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.01 | optimizer_gradients: 3.35 | optimizer_step: 19.66 +[2025-05-14 21:37:26,577] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 376.83 | bwd_microstep: 605.61 | bwd_inner_microstep: 424.74 | bwd_allreduce_microstep: 180.80 | step_microstep: 32.29 +[2025-05-14 21:37:26,578] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2455.93 | bwd: 3750.77 | bwd_inner: 3569.11 | bwd_allreduce: 181.11 | step: 39.81 + 6%|▋ | 117/1859 [10:36<3:04:40, 6.36s/it] {'loss': 4.4263, 'grad_norm': 15.304198265075684, 'learning_rate': 9.971783764232516e-11, 'epoch': 0.06} + 6%|▋ | 117/1859 [10:36<3:04:40, 6.36s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1897 +[2025-05-14 21:37:27,404] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 297.61 | bwd_microstep: 490.47 | bwd_inner_microstep: 490.43 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 875 +[2025-05-14 21:37:27,839] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 182.51 | bwd_microstep: 219.93 | bwd_inner_microstep: 218.60 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.32 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-14 21:37:28,675] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 303.93 | bwd_microstep: 498.60 | bwd_inner_microstep: 498.55 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-14 21:37:29,541] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 341.15 | bwd_microstep: 492.43 | bwd_inner_microstep: 492.27 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-14 21:37:30,448] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 394.22 | bwd_microstep: 492.03 | bwd_inner_microstep: 491.63 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.23 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-14 21:37:31,248] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 299.51 | bwd_microstep: 480.77 | bwd_inner_microstep: 480.61 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-14 21:37:32,043] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 278.30 | bwd_microstep: 496.80 | bwd_inner_microstep: 496.76 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.55 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1483 +[2025-05-14 21:37:32,984] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.20 | optimizer_step: 18.37 +[2025-05-14 21:37:32,985] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 214.86 | bwd_microstep: 672.44 | bwd_inner_microstep: 392.25 | bwd_allreduce_microstep: 280.13 | step_microstep: 27.05 +[2025-05-14 21:37:32,985] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2312.05 | bwd: 3843.52 | bwd_inner: 3561.16 | bwd_allreduce: 281.43 | step: 37.15 + 6%|▋ | 118/1859 [10:43<3:04:56, 6.37s/it] {'loss': 4.4659, 'grad_norm': 24.643327713012695, 'learning_rate': 9.970851966036229e-11, 'epoch': 0.06} + 6%|▋ | 118/1859 [10:43<3:04:56, 6.37s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1900 +[2025-05-14 21:37:33,856] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 342.55 | bwd_microstep: 503.16 | bwd_inner_microstep: 503.13 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1887 +[2025-05-14 21:37:34,683] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 295.20 | bwd_microstep: 497.93 | bwd_inner_microstep: 497.89 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1902 +[2025-05-14 21:37:35,524] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 300.99 | bwd_microstep: 504.90 | bwd_inner_microstep: 504.85 | bwd_allreduce_microstep: 0.02 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-14 21:37:36,398] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 343.16 | bwd_microstep: 498.67 | bwd_inner_microstep: 498.53 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1899 +[2025-05-14 21:37:37,310] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 399.37 | bwd_microstep: 494.42 | bwd_inner_microstep: 494.38 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.39 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1894 +[2025-05-14 21:37:38,143] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 307.16 | bwd_microstep: 503.94 | bwd_inner_microstep: 503.90 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.53 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1370 +[2025-05-14 21:37:38,795] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 199.32 | bwd_microstep: 420.51 | bwd_inner_microstep: 420.37 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 836 +[2025-05-14 21:37:39,372] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.10 | optimizer_step: 25.98 +[2025-05-14 21:37:39,373] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 127.71 | bwd_microstep: 399.67 | bwd_inner_microstep: 284.62 | bwd_allreduce_microstep: 114.98 | step_microstep: 34.42 +[2025-05-14 21:37:39,374] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2315.43 | bwd: 3823.53 | bwd_inner: 3707.71 | bwd_allreduce: 115.16 | step: 44.60 + 6%|▋ | 119/1859 [10:49<3:04:59, 6.38s/it] {'loss': 2.9858, 'grad_norm': 8.0604887008667, 'learning_rate': 9.969905076110458e-11, 'epoch': 0.06} + 6%|▋ | 119/1859 [10:49<3:04:59, 6.38s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1950 +[2025-05-14 21:37:40,115] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 254.97 | bwd_microstep: 443.70 | bwd_inner_microstep: 443.66 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1905 +[2025-05-14 21:37:40,959] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 311.16 | bwd_microstep: 502.52 | bwd_inner_microstep: 502.48 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1897 +[2025-05-14 21:37:41,852] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 362.21 | bwd_microstep: 499.34 | bwd_inner_microstep: 499.20 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1894 +[2025-05-14 21:37:42,675] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 361.58 | bwd_microstep: 440.70 | bwd_inner_microstep: 440.55 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.10 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1109 +[2025-05-14 21:37:43,184] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 178.03 | bwd_microstep: 315.50 | bwd_inner_microstep: 315.37 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-14 21:37:44,006] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 302.77 | bwd_microstep: 500.14 | bwd_inner_microstep: 499.96 | bwd_allreduce_microstep: 0.08 | step_microstep: 0.14 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-14 21:37:44,928] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 408.25 | bwd_microstep: 495.67 | bwd_inner_microstep: 495.52 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1474 +[2025-05-14 21:37:45,861] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.01 | optimizer_gradients: 4.58 | optimizer_step: 21.56 +[2025-05-14 21:37:45,863] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 229.01 | bwd_microstep: 653.28 | bwd_inner_microstep: 389.13 | bwd_allreduce_microstep: 264.09 | step_microstep: 33.44 +[2025-05-14 21:37:45,863] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2407.90 | bwd: 3850.92 | bwd_inner: 3585.97 | bwd_allreduce: 264.41 | step: 38.69 + 6%|▋ | 120/1859 [10:56<3:05:51, 6.41s/it] {'loss': 2.2254, 'grad_norm': 4.308813095092773, 'learning_rate': 9.968943097330005e-11, 'epoch': 0.06} + 6%|▋ | 120/1859 [10:56<3:05:51, 6.41s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1899 +[2025-05-14 21:37:46,747] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 343.43 | bwd_microstep: 497.67 | bwd_inner_microstep: 497.53 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-14 21:37:47,655] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 398.82 | bwd_microstep: 491.45 | bwd_inner_microstep: 491.21 | bwd_allreduce_microstep: 0.21 | step_microstep: 0.23 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-14 21:37:48,442] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 284.10 | bwd_microstep: 484.14 | bwd_inner_microstep: 484.11 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-14 21:37:49,256] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 294.12 | bwd_microstep: 492.00 | bwd_inner_microstep: 491.85 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-14 21:37:50,156] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 388.33 | bwd_microstep: 490.24 | bwd_inner_microstep: 490.21 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 330 +[2025-05-14 21:37:50,402] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 78.67 | bwd_microstep: 148.24 | bwd_inner_microstep: 148.19 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.32 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-14 21:37:51,225] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 301.58 | bwd_microstep: 487.38 | bwd_inner_microstep: 487.33 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-14 21:37:52,392] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.28 | optimizer_step: 25.04 +[2025-05-14 21:37:52,393] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 335.71 | bwd_microstep: 765.63 | bwd_inner_microstep: 496.67 | bwd_allreduce_microstep: 268.87 | step_microstep: 33.85 +[2025-05-14 21:37:52,393] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2424.48 | bwd: 3856.77 | bwd_inner: 3587.16 | bwd_allreduce: 269.23 | step: 41.41 + 7%|▋ | 121/1859 [11:02<3:06:44, 6.45s/it] {'loss': 7.1318, 'grad_norm': 25.92103385925293, 'learning_rate': 9.96796603261548e-11, 'epoch': 0.07} + 7%|▋ | 121/1859 [11:02<3:06:44, 6.45s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1922 +[2025-05-14 21:37:53,334] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 406.26 | bwd_microstep: 510.71 | bwd_inner_microstep: 510.57 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1896 +[2025-05-14 21:37:54,214] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 353.70 | bwd_microstep: 502.64 | bwd_inner_microstep: 502.61 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.54 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-14 21:37:55,039] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 291.76 | bwd_microstep: 499.58 | bwd_inner_microstep: 499.53 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-14 21:37:55,867] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 298.50 | bwd_microstep: 495.61 | bwd_inner_microstep: 495.56 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.37 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-14 21:37:56,597] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 331.44 | bwd_microstep: 363.50 | bwd_inner_microstep: 363.46 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-14 21:37:57,424] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 295.40 | bwd_microstep: 497.69 | bwd_inner_microstep: 497.67 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.32 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-14 21:37:58,289] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 344.64 | bwd_microstep: 488.60 | bwd_inner_microstep: 488.46 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-14 21:37:59,320] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.07 | optimizer_gradients: 2.24 | optimizer_step: 18.33 +[2025-05-14 21:37:59,321] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 389.12 | bwd_microstep: 596.89 | bwd_inner_microstep: 493.95 | bwd_allreduce_microstep: 102.90 | step_microstep: 27.91 +[2025-05-14 21:37:59,321] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2710.78 | bwd: 3955.25 | bwd_inner: 3851.84 | bwd_allreduce: 103.07 | step: 40.07 + 7%|▋ | 122/1859 [11:09<3:10:49, 6.59s/it] {'loss': 6.6627, 'grad_norm': 34.20577621459961, 'learning_rate': 9.966973884933297e-11, 'epoch': 0.07} + 7%|▋ | 122/1859 [11:09<3:10:49, 6.59s/it]dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 883 +[2025-05-14 21:37:59,785] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 209.89 | bwd_microstep: 229.15 | bwd_inner_microstep: 229.02 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1889 +[2025-05-14 21:38:00,606] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 302.56 | bwd_microstep: 498.85 | bwd_inner_microstep: 498.78 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-14 21:38:01,490] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 356.68 | bwd_microstep: 495.62 | bwd_inner_microstep: 495.49 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.10 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 336 +[2025-05-14 21:38:01,741] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 84.98 | bwd_microstep: 148.74 | bwd_inner_microstep: 148.70 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.37 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 840 +[2025-05-14 21:38:02,134] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 144.62 | bwd_microstep: 215.17 | bwd_inner_microstep: 215.13 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-14 21:38:02,945] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 279.93 | bwd_microstep: 498.99 | bwd_inner_microstep: 498.84 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.11 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 322 +[2025-05-14 21:38:03,205] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 99.38 | bwd_microstep: 142.80 | bwd_inner_microstep: 142.76 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.58 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 835 +[2025-05-14 21:38:03,817] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.14 | optimizer_step: 20.61 +[2025-05-14 21:38:03,819] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 129.02 | bwd_microstep: 425.10 | bwd_inner_microstep: 265.11 | bwd_allreduce_microstep: 159.95 | step_microstep: 29.83 +[2025-05-14 21:38:03,820] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 1607.01 | bwd: 2654.48 | bwd_inner: 2493.90 | bwd_allreduce: 160.18 | step: 39.82 + 7%|▋ | 123/1859 [11:14<2:52:34, 5.96s/it] {'loss': 6.9748, 'grad_norm': 23.997770309448242, 'learning_rate': 9.965966657295657e-11, 'epoch': 0.07} + 7%|▋ | 123/1859 [11:14<2:52:34, 5.96s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1939 +[2025-05-14 21:38:04,628] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 355.49 | bwd_microstep: 407.45 | bwd_inner_microstep: 407.43 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.31 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1887 +[2025-05-14 21:38:05,453] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 289.17 | bwd_microstep: 501.65 | bwd_inner_microstep: 501.63 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 342 +[2025-05-14 21:38:05,707] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 102.10 | bwd_microstep: 122.46 | bwd_inner_microstep: 122.32 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-14 21:38:06,558] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 325.90 | bwd_microstep: 503.06 | bwd_inner_microstep: 503.01 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.32 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-14 21:38:07,374] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 289.45 | bwd_microstep: 492.53 | bwd_inner_microstep: 492.49 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-14 21:38:08,199] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 311.17 | bwd_microstep: 489.00 | bwd_inner_microstep: 488.85 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-14 21:38:09,104] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 394.68 | bwd_microstep: 492.27 | bwd_inner_microstep: 491.92 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.22 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-14 21:38:10,138] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.07 | optimizer_gradients: 1.98 | optimizer_step: 17.77 +[2025-05-14 21:38:10,139] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 314.39 | bwd_microstep: 674.12 | bwd_inner_microstep: 502.43 | bwd_allreduce_microstep: 171.63 | step_microstep: 26.42 +[2025-05-14 21:38:10,140] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2382.31 | bwd: 3682.56 | bwd_inner: 3510.14 | bwd_allreduce: 171.79 | step: 36.19 + 7%|▋ | 124/1859 [11:20<2:55:32, 6.07s/it] {'loss': 5.9442, 'grad_norm': 39.009620666503906, 'learning_rate': 9.964944352760552e-11, 'epoch': 0.07} + 7%|▋ | 124/1859 [11:20<2:55:32, 6.07s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1915 +[2025-05-14 21:38:11,070] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 405.42 | bwd_microstep: 497.97 | bwd_inner_microstep: 497.83 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-14 21:38:11,946] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 366.87 | bwd_microstep: 486.51 | bwd_inner_microstep: 486.46 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.54 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 845 +[2025-05-14 21:38:12,364] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 107.14 | bwd_microstep: 278.60 | bwd_inner_microstep: 278.56 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.57 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1349 +[2025-05-14 21:38:12,993] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 175.16 | bwd_microstep: 420.86 | bwd_inner_microstep: 420.72 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.10 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 329 +[2025-05-14 21:38:13,244] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 86.79 | bwd_microstep: 146.37 | bwd_inner_microstep: 146.32 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.28 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 835 +[2025-05-14 21:38:13,555] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 155.40 | bwd_microstep: 127.92 | bwd_inner_microstep: 127.77 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 836 +[2025-05-14 21:38:13,998] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 152.94 | bwd_microstep: 274.04 | bwd_inner_microstep: 274.00 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.61 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1894 +[2025-05-14 21:38:15,039] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.01 | optimizer_gradients: 3.90 | optimizer_step: 22.17 +[2025-05-14 21:38:15,041] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 316.48 | bwd_microstep: 675.72 | bwd_inner_microstep: 508.64 | bwd_allreduce_microstep: 167.02 | step_microstep: 32.10 +[2025-05-14 21:38:15,042] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 1766.16 | bwd: 2908.02 | bwd_inner: 2740.35 | bwd_allreduce: 167.24 | step: 39.99 + 7%|▋ | 125/1859 [11:25<2:45:19, 5.72s/it] {'loss': 5.9082, 'grad_norm': 21.882688522338867, 'learning_rate': 9.963906974431741e-11, 'epoch': 0.07} + 7%|▋ | 125/1859 [11:25<2:45:19, 5.72s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1892 +[2025-05-14 21:38:15,921] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 341.71 | bwd_microstep: 494.51 | bwd_inner_microstep: 494.37 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 346 +[2025-05-14 21:38:16,171] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 100.95 | bwd_microstep: 132.30 | bwd_inner_microstep: 132.24 | bwd_allreduce_microstep: 0.02 | step_microstep: 2.35 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1108 +[2025-05-14 21:38:16,699] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 159.71 | bwd_microstep: 336.39 | bwd_inner_microstep: 336.35 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 331 +[2025-05-14 21:38:16,954] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 71.53 | bwd_microstep: 156.90 | bwd_inner_microstep: 156.86 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-14 21:38:17,782] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 309.77 | bwd_microstep: 487.71 | bwd_inner_microstep: 487.67 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-14 21:38:18,659] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 350.96 | bwd_microstep: 494.03 | bwd_inner_microstep: 493.87 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-14 21:38:19,557] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 384.51 | bwd_microstep: 493.72 | bwd_inner_microstep: 493.67 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-14 21:38:20,652] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 3.72 | optimizer_step: 19.13 +[2025-05-14 21:38:20,653] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 293.81 | bwd_microstep: 749.18 | bwd_inner_microstep: 493.60 | bwd_allreduce_microstep: 255.55 | step_microstep: 30.38 +[2025-05-14 21:38:20,654] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2012.91 | bwd: 3344.77 | bwd_inner: 3088.69 | bwd_allreduce: 255.73 | step: 40.21 + 7%|▋ | 126/1859 [11:30<2:44:17, 5.69s/it] {'loss': 5.6729, 'grad_norm': 17.247671127319336, 'learning_rate': 9.962854525458753e-11, 'epoch': 0.07} + 7%|▋ | 126/1859 [11:30<2:44:17, 5.69s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 352 +[2025-05-14 21:38:20,932] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 84.08 | bwd_microstep: 152.62 | bwd_inner_microstep: 152.38 | bwd_allreduce_microstep: 0.22 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-14 21:38:21,789] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 334.52 | bwd_microstep: 493.71 | bwd_inner_microstep: 493.68 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.52 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 847 +[2025-05-14 21:38:22,083] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 129.76 | bwd_microstep: 133.47 | bwd_inner_microstep: 133.23 | bwd_allreduce_microstep: 0.09 | step_microstep: 0.09 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 331 +[2025-05-14 21:38:22,332] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 80.67 | bwd_microstep: 153.56 | bwd_inner_microstep: 153.53 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.26 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-14 21:38:23,168] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 305.29 | bwd_microstep: 497.94 | bwd_inner_microstep: 497.90 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-14 21:38:24,041] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 342.81 | bwd_microstep: 495.90 | bwd_inner_microstep: 495.57 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-14 21:38:24,954] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 405.08 | bwd_microstep: 489.20 | bwd_inner_microstep: 488.86 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.13 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 834 +[2025-05-14 21:38:25,520] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.64 | optimizer_step: 21.99 +[2025-05-14 21:38:25,523] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.78 | bwd_microstep: 425.66 | bwd_inner_microstep: 282.49 | bwd_allreduce_microstep: 143.11 | step_microstep: 31.70 +[2025-05-14 21:38:25,523] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 1777.94 | bwd: 2842.14 | bwd_inner: 2697.82 | bwd_allreduce: 143.70 | step: 39.27 + 7%|▋ | 127/1859 [11:35<2:37:05, 5.44s/it] {'loss': 6.3811, 'grad_norm': 31.243478775024414, 'learning_rate': 9.961787009036872e-11, 'epoch': 0.07} + 7%|▋ | 127/1859 [11:35<2:37:05, 5.44s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1895 +[2025-05-14 21:38:26,420] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 348.51 | bwd_microstep: 504.66 | bwd_inner_microstep: 504.51 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1895 +[2025-05-14 21:38:27,307] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 371.81 | bwd_microstep: 494.92 | bwd_inner_microstep: 494.88 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.33 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-14 21:38:28,140] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 296.78 | bwd_microstep: 501.74 | bwd_inner_microstep: 501.71 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.59 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-14 21:38:28,988] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 320.05 | bwd_microstep: 494.27 | bwd_inner_microstep: 494.23 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.37 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1099 +[2025-05-14 21:38:29,523] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 238.54 | bwd_microstep: 263.29 | bwd_inner_microstep: 263.26 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.61 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-14 21:38:30,310] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 301.38 | bwd_microstep: 453.41 | bwd_inner_microstep: 453.27 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.08 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 325 +[2025-05-14 21:38:30,556] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 72.39 | bwd_microstep: 158.90 | bwd_inner_microstep: 158.85 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.33 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-14 21:38:31,691] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 5.93 | optimizer_step: 21.02 +[2025-05-14 21:38:31,693] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 295.55 | bwd_microstep: 775.29 | bwd_inner_microstep: 491.11 | bwd_allreduce_microstep: 284.07 | step_microstep: 35.75 +[2025-05-14 21:38:31,694] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2244.97 | bwd: 3646.50 | bwd_inner: 3361.87 | bwd_allreduce: 284.21 | step: 48.16 + 7%|▋ | 128/1859 [11:41<2:43:18, 5.66s/it] {'loss': 6.0198, 'grad_norm': 28.645858764648438, 'learning_rate': 9.960704428407124e-11, 'epoch': 0.07} + 7%|▋ | 128/1859 [11:41<2:43:18, 5.66s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 370 +[2025-05-14 21:38:31,988] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 111.44 | bwd_microstep: 142.31 | bwd_inner_microstep: 142.04 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.25 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1909 +[2025-05-14 21:38:32,804] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 296.44 | bwd_microstep: 498.47 | bwd_inner_microstep: 498.44 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.49 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-14 21:38:33,630] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 300.10 | bwd_microstep: 491.51 | bwd_inner_microstep: 491.49 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-14 21:38:34,478] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 323.74 | bwd_microstep: 495.41 | bwd_inner_microstep: 495.26 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-14 21:38:35,378] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 386.70 | bwd_microstep: 493.28 | bwd_inner_microstep: 493.23 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-14 21:38:36,199] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 299.40 | bwd_microstep: 496.76 | bwd_inner_microstep: 496.73 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.50 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-14 21:38:37,030] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 302.88 | bwd_microstep: 492.10 | bwd_inner_microstep: 492.04 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.37 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1905 +[2025-05-14 21:38:38,198] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.12 | optimizer_step: 17.91 +[2025-05-14 21:38:38,199] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 326.03 | bwd_microstep: 784.44 | bwd_inner_microstep: 498.74 | bwd_allreduce_microstep: 285.60 | step_microstep: 26.51 +[2025-05-14 21:38:38,200] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2346.70 | bwd: 3894.28 | bwd_inner: 3608.02 | bwd_allreduce: 285.94 | step: 38.94 + 7%|▋ | 129/1859 [11:48<2:50:30, 5.91s/it] {'loss': 4.9524, 'grad_norm': 20.042753219604492, 'learning_rate': 9.959606786856272e-11, 'epoch': 0.07} + 7%|▋ | 129/1859 [11:48<2:50:30, 5.91s/it]dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1386 +[2025-05-14 21:38:38,871] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 307.75 | bwd_microstep: 340.09 | bwd_inner_microstep: 339.94 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1891 +[2025-05-14 21:38:39,655] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 266.47 | bwd_microstep: 499.41 | bwd_inner_microstep: 499.38 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.29 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1887 +[2025-05-14 21:38:40,497] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 309.40 | bwd_microstep: 498.54 | bwd_inner_microstep: 498.50 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.49 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-14 21:38:41,310] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 284.57 | bwd_microstep: 496.22 | bwd_inner_microstep: 496.17 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.56 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-14 21:38:42,166] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 331.37 | bwd_microstep: 491.73 | bwd_inner_microstep: 491.59 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-14 21:38:43,027] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 358.20 | bwd_microstep: 483.18 | bwd_inner_microstep: 483.14 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-14 21:38:43,868] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 294.18 | bwd_microstep: 512.38 | bwd_inner_microstep: 512.33 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.32 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1098 +[2025-05-14 21:38:44,586] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.29 | optimizer_step: 20.48 +[2025-05-14 21:38:44,589] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.23 | bwd_microstep: 470.37 | bwd_inner_microstep: 334.55 | bwd_allreduce_microstep: 135.75 | step_microstep: 29.46 +[2025-05-14 21:38:44,589] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2341.11 | bwd: 3791.94 | bwd_inner: 3655.66 | bwd_allreduce: 135.93 | step: 41.65 + 7%|▋ | 130/1859 [11:54<2:54:32, 6.06s/it] {'loss': 5.407, 'grad_norm': 16.70172882080078, 'learning_rate': 9.958494087716806e-11, 'epoch': 0.07} + 7%|▋ | 130/1859 [11:54<2:54:32, 6.06s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1973 +[2025-05-14 21:38:45,508] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 357.80 | bwd_microstep: 515.87 | bwd_inner_microstep: 515.83 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 868 +[2025-05-14 21:38:45,942] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 214.36 | bwd_microstep: 187.91 | bwd_inner_microstep: 187.74 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1908 +[2025-05-14 21:38:46,846] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 368.96 | bwd_microstep: 499.12 | bwd_inner_microstep: 498.97 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-14 21:38:47,551] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 284.81 | bwd_microstep: 399.89 | bwd_inner_microstep: 399.75 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-14 21:38:48,445] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 373.89 | bwd_microstep: 491.24 | bwd_inner_microstep: 491.09 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-14 21:38:49,326] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 354.70 | bwd_microstep: 502.26 | bwd_inner_microstep: 502.22 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.29 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-14 21:38:50,151] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 292.89 | bwd_microstep: 497.75 | bwd_inner_microstep: 497.71 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-14 21:38:51,276] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 4.52 | optimizer_step: 22.62 +[2025-05-14 21:38:51,278] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 308.01 | bwd_microstep: 749.98 | bwd_inner_microstep: 518.83 | bwd_allreduce_microstep: 231.09 | step_microstep: 34.06 +[2025-05-14 21:38:51,278] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2555.38 | bwd: 3844.10 | bwd_inner: 3612.23 | bwd_allreduce: 231.38 | step: 41.48 + 7%|▋ | 131/1859 [12:01<2:59:54, 6.25s/it] {'loss': 3.1261, 'grad_norm': 17.375246047973633, 'learning_rate': 9.957366334366927e-11, 'epoch': 0.07} + 7%|▋ | 131/1859 [12:01<2:59:54, 6.25s/it]dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1154 +[2025-05-14 21:38:51,844] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 264.10 | bwd_microstep: 259.21 | bwd_inner_microstep: 259.16 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.37 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 382 +[2025-05-14 21:38:52,137] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 109.16 | bwd_microstep: 151.90 | bwd_inner_microstep: 151.85 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1378 +[2025-05-14 21:38:52,831] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 250.94 | bwd_microstep: 406.70 | bwd_inner_microstep: 406.67 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.55 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1887 +[2025-05-14 21:38:53,644] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 293.79 | bwd_microstep: 498.28 | bwd_inner_microstep: 498.24 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.32 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-14 21:38:54,475] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 301.26 | bwd_microstep: 493.22 | bwd_inner_microstep: 493.18 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-14 21:38:55,223] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 324.69 | bwd_microstep: 390.23 | bwd_inner_microstep: 390.00 | bwd_allreduce_microstep: 0.08 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-14 21:38:56,043] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 306.23 | bwd_microstep: 499.02 | bwd_inner_microstep: 498.96 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-14 21:38:57,076] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.01 | optimizer_gradients: 4.22 | optimizer_step: 19.25 +[2025-05-14 21:38:57,078] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 314.95 | bwd_microstep: 668.48 | bwd_inner_microstep: 494.24 | bwd_allreduce_microstep: 174.16 | step_microstep: 30.83 +[2025-05-14 21:38:57,079] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2165.08 | bwd: 3367.06 | bwd_inner: 3192.36 | bwd_allreduce: 174.32 | step: 42.92 + 7%|▋ | 132/1859 [12:07<2:55:56, 6.11s/it] {'loss': 4.2527, 'grad_norm': 17.20660400390625, 'learning_rate': 9.95622353023055e-11, 'epoch': 0.07} + 7%|▋ | 132/1859 [12:07<2:55:56, 6.11s/it]dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1127 +[2025-05-14 21:38:57,636] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 258.84 | bwd_microstep: 255.26 | bwd_inner_microstep: 255.22 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.53 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1891 +[2025-05-14 21:38:58,447] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 289.42 | bwd_microstep: 492.77 | bwd_inner_microstep: 492.40 | bwd_allreduce_microstep: 0.14 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-14 21:38:59,297] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 327.75 | bwd_microstep: 495.39 | bwd_inner_microstep: 495.03 | bwd_allreduce_microstep: 0.14 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-14 21:39:00,208] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 397.20 | bwd_microstep: 494.67 | bwd_inner_microstep: 494.24 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.26 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-14 21:39:01,020] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 298.07 | bwd_microstep: 491.83 | bwd_inner_microstep: 491.78 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.33 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-14 21:39:01,843] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 292.72 | bwd_microstep: 496.71 | bwd_inner_microstep: 496.67 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-14 21:39:02,685] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 328.06 | bwd_microstep: 478.71 | bwd_inner_microstep: 478.67 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1348 +[2025-05-14 21:39:03,485] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.22 | optimizer_step: 18.85 +[2025-05-14 21:39:03,486] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 225.57 | bwd_microstep: 514.83 | bwd_inner_microstep: 422.23 | bwd_allreduce_microstep: 92.54 | step_microstep: 28.52 +[2025-05-14 21:39:03,487] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2417.60 | bwd: 3720.22 | bwd_inner: 3626.37 | bwd_allreduce: 92.85 | step: 38.55 + 7%|▋ | 133/1859 [12:13<2:58:23, 6.20s/it] {'loss': 6.294, 'grad_norm': 25.297779083251953, 'learning_rate': 9.955065678777277e-11, 'epoch': 0.07} + 7%|▋ | 133/1859 [12:13<2:58:23, 6.20s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1887 +[2025-05-14 21:39:04,351] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 321.55 | bwd_microstep: 497.56 | bwd_inner_microstep: 497.23 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.22 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1893 +[2025-05-14 21:39:05,251] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 378.88 | bwd_microstep: 493.25 | bwd_inner_microstep: 493.10 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1357 +[2025-05-14 21:39:05,902] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 264.53 | bwd_microstep: 367.85 | bwd_inner_microstep: 367.79 | bwd_allreduce_microstep: 0.02 | step_microstep: 2.33 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-14 21:39:06,631] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 200.59 | bwd_microstep: 496.02 | bwd_inner_microstep: 495.64 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-14 21:39:07,545] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 400.73 | bwd_microstep: 492.65 | bwd_inner_microstep: 492.24 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.49 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 838 +[2025-05-14 21:39:07,974] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 125.60 | bwd_microstep: 284.95 | bwd_inner_microstep: 284.89 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-14 21:39:08,806] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 309.57 | bwd_microstep: 498.58 | bwd_inner_microstep: 498.55 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1895 +[2025-05-14 21:39:09,896] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.01 | optimizer_gradients: 2.09 | optimizer_step: 18.41 +[2025-05-14 21:39:09,898] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 351.48 | bwd_microstep: 693.63 | bwd_inner_microstep: 447.38 | bwd_allreduce_microstep: 246.19 | step_microstep: 26.96 +[2025-05-14 21:39:09,899] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2352.89 | bwd: 3824.58 | bwd_inner: 3576.97 | bwd_allreduce: 246.56 | step: 32.48 + 7%|▋ | 134/1859 [12:20<3:00:06, 6.26s/it] {'loss': 6.3534, 'grad_norm': 38.74550247192383, 'learning_rate': 9.953892783522396e-11, 'epoch': 0.07} + 7%|▋ | 134/1859 [12:20<3:00:06, 6.26s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1903 +[2025-05-14 21:39:10,786] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 350.23 | bwd_microstep: 493.81 | bwd_inner_microstep: 493.52 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1902 +[2025-05-14 21:39:11,489] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 384.38 | bwd_microstep: 300.91 | bwd_inner_microstep: 300.61 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1896 +[2025-05-14 21:39:12,288] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 344.13 | bwd_microstep: 435.59 | bwd_inner_microstep: 435.44 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-14 21:39:12,775] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 194.67 | bwd_microstep: 276.65 | bwd_inner_microstep: 276.35 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1365 +[2025-05-14 21:39:13,273] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 151.12 | bwd_microstep: 328.25 | bwd_inner_microstep: 328.22 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.55 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-14 21:39:14,162] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 362.11 | bwd_microstep: 492.80 | bwd_inner_microstep: 492.65 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 833 +[2025-05-14 21:39:14,601] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 147.76 | bwd_microstep: 274.27 | bwd_inner_microstep: 274.00 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.21 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-14 21:39:15,630] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 6.17 | optimizer_step: 19.39 +[2025-05-14 21:39:15,632] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 291.48 | bwd_microstep: 683.96 | bwd_inner_microstep: 485.46 | bwd_allreduce_microstep: 198.44 | step_microstep: 33.60 +[2025-05-14 21:39:15,633] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2225.80 | bwd: 3286.31 | bwd_inner: 3086.48 | bwd_allreduce: 198.93 | step: 36.84 + 7%|▋ | 135/1859 [12:25<2:55:25, 6.11s/it] {'loss': 5.2708, 'grad_norm': 25.575010299682617, 'learning_rate': 9.952704848026872e-11, 'epoch': 0.07} + 7%|▋ | 135/1859 [12:25<2:55:25, 6.11s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-14 21:39:16,518] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 348.25 | bwd_microstep: 494.65 | bwd_inner_microstep: 494.49 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-14 21:39:17,392] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 384.59 | bwd_microstep: 470.63 | bwd_inner_microstep: 470.48 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 326 +[2025-05-14 21:39:17,639] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 82.26 | bwd_microstep: 147.20 | bwd_inner_microstep: 147.16 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-14 21:39:18,476] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 282.52 | bwd_microstep: 520.14 | bwd_inner_microstep: 520.10 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-14 21:39:19,312] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 306.70 | bwd_microstep: 494.63 | bwd_inner_microstep: 494.47 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.09 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1086 +[2025-05-14 21:39:19,818] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 257.98 | bwd_microstep: 231.25 | bwd_inner_microstep: 231.05 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.09 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 320 +[2025-05-14 21:39:20,070] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 89.87 | bwd_microstep: 132.89 | bwd_inner_microstep: 132.87 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.28 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 827 +[2025-05-14 21:39:20,505] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.14 | optimizer_step: 18.94 +[2025-05-14 21:39:20,506] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 102.01 | bwd_microstep: 285.63 | bwd_inner_microstep: 191.62 | bwd_allreduce_microstep: 93.95 | step_microstep: 30.65 +[2025-05-14 21:39:20,507] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 1854.12 | bwd: 2777.06 | bwd_inner: 2682.42 | bwd_allreduce: 94.20 | step: 38.26 + 7%|▋ | 136/1859 [12:30<2:44:41, 5.74s/it] {'loss': 8.0296, 'grad_norm': 54.428306579589844, 'learning_rate': 9.951501875897329e-11, 'epoch': 0.07} + 7%|▋ | 136/1859 [12:30<2:44:41, 5.74s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 365 +[2025-05-14 21:39:20,797] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 112.10 | bwd_microstep: 137.45 | bwd_inner_microstep: 137.41 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1888 +[2025-05-14 21:39:21,679] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 352.31 | bwd_microstep: 494.80 | bwd_inner_microstep: 494.59 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-14 21:39:22,541] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 354.40 | bwd_microstep: 490.75 | bwd_inner_microstep: 490.72 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.24 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-14 21:39:23,368] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 326.46 | bwd_microstep: 478.14 | bwd_inner_microstep: 478.11 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.51 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-14 21:39:24,207] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 317.85 | bwd_microstep: 486.48 | bwd_inner_microstep: 486.44 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-14 21:39:25,053] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 333.39 | bwd_microstep: 478.83 | bwd_inner_microstep: 478.79 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-14 21:39:25,886] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 300.53 | bwd_microstep: 496.31 | bwd_inner_microstep: 496.27 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.53 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1916 +[2025-05-14 21:39:27,050] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.42 | optimizer_step: 21.41 +[2025-05-14 21:39:27,051] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 316.10 | bwd_microstep: 784.08 | bwd_inner_microstep: 501.73 | bwd_allreduce_microstep: 282.30 | step_microstep: 30.22 +[2025-05-14 21:39:27,051] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2413.09 | bwd: 3846.86 | bwd_inner: 3564.12 | bwd_allreduce: 282.42 | step: 42.65 + 7%|▋ | 137/1859 [12:37<2:51:33, 5.98s/it] {'loss': 3.8704, 'grad_norm': 16.965641021728516, 'learning_rate': 9.950283870786043e-11, 'epoch': 0.07} + 7%|▋ | 137/1859 [12:37<2:51:33, 5.98s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1897 +[2025-05-14 21:39:27,962] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 369.85 | bwd_microstep: 497.57 | bwd_inner_microstep: 497.25 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.10 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 866 +[2025-05-14 21:39:28,422] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 162.89 | bwd_microstep: 279.43 | bwd_inner_microstep: 279.11 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-14 21:39:29,107] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.16 | bwd_microstep: 472.97 | bwd_inner_microstep: 472.93 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.95 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-14 21:39:29,917] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 294.80 | bwd_microstep: 494.03 | bwd_inner_microstep: 493.97 | bwd_allreduce_microstep: 0.02 | step_microstep: 2.28 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-14 21:39:30,722] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 281.19 | bwd_microstep: 489.10 | bwd_inner_microstep: 489.06 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.37 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-14 21:39:31,595] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 347.11 | bwd_microstep: 494.01 | bwd_inner_microstep: 493.72 | bwd_allreduce_microstep: 0.14 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-14 21:39:32,408] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 301.69 | bwd_microstep: 494.72 | bwd_inner_microstep: 494.56 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 838 +[2025-05-14 21:39:33,164] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.47 | optimizer_step: 20.63 +[2025-05-14 21:39:33,164] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 184.50 | bwd_microstep: 521.75 | bwd_inner_microstep: 250.44 | bwd_allreduce_microstep: 271.16 | step_microstep: 29.43 +[2025-05-14 21:39:33,165] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2132.12 | bwd: 3743.64 | bwd_inner: 3471.35 | bwd_allreduce: 271.58 | step: 35.44 + 7%|▋ | 138/1859 [12:43<2:52:37, 6.02s/it] {'loss': 3.8739, 'grad_norm': 31.230335235595703, 'learning_rate': 9.949050836390935e-11, 'epoch': 0.07} + 7%|▋ | 138/1859 [12:43<2:52:37, 6.02s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1897 +[2025-05-14 21:39:34,044] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 348.92 | bwd_microstep: 501.60 | bwd_inner_microstep: 501.56 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-14 21:39:34,872] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 298.44 | bwd_microstep: 491.36 | bwd_inner_microstep: 491.31 | bwd_allreduce_microstep: 0.02 | step_microstep: 2.37 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-14 21:39:35,737] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 317.20 | bwd_microstep: 511.28 | bwd_inner_microstep: 511.23 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-14 21:39:36,562] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 301.73 | bwd_microstep: 489.46 | bwd_inner_microstep: 489.43 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 329 +[2025-05-14 21:39:36,837] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 106.78 | bwd_microstep: 131.94 | bwd_inner_microstep: 131.77 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-14 21:39:37,598] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 249.31 | bwd_microstep: 491.60 | bwd_inner_microstep: 491.56 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.49 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 837 +[2025-05-14 21:39:38,032] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 207.20 | bwd_microstep: 196.80 | bwd_inner_microstep: 196.76 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-14 21:39:39,172] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 4.16 | optimizer_step: 20.76 +[2025-05-14 21:39:39,174] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 309.30 | bwd_microstep: 775.34 | bwd_inner_microstep: 505.70 | bwd_allreduce_microstep: 269.56 | step_microstep: 33.15 +[2025-05-14 21:39:39,174] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2138.83 | bwd: 3589.40 | bwd_inner: 3319.35 | bwd_allreduce: 269.70 | step: 47.49 + 7%|▋ | 139/1859 [12:49<2:52:28, 6.02s/it] {'loss': 4.5897, 'grad_norm': 22.408205032348633, 'learning_rate': 9.94780277645555e-11, 'epoch': 0.07} + 7%|▋ | 139/1859 [12:49<2:52:28, 6.02s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1917 +[2025-05-14 21:39:40,067] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 350.95 | bwd_microstep: 498.17 | bwd_inner_microstep: 497.94 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1889 +[2025-05-14 21:39:40,977] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 397.01 | bwd_microstep: 492.45 | bwd_inner_microstep: 492.20 | bwd_allreduce_microstep: 0.23 | step_microstep: 0.40 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 857 +[2025-05-14 21:39:41,431] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 133.75 | bwd_microstep: 299.49 | bwd_inner_microstep: 299.44 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1356 +[2025-05-14 21:39:42,024] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 199.60 | bwd_microstep: 371.95 | bwd_inner_microstep: 371.74 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.12 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 837 +[2025-05-14 21:39:42,476] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 191.64 | bwd_microstep: 240.74 | bwd_inner_microstep: 240.41 | bwd_allreduce_microstep: 0.14 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-14 21:39:43,358] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 374.70 | bwd_microstep: 482.78 | bwd_inner_microstep: 482.75 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-14 21:39:44,187] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 288.85 | bwd_microstep: 507.27 | bwd_inner_microstep: 507.02 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.40 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-14 21:39:45,182] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 1.87 | optimizer_step: 13.42 +[2025-05-14 21:39:45,182] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 315.91 | bwd_microstep: 637.73 | bwd_inner_microstep: 488.33 | bwd_allreduce_microstep: 149.34 | step_microstep: 20.03 +[2025-05-14 21:39:45,183] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2252.33 | bwd: 3530.65 | bwd_inner: 3380.02 | bwd_allreduce: 150.07 | step: 25.85 + 8%|▊ | 140/1859 [12:55<2:52:15, 6.01s/it] {'loss': 5.6953, 'grad_norm': 21.07536506652832, 'learning_rate': 9.946539694769056e-11, 'epoch': 0.08} + 8%|▊ | 140/1859 [12:55<2:52:15, 6.01s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1902 +[2025-05-14 21:39:45,782] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 192.18 | bwd_microstep: 384.97 | bwd_inner_microstep: 384.94 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1883 +[2025-05-14 21:39:46,591] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 285.94 | bwd_microstep: 485.95 | bwd_inner_microstep: 485.89 | bwd_allreduce_microstep: 0.02 | step_microstep: 2.35 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 331 +[2025-05-14 21:39:46,867] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 103.22 | bwd_microstep: 142.74 | bwd_inner_microstep: 142.31 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.22 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 839 +[2025-05-14 21:39:47,266] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 100.43 | bwd_microstep: 276.38 | bwd_inner_microstep: 276.32 | bwd_allreduce_microstep: 0.02 | step_microstep: 2.40 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-14 21:39:48,085] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 291.96 | bwd_microstep: 493.41 | bwd_inner_microstep: 493.34 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.19 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 838 +[2025-05-14 21:39:48,487] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.45 | bwd_microstep: 186.17 | bwd_inner_microstep: 186.00 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.24 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-14 21:39:49,315] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 302.32 | bwd_microstep: 495.97 | bwd_inner_microstep: 495.92 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.32 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-14 21:39:50,482] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.18 | optimizer_step: 18.27 +[2025-05-14 21:39:50,483] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 325.06 | bwd_microstep: 783.76 | bwd_inner_microstep: 496.26 | bwd_allreduce_microstep: 287.32 | step_microstep: 27.45 +[2025-05-14 21:39:50,484] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 1791.53 | bwd: 3249.40 | bwd_inner: 2961.12 | bwd_allreduce: 287.44 | step: 37.53 + 8%|▊ | 141/1859 [13:00<2:46:05, 5.80s/it] {'loss': 5.7522, 'grad_norm': 28.253515243530273, 'learning_rate': 9.945261595166227e-11, 'epoch': 0.08} + 8%|▊ | 141/1859 [13:00<2:46:05, 5.80s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1919 +[2025-05-14 21:39:51,196] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 404.79 | bwd_microstep: 280.26 | bwd_inner_microstep: 280.09 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1907 +[2025-05-14 21:39:51,695] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 193.05 | bwd_microstep: 280.28 | bwd_inner_microstep: 279.97 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1886 +[2025-05-14 21:39:52,227] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.50 | bwd_microstep: 321.17 | bwd_inner_microstep: 321.11 | bwd_allreduce_microstep: 0.02 | step_microstep: 2.59 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-14 21:39:53,079] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 326.19 | bwd_microstep: 493.91 | bwd_inner_microstep: 493.75 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-14 21:39:53,860] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 393.63 | bwd_microstep: 368.06 | bwd_inner_microstep: 367.81 | bwd_allreduce_microstep: 0.09 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-14 21:39:54,687] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 309.48 | bwd_microstep: 485.37 | bwd_inner_microstep: 485.34 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-14 21:39:55,563] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 351.62 | bwd_microstep: 492.49 | bwd_inner_microstep: 492.13 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1933 +[2025-05-14 21:39:56,702] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.07 | optimizer_gradients: 1.92 | optimizer_step: 14.09 +[2025-05-14 21:39:56,703] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 311.26 | bwd_microstep: 789.51 | bwd_inner_microstep: 507.38 | bwd_allreduce_microstep: 281.97 | step_microstep: 22.28 +[2025-05-14 21:39:56,704] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2480.41 | bwd: 3511.14 | bwd_inner: 3227.92 | bwd_allreduce: 282.42 | step: 27.93 + 8%|▊ | 142/1859 [13:06<2:49:34, 5.93s/it] {'loss': 3.1581, 'grad_norm': 7.987959384918213, 'learning_rate': 9.943968481527426e-11, 'epoch': 0.08} + 8%|▊ | 142/1859 [13:06<2:49:34, 5.93s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1916 +[2025-05-14 21:39:57,630] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 403.02 | bwd_microstep: 499.38 | bwd_inner_microstep: 499.23 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 362 +[2025-05-14 21:39:57,930] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 121.00 | bwd_microstep: 159.62 | bwd_inner_microstep: 159.58 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-14 21:39:58,767] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 309.81 | bwd_microstep: 493.78 | bwd_inner_microstep: 493.75 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.46 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-14 21:39:59,576] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 294.49 | bwd_microstep: 484.78 | bwd_inner_microstep: 483.62 | bwd_allreduce_microstep: 0.02 | step_microstep: 2.33 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-14 21:40:00,426] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 324.85 | bwd_microstep: 490.87 | bwd_inner_microstep: 490.80 | bwd_allreduce_microstep: 0.02 | step_microstep: 2.32 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-14 21:40:01,257] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 301.84 | bwd_microstep: 492.94 | bwd_inner_microstep: 492.51 | bwd_allreduce_microstep: 0.29 | step_microstep: 0.19 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 836 +[2025-05-14 21:40:01,672] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.19 | bwd_microstep: 195.62 | bwd_inner_microstep: 195.60 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 831 +[2025-05-14 21:40:02,160] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 4.39 | optimizer_step: 29.15 +[2025-05-14 21:40:02,160] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 197.87 | bwd_microstep: 219.55 | bwd_inner_microstep: 130.05 | bwd_allreduce_microstep: 89.40 | step_microstep: 39.99 +[2025-05-14 21:40:02,161] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2139.04 | bwd: 3036.56 | bwd_inner: 2945.24 | bwd_allreduce: 89.79 | step: 52.11 + 8%|▊ | 143/1859 [13:12<2:45:27, 5.79s/it] {'loss': 7.2205, 'grad_norm': 39.64183807373047, 'learning_rate': 9.942660357778607e-11, 'epoch': 0.08} + 8%|▊ | 143/1859 [13:12<2:45:27, 5.79s/it]dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1149 +[2025-05-14 21:40:02,723] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 265.67 | bwd_microstep: 255.38 | bwd_inner_microstep: 255.32 | bwd_allreduce_microstep: 0.02 | step_microstep: 2.37 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1887 +[2025-05-14 21:40:03,564] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 310.89 | bwd_microstep: 496.22 | bwd_inner_microstep: 495.93 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-14 21:40:04,474] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 398.57 | bwd_microstep: 492.37 | bwd_inner_microstep: 492.02 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1886 +[2025-05-14 21:40:05,278] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 342.58 | bwd_microstep: 437.85 | bwd_inner_microstep: 437.81 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-14 21:40:06,098] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 293.37 | bwd_microstep: 490.32 | bwd_inner_microstep: 490.28 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.55 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-14 21:40:06,961] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 338.90 | bwd_microstep: 492.05 | bwd_inner_microstep: 491.87 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-14 21:40:07,845] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 376.76 | bwd_microstep: 487.12 | bwd_inner_microstep: 487.08 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.32 +dynamic ViT batch size: 2, images per sample: 2.0, dynamic token length: 898 +[2025-05-14 21:40:08,526] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.47 | optimizer_step: 19.38 +[2025-05-14 21:40:08,527] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 101.09 | bwd_microstep: 528.18 | bwd_inner_microstep: 305.58 | bwd_allreduce_microstep: 222.57 | step_microstep: 29.15 +[2025-05-14 21:40:08,528] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2427.80 | bwd: 3679.56 | bwd_inner: 3456.06 | bwd_allreduce: 222.92 | step: 39.15 + 8%|▊ | 144/1859 [13:18<2:50:20, 5.96s/it] {'loss': 2.5987, 'grad_norm': 8.111407279968262, 'learning_rate': 9.941337227891292e-11, 'epoch': 0.08} + 8%|▊ | 144/1859 [13:18<2:50:20, 5.96s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1914 +[2025-05-14 21:40:09,394] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 334.64 | bwd_microstep: 503.98 | bwd_inner_microstep: 503.94 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.33 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1887 +[2025-05-14 21:40:10,226] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 304.56 | bwd_microstep: 495.67 | bwd_inner_microstep: 495.32 | bwd_allreduce_microstep: 0.21 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1892 +[2025-05-14 21:40:10,968] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 222.94 | bwd_microstep: 501.01 | bwd_inner_microstep: 500.96 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.49 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1887 +[2025-05-14 21:40:11,790] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 288.88 | bwd_microstep: 496.11 | bwd_inner_microstep: 496.09 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-14 21:40:12,626] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 312.91 | bwd_microstep: 491.39 | bwd_inner_microstep: 491.20 | bwd_allreduce_microstep: 0.08 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1984 +[2025-05-14 21:40:13,559] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 390.58 | bwd_microstep: 513.67 | bwd_inner_microstep: 513.47 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1456 +[2025-05-14 21:40:14,239] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 288.73 | bwd_microstep: 371.90 | bwd_inner_microstep: 371.85 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1966 +[2025-05-14 21:40:15,409] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 4.56 | optimizer_step: 26.45 +[2025-05-14 21:40:15,410] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 325.04 | bwd_microstep: 778.25 | bwd_inner_microstep: 539.27 | bwd_allreduce_microstep: 238.93 | step_microstep: 37.76 +[2025-05-14 21:40:15,411] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2468.24 | bwd: 4152.02 | bwd_inner: 3912.27 | bwd_allreduce: 239.11 | step: 47.67 + 8%|▊ | 145/1859 [13:25<2:58:11, 6.24s/it] {'loss': 3.0063, 'grad_norm': 6.604882717132568, 'learning_rate': 9.939999095882564e-11, 'epoch': 0.08} + 8%|▊ | 145/1859 [13:25<2:58:11, 6.24s/it]dynamic ViT batch size: 2, images per sample: 2.0, dynamic token length: 593 +[2025-05-14 21:40:15,764] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 144.91 | bwd_microstep: 167.26 | bwd_inner_microstep: 167.10 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-14 21:40:16,669] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 363.54 | bwd_microstep: 518.69 | bwd_inner_microstep: 518.64 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-14 21:40:17,500] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 309.22 | bwd_microstep: 500.99 | bwd_inner_microstep: 500.46 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.38 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-14 21:40:18,295] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 314.58 | bwd_microstep: 459.80 | bwd_inner_microstep: 459.64 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-14 21:40:19,120] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 313.42 | bwd_microstep: 495.73 | bwd_inner_microstep: 495.42 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-14 21:40:20,029] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 395.48 | bwd_microstep: 492.94 | bwd_inner_microstep: 492.42 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.22 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-14 21:40:20,833] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 286.23 | bwd_microstep: 495.51 | bwd_inner_microstep: 495.47 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2070 +[2025-05-14 21:40:21,998] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.01 | optimizer_gradients: 2.53 | optimizer_step: 19.47 +[2025-05-14 21:40:22,000] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 353.30 | bwd_microstep: 751.58 | bwd_inner_microstep: 550.89 | bwd_allreduce_microstep: 200.62 | step_microstep: 31.11 +[2025-05-14 21:40:22,001] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2480.62 | bwd: 3882.54 | bwd_inner: 3680.44 | bwd_allreduce: 200.95 | step: 36.71 + 8%|▊ | 146/1859 [13:32<3:01:06, 6.34s/it] {'loss': 7.8759, 'grad_norm': 33.626338958740234, 'learning_rate': 9.938645965815049e-11, 'epoch': 0.08} + 8%|▊ | 146/1859 [13:32<3:01:06, 6.34s/it]dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1459 +[2025-05-14 21:40:22,754] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 298.06 | bwd_microstep: 410.55 | bwd_inner_microstep: 410.51 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1889 +[2025-05-14 21:40:23,582] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 298.52 | bwd_microstep: 501.39 | bwd_inner_microstep: 501.34 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.32 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-14 21:40:24,445] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 319.88 | bwd_microstep: 506.22 | bwd_inner_microstep: 506.18 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-14 21:40:25,263] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 288.46 | bwd_microstep: 494.41 | bwd_inner_microstep: 492.01 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.37 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 842 +[2025-05-14 21:40:25,694] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 183.70 | bwd_microstep: 215.68 | bwd_inner_microstep: 215.44 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-14 21:40:26,468] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 324.58 | bwd_microstep: 416.05 | bwd_inner_microstep: 416.01 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-14 21:40:27,288] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 292.35 | bwd_microstep: 495.05 | bwd_inner_microstep: 495.00 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 831 +[2025-05-14 21:40:27,948] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 4.73 | optimizer_step: 21.57 +[2025-05-14 21:40:27,951] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 170.75 | bwd_microstep: 426.18 | bwd_inner_microstep: 213.48 | bwd_allreduce_microstep: 212.62 | step_microstep: 34.06 +[2025-05-14 21:40:27,951] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2176.28 | bwd: 3465.55 | bwd_inner: 3249.98 | bwd_allreduce: 212.80 | step: 48.28 + 8%|▊ | 147/1859 [13:38<2:57:37, 6.23s/it] {'loss': 6.8834, 'grad_norm': 38.41349792480469, 'learning_rate': 9.937277841796912e-11, 'epoch': 0.08} + 8%|▊ | 147/1859 [13:38<2:57:37, 6.23s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1887 +[2025-05-14 21:40:28,840] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 350.03 | bwd_microstep: 497.66 | bwd_inner_microstep: 497.39 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-14 21:40:29,720] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 359.43 | bwd_microstep: 499.24 | bwd_inner_microstep: 499.20 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.55 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1883 +[2025-05-14 21:40:30,550] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 298.87 | bwd_microstep: 498.43 | bwd_inner_microstep: 498.38 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-14 21:40:31,360] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 279.97 | bwd_microstep: 495.50 | bwd_inner_microstep: 495.47 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-14 21:40:32,242] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 353.45 | bwd_microstep: 496.03 | bwd_inner_microstep: 495.88 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-14 21:40:33,125] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 368.63 | bwd_microstep: 491.23 | bwd_inner_microstep: 491.18 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.29 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-14 21:40:33,942] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 291.25 | bwd_microstep: 493.80 | bwd_inner_microstep: 493.75 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1999 +[2025-05-14 21:40:35,086] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.01 | optimizer_gradients: 5.14 | optimizer_step: 25.19 +[2025-05-14 21:40:35,089] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 316.40 | bwd_microstep: 758.39 | bwd_inner_microstep: 478.80 | bwd_allreduce_microstep: 279.49 | step_microstep: 37.58 +[2025-05-14 21:40:35,089] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2618.01 | bwd: 4230.31 | bwd_inner: 3950.14 | bwd_allreduce: 279.73 | step: 49.68 + 8%|▊ | 148/1859 [13:45<3:05:20, 6.50s/it] {'loss': 4.9655, 'grad_norm': 15.923096656799316, 'learning_rate': 9.935894727981839e-11, 'epoch': 0.08} + 8%|▊ | 148/1859 [13:45<3:05:20, 6.50s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1899 +[2025-05-14 21:40:35,974] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 346.90 | bwd_microstep: 494.32 | bwd_inner_microstep: 494.15 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1883 +[2025-05-14 21:40:36,864] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 374.21 | bwd_microstep: 496.60 | bwd_inner_microstep: 496.57 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1888 +[2025-05-14 21:40:37,666] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 284.20 | bwd_microstep: 492.63 | bwd_inner_microstep: 492.44 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.21 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 856 +[2025-05-14 21:40:38,090] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 193.26 | bwd_microstep: 201.49 | bwd_inner_microstep: 201.44 | bwd_allreduce_microstep: 0.02 | step_microstep: 2.36 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 853 +[2025-05-14 21:40:38,523] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 201.26 | bwd_microstep: 198.88 | bwd_inner_microstep: 198.83 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-14 21:40:39,369] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 326.67 | bwd_microstep: 490.63 | bwd_inner_microstep: 490.57 | bwd_allreduce_microstep: 0.02 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-14 21:40:40,236] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 343.73 | bwd_microstep: 491.06 | bwd_inner_microstep: 490.76 | bwd_allreduce_microstep: 0.14 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-14 21:40:41,286] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.01 | optimizer_gradients: 2.35 | optimizer_step: 20.66 +[2025-05-14 21:40:41,288] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 381.44 | bwd_microstep: 621.00 | bwd_inner_microstep: 510.89 | bwd_allreduce_microstep: 110.06 | step_microstep: 29.48 +[2025-05-14 21:40:41,289] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2451.63 | bwd: 3486.67 | bwd_inner: 3375.84 | bwd_allreduce: 110.15 | step: 39.31 + 8%|▊ | 149/1859 [13:51<3:02:39, 6.41s/it] {'loss': 3.571, 'grad_norm': 20.613624572753906, 'learning_rate': 9.934496628569026e-11, 'epoch': 0.08} + 8%|▊ | 149/1859 [13:51<3:02:39, 6.41s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1889 +[2025-05-14 21:40:42,167] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 336.51 | bwd_microstep: 499.03 | bwd_inner_microstep: 498.87 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-14 21:40:42,867] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 398.88 | bwd_microstep: 280.74 | bwd_inner_microstep: 280.60 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-14 21:40:43,572] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 192.61 | bwd_microstep: 496.40 | bwd_inner_microstep: 496.23 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-14 21:40:44,491] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 404.23 | bwd_microstep: 494.52 | bwd_inner_microstep: 494.31 | bwd_allreduce_microstep: 0.08 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-14 21:40:45,295] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 277.23 | bwd_microstep: 497.34 | bwd_inner_microstep: 497.30 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.28 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-14 21:40:46,064] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 281.14 | bwd_microstep: 454.66 | bwd_inner_microstep: 454.63 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.38 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-14 21:40:46,918] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 325.43 | bwd_microstep: 494.67 | bwd_inner_microstep: 494.29 | bwd_allreduce_microstep: 0.15 | step_microstep: 0.24 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-14 21:40:47,971] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.09 | optimizer_gradients: 8.35 | optimizer_step: 21.08 +[2025-05-14 21:40:47,972] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 321.78 | bwd_microstep: 664.52 | bwd_inner_microstep: 462.85 | bwd_allreduce_microstep: 201.60 | step_microstep: 37.63 +[2025-05-14 21:40:47,973] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2537.74 | bwd: 3882.00 | bwd_inner: 3679.25 | bwd_allreduce: 202.06 | step: 42.97 + 8%|▊ | 150/1859 [13:58<3:04:53, 6.49s/it] {'loss': 4.5285, 'grad_norm': 17.58492660522461, 'learning_rate': 9.933083547803164e-11, 'epoch': 0.08} + 8%|▊ | 150/1859 [13:58<3:04:53, 6.49s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1897 +[2025-05-14 21:40:48,886] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 399.75 | bwd_microstep: 487.94 | bwd_inner_microstep: 487.55 | bwd_allreduce_microstep: 0.36 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-14 21:40:49,683] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 301.77 | bwd_microstep: 471.14 | bwd_inner_microstep: 471.08 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.20 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 839 +[2025-05-14 21:40:50,093] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 192.24 | bwd_microstep: 187.83 | bwd_inner_microstep: 187.79 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.55 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-14 21:40:50,919] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 307.15 | bwd_microstep: 488.88 | bwd_inner_microstep: 488.69 | bwd_allreduce_microstep: 0.08 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-14 21:40:51,707] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 275.91 | bwd_microstep: 494.54 | bwd_inner_microstep: 493.37 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.33 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 834 +[2025-05-14 21:40:52,122] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 178.15 | bwd_microstep: 202.39 | bwd_inner_microstep: 202.35 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.51 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-14 21:40:52,948] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 303.00 | bwd_microstep: 487.71 | bwd_inner_microstep: 487.68 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.37 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-14 21:40:53,938] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.07 | optimizer_gradients: 2.85 | optimizer_step: 18.11 +[2025-05-14 21:40:53,938] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 351.35 | bwd_microstep: 579.51 | bwd_inner_microstep: 487.64 | bwd_allreduce_microstep: 91.74 | step_microstep: 27.71 +[2025-05-14 21:40:53,939] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2309.30 | bwd: 3399.97 | bwd_inner: 3306.26 | bwd_allreduce: 92.24 | step: 37.99 + 8%|▊ | 151/1859 [14:04<3:00:17, 6.33s/it] {'loss': 5.7705, 'grad_norm': 32.84267807006836, 'learning_rate': 9.931655489974432e-11, 'epoch': 0.08} + 8%|▊ | 151/1859 [14:04<3:00:17, 6.33s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1905 +[2025-05-14 21:40:54,862] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 397.54 | bwd_microstep: 502.49 | bwd_inner_microstep: 502.24 | bwd_allreduce_microstep: 0.22 | step_microstep: 0.39 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-14 21:40:55,689] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 308.82 | bwd_microstep: 496.23 | bwd_inner_microstep: 496.18 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.58 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1368 +[2025-05-14 21:40:56,348] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 199.41 | bwd_microstep: 424.85 | bwd_inner_microstep: 424.51 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.21 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-14 21:40:57,233] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 360.44 | bwd_microstep: 499.47 | bwd_inner_microstep: 499.42 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.28 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-14 21:40:58,063] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 298.61 | bwd_microstep: 497.77 | bwd_inner_microstep: 497.73 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 836 +[2025-05-14 21:40:58,468] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 166.96 | bwd_microstep: 200.79 | bwd_inner_microstep: 200.74 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.37 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2088 +[2025-05-14 21:40:59,410] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 335.42 | bwd_microstep: 570.38 | bwd_inner_microstep: 570.35 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.49 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1907 +[2025-05-14 21:41:00,555] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.07 | optimizer_gradients: 2.25 | optimizer_step: 18.71 +[2025-05-14 21:41:00,555] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 314.19 | bwd_microstep: 784.66 | bwd_inner_microstep: 498.97 | bwd_allreduce_microstep: 285.54 | step_microstep: 28.25 +[2025-05-14 21:41:00,556] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2381.33 | bwd: 3976.68 | bwd_inner: 3690.27 | bwd_allreduce: 285.94 | step: 40.98 + 8%|▊ | 152/1859 [14:10<3:02:37, 6.42s/it] {'loss': 2.6005, 'grad_norm': 14.107369422912598, 'learning_rate': 9.930212459418474e-11, 'epoch': 0.08} + 8%|▊ | 152/1859 [14:10<3:02:37, 6.42s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-14 21:41:01,410] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 402.00 | bwd_microstep: 422.03 | bwd_inner_microstep: 421.98 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 849 +[2025-05-14 21:41:01,837] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 207.95 | bwd_microstep: 181.32 | bwd_inner_microstep: 181.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-14 21:41:02,706] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 343.73 | bwd_microstep: 491.36 | bwd_inner_microstep: 491.13 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-14 21:41:03,618] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 394.34 | bwd_microstep: 495.97 | bwd_inner_microstep: 495.94 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.19 +dynamic ViT batch size: 2, images per sample: 2.0, dynamic token length: 591 +[2025-05-14 21:41:03,908] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 89.68 | bwd_microstep: 179.61 | bwd_inner_microstep: 179.55 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.28 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-14 21:41:04,755] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 320.54 | bwd_microstep: 494.03 | bwd_inner_microstep: 493.98 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-14 21:41:05,581] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 300.88 | bwd_microstep: 491.19 | bwd_inner_microstep: 490.97 | bwd_allreduce_microstep: 0.18 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1951 +[2025-05-14 21:41:06,734] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.01 | optimizer_gradients: 2.06 | optimizer_step: 18.87 +[2025-05-14 21:41:06,736] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 324.94 | bwd_microstep: 772.40 | bwd_inner_microstep: 524.81 | bwd_allreduce_microstep: 247.53 | step_microstep: 29.25 +[2025-05-14 21:41:06,737] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2383.84 | bwd: 3527.91 | bwd_inner: 3279.72 | bwd_allreduce: 247.65 | step: 39.07 + 8%|▊ | 153/1859 [14:16<3:00:29, 6.35s/it] {'loss': 5.3659, 'grad_norm': 35.08295822143555, 'learning_rate': 9.928754460516398e-11, 'epoch': 0.08} + 8%|▊ | 153/1859 [14:17<3:00:29, 6.35s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1909 +[2025-05-14 21:41:07,595] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 321.69 | bwd_microstep: 492.48 | bwd_inner_microstep: 492.33 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1892 +[2025-05-14 21:41:08,153] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.22 | bwd_microstep: 349.58 | bwd_inner_microstep: 349.55 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.37 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-14 21:41:08,990] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 307.66 | bwd_microstep: 492.68 | bwd_inner_microstep: 492.64 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.57 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 330 +[2025-05-14 21:41:09,264] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 103.83 | bwd_microstep: 140.26 | bwd_inner_microstep: 139.99 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.41 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-14 21:41:10,083] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 297.42 | bwd_microstep: 500.17 | bwd_inner_microstep: 500.13 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.29 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-14 21:41:10,918] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 305.14 | bwd_microstep: 495.25 | bwd_inner_microstep: 495.22 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.37 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-14 21:41:11,756] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 312.12 | bwd_microstep: 493.18 | bwd_inner_microstep: 492.81 | bwd_allreduce_microstep: 0.15 | step_microstep: 0.21 +dynamic ViT batch size: 2, images per sample: 2.0, dynamic token length: 583 +[2025-05-14 21:41:12,251] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.01 | optimizer_gradients: 2.32 | optimizer_step: 18.80 +[2025-05-14 21:41:12,252] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 140.36 | bwd_microstep: 300.68 | bwd_inner_microstep: 202.22 | bwd_allreduce_microstep: 98.37 | step_microstep: 28.41 +[2025-05-14 21:41:12,252] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 1978.42 | bwd: 3264.33 | bwd_inner: 3165.03 | bwd_allreduce: 98.62 | step: 38.72 + 8%|▊ | 154/1859 [14:22<2:53:17, 6.10s/it] {'loss': 5.1712, 'grad_norm': 17.686275482177734, 'learning_rate': 9.927281497694756e-11, 'epoch': 0.08} + 8%|▊ | 154/1859 [14:22<2:53:17, 6.10s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 374 +[2025-05-14 21:41:12,535] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 113.08 | bwd_microstep: 128.64 | bwd_inner_microstep: 128.30 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.22 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-14 21:41:13,357] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 304.58 | bwd_microstep: 496.11 | bwd_inner_microstep: 495.96 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-14 21:41:14,262] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 395.48 | bwd_microstep: 489.10 | bwd_inner_microstep: 489.05 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.60 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-14 21:41:15,065] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 301.20 | bwd_microstep: 481.19 | bwd_inner_microstep: 481.15 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-14 21:41:15,862] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 300.16 | bwd_microstep: 462.99 | bwd_inner_microstep: 462.73 | bwd_allreduce_microstep: 0.09 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-14 21:41:16,586] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 218.75 | bwd_microstep: 487.73 | bwd_inner_microstep: 487.69 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 1034 +[2025-05-14 21:41:17,092] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 237.09 | bwd_microstep: 235.96 | bwd_inner_microstep: 235.93 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 407 +[2025-05-14 21:41:17,676] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.22 | optimizer_step: 26.34 +[2025-05-14 21:41:17,677] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 118.87 | bwd_microstep: 404.77 | bwd_inner_microstep: 149.05 | bwd_allreduce_microstep: 255.57 | step_microstep: 35.05 +[2025-05-14 21:41:17,677] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 1989.18 | bwd: 3186.54 | bwd_inner: 2930.07 | bwd_allreduce: 255.81 | step: 43.17 + 8%|▊ | 155/1859 [14:27<2:47:25, 5.90s/it] {'loss': 4.7326, 'grad_norm': 19.67642593383789, 'learning_rate': 9.925793575425525e-11, 'epoch': 0.08} + 8%|▊ | 155/1859 [14:27<2:47:25, 5.90s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1900 +[2025-05-14 21:41:18,579] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 372.25 | bwd_microstep: 502.65 | bwd_inner_microstep: 502.59 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.37 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-14 21:41:19,392] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 293.58 | bwd_microstep: 494.36 | bwd_inner_microstep: 494.34 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1361 +[2025-05-14 21:41:20,002] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 225.00 | bwd_microstep: 350.49 | bwd_inner_microstep: 350.43 | bwd_allreduce_microstep: 0.02 | step_microstep: 2.36 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1375 +[2025-05-14 21:41:20,724] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 278.75 | bwd_microstep: 406.13 | bwd_inner_microstep: 406.09 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-14 21:41:21,558] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 302.78 | bwd_microstep: 507.64 | bwd_inner_microstep: 507.46 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-14 21:41:22,418] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 344.66 | bwd_microstep: 490.56 | bwd_inner_microstep: 490.52 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.33 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2125 +[2025-05-14 21:41:23,368] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 324.43 | bwd_microstep: 589.22 | bwd_inner_microstep: 589.18 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1428 +[2025-05-14 21:41:24,321] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.09 | optimizer_gradients: 2.74 | optimizer_step: 25.05 +[2025-05-14 21:41:24,321] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 201.15 | bwd_microstep: 682.96 | bwd_inner_microstep: 397.88 | bwd_allreduce_microstep: 284.94 | step_microstep: 34.37 +[2025-05-14 21:41:24,322] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2342.55 | bwd: 4024.04 | bwd_inner: 3738.61 | bwd_allreduce: 285.07 | step: 48.59 + 8%|▊ | 156/1859 [14:34<2:53:42, 6.12s/it] {'loss': 2.4998, 'grad_norm': 9.629687309265137, 'learning_rate': 9.924290698226105e-11, 'epoch': 0.08} + 8%|▊ | 156/1859 [14:34<2:53:42, 6.12s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1951 +[2025-05-14 21:41:25,251] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 394.52 | bwd_microstep: 506.84 | bwd_inner_microstep: 506.49 | bwd_allreduce_microstep: 0.14 | step_microstep: 0.19 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1396 +[2025-05-14 21:41:25,875] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 266.55 | bwd_microstep: 338.25 | bwd_inner_microstep: 338.20 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.37 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-14 21:41:26,719] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 333.35 | bwd_microstep: 477.75 | bwd_inner_microstep: 477.48 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-14 21:41:27,528] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 262.86 | bwd_microstep: 528.41 | bwd_inner_microstep: 528.11 | bwd_allreduce_microstep: 0.26 | step_microstep: 0.25 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-14 21:41:28,334] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 283.72 | bwd_microstep: 497.89 | bwd_inner_microstep: 497.84 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.33 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-14 21:41:29,165] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 299.57 | bwd_microstep: 494.51 | bwd_inner_microstep: 494.46 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.37 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-14 21:41:30,018] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 327.88 | bwd_microstep: 490.05 | bwd_inner_microstep: 490.00 | bwd_allreduce_microstep: 0.02 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1949 +[2025-05-14 21:41:31,142] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.40 | optimizer_step: 18.41 +[2025-05-14 21:41:31,143] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 311.55 | bwd_microstep: 751.64 | bwd_inner_microstep: 528.22 | bwd_allreduce_microstep: 223.36 | step_microstep: 29.54 +[2025-05-14 21:41:31,144] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2479.95 | bwd: 4085.40 | bwd_inner: 3860.93 | bwd_allreduce: 223.92 | step: 39.49 + 8%|▊ | 157/1859 [14:41<2:59:36, 6.33s/it] {'loss': 4.5221, 'grad_norm': 18.984766006469727, 'learning_rate': 9.9227728706593e-11, 'epoch': 0.08} + 8%|▊ | 157/1859 [14:41<2:59:36, 6.33s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1900 +[2025-05-14 21:41:32,035] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 351.87 | bwd_microstep: 496.52 | bwd_inner_microstep: 496.35 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.09 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1110 +[2025-05-14 21:41:32,554] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 229.64 | bwd_microstep: 269.17 | bwd_inner_microstep: 269.11 | bwd_allreduce_microstep: 0.02 | step_microstep: 2.56 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-14 21:41:33,398] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 301.18 | bwd_microstep: 506.17 | bwd_inner_microstep: 506.10 | bwd_allreduce_microstep: 0.02 | step_microstep: 2.31 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-14 21:41:34,226] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 302.15 | bwd_microstep: 492.04 | bwd_inner_microstep: 492.01 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-14 21:41:35,027] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 273.60 | bwd_microstep: 493.29 | bwd_inner_microstep: 493.08 | bwd_allreduce_microstep: 0.09 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-14 21:41:35,944] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 403.16 | bwd_microstep: 493.06 | bwd_inner_microstep: 492.92 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-14 21:41:36,783] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 319.20 | bwd_microstep: 498.28 | bwd_inner_microstep: 498.22 | bwd_allreduce_microstep: 0.02 | step_microstep: 2.36 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 325 +[2025-05-14 21:41:37,332] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.28 | optimizer_step: 18.89 +[2025-05-14 21:41:37,334] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.33 | bwd_microstep: 396.54 | bwd_inner_microstep: 174.31 | bwd_allreduce_microstep: 222.19 | step_microstep: 28.62 +[2025-05-14 21:41:37,334] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2274.06 | bwd: 3645.11 | bwd_inner: 3422.20 | bwd_allreduce: 222.47 | step: 38.52 + 8%|▊ | 158/1859 [14:47<2:58:18, 6.29s/it] {'loss': 3.5342, 'grad_norm': 18.47201919555664, 'learning_rate': 9.921240097333302e-11, 'epoch': 0.08} + 8%|▊ | 158/1859 [14:47<2:58:18, 6.29s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1903 +[2025-05-14 21:41:38,181] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 305.43 | bwd_microstep: 496.25 | bwd_inner_microstep: 494.91 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.32 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1916 +[2025-05-14 21:41:39,024] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 303.80 | bwd_microstep: 505.01 | bwd_inner_microstep: 504.98 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.37 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-14 21:41:39,880] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 341.99 | bwd_microstep: 480.74 | bwd_inner_microstep: 480.72 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.25 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 845 +[2025-05-14 21:41:40,256] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 98.30 | bwd_microstep: 260.01 | bwd_inner_microstep: 259.96 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.32 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1349 +[2025-05-14 21:41:40,908] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 193.28 | bwd_microstep: 424.01 | bwd_inner_microstep: 423.63 | bwd_allreduce_microstep: 0.14 | step_microstep: 0.20 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 322 +[2025-05-14 21:41:41,198] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 116.33 | bwd_microstep: 153.23 | bwd_inner_microstep: 153.17 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-14 21:41:42,026] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 301.18 | bwd_microstep: 492.44 | bwd_inner_microstep: 492.40 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1954 +[2025-05-14 21:41:43,194] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.07 | optimizer_gradients: 2.31 | optimizer_step: 28.22 +[2025-05-14 21:41:43,194] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 317.99 | bwd_microstep: 782.25 | bwd_inner_microstep: 480.26 | bwd_allreduce_microstep: 301.81 | step_microstep: 38.39 +[2025-05-14 21:41:43,195] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 1978.27 | bwd: 3594.21 | bwd_inner: 3287.81 | bwd_allreduce: 303.08 | step: 48.40 + 9%|▊ | 159/1859 [14:53<2:54:32, 6.16s/it] {'loss': 6.899, 'grad_norm': 31.1981201171875, 'learning_rate': 9.919692382901679e-11, 'epoch': 0.09} + 9%|▊ | 159/1859 [14:53<2:54:32, 6.16s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1905 +[2025-05-14 21:41:44,122] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 401.99 | bwd_microstep: 496.05 | bwd_inner_microstep: 495.77 | bwd_allreduce_microstep: 0.10 | step_microstep: 0.11 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1365 +[2025-05-14 21:41:44,706] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 229.22 | bwd_microstep: 334.80 | bwd_inner_microstep: 334.34 | bwd_allreduce_microstep: 0.09 | step_microstep: 0.05 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 335 +[2025-05-14 21:41:44,985] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 106.07 | bwd_microstep: 151.46 | bwd_inner_microstep: 151.41 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.32 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1888 +[2025-05-14 21:41:45,829] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 309.14 | bwd_microstep: 501.86 | bwd_inner_microstep: 501.57 | bwd_allreduce_microstep: 0.27 | step_microstep: 0.24 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-14 21:41:46,664] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 319.58 | bwd_microstep: 492.90 | bwd_inner_microstep: 492.86 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.53 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-14 21:41:47,507] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 316.19 | bwd_microstep: 492.77 | bwd_inner_microstep: 492.69 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-14 21:41:48,311] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 300.95 | bwd_microstep: 468.54 | bwd_inner_microstep: 468.24 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1954 +[2025-05-14 21:41:49,217] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.01 | optimizer_gradients: 2.34 | optimizer_step: 20.69 +[2025-05-14 21:41:49,220] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 198.18 | bwd_microstep: 662.35 | bwd_inner_microstep: 511.73 | bwd_allreduce_microstep: 150.55 | step_microstep: 30.29 +[2025-05-14 21:41:49,220] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2181.27 | bwd: 3600.95 | bwd_inner: 3448.82 | bwd_allreduce: 151.32 | step: 35.87 + 9%|▊ | 160/1859 [14:59<2:53:18, 6.12s/it] {'loss': 3.6529, 'grad_norm': 12.86482048034668, 'learning_rate': 9.918129732063362e-11, 'epoch': 0.09} + 9%|▊ | 160/1859 [14:59<2:53:18, 6.12s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1906 +[2025-05-14 21:41:50,073] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 307.65 | bwd_microstep: 499.29 | bwd_inner_microstep: 499.24 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.53 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-14 21:41:50,900] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 294.62 | bwd_microstep: 497.89 | bwd_inner_microstep: 497.82 | bwd_allreduce_microstep: 0.02 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-14 21:41:51,708] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 360.00 | bwd_microstep: 414.09 | bwd_inner_microstep: 414.06 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.55 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-14 21:41:52,548] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 307.95 | bwd_microstep: 497.19 | bwd_inner_microstep: 496.97 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-14 21:41:53,364] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 294.53 | bwd_microstep: 489.32 | bwd_inner_microstep: 489.26 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-14 21:41:54,250] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 362.27 | bwd_microstep: 491.69 | bwd_inner_microstep: 491.54 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-14 21:41:55,147] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 376.35 | bwd_microstep: 499.83 | bwd_inner_microstep: 499.80 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2071 +[2025-05-14 21:41:56,238] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.33 | optimizer_step: 18.29 +[2025-05-14 21:41:56,239] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 323.05 | bwd_microstep: 719.21 | bwd_inner_microstep: 574.61 | bwd_allreduce_microstep: 144.54 | step_microstep: 26.71 +[2025-05-14 21:41:56,239] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2626.39 | bwd: 4108.53 | bwd_inner: 3963.32 | bwd_allreduce: 144.79 | step: 39.05 + 9%|▊ | 161/1859 [15:06<3:00:50, 6.39s/it] {'loss': 4.4551, 'grad_norm': 34.817344665527344, 'learning_rate': 9.916552149562628e-11, 'epoch': 0.09} + 9%|▊ | 161/1859 [15:06<3:00:50, 6.39s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1902 +[2025-05-14 21:41:56,903] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 343.12 | bwd_microstep: 277.32 | bwd_inner_microstep: 277.18 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-14 21:41:57,705] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 279.95 | bwd_microstep: 501.04 | bwd_inner_microstep: 500.99 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.37 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-14 21:41:58,551] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 314.18 | bwd_microstep: 495.25 | bwd_inner_microstep: 495.21 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.54 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-14 21:41:59,373] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 298.86 | bwd_microstep: 489.84 | bwd_inner_microstep: 489.80 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.41 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-14 21:42:00,183] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 288.74 | bwd_microstep: 491.67 | bwd_inner_microstep: 491.36 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-14 21:42:01,086] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 395.43 | bwd_microstep: 487.41 | bwd_inner_microstep: 486.99 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.23 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1937 +[2025-05-14 21:42:01,944] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 300.52 | bwd_microstep: 536.01 | bwd_inner_microstep: 535.97 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1883 +[2025-05-14 21:42:03,030] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.34 | optimizer_step: 20.43 +[2025-05-14 21:42:03,030] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 285.51 | bwd_microstep: 739.57 | bwd_inner_microstep: 498.18 | bwd_allreduce_microstep: 241.33 | step_microstep: 29.00 +[2025-05-14 21:42:03,031] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2506.26 | bwd: 4018.16 | bwd_inner: 3775.79 | bwd_allreduce: 241.58 | step: 38.13 + 9%|▊ | 162/1859 [15:13<3:04:06, 6.51s/it] {'loss': 4.9886, 'grad_norm': 32.621421813964844, 'learning_rate': 9.914959640189088e-11, 'epoch': 0.09} + 9%|▊ | 162/1859 [15:13<3:04:06, 6.51s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1937 +[2025-05-14 21:42:03,963] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 374.01 | bwd_microstep: 533.51 | bwd_inner_microstep: 533.47 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.92 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1916 +[2025-05-14 21:42:04,783] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 304.95 | bwd_microstep: 493.25 | bwd_inner_microstep: 493.21 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.33 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-14 21:42:05,544] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 258.21 | bwd_microstep: 465.44 | bwd_inner_microstep: 465.40 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-14 21:42:06,391] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 296.94 | bwd_microstep: 524.88 | bwd_inner_microstep: 524.84 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.33 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-14 21:42:07,218] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 301.55 | bwd_microstep: 491.93 | bwd_inner_microstep: 491.90 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.32 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-14 21:42:08,089] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 339.23 | bwd_microstep: 497.63 | bwd_inner_microstep: 497.61 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-14 21:42:08,856] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 242.56 | bwd_microstep: 490.50 | bwd_inner_microstep: 490.46 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.37 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-14 21:42:10,027] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.24 | optimizer_step: 25.53 +[2025-05-14 21:42:10,027] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 336.57 | bwd_microstep: 765.72 | bwd_inner_microstep: 494.03 | bwd_allreduce_microstep: 271.52 | step_microstep: 34.34 +[2025-05-14 21:42:10,028] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2454.00 | bwd: 4262.87 | bwd_inner: 3990.99 | bwd_allreduce: 271.60 | step: 49.34 + 9%|▉ | 163/1859 [15:20<3:08:07, 6.66s/it] {'loss': 3.7464, 'grad_norm': 19.15847396850586, 'learning_rate': 9.913352208777675e-11, 'epoch': 0.09} + 9%|▉ | 163/1859 [15:20<3:08:07, 6.66s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1930 +[2025-05-14 21:42:10,980] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 416.12 | bwd_microstep: 509.67 | bwd_inner_microstep: 509.51 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1917 +[2025-05-14 21:42:11,881] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 344.16 | bwd_microstep: 533.42 | bwd_inner_microstep: 533.38 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 6, images per sample: 6.0, dynamic token length: 1623 +[2025-05-14 21:42:12,590] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 255.04 | bwd_microstep: 428.82 | bwd_inner_microstep: 428.77 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-14 21:42:13,439] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 322.44 | bwd_microstep: 494.40 | bwd_inner_microstep: 494.08 | bwd_allreduce_microstep: 0.14 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-14 21:42:14,141] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.80 | bwd_microstep: 495.70 | bwd_inner_microstep: 495.39 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.11 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 323 +[2025-05-14 21:42:14,386] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 88.56 | bwd_microstep: 138.32 | bwd_inner_microstep: 138.26 | bwd_allreduce_microstep: 0.02 | step_microstep: 2.38 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-14 21:42:15,220] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 306.80 | bwd_microstep: 491.16 | bwd_inner_microstep: 490.79 | bwd_allreduce_microstep: 0.14 | step_microstep: 0.23 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1923 +[2025-05-14 21:42:16,365] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.01 | optimizer_gradients: 2.25 | optimizer_step: 19.35 +[2025-05-14 21:42:16,366] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 373.36 | bwd_microstep: 711.03 | bwd_inner_microstep: 487.95 | bwd_allreduce_microstep: 222.77 | step_microstep: 28.82 +[2025-05-14 21:42:16,366] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2296.99 | bwd: 3802.61 | bwd_inner: 3578.35 | bwd_allreduce: 223.25 | step: 36.44 + 9%|▉ | 164/1859 [15:26<3:05:21, 6.56s/it] {'loss': 4.2294, 'grad_norm': 31.17864418029785, 'learning_rate': 9.911729860208619e-11, 'epoch': 0.09} + 9%|▉ | 164/1859 [15:26<3:05:21, 6.56s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1895 +[2025-05-14 21:42:17,240] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 334.07 | bwd_microstep: 496.83 | bwd_inner_microstep: 496.65 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1887 +[2025-05-14 21:42:17,947] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 400.21 | bwd_microstep: 284.88 | bwd_inner_microstep: 284.50 | bwd_allreduce_microstep: 0.14 | step_microstep: 0.24 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1883 +[2025-05-14 21:42:18,438] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.82 | bwd_microstep: 278.36 | bwd_inner_microstep: 278.06 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1897 +[2025-05-14 21:42:19,015] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 191.71 | bwd_microstep: 365.24 | bwd_inner_microstep: 364.09 | bwd_allreduce_microstep: 0.02 | step_microstep: 2.33 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1360 +[2025-05-14 21:42:19,687] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 232.47 | bwd_microstep: 407.61 | bwd_inner_microstep: 407.34 | bwd_allreduce_microstep: 0.23 | step_microstep: 0.26 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-14 21:42:20,503] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 296.13 | bwd_microstep: 498.03 | bwd_inner_microstep: 497.99 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.28 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-14 21:42:21,352] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 325.87 | bwd_microstep: 486.73 | bwd_inner_microstep: 486.70 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-14 21:42:22,290] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.20 | optimizer_step: 19.26 +[2025-05-14 21:42:22,291] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 306.79 | bwd_microstep: 576.87 | bwd_inner_microstep: 347.89 | bwd_allreduce_microstep: 228.92 | step_microstep: 28.66 +[2025-05-14 21:42:22,292] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2278.02 | bwd: 3394.64 | bwd_inner: 3163.47 | bwd_allreduce: 229.26 | step: 36.34 + 9%|▉ | 165/1859 [15:32<2:59:51, 6.37s/it] {'loss': 4.3781, 'grad_norm': 23.616928100585938, 'learning_rate': 9.910092599407446e-11, 'epoch': 0.09} + 9%|▉ | 165/1859 [15:32<2:59:51, 6.37s/it]dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1496 +[2025-05-14 21:42:23,068] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 298.46 | bwd_microstep: 433.72 | bwd_inner_microstep: 433.68 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.86 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-14 21:42:23,888] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 301.11 | bwd_microstep: 497.00 | bwd_inner_microstep: 496.97 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-14 21:42:24,683] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 304.91 | bwd_microstep: 453.70 | bwd_inner_microstep: 453.66 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-14 21:42:25,568] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 353.87 | bwd_microstep: 498.91 | bwd_inner_microstep: 498.73 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.12 +dynamic ViT batch size: 2, images per sample: 2.0, dynamic token length: 582 +[2025-05-14 21:42:25,907] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 120.30 | bwd_microstep: 200.98 | bwd_inner_microstep: 200.94 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-14 21:42:26,720] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 288.42 | bwd_microstep: 489.80 | bwd_inner_microstep: 489.76 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-14 21:42:27,557] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 306.04 | bwd_microstep: 499.22 | bwd_inner_microstep: 499.18 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 867 +[2025-05-14 21:42:28,305] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.18 | optimizer_gradients: 4.77 | optimizer_step: 19.59 +[2025-05-14 21:42:28,306] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 210.61 | bwd_microstep: 474.88 | bwd_inner_microstep: 186.71 | bwd_allreduce_microstep: 288.09 | step_microstep: 33.79 +[2025-05-14 21:42:28,307] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2183.70 | bwd: 3548.23 | bwd_inner: 3259.66 | bwd_allreduce: 288.24 | step: 45.35 + 9%|▉ | 166/1859 [15:38<2:56:44, 6.26s/it] {'loss': 3.9832, 'grad_norm': 16.80715560913086, 'learning_rate': 9.90844043134495e-11, 'epoch': 0.09} + 9%|▉ | 166/1859 [15:38<2:56:44, 6.26s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1883 +[2025-05-14 21:42:29,200] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 354.36 | bwd_microstep: 495.32 | bwd_inner_microstep: 494.82 | bwd_allreduce_microstep: 0.19 | step_microstep: 0.31 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-14 21:42:30,005] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 411.69 | bwd_microstep: 371.49 | bwd_inner_microstep: 371.22 | bwd_allreduce_microstep: 0.09 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-14 21:42:30,823] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 309.84 | bwd_microstep: 493.22 | bwd_inner_microstep: 493.06 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.11 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1356 +[2025-05-14 21:42:31,463] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 259.38 | bwd_microstep: 358.93 | bwd_inner_microstep: 358.89 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.37 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-14 21:42:32,298] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 321.00 | bwd_microstep: 479.93 | bwd_inner_microstep: 479.75 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.11 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1345 +[2025-05-14 21:42:32,669] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 143.32 | bwd_microstep: 208.37 | bwd_inner_microstep: 208.21 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 324 +[2025-05-14 21:42:32,895] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 83.38 | bwd_microstep: 127.02 | bwd_inner_microstep: 126.86 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-14 21:42:33,466] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.78 | optimizer_step: 17.88 +[2025-05-14 21:42:33,467] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.99 | bwd_microstep: 336.91 | bwd_inner_microstep: 275.18 | bwd_allreduce_microstep: 61.57 | step_microstep: 26.85 +[2025-05-14 21:42:33,467] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2072.87 | bwd: 2871.32 | bwd_inner: 2808.30 | bwd_allreduce: 62.05 | step: 30.06 + 9%|▉ | 167/1859 [15:43<2:47:16, 5.93s/it] {'loss': 5.0854, 'grad_norm': 27.40382194519043, 'learning_rate': 9.90677336103719e-11, 'epoch': 0.09} + 9%|▉ | 167/1859 [15:43<2:47:16, 5.93s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-14 21:42:33,958] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 191.39 | bwd_microstep: 275.58 | bwd_inner_microstep: 275.43 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-14 21:42:34,446] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 191.48 | bwd_microstep: 277.88 | bwd_inner_microstep: 277.54 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.19 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 333 +[2025-05-14 21:42:34,712] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 104.68 | bwd_microstep: 143.68 | bwd_inner_microstep: 143.43 | bwd_allreduce_microstep: 0.08 | step_microstep: 0.11 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 833 +[2025-05-14 21:42:34,985] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 108.27 | bwd_microstep: 143.48 | bwd_inner_microstep: 143.30 | bwd_allreduce_microstep: 0.08 | step_microstep: 0.12 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 838 +[2025-05-14 21:42:35,281] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 108.76 | bwd_microstep: 167.33 | bwd_inner_microstep: 166.97 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-14 21:42:35,766] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.64 | bwd_microstep: 275.85 | bwd_inner_microstep: 275.60 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-14 21:42:36,255] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.41 | bwd_microstep: 277.67 | bwd_inner_microstep: 277.49 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-14 21:42:36,844] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.18 | optimizer_step: 18.05 +[2025-05-14 21:42:36,844] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 191.48 | bwd_microstep: 347.18 | bwd_inner_microstep: 274.60 | bwd_allreduce_microstep: 72.40 | step_microstep: 26.78 +[2025-05-14 21:42:36,845] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 1276.95 | bwd: 1908.79 | bwd_inner: 1834.74 | bwd_allreduce: 73.00 | step: 27.73 + 9%|▉ | 168/1859 [15:47<2:25:35, 5.17s/it] {'loss': 6.8057, 'grad_norm': 36.31830596923828, 'learning_rate': 9.905091393545466e-11, 'epoch': 0.09} + 9%|▉ | 168/1859 [15:47<2:25:35, 5.17s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 348 +[2025-05-14 21:42:37,090] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 82.79 | bwd_microstep: 140.21 | bwd_inner_microstep: 140.06 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.09 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 851 +[2025-05-14 21:42:37,338] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.62 | bwd_microstep: 137.68 | bwd_inner_microstep: 137.53 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-14 21:42:37,822] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.36 | bwd_microstep: 275.96 | bwd_inner_microstep: 275.82 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-14 21:42:38,303] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.05 | bwd_microstep: 275.11 | bwd_inner_microstep: 274.97 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-14 21:42:38,786] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.01 | bwd_microstep: 275.90 | bwd_inner_microstep: 275.74 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-14 21:42:39,271] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.36 | bwd_microstep: 276.11 | bwd_inner_microstep: 275.83 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1342 +[2025-05-14 21:42:39,638] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 142.14 | bwd_microstep: 207.42 | bwd_inner_microstep: 207.14 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2012 +[2025-05-14 21:42:40,242] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.25 | optimizer_step: 18.16 +[2025-05-14 21:42:40,242] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 199.62 | bwd_microstep: 359.93 | bwd_inner_microstep: 298.64 | bwd_allreduce_microstep: 61.11 | step_microstep: 26.68 +[2025-05-14 21:42:40,243] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 1279.84 | bwd: 1948.42 | bwd_inner: 1886.02 | bwd_allreduce: 61.60 | step: 27.36 + 9%|▉ | 169/1859 [15:50<2:10:33, 4.64s/it] {'loss': 3.7198, 'grad_norm': 19.1610164642334, 'learning_rate': 9.903394533976307e-11, 'epoch': 0.09} + 9%|▉ | 169/1859 [15:50<2:10:33, 4.64s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1893 +[2025-05-14 21:42:40,734] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.92 | bwd_microstep: 277.28 | bwd_inner_microstep: 277.11 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 862 +[2025-05-14 21:42:40,979] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.40 | bwd_microstep: 135.21 | bwd_inner_microstep: 135.02 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-14 21:42:41,463] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.53 | bwd_microstep: 276.00 | bwd_inner_microstep: 275.70 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-14 21:42:41,948] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.02 | bwd_microstep: 277.10 | bwd_inner_microstep: 276.78 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.11 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 860 +[2025-05-14 21:42:42,195] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.35 | bwd_microstep: 136.00 | bwd_inner_microstep: 135.85 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-14 21:42:42,681] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.59 | bwd_microstep: 277.30 | bwd_inner_microstep: 276.97 | bwd_allreduce_microstep: 0.14 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-14 21:42:43,164] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.87 | bwd_microstep: 275.00 | bwd_inner_microstep: 274.84 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-14 21:42:43,734] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.27 | optimizer_step: 17.54 +[2025-05-14 21:42:43,735] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.45 | bwd_microstep: 337.70 | bwd_inner_microstep: 276.11 | bwd_allreduce_microstep: 61.44 | step_microstep: 25.89 +[2025-05-14 21:42:43,736] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 1332.02 | bwd: 1991.66 | bwd_inner: 1928.75 | bwd_allreduce: 62.04 | step: 26.59 + 9%|▉ | 170/1859 [15:53<2:00:50, 4.29s/it] {'loss': 4.7781, 'grad_norm': 14.47048282623291, 'learning_rate': 9.901682787481453e-11, 'epoch': 0.09} + 9%|▉ | 170/1859 [15:53<2:00:50, 4.29s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1906 +[2025-05-14 21:42:44,230] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 191.26 | bwd_microstep: 278.52 | bwd_inner_microstep: 278.29 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-14 21:42:44,719] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 191.66 | bwd_microstep: 276.77 | bwd_inner_microstep: 276.42 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-14 21:42:45,208] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.66 | bwd_microstep: 277.37 | bwd_inner_microstep: 277.05 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-14 21:42:45,696] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 191.38 | bwd_microstep: 275.63 | bwd_inner_microstep: 275.45 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-14 21:42:46,183] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.14 | bwd_microstep: 274.62 | bwd_inner_microstep: 274.46 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-14 21:42:46,670] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.26 | bwd_microstep: 275.13 | bwd_inner_microstep: 274.80 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.11 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1351 +[2025-05-14 21:42:47,040] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 142.61 | bwd_microstep: 209.17 | bwd_inner_microstep: 208.88 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-14 21:42:47,627] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.07 | optimizer_gradients: 2.19 | optimizer_step: 17.88 +[2025-05-14 21:42:47,628] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.73 | bwd_microstep: 347.81 | bwd_inner_microstep: 275.22 | bwd_allreduce_microstep: 72.44 | step_microstep: 27.13 +[2025-05-14 21:42:47,629] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 1477.54 | bwd: 2215.16 | bwd_inner: 2140.99 | bwd_allreduce: 73.12 | step: 28.00 + 9%|▉ | 171/1859 [15:57<1:57:23, 4.17s/it] {'loss': 6.2062, 'grad_norm': 35.257179260253906, 'learning_rate': 9.899956159257842e-11, 'epoch': 0.09} + 9%|▉ | 171/1859 [15:57<1:57:23, 4.17s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1889 +[2025-05-14 21:42:48,123] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 191.66 | bwd_microstep: 276.90 | bwd_inner_microstep: 276.73 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1889 +[2025-05-14 21:42:48,611] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.59 | bwd_microstep: 278.16 | bwd_inner_microstep: 277.97 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-14 21:42:49,095] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.91 | bwd_microstep: 274.67 | bwd_inner_microstep: 274.47 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-14 21:42:49,581] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 191.36 | bwd_microstep: 276.47 | bwd_inner_microstep: 276.24 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-14 21:42:50,066] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.12 | bwd_microstep: 275.72 | bwd_inner_microstep: 275.35 | bwd_allreduce_microstep: 0.15 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-14 21:42:50,550] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.03 | bwd_microstep: 275.24 | bwd_inner_microstep: 274.93 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-14 21:42:51,035] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.93 | bwd_microstep: 275.63 | bwd_inner_microstep: 275.37 | bwd_allreduce_microstep: 0.08 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1985 +[2025-05-14 21:42:51,650] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.23 | optimizer_step: 18.85 +[2025-05-14 21:42:51,650] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 199.55 | bwd_microstep: 368.03 | bwd_inner_microstep: 296.80 | bwd_allreduce_microstep: 71.06 | step_microstep: 27.49 +[2025-05-14 21:42:51,651] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 1535.02 | bwd: 2300.94 | bwd_inner: 2228.32 | bwd_allreduce: 71.62 | step: 28.28 + 9%|▉ | 172/1859 [16:01<1:56:03, 4.13s/it] {'loss': 4.5907, 'grad_norm': 23.015949249267578, 'learning_rate': 9.898214654547598e-11, 'epoch': 0.09} + 9%|▉ | 172/1859 [16:01<1:56:03, 4.13s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-14 21:42:52,141] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.26 | bwd_microstep: 275.97 | bwd_inner_microstep: 275.73 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-14 21:42:52,626] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.14 | bwd_microstep: 277.80 | bwd_inner_microstep: 277.63 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-14 21:42:53,111] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.44 | bwd_microstep: 276.64 | bwd_inner_microstep: 276.50 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-14 21:42:53,596] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.82 | bwd_microstep: 275.40 | bwd_inner_microstep: 275.25 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-14 21:42:54,081] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.75 | bwd_microstep: 275.32 | bwd_inner_microstep: 275.00 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-14 21:42:54,560] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.78 | bwd_microstep: 274.73 | bwd_inner_microstep: 274.41 | bwd_allreduce_microstep: 0.14 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-14 21:42:55,042] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.30 | bwd_microstep: 273.28 | bwd_inner_microstep: 273.13 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.11 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 320 +[2025-05-14 21:42:55,394] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.19 | optimizer_step: 18.70 +[2025-05-14 21:42:55,394] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 86.22 | bwd_microstep: 223.59 | bwd_inner_microstep: 161.73 | bwd_allreduce_microstep: 61.66 | step_microstep: 27.40 +[2025-05-14 21:42:55,395] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 1415.58 | bwd: 2152.81 | bwd_inner: 2089.75 | bwd_allreduce: 62.22 | step: 28.10 + 9%|▉ | 173/1859 [16:05<1:52:45, 4.01s/it] {'loss': 6.9155, 'grad_norm': 28.80283546447754, 'learning_rate': 9.896458278638008e-11, 'epoch': 0.09} + 9%|▉ | 173/1859 [16:05<1:52:45, 4.01s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1899 +[2025-05-14 21:42:55,888] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 191.41 | bwd_microstep: 278.43 | bwd_inner_microstep: 278.26 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1883 +[2025-05-14 21:42:56,374] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 191.05 | bwd_microstep: 277.60 | bwd_inner_microstep: 277.38 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-14 21:42:56,859] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.82 | bwd_microstep: 275.82 | bwd_inner_microstep: 275.67 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-14 21:42:57,343] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.15 | bwd_microstep: 276.53 | bwd_inner_microstep: 276.39 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-14 21:42:57,827] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.09 | bwd_microstep: 275.62 | bwd_inner_microstep: 275.47 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-14 21:42:58,311] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.55 | bwd_microstep: 275.95 | bwd_inner_microstep: 275.68 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-14 21:42:58,796] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.61 | bwd_microstep: 276.46 | bwd_inner_microstep: 276.14 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-14 21:42:59,366] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.93 | optimizer_step: 17.61 +[2025-05-14 21:42:59,366] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.71 | bwd_microstep: 336.40 | bwd_inner_microstep: 274.71 | bwd_allreduce_microstep: 61.60 | step_microstep: 26.76 +[2025-05-14 21:42:59,367] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 1524.29 | bwd: 2272.89 | bwd_inner: 2210.00 | bwd_allreduce: 62.10 | step: 27.43 + 9%|▉ | 174/1859 [16:09<1:52:20, 4.00s/it] {'loss': 5.6875, 'grad_norm': 41.57365798950195, 'learning_rate': 9.894687036861503e-11, 'epoch': 0.09} + 9%|▉ | 174/1859 [16:09<1:52:20, 4.00s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1964 +[2025-05-14 21:42:59,883] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 198.81 | bwd_microstep: 293.41 | bwd_inner_microstep: 293.25 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1951 +[2025-05-14 21:43:00,391] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 197.20 | bwd_microstep: 292.93 | bwd_inner_microstep: 292.66 | bwd_allreduce_microstep: 0.10 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1904 +[2025-05-14 21:43:00,878] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 191.17 | bwd_microstep: 278.55 | bwd_inner_microstep: 278.24 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.10 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 348 +[2025-05-14 21:43:01,126] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 87.43 | bwd_microstep: 143.74 | bwd_inner_microstep: 143.47 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-14 21:43:01,612] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.91 | bwd_microstep: 277.53 | bwd_inner_microstep: 277.38 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-14 21:43:02,097] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 191.29 | bwd_microstep: 275.50 | bwd_inner_microstep: 275.33 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-14 21:43:02,576] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.83 | bwd_microstep: 274.48 | bwd_inner_microstep: 274.34 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-14 21:43:03,146] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.26 | optimizer_step: 18.27 +[2025-05-14 21:43:03,147] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.01 | bwd_microstep: 336.55 | bwd_inner_microstep: 275.41 | bwd_allreduce_microstep: 60.98 | step_microstep: 26.99 +[2025-05-14 21:43:03,147] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 1435.55 | bwd: 2172.76 | bwd_inner: 2110.44 | bwd_allreduce: 61.48 | step: 27.69 + 9%|▉ | 175/1859 [16:13<1:50:25, 3.93s/it] {'loss': 4.0494, 'grad_norm': 12.918890953063965, 'learning_rate': 9.892900934595657e-11, 'epoch': 0.09} + 9%|▉ | 175/1859 [16:13<1:50:25, 3.93s/it]dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1403 +[2025-05-14 21:43:03,528] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 144.64 | bwd_microstep: 212.37 | bwd_inner_microstep: 212.10 | bwd_allreduce_microstep: 0.09 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-14 21:43:04,015] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 191.10 | bwd_microstep: 276.75 | bwd_inner_microstep: 276.60 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1115 +[2025-05-14 21:43:04,314] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 116.92 | bwd_microstep: 165.05 | bwd_inner_microstep: 164.90 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-14 21:43:04,797] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.08 | bwd_microstep: 275.27 | bwd_inner_microstep: 275.12 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-14 21:43:05,280] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.09 | bwd_microstep: 275.02 | bwd_inner_microstep: 274.70 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.10 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 330 +[2025-05-14 21:43:05,517] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 82.01 | bwd_microstep: 141.69 | bwd_inner_microstep: 141.43 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-14 21:43:06,000] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.39 | bwd_microstep: 275.65 | bwd_inner_microstep: 275.48 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-14 21:43:06,574] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.26 | optimizer_step: 18.69 +[2025-05-14 21:43:06,575] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.15 | bwd_microstep: 338.39 | bwd_inner_microstep: 275.85 | bwd_allreduce_microstep: 62.40 | step_microstep: 27.40 +[2025-05-14 21:43:06,575] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 1292.26 | bwd: 1960.27 | bwd_inner: 1896.53 | bwd_allreduce: 62.89 | step: 28.11 + 9%|▉ | 176/1859 [16:16<1:46:05, 3.78s/it] {'loss': 4.2363, 'grad_norm': 16.551984786987305, 'learning_rate': 9.891099977263157e-11, 'epoch': 0.09} + 9%|▉ | 176/1859 [16:16<1:46:05, 3.78s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-14 21:43:07,065] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 191.03 | bwd_microstep: 275.63 | bwd_inner_microstep: 275.45 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-14 21:43:07,550] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.22 | bwd_microstep: 275.50 | bwd_inner_microstep: 275.36 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-14 21:43:08,035] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.83 | bwd_microstep: 275.33 | bwd_inner_microstep: 274.98 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.21 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-14 21:43:08,520] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.43 | bwd_microstep: 274.59 | bwd_inner_microstep: 274.42 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-14 21:43:09,005] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.57 | bwd_microstep: 275.14 | bwd_inner_microstep: 274.98 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-14 21:43:09,489] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.09 | bwd_microstep: 275.80 | bwd_inner_microstep: 275.50 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 836 +[2025-05-14 21:43:09,746] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 106.43 | bwd_microstep: 133.07 | bwd_inner_microstep: 132.74 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-14 21:43:10,320] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.07 | optimizer_gradients: 1.86 | optimizer_step: 13.14 +[2025-05-14 21:43:10,320] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.48 | bwd_microstep: 344.03 | bwd_inner_microstep: 273.77 | bwd_allreduce_microstep: 70.11 | step_microstep: 20.86 +[2025-05-14 21:43:10,321] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 1435.95 | bwd: 2129.20 | bwd_inner: 2057.60 | bwd_allreduce: 70.71 | step: 21.70 + 10%|▉ | 177/1859 [16:20<1:45:43, 3.77s/it] {'loss': 6.408, 'grad_norm': 29.756589889526367, 'learning_rate': 9.889284170331785e-11, 'epoch': 0.1} + 10%|▉ | 177/1859 [16:20<1:45:43, 3.77s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-14 21:43:10,813] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.75 | bwd_microstep: 277.33 | bwd_inner_microstep: 277.04 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-14 21:43:11,299] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.03 | bwd_microstep: 277.23 | bwd_inner_microstep: 277.08 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.12 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 332 +[2025-05-14 21:43:11,553] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 97.27 | bwd_microstep: 139.89 | bwd_inner_microstep: 139.69 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.12 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 840 +[2025-05-14 21:43:11,815] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 102.77 | bwd_microstep: 140.21 | bwd_inner_microstep: 140.01 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-14 21:43:12,301] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.71 | bwd_microstep: 275.67 | bwd_inner_microstep: 275.36 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.11 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 322 +[2025-05-14 21:43:12,568] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.83 | bwd_microstep: 153.25 | bwd_inner_microstep: 152.92 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-14 21:43:13,054] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.73 | bwd_microstep: 275.35 | bwd_inner_microstep: 274.99 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.17 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 317 +[2025-05-14 21:43:13,403] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.13 | optimizer_step: 18.03 +[2025-05-14 21:43:13,403] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.82 | bwd_microstep: 208.41 | bwd_inner_microstep: 138.63 | bwd_allreduce_microstep: 69.62 | step_microstep: 26.88 +[2025-05-14 21:43:13,404] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 1150.75 | bwd: 1747.48 | bwd_inner: 1676.18 | bwd_allreduce: 70.30 | step: 27.73 + 10%|▉ | 178/1859 [16:23<1:39:53, 3.57s/it] {'loss': 5.9207, 'grad_norm': 50.19845962524414, 'learning_rate': 9.887453519314418e-11, 'epoch': 0.1} + 10%|▉ | 178/1859 [16:23<1:39:53, 3.57s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1890 +[2025-05-14 21:43:13,899] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.89 | bwd_microstep: 276.61 | bwd_inner_microstep: 276.43 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1903 +[2025-05-14 21:43:14,394] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 192.83 | bwd_microstep: 279.51 | bwd_inner_microstep: 279.13 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.17 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1890 +[2025-05-14 21:43:14,883] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 191.13 | bwd_microstep: 277.46 | bwd_inner_microstep: 277.29 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-14 21:43:15,372] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.99 | bwd_microstep: 275.54 | bwd_inner_microstep: 275.38 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-14 21:43:15,873] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.85 | bwd_microstep: 290.08 | bwd_inner_microstep: 289.93 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 324 +[2025-05-14 21:43:16,131] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 90.68 | bwd_microstep: 151.68 | bwd_inner_microstep: 151.42 | bwd_allreduce_microstep: 0.09 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-14 21:43:16,636] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 194.80 | bwd_microstep: 289.49 | bwd_inner_microstep: 289.34 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-14 21:43:17,246] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.21 | optimizer_gradients: 2.28 | optimizer_step: 21.76 +[2025-05-14 21:43:17,247] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 197.40 | bwd_microstep: 362.82 | bwd_inner_microstep: 291.96 | bwd_allreduce_microstep: 70.76 | step_microstep: 32.10 +[2025-05-14 21:43:17,248] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 1438.42 | bwd: 2203.32 | bwd_inner: 2131.16 | bwd_allreduce: 71.26 | step: 32.90 + 10%|▉ | 179/1859 [16:27<1:42:09, 3.65s/it] {'loss': 5.3393, 'grad_norm': 22.279247283935547, 'learning_rate': 9.885608029768991e-11, 'epoch': 0.1} + 10%|▉ | 179/1859 [16:27<1:42:09, 3.65s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1894 +[2025-05-14 21:43:17,761] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.37 | bwd_microstep: 292.71 | bwd_inner_microstep: 292.36 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.21 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-14 21:43:18,491] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 295.81 | bwd_microstep: 414.54 | bwd_inner_microstep: 414.21 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-14 21:43:19,195] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 302.46 | bwd_microstep: 382.91 | bwd_inner_microstep: 382.64 | bwd_allreduce_microstep: 0.10 | step_microstep: 0.17 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-14 21:43:20,112] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 401.43 | bwd_microstep: 493.86 | bwd_inner_microstep: 493.54 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-14 21:43:21,024] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 381.92 | bwd_microstep: 510.22 | bwd_inner_microstep: 509.81 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.24 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 333 +[2025-05-14 21:43:21,282] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 87.48 | bwd_microstep: 152.34 | bwd_inner_microstep: 152.28 | bwd_allreduce_microstep: 0.02 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-14 21:43:22,147] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 322.54 | bwd_microstep: 507.85 | bwd_inner_microstep: 507.80 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2036 +[2025-05-14 21:43:22,772] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.21 | optimizer_step: 17.74 +[2025-05-14 21:43:22,773] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 201.63 | bwd_microstep: 371.92 | bwd_inner_microstep: 310.00 | bwd_allreduce_microstep: 61.76 | step_microstep: 25.84 +[2025-05-14 21:43:22,773] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2188.53 | bwd: 3126.45 | bwd_inner: 3062.92 | bwd_allreduce: 62.28 | step: 31.40 + 10%|▉ | 180/1859 [16:33<1:57:51, 4.21s/it] {'loss': 7.5056, 'grad_norm': 44.20063781738281, 'learning_rate': 9.883747707298497e-11, 'epoch': 0.1} + 10%|▉ | 180/1859 [16:33<1:57:51, 4.21s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1912 +[2025-05-14 21:43:23,343] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 200.59 | bwd_microstep: 342.41 | bwd_inner_microstep: 342.37 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1890 +[2025-05-14 21:43:24,217] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 325.59 | bwd_microstep: 522.89 | bwd_inner_microstep: 522.84 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.61 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1888 +[2025-05-14 21:43:25,087] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 317.32 | bwd_microstep: 518.93 | bwd_inner_microstep: 518.89 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.32 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-14 21:43:25,955] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 320.72 | bwd_microstep: 510.28 | bwd_inner_microstep: 510.23 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.61 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-14 21:43:26,827] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 320.63 | bwd_microstep: 519.39 | bwd_inner_microstep: 518.99 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-14 21:43:27,518] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 283.98 | bwd_microstep: 375.80 | bwd_inner_microstep: 375.77 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.33 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-14 21:43:28,399] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 323.02 | bwd_microstep: 524.22 | bwd_inner_microstep: 523.97 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-14 21:43:29,525] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.01 | optimizer_gradients: 2.15 | optimizer_step: 18.93 +[2025-05-14 21:43:29,527] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 326.01 | bwd_microstep: 743.01 | bwd_inner_microstep: 518.71 | bwd_allreduce_microstep: 224.23 | step_microstep: 29.31 +[2025-05-14 21:43:29,527] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2417.81 | bwd: 4056.93 | bwd_inner: 3832.05 | bwd_allreduce: 224.54 | step: 41.91 + 10%|▉ | 181/1859 [16:39<2:19:08, 4.98s/it] {'loss': 2.7464, 'grad_norm': 4.251251220703125, 'learning_rate': 9.881872557550952e-11, 'epoch': 0.1} + 10%|▉ | 181/1859 [16:39<2:19:08, 4.98s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 339 +[2025-05-14 21:43:29,827] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 103.18 | bwd_microstep: 155.01 | bwd_inner_microstep: 154.59 | bwd_allreduce_microstep: 0.15 | step_microstep: 0.13 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1892 +[2025-05-14 21:43:30,750] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 400.17 | bwd_microstep: 496.30 | bwd_inner_microstep: 496.14 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.12 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 854 +[2025-05-14 21:43:31,208] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 185.60 | bwd_microstep: 253.26 | bwd_inner_microstep: 253.10 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-14 21:43:32,128] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 391.04 | bwd_microstep: 507.58 | bwd_inner_microstep: 507.42 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 851 +[2025-05-14 21:43:32,584] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 154.09 | bwd_microstep: 283.81 | bwd_inner_microstep: 283.37 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.24 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-14 21:43:33,482] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 349.81 | bwd_microstep: 525.69 | bwd_inner_microstep: 525.65 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-14 21:43:34,352] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 324.00 | bwd_microstep: 521.12 | bwd_inner_microstep: 521.07 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-14 21:43:35,276] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.04 | optimizer_gradients: 2.86 | optimizer_step: 12.74 +[2025-05-14 21:43:35,276] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 320.10 | bwd_microstep: 549.70 | bwd_inner_microstep: 490.77 | bwd_allreduce_microstep: 58.75 | step_microstep: 20.23 +[2025-05-14 21:43:35,277] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2227.94 | bwd: 3292.55 | bwd_inner: 3232.32 | bwd_allreduce: 59.13 | step: 25.62 + 10%|▉ | 182/1859 [16:45<2:25:30, 5.21s/it] {'loss': 4.6629, 'grad_norm': 13.257210731506348, 'learning_rate': 9.879982586219401e-11, 'epoch': 0.1} + 10%|▉ | 182/1859 [16:45<2:25:30, 5.21s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1944 +[2025-05-14 21:43:36,097] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 288.11 | bwd_microstep: 511.33 | bwd_inner_microstep: 511.00 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.19 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1363 +[2025-05-14 21:43:36,681] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 175.87 | bwd_microstep: 390.24 | bwd_inner_microstep: 389.83 | bwd_allreduce_microstep: 0.16 | step_microstep: 0.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-14 21:43:37,592] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 398.01 | bwd_microstep: 492.07 | bwd_inner_microstep: 491.80 | bwd_allreduce_microstep: 0.08 | step_microstep: 0.10 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 839 +[2025-05-14 21:43:38,039] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 173.22 | bwd_microstep: 254.13 | bwd_inner_microstep: 253.83 | bwd_allreduce_microstep: 0.14 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-14 21:43:38,944] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 368.59 | bwd_microstep: 516.12 | bwd_inner_microstep: 516.08 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.21 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-14 21:43:39,806] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 320.33 | bwd_microstep: 520.37 | bwd_inner_microstep: 520.31 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.37 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-14 21:43:40,672] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 310.01 | bwd_microstep: 519.02 | bwd_inner_microstep: 518.96 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.28 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-14 21:43:41,761] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.01 | optimizer_gradients: 2.90 | optimizer_step: 20.13 +[2025-05-14 21:43:41,763] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 311.37 | bwd_microstep: 716.14 | bwd_inner_microstep: 515.41 | bwd_allreduce_microstep: 200.70 | step_microstep: 30.27 +[2025-05-14 21:43:41,764] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2345.45 | bwd: 3919.52 | bwd_inner: 3717.48 | bwd_allreduce: 201.21 | step: 35.81 + 10%|▉ | 183/1859 [16:52<2:36:12, 5.59s/it] {'loss': 7.2683, 'grad_norm': 34.22819900512695, 'learning_rate': 9.878077799041877e-11, 'epoch': 0.1} + 10%|▉ | 183/1859 [16:52<2:36:12, 5.59s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1887 +[2025-05-14 21:43:42,680] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 340.13 | bwd_microstep: 533.83 | bwd_inner_microstep: 533.79 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.37 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-14 21:43:43,502] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 334.64 | bwd_microstep: 459.17 | bwd_inner_microstep: 459.02 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1891 +[2025-05-14 21:43:44,203] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 191.23 | bwd_microstep: 494.40 | bwd_inner_microstep: 494.13 | bwd_allreduce_microstep: 0.24 | step_microstep: 0.24 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-14 21:43:45,074] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 338.91 | bwd_microstep: 509.66 | bwd_inner_microstep: 509.63 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.31 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-14 21:43:45,947] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 317.25 | bwd_microstep: 521.28 | bwd_inner_microstep: 521.24 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 842 +[2025-05-14 21:43:46,384] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 130.03 | bwd_microstep: 274.40 | bwd_inner_microstep: 274.38 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.32 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-14 21:43:47,198] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 259.31 | bwd_microstep: 518.01 | bwd_inner_microstep: 517.97 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.37 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-14 21:43:48,438] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.01 | optimizer_gradients: 2.30 | optimizer_step: 20.82 +[2025-05-14 21:43:48,440] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 328.83 | bwd_microstep: 846.56 | bwd_inner_microstep: 527.19 | bwd_allreduce_microstep: 319.34 | step_microstep: 32.90 +[2025-05-14 21:43:48,441] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2240.28 | bwd: 4157.32 | bwd_inner: 3837.37 | bwd_allreduce: 319.68 | step: 44.97 + 10%|▉ | 184/1859 [16:58<2:45:11, 5.92s/it] {'loss': 4.3059, 'grad_norm': 19.712343215942383, 'learning_rate': 9.876158201801403e-11, 'epoch': 0.1} + 10%|▉ | 184/1859 [16:58<2:45:11, 5.92s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1893 +[2025-05-14 21:43:49,335] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 322.32 | bwd_microstep: 525.07 | bwd_inner_microstep: 525.02 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.32 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 353 +[2025-05-14 21:43:49,625] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 106.12 | bwd_microstep: 149.60 | bwd_inner_microstep: 149.55 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1097 +[2025-05-14 21:43:50,190] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 217.52 | bwd_microstep: 318.39 | bwd_inner_microstep: 318.34 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.45 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-14 21:43:51,067] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 319.06 | bwd_microstep: 523.43 | bwd_inner_microstep: 523.40 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-14 21:43:51,930] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 316.01 | bwd_microstep: 514.52 | bwd_inner_microstep: 514.49 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.99 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 323 +[2025-05-14 21:43:52,159] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 83.32 | bwd_microstep: 128.26 | bwd_inner_microstep: 128.22 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.32 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-14 21:43:53,002] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 307.83 | bwd_microstep: 498.26 | bwd_inner_microstep: 498.22 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.48 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-14 21:43:54,127] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.01 | optimizer_gradients: 2.15 | optimizer_step: 18.81 +[2025-05-14 21:43:54,128] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 301.32 | bwd_microstep: 762.61 | bwd_inner_microstep: 523.40 | bwd_allreduce_microstep: 239.18 | step_microstep: 28.25 +[2025-05-14 21:43:54,129] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 1973.47 | bwd: 3420.13 | bwd_inner: 3180.65 | bwd_allreduce: 239.25 | step: 43.54 + 10%|▉ | 185/1859 [17:04<2:43:10, 5.85s/it] {'loss': 5.6521, 'grad_norm': 28.408668518066406, 'learning_rate': 9.87422380032596e-11, 'epoch': 0.1} + 10%|▉ | 185/1859 [17:04<2:43:10, 5.85s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-14 21:43:55,014] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 326.24 | bwd_microstep: 519.23 | bwd_inner_microstep: 519.21 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-14 21:43:55,900] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 329.37 | bwd_microstep: 526.25 | bwd_inner_microstep: 526.21 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.37 +dynamic ViT batch size: 6, images per sample: 6.0, dynamic token length: 1612 +[2025-05-14 21:43:56,683] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 286.07 | bwd_microstep: 463.81 | bwd_inner_microstep: 463.39 | bwd_allreduce_microstep: 0.16 | step_microstep: 0.23 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-14 21:43:57,603] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 405.45 | bwd_microstep: 495.23 | bwd_inner_microstep: 494.98 | bwd_allreduce_microstep: 0.10 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-14 21:43:58,494] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 348.50 | bwd_microstep: 518.96 | bwd_inner_microstep: 518.92 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.32 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-14 21:43:59,366] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 322.62 | bwd_microstep: 520.99 | bwd_inner_microstep: 520.95 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.57 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-14 21:44:00,237] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 309.47 | bwd_microstep: 525.63 | bwd_inner_microstep: 525.60 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.28 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1952 +[2025-05-14 21:44:01,340] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.01 | optimizer_gradients: 2.16 | optimizer_step: 18.74 +[2025-05-14 21:44:01,341] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 244.23 | bwd_microstep: 799.12 | bwd_inner_microstep: 554.43 | bwd_allreduce_microstep: 244.64 | step_microstep: 29.10 +[2025-05-14 21:44:01,342] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2571.91 | bwd: 4369.31 | bwd_inner: 4123.85 | bwd_allreduce: 244.92 | step: 41.33 + 10%|█ | 186/1859 [17:11<2:54:29, 6.26s/it] {'loss': 7.2136, 'grad_norm': 25.948720932006836, 'learning_rate': 9.872274600488479e-11, 'epoch': 0.1} + 10%|█ | 186/1859 [17:11<2:54:29, 6.26s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 516 +[2025-05-14 21:44:01,645] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 121.14 | bwd_microstep: 141.00 | bwd_inner_microstep: 140.65 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.17 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 855 +[2025-05-14 21:44:02,108] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 177.27 | bwd_microstep: 266.53 | bwd_inner_microstep: 266.16 | bwd_allreduce_microstep: 0.14 | step_microstep: 0.20 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 334 +[2025-05-14 21:44:02,384] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 107.08 | bwd_microstep: 148.76 | bwd_inner_microstep: 148.70 | bwd_allreduce_microstep: 0.02 | step_microstep: 2.55 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 837 +[2025-05-14 21:44:02,843] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 147.85 | bwd_microstep: 278.82 | bwd_inner_microstep: 278.76 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.57 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-14 21:44:03,641] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 306.46 | bwd_microstep: 456.43 | bwd_inner_microstep: 456.40 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.37 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 329 +[2025-05-14 21:44:03,951] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 111.87 | bwd_microstep: 164.01 | bwd_inner_microstep: 163.97 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.33 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-14 21:44:04,831] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 333.51 | bwd_microstep: 509.35 | bwd_inner_microstep: 509.30 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 915 +[2025-05-14 21:44:05,683] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.01 | optimizer_gradients: 2.24 | optimizer_step: 18.61 +[2025-05-14 21:44:05,686] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 223.01 | bwd_microstep: 567.33 | bwd_inner_microstep: 238.37 | bwd_allreduce_microstep: 328.93 | step_microstep: 32.55 +[2025-05-14 21:44:05,686] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 1528.14 | bwd: 2532.31 | bwd_inner: 2202.45 | bwd_allreduce: 329.26 | step: 45.02 + 10%|█ | 187/1859 [17:15<2:38:23, 5.68s/it] {'loss': 5.1177, 'grad_norm': 36.41313552856445, 'learning_rate': 9.870310608206817e-11, 'epoch': 0.1} + 10%|█ | 187/1859 [17:15<2:38:23, 5.68s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1959 +[2025-05-14 21:44:06,632] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 340.64 | bwd_microstep: 559.12 | bwd_inner_microstep: 559.07 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.32 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1893 +[2025-05-14 21:44:07,522] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 322.94 | bwd_microstep: 533.60 | bwd_inner_microstep: 533.57 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 345 +[2025-05-14 21:44:07,817] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 97.50 | bwd_microstep: 165.22 | bwd_inner_microstep: 165.19 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.32 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1361 +[2025-05-14 21:44:08,491] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 222.32 | bwd_microstep: 418.87 | bwd_inner_microstep: 418.69 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-14 21:44:09,347] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 313.12 | bwd_microstep: 521.72 | bwd_inner_microstep: 521.69 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.47 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1355 +[2025-05-14 21:44:09,983] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 222.27 | bwd_microstep: 371.76 | bwd_inner_microstep: 371.72 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-14 21:44:10,859] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 348.80 | bwd_microstep: 493.67 | bwd_inner_microstep: 493.26 | bwd_allreduce_microstep: 0.15 | step_microstep: 0.21 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-14 21:44:12,073] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.14 | optimizer_step: 19.39 +[2025-05-14 21:44:12,075] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 377.07 | bwd_microstep: 783.40 | bwd_inner_microstep: 490.32 | bwd_allreduce_microstep: 292.95 | step_microstep: 28.82 +[2025-05-14 21:44:12,075] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2242.28 | bwd: 3847.41 | bwd_inner: 3553.66 | bwd_allreduce: 293.20 | step: 40.96 + 10%|█ | 188/1859 [17:22<2:44:10, 5.90s/it] {'loss': 5.3432, 'grad_norm': 20.294124603271484, 'learning_rate': 9.868331829443744e-11, 'epoch': 0.1} + 10%|█ | 188/1859 [17:22<2:44:10, 5.90s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1895 +[2025-05-14 21:44:12,977] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 342.90 | bwd_microstep: 514.37 | bwd_inner_microstep: 514.32 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.29 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-14 21:44:13,863] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 345.20 | bwd_microstep: 504.24 | bwd_inner_microstep: 504.19 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 850 +[2025-05-14 21:44:14,312] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 206.94 | bwd_microstep: 207.38 | bwd_inner_microstep: 207.34 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-14 21:44:15,190] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 342.06 | bwd_microstep: 501.58 | bwd_inner_microstep: 501.54 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-14 21:44:16,084] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 365.98 | bwd_microstep: 495.19 | bwd_inner_microstep: 494.98 | bwd_allreduce_microstep: 0.08 | step_microstep: 0.14 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-14 21:44:16,897] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 401.41 | bwd_microstep: 392.00 | bwd_inner_microstep: 391.66 | bwd_allreduce_microstep: 0.14 | step_microstep: 0.10 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 323 +[2025-05-14 21:44:17,130] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.65 | bwd_microstep: 123.14 | bwd_inner_microstep: 122.88 | bwd_allreduce_microstep: 0.24 | step_microstep: 0.40 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-14 21:44:18,322] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.01 | optimizer_gradients: 3.04 | optimizer_step: 18.24 +[2025-05-14 21:44:18,323] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 343.94 | bwd_microstep: 800.11 | bwd_inner_microstep: 521.99 | bwd_allreduce_microstep: 278.08 | step_microstep: 30.79 +[2025-05-14 21:44:18,324] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2444.01 | bwd: 3538.03 | bwd_inner: 3259.00 | bwd_allreduce: 278.58 | step: 40.77 + 10%|█ | 189/1859 [17:28<2:47:00, 6.00s/it] {'loss': 6.2677, 'grad_norm': 36.268863677978516, 'learning_rate': 9.86633827020692e-11, 'epoch': 0.1} + 10%|█ | 189/1859 [17:28<2:47:00, 6.00s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1919 +[2025-05-14 21:44:19,212] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 332.99 | bwd_microstep: 528.91 | bwd_inner_microstep: 528.88 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1887 +[2025-05-14 21:44:20,042] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 328.16 | bwd_microstep: 466.32 | bwd_inner_microstep: 466.28 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-14 21:44:20,928] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 334.72 | bwd_microstep: 517.66 | bwd_inner_microstep: 515.26 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.37 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 339 +[2025-05-14 21:44:21,209] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 103.93 | bwd_microstep: 142.74 | bwd_inner_microstep: 142.70 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.32 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-14 21:44:22,087] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 345.31 | bwd_microstep: 498.00 | bwd_inner_microstep: 497.96 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1095 +[2025-05-14 21:44:22,652] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 259.58 | bwd_microstep: 275.70 | bwd_inner_microstep: 275.47 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-14 21:44:23,531] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 332.16 | bwd_microstep: 515.56 | bwd_inner_microstep: 515.53 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-14 21:44:24,665] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.01 | optimizer_gradients: 2.17 | optimizer_step: 18.69 +[2025-05-14 21:44:24,666] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 335.14 | bwd_microstep: 738.14 | bwd_inner_microstep: 510.88 | bwd_allreduce_microstep: 227.20 | step_microstep: 27.41 +[2025-05-14 21:44:24,667] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2371.97 | bwd: 3683.06 | bwd_inner: 3452.96 | bwd_allreduce: 227.39 | step: 41.79 + 10%|█ | 190/1859 [17:34<2:49:47, 6.10s/it] {'loss': 6.3888, 'grad_norm': 22.69805335998535, 'learning_rate': 9.864329936548879e-11, 'epoch': 0.1} + 10%|█ | 190/1859 [17:34<2:49:47, 6.10s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1892 +[2025-05-14 21:44:25,440] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 320.52 | bwd_microstep: 407.83 | bwd_inner_microstep: 407.80 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1898 +[2025-05-14 21:44:26,322] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 324.41 | bwd_microstep: 522.82 | bwd_inner_microstep: 522.78 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1883 +[2025-05-14 21:44:27,196] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 323.48 | bwd_microstep: 513.34 | bwd_inner_microstep: 513.31 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.33 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-14 21:44:28,082] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 330.44 | bwd_microstep: 521.98 | bwd_inner_microstep: 521.93 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.17 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-14 21:44:28,969] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 334.60 | bwd_microstep: 519.38 | bwd_inner_microstep: 519.35 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 838 +[2025-05-14 21:44:29,408] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 196.07 | bwd_microstep: 212.43 | bwd_inner_microstep: 211.94 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.18 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1342 +[2025-05-14 21:44:30,096] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 239.10 | bwd_microstep: 421.21 | bwd_inner_microstep: 421.06 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.09 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1504 +[2025-05-14 21:44:31,045] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.01 | optimizer_gradients: 2.18 | optimizer_step: 18.89 +[2025-05-14 21:44:31,046] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 262.97 | bwd_microstep: 638.67 | bwd_inner_microstep: 430.39 | bwd_allreduce_microstep: 208.22 | step_microstep: 28.97 +[2025-05-14 21:44:31,047] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2331.55 | bwd: 3757.69 | bwd_inner: 3548.67 | bwd_allreduce: 208.47 | step: 40.80 + 10%|█ | 191/1859 [17:41<2:51:59, 6.19s/it] {'loss': 5.5335, 'grad_norm': 21.414472579956055, 'learning_rate': 9.862306834567015e-11, 'epoch': 0.1} + 10%|█ | 191/1859 [17:41<2:51:59, 6.19s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1920 +[2025-05-14 21:44:31,958] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 335.62 | bwd_microstep: 528.72 | bwd_inner_microstep: 528.68 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.37 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1892 +[2025-05-14 21:44:32,853] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 333.10 | bwd_microstep: 525.57 | bwd_inner_microstep: 525.54 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.59 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-14 21:44:33,693] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 314.11 | bwd_microstep: 493.89 | bwd_inner_microstep: 493.73 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-14 21:44:34,587] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 371.35 | bwd_microstep: 492.02 | bwd_inner_microstep: 491.74 | bwd_allreduce_microstep: 0.10 | step_microstep: 0.14 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-14 21:44:35,509] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 401.53 | bwd_microstep: 498.30 | bwd_inner_microstep: 497.98 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-14 21:44:36,419] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 388.95 | bwd_microstep: 499.81 | bwd_inner_microstep: 499.52 | bwd_allreduce_microstep: 0.27 | step_microstep: 0.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-14 21:44:37,303] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 343.61 | bwd_microstep: 517.40 | bwd_inner_microstep: 517.35 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.46 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-14 21:44:38,543] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.30 | optimizer_step: 17.99 +[2025-05-14 21:44:38,543] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 327.01 | bwd_microstep: 855.99 | bwd_inner_microstep: 522.62 | bwd_allreduce_microstep: 333.35 | step_microstep: 28.18 +[2025-05-14 21:44:38,544] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2815.21 | bwd: 4411.74 | bwd_inner: 4077.32 | bwd_allreduce: 333.92 | step: 36.32 + 10%|█ | 192/1859 [17:48<3:02:47, 6.58s/it] {'loss': 5.8364, 'grad_norm': 37.60972213745117, 'learning_rate': 9.860268970403554e-11, 'epoch': 0.1} + 10%|█ | 192/1859 [17:48<3:02:47, 6.58s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 379 +[2025-05-14 21:44:38,820] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 106.24 | bwd_microstep: 145.51 | bwd_inner_microstep: 145.46 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.28 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-14 21:44:39,695] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 327.48 | bwd_microstep: 513.10 | bwd_inner_microstep: 513.06 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 847 +[2025-05-14 21:44:40,146] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 174.54 | bwd_microstep: 244.32 | bwd_inner_microstep: 244.27 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.61 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 844 +[2025-05-14 21:44:40,605] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 159.84 | bwd_microstep: 267.80 | bwd_inner_microstep: 267.75 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-14 21:44:41,444] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 321.92 | bwd_microstep: 480.27 | bwd_inner_microstep: 479.98 | bwd_allreduce_microstep: 0.23 | step_microstep: 2.37 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-14 21:44:42,328] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 329.95 | bwd_microstep: 518.16 | bwd_inner_microstep: 518.14 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.50 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-14 21:44:43,193] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 317.12 | bwd_microstep: 516.13 | bwd_inner_microstep: 516.09 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.54 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 2025 +[2025-05-14 21:44:44,433] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.01 | optimizer_gradients: 2.30 | optimizer_step: 16.39 +[2025-05-14 21:44:44,435] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 316.06 | bwd_microstep: 868.75 | bwd_inner_microstep: 577.23 | bwd_allreduce_microstep: 291.50 | step_microstep: 30.23 +[2025-05-14 21:44:44,436] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2053.13 | bwd: 3554.04 | bwd_inner: 3261.99 | bwd_allreduce: 291.57 | step: 46.09 + 10%|█ | 193/1859 [17:54<2:56:58, 6.37s/it] {'loss': 5.2125, 'grad_norm': 29.363000869750977, 'learning_rate': 9.858216350245544e-11, 'epoch': 0.1} + 10%|█ | 193/1859 [17:54<2:56:58, 6.37s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1886 +[2025-05-14 21:44:45,314] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 327.24 | bwd_microstep: 508.29 | bwd_inner_microstep: 508.24 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-14 21:44:46,192] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 333.84 | bwd_microstep: 509.75 | bwd_inner_microstep: 509.70 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.37 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-14 21:44:47,032] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 336.93 | bwd_microstep: 471.32 | bwd_inner_microstep: 470.99 | bwd_allreduce_microstep: 0.14 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-14 21:44:47,912] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 353.54 | bwd_microstep: 507.21 | bwd_inner_microstep: 507.12 | bwd_allreduce_microstep: 0.03 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-14 21:44:48,798] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 332.88 | bwd_microstep: 524.73 | bwd_inner_microstep: 524.46 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.21 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-14 21:44:49,602] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 337.47 | bwd_microstep: 444.08 | bwd_inner_microstep: 444.05 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.32 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-14 21:44:50,397] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 245.59 | bwd_microstep: 527.68 | bwd_inner_microstep: 527.64 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.37 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 832 +[2025-05-14 21:44:51,187] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.29 | optimizer_step: 20.70 +[2025-05-14 21:44:51,189] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 203.62 | bwd_microstep: 524.67 | bwd_inner_microstep: 209.52 | bwd_allreduce_microstep: 315.11 | step_microstep: 31.36 +[2025-05-14 21:44:51,190] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2471.06 | bwd: 4017.98 | bwd_inner: 3701.81 | bwd_allreduce: 315.32 | step: 41.19 + 10%|█ | 194/1859 [18:01<3:00:01, 6.49s/it] {'loss': 5.0876, 'grad_norm': 31.038009643554688, 'learning_rate': 9.856148980324832e-11, 'epoch': 0.1} + 10%|█ | 194/1859 [18:01<3:00:01, 6.49s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-14 21:44:52,069] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 322.55 | bwd_microstep: 513.95 | bwd_inner_microstep: 513.88 | bwd_allreduce_microstep: 0.02 | step_microstep: 2.38 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-14 21:44:52,947] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 332.48 | bwd_microstep: 510.50 | bwd_inner_microstep: 510.46 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-14 21:44:53,827] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 320.54 | bwd_microstep: 527.32 | bwd_inner_microstep: 527.28 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.19 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 332 +[2025-05-14 21:44:54,120] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 116.38 | bwd_microstep: 146.67 | bwd_inner_microstep: 146.63 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-14 21:44:54,995] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 335.59 | bwd_microstep: 503.24 | bwd_inner_microstep: 503.19 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 328 +[2025-05-14 21:44:55,280] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 117.23 | bwd_microstep: 136.58 | bwd_inner_microstep: 136.31 | bwd_allreduce_microstep: 0.23 | step_microstep: 0.24 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1351 +[2025-05-14 21:44:55,895] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 226.22 | bwd_microstep: 369.95 | bwd_inner_microstep: 369.91 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-14 21:44:57,108] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.22 | optimizer_step: 18.62 +[2025-05-14 21:44:57,109] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 330.61 | bwd_microstep: 818.37 | bwd_inner_microstep: 507.07 | bwd_allreduce_microstep: 311.27 | step_microstep: 30.50 +[2025-05-14 21:44:57,110] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2101.61 | bwd: 3526.59 | bwd_inner: 3214.75 | bwd_allreduce: 311.36 | step: 42.75 + 10%|█ | 195/1859 [18:07<2:55:11, 6.32s/it] {'loss': 5.4692, 'grad_norm': 22.423614501953125, 'learning_rate': 9.854066866918046e-11, 'epoch': 0.1} + 10%|█ | 195/1859 [18:07<2:55:11, 6.32s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1895 +[2025-05-14 21:44:57,927] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 334.72 | bwd_microstep: 442.10 | bwd_inner_microstep: 441.89 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-14 21:44:58,629] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 191.33 | bwd_microstep: 494.53 | bwd_inner_microstep: 494.36 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.11 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1122 +[2025-05-14 21:44:59,158] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 228.99 | bwd_microstep: 281.62 | bwd_inner_microstep: 281.58 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-14 21:45:00,033] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 344.98 | bwd_microstep: 495.41 | bwd_inner_microstep: 495.07 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-14 21:45:00,923] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 372.61 | bwd_microstep: 486.82 | bwd_inner_microstep: 486.66 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-14 21:45:01,830] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 402.69 | bwd_microstep: 485.51 | bwd_inner_microstep: 485.20 | bwd_allreduce_microstep: 0.29 | step_microstep: 0.41 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1099 +[2025-05-14 21:45:02,355] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 200.09 | bwd_microstep: 298.80 | bwd_inner_microstep: 298.40 | bwd_allreduce_microstep: 0.15 | step_microstep: 0.22 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-14 21:45:03,603] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.29 | optimizer_step: 28.59 +[2025-05-14 21:45:03,604] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 391.65 | bwd_microstep: 799.95 | bwd_inner_microstep: 500.99 | bwd_allreduce_microstep: 298.77 | step_microstep: 38.97 +[2025-05-14 21:45:03,605] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2466.97 | bwd: 3784.84 | bwd_inner: 3484.50 | bwd_allreduce: 299.48 | step: 42.41 + 11%|█ | 196/1859 [18:13<2:56:33, 6.37s/it] {'loss': 3.9681, 'grad_norm': 16.42364501953125, 'learning_rate': 9.851970016346575e-11, 'epoch': 0.11} + 11%|█ | 196/1859 [18:13<2:56:33, 6.37s/it]dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1397 +[2025-05-14 21:45:04,315] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 313.55 | bwd_microstep: 370.91 | bwd_inner_microstep: 370.86 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1916 +[2025-05-14 21:45:05,191] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 328.54 | bwd_microstep: 512.63 | bwd_inner_microstep: 512.59 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.48 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1891 +[2025-05-14 21:45:06,068] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 324.55 | bwd_microstep: 518.51 | bwd_inner_microstep: 518.12 | bwd_allreduce_microstep: 0.24 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1886 +[2025-05-14 21:45:06,882] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 330.58 | bwd_microstep: 451.30 | bwd_inner_microstep: 451.27 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-14 21:45:07,767] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 360.49 | bwd_microstep: 490.27 | bwd_inner_microstep: 489.92 | bwd_allreduce_microstep: 0.15 | step_microstep: 0.17 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-14 21:45:08,682] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 404.95 | bwd_microstep: 491.07 | bwd_inner_microstep: 490.84 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-14 21:45:09,604] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 393.84 | bwd_microstep: 506.64 | bwd_inner_microstep: 506.31 | bwd_allreduce_microstep: 0.15 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-14 21:45:10,838] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.07 | optimizer_gradients: 2.25 | optimizer_step: 18.14 +[2025-05-14 21:45:10,839] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 364.26 | bwd_microstep: 820.43 | bwd_inner_microstep: 521.09 | bwd_allreduce_microstep: 299.30 | step_microstep: 28.31 +[2025-05-14 21:45:10,839] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2820.70 | bwd: 4161.81 | bwd_inner: 3861.28 | bwd_allreduce: 299.84 | step: 36.08 + 11%|█ | 197/1859 [18:21<3:03:38, 6.63s/it] {'loss': 2.9184, 'grad_norm': 12.841365814208984, 'learning_rate': 9.849858434976548e-11, 'epoch': 0.11} + 11%|█ | 197/1859 [18:21<3:03:38, 6.63s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1903 +[2025-05-14 21:45:11,766] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 379.96 | bwd_microstep: 519.44 | bwd_inner_microstep: 519.40 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.48 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-14 21:45:12,646] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 331.45 | bwd_microstep: 519.32 | bwd_inner_microstep: 519.27 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.37 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-14 21:45:13,528] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 323.66 | bwd_microstep: 523.62 | bwd_inner_microstep: 523.58 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-14 21:45:14,407] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 318.94 | bwd_microstep: 518.72 | bwd_inner_microstep: 518.68 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-14 21:45:15,265] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 315.08 | bwd_microstep: 508.25 | bwd_inner_microstep: 508.21 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.33 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 839 +[2025-05-14 21:45:15,689] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 162.37 | bwd_microstep: 227.62 | bwd_inner_microstep: 227.60 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.31 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-14 21:45:16,541] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 310.85 | bwd_microstep: 520.34 | bwd_inner_microstep: 520.31 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-14 21:45:17,764] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 1.85 | optimizer_step: 14.88 +[2025-05-14 21:45:17,766] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 328.22 | bwd_microstep: 837.70 | bwd_inner_microstep: 509.03 | bwd_allreduce_microstep: 328.64 | step_microstep: 24.98 +[2025-05-14 21:45:17,767] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2470.48 | bwd: 4174.99 | bwd_inner: 3846.08 | bwd_allreduce: 328.70 | step: 39.29 + 11%|█ | 198/1859 [18:28<3:06:00, 6.72s/it] {'loss': 4.2152, 'grad_norm': 18.048572540283203, 'learning_rate': 9.847732129218828e-11, 'epoch': 0.11} + 11%|█ | 198/1859 [18:28<3:06:00, 6.72s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1901 +[2025-05-14 21:45:18,648] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 326.40 | bwd_microstep: 512.63 | bwd_inner_microstep: 512.60 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-14 21:45:19,531] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 334.78 | bwd_microstep: 516.04 | bwd_inner_microstep: 515.64 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-14 21:45:20,423] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 335.63 | bwd_microstep: 524.93 | bwd_inner_microstep: 524.88 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-14 21:45:21,314] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 330.42 | bwd_microstep: 530.91 | bwd_inner_microstep: 530.85 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.38 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 844 +[2025-05-14 21:45:21,765] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 182.93 | bwd_microstep: 227.76 | bwd_inner_microstep: 227.70 | bwd_allreduce_microstep: 0.02 | step_microstep: 2.33 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-14 21:45:22,648] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 325.72 | bwd_microstep: 524.44 | bwd_inner_microstep: 524.20 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-14 21:45:23,364] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 289.27 | bwd_microstep: 395.26 | bwd_inner_microstep: 395.22 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.53 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-14 21:45:24,631] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.01 | optimizer_gradients: 2.23 | optimizer_step: 18.79 +[2025-05-14 21:45:24,632] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 327.79 | bwd_microstep: 877.04 | bwd_inner_microstep: 508.49 | bwd_allreduce_microstep: 368.51 | step_microstep: 30.69 +[2025-05-14 21:45:24,633] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2452.92 | bwd: 4109.03 | bwd_inner: 3739.61 | bwd_allreduce: 368.60 | step: 41.65 + 11%|█ | 199/1859 [18:34<3:07:06, 6.76s/it] {'loss': 4.1614, 'grad_norm': 18.51676368713379, 'learning_rate': 9.845591105528971e-11, 'epoch': 0.11} + 11%|█ | 199/1859 [18:34<3:07:06, 6.76s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1890 +[2025-05-14 21:45:25,533] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 346.22 | bwd_microstep: 526.03 | bwd_inner_microstep: 525.99 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.32 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1113 +[2025-05-14 21:45:26,060] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 166.42 | bwd_microstep: 333.04 | bwd_inner_microstep: 332.66 | bwd_allreduce_microstep: 0.16 | step_microstep: 0.22 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-14 21:45:26,968] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 371.57 | bwd_microstep: 516.70 | bwd_inner_microstep: 516.43 | bwd_allreduce_microstep: 0.24 | step_microstep: 0.40 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 849 +[2025-05-14 21:45:27,424] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 139.07 | bwd_microstep: 298.19 | bwd_inner_microstep: 298.14 | bwd_allreduce_microstep: 0.02 | step_microstep: 1.70 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-14 21:45:28,288] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 326.35 | bwd_microstep: 516.20 | bwd_inner_microstep: 516.13 | bwd_allreduce_microstep: 0.02 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-14 21:45:29,167] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 319.23 | bwd_microstep: 523.16 | bwd_inner_microstep: 523.13 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.31 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-14 21:45:30,039] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 318.38 | bwd_microstep: 519.45 | bwd_inner_microstep: 519.40 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.53 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-14 21:45:31,130] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 1.83 | optimizer_step: 12.80 +[2025-05-14 21:45:31,130] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 337.51 | bwd_microstep: 698.22 | bwd_inner_microstep: 498.97 | bwd_allreduce_microstep: 199.19 | step_microstep: 20.99 +[2025-05-14 21:45:31,131] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2324.71 | bwd: 3931.05 | bwd_inner: 3730.92 | bwd_allreduce: 199.67 | step: 32.82 + 11%|█ | 200/1859 [18:41<3:04:46, 6.68s/it] {'loss': 4.0148, 'grad_norm': 21.321678161621094, 'learning_rate': 9.843435370407219e-11, 'epoch': 0.11} + 11%|█ | 200/1859 [18:41<3:04:46, 6.68s/it][INFO|trainer.py:3503] 2025-05-14 21:45:34,423 >> Saving model checkpoint to work_dirs/internvl_chat_v2_5/mmvet/checkpoint-200 +[INFO|configuration_utils.py:472] 2025-05-14 21:45:34,425 >> Configuration saved in work_dirs/internvl_chat_v2_5/mmvet/checkpoint-200/config.json +[INFO|configuration_utils.py:807] 2025-05-14 21:45:34,426 >> Configuration saved in work_dirs/internvl_chat_v2_5/mmvet/checkpoint-200/generation_config.json +[INFO|modeling_utils.py:2755] 2025-05-14 21:45:40,036 >> Model weights saved in work_dirs/internvl_chat_v2_5/mmvet/checkpoint-200/model.safetensors +[INFO|tokenization_utils_base.py:2702] 2025-05-14 21:45:40,037 >> tokenizer config file saved in work_dirs/internvl_chat_v2_5/mmvet/checkpoint-200/tokenizer_config.json +[INFO|tokenization_utils_base.py:2711] 2025-05-14 21:45:40,038 >> Special tokens file saved in work_dirs/internvl_chat_v2_5/mmvet/checkpoint-200/special_tokens_map.json +[INFO|tokenization_utils_base.py:2762] 2025-05-14 21:45:40,038 >> added tokens file saved in work_dirs/internvl_chat_v2_5/mmvet/checkpoint-200/added_tokens.json +[2025-05-14 21:45:40,238] [INFO] [logging.py:96:log_dist] [Rank 0] [Torch] Checkpoint global_step200 is about to be saved! +[2025-05-14 21:45:40,263] [INFO] [logging.py:96:log_dist] [Rank 0] Saving model checkpoint: work_dirs/internvl_chat_v2_5/mmvet/checkpoint-200/global_step200/mp_rank_00_model_states.pt +[2025-05-14 21:45:40,263] [INFO] [torch_checkpoint_engine.py:21:save] [Torch] Saving work_dirs/internvl_chat_v2_5/mmvet/checkpoint-200/global_step200/mp_rank_00_model_states.pt... +[2025-05-14 21:45:45,143] [INFO] [torch_checkpoint_engine.py:23:save] [Torch] Saved work_dirs/internvl_chat_v2_5/mmvet/checkpoint-200/global_step200/mp_rank_00_model_states.pt. +[2025-05-14 21:45:45,144] [INFO] [torch_checkpoint_engine.py:21:save] [Torch] Saving work_dirs/internvl_chat_v2_5/mmvet/checkpoint-200/global_step200/bf16_zero_pp_rank_0_mp_rank_00_optim_states.pt... +[2025-05-14 21:45:45,310] [INFO] [torch_checkpoint_engine.py:23:save] [Torch] Saved work_dirs/internvl_chat_v2_5/mmvet/checkpoint-200/global_step200/bf16_zero_pp_rank_0_mp_rank_00_optim_states.pt. +[2025-05-14 21:45:45,310] [INFO] [engine.py:3536:_save_zero_checkpoint] zero checkpoint saved work_dirs/internvl_chat_v2_5/mmvet/checkpoint-200/global_step200/bf16_zero_pp_rank_0_mp_rank_00_optim_states.pt +[2025-05-14 21:45:45,310] [INFO] [torch_checkpoint_engine.py:33:commit] [Torch] Checkpoint global_step200 is ready now! +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1905 +[2025-05-14 21:45:46,235] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 388.56 | bwd_microstep: 515.80 | bwd_inner_microstep: 515.76 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.41 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-14 21:45:47,191] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 391.07 | bwd_microstep: 514.16 | bwd_inner_microstep: 513.99 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-14 21:45:48,092] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 357.99 | bwd_microstep: 521.40 | bwd_inner_microstep: 521.37 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-14 21:45:48,802] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 323.11 | bwd_microstep: 363.73 | bwd_inner_microstep: 363.40 | bwd_allreduce_microstep: 0.14 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-14 21:45:49,612] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 276.51 | bwd_microstep: 515.40 | bwd_inner_microstep: 515.34 | bwd_allreduce_microstep: 0.02 | step_microstep: 2.37 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-14 21:45:50,488] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 328.45 | bwd_microstep: 510.71 | bwd_inner_microstep: 510.67 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-14 21:45:51,371] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 326.64 | bwd_microstep: 522.39 | bwd_inner_microstep: 522.36 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-14 21:45:52,517] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.21 | optimizer_step: 18.99 +[2025-05-14 21:45:52,517] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 286.91 | bwd_microstep: 802.67 | bwd_inner_microstep: 492.93 | bwd_allreduce_microstep: 309.59 | step_microstep: 28.69 +[2025-05-14 21:45:52,518] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2679.16 | bwd: 4266.28 | bwd_inner: 3955.97 | bwd_allreduce: 309.79 | step: 38.76 + 11%|█ | 201/1859 [19:02<5:06:35, 11.09s/it] {'loss': 3.8181, 'grad_norm': 13.7704439163208, 'learning_rate': 9.841264930398484e-11, 'epoch': 0.11} + 11%|█ | 201/1859 [19:02<5:06:35, 11.09s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1962 +[2025-05-14 21:45:53,326] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 322.70 | bwd_microstep: 457.53 | bwd_inner_microstep: 457.49 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.37 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 870 +[2025-05-14 21:45:53,705] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 148.33 | bwd_microstep: 212.93 | bwd_inner_microstep: 212.89 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.22 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-14 21:45:54,557] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 311.92 | bwd_microstep: 517.25 | bwd_inner_microstep: 517.22 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.33 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-14 21:45:55,417] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 313.40 | bwd_microstep: 510.34 | bwd_inner_microstep: 510.30 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.58 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-14 21:45:56,288] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 330.11 | bwd_microstep: 508.40 | bwd_inner_microstep: 508.37 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-14 21:45:56,994] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 322.04 | bwd_microstep: 354.33 | bwd_inner_microstep: 354.14 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.10 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1096 +[2025-05-14 21:45:57,465] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 185.20 | bwd_microstep: 270.97 | bwd_inner_microstep: 270.69 | bwd_allreduce_microstep: 0.21 | step_microstep: 0.18 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1351 +[2025-05-14 21:45:58,484] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.28 | optimizer_step: 27.39 +[2025-05-14 21:45:58,485] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 240.23 | bwd_microstep: 714.32 | bwd_inner_microstep: 415.69 | bwd_allreduce_microstep: 298.43 | step_microstep: 37.68 +[2025-05-14 21:45:58,485] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2173.90 | bwd: 3546.26 | bwd_inner: 3246.90 | bwd_allreduce: 298.74 | step: 43.64 + 11%|█ | 202/1859 [19:08<4:23:55, 9.56s/it] {'loss': 5.3492, 'grad_norm': 20.134994506835938, 'learning_rate': 9.839079792092317e-11, 'epoch': 0.11} + 11%|█ | 202/1859 [19:08<4:23:55, 9.56s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-14 21:45:59,400] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 397.26 | bwd_microstep: 491.70 | bwd_inner_microstep: 491.53 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-14 21:46:00,308] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 386.09 | bwd_microstep: 503.07 | bwd_inner_microstep: 503.05 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.43 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-14 21:46:01,198] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 347.84 | bwd_microstep: 520.25 | bwd_inner_microstep: 520.22 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-14 21:46:02,051] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 307.84 | bwd_microstep: 516.54 | bwd_inner_microstep: 516.48 | bwd_allreduce_microstep: 0.02 | step_microstep: 2.33 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 330 +[2025-05-14 21:46:02,341] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 106.05 | bwd_microstep: 149.90 | bwd_inner_microstep: 149.85 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-14 21:46:03,230] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 330.57 | bwd_microstep: 522.13 | bwd_inner_microstep: 522.09 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.37 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-14 21:46:04,086] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 314.96 | bwd_microstep: 506.90 | bwd_inner_microstep: 506.86 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.54 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-14 21:46:05,249] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 1.84 | optimizer_step: 12.78 +[2025-05-14 21:46:05,250] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 324.20 | bwd_microstep: 785.55 | bwd_inner_microstep: 514.85 | bwd_allreduce_microstep: 270.64 | step_microstep: 21.19 +[2025-05-14 21:46:05,250] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2514.75 | bwd: 3996.08 | bwd_inner: 3724.97 | bwd_allreduce: 270.79 | step: 33.67 + 11%|█ | 203/1859 [19:15<4:00:37, 8.72s/it] {'loss': 6.5745, 'grad_norm': 21.98171043395996, 'learning_rate': 9.836879962122894e-11, 'epoch': 0.11} + 11%|█ | 203/1859 [19:15<4:00:37, 8.72s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1949 +[2025-05-14 21:46:06,104] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 288.40 | bwd_microstep: 542.33 | bwd_inner_microstep: 542.27 | bwd_allreduce_microstep: 0.02 | step_microstep: 2.38 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1887 +[2025-05-14 21:46:06,974] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 319.01 | bwd_microstep: 515.20 | bwd_inner_microstep: 515.14 | bwd_allreduce_microstep: 0.02 | step_microstep: 2.60 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 853 +[2025-05-14 21:46:07,415] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 162.11 | bwd_microstep: 244.74 | bwd_inner_microstep: 244.72 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.49 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-14 21:46:08,244] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 328.72 | bwd_microstep: 465.76 | bwd_inner_microstep: 465.60 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 6, images per sample: 6.0, dynamic token length: 1615 +[2025-05-14 21:46:08,899] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 251.28 | bwd_microstep: 387.36 | bwd_inner_microstep: 387.20 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-14 21:46:09,672] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 302.78 | bwd_microstep: 445.24 | bwd_inner_microstep: 445.19 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-14 21:46:10,520] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 312.60 | bwd_microstep: 514.03 | bwd_inner_microstep: 513.99 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.37 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-14 21:46:11,653] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.22 | optimizer_step: 18.62 +[2025-05-14 21:46:11,656] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 328.45 | bwd_microstep: 740.33 | bwd_inner_microstep: 511.30 | bwd_allreduce_microstep: 229.00 | step_microstep: 32.60 +[2025-05-14 21:46:11,657] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2293.33 | bwd: 3855.01 | bwd_inner: 3625.46 | bwd_allreduce: 229.18 | step: 42.82 + 11%|█ | 204/1859 [19:21<3:41:23, 8.03s/it] {'loss': 7.5257, 'grad_norm': 24.504919052124023, 'learning_rate': 9.834665447169002e-11, 'epoch': 0.11} + 11%|█ | 204/1859 [19:21<3:41:23, 8.03s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1899 +[2025-05-14 21:46:12,558] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 335.32 | bwd_microstep: 518.22 | bwd_inner_microstep: 518.19 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-14 21:46:13,384] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 331.15 | bwd_microstep: 468.92 | bwd_inner_microstep: 468.58 | bwd_allreduce_microstep: 0.15 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-14 21:46:14,116] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 192.88 | bwd_microstep: 520.83 | bwd_inner_microstep: 520.79 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-14 21:46:14,988] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 330.39 | bwd_microstep: 506.00 | bwd_inner_microstep: 505.94 | bwd_allreduce_microstep: 0.02 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-14 21:46:15,869] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 348.72 | bwd_microstep: 495.41 | bwd_inner_microstep: 495.37 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-14 21:46:16,748] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 354.78 | bwd_microstep: 489.47 | bwd_inner_microstep: 489.29 | bwd_allreduce_microstep: 0.08 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-14 21:46:17,651] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 378.60 | bwd_microstep: 494.54 | bwd_inner_microstep: 494.12 | bwd_allreduce_microstep: 0.17 | step_microstep: 0.22 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-14 21:46:18,898] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.09 | optimizer_gradients: 2.24 | optimizer_step: 18.59 +[2025-05-14 21:46:18,899] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 405.51 | bwd_microstep: 795.37 | bwd_inner_microstep: 496.96 | bwd_allreduce_microstep: 298.28 | step_microstep: 28.57 +[2025-05-14 21:46:18,900] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2677.30 | bwd: 4288.85 | bwd_inner: 3989.44 | bwd_allreduce: 298.73 | step: 38.45 + 11%|█ | 205/1859 [19:29<3:34:45, 7.79s/it] {'loss': 4.4518, 'grad_norm': 15.380233764648438, 'learning_rate': 9.832436253954005e-11, 'epoch': 0.11} + 11%|█ | 205/1859 [19:29<3:34:45, 7.79s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1893 +[2025-05-14 21:46:19,816] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 395.24 | bwd_microstep: 494.93 | bwd_inner_microstep: 494.62 | bwd_allreduce_microstep: 0.15 | step_microstep: 0.14 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-14 21:46:20,735] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 394.49 | bwd_microstep: 503.22 | bwd_inner_microstep: 503.06 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-14 21:46:21,546] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 366.04 | bwd_microstep: 422.39 | bwd_inner_microstep: 422.23 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-14 21:46:22,337] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 256.88 | bwd_microstep: 518.11 | bwd_inner_microstep: 518.07 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-14 21:46:23,192] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 322.41 | bwd_microstep: 511.60 | bwd_inner_microstep: 511.54 | bwd_allreduce_microstep: 0.02 | step_microstep: 2.36 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 846 +[2025-05-14 21:46:23,644] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 118.27 | bwd_microstep: 299.35 | bwd_inner_microstep: 299.29 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-14 21:46:24,518] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 318.91 | bwd_microstep: 521.85 | bwd_inner_microstep: 521.83 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-14 21:46:25,665] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.07 | optimizer_gradients: 2.24 | optimizer_step: 26.55 +[2025-05-14 21:46:25,666] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 271.88 | bwd_microstep: 807.74 | bwd_inner_microstep: 483.89 | bwd_allreduce_microstep: 323.65 | step_microstep: 36.89 +[2025-05-14 21:46:25,667] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2444.06 | bwd: 4079.24 | bwd_inner: 3754.76 | bwd_allreduce: 323.91 | step: 44.49 + 11%|█ | 206/1859 [19:35<3:26:09, 7.48s/it] {'loss': 4.5953, 'grad_norm': 12.44635009765625, 'learning_rate': 9.830192389245835e-11, 'epoch': 0.11} + 11%|█ | 206/1859 [19:35<3:26:09, 7.48s/it]dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1410 +[2025-05-14 21:46:26,350] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 275.59 | bwd_microstep: 379.96 | bwd_inner_microstep: 379.92 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.57 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1883 +[2025-05-14 21:46:27,208] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 341.23 | bwd_microstep: 486.92 | bwd_inner_microstep: 486.87 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-14 21:46:28,094] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 333.58 | bwd_microstep: 517.87 | bwd_inner_microstep: 517.83 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-14 21:46:28,971] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 329.51 | bwd_microstep: 513.56 | bwd_inner_microstep: 510.99 | bwd_allreduce_microstep: 0.02 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-14 21:46:29,852] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 330.95 | bwd_microstep: 517.84 | bwd_inner_microstep: 517.48 | bwd_allreduce_microstep: 0.23 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-14 21:46:30,531] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 238.16 | bwd_microstep: 422.66 | bwd_inner_microstep: 422.63 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.58 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-14 21:46:31,420] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 336.10 | bwd_microstep: 521.08 | bwd_inner_microstep: 521.00 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-14 21:46:32,618] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.24 | optimizer_step: 24.95 +[2025-05-14 21:46:32,620] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 332.75 | bwd_microstep: 801.27 | bwd_inner_microstep: 512.58 | bwd_allreduce_microstep: 288.66 | step_microstep: 35.47 +[2025-05-14 21:46:32,621] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2517.81 | bwd: 4161.19 | bwd_inner: 3869.37 | bwd_allreduce: 288.76 | step: 48.02 + 11%|█ | 207/1859 [19:42<3:21:41, 7.33s/it] {'loss': 5.9225, 'grad_norm': 17.673559188842773, 'learning_rate': 9.827933859856963e-11, 'epoch': 0.11} + 11%|█ | 207/1859 [19:42<3:21:41, 7.33s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-14 21:46:33,511] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 314.14 | bwd_microstep: 530.46 | bwd_inner_microstep: 530.42 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-14 21:46:34,382] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 327.14 | bwd_microstep: 508.31 | bwd_inner_microstep: 508.27 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-14 21:46:35,264] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 334.72 | bwd_microstep: 513.13 | bwd_inner_microstep: 510.54 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-14 21:46:36,153] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 330.10 | bwd_microstep: 525.83 | bwd_inner_microstep: 525.77 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.19 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 839 +[2025-05-14 21:46:36,587] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.32 | bwd_microstep: 214.09 | bwd_inner_microstep: 211.51 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-14 21:46:37,477] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 331.80 | bwd_microstep: 526.49 | bwd_inner_microstep: 526.44 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-14 21:46:38,286] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 328.02 | bwd_microstep: 450.77 | bwd_inner_microstep: 450.61 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.11 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 321 +[2025-05-14 21:46:38,842] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.20 | optimizer_step: 18.58 +[2025-05-14 21:46:38,844] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 78.58 | bwd_microstep: 435.96 | bwd_inner_microstep: 164.89 | bwd_allreduce_microstep: 271.03 | step_microstep: 30.61 +[2025-05-14 21:46:38,845] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2234.80 | bwd: 3705.05 | bwd_inner: 3428.49 | bwd_allreduce: 275.86 | step: 40.56 + 11%|█ | 208/1859 [19:49<3:12:28, 7.00s/it] {'loss': 5.0932, 'grad_norm': 29.66409683227539, 'learning_rate': 9.82566067264439e-11, 'epoch': 0.11} + 11%|█ | 208/1859 [19:49<3:12:28, 7.00s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1927 +[2025-05-14 21:46:39,789] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 342.59 | bwd_microstep: 556.44 | bwd_inner_microstep: 556.39 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.29 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1921 +[2025-05-14 21:46:40,714] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 338.51 | bwd_microstep: 555.80 | bwd_inner_microstep: 555.76 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.33 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 866 +[2025-05-14 21:46:41,161] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 124.25 | bwd_microstep: 297.06 | bwd_inner_microstep: 297.04 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1896 +[2025-05-14 21:46:42,022] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 307.37 | bwd_microstep: 530.10 | bwd_inner_microstep: 530.07 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.49 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1889 +[2025-05-14 21:46:42,914] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 325.85 | bwd_microstep: 530.28 | bwd_inner_microstep: 530.24 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-14 21:46:43,786] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 320.18 | bwd_microstep: 516.32 | bwd_inner_microstep: 516.26 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.58 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-14 21:46:44,664] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 328.05 | bwd_microstep: 514.41 | bwd_inner_microstep: 514.36 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.37 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2027 +[2025-05-14 21:46:45,936] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.18 | optimizer_step: 18.74 +[2025-05-14 21:46:45,938] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 356.80 | bwd_microstep: 856.99 | bwd_inner_microstep: 571.47 | bwd_allreduce_microstep: 285.48 | step_microstep: 28.21 +[2025-05-14 21:46:45,939] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2443.61 | bwd: 4357.38 | bwd_inner: 4071.60 | bwd_allreduce: 285.55 | step: 44.98 + 11%|█ | 209/1859 [19:56<3:13:10, 7.02s/it] {'loss': 3.1093, 'grad_norm': 13.204615592956543, 'learning_rate': 9.82337283450961e-11, 'epoch': 0.11} + 11%|█ | 209/1859 [19:56<3:13:10, 7.02s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1894 +[2025-05-14 21:46:46,760] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 324.15 | bwd_microstep: 454.62 | bwd_inner_microstep: 454.58 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1913 +[2025-05-14 21:46:47,654] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 333.36 | bwd_microstep: 532.95 | bwd_inner_microstep: 532.88 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1889 +[2025-05-14 21:46:48,549] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 337.13 | bwd_microstep: 527.87 | bwd_inner_microstep: 527.82 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.39 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1888 +[2025-05-14 21:46:49,442] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 334.80 | bwd_microstep: 528.20 | bwd_inner_microstep: 528.14 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-14 21:46:50,329] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 329.72 | bwd_microstep: 528.92 | bwd_inner_microstep: 528.87 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.37 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-14 21:46:51,224] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 332.85 | bwd_microstep: 531.87 | bwd_inner_microstep: 531.83 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-14 21:46:52,116] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 338.64 | bwd_microstep: 523.74 | bwd_inner_microstep: 523.67 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.11 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1087 +[2025-05-14 21:46:52,972] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 5.89 | optimizer_step: 19.11 +[2025-05-14 21:46:52,974] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 214.12 | bwd_microstep: 585.01 | bwd_inner_microstep: 312.46 | bwd_allreduce_microstep: 272.52 | step_microstep: 32.63 +[2025-05-14 21:46:52,975] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2544.76 | bwd: 4213.23 | bwd_inner: 3940.27 | bwd_allreduce: 272.64 | step: 36.08 + 11%|█▏ | 210/1859 [20:03<3:13:09, 7.03s/it] {'loss': 3.9809, 'grad_norm': 18.28333282470703, 'learning_rate': 9.821070352398605e-11, 'epoch': 0.11} + 11%|█▏ | 210/1859 [20:03<3:13:09, 7.03s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2020 +[2025-05-14 21:46:53,940] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 362.92 | bwd_microstep: 573.67 | bwd_inner_microstep: 573.63 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1942 +[2025-05-14 21:46:54,678] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 351.18 | bwd_microstep: 366.21 | bwd_inner_microstep: 366.07 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-14 21:46:55,383] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 192.56 | bwd_microstep: 495.97 | bwd_inner_microstep: 495.80 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-14 21:46:56,292] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 396.52 | bwd_microstep: 493.48 | bwd_inner_microstep: 493.21 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.10 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 841 +[2025-05-14 21:46:56,750] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 181.41 | bwd_microstep: 255.94 | bwd_inner_microstep: 255.59 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.22 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-14 21:46:57,662] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 395.70 | bwd_microstep: 494.80 | bwd_inner_microstep: 494.47 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.22 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-14 21:46:58,518] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 319.41 | bwd_microstep: 517.41 | bwd_inner_microstep: 517.35 | bwd_allreduce_microstep: 0.02 | step_microstep: 2.64 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-14 21:46:59,728] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.01 | optimizer_gradients: 2.24 | optimizer_step: 17.89 +[2025-05-14 21:46:59,728] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 318.15 | bwd_microstep: 830.58 | bwd_inner_microstep: 526.37 | bwd_allreduce_microstep: 304.16 | step_microstep: 29.54 +[2025-05-14 21:46:59,729] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2517.79 | bwd: 4028.15 | bwd_inner: 3722.72 | bwd_allreduce: 304.67 | step: 33.11 + 11%|█▏ | 211/1859 [20:09<3:10:45, 6.94s/it] {'loss': 5.7916, 'grad_norm': 23.917987823486328, 'learning_rate': 9.818753233301812e-11, 'epoch': 0.11} + 11%|█▏ | 211/1859 [20:09<3:10:45, 6.94s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 341 +[2025-05-14 21:46:59,987] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 85.75 | bwd_microstep: 147.40 | bwd_inner_microstep: 147.35 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1900 +[2025-05-14 21:47:00,872] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 329.69 | bwd_microstep: 520.63 | bwd_inner_microstep: 520.59 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.31 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1890 +[2025-05-14 21:47:01,753] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 325.05 | bwd_microstep: 524.87 | bwd_inner_microstep: 524.83 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-14 21:47:02,632] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 331.40 | bwd_microstep: 517.84 | bwd_inner_microstep: 517.80 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.37 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-14 21:47:03,437] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 331.83 | bwd_microstep: 440.94 | bwd_inner_microstep: 440.71 | bwd_allreduce_microstep: 0.20 | step_microstep: 0.22 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-14 21:47:04,297] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 313.37 | bwd_microstep: 525.95 | bwd_inner_microstep: 525.89 | bwd_allreduce_microstep: 0.02 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-14 21:47:05,167] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 312.83 | bwd_microstep: 518.55 | bwd_inner_microstep: 518.51 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1349 +[2025-05-14 21:47:06,128] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 4.32 | optimizer_step: 19.52 +[2025-05-14 21:47:06,128] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 211.38 | bwd_microstep: 687.57 | bwd_inner_microstep: 402.65 | bwd_allreduce_microstep: 284.81 | step_microstep: 29.94 +[2025-05-14 21:47:06,129] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2241.29 | bwd: 3883.76 | bwd_inner: 3598.37 | bwd_allreduce: 285.08 | step: 42.11 + 11%|█▏ | 212/1859 [20:16<3:06:09, 6.78s/it] {'loss': 4.7007, 'grad_norm': 18.298877716064453, 'learning_rate': 9.81642148425411e-11, 'epoch': 0.11} + 11%|█▏ | 212/1859 [20:16<3:06:09, 6.78s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1892 +[2025-05-14 21:47:07,029] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 363.76 | bwd_microstep: 496.82 | bwd_inner_microstep: 496.65 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1900 +[2025-05-14 21:47:07,941] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 398.75 | bwd_microstep: 494.66 | bwd_inner_microstep: 494.41 | bwd_allreduce_microstep: 0.09 | step_microstep: 0.10 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 361 +[2025-05-14 21:47:08,204] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 101.91 | bwd_microstep: 141.23 | bwd_inner_microstep: 141.18 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1886 +[2025-05-14 21:47:09,076] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 310.58 | bwd_microstep: 525.73 | bwd_inner_microstep: 525.69 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-14 21:47:09,954] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 326.39 | bwd_microstep: 516.87 | bwd_inner_microstep: 516.83 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.28 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-14 21:47:10,827] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 323.84 | bwd_microstep: 513.75 | bwd_inner_microstep: 513.69 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-14 21:47:11,632] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 328.43 | bwd_microstep: 441.68 | bwd_inner_microstep: 441.48 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2354 +[2025-05-14 21:47:13,044] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.01 | optimizer_gradients: 2.24 | optimizer_step: 18.69 +[2025-05-14 21:47:13,045] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 413.74 | bwd_microstep: 944.69 | bwd_inner_microstep: 645.72 | bwd_allreduce_microstep: 298.93 | step_microstep: 28.23 +[2025-05-14 21:47:13,046] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2567.35 | bwd: 4075.47 | bwd_inner: 3775.79 | bwd_allreduce: 299.16 | step: 35.75 + 11%|█▏ | 213/1859 [20:23<3:07:10, 6.82s/it] {'loss': 4.3474, 'grad_norm': 35.43976593017578, 'learning_rate': 9.814075112334793e-11, 'epoch': 0.11} + 11%|█▏ | 213/1859 [20:23<3:07:10, 6.82s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1890 +[2025-05-14 21:47:13,935] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 311.97 | bwd_microstep: 532.47 | bwd_inner_microstep: 532.44 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.44 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 880 +[2025-05-14 21:47:14,330] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 144.59 | bwd_microstep: 218.19 | bwd_inner_microstep: 215.83 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.32 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-14 21:47:15,216] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 336.79 | bwd_microstep: 517.07 | bwd_inner_microstep: 516.68 | bwd_allreduce_microstep: 0.25 | step_microstep: 0.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-14 21:47:16,112] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 336.62 | bwd_microstep: 526.99 | bwd_inner_microstep: 526.94 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.77 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1096 +[2025-05-14 21:47:16,669] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 216.78 | bwd_microstep: 312.17 | bwd_inner_microstep: 312.12 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.56 +dynamic ViT batch size: 6, images per sample: 6.0, dynamic token length: 1608 +[2025-05-14 21:47:17,429] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 268.26 | bwd_microstep: 458.01 | bwd_inner_microstep: 457.98 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.37 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-14 21:47:18,323] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 329.05 | bwd_microstep: 529.73 | bwd_inner_microstep: 529.69 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-14 21:47:19,467] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.01 | optimizer_gradients: 2.21 | optimizer_step: 20.79 +[2025-05-14 21:47:19,470] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 340.38 | bwd_microstep: 746.10 | bwd_inner_microstep: 523.19 | bwd_allreduce_microstep: 222.87 | step_microstep: 30.47 +[2025-05-14 21:47:19,470] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2284.46 | bwd: 3840.71 | bwd_inner: 3614.94 | bwd_allreduce: 225.47 | step: 44.48 + 12%|█▏ | 214/1859 [20:29<3:03:47, 6.70s/it] {'loss': 8.9558, 'grad_norm': 26.91497039794922, 'learning_rate': 9.81171412466755e-11, 'epoch': 0.12} + 12%|█▏ | 214/1859 [20:29<3:03:47, 6.70s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1977 +[2025-05-14 21:47:20,342] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 317.12 | bwd_microstep: 514.18 | bwd_inner_microstep: 513.89 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1883 +[2025-05-14 21:47:21,261] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 391.16 | bwd_microstep: 503.27 | bwd_inner_microstep: 503.13 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1891 +[2025-05-14 21:47:22,167] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 363.08 | bwd_microstep: 523.29 | bwd_inner_microstep: 522.67 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.26 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 861 +[2025-05-14 21:47:22,618] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 130.89 | bwd_microstep: 300.84 | bwd_inner_microstep: 300.78 | bwd_allreduce_microstep: 0.02 | step_microstep: 2.56 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-14 21:47:23,502] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 330.97 | bwd_microstep: 530.28 | bwd_inner_microstep: 530.24 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.43 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-14 21:47:24,384] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 318.82 | bwd_microstep: 528.25 | bwd_inner_microstep: 528.22 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.32 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-14 21:47:25,260] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 314.38 | bwd_microstep: 525.55 | bwd_inner_microstep: 525.50 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-14 21:47:26,449] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.01 | optimizer_gradients: 3.53 | optimizer_step: 19.72 +[2025-05-14 21:47:26,451] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 324.53 | bwd_microstep: 803.87 | bwd_inner_microstep: 518.34 | bwd_allreduce_microstep: 285.49 | step_microstep: 30.53 +[2025-05-14 21:47:26,451] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2490.92 | bwd: 4229.56 | bwd_inner: 3942.84 | bwd_allreduce: 285.72 | step: 40.68 + 12%|█▏ | 215/1859 [20:36<3:05:57, 6.79s/it] {'loss': 4.9911, 'grad_norm': 39.19904708862305, 'learning_rate': 9.809338528420449e-11, 'epoch': 0.12} + 12%|█▏ | 215/1859 [20:36<3:05:57, 6.79s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 383 +[2025-05-14 21:47:26,740] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 89.08 | bwd_microstep: 158.73 | bwd_inner_microstep: 158.69 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.22 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-14 21:47:27,627] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 334.97 | bwd_microstep: 522.53 | bwd_inner_microstep: 522.51 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-14 21:47:28,356] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 198.77 | bwd_microstep: 497.34 | bwd_inner_microstep: 497.32 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.29 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-14 21:47:29,221] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 325.57 | bwd_microstep: 502.61 | bwd_inner_microstep: 502.57 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-14 21:47:30,075] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 295.21 | bwd_microstep: 525.05 | bwd_inner_microstep: 525.02 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 328 +[2025-05-14 21:47:30,337] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 102.94 | bwd_microstep: 130.79 | bwd_inner_microstep: 130.52 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-14 21:47:31,250] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 381.45 | bwd_microstep: 509.32 | bwd_inner_microstep: 509.27 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.21 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-14 21:47:32,425] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.01 | optimizer_gradients: 2.23 | optimizer_step: 18.60 +[2025-05-14 21:47:32,426] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 335.98 | bwd_microstep: 792.89 | bwd_inner_microstep: 514.39 | bwd_allreduce_microstep: 278.47 | step_microstep: 28.39 +[2025-05-14 21:47:32,427] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2063.94 | bwd: 3639.45 | bwd_inner: 3360.34 | bwd_allreduce: 278.60 | step: 38.28 + 12%|█▏ | 216/1859 [20:42<2:59:11, 6.54s/it] {'loss': 4.9185, 'grad_norm': 27.301897048950195, 'learning_rate': 9.806948330805904e-11, 'epoch': 0.12} + 12%|█▏ | 216/1859 [20:42<2:59:11, 6.54s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1930 +[2025-05-14 21:47:33,367] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 353.01 | bwd_microstep: 555.17 | bwd_inner_microstep: 555.13 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1895 +[2025-05-14 21:47:34,238] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 322.51 | bwd_microstep: 523.52 | bwd_inner_microstep: 523.47 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.37 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-14 21:47:35,106] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 311.69 | bwd_microstep: 522.02 | bwd_inner_microstep: 521.98 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-14 21:47:35,864] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 318.21 | bwd_microstep: 405.17 | bwd_inner_microstep: 404.97 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-14 21:47:36,648] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 252.29 | bwd_microstep: 514.92 | bwd_inner_microstep: 514.64 | bwd_allreduce_microstep: 0.02 | step_microstep: 1.30 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-14 21:47:37,537] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 328.46 | bwd_microstep: 527.95 | bwd_inner_microstep: 527.89 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-14 21:47:38,423] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 341.94 | bwd_microstep: 517.09 | bwd_inner_microstep: 517.02 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1936 +[2025-05-14 21:47:39,665] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.01 | optimizer_gradients: 3.30 | optimizer_step: 19.65 +[2025-05-14 21:47:39,667] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 317.02 | bwd_microstep: 869.93 | bwd_inner_microstep: 564.74 | bwd_allreduce_microstep: 305.15 | step_microstep: 30.22 +[2025-05-14 21:47:39,668] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2545.12 | bwd: 4435.79 | bwd_inner: 4129.90 | bwd_allreduce: 305.31 | step: 38.80 + 12%|█▏ | 217/1859 [20:49<3:04:47, 6.75s/it] {'loss': 4.2427, 'grad_norm': 21.11517906188965, 'learning_rate': 9.804543539080662e-11, 'epoch': 0.12} + 12%|█▏ | 217/1859 [20:49<3:04:47, 6.75s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1912 +[2025-05-14 21:47:40,570] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 324.80 | bwd_microstep: 532.59 | bwd_inner_microstep: 532.53 | bwd_allreduce_microstep: 0.02 | step_microstep: 2.38 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1903 +[2025-05-14 21:47:41,462] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 316.33 | bwd_microstep: 540.46 | bwd_inner_microstep: 540.42 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 851 +[2025-05-14 21:47:41,906] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.66 | bwd_microstep: 268.38 | bwd_inner_microstep: 268.33 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-14 21:47:42,774] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 309.15 | bwd_microstep: 524.25 | bwd_inner_microstep: 524.21 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.33 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 329 +[2025-05-14 21:47:43,055] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.17 | bwd_microstep: 151.46 | bwd_inner_microstep: 151.43 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.37 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-14 21:47:43,889] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 341.62 | bwd_microstep: 458.88 | bwd_inner_microstep: 458.73 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 842 +[2025-05-14 21:47:44,273] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.29 | bwd_microstep: 271.68 | bwd_inner_microstep: 271.60 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 330 +[2025-05-14 21:47:44,906] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.16 | optimizer_step: 18.65 +[2025-05-14 21:47:44,908] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 92.53 | bwd_microstep: 479.95 | bwd_inner_microstep: 155.38 | bwd_allreduce_microstep: 324.44 | step_microstep: 30.45 +[2025-05-14 21:47:44,909] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 1716.56 | bwd: 3227.67 | bwd_inner: 2902.72 | bwd_allreduce: 324.54 | step: 44.67 + 12%|█▏ | 218/1859 [20:55<2:52:16, 6.30s/it] {'loss': 4.5833, 'grad_norm': 31.21564483642578, 'learning_rate': 9.80212416054578e-11, 'epoch': 0.12} + 12%|█▏ | 218/1859 [20:55<2:52:16, 6.30s/it]dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1373 +[2025-05-14 21:47:45,565] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 238.90 | bwd_microstep: 377.54 | bwd_inner_microstep: 377.52 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-14 21:47:46,452] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 327.69 | bwd_microstep: 522.42 | bwd_inner_microstep: 522.39 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.51 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1369 +[2025-05-14 21:47:47,168] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 283.57 | bwd_microstep: 398.36 | bwd_inner_microstep: 398.34 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-14 21:47:48,041] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 323.33 | bwd_microstep: 524.06 | bwd_inner_microstep: 524.02 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.56 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 847 +[2025-05-14 21:47:48,494] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 119.12 | bwd_microstep: 302.05 | bwd_inner_microstep: 302.00 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.32 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-14 21:47:49,372] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 327.17 | bwd_microstep: 516.62 | bwd_inner_microstep: 516.57 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.33 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-14 21:47:50,253] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 320.78 | bwd_microstep: 525.89 | bwd_inner_microstep: 525.86 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-14 21:47:51,414] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.01 | optimizer_gradients: 2.20 | optimizer_step: 18.80 +[2025-05-14 21:47:51,415] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 319.51 | bwd_microstep: 782.74 | bwd_inner_microstep: 525.39 | bwd_allreduce_microstep: 257.32 | step_microstep: 28.61 +[2025-05-14 21:47:51,416] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2260.06 | bwd: 3949.68 | bwd_inner: 3692.11 | bwd_allreduce: 257.38 | step: 45.42 + 12%|█▏ | 219/1859 [21:01<2:53:53, 6.36s/it] {'loss': 7.204, 'grad_norm': 44.71119689941406, 'learning_rate': 9.799690202546599e-11, 'epoch': 0.12} + 12%|█▏ | 219/1859 [21:01<2:53:53, 6.36s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 355 +[2025-05-14 21:47:51,732] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 101.07 | bwd_microstep: 172.04 | bwd_inner_microstep: 171.99 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-14 21:47:52,512] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 324.94 | bwd_microstep: 422.42 | bwd_inner_microstep: 422.24 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1361 +[2025-05-14 21:47:53,125] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 222.91 | bwd_microstep: 372.80 | bwd_inner_microstep: 372.76 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 844 +[2025-05-14 21:47:53,577] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 210.41 | bwd_microstep: 209.74 | bwd_inner_microstep: 209.71 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 337 +[2025-05-14 21:47:53,841] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 92.22 | bwd_microstep: 140.44 | bwd_inner_microstep: 140.22 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.24 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-14 21:47:54,713] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 324.99 | bwd_microstep: 524.35 | bwd_inner_microstep: 524.31 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.53 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-14 21:47:55,539] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 315.95 | bwd_microstep: 475.71 | bwd_inner_microstep: 475.67 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 836 +[2025-05-14 21:47:56,140] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.01 | optimizer_gradients: 2.18 | optimizer_step: 18.89 +[2025-05-14 21:47:56,141] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 143.04 | bwd_microstep: 408.04 | bwd_inner_microstep: 197.48 | bwd_allreduce_microstep: 210.50 | step_microstep: 29.45 +[2025-05-14 21:47:56,142] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 1733.25 | bwd: 2725.55 | bwd_inner: 2514.46 | bwd_allreduce: 210.79 | step: 41.74 + 12%|█▏ | 220/1859 [21:06<2:40:22, 5.87s/it] {'loss': 4.4693, 'grad_norm': 32.02063751220703, 'learning_rate': 9.797241672472725e-11, 'epoch': 0.12} + 12%|█▏ | 220/1859 [21:06<2:40:22, 5.87s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1921 +[2025-05-14 21:47:57,003] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 316.43 | bwd_microstep: 512.01 | bwd_inner_microstep: 511.70 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1907 +[2025-05-14 21:47:57,822] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 334.61 | bwd_microstep: 452.85 | bwd_inner_microstep: 452.53 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-14 21:47:58,602] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 303.50 | bwd_microstep: 453.15 | bwd_inner_microstep: 453.10 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.52 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-14 21:47:59,363] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 295.36 | bwd_microstep: 440.96 | bwd_inner_microstep: 440.72 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-14 21:48:00,131] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 306.48 | bwd_microstep: 439.44 | bwd_inner_microstep: 439.41 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-14 21:48:00,790] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 307.12 | bwd_microstep: 329.84 | bwd_inner_microstep: 329.82 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.22 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-14 21:48:01,509] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 256.38 | bwd_microstep: 443.53 | bwd_inner_microstep: 443.49 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-14 21:48:02,454] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.07 | optimizer_gradients: 2.20 | optimizer_step: 17.97 +[2025-05-14 21:48:02,455] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 306.51 | bwd_microstep: 589.10 | bwd_inner_microstep: 448.32 | bwd_allreduce_microstep: 140.73 | step_microstep: 27.60 +[2025-05-14 21:48:02,455] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2426.39 | bwd: 3660.97 | bwd_inner: 3519.22 | bwd_allreduce: 141.04 | step: 35.56 + 12%|█▏ | 221/1859 [21:12<2:43:51, 6.00s/it] {'loss': 6.2365, 'grad_norm': 24.28200340270996, 'learning_rate': 9.794778577758004e-11, 'epoch': 0.12} + 12%|█▏ | 221/1859 [21:12<2:43:51, 6.00s/it]dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1372 +[2025-05-14 21:48:03,052] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 236.48 | bwd_microstep: 335.72 | bwd_inner_microstep: 335.69 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-14 21:48:03,861] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 268.54 | bwd_microstep: 518.56 | bwd_inner_microstep: 518.51 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.37 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1353 +[2025-05-14 21:48:04,569] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 287.60 | bwd_microstep: 386.16 | bwd_inner_microstep: 386.12 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.53 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-14 21:48:05,458] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 326.60 | bwd_microstep: 529.67 | bwd_inner_microstep: 529.61 | bwd_allreduce_microstep: 0.02 | step_microstep: 2.37 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-14 21:48:06,332] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 317.46 | bwd_microstep: 520.78 | bwd_inner_microstep: 520.74 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.37 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-14 21:48:07,201] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 321.55 | bwd_microstep: 510.56 | bwd_inner_microstep: 510.52 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.29 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-14 21:48:08,063] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 321.64 | bwd_microstep: 504.14 | bwd_inner_microstep: 504.09 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 1657 +[2025-05-14 21:48:09,107] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 2.35 | optimizer_gradients: 2.20 | optimizer_step: 18.12 +[2025-05-14 21:48:09,109] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 231.52 | bwd_microstep: 755.96 | bwd_inner_microstep: 468.71 | bwd_allreduce_microstep: 287.06 | step_microstep: 29.02 +[2025-05-14 21:48:09,110] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2311.38 | bwd: 4061.58 | bwd_inner: 3774.07 | bwd_allreduce: 287.13 | step: 43.49 + 12%|█▏ | 222/1859 [21:19<2:49:08, 6.20s/it] {'loss': 7.1291, 'grad_norm': 38.574615478515625, 'learning_rate': 9.792300925880502e-11, 'epoch': 0.12} + 12%|█▏ | 222/1859 [21:19<2:49:08, 6.20s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1946 +[2025-05-14 21:48:09,906] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 288.35 | bwd_microstep: 462.63 | bwd_inner_microstep: 462.60 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1126 +[2025-05-14 21:48:10,475] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 179.49 | bwd_microstep: 356.45 | bwd_inner_microstep: 356.40 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1888 +[2025-05-14 21:48:11,358] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 324.44 | bwd_microstep: 534.98 | bwd_inner_microstep: 534.95 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 331 +[2025-05-14 21:48:11,614] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 83.05 | bwd_microstep: 141.19 | bwd_inner_microstep: 140.78 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.32 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-14 21:48:12,491] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 332.89 | bwd_microstep: 510.88 | bwd_inner_microstep: 510.85 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-14 21:48:13,374] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 327.21 | bwd_microstep: 520.55 | bwd_inner_microstep: 520.51 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.31 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-14 21:48:14,264] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 332.22 | bwd_microstep: 524.98 | bwd_inner_microstep: 524.96 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1944 +[2025-05-14 21:48:15,441] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.31 | optimizer_step: 18.61 +[2025-05-14 21:48:15,442] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 353.26 | bwd_microstep: 768.16 | bwd_inner_microstep: 553.23 | bwd_allreduce_microstep: 214.86 | step_microstep: 30.51 +[2025-05-14 21:48:15,443] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2220.91 | bwd: 3819.82 | bwd_inner: 3604.29 | bwd_allreduce: 215.07 | step: 42.61 + 12%|█▏ | 223/1859 [21:25<2:50:07, 6.24s/it] {'loss': 3.899, 'grad_norm': 9.308656692504883, 'learning_rate': 9.789808724362483e-11, 'epoch': 0.12} + 12%|█▏ | 223/1859 [21:25<2:50:07, 6.24s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1895 +[2025-05-14 21:48:16,350] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 338.26 | bwd_microstep: 522.07 | bwd_inner_microstep: 522.02 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1374 +[2025-05-14 21:48:17,070] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 266.90 | bwd_microstep: 420.85 | bwd_inner_microstep: 420.60 | bwd_allreduce_microstep: 0.09 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-14 21:48:17,883] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 356.97 | bwd_microstep: 436.27 | bwd_inner_microstep: 436.05 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-14 21:48:18,691] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 295.41 | bwd_microstep: 495.59 | bwd_inner_microstep: 495.43 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-14 21:48:19,581] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 367.84 | bwd_microstep: 492.58 | bwd_inner_microstep: 492.39 | bwd_allreduce_microstep: 0.08 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-14 21:48:20,491] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 397.42 | bwd_microstep: 492.72 | bwd_inner_microstep: 492.43 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-14 21:48:21,409] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 396.92 | bwd_microstep: 500.48 | bwd_inner_microstep: 500.33 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-14 21:48:22,565] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.01 | optimizer_gradients: 2.17 | optimizer_step: 18.74 +[2025-05-14 21:48:22,567] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 368.51 | bwd_microstep: 739.01 | bwd_inner_microstep: 514.57 | bwd_allreduce_microstep: 224.41 | step_microstep: 30.28 +[2025-05-14 21:48:22,567] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2788.17 | bwd: 4099.63 | bwd_inner: 3874.07 | bwd_allreduce: 224.83 | step: 33.26 + 12%|█▏ | 224/1859 [21:32<2:57:15, 6.50s/it] {'loss': 7.3283, 'grad_norm': 31.848270416259766, 'learning_rate': 9.787301980770383e-11, 'epoch': 0.12} + 12%|█▏ | 224/1859 [21:32<2:57:15, 6.50s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1915 +[2025-05-14 21:48:23,463] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 327.00 | bwd_microstep: 530.37 | bwd_inner_microstep: 530.30 | bwd_allreduce_microstep: 0.02 | step_microstep: 2.33 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-14 21:48:24,329] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 305.43 | bwd_microstep: 521.79 | bwd_inner_microstep: 521.75 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-14 21:48:25,191] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 325.48 | bwd_microstep: 500.43 | bwd_inner_microstep: 498.04 | bwd_allreduce_microstep: 2.36 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-14 21:48:25,997] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 331.82 | bwd_microstep: 441.24 | bwd_inner_microstep: 440.91 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-14 21:48:26,782] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 255.20 | bwd_microstep: 513.48 | bwd_inner_microstep: 513.22 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-14 21:48:27,671] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 328.97 | bwd_microstep: 524.52 | bwd_inner_microstep: 524.48 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.83 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 846 +[2025-05-14 21:48:28,118] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 196.37 | bwd_microstep: 222.97 | bwd_inner_microstep: 222.94 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-14 21:48:29,269] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.01 | optimizer_gradients: 1.92 | optimizer_step: 19.21 +[2025-05-14 21:48:29,271] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 329.13 | bwd_microstep: 763.53 | bwd_inner_microstep: 521.65 | bwd_allreduce_microstep: 241.86 | step_microstep: 28.65 +[2025-05-14 21:48:29,272] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2399.39 | bwd: 4018.35 | bwd_inner: 3771.00 | bwd_allreduce: 242.04 | step: 40.26 + 12%|█▏ | 225/1859 [21:39<2:58:46, 6.56s/it] {'loss': 3.4985, 'grad_norm': 12.587929725646973, 'learning_rate': 9.784780702714785e-11, 'epoch': 0.12} + 12%|█▏ | 225/1859 [21:39<2:58:46, 6.56s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-14 21:48:30,172] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 332.63 | bwd_microstep: 521.75 | bwd_inner_microstep: 521.70 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.37 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-14 21:48:31,065] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 332.28 | bwd_microstep: 526.03 | bwd_inner_microstep: 525.98 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.53 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1363 +[2025-05-14 21:48:31,767] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 244.39 | bwd_microstep: 425.39 | bwd_inner_microstep: 425.23 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-14 21:48:32,675] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 366.47 | bwd_microstep: 519.21 | bwd_inner_microstep: 519.17 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.88 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-14 21:48:33,541] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 318.79 | bwd_microstep: 525.19 | bwd_inner_microstep: 525.14 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-14 21:48:34,388] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 319.57 | bwd_microstep: 489.95 | bwd_inner_microstep: 489.79 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 327 +[2025-05-14 21:48:34,618] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 90.43 | bwd_microstep: 123.29 | bwd_inner_microstep: 122.97 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-14 21:48:35,726] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.01 | optimizer_gradients: 2.21 | optimizer_step: 18.86 +[2025-05-14 21:48:35,727] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 261.85 | bwd_microstep: 798.15 | bwd_inner_microstep: 530.79 | bwd_allreduce_microstep: 267.32 | step_microstep: 30.43 +[2025-05-14 21:48:35,728] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2266.36 | bwd: 3929.04 | bwd_inner: 3660.92 | bwd_allreduce: 267.61 | step: 39.95 + 12%|█▏ | 226/1859 [21:45<2:57:46, 6.53s/it] {'loss': 4.9985, 'grad_norm': 28.28873634338379, 'learning_rate': 9.782244897850402e-11, 'epoch': 0.12} + 12%|█▏ | 226/1859 [21:45<2:57:46, 6.53s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1902 +[2025-05-14 21:48:36,631] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 338.04 | bwd_microstep: 522.61 | bwd_inner_microstep: 522.56 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-14 21:48:37,517] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 337.78 | bwd_microstep: 518.13 | bwd_inner_microstep: 518.10 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-14 21:48:38,407] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 335.39 | bwd_microstep: 523.29 | bwd_inner_microstep: 523.25 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.37 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1366 +[2025-05-14 21:48:39,104] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 242.39 | bwd_microstep: 423.84 | bwd_inner_microstep: 423.50 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.21 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-14 21:48:40,017] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 378.94 | bwd_microstep: 514.07 | bwd_inner_microstep: 513.66 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.24 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-14 21:48:40,889] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 329.66 | bwd_microstep: 519.53 | bwd_inner_microstep: 519.49 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.54 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-14 21:48:41,543] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 211.04 | bwd_microstep: 407.61 | bwd_inner_microstep: 407.56 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.52 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-14 21:48:42,697] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.29 | optimizer_step: 16.69 +[2025-05-14 21:48:42,700] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 321.00 | bwd_microstep: 775.90 | bwd_inner_microstep: 515.09 | bwd_allreduce_microstep: 260.78 | step_microstep: 27.41 +[2025-05-14 21:48:42,700] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2494.23 | bwd: 4205.00 | bwd_inner: 3943.28 | bwd_allreduce: 260.96 | step: 37.59 + 12%|█▏ | 227/1859 [21:52<3:01:15, 6.66s/it] {'loss': 4.8119, 'grad_norm': 15.17494010925293, 'learning_rate': 9.779694573876055e-11, 'epoch': 0.12} + 12%|█▏ | 227/1859 [21:52<3:01:15, 6.66s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1887 +[2025-05-14 21:48:43,484] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 240.63 | bwd_microstep: 502.39 | bwd_inner_microstep: 502.13 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.11 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1117 +[2025-05-14 21:48:44,040] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 253.31 | bwd_microstep: 282.37 | bwd_inner_microstep: 282.31 | bwd_allreduce_microstep: 0.02 | step_microstep: 2.34 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1366 +[2025-05-14 21:48:44,758] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 277.06 | bwd_microstep: 408.38 | bwd_inner_microstep: 408.32 | bwd_allreduce_microstep: 0.02 | step_microstep: 1.48 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-14 21:48:45,628] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 319.83 | bwd_microstep: 528.32 | bwd_inner_microstep: 528.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.53 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-14 21:48:46,426] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 241.35 | bwd_microstep: 524.06 | bwd_inner_microstep: 524.01 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.38 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-14 21:48:47,309] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 332.17 | bwd_microstep: 521.55 | bwd_inner_microstep: 521.49 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.56 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1346 +[2025-05-14 21:48:48,015] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 261.27 | bwd_microstep: 413.45 | bwd_inner_microstep: 413.03 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.25 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-14 21:48:49,127] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.24 | optimizer_step: 18.67 +[2025-05-14 21:48:49,128] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 344.51 | bwd_microstep: 718.78 | bwd_inner_microstep: 515.06 | bwd_allreduce_microstep: 203.68 | step_microstep: 29.47 +[2025-05-14 21:48:49,129] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2270.10 | bwd: 3899.31 | bwd_inner: 3694.75 | bwd_allreduce: 203.82 | step: 41.15 + 12%|█▏ | 228/1859 [21:59<2:59:14, 6.59s/it] {'loss': 5.9098, 'grad_norm': 44.85389709472656, 'learning_rate': 9.777129738534639e-11, 'epoch': 0.12} + 12%|█▏ | 228/1859 [21:59<2:59:14, 6.59s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1889 +[2025-05-14 21:48:50,016] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 322.10 | bwd_microstep: 519.50 | bwd_inner_microstep: 519.47 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.56 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-14 21:48:50,891] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 326.77 | bwd_microstep: 515.08 | bwd_inner_microstep: 514.70 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-14 21:48:51,700] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 262.03 | bwd_microstep: 519.00 | bwd_inner_microstep: 518.71 | bwd_allreduce_microstep: 0.26 | step_microstep: 0.22 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-14 21:48:52,569] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 323.39 | bwd_microstep: 524.02 | bwd_inner_microstep: 524.00 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-14 21:48:53,436] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 317.08 | bwd_microstep: 513.71 | bwd_inner_microstep: 513.66 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-14 21:48:54,303] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 319.08 | bwd_microstep: 511.76 | bwd_inner_microstep: 511.72 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1952 +[2025-05-14 21:48:55,237] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 339.27 | bwd_microstep: 560.39 | bwd_inner_microstep: 560.35 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1894 +[2025-05-14 21:48:56,404] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.24 | optimizer_step: 18.69 +[2025-05-14 21:48:56,406] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 319.05 | bwd_microstep: 790.08 | bwd_inner_microstep: 525.95 | bwd_allreduce_microstep: 264.10 | step_microstep: 28.22 +[2025-05-14 21:48:56,407] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2528.75 | bwd: 4453.53 | bwd_inner: 4188.56 | bwd_allreduce: 264.41 | step: 40.61 + 12%|█▏ | 229/1859 [22:06<3:04:42, 6.80s/it] {'loss': 4.8533, 'grad_norm': 29.28453254699707, 'learning_rate': 9.774550399613111e-11, 'epoch': 0.12} + 12%|█▏ | 229/1859 [22:06<3:04:42, 6.80s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1955 +[2025-05-14 21:48:57,331] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 327.88 | bwd_microstep: 552.06 | bwd_inner_microstep: 552.02 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.32 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-14 21:48:58,207] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 324.34 | bwd_microstep: 515.96 | bwd_inner_microstep: 515.91 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.32 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-14 21:48:59,083] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 331.07 | bwd_microstep: 512.20 | bwd_inner_microstep: 512.18 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.50 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-14 21:48:59,902] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 294.14 | bwd_microstep: 496.69 | bwd_inner_microstep: 496.48 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.13 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-14 21:49:00,817] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 403.73 | bwd_microstep: 489.43 | bwd_inner_microstep: 489.28 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-14 21:49:01,730] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 378.18 | bwd_microstep: 512.68 | bwd_inner_microstep: 512.26 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.23 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-14 21:49:02,601] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 327.37 | bwd_microstep: 522.23 | bwd_inner_microstep: 522.20 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.32 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-14 21:49:03,735] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.01 | optimizer_gradients: 3.64 | optimizer_step: 19.61 +[2025-05-14 21:49:03,738] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 314.50 | bwd_microstep: 758.59 | bwd_inner_microstep: 520.78 | bwd_allreduce_microstep: 237.78 | step_microstep: 31.34 +[2025-05-14 21:49:03,738] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2701.16 | bwd: 4359.87 | bwd_inner: 4121.21 | bwd_allreduce: 237.95 | step: 40.29 + 12%|█▏ | 230/1859 [22:13<3:08:55, 6.96s/it] {'loss': 2.918, 'grad_norm': 8.751189231872559, 'learning_rate': 9.771956564942459e-11, 'epoch': 0.12} + 12%|█▏ | 230/1859 [22:14<3:08:55, 6.96s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1891 +[2025-05-14 21:49:04,639] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 323.45 | bwd_microstep: 531.92 | bwd_inner_microstep: 531.88 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.59 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1889 +[2025-05-14 21:49:05,520] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 332.38 | bwd_microstep: 513.14 | bwd_inner_microstep: 513.09 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.51 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1886 +[2025-05-14 21:49:06,400] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 336.46 | bwd_microstep: 511.28 | bwd_inner_microstep: 511.06 | bwd_allreduce_microstep: 0.19 | step_microstep: 0.21 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 845 +[2025-05-14 21:49:06,840] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.99 | bwd_microstep: 219.75 | bwd_inner_microstep: 217.37 | bwd_allreduce_microstep: 2.35 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-14 21:49:07,423] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 275.83 | bwd_microstep: 275.69 | bwd_inner_microstep: 275.35 | bwd_allreduce_microstep: 0.16 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-14 21:49:08,322] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 356.43 | bwd_microstep: 520.64 | bwd_inner_microstep: 520.59 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 324 +[2025-05-14 21:49:08,582] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 80.87 | bwd_microstep: 155.87 | bwd_inner_microstep: 155.83 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.32 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-14 21:49:09,766] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.01 | optimizer_gradients: 2.20 | optimizer_step: 18.68 +[2025-05-14 21:49:09,767] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 333.15 | bwd_microstep: 788.48 | bwd_inner_microstep: 509.33 | bwd_allreduce_microstep: 279.11 | step_microstep: 29.13 +[2025-05-14 21:49:09,767] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2225.54 | bwd: 3516.95 | bwd_inner: 3234.56 | bwd_allreduce: 281.64 | step: 41.58 + 12%|█▏ | 231/1859 [22:20<3:01:14, 6.68s/it] {'loss': 3.3368, 'grad_norm': 8.308090209960938, 'learning_rate': 9.76934824239768e-11, 'epoch': 0.12} + 12%|█▏ | 231/1859 [22:20<3:01:14, 6.68s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1914 +[2025-05-14 21:49:10,626] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 323.25 | bwd_microstep: 494.66 | bwd_inner_microstep: 494.63 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1901 +[2025-05-14 21:49:11,512] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 331.65 | bwd_microstep: 524.05 | bwd_inner_microstep: 524.01 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.37 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1889 +[2025-05-14 21:49:12,412] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 339.36 | bwd_microstep: 532.38 | bwd_inner_microstep: 532.34 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.37 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 844 +[2025-05-14 21:49:12,860] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 210.66 | bwd_microstep: 212.37 | bwd_inner_microstep: 212.33 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.13 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-14 21:49:13,750] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 336.87 | bwd_microstep: 524.08 | bwd_inner_microstep: 524.03 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.25 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-14 21:49:14,636] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 329.30 | bwd_microstep: 527.01 | bwd_inner_microstep: 526.96 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.29 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-14 21:49:15,447] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 335.11 | bwd_microstep: 444.48 | bwd_inner_microstep: 444.32 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2020 +[2025-05-14 21:49:16,669] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.01 | optimizer_gradients: 1.98 | optimizer_step: 18.24 +[2025-05-14 21:49:16,670] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 337.85 | bwd_microstep: 841.31 | bwd_inner_microstep: 528.20 | bwd_allreduce_microstep: 313.07 | step_microstep: 27.55 +[2025-05-14 21:49:16,671] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2544.02 | bwd: 4100.34 | bwd_inner: 3786.85 | bwd_allreduce: 313.18 | step: 37.25 + 12%|█▏ | 232/1859 [22:26<3:02:55, 6.75s/it] {'loss': 4.8759, 'grad_norm': 27.460067749023438, 'learning_rate': 9.76672543989776e-11, 'epoch': 0.12} + 12%|█▏ | 232/1859 [22:26<3:02:55, 6.75s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1889 +[2025-05-14 21:49:17,565] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 343.68 | bwd_microstep: 523.25 | bwd_inner_microstep: 523.23 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.32 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1375 +[2025-05-14 21:49:18,200] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 229.70 | bwd_microstep: 373.89 | bwd_inner_microstep: 373.86 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.51 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 853 +[2025-05-14 21:49:18,647] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 208.34 | bwd_microstep: 207.24 | bwd_inner_microstep: 207.20 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.37 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-14 21:49:19,546] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 339.48 | bwd_microstep: 524.64 | bwd_inner_microstep: 524.58 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.37 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-14 21:49:20,436] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 337.24 | bwd_microstep: 519.96 | bwd_inner_microstep: 519.92 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.37 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-14 21:49:21,336] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 338.49 | bwd_microstep: 526.29 | bwd_inner_microstep: 526.25 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-14 21:49:22,214] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 332.76 | bwd_microstep: 513.66 | bwd_inner_microstep: 513.63 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2091 +[2025-05-14 21:49:23,412] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 1.86 | optimizer_step: 12.78 +[2025-05-14 21:49:23,412] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 368.48 | bwd_microstep: 778.78 | bwd_inner_microstep: 579.24 | bwd_allreduce_microstep: 199.49 | step_microstep: 19.81 +[2025-05-14 21:49:23,413] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2498.14 | bwd: 3967.73 | bwd_inner: 3767.91 | bwd_allreduce: 199.57 | step: 36.48 + 13%|█▎ | 233/1859 [22:33<3:02:46, 6.74s/it] {'loss': 5.6083, 'grad_norm': 45.45652389526367, 'learning_rate': 9.764088165405645e-11, 'epoch': 0.13} + 13%|█▎ | 233/1859 [22:33<3:02:46, 6.74s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1893 +[2025-05-14 21:49:24,186] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 221.84 | bwd_microstep: 528.90 | bwd_inner_microstep: 528.86 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.37 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-14 21:49:25,078] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 337.64 | bwd_microstep: 529.38 | bwd_inner_microstep: 529.34 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.29 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1108 +[2025-05-14 21:49:25,645] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 222.13 | bwd_microstep: 311.40 | bwd_inner_microstep: 311.34 | bwd_allreduce_microstep: 0.02 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-14 21:49:26,524] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 320.19 | bwd_microstep: 524.68 | bwd_inner_microstep: 524.62 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.54 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-14 21:49:27,400] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 319.97 | bwd_microstep: 521.85 | bwd_inner_microstep: 521.80 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.32 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1351 +[2025-05-14 21:49:28,044] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 221.14 | bwd_microstep: 390.30 | bwd_inner_microstep: 390.08 | bwd_allreduce_microstep: 0.08 | step_microstep: 0.14 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-14 21:49:28,963] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 399.87 | bwd_microstep: 492.11 | bwd_inner_microstep: 491.87 | bwd_allreduce_microstep: 0.09 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-14 21:49:30,211] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.24 | optimizer_step: 28.75 +[2025-05-14 21:49:30,212] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 398.35 | bwd_microstep: 794.27 | bwd_inner_microstep: 506.99 | bwd_allreduce_microstep: 287.12 | step_microstep: 37.72 +[2025-05-14 21:49:30,212] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2441.10 | bwd: 4092.95 | bwd_inner: 3805.06 | bwd_allreduce: 287.32 | step: 49.83 + 13%|█▎ | 234/1859 [22:40<3:03:07, 6.76s/it] {'loss': 7.1686, 'grad_norm': 21.25074577331543, 'learning_rate': 9.761436426928216e-11, 'epoch': 0.13} + 13%|█▎ | 234/1859 [22:40<3:03:07, 6.76s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1911 +[2025-05-14 21:49:31,141] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 404.23 | bwd_microstep: 498.79 | bwd_inner_microstep: 498.50 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1919 +[2025-05-14 21:49:32,063] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 406.26 | bwd_microstep: 497.19 | bwd_inner_microstep: 497.01 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1886 +[2025-05-14 21:49:32,746] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.01 | bwd_microstep: 475.18 | bwd_inner_microstep: 475.14 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.52 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 848 +[2025-05-14 21:49:33,183] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 121.81 | bwd_microstep: 294.18 | bwd_inner_microstep: 294.15 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-14 21:49:34,057] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 332.32 | bwd_microstep: 516.05 | bwd_inner_microstep: 516.02 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.36 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1357 +[2025-05-14 21:49:34,683] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 229.75 | bwd_microstep: 360.26 | bwd_inner_microstep: 360.22 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.33 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-14 21:49:35,341] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 349.47 | bwd_microstep: 275.56 | bwd_inner_microstep: 275.24 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-14 21:49:35,938] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.07 | optimizer_gradients: 3.50 | optimizer_step: 15.32 +[2025-05-14 21:49:35,939] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.79 | bwd_microstep: 366.48 | bwd_inner_microstep: 275.11 | bwd_allreduce_microstep: 91.23 | step_microstep: 24.21 +[2025-05-14 21:49:35,940] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2224.60 | bwd: 3283.71 | bwd_inner: 3191.64 | bwd_allreduce: 91.50 | step: 34.09 + 13%|█▎ | 235/1859 [22:46<2:54:35, 6.45s/it] {'loss': 3.1868, 'grad_norm': 16.668916702270508, 'learning_rate': 9.758770232516273e-11, 'epoch': 0.13} + 13%|█▎ | 235/1859 [22:46<2:54:35, 6.45s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-14 21:49:36,879] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 398.48 | bwd_microstep: 515.46 | bwd_inner_microstep: 515.24 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1902 +[2025-05-14 21:49:37,835] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 418.24 | bwd_microstep: 518.04 | bwd_inner_microstep: 517.74 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-14 21:49:38,758] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 368.20 | bwd_microstep: 530.96 | bwd_inner_microstep: 530.92 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-14 21:49:39,855] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 333.81 | bwd_microstep: 735.72 | bwd_inner_microstep: 735.68 | bwd_allreduce_microstep: 0.01 | step_microstep: 4.60 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-14 21:49:41,122] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 414.41 | bwd_microstep: 804.89 | bwd_inner_microstep: 804.63 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.25 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-14 21:49:42,112] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 305.38 | bwd_microstep: 662.55 | bwd_inner_microstep: 662.53 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.44 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-14 21:49:43,404] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 616.86 | bwd_microstep: 634.67 | bwd_inner_microstep: 634.64 | bwd_allreduce_microstep: 0.01 | step_microstep: 4.76 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-14 21:49:45,285] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.29 | optimizer_step: 18.19 +[2025-05-14 21:49:45,286] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 598.04 | bwd_microstep: 1210.03 | bwd_inner_microstep: 772.47 | bwd_allreduce_microstep: 437.48 | step_microstep: 26.90 +[2025-05-14 21:49:45,286] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 3453.39 | bwd: 5612.73 | bwd_inner: 5173.93 | bwd_allreduce: 437.73 | step: 41.52 + 13%|█▎ | 236/1859 [22:55<3:18:00, 7.32s/it] {'loss': 5.1104, 'grad_norm': 19.112035751342773, 'learning_rate': 9.756089590264501e-11, 'epoch': 0.13} + 13%|█▎ | 236/1859 [22:55<3:18:00, 7.32s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 382 +[2025-05-14 21:49:45,535] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 80.75 | bwd_microstep: 146.35 | bwd_inner_microstep: 146.19 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1895 +[2025-05-14 21:49:46,056] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 191.53 | bwd_microstep: 309.30 | bwd_inner_microstep: 308.95 | bwd_allreduce_microstep: 0.14 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-14 21:49:47,304] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 579.22 | bwd_microstep: 642.60 | bwd_inner_microstep: 642.54 | bwd_allreduce_microstep: 0.01 | step_microstep: 4.74 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-14 21:49:48,723] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 585.90 | bwd_microstep: 783.63 | bwd_inner_microstep: 783.59 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.28 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 334 +[2025-05-14 21:49:49,084] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 115.71 | bwd_microstep: 217.57 | bwd_inner_microstep: 217.53 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.45 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1359 +[2025-05-14 21:49:50,133] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 439.35 | bwd_microstep: 566.92 | bwd_inner_microstep: 566.75 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-14 21:49:51,520] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 491.39 | bwd_microstep: 867.58 | bwd_inner_microstep: 867.54 | bwd_allreduce_microstep: 0.01 | step_microstep: 4.94 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-14 21:49:53,492] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.01 | optimizer_gradients: 3.86 | optimizer_step: 19.57 +[2025-05-14 21:49:53,496] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 412.06 | bwd_microstep: 1482.02 | bwd_inner_microstep: 789.56 | bwd_allreduce_microstep: 692.39 | step_microstep: 33.84 +[2025-05-14 21:49:53,496] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2895.83 | bwd: 5016.04 | bwd_inner: 4322.76 | bwd_allreduce: 692.72 | step: 48.67 + 13%|█▎ | 237/1859 [23:03<3:25:09, 7.59s/it] {'loss': 2.6589, 'grad_norm': 8.130491256713867, 'learning_rate': 9.753394508311448e-11, 'epoch': 0.13} + 13%|█▎ | 237/1859 [23:03<3:25:09, 7.59s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1906 +[2025-05-14 21:49:54,994] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 588.96 | bwd_microstep: 840.83 | bwd_inner_microstep: 840.80 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-14 21:49:56,493] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 546.16 | bwd_microstep: 916.86 | bwd_inner_microstep: 916.82 | bwd_allreduce_microstep: 0.01 | step_microstep: 4.47 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1886 +[2025-05-14 21:49:57,744] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 303.33 | bwd_microstep: 907.53 | bwd_inner_microstep: 907.50 | bwd_allreduce_microstep: 0.01 | step_microstep: 4.61 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-14 21:49:59,044] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 547.24 | bwd_microstep: 708.12 | bwd_inner_microstep: 708.06 | bwd_allreduce_microstep: 0.02 | step_microstep: 3.90 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-14 21:50:00,441] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 631.58 | bwd_microstep: 721.97 | bwd_inner_microstep: 721.94 | bwd_allreduce_microstep: 0.00 | step_microstep: 4.60 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-14 21:50:01,689] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 563.78 | bwd_microstep: 637.36 | bwd_inner_microstep: 637.07 | bwd_allreduce_microstep: 0.14 | step_microstep: 0.11 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1087 +[2025-05-14 21:50:02,609] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 381.14 | bwd_microstep: 504.15 | bwd_inner_microstep: 504.11 | bwd_allreduce_microstep: 0.01 | step_microstep: 4.77 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-14 21:50:04,945] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 2.50 | optimizer_gradients: 2.31 | optimizer_step: 29.02 +[2025-05-14 21:50:04,947] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 550.07 | bwd_microstep: 1697.91 | bwd_inner_microstep: 798.78 | bwd_allreduce_microstep: 899.09 | step_microstep: 43.40 +[2025-05-14 21:50:04,948] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4112.26 | bwd: 6934.74 | bwd_inner: 6032.80 | bwd_allreduce: 899.25 | step: 68.24 + 13%|█▎ | 238/1859 [23:15<3:56:19, 8.75s/it] {'loss': 6.411, 'grad_norm': 46.41680908203125, 'learning_rate': 9.750684994839507e-11, 'epoch': 0.13} + 13%|█▎ | 238/1859 [23:15<3:56:19, 8.75s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-14 21:50:06,267] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 627.09 | bwd_microstep: 638.88 | bwd_inner_microstep: 638.82 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-14 21:50:07,689] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 492.12 | bwd_microstep: 893.12 | bwd_inner_microstep: 893.06 | bwd_allreduce_microstep: 0.02 | step_microstep: 4.90 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-14 21:50:08,964] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 352.75 | bwd_microstep: 879.09 | bwd_inner_microstep: 879.03 | bwd_allreduce_microstep: 0.02 | step_microstep: 4.62 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-14 21:50:09,928] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 540.77 | bwd_microstep: 373.93 | bwd_inner_microstep: 373.91 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-14 21:50:11,270] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 418.24 | bwd_microstep: 896.85 | bwd_inner_microstep: 896.79 | bwd_allreduce_microstep: 0.02 | step_microstep: 4.77 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 836 +[2025-05-14 21:50:11,858] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 236.09 | bwd_microstep: 306.81 | bwd_inner_microstep: 306.76 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.49 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-14 21:50:13,223] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 618.97 | bwd_microstep: 711.07 | bwd_inner_microstep: 710.73 | bwd_allreduce_microstep: 0.15 | step_microstep: 0.13 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1975 +[2025-05-14 21:50:15,108] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 1.90 | optimizer_step: 13.03 +[2025-05-14 21:50:15,108] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 577.48 | bwd_microstep: 1264.65 | bwd_inner_microstep: 953.12 | bwd_allreduce_microstep: 311.46 | step_microstep: 20.00 +[2025-05-14 21:50:15,109] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 3863.50 | bwd: 5964.43 | bwd_inner: 5652.32 | bwd_allreduce: 311.68 | step: 41.61 + 13%|█▎ | 239/1859 [23:25<4:07:33, 9.17s/it] {'loss': 4.9316, 'grad_norm': 14.577251434326172, 'learning_rate': 9.747961058074882e-11, 'epoch': 0.13} + 13%|█▎ | 239/1859 [23:25<4:07:33, 9.17s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1920 +[2025-05-14 21:50:16,201] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 221.76 | bwd_microstep: 846.55 | bwd_inner_microstep: 846.51 | bwd_allreduce_microstep: 0.01 | step_microstep: 4.58 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 863 +[2025-05-14 21:50:16,898] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 298.25 | bwd_microstep: 351.08 | bwd_inner_microstep: 350.82 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1886 +[2025-05-14 21:50:18,273] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 479.83 | bwd_microstep: 873.01 | bwd_inner_microstep: 872.95 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-14 21:50:19,657] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 469.82 | bwd_microstep: 875.20 | bwd_inner_microstep: 875.16 | bwd_allreduce_microstep: 0.01 | step_microstep: 4.64 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-14 21:50:20,940] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 444.82 | bwd_microstep: 785.66 | bwd_inner_microstep: 785.61 | bwd_allreduce_microstep: 0.01 | step_microstep: 4.82 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-14 21:50:22,255] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 621.16 | bwd_microstep: 644.33 | bwd_inner_microstep: 644.27 | bwd_allreduce_microstep: 0.02 | step_microstep: 4.77 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 841 +[2025-05-14 21:50:23,045] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 298.23 | bwd_microstep: 440.04 | bwd_inner_microstep: 439.99 | bwd_allreduce_microstep: 0.01 | step_microstep: 4.88 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-14 21:50:24,942] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 4.84 | optimizer_step: 23.76 +[2025-05-14 21:50:24,944] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 316.65 | bwd_microstep: 1499.77 | bwd_inner_microstep: 450.49 | bwd_allreduce_microstep: 1049.22 | step_microstep: 35.70 +[2025-05-14 21:50:24,944] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 3150.48 | bwd: 6315.68 | bwd_inner: 5265.88 | bwd_allreduce: 1049.40 | step: 61.83 + 13%|█▎ | 240/1859 [23:35<4:12:50, 9.37s/it] {'loss': 3.1515, 'grad_norm': 16.75438117980957, 'learning_rate': 9.745222706287565e-11, 'epoch': 0.13} + 13%|█▎ | 240/1859 [23:35<4:12:50, 9.37s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1888 +[2025-05-14 21:50:26,435] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 566.58 | bwd_microstep: 876.89 | bwd_inner_microstep: 876.85 | bwd_allreduce_microstep: 0.01 | step_microstep: 4.08 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 845 +[2025-05-14 21:50:26,963] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 156.60 | bwd_microstep: 328.68 | bwd_inner_microstep: 328.62 | bwd_allreduce_microstep: 0.02 | step_microstep: 4.63 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1361 +[2025-05-14 21:50:28,129] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 432.48 | bwd_microstep: 684.17 | bwd_inner_microstep: 684.13 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.37 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1357 +[2025-05-14 21:50:29,052] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 243.20 | bwd_microstep: 646.75 | bwd_inner_microstep: 646.70 | bwd_allreduce_microstep: 0.02 | step_microstep: 2.58 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-14 21:50:30,384] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 639.10 | bwd_microstep: 650.98 | bwd_inner_microstep: 650.94 | bwd_allreduce_microstep: 0.01 | step_microstep: 4.63 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1345 +[2025-05-14 21:50:31,527] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 444.07 | bwd_microstep: 651.18 | bwd_inner_microstep: 650.85 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-14 21:50:32,824] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 406.03 | bwd_microstep: 868.14 | bwd_inner_microstep: 868.09 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.37 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-14 21:50:34,903] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.01 | optimizer_gradients: 1.98 | optimizer_step: 29.63 +[2025-05-14 21:50:34,905] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 501.65 | bwd_microstep: 1502.45 | bwd_inner_microstep: 703.80 | bwd_allreduce_microstep: 798.59 | step_microstep: 39.76 +[2025-05-14 21:50:34,906] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 3389.69 | bwd: 6209.29 | bwd_inner: 5410.05 | bwd_allreduce: 798.80 | step: 60.60 + 13%|█▎ | 241/1859 [23:45<4:17:29, 9.55s/it] {'loss': 5.189, 'grad_norm': 23.929485321044922, 'learning_rate': 9.742469947791315e-11, 'epoch': 0.13} + 13%|█▎ | 241/1859 [23:45<4:17:29, 9.55s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-14 21:50:36,274] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 616.05 | bwd_microstep: 702.60 | bwd_inner_microstep: 702.25 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.20 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 331 +[2025-05-14 21:50:36,614] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 111.57 | bwd_microstep: 202.66 | bwd_inner_microstep: 202.62 | bwd_allreduce_microstep: 0.01 | step_microstep: 4.78 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-14 21:50:38,012] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 600.08 | bwd_microstep: 751.13 | bwd_inner_microstep: 750.77 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.20 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 848 +[2025-05-14 21:50:38,684] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 231.89 | bwd_microstep: 419.44 | bwd_inner_microstep: 419.40 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-14 21:50:40,064] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 630.59 | bwd_microstep: 710.98 | bwd_inner_microstep: 710.97 | bwd_allreduce_microstep: 0.01 | step_microstep: 4.76 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-14 21:50:41,331] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 596.66 | bwd_microstep: 620.60 | bwd_inner_microstep: 620.56 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-14 21:50:42,813] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 575.91 | bwd_microstep: 870.88 | bwd_inner_microstep: 870.82 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1926 +[2025-05-14 21:50:44,649] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 4.55 | optimizer_step: 21.20 +[2025-05-14 21:50:44,651] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 374.32 | bwd_microstep: 1395.94 | bwd_inner_microstep: 927.73 | bwd_allreduce_microstep: 468.15 | step_microstep: 34.49 +[2025-05-14 21:50:44,652] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 3737.06 | bwd: 5674.30 | bwd_inner: 5205.25 | bwd_allreduce: 468.48 | step: 51.53 + 13%|█▎ | 242/1859 [23:54<4:18:54, 9.61s/it] {'loss': 4.869, 'grad_norm': 17.282793045043945, 'learning_rate': 9.739702790943631e-11, 'epoch': 0.13} + 13%|█▎ | 242/1859 [23:54<4:18:54, 9.61s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-14 21:50:46,146] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 592.62 | bwd_microstep: 838.34 | bwd_inner_microstep: 838.12 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-14 21:50:47,642] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 541.18 | bwd_microstep: 917.01 | bwd_inner_microstep: 916.98 | bwd_allreduce_microstep: 0.00 | step_microstep: 4.78 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 847 +[2025-05-14 21:50:48,059] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 107.73 | bwd_microstep: 274.78 | bwd_inner_microstep: 274.74 | bwd_allreduce_microstep: 0.01 | step_microstep: 4.76 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-14 21:50:49,526] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 594.58 | bwd_microstep: 825.44 | bwd_inner_microstep: 825.00 | bwd_allreduce_microstep: 0.40 | step_microstep: 0.22 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-14 21:50:50,866] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 431.51 | bwd_microstep: 884.51 | bwd_inner_microstep: 884.47 | bwd_allreduce_microstep: 0.01 | step_microstep: 4.12 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 831 +[2025-05-14 21:50:51,431] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 191.12 | bwd_microstep: 338.72 | bwd_inner_microstep: 338.68 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.47 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-14 21:50:52,804] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 606.07 | bwd_microstep: 726.48 | bwd_inner_microstep: 726.06 | bwd_allreduce_microstep: 0.15 | step_microstep: 0.22 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1957 +[2025-05-14 21:50:54,591] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 2.35 | optimizer_gradients: 2.06 | optimizer_step: 18.99 +[2025-05-14 21:50:54,593] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 577.80 | bwd_microstep: 1159.00 | bwd_inner_microstep: 922.02 | bwd_allreduce_microstep: 236.92 | step_microstep: 29.71 +[2025-05-14 21:50:54,595] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 3642.57 | bwd: 5964.32 | bwd_inner: 5726.14 | bwd_allreduce: 237.15 | step: 48.65 + 13%|█▎ | 243/1859 [24:04<4:21:27, 9.71s/it] {'loss': 5.7525, 'grad_norm': 36.458213806152344, 'learning_rate': 9.736921244145725e-11, 'epoch': 0.13} + 13%|█▎ | 243/1859 [24:04<4:21:27, 9.71s/it]dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 867 +[2025-05-14 21:50:55,377] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 326.28 | bwd_microstep: 409.78 | bwd_inner_microstep: 409.73 | bwd_allreduce_microstep: 0.01 | step_microstep: 4.81 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-14 21:50:56,523] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 588.95 | bwd_microstep: 505.05 | bwd_inner_microstep: 505.02 | bwd_allreduce_microstep: 0.01 | step_microstep: 4.63 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-14 21:50:57,910] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 595.44 | bwd_microstep: 743.44 | bwd_inner_microstep: 743.40 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.47 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-14 21:50:59,406] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 562.16 | bwd_microstep: 900.17 | bwd_inner_microstep: 900.14 | bwd_allreduce_microstep: 0.01 | step_microstep: 4.54 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-14 21:51:00,571] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 281.62 | bwd_microstep: 846.30 | bwd_inner_microstep: 846.27 | bwd_allreduce_microstep: 0.01 | step_microstep: 4.55 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-14 21:51:01,883] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 584.81 | bwd_microstep: 676.00 | bwd_inner_microstep: 675.95 | bwd_allreduce_microstep: 0.01 | step_microstep: 4.55 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-14 21:51:03,245] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 589.68 | bwd_microstep: 724.04 | bwd_inner_microstep: 723.99 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1888 +[2025-05-14 21:51:04,774] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 1.98 | optimizer_step: 13.05 +[2025-05-14 21:51:04,775] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 605.10 | bwd_microstep: 861.85 | bwd_inner_microstep: 712.04 | bwd_allreduce_microstep: 149.75 | step_microstep: 20.56 +[2025-05-14 21:51:04,776] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4134.04 | bwd: 5666.64 | bwd_inner: 5516.55 | bwd_allreduce: 149.83 | step: 46.48 + 13%|█▎ | 244/1859 [24:15<4:25:05, 9.85s/it] {'loss': 5.6452, 'grad_norm': 16.03765106201172, 'learning_rate': 9.7341253158425e-11, 'epoch': 0.13} + 13%|█▎ | 244/1859 [24:15<4:25:05, 9.85s/it]dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 871 +[2025-05-14 21:51:05,344] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 113.32 | bwd_microstep: 428.10 | bwd_inner_microstep: 428.07 | bwd_allreduce_microstep: 0.01 | step_microstep: 4.83 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1907 +[2025-05-14 21:51:06,617] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 606.56 | bwd_microstep: 614.73 | bwd_inner_microstep: 614.68 | bwd_allreduce_microstep: 0.02 | step_microstep: 4.77 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 347 +[2025-05-14 21:51:07,038] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 158.91 | bwd_microstep: 215.17 | bwd_inner_microstep: 215.14 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.49 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-14 21:51:08,426] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 637.51 | bwd_microstep: 710.48 | bwd_inner_microstep: 710.44 | bwd_allreduce_microstep: 0.01 | step_microstep: 4.61 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 846 +[2025-05-14 21:51:09,210] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 310.88 | bwd_microstep: 421.65 | bwd_inner_microstep: 421.59 | bwd_allreduce_microstep: 0.01 | step_microstep: 4.62 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-14 21:51:10,471] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 402.18 | bwd_microstep: 807.12 | bwd_inner_microstep: 807.08 | bwd_allreduce_microstep: 0.01 | step_microstep: 4.77 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-14 21:51:11,766] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 608.14 | bwd_microstep: 634.35 | bwd_inner_microstep: 634.31 | bwd_allreduce_microstep: 0.01 | step_microstep: 4.63 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-14 21:51:13,126] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 1.90 | optimizer_step: 22.89 +[2025-05-14 21:51:13,128] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 591.92 | bwd_microstep: 693.94 | bwd_inner_microstep: 630.66 | bwd_allreduce_microstep: 63.12 | step_microstep: 29.96 +[2025-05-14 21:51:13,129] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 3429.39 | bwd: 4525.56 | bwd_inner: 4462.03 | bwd_allreduce: 63.17 | step: 60.69 + 13%|█▎ | 245/1859 [24:23<4:12:52, 9.40s/it] {'loss': 4.8691, 'grad_norm': 15.115960121154785, 'learning_rate': 9.731315014522517e-11, 'epoch': 0.13} + 13%|█▎ | 245/1859 [24:23<4:12:52, 9.40s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1896 +[2025-05-14 21:51:14,382] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 326.18 | bwd_microstep: 879.48 | bwd_inner_microstep: 879.45 | bwd_allreduce_microstep: 0.01 | step_microstep: 4.78 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1382 +[2025-05-14 21:51:15,312] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 438.58 | bwd_microstep: 439.93 | bwd_inner_microstep: 439.89 | bwd_allreduce_microstep: 0.01 | step_microstep: 4.64 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-14 21:51:16,749] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 596.19 | bwd_microstep: 793.09 | bwd_inner_microstep: 793.07 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.58 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-14 21:51:18,239] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 580.16 | bwd_microstep: 875.68 | bwd_inner_microstep: 875.47 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-14 21:51:19,530] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 379.27 | bwd_microstep: 888.96 | bwd_inner_microstep: 888.93 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.56 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-14 21:51:20,816] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 519.46 | bwd_microstep: 729.23 | bwd_inner_microstep: 729.19 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.41 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-14 21:51:22,054] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 621.79 | bwd_microstep: 571.46 | bwd_inner_microstep: 571.43 | bwd_allreduce_microstep: 0.01 | step_microstep: 4.62 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1921 +[2025-05-14 21:51:24,378] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 1.92 | optimizer_step: 13.05 +[2025-05-14 21:51:24,379] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 625.60 | bwd_microstep: 1640.24 | bwd_inner_microstep: 698.48 | bwd_allreduce_microstep: 941.65 | step_microstep: 19.97 +[2025-05-14 21:51:24,379] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 4087.21 | bwd: 6818.10 | bwd_inner: 5876.02 | bwd_allreduce: 941.76 | step: 41.68 + 13%|█▎ | 246/1859 [24:34<4:27:36, 9.95s/it] {'loss': 3.0918, 'grad_norm': 19.162397384643555, 'learning_rate': 9.728490348717978e-11, 'epoch': 0.13} + 13%|█▎ | 246/1859 [24:34<4:27:36, 9.95s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1888 +[2025-05-14 21:51:25,645] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 334.87 | bwd_microstep: 906.21 | bwd_inner_microstep: 906.16 | bwd_allreduce_microstep: 0.01 | step_microstep: 4.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-14 21:51:26,925] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 540.04 | bwd_microstep: 700.95 | bwd_inner_microstep: 700.49 | bwd_allreduce_microstep: 0.43 | step_microstep: 0.59 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-14 21:51:28,293] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 634.64 | bwd_microstep: 693.65 | bwd_inner_microstep: 693.61 | bwd_allreduce_microstep: 0.01 | step_microstep: 4.55 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-15 00:27:48,637] [INFO] [real_accelerator.py:203:get_accelerator] Setting ds_accelerator to cuda (auto detect) +/home1/gmh/anaconda3/envs/promptbench/lib/python3.9/site-packages/timm/models/layers/__init__.py:48: FutureWarning: Importing from timm.models.layers is deprecated, please import via timm.layers + warnings.warn(f"Importing from {__name__} is deprecated, please import via timm.layers", FutureWarning) +petrel_client is not installed. If you read data locally instead of from ceph, ignore it. +petrel_client is not installed. Using PIL to load images. +[2025-05-15 00:27:53,255] [INFO] [comm.py:652:init_distributed] cdb=None +[2025-05-15 00:27:53,255] [INFO] [comm.py:683:init_distributed] Initializing TorchBackend in DeepSpeed with backend nccl +05/15/2025 00:27:53 - WARNING - __main__ - Process rank: 0, device: cuda:0, n_gpu: 1distributed training: True, 16-bits training: False +05/15/2025 00:27:53 - INFO - __main__ - Training/evaluation parameters TrainingArguments( +_n_gpu=1, +accelerator_config={'split_batches': False, 'dispatch_batches': None, 'even_batches': True, 'use_seedable_sampler': True, 'non_blocking': False, 'gradient_accumulation_kwargs': None, 'use_configured_state': False}, +adafactor=False, +adam_beta1=0.9, +adam_beta2=0.999, +adam_epsilon=1e-08, +auto_find_batch_size=False, +batch_eval_metrics=False, +bf16=True, +bf16_full_eval=False, +data_seed=None, +dataloader_drop_last=False, +dataloader_num_workers=4, +dataloader_persistent_workers=False, +dataloader_pin_memory=True, +dataloader_prefetch_factor=None, +ddp_backend=None, +ddp_broadcast_buffers=None, +ddp_bucket_cap_mb=None, +ddp_find_unused_parameters=None, +ddp_timeout=1800, +debug=[], +deepspeed=zero_stage1_config.json, +disable_tqdm=False, +dispatch_batches=None, +do_eval=False, +do_predict=False, +do_train=True, +eval_accumulation_steps=None, +eval_delay=0, +eval_do_concat_batches=True, +eval_on_start=False, +eval_steps=None, +eval_strategy=no, +eval_use_gather_object=False, +evaluation_strategy=no, +fp16=False, +fp16_backend=auto, +fp16_full_eval=False, +fp16_opt_level=O1, +fsdp=[], +fsdp_config={'min_num_params': 0, 'xla': False, 'xla_fsdp_v2': False, 'xla_fsdp_grad_ckpt': False}, +fsdp_min_num_params=0, +fsdp_transformer_layer_cls_to_wrap=None, +full_determinism=False, +gradient_accumulation_steps=8, +gradient_checkpointing=False, +gradient_checkpointing_kwargs=None, +greater_is_better=None, +group_by_length=True, +half_precision_backend=auto, +hub_always_push=False, +hub_model_id=None, +hub_private_repo=False, +hub_strategy=every_save, +hub_token=, +ignore_data_skip=False, +include_inputs_for_metrics=False, +include_num_input_tokens_seen=False, +include_tokens_per_second=False, +jit_mode_eval=False, +label_names=None, +label_smoothing_factor=0.0, +learning_rate=1e-15, +length_column_name=length, +load_best_model_at_end=False, +local_rank=0, +log_level=passive, +log_level_replica=warning, +log_on_each_node=True, +logging_dir=work_dirs/internvl_chat_v2_5/mmvet/runs/May15_00-27-53_9007, +logging_first_step=False, +logging_nan_inf_filter=True, +logging_steps=1.0, +logging_strategy=steps, +lr_scheduler_kwargs={}, +lr_scheduler_type=cosine, +max_grad_norm=1.0, +max_steps=-1, +metric_for_best_model=None, +mp_parameters=, +neftune_noise_alpha=None, +no_cuda=False, +num_train_epochs=0.3, +optim=adamw_torch, +optim_args=None, +optim_target_modules=None, +output_dir=work_dirs/internvl_chat_v2_5/mmvet, +overwrite_output_dir=True, +past_index=-1, +per_device_eval_batch_size=8, +per_device_train_batch_size=1, +prediction_loss_only=False, +push_to_hub=False, +push_to_hub_model_id=None, +push_to_hub_organization=None, +push_to_hub_token=, +ray_scope=last, +remove_unused_columns=True, +report_to=['tensorboard'], +restore_callback_states_from_checkpoint=False, +resume_from_checkpoint=None, +run_name=work_dirs/internvl_chat_v2_5/mmvet, +save_on_each_node=False, +save_only_model=False, +save_safetensors=True, +save_steps=100, +save_strategy=steps, +save_total_limit=100, +seed=42, +skip_memory_metrics=True, +split_batches=None, +tf32=None, +torch_compile=False, +torch_compile_backend=None, +torch_compile_mode=None, +torch_empty_cache_steps=None, +torchdynamo=None, +tpu_metrics_debug=False, +tpu_num_cores=None, +use_cpu=False, +use_ipex=False, +use_legacy_prediction_loop=False, +use_mps_device=False, +warmup_ratio=0.03, +warmup_steps=0, +weight_decay=0.01, +) +05/15/2025 00:27:53 - INFO - __main__ - Loading Tokenizer: /home1/gmh/InternVL/InternVL_2_5 +[INFO|tokenization_utils_base.py:2287] 2025-05-15 00:27:53,378 >> loading file ./tokenizer.model +[INFO|tokenization_utils_base.py:2287] 2025-05-15 00:27:53,378 >> loading file added_tokens.json +[INFO|tokenization_utils_base.py:2287] 2025-05-15 00:27:53,378 >> loading file special_tokens_map.json +[INFO|tokenization_utils_base.py:2287] 2025-05-15 00:27:53,378 >> loading file tokenizer_config.json +[INFO|tokenization_utils_base.py:2287] 2025-05-15 00:27:53,378 >> loading file tokenizer.json +[INFO|tokenization_utils_base.py:2533] 2025-05-15 00:27:53,566 >> Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained. +05/15/2025 00:27:53 - INFO - __main__ - Loading InternVLChatModel... +[INFO|configuration_utils.py:731] 2025-05-15 00:27:53,708 >> loading configuration file /home1/gmh/InternVL/InternVL_2_5/config.json +[INFO|configuration_utils.py:800] 2025-05-15 00:27:53,710 >> Model config InternVLChatConfig { + "_commit_hash": null, + "architectures": [ + "InternVLChatModel" + ], + "auto_map": { + "AutoConfig": "configuration_internvl_chat.InternVLChatConfig", + "AutoModel": "modeling_internvl_chat.InternVLChatModel", + "AutoModelForCausalLM": "modeling_internvl_chat.InternVLChatModel" + }, + "downsample_ratio": 0.5, + "dynamic_image_size": true, + "force_image_size": 448, + "hidden_size": 2048, + "llm_config": { + "_name_or_path": "internlm/internlm2_5-1_8b-chat", + "add_cross_attention": false, + "architectures": [ + "InternLM2ForCausalLM" + ], + "attn_implementation": "flash_attention_2", + "auto_map": { + "AutoConfig": "configuration_internlm2.InternLM2Config", + "AutoModel": "modeling_internlm2.InternLM2ForCausalLM", + "AutoModelForCausalLM": "modeling_internlm2.InternLM2ForCausalLM", + "AutoModelForSequenceClassification": "modeling_internlm2.InternLM2ForSequenceClassification" + }, + "bad_words_ids": null, + "begin_suppress_tokens": null, + "bias": false, + "bos_token_id": 1, + "chunk_size_feed_forward": 0, + "cross_attention_hidden_size": null, + "decoder_start_token_id": null, + "diversity_penalty": 0.0, + "do_sample": false, + "early_stopping": false, + "encoder_no_repeat_ngram_size": 0, + "eos_token_id": 2, + "exponential_decay_length_penalty": null, + "finetuning_task": null, + "forced_bos_token_id": null, + "forced_eos_token_id": null, + "hidden_act": "silu", + "hidden_size": 2048, + "id2label": { + "0": "LABEL_0", + "1": "LABEL_1" + }, + "initializer_range": 0.02, + "intermediate_size": 8192, + "is_decoder": false, + "is_encoder_decoder": false, + "label2id": { + "LABEL_0": 0, + "LABEL_1": 1 + }, + "length_penalty": 1.0, + "max_length": 20, + "max_position_embeddings": 32768, + "min_length": 0, + "model_type": "internlm2", + "no_repeat_ngram_size": 0, + "num_attention_heads": 16, + "num_beam_groups": 1, + "num_beams": 1, + "num_hidden_layers": 24, + "num_key_value_heads": 8, + "num_return_sequences": 1, + "output_attentions": false, + "output_hidden_states": false, + "output_scores": false, + "pad_token_id": 2, + "prefix": null, + "pretraining_tp": 1, + "problem_type": null, + "pruned_heads": {}, + "remove_invalid_values": false, + "repetition_penalty": 1.0, + "return_dict": true, + "return_dict_in_generate": false, + "rms_norm_eps": 1e-05, + "rope_scaling": { + "factor": 2.0, + "type": "dynamic" + }, + "rope_theta": 1000000, + "sep_token_id": null, + "suppress_tokens": null, + "task_specific_params": null, + "temperature": 1.0, + "tf_legacy_loss": false, + "tie_encoder_decoder": false, + "tie_word_embeddings": false, + "tokenizer_class": null, + "top_k": 50, + "top_p": 1.0, + "torch_dtype": "bfloat16", + "torchscript": false, + "transformers_version": "4.43.2", + "typical_p": 1.0, + "use_bfloat16": true, + "use_cache": true, + "vocab_size": 92553 + }, + "max_dynamic_patch": 12, + "min_dynamic_patch": 1, + "model_type": "internvl_chat", + "pad2square": false, + "ps_version": "v2", + "select_layer": -1, + "template": "internvl2_5", + "tie_word_embeddings": false, + "torch_dtype": "bfloat16", + "transformers_version": null, + "use_backbone_lora": 0, + "use_llm_lora": 0, + "use_thumbnail": true, + "vision_config": { + "_name_or_path": "", + "add_cross_attention": false, + "architectures": [ + "InternVisionModel" + ], + "attention_dropout": 0.0, + "bad_words_ids": null, + "begin_suppress_tokens": null, + "bos_token_id": null, + "chunk_size_feed_forward": 0, + "cross_attention_hidden_size": null, + "decoder_start_token_id": null, + "diversity_penalty": 0.0, + "do_sample": false, + "drop_path_rate": 0.0, + "dropout": 0.0, + "early_stopping": false, + "encoder_no_repeat_ngram_size": 0, + "eos_token_id": null, + "exponential_decay_length_penalty": null, + "finetuning_task": null, + "forced_bos_token_id": null, + "forced_eos_token_id": null, + "hidden_act": "gelu", + "hidden_size": 1024, + "id2label": { + "0": "LABEL_0", + "1": "LABEL_1" + }, + "image_size": 448, + "initializer_factor": 1.0, + "initializer_range": 0.02, + "intermediate_size": 4096, + "is_decoder": false, + "is_encoder_decoder": false, + "label2id": { + "LABEL_0": 0, + "LABEL_1": 1 + }, + "layer_norm_eps": 1e-06, + "length_penalty": 1.0, + "max_length": 20, + "min_length": 0, + "model_type": "intern_vit_6b", + "no_repeat_ngram_size": 0, + "norm_type": "layer_norm", + "num_attention_heads": 16, + "num_beam_groups": 1, + "num_beams": 1, + "num_channels": 3, + "num_hidden_layers": 24, + "num_return_sequences": 1, + "output_attentions": false, + "output_hidden_states": false, + "output_scores": false, + "pad_token_id": null, + "patch_size": 14, + "prefix": null, + "problem_type": null, + "pruned_heads": {}, + "qk_normalization": false, + "qkv_bias": true, + "remove_invalid_values": false, + "repetition_penalty": 1.0, + "return_dict": true, + "return_dict_in_generate": false, + "sep_token_id": null, + "suppress_tokens": null, + "task_specific_params": null, + "temperature": 1.0, + "tf_legacy_loss": false, + "tie_encoder_decoder": false, + "tie_word_embeddings": true, + "tokenizer_class": null, + "top_k": 50, + "top_p": 1.0, + "torch_dtype": "bfloat16", + "torchscript": false, + "transformers_version": "4.43.2", + "typical_p": 1.0, + "use_bfloat16": true, + "use_flash_attn": true + } +} + +05/15/2025 00:27:53 - INFO - __main__ - Using flash_attention_2 for InternLM +[INFO|modeling_utils.py:3631] 2025-05-15 00:27:53,711 >> loading weights file /home1/gmh/InternVL/InternVL_2_5/model.safetensors +[INFO|modeling_utils.py:1572] 2025-05-15 00:27:53,730 >> Instantiating InternVLChatModel model under default dtype torch.bfloat16. +[INFO|configuration_utils.py:1038] 2025-05-15 00:27:53,732 >> Generate config GenerationConfig {} + +[INFO|configuration_utils.py:1038] 2025-05-15 00:27:53,782 >> Generate config GenerationConfig { + "bos_token_id": 1, + "eos_token_id": 2, + "pad_token_id": 2 +} + +[INFO|modeling_utils.py:4463] 2025-05-15 00:27:54,091 >> All model checkpoint weights were used when initializing InternVLChatModel. + +[INFO|modeling_utils.py:4471] 2025-05-15 00:27:54,091 >> All the weights of InternVLChatModel were initialized from the model checkpoint at /home1/gmh/InternVL/InternVL_2_5. +If your task is similar to the task the model of the checkpoint was trained on, you can already use InternVLChatModel for predictions without further training. +[INFO|configuration_utils.py:991] 2025-05-15 00:27:54,100 >> loading configuration file /home1/gmh/InternVL/InternVL_2_5/generation_config.json +[INFO|configuration_utils.py:1038] 2025-05-15 00:27:54,101 >> Generate config GenerationConfig { + "eos_token_id": [ + 92542, + 92543 + ] +} + +05/15/2025 00:27:54 - INFO - __main__ - Finished +05/15/2025 00:27:54 - INFO - __main__ - model.config.force_image_size: 448 +05/15/2025 00:27:54 - INFO - __main__ - data_args.force_image_size: 448 +05/15/2025 00:27:54 - INFO - __main__ - model.config.vision_config.image_size: 448 +05/15/2025 00:27:54 - INFO - __main__ - [Dataset] num_image_token: 256 +05/15/2025 00:27:54 - INFO - __main__ - [Dataset] dynamic_image_size: True +05/15/2025 00:27:54 - INFO - __main__ - [Dataset] use_thumbnail: True +05/15/2025 00:27:54 - INFO - __main__ - [Dataset] min_dynamic_patch: 1, max_dynamic_patch: 6 +05/15/2025 00:27:54 - INFO - __main__ - Formatting inputs...Skip in lazy mode +05/15/2025 00:27:54 - INFO - __main__ - Add dataset: extend2 with length: 14874 +trainable params: 15,728,640 || all params: 1,904,875,520 || trainable%: 0.8257 +05/15/2025 00:27:55 - INFO - __main__ - language_model.base_model.model.model.layers.0.attention.wqkv.lora_A.default.weight +05/15/2025 00:27:55 - INFO - __main__ - language_model.base_model.model.model.layers.0.attention.wqkv.lora_B.default.weight +05/15/2025 00:27:55 - INFO - __main__ - language_model.base_model.model.model.layers.0.attention.wo.lora_A.default.weight +05/15/2025 00:27:55 - INFO - __main__ - language_model.base_model.model.model.layers.0.attention.wo.lora_B.default.weight 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__main__ - language_model.base_model.model.model.layers.23.feed_forward.w2.lora_B.default.weight +[INFO|trainer.py:648] 2025-05-15 00:27:55,447 >> Using auto half precision backend +[2025-05-15 00:27:55,972] [INFO] [logging.py:96:log_dist] [Rank 0] DeepSpeed info: version=0.15.1, git-hash=unknown, git-branch=unknown +[2025-05-15 00:27:55,972] [INFO] [config.py:733:__init__] Config mesh_device None world_size = 1 +[2025-05-15 00:27:58,734] [INFO] [logging.py:96:log_dist] [Rank 0] DeepSpeed Flops Profiler Enabled: False +Using /home1/gmh/.cache/torch_extensions/py39_cu121 as PyTorch extensions root... +Emitting ninja build file /home1/gmh/.cache/torch_extensions/py39_cu121/cpu_adam/build.ninja... +Building extension module cpu_adam... +Allowing ninja to set a default number of workers... (overridable by setting the environment variable MAX_JOBS=N) +ninja: no work to do. +Loading extension module cpu_adam... +Time to load cpu_adam op: 3.152613639831543 seconds +Adam Optimizer #0 is created with AVX512 arithmetic capability. +Config: alpha=0.000000, betas=(0.900000, 0.999000), weight_decay=0.010000, adam_w=1 +[2025-05-15 00:28:03,150] [INFO] [logging.py:96:log_dist] [Rank 0] Using DeepSpeed Optimizer param name adamw as basic optimizer +[2025-05-15 00:28:03,150] [INFO] [logging.py:96:log_dist] [Rank 0] Removing param_group that has no 'params' in the basic Optimizer +[2025-05-15 00:28:03,198] [INFO] [logging.py:96:log_dist] [Rank 0] DeepSpeed Basic Optimizer = DeepSpeedCPUAdam +[2025-05-15 00:28:03,198] [INFO] [utils.py:59:is_zero_supported_optimizer] Checking ZeRO support for optimizer=DeepSpeedCPUAdam type= +[2025-05-15 00:28:03,199] [INFO] [logging.py:96:log_dist] [Rank 0] Creating torch.bfloat16 ZeRO stage 1 optimizer +[2025-05-15 00:28:03,199] [INFO] [stage_1_and_2.py:148:__init__] Reduce bucket size 1000000000 +[2025-05-15 00:28:03,199] [INFO] [stage_1_and_2.py:149:__init__] Allgather bucket size 1000000000 +[2025-05-15 00:28:03,199] [INFO] [stage_1_and_2.py:150:__init__] CPU Offload: True +[2025-05-15 00:28:03,199] [INFO] [stage_1_and_2.py:151:__init__] Round robin gradient partitioning: False +[2025-05-15 00:28:03,891] [INFO] [utils.py:781:see_memory_usage] Before initializing optimizer states +[2025-05-15 00:28:03,892] [INFO] [utils.py:782:see_memory_usage] MA 4.51 GB Max_MA 4.51 GB CA 4.7 GB Max_CA 5 GB +[2025-05-15 00:28:03,892] [INFO] [utils.py:789:see_memory_usage] CPU Virtual Memory: used = 358.48 GB, percent = 47.5% +[2025-05-15 00:28:04,164] [INFO] [utils.py:781:see_memory_usage] After initializing optimizer states +[2025-05-15 00:28:04,165] [INFO] [utils.py:782:see_memory_usage] MA 4.51 GB Max_MA 4.51 GB CA 4.7 GB Max_CA 5 GB +[2025-05-15 00:28:04,165] [INFO] [utils.py:789:see_memory_usage] CPU Virtual Memory: used = 358.55 GB, percent = 47.5% +[2025-05-15 00:28:04,165] [INFO] [stage_1_and_2.py:543:__init__] optimizer state initialized +[2025-05-15 00:28:04,403] [INFO] [utils.py:781:see_memory_usage] After initializing ZeRO optimizer +[2025-05-15 00:28:04,404] [INFO] [utils.py:782:see_memory_usage] MA 4.51 GB Max_MA 4.51 GB CA 4.7 GB Max_CA 5 GB +[2025-05-15 00:28:04,404] [INFO] [utils.py:789:see_memory_usage] CPU Virtual Memory: used = 358.57 GB, percent = 47.5% +[2025-05-15 00:28:04,413] [INFO] [logging.py:96:log_dist] [Rank 0] DeepSpeed Final Optimizer = DeepSpeedZeroOptimizer +[2025-05-15 00:28:04,413] [INFO] [logging.py:96:log_dist] [Rank 0] DeepSpeed using client callable to create LR scheduler +[2025-05-15 00:28:04,413] [INFO] [logging.py:96:log_dist] [Rank 0] DeepSpeed LR Scheduler = +[2025-05-15 00:28:04,413] [INFO] [logging.py:96:log_dist] [Rank 0] step=0, skipped=0, lr=[0.0], mom=[[0.9, 0.999]] +[2025-05-15 00:28:04,419] [INFO] [config.py:999:print] DeepSpeedEngine configuration: +[2025-05-15 00:28:04,419] [INFO] [config.py:1003:print] activation_checkpointing_config { + "partition_activations": false, + "contiguous_memory_optimization": false, + "cpu_checkpointing": false, + "number_checkpoints": null, + "synchronize_checkpoint_boundary": false, + "profile": false +} +[2025-05-15 00:28:04,419] [INFO] [config.py:1003:print] aio_config ................... {'block_size': 1048576, 'queue_depth': 8, 'thread_count': 1, 'single_submit': False, 'overlap_events': True, 'use_gds': False} +[2025-05-15 00:28:04,419] [INFO] [config.py:1003:print] amp_enabled .................. False +[2025-05-15 00:28:04,419] [INFO] [config.py:1003:print] amp_params ................... False +[2025-05-15 00:28:04,419] [INFO] [config.py:1003:print] autotuning_config ............ { + "enabled": false, + "start_step": null, + "end_step": null, + "metric_path": null, + "arg_mappings": null, + "metric": "throughput", + "model_info": null, + "results_dir": "autotuning_results", + "exps_dir": "autotuning_exps", + "overwrite": true, + "fast": true, + "start_profile_step": 3, + "end_profile_step": 5, + "tuner_type": "gridsearch", + "tuner_early_stopping": 5, + "tuner_num_trials": 50, + "model_info_path": null, + "mp_size": 1, + "max_train_batch_size": null, + "min_train_batch_size": 1, + "max_train_micro_batch_size_per_gpu": 1.024000e+03, + "min_train_micro_batch_size_per_gpu": 1, + "num_tuning_micro_batch_sizes": 3 +} +[2025-05-15 00:28:04,420] [INFO] [config.py:1003:print] bfloat16_enabled ............. True +[2025-05-15 00:28:04,420] [INFO] [config.py:1003:print] bfloat16_immediate_grad_update False +[2025-05-15 00:28:04,420] [INFO] [config.py:1003:print] checkpoint_parallel_write_pipeline False +[2025-05-15 00:28:04,420] [INFO] [config.py:1003:print] checkpoint_tag_validation_enabled True +[2025-05-15 00:28:04,420] [INFO] [config.py:1003:print] checkpoint_tag_validation_fail False +[2025-05-15 00:28:04,420] [INFO] [config.py:1003:print] comms_config ................. +[2025-05-15 00:28:04,420] [INFO] [config.py:1003:print] communication_data_type ...... None +[2025-05-15 00:28:04,420] [INFO] [config.py:1003:print] compression_config ........... {'weight_quantization': {'shared_parameters': {'enabled': False, 'quantizer_kernel': False, 'schedule_offset': 0, 'quantize_groups': 1, 'quantize_verbose': False, 'quantization_type': 'symmetric', 'quantize_weight_in_forward': False, 'rounding': 'nearest', 'fp16_mixed_quantize': False, 'quantize_change_ratio': 0.001}, 'different_groups': {}}, 'activation_quantization': {'shared_parameters': {'enabled': False, 'quantization_type': 'symmetric', 'range_calibration': 'dynamic', 'schedule_offset': 1000}, 'different_groups': {}}, 'sparse_pruning': {'shared_parameters': {'enabled': False, 'method': 'l1', 'schedule_offset': 1000}, 'different_groups': {}}, 'row_pruning': {'shared_parameters': {'enabled': False, 'method': 'l1', 'schedule_offset': 1000}, 'different_groups': {}}, 'head_pruning': {'shared_parameters': {'enabled': False, 'method': 'topk', 'schedule_offset': 1000}, 'different_groups': {}}, 'channel_pruning': {'shared_parameters': {'enabled': False, 'method': 'l1', 'schedule_offset': 1000}, 'different_groups': {}}, 'layer_reduction': {'enabled': False}} +[2025-05-15 00:28:04,420] [INFO] [config.py:1003:print] curriculum_enabled_legacy .... False +[2025-05-15 00:28:04,420] [INFO] [config.py:1003:print] curriculum_params_legacy ..... False +[2025-05-15 00:28:04,420] [INFO] [config.py:1003:print] data_efficiency_config ....... {'enabled': False, 'seed': 1234, 'data_sampling': {'enabled': False, 'num_epochs': 1000, 'num_workers': 0, 'curriculum_learning': {'enabled': False}}, 'data_routing': {'enabled': False, 'random_ltd': {'enabled': False, 'layer_token_lr_schedule': {'enabled': False}}}} +[2025-05-15 00:28:04,420] [INFO] [config.py:1003:print] data_efficiency_enabled ...... False +[2025-05-15 00:28:04,420] [INFO] [config.py:1003:print] dataloader_drop_last ......... False +[2025-05-15 00:28:04,420] [INFO] [config.py:1003:print] disable_allgather ............ False +[2025-05-15 00:28:04,420] [INFO] [config.py:1003:print] dump_state ................... False +[2025-05-15 00:28:04,420] [INFO] [config.py:1003:print] dynamic_loss_scale_args ...... None +[2025-05-15 00:28:04,420] [INFO] [config.py:1003:print] eigenvalue_enabled ........... False +[2025-05-15 00:28:04,420] [INFO] [config.py:1003:print] eigenvalue_gas_boundary_resolution 1 +[2025-05-15 00:28:04,420] [INFO] [config.py:1003:print] eigenvalue_layer_name ........ bert.encoder.layer +[2025-05-15 00:28:04,420] [INFO] [config.py:1003:print] eigenvalue_layer_num ......... 0 +[2025-05-15 00:28:04,420] [INFO] [config.py:1003:print] eigenvalue_max_iter .......... 100 +[2025-05-15 00:28:04,420] [INFO] [config.py:1003:print] eigenvalue_stability ......... 1e-06 +[2025-05-15 00:28:04,420] [INFO] [config.py:1003:print] eigenvalue_tol ............... 0.01 +[2025-05-15 00:28:04,420] [INFO] [config.py:1003:print] eigenvalue_verbose ........... False +[2025-05-15 00:28:04,420] [INFO] [config.py:1003:print] elasticity_enabled ........... False +[2025-05-15 00:28:04,420] [INFO] [config.py:1003:print] flops_profiler_config ........ { + "enabled": false, + "recompute_fwd_factor": 0.0, + "profile_step": 1, + "module_depth": -1, + "top_modules": 1, + "detailed": true, + "output_file": null +} +[2025-05-15 00:28:04,420] [INFO] [config.py:1003:print] fp16_auto_cast ............... None +[2025-05-15 00:28:04,420] [INFO] [config.py:1003:print] fp16_enabled ................. False +[2025-05-15 00:28:04,420] [INFO] [config.py:1003:print] fp16_master_weights_and_gradients False +[2025-05-15 00:28:04,420] [INFO] [config.py:1003:print] global_rank .................. 0 +[2025-05-15 00:28:04,420] [INFO] [config.py:1003:print] grad_accum_dtype ............. None +[2025-05-15 00:28:04,420] [INFO] [config.py:1003:print] gradient_accumulation_steps .. 8 +[2025-05-15 00:28:04,420] [INFO] [config.py:1003:print] gradient_clipping ............ 1.0 +[2025-05-15 00:28:04,420] [INFO] [config.py:1003:print] gradient_predivide_factor .... 1.0 +[2025-05-15 00:28:04,420] [INFO] [config.py:1003:print] graph_harvesting ............. False +[2025-05-15 00:28:04,420] [INFO] [config.py:1003:print] hybrid_engine ................ enabled=False max_out_tokens=512 inference_tp_size=1 release_inference_cache=False pin_parameters=True tp_gather_partition_size=8 +[2025-05-15 00:28:04,420] [INFO] [config.py:1003:print] initial_dynamic_scale ........ 1 +[2025-05-15 00:28:04,420] [INFO] [config.py:1003:print] load_universal_checkpoint .... False +[2025-05-15 00:28:04,420] [INFO] [config.py:1003:print] loss_scale ................... 1.0 +[2025-05-15 00:28:04,420] [INFO] [config.py:1003:print] memory_breakdown ............. False +[2025-05-15 00:28:04,420] [INFO] [config.py:1003:print] mics_hierarchial_params_gather False +[2025-05-15 00:28:04,420] [INFO] [config.py:1003:print] mics_shard_size .............. -1 +[2025-05-15 00:28:04,420] [INFO] [config.py:1003:print] monitor_config ............... tensorboard=TensorBoardConfig(enabled=False, output_path='', job_name='DeepSpeedJobName') comet=CometConfig(enabled=False, samples_log_interval=100, project=None, workspace=None, api_key=None, experiment_name=None, experiment_key=None, online=None, mode=None) wandb=WandbConfig(enabled=False, group=None, team=None, project='deepspeed') csv_monitor=CSVConfig(enabled=False, output_path='', job_name='DeepSpeedJobName') +[2025-05-15 00:28:04,421] [INFO] [config.py:1003:print] nebula_config ................ { + "enabled": false, + "persistent_storage_path": null, + "persistent_time_interval": 100, + "num_of_version_in_retention": 2, + "enable_nebula_load": true, + "load_path": null +} +[2025-05-15 00:28:04,421] [INFO] [config.py:1003:print] optimizer_legacy_fusion ...... False +[2025-05-15 00:28:04,421] [INFO] [config.py:1003:print] optimizer_name ............... adamw +[2025-05-15 00:28:04,421] [INFO] [config.py:1003:print] optimizer_params ............. {'lr': 1e-15, 'betas': [0.9, 0.999], 'eps': 1e-08, 'weight_decay': 0.01} +[2025-05-15 00:28:04,421] [INFO] [config.py:1003:print] pipeline ..................... {'stages': 'auto', 'partition': 'best', 'seed_layers': False, 'activation_checkpoint_interval': 0, 'pipe_partitioned': True, 'grad_partitioned': True} +[2025-05-15 00:28:04,421] [INFO] [config.py:1003:print] pld_enabled .................. False +[2025-05-15 00:28:04,421] [INFO] [config.py:1003:print] pld_params ................... False +[2025-05-15 00:28:04,421] [INFO] [config.py:1003:print] prescale_gradients ........... False +[2025-05-15 00:28:04,421] [INFO] [config.py:1003:print] scheduler_name ............... None +[2025-05-15 00:28:04,421] [INFO] [config.py:1003:print] scheduler_params ............. None +[2025-05-15 00:28:04,421] [INFO] [config.py:1003:print] seq_parallel_communication_data_type torch.float32 +[2025-05-15 00:28:04,421] [INFO] [config.py:1003:print] sparse_attention ............. None +[2025-05-15 00:28:04,421] [INFO] [config.py:1003:print] sparse_gradients_enabled ..... False +[2025-05-15 00:28:04,421] [INFO] [config.py:1003:print] steps_per_print .............. inf +[2025-05-15 00:28:04,421] [INFO] [config.py:1003:print] timers_config ................ enabled=True synchronized=True +[2025-05-15 00:28:04,421] [INFO] [config.py:1003:print] train_batch_size ............. 8 +[2025-05-15 00:28:04,421] [INFO] [config.py:1003:print] train_micro_batch_size_per_gpu 1 +[2025-05-15 00:28:04,421] [INFO] [config.py:1003:print] use_data_before_expert_parallel_ False +[2025-05-15 00:28:04,421] [INFO] [config.py:1003:print] use_node_local_storage ....... False +[2025-05-15 00:28:04,421] [INFO] [config.py:1003:print] wall_clock_breakdown ......... True +[2025-05-15 00:28:04,421] [INFO] [config.py:1003:print] weight_quantization_config ... None +[2025-05-15 00:28:04,421] [INFO] [config.py:1003:print] world_size ................... 1 +[2025-05-15 00:28:04,421] [INFO] [config.py:1003:print] zero_allow_untested_optimizer False +[2025-05-15 00:28:04,421] [INFO] [config.py:1003:print] zero_config .................. stage=1 contiguous_gradients=True reduce_scatter=True reduce_bucket_size=1000000000 use_multi_rank_bucket_allreduce=True allgather_partitions=True allgather_bucket_size=1000000000 overlap_comm=True load_from_fp32_weights=True elastic_checkpoint=False offload_param=DeepSpeedZeroOffloadParamConfig(device='cpu', nvme_path=None, buffer_count=5, buffer_size=100000000, max_in_cpu=1000000000, pin_memory=True) offload_optimizer=DeepSpeedZeroOffloadOptimizerConfig(device='cpu', nvme_path=None, buffer_count=4, pin_memory=True, pipeline_read=False, pipeline_write=False, fast_init=False, ratio=1.0) sub_group_size=1000000000 cpu_offload_param=None cpu_offload_use_pin_memory=None cpu_offload=None prefetch_bucket_size=50000000 param_persistence_threshold=100000 model_persistence_threshold=9223372036854775807 max_live_parameters=1000000000 max_reuse_distance=1000000000 gather_16bit_weights_on_model_save=False use_all_reduce_for_fetch_params=False stage3_gather_fp16_weights_on_model_save=False ignore_unused_parameters=True legacy_stage1=False round_robin_gradients=False zero_hpz_partition_size=1 zero_quantized_weights=False zero_quantized_nontrainable_weights=False zero_quantized_gradients=False mics_shard_size=-1 mics_hierarchical_params_gather=False memory_efficient_linear=True pipeline_loading_checkpoint=False override_module_apply=True +[2025-05-15 00:28:04,421] [INFO] [config.py:1003:print] zero_enabled ................. True +[2025-05-15 00:28:04,421] [INFO] [config.py:1003:print] zero_force_ds_cpu_optimizer .. True +[2025-05-15 00:28:04,421] [INFO] [config.py:1003:print] zero_optimization_stage ...... 1 +[2025-05-15 00:28:04,421] [INFO] [config.py:989:print_user_config] json = { + "zero_optimization": { + "stage": 1, + "allgather_partitions": true, + "allgather_bucket_size": 1.000000e+09, + "overlap_comm": true, + "reduce_scatter": true, + "reduce_bucket_size": 1.000000e+09, + "contiguous_gradients": true, + "offload_param": { + "device": "cpu", + "pin_memory": true + }, + "offload_optimizer": { + "device": "cpu", + "pin_memory": true + } + }, + "fp16": { + "enabled": false, + "auto_cast": true, + "loss_scale": 0, + "initial_scale_power": 32, + "loss_scale_window": 1000, + "hysteresis": 2, + "min_loss_scale": 1 + }, + "bf16": { + "enabled": true + }, + "optimizer": { + "type": "AdamW", + "params": { + "lr": 1e-15, + "betas": [0.9, 0.999], + "eps": 1e-08, + "weight_decay": 0.01 + } + }, + "gradient_accumulation_steps": 8, + "gradient_clipping": 1.0, + "steps_per_print": inf, + "train_batch_size": 8, + "train_micro_batch_size_per_gpu": 1, + "wall_clock_breakdown": true +} +[INFO|trainer.py:2134] 2025-05-15 00:28:04,422 >> ***** Running training ***** +[INFO|trainer.py:2135] 2025-05-15 00:28:04,422 >> Num examples = 14,874 +[INFO|trainer.py:2136] 2025-05-15 00:28:04,422 >> Num Epochs = 1 +[INFO|trainer.py:2137] 2025-05-15 00:28:04,422 >> Instantaneous batch size per device = 1 +[INFO|trainer.py:2140] 2025-05-15 00:28:04,422 >> Total train batch size (w. parallel, distributed & accumulation) = 8 +[INFO|trainer.py:2141] 2025-05-15 00:28:04,422 >> Gradient Accumulation steps = 8 +[INFO|trainer.py:2142] 2025-05-15 00:28:04,422 >> Total optimization steps = 558 +[INFO|trainer.py:2143] 2025-05-15 00:28:04,425 >> Number of trainable parameters = 15,728,640 + 0%| | 0/558 [00:00> Saving model checkpoint to work_dirs/internvl_chat_v2_5/mmvet/checkpoint-100 +[INFO|configuration_utils.py:472] 2025-05-15 00:39:46,097 >> Configuration saved in work_dirs/internvl_chat_v2_5/mmvet/checkpoint-100/config.json +[INFO|configuration_utils.py:807] 2025-05-15 00:39:46,097 >> Configuration saved in work_dirs/internvl_chat_v2_5/mmvet/checkpoint-100/generation_config.json +[INFO|modeling_utils.py:2755] 2025-05-15 00:39:54,663 >> Model weights saved in work_dirs/internvl_chat_v2_5/mmvet/checkpoint-100/model.safetensors +[INFO|tokenization_utils_base.py:2702] 2025-05-15 00:39:54,666 >> tokenizer config file saved in work_dirs/internvl_chat_v2_5/mmvet/checkpoint-100/tokenizer_config.json +[INFO|tokenization_utils_base.py:2711] 2025-05-15 00:39:54,666 >> Special tokens file saved in work_dirs/internvl_chat_v2_5/mmvet/checkpoint-100/special_tokens_map.json +[INFO|tokenization_utils_base.py:2762] 2025-05-15 00:39:54,666 >> added tokens file saved in work_dirs/internvl_chat_v2_5/mmvet/checkpoint-100/added_tokens.json +[2025-05-15 00:39:54,817] [INFO] [logging.py:96:log_dist] [Rank 0] [Torch] Checkpoint global_step100 is about to be saved! +[2025-05-15 00:39:54,845] [INFO] [logging.py:96:log_dist] [Rank 0] Saving model checkpoint: work_dirs/internvl_chat_v2_5/mmvet/checkpoint-100/global_step100/mp_rank_00_model_states.pt +[2025-05-15 00:39:54,845] [INFO] [torch_checkpoint_engine.py:21:save] [Torch] Saving work_dirs/internvl_chat_v2_5/mmvet/checkpoint-100/global_step100/mp_rank_00_model_states.pt... +[2025-05-15 00:40:06,362] [INFO] [torch_checkpoint_engine.py:23:save] [Torch] Saved work_dirs/internvl_chat_v2_5/mmvet/checkpoint-100/global_step100/mp_rank_00_model_states.pt. +[2025-05-15 00:40:06,365] [INFO] [torch_checkpoint_engine.py:21:save] [Torch] Saving work_dirs/internvl_chat_v2_5/mmvet/checkpoint-100/global_step100/bf16_zero_pp_rank_0_mp_rank_00_optim_states.pt... +[2025-05-15 00:40:06,714] [INFO] [torch_checkpoint_engine.py:23:save] [Torch] Saved work_dirs/internvl_chat_v2_5/mmvet/checkpoint-100/global_step100/bf16_zero_pp_rank_0_mp_rank_00_optim_states.pt. +[2025-05-15 00:40:06,715] [INFO] [engine.py:3536:_save_zero_checkpoint] zero checkpoint saved work_dirs/internvl_chat_v2_5/mmvet/checkpoint-100/global_step100/bf16_zero_pp_rank_0_mp_rank_00_optim_states.pt +[2025-05-15 00:40:06,715] [INFO] [torch_checkpoint_engine.py:33:commit] [Torch] Checkpoint global_step100 is ready now! +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2023 +[2025-05-15 00:40:07,376] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 327.92 | bwd_microstep: 303.42 | bwd_inner_microstep: 303.06 | bwd_allreduce_microstep: 0.14 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1894 +[2025-05-15 00:40:08,418] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 387.45 | bwd_microstep: 635.77 | bwd_inner_microstep: 635.71 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.41 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-15 00:40:09,203] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 353.61 | bwd_microstep: 407.12 | bwd_inner_microstep: 407.08 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.78 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 327 +[2025-05-15 00:40:09,504] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.59 | bwd_microstep: 176.47 | bwd_inner_microstep: 176.43 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-15 00:40:10,405] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 406.81 | bwd_microstep: 461.38 | bwd_inner_microstep: 461.22 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.11 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 844 +[2025-05-15 00:40:10,809] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 103.17 | bwd_microstep: 282.80 | bwd_inner_microstep: 282.74 | bwd_allreduce_microstep: 0.02 | step_microstep: 1.90 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-15 00:40:11,820] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 440.90 | bwd_microstep: 546.19 | bwd_inner_microstep: 546.13 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.94 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 320 +[2025-05-15 00:40:12,323] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.07 | optimizer_gradients: 2.14 | optimizer_step: 18.25 +[2025-05-15 00:40:12,323] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.10 | bwd_microstep: 364.95 | bwd_inner_microstep: 174.39 | bwd_allreduce_microstep: 190.28 | step_microstep: 26.78 +[2025-05-15 00:40:12,324] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2207.53 | bwd: 3178.13 | bwd_inner: 2986.87 | bwd_allreduce: 190.56 | step: 33.66 + 18%|█▊ | 101/558 [12:07<1:43:08, 13.54s/it] {'loss': 6.722, 'grad_norm': 17.381742477416992, 'learning_rate': 9.416856561061847e-16, 'epoch': 0.05} + 18%|█▊ | 101/558 [12:07<1:43:08, 13.54s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1941 +[2025-05-15 00:40:13,338] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 341.90 | bwd_microstep: 645.36 | bwd_inner_microstep: 645.32 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.55 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-15 00:40:14,241] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 346.12 | bwd_microstep: 522.20 | bwd_inner_microstep: 522.14 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.31 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-15 00:40:15,019] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 351.07 | bwd_microstep: 406.79 | bwd_inner_microstep: 406.42 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.20 +dynamic ViT batch size: 2, images per sample: 2.0, dynamic token length: 584 +[2025-05-15 00:40:15,349] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 137.06 | bwd_microstep: 174.21 | bwd_inner_microstep: 174.18 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-15 00:40:16,348] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 433.60 | bwd_microstep: 533.51 | bwd_inner_microstep: 533.28 | bwd_allreduce_microstep: 0.18 | step_microstep: 0.25 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-15 00:40:17,140] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 355.58 | bwd_microstep: 414.53 | bwd_inner_microstep: 414.48 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.93 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-15 00:40:18,138] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 410.03 | bwd_microstep: 564.33 | bwd_inner_microstep: 564.31 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.22 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 829 +[2025-05-15 00:40:18,797] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.07 | optimizer_step: 18.17 +[2025-05-15 00:40:18,797] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 166.09 | bwd_microstep: 446.79 | bwd_inner_microstep: 245.25 | bwd_allreduce_microstep: 201.51 | step_microstep: 28.06 +[2025-05-15 00:40:18,798] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2541.40 | bwd: 3707.73 | bwd_inner: 3505.39 | bwd_allreduce: 202.04 | step: 36.93 + 18%|█▊ | 102/558 [12:14<1:26:47, 11.42s/it] {'loss': 7.2003, 'grad_norm': 72.85211944580078, 'learning_rate': 9.403174198438372e-16, 'epoch': 0.05} + 18%|█▊ | 102/558 [12:14<1:26:47, 11.42s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1886 +[2025-05-15 00:40:19,684] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 251.78 | bwd_microstep: 604.25 | bwd_inner_microstep: 604.19 | bwd_allreduce_microstep: 0.02 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-15 00:40:20,641] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 399.28 | bwd_microstep: 523.01 | bwd_inner_microstep: 522.97 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.99 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 858 +[2025-05-15 00:40:21,075] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 165.30 | bwd_microstep: 248.94 | bwd_inner_microstep: 248.72 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.42 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-15 00:40:21,878] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 246.00 | bwd_microstep: 534.95 | bwd_inner_microstep: 534.89 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.57 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-15 00:40:22,862] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 425.40 | bwd_microstep: 522.17 | bwd_inner_microstep: 522.13 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.02 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-15 00:40:23,629] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 292.05 | bwd_microstep: 454.33 | bwd_inner_microstep: 454.17 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-15 00:40:24,574] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 342.92 | bwd_microstep: 584.99 | bwd_inner_microstep: 584.76 | bwd_allreduce_microstep: 0.19 | step_microstep: 0.24 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1996 +[2025-05-15 00:40:25,612] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.08 | optimizer_gradients: 2.13 | optimizer_step: 18.17 +[2025-05-15 00:40:25,613] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 366.62 | bwd_microstep: 626.06 | bwd_inner_microstep: 552.39 | bwd_allreduce_microstep: 73.54 | step_microstep: 26.92 +[2025-05-15 00:40:25,613] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2489.33 | bwd: 4098.72 | bwd_inner: 4024.29 | bwd_allreduce: 73.84 | step: 35.41 + 18%|█▊ | 103/558 [12:21<1:16:08, 10.04s/it] {'loss': 4.8069, 'grad_norm': 38.990455627441406, 'learning_rate': 9.3893433551642e-16, 'epoch': 0.06} + 18%|█▊ | 103/558 [12:21<1:16:08, 10.04s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1887 +[2025-05-15 00:40:26,659] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 389.84 | bwd_microstep: 625.22 | bwd_inner_microstep: 625.02 | bwd_allreduce_microstep: 0.18 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1888 +[2025-05-15 00:40:27,460] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 353.05 | bwd_microstep: 428.79 | bwd_inner_microstep: 428.65 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-15 00:40:28,469] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 359.96 | bwd_microstep: 628.67 | bwd_inner_microstep: 628.64 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.58 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-15 00:40:29,363] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 364.27 | bwd_microstep: 504.37 | bwd_inner_microstep: 504.34 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.25 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-15 00:40:30,144] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 355.01 | bwd_microstep: 402.39 | bwd_inner_microstep: 402.35 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.84 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-15 00:40:31,168] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 409.72 | bwd_microstep: 588.52 | bwd_inner_microstep: 588.47 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.00 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 321 +[2025-05-15 00:40:31,414] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 85.23 | bwd_microstep: 142.98 | bwd_inner_microstep: 142.01 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-15 00:40:32,781] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.01 | optimizer_gradients: 2.07 | optimizer_step: 18.36 +[2025-05-15 00:40:32,782] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 348.42 | bwd_microstep: 969.98 | bwd_inner_microstep: 419.64 | bwd_allreduce_microstep: 550.21 | step_microstep: 28.02 +[2025-05-15 00:40:32,782] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2665.49 | bwd: 4290.95 | bwd_inner: 3739.22 | bwd_allreduce: 550.47 | step: 34.17 + 19%|█▊ | 104/558 [12:28<1:09:26, 9.18s/it] {'loss': 5.0759, 'grad_norm': 18.078683853149414, 'learning_rate': 9.375364497633006e-16, 'epoch': 0.06} + 19%|█▊ | 104/558 [12:28<1:09:26, 9.18s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1909 +[2025-05-15 00:40:33,685] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 358.48 | bwd_microstep: 517.56 | bwd_inner_microstep: 517.39 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.13 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1904 +[2025-05-15 00:40:34,582] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 266.61 | bwd_microstep: 605.67 | bwd_inner_microstep: 605.64 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.33 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1892 +[2025-05-15 00:40:35,510] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 365.22 | bwd_microstep: 529.13 | bwd_inner_microstep: 529.10 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.53 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-15 00:40:36,347] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 222.96 | bwd_microstep: 588.08 | bwd_inner_microstep: 588.05 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.45 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-15 00:40:37,320] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 430.87 | bwd_microstep: 510.19 | bwd_inner_microstep: 509.77 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-15 00:40:38,197] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 353.54 | bwd_microstep: 502.76 | bwd_inner_microstep: 502.72 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.26 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-15 00:40:39,074] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 350.08 | bwd_microstep: 504.21 | bwd_inner_microstep: 503.73 | bwd_allreduce_microstep: 0.44 | step_microstep: 0.76 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-15 00:40:40,275] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 1.68 | optimizer_step: 16.32 +[2025-05-15 00:40:40,275] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 216.24 | bwd_microstep: 941.88 | bwd_inner_microstep: 597.47 | bwd_allreduce_microstep: 344.39 | step_microstep: 22.97 +[2025-05-15 00:40:40,276] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2564.00 | bwd: 4699.48 | bwd_inner: 4353.89 | bwd_allreduce: 344.94 | step: 31.64 + 19%|█▉ | 105/558 [12:35<1:05:28, 8.67s/it] {'loss': 5.6259, 'grad_norm': 21.6239070892334, 'learning_rate': 9.361238097229698e-16, 'epoch': 0.06} + 19%|█▉ | 105/558 [12:35<1:05:28, 8.67s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-15 00:40:41,172] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 355.50 | bwd_microstep: 517.64 | bwd_inner_microstep: 517.60 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.22 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-15 00:40:41,954] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 343.13 | bwd_microstep: 417.16 | bwd_inner_microstep: 417.12 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.82 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 351 +[2025-05-15 00:40:42,228] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 101.80 | bwd_microstep: 147.02 | bwd_inner_microstep: 146.97 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.40 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-15 00:40:43,185] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 421.24 | bwd_microstep: 504.43 | bwd_inner_microstep: 503.39 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.22 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-15 00:40:44,062] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 343.25 | bwd_microstep: 515.03 | bwd_inner_microstep: 515.00 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.28 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 329 +[2025-05-15 00:40:44,307] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 90.29 | bwd_microstep: 136.86 | bwd_inner_microstep: 136.82 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.23 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-15 00:40:45,088] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 308.71 | bwd_microstep: 451.77 | bwd_inner_microstep: 451.54 | bwd_allreduce_microstep: 0.19 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-15 00:40:46,324] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.01 | optimizer_gradients: 2.05 | optimizer_step: 18.32 +[2025-05-15 00:40:46,325] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 441.64 | bwd_microstep: 739.58 | bwd_inner_microstep: 546.53 | bwd_allreduce_microstep: 192.76 | step_microstep: 27.24 +[2025-05-15 00:40:46,326] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2405.55 | bwd: 3429.50 | bwd_inner: 3236.26 | bwd_allreduce: 193.01 | step: 32.61 + 19%|█▉ | 106/558 [12:41<59:24, 7.89s/it] {'loss': 6.1379, 'grad_norm': 22.64780616760254, 'learning_rate': 9.34696463031452e-16, 'epoch': 0.06} + 19%|█▉ | 106/558 [12:41<59:24, 7.89s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1953 +[2025-05-15 00:40:47,169] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 367.99 | bwd_microstep: 447.14 | bwd_inner_microstep: 447.08 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.84 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-15 00:40:48,196] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 442.89 | bwd_microstep: 557.87 | bwd_inner_microstep: 557.42 | bwd_allreduce_microstep: 0.23 | step_microstep: 0.44 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-15 00:40:49,029] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 353.79 | bwd_microstep: 458.64 | bwd_inner_microstep: 458.28 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.10 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 836 +[2025-05-15 00:40:49,433] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 108.56 | bwd_microstep: 276.16 | bwd_inner_microstep: 276.12 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.99 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1353 +[2025-05-15 00:40:50,222] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 330.21 | bwd_microstep: 428.23 | bwd_inner_microstep: 427.02 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-15 00:40:51,121] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 356.05 | bwd_microstep: 519.71 | bwd_inner_microstep: 519.67 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.31 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-15 00:40:51,937] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 252.92 | bwd_microstep: 537.90 | bwd_inner_microstep: 537.85 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1354 +[2025-05-15 00:40:52,938] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.12 | optimizer_step: 19.73 +[2025-05-15 00:40:52,939] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 326.49 | bwd_microstep: 614.36 | bwd_inner_microstep: 413.00 | bwd_allreduce_microstep: 201.33 | step_microstep: 28.02 +[2025-05-15 00:40:52,939] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2538.88 | bwd: 3840.04 | bwd_inner: 3636.52 | bwd_allreduce: 201.76 | step: 37.05 + 19%|█▉ | 107/558 [12:48<56:24, 7.50s/it] {'loss': 6.6444, 'grad_norm': 26.35208511352539, 'learning_rate': 9.332544578206985e-16, 'epoch': 0.06} + 19%|█▉ | 107/558 [12:48<56:24, 7.50s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1901 +[2025-05-15 00:40:53,714] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 350.08 | bwd_microstep: 397.18 | bwd_inner_microstep: 397.14 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.78 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-15 00:40:54,752] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 398.14 | bwd_microstep: 611.80 | bwd_inner_microstep: 611.76 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.77 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-15 00:40:55,630] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 348.96 | bwd_microstep: 508.58 | bwd_inner_microstep: 508.35 | bwd_allreduce_microstep: 0.19 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-15 00:40:56,423] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 321.56 | bwd_microstep: 449.82 | bwd_inner_microstep: 449.76 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.18 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 856 +[2025-05-15 00:40:56,983] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 223.49 | bwd_microstep: 308.58 | bwd_inner_microstep: 308.57 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.51 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-15 00:40:57,868] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 337.79 | bwd_microstep: 513.92 | bwd_inner_microstep: 513.88 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.26 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-15 00:40:58,713] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 224.60 | bwd_microstep: 597.90 | bwd_inner_microstep: 597.87 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.48 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-15 00:40:59,838] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 1.68 | optimizer_step: 15.83 +[2025-05-15 00:40:59,839] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 402.13 | bwd_microstep: 668.75 | bwd_inner_microstep: 501.84 | bwd_allreduce_microstep: 166.85 | step_microstep: 22.54 +[2025-05-15 00:40:59,839] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2606.71 | bwd: 4056.54 | bwd_inner: 3889.17 | bwd_allreduce: 167.12 | step: 31.74 + 19%|█▉ | 108/558 [12:55<54:55, 7.32s/it] {'loss': 4.9493, 'grad_norm': 14.358107566833496, 'learning_rate': 9.317978427169638e-16, 'epoch': 0.06} + 19%|█▉ | 108/558 [12:55<54:55, 7.32s/it]dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 858 +[2025-05-15 00:41:00,215] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 96.21 | bwd_microstep: 254.05 | bwd_inner_microstep: 254.01 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.82 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 360 +[2025-05-15 00:41:00,498] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 101.87 | bwd_microstep: 153.36 | bwd_inner_microstep: 153.32 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-15 00:41:01,486] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 431.17 | bwd_microstep: 523.70 | bwd_inner_microstep: 523.50 | bwd_allreduce_microstep: 0.18 | step_microstep: 0.18 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1383 +[2025-05-15 00:41:02,045] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 237.60 | bwd_microstep: 300.94 | bwd_inner_microstep: 300.90 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.76 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-15 00:41:03,068] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 406.94 | bwd_microstep: 590.25 | bwd_inner_microstep: 590.21 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.14 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-15 00:41:03,908] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 356.23 | bwd_microstep: 462.90 | bwd_inner_microstep: 462.75 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 840 +[2025-05-15 00:41:04,313] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 107.80 | bwd_microstep: 279.52 | bwd_inner_microstep: 279.47 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.83 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 926 +[2025-05-15 00:41:05,187] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.04 | optimizer_step: 18.10 +[2025-05-15 00:41:05,188] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 238.86 | bwd_microstep: 577.94 | bwd_inner_microstep: 352.41 | bwd_allreduce_microstep: 225.50 | step_microstep: 27.13 +[2025-05-15 00:41:05,189] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 1976.64 | bwd: 3142.68 | bwd_inner: 2916.59 | bwd_allreduce: 225.79 | step: 36.31 + 20%|█▉ | 109/558 [13:00<50:22, 6.73s/it] {'loss': 4.4817, 'grad_norm': 23.138160705566406, 'learning_rate': 9.30326666839168e-16, 'epoch': 0.06} + 20%|█▉ | 109/558 [13:00<50:22, 6.73s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1897 +[2025-05-15 00:41:05,967] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 360.10 | bwd_microstep: 390.27 | bwd_inner_microstep: 390.25 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.75 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1902 +[2025-05-15 00:41:07,002] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 397.31 | bwd_microstep: 609.57 | bwd_inner_microstep: 609.50 | bwd_allreduce_microstep: 0.02 | step_microstep: 2.49 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1377 +[2025-05-15 00:41:07,565] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 236.72 | bwd_microstep: 304.63 | bwd_inner_microstep: 304.59 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.86 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-15 00:41:08,585] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 411.28 | bwd_microstep: 585.13 | bwd_inner_microstep: 585.09 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.24 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-15 00:41:09,458] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 344.24 | bwd_microstep: 507.45 | bwd_inner_microstep: 507.40 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.99 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-15 00:41:10,212] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 344.09 | bwd_microstep: 386.81 | bwd_inner_microstep: 386.75 | bwd_allreduce_microstep: 0.02 | step_microstep: 1.95 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-15 00:41:11,248] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 402.59 | bwd_microstep: 607.43 | bwd_inner_microstep: 607.18 | bwd_allreduce_microstep: 0.22 | step_microstep: 0.22 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 864 +[2025-05-15 00:41:11,918] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.07 | optimizer_step: 18.48 +[2025-05-15 00:41:11,918] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 174.69 | bwd_microstep: 449.42 | bwd_inner_microstep: 250.70 | bwd_allreduce_microstep: 198.69 | step_microstep: 27.11 +[2025-05-15 00:41:11,919] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2671.02 | bwd: 3840.72 | bwd_inner: 3641.48 | bwd_allreduce: 198.98 | step: 36.59 + 20%|█▉ | 110/558 [13:07<50:15, 6.73s/it] {'loss': 4.4446, 'grad_norm': 27.67401695251465, 'learning_rate': 9.288409797972376e-16, 'epoch': 0.06} + 20%|█▉ | 110/558 [13:07<50:15, 6.73s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1900 +[2025-05-15 00:41:12,719] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 351.67 | bwd_microstep: 420.28 | bwd_inner_microstep: 420.24 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.81 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1364 +[2025-05-15 00:41:13,509] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 312.02 | bwd_microstep: 454.65 | bwd_inner_microstep: 454.61 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.52 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-15 00:41:14,385] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 344.73 | bwd_microstep: 510.15 | bwd_inner_microstep: 509.16 | bwd_allreduce_microstep: 0.95 | step_microstep: 0.21 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-15 00:41:15,197] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 236.49 | bwd_microstep: 552.52 | bwd_inner_microstep: 552.48 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.33 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1095 +[2025-05-15 00:41:15,819] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 270.91 | bwd_microstep: 318.47 | bwd_inner_microstep: 318.43 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.27 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-15 00:41:16,694] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 337.30 | bwd_microstep: 516.13 | bwd_inner_microstep: 516.10 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.28 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-15 00:41:17,500] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 256.42 | bwd_microstep: 526.58 | bwd_inner_microstep: 526.54 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-15 00:41:18,688] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.11 | optimizer_step: 18.08 +[2025-05-15 00:41:18,689] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 439.60 | bwd_microstep: 690.58 | bwd_inner_microstep: 511.02 | bwd_allreduce_microstep: 179.50 | step_microstep: 26.69 +[2025-05-15 00:41:18,689] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2549.12 | bwd: 3989.38 | bwd_inner: 3806.26 | bwd_allreduce: 180.51 | step: 34.48 + 20%|█▉ | 111/558 [13:14<50:13, 6.74s/it] {'loss': 6.8374, 'grad_norm': 28.098834991455078, 'learning_rate': 9.273408316904353e-16, 'epoch': 0.06} + 20%|█▉ | 111/558 [13:14<50:13, 6.74s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1906 +[2025-05-15 00:41:19,670] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 331.36 | bwd_microstep: 622.83 | bwd_inner_microstep: 622.77 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.58 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1897 +[2025-05-15 00:41:20,592] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 360.51 | bwd_microstep: 526.09 | bwd_inner_microstep: 526.04 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.39 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-15 00:41:21,393] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 288.99 | bwd_microstep: 487.62 | bwd_inner_microstep: 487.58 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.49 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-15 00:41:22,403] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 448.50 | bwd_microstep: 526.28 | bwd_inner_microstep: 526.24 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-15 00:41:23,218] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 248.51 | bwd_microstep: 545.50 | bwd_inner_microstep: 545.46 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.53 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-15 00:41:24,196] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 423.03 | bwd_microstep: 517.41 | bwd_inner_microstep: 517.36 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.32 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-15 00:41:25,048] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 232.91 | bwd_microstep: 592.50 | bwd_inner_microstep: 592.45 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-15 00:41:26,123] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 1.80 | optimizer_step: 18.07 +[2025-05-15 00:41:26,123] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 398.71 | bwd_microstep: 616.30 | bwd_inner_microstep: 507.27 | bwd_allreduce_microstep: 108.97 | step_microstep: 26.35 +[2025-05-15 00:41:26,124] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2732.49 | bwd: 4434.53 | bwd_inner: 4325.18 | bwd_allreduce: 109.06 | step: 41.22 + 20%|██ | 112/558 [13:21<51:39, 6.95s/it] {'loss': 4.6847, 'grad_norm': 19.6932315826416, 'learning_rate': 9.258262731056688e-16, 'epoch': 0.06} + 20%|██ | 112/558 [13:21<51:39, 6.95s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1899 +[2025-05-15 00:41:27,132] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 359.97 | bwd_microstep: 621.71 | bwd_inner_microstep: 621.67 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1893 +[2025-05-15 00:41:27,925] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 358.24 | bwd_microstep: 402.85 | bwd_inner_microstep: 402.43 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1886 +[2025-05-15 00:41:28,966] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 389.80 | bwd_microstep: 626.29 | bwd_inner_microstep: 626.06 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-15 00:41:29,716] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 355.50 | bwd_microstep: 373.20 | bwd_inner_microstep: 373.16 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.80 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-15 00:41:30,747] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 400.40 | bwd_microstep: 605.16 | bwd_inner_microstep: 604.39 | bwd_allreduce_microstep: 0.75 | step_microstep: 0.22 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1356 +[2025-05-15 00:41:31,423] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 261.02 | bwd_microstep: 394.41 | bwd_inner_microstep: 394.37 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-15 00:41:32,255] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 222.50 | bwd_microstep: 586.15 | bwd_inner_microstep: 586.12 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1346 +[2025-05-15 00:41:33,226] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.04 | optimizer_step: 18.02 +[2025-05-15 00:41:33,227] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 326.45 | bwd_microstep: 588.84 | bwd_inner_microstep: 386.85 | bwd_allreduce_microstep: 201.95 | step_microstep: 26.80 +[2025-05-15 00:41:33,227] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2673.86 | bwd: 4198.62 | bwd_inner: 3995.05 | bwd_allreduce: 202.76 | step: 33.95 + 20%|██ | 113/558 [13:28<51:53, 7.00s/it] {'loss': 5.6563, 'grad_norm': 20.30397605895996, 'learning_rate': 9.242973551157856e-16, 'epoch': 0.06} + 20%|██ | 113/558 [13:28<51:53, 7.00s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1921 +[2025-05-15 00:41:34,135] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 247.75 | bwd_microstep: 631.41 | bwd_inner_microstep: 631.38 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1915 +[2025-05-15 00:41:35,099] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 394.08 | bwd_microstep: 537.32 | bwd_inner_microstep: 537.27 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.51 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 357 +[2025-05-15 00:41:35,359] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 88.70 | bwd_microstep: 154.66 | bwd_inner_microstep: 154.62 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.07 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1886 +[2025-05-15 00:41:36,396] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 401.93 | bwd_microstep: 608.83 | bwd_inner_microstep: 608.80 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.48 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-15 00:41:37,184] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 357.52 | bwd_microstep: 409.11 | bwd_inner_microstep: 409.08 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.81 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-15 00:41:38,182] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 409.60 | bwd_microstep: 563.23 | bwd_inner_microstep: 563.20 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.26 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-15 00:41:38,946] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 352.47 | bwd_microstep: 388.91 | bwd_inner_microstep: 388.85 | bwd_allreduce_microstep: 0.02 | step_microstep: 1.94 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-15 00:41:40,218] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.01 | optimizer_gradients: 2.04 | optimizer_step: 18.71 +[2025-05-15 00:41:40,219] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 420.27 | bwd_microstep: 799.08 | bwd_inner_microstep: 590.85 | bwd_allreduce_microstep: 207.98 | step_microstep: 27.95 +[2025-05-15 00:41:40,220] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2672.31 | bwd: 4092.57 | bwd_inner: 3884.06 | bwd_allreduce: 208.05 | step: 36.66 + 20%|██ | 114/558 [13:35<51:45, 7.00s/it] {'loss': 3.68, 'grad_norm': 8.174397468566895, 'learning_rate': 9.227541292778504e-16, 'epoch': 0.06} + 20%|██ | 114/558 [13:35<51:45, 7.00s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1907 +[2025-05-15 00:41:41,084] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 357.84 | bwd_microstep: 479.57 | bwd_inner_microstep: 479.40 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.11 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 366 +[2025-05-15 00:41:41,342] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 85.82 | bwd_microstep: 154.19 | bwd_inner_microstep: 154.15 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.83 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1368 +[2025-05-15 00:41:42,137] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 297.96 | bwd_microstep: 471.92 | bwd_inner_microstep: 471.64 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.26 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-15 00:41:42,947] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 248.37 | bwd_microstep: 538.92 | bwd_inner_microstep: 538.88 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.46 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-15 00:41:43,931] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 441.95 | bwd_microstep: 508.69 | bwd_inner_microstep: 508.48 | bwd_allreduce_microstep: 0.18 | step_microstep: 0.19 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 322 +[2025-05-15 00:41:44,180] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.60 | bwd_microstep: 139.12 | bwd_inner_microstep: 139.09 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-15 00:41:44,966] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 280.19 | bwd_microstep: 482.86 | bwd_inner_microstep: 482.82 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-15 00:41:46,142] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.01 | optimizer_gradients: 2.04 | optimizer_step: 17.92 +[2025-05-15 00:41:46,142] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 447.58 | bwd_microstep: 669.10 | bwd_inner_microstep: 469.98 | bwd_allreduce_microstep: 199.09 | step_microstep: 27.05 +[2025-05-15 00:41:46,143] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2253.30 | bwd: 3444.38 | bwd_inner: 3244.50 | bwd_allreduce: 199.37 | step: 34.46 + 21%|██ | 115/558 [13:41<49:16, 6.67s/it] {'loss': 3.849, 'grad_norm': 31.424781799316406, 'learning_rate': 9.211966476314073e-16, 'epoch': 0.06} + 21%|██ | 115/558 [13:41<49:16, 6.67s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1934 +[2025-05-15 00:41:47,049] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 366.72 | bwd_microstep: 512.11 | bwd_inner_microstep: 511.96 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1394 +[2025-05-15 00:41:47,695] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 180.23 | bwd_microstep: 447.85 | bwd_inner_microstep: 447.81 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.55 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1899 +[2025-05-15 00:41:48,680] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 434.29 | bwd_microstep: 516.25 | bwd_inner_microstep: 516.23 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-15 00:41:49,564] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 343.72 | bwd_microstep: 521.56 | bwd_inner_microstep: 521.53 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.26 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-15 00:41:50,385] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 228.25 | bwd_microstep: 570.40 | bwd_inner_microstep: 570.35 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-15 00:41:51,376] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 429.63 | bwd_microstep: 526.12 | bwd_inner_microstep: 526.09 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.26 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-15 00:41:52,265] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 352.99 | bwd_microstep: 515.67 | bwd_inner_microstep: 515.46 | bwd_allreduce_microstep: 0.18 | step_microstep: 0.17 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1943 +[2025-05-15 00:41:53,569] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.39 | optimizer_gradients: 2.07 | optimizer_step: 18.65 +[2025-05-15 00:41:53,570] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 294.35 | bwd_microstep: 962.02 | bwd_inner_microstep: 535.00 | bwd_allreduce_microstep: 426.98 | step_microstep: 27.91 +[2025-05-15 00:41:53,570] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2630.16 | bwd: 4572.00 | bwd_inner: 4144.42 | bwd_allreduce: 427.27 | step: 33.96 + 21%|██ | 116/558 [13:49<50:49, 6.90s/it] {'loss': 6.7787, 'grad_norm': 30.755197525024414, 'learning_rate': 9.196249626967238e-16, 'epoch': 0.06} + 21%|██ | 116/558 [13:49<50:49, 6.90s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1927 +[2025-05-15 00:41:54,507] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 368.30 | bwd_microstep: 538.21 | bwd_inner_microstep: 538.17 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.31 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1887 +[2025-05-15 00:41:55,301] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 283.39 | bwd_microstep: 485.69 | bwd_inner_microstep: 485.66 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-15 00:41:56,303] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 445.54 | bwd_microstep: 523.45 | bwd_inner_microstep: 522.47 | bwd_allreduce_microstep: 0.95 | step_microstep: 0.23 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 346 +[2025-05-15 00:41:56,544] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 88.17 | bwd_microstep: 134.70 | bwd_inner_microstep: 133.74 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.21 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-15 00:41:57,428] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 351.30 | bwd_microstep: 511.94 | bwd_inner_microstep: 511.91 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.22 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-15 00:41:58,257] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 215.71 | bwd_microstep: 591.18 | bwd_inner_microstep: 591.14 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-15 00:41:59,222] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 411.34 | bwd_microstep: 518.27 | bwd_inner_microstep: 518.24 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.48 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-15 00:42:00,349] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.14 | optimizer_step: 28.15 +[2025-05-15 00:42:00,350] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 337.84 | bwd_microstep: 731.16 | bwd_inner_microstep: 526.19 | bwd_allreduce_microstep: 204.94 | step_microstep: 37.16 +[2025-05-15 00:42:00,351] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2501.57 | bwd: 4034.60 | bwd_inner: 3827.53 | bwd_allreduce: 205.00 | step: 45.31 + 21%|██ | 117/558 [13:55<50:26, 6.86s/it] {'loss': 4.423, 'grad_norm': 15.260701179504395, 'learning_rate': 9.18039127473021e-16, 'epoch': 0.06} + 21%|██ | 117/558 [13:55<50:26, 6.86s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1897 +[2025-05-15 00:42:01,264] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 274.36 | bwd_microstep: 612.17 | bwd_inner_microstep: 612.13 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 875 +[2025-05-15 00:42:01,755] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 215.66 | bwd_microstep: 245.23 | bwd_inner_microstep: 244.97 | bwd_allreduce_microstep: 0.23 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-15 00:42:02,632] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 356.26 | bwd_microstep: 501.28 | bwd_inner_microstep: 501.01 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.26 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-15 00:42:03,393] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 358.31 | bwd_microstep: 380.19 | bwd_inner_microstep: 380.16 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.82 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-15 00:42:04,431] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 397.15 | bwd_microstep: 615.60 | bwd_inner_microstep: 615.16 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.23 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-15 00:42:05,311] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 359.16 | bwd_microstep: 500.29 | bwd_inner_microstep: 500.25 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.21 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-15 00:42:06,062] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 352.29 | bwd_microstep: 378.18 | bwd_inner_microstep: 378.15 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.29 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1483 +[2025-05-15 00:42:07,195] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.01 | optimizer_gradients: 2.13 | optimizer_step: 18.49 +[2025-05-15 00:42:07,196] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 302.26 | bwd_microstep: 780.93 | bwd_inner_microstep: 545.99 | bwd_allreduce_microstep: 234.90 | step_microstep: 27.56 +[2025-05-15 00:42:07,197] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2615.43 | bwd: 4013.88 | bwd_inner: 3777.83 | bwd_allreduce: 235.20 | step: 32.93 + 21%|██ | 118/558 [14:02<50:17, 6.86s/it] {'loss': 4.4661, 'grad_norm': 24.318517684936523, 'learning_rate': 9.164391954366855e-16, 'epoch': 0.06} + 21%|██ | 118/558 [14:02<50:17, 6.86s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1900 +[2025-05-15 00:42:08,098] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 356.13 | bwd_microstep: 516.66 | bwd_inner_microstep: 516.15 | bwd_allreduce_microstep: 0.48 | step_microstep: 0.76 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1887 +[2025-05-15 00:42:08,913] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 235.99 | bwd_microstep: 556.81 | bwd_inner_microstep: 556.77 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1902 +[2025-05-15 00:42:09,914] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 432.57 | bwd_microstep: 533.13 | bwd_inner_microstep: 533.09 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.50 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-15 00:42:10,620] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 317.35 | bwd_microstep: 367.22 | bwd_inner_microstep: 367.20 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.28 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1899 +[2025-05-15 00:42:11,658] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 410.82 | bwd_microstep: 601.94 | bwd_inner_microstep: 601.90 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.32 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1894 +[2025-05-15 00:42:12,448] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 361.38 | bwd_microstep: 404.23 | bwd_inner_microstep: 404.18 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.82 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1370 +[2025-05-15 00:42:13,246] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 297.69 | bwd_microstep: 472.28 | bwd_inner_microstep: 472.24 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.32 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 836 +[2025-05-15 00:42:13,906] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.01 | optimizer_gradients: 2.04 | optimizer_step: 18.23 +[2025-05-15 00:42:13,907] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 174.05 | bwd_microstep: 439.85 | bwd_inner_microstep: 236.21 | bwd_allreduce_microstep: 203.60 | step_microstep: 27.18 +[2025-05-15 00:42:13,908] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2585.99 | bwd: 3892.12 | bwd_inner: 3687.74 | bwd_allreduce: 204.14 | step: 39.54 + 21%|██▏ | 119/558 [14:09<49:51, 6.81s/it] {'loss': 2.9845, 'grad_norm': 8.03186321258545, 'learning_rate': 9.148252205394665e-16, 'epoch': 0.06} + 21%|██▏ | 119/558 [14:09<49:51, 6.81s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1950 +[2025-05-15 00:42:14,749] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 326.35 | bwd_microstep: 485.35 | bwd_inner_microstep: 485.30 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1905 +[2025-05-15 00:42:15,773] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 447.52 | bwd_microstep: 542.30 | bwd_inner_microstep: 542.26 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.31 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1897 +[2025-05-15 00:42:16,580] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 331.92 | bwd_microstep: 452.65 | bwd_inner_microstep: 452.39 | bwd_allreduce_microstep: 0.21 | step_microstep: 0.22 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1894 +[2025-05-15 00:42:17,602] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 447.87 | bwd_microstep: 544.16 | bwd_inner_microstep: 543.94 | bwd_allreduce_microstep: 0.19 | step_microstep: 0.20 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1109 +[2025-05-15 00:42:18,035] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 213.27 | bwd_microstep: 200.46 | bwd_inner_microstep: 200.24 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-15 00:42:19,065] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 383.95 | bwd_microstep: 627.37 | bwd_inner_microstep: 627.33 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.27 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-15 00:42:19,946] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 350.37 | bwd_microstep: 508.87 | bwd_inner_microstep: 507.84 | bwd_allreduce_microstep: 0.98 | step_microstep: 0.23 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1474 +[2025-05-15 00:42:21,067] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.22 | optimizer_gradients: 2.14 | optimizer_step: 18.73 +[2025-05-15 00:42:21,068] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 158.47 | bwd_microstep: 916.47 | bwd_inner_microstep: 456.09 | bwd_allreduce_microstep: 460.34 | step_microstep: 27.80 +[2025-05-15 00:42:21,069] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2659.72 | bwd: 4277.65 | bwd_inner: 3815.48 | bwd_allreduce: 461.81 | step: 33.48 + 22%|██▏ | 120/558 [14:16<50:29, 6.92s/it] {'loss': 2.2242, 'grad_norm': 4.3011155128479, 'learning_rate': 9.131972572066564e-16, 'epoch': 0.06} + 22%|██▏ | 120/558 [14:16<50:29, 6.92s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1899 +[2025-05-15 00:42:21,859] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 340.31 | bwd_microstep: 423.07 | bwd_inner_microstep: 423.01 | bwd_allreduce_microstep: 0.02 | step_microstep: 1.84 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-15 00:42:22,883] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 448.66 | bwd_microstep: 549.49 | bwd_inner_microstep: 549.26 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-15 00:42:23,765] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 354.30 | bwd_microstep: 507.10 | bwd_inner_microstep: 507.06 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.25 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-15 00:42:24,562] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 275.20 | bwd_microstep: 497.38 | bwd_inner_microstep: 497.34 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.53 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-15 00:42:25,562] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 442.78 | bwd_microstep: 524.82 | bwd_inner_microstep: 524.59 | bwd_allreduce_microstep: 0.19 | step_microstep: 0.18 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 330 +[2025-05-15 00:42:25,817] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 92.77 | bwd_microstep: 145.06 | bwd_inner_microstep: 144.10 | bwd_allreduce_microstep: 0.94 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-15 00:42:26,647] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 214.31 | bwd_microstep: 593.29 | bwd_inner_microstep: 593.27 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.50 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-15 00:42:27,778] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.03 | optimizer_step: 18.29 +[2025-05-15 00:42:27,778] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 419.71 | bwd_microstep: 654.60 | bwd_inner_microstep: 510.45 | bwd_allreduce_microstep: 144.09 | step_microstep: 27.04 +[2025-05-15 00:42:27,779] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2588.05 | bwd: 3894.83 | bwd_inner: 3749.07 | bwd_allreduce: 145.29 | step: 34.75 + 22%|██▏ | 121/558 [14:23<49:55, 6.86s/it] {'loss': 7.1367, 'grad_norm': 25.76321029663086, 'learning_rate': 9.115553603352552e-16, 'epoch': 0.07} + 22%|██▏ | 121/558 [14:23<49:55, 6.86s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1922 +[2025-05-15 00:42:28,806] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 358.07 | bwd_microstep: 642.73 | bwd_inner_microstep: 642.67 | bwd_allreduce_microstep: 0.02 | step_microstep: 2.54 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1896 +[2025-05-15 00:42:29,716] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 350.95 | bwd_microstep: 526.53 | bwd_inner_microstep: 526.50 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-15 00:42:30,546] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 221.51 | bwd_microstep: 588.28 | bwd_inner_microstep: 588.23 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.58 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-15 00:42:31,518] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 431.46 | bwd_microstep: 508.62 | bwd_inner_microstep: 508.56 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.25 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-15 00:42:32,289] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 354.79 | bwd_microstep: 393.22 | bwd_inner_microstep: 393.19 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.77 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-15 00:42:33,320] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 399.25 | bwd_microstep: 605.09 | bwd_inner_microstep: 605.02 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-15 00:42:34,112] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 321.15 | bwd_microstep: 451.50 | bwd_inner_microstep: 451.28 | bwd_allreduce_microstep: 0.19 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-15 00:42:35,345] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.06 | optimizer_step: 17.79 +[2025-05-15 00:42:35,345] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 442.41 | bwd_microstep: 735.83 | bwd_inner_microstep: 539.21 | bwd_allreduce_microstep: 196.57 | step_microstep: 26.32 +[2025-05-15 00:42:35,346] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2879.57 | bwd: 4451.82 | bwd_inner: 4254.66 | bwd_allreduce: 196.85 | step: 34.04 + 22%|██▏ | 122/558 [14:30<51:22, 7.07s/it] {'loss': 6.6844, 'grad_norm': 33.95225143432617, 'learning_rate': 9.098995852921197e-16, 'epoch': 0.07} + 22%|██▏ | 122/558 [14:30<51:22, 7.07s/it]dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 883 +[2025-05-15 00:42:35,768] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 118.18 | bwd_microstep: 281.07 | bwd_inner_microstep: 280.83 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1889 +[2025-05-15 00:42:36,784] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 443.02 | bwd_microstep: 545.13 | bwd_inner_microstep: 544.74 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.17 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-15 00:42:37,564] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 353.96 | bwd_microstep: 405.66 | bwd_inner_microstep: 405.62 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.28 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 336 +[2025-05-15 00:42:37,825] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 91.62 | bwd_microstep: 144.18 | bwd_inner_microstep: 144.12 | bwd_allreduce_microstep: 0.02 | step_microstep: 2.32 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 840 +[2025-05-15 00:42:38,328] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 215.76 | bwd_microstep: 259.56 | bwd_inner_microstep: 259.52 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.28 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-15 00:42:39,119] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 349.19 | bwd_microstep: 421.68 | bwd_inner_microstep: 421.54 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.11 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 322 +[2025-05-15 00:42:39,355] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 86.79 | bwd_microstep: 131.84 | bwd_inner_microstep: 131.79 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.74 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 835 +[2025-05-15 00:42:40,173] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.01 | optimizer_gradients: 2.11 | optimizer_step: 17.75 +[2025-05-15 00:42:40,173] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 184.35 | bwd_microstep: 584.15 | bwd_inner_microstep: 303.37 | bwd_allreduce_microstep: 280.75 | step_microstep: 26.67 +[2025-05-15 00:42:40,174] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 1842.84 | bwd: 2773.27 | bwd_inner: 2491.55 | bwd_allreduce: 281.06 | step: 31.76 + 22%|██▏ | 123/558 [14:35<46:22, 6.40s/it] {'loss': 6.9772, 'grad_norm': 23.99325942993164, 'learning_rate': 9.08229987912097e-16, 'epoch': 0.07} + 22%|██▏ | 123/558 [14:35<46:22, 6.40s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1939 +[2025-05-15 00:42:41,055] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 234.85 | bwd_microstep: 618.12 | bwd_inner_microstep: 618.08 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1887 +[2025-05-15 00:42:42,007] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 404.60 | bwd_microstep: 514.37 | bwd_inner_microstep: 514.03 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.21 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 342 +[2025-05-15 00:42:42,253] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 78.31 | bwd_microstep: 150.15 | bwd_inner_microstep: 150.10 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.32 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-15 00:42:43,206] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 416.05 | bwd_microstep: 514.93 | bwd_inner_microstep: 514.79 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-15 00:42:44,016] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 292.31 | bwd_microstep: 502.30 | bwd_inner_microstep: 502.09 | bwd_allreduce_microstep: 0.19 | step_microstep: 0.23 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-15 00:42:44,805] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 280.34 | bwd_microstep: 486.45 | bwd_inner_microstep: 486.40 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-15 00:42:45,805] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 440.30 | bwd_microstep: 523.34 | bwd_inner_microstep: 523.28 | bwd_allreduce_microstep: 0.02 | step_microstep: 2.32 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-15 00:42:46,776] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.06 | optimizer_step: 17.80 +[2025-05-15 00:42:46,777] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 356.82 | bwd_microstep: 567.17 | bwd_inner_microstep: 497.58 | bwd_allreduce_microstep: 69.42 | step_microstep: 26.31 +[2025-05-15 00:42:46,777] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2503.55 | bwd: 3876.88 | bwd_inner: 3806.50 | bwd_allreduce: 69.82 | step: 36.21 + 22%|██▏ | 124/558 [14:42<46:43, 6.46s/it] {'loss': 5.9402, 'grad_norm': 39.041259765625, 'learning_rate': 9.0654662449614e-16, 'epoch': 0.07} + 22%|██▏ | 124/558 [14:42<46:43, 6.46s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1915 +[2025-05-15 00:42:47,816] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 370.79 | bwd_microstep: 641.95 | bwd_inner_microstep: 641.66 | bwd_allreduce_microstep: 0.26 | step_microstep: 0.25 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-15 00:42:48,719] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 363.00 | bwd_microstep: 519.94 | bwd_inner_microstep: 519.90 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.98 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 845 +[2025-05-15 00:42:49,045] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.61 | bwd_microstep: 209.47 | bwd_inner_microstep: 209.42 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.75 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1349 +[2025-05-15 00:42:49,843] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 289.39 | bwd_microstep: 483.40 | bwd_inner_microstep: 483.17 | bwd_allreduce_microstep: 0.19 | step_microstep: 0.20 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 329 +[2025-05-15 00:42:50,089] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.32 | bwd_microstep: 133.12 | bwd_inner_microstep: 132.87 | bwd_allreduce_microstep: 0.19 | step_microstep: 0.18 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 835 +[2025-05-15 00:42:50,421] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 166.16 | bwd_microstep: 147.79 | bwd_inner_microstep: 147.52 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 836 +[2025-05-15 00:42:50,860] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 163.92 | bwd_microstep: 256.54 | bwd_inner_microstep: 256.51 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.30 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1894 +[2025-05-15 00:42:51,948] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.04 | optimizer_gradients: 1.65 | optimizer_step: 12.77 +[2025-05-15 00:42:51,948] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 447.65 | bwd_microstep: 587.08 | bwd_inner_microstep: 527.99 | bwd_allreduce_microstep: 59.05 | step_microstep: 19.25 +[2025-05-15 00:42:51,949] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 1990.83 | bwd: 2979.32 | bwd_inner: 2919.11 | bwd_allreduce: 59.46 | step: 25.01 + 22%|██▏ | 125/558 [14:47<43:49, 6.07s/it] {'loss': 5.9092, 'grad_norm': 21.72999382019043, 'learning_rate': 9.048495518094108e-16, 'epoch': 0.07} + 22%|██▏ | 125/558 [14:47<43:49, 6.07s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1892 +[2025-05-15 00:42:52,635] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.91 | bwd_microstep: 473.04 | bwd_inner_microstep: 473.00 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.55 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 346 +[2025-05-15 00:42:52,921] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 106.85 | bwd_microstep: 146.68 | bwd_inner_microstep: 146.65 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1108 +[2025-05-15 00:42:53,502] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 251.79 | bwd_microstep: 298.08 | bwd_inner_microstep: 298.03 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.26 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 331 +[2025-05-15 00:42:53,738] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 87.54 | bwd_microstep: 130.37 | bwd_inner_microstep: 130.22 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-15 00:42:54,598] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 240.91 | bwd_microstep: 597.29 | bwd_inner_microstep: 597.24 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.33 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-15 00:42:55,538] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 379.01 | bwd_microstep: 525.28 | bwd_inner_microstep: 525.24 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.48 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-15 00:42:56,379] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 224.11 | bwd_microstep: 593.02 | bwd_inner_microstep: 592.99 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-15 00:42:57,425] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.11 | optimizer_step: 18.20 +[2025-05-15 00:42:57,428] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 408.57 | bwd_microstep: 576.52 | bwd_inner_microstep: 457.27 | bwd_allreduce_microstep: 119.14 | step_microstep: 31.10 +[2025-05-15 00:42:57,429] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 1889.68 | bwd: 3340.29 | bwd_inner: 3220.72 | bwd_allreduce: 119.25 | step: 43.52 + 23%|██▎ | 126/558 [14:52<42:26, 5.90s/it] {'loss': 5.6768, 'grad_norm': 17.191312789916992, 'learning_rate': 9.031388270793651e-16, 'epoch': 0.07} + 23%|██▎ | 126/558 [14:52<42:26, 5.90s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 352 +[2025-05-15 00:42:57,709] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 101.36 | bwd_microstep: 145.58 | bwd_inner_microstep: 145.54 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-15 00:42:58,700] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 429.98 | bwd_microstep: 529.50 | bwd_inner_microstep: 529.43 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.20 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 847 +[2025-05-15 00:42:59,049] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.69 | bwd_microstep: 235.82 | bwd_inner_microstep: 235.76 | bwd_allreduce_microstep: 0.02 | step_microstep: 1.80 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 331 +[2025-05-15 00:42:59,317] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 100.12 | bwd_microstep: 143.53 | bwd_inner_microstep: 143.49 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-15 00:43:00,302] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 432.22 | bwd_microstep: 515.82 | bwd_inner_microstep: 515.80 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.31 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-15 00:43:01,038] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 246.87 | bwd_microstep: 466.03 | bwd_inner_microstep: 465.98 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.45 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-15 00:43:02,051] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 443.38 | bwd_microstep: 537.23 | bwd_inner_microstep: 537.04 | bwd_allreduce_microstep: 0.17 | step_microstep: 0.18 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 834 +[2025-05-15 00:43:02,590] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.07 | optimizer_step: 18.01 +[2025-05-15 00:43:02,591] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 164.03 | bwd_microstep: 332.29 | bwd_inner_microstep: 235.83 | bwd_allreduce_microstep: 96.39 | step_microstep: 26.39 +[2025-05-15 00:43:02,591] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2011.64 | bwd: 2905.79 | bwd_inner: 2808.85 | bwd_allreduce: 96.64 | step: 38.03 + 23%|██▎ | 127/558 [14:58<40:46, 5.68s/it] {'loss': 6.3889, 'grad_norm': 31.28111457824707, 'learning_rate': 9.014145079938228e-16, 'epoch': 0.07} + 23%|██▎ | 127/558 [14:58<40:46, 5.68s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1895 +[2025-05-15 00:43:03,601] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 357.60 | bwd_microstep: 625.91 | bwd_inner_microstep: 625.87 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1895 +[2025-05-15 00:43:04,500] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 358.79 | bwd_microstep: 512.29 | bwd_inner_microstep: 511.83 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.27 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-15 00:43:05,314] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 247.72 | bwd_microstep: 543.90 | bwd_inner_microstep: 543.87 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-15 00:43:06,305] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 429.87 | bwd_microstep: 524.72 | bwd_inner_microstep: 524.67 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.27 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1099 +[2025-05-15 00:43:06,731] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 182.07 | bwd_microstep: 223.35 | bwd_inner_microstep: 223.30 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.82 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-15 00:43:07,769] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 402.04 | bwd_microstep: 610.22 | bwd_inner_microstep: 610.01 | bwd_allreduce_microstep: 0.17 | step_microstep: 0.18 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 325 +[2025-05-15 00:43:08,014] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.00 | bwd_microstep: 135.05 | bwd_inner_microstep: 134.84 | bwd_allreduce_microstep: 0.18 | step_microstep: 0.17 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-15 00:43:09,316] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.01 | optimizer_gradients: 2.21 | optimizer_step: 18.67 +[2025-05-15 00:43:09,317] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 356.02 | bwd_microstep: 899.26 | bwd_inner_microstep: 344.15 | bwd_allreduce_microstep: 555.09 | step_microstep: 28.03 +[2025-05-15 00:43:09,318] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2427.10 | bwd: 4074.70 | bwd_inner: 3518.55 | bwd_allreduce: 555.49 | step: 37.45 + 23%|██▎ | 128/558 [15:04<42:55, 5.99s/it] {'loss': 6.0152, 'grad_norm': 28.584117889404297, 'learning_rate': 8.99676652699023e-16, 'epoch': 0.07} + 23%|██▎ | 128/558 [15:04<42:55, 5.99s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 370 +[2025-05-15 00:43:09,572] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 87.73 | bwd_microstep: 142.14 | bwd_inner_microstep: 142.10 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.23 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1909 +[2025-05-15 00:43:10,378] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 275.06 | bwd_microstep: 508.46 | bwd_inner_microstep: 508.42 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-15 00:43:11,378] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 442.35 | bwd_microstep: 523.21 | bwd_inner_microstep: 523.18 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.37 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-15 00:43:12,201] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 248.86 | bwd_microstep: 549.47 | bwd_inner_microstep: 549.43 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-15 00:43:13,151] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 424.03 | bwd_microstep: 491.07 | bwd_inner_microstep: 490.84 | bwd_allreduce_microstep: 0.08 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-15 00:43:14,064] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 283.42 | bwd_microstep: 609.81 | bwd_inner_microstep: 609.78 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-15 00:43:14,994] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 380.77 | bwd_microstep: 516.31 | bwd_inner_microstep: 515.92 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1905 +[2025-05-15 00:43:16,315] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.01 | optimizer_gradients: 2.11 | optimizer_step: 18.65 +[2025-05-15 00:43:16,315] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 323.03 | bwd_microstep: 951.18 | bwd_inner_microstep: 456.62 | bwd_allreduce_microstep: 494.35 | step_microstep: 27.28 +[2025-05-15 00:43:16,316] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2465.23 | bwd: 4291.66 | bwd_inner: 3796.36 | bwd_allreduce: 494.62 | step: 37.23 + 23%|██▎ | 129/558 [15:11<44:59, 6.29s/it] {'loss': 4.9479, 'grad_norm': 19.889568328857422, 'learning_rate': 8.979253197976633e-16, 'epoch': 0.07} + 23%|██▎ | 129/558 [15:11<44:59, 6.29s/it]dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1386 +[2025-05-15 00:43:16,958] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 262.10 | bwd_microstep: 354.72 | bwd_inner_microstep: 354.57 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1891 +[2025-05-15 00:43:17,799] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 220.16 | bwd_microstep: 602.49 | bwd_inner_microstep: 602.43 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1887 +[2025-05-15 00:43:18,758] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 409.67 | bwd_microstep: 515.70 | bwd_inner_microstep: 515.55 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-15 00:43:19,632] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 246.70 | bwd_microstep: 601.99 | bwd_inner_microstep: 601.94 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-15 00:43:20,583] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 402.50 | bwd_microstep: 516.25 | bwd_inner_microstep: 515.45 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.24 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-15 00:43:21,398] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 236.22 | bwd_microstep: 555.25 | bwd_inner_microstep: 555.20 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-15 00:43:22,392] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 428.93 | bwd_microstep: 528.33 | bwd_inner_microstep: 528.29 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.32 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1098 +[2025-05-15 00:43:22,985] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.13 | optimizer_step: 17.98 +[2025-05-15 00:43:22,986] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 213.11 | bwd_microstep: 332.69 | bwd_inner_microstep: 272.53 | bwd_allreduce_microstep: 60.07 | step_microstep: 26.64 +[2025-05-15 00:43:22,986] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2419.36 | bwd: 4007.46 | bwd_inner: 3946.80 | bwd_allreduce: 60.25 | step: 36.47 + 23%|██▎ | 130/558 [15:18<45:41, 6.41s/it] {'loss': 5.4194, 'grad_norm': 16.633087158203125, 'learning_rate': 8.961605683469233e-16, 'epoch': 0.07} + 23%|██▎ | 130/558 [15:18<45:41, 6.41s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1973 +[2025-05-15 00:43:24,081] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 410.18 | bwd_microstep: 658.14 | bwd_inner_microstep: 657.75 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.19 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 868 +[2025-05-15 00:43:24,531] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 174.27 | bwd_microstep: 258.51 | bwd_inner_microstep: 258.47 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1908 +[2025-05-15 00:43:25,158] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 324.31 | bwd_microstep: 281.27 | bwd_inner_microstep: 281.15 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-15 00:43:26,201] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 397.93 | bwd_microstep: 627.01 | bwd_inner_microstep: 626.81 | bwd_allreduce_microstep: 0.18 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-15 00:43:26,968] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 354.61 | bwd_microstep: 388.86 | bwd_inner_microstep: 388.83 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.82 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-15 00:43:28,010] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 403.95 | bwd_microstep: 608.50 | bwd_inner_microstep: 608.46 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.28 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-15 00:43:28,810] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 324.76 | bwd_microstep: 452.96 | bwd_inner_microstep: 452.87 | bwd_allreduce_microstep: 0.03 | step_microstep: 0.23 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-15 00:43:30,064] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.01 | optimizer_gradients: 2.08 | optimizer_step: 18.60 +[2025-05-15 00:43:30,065] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 443.40 | bwd_microstep: 753.53 | bwd_inner_microstep: 548.26 | bwd_allreduce_microstep: 205.25 | step_microstep: 27.41 +[2025-05-15 00:43:30,065] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2833.41 | bwd: 4028.81 | bwd_inner: 3822.60 | bwd_allreduce: 205.78 | step: 32.46 + 23%|██▎ | 131/558 [15:25<47:01, 6.61s/it] {'loss': 3.1265, 'grad_norm': 17.63965606689453, 'learning_rate': 8.943824578564723e-16, 'epoch': 0.07} + 23%|██▎ | 131/558 [15:25<47:01, 6.61s/it]dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1154 +[2025-05-15 00:43:30,529] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 128.69 | bwd_microstep: 307.73 | bwd_inner_microstep: 307.69 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.82 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 382 +[2025-05-15 00:43:30,816] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 103.34 | bwd_microstep: 157.40 | bwd_inner_microstep: 157.34 | bwd_allreduce_microstep: 0.02 | step_microstep: 2.58 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1378 +[2025-05-15 00:43:31,579] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 330.40 | bwd_microstep: 397.97 | bwd_inner_microstep: 397.62 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.17 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1887 +[2025-05-15 00:43:32,342] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 358.12 | bwd_microstep: 385.53 | bwd_inner_microstep: 385.50 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.77 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-15 00:43:33,371] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 399.96 | bwd_microstep: 603.26 | bwd_inner_microstep: 603.00 | bwd_allreduce_microstep: 0.24 | step_microstep: 0.43 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-15 00:43:34,257] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 356.02 | bwd_microstep: 511.56 | bwd_inner_microstep: 511.52 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.29 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-15 00:43:35,091] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 215.80 | bwd_microstep: 597.04 | bwd_inner_microstep: 596.97 | bwd_allreduce_microstep: 0.02 | step_microstep: 2.37 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-15 00:43:36,161] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 1.74 | optimizer_step: 14.04 +[2025-05-15 00:43:36,162] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 407.13 | bwd_microstep: 608.25 | bwd_inner_microstep: 524.85 | bwd_allreduce_microstep: 83.34 | step_microstep: 21.01 +[2025-05-15 00:43:36,163] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2299.46 | bwd: 3568.74 | bwd_inner: 3484.49 | bwd_allreduce: 83.82 | step: 30.44 + 24%|██▎ | 132/558 [15:31<45:49, 6.45s/it] {'loss': 4.25, 'grad_norm': 17.284618377685547, 'learning_rate': 8.925910482864653e-16, 'epoch': 0.07} + 24%|██▎ | 132/558 [15:31<45:49, 6.45s/it]dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1127 +[2025-05-15 00:43:36,752] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 218.71 | bwd_microstep: 349.15 | bwd_inner_microstep: 349.12 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1891 +[2025-05-15 00:43:37,724] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 429.18 | bwd_microstep: 509.73 | bwd_inner_microstep: 509.46 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.24 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-15 00:43:38,543] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 245.29 | bwd_microstep: 551.44 | bwd_inner_microstep: 551.39 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-15 00:43:39,540] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 435.85 | bwd_microstep: 524.40 | bwd_inner_microstep: 524.36 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.77 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-15 00:43:40,330] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 354.90 | bwd_microstep: 412.26 | bwd_inner_microstep: 412.21 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.33 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-15 00:43:41,340] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 413.20 | bwd_microstep: 575.68 | bwd_inner_microstep: 575.46 | bwd_allreduce_microstep: 0.18 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-15 00:43:42,137] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 356.41 | bwd_microstep: 421.36 | bwd_inner_microstep: 421.04 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.09 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1348 +[2025-05-15 00:43:43,231] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.01 | optimizer_gradients: 2.04 | optimizer_step: 18.30 +[2025-05-15 00:43:43,232] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 257.08 | bwd_microstep: 792.57 | bwd_inner_microstep: 448.23 | bwd_allreduce_microstep: 344.31 | step_microstep: 27.81 +[2025-05-15 00:43:43,233] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2710.59 | bwd: 4136.64 | bwd_inner: 3791.34 | bwd_allreduce: 344.68 | step: 37.14 + 24%|██▍ | 133/558 [15:38<47:01, 6.64s/it] {'loss': 6.2689, 'grad_norm': 25.09337615966797, 'learning_rate': 8.907864000455172e-16, 'epoch': 0.07} + 24%|██▍ | 133/558 [15:38<47:01, 6.64s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1887 +[2025-05-15 00:43:44,038] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 286.95 | bwd_microstep: 489.20 | bwd_inner_microstep: 489.16 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.46 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1893 +[2025-05-15 00:43:45,006] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 442.71 | bwd_microstep: 491.59 | bwd_inner_microstep: 491.42 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.11 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1357 +[2025-05-15 00:43:45,649] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 180.81 | bwd_microstep: 442.54 | bwd_inner_microstep: 442.49 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-15 00:43:46,629] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 433.99 | bwd_microstep: 514.22 | bwd_inner_microstep: 514.17 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.27 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-15 00:43:47,444] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 234.39 | bwd_microstep: 556.58 | bwd_inner_microstep: 556.55 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 838 +[2025-05-15 00:43:47,958] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 215.97 | bwd_microstep: 267.98 | bwd_inner_microstep: 267.57 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.24 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-15 00:43:48,721] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 356.74 | bwd_microstep: 384.73 | bwd_inner_microstep: 384.69 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.80 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1895 +[2025-05-15 00:43:50,015] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.03 | optimizer_step: 18.07 +[2025-05-15 00:43:50,015] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 401.46 | bwd_microstep: 839.23 | bwd_inner_microstep: 609.31 | bwd_allreduce_microstep: 229.89 | step_microstep: 27.29 +[2025-05-15 00:43:50,016] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2553.00 | bwd: 3986.07 | bwd_inner: 3755.40 | bwd_allreduce: 230.01 | step: 36.88 + 24%|██▍ | 134/558 [15:45<47:13, 6.68s/it] {'loss': 6.3651, 'grad_norm': 38.75448226928711, 'learning_rate': 8.88968573988669e-16, 'epoch': 0.07} + 24%|██▍ | 134/558 [15:45<47:13, 6.68s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1903 +[2025-05-15 00:43:50,846] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 239.66 | bwd_microstep: 561.82 | bwd_inner_microstep: 561.78 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1902 +[2025-05-15 00:43:51,833] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 429.30 | bwd_microstep: 525.94 | bwd_inner_microstep: 525.72 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1896 +[2025-05-15 00:43:52,672] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 226.85 | bwd_microstep: 590.59 | bwd_inner_microstep: 590.56 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.32 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-15 00:43:53,643] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 410.23 | bwd_microstep: 528.47 | bwd_inner_microstep: 528.44 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.30 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1365 +[2025-05-15 00:43:54,220] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 200.96 | bwd_microstep: 352.59 | bwd_inner_microstep: 352.54 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.73 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-15 00:43:55,221] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 439.03 | bwd_microstep: 537.96 | bwd_inner_microstep: 537.92 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.22 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 833 +[2025-05-15 00:43:55,625] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 166.33 | bwd_microstep: 218.43 | bwd_inner_microstep: 218.23 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-15 00:43:56,844] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.01 | optimizer_gradients: 2.13 | optimizer_step: 18.51 +[2025-05-15 00:43:56,845] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 265.62 | bwd_microstep: 909.51 | bwd_inner_microstep: 604.75 | bwd_allreduce_microstep: 304.74 | step_microstep: 27.47 +[2025-05-15 00:43:56,846] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2377.97 | bwd: 4225.33 | bwd_inner: 3920.00 | bwd_allreduce: 304.85 | step: 36.68 + 24%|██▍ | 135/558 [15:52<47:25, 6.73s/it] {'loss': 5.275, 'grad_norm': 25.614803314208984, 'learning_rate': 8.871376314153344e-16, 'epoch': 0.07} + 24%|██▍ | 135/558 [15:52<47:25, 6.73s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-15 00:43:57,629] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 359.70 | bwd_microstep: 397.59 | bwd_inner_microstep: 397.43 | bwd_allreduce_microstep: 0.09 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-15 00:43:58,662] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 391.46 | bwd_microstep: 618.29 | bwd_inner_microstep: 618.24 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.34 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 326 +[2025-05-15 00:43:58,905] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 92.15 | bwd_microstep: 134.74 | bwd_inner_microstep: 134.36 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-15 00:43:59,693] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 317.31 | bwd_microstep: 448.59 | bwd_inner_microstep: 448.48 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-15 00:44:00,708] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 443.74 | bwd_microstep: 540.82 | bwd_inner_microstep: 540.44 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.35 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1086 +[2025-05-15 00:44:01,137] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 209.52 | bwd_microstep: 199.52 | bwd_inner_microstep: 199.12 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.15 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 320 +[2025-05-15 00:44:01,378] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 92.59 | bwd_microstep: 123.43 | bwd_inner_microstep: 123.41 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.78 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 827 +[2025-05-15 00:44:02,163] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.01 | optimizer_gradients: 2.04 | optimizer_step: 19.44 +[2025-05-15 00:44:02,163] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 111.17 | bwd_microstep: 626.09 | bwd_inner_microstep: 306.24 | bwd_allreduce_microstep: 319.83 | step_microstep: 27.67 +[2025-05-15 00:44:02,164] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2017.61 | bwd: 3089.09 | bwd_inner: 2765.38 | bwd_allreduce: 320.36 | step: 31.49 + 24%|██▍ | 136/558 [15:57<44:20, 6.30s/it] {'loss': 8.0141, 'grad_norm': 54.21665954589844, 'learning_rate': 8.852936340672325e-16, 'epoch': 0.07} + 24%|██▍ | 136/558 [15:57<44:20, 6.30s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 365 +[2025-05-15 00:44:02,419] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 92.13 | bwd_microstep: 137.95 | bwd_inner_microstep: 137.00 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1888 +[2025-05-15 00:44:03,262] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 219.63 | bwd_microstep: 600.20 | bwd_inner_microstep: 600.16 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.37 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-15 00:44:04,212] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 406.72 | bwd_microstep: 511.18 | bwd_inner_microstep: 510.96 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-15 00:44:05,031] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 248.59 | bwd_microstep: 547.45 | bwd_inner_microstep: 547.40 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.53 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-15 00:44:05,998] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 423.90 | bwd_microstep: 510.66 | bwd_inner_microstep: 510.63 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.27 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-15 00:44:06,747] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 272.27 | bwd_microstep: 455.75 | bwd_inner_microstep: 455.61 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-15 00:44:07,671] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 311.55 | bwd_microstep: 597.18 | bwd_inner_microstep: 596.79 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1916 +[2025-05-15 00:44:09,052] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 4.54 | optimizer_step: 27.40 +[2025-05-15 00:44:09,052] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 361.21 | bwd_microstep: 959.79 | bwd_inner_microstep: 402.29 | bwd_allreduce_microstep: 557.46 | step_microstep: 39.21 +[2025-05-15 00:44:09,053] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2336.00 | bwd: 4320.16 | bwd_inner: 3760.85 | bwd_allreduce: 558.66 | step: 45.05 + 25%|██▍ | 137/558 [16:04<45:27, 6.48s/it] {'loss': 3.8987, 'grad_norm': 16.949356079101562, 'learning_rate': 8.834366441263057e-16, 'epoch': 0.07} + 25%|██▍ | 137/558 [16:04<45:27, 6.48s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1897 +[2025-05-15 00:44:09,849] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 348.76 | bwd_microstep: 421.78 | bwd_inner_microstep: 421.44 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.11 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 866 +[2025-05-15 00:44:10,319] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 173.36 | bwd_microstep: 275.64 | bwd_inner_microstep: 275.60 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.44 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-15 00:44:11,319] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 443.34 | bwd_microstep: 522.83 | bwd_inner_microstep: 522.80 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-15 00:44:12,111] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 359.72 | bwd_microstep: 410.42 | bwd_inner_microstep: 410.38 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.84 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-15 00:44:13,116] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 409.83 | bwd_microstep: 569.17 | bwd_inner_microstep: 568.94 | bwd_allreduce_microstep: 0.20 | step_microstep: 0.22 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-15 00:44:13,912] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 358.04 | bwd_microstep: 415.54 | bwd_inner_microstep: 415.49 | bwd_allreduce_microstep: 0.02 | step_microstep: 1.84 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-15 00:44:14,915] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 412.52 | bwd_microstep: 564.68 | bwd_inner_microstep: 564.65 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.21 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 838 +[2025-05-15 00:44:15,397] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.03 | optimizer_step: 17.88 +[2025-05-15 00:44:15,397] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 168.76 | bwd_microstep: 270.43 | bwd_inner_microstep: 210.66 | bwd_allreduce_microstep: 59.67 | step_microstep: 26.24 +[2025-05-15 00:44:15,398] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2674.35 | bwd: 3450.53 | bwd_inner: 3390.05 | bwd_allreduce: 60.05 | step: 33.10 + 25%|██▍ | 138/558 [16:10<45:04, 6.44s/it] {'loss': 3.8587, 'grad_norm': 30.99579429626465, 'learning_rate': 8.81566724212624e-16, 'epoch': 0.07} + 25%|██▍ | 138/558 [16:10<45:04, 6.44s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1897 +[2025-05-15 00:44:16,447] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 390.85 | bwd_microstep: 632.07 | bwd_inner_microstep: 632.03 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-15 00:44:17,204] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 361.42 | bwd_microstep: 374.84 | bwd_inner_microstep: 374.79 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.81 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-15 00:44:18,238] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 394.92 | bwd_microstep: 612.53 | bwd_inner_microstep: 612.32 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.24 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-15 00:44:18,987] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 352.96 | bwd_microstep: 374.89 | bwd_inner_microstep: 374.85 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.81 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 329 +[2025-05-15 00:44:19,246] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 91.55 | bwd_microstep: 140.93 | bwd_inner_microstep: 140.88 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-15 00:44:20,262] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 439.78 | bwd_microstep: 542.16 | bwd_inner_microstep: 541.94 | bwd_allreduce_microstep: 0.19 | step_microstep: 0.17 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 837 +[2025-05-15 00:44:20,677] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 165.74 | bwd_microstep: 230.83 | bwd_inner_microstep: 229.85 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.21 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-15 00:44:21,998] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.01 | optimizer_gradients: 2.16 | optimizer_step: 18.23 +[2025-05-15 00:44:21,999] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 349.84 | bwd_microstep: 923.83 | bwd_inner_microstep: 414.27 | bwd_allreduce_microstep: 509.53 | step_microstep: 27.06 +[2025-05-15 00:44:21,999] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2547.07 | bwd: 3832.07 | bwd_inner: 3320.93 | bwd_allreduce: 509.78 | step: 33.84 + 25%|██▍ | 139/558 [16:17<45:18, 6.49s/it] {'loss': 4.58, 'grad_norm': 22.40341567993164, 'learning_rate': 8.796839373822721e-16, 'epoch': 0.07} + 25%|██▍ | 139/558 [16:17<45:18, 6.49s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1917 +[2025-05-15 00:44:22,771] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 355.41 | bwd_microstep: 388.75 | bwd_inner_microstep: 388.72 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.76 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1889 +[2025-05-15 00:44:23,811] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 405.03 | bwd_microstep: 611.89 | bwd_inner_microstep: 611.83 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.26 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 857 +[2025-05-15 00:44:24,253] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 175.79 | bwd_microstep: 247.81 | bwd_inner_microstep: 247.61 | bwd_allreduce_microstep: 0.17 | step_microstep: 0.18 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1356 +[2025-05-15 00:44:24,798] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 264.51 | bwd_microstep: 261.32 | bwd_inner_microstep: 260.93 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.20 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 837 +[2025-05-15 00:44:25,289] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 199.46 | bwd_microstep: 268.04 | bwd_inner_microstep: 267.99 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-15 00:44:26,262] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 424.23 | bwd_microstep: 517.07 | bwd_inner_microstep: 516.69 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.17 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-15 00:44:27,056] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 282.90 | bwd_microstep: 489.69 | bwd_inner_microstep: 489.64 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-15 00:44:28,252] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.07 | optimizer_gradients: 2.09 | optimizer_step: 18.34 +[2025-05-15 00:44:28,252] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 439.81 | bwd_microstep: 696.50 | bwd_inner_microstep: 527.90 | bwd_allreduce_microstep: 168.54 | step_microstep: 27.19 +[2025-05-15 00:44:28,253] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2547.13 | bwd: 3481.09 | bwd_inner: 3311.32 | bwd_allreduce: 169.14 | step: 34.49 + 25%|██▌ | 140/558 [16:23<44:42, 6.42s/it] {'loss': 5.6946, 'grad_norm': 20.987539291381836, 'learning_rate': 8.777883471252235e-16, 'epoch': 0.08} + 25%|██▌ | 140/558 [16:23<44:42, 6.42s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1902 +[2025-05-15 00:44:29,240] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 346.21 | bwd_microstep: 614.06 | bwd_inner_microstep: 614.02 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.48 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1883 +[2025-05-15 00:44:30,139] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 360.20 | bwd_microstep: 504.00 | bwd_inner_microstep: 503.84 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.10 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 331 +[2025-05-15 00:44:30,390] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 87.02 | bwd_microstep: 146.68 | bwd_inner_microstep: 146.65 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.79 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 839 +[2025-05-15 00:44:30,914] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 202.89 | bwd_microstep: 295.51 | bwd_inner_microstep: 295.47 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.33 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-15 00:44:31,850] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 386.52 | bwd_microstep: 514.83 | bwd_inner_microstep: 514.79 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.29 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 838 +[2025-05-15 00:44:32,271] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 166.74 | bwd_microstep: 232.94 | bwd_inner_microstep: 232.90 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.32 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-15 00:44:33,100] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 222.42 | bwd_microstep: 581.21 | bwd_inner_microstep: 581.17 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.37 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-15 00:44:34,288] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.01 | optimizer_gradients: 2.06 | optimizer_step: 18.65 +[2025-05-15 00:44:34,289] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 423.31 | bwd_microstep: 703.40 | bwd_inner_microstep: 499.86 | bwd_allreduce_microstep: 202.59 | step_microstep: 27.03 +[2025-05-15 00:44:34,290] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2195.27 | bwd: 3592.66 | bwd_inner: 3388.73 | bwd_allreduce: 202.72 | step: 38.72 + 25%|██▌ | 141/558 [16:29<43:48, 6.30s/it] {'loss': 5.7679, 'grad_norm': 28.077455520629883, 'learning_rate': 8.758800173631998e-16, 'epoch': 0.08} + 25%|██▌ | 141/558 [16:29<43:48, 6.30s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1919 +[2025-05-15 00:44:35,105] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 267.94 | bwd_microstep: 520.04 | bwd_inner_microstep: 519.97 | bwd_allreduce_microstep: 0.02 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1907 +[2025-05-15 00:44:36,117] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 447.03 | bwd_microstep: 527.95 | bwd_inner_microstep: 527.90 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.26 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1886 +[2025-05-15 00:44:36,915] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 286.64 | bwd_microstep: 489.04 | bwd_inner_microstep: 488.99 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-15 00:44:37,926] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 448.91 | bwd_microstep: 527.52 | bwd_inner_microstep: 527.47 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.23 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-15 00:44:38,709] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 352.70 | bwd_microstep: 408.35 | bwd_inner_microstep: 408.32 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.85 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-15 00:44:39,711] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 391.95 | bwd_microstep: 582.44 | bwd_inner_microstep: 582.17 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.25 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-15 00:44:40,484] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 356.19 | bwd_microstep: 396.37 | bwd_inner_microstep: 396.10 | bwd_allreduce_microstep: 0.22 | step_microstep: 0.22 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1933 +[2025-05-15 00:44:41,795] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 1.69 | optimizer_step: 14.24 +[2025-05-15 00:44:41,795] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 416.03 | bwd_microstep: 850.98 | bwd_inner_microstep: 636.49 | bwd_allreduce_microstep: 214.47 | step_microstep: 21.58 +[2025-05-15 00:44:41,796] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2967.40 | bwd: 4302.68 | bwd_inner: 4087.42 | bwd_allreduce: 214.56 | step: 31.11 + 25%|██▌ | 142/558 [16:37<46:12, 6.66s/it] {'loss': 3.1653, 'grad_norm': 8.087127685546875, 'learning_rate': 8.739590124475148e-16, 'epoch': 0.08} + 25%|██▌ | 142/558 [16:37<46:12, 6.66s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1916 +[2025-05-15 00:44:42,620] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 284.96 | bwd_microstep: 512.87 | bwd_inner_microstep: 512.81 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.59 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 362 +[2025-05-15 00:44:42,915] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 110.72 | bwd_microstep: 152.84 | bwd_inner_microstep: 152.80 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-15 00:44:43,845] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 391.48 | bwd_microstep: 505.14 | bwd_inner_microstep: 504.91 | bwd_allreduce_microstep: 0.21 | step_microstep: 0.21 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-15 00:44:44,635] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 317.12 | bwd_microstep: 451.92 | bwd_inner_microstep: 451.51 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-15 00:44:45,575] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 442.24 | bwd_microstep: 465.53 | bwd_inner_microstep: 465.38 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-15 00:44:46,555] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 345.16 | bwd_microstep: 614.54 | bwd_inner_microstep: 614.50 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 836 +[2025-05-15 00:44:46,959] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 172.30 | bwd_microstep: 199.14 | bwd_inner_microstep: 198.87 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.10 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 831 +[2025-05-15 00:44:47,274] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 1.68 | optimizer_step: 12.96 +[2025-05-15 00:44:47,275] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.58 | bwd_microstep: 187.82 | bwd_inner_microstep: 131.10 | bwd_allreduce_microstep: 56.60 | step_microstep: 19.42 +[2025-05-15 00:44:47,275] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2157.53 | bwd: 3089.83 | bwd_inner: 3031.99 | bwd_allreduce: 57.02 | step: 27.17 + 26%|██▌ | 143/558 [16:42<43:37, 6.31s/it] {'loss': 7.1918, 'grad_norm': 39.446624755859375, 'learning_rate': 8.720253971569047e-16, 'epoch': 0.08} + 26%|██▌ | 143/558 [16:42<43:37, 6.31s/it]dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1149 +[2025-05-15 00:44:47,752] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 123.00 | bwd_microstep: 334.16 | bwd_inner_microstep: 334.05 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1887 +[2025-05-15 00:44:48,716] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 442.06 | bwd_microstep: 490.93 | bwd_inner_microstep: 490.78 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-15 00:44:49,694] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 340.51 | bwd_microstep: 617.09 | bwd_inner_microstep: 617.02 | bwd_allreduce_microstep: 0.02 | step_microstep: 2.38 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1886 +[2025-05-15 00:44:50,504] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 326.35 | bwd_microstep: 448.31 | bwd_inner_microstep: 448.11 | bwd_allreduce_microstep: 0.18 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-15 00:44:51,460] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 443.59 | bwd_microstep: 482.47 | bwd_inner_microstep: 479.81 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-15 00:44:52,443] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 346.15 | bwd_microstep: 616.50 | bwd_inner_microstep: 616.44 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.54 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-15 00:44:53,250] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 324.90 | bwd_microstep: 449.46 | bwd_inner_microstep: 449.23 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.20 +dynamic ViT batch size: 2, images per sample: 2.0, dynamic token length: 898 +[2025-05-15 00:44:54,054] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.01 | optimizer_gradients: 2.11 | optimizer_step: 18.79 +[2025-05-15 00:44:54,055] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 210.81 | bwd_microstep: 538.50 | bwd_inner_microstep: 343.93 | bwd_allreduce_microstep: 194.53 | step_microstep: 27.28 +[2025-05-15 00:44:54,055] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2557.33 | bwd: 3977.62 | bwd_inner: 3779.43 | bwd_allreduce: 194.93 | step: 32.98 + 26%|██▌ | 144/558 [16:49<44:30, 6.45s/it] {'loss': 2.5806, 'grad_norm': 8.076020240783691, 'learning_rate': 8.700792366953437e-16, 'epoch': 0.08} + 26%|██▌ | 144/558 [16:49<44:30, 6.45s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1914 +[2025-05-15 00:44:54,889] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 221.05 | bwd_microstep: 582.63 | bwd_inner_microstep: 582.58 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1887 +[2025-05-15 00:44:55,690] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 419.94 | bwd_microstep: 348.93 | bwd_inner_microstep: 348.66 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1892 +[2025-05-15 00:44:56,353] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.43 | bwd_microstep: 454.62 | bwd_inner_microstep: 454.58 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1887 +[2025-05-15 00:44:57,288] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 442.97 | bwd_microstep: 458.15 | bwd_inner_microstep: 457.83 | bwd_allreduce_microstep: 0.17 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-15 00:44:58,273] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 348.93 | bwd_microstep: 614.52 | bwd_inner_microstep: 614.46 | bwd_allreduce_microstep: 0.02 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1984 +[2025-05-15 00:44:59,146] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 303.59 | bwd_microstep: 534.56 | bwd_inner_microstep: 534.52 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1456 +[2025-05-15 00:44:59,918] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 346.83 | bwd_microstep: 392.80 | bwd_inner_microstep: 392.64 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1966 +[2025-05-15 00:45:01,172] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.01 | optimizer_gradients: 2.16 | optimizer_step: 16.46 +[2025-05-15 00:45:01,173] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 311.82 | bwd_microstep: 898.59 | bwd_inner_microstep: 647.23 | bwd_allreduce_microstep: 251.32 | step_microstep: 25.58 +[2025-05-15 00:45:01,173] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2585.52 | bwd: 4284.82 | bwd_inner: 4032.64 | bwd_allreduce: 251.62 | step: 35.29 + 26%|██▌ | 145/558 [16:56<45:46, 6.65s/it] {'loss': 2.9953, 'grad_norm': 6.534360408782959, 'learning_rate': 8.681205966898452e-16, 'epoch': 0.08} + 26%|██▌ | 145/558 [16:56<45:46, 6.65s/it]dynamic ViT batch size: 2, images per sample: 2.0, dynamic token length: 593 +[2025-05-15 00:45:01,460] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 104.57 | bwd_microstep: 157.02 | bwd_inner_microstep: 154.66 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.79 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-15 00:45:02,498] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 403.30 | bwd_microstep: 608.95 | bwd_inner_microstep: 608.89 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.68 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-15 00:45:03,382] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 350.47 | bwd_microstep: 514.16 | bwd_inner_microstep: 513.96 | bwd_allreduce_microstep: 0.17 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-15 00:45:03,969] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 285.22 | bwd_microstep: 282.22 | bwd_inner_microstep: 281.84 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.24 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-15 00:45:05,009] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 397.76 | bwd_microstep: 621.78 | bwd_inner_microstep: 621.57 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-15 00:45:05,800] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 322.10 | bwd_microstep: 447.28 | bwd_inner_microstep: 447.03 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.22 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-15 00:45:06,807] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 440.18 | bwd_microstep: 537.42 | bwd_inner_microstep: 537.39 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.53 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2070 +[2025-05-15 00:45:08,071] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.07 | optimizer_gradients: 2.12 | optimizer_step: 27.76 +[2025-05-15 00:45:08,072] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 224.07 | bwd_microstep: 987.97 | bwd_inner_microstep: 671.76 | bwd_allreduce_microstep: 316.15 | step_microstep: 36.50 +[2025-05-15 00:45:08,072] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2527.67 | bwd: 4156.82 | bwd_inner: 3839.43 | bwd_allreduce: 316.77 | step: 42.35 + 26%|██▌ | 146/558 [17:03<46:10, 6.73s/it] {'loss': 7.8741, 'grad_norm': 34.02135467529297, 'learning_rate': 8.661495431882483e-16, 'epoch': 0.08} + 26%|██▌ | 146/558 [17:03<46:10, 6.73s/it]dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1459 +[2025-05-15 00:45:08,790] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.65 | bwd_microstep: 497.06 | bwd_inner_microstep: 497.03 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.54 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1889 +[2025-05-15 00:45:09,634] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 416.94 | bwd_microstep: 393.10 | bwd_inner_microstep: 393.06 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.83 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-15 00:45:10,677] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 402.96 | bwd_microstep: 611.59 | bwd_inner_microstep: 611.56 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.48 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-15 00:45:11,515] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 225.76 | bwd_microstep: 589.71 | bwd_inner_microstep: 589.68 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.37 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 842 +[2025-05-15 00:45:12,026] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 224.36 | bwd_microstep: 254.18 | bwd_inner_microstep: 253.96 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.23 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-15 00:45:12,792] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 353.10 | bwd_microstep: 394.57 | bwd_inner_microstep: 394.36 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-15 00:45:13,822] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 391.97 | bwd_microstep: 615.89 | bwd_inner_microstep: 615.69 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.34 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 831 +[2025-05-15 00:45:14,736] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.01 | optimizer_gradients: 2.11 | optimizer_step: 19.27 +[2025-05-15 00:45:14,736] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 149.93 | bwd_microstep: 718.30 | bwd_inner_microstep: 139.08 | bwd_allreduce_microstep: 579.01 | step_microstep: 27.62 +[2025-05-15 00:45:14,737] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2360.63 | bwd: 4074.40 | bwd_inner: 3494.43 | bwd_allreduce: 579.06 | step: 37.43 + 26%|██▋ | 147/558 [17:10<45:56, 6.71s/it] {'loss': 6.8574, 'grad_norm': 38.429832458496094, 'learning_rate': 8.641661426569916e-16, 'epoch': 0.08} + 26%|██▋ | 147/558 [17:10<45:56, 6.71s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1887 +[2025-05-15 00:45:15,550] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 243.57 | bwd_microstep: 540.71 | bwd_inner_microstep: 540.67 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-15 00:45:16,432] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 431.37 | bwd_microstep: 416.57 | bwd_inner_microstep: 416.40 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1883 +[2025-05-15 00:45:17,475] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 393.36 | bwd_microstep: 629.55 | bwd_inner_microstep: 629.51 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.28 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-15 00:45:18,293] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 249.82 | bwd_microstep: 542.61 | bwd_inner_microstep: 542.54 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-15 00:45:19,149] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 431.22 | bwd_microstep: 392.91 | bwd_inner_microstep: 392.67 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-15 00:45:20,190] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 393.75 | bwd_microstep: 624.04 | bwd_inner_microstep: 623.66 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-15 00:45:20,752] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 244.18 | bwd_microstep: 296.70 | bwd_inner_microstep: 296.67 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.84 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1999 +[2025-05-15 00:45:21,997] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.08 | optimizer_gradients: 2.09 | optimizer_step: 20.37 +[2025-05-15 00:45:21,998] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 427.92 | bwd_microstep: 764.54 | bwd_inner_microstep: 648.15 | bwd_allreduce_microstep: 116.16 | step_microstep: 29.18 +[2025-05-15 00:45:21,998] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2815.20 | bwd: 4207.64 | bwd_inner: 4090.29 | bwd_allreduce: 116.31 | step: 38.51 + 27%|██▋ | 148/558 [17:17<46:58, 6.87s/it] {'loss': 4.9474, 'grad_norm': 15.876785278320312, 'learning_rate': 8.621704619788711e-16, 'epoch': 0.08} + 27%|██▋ | 148/558 [17:17<46:58, 6.87s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1899 +[2025-05-15 00:45:22,986] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 347.69 | bwd_microstep: 613.33 | bwd_inner_microstep: 613.29 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.43 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1883 +[2025-05-15 00:45:23,662] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 308.80 | bwd_microstep: 333.23 | bwd_inner_microstep: 333.21 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.87 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1888 +[2025-05-15 00:45:24,692] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 405.99 | bwd_microstep: 597.98 | bwd_inner_microstep: 597.76 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.20 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 856 +[2025-05-15 00:45:25,015] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 121.77 | bwd_microstep: 181.31 | bwd_inner_microstep: 181.26 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.79 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 853 +[2025-05-15 00:45:25,537] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.70 | bwd_microstep: 307.58 | bwd_inner_microstep: 307.52 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-15 00:45:26,373] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 407.63 | bwd_microstep: 394.00 | bwd_inner_microstep: 393.96 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.81 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-15 00:45:27,405] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 422.38 | bwd_microstep: 583.27 | bwd_inner_microstep: 583.22 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-15 00:45:28,599] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 1.70 | optimizer_step: 12.70 +[2025-05-15 00:45:28,600] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 213.52 | bwd_microstep: 942.46 | bwd_inner_microstep: 592.48 | bwd_allreduce_microstep: 349.92 | step_microstep: 19.47 +[2025-05-15 00:45:28,600] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2416.46 | bwd: 3953.34 | bwd_inner: 3602.71 | bwd_allreduce: 350.01 | step: 30.97 + 27%|██▋ | 149/558 [17:24<46:17, 6.79s/it] {'loss': 3.5724, 'grad_norm': 19.434858322143555, 'learning_rate': 8.60162568450785e-16, 'epoch': 0.08} + 27%|██▋ | 149/558 [17:24<46:17, 6.79s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1889 +[2025-05-15 00:45:29,267] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.54 | bwd_microstep: 456.38 | bwd_inner_microstep: 456.15 | bwd_allreduce_microstep: 0.19 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-15 00:45:30,209] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 441.93 | bwd_microstep: 468.73 | bwd_inner_microstep: 468.46 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-15 00:45:31,195] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 350.24 | bwd_microstep: 615.98 | bwd_inner_microstep: 615.94 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.42 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-15 00:45:32,090] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 358.17 | bwd_microstep: 504.32 | bwd_inner_microstep: 504.27 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.24 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-15 00:45:32,881] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 322.53 | bwd_microstep: 447.35 | bwd_inner_microstep: 447.27 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.28 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-15 00:45:33,903] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 444.48 | bwd_microstep: 549.49 | bwd_inner_microstep: 549.45 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.96 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-15 00:45:34,793] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 357.46 | bwd_microstep: 510.17 | bwd_inner_microstep: 509.94 | bwd_allreduce_microstep: 0.19 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-15 00:45:36,117] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.12 | optimizer_step: 18.65 +[2025-05-15 00:45:36,118] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 357.21 | bwd_microstep: 920.49 | bwd_inner_microstep: 403.24 | bwd_allreduce_microstep: 517.21 | step_microstep: 27.62 +[2025-05-15 00:45:36,118] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2822.55 | bwd: 4472.94 | bwd_inner: 3954.79 | bwd_allreduce: 517.75 | step: 31.87 + 27%|██▋ | 150/558 [17:31<47:39, 7.01s/it] {'loss': 4.5296, 'grad_norm': 17.500885009765625, 'learning_rate': 8.581425297814641e-16, 'epoch': 0.08} + 27%|██▋ | 150/558 [17:31<47:39, 7.01s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1897 +[2025-05-15 00:45:36,876] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 346.06 | bwd_microstep: 386.53 | bwd_inner_microstep: 386.25 | bwd_allreduce_microstep: 0.10 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-15 00:45:37,591] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.71 | bwd_microstep: 507.51 | bwd_inner_microstep: 507.44 | bwd_allreduce_microstep: 0.02 | step_microstep: 2.36 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 839 +[2025-05-15 00:45:38,126] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 220.20 | bwd_microstep: 285.13 | bwd_inner_microstep: 284.71 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-15 00:45:39,006] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 358.88 | bwd_microstep: 500.70 | bwd_inner_microstep: 499.75 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-15 00:45:39,845] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 354.75 | bwd_microstep: 463.18 | bwd_inner_microstep: 463.01 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 834 +[2025-05-15 00:45:40,240] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 102.83 | bwd_microstep: 274.96 | bwd_inner_microstep: 274.91 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.30 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-15 00:45:41,255] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 440.15 | bwd_microstep: 548.70 | bwd_inner_microstep: 548.25 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.27 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-15 00:45:42,356] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.01 | optimizer_gradients: 2.17 | optimizer_step: 19.09 +[2025-05-15 00:45:42,356] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 358.71 | bwd_microstep: 694.21 | bwd_inner_microstep: 499.51 | bwd_allreduce_microstep: 194.50 | step_microstep: 27.03 +[2025-05-15 00:45:42,357] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2371.27 | bwd: 3660.94 | bwd_inner: 3463.92 | bwd_allreduce: 194.92 | step: 30.52 + 27%|██▋ | 151/558 [17:37<45:58, 6.78s/it] {'loss': 5.7742, 'grad_norm': 32.724613189697266, 'learning_rate': 8.561104140891893e-16, 'epoch': 0.08} + 27%|██▋ | 151/558 [17:37<45:58, 6.78s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1905 +[2025-05-15 00:45:43,157] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 319.49 | bwd_microstep: 454.17 | bwd_inner_microstep: 454.11 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.23 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-15 00:45:44,179] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 442.90 | bwd_microstep: 549.55 | bwd_inner_microstep: 549.50 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.50 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1368 +[2025-05-15 00:45:44,842] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 256.07 | bwd_microstep: 388.08 | bwd_inner_microstep: 387.68 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.23 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-15 00:45:45,685] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 355.19 | bwd_microstep: 468.11 | bwd_inner_microstep: 467.84 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-15 00:45:46,642] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 324.75 | bwd_microstep: 613.43 | bwd_inner_microstep: 613.38 | bwd_allreduce_microstep: 0.02 | step_microstep: 2.36 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 836 +[2025-05-15 00:45:47,094] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.32 | bwd_microstep: 232.97 | bwd_inner_microstep: 231.82 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2088 +[2025-05-15 00:45:48,081] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 379.28 | bwd_microstep: 584.86 | bwd_inner_microstep: 584.83 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.29 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1907 +[2025-05-15 00:45:49,398] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.01 | optimizer_gradients: 2.22 | optimizer_step: 19.75 +[2025-05-15 00:45:49,399] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 324.98 | bwd_microstep: 941.11 | bwd_inner_microstep: 462.98 | bwd_allreduce_microstep: 478.10 | step_microstep: 28.85 +[2025-05-15 00:45:49,400] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2590.97 | bwd: 4232.30 | bwd_inner: 3752.18 | bwd_allreduce: 478.46 | step: 35.76 + 27%|██▋ | 152/558 [17:44<46:24, 6.86s/it] {'loss': 2.5922, 'grad_norm': 14.02907657623291, 'learning_rate': 8.540662898994941e-16, 'epoch': 0.08} + 27%|██▋ | 152/558 [17:44<46:24, 6.86s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-15 00:45:50,167] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 344.92 | bwd_microstep: 396.09 | bwd_inner_microstep: 395.87 | bwd_allreduce_microstep: 0.20 | step_microstep: 0.21 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 849 +[2025-05-15 00:45:50,682] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 207.51 | bwd_microstep: 282.19 | bwd_inner_microstep: 282.16 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-15 00:45:51,664] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 429.47 | bwd_microstep: 519.81 | bwd_inner_microstep: 519.77 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-15 00:45:52,548] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 360.35 | bwd_microstep: 503.02 | bwd_inner_microstep: 502.98 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.75 +dynamic ViT batch size: 2, images per sample: 2.0, dynamic token length: 591 +[2025-05-15 00:45:52,853] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 121.20 | bwd_microstep: 165.75 | bwd_inner_microstep: 165.72 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.25 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-15 00:45:53,409] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 216.91 | bwd_microstep: 318.03 | bwd_inner_microstep: 318.00 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.85 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-15 00:45:54,446] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 407.09 | bwd_microstep: 601.69 | bwd_inner_microstep: 601.63 | bwd_allreduce_microstep: 0.02 | step_microstep: 2.51 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1951 +[2025-05-15 00:45:55,832] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.01 | optimizer_gradients: 2.00 | optimizer_step: 18.60 +[2025-05-15 00:45:55,832] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 364.55 | bwd_microstep: 972.92 | bwd_inner_microstep: 428.72 | bwd_allreduce_microstep: 544.18 | step_microstep: 26.85 +[2025-05-15 00:45:55,833] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2451.99 | bwd: 3759.52 | bwd_inner: 3214.87 | bwd_allreduce: 544.44 | step: 34.97 + 27%|██▋ | 153/558 [17:51<45:25, 6.73s/it] {'loss': 5.3647, 'grad_norm': 34.94285583496094, 'learning_rate': 8.520102261428533e-16, 'epoch': 0.08} + 27%|██▋ | 153/558 [17:51<45:25, 6.73s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1909 +[2025-05-15 00:45:56,736] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 350.13 | bwd_microstep: 525.15 | bwd_inner_microstep: 525.11 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.00 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1892 +[2025-05-15 00:45:57,547] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 367.20 | bwd_microstep: 420.34 | bwd_inner_microstep: 420.29 | bwd_allreduce_microstep: 0.02 | step_microstep: 1.80 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-15 00:45:58,549] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 408.58 | bwd_microstep: 569.36 | bwd_inner_microstep: 569.31 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.31 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 330 +[2025-05-15 00:45:58,807] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 91.46 | bwd_microstep: 146.65 | bwd_inner_microstep: 146.61 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.79 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-15 00:45:59,580] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 360.45 | bwd_microstep: 392.71 | bwd_inner_microstep: 392.48 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-15 00:46:00,638] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 398.51 | bwd_microstep: 634.20 | bwd_inner_microstep: 634.16 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.39 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-15 00:46:01,480] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 358.56 | bwd_microstep: 462.71 | bwd_inner_microstep: 462.57 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 2, images per sample: 2.0, dynamic token length: 583 +[2025-05-15 00:46:02,332] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.01 | optimizer_gradients: 2.12 | optimizer_step: 18.32 +[2025-05-15 00:46:02,334] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 73.77 | bwd_microstep: 738.44 | bwd_inner_microstep: 159.71 | bwd_allreduce_microstep: 578.71 | step_microstep: 28.74 +[2025-05-15 00:46:02,335] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2408.66 | bwd: 3889.59 | bwd_inner: 3310.27 | bwd_allreduce: 578.84 | step: 35.31 + 28%|██▊ | 154/558 [17:57<44:51, 6.66s/it] {'loss': 5.1607, 'grad_norm': 17.69561195373535, 'learning_rate': 8.499422921523597e-16, 'epoch': 0.08} + 28%|██▊ | 154/558 [17:57<44:51, 6.66s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 374 +[2025-05-15 00:46:02,606] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 99.13 | bwd_microstep: 148.43 | bwd_inner_microstep: 148.13 | bwd_allreduce_microstep: 0.27 | step_microstep: 0.93 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-15 00:46:03,387] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 346.32 | bwd_microstep: 413.90 | bwd_inner_microstep: 413.86 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.82 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-15 00:46:04,389] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 407.40 | bwd_microstep: 567.17 | bwd_inner_microstep: 567.14 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.30 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-15 00:46:05,266] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 352.83 | bwd_microstep: 501.70 | bwd_inner_microstep: 501.37 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-15 00:46:06,138] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 251.51 | bwd_microstep: 598.02 | bwd_inner_microstep: 597.98 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-15 00:46:07,080] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 386.14 | bwd_microstep: 522.73 | bwd_inner_microstep: 522.69 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.81 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 1034 +[2025-05-15 00:46:07,595] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 202.59 | bwd_microstep: 293.72 | bwd_inner_microstep: 293.66 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.94 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 407 +[2025-05-15 00:46:08,430] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.01 | optimizer_gradients: 3.16 | optimizer_step: 16.38 +[2025-05-15 00:46:08,431] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 86.82 | bwd_microstep: 704.01 | bwd_inner_microstep: 165.88 | bwd_allreduce_microstep: 538.10 | step_microstep: 26.13 +[2025-05-15 00:46:08,431] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2132.71 | bwd: 3749.73 | bwd_inner: 3210.77 | bwd_allreduce: 538.56 | step: 36.48 + 28%|██▊ | 155/558 [18:03<43:36, 6.49s/it] {'loss': 4.7352, 'grad_norm': 19.59267807006836, 'learning_rate': 8.478625576613853e-16, 'epoch': 0.08} + 28%|██▊ | 155/558 [18:03<43:36, 6.49s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1900 +[2025-05-15 00:46:09,320] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 342.56 | bwd_microstep: 518.59 | bwd_inner_microstep: 518.56 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.23 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-15 00:46:09,858] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.15 | bwd_microstep: 325.68 | bwd_inner_microstep: 325.65 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.29 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1361 +[2025-05-15 00:46:10,667] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 294.48 | bwd_microstep: 488.92 | bwd_inner_microstep: 488.87 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1375 +[2025-05-15 00:46:11,350] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 262.14 | bwd_microstep: 388.85 | bwd_inner_microstep: 388.45 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.23 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-15 00:46:12,141] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 320.46 | bwd_microstep: 450.62 | bwd_inner_microstep: 450.22 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.25 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-15 00:46:13,161] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 442.14 | bwd_microstep: 542.87 | bwd_inner_microstep: 542.83 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.32 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2125 +[2025-05-15 00:46:14,029] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 381.81 | bwd_microstep: 465.93 | bwd_inner_microstep: 465.88 | bwd_allreduce_microstep: 0.02 | step_microstep: 1.84 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1428 +[2025-05-15 00:46:15,117] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.01 | optimizer_gradients: 2.14 | optimizer_step: 20.50 +[2025-05-15 00:46:15,118] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 298.81 | bwd_microstep: 734.99 | bwd_inner_microstep: 504.82 | bwd_allreduce_microstep: 230.13 | step_microstep: 28.42 +[2025-05-15 00:46:15,118] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2532.53 | bwd: 3916.46 | bwd_inner: 3685.29 | bwd_allreduce: 230.56 | step: 35.81 + 28%|██▊ | 156/558 [18:10<43:53, 6.55s/it] {'loss': 2.5068, 'grad_norm': 9.649740219116211, 'learning_rate': 8.457710928012301e-16, 'epoch': 0.08} + 28%|██▊ | 156/558 [18:10<43:53, 6.55s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1951 +[2025-05-15 00:46:15,924] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 363.37 | bwd_microstep: 415.30 | bwd_inner_microstep: 414.78 | bwd_allreduce_microstep: 0.49 | step_microstep: 0.63 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1396 +[2025-05-15 00:46:16,729] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 289.90 | bwd_microstep: 492.63 | bwd_inner_microstep: 492.58 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-15 00:46:17,656] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 370.02 | bwd_microstep: 523.33 | bwd_inner_microstep: 523.31 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.58 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-15 00:46:18,450] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 214.74 | bwd_microstep: 559.10 | bwd_inner_microstep: 559.07 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-15 00:46:19,441] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 429.25 | bwd_microstep: 525.07 | bwd_inner_microstep: 525.05 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.30 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-15 00:46:20,198] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 354.62 | bwd_microstep: 379.62 | bwd_inner_microstep: 379.59 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.80 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-15 00:46:21,225] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 391.97 | bwd_microstep: 608.70 | bwd_inner_microstep: 608.48 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.24 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1949 +[2025-05-15 00:46:22,376] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.01 | optimizer_gradients: 2.11 | optimizer_step: 18.86 +[2025-05-15 00:46:22,377] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 365.86 | bwd_microstep: 739.99 | bwd_inner_microstep: 551.19 | bwd_allreduce_microstep: 188.76 | step_microstep: 27.26 +[2025-05-15 00:46:22,378] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2779.71 | bwd: 4243.94 | bwd_inner: 4054.06 | bwd_allreduce: 189.30 | step: 38.53 + 28%|██▊ | 157/558 [18:17<45:12, 6.76s/it] {'loss': 4.5137, 'grad_norm': 18.7924861907959, 'learning_rate': 8.436679680987572e-16, 'epoch': 0.08} + 28%|██▊ | 157/558 [18:17<45:12, 6.76s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1900 +[2025-05-15 00:46:23,227] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 223.31 | bwd_microstep: 594.52 | bwd_inner_microstep: 594.48 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1110 +[2025-05-15 00:46:23,853] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 272.69 | bwd_microstep: 322.44 | bwd_inner_microstep: 322.23 | bwd_allreduce_microstep: 0.17 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-15 00:46:24,727] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 357.61 | bwd_microstep: 497.22 | bwd_inner_microstep: 497.06 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-15 00:46:25,615] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 263.97 | bwd_microstep: 600.19 | bwd_inner_microstep: 600.16 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.33 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-15 00:46:26,558] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 391.89 | bwd_microstep: 519.47 | bwd_inner_microstep: 519.43 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-15 00:46:27,369] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 248.05 | bwd_microstep: 540.42 | bwd_inner_microstep: 540.38 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-15 00:46:28,346] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 443.20 | bwd_microstep: 501.37 | bwd_inner_microstep: 501.14 | bwd_allreduce_microstep: 0.21 | step_microstep: 0.21 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 325 +[2025-05-15 00:46:28,757] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.06 | optimizer_step: 17.68 +[2025-05-15 00:46:28,757] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 92.49 | bwd_microstep: 275.55 | bwd_inner_microstep: 126.26 | bwd_allreduce_microstep: 149.08 | step_microstep: 26.11 +[2025-05-15 00:46:28,758] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2293.19 | bwd: 3851.20 | bwd_inner: 3701.16 | bwd_allreduce: 149.58 | step: 33.86 + 28%|██▊ | 158/558 [18:24<44:19, 6.65s/it] {'loss': 3.5334, 'grad_norm': 18.4650821685791, 'learning_rate': 8.41553254474014e-16, 'epoch': 0.08} + 28%|██▊ | 158/558 [18:24<44:19, 6.65s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1903 +[2025-05-15 00:46:29,755] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 346.73 | bwd_microstep: 624.62 | bwd_inner_microstep: 624.59 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.28 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1916 +[2025-05-15 00:46:30,680] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 360.42 | bwd_microstep: 529.66 | bwd_inner_microstep: 529.61 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.32 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-15 00:46:31,446] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 365.37 | bwd_microstep: 378.99 | bwd_inner_microstep: 378.93 | bwd_allreduce_microstep: 0.02 | step_microstep: 1.79 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 845 +[2025-05-15 00:46:31,963] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 206.67 | bwd_microstep: 285.06 | bwd_inner_microstep: 285.02 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.50 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1349 +[2025-05-15 00:46:32,722] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 330.83 | bwd_microstep: 395.11 | bwd_inner_microstep: 395.06 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.19 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 322 +[2025-05-15 00:46:32,982] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.91 | bwd_microstep: 148.76 | bwd_inner_microstep: 148.71 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.21 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-15 00:46:33,758] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 307.16 | bwd_microstep: 447.93 | bwd_inner_microstep: 447.73 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1954 +[2025-05-15 00:46:35,000] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.01 | optimizer_gradients: 2.05 | optimizer_step: 18.38 +[2025-05-15 00:46:35,001] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 400.40 | bwd_microstep: 797.89 | bwd_inner_microstep: 598.90 | bwd_allreduce_microstep: 198.97 | step_microstep: 27.45 +[2025-05-15 00:46:35,002] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2411.47 | bwd: 3608.01 | bwd_inner: 3408.55 | bwd_allreduce: 199.22 | step: 36.94 + 28%|██▊ | 159/558 [18:30<43:24, 6.53s/it] {'loss': 6.8833, 'grad_norm': 31.07752799987793, 'learning_rate': 8.394270232378419e-16, 'epoch': 0.09} + 28%|██▊ | 159/558 [18:30<43:24, 6.53s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1905 +[2025-05-15 00:46:35,812] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 359.13 | bwd_microstep: 422.22 | bwd_inner_microstep: 422.19 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.84 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1365 +[2025-05-15 00:46:36,610] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 317.64 | bwd_microstep: 456.68 | bwd_inner_microstep: 456.28 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.24 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 335 +[2025-05-15 00:46:36,852] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 92.90 | bwd_microstep: 133.05 | bwd_inner_microstep: 132.84 | bwd_allreduce_microstep: 0.18 | step_microstep: 0.17 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1888 +[2025-05-15 00:46:37,726] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 356.83 | bwd_microstep: 497.94 | bwd_inner_microstep: 497.62 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-15 00:46:38,618] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 266.82 | bwd_microstep: 604.98 | bwd_inner_microstep: 604.95 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-15 00:46:39,561] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 390.89 | bwd_microstep: 516.60 | bwd_inner_microstep: 516.56 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.96 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-15 00:46:40,341] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 351.93 | bwd_microstep: 405.20 | bwd_inner_microstep: 405.16 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.83 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1954 +[2025-05-15 00:46:41,614] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.01 | optimizer_gradients: 2.14 | optimizer_step: 17.76 +[2025-05-15 00:46:41,615] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 429.33 | bwd_microstep: 790.49 | bwd_inner_microstep: 597.95 | bwd_allreduce_microstep: 192.51 | step_microstep: 27.24 +[2025-05-15 00:46:41,615] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2565.44 | bwd: 3827.17 | bwd_inner: 3633.61 | bwd_allreduce: 193.05 | step: 34.71 + 29%|██▊ | 160/558 [18:37<43:28, 6.55s/it] {'loss': 3.6494, 'grad_norm': 12.845274925231934, 'learning_rate': 8.3728934608947e-16, 'epoch': 0.09} + 29%|██▊ | 160/558 [18:37<43:28, 6.55s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1906 +[2025-05-15 00:46:42,274] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 351.09 | bwd_microstep: 280.21 | bwd_inner_microstep: 280.06 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-15 00:46:43,070] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 196.13 | bwd_microstep: 582.27 | bwd_inner_microstep: 582.23 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.58 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-15 00:46:44,034] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 425.01 | bwd_microstep: 505.10 | bwd_inner_microstep: 504.86 | bwd_allreduce_microstep: 0.22 | step_microstep: 0.24 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-15 00:46:44,910] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 356.22 | bwd_microstep: 499.14 | bwd_inner_microstep: 499.07 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.77 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-15 00:46:45,740] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 219.79 | bwd_microstep: 587.49 | bwd_inner_microstep: 587.44 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-15 00:46:46,691] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 402.83 | bwd_microstep: 515.12 | bwd_inner_microstep: 515.09 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.26 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-15 00:46:47,458] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 352.69 | bwd_microstep: 392.50 | bwd_inner_microstep: 392.45 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.93 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2071 +[2025-05-15 00:46:48,818] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.01 | optimizer_gradients: 2.11 | optimizer_step: 18.43 +[2025-05-15 00:46:48,818] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 438.58 | bwd_microstep: 867.97 | bwd_inner_microstep: 662.60 | bwd_allreduce_microstep: 205.18 | step_microstep: 27.29 +[2025-05-15 00:46:48,819] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2742.32 | bwd: 4229.80 | bwd_inner: 4023.83 | bwd_allreduce: 205.51 | step: 35.51 + 29%|██▉ | 161/558 [18:44<44:39, 6.75s/it] {'loss': 4.4707, 'grad_norm': 37.6964225769043, 'learning_rate': 8.351402951140988e-16, 'epoch': 0.09} + 29%|██▉ | 161/558 [18:44<44:39, 6.75s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1902 +[2025-05-15 00:46:49,717] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 336.60 | bwd_microstep: 531.68 | bwd_inner_microstep: 531.64 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.32 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-15 00:46:50,472] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 361.25 | bwd_microstep: 368.43 | bwd_inner_microstep: 368.41 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.91 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-15 00:46:51,509] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 401.48 | bwd_microstep: 605.29 | bwd_inner_microstep: 605.24 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.32 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-15 00:46:52,403] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 355.13 | bwd_microstep: 516.34 | bwd_inner_microstep: 516.28 | bwd_allreduce_microstep: 0.02 | step_microstep: 1.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-15 00:46:53,165] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 341.76 | bwd_microstep: 398.35 | bwd_inner_microstep: 398.32 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.29 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-15 00:46:54,169] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 407.85 | bwd_microstep: 571.25 | bwd_inner_microstep: 570.89 | bwd_allreduce_microstep: 0.18 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1937 +[2025-05-15 00:46:55,102] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 364.37 | bwd_microstep: 546.84 | bwd_inner_microstep: 546.79 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.30 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1883 +[2025-05-15 00:46:56,401] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.01 | optimizer_gradients: 3.18 | optimizer_step: 18.64 +[2025-05-15 00:46:56,402] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 286.45 | bwd_microstep: 963.87 | bwd_inner_microstep: 500.29 | bwd_allreduce_microstep: 463.55 | step_microstep: 28.51 +[2025-05-15 00:46:56,403] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2854.90 | bwd: 4502.04 | bwd_inner: 4037.86 | bwd_allreduce: 463.79 | step: 38.96 + 29%|██▉ | 162/558 [18:51<46:11, 7.00s/it] {'loss': 4.9979, 'grad_norm': 32.65323257446289, 'learning_rate': 8.329799427804683e-16, 'epoch': 0.09} + 29%|██▉ | 162/558 [18:51<46:11, 7.00s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1937 +[2025-05-15 00:46:57,338] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 356.52 | bwd_microstep: 550.42 | bwd_inner_microstep: 550.16 | bwd_allreduce_microstep: 0.19 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1916 +[2025-05-15 00:46:58,152] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 364.27 | bwd_microstep: 430.29 | bwd_inner_microstep: 430.14 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-15 00:46:59,176] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 358.86 | bwd_microstep: 644.45 | bwd_inner_microstep: 644.42 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-15 00:47:00,065] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 353.46 | bwd_microstep: 511.13 | bwd_inner_microstep: 510.76 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-15 00:47:00,834] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 356.73 | bwd_microstep: 390.46 | bwd_inner_microstep: 390.44 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.76 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-15 00:47:01,865] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 395.89 | bwd_microstep: 609.33 | bwd_inner_microstep: 609.31 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-15 00:47:02,680] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 338.84 | bwd_microstep: 458.65 | bwd_inner_microstep: 458.44 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-15 00:47:03,922] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.53 | optimizer_gradients: 2.11 | optimizer_step: 18.42 +[2025-05-15 00:47:03,923] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 314.73 | bwd_microstep: 881.67 | bwd_inner_microstep: 611.11 | bwd_allreduce_microstep: 270.53 | step_microstep: 27.33 +[2025-05-15 00:47:03,923] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2839.25 | bwd: 4476.59 | bwd_inner: 4204.88 | bwd_allreduce: 270.84 | step: 33.11 + 29%|██▉ | 163/558 [18:59<47:06, 7.16s/it] {'loss': 3.7451, 'grad_norm': 19.39345359802246, 'learning_rate': 8.308083619384155e-16, 'epoch': 0.09} + 29%|██▉ | 163/558 [18:59<47:06, 7.16s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1930 +[2025-05-15 00:47:04,799] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 366.99 | bwd_microstep: 479.69 | bwd_inner_microstep: 479.53 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1917 +[2025-05-15 00:47:05,788] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 340.03 | bwd_microstep: 628.46 | bwd_inner_microstep: 628.41 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.46 +dynamic ViT batch size: 6, images per sample: 6.0, dynamic token length: 1623 +[2025-05-15 00:47:06,598] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 324.36 | bwd_microstep: 453.34 | bwd_inner_microstep: 453.12 | bwd_allreduce_microstep: 0.18 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-15 00:47:07,389] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 248.29 | bwd_microstep: 521.23 | bwd_inner_microstep: 521.21 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-15 00:47:08,382] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 441.84 | bwd_microstep: 520.71 | bwd_inner_microstep: 520.32 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.19 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 323 +[2025-05-15 00:47:08,635] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.50 | bwd_microstep: 139.19 | bwd_inner_microstep: 139.14 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.25 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-15 00:47:09,400] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 346.74 | bwd_microstep: 394.52 | bwd_inner_microstep: 394.46 | bwd_allreduce_microstep: 0.02 | step_microstep: 2.33 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1923 +[2025-05-15 00:47:10,696] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.01 | optimizer_gradients: 2.14 | optimizer_step: 19.16 +[2025-05-15 00:47:10,696] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 416.71 | bwd_microstep: 829.83 | bwd_inner_microstep: 627.88 | bwd_allreduce_microstep: 201.74 | step_microstep: 27.50 +[2025-05-15 00:47:10,697] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2580.43 | bwd: 3966.97 | bwd_inner: 3764.09 | bwd_allreduce: 202.05 | step: 35.38 + 29%|██▉ | 164/558 [19:06<46:14, 7.04s/it] {'loss': 4.2398, 'grad_norm': 31.223247528076172, 'learning_rate': 8.286256258164159e-16, 'epoch': 0.09} + 29%|██▉ | 164/558 [19:06<46:14, 7.04s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1895 +[2025-05-15 00:47:11,599] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 347.83 | bwd_microstep: 525.92 | bwd_inner_microstep: 525.90 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.32 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1887 +[2025-05-15 00:47:12,418] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 247.81 | bwd_microstep: 544.42 | bwd_inner_microstep: 544.35 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1883 +[2025-05-15 00:47:13,400] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 440.77 | bwd_microstep: 509.77 | bwd_inner_microstep: 508.79 | bwd_allreduce_microstep: 0.94 | step_microstep: 0.21 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1897 +[2025-05-15 00:47:14,296] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 357.74 | bwd_microstep: 517.11 | bwd_inner_microstep: 517.07 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.25 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1360 +[2025-05-15 00:47:14,857] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 256.23 | bwd_microstep: 284.69 | bwd_inner_microstep: 284.30 | bwd_allreduce_microstep: 0.31 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-15 00:47:15,905] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 394.31 | bwd_microstep: 628.42 | bwd_inner_microstep: 628.38 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.27 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-15 00:47:16,787] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 356.82 | bwd_microstep: 505.80 | bwd_inner_microstep: 505.51 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-15 00:47:18,164] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.01 | optimizer_gradients: 2.13 | optimizer_step: 18.38 +[2025-05-15 00:47:18,165] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 355.77 | bwd_microstep: 972.67 | bwd_inner_microstep: 391.73 | bwd_allreduce_microstep: 580.92 | step_microstep: 27.57 +[2025-05-15 00:47:18,165] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2757.27 | bwd: 4488.78 | bwd_inner: 3906.02 | bwd_allreduce: 582.18 | step: 35.36 + 30%|██▉ | 165/558 [19:13<46:57, 7.17s/it] {'loss': 4.3798, 'grad_norm': 22.987125396728516, 'learning_rate': 8.264318080191163e-16, 'epoch': 0.09} + 30%|██▉ | 165/558 [19:13<46:57, 7.17s/it]dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1496 +[2025-05-15 00:47:18,901] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 267.63 | bwd_microstep: 440.73 | bwd_inner_microstep: 440.53 | bwd_allreduce_microstep: 0.18 | step_microstep: 0.17 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-15 00:47:19,681] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 358.33 | bwd_microstep: 400.68 | bwd_inner_microstep: 400.63 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.33 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-15 00:47:20,713] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 421.11 | bwd_microstep: 589.93 | bwd_inner_microstep: 589.89 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.27 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-15 00:47:21,500] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 342.03 | bwd_microstep: 423.87 | bwd_inner_microstep: 423.55 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.10 +dynamic ViT batch size: 2, images per sample: 2.0, dynamic token length: 582 +[2025-05-15 00:47:21,833] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 114.97 | bwd_microstep: 200.99 | bwd_inner_microstep: 200.93 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.23 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-15 00:47:22,854] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 447.20 | bwd_microstep: 543.88 | bwd_inner_microstep: 543.84 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-15 00:47:23,741] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 347.96 | bwd_microstep: 519.91 | bwd_inner_microstep: 519.62 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.10 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 867 +[2025-05-15 00:47:24,084] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.07 | optimizer_gradients: 2.12 | optimizer_step: 17.76 +[2025-05-15 00:47:24,085] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.12 | bwd_microstep: 207.18 | bwd_inner_microstep: 135.40 | bwd_allreduce_microstep: 71.63 | step_microstep: 26.94 +[2025-05-15 00:47:24,086] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2393.31 | bwd: 3327.23 | bwd_inner: 3254.58 | bwd_allreduce: 72.08 | step: 31.26 + 30%|██▉ | 166/558 [19:19<44:23, 6.79s/it] {'loss': 3.9717, 'grad_norm': 16.388038635253906, 'learning_rate': 8.242269825248509e-16, 'epoch': 0.09} + 30%|██▉ | 166/558 [19:19<44:23, 6.79s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1883 +[2025-05-15 00:47:25,098] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 363.03 | bwd_microstep: 620.46 | bwd_inner_microstep: 620.42 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.33 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-15 00:47:26,004] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 345.76 | bwd_microstep: 523.56 | bwd_inner_microstep: 523.52 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.32 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-15 00:47:26,799] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 323.22 | bwd_microstep: 448.34 | bwd_inner_microstep: 448.01 | bwd_allreduce_microstep: 0.28 | step_microstep: 0.20 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1356 +[2025-05-15 00:47:27,598] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 325.46 | bwd_microstep: 438.35 | bwd_inner_microstep: 438.12 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.24 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-15 00:47:28,486] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 358.13 | bwd_microstep: 510.22 | bwd_inner_microstep: 510.18 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.23 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1345 +[2025-05-15 00:47:29,164] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 259.44 | bwd_microstep: 398.06 | bwd_inner_microstep: 397.86 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.18 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 324 +[2025-05-15 00:47:29,410] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.58 | bwd_microstep: 135.12 | bwd_inner_microstep: 134.65 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-15 00:47:30,693] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.91 | optimizer_gradients: 2.09 | optimizer_step: 18.03 +[2025-05-15 00:47:30,694] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 281.55 | bwd_microstep: 956.08 | bwd_inner_microstep: 491.61 | bwd_allreduce_microstep: 464.44 | step_microstep: 25.84 +[2025-05-15 00:47:30,694] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2350.18 | bwd: 4030.38 | bwd_inner: 3564.37 | bwd_allreduce: 464.75 | step: 31.54 + 30%|██▉ | 167/558 [19:26<43:54, 6.74s/it] {'loss': 5.089, 'grad_norm': 28.506898880004883, 'learning_rate': 8.220112236831481e-16, 'epoch': 0.09} + 30%|██▉ | 167/558 [19:26<43:54, 6.74s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-15 00:47:31,566] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 352.24 | bwd_microstep: 494.83 | bwd_inner_microstep: 494.68 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-15 00:47:32,447] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 265.53 | bwd_microstep: 594.78 | bwd_inner_microstep: 594.74 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.44 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 333 +[2025-05-15 00:47:32,718] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 100.27 | bwd_microstep: 138.41 | bwd_inner_microstep: 137.47 | bwd_allreduce_microstep: 0.92 | step_microstep: 0.25 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 833 +[2025-05-15 00:47:33,137] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 163.49 | bwd_microstep: 235.48 | bwd_inner_microstep: 235.45 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.64 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 838 +[2025-05-15 00:47:33,567] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 175.23 | bwd_microstep: 234.99 | bwd_inner_microstep: 234.95 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.26 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-15 00:47:34,360] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 267.33 | bwd_microstep: 503.43 | bwd_inner_microstep: 503.39 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-15 00:47:35,368] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 442.83 | bwd_microstep: 530.80 | bwd_inner_microstep: 530.77 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-15 00:47:36,753] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.13 | optimizer_step: 17.74 +[2025-05-15 00:47:36,754] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 356.34 | bwd_microstep: 982.81 | bwd_inner_microstep: 391.18 | bwd_allreduce_microstep: 591.60 | step_microstep: 26.97 +[2025-05-15 00:47:36,755] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2123.25 | bwd: 3715.54 | bwd_inner: 3122.66 | bwd_allreduce: 591.71 | step: 36.13 + 30%|███ | 168/558 [19:32<42:28, 6.54s/it] {'loss': 6.8229, 'grad_norm': 36.39131164550781, 'learning_rate': 8.197846062122224e-16, 'epoch': 0.09} + 30%|███ | 168/558 [19:32<42:28, 6.54s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 348 +[2025-05-15 00:47:37,014] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 97.53 | bwd_microstep: 137.29 | bwd_inner_microstep: 137.04 | bwd_allreduce_microstep: 0.21 | step_microstep: 0.24 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 851 +[2025-05-15 00:47:37,357] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 175.40 | bwd_microstep: 150.19 | bwd_inner_microstep: 150.03 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-15 00:47:38,396] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 390.04 | bwd_microstep: 630.24 | bwd_inner_microstep: 629.98 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.24 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-15 00:47:39,289] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 356.83 | bwd_microstep: 516.33 | bwd_inner_microstep: 515.32 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.22 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-15 00:47:40,164] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 339.94 | bwd_microstep: 513.89 | bwd_inner_microstep: 513.84 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.27 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-15 00:47:40,923] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 338.41 | bwd_microstep: 400.18 | bwd_inner_microstep: 400.15 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.82 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1342 +[2025-05-15 00:47:41,717] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 310.33 | bwd_microstep: 460.36 | bwd_inner_microstep: 460.31 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.25 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2012 +[2025-05-15 00:47:42,798] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.12 | optimizer_step: 18.12 +[2025-05-15 00:47:42,798] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 370.46 | bwd_microstep: 666.30 | bwd_inner_microstep: 552.12 | bwd_allreduce_microstep: 114.11 | step_microstep: 26.86 +[2025-05-15 00:47:42,799] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2378.94 | bwd: 3474.81 | bwd_inner: 3358.83 | bwd_allreduce: 114.46 | step: 29.99 + 30%|███ | 169/558 [19:38<41:24, 6.39s/it] {'loss': 3.7372, 'grad_norm': 19.34363555908203, 'learning_rate': 8.175472051964552e-16, 'epoch': 0.09} + 30%|███ | 169/558 [19:38<41:24, 6.39s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1893 +[2025-05-15 00:47:43,759] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 352.99 | bwd_microstep: 582.58 | bwd_inner_microstep: 582.54 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.33 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 862 +[2025-05-15 00:47:44,237] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.10 | bwd_microstep: 252.55 | bwd_inner_microstep: 252.51 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.69 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-15 00:47:45,130] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 364.54 | bwd_microstep: 504.46 | bwd_inner_microstep: 504.43 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.24 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-15 00:47:45,914] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 356.07 | bwd_microstep: 405.56 | bwd_inner_microstep: 405.52 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.81 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 860 +[2025-05-15 00:47:46,443] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.30 | bwd_microstep: 315.60 | bwd_inner_microstep: 315.57 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-15 00:47:47,383] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 382.18 | bwd_microstep: 523.08 | bwd_inner_microstep: 523.04 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.27 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-15 00:47:48,269] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 356.45 | bwd_microstep: 507.07 | bwd_inner_microstep: 506.86 | bwd_allreduce_microstep: 0.19 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-15 00:47:49,397] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.01 | optimizer_gradients: 2.12 | optimizer_step: 18.13 +[2025-05-15 00:47:49,398] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 209.82 | bwd_microstep: 872.83 | bwd_inner_microstep: 288.94 | bwd_allreduce_microstep: 583.87 | step_microstep: 27.58 +[2025-05-15 00:47:49,398] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2405.43 | bwd: 3963.73 | bwd_inner: 3379.43 | bwd_allreduce: 584.10 | step: 37.46 + 30%|███ | 170/558 [19:44<41:43, 6.45s/it] {'loss': 4.7705, 'grad_norm': 14.363718032836914, 'learning_rate': 8.152990960838629e-16, 'epoch': 0.09} + 30%|███ | 170/558 [19:44<41:43, 6.45s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1906 +[2025-05-15 00:47:50,225] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 244.85 | bwd_microstep: 554.15 | bwd_inner_microstep: 554.10 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.53 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-15 00:47:51,095] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 428.81 | bwd_microstep: 408.37 | bwd_inner_microstep: 408.12 | bwd_allreduce_microstep: 0.09 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-15 00:47:52,144] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 394.95 | bwd_microstep: 631.14 | bwd_inner_microstep: 631.10 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.48 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-15 00:47:52,944] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 284.90 | bwd_microstep: 492.19 | bwd_inner_microstep: 492.14 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-15 00:47:53,873] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 444.21 | bwd_microstep: 450.81 | bwd_inner_microstep: 450.62 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-15 00:47:54,851] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 343.97 | bwd_microstep: 614.59 | bwd_inner_microstep: 614.54 | bwd_allreduce_microstep: 0.02 | step_microstep: 2.35 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1351 +[2025-05-15 00:47:55,405] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 258.49 | bwd_microstep: 263.89 | bwd_inner_microstep: 263.85 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.70 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-15 00:47:56,637] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.23 | optimizer_step: 17.96 +[2025-05-15 00:47:56,638] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 396.51 | bwd_microstep: 783.79 | bwd_inner_microstep: 604.66 | bwd_allreduce_microstep: 178.16 | step_microstep: 26.78 +[2025-05-15 00:47:56,639] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2796.66 | bwd: 4198.96 | bwd_inner: 4019.26 | bwd_allreduce: 178.36 | step: 38.41 + 31%|███ | 171/558 [19:52<43:08, 6.69s/it] {'loss': 6.2096, 'grad_norm': 35.147666931152344, 'learning_rate': 8.130403546835522e-16, 'epoch': 0.09} + 31%|███ | 171/558 [19:52<43:08, 6.69s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1889 +[2025-05-15 00:47:57,212] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 197.19 | bwd_microstep: 349.65 | bwd_inner_microstep: 349.63 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.79 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1889 +[2025-05-15 00:47:58,241] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 414.07 | bwd_microstep: 588.36 | bwd_inner_microstep: 588.33 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.15 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-15 00:47:59,073] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 222.37 | bwd_microstep: 588.72 | bwd_inner_microstep: 588.67 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.48 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-15 00:47:59,907] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 408.94 | bwd_microstep: 392.70 | bwd_inner_microstep: 392.50 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-15 00:48:00,944] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 392.20 | bwd_microstep: 621.04 | bwd_inner_microstep: 620.81 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-15 00:48:01,738] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 281.90 | bwd_microstep: 489.79 | bwd_inner_microstep: 489.74 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-15 00:48:02,667] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 444.06 | bwd_microstep: 451.12 | bwd_inner_microstep: 450.96 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1985 +[2025-05-15 00:48:03,974] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.16 | optimizer_step: 21.97 +[2025-05-15 00:48:03,975] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 366.68 | bwd_microstep: 891.56 | bwd_inner_microstep: 669.19 | bwd_allreduce_microstep: 222.35 | step_microstep: 31.02 +[2025-05-15 00:48:03,975] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2727.37 | bwd: 4372.96 | bwd_inner: 4149.87 | bwd_allreduce: 222.49 | step: 40.29 + 31%|███ | 172/558 [19:59<44:16, 6.88s/it] {'loss': 4.5955, 'grad_norm': 23.094282150268555, 'learning_rate': 8.107710571631648e-16, 'epoch': 0.09} + 31%|███ | 172/558 [19:59<44:16, 6.88s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-15 00:48:04,876] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 268.79 | bwd_microstep: 602.05 | bwd_inner_microstep: 602.02 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.49 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-15 00:48:05,675] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 380.75 | bwd_microstep: 385.17 | bwd_inner_microstep: 385.14 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.82 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-15 00:48:06,713] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 398.95 | bwd_microstep: 612.38 | bwd_inner_microstep: 612.31 | bwd_allreduce_microstep: 0.02 | step_microstep: 1.07 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-15 00:48:07,502] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 266.16 | bwd_microstep: 499.73 | bwd_inner_microstep: 499.66 | bwd_allreduce_microstep: 0.02 | step_microstep: 2.54 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-15 00:48:08,451] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 431.50 | bwd_microstep: 484.35 | bwd_inner_microstep: 484.19 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-15 00:48:09,366] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 281.74 | bwd_microstep: 612.39 | bwd_inner_microstep: 612.34 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.52 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-15 00:48:10,163] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 379.14 | bwd_microstep: 382.03 | bwd_inner_microstep: 381.99 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.79 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 320 +[2025-05-15 00:48:10,894] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.01 | optimizer_gradients: 1.77 | optimizer_step: 17.27 +[2025-05-15 00:48:10,894] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.51 | bwd_microstep: 584.92 | bwd_inner_microstep: 160.62 | bwd_allreduce_microstep: 424.26 | step_microstep: 25.82 +[2025-05-15 00:48:10,895] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2502.51 | bwd: 4163.01 | bwd_inner: 3738.31 | bwd_allreduce: 424.39 | step: 37.95 + 31%|███ | 173/558 [20:06<44:14, 6.89s/it] {'loss': 6.8903, 'grad_norm': 28.586484909057617, 'learning_rate': 8.084912800463076e-16, 'epoch': 0.09} + 31%|███ | 173/558 [20:06<44:14, 6.89s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1899 +[2025-05-15 00:48:11,724] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 248.81 | bwd_microstep: 551.16 | bwd_inner_microstep: 551.12 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.56 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1883 +[2025-05-15 00:48:12,646] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 432.84 | bwd_microstep: 454.66 | bwd_inner_microstep: 454.36 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-15 00:48:13,522] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 343.94 | bwd_microstep: 511.41 | bwd_inner_microstep: 511.37 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-15 00:48:14,316] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 350.91 | bwd_microstep: 408.80 | bwd_inner_microstep: 408.49 | bwd_allreduce_microstep: 0.19 | step_microstep: 0.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-15 00:48:15,356] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 393.20 | bwd_microstep: 622.45 | bwd_inner_microstep: 622.23 | bwd_allreduce_microstep: 0.18 | step_microstep: 0.17 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-15 00:48:16,143] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 319.15 | bwd_microstep: 449.49 | bwd_inner_microstep: 449.26 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-15 00:48:17,155] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 442.61 | bwd_microstep: 537.17 | bwd_inner_microstep: 537.03 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-15 00:48:18,373] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.09 | optimizer_step: 17.50 +[2025-05-15 00:48:18,374] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 241.52 | bwd_microstep: 929.80 | bwd_inner_microstep: 598.69 | bwd_allreduce_microstep: 331.07 | step_microstep: 26.91 +[2025-05-15 00:48:18,375] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2772.93 | bwd: 4464.96 | bwd_inner: 4132.70 | bwd_allreduce: 331.47 | step: 32.56 + 31%|███ | 174/558 [20:13<45:14, 7.07s/it] {'loss': 5.6975, 'grad_norm': 41.89978790283203, 'learning_rate': 8.062011002099729e-16, 'epoch': 0.09} + 31%|███ | 174/558 [20:13<45:14, 7.07s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1964 +[2025-05-15 00:48:19,267] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 234.66 | bwd_microstep: 628.98 | bwd_inner_microstep: 628.94 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.33 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1951 +[2025-05-15 00:48:20,137] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 419.39 | bwd_microstep: 417.93 | bwd_inner_microstep: 417.67 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.17 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1904 +[2025-05-15 00:48:21,178] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 393.59 | bwd_microstep: 622.99 | bwd_inner_microstep: 622.77 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.44 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 348 +[2025-05-15 00:48:21,402] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.45 | bwd_microstep: 113.18 | bwd_inner_microstep: 113.16 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.23 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-15 00:48:22,104] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 200.88 | bwd_microstep: 479.82 | bwd_inner_microstep: 479.78 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-15 00:48:23,079] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 438.83 | bwd_microstep: 502.04 | bwd_inner_microstep: 501.88 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-15 00:48:23,979] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 270.10 | bwd_microstep: 609.11 | bwd_inner_microstep: 609.07 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.56 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-15 00:48:25,374] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.01 | optimizer_gradients: 2.09 | optimizer_step: 18.13 +[2025-05-15 00:48:25,375] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 383.73 | bwd_microstep: 949.60 | bwd_inner_microstep: 385.72 | bwd_allreduce_microstep: 563.85 | step_microstep: 27.19 +[2025-05-15 00:48:25,375] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2435.59 | bwd: 4323.86 | bwd_inner: 3759.04 | bwd_allreduce: 563.97 | step: 35.31 + 31%|███▏ | 175/558 [20:20<44:59, 7.05s/it] {'loss': 4.055, 'grad_norm': 12.941459655761719, 'learning_rate': 8.039005948819467e-16, 'epoch': 0.09} + 31%|███▏ | 175/558 [20:20<44:59, 7.05s/it]dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1403 +[2025-05-15 00:48:25,955] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 226.26 | bwd_microstep: 326.37 | bwd_inner_microstep: 326.33 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.81 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-15 00:48:26,955] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 410.57 | bwd_microstep: 563.75 | bwd_inner_microstep: 563.51 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.23 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1115 +[2025-05-15 00:48:27,375] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 173.40 | bwd_microstep: 227.05 | bwd_inner_microstep: 227.00 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.79 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-15 00:48:28,397] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 415.33 | bwd_microstep: 581.80 | bwd_inner_microstep: 581.77 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.27 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-15 00:48:29,193] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 274.53 | bwd_microstep: 497.69 | bwd_inner_microstep: 497.66 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.44 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 330 +[2025-05-15 00:48:29,474] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 105.59 | bwd_microstep: 142.48 | bwd_inner_microstep: 142.43 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-15 00:48:30,272] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 379.00 | bwd_microstep: 382.90 | bwd_inner_microstep: 382.87 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.77 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-15 00:48:31,533] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.09 | optimizer_step: 18.20 +[2025-05-15 00:48:31,533] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 400.30 | bwd_microstep: 809.19 | bwd_inner_microstep: 607.50 | bwd_allreduce_microstep: 201.63 | step_microstep: 27.01 +[2025-05-15 00:48:31,534] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2384.95 | bwd: 3531.25 | bwd_inner: 3329.09 | bwd_allreduce: 201.71 | step: 37.67 + 32%|███▏ | 176/558 [20:27<43:10, 6.78s/it] {'loss': 4.2273, 'grad_norm': 16.7602481842041, 'learning_rate': 8.015898416382026e-16, 'epoch': 0.09} + 32%|███▏ | 176/558 [20:27<43:10, 6.78s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-15 00:48:32,480] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 312.54 | bwd_microstep: 608.85 | bwd_inner_microstep: 608.79 | bwd_allreduce_microstep: 0.02 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-15 00:48:33,293] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 362.07 | bwd_microstep: 415.39 | bwd_inner_microstep: 415.36 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.85 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-15 00:48:34,289] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 411.79 | bwd_microstep: 557.32 | bwd_inner_microstep: 556.86 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.26 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-15 00:48:35,124] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 222.58 | bwd_microstep: 590.29 | bwd_inner_microstep: 590.25 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-15 00:48:35,962] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 408.86 | bwd_microstep: 394.07 | bwd_inner_microstep: 393.84 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-15 00:48:36,993] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 387.24 | bwd_microstep: 621.88 | bwd_inner_microstep: 621.67 | bwd_allreduce_microstep: 0.18 | step_microstep: 0.19 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 836 +[2025-05-15 00:48:37,363] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 165.82 | bwd_microstep: 186.21 | bwd_inner_microstep: 186.00 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.15 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-15 00:48:38,616] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.01 | optimizer_gradients: 2.13 | optimizer_step: 18.21 +[2025-05-15 00:48:38,616] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 327.60 | bwd_microstep: 880.17 | bwd_inner_microstep: 611.95 | bwd_allreduce_microstep: 268.20 | step_microstep: 27.18 +[2025-05-15 00:48:38,617] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2598.47 | bwd: 4254.20 | bwd_inner: 3984.78 | bwd_allreduce: 268.72 | step: 34.49 + 32%|███▏ | 177/558 [20:34<43:38, 6.87s/it] {'loss': 6.4287, 'grad_norm': 29.731672286987305, 'learning_rate': 7.99268918400288e-16, 'epoch': 0.1} + 32%|███▏ | 177/558 [20:34<43:38, 6.87s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-15 00:48:39,475] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 231.47 | bwd_microstep: 596.63 | bwd_inner_microstep: 596.59 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.55 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-15 00:48:40,303] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 399.70 | bwd_microstep: 394.23 | bwd_inner_microstep: 394.12 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.22 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 332 +[2025-05-15 00:48:40,553] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.93 | bwd_microstep: 130.55 | bwd_inner_microstep: 130.51 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.33 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 840 +[2025-05-15 00:48:41,099] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 218.73 | bwd_microstep: 296.81 | bwd_inner_microstep: 296.78 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.33 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-15 00:48:41,894] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 357.72 | bwd_microstep: 404.66 | bwd_inner_microstep: 404.63 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.77 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 322 +[2025-05-15 00:48:42,156] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 92.68 | bwd_microstep: 141.89 | bwd_inner_microstep: 141.86 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-15 00:48:43,049] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 432.19 | bwd_microstep: 427.53 | bwd_inner_microstep: 427.37 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.09 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 317 +[2025-05-15 00:48:43,817] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.10 | optimizer_step: 18.22 +[2025-05-15 00:48:43,818] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 86.58 | bwd_microstep: 640.29 | bwd_inner_microstep: 152.17 | bwd_allreduce_microstep: 488.09 | step_microstep: 27.07 +[2025-05-15 00:48:43,819] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 1912.97 | bwd: 3032.60 | bwd_inner: 2544.05 | bwd_allreduce: 488.25 | step: 38.73 + 32%|███▏ | 178/558 [20:39<40:21, 6.37s/it] {'loss': 5.9038, 'grad_norm': 50.09251022338867, 'learning_rate': 7.96937903432695e-16, 'epoch': 0.1} + 32%|███▏ | 178/558 [20:39<40:21, 6.37s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1890 +[2025-05-15 00:48:44,644] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 246.16 | bwd_microstep: 548.45 | bwd_inner_microstep: 548.41 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1903 +[2025-05-15 00:48:45,568] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 430.15 | bwd_microstep: 461.45 | bwd_inner_microstep: 461.29 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1890 +[2025-05-15 00:48:46,548] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 347.72 | bwd_microstep: 611.73 | bwd_inner_microstep: 611.71 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.48 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-15 00:48:47,331] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 351.19 | bwd_microstep: 402.08 | bwd_inner_microstep: 402.05 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.28 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-15 00:48:48,357] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 415.43 | bwd_microstep: 586.22 | bwd_inner_microstep: 586.02 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.18 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 324 +[2025-05-15 00:48:48,609] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.87 | bwd_microstep: 141.70 | bwd_inner_microstep: 141.67 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-15 00:48:49,645] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 390.41 | bwd_microstep: 623.47 | bwd_inner_microstep: 623.25 | bwd_allreduce_microstep: 0.19 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-15 00:48:50,943] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.01 | optimizer_gradients: 2.08 | optimizer_step: 18.49 +[2025-05-15 00:48:50,944] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 321.65 | bwd_microstep: 929.12 | bwd_inner_microstep: 448.53 | bwd_allreduce_microstep: 480.39 | step_microstep: 27.48 +[2025-05-15 00:48:50,944] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2596.56 | bwd: 4304.23 | bwd_inner: 3822.94 | bwd_allreduce: 480.67 | step: 33.10 + 32%|███▏ | 179/558 [20:46<41:40, 6.60s/it] {'loss': 5.3337, 'grad_norm': 22.26325225830078, 'learning_rate': 7.945968753402215e-16, 'epoch': 0.1} + 32%|███▏ | 179/558 [20:46<41:40, 6.60s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1894 +[2025-05-15 00:48:51,771] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 241.44 | bwd_microstep: 556.74 | bwd_inner_microstep: 556.69 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-15 00:48:52,677] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 425.01 | bwd_microstep: 449.19 | bwd_inner_microstep: 449.05 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-15 00:48:53,669] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 351.95 | bwd_microstep: 620.34 | bwd_inner_microstep: 620.29 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.32 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-15 00:48:54,458] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 342.65 | bwd_microstep: 411.51 | bwd_inner_microstep: 411.48 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.95 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-15 00:48:55,364] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 244.32 | bwd_microstep: 635.58 | bwd_inner_microstep: 635.37 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.19 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 333 +[2025-05-15 00:48:55,611] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.22 | bwd_microstep: 134.88 | bwd_inner_microstep: 134.68 | bwd_allreduce_microstep: 0.17 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-15 00:48:56,445] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 224.69 | bwd_microstep: 589.16 | bwd_inner_microstep: 589.11 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.57 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2036 +[2025-05-15 00:48:57,956] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.14 | optimizer_step: 18.55 +[2025-05-15 00:48:57,957] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 431.00 | bwd_microstep: 1019.68 | bwd_inner_microstep: 434.24 | bwd_allreduce_microstep: 585.21 | step_microstep: 27.67 +[2025-05-15 00:48:57,958] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2356.26 | bwd: 4417.10 | bwd_inner: 3830.93 | bwd_allreduce: 585.49 | step: 37.35 + 32%|███▏ | 180/558 [20:53<42:20, 6.72s/it] {'loss': 7.5052, 'grad_norm': 44.179786682128906, 'learning_rate': 7.922459130653212e-16, 'epoch': 0.1} + 32%|███▏ | 180/558 [20:53<42:20, 6.72s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1912 +[2025-05-15 00:48:58,777] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 275.34 | bwd_microstep: 516.55 | bwd_inner_microstep: 516.51 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.59 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1890 +[2025-05-15 00:48:59,804] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 449.12 | bwd_microstep: 540.92 | bwd_inner_microstep: 540.90 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.27 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1888 +[2025-05-15 00:49:00,698] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 362.11 | bwd_microstep: 509.46 | bwd_inner_microstep: 509.23 | bwd_allreduce_microstep: 0.21 | step_microstep: 0.23 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-15 00:49:01,543] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 356.86 | bwd_microstep: 468.50 | bwd_inner_microstep: 468.35 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-15 00:49:02,484] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 309.72 | bwd_microstep: 609.61 | bwd_inner_microstep: 609.54 | bwd_allreduce_microstep: 0.02 | step_microstep: 2.57 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-15 00:49:03,412] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 379.53 | bwd_microstep: 517.28 | bwd_inner_microstep: 517.23 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.47 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-15 00:49:04,196] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 342.79 | bwd_microstep: 419.02 | bwd_inner_microstep: 418.96 | bwd_allreduce_microstep: 0.02 | step_microstep: 1.82 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-15 00:49:05,466] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 1.68 | optimizer_step: 15.33 +[2025-05-15 00:49:05,467] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 433.18 | bwd_microstep: 790.21 | bwd_inner_microstep: 581.47 | bwd_allreduce_microstep: 208.71 | step_microstep: 23.73 +[2025-05-15 00:49:05,468] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2908.62 | bwd: 4371.58 | bwd_inner: 4162.25 | bwd_allreduce: 209.05 | step: 33.78 + 32%|███▏ | 181/558 [21:00<43:43, 6.96s/it] {'loss': 2.7532, 'grad_norm': 4.244930744171143, 'learning_rate': 7.898850958854411e-16, 'epoch': 0.1} + 32%|███▏ | 181/558 [21:01<43:43, 6.96s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 339 +[2025-05-15 00:49:05,718] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.37 | bwd_microstep: 129.10 | bwd_inner_microstep: 129.08 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.26 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1892 +[2025-05-15 00:49:06,598] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 340.04 | bwd_microstep: 518.25 | bwd_inner_microstep: 518.19 | bwd_allreduce_microstep: 0.02 | step_microstep: 2.32 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 854 +[2025-05-15 00:49:07,023] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 181.23 | bwd_microstep: 222.45 | bwd_inner_microstep: 222.29 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-15 00:49:07,930] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 280.97 | bwd_microstep: 605.48 | bwd_inner_microstep: 605.44 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.57 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 851 +[2025-05-15 00:49:08,422] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 207.82 | bwd_microstep: 251.40 | bwd_inner_microstep: 250.45 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-15 00:49:09,298] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 353.51 | bwd_microstep: 501.39 | bwd_inner_microstep: 501.14 | bwd_allreduce_microstep: 0.21 | step_microstep: 0.22 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-15 00:49:10,135] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 222.85 | bwd_microstep: 592.16 | bwd_inner_microstep: 592.12 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-15 00:49:11,339] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.01 | optimizer_gradients: 2.06 | optimizer_step: 17.93 +[2025-05-15 00:49:11,339] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 430.70 | bwd_microstep: 712.74 | bwd_inner_microstep: 501.78 | bwd_allreduce_microstep: 210.77 | step_microstep: 26.48 +[2025-05-15 00:49:11,340] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2110.47 | bwd: 3532.99 | bwd_inner: 3320.51 | bwd_allreduce: 211.10 | step: 36.52 + 33%|███▎ | 182/558 [21:06<41:33, 6.63s/it] {'loss': 4.6743, 'grad_norm': 13.205988883972168, 'learning_rate': 7.875145034103479e-16, 'epoch': 0.1} + 33%|███▎ | 182/558 [21:06<41:33, 6.63s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1944 +[2025-05-15 00:49:12,171] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 339.67 | bwd_microstep: 463.02 | bwd_inner_microstep: 462.78 | bwd_allreduce_microstep: 0.20 | step_microstep: 2.35 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1363 +[2025-05-15 00:49:12,984] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 331.69 | bwd_microstep: 449.03 | bwd_inner_microstep: 448.85 | bwd_allreduce_microstep: 0.17 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-15 00:49:13,861] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 359.28 | bwd_microstep: 498.67 | bwd_inner_microstep: 498.42 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.27 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 839 +[2025-05-15 00:49:14,191] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 166.30 | bwd_microstep: 145.58 | bwd_inner_microstep: 145.33 | bwd_allreduce_microstep: 0.10 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-15 00:49:15,216] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 357.32 | bwd_microstep: 646.75 | bwd_inner_microstep: 646.70 | bwd_allreduce_microstep: 0.02 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-15 00:49:16,115] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 351.29 | bwd_microstep: 516.99 | bwd_inner_microstep: 516.55 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.26 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-15 00:49:16,901] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 318.97 | bwd_microstep: 446.90 | bwd_inner_microstep: 446.83 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-15 00:49:18,170] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.01 | optimizer_gradients: 2.11 | optimizer_step: 18.53 +[2025-05-15 00:49:18,170] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 442.09 | bwd_microstep: 769.11 | bwd_inner_microstep: 564.51 | bwd_allreduce_microstep: 204.57 | step_microstep: 27.32 +[2025-05-15 00:49:18,171] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2666.60 | bwd: 3936.09 | bwd_inner: 3729.88 | bwd_allreduce: 205.51 | step: 32.95 + 33%|███▎ | 183/558 [21:13<41:49, 6.69s/it] {'loss': 7.2857, 'grad_norm': 34.05772399902344, 'learning_rate': 7.851342155794435e-16, 'epoch': 0.1} + 33%|███▎ | 183/558 [21:13<41:49, 6.69s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1887 +[2025-05-15 00:49:18,976] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 348.79 | bwd_microstep: 426.91 | bwd_inner_microstep: 426.87 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.81 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-15 00:49:20,003] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 436.28 | bwd_microstep: 565.04 | bwd_inner_microstep: 564.99 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.26 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1891 +[2025-05-15 00:49:20,888] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 356.16 | bwd_microstep: 509.00 | bwd_inner_microstep: 508.00 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-15 00:49:21,686] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 277.58 | bwd_microstep: 497.34 | bwd_inner_microstep: 497.29 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.56 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-15 00:49:22,653] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 441.76 | bwd_microstep: 490.19 | bwd_inner_microstep: 489.98 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 842 +[2025-05-15 00:49:23,038] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 101.82 | bwd_microstep: 265.68 | bwd_inner_microstep: 265.63 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.76 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-15 00:49:24,012] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 435.31 | bwd_microstep: 515.07 | bwd_inner_microstep: 514.92 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-15 00:49:25,258] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.01 | optimizer_gradients: 2.89 | optimizer_step: 18.58 +[2025-05-15 00:49:25,259] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 297.67 | bwd_microstep: 902.45 | bwd_inner_microstep: 607.87 | bwd_allreduce_microstep: 294.55 | step_microstep: 28.71 +[2025-05-15 00:49:25,259] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2695.35 | bwd: 4171.69 | bwd_inner: 3876.59 | bwd_allreduce: 294.72 | step: 35.50 + 33%|███▎ | 184/558 [21:20<42:27, 6.81s/it] {'loss': 4.3171, 'grad_norm': 20.15789031982422, 'learning_rate': 7.827443126590701e-16, 'epoch': 0.1} + 33%|███▎ | 184/558 [21:20<42:27, 6.81s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1893 +[2025-05-15 00:49:26,154] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 353.61 | bwd_microstep: 513.43 | bwd_inner_microstep: 513.23 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.18 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 353 +[2025-05-15 00:49:26,417] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 99.28 | bwd_microstep: 146.86 | bwd_inner_microstep: 146.72 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1097 +[2025-05-15 00:49:26,952] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 174.23 | bwd_microstep: 341.22 | bwd_inner_microstep: 341.17 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-15 00:49:27,946] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 436.43 | bwd_microstep: 523.25 | bwd_inner_microstep: 523.04 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-15 00:49:28,836] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 360.47 | bwd_microstep: 510.39 | bwd_inner_microstep: 509.62 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.23 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 323 +[2025-05-15 00:49:29,083] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 86.88 | bwd_microstep: 139.49 | bwd_inner_microstep: 139.46 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.78 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-15 00:49:30,100] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 410.83 | bwd_microstep: 580.60 | bwd_inner_microstep: 580.37 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.21 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-15 00:49:31,391] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.11 | optimizer_step: 18.20 +[2025-05-15 00:49:31,391] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 278.59 | bwd_microstep: 964.30 | bwd_inner_microstep: 506.72 | bwd_allreduce_microstep: 457.54 | step_microstep: 26.98 +[2025-05-15 00:49:31,392] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2200.31 | bwd: 3719.71 | bwd_inner: 3260.35 | bwd_allreduce: 458.54 | step: 32.01 + 33%|███▎ | 185/558 [21:26<41:04, 6.61s/it] {'loss': 5.6587, 'grad_norm': 28.435171127319336, 'learning_rate': 7.80344875239803e-16, 'epoch': 0.1} + 33%|███▎ | 185/558 [21:26<41:04, 6.61s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-15 00:49:32,291] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 352.26 | bwd_microstep: 520.15 | bwd_inner_microstep: 520.10 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.01 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-15 00:49:33,091] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 332.65 | bwd_microstep: 444.43 | bwd_inner_microstep: 444.37 | bwd_allreduce_microstep: 0.02 | step_microstep: 1.98 +dynamic ViT batch size: 6, images per sample: 6.0, dynamic token length: 1612 +[2025-05-15 00:49:33,998] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 388.69 | bwd_microstep: 486.39 | bwd_inner_microstep: 486.06 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-15 00:49:34,877] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 254.63 | bwd_microstep: 604.01 | bwd_inner_microstep: 603.95 | bwd_allreduce_microstep: 0.02 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-15 00:49:35,641] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 339.67 | bwd_microstep: 389.99 | bwd_inner_microstep: 389.69 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-15 00:49:36,643] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 359.99 | bwd_microstep: 621.20 | bwd_inner_microstep: 621.13 | bwd_allreduce_microstep: 0.02 | step_microstep: 2.37 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-15 00:49:37,410] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 341.21 | bwd_microstep: 393.98 | bwd_inner_microstep: 393.73 | bwd_allreduce_microstep: 0.21 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1952 +[2025-05-15 00:49:38,683] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.07 | optimizer_gradients: 3.04 | optimizer_step: 17.94 +[2025-05-15 00:49:38,684] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 413.99 | bwd_microstep: 809.87 | bwd_inner_microstep: 645.86 | bwd_allreduce_microstep: 163.96 | step_microstep: 27.36 +[2025-05-15 00:49:38,685] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2783.06 | bwd: 4270.08 | bwd_inner: 4105.01 | bwd_allreduce: 164.51 | step: 35.54 + 33%|███▎ | 186/558 [21:34<42:14, 6.81s/it] {'loss': 7.2282, 'grad_norm': 25.976219177246094, 'learning_rate': 7.779359842337322e-16, 'epoch': 0.1} + 33%|███▎ | 186/558 [21:34<42:14, 6.81s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 516 +[2025-05-15 00:49:38,979] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.04 | bwd_microstep: 178.75 | bwd_inner_microstep: 178.71 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.79 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 855 +[2025-05-15 00:49:39,516] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.09 | bwd_microstep: 315.52 | bwd_inner_microstep: 315.47 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 334 +[2025-05-15 00:49:39,775] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 97.13 | bwd_microstep: 131.31 | bwd_inner_microstep: 131.11 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.18 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 837 +[2025-05-15 00:49:40,077] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 149.38 | bwd_microstep: 135.35 | bwd_inner_microstep: 135.14 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.21 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-15 00:49:41,105] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 394.68 | bwd_microstep: 612.12 | bwd_inner_microstep: 611.92 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.18 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 329 +[2025-05-15 00:49:41,353] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 96.32 | bwd_microstep: 134.53 | bwd_inner_microstep: 134.31 | bwd_allreduce_microstep: 0.08 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-15 00:49:42,307] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 322.62 | bwd_microstep: 610.84 | bwd_inner_microstep: 610.78 | bwd_allreduce_microstep: 0.02 | step_microstep: 2.55 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 915 +[2025-05-15 00:49:43,184] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 1.70 | optimizer_step: 15.07 +[2025-05-15 00:49:43,186] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 203.64 | bwd_microstep: 619.48 | bwd_inner_microstep: 191.17 | bwd_allreduce_microstep: 428.26 | step_microstep: 23.97 +[2025-05-15 00:49:43,187] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 1551.88 | bwd: 2738.08 | bwd_inner: 2308.69 | bwd_allreduce: 428.36 | step: 31.38 + 34%|███▎ | 187/558 [21:38<37:50, 6.12s/it] {'loss': 5.0928, 'grad_norm': 35.43357849121094, 'learning_rate': 7.755177208717357e-16, 'epoch': 0.1} + 34%|███▎ | 187/558 [21:38<37:50, 6.12s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1959 +[2025-05-15 00:49:43,980] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 299.36 | bwd_microstep: 451.08 | bwd_inner_microstep: 451.05 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.82 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1893 +[2025-05-15 00:49:44,996] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 412.89 | bwd_microstep: 577.53 | bwd_inner_microstep: 577.22 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.96 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 345 +[2025-05-15 00:49:45,240] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 84.03 | bwd_microstep: 139.20 | bwd_inner_microstep: 139.16 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.82 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1361 +[2025-05-15 00:49:46,048] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 292.18 | bwd_microstep: 488.41 | bwd_inner_microstep: 488.37 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.42 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-15 00:49:46,853] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 326.23 | bwd_microstep: 448.04 | bwd_inner_microstep: 447.84 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.18 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1355 +[2025-05-15 00:49:47,647] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 333.07 | bwd_microstep: 432.23 | bwd_inner_microstep: 431.97 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.92 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-15 00:49:48,475] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 220.49 | bwd_microstep: 585.46 | bwd_inner_microstep: 585.43 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-15 00:49:49,670] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.01 | optimizer_gradients: 2.12 | optimizer_step: 18.29 +[2025-05-15 00:49:49,670] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 429.11 | bwd_microstep: 704.93 | bwd_inner_microstep: 503.70 | bwd_allreduce_microstep: 201.19 | step_microstep: 27.46 +[2025-05-15 00:49:49,671] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2397.34 | bwd: 3827.05 | bwd_inner: 3624.73 | bwd_allreduce: 201.25 | step: 37.93 + 34%|███▎ | 188/558 [21:45<38:24, 6.23s/it] {'loss': 5.3622, 'grad_norm': 20.35755157470703, 'learning_rate': 7.730901667007384e-16, 'epoch': 0.1} + 34%|███▎ | 188/558 [21:45<38:24, 6.23s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1895 +[2025-05-15 00:49:50,459] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 343.93 | bwd_microstep: 416.03 | bwd_inner_microstep: 416.01 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.82 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-15 00:49:51,477] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 408.12 | bwd_microstep: 581.92 | bwd_inner_microstep: 581.89 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.27 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 850 +[2025-05-15 00:49:51,725] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.97 | bwd_microstep: 134.23 | bwd_inner_microstep: 134.04 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-15 00:49:52,529] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 198.64 | bwd_microstep: 588.00 | bwd_inner_microstep: 587.96 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.29 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-15 00:49:53,368] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 422.09 | bwd_microstep: 383.44 | bwd_inner_microstep: 383.40 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.80 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-15 00:49:54,403] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 400.93 | bwd_microstep: 608.93 | bwd_inner_microstep: 608.87 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.23 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 323 +[2025-05-15 00:49:54,631] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 82.26 | bwd_microstep: 125.37 | bwd_inner_microstep: 125.30 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-15 00:49:55,849] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.08 | optimizer_step: 17.71 +[2025-05-15 00:49:55,850] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 394.87 | bwd_microstep: 774.11 | bwd_inner_microstep: 619.95 | bwd_allreduce_microstep: 154.10 | step_microstep: 26.29 +[2025-05-15 00:49:55,850] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2344.78 | bwd: 3612.07 | bwd_inner: 3457.46 | bwd_allreduce: 154.25 | step: 35.01 + 34%|███▍ | 189/558 [21:51<38:12, 6.21s/it] {'loss': 6.2643, 'grad_norm': 36.194122314453125, 'learning_rate': 7.70653403580964e-16, 'epoch': 0.1} + 34%|███▍ | 189/558 [21:51<38:12, 6.21s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1919 +[2025-05-15 00:49:56,857] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 351.58 | bwd_microstep: 629.35 | bwd_inner_microstep: 629.31 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.51 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1887 +[2025-05-15 00:49:57,674] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 298.47 | bwd_microstep: 483.56 | bwd_inner_microstep: 483.53 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.57 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-15 00:49:58,586] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 444.34 | bwd_microstep: 435.35 | bwd_inner_microstep: 435.19 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.11 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 339 +[2025-05-15 00:49:58,842] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 96.25 | bwd_microstep: 142.72 | bwd_inner_microstep: 142.67 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.83 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-15 00:49:59,804] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 443.11 | bwd_microstep: 489.65 | bwd_inner_microstep: 489.42 | bwd_allreduce_microstep: 0.08 | step_microstep: 0.09 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1095 +[2025-05-15 00:50:00,096] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 115.76 | bwd_microstep: 162.08 | bwd_inner_microstep: 161.95 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-15 00:50:01,083] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 355.34 | bwd_microstep: 612.91 | bwd_inner_microstep: 611.17 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-15 00:50:02,016] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.01 | optimizer_gradients: 1.71 | optimizer_step: 17.36 +[2025-05-15 00:50:02,017] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 353.42 | bwd_microstep: 520.85 | bwd_inner_microstep: 458.32 | bwd_allreduce_microstep: 62.38 | step_microstep: 24.72 +[2025-05-15 00:50:02,017] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2458.23 | bwd: 3476.51 | bwd_inner: 3411.71 | bwd_allreduce: 62.57 | step: 34.26 + 34%|███▍ | 190/558 [21:57<38:01, 6.20s/it] {'loss': 6.4275, 'grad_norm': 22.78108787536621, 'learning_rate': 7.68207513683173e-16, 'epoch': 0.1} + 34%|███▍ | 190/558 [21:57<38:01, 6.20s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1892 +[2025-05-15 00:50:03,063] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 403.14 | bwd_microstep: 607.99 | bwd_inner_microstep: 607.96 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.30 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1898 +[2025-05-15 00:50:03,834] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 355.26 | bwd_microstep: 396.07 | bwd_inner_microstep: 396.04 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.81 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1883 +[2025-05-15 00:50:04,880] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 401.98 | bwd_microstep: 617.84 | bwd_inner_microstep: 614.52 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-15 00:50:05,667] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 351.96 | bwd_microstep: 412.78 | bwd_inner_microstep: 412.75 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.86 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-15 00:50:06,699] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 410.25 | bwd_microstep: 594.68 | bwd_inner_microstep: 594.64 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.22 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 838 +[2025-05-15 00:50:07,046] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 163.30 | bwd_microstep: 163.80 | bwd_inner_microstep: 163.50 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1342 +[2025-05-15 00:50:07,774] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 251.29 | bwd_microstep: 456.50 | bwd_inner_microstep: 456.44 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.54 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1504 +[2025-05-15 00:50:08,590] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 1.68 | optimizer_gradients: 2.08 | optimizer_step: 18.11 +[2025-05-15 00:50:08,593] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 331.71 | bwd_microstep: 422.90 | bwd_inner_microstep: 357.47 | bwd_allreduce_microstep: 65.29 | step_microstep: 30.15 +[2025-05-15 00:50:08,593] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2668.88 | bwd: 3672.58 | bwd_inner: 3603.45 | bwd_allreduce: 65.47 | step: 37.17 + 34%|███▍ | 191/558 [22:04<38:36, 6.31s/it] {'loss': 5.527, 'grad_norm': 21.429006576538086, 'learning_rate': 7.657525794858926e-16, 'epoch': 0.1} + 34%|███▍ | 191/558 [22:04<38:36, 6.31s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1920 +[2025-05-15 00:50:09,653] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 407.99 | bwd_microstep: 619.18 | bwd_inner_microstep: 619.15 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.27 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1892 +[2025-05-15 00:50:10,436] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 354.54 | bwd_microstep: 404.58 | bwd_inner_microstep: 404.53 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.84 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-15 00:50:11,469] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 418.38 | bwd_microstep: 588.26 | bwd_inner_microstep: 587.97 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.25 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-15 00:50:12,308] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 355.98 | bwd_microstep: 462.21 | bwd_inner_microstep: 462.02 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-15 00:50:13,254] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 314.07 | bwd_microstep: 611.28 | bwd_inner_microstep: 611.23 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-15 00:50:14,061] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 375.51 | bwd_microstep: 395.19 | bwd_inner_microstep: 395.16 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.84 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-15 00:50:15,077] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 408.02 | bwd_microstep: 582.18 | bwd_inner_microstep: 582.12 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.25 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-15 00:50:16,430] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.12 | optimizer_step: 18.03 +[2025-05-15 00:50:16,431] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 352.19 | bwd_microstep: 953.68 | bwd_inner_microstep: 421.63 | bwd_allreduce_microstep: 531.91 | step_microstep: 27.29 +[2025-05-15 00:50:16,431] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2986.67 | bwd: 4616.56 | bwd_inner: 4083.94 | bwd_allreduce: 532.00 | step: 36.15 + 34%|███▍ | 192/558 [22:11<41:17, 6.77s/it] {'loss': 5.8492, 'grad_norm': 37.17806625366211, 'learning_rate': 7.632886837726358e-16, 'epoch': 0.1} + 34%|███▍ | 192/558 [22:11<41:17, 6.77s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 379 +[2025-05-15 00:50:16,699] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 100.09 | bwd_microstep: 143.03 | bwd_inner_microstep: 142.71 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.17 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-15 00:50:17,570] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 249.16 | bwd_microstep: 599.81 | bwd_inner_microstep: 599.78 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 847 +[2025-05-15 00:50:18,054] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 207.48 | bwd_microstep: 243.40 | bwd_inner_microstep: 242.96 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.27 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 844 +[2025-05-15 00:50:18,394] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 173.67 | bwd_microstep: 150.49 | bwd_inner_microstep: 150.28 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-15 00:50:19,436] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 391.72 | bwd_microstep: 623.96 | bwd_inner_microstep: 623.92 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.32 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-15 00:50:20,245] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 361.33 | bwd_microstep: 426.58 | bwd_inner_microstep: 426.44 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-15 00:50:21,237] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 349.70 | bwd_microstep: 621.83 | bwd_inner_microstep: 621.76 | bwd_allreduce_microstep: 0.02 | step_microstep: 2.30 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 2025 +[2025-05-15 00:50:22,662] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.00 | optimizer_step: 15.39 +[2025-05-15 00:50:22,663] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 353.66 | bwd_microstep: 1015.95 | bwd_inner_microstep: 432.53 | bwd_allreduce_microstep: 583.36 | step_microstep: 24.42 +[2025-05-15 00:50:22,664] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2186.79 | bwd: 3825.10 | bwd_inner: 3240.47 | bwd_allreduce: 583.79 | step: 32.09 + 35%|███▍ | 193/558 [22:18<40:12, 6.61s/it] {'loss': 5.2229, 'grad_norm': 29.299610137939453, 'learning_rate': 7.60815909629109e-16, 'epoch': 0.1} + 35%|███▍ | 193/558 [22:18<40:12, 6.61s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1886 +[2025-05-15 00:50:23,486] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 236.82 | bwd_microstep: 557.47 | bwd_inner_microstep: 557.43 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-15 00:50:24,455] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 440.44 | bwd_microstep: 496.08 | bwd_inner_microstep: 495.92 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-15 00:50:25,355] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 275.38 | bwd_microstep: 604.12 | bwd_inner_microstep: 604.08 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-15 00:50:26,178] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 390.75 | bwd_microstep: 398.28 | bwd_inner_microstep: 398.21 | bwd_allreduce_microstep: 0.02 | step_microstep: 1.97 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-15 00:50:27,220] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 399.60 | bwd_microstep: 612.60 | bwd_inner_microstep: 612.52 | bwd_allreduce_microstep: 0.02 | step_microstep: 2.33 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-15 00:50:28,054] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 255.41 | bwd_microstep: 553.62 | bwd_inner_microstep: 553.54 | bwd_allreduce_microstep: 0.02 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-15 00:50:29,043] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 437.09 | bwd_microstep: 520.33 | bwd_inner_microstep: 520.29 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.23 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 832 +[2025-05-15 00:50:29,690] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.11 | optimizer_step: 17.94 +[2025-05-15 00:50:29,690] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 170.81 | bwd_microstep: 430.87 | bwd_inner_microstep: 240.81 | bwd_allreduce_microstep: 189.83 | step_microstep: 26.57 +[2025-05-15 00:50:29,691] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2606.28 | bwd: 4173.39 | bwd_inner: 3982.86 | bwd_allreduce: 189.99 | step: 38.28 + 35%|███▍ | 194/558 [22:25<40:51, 6.73s/it] {'loss': 5.0898, 'grad_norm': 30.976104736328125, 'learning_rate': 7.583343404404104e-16, 'epoch': 0.1} + 35%|███▍ | 194/558 [22:25<40:51, 6.73s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-15 00:50:30,659] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 325.40 | bwd_microstep: 616.30 | bwd_inner_microstep: 616.26 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-15 00:50:31,471] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 370.02 | bwd_microstep: 408.37 | bwd_inner_microstep: 408.33 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.83 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-15 00:50:32,499] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 410.69 | bwd_microstep: 590.49 | bwd_inner_microstep: 590.47 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.31 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 332 +[2025-05-15 00:50:32,771] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 88.57 | bwd_microstep: 162.50 | bwd_inner_microstep: 162.46 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.82 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-15 00:50:33,800] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 415.06 | bwd_microstep: 589.46 | bwd_inner_microstep: 589.21 | bwd_allreduce_microstep: 0.23 | step_microstep: 0.27 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 328 +[2025-05-15 00:50:34,015] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 91.00 | bwd_microstep: 107.71 | bwd_inner_microstep: 107.57 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.09 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1351 +[2025-05-15 00:50:34,727] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 250.70 | bwd_microstep: 444.48 | bwd_inner_microstep: 444.46 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.32 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-15 00:50:36,159] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 1.67 | optimizer_step: 13.06 +[2025-05-15 00:50:36,159] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 401.95 | bwd_microstep: 978.82 | bwd_inner_microstep: 383.77 | bwd_allreduce_microstep: 595.03 | step_microstep: 20.19 +[2025-05-15 00:50:36,160] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2353.36 | bwd: 3898.12 | bwd_inner: 3302.55 | bwd_allreduce: 595.35 | step: 31.20 + 35%|███▍ | 195/558 [22:31<40:15, 6.65s/it] {'loss': 5.4618, 'grad_norm': 22.48573112487793, 'learning_rate': 7.558440598882185e-16, 'epoch': 0.1} + 35%|███▍ | 195/558 [22:31<40:15, 6.65s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1895 +[2025-05-15 00:50:36,981] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 248.40 | bwd_microstep: 548.33 | bwd_inner_microstep: 548.31 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.43 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-15 00:50:37,874] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 423.45 | bwd_microstep: 437.33 | bwd_inner_microstep: 437.05 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1122 +[2025-05-15 00:50:38,425] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 192.32 | bwd_microstep: 342.52 | bwd_inner_microstep: 342.50 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-15 00:50:39,332] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 419.95 | bwd_microstep: 454.89 | bwd_inner_microstep: 454.75 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-15 00:50:40,288] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 335.10 | bwd_microstep: 603.56 | bwd_inner_microstep: 603.54 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-15 00:50:41,073] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 344.78 | bwd_microstep: 407.95 | bwd_inner_microstep: 407.93 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.78 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1099 +[2025-05-15 00:50:41,716] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 243.55 | bwd_microstep: 374.82 | bwd_inner_microstep: 374.80 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-15 00:50:43,062] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 1.68 | optimizer_step: 13.19 +[2025-05-15 00:50:43,063] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 344.16 | bwd_microstep: 949.34 | bwd_inner_microstep: 406.73 | bwd_allreduce_microstep: 542.60 | step_microstep: 20.69 +[2025-05-15 00:50:43,063] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2551.67 | bwd: 4118.76 | bwd_inner: 3575.70 | bwd_allreduce: 542.79 | step: 32.11 + 35%|███▌ | 196/558 [22:38<40:35, 6.73s/it] {'loss': 3.9644, 'grad_norm': 16.347129821777344, 'learning_rate': 7.533451519479704e-16, 'epoch': 0.11} + 35%|███▌ | 196/558 [22:38<40:35, 6.73s/it]dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1397 +[2025-05-15 00:50:43,638] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 178.55 | bwd_microstep: 373.85 | bwd_inner_microstep: 373.59 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1916 +[2025-05-15 00:50:44,637] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 439.81 | bwd_microstep: 524.09 | bwd_inner_microstep: 523.75 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.21 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1891 +[2025-05-15 00:50:45,528] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 267.83 | bwd_microstep: 601.62 | bwd_inner_microstep: 601.60 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.33 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1886 +[2025-05-15 00:50:46,342] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 383.13 | bwd_microstep: 394.40 | bwd_inner_microstep: 394.38 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.88 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-15 00:50:47,360] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 397.13 | bwd_microstep: 595.59 | bwd_inner_microstep: 595.40 | bwd_allreduce_microstep: 0.18 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-15 00:50:48,156] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 279.83 | bwd_microstep: 496.28 | bwd_inner_microstep: 496.27 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-15 00:50:49,100] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 440.13 | bwd_microstep: 471.63 | bwd_inner_microstep: 471.32 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-15 00:50:50,330] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 1.67 | optimizer_step: 13.32 +[2025-05-15 00:50:50,330] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 303.33 | bwd_microstep: 889.05 | bwd_inner_microstep: 596.07 | bwd_allreduce_microstep: 292.97 | step_microstep: 20.25 +[2025-05-15 00:50:50,331] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2689.69 | bwd: 4346.62 | bwd_inner: 4052.51 | bwd_allreduce: 293.45 | step: 27.58 + 35%|███▌ | 197/558 [22:45<41:27, 6.89s/it] {'loss': 2.9116, 'grad_norm': 12.680492401123047, 'learning_rate': 7.508377008860293e-16, 'epoch': 0.11} + 35%|███▌ | 197/558 [22:45<41:27, 6.89s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1903 +[2025-05-15 00:50:51,207] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 254.92 | bwd_microstep: 594.61 | bwd_inner_microstep: 594.59 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.32 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-15 00:50:52,014] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 381.66 | bwd_microstep: 391.48 | bwd_inner_microstep: 391.46 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.82 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-15 00:50:53,040] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 394.64 | bwd_microstep: 603.28 | bwd_inner_microstep: 603.26 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.27 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-15 00:50:53,837] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 285.06 | bwd_microstep: 488.95 | bwd_inner_microstep: 488.93 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-15 00:50:54,785] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 439.55 | bwd_microstep: 476.92 | bwd_inner_microstep: 476.60 | bwd_allreduce_microstep: 0.14 | step_microstep: 0.09 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 839 +[2025-05-15 00:50:55,152] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 99.22 | bwd_microstep: 250.87 | bwd_inner_microstep: 250.85 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.89 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-15 00:50:56,134] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 401.06 | bwd_microstep: 554.00 | bwd_inner_microstep: 553.98 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.30 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-15 00:50:57,362] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 1.67 | optimizer_step: 13.09 +[2025-05-15 00:50:57,363] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 223.27 | bwd_microstep: 963.22 | bwd_inner_microstep: 582.36 | bwd_allreduce_microstep: 380.84 | step_microstep: 20.71 +[2025-05-15 00:50:57,363] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2479.35 | bwd: 4323.34 | bwd_inner: 3942.11 | bwd_allreduce: 381.02 | step: 33.76 + 35%|███▌ | 198/558 [22:52<41:35, 6.93s/it] {'loss': 4.2121, 'grad_norm': 18.058595657348633, 'learning_rate': 7.483217912568436e-16, 'epoch': 0.11} + 35%|███▌ | 198/558 [22:52<41:35, 6.93s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1901 +[2025-05-15 00:50:58,205] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 227.74 | bwd_microstep: 589.68 | bwd_inner_microstep: 589.66 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-15 00:50:59,025] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 397.62 | bwd_microstep: 392.03 | bwd_inner_microstep: 391.83 | bwd_allreduce_microstep: 0.18 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-15 00:51:00,041] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 392.47 | bwd_microstep: 601.83 | bwd_inner_microstep: 601.44 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.24 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-15 00:51:00,826] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 315.25 | bwd_microstep: 449.91 | bwd_inner_microstep: 447.55 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.52 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 844 +[2025-05-15 00:51:01,390] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 219.22 | bwd_microstep: 312.24 | bwd_inner_microstep: 312.22 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-15 00:51:02,180] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 353.79 | bwd_microstep: 416.40 | bwd_inner_microstep: 416.38 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.92 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-15 00:51:03,181] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 431.01 | bwd_microstep: 542.23 | bwd_inner_microstep: 542.21 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.22 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-15 00:51:04,489] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 1.70 | optimizer_step: 13.13 +[2025-05-15 00:51:04,490] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 340.86 | bwd_microstep: 929.92 | bwd_inner_microstep: 421.14 | bwd_allreduce_microstep: 508.76 | step_microstep: 20.16 +[2025-05-15 00:51:04,491] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2677.95 | bwd: 4234.23 | bwd_inner: 3722.44 | bwd_allreduce: 511.50 | step: 29.92 + 36%|███▌ | 199/558 [23:00<41:49, 6.99s/it] {'loss': 4.166, 'grad_norm': 18.508100509643555, 'learning_rate': 7.457975079000954e-16, 'epoch': 0.11} + 36%|███▌ | 199/558 [23:00<41:49, 6.99s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1890 +[2025-05-15 00:51:05,309] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 254.19 | bwd_microstep: 539.91 | bwd_inner_microstep: 539.87 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1113 +[2025-05-15 00:51:05,925] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 269.70 | bwd_microstep: 317.38 | bwd_inner_microstep: 317.36 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.31 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-15 00:51:06,762] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 227.49 | bwd_microstep: 590.03 | bwd_inner_microstep: 590.01 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 849 +[2025-05-15 00:51:07,267] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 222.64 | bwd_microstep: 252.63 | bwd_inner_microstep: 252.61 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.30 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-15 00:51:08,037] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 349.98 | bwd_microstep: 401.54 | bwd_inner_microstep: 399.78 | bwd_allreduce_microstep: 1.74 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-15 00:51:09,081] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 394.40 | bwd_microstep: 626.58 | bwd_inner_microstep: 626.55 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.31 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-15 00:51:09,873] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 354.00 | bwd_microstep: 418.32 | bwd_inner_microstep: 418.14 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-15 00:51:11,141] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 1.62 | optimizer_step: 13.07 +[2025-05-15 00:51:11,141] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 355.66 | bwd_microstep: 876.69 | bwd_inner_microstep: 631.29 | bwd_allreduce_microstep: 245.38 | step_microstep: 20.31 +[2025-05-15 00:51:11,142] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2428.05 | bwd: 4023.07 | bwd_inner: 3775.68 | bwd_allreduce: 247.21 | step: 30.20 + 36%|███▌ | 200/558 [23:06<41:06, 6.89s/it] {'loss': 4.0209, 'grad_norm': 21.40829086303711, 'learning_rate': 7.432649359378393e-16, 'epoch': 0.11} + 36%|███▌ | 200/558 [23:06<41:06, 6.89s/it][INFO|trainer.py:3503] 2025-05-15 00:51:14,117 >> Saving model checkpoint to work_dirs/internvl_chat_v2_5/mmvet/checkpoint-200 +[INFO|configuration_utils.py:472] 2025-05-15 00:51:14,120 >> Configuration saved in work_dirs/internvl_chat_v2_5/mmvet/checkpoint-200/config.json +[INFO|configuration_utils.py:807] 2025-05-15 00:51:14,120 >> Configuration saved in work_dirs/internvl_chat_v2_5/mmvet/checkpoint-200/generation_config.json +[INFO|modeling_utils.py:2755] 2025-05-15 00:51:22,413 >> Model weights saved in work_dirs/internvl_chat_v2_5/mmvet/checkpoint-200/model.safetensors +[INFO|tokenization_utils_base.py:2702] 2025-05-15 00:51:22,415 >> tokenizer config file saved in work_dirs/internvl_chat_v2_5/mmvet/checkpoint-200/tokenizer_config.json +[INFO|tokenization_utils_base.py:2711] 2025-05-15 00:51:22,415 >> Special tokens file saved in work_dirs/internvl_chat_v2_5/mmvet/checkpoint-200/special_tokens_map.json +[INFO|tokenization_utils_base.py:2762] 2025-05-15 00:51:22,415 >> added tokens file saved in work_dirs/internvl_chat_v2_5/mmvet/checkpoint-200/added_tokens.json +[2025-05-15 00:51:22,527] [INFO] [logging.py:96:log_dist] [Rank 0] [Torch] Checkpoint global_step200 is about to be saved! +[2025-05-15 00:51:22,553] [INFO] [logging.py:96:log_dist] [Rank 0] Saving model checkpoint: work_dirs/internvl_chat_v2_5/mmvet/checkpoint-200/global_step200/mp_rank_00_model_states.pt +[2025-05-15 00:51:22,553] [INFO] [torch_checkpoint_engine.py:21:save] [Torch] Saving work_dirs/internvl_chat_v2_5/mmvet/checkpoint-200/global_step200/mp_rank_00_model_states.pt... +[2025-05-15 00:51:30,544] [INFO] [torch_checkpoint_engine.py:23:save] [Torch] Saved work_dirs/internvl_chat_v2_5/mmvet/checkpoint-200/global_step200/mp_rank_00_model_states.pt. +[2025-05-15 00:51:30,546] [INFO] [torch_checkpoint_engine.py:21:save] [Torch] Saving work_dirs/internvl_chat_v2_5/mmvet/checkpoint-200/global_step200/bf16_zero_pp_rank_0_mp_rank_00_optim_states.pt... +[2025-05-15 00:51:30,818] [INFO] [torch_checkpoint_engine.py:23:save] [Torch] Saved work_dirs/internvl_chat_v2_5/mmvet/checkpoint-200/global_step200/bf16_zero_pp_rank_0_mp_rank_00_optim_states.pt. +[2025-05-15 00:51:30,819] [INFO] [engine.py:3536:_save_zero_checkpoint] zero checkpoint saved work_dirs/internvl_chat_v2_5/mmvet/checkpoint-200/global_step200/bf16_zero_pp_rank_0_mp_rank_00_optim_states.pt +[2025-05-15 00:51:30,819] [INFO] [torch_checkpoint_engine.py:33:commit] [Torch] Checkpoint global_step200 is ready now! +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1905 +[2025-05-15 00:51:31,668] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 233.23 | bwd_microstep: 590.81 | bwd_inner_microstep: 590.79 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.51 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-15 00:51:32,502] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 398.16 | bwd_microstep: 401.39 | bwd_inner_microstep: 401.33 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-15 00:51:33,560] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 391.59 | bwd_microstep: 619.58 | bwd_inner_microstep: 619.56 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.27 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-15 00:51:34,348] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 292.02 | bwd_microstep: 473.11 | bwd_inner_microstep: 473.09 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.42 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-15 00:51:35,370] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 431.71 | bwd_microstep: 556.71 | bwd_inner_microstep: 556.69 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.30 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-15 00:51:36,176] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 349.41 | bwd_microstep: 434.08 | bwd_inner_microstep: 433.79 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-15 00:51:37,134] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 340.21 | bwd_microstep: 600.42 | bwd_inner_microstep: 600.40 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.47 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-15 00:51:38,064] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 1.68 | optimizer_step: 14.75 +[2025-05-15 00:51:38,066] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 370.08 | bwd_microstep: 507.66 | bwd_inner_microstep: 450.07 | bwd_allreduce_microstep: 57.46 | step_microstep: 22.90 +[2025-05-15 00:51:38,067] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2806.35 | bwd: 4183.81 | bwd_inner: 4125.86 | bwd_allreduce: 57.64 | step: 35.14 + 36%|███▌ | 201/558 [23:33<1:16:45, 12.90s/it] {'loss': 3.8262, 'grad_norm': 14.148545265197754, 'learning_rate': 7.407241607716327e-16, 'epoch': 0.11} + 36%|███▌ | 201/558 [23:33<1:16:45, 12.90s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1962 +[2025-05-15 00:51:39,148] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 415.01 | bwd_microstep: 631.06 | bwd_inner_microstep: 631.05 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.43 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 870 +[2025-05-15 00:51:39,488] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 172.25 | bwd_microstep: 150.06 | bwd_inner_microstep: 149.68 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.17 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-15 00:51:40,507] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 387.45 | bwd_microstep: 609.41 | bwd_inner_microstep: 609.23 | bwd_allreduce_microstep: 0.17 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-15 00:51:41,321] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 246.30 | bwd_microstep: 547.23 | bwd_inner_microstep: 547.21 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.32 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-15 00:51:42,282] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 418.90 | bwd_microstep: 508.46 | bwd_inner_microstep: 508.27 | bwd_allreduce_microstep: 0.17 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-15 00:51:43,142] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 249.42 | bwd_microstep: 589.81 | bwd_inner_microstep: 589.79 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.33 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1096 +[2025-05-15 00:51:43,672] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 250.65 | bwd_microstep: 249.54 | bwd_inner_microstep: 249.23 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1351 +[2025-05-15 00:51:44,800] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 1.69 | optimizer_step: 13.47 +[2025-05-15 00:51:44,801] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 200.49 | bwd_microstep: 893.43 | bwd_inner_microstep: 440.45 | bwd_allreduce_microstep: 452.97 | step_microstep: 20.32 +[2025-05-15 00:51:44,801] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2340.43 | bwd: 4179.03 | bwd_inner: 3725.18 | bwd_allreduce: 453.62 | step: 27.90 + 36%|███▌ | 202/558 [23:40<1:05:33, 11.05s/it] {'loss': 5.3362, 'grad_norm': 20.191728591918945, 'learning_rate': 7.381752680796548e-16, 'epoch': 0.11} + 36%|███▌ | 202/558 [23:40<1:05:33, 11.05s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-15 00:51:45,660] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 344.56 | bwd_microstep: 490.25 | bwd_inner_microstep: 490.10 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-15 00:51:46,547] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 273.92 | bwd_microstep: 592.83 | bwd_inner_microstep: 592.81 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-15 00:51:47,476] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 396.49 | bwd_microstep: 500.61 | bwd_inner_microstep: 500.60 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-15 00:51:48,227] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 347.19 | bwd_microstep: 384.17 | bwd_inner_microstep: 384.15 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.85 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 330 +[2025-05-15 00:51:48,467] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 91.15 | bwd_microstep: 125.54 | bwd_inner_microstep: 125.52 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.31 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-15 00:51:49,472] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 433.43 | bwd_microstep: 541.33 | bwd_inner_microstep: 541.13 | bwd_allreduce_microstep: 0.18 | step_microstep: 0.17 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-15 00:51:50,250] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 315.38 | bwd_microstep: 444.16 | bwd_inner_microstep: 443.96 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-15 00:51:51,524] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 1.66 | optimizer_step: 13.01 +[2025-05-15 00:51:51,524] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 435.82 | bwd_microstep: 787.79 | bwd_inner_microstep: 556.78 | bwd_allreduce_microstep: 231.00 | step_microstep: 20.30 +[2025-05-15 00:51:51,525] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2637.92 | bwd: 3866.69 | bwd_inner: 3635.09 | bwd_allreduce: 231.26 | step: 27.26 + 36%|███▋ | 203/558 [23:47<57:42, 9.75s/it] {'loss': 6.5849, 'grad_norm': 22.028812408447266, 'learning_rate': 7.35618343813819e-16, 'epoch': 0.11} + 36%|███▋ | 203/558 [23:47<57:42, 9.75s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1949 +[2025-05-15 00:51:52,365] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 282.46 | bwd_microstep: 532.61 | bwd_inner_microstep: 532.59 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.51 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1887 +[2025-05-15 00:51:53,358] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 438.78 | bwd_microstep: 524.30 | bwd_inner_microstep: 524.08 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.22 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 853 +[2025-05-15 00:51:53,696] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 170.54 | bwd_microstep: 150.34 | bwd_inner_microstep: 150.08 | bwd_allreduce_microstep: 0.22 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-15 00:51:54,741] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 386.92 | bwd_microstep: 634.42 | bwd_inner_microstep: 634.40 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 6, images per sample: 6.0, dynamic token length: 1615 +[2025-05-15 00:51:55,484] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 318.06 | bwd_microstep: 404.22 | bwd_inner_microstep: 404.08 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-15 00:51:56,431] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 325.45 | bwd_microstep: 602.66 | bwd_inner_microstep: 602.64 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.38 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-15 00:51:57,328] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 359.27 | bwd_microstep: 505.27 | bwd_inner_microstep: 505.09 | bwd_allreduce_microstep: 0.17 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-15 00:51:58,638] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 1.66 | optimizer_step: 13.13 +[2025-05-15 00:51:58,639] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 314.86 | bwd_microstep: 958.11 | bwd_inner_microstep: 442.44 | bwd_allreduce_microstep: 515.48 | step_microstep: 21.02 +[2025-05-15 00:51:58,640] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2596.33 | bwd: 4311.95 | bwd_inner: 3795.45 | bwd_allreduce: 515.91 | step: 28.93 + 37%|███▋ | 204/558 [23:54<52:52, 8.96s/it] {'loss': 7.4984, 'grad_norm': 24.441356658935547, 'learning_rate': 7.330534741968729e-16, 'epoch': 0.11} + 37%|███▋ | 204/558 [23:54<52:52, 8.96s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1899 +[2025-05-15 00:51:59,412] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 356.45 | bwd_microstep: 392.17 | bwd_inner_microstep: 391.98 | bwd_allreduce_microstep: 0.18 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-15 00:52:00,454] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 394.41 | bwd_microstep: 623.14 | bwd_inner_microstep: 623.12 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.30 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-15 00:52:01,245] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 281.37 | bwd_microstep: 487.00 | bwd_inner_microstep: 486.98 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-15 00:52:02,232] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 437.68 | bwd_microstep: 517.08 | bwd_inner_microstep: 517.06 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.24 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-15 00:52:03,086] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 344.17 | bwd_microstep: 491.41 | bwd_inner_microstep: 491.07 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.21 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-15 00:52:03,969] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 273.51 | bwd_microstep: 590.32 | bwd_inner_microstep: 590.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.37 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-15 00:52:04,796] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 382.56 | bwd_microstep: 410.08 | bwd_inner_microstep: 410.06 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.82 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-15 00:52:05,845] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 1.69 | optimizer_step: 18.59 +[2025-05-15 00:52:05,845] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 402.37 | bwd_microstep: 596.67 | bwd_inner_microstep: 537.22 | bwd_allreduce_microstep: 59.34 | step_microstep: 25.46 +[2025-05-15 00:52:05,846] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2872.51 | bwd: 4107.93 | bwd_inner: 4047.93 | bwd_allreduce: 59.68 | step: 34.94 + 37%|███▋ | 205/558 [24:01<49:37, 8.43s/it] {'loss': 4.4676, 'grad_norm': 15.451330184936523, 'learning_rate': 7.304807457194919e-16, 'epoch': 0.11} + 37%|███▋ | 205/558 [24:01<49:37, 8.43s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1893 +[2025-05-15 00:52:06,883] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 390.63 | bwd_microstep: 622.38 | bwd_inner_microstep: 622.36 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.02 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-15 00:52:07,695] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 246.49 | bwd_microstep: 545.56 | bwd_inner_microstep: 545.54 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.33 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-15 00:52:08,559] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 420.80 | bwd_microstep: 410.87 | bwd_inner_microstep: 410.66 | bwd_allreduce_microstep: 0.19 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-15 00:52:09,587] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 394.52 | bwd_microstep: 612.61 | bwd_inner_microstep: 612.42 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.17 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-15 00:52:10,383] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 281.17 | bwd_microstep: 494.34 | bwd_inner_microstep: 494.32 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 846 +[2025-05-15 00:52:10,924] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 218.33 | bwd_microstep: 290.19 | bwd_inner_microstep: 290.17 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.27 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-15 00:52:11,694] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 298.68 | bwd_microstep: 450.55 | bwd_inner_microstep: 450.53 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.51 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-15 00:52:12,732] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 1.67 | optimizer_step: 18.39 +[2025-05-15 00:52:12,733] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 436.69 | bwd_microstep: 543.43 | bwd_inner_microstep: 485.97 | bwd_allreduce_microstep: 57.35 | step_microstep: 27.37 +[2025-05-15 00:52:12,734] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2687.31 | bwd: 3970.10 | bwd_inner: 3912.03 | bwd_allreduce: 57.56 | step: 39.20 + 37%|███▋ | 206/558 [24:08<46:45, 7.97s/it] {'loss': 4.5981, 'grad_norm': 12.456034660339355, 'learning_rate': 7.27900245137362e-16, 'epoch': 0.11} + 37%|███▋ | 206/558 [24:08<46:45, 7.97s/it]dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1410 +[2025-05-15 00:52:13,549] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 295.50 | bwd_microstep: 483.93 | bwd_inner_microstep: 483.91 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1883 +[2025-05-15 00:52:14,348] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 325.46 | bwd_microstep: 443.58 | bwd_inner_microstep: 443.32 | bwd_allreduce_microstep: 0.23 | step_microstep: 0.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-15 00:52:15,307] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 434.29 | bwd_microstep: 493.88 | bwd_inner_microstep: 493.56 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-15 00:52:16,221] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 305.65 | bwd_microstep: 590.44 | bwd_inner_microstep: 590.42 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-15 00:52:17,033] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 362.87 | bwd_microstep: 417.64 | bwd_inner_microstep: 417.62 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.92 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-15 00:52:18,032] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 403.58 | bwd_microstep: 567.02 | bwd_inner_microstep: 566.84 | bwd_allreduce_microstep: 0.17 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-15 00:52:18,857] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 224.78 | bwd_microstep: 580.15 | bwd_inner_microstep: 580.13 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-15 00:52:20,306] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 1.68 | optimizer_step: 13.20 +[2025-05-15 00:52:20,307] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 398.27 | bwd_microstep: 1000.70 | bwd_inner_microstep: 408.92 | bwd_allreduce_microstep: 591.58 | step_microstep: 21.37 +[2025-05-15 00:52:20,307] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2750.39 | bwd: 4577.40 | bwd_inner: 3984.79 | bwd_allreduce: 592.08 | step: 30.87 + 37%|███▋ | 207/558 [24:15<45:55, 7.85s/it] {'loss': 5.9371, 'grad_norm': 17.86151885986328, 'learning_rate': 7.253120594682547e-16, 'epoch': 0.11} + 37%|███▋ | 207/558 [24:15<45:55, 7.85s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-15 00:52:21,145] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 228.70 | bwd_microstep: 581.77 | bwd_inner_microstep: 581.75 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.30 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-15 00:52:21,968] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 399.77 | bwd_microstep: 391.09 | bwd_inner_microstep: 391.07 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-15 00:52:22,985] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 389.21 | bwd_microstep: 599.70 | bwd_inner_microstep: 599.47 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.43 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-15 00:52:23,784] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 277.87 | bwd_microstep: 501.11 | bwd_inner_microstep: 501.09 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.33 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 839 +[2025-05-15 00:52:24,300] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 213.72 | bwd_microstep: 272.30 | bwd_inner_microstep: 272.28 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.33 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-15 00:52:25,172] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 348.53 | bwd_microstep: 503.81 | bwd_inner_microstep: 503.79 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.31 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-15 00:52:25,984] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 232.01 | bwd_microstep: 557.61 | bwd_inner_microstep: 557.59 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.33 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 321 +[2025-05-15 00:52:26,541] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 1.68 | optimizer_step: 13.44 +[2025-05-15 00:52:26,542] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 100.06 | bwd_microstep: 405.79 | bwd_inner_microstep: 140.40 | bwd_allreduce_microstep: 265.38 | step_microstep: 20.59 +[2025-05-15 00:52:26,542] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2189.86 | bwd: 3813.17 | bwd_inner: 3547.45 | bwd_allreduce: 265.41 | step: 31.72 + 37%|███▋ | 208/558 [24:22<42:58, 7.37s/it] {'loss': 5.0695, 'grad_norm': 29.669710159301758, 'learning_rate': 7.227162759890919e-16, 'epoch': 0.11} + 37%|███▋ | 208/558 [24:22<42:58, 7.37s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1927 +[2025-05-15 00:52:27,392] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 282.91 | bwd_microstep: 541.69 | bwd_inner_microstep: 541.67 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.28 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1921 +[2025-05-15 00:52:28,402] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 438.66 | bwd_microstep: 538.67 | bwd_inner_microstep: 538.46 | bwd_allreduce_microstep: 0.19 | step_microstep: 0.23 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 866 +[2025-05-15 00:52:28,730] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 115.22 | bwd_microstep: 194.83 | bwd_inner_microstep: 194.81 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.77 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1896 +[2025-05-15 00:52:29,757] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 416.07 | bwd_microstep: 582.67 | bwd_inner_microstep: 582.65 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.30 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1889 +[2025-05-15 00:52:30,568] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 251.30 | bwd_microstep: 534.96 | bwd_inner_microstep: 534.94 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.50 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-15 00:52:31,475] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 420.17 | bwd_microstep: 456.74 | bwd_inner_microstep: 456.56 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-15 00:52:32,433] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 337.42 | bwd_microstep: 603.12 | bwd_inner_microstep: 603.10 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2027 +[2025-05-15 00:52:33,837] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 1.73 | optimizer_step: 20.96 +[2025-05-15 00:52:33,837] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 374.40 | bwd_microstep: 971.43 | bwd_inner_microstep: 466.17 | bwd_allreduce_microstep: 505.21 | step_microstep: 27.92 +[2025-05-15 00:52:33,838] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2636.14 | bwd: 4424.14 | bwd_inner: 3918.45 | bwd_allreduce: 505.50 | step: 39.44 + 37%|███▋ | 209/558 [24:29<42:43, 7.34s/it] {'loss': 3.1087, 'grad_norm': 13.118513107299805, 'learning_rate': 7.20112982233004e-16, 'epoch': 0.11} + 37%|███▋ | 209/558 [24:29<42:43, 7.34s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1894 +[2025-05-15 00:52:34,752] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 288.12 | bwd_microstep: 603.54 | bwd_inner_microstep: 603.52 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1913 +[2025-05-15 00:52:35,592] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 371.15 | bwd_microstep: 435.90 | bwd_inner_microstep: 435.88 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.94 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1889 +[2025-05-15 00:52:36,593] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 435.81 | bwd_microstep: 541.65 | bwd_inner_microstep: 541.63 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.30 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1888 +[2025-05-15 00:52:37,447] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 237.33 | bwd_microstep: 592.76 | bwd_inner_microstep: 592.74 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-15 00:52:38,278] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 392.53 | bwd_microstep: 407.07 | bwd_inner_microstep: 407.05 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.93 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-15 00:52:39,276] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 397.47 | bwd_microstep: 574.55 | bwd_inner_microstep: 574.36 | bwd_allreduce_microstep: 0.18 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-15 00:52:40,072] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 244.39 | bwd_microstep: 531.59 | bwd_inner_microstep: 531.57 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.33 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1087 +[2025-05-15 00:52:40,818] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 1.69 | optimizer_step: 15.00 +[2025-05-15 00:52:40,818] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 264.27 | bwd_microstep: 430.21 | bwd_inner_microstep: 320.27 | bwd_allreduce_microstep: 109.70 | step_microstep: 21.70 +[2025-05-15 00:52:40,819] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2631.05 | bwd: 4117.29 | bwd_inner: 4007.04 | bwd_allreduce: 109.92 | step: 35.08 + 38%|███▊ | 210/558 [24:36<41:58, 7.24s/it] {'loss': 3.9617, 'grad_norm': 17.933809280395508, 'learning_rate': 7.175022659863774e-16, 'epoch': 0.11} + 38%|███▊ | 210/558 [24:36<41:58, 7.24s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2020 +[2025-05-15 00:52:41,863] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 369.59 | bwd_microstep: 653.33 | bwd_inner_microstep: 653.12 | bwd_allreduce_microstep: 0.19 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1942 +[2025-05-15 00:52:42,716] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 287.64 | bwd_microstep: 545.83 | bwd_inner_microstep: 545.81 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-15 00:52:43,565] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 422.93 | bwd_microstep: 393.27 | bwd_inner_microstep: 393.01 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-15 00:52:44,579] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 388.35 | bwd_microstep: 598.57 | bwd_inner_microstep: 598.32 | bwd_allreduce_microstep: 0.24 | step_microstep: 0.03 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 841 +[2025-05-15 00:52:44,950] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 171.05 | bwd_microstep: 182.02 | bwd_inner_microstep: 181.79 | bwd_allreduce_microstep: 0.08 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-15 00:52:45,908] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 337.69 | bwd_microstep: 601.19 | bwd_inner_microstep: 601.18 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.45 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-15 00:52:46,692] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 346.06 | bwd_microstep: 404.32 | bwd_inner_microstep: 404.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.78 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-15 00:52:47,776] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 1.66 | optimizer_step: 13.04 +[2025-05-15 00:52:47,776] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 395.33 | bwd_microstep: 646.62 | bwd_inner_microstep: 570.89 | bwd_allreduce_microstep: 75.68 | step_microstep: 19.78 +[2025-05-15 00:52:47,777] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2718.61 | bwd: 4025.65 | bwd_inner: 3948.50 | bwd_allreduce: 76.20 | step: 27.96 + 38%|███▊ | 211/558 [24:43<41:21, 7.15s/it] {'loss': 5.7621, 'grad_norm': 23.93307113647461, 'learning_rate': 7.148842152858938e-16, 'epoch': 0.11} + 38%|███▊ | 211/558 [24:43<41:21, 7.15s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 341 +[2025-05-15 00:52:48,013] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 84.13 | bwd_microstep: 131.83 | bwd_inner_microstep: 131.81 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.81 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1900 +[2025-05-15 00:52:49,020] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 412.67 | bwd_microstep: 567.02 | bwd_inner_microstep: 567.00 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.31 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1890 +[2025-05-15 00:52:49,852] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 223.54 | bwd_microstep: 584.71 | bwd_inner_microstep: 584.69 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-15 00:52:50,693] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 401.95 | bwd_microstep: 403.33 | bwd_inner_microstep: 403.31 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.89 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-15 00:52:51,698] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 403.50 | bwd_microstep: 575.64 | bwd_inner_microstep: 575.61 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.30 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-15 00:52:52,487] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 267.60 | bwd_microstep: 501.00 | bwd_inner_microstep: 500.98 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.32 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-15 00:52:53,463] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 431.72 | bwd_microstep: 511.95 | bwd_inner_microstep: 511.76 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.17 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1349 +[2025-05-15 00:52:54,544] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 1.67 | optimizer_step: 13.83 +[2025-05-15 00:52:54,546] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 163.14 | bwd_microstep: 879.86 | bwd_inner_microstep: 381.96 | bwd_allreduce_microstep: 497.88 | step_microstep: 22.09 +[2025-05-15 00:52:54,546] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2388.23 | bwd: 4155.33 | bwd_inner: 3657.13 | bwd_allreduce: 497.92 | step: 33.23 + 38%|███▊ | 212/558 [24:50<40:35, 7.04s/it] {'loss': 4.699, 'grad_norm': 18.200551986694336, 'learning_rate': 7.122589184155626e-16, 'epoch': 0.11} + 38%|███▊ | 212/558 [24:50<40:35, 7.04s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1892 +[2025-05-15 00:52:55,351] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 277.18 | bwd_microstep: 501.32 | bwd_inner_microstep: 501.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.32 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1900 +[2025-05-15 00:52:56,331] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 437.28 | bwd_microstep: 510.57 | bwd_inner_microstep: 510.56 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.17 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 361 +[2025-05-15 00:52:56,594] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.76 | bwd_microstep: 149.86 | bwd_inner_microstep: 149.84 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.72 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1886 +[2025-05-15 00:52:57,613] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 410.17 | bwd_microstep: 577.11 | bwd_inner_microstep: 577.09 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.27 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-15 00:52:58,401] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 353.97 | bwd_microstep: 410.54 | bwd_inner_microstep: 410.52 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.83 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-15 00:52:59,394] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 407.26 | bwd_microstep: 558.06 | bwd_inner_microstep: 558.04 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.29 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-15 00:53:00,173] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 316.79 | bwd_microstep: 440.87 | bwd_inner_microstep: 440.81 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.23 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2354 +[2025-05-15 00:53:01,513] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 1.82 | optimizer_step: 15.24 +[2025-05-15 00:53:01,513] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 499.40 | bwd_microstep: 790.12 | bwd_inner_microstep: 644.70 | bwd_allreduce_microstep: 145.38 | step_microstep: 22.11 +[2025-05-15 00:53:01,514] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2796.81 | bwd: 3938.65 | bwd_inner: 3792.87 | bwd_allreduce: 145.45 | step: 32.95 + 38%|███▊ | 213/558 [24:57<40:20, 7.02s/it] {'loss': 4.3142, 'grad_norm': 35.062557220458984, 'learning_rate': 7.096264639037431e-16, 'epoch': 0.11} + 38%|███▊ | 213/558 [24:57<40:20, 7.02s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1890 +[2025-05-15 00:53:02,484] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 340.31 | bwd_microstep: 607.72 | bwd_inner_microstep: 607.70 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.51 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 880 +[2025-05-15 00:53:02,951] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 182.92 | bwd_microstep: 253.92 | bwd_inner_microstep: 253.57 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.17 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-15 00:53:03,739] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 279.19 | bwd_microstep: 490.32 | bwd_inner_microstep: 490.30 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-15 00:53:04,724] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 435.45 | bwd_microstep: 516.32 | bwd_inner_microstep: 516.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.30 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1096 +[2025-05-15 00:53:05,184] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 207.44 | bwd_microstep: 231.82 | bwd_inner_microstep: 231.57 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.09 +dynamic ViT batch size: 6, images per sample: 6.0, dynamic token length: 1608 +[2025-05-15 00:53:06,025] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 289.74 | bwd_microstep: 533.15 | bwd_inner_microstep: 533.13 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.30 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-15 00:53:06,880] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 369.63 | bwd_microstep: 452.89 | bwd_inner_microstep: 452.71 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-15 00:53:08,119] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 1.67 | optimizer_step: 13.41 +[2025-05-15 00:53:08,120] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 331.78 | bwd_microstep: 872.33 | bwd_inner_microstep: 598.22 | bwd_allreduce_microstep: 274.09 | step_microstep: 20.73 +[2025-05-15 00:53:08,120] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2436.41 | bwd: 3958.50 | bwd_inner: 3683.64 | bwd_allreduce: 274.26 | step: 30.56 + 38%|███▊ | 214/558 [25:03<39:31, 6.89s/it] {'loss': 8.9868, 'grad_norm': 27.104211807250977, 'learning_rate': 7.069869405201596e-16, 'epoch': 0.12} + 38%|███▊ | 214/558 [25:03<39:31, 6.89s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1977 +[2025-05-15 00:53:08,953] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 313.76 | bwd_microstep: 494.36 | bwd_inner_microstep: 494.34 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1883 +[2025-05-15 00:53:09,939] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 435.57 | bwd_microstep: 519.67 | bwd_inner_microstep: 519.39 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.94 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1891 +[2025-05-15 00:53:10,739] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 278.53 | bwd_microstep: 501.34 | bwd_inner_microstep: 501.32 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.54 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 861 +[2025-05-15 00:53:11,292] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 225.74 | bwd_microstep: 296.56 | bwd_inner_microstep: 296.54 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.32 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-15 00:53:12,061] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 349.90 | bwd_microstep: 397.21 | bwd_inner_microstep: 396.99 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-15 00:53:13,084] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 387.31 | bwd_microstep: 614.57 | bwd_inner_microstep: 614.18 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.17 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-15 00:53:13,856] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 354.53 | bwd_microstep: 397.22 | bwd_inner_microstep: 397.18 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.79 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-15 00:53:15,126] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 1.70 | optimizer_step: 13.22 +[2025-05-15 00:53:15,126] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 397.83 | bwd_microstep: 826.96 | bwd_inner_microstep: 595.72 | bwd_allreduce_microstep: 231.23 | step_microstep: 20.90 +[2025-05-15 00:53:15,127] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2743.15 | bwd: 4047.89 | bwd_inner: 3815.67 | bwd_allreduce: 231.64 | step: 31.17 + 39%|███▊ | 215/558 [25:10<39:36, 6.93s/it] {'loss': 4.9505, 'grad_norm': 38.35084533691406, 'learning_rate': 7.043404372729072e-16, 'epoch': 0.12} + 39%|███▊ | 215/558 [25:10<39:36, 6.93s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 383 +[2025-05-15 00:53:15,358] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 73.16 | bwd_microstep: 134.20 | bwd_inner_microstep: 134.18 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.73 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-15 00:53:16,360] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 396.22 | bwd_microstep: 579.89 | bwd_inner_microstep: 579.44 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.22 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-15 00:53:17,119] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 350.28 | bwd_microstep: 390.93 | bwd_inner_microstep: 390.57 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-15 00:53:18,138] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 390.69 | bwd_microstep: 607.46 | bwd_inner_microstep: 607.27 | bwd_allreduce_microstep: 0.18 | step_microstep: 0.17 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-15 00:53:18,899] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 351.76 | bwd_microstep: 391.27 | bwd_inner_microstep: 391.08 | bwd_allreduce_microstep: 0.18 | step_microstep: 0.23 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 328 +[2025-05-15 00:53:19,140] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 92.82 | bwd_microstep: 125.64 | bwd_inner_microstep: 125.62 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.75 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-15 00:53:20,145] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 431.78 | bwd_microstep: 542.59 | bwd_inner_microstep: 542.39 | bwd_allreduce_microstep: 0.18 | step_microstep: 0.17 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-15 00:53:21,471] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.01 | optimizer_gradients: 1.80 | optimizer_step: 19.57 +[2025-05-15 00:53:21,472] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 315.84 | bwd_microstep: 963.58 | bwd_inner_microstep: 447.39 | bwd_allreduce_microstep: 516.16 | step_microstep: 29.62 +[2025-05-15 00:53:21,473] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2402.53 | bwd: 3735.57 | bwd_inner: 3217.95 | bwd_allreduce: 516.55 | step: 34.07 + 39%|███▊ | 216/558 [25:17<38:29, 6.75s/it] {'loss': 4.9019, 'grad_norm': 27.044048309326172, 'learning_rate': 7.016870434054517e-16, 'epoch': 0.12} + 39%|███▊ | 216/558 [25:17<38:29, 6.75s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1930 +[2025-05-15 00:53:22,281] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 361.06 | bwd_microstep: 419.58 | bwd_inner_microstep: 419.50 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.66 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1895 +[2025-05-15 00:53:23,328] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 397.27 | bwd_microstep: 621.85 | bwd_inner_microstep: 621.66 | bwd_allreduce_microstep: 0.19 | step_microstep: 0.17 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-15 00:53:24,208] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 352.17 | bwd_microstep: 509.31 | bwd_inner_microstep: 509.29 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.33 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-15 00:53:24,989] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 344.98 | bwd_microstep: 416.95 | bwd_inner_microstep: 416.91 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.81 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-15 00:53:25,992] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 440.81 | bwd_microstep: 536.70 | bwd_inner_microstep: 536.67 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.21 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-15 00:53:26,781] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 354.68 | bwd_microstep: 411.53 | bwd_inner_microstep: 411.51 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.83 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-15 00:53:27,794] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 412.92 | bwd_microstep: 574.14 | bwd_inner_microstep: 574.09 | bwd_allreduce_microstep: 0.02 | step_microstep: 1.01 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1936 +[2025-05-15 00:53:28,918] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 1.65 | optimizer_step: 17.26 +[2025-05-15 00:53:28,919] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 352.58 | bwd_microstep: 727.30 | bwd_inner_microstep: 546.05 | bwd_allreduce_microstep: 181.19 | step_microstep: 24.41 +[2025-05-15 00:53:28,920] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 3016.47 | bwd: 4217.38 | bwd_inner: 4035.68 | bwd_allreduce: 181.45 | step: 30.45 + 39%|███▉ | 217/558 [25:24<39:33, 6.96s/it] {'loss': 4.2346, 'grad_norm': 22.390724182128906, 'learning_rate': 6.990268483936189e-16, 'epoch': 0.12} + 39%|███▉ | 217/558 [25:24<39:33, 6.96s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1912 +[2025-05-15 00:53:29,905] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 342.02 | bwd_microstep: 616.68 | bwd_inner_microstep: 616.65 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1903 +[2025-05-15 00:53:30,751] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 350.54 | bwd_microstep: 463.39 | bwd_inner_microstep: 463.18 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.11 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 851 +[2025-05-15 00:53:31,163] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 104.27 | bwd_microstep: 291.16 | bwd_inner_microstep: 291.10 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.24 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-15 00:53:32,184] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 433.22 | bwd_microstep: 554.84 | bwd_inner_microstep: 554.80 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.32 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 329 +[2025-05-15 00:53:32,435] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.93 | bwd_microstep: 137.13 | bwd_inner_microstep: 136.93 | bwd_allreduce_microstep: 0.17 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-15 00:53:33,213] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 356.41 | bwd_microstep: 400.52 | bwd_inner_microstep: 400.46 | bwd_allreduce_microstep: 0.02 | step_microstep: 1.80 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 842 +[2025-05-15 00:53:33,735] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.14 | bwd_microstep: 309.04 | bwd_inner_microstep: 309.00 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.48 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 330 +[2025-05-15 00:53:34,244] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 1.59 | optimizer_step: 16.29 +[2025-05-15 00:53:34,245] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 100.23 | bwd_microstep: 355.42 | bwd_inner_microstep: 149.96 | bwd_allreduce_microstep: 205.20 | step_microstep: 24.35 +[2025-05-15 00:53:34,245] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 1967.72 | bwd: 3128.20 | bwd_inner: 2922.14 | bwd_allreduce: 205.49 | step: 33.60 + 39%|███▉ | 218/558 [25:29<36:40, 6.47s/it] {'loss': 4.6176, 'grad_norm': 31.395326614379883, 'learning_rate': 6.963599419425777e-16, 'epoch': 0.12} + 39%|███▉ | 218/558 [25:29<36:40, 6.47s/it]dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1373 +[2025-05-15 00:53:34,934] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 263.68 | bwd_microstep: 394.79 | bwd_inner_microstep: 394.74 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.26 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-15 00:53:35,777] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 233.04 | bwd_microstep: 588.56 | bwd_inner_microstep: 588.52 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1369 +[2025-05-15 00:53:36,524] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 319.89 | bwd_microstep: 395.00 | bwd_inner_microstep: 394.78 | bwd_allreduce_microstep: 0.18 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-15 00:53:37,394] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 356.77 | bwd_microstep: 493.89 | bwd_inner_microstep: 493.67 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.09 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 847 +[2025-05-15 00:53:37,765] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 96.31 | bwd_microstep: 254.43 | bwd_inner_microstep: 254.41 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.33 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-15 00:53:38,769] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 409.18 | bwd_microstep: 572.91 | bwd_inner_microstep: 572.52 | bwd_allreduce_microstep: 0.19 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-15 00:53:39,653] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 354.97 | bwd_microstep: 507.66 | bwd_inner_microstep: 507.64 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.26 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-15 00:53:40,911] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.01 | optimizer_gradients: 2.14 | optimizer_step: 18.01 +[2025-05-15 00:53:40,912] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 237.40 | bwd_microstep: 973.89 | bwd_inner_microstep: 552.07 | bwd_allreduce_microstep: 421.78 | step_microstep: 27.18 +[2025-05-15 00:53:40,912] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2271.23 | bwd: 4181.12 | bwd_inner: 3758.40 | bwd_allreduce: 422.23 | step: 33.86 + 39%|███▉ | 219/558 [25:36<36:53, 6.53s/it] {'loss': 7.2693, 'grad_norm': 44.81270217895508, 'learning_rate': 6.936864139838159e-16, 'epoch': 0.12} + 39%|███▉ | 219/558 [25:36<36:53, 6.53s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 355 +[2025-05-15 00:53:41,187] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 97.73 | bwd_microstep: 151.17 | bwd_inner_microstep: 151.14 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-15 00:53:41,951] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 344.00 | bwd_microstep: 399.19 | bwd_inner_microstep: 398.92 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.50 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1361 +[2025-05-15 00:53:42,747] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 283.57 | bwd_microstep: 489.84 | bwd_inner_microstep: 489.79 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.28 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 844 +[2025-05-15 00:53:43,228] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 200.24 | bwd_microstep: 248.24 | bwd_inner_microstep: 248.20 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.38 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 337 +[2025-05-15 00:53:43,475] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.86 | bwd_microstep: 131.84 | bwd_inner_microstep: 131.64 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.23 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-15 00:53:44,242] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 353.41 | bwd_microstep: 393.91 | bwd_inner_microstep: 393.88 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.84 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-15 00:53:45,270] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 399.59 | bwd_microstep: 601.07 | bwd_inner_microstep: 601.05 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.05 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 836 +[2025-05-15 00:53:45,928] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 3.00 | optimizer_step: 18.54 +[2025-05-15 00:53:45,929] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 164.87 | bwd_microstep: 449.00 | bwd_inner_microstep: 233.11 | bwd_allreduce_microstep: 215.86 | step_microstep: 28.15 +[2025-05-15 00:53:45,930] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 1938.28 | bwd: 2864.24 | bwd_inner: 2647.73 | bwd_allreduce: 215.91 | step: 37.62 + 39%|███▉ | 220/558 [25:41<34:13, 6.08s/it] {'loss': 4.4608, 'grad_norm': 31.09170150756836, 'learning_rate': 6.910063546721064e-16, 'epoch': 0.12} + 39%|███▉ | 220/558 [25:41<34:13, 6.08s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1921 +[2025-05-15 00:53:46,747] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 304.55 | bwd_microstep: 486.49 | bwd_inner_microstep: 486.43 | bwd_allreduce_microstep: 0.02 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1907 +[2025-05-15 00:53:47,765] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 445.63 | bwd_microstep: 537.69 | bwd_inner_microstep: 537.67 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.31 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-15 00:53:48,602] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 355.81 | bwd_microstep: 460.06 | bwd_inner_microstep: 459.92 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-15 00:53:49,566] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 331.15 | bwd_microstep: 613.25 | bwd_inner_microstep: 613.22 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.33 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-15 00:53:50,477] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 364.15 | bwd_microstep: 511.45 | bwd_inner_microstep: 511.25 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-15 00:53:51,256] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 357.12 | bwd_microstep: 400.18 | bwd_inner_microstep: 400.16 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.32 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-15 00:53:52,269] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 406.25 | bwd_microstep: 584.43 | bwd_inner_microstep: 584.40 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.24 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-15 00:53:53,346] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.06 | optimizer_step: 17.95 +[2025-05-15 00:53:53,346] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 346.86 | bwd_microstep: 684.22 | bwd_inner_microstep: 514.21 | bwd_allreduce_microstep: 169.95 | step_microstep: 26.50 +[2025-05-15 00:53:53,347] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2911.50 | bwd: 4278.03 | bwd_inner: 4107.28 | bwd_allreduce: 170.07 | step: 36.34 + 40%|███▉ | 221/558 [25:48<36:23, 6.48s/it] {'loss': 6.2438, 'grad_norm': 24.411144256591797, 'learning_rate': 6.883198543824682e-16, 'epoch': 0.12} + 40%|███▉ | 221/558 [25:48<36:23, 6.48s/it]dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1372 +[2025-05-15 00:53:54,052] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 234.12 | bwd_microstep: 446.54 | bwd_inner_microstep: 446.50 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.53 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-15 00:53:55,019] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 411.29 | bwd_microstep: 521.13 | bwd_inner_microstep: 521.08 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.32 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1353 +[2025-05-15 00:53:55,674] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 258.03 | bwd_microstep: 373.12 | bwd_inner_microstep: 372.82 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-15 00:53:56,566] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 276.21 | bwd_microstep: 596.09 | bwd_inner_microstep: 596.06 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-15 00:53:57,444] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 384.44 | bwd_microstep: 461.68 | bwd_inner_microstep: 461.52 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-15 00:53:58,379] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 310.95 | bwd_microstep: 603.22 | bwd_inner_microstep: 603.19 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.53 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-15 00:53:59,215] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 360.94 | bwd_microstep: 442.48 | bwd_inner_microstep: 442.32 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 1657 +[2025-05-15 00:54:00,362] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 1.77 | optimizer_step: 17.95 +[2025-05-15 00:54:00,362] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 246.99 | bwd_microstep: 857.51 | bwd_inner_microstep: 549.86 | bwd_allreduce_microstep: 307.63 | step_microstep: 26.05 +[2025-05-15 00:54:00,363] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2482.92 | bwd: 4301.79 | bwd_inner: 3993.48 | bwd_allreduce: 307.91 | step: 36.10 + 40%|███▉ | 222/558 [25:55<37:11, 6.64s/it] {'loss': 7.1496, 'grad_norm': 38.55023956298828, 'learning_rate': 6.856270037071175e-16, 'epoch': 0.12} + 40%|███▉ | 222/558 [25:55<37:11, 6.64s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1946 +[2025-05-15 00:54:01,242] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 255.02 | bwd_microstep: 593.97 | bwd_inner_microstep: 593.94 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.55 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1126 +[2025-05-15 00:54:01,856] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 275.05 | bwd_microstep: 308.64 | bwd_inner_microstep: 308.39 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.23 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1888 +[2025-05-15 00:54:02,655] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 355.67 | bwd_microstep: 421.56 | bwd_inner_microstep: 421.54 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.89 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 331 +[2025-05-15 00:54:02,925] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 99.63 | bwd_microstep: 142.77 | bwd_inner_microstep: 142.71 | bwd_allreduce_microstep: 0.02 | step_microstep: 2.51 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-15 00:54:03,817] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 406.49 | bwd_microstep: 452.25 | bwd_inner_microstep: 452.09 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-15 00:54:04,783] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 338.95 | bwd_microstep: 606.88 | bwd_inner_microstep: 606.85 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-15 00:54:05,572] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 350.29 | bwd_microstep: 404.68 | bwd_inner_microstep: 404.64 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.85 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1944 +[2025-05-15 00:54:06,855] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 1.65 | optimizer_step: 12.98 +[2025-05-15 00:54:06,855] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 422.17 | bwd_microstep: 816.24 | bwd_inner_microstep: 623.02 | bwd_allreduce_microstep: 193.14 | step_microstep: 19.78 +[2025-05-15 00:54:06,856] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2503.27 | bwd: 3747.24 | bwd_inner: 3553.22 | bwd_allreduce: 193.27 | step: 31.26 + 40%|███▉ | 223/558 [26:02<36:49, 6.60s/it] {'loss': 3.8989, 'grad_norm': 9.303489685058594, 'learning_rate': 6.829278934524146e-16, 'epoch': 0.12} + 40%|███▉ | 223/558 [26:02<36:49, 6.60s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1895 +[2025-05-15 00:54:07,827] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 331.38 | bwd_microstep: 616.89 | bwd_inner_microstep: 616.82 | bwd_allreduce_microstep: 0.02 | step_microstep: 2.37 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1374 +[2025-05-15 00:54:08,454] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 269.08 | bwd_microstep: 323.77 | bwd_inner_microstep: 323.61 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-15 00:54:09,435] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 344.63 | bwd_microstep: 616.45 | bwd_inner_microstep: 616.41 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.46 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-15 00:54:10,213] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 349.94 | bwd_microstep: 394.69 | bwd_inner_microstep: 394.62 | bwd_allreduce_microstep: 0.02 | step_microstep: 1.74 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-15 00:54:11,242] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 405.18 | bwd_microstep: 598.74 | bwd_inner_microstep: 598.51 | bwd_allreduce_microstep: 0.21 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-15 00:54:12,033] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 320.39 | bwd_microstep: 450.04 | bwd_inner_microstep: 449.71 | bwd_allreduce_microstep: 0.27 | step_microstep: 0.38 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-15 00:54:13,045] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 438.55 | bwd_microstep: 543.21 | bwd_inner_microstep: 543.02 | bwd_allreduce_microstep: 0.18 | step_microstep: 0.17 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-15 00:54:14,267] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.01 | optimizer_gradients: 1.65 | optimizer_step: 14.26 +[2025-05-15 00:54:14,268] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 222.20 | bwd_microstep: 960.10 | bwd_inner_microstep: 588.33 | bwd_allreduce_microstep: 371.74 | step_microstep: 23.19 +[2025-05-15 00:54:14,268] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2681.32 | bwd: 4503.91 | bwd_inner: 4131.08 | bwd_allreduce: 372.47 | step: 30.41 + 40%|████ | 224/558 [26:09<38:04, 6.84s/it] {'loss': 7.3537, 'grad_norm': 32.002689361572266, 'learning_rate': 6.802226146358002e-16, 'epoch': 0.12} + 40%|████ | 224/558 [26:09<38:04, 6.84s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1915 +[2025-05-15 00:54:15,158] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 246.01 | bwd_microstep: 613.45 | bwd_inner_microstep: 613.43 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.50 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-15 00:54:15,962] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 384.43 | bwd_microstep: 386.58 | bwd_inner_microstep: 386.56 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.63 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-15 00:54:16,987] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 390.58 | bwd_microstep: 609.24 | bwd_inner_microstep: 609.05 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.23 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-15 00:54:17,774] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 353.36 | bwd_microstep: 413.05 | bwd_inner_microstep: 413.01 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.83 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-15 00:54:18,776] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 408.82 | bwd_microstep: 565.17 | bwd_inner_microstep: 565.15 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.30 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-15 00:54:19,585] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 247.09 | bwd_microstep: 536.91 | bwd_inner_microstep: 536.89 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.53 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 846 +[2025-05-15 00:54:20,114] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 223.52 | bwd_microstep: 275.44 | bwd_inner_microstep: 275.16 | bwd_allreduce_microstep: 0.23 | step_microstep: 0.21 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-15 00:54:21,418] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 1.63 | optimizer_step: 13.10 +[2025-05-15 00:54:21,418] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 354.41 | bwd_microstep: 909.72 | bwd_inner_microstep: 411.90 | bwd_allreduce_microstep: 497.79 | step_microstep: 20.34 +[2025-05-15 00:54:21,419] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2608.20 | bwd: 4309.74 | bwd_inner: 3811.15 | bwd_allreduce: 498.06 | step: 30.58 + 40%|████ | 225/558 [26:16<38:28, 6.93s/it] {'loss': 3.505, 'grad_norm': 13.150622367858887, 'learning_rate': 6.775112584827265e-16, 'epoch': 0.12} + 40%|████ | 225/558 [26:16<38:28, 6.93s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-15 00:54:22,219] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 280.25 | bwd_microstep: 495.50 | bwd_inner_microstep: 495.47 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-15 00:54:23,222] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 448.49 | bwd_microstep: 521.66 | bwd_inner_microstep: 521.60 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.10 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1363 +[2025-05-15 00:54:23,817] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 151.66 | bwd_microstep: 421.04 | bwd_inner_microstep: 421.00 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-15 00:54:24,811] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 442.57 | bwd_microstep: 516.36 | bwd_inner_microstep: 516.05 | bwd_allreduce_microstep: 0.14 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-15 00:54:25,675] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 241.91 | bwd_microstep: 599.87 | bwd_inner_microstep: 599.85 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.31 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-15 00:54:26,526] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 394.98 | bwd_microstep: 423.49 | bwd_inner_microstep: 423.35 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.11 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 327 +[2025-05-15 00:54:26,773] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 88.69 | bwd_microstep: 141.23 | bwd_inner_microstep: 141.16 | bwd_allreduce_microstep: 0.02 | step_microstep: 1.87 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-15 00:54:27,958] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.07 | optimizer_gradients: 2.10 | optimizer_step: 17.51 +[2025-05-15 00:54:27,959] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 412.95 | bwd_microstep: 719.77 | bwd_inner_microstep: 562.34 | bwd_allreduce_microstep: 157.37 | step_microstep: 26.12 +[2025-05-15 00:54:27,959] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2461.46 | bwd: 3838.96 | bwd_inner: 3680.91 | bwd_allreduce: 157.62 | step: 35.30 + 41%|████ | 226/558 [26:23<37:42, 6.82s/it] {'loss': 4.9761, 'grad_norm': 28.329448699951172, 'learning_rate': 6.747939164235819e-16, 'epoch': 0.12} + 41%|████ | 226/558 [26:23<37:42, 6.82s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1902 +[2025-05-15 00:54:28,951] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 346.94 | bwd_microstep: 618.13 | bwd_inner_microstep: 618.09 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.51 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-15 00:54:29,725] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 343.04 | bwd_microstep: 396.12 | bwd_inner_microstep: 396.10 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.28 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-15 00:54:30,747] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 396.40 | bwd_microstep: 601.37 | bwd_inner_microstep: 601.16 | bwd_allreduce_microstep: 0.18 | step_microstep: 0.19 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1366 +[2025-05-15 00:54:31,296] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 267.80 | bwd_microstep: 259.97 | bwd_inner_microstep: 259.93 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-15 00:54:32,324] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 401.28 | bwd_microstep: 606.10 | bwd_inner_microstep: 606.06 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-15 00:54:33,113] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 322.40 | bwd_microstep: 447.24 | bwd_inner_microstep: 446.92 | bwd_allreduce_microstep: 0.28 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-15 00:54:34,118] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 436.70 | bwd_microstep: 539.46 | bwd_inner_microstep: 539.25 | bwd_allreduce_microstep: 0.17 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-15 00:54:35,351] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.01 | optimizer_gradients: 2.09 | optimizer_step: 18.85 +[2025-05-15 00:54:35,352] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 221.66 | bwd_microstep: 963.69 | bwd_inner_microstep: 587.51 | bwd_allreduce_microstep: 376.15 | step_microstep: 27.80 +[2025-05-15 00:54:35,353] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2736.21 | bwd: 4432.08 | bwd_inner: 4054.99 | bwd_allreduce: 376.79 | step: 35.69 + 41%|████ | 227/558 [26:30<38:33, 6.99s/it] {'loss': 4.8288, 'grad_norm': 15.216848373413086, 'learning_rate': 6.720706800906071e-16, 'epoch': 0.12} + 41%|████ | 227/558 [26:30<38:33, 6.99s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1887 +[2025-05-15 00:54:36,165] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 282.70 | bwd_microstep: 501.42 | bwd_inner_microstep: 501.35 | bwd_allreduce_microstep: 0.02 | step_microstep: 2.56 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1117 +[2025-05-15 00:54:36,828] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 276.19 | bwd_microstep: 353.10 | bwd_inner_microstep: 353.06 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.91 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1366 +[2025-05-15 00:54:37,379] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 262.77 | bwd_microstep: 267.00 | bwd_inner_microstep: 266.97 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.76 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-15 00:54:38,399] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 398.69 | bwd_microstep: 593.75 | bwd_inner_microstep: 593.55 | bwd_allreduce_microstep: 0.18 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-15 00:54:39,188] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 320.87 | bwd_microstep: 447.50 | bwd_inner_microstep: 447.29 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-15 00:54:40,193] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 438.05 | bwd_microstep: 539.07 | bwd_inner_microstep: 538.86 | bwd_allreduce_microstep: 0.18 | step_microstep: 0.17 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1346 +[2025-05-15 00:54:40,756] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 164.14 | bwd_microstep: 380.11 | bwd_inner_microstep: 379.89 | bwd_allreduce_microstep: 0.19 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-15 00:54:41,901] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 1.67 | optimizer_step: 14.64 +[2025-05-15 00:54:41,902] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 441.00 | bwd_microstep: 651.99 | bwd_inner_microstep: 536.81 | bwd_allreduce_microstep: 115.11 | step_microstep: 22.02 +[2025-05-15 00:54:41,903] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2584.42 | bwd: 3733.94 | bwd_inner: 3617.77 | bwd_allreduce: 115.37 | step: 28.85 + 41%|████ | 228/558 [26:37<37:42, 6.86s/it] {'loss': 5.8994, 'grad_norm': 44.5737190246582, 'learning_rate': 6.693416413148046e-16, 'epoch': 0.12} + 41%|████ | 228/558 [26:37<37:42, 6.86s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1889 +[2025-05-15 00:54:42,912] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 354.94 | bwd_microstep: 627.39 | bwd_inner_microstep: 627.36 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-15 00:54:43,707] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 365.04 | bwd_microstep: 395.87 | bwd_inner_microstep: 395.83 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.85 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-15 00:54:44,729] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 410.75 | bwd_microstep: 585.11 | bwd_inner_microstep: 585.05 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-15 00:54:45,514] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 293.32 | bwd_microstep: 470.70 | bwd_inner_microstep: 470.67 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.33 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-15 00:54:46,498] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 433.79 | bwd_microstep: 514.87 | bwd_inner_microstep: 514.84 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.23 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-15 00:54:47,319] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 220.30 | bwd_microstep: 580.76 | bwd_inner_microstep: 580.72 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.52 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1952 +[2025-05-15 00:54:48,249] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 425.59 | bwd_microstep: 469.43 | bwd_inner_microstep: 469.27 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1894 +[2025-05-15 00:54:49,476] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 1.89 | optimizer_step: 14.21 +[2025-05-15 00:54:49,477] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 350.80 | bwd_microstep: 837.63 | bwd_inner_microstep: 622.25 | bwd_allreduce_microstep: 215.35 | step_microstep: 22.56 +[2025-05-15 00:54:49,478] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2854.51 | bwd: 4481.96 | bwd_inner: 4266.03 | bwd_allreduce: 215.45 | step: 32.99 + 41%|████ | 229/558 [26:45<38:46, 7.07s/it] {'loss': 4.8148, 'grad_norm': 28.977731704711914, 'learning_rate': 6.666068921228433e-16, 'epoch': 0.12} + 41%|████ | 229/558 [26:45<38:46, 7.07s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1955 +[2025-05-15 00:54:50,344] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 260.47 | bwd_microstep: 580.39 | bwd_inner_microstep: 580.37 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-15 00:54:51,294] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 422.51 | bwd_microstep: 495.28 | bwd_inner_microstep: 494.97 | bwd_allreduce_microstep: 0.27 | step_microstep: 1.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-15 00:54:52,094] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 243.76 | bwd_microstep: 536.05 | bwd_inner_microstep: 536.01 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.32 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-15 00:54:53,074] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 426.35 | bwd_microstep: 518.78 | bwd_inner_microstep: 518.77 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.30 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-15 00:54:53,889] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 249.41 | bwd_microstep: 542.29 | bwd_inner_microstep: 542.22 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-15 00:54:54,869] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 428.19 | bwd_microstep: 519.64 | bwd_inner_microstep: 518.88 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.21 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-15 00:54:55,645] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 305.67 | bwd_microstep: 451.82 | bwd_inner_microstep: 451.60 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-15 00:54:56,913] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.01 | optimizer_gradients: 1.65 | optimizer_step: 17.45 +[2025-05-15 00:54:56,914] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 440.23 | bwd_microstep: 770.12 | bwd_inner_microstep: 554.81 | bwd_allreduce_microstep: 215.28 | step_microstep: 26.01 +[2025-05-15 00:54:56,915] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2776.60 | bwd: 4414.37 | bwd_inner: 4197.61 | bwd_allreduce: 216.33 | step: 36.78 + 41%|████ | 230/558 [26:52<39:15, 7.18s/it] {'loss': 2.9217, 'grad_norm': 8.772462844848633, 'learning_rate': 6.638665247339546e-16, 'epoch': 0.12} + 41%|████ | 230/558 [26:52<39:15, 7.18s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1891 +[2025-05-15 00:54:57,783] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 241.60 | bwd_microstep: 600.14 | bwd_inner_microstep: 600.09 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.55 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1889 +[2025-05-15 00:54:58,737] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 396.41 | bwd_microstep: 522.18 | bwd_inner_microstep: 522.15 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.30 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1886 +[2025-05-15 00:54:59,538] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 324.96 | bwd_microstep: 454.82 | bwd_inner_microstep: 454.61 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.10 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 845 +[2025-05-15 00:55:00,105] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 224.75 | bwd_microstep: 312.16 | bwd_inner_microstep: 312.11 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-15 00:55:00,888] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 359.83 | bwd_microstep: 398.34 | bwd_inner_microstep: 398.27 | bwd_allreduce_microstep: 0.02 | step_microstep: 1.90 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-15 00:55:01,910] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 411.38 | bwd_microstep: 584.93 | bwd_inner_microstep: 584.88 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.24 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 324 +[2025-05-15 00:55:02,137] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 81.14 | bwd_microstep: 128.97 | bwd_inner_microstep: 128.53 | bwd_allreduce_microstep: 0.22 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-15 00:55:03,364] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.01 | optimizer_gradients: 2.07 | optimizer_step: 18.37 +[2025-05-15 00:55:03,365] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 243.45 | bwd_microstep: 937.37 | bwd_inner_microstep: 599.04 | bwd_allreduce_microstep: 338.29 | step_microstep: 27.75 +[2025-05-15 00:55:03,366] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2283.49 | bwd: 3938.90 | bwd_inner: 3600.02 | bwd_allreduce: 338.57 | step: 37.40 + 41%|████▏ | 231/558 [26:58<37:56, 6.96s/it] {'loss': 3.3324, 'grad_norm': 8.315736770629883, 'learning_rate': 6.611206315568223e-16, 'epoch': 0.12} + 41%|████▏ | 231/558 [26:58<37:56, 6.96s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1914 +[2025-05-15 00:55:04,177] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 295.11 | bwd_microstep: 487.39 | bwd_inner_microstep: 487.35 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.52 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1901 +[2025-05-15 00:55:05,191] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 443.90 | bwd_microstep: 535.25 | bwd_inner_microstep: 535.18 | bwd_allreduce_microstep: 0.02 | step_microstep: 2.27 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1889 +[2025-05-15 00:55:06,037] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 224.96 | bwd_microstep: 598.20 | bwd_inner_microstep: 598.14 | bwd_allreduce_microstep: 0.02 | step_microstep: 2.36 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 844 +[2025-05-15 00:55:06,561] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 223.99 | bwd_microstep: 269.82 | bwd_inner_microstep: 269.42 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.22 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-15 00:55:07,367] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 356.88 | bwd_microstep: 428.03 | bwd_inner_microstep: 427.97 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.88 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-15 00:55:08,387] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 441.75 | bwd_microstep: 550.49 | bwd_inner_microstep: 550.43 | bwd_allreduce_microstep: 0.02 | step_microstep: 2.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-15 00:55:09,173] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 348.91 | bwd_microstep: 415.26 | bwd_inner_microstep: 415.24 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.82 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2020 +[2025-05-15 00:55:10,486] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.04 | optimizer_step: 18.20 +[2025-05-15 00:55:10,487] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 432.53 | bwd_microstep: 827.34 | bwd_inner_microstep: 603.87 | bwd_allreduce_microstep: 223.44 | step_microstep: 27.27 +[2025-05-15 00:55:10,487] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2768.02 | bwd: 4111.81 | bwd_inner: 3887.65 | bwd_allreduce: 223.29 | step: 40.43 + 42%|████▏ | 232/558 [27:06<38:05, 7.01s/it] {'loss': 4.8634, 'grad_norm': 27.616735458374023, 'learning_rate': 6.583693051864669e-16, 'epoch': 0.12} + 42%|████▏ | 232/558 [27:06<38:05, 7.01s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1889 +[2025-05-15 00:55:11,392] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 265.58 | bwd_microstep: 608.78 | bwd_inner_microstep: 608.74 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1375 +[2025-05-15 00:55:12,118] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 297.99 | bwd_microstep: 394.34 | bwd_inner_microstep: 394.31 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.90 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 853 +[2025-05-15 00:55:12,449] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 129.28 | bwd_microstep: 181.70 | bwd_inner_microstep: 181.62 | bwd_allreduce_microstep: 0.02 | step_microstep: 1.45 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-15 00:55:13,482] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 403.18 | bwd_microstep: 602.80 | bwd_inner_microstep: 602.41 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-15 00:55:14,253] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 360.49 | bwd_microstep: 390.44 | bwd_inner_microstep: 390.40 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.84 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-15 00:55:15,284] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 399.18 | bwd_microstep: 600.19 | bwd_inner_microstep: 600.13 | bwd_allreduce_microstep: 0.02 | step_microstep: 2.48 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-15 00:55:16,048] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 355.91 | bwd_microstep: 384.66 | bwd_inner_microstep: 384.63 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.83 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2091 +[2025-05-15 00:55:17,418] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.08 | optimizer_step: 15.84 +[2025-05-15 00:55:17,419] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 435.62 | bwd_microstep: 885.55 | bwd_inner_microstep: 666.49 | bwd_allreduce_microstep: 218.86 | step_microstep: 24.95 +[2025-05-15 00:55:17,420] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2647.21 | bwd: 4048.46 | bwd_inner: 3828.91 | bwd_allreduce: 219.11 | step: 36.97 + 42%|████▏ | 233/558 [27:12<37:50, 6.99s/it] {'loss': 5.6622, 'grad_norm': 45.81671142578125, 'learning_rate': 6.556126384011233e-16, 'epoch': 0.13} + 42%|████▏ | 233/558 [27:12<37:50, 6.99s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1893 +[2025-05-15 00:55:18,301] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 248.02 | bwd_microstep: 606.77 | bwd_inner_microstep: 606.74 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.33 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-15 00:55:19,141] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 390.11 | bwd_microstep: 417.78 | bwd_inner_microstep: 417.62 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.10 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1108 +[2025-05-15 00:55:19,768] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 252.81 | bwd_microstep: 354.13 | bwd_inner_microstep: 354.10 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-15 00:55:20,716] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 403.19 | bwd_microstep: 511.77 | bwd_inner_microstep: 511.37 | bwd_allreduce_microstep: 0.19 | step_microstep: 0.22 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-15 00:55:21,498] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 355.14 | bwd_microstep: 405.48 | bwd_inner_microstep: 405.44 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.85 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1351 +[2025-05-15 00:55:22,302] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 306.56 | bwd_microstep: 470.66 | bwd_inner_microstep: 470.63 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.31 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-15 00:55:23,063] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 338.48 | bwd_microstep: 398.04 | bwd_inner_microstep: 397.99 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.85 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-15 00:55:24,335] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.07 | optimizer_step: 19.75 +[2025-05-15 00:55:24,335] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 395.71 | bwd_microstep: 823.54 | bwd_inner_microstep: 601.97 | bwd_allreduce_microstep: 221.54 | step_microstep: 28.45 +[2025-05-15 00:55:24,336] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2690.01 | bwd: 3988.19 | bwd_inner: 3766.05 | bwd_allreduce: 221.83 | step: 39.46 + 42%|████▏ | 234/558 [27:19<37:37, 6.97s/it] {'loss': 7.1575, 'grad_norm': 21.042024612426758, 'learning_rate': 6.528507241591121e-16, 'epoch': 0.13} + 42%|████▏ | 234/558 [27:19<37:37, 6.97s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1911 +[2025-05-15 00:55:25,177] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 247.56 | bwd_microstep: 565.01 | bwd_inner_microstep: 564.96 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1919 +[2025-05-15 00:55:26,163] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 436.44 | bwd_microstep: 517.19 | bwd_inner_microstep: 516.96 | bwd_allreduce_microstep: 0.21 | step_microstep: 0.25 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1886 +[2025-05-15 00:55:26,984] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 246.15 | bwd_microstep: 554.56 | bwd_inner_microstep: 554.51 | bwd_allreduce_microstep: 0.02 | step_microstep: 2.35 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 848 +[2025-05-15 00:55:27,517] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 225.15 | bwd_microstep: 277.63 | bwd_inner_microstep: 276.63 | bwd_allreduce_microstep: 0.95 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-15 00:55:28,344] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 345.58 | bwd_microstep: 460.94 | bwd_inner_microstep: 460.61 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1357 +[2025-05-15 00:55:29,030] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 224.40 | bwd_microstep: 444.10 | bwd_inner_microstep: 444.07 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-15 00:55:29,992] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 408.00 | bwd_microstep: 519.73 | bwd_inner_microstep: 519.70 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.27 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-15 00:55:31,238] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.05 | optimizer_step: 19.55 +[2025-05-15 00:55:31,238] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 225.29 | bwd_microstep: 969.42 | bwd_inner_microstep: 592.32 | bwd_allreduce_microstep: 377.08 | step_microstep: 27.51 +[2025-05-15 00:55:31,239] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2358.56 | bwd: 4308.56 | bwd_inner: 3929.82 | bwd_allreduce: 378.42 | step: 37.36 + 42%|████▏ | 235/558 [27:26<37:23, 6.95s/it] {'loss': 3.1721, 'grad_norm': 16.53148651123047, 'learning_rate': 6.500836555957046e-16, 'epoch': 0.13} + 42%|████▏ | 235/558 [27:26<37:23, 6.95s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-15 00:55:32,034] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 354.80 | bwd_microstep: 413.85 | bwd_inner_microstep: 413.82 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.83 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1902 +[2025-05-15 00:55:33,053] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 416.34 | bwd_microstep: 577.46 | bwd_inner_microstep: 577.26 | bwd_allreduce_microstep: 0.18 | step_microstep: 0.17 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-15 00:55:33,845] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 320.99 | bwd_microstep: 452.67 | bwd_inner_microstep: 452.41 | bwd_allreduce_microstep: 0.21 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-15 00:55:34,864] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 448.03 | bwd_microstep: 542.08 | bwd_inner_microstep: 541.88 | bwd_allreduce_microstep: 0.18 | step_microstep: 0.17 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-15 00:55:35,656] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 322.24 | bwd_microstep: 450.74 | bwd_inner_microstep: 450.52 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-15 00:55:36,669] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 441.50 | bwd_microstep: 539.18 | bwd_inner_microstep: 538.96 | bwd_allreduce_microstep: 0.19 | step_microstep: 0.17 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-15 00:55:37,485] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 246.46 | bwd_microstep: 546.94 | bwd_inner_microstep: 546.89 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.56 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-15 00:55:38,704] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.07 | optimizer_gradients: 1.69 | optimizer_step: 27.60 +[2025-05-15 00:55:38,705] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 419.28 | bwd_microstep: 733.62 | bwd_inner_microstep: 515.12 | bwd_allreduce_microstep: 218.44 | step_microstep: 34.81 +[2025-05-15 00:55:38,705] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2969.64 | bwd: 4256.53 | bwd_inner: 4036.84 | bwd_allreduce: 219.04 | step: 40.13 + 42%|████▏ | 236/558 [27:34<38:07, 7.10s/it] {'loss': 5.1256, 'grad_norm': 19.148164749145508, 'learning_rate': 6.473115260199823e-16, 'epoch': 0.13} + 42%|████▏ | 236/558 [27:34<38:07, 7.10s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 382 +[2025-05-15 00:55:38,948] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 77.68 | bwd_microstep: 141.22 | bwd_inner_microstep: 141.16 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.78 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1895 +[2025-05-15 00:55:39,972] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 413.38 | bwd_microstep: 588.05 | bwd_inner_microstep: 588.01 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-15 00:55:40,745] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 358.46 | bwd_microstep: 396.58 | bwd_inner_microstep: 396.36 | bwd_allreduce_microstep: 0.18 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-15 00:55:41,782] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 393.25 | bwd_microstep: 619.80 | bwd_inner_microstep: 619.59 | bwd_allreduce_microstep: 0.19 | step_microstep: 0.17 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 334 +[2025-05-15 00:55:42,018] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.02 | bwd_microstep: 123.96 | bwd_inner_microstep: 123.91 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.94 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1359 +[2025-05-15 00:55:42,638] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 263.58 | bwd_microstep: 336.60 | bwd_inner_microstep: 336.45 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-15 00:55:43,609] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 333.55 | bwd_microstep: 617.17 | bwd_inner_microstep: 617.11 | bwd_allreduce_microstep: 0.02 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-15 00:55:44,543] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.01 | optimizer_gradients: 1.72 | optimizer_step: 17.75 +[2025-05-15 00:55:44,545] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 351.56 | bwd_microstep: 524.72 | bwd_inner_microstep: 457.71 | bwd_allreduce_microstep: 66.95 | step_microstep: 27.67 +[2025-05-15 00:55:44,546] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2286.45 | bwd: 3348.09 | bwd_inner: 3280.34 | bwd_allreduce: 67.42 | step: 33.24 + 42%|████▏ | 237/558 [27:40<35:58, 6.73s/it] {'loss': 2.6558, 'grad_norm': 8.047652244567871, 'learning_rate': 6.44534428911691e-16, 'epoch': 0.13} + 42%|████▏ | 237/558 [27:40<35:58, 6.73s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1906 +[2025-05-15 00:55:45,584] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 403.74 | bwd_microstep: 601.27 | bwd_inner_microstep: 600.86 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-15 00:55:46,361] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 359.02 | bwd_microstep: 396.31 | bwd_inner_microstep: 396.24 | bwd_allreduce_microstep: 0.02 | step_microstep: 1.96 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1886 +[2025-05-15 00:55:47,410] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 404.07 | bwd_microstep: 615.34 | bwd_inner_microstep: 615.29 | bwd_allreduce_microstep: 0.02 | step_microstep: 2.32 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-15 00:55:48,223] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 365.80 | bwd_microstep: 427.26 | bwd_inner_microstep: 427.12 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-15 00:55:49,240] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 363.05 | bwd_microstep: 636.37 | bwd_inner_microstep: 636.15 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.41 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-15 00:55:50,120] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 360.95 | bwd_microstep: 498.13 | bwd_inner_microstep: 497.80 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.19 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1087 +[2025-05-15 00:55:50,587] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 123.83 | bwd_microstep: 324.97 | bwd_inner_microstep: 324.74 | bwd_allreduce_microstep: 0.19 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-15 00:55:51,832] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.01 | optimizer_gradients: 2.02 | optimizer_step: 18.57 +[2025-05-15 00:55:51,833] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 435.85 | bwd_microstep: 752.75 | bwd_inner_microstep: 538.95 | bwd_allreduce_microstep: 213.77 | step_microstep: 27.65 +[2025-05-15 00:55:51,834] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2816.28 | bwd: 4252.47 | bwd_inner: 4037.27 | bwd_allreduce: 214.20 | step: 32.70 + 43%|████▎ | 238/558 [27:47<36:45, 6.89s/it] {'loss': 6.4445, 'grad_norm': 46.75847244262695, 'learning_rate': 6.417524579180873e-16, 'epoch': 0.13} + 43%|████▎ | 238/558 [27:47<36:45, 6.89s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-15 00:55:52,659] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 250.45 | bwd_microstep: 546.94 | bwd_inner_microstep: 546.88 | bwd_allreduce_microstep: 0.02 | step_microstep: 2.53 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-15 00:55:53,643] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 425.16 | bwd_microstep: 526.85 | bwd_inner_microstep: 526.81 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.27 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-15 00:55:54,517] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 243.59 | bwd_microstep: 605.81 | bwd_inner_microstep: 605.79 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.55 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-15 00:55:55,458] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 385.15 | bwd_microstep: 519.87 | bwd_inner_microstep: 519.81 | bwd_allreduce_microstep: 0.02 | step_microstep: 2.27 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-15 00:55:56,295] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 232.55 | bwd_microstep: 581.82 | bwd_inner_microstep: 581.78 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.52 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 836 +[2025-05-15 00:55:56,804] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 219.24 | bwd_microstep: 260.10 | bwd_inner_microstep: 260.04 | bwd_allreduce_microstep: 0.02 | step_microstep: 2.17 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-15 00:55:57,583] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 355.01 | bwd_microstep: 403.59 | bwd_inner_microstep: 403.56 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.28 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1975 +[2025-05-15 00:55:58,890] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 1.69 | optimizer_step: 19.22 +[2025-05-15 00:55:58,891] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 437.70 | bwd_microstep: 819.28 | bwd_inner_microstep: 603.24 | bwd_allreduce_microstep: 216.02 | step_microstep: 26.78 +[2025-05-15 00:55:58,892] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2548.85 | bwd: 4264.25 | bwd_inner: 4047.94 | bwd_allreduce: 216.09 | step: 41.40 + 43%|████▎ | 239/558 [27:54<36:54, 6.94s/it] {'loss': 4.936, 'grad_norm': 14.695642471313477, 'learning_rate': 6.389657068507819e-16, 'epoch': 0.13} + 43%|████▎ | 239/558 [27:54<36:54, 6.94s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1920 +[2025-05-15 00:55:59,792] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 261.19 | bwd_microstep: 612.89 | bwd_inner_microstep: 612.84 | bwd_allreduce_microstep: 0.02 | step_microstep: 2.35 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 863 +[2025-05-15 00:56:00,293] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 212.18 | bwd_microstep: 255.51 | bwd_inner_microstep: 255.44 | bwd_allreduce_microstep: 0.02 | step_microstep: 2.32 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1886 +[2025-05-15 00:56:01,092] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 359.59 | bwd_microstep: 415.82 | bwd_inner_microstep: 415.79 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.80 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-15 00:56:02,092] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 417.63 | bwd_microstep: 559.13 | bwd_inner_microstep: 559.09 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.26 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-15 00:56:02,978] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 338.62 | bwd_microstep: 522.65 | bwd_inner_microstep: 522.60 | bwd_allreduce_microstep: 0.02 | step_microstep: 2.31 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-15 00:56:03,842] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 238.10 | bwd_microstep: 599.88 | bwd_inner_microstep: 599.84 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 841 +[2025-05-15 00:56:04,344] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 222.40 | bwd_microstep: 246.51 | bwd_inner_microstep: 246.12 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.38 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-15 00:56:05,305] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.09 | optimizer_step: 18.16 +[2025-05-15 00:56:05,306] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 351.49 | bwd_microstep: 562.80 | bwd_inner_microstep: 496.82 | bwd_allreduce_microstep: 65.88 | step_microstep: 26.90 +[2025-05-15 00:56:05,306] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2401.15 | bwd: 3775.22 | bwd_inner: 3708.59 | bwd_allreduce: 66.14 | step: 38.51 + 43%|████▎ | 240/558 [28:00<35:57, 6.78s/it] {'loss': 3.1498, 'grad_norm': 17.284889221191406, 'learning_rate': 6.361742696825755e-16, 'epoch': 0.13} + 43%|████▎ | 240/558 [28:00<35:57, 6.78s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1888 +[2025-05-15 00:56:06,358] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 390.47 | bwd_microstep: 633.05 | bwd_inner_microstep: 633.01 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.28 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 845 +[2025-05-15 00:56:06,804] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 171.49 | bwd_microstep: 250.24 | bwd_inner_microstep: 250.20 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.38 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1361 +[2025-05-15 00:56:07,454] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 263.16 | bwd_microstep: 363.88 | bwd_inner_microstep: 363.72 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.09 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1357 +[2025-05-15 00:56:08,087] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 176.05 | bwd_microstep: 438.74 | bwd_inner_microstep: 438.71 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-15 00:56:09,074] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 427.65 | bwd_microstep: 522.50 | bwd_inner_microstep: 522.44 | bwd_allreduce_microstep: 0.02 | step_microstep: 2.32 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1345 +[2025-05-15 00:56:09,625] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 264.40 | bwd_microstep: 265.71 | bwd_inner_microstep: 265.69 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.76 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-15 00:56:10,653] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 400.28 | bwd_microstep: 601.94 | bwd_inner_microstep: 601.88 | bwd_allreduce_microstep: 0.02 | step_microstep: 1.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-15 00:56:12,036] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.01 | optimizer_gradients: 1.71 | optimizer_step: 16.61 +[2025-05-15 00:56:12,037] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 347.88 | bwd_microstep: 992.13 | bwd_inner_microstep: 400.49 | bwd_allreduce_microstep: 591.57 | step_microstep: 25.52 +[2025-05-15 00:56:12,038] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2441.34 | bwd: 4068.21 | bwd_inner: 3476.20 | bwd_allreduce: 591.69 | step: 37.80 + 43%|████▎ | 241/558 [28:07<35:45, 6.77s/it] {'loss': 5.1806, 'grad_norm': 23.979333877563477, 'learning_rate': 6.333782405442904e-16, 'epoch': 0.13} + 43%|████▎ | 241/558 [28:07<35:45, 6.77s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-15 00:56:12,926] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 345.17 | bwd_microstep: 514.64 | bwd_inner_microstep: 514.62 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.27 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 331 +[2025-05-15 00:56:13,155] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 73.33 | bwd_microstep: 132.12 | bwd_inner_microstep: 132.05 | bwd_allreduce_microstep: 0.02 | step_microstep: 2.33 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-15 00:56:14,178] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 410.42 | bwd_microstep: 590.26 | bwd_inner_microstep: 590.22 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.22 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 848 +[2025-05-15 00:56:14,612] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 173.02 | bwd_microstep: 241.80 | bwd_inner_microstep: 241.53 | bwd_allreduce_microstep: 0.24 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-15 00:56:15,419] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 283.80 | bwd_microstep: 501.00 | bwd_inner_microstep: 500.93 | bwd_allreduce_microstep: 0.02 | step_microstep: 2.53 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-15 00:56:16,418] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 440.47 | bwd_microstep: 525.34 | bwd_inner_microstep: 525.30 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-15 00:56:17,210] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 319.87 | bwd_microstep: 451.92 | bwd_inner_microstep: 451.66 | bwd_allreduce_microstep: 0.21 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1926 +[2025-05-15 00:56:18,483] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 1.65 | optimizer_step: 12.97 +[2025-05-15 00:56:18,484] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 461.06 | bwd_microstep: 763.15 | bwd_inner_microstep: 561.27 | bwd_allreduce_microstep: 201.81 | step_microstep: 19.66 +[2025-05-15 00:56:18,484] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2507.13 | bwd: 3720.23 | bwd_inner: 3517.58 | bwd_allreduce: 202.34 | step: 27.59 + 43%|████▎ | 242/558 [28:14<35:08, 6.67s/it] {'loss': 4.8574, 'grad_norm': 17.231584548950195, 'learning_rate': 6.305777137215961e-16, 'epoch': 0.13} + 43%|████▎ | 242/558 [28:14<35:08, 6.67s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-15 00:56:19,444] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 327.28 | bwd_microstep: 608.59 | bwd_inner_microstep: 608.53 | bwd_allreduce_microstep: 0.02 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-15 00:56:20,252] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 367.53 | bwd_microstep: 405.19 | bwd_inner_microstep: 405.17 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.77 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 847 +[2025-05-15 00:56:20,782] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.95 | bwd_microstep: 315.72 | bwd_inner_microstep: 315.67 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-15 00:56:21,585] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 385.72 | bwd_microstep: 383.98 | bwd_inner_microstep: 383.92 | bwd_allreduce_microstep: 0.02 | step_microstep: 1.79 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-15 00:56:22,616] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 398.07 | bwd_microstep: 607.65 | bwd_inner_microstep: 607.62 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.31 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 831 +[2025-05-15 00:56:22,970] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 166.79 | bwd_microstep: 168.32 | bwd_inner_microstep: 168.13 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-15 00:56:23,936] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 350.71 | bwd_microstep: 595.73 | bwd_inner_microstep: 595.70 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.28 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1957 +[2025-05-15 00:56:25,326] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.01 | optimizer_gradients: 2.06 | optimizer_step: 16.98 +[2025-05-15 00:56:25,327] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 361.16 | bwd_microstep: 970.18 | bwd_inner_microstep: 459.89 | bwd_allreduce_microstep: 510.24 | step_microstep: 26.48 +[2025-05-15 00:56:25,327] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2545.20 | bwd: 4055.36 | bwd_inner: 3544.71 | bwd_allreduce: 510.36 | step: 38.45 + 44%|████▎ | 243/558 [28:20<35:17, 6.72s/it] {'loss': 5.7462, 'grad_norm': 37.190269470214844, 'learning_rate': 6.277727836518286e-16, 'epoch': 0.13} + 44%|████▎ | 243/558 [28:20<35:17, 6.72s/it]dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 867 +[2025-05-15 00:56:25,642] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 147.02 | bwd_microstep: 146.22 | bwd_inner_microstep: 145.71 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.63 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-15 00:56:26,672] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 395.92 | bwd_microstep: 612.94 | bwd_inner_microstep: 612.74 | bwd_allreduce_microstep: 0.19 | step_microstep: 0.24 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-15 00:56:27,455] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 319.64 | bwd_microstep: 445.72 | bwd_inner_microstep: 445.64 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-15 00:56:28,466] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 442.48 | bwd_microstep: 539.44 | bwd_inner_microstep: 539.29 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-15 00:56:29,328] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 244.10 | bwd_microstep: 594.25 | bwd_inner_microstep: 594.23 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.32 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-15 00:56:30,141] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 385.10 | bwd_microstep: 395.12 | bwd_inner_microstep: 394.89 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-15 00:56:31,174] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 392.93 | bwd_microstep: 615.09 | bwd_inner_microstep: 614.84 | bwd_allreduce_microstep: 0.21 | step_microstep: 0.25 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1888 +[2025-05-15 00:56:32,480] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.10 | optimizer_step: 17.93 +[2025-05-15 00:56:32,480] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 320.24 | bwd_microstep: 939.61 | bwd_inner_microstep: 448.86 | bwd_allreduce_microstep: 490.72 | step_microstep: 26.69 +[2025-05-15 00:56:32,481] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2647.38 | bwd: 4288.43 | bwd_inner: 3796.22 | bwd_allreduce: 491.27 | step: 30.61 + 44%|████▎ | 244/558 [28:28<35:51, 6.85s/it] {'loss': 5.636, 'grad_norm': 16.041194915771484, 'learning_rate': 6.249635449208085e-16, 'epoch': 0.13} + 44%|████▎ | 244/558 [28:28<35:51, 6.85s/it]dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 871 +[2025-05-15 00:56:32,824] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 132.55 | bwd_microstep: 187.14 | bwd_inner_microstep: 187.10 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.75 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1907 +[2025-05-15 00:56:33,852] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 402.70 | bwd_microstep: 602.68 | bwd_inner_microstep: 602.41 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.20 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 347 +[2025-05-15 00:56:34,085] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 96.36 | bwd_microstep: 118.97 | bwd_inner_microstep: 118.81 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-15 00:56:35,005] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 294.79 | bwd_microstep: 605.32 | bwd_inner_microstep: 605.26 | bwd_allreduce_microstep: 0.02 | step_microstep: 2.36 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 846 +[2025-05-15 00:56:35,480] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 199.13 | bwd_microstep: 244.74 | bwd_inner_microstep: 244.35 | bwd_allreduce_microstep: 0.19 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-15 00:56:36,317] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 221.97 | bwd_microstep: 593.69 | bwd_inner_microstep: 593.63 | bwd_allreduce_microstep: 0.02 | step_microstep: 2.57 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-15 00:56:37,169] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 402.38 | bwd_microstep: 415.43 | bwd_inner_microstep: 415.28 | bwd_allreduce_microstep: 0.08 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-15 00:56:38,446] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 1.92 | optimizer_step: 14.47 +[2025-05-15 00:56:38,447] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 389.81 | bwd_microstep: 846.87 | bwd_inner_microstep: 627.83 | bwd_allreduce_microstep: 218.99 | step_microstep: 23.36 +[2025-05-15 00:56:38,447] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2139.66 | bwd: 3614.88 | bwd_inner: 3394.70 | bwd_allreduce: 219.39 | step: 30.65 + 44%|████▍ | 245/558 [28:33<34:21, 6.59s/it] {'loss': 4.8566, 'grad_norm': 14.943180084228516, 'learning_rate': 6.221500922596488e-16, 'epoch': 0.13} + 44%|████▍ | 245/558 [28:33<34:21, 6.59s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1896 +[2025-05-15 00:56:39,390] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 304.58 | bwd_microstep: 611.82 | bwd_inner_microstep: 611.79 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.42 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1382 +[2025-05-15 00:56:40,009] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 273.29 | bwd_microstep: 312.81 | bwd_inner_microstep: 312.56 | bwd_allreduce_microstep: 0.09 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-15 00:56:41,004] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 356.36 | bwd_microstep: 619.20 | bwd_inner_microstep: 619.14 | bwd_allreduce_microstep: 0.02 | step_microstep: 2.44 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-15 00:56:41,806] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 361.13 | bwd_microstep: 410.42 | bwd_inner_microstep: 410.37 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-15 00:56:42,813] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 416.64 | bwd_microstep: 567.92 | bwd_inner_microstep: 567.87 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-15 00:56:43,631] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 230.97 | bwd_microstep: 565.13 | bwd_inner_microstep: 565.11 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.33 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-15 00:56:44,494] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 412.40 | bwd_microstep: 418.49 | bwd_inner_microstep: 418.33 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1921 +[2025-05-15 00:56:45,825] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 1.77 | optimizer_step: 19.50 +[2025-05-15 00:56:45,825] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 412.99 | bwd_microstep: 869.37 | bwd_inner_microstep: 645.32 | bwd_allreduce_microstep: 223.97 | step_microstep: 28.65 +[2025-05-15 00:56:45,826] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2768.32 | bwd: 4375.18 | bwd_inner: 4150.58 | bwd_allreduce: 224.16 | step: 39.59 + 44%|████▍ | 246/558 [28:41<35:29, 6.82s/it] {'loss': 3.1048, 'grad_norm': 19.09676742553711, 'learning_rate': 6.193325205415629e-16, 'epoch': 0.13} + 44%|████▍ | 246/558 [28:41<35:29, 6.82s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1888 +[2025-05-15 00:56:46,820] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 346.17 | bwd_microstep: 622.94 | bwd_inner_microstep: 622.87 | bwd_allreduce_microstep: 0.02 | step_microstep: 2.38 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-15 00:56:47,626] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 353.15 | bwd_microstep: 418.51 | bwd_inner_microstep: 418.48 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.87 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-15 00:56:48,621] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 408.15 | bwd_microstep: 559.92 | bwd_inner_microstep: 559.56 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-15 00:56:49,430] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 245.25 | bwd_microstep: 543.72 | bwd_inner_microstep: 543.67 | bwd_allreduce_microstep: 0.02 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-15 00:56:50,341] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 427.05 | bwd_microstep: 450.89 | bwd_inner_microstep: 450.62 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-15 00:56:51,317] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 341.53 | bwd_microstep: 613.68 | bwd_inner_microstep: 613.64 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.60 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-15 00:56:52,104] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 342.91 | bwd_microstep: 407.96 | bwd_inner_microstep: 407.91 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.79 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-15 00:56:53,302] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.10 | optimizer_step: 18.16 +[2025-05-15 00:56:53,303] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 408.14 | bwd_microstep: 739.46 | bwd_inner_microstep: 586.79 | bwd_allreduce_microstep: 152.59 | step_microstep: 26.67 +[2025-05-15 00:56:53,304] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2872.33 | bwd: 4357.11 | bwd_inner: 4203.60 | bwd_allreduce: 152.95 | step: 37.97 + 44%|████▍ | 247/558 [28:48<36:23, 7.02s/it] {'loss': 6.0165, 'grad_norm': 24.19774627685547, 'learning_rate': 6.165109247786624e-16, 'epoch': 0.13} + 44%|████▍ | 247/558 [28:48<36:23, 7.02s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1890 +[2025-05-15 00:56:54,300] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 344.46 | bwd_microstep: 625.85 | bwd_inner_microstep: 625.80 | bwd_allreduce_microstep: 0.02 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1888 +[2025-05-15 00:56:55,074] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 347.71 | bwd_microstep: 392.82 | bwd_inner_microstep: 392.77 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.83 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-15 00:56:56,108] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 399.89 | bwd_microstep: 606.28 | bwd_inner_microstep: 606.24 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.47 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-15 00:56:56,730] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 320.78 | bwd_microstep: 280.47 | bwd_inner_microstep: 280.31 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-15 00:56:57,721] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 354.23 | bwd_microstep: 619.25 | bwd_inner_microstep: 619.21 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.37 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-15 00:56:58,498] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 354.40 | bwd_microstep: 392.06 | bwd_inner_microstep: 392.01 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.83 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-15 00:56:59,526] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 415.21 | bwd_microstep: 586.50 | bwd_inner_microstep: 586.47 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.32 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2164 +[2025-05-15 00:57:00,886] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.01 | optimizer_gradients: 2.07 | optimizer_step: 18.06 +[2025-05-15 00:57:00,887] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 306.22 | bwd_microstep: 1004.97 | bwd_inner_microstep: 601.28 | bwd_allreduce_microstep: 403.66 | step_microstep: 27.38 +[2025-05-15 00:57:00,888] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2842.87 | bwd: 4508.21 | bwd_inner: 4104.13 | bwd_allreduce: 403.78 | step: 40.64 + 44%|████▍ | 248/558 [28:56<37:08, 7.19s/it] {'loss': 5.4769, 'grad_norm': 27.337797164916992, 'learning_rate': 6.13685400118756e-16, 'epoch': 0.13} + 44%|████▍ | 248/558 [28:56<37:08, 7.19s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-15 00:57:01,711] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 258.97 | bwd_microstep: 533.56 | bwd_inner_microstep: 533.51 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.53 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-15 00:57:02,679] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 434.79 | bwd_microstep: 500.03 | bwd_inner_microstep: 499.69 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.21 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-15 00:57:03,584] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 280.03 | bwd_microstep: 604.18 | bwd_inner_microstep: 604.12 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-15 00:57:04,401] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 387.97 | bwd_microstep: 397.08 | bwd_inner_microstep: 396.86 | bwd_allreduce_microstep: 0.19 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-15 00:57:05,431] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 396.96 | bwd_microstep: 607.88 | bwd_inner_microstep: 607.68 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-15 00:57:06,221] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 355.45 | bwd_microstep: 413.98 | bwd_inner_microstep: 413.95 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.76 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-15 00:57:07,221] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 408.89 | bwd_microstep: 563.69 | bwd_inner_microstep: 563.65 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.31 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-15 00:57:08,480] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.52 | optimizer_gradients: 2.13 | optimizer_step: 19.13 +[2025-05-15 00:57:08,481] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 246.60 | bwd_microstep: 962.03 | bwd_inner_microstep: 544.12 | bwd_allreduce_microstep: 417.88 | step_microstep: 28.11 +[2025-05-15 00:57:08,481] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2769.63 | bwd: 4582.63 | bwd_inner: 4163.65 | bwd_allreduce: 418.07 | step: 37.64 + 45%|████▍ | 249/558 [29:04<37:39, 7.31s/it] {'loss': 5.976, 'grad_norm': 25.61820411682129, 'learning_rate': 6.108560418421398e-16, 'epoch': 0.13} + 45%|████▍ | 249/558 [29:04<37:39, 7.31s/it]dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1408 +[2025-05-15 00:57:09,072] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 197.30 | bwd_microstep: 366.93 | bwd_inner_microstep: 366.89 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.81 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1894 +[2025-05-15 00:57:10,106] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 444.31 | bwd_microstep: 561.82 | bwd_inner_microstep: 561.77 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.48 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1395 +[2025-05-15 00:57:10,679] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 170.33 | bwd_microstep: 380.99 | bwd_inner_microstep: 380.74 | bwd_allreduce_microstep: 0.22 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1892 +[2025-05-15 00:57:11,687] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 441.56 | bwd_microstep: 533.99 | bwd_inner_microstep: 533.58 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.42 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-15 00:57:12,520] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 221.12 | bwd_microstep: 588.92 | bwd_inner_microstep: 588.88 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.48 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-15 00:57:13,428] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 414.37 | bwd_microstep: 461.45 | bwd_inner_microstep: 461.25 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.12 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 846 +[2025-05-15 00:57:13,672] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.70 | bwd_microstep: 134.97 | bwd_inner_microstep: 134.77 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-15 00:57:14,899] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.03 | optimizer_step: 14.78 +[2025-05-15 00:57:14,900] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 276.54 | bwd_microstep: 910.56 | bwd_inner_microstep: 613.66 | bwd_allreduce_microstep: 296.87 | step_microstep: 24.59 +[2025-05-15 00:57:14,901] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2260.20 | bwd: 3939.63 | bwd_inner: 3641.62 | bwd_allreduce: 297.37 | step: 34.21 + 45%|████▍ | 250/558 [29:10<36:09, 7.04s/it] {'loss': 4.0046, 'grad_norm': 19.016714096069336, 'learning_rate': 6.080229453583835e-16, 'epoch': 0.13} + 45%|████▍ | 250/558 [29:10<36:09, 7.04s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1900 +[2025-05-15 00:57:15,718] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 241.39 | bwd_microstep: 546.08 | bwd_inner_microstep: 546.01 | bwd_allreduce_microstep: 0.02 | step_microstep: 2.29 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-15 00:57:16,667] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 429.28 | bwd_microstep: 487.43 | bwd_inner_microstep: 487.11 | bwd_allreduce_microstep: 0.16 | step_microstep: 0.10 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 838 +[2025-05-15 00:57:17,031] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 98.18 | bwd_microstep: 248.80 | bwd_inner_microstep: 248.75 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.29 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-15 00:57:18,034] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 405.99 | bwd_microstep: 571.80 | bwd_inner_microstep: 571.75 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-15 00:57:18,825] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 267.29 | bwd_microstep: 501.10 | bwd_inner_microstep: 501.06 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.55 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 839 +[2025-05-15 00:57:19,353] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 217.12 | bwd_microstep: 279.15 | bwd_inner_microstep: 278.90 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.28 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2080 +[2025-05-15 00:57:20,244] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 386.71 | bwd_microstep: 481.65 | bwd_inner_microstep: 481.61 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.85 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1958 +[2025-05-15 00:57:21,454] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.12 | optimizer_step: 17.75 +[2025-05-15 00:57:21,455] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 465.20 | bwd_microstep: 692.85 | bwd_inner_microstep: 575.91 | bwd_allreduce_microstep: 116.71 | step_microstep: 26.36 +[2025-05-15 00:57:21,455] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2511.15 | bwd: 3808.90 | bwd_inner: 3691.35 | bwd_allreduce: 116.94 | step: 34.77 + 45%|████▍ | 251/558 [29:16<35:17, 6.90s/it] {'loss': 5.6583, 'grad_norm': 22.66902732849121, 'learning_rate': 6.051862062031147e-16, 'epoch': 0.14} + 45%|████▍ | 251/558 [29:16<35:17, 6.90s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 355 +[2025-05-15 00:57:21,704] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 89.41 | bwd_microstep: 136.46 | bwd_inner_microstep: 136.43 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.78 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-15 00:57:22,713] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 409.52 | bwd_microstep: 575.10 | bwd_inner_microstep: 575.06 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.90 +dynamic ViT batch size: 6, images per sample: 6.0, dynamic token length: 1618 +[2025-05-15 00:57:23,402] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 233.18 | bwd_microstep: 432.05 | bwd_inner_microstep: 432.00 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-15 00:57:24,400] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 438.89 | bwd_microstep: 524.68 | bwd_inner_microstep: 524.41 | bwd_allreduce_microstep: 0.23 | step_microstep: 0.25 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 336 +[2025-05-15 00:57:24,655] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 91.63 | bwd_microstep: 146.06 | bwd_inner_microstep: 146.02 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.30 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-15 00:57:25,670] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 399.29 | bwd_microstep: 590.34 | bwd_inner_microstep: 590.08 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-15 00:57:26,457] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 318.94 | bwd_microstep: 447.69 | bwd_inner_microstep: 447.29 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-15 00:57:27,614] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.07 | optimizer_step: 18.11 +[2025-05-15 00:57:27,614] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 442.93 | bwd_microstep: 657.27 | bwd_inner_microstep: 541.57 | bwd_allreduce_microstep: 115.47 | step_microstep: 26.81 +[2025-05-15 00:57:27,615] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2423.76 | bwd: 3509.65 | bwd_inner: 3392.87 | bwd_allreduce: 115.88 | step: 32.77 + 45%|████▌ | 252/558 [29:23<34:02, 6.68s/it] {'loss': 4.2534, 'grad_norm': 16.683757781982422, 'learning_rate': 6.023459200347964e-16, 'epoch': 0.14} + 45%|████▌ | 252/558 [29:23<34:02, 6.68s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-15 00:57:28,624] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 366.73 | bwd_microstep: 615.39 | bwd_inner_microstep: 615.35 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.46 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 842 +[2025-05-15 00:57:29,075] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 180.55 | bwd_microstep: 240.44 | bwd_inner_microstep: 240.20 | bwd_allreduce_microstep: 0.20 | step_microstep: 0.21 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 327 +[2025-05-15 00:57:29,331] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 90.64 | bwd_microstep: 146.25 | bwd_inner_microstep: 146.19 | bwd_allreduce_microstep: 0.02 | step_microstep: 1.82 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1097 +[2025-05-15 00:57:29,973] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 231.07 | bwd_microstep: 384.70 | bwd_inner_microstep: 384.64 | bwd_allreduce_microstep: 0.02 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-15 00:57:30,775] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 378.20 | bwd_microstep: 391.00 | bwd_inner_microstep: 390.78 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-15 00:57:31,814] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 395.81 | bwd_microstep: 620.80 | bwd_inner_microstep: 620.58 | bwd_allreduce_microstep: 0.19 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-15 00:57:32,599] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 355.58 | bwd_microstep: 408.88 | bwd_inner_microstep: 408.84 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.29 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-15 00:57:33,830] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.10 | optimizer_step: 17.23 +[2025-05-15 00:57:33,830] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 407.80 | bwd_microstep: 772.64 | bwd_inner_microstep: 564.73 | bwd_allreduce_microstep: 207.87 | step_microstep: 25.80 +[2025-05-15 00:57:33,831] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2406.36 | bwd: 3580.12 | bwd_inner: 3371.35 | bwd_allreduce: 208.32 | step: 33.15 + 45%|████▌ | 253/558 [29:29<33:14, 6.54s/it] {'loss': 4.7424, 'grad_norm': 25.092960357666016, 'learning_rate': 5.995021826315011e-16, 'epoch': 0.14} + 45%|████▌ | 253/558 [29:29<33:14, 6.54s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-15 00:57:34,617] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 339.03 | bwd_microstep: 420.83 | bwd_inner_microstep: 420.66 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.18 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1361 +[2025-05-15 00:57:35,410] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 298.64 | bwd_microstep: 472.29 | bwd_inner_microstep: 472.25 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.52 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 330 +[2025-05-15 00:57:35,684] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 104.12 | bwd_microstep: 139.51 | bwd_inner_microstep: 138.56 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.20 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1357 +[2025-05-15 00:57:36,332] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 261.90 | bwd_microstep: 365.48 | bwd_inner_microstep: 365.33 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-15 00:57:37,237] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 280.72 | bwd_microstep: 604.17 | bwd_inner_microstep: 604.13 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.62 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 323 +[2025-05-15 00:57:37,507] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 101.39 | bwd_microstep: 136.09 | bwd_inner_microstep: 136.04 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.82 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1976 +[2025-05-15 00:57:38,450] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 377.72 | bwd_microstep: 544.95 | bwd_inner_microstep: 544.67 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.26 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1938 +[2025-05-15 00:57:39,796] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.01 | optimizer_gradients: 2.01 | optimizer_step: 18.66 +[2025-05-15 00:57:39,796] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 361.38 | bwd_microstep: 940.92 | bwd_inner_microstep: 459.53 | bwd_allreduce_microstep: 481.37 | step_microstep: 26.13 +[2025-05-15 00:57:39,797] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2124.88 | bwd: 3624.45 | bwd_inner: 3141.25 | bwd_allreduce: 481.54 | step: 32.86 + 46%|████▌ | 254/558 [29:35<32:15, 6.37s/it] {'loss': 5.3661, 'grad_norm': 18.729555130004883, 'learning_rate': 5.966550898876818e-16, 'epoch': 0.14} + 46%|████▌ | 254/558 [29:35<32:15, 6.37s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1895 +[2025-05-15 00:57:40,609] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 275.82 | bwd_microstep: 507.32 | bwd_inner_microstep: 507.28 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.53 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-15 00:57:41,601] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 441.60 | bwd_microstep: 518.31 | bwd_inner_microstep: 518.09 | bwd_allreduce_microstep: 0.19 | step_microstep: 0.17 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 846 +[2025-05-15 00:57:41,915] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 154.39 | bwd_microstep: 142.21 | bwd_inner_microstep: 141.99 | bwd_allreduce_microstep: 0.19 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-15 00:57:42,964] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 395.82 | bwd_microstep: 629.81 | bwd_inner_microstep: 629.77 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.37 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-15 00:57:43,726] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 359.05 | bwd_microstep: 379.38 | bwd_inner_microstep: 379.33 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.80 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-15 00:57:44,766] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 401.86 | bwd_microstep: 612.01 | bwd_inner_microstep: 611.97 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.33 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-15 00:57:45,555] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 295.74 | bwd_microstep: 470.79 | bwd_inner_microstep: 470.75 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-15 00:57:46,637] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.04 | optimizer_step: 17.87 +[2025-05-15 00:57:46,637] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 442.68 | bwd_microstep: 580.99 | bwd_inner_microstep: 504.09 | bwd_allreduce_microstep: 76.79 | step_microstep: 26.14 +[2025-05-15 00:57:46,638] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2766.95 | bwd: 3840.83 | bwd_inner: 3763.30 | bwd_allreduce: 77.21 | step: 35.88 + 46%|████▌ | 255/558 [29:42<32:52, 6.51s/it] {'loss': 4.2603, 'grad_norm': 17.496318817138672, 'learning_rate': 5.938047378109373e-16, 'epoch': 0.14} + 46%|████▌ | 255/558 [29:42<32:52, 6.51s/it]dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1356 +[2025-05-15 00:57:47,333] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 223.53 | bwd_microstep: 446.49 | bwd_inner_microstep: 446.45 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 838 +[2025-05-15 00:57:47,833] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 216.24 | bwd_microstep: 253.60 | bwd_inner_microstep: 253.19 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-15 00:57:48,617] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 317.48 | bwd_microstep: 445.88 | bwd_inner_microstep: 445.66 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-15 00:57:49,630] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 446.75 | bwd_microstep: 536.46 | bwd_inner_microstep: 536.22 | bwd_allreduce_microstep: 0.20 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-15 00:57:50,433] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 246.43 | bwd_microstep: 534.29 | bwd_inner_microstep: 534.25 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-15 00:57:51,360] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 432.43 | bwd_microstep: 460.61 | bwd_inner_microstep: 460.45 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-15 00:57:52,327] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 331.32 | bwd_microstep: 614.65 | bwd_inner_microstep: 614.61 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.31 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-15 00:57:53,481] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.01 | optimizer_gradients: 2.10 | optimizer_step: 17.86 +[2025-05-15 00:57:53,482] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 367.68 | bwd_microstep: 726.51 | bwd_inner_microstep: 519.28 | bwd_allreduce_microstep: 207.21 | step_microstep: 26.92 +[2025-05-15 00:57:53,483] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2581.82 | bwd: 4018.49 | bwd_inner: 3810.14 | bwd_allreduce: 207.70 | step: 34.59 + 46%|████▌ | 256/558 [29:49<33:16, 6.61s/it] {'loss': 6.6977, 'grad_norm': 41.70064163208008, 'learning_rate': 5.909512225187759e-16, 'epoch': 0.14} + 46%|████▌ | 256/558 [29:49<33:16, 6.61s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 355 +[2025-05-15 00:57:53,748] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.26 | bwd_microstep: 144.22 | bwd_inner_microstep: 144.18 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-15 00:57:54,554] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 357.58 | bwd_microstep: 428.23 | bwd_inner_microstep: 428.09 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.09 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1099 +[2025-05-15 00:57:54,884] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 115.99 | bwd_microstep: 198.07 | bwd_inner_microstep: 198.03 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.78 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-15 00:57:55,928] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 406.46 | bwd_microstep: 609.28 | bwd_inner_microstep: 609.24 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.14 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-15 00:57:56,766] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 354.53 | bwd_microstep: 462.75 | bwd_inner_microstep: 462.60 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-15 00:57:57,694] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 305.15 | bwd_microstep: 602.38 | bwd_inner_microstep: 602.34 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-15 00:57:58,618] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 361.86 | bwd_microstep: 526.82 | bwd_inner_microstep: 526.60 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.18 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 2073 +[2025-05-15 00:57:59,910] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 1.73 | optimizer_step: 17.38 +[2025-05-15 00:57:59,911] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 243.57 | bwd_microstep: 1004.22 | bwd_inner_microstep: 627.36 | bwd_allreduce_microstep: 376.83 | step_microstep: 25.93 +[2025-05-15 00:57:59,911] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2240.37 | bwd: 3975.99 | bwd_inner: 3598.47 | bwd_allreduce: 377.00 | step: 32.76 + 46%|████▌ | 257/558 [29:55<32:53, 6.56s/it] {'loss': 5.0639, 'grad_norm': 21.16514778137207, 'learning_rate': 5.880946402353726e-16, 'epoch': 0.14} + 46%|████▌ | 257/558 [29:55<32:53, 6.56s/it]dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1386 +[2025-05-15 00:58:00,497] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 209.27 | bwd_microstep: 349.73 | bwd_inner_microstep: 349.70 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.75 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 334 +[2025-05-15 00:58:00,763] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 97.98 | bwd_microstep: 143.61 | bwd_inner_microstep: 143.56 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-15 00:58:01,707] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 411.12 | bwd_microstep: 500.08 | bwd_inner_microstep: 499.94 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-15 00:58:02,609] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 267.43 | bwd_microstep: 614.75 | bwd_inner_microstep: 614.71 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-15 00:58:03,497] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 327.98 | bwd_microstep: 524.62 | bwd_inner_microstep: 524.26 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-15 00:58:04,289] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 322.03 | bwd_microstep: 450.43 | bwd_inner_microstep: 450.21 | bwd_allreduce_microstep: 0.19 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-15 00:58:05,301] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 441.71 | bwd_microstep: 539.44 | bwd_inner_microstep: 539.22 | bwd_allreduce_microstep: 0.19 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-15 00:58:06,659] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.01 | optimizer_gradients: 2.18 | optimizer_step: 19.21 +[2025-05-15 00:58:06,659] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 356.71 | bwd_microstep: 953.20 | bwd_inner_microstep: 360.43 | bwd_allreduce_microstep: 592.74 | step_microstep: 27.54 +[2025-05-15 00:58:06,660] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2434.20 | bwd: 4075.88 | bwd_inner: 3482.06 | bwd_allreduce: 593.37 | step: 34.68 + 46%|████▌ | 258/558 [30:02<33:03, 6.61s/it] {'loss': 3.6333, 'grad_norm': 31.181116104125977, 'learning_rate': 5.852350872883266e-16, 'epoch': 0.14} + 46%|████▌ | 258/558 [30:02<33:03, 6.61s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1906 +[2025-05-15 00:58:07,496] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 345.84 | bwd_microstep: 462.73 | bwd_inner_microstep: 462.58 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 362 +[2025-05-15 00:58:07,741] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 88.69 | bwd_microstep: 139.17 | bwd_inner_microstep: 139.12 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.75 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1897 +[2025-05-15 00:58:08,760] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 414.55 | bwd_microstep: 578.58 | bwd_inner_microstep: 577.62 | bwd_allreduce_microstep: 0.94 | step_microstep: 0.21 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-15 00:58:09,555] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 349.40 | bwd_microstep: 423.79 | bwd_inner_microstep: 423.55 | bwd_allreduce_microstep: 0.08 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-15 00:58:10,556] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 359.27 | bwd_microstep: 621.14 | bwd_inner_microstep: 621.10 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.43 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-15 00:58:11,375] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 361.42 | bwd_microstep: 430.09 | bwd_inner_microstep: 429.95 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.09 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1355 +[2025-05-15 00:58:11,804] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 142.77 | bwd_microstep: 269.96 | bwd_inner_microstep: 269.92 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.78 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-15 00:58:13,079] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.06 | optimizer_step: 17.79 +[2025-05-15 00:58:13,080] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 431.95 | bwd_microstep: 791.67 | bwd_inner_microstep: 581.09 | bwd_allreduce_microstep: 210.54 | step_microstep: 27.16 +[2025-05-15 00:58:13,081] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2493.84 | bwd: 3717.16 | bwd_inner: 3505.04 | bwd_allreduce: 211.69 | step: 33.63 + 46%|████▋ | 259/558 [30:08<32:40, 6.56s/it] {'loss': 3.6261, 'grad_norm': 14.556857109069824, 'learning_rate': 5.823726601054105e-16, 'epoch': 0.14} + 46%|████▋ | 259/558 [30:08<32:40, 6.56s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1935 +[2025-05-15 00:58:13,954] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 265.11 | bwd_microstep: 579.57 | bwd_inner_microstep: 579.53 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.53 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-15 00:58:14,929] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 428.58 | bwd_microstep: 513.16 | bwd_inner_microstep: 513.12 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.25 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-15 00:58:15,713] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 357.47 | bwd_microstep: 405.53 | bwd_inner_microstep: 405.50 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.28 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-15 00:58:16,713] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 406.04 | bwd_microstep: 569.82 | bwd_inner_microstep: 569.78 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.22 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-15 00:58:17,505] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 345.23 | bwd_microstep: 424.75 | bwd_inner_microstep: 424.43 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.22 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 834 +[2025-05-15 00:58:17,947] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 161.26 | bwd_microstep: 261.24 | bwd_inner_microstep: 261.21 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.54 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-15 00:58:18,920] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 443.08 | bwd_microstep: 495.61 | bwd_inner_microstep: 495.45 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1946 +[2025-05-15 00:58:20,175] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.06 | optimizer_step: 18.34 +[2025-05-15 00:58:20,176] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 292.42 | bwd_microstep: 917.91 | bwd_inner_microstep: 640.62 | bwd_allreduce_microstep: 277.26 | step_microstep: 27.23 +[2025-05-15 00:58:20,176] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2699.16 | bwd: 4167.65 | bwd_inner: 3889.71 | bwd_allreduce: 277.50 | step: 33.39 + 47%|████▋ | 260/558 [30:15<33:21, 6.72s/it] {'loss': 5.6252, 'grad_norm': 34.048118591308594, 'learning_rate': 5.795074552113204e-16, 'epoch': 0.14} + 47%|████▋ | 260/558 [30:15<33:21, 6.72s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1938 +[2025-05-15 00:58:21,064] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 230.89 | bwd_microstep: 628.07 | bwd_inner_microstep: 628.04 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.45 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1935 +[2025-05-15 00:58:22,063] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 416.21 | bwd_microstep: 548.56 | bwd_inner_microstep: 548.51 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1889 +[2025-05-15 00:58:22,942] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 244.91 | bwd_microstep: 609.94 | bwd_inner_microstep: 609.90 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 337 +[2025-05-15 00:58:23,217] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 103.71 | bwd_microstep: 139.92 | bwd_inner_microstep: 139.86 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.22 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-15 00:58:24,010] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 355.12 | bwd_microstep: 414.55 | bwd_inner_microstep: 414.52 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.78 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 838 +[2025-05-15 00:58:24,524] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.78 | bwd_microstep: 300.42 | bwd_inner_microstep: 300.37 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-15 00:58:25,453] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 383.37 | bwd_microstep: 512.91 | bwd_inner_microstep: 512.87 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.25 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-15 00:58:26,795] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.01 | optimizer_gradients: 2.19 | optimizer_step: 18.64 +[2025-05-15 00:58:26,796] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 343.94 | bwd_microstep: 950.24 | bwd_inner_microstep: 405.53 | bwd_allreduce_microstep: 544.68 | step_microstep: 27.64 +[2025-05-15 00:58:26,797] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2264.91 | bwd: 4104.61 | bwd_inner: 3559.60 | bwd_allreduce: 544.75 | step: 37.24 + 47%|████▋ | 261/558 [30:22<33:06, 6.69s/it] {'loss': 3.6292, 'grad_norm': 24.88662338256836, 'learning_rate': 5.766395692244202e-16, 'epoch': 0.14} + 47%|████▋ | 261/558 [30:22<33:06, 6.69s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1916 +[2025-05-15 00:58:27,584] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 294.85 | bwd_microstep: 463.48 | bwd_inner_microstep: 463.29 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-15 00:58:28,590] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 417.42 | bwd_microstep: 571.85 | bwd_inner_microstep: 571.81 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.16 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1362 +[2025-05-15 00:58:29,240] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 258.30 | bwd_microstep: 371.78 | bwd_inner_microstep: 371.60 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 844 +[2025-05-15 00:58:29,618] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 102.65 | bwd_microstep: 259.02 | bwd_inner_microstep: 258.98 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.77 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1351 +[2025-05-15 00:58:30,402] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 301.47 | bwd_microstep: 456.92 | bwd_inner_microstep: 456.71 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.42 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-15 00:58:31,274] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 352.35 | bwd_microstep: 497.09 | bwd_inner_microstep: 496.94 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-15 00:58:32,152] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 259.40 | bwd_microstep: 596.66 | bwd_inner_microstep: 596.62 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1925 +[2025-05-15 00:58:33,332] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.10 | optimizer_step: 18.07 +[2025-05-15 00:58:33,333] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 402.77 | bwd_microstep: 716.70 | bwd_inner_microstep: 541.08 | bwd_allreduce_microstep: 175.57 | step_microstep: 26.65 +[2025-05-15 00:58:33,333] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2389.16 | bwd: 3933.54 | bwd_inner: 3754.86 | bwd_allreduce: 175.81 | step: 33.44 + 47%|████▋ | 262/558 [30:28<32:46, 6.64s/it] {'loss': 7.1546, 'grad_norm': 22.124664306640625, 'learning_rate': 5.737690988534837e-16, 'epoch': 0.14} + 47%|████▋ | 262/558 [30:28<32:46, 6.64s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1975 +[2025-05-15 00:58:34,373] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 358.78 | bwd_microstep: 654.91 | bwd_inner_microstep: 654.87 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 368 +[2025-05-15 00:58:34,641] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 107.49 | bwd_microstep: 137.36 | bwd_inner_microstep: 137.31 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.19 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 345 +[2025-05-15 00:58:34,888] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.97 | bwd_microstep: 134.22 | bwd_inner_microstep: 133.99 | bwd_allreduce_microstep: 0.18 | step_microstep: 0.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-15 00:58:35,938] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 397.81 | bwd_microstep: 627.73 | bwd_inner_microstep: 627.70 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.31 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-15 00:58:36,718] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 241.98 | bwd_microstep: 517.90 | bwd_inner_microstep: 517.69 | bwd_allreduce_microstep: 0.18 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-15 00:58:37,493] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 359.99 | bwd_microstep: 395.70 | bwd_inner_microstep: 395.49 | bwd_allreduce_microstep: 0.18 | step_microstep: 0.18 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1345 +[2025-05-15 00:58:38,277] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 277.75 | bwd_microstep: 481.94 | bwd_inner_microstep: 481.90 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-15 00:58:39,426] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.92 | optimizer_gradients: 2.11 | optimizer_step: 18.45 +[2025-05-15 00:58:39,426] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 370.05 | bwd_microstep: 720.17 | bwd_inner_microstep: 512.20 | bwd_allreduce_microstep: 207.93 | step_microstep: 27.01 +[2025-05-15 00:58:39,427] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2208.79 | bwd: 3669.94 | bwd_inner: 3461.17 | bwd_allreduce: 208.35 | step: 34.74 + 47%|████▋ | 263/558 [30:34<31:50, 6.48s/it] {'loss': 3.7424, 'grad_norm': 21.841594696044922, 'learning_rate': 5.708961408944333e-16, 'epoch': 0.14} + 47%|████▋ | 263/558 [30:34<31:50, 6.48s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1901 +[2025-05-15 00:58:40,246] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 259.71 | bwd_microstep: 531.11 | bwd_inner_microstep: 531.07 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-15 00:58:41,188] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 441.90 | bwd_microstep: 467.32 | bwd_inner_microstep: 467.18 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-15 00:58:42,155] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 328.92 | bwd_microstep: 617.87 | bwd_inner_microstep: 617.83 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-15 00:58:42,946] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 366.76 | bwd_microstep: 387.65 | bwd_inner_microstep: 387.62 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.82 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 844 +[2025-05-15 00:58:43,472] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 196.79 | bwd_microstep: 301.39 | bwd_inner_microstep: 301.34 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-15 00:58:44,367] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 408.87 | bwd_microstep: 453.55 | bwd_inner_microstep: 453.20 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-15 00:58:45,341] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 342.22 | bwd_microstep: 610.36 | bwd_inner_microstep: 610.33 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.45 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-15 00:58:46,715] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.03 | optimizer_step: 18.09 +[2025-05-15 00:58:46,715] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 345.84 | bwd_microstep: 968.82 | bwd_inner_microstep: 385.60 | bwd_allreduce_microstep: 583.17 | step_microstep: 27.16 +[2025-05-15 00:58:46,716] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2690.98 | bwd: 4338.11 | bwd_inner: 3754.27 | bwd_allreduce: 583.40 | step: 38.79 + 47%|████▋ | 264/558 [30:42<32:56, 6.72s/it] {'loss': 5.5687, 'grad_norm': 24.968435287475586, 'learning_rate': 5.680207922270762e-16, 'epoch': 0.14} + 47%|████▋ | 264/558 [30:42<32:56, 6.72s/it]dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 881 +[2025-05-15 00:58:47,163] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 172.84 | bwd_microstep: 249.93 | bwd_inner_microstep: 249.91 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.26 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1891 +[2025-05-15 00:58:47,949] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 312.75 | bwd_microstep: 452.36 | bwd_inner_microstep: 452.12 | bwd_allreduce_microstep: 0.02 | step_microstep: 2.61 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1899 +[2025-05-15 00:58:48,968] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 448.83 | bwd_microstep: 535.96 | bwd_inner_microstep: 535.75 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.25 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1896 +[2025-05-15 00:58:49,745] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 359.88 | bwd_microstep: 395.23 | bwd_inner_microstep: 395.19 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.85 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1886 +[2025-05-15 00:58:50,795] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 405.54 | bwd_microstep: 617.32 | bwd_inner_microstep: 617.28 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.96 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-15 00:58:51,647] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 356.52 | bwd_microstep: 473.87 | bwd_inner_microstep: 473.52 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-15 00:58:52,584] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 308.45 | bwd_microstep: 607.90 | bwd_inner_microstep: 607.87 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.48 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-15 00:58:53,637] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.10 | optimizer_step: 18.04 +[2025-05-15 00:58:53,638] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 346.16 | bwd_microstep: 648.47 | bwd_inner_microstep: 530.60 | bwd_allreduce_microstep: 117.81 | step_microstep: 26.97 +[2025-05-15 00:58:53,639] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2710.94 | bwd: 3981.07 | bwd_inner: 3862.28 | bwd_allreduce: 118.00 | step: 36.34 + 47%|████▋ | 265/558 [30:49<33:07, 6.78s/it] {'loss': 3.9921, 'grad_norm': 12.000906944274902, 'learning_rate': 5.651431498118372e-16, 'epoch': 0.14} + 47%|████▋ | 265/558 [30:49<33:07, 6.78s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1889 +[2025-05-15 00:58:54,640] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 353.27 | bwd_microstep: 620.12 | bwd_inner_microstep: 620.07 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-15 00:58:55,505] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 358.68 | bwd_microstep: 474.27 | bwd_inner_microstep: 474.01 | bwd_allreduce_microstep: 0.08 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-15 00:58:56,445] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 309.16 | bwd_microstep: 609.78 | bwd_inner_microstep: 609.75 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.54 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-15 00:58:57,370] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 376.63 | bwd_microstep: 516.07 | bwd_inner_microstep: 516.04 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.26 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-15 00:58:58,152] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 273.17 | bwd_microstep: 487.17 | bwd_inner_microstep: 487.13 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.28 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-15 00:58:59,161] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 445.28 | bwd_microstep: 530.46 | bwd_inner_microstep: 530.40 | bwd_allreduce_microstep: 0.02 | step_microstep: 1.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-15 00:58:59,937] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 343.54 | bwd_microstep: 410.51 | bwd_inner_microstep: 410.45 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.86 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 320 +[2025-05-15 00:59:00,649] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.01 | optimizer_gradients: 2.01 | optimizer_step: 17.77 +[2025-05-15 00:59:00,649] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 88.71 | bwd_microstep: 573.94 | bwd_inner_microstep: 160.72 | bwd_allreduce_microstep: 413.18 | step_microstep: 26.37 +[2025-05-15 00:59:00,650] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2548.39 | bwd: 4222.33 | bwd_inner: 3808.67 | bwd_allreduce: 413.33 | step: 36.84 + 48%|████▊ | 266/558 [30:56<33:20, 6.85s/it] {'loss': 5.2314, 'grad_norm': 28.287038803100586, 'learning_rate': 5.622633106864895e-16, 'epoch': 0.14} + 48%|████▊ | 266/558 [30:56<33:20, 6.85s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1938 +[2025-05-15 00:59:01,443] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 351.35 | bwd_microstep: 413.66 | bwd_inner_microstep: 413.61 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.78 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1901 +[2025-05-15 00:59:02,480] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 400.74 | bwd_microstep: 612.03 | bwd_inner_microstep: 612.00 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.29 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1900 +[2025-05-15 00:59:03,261] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 304.76 | bwd_microstep: 453.89 | bwd_inner_microstep: 453.84 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.52 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 335 +[2025-05-15 00:59:03,540] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 103.58 | bwd_microstep: 143.14 | bwd_inner_microstep: 143.11 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-15 00:59:04,494] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 397.15 | bwd_microstep: 521.31 | bwd_inner_microstep: 521.25 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-15 00:59:05,306] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 352.68 | bwd_microstep: 437.68 | bwd_inner_microstep: 437.52 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-15 00:59:06,283] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 344.81 | bwd_microstep: 613.38 | bwd_inner_microstep: 613.32 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.43 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-15 00:59:07,336] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.06 | optimizer_step: 17.96 +[2025-05-15 00:59:07,337] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 347.64 | bwd_microstep: 647.14 | bwd_inner_microstep: 514.35 | bwd_allreduce_microstep: 132.73 | step_microstep: 26.44 +[2025-05-15 00:59:07,337] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2602.71 | bwd: 3842.24 | bwd_inner: 3709.04 | bwd_allreduce: 132.88 | step: 37.27 + 48%|████▊ | 267/558 [31:02<32:59, 6.80s/it] {'loss': 5.6053, 'grad_norm': 24.04661750793457, 'learning_rate': 5.593813719628818e-16, 'epoch': 0.14} + 48%|████▊ | 267/558 [31:02<32:59, 6.80s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1890 +[2025-05-15 00:59:08,327] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 344.36 | bwd_microstep: 619.44 | bwd_inner_microstep: 619.40 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 337 +[2025-05-15 00:59:08,594] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 100.83 | bwd_microstep: 135.69 | bwd_inner_microstep: 135.49 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-15 00:59:09,394] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 358.31 | bwd_microstep: 421.77 | bwd_inner_microstep: 421.63 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-15 00:59:10,404] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 361.11 | bwd_microstep: 628.81 | bwd_inner_microstep: 628.78 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.56 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-15 00:59:11,185] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 360.71 | bwd_microstep: 386.55 | bwd_inner_microstep: 386.48 | bwd_allreduce_microstep: 0.02 | step_microstep: 1.83 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-15 00:59:12,224] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 399.69 | bwd_microstep: 615.09 | bwd_inner_microstep: 615.07 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.26 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-15 00:59:12,986] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 341.48 | bwd_microstep: 398.29 | bwd_inner_microstep: 398.25 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.81 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-15 00:59:14,245] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.01 | optimizer_gradients: 2.17 | optimizer_step: 17.86 +[2025-05-15 00:59:14,245] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 399.71 | bwd_microstep: 806.33 | bwd_inner_microstep: 602.56 | bwd_allreduce_microstep: 203.74 | step_microstep: 28.11 +[2025-05-15 00:59:14,246] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2666.18 | bwd: 4011.99 | bwd_inner: 3807.68 | bwd_allreduce: 203.87 | step: 36.27 + 48%|████▊ | 268/558 [31:09<33:01, 6.83s/it] {'loss': 5.5572, 'grad_norm': 22.051433563232422, 'learning_rate': 5.564974308236642e-16, 'epoch': 0.14} + 48%|████▊ | 268/558 [31:09<33:01, 6.83s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1964 +[2025-05-15 00:59:15,099] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 354.05 | bwd_microstep: 473.83 | bwd_inner_microstep: 473.53 | bwd_allreduce_microstep: 0.14 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1889 +[2025-05-15 00:59:16,091] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 351.55 | bwd_microstep: 618.48 | bwd_inner_microstep: 618.44 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.33 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-15 00:59:17,008] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 364.84 | bwd_microstep: 520.07 | bwd_inner_microstep: 520.02 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.25 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-15 00:59:17,669] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 329.84 | bwd_microstep: 308.24 | bwd_inner_microstep: 308.20 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.82 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 846 +[2025-05-15 00:59:18,194] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 198.81 | bwd_microstep: 298.40 | bwd_inner_microstep: 298.37 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.33 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-15 00:59:19,160] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 408.89 | bwd_microstep: 521.99 | bwd_inner_microstep: 521.78 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-15 00:59:19,957] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 282.48 | bwd_microstep: 492.91 | bwd_inner_microstep: 492.87 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-15 00:59:21,183] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.01 | optimizer_gradients: 2.16 | optimizer_step: 18.49 +[2025-05-15 00:59:21,183] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 435.62 | bwd_microstep: 727.94 | bwd_inner_microstep: 521.44 | bwd_allreduce_microstep: 206.46 | step_microstep: 28.05 +[2025-05-15 00:59:21,184] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2726.05 | bwd: 3961.87 | bwd_inner: 3754.72 | bwd_allreduce: 206.64 | step: 37.42 + 48%|████▊ | 269/558 [31:16<33:04, 6.87s/it] {'loss': 4.6943, 'grad_norm': 24.78156852722168, 'learning_rate': 5.5361158451901055e-16, 'epoch': 0.14} + 48%|████▊ | 269/558 [31:16<33:04, 6.87s/it]dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1368 +[2025-05-15 00:59:21,746] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 253.23 | bwd_microstep: 280.21 | bwd_inner_microstep: 280.16 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.78 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 856 +[2025-05-15 00:59:22,272] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 180.88 | bwd_microstep: 317.51 | bwd_inner_microstep: 317.45 | bwd_allreduce_microstep: 0.02 | step_microstep: 2.55 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1363 +[2025-05-15 00:59:22,998] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 297.14 | bwd_microstep: 394.46 | bwd_inner_microstep: 394.23 | bwd_allreduce_microstep: 0.19 | step_microstep: 0.24 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-15 00:59:23,797] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 246.05 | bwd_microstep: 533.13 | bwd_inner_microstep: 533.09 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.54 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-15 00:59:24,786] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 444.04 | bwd_microstep: 512.05 | bwd_inner_microstep: 511.67 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-15 00:59:25,542] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 283.52 | bwd_microstep: 453.24 | bwd_inner_microstep: 453.10 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-15 00:59:26,484] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 322.05 | bwd_microstep: 604.63 | bwd_inner_microstep: 604.24 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-15 00:59:27,844] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.06 | optimizer_step: 19.22 +[2025-05-15 00:59:27,845] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 355.20 | bwd_microstep: 957.66 | bwd_inner_microstep: 381.95 | bwd_allreduce_microstep: 575.68 | step_microstep: 27.43 +[2025-05-15 00:59:27,846] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2382.09 | bwd: 4052.89 | bwd_inner: 3475.92 | bwd_allreduce: 576.33 | step: 34.99 + 48%|████▊ | 270/558 [31:23<32:39, 6.80s/it] {'loss': 5.3852, 'grad_norm': 20.612918853759766, 'learning_rate': 5.507239303633396e-16, 'epoch': 0.15} + 48%|████▊ | 270/558 [31:23<32:39, 6.80s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-15 00:59:28,610] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 345.16 | bwd_microstep: 391.86 | bwd_inner_microstep: 391.84 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.81 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 335 +[2025-05-15 00:59:28,890] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.16 | bwd_microstep: 155.66 | bwd_inner_microstep: 155.61 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-15 00:59:29,878] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 443.20 | bwd_microstep: 513.44 | bwd_inner_microstep: 513.40 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-15 00:59:30,667] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 324.15 | bwd_microstep: 445.68 | bwd_inner_microstep: 445.46 | bwd_allreduce_microstep: 0.19 | step_microstep: 0.04 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 833 +[2025-05-15 00:59:31,211] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 214.39 | bwd_microstep: 299.93 | bwd_inner_microstep: 299.88 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 6, images per sample: 6.0, dynamic token length: 1800 +[2025-05-15 00:59:31,998] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 321.62 | bwd_microstep: 432.58 | bwd_inner_microstep: 432.54 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.86 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1966 +[2025-05-15 00:59:33,074] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 470.00 | bwd_microstep: 574.22 | bwd_inner_microstep: 574.17 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.31 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1915 +[2025-05-15 00:59:34,419] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.01 | optimizer_gradients: 2.05 | optimizer_step: 18.45 +[2025-05-15 00:59:34,420] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 346.52 | bwd_microstep: 951.79 | bwd_inner_microstep: 427.48 | bwd_allreduce_microstep: 524.28 | step_microstep: 28.03 +[2025-05-15 00:59:34,421] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2560.21 | bwd: 3765.17 | bwd_inner: 3240.37 | bwd_allreduce: 524.53 | step: 36.96 + 49%|████▊ | 271/558 [31:29<32:13, 6.74s/it] {'loss': 4.8726, 'grad_norm': 26.86125373840332, 'learning_rate': 5.478345657320329e-16, 'epoch': 0.15} + 49%|████▊ | 271/558 [31:29<32:13, 6.74s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1889 +[2025-05-15 00:59:35,283] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 234.03 | bwd_microstep: 597.76 | bwd_inner_microstep: 597.72 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.53 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-15 00:59:36,227] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 406.32 | bwd_microstep: 504.30 | bwd_inner_microstep: 504.07 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.92 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1387 +[2025-05-15 00:59:36,794] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 229.41 | bwd_microstep: 317.89 | bwd_inner_microstep: 317.83 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.80 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-15 00:59:37,825] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 411.92 | bwd_microstep: 594.67 | bwd_inner_microstep: 594.64 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-15 00:59:38,596] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 357.89 | bwd_microstep: 391.00 | bwd_inner_microstep: 390.96 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.86 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-15 00:59:39,624] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 398.95 | bwd_microstep: 603.65 | bwd_inner_microstep: 603.60 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.25 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 323 +[2025-05-15 00:59:39,876] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 91.95 | bwd_microstep: 141.70 | bwd_inner_microstep: 141.66 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-15 00:59:41,162] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 1.76 | optimizer_step: 16.46 +[2025-05-15 00:59:41,163] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 310.38 | bwd_microstep: 930.17 | bwd_inner_microstep: 447.69 | bwd_allreduce_microstep: 482.45 | step_microstep: 25.74 +[2025-05-15 00:59:41,164] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2440.84 | bwd: 4081.34 | bwd_inner: 3598.17 | bwd_allreduce: 482.53 | step: 33.47 + 49%|████▊ | 272/558 [31:36<32:07, 6.74s/it] {'loss': 6.036, 'grad_norm': 24.78493309020996, 'learning_rate': 5.449435880581513e-16, 'epoch': 0.15} + 49%|████▊ | 272/558 [31:36<32:07, 6.74s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1893 +[2025-05-15 00:59:41,942] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 346.50 | bwd_microstep: 404.06 | bwd_inner_microstep: 404.02 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.28 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 357 +[2025-05-15 00:59:42,201] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 100.28 | bwd_microstep: 133.49 | bwd_inner_microstep: 133.46 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.50 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 362 +[2025-05-15 00:59:42,497] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 108.91 | bwd_microstep: 153.85 | bwd_inner_microstep: 153.81 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-15 00:59:43,450] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 387.58 | bwd_microstep: 531.23 | bwd_inner_microstep: 531.19 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.31 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-15 00:59:44,329] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 354.25 | bwd_microstep: 503.81 | bwd_inner_microstep: 503.51 | bwd_allreduce_microstep: 0.25 | step_microstep: 0.27 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 332 +[2025-05-15 00:59:44,569] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.51 | bwd_microstep: 124.42 | bwd_inner_microstep: 124.40 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.97 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 316 +[2025-05-15 00:59:44,814] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 79.25 | bwd_microstep: 150.24 | bwd_inner_microstep: 150.18 | bwd_allreduce_microstep: 0.02 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-15 00:59:46,089] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.01 | optimizer_gradients: 2.09 | optimizer_step: 18.56 +[2025-05-15 00:59:46,090] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 418.81 | bwd_microstep: 803.76 | bwd_inner_microstep: 595.96 | bwd_allreduce_microstep: 207.76 | step_microstep: 27.52 +[2025-05-15 00:59:46,090] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 1891.07 | bwd: 2804.85 | bwd_inner: 2596.55 | bwd_allreduce: 207.16 | step: 39.55 + 49%|████▉ | 273/558 [31:41<29:25, 6.19s/it] {'loss': 5.5465, 'grad_norm': 28.8708553314209, 'learning_rate': 5.420510948291502e-16, 'epoch': 0.15} + 49%|████▉ | 273/558 [31:41<29:25, 6.19s/it]dynamic ViT batch size: 6, images per sample: 6.0, dynamic token length: 1678 +[2025-05-15 00:59:46,921] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 319.28 | bwd_microstep: 487.25 | bwd_inner_microstep: 487.19 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.24 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1896 +[2025-05-15 00:59:47,702] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 359.28 | bwd_microstep: 401.38 | bwd_inner_microstep: 401.14 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1907 +[2025-05-15 00:59:48,771] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 397.70 | bwd_microstep: 645.86 | bwd_inner_microstep: 645.82 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.47 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-15 00:59:49,661] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 360.19 | bwd_microstep: 509.79 | bwd_inner_microstep: 509.76 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.21 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-15 00:59:50,338] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 346.69 | bwd_microstep: 312.07 | bwd_inner_microstep: 311.73 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-15 00:59:51,373] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 361.21 | bwd_microstep: 652.12 | bwd_inner_microstep: 652.08 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-15 00:59:52,265] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 357.78 | bwd_microstep: 512.41 | bwd_inner_microstep: 512.19 | bwd_allreduce_microstep: 0.18 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-15 00:59:53,376] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.11 | optimizer_step: 18.25 +[2025-05-15 00:59:53,376] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 353.93 | bwd_microstep: 709.49 | bwd_inner_microstep: 505.04 | bwd_allreduce_microstep: 204.42 | step_microstep: 27.23 +[2025-05-15 00:59:53,377] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2856.07 | bwd: 4230.40 | bwd_inner: 4025.03 | bwd_allreduce: 204.80 | step: 33.09 + 49%|████▉ | 274/558 [31:48<30:52, 6.52s/it] {'loss': 5.5145, 'grad_norm': 31.663747787475586, 'learning_rate': 5.391571835835907e-16, 'epoch': 0.15} + 49%|████▉ | 274/558 [31:48<30:52, 6.52s/it]dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 941 +[2025-05-15 00:59:53,867] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 197.36 | bwd_microstep: 269.58 | bwd_inner_microstep: 269.38 | bwd_allreduce_microstep: 0.18 | step_microstep: 0.24 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 925 +[2025-05-15 00:59:54,347] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 194.83 | bwd_microstep: 266.46 | bwd_inner_microstep: 266.28 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1915 +[2025-05-15 00:59:55,244] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 258.73 | bwd_microstep: 616.69 | bwd_inner_microstep: 616.63 | bwd_allreduce_microstep: 0.02 | step_microstep: 2.54 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-15 00:59:56,196] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 393.67 | bwd_microstep: 523.13 | bwd_inner_microstep: 523.09 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.32 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-15 00:59:57,084] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 357.60 | bwd_microstep: 510.06 | bwd_inner_microstep: 509.83 | bwd_allreduce_microstep: 0.19 | step_microstep: 0.26 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-15 00:59:57,924] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 357.36 | bwd_microstep: 463.42 | bwd_inner_microstep: 463.12 | bwd_allreduce_microstep: 0.14 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-15 00:59:58,450] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 196.57 | bwd_microstep: 310.41 | bwd_inner_microstep: 310.37 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.67 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-15 00:59:59,716] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.01 | optimizer_gradients: 2.05 | optimizer_step: 18.30 +[2025-05-15 00:59:59,717] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 401.34 | bwd_microstep: 812.98 | bwd_inner_microstep: 604.91 | bwd_allreduce_microstep: 208.03 | step_microstep: 27.49 +[2025-05-15 00:59:59,717] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2357.43 | bwd: 3772.74 | bwd_inner: 3563.73 | bwd_allreduce: 208.44 | step: 34.74 + 49%|████▉ | 275/558 [31:55<30:30, 6.47s/it] {'loss': 5.1233, 'grad_norm': 26.227270126342773, 'learning_rate': 5.362619519078514e-16, 'epoch': 0.15} + 49%|████▉ | 275/558 [31:55<30:30, 6.47s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1911 +[2025-05-15 01:00:00,625] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 364.20 | bwd_microstep: 516.38 | bwd_inner_microstep: 516.11 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.95 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1907 +[2025-05-15 01:00:01,515] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 359.00 | bwd_microstep: 512.34 | bwd_inner_microstep: 511.35 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.26 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1900 +[2025-05-15 01:00:02,316] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 351.84 | bwd_microstep: 428.44 | bwd_inner_microstep: 428.29 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-15 01:00:03,327] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 362.76 | bwd_microstep: 628.00 | bwd_inner_microstep: 627.96 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.28 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-15 01:00:04,218] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 343.97 | bwd_microstep: 514.62 | bwd_inner_microstep: 513.83 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.24 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-15 01:00:05,097] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 348.36 | bwd_microstep: 508.78 | bwd_inner_microstep: 508.75 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.96 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-15 01:00:05,980] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 345.57 | bwd_microstep: 516.76 | bwd_inner_microstep: 516.71 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.29 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1949 +[2025-05-15 01:00:07,319] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.01 | optimizer_gradients: 1.99 | optimizer_step: 18.57 +[2025-05-15 01:00:07,320] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 314.74 | bwd_microstep: 977.91 | bwd_inner_microstep: 464.67 | bwd_allreduce_microstep: 513.21 | step_microstep: 27.15 +[2025-05-15 01:00:07,320] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2790.45 | bwd: 4603.23 | bwd_inner: 4088.44 | bwd_allreduce: 513.15 | step: 32.24 + 49%|████▉ | 276/558 [32:02<31:59, 6.81s/it] {'loss': 3.5137, 'grad_norm': 12.473506927490234, 'learning_rate': 5.333654974328378e-16, 'epoch': 0.15} + 49%|████▉ | 276/558 [32:02<31:59, 6.81s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1952 +[2025-05-15 01:00:08,258] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 352.79 | bwd_microstep: 557.50 | bwd_inner_microstep: 557.29 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.17 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 379 +[2025-05-15 01:00:08,511] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 100.42 | bwd_microstep: 133.46 | bwd_inner_microstep: 133.42 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.47 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-15 01:00:09,394] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 359.04 | bwd_microstep: 502.53 | bwd_inner_microstep: 502.49 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.76 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 337 +[2025-05-15 01:00:09,634] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 91.09 | bwd_microstep: 130.22 | bwd_inner_microstep: 130.00 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-15 01:00:10,426] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 320.54 | bwd_microstep: 451.65 | bwd_inner_microstep: 451.31 | bwd_allreduce_microstep: 0.28 | step_microstep: 0.18 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1347 +[2025-05-15 01:00:11,235] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 331.54 | bwd_microstep: 445.69 | bwd_inner_microstep: 445.30 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-15 01:00:12,114] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 357.71 | bwd_microstep: 501.24 | bwd_inner_microstep: 501.20 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.24 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-15 01:00:13,233] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.07 | optimizer_step: 29.36 +[2025-05-15 01:00:13,234] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 356.43 | bwd_microstep: 704.99 | bwd_inner_microstep: 498.71 | bwd_allreduce_microstep: 206.22 | step_microstep: 38.32 +[2025-05-15 01:00:13,235] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2269.56 | bwd: 3427.28 | bwd_inner: 3219.73 | bwd_allreduce: 206.87 | step: 42.52 + 50%|████▉ | 277/558 [32:08<30:37, 6.54s/it] {'loss': 6.3813, 'grad_norm': 35.466373443603516, 'learning_rate': 5.304679178306894e-16, 'epoch': 0.15} + 50%|████▉ | 277/558 [32:08<30:37, 6.54s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1888 +[2025-05-15 01:00:14,172] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 296.22 | bwd_microstep: 614.07 | bwd_inner_microstep: 614.04 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.48 +dynamic ViT batch size: 6, images per sample: 6.0, dynamic token length: 1619 +[2025-05-15 01:00:14,958] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 289.44 | bwd_microstep: 459.89 | bwd_inner_microstep: 459.86 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.31 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-15 01:00:15,838] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 347.80 | bwd_microstep: 508.91 | bwd_inner_microstep: 508.67 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.22 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-15 01:00:16,717] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 355.63 | bwd_microstep: 502.29 | bwd_inner_microstep: 502.03 | bwd_allreduce_microstep: 0.24 | step_microstep: 0.27 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-15 01:00:17,593] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 357.80 | bwd_microstep: 498.16 | bwd_inner_microstep: 497.40 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.23 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-15 01:00:18,400] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 283.09 | bwd_microstep: 501.63 | bwd_inner_microstep: 501.58 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.28 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-15 01:00:19,400] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 444.85 | bwd_microstep: 522.71 | bwd_inner_microstep: 522.47 | bwd_allreduce_microstep: 0.20 | step_microstep: 0.26 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-15 01:00:20,512] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.00 | optimizer_step: 18.46 +[2025-05-15 01:00:20,513] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 355.82 | bwd_microstep: 711.49 | bwd_inner_microstep: 501.13 | bwd_allreduce_microstep: 210.12 | step_microstep: 27.14 +[2025-05-15 01:00:20,514] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2730.63 | bwd: 4319.16 | bwd_inner: 4107.18 | bwd_allreduce: 210.92 | step: 35.20 + 50%|████▉ | 278/558 [32:16<31:33, 6.76s/it] {'loss': 5.2254, 'grad_norm': 26.78353500366211, 'learning_rate': 5.275693108114868e-16, 'epoch': 0.15} + 50%|████▉ | 278/558 [32:16<31:33, 6.76s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1912 +[2025-05-15 01:00:21,327] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 294.68 | bwd_microstep: 489.67 | bwd_inner_microstep: 489.62 | bwd_allreduce_microstep: 0.02 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1887 +[2025-05-15 01:00:22,345] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 448.14 | bwd_microstep: 536.81 | bwd_inner_microstep: 536.77 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.80 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1892 +[2025-05-15 01:00:23,057] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 341.00 | bwd_microstep: 349.45 | bwd_inner_microstep: 349.06 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 334 +[2025-05-15 01:00:23,299] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 90.04 | bwd_microstep: 132.21 | bwd_inner_microstep: 132.18 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.78 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-15 01:00:24,317] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 440.92 | bwd_microstep: 544.55 | bwd_inner_microstep: 544.49 | bwd_allreduce_microstep: 0.02 | step_microstep: 2.32 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-15 01:00:25,078] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 358.01 | bwd_microstep: 381.32 | bwd_inner_microstep: 381.27 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.82 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-15 01:00:26,101] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 400.42 | bwd_microstep: 596.89 | bwd_inner_microstep: 596.74 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-15 01:00:27,222] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.00 | optimizer_step: 29.35 +[2025-05-15 01:00:27,223] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 356.49 | bwd_microstep: 710.35 | bwd_inner_microstep: 503.51 | bwd_allreduce_microstep: 206.55 | step_microstep: 37.91 +[2025-05-15 01:00:27,223] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2729.70 | bwd: 3741.28 | bwd_inner: 3533.69 | bwd_allreduce: 206.69 | step: 47.12 + 50%|█████ | 279/558 [32:22<31:22, 6.75s/it] {'loss': 5.0818, 'grad_norm': 20.475709915161133, 'learning_rate': 5.246697741199557e-16, 'epoch': 0.15} + 50%|█████ | 279/558 [32:22<31:22, 6.75s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1930 +[2025-05-15 01:00:28,196] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 307.28 | bwd_microstep: 638.72 | bwd_inner_microstep: 638.68 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1906 +[2025-05-15 01:00:29,122] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 372.76 | bwd_microstep: 520.52 | bwd_inner_microstep: 520.09 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.24 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1899 +[2025-05-15 01:00:29,920] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 355.08 | bwd_microstep: 420.71 | bwd_inner_microstep: 420.67 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.83 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-15 01:00:30,931] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 429.94 | bwd_microstep: 557.81 | bwd_inner_microstep: 557.42 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.17 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1896 +[2025-05-15 01:00:31,650] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 355.92 | bwd_microstep: 342.62 | bwd_inner_microstep: 342.57 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.80 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1092 +[2025-05-15 01:00:32,290] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 232.70 | bwd_microstep: 382.57 | bwd_inner_microstep: 382.53 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-15 01:00:33,235] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 388.75 | bwd_microstep: 523.97 | bwd_inner_microstep: 523.91 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.76 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1916 +[2025-05-15 01:00:34,543] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.01 | optimizer_gradients: 2.14 | optimizer_step: 18.41 +[2025-05-15 01:00:34,544] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 326.42 | bwd_microstep: 935.52 | bwd_inner_microstep: 458.22 | bwd_allreduce_microstep: 477.25 | step_microstep: 28.00 +[2025-05-15 01:00:34,545] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2768.84 | bwd: 4322.44 | bwd_inner: 3844.12 | bwd_allreduce: 477.71 | step: 37.52 + 50%|█████ | 280/558 [32:30<32:03, 6.92s/it] {'loss': 4.2694, 'grad_norm': 20.726543426513672, 'learning_rate': 5.217694055321725e-16, 'epoch': 0.15} + 50%|█████ | 280/558 [32:30<32:03, 6.92s/it]dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 905 +[2025-05-15 01:00:35,019] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.14 | bwd_microstep: 259.38 | bwd_inner_microstep: 259.10 | bwd_allreduce_microstep: 0.24 | step_microstep: 0.25 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-15 01:00:35,825] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 283.72 | bwd_microstep: 500.38 | bwd_inner_microstep: 500.32 | bwd_allreduce_microstep: 0.02 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-15 01:00:36,828] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 443.04 | bwd_microstep: 526.61 | bwd_inner_microstep: 526.56 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-15 01:00:37,594] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 340.77 | bwd_microstep: 402.95 | bwd_inner_microstep: 402.91 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.81 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 335 +[2025-05-15 01:00:37,850] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.85 | bwd_microstep: 135.44 | bwd_inner_microstep: 135.41 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-15 01:00:38,858] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 445.81 | bwd_microstep: 528.66 | bwd_inner_microstep: 528.61 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-15 01:00:39,557] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 354.46 | bwd_microstep: 323.81 | bwd_inner_microstep: 323.62 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1944 +[2025-05-15 01:00:40,802] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.10 | optimizer_step: 15.42 +[2025-05-15 01:00:40,803] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 239.59 | bwd_microstep: 963.72 | bwd_inner_microstep: 641.39 | bwd_allreduce_microstep: 322.29 | step_microstep: 26.17 +[2025-05-15 01:00:40,804] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2391.36 | bwd: 3640.96 | bwd_inner: 3315.65 | bwd_allreduce: 322.66 | step: 36.10 + 50%|█████ | 281/558 [32:36<31:01, 6.72s/it] {'loss': 3.6652, 'grad_norm': 15.951531410217285, 'learning_rate': 5.188683028522654e-16, 'epoch': 0.15} + 50%|█████ | 281/558 [32:36<31:01, 6.72s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-15 01:00:41,611] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 357.36 | bwd_microstep: 422.39 | bwd_inner_microstep: 422.10 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.11 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 339 +[2025-05-15 01:00:41,865] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.31 | bwd_microstep: 144.37 | bwd_inner_microstep: 144.31 | bwd_allreduce_microstep: 0.02 | step_microstep: 1.84 +dynamic ViT batch size: 8, images per sample: 8.0, dynamic token length: 2130 +[2025-05-15 01:00:43,013] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 494.21 | bwd_microstep: 623.98 | bwd_inner_microstep: 623.94 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.32 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-15 01:00:43,780] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 363.71 | bwd_microstep: 380.22 | bwd_inner_microstep: 380.18 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.82 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-15 01:00:44,818] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 401.14 | bwd_microstep: 611.83 | bwd_inner_microstep: 611.56 | bwd_allreduce_microstep: 0.24 | step_microstep: 0.22 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-15 01:00:45,700] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 354.11 | bwd_microstep: 508.03 | bwd_inner_microstep: 507.98 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.26 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-15 01:00:46,494] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 274.84 | bwd_microstep: 496.45 | bwd_inner_microstep: 496.41 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1888 +[2025-05-15 01:00:47,712] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 1.65 | optimizer_step: 12.81 +[2025-05-15 01:00:47,712] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 443.34 | bwd_microstep: 720.02 | bwd_inner_microstep: 523.60 | bwd_allreduce_microstep: 196.36 | step_microstep: 19.62 +[2025-05-15 01:00:47,713] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2781.99 | bwd: 3907.33 | bwd_inner: 3710.17 | bwd_allreduce: 196.78 | step: 28.53 + 51%|█████ | 282/558 [32:43<31:10, 6.78s/it] {'loss': 5.9818, 'grad_norm': 29.987150192260742, 'learning_rate': 5.159665639091176e-16, 'epoch': 0.15} + 51%|█████ | 282/558 [32:43<31:10, 6.78s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1990 +[2025-05-15 01:00:48,424] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 199.91 | bwd_microstep: 488.68 | bwd_inner_microstep: 488.66 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-15 01:00:49,434] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 444.08 | bwd_microstep: 535.79 | bwd_inner_microstep: 535.53 | bwd_allreduce_microstep: 0.24 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-15 01:00:50,231] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 354.23 | bwd_microstep: 424.07 | bwd_inner_microstep: 423.74 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-15 01:00:51,229] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 358.60 | bwd_microstep: 618.38 | bwd_inner_microstep: 618.33 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-15 01:00:52,124] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 352.25 | bwd_microstep: 511.43 | bwd_inner_microstep: 511.20 | bwd_allreduce_microstep: 0.19 | step_microstep: 0.24 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-15 01:00:52,910] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 318.68 | bwd_microstep: 447.79 | bwd_inner_microstep: 447.57 | bwd_allreduce_microstep: 0.18 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-15 01:00:53,925] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 440.84 | bwd_microstep: 547.24 | bwd_inner_microstep: 547.19 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.00 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1893 +[2025-05-15 01:00:54,999] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.09 | optimizer_step: 18.18 +[2025-05-15 01:00:55,000] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 342.45 | bwd_microstep: 685.38 | bwd_inner_microstep: 531.76 | bwd_allreduce_microstep: 153.58 | step_microstep: 26.86 +[2025-05-15 01:00:55,001] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2811.02 | bwd: 4258.80 | bwd_inner: 4104.04 | bwd_allreduce: 154.37 | step: 33.38 + 51%|█████ | 283/558 [32:50<31:45, 6.93s/it] {'loss': 5.0576, 'grad_norm': 19.858369827270508, 'learning_rate': 5.130642865530677e-16, 'epoch': 0.15} + 51%|█████ | 283/558 [32:50<31:45, 6.93s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1910 +[2025-05-15 01:00:55,997] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 351.86 | bwd_microstep: 618.24 | bwd_inner_microstep: 618.20 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 865 +[2025-05-15 01:00:56,402] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 132.17 | bwd_microstep: 241.92 | bwd_inner_microstep: 241.56 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.17 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 855 +[2025-05-15 01:00:56,847] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 172.74 | bwd_microstep: 253.43 | bwd_inner_microstep: 253.38 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.32 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-15 01:00:57,679] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 223.05 | bwd_microstep: 585.75 | bwd_inner_microstep: 585.72 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.40 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-15 01:00:58,638] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 427.43 | bwd_microstep: 497.23 | bwd_inner_microstep: 496.78 | bwd_allreduce_microstep: 0.43 | step_microstep: 0.73 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-15 01:00:59,424] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 316.34 | bwd_microstep: 448.39 | bwd_inner_microstep: 448.18 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-15 01:01:00,439] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 440.51 | bwd_microstep: 541.76 | bwd_inner_microstep: 541.55 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1937 +[2025-05-15 01:01:01,869] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.01 | optimizer_gradients: 2.15 | optimizer_step: 18.01 +[2025-05-15 01:01:01,870] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 365.56 | bwd_microstep: 1019.18 | bwd_inner_microstep: 440.49 | bwd_allreduce_microstep: 578.63 | step_microstep: 26.84 +[2025-05-15 01:01:01,871] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2429.65 | bwd: 4206.04 | bwd_inner: 3625.86 | bwd_allreduce: 579.24 | step: 35.20 + 51%|█████ | 284/558 [32:57<31:34, 6.91s/it] {'loss': 4.9721, 'grad_norm': 23.39105224609375, 'learning_rate': 5.101615686526102e-16, 'epoch': 0.15} + 51%|█████ | 284/558 [32:57<31:34, 6.91s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1899 +[2025-05-15 01:01:02,770] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 359.81 | bwd_microstep: 513.19 | bwd_inner_microstep: 513.15 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.23 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-15 01:01:03,557] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 314.09 | bwd_microstep: 452.47 | bwd_inner_microstep: 452.26 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-15 01:01:04,573] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 441.74 | bwd_microstep: 543.91 | bwd_inner_microstep: 543.70 | bwd_allreduce_microstep: 0.18 | step_microstep: 0.17 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-15 01:01:05,406] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 354.48 | bwd_microstep: 460.93 | bwd_inner_microstep: 460.75 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-15 01:01:06,354] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 319.84 | bwd_microstep: 608.41 | bwd_inner_microstep: 608.34 | bwd_allreduce_microstep: 0.02 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-15 01:01:07,260] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 368.18 | bwd_microstep: 505.48 | bwd_inner_microstep: 505.22 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.26 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 833 +[2025-05-15 01:01:07,587] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 163.93 | bwd_microstep: 143.56 | bwd_inner_microstep: 143.32 | bwd_allreduce_microstep: 0.09 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1912 +[2025-05-15 01:01:08,865] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.01 | optimizer_gradients: 2.13 | optimizer_step: 18.76 +[2025-05-15 01:01:08,866] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 363.52 | bwd_microstep: 869.52 | bwd_inner_microstep: 660.49 | bwd_allreduce_microstep: 209.00 | step_microstep: 27.87 +[2025-05-15 01:01:08,866] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2685.56 | bwd: 4097.72 | bwd_inner: 3887.37 | bwd_allreduce: 209.36 | step: 31.30 + 51%|█████ | 285/558 [33:04<31:33, 6.94s/it] {'loss': 5.3533, 'grad_norm': 18.122770309448242, 'learning_rate': 5.072585080910958e-16, 'epoch': 0.15} + 51%|█████ | 285/558 [33:04<31:33, 6.94s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 371 +[2025-05-15 01:01:09,142] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.05 | bwd_microstep: 157.86 | bwd_inner_microstep: 157.81 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.23 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 347 +[2025-05-15 01:01:09,397] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 98.33 | bwd_microstep: 138.01 | bwd_inner_microstep: 137.86 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-15 01:01:10,270] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 247.77 | bwd_microstep: 601.92 | bwd_inner_microstep: 601.86 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.64 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-15 01:01:11,219] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 401.24 | bwd_microstep: 512.58 | bwd_inner_microstep: 512.29 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.40 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-15 01:01:11,996] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 306.12 | bwd_microstep: 450.94 | bwd_inner_microstep: 450.72 | bwd_allreduce_microstep: 0.19 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-15 01:01:13,010] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 442.59 | bwd_microstep: 539.16 | bwd_inner_microstep: 539.14 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.27 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-15 01:01:13,796] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 360.78 | bwd_microstep: 401.89 | bwd_inner_microstep: 401.85 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.85 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-15 01:01:15,039] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.23 | optimizer_gradients: 2.03 | optimizer_step: 18.69 +[2025-05-15 01:01:15,040] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 409.81 | bwd_microstep: 781.91 | bwd_inner_microstep: 580.16 | bwd_allreduce_microstep: 201.73 | step_microstep: 27.59 +[2025-05-15 01:01:15,040] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2360.68 | bwd: 3584.29 | bwd_inner: 3381.96 | bwd_allreduce: 202.04 | step: 35.14 + 51%|█████▏ | 286/558 [33:10<30:24, 6.71s/it] {'loss': 4.7339, 'grad_norm': 30.226999282836914, 'learning_rate': 5.043552027634293e-16, 'epoch': 0.15} + 51%|█████▏ | 286/558 [33:10<30:24, 6.71s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1892 +[2025-05-15 01:01:15,851] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 361.93 | bwd_microstep: 418.70 | bwd_inner_microstep: 418.66 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.83 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1888 +[2025-05-15 01:01:16,858] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 408.65 | bwd_microstep: 570.70 | bwd_inner_microstep: 570.68 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.31 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-15 01:01:17,628] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 361.63 | bwd_microstep: 384.15 | bwd_inner_microstep: 384.12 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.83 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-15 01:01:18,654] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 395.51 | bwd_microstep: 603.38 | bwd_inner_microstep: 603.34 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-15 01:01:19,534] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 338.69 | bwd_microstep: 518.43 | bwd_inner_microstep: 518.39 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.97 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1356 +[2025-05-15 01:01:20,106] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 172.38 | bwd_microstep: 378.56 | bwd_inner_microstep: 378.49 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.28 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-15 01:01:21,121] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 439.72 | bwd_microstep: 545.33 | bwd_inner_microstep: 545.31 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.30 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1953 +[2025-05-15 01:01:22,569] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.03 | optimizer_step: 15.30 +[2025-05-15 01:01:22,570] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 368.76 | bwd_microstep: 1033.65 | bwd_inner_microstep: 442.32 | bwd_allreduce_microstep: 591.20 | step_microstep: 24.26 +[2025-05-15 01:01:22,571] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2847.28 | bwd: 4452.93 | bwd_inner: 3861.36 | bwd_allreduce: 591.25 | step: 35.12 + 51%|█████▏ | 287/558 [33:18<31:24, 6.95s/it] {'loss': 3.7537, 'grad_norm': 12.085613250732422, 'learning_rate': 5.014517505727702e-16, 'epoch': 0.15} + 51%|█████▏ | 287/558 [33:18<31:24, 6.95s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1897 +[2025-05-15 01:01:23,464] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 356.84 | bwd_microstep: 508.73 | bwd_inner_microstep: 508.46 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 346 +[2025-05-15 01:01:23,702] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 76.42 | bwd_microstep: 144.11 | bwd_inner_microstep: 144.07 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.33 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-15 01:01:24,728] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 408.42 | bwd_microstep: 594.71 | bwd_inner_microstep: 593.74 | bwd_allreduce_microstep: 0.94 | step_microstep: 0.21 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-15 01:01:25,589] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 344.00 | bwd_microstep: 495.43 | bwd_inner_microstep: 495.29 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-15 01:01:26,492] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 274.83 | bwd_microstep: 608.65 | bwd_inner_microstep: 608.60 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1348 +[2025-05-15 01:01:27,210] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 295.21 | bwd_microstep: 389.87 | bwd_inner_microstep: 389.45 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.76 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 837 +[2025-05-15 01:01:27,624] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 162.93 | bwd_microstep: 231.24 | bwd_inner_microstep: 230.81 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.78 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2040 +[2025-05-15 01:01:28,935] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.01 | optimizer_gradients: 2.02 | optimizer_step: 18.38 +[2025-05-15 01:01:28,935] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 251.85 | bwd_microstep: 1010.45 | bwd_inner_microstep: 630.79 | bwd_allreduce_microstep: 379.63 | step_microstep: 26.96 +[2025-05-15 01:01:28,936] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2170.47 | bwd: 3983.23 | bwd_inner: 3601.29 | bwd_allreduce: 380.78 | step: 33.59 + 52%|█████▏ | 288/558 [33:24<30:30, 6.78s/it] {'loss': 6.3971, 'grad_norm': 20.01487159729004, 'learning_rate': 4.9854824942723e-16, 'epoch': 0.15} + 52%|█████▏ | 288/558 [33:24<30:30, 6.78s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1908 +[2025-05-15 01:01:29,833] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 335.57 | bwd_microstep: 536.38 | bwd_inner_microstep: 536.00 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.18 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1385 +[2025-05-15 01:01:30,411] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 270.78 | bwd_microstep: 287.78 | bwd_inner_microstep: 287.61 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-15 01:01:31,450] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 390.80 | bwd_microstep: 627.47 | bwd_inner_microstep: 626.47 | bwd_allreduce_microstep: 0.97 | step_microstep: 0.22 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 350 +[2025-05-15 01:01:31,694] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 96.05 | bwd_microstep: 128.40 | bwd_inner_microstep: 128.36 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-15 01:01:32,467] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 355.57 | bwd_microstep: 396.89 | bwd_inner_microstep: 396.64 | bwd_allreduce_microstep: 0.21 | step_microstep: 0.20 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 832 +[2025-05-15 01:01:32,963] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 198.29 | bwd_microstep: 273.11 | bwd_inner_microstep: 273.08 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.57 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-15 01:01:33,934] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 426.39 | bwd_microstep: 509.98 | bwd_inner_microstep: 509.79 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.17 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-15 01:01:35,291] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.01 | optimizer_gradients: 2.11 | optimizer_step: 18.44 +[2025-05-15 01:01:35,292] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 355.66 | bwd_microstep: 954.86 | bwd_inner_microstep: 422.98 | bwd_allreduce_microstep: 531.80 | step_microstep: 27.47 +[2025-05-15 01:01:35,292] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2429.10 | bwd: 3714.89 | bwd_inner: 3180.98 | bwd_allreduce: 533.25 | step: 33.00 + 52%|█████▏ | 289/558 [33:30<29:49, 6.65s/it] {'loss': 4.9662, 'grad_norm': 24.339570999145508, 'learning_rate': 4.956447972365708e-16, 'epoch': 0.16} + 52%|█████▏ | 289/558 [33:30<29:49, 6.65s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-15 01:01:36,193] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 354.92 | bwd_microstep: 518.16 | bwd_inner_microstep: 517.95 | bwd_allreduce_microstep: 0.18 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-15 01:01:36,987] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 360.56 | bwd_microstep: 412.34 | bwd_inner_microstep: 412.30 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.79 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-15 01:01:37,889] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 262.03 | bwd_microstep: 614.35 | bwd_inner_microstep: 614.14 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.19 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 330 +[2025-05-15 01:01:38,134] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 96.69 | bwd_microstep: 131.13 | bwd_inner_microstep: 130.89 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.43 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 323 +[2025-05-15 01:01:38,377] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 91.60 | bwd_microstep: 132.58 | bwd_inner_microstep: 132.38 | bwd_allreduce_microstep: 0.18 | step_microstep: 0.17 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-15 01:01:39,154] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 357.04 | bwd_microstep: 399.64 | bwd_inner_microstep: 399.59 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.81 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-15 01:01:40,177] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 414.76 | bwd_microstep: 584.17 | bwd_inner_microstep: 584.14 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.37 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2064 +[2025-05-15 01:01:41,332] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 1.67 | optimizer_step: 17.76 +[2025-05-15 01:01:41,333] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 371.20 | bwd_microstep: 739.73 | bwd_inner_microstep: 572.46 | bwd_allreduce_microstep: 167.21 | step_microstep: 24.82 +[2025-05-15 01:01:41,333] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2308.79 | bwd: 3532.10 | bwd_inner: 3363.83 | bwd_allreduce: 167.63 | step: 29.57 + 52%|█████▏ | 290/558 [33:36<28:53, 6.47s/it] {'loss': 4.2178, 'grad_norm': 23.074317932128906, 'learning_rate': 4.927414919089045e-16, 'epoch': 0.16} + 52%|█████▏ | 290/558 [33:36<28:53, 6.47s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-15 01:01:42,320] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 343.99 | bwd_microstep: 616.55 | bwd_inner_microstep: 616.51 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-15 01:01:43,230] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 349.50 | bwd_microstep: 526.36 | bwd_inner_microstep: 526.31 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.30 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-15 01:01:44,029] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 327.41 | bwd_microstep: 450.78 | bwd_inner_microstep: 450.56 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-15 01:01:45,053] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 449.70 | bwd_microstep: 541.85 | bwd_inner_microstep: 541.80 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.27 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-15 01:01:45,826] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 355.01 | bwd_microstep: 396.54 | bwd_inner_microstep: 396.29 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-15 01:01:46,865] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 389.74 | bwd_microstep: 626.86 | bwd_inner_microstep: 626.79 | bwd_allreduce_microstep: 0.02 | step_microstep: 2.32 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-15 01:01:47,745] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 355.71 | bwd_microstep: 500.76 | bwd_inner_microstep: 500.54 | bwd_allreduce_microstep: 0.19 | step_microstep: 0.24 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-15 01:01:48,959] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.23 | optimizer_gradients: 2.08 | optimizer_step: 18.21 +[2025-05-15 01:01:48,960] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 213.54 | bwd_microstep: 955.65 | bwd_inner_microstep: 491.07 | bwd_allreduce_microstep: 464.55 | step_microstep: 27.14 +[2025-05-15 01:01:48,961] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2784.57 | bwd: 4615.39 | bwd_inner: 4149.90 | bwd_allreduce: 464.93 | step: 36.69 + 52%|█████▏ | 291/558 [33:44<30:19, 6.82s/it] {'loss': 6.1729, 'grad_norm': 40.120750427246094, 'learning_rate': 4.898384313473899e-16, 'epoch': 0.16} + 52%|█████▏ | 291/558 [33:44<30:19, 6.82s/it]dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1402 +[2025-05-15 01:01:49,641] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 257.76 | bwd_microstep: 397.09 | bwd_inner_microstep: 396.93 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-15 01:01:50,511] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 242.31 | bwd_microstep: 605.02 | bwd_inner_microstep: 605.00 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-15 01:01:51,457] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 411.14 | bwd_microstep: 501.05 | bwd_inner_microstep: 500.79 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.92 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-15 01:01:52,249] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 354.85 | bwd_microstep: 415.54 | bwd_inner_microstep: 415.50 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.84 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-15 01:01:53,249] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 407.85 | bwd_microstep: 566.59 | bwd_inner_microstep: 566.57 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.33 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 843 +[2025-05-15 01:01:53,683] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 173.71 | bwd_microstep: 243.85 | bwd_inner_microstep: 243.62 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.26 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 840 +[2025-05-15 01:01:53,994] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 117.58 | bwd_microstep: 173.61 | bwd_inner_microstep: 173.57 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.33 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-15 01:01:55,263] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.01 | optimizer_gradients: 2.07 | optimizer_step: 15.17 +[2025-05-15 01:01:55,264] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 399.86 | bwd_microstep: 822.59 | bwd_inner_microstep: 613.75 | bwd_allreduce_microstep: 208.82 | step_microstep: 24.42 +[2025-05-15 01:01:55,264] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2365.04 | bwd: 3725.36 | bwd_inner: 3515.97 | bwd_allreduce: 208.93 | step: 32.57 + 52%|█████▏ | 292/558 [33:50<29:32, 6.66s/it] {'loss': 4.6753, 'grad_norm': 19.557374954223633, 'learning_rate': 4.869357134469325e-16, 'epoch': 0.16} + 52%|█████▏ | 292/558 [33:50<29:32, 6.66s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1894 +[2025-05-15 01:01:56,027] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 347.77 | bwd_microstep: 387.13 | bwd_inner_microstep: 387.07 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.29 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1899 +[2025-05-15 01:01:57,058] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 382.65 | bwd_microstep: 623.38 | bwd_inner_microstep: 622.98 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.23 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 335 +[2025-05-15 01:01:57,316] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.84 | bwd_microstep: 146.40 | bwd_inner_microstep: 146.37 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.20 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 850 +[2025-05-15 01:01:57,755] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 173.93 | bwd_microstep: 244.80 | bwd_inner_microstep: 244.40 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-15 01:01:58,546] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 320.83 | bwd_microstep: 449.91 | bwd_inner_microstep: 449.70 | bwd_allreduce_microstep: 0.18 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-15 01:01:59,578] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 443.08 | bwd_microstep: 556.63 | bwd_inner_microstep: 556.60 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.31 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-15 01:02:00,463] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 357.92 | bwd_microstep: 505.50 | bwd_inner_microstep: 505.07 | bwd_allreduce_microstep: 0.39 | step_microstep: 0.74 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-15 01:02:01,615] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 1.66 | optimizer_step: 13.19 +[2025-05-15 01:02:01,616] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 217.27 | bwd_microstep: 894.89 | bwd_inner_microstep: 587.40 | bwd_allreduce_microstep: 307.43 | step_microstep: 19.99 +[2025-05-15 01:02:01,616] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2338.30 | bwd: 3808.64 | bwd_inner: 3499.57 | bwd_allreduce: 308.06 | step: 24.00 + 53%|█████▎ | 293/558 [33:57<29:00, 6.57s/it] {'loss': 5.9715, 'grad_norm': 23.374515533447266, 'learning_rate': 4.840334360908826e-16, 'epoch': 0.16} + 53%|█████▎ | 293/558 [33:57<29:00, 6.57s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1898 +[2025-05-15 01:02:02,519] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 361.20 | bwd_microstep: 518.12 | bwd_inner_microstep: 518.06 | bwd_allreduce_microstep: 0.02 | step_microstep: 1.01 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1883 +[2025-05-15 01:02:03,305] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 345.40 | bwd_microstep: 418.19 | bwd_inner_microstep: 418.15 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.80 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-15 01:02:04,325] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 409.51 | bwd_microstep: 586.15 | bwd_inner_microstep: 586.10 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.32 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-15 01:02:05,216] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 359.39 | bwd_microstep: 508.98 | bwd_inner_microstep: 508.55 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.76 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-15 01:02:05,985] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 349.90 | bwd_microstep: 397.67 | bwd_inner_microstep: 397.39 | bwd_allreduce_microstep: 0.23 | step_microstep: 0.21 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 844 +[2025-05-15 01:02:06,491] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 203.27 | bwd_microstep: 277.69 | bwd_inner_microstep: 277.66 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.54 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-15 01:02:07,475] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 431.30 | bwd_microstep: 520.16 | bwd_inner_microstep: 520.11 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-15 01:02:08,870] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.92 | optimizer_gradients: 2.08 | optimizer_step: 18.38 +[2025-05-15 01:02:08,871] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 358.18 | bwd_microstep: 990.22 | bwd_inner_microstep: 393.50 | bwd_allreduce_microstep: 596.50 | step_microstep: 27.51 +[2025-05-15 01:02:08,871] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2818.15 | bwd: 4217.17 | bwd_inner: 3619.53 | bwd_allreduce: 596.77 | step: 36.34 + 53%|█████▎ | 294/558 [34:04<29:48, 6.78s/it] {'loss': 5.6466, 'grad_norm': 42.29438400268555, 'learning_rate': 4.811316971477346e-16, 'epoch': 0.16} + 53%|█████▎ | 294/558 [34:04<29:48, 6.78s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1887 +[2025-05-15 01:02:09,771] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 355.27 | bwd_microstep: 516.36 | bwd_inner_microstep: 516.34 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.29 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1883 +[2025-05-15 01:02:10,624] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 230.23 | bwd_microstep: 599.44 | bwd_inner_microstep: 599.37 | bwd_allreduce_microstep: 0.02 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-15 01:02:11,585] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 411.13 | bwd_microstep: 516.36 | bwd_inner_microstep: 516.32 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.98 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-15 01:02:12,442] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 342.44 | bwd_microstep: 494.70 | bwd_inner_microstep: 494.49 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-15 01:02:13,335] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 269.48 | bwd_microstep: 602.08 | bwd_inner_microstep: 602.04 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-15 01:02:14,270] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 387.29 | bwd_microstep: 513.57 | bwd_inner_microstep: 513.18 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.18 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 836 +[2025-05-15 01:02:14,639] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 163.48 | bwd_microstep: 186.58 | bwd_inner_microstep: 186.43 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2481 +[2025-05-15 01:02:16,069] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.01 | optimizer_gradients: 2.00 | optimizer_step: 18.44 +[2025-05-15 01:02:16,070] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 397.04 | bwd_microstep: 988.76 | bwd_inner_microstep: 793.20 | bwd_allreduce_microstep: 195.52 | step_microstep: 27.09 +[2025-05-15 01:02:16,071] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2556.33 | bwd: 4417.86 | bwd_inner: 4221.44 | bwd_allreduce: 195.87 | step: 35.46 + 53%|█████▎ | 295/558 [34:11<30:15, 6.90s/it] {'loss': 3.6917, 'grad_norm': 24.06245231628418, 'learning_rate': 4.782305944678277e-16, 'epoch': 0.16} + 53%|█████▎ | 295/558 [34:11<30:15, 6.90s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1909 +[2025-05-15 01:02:16,977] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 349.92 | bwd_microstep: 528.70 | bwd_inner_microstep: 528.67 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.32 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1899 +[2025-05-15 01:02:17,775] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 356.29 | bwd_microstep: 419.82 | bwd_inner_microstep: 419.77 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.80 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-15 01:02:18,781] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 404.79 | bwd_microstep: 575.65 | bwd_inner_microstep: 575.39 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.94 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-15 01:02:19,674] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 349.31 | bwd_microstep: 522.92 | bwd_inner_microstep: 522.87 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.32 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-15 01:02:20,461] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 292.55 | bwd_microstep: 473.06 | bwd_inner_microstep: 473.02 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 331 +[2025-05-15 01:02:20,743] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 102.76 | bwd_microstep: 145.25 | bwd_inner_microstep: 145.19 | bwd_allreduce_microstep: 0.02 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-15 01:02:21,684] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 384.61 | bwd_microstep: 522.05 | bwd_inner_microstep: 521.86 | bwd_allreduce_microstep: 0.17 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-15 01:02:22,973] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.01 | optimizer_gradients: 2.08 | optimizer_step: 18.56 +[2025-05-15 01:02:22,973] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 283.51 | bwd_microstep: 959.26 | bwd_inner_microstep: 496.29 | bwd_allreduce_microstep: 462.94 | step_microstep: 27.65 +[2025-05-15 01:02:22,974] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2523.75 | bwd: 4146.70 | bwd_inner: 3683.07 | bwd_allreduce: 463.18 | step: 39.91 + 53%|█████▎ | 296/558 [34:18<30:08, 6.90s/it] {'loss': 3.2949, 'grad_norm': 16.13903045654297, 'learning_rate': 4.753302258800445e-16, 'epoch': 0.16} + 53%|█████▎ | 296/558 [34:18<30:08, 6.90s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1909 +[2025-05-15 01:02:23,883] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 349.06 | bwd_microstep: 532.13 | bwd_inner_microstep: 532.09 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.32 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-15 01:02:24,728] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 358.99 | bwd_microstep: 463.57 | bwd_inner_microstep: 463.43 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1886 +[2025-05-15 01:02:25,701] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 330.79 | bwd_microstep: 622.60 | bwd_inner_microstep: 622.56 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-15 01:02:26,611] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 361.08 | bwd_microstep: 516.38 | bwd_inner_microstep: 515.97 | bwd_allreduce_microstep: 0.19 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-15 01:02:27,415] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 357.82 | bwd_microstep: 425.76 | bwd_inner_microstep: 425.60 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-15 01:02:28,447] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 389.20 | bwd_microstep: 623.94 | bwd_inner_microstep: 623.67 | bwd_allreduce_microstep: 0.23 | step_microstep: 0.97 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1101 +[2025-05-15 01:02:28,979] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 211.07 | bwd_microstep: 301.34 | bwd_inner_microstep: 301.15 | bwd_allreduce_microstep: 0.17 | step_microstep: 0.17 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-15 01:02:30,092] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.21 | optimizer_gradients: 2.11 | optimizer_step: 18.63 +[2025-05-15 01:02:30,093] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 354.88 | bwd_microstep: 714.31 | bwd_inner_microstep: 507.39 | bwd_allreduce_microstep: 206.90 | step_microstep: 27.43 +[2025-05-15 01:02:30,094] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2712.88 | bwd: 4200.04 | bwd_inner: 3991.91 | bwd_allreduce: 207.45 | step: 33.63 + 53%|█████▎ | 297/558 [34:25<30:18, 6.97s/it] {'loss': 6.8857, 'grad_norm': 17.71091079711914, 'learning_rate': 4.724306891885134e-16, 'epoch': 0.16} + 53%|█████▎ | 297/558 [34:25<30:18, 6.97s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1907 +[2025-05-15 01:02:30,921] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 249.52 | bwd_microstep: 548.66 | bwd_inner_microstep: 548.61 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.28 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1893 +[2025-05-15 01:02:31,920] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 444.18 | bwd_microstep: 521.80 | bwd_inner_microstep: 520.81 | bwd_allreduce_microstep: 0.95 | step_microstep: 0.22 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1378 +[2025-05-15 01:02:32,596] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 258.47 | bwd_microstep: 396.80 | bwd_inner_microstep: 396.42 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.17 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1889 +[2025-05-15 01:02:33,404] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 360.65 | bwd_microstep: 428.08 | bwd_inner_microstep: 427.78 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.12 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 335 +[2025-05-15 01:02:33,647] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 87.47 | bwd_microstep: 138.99 | bwd_inner_microstep: 138.94 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.81 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-15 01:02:34,652] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 413.27 | bwd_microstep: 566.44 | bwd_inner_microstep: 566.40 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.26 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-15 01:02:35,538] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 345.69 | bwd_microstep: 518.02 | bwd_inner_microstep: 517.96 | bwd_allreduce_microstep: 0.02 | step_microstep: 2.01 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1907 +[2025-05-15 01:02:36,807] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.01 | optimizer_gradients: 2.06 | optimizer_step: 18.72 +[2025-05-15 01:02:36,807] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 258.46 | bwd_microstep: 962.13 | bwd_inner_microstep: 543.91 | bwd_allreduce_microstep: 418.18 | step_microstep: 27.33 +[2025-05-15 01:02:36,808] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2417.71 | bwd: 4080.90 | bwd_inner: 3660.89 | bwd_allreduce: 418.52 | step: 34.21 + 53%|█████▎ | 298/558 [34:32<29:51, 6.89s/it] {'loss': 2.4573, 'grad_norm': 6.986796855926514, 'learning_rate': 4.695320821693107e-16, 'epoch': 0.16} + 53%|█████▎ | 298/558 [34:32<29:51, 6.89s/it]dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1531 +[2025-05-15 01:02:37,510] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 274.47 | bwd_microstep: 402.30 | bwd_inner_microstep: 401.99 | bwd_allreduce_microstep: 0.15 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1887 +[2025-05-15 01:02:38,372] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 238.90 | bwd_microstep: 602.19 | bwd_inner_microstep: 602.14 | bwd_allreduce_microstep: 0.02 | step_microstep: 2.36 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 345 +[2025-05-15 01:02:38,646] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 105.22 | bwd_microstep: 138.96 | bwd_inner_microstep: 138.74 | bwd_allreduce_microstep: 0.19 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-15 01:02:39,547] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 363.02 | bwd_microstep: 517.93 | bwd_inner_microstep: 517.88 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.33 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-15 01:02:40,364] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 357.12 | bwd_microstep: 437.60 | bwd_inner_microstep: 437.45 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-15 01:02:41,348] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 349.32 | bwd_microstep: 614.29 | bwd_inner_microstep: 614.25 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-15 01:02:42,263] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 363.69 | bwd_microstep: 516.06 | bwd_inner_microstep: 516.03 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.30 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-15 01:02:43,109] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.09 | optimizer_step: 17.77 +[2025-05-15 01:02:43,110] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 338.43 | bwd_microstep: 461.00 | bwd_inner_microstep: 382.96 | bwd_allreduce_microstep: 77.95 | step_microstep: 26.43 +[2025-05-15 01:02:43,110] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2390.13 | bwd: 3690.38 | bwd_inner: 3611.54 | bwd_allreduce: 78.39 | step: 32.21 + 54%|█████▎ | 299/558 [34:38<28:59, 6.71s/it] {'loss': 4.7827, 'grad_norm': 36.214141845703125, 'learning_rate': 4.666345025671623e-16, 'epoch': 0.16} + 54%|█████▎ | 299/558 [34:38<28:59, 6.71s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1927 +[2025-05-15 01:02:44,122] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 339.55 | bwd_microstep: 645.19 | bwd_inner_microstep: 645.16 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.51 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1913 +[2025-05-15 01:02:44,967] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 346.43 | bwd_microstep: 466.68 | bwd_inner_microstep: 466.53 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 2, images per sample: 2.0, dynamic token length: 614 +[2025-05-15 01:02:45,290] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 98.85 | bwd_microstep: 206.42 | bwd_inner_microstep: 206.37 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.78 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1117 +[2025-05-15 01:02:45,968] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 270.59 | bwd_microstep: 385.41 | bwd_inner_microstep: 385.19 | bwd_allreduce_microstep: 0.19 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-15 01:02:46,860] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 361.45 | bwd_microstep: 512.34 | bwd_inner_microstep: 512.31 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.22 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 842 +[2025-05-15 01:02:47,297] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 174.25 | bwd_microstep: 243.54 | bwd_inner_microstep: 243.40 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-15 01:02:48,179] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 250.82 | bwd_microstep: 607.09 | bwd_inner_microstep: 607.03 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.29 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-15 01:02:49,350] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.01 | optimizer_gradients: 2.08 | optimizer_step: 18.37 +[2025-05-15 01:02:49,351] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 386.73 | bwd_microstep: 722.86 | bwd_inner_microstep: 522.52 | bwd_allreduce_microstep: 200.31 | step_microstep: 28.00 +[2025-05-15 01:02:49,352] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2228.63 | bwd: 3789.54 | bwd_inner: 3588.57 | bwd_allreduce: 200.65 | step: 35.18 + 54%|█████▍ | 300/558 [34:44<28:15, 6.57s/it] {'loss': 3.1608, 'grad_norm': 17.696813583374023, 'learning_rate': 4.6373804809214875e-16, 'epoch': 0.16} + 54%|█████▍ | 300/558 [34:44<28:15, 6.57s/it][INFO|trainer.py:3503] 2025-05-15 01:02:52,229 >> Saving model checkpoint to work_dirs/internvl_chat_v2_5/mmvet/checkpoint-300 +[INFO|configuration_utils.py:472] 2025-05-15 01:02:52,233 >> Configuration saved in work_dirs/internvl_chat_v2_5/mmvet/checkpoint-300/config.json +[INFO|configuration_utils.py:807] 2025-05-15 01:02:52,233 >> Configuration saved in work_dirs/internvl_chat_v2_5/mmvet/checkpoint-300/generation_config.json +[INFO|modeling_utils.py:2755] 2025-05-15 01:02:57,422 >> Model weights saved in work_dirs/internvl_chat_v2_5/mmvet/checkpoint-300/model.safetensors +[INFO|tokenization_utils_base.py:2702] 2025-05-15 01:02:57,423 >> tokenizer config file saved in work_dirs/internvl_chat_v2_5/mmvet/checkpoint-300/tokenizer_config.json +[INFO|tokenization_utils_base.py:2711] 2025-05-15 01:02:57,424 >> Special tokens file saved in work_dirs/internvl_chat_v2_5/mmvet/checkpoint-300/special_tokens_map.json +[INFO|tokenization_utils_base.py:2762] 2025-05-15 01:02:57,424 >> added tokens file saved in work_dirs/internvl_chat_v2_5/mmvet/checkpoint-300/added_tokens.json +[2025-05-15 01:02:57,536] [INFO] [logging.py:96:log_dist] [Rank 0] [Torch] Checkpoint global_step300 is about to be saved! +[2025-05-15 01:02:57,556] [INFO] [logging.py:96:log_dist] [Rank 0] Saving model checkpoint: work_dirs/internvl_chat_v2_5/mmvet/checkpoint-300/global_step300/mp_rank_00_model_states.pt +[2025-05-15 01:02:57,556] [INFO] [torch_checkpoint_engine.py:21:save] [Torch] Saving work_dirs/internvl_chat_v2_5/mmvet/checkpoint-300/global_step300/mp_rank_00_model_states.pt... +[2025-05-15 01:03:02,201] [INFO] [torch_checkpoint_engine.py:23:save] [Torch] Saved work_dirs/internvl_chat_v2_5/mmvet/checkpoint-300/global_step300/mp_rank_00_model_states.pt. +[2025-05-15 01:03:02,202] [INFO] [torch_checkpoint_engine.py:21:save] [Torch] Saving work_dirs/internvl_chat_v2_5/mmvet/checkpoint-300/global_step300/bf16_zero_pp_rank_0_mp_rank_00_optim_states.pt... +[2025-05-15 01:03:02,358] [INFO] [torch_checkpoint_engine.py:23:save] [Torch] Saved work_dirs/internvl_chat_v2_5/mmvet/checkpoint-300/global_step300/bf16_zero_pp_rank_0_mp_rank_00_optim_states.pt. +[2025-05-15 01:03:02,359] [INFO] [engine.py:3536:_save_zero_checkpoint] zero checkpoint saved work_dirs/internvl_chat_v2_5/mmvet/checkpoint-300/global_step300/bf16_zero_pp_rank_0_mp_rank_00_optim_states.pt +[2025-05-15 01:03:02,359] [INFO] [torch_checkpoint_engine.py:33:commit] [Torch] Checkpoint global_step300 is ready now! +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1425 +[2025-05-15 01:03:02,966] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 153.67 | bwd_microstep: 431.09 | bwd_inner_microstep: 431.06 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.33 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1939 +[2025-05-15 01:03:04,004] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 461.99 | bwd_microstep: 543.31 | bwd_inner_microstep: 543.09 | bwd_allreduce_microstep: 0.19 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1924 +[2025-05-15 01:03:04,936] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 366.86 | bwd_microstep: 544.57 | bwd_inner_microstep: 544.51 | bwd_allreduce_microstep: 0.02 | step_microstep: 2.28 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-15 01:03:05,793] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 236.56 | bwd_microstep: 595.66 | bwd_inner_microstep: 595.63 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-15 01:03:06,734] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 403.00 | bwd_microstep: 506.10 | bwd_inner_microstep: 505.89 | bwd_allreduce_microstep: 0.17 | step_microstep: 0.17 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-15 01:03:07,462] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 357.45 | bwd_microstep: 350.85 | bwd_inner_microstep: 350.60 | bwd_allreduce_microstep: 0.10 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-15 01:03:08,308] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 226.47 | bwd_microstep: 601.17 | bwd_inner_microstep: 601.12 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-15 01:03:09,486] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.92 | optimizer_gradients: 2.12 | optimizer_step: 18.70 +[2025-05-15 01:03:09,486] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 402.71 | bwd_microstep: 713.76 | bwd_inner_microstep: 513.60 | bwd_allreduce_microstep: 200.14 | step_microstep: 27.60 +[2025-05-15 01:03:09,487] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2608.64 | bwd: 4286.54 | bwd_inner: 4085.58 | bwd_allreduce: 200.62 | step: 37.39 + 54%|█████▍ | 301/558 [35:05<45:36, 10.65s/it] {'loss': 4.7875, 'grad_norm': 26.066144943237305, 'learning_rate': 4.608428164164095e-16, 'epoch': 0.16} + 54%|█████▍ | 301/558 [35:05<45:36, 10.65s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1888 +[2025-05-15 01:03:10,294] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 355.68 | bwd_microstep: 404.78 | bwd_inner_microstep: 404.76 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.85 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-15 01:03:11,260] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 357.15 | bwd_microstep: 583.15 | bwd_inner_microstep: 582.87 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-15 01:03:12,078] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 244.16 | bwd_microstep: 549.61 | bwd_inner_microstep: 549.56 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.59 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-15 01:03:12,936] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 428.80 | bwd_microstep: 394.28 | bwd_inner_microstep: 394.07 | bwd_allreduce_microstep: 0.19 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-15 01:03:13,975] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 398.15 | bwd_microstep: 619.51 | bwd_inner_microstep: 619.28 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-15 01:03:14,768] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 322.73 | bwd_microstep: 450.34 | bwd_inner_microstep: 450.24 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-15 01:03:15,713] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 445.54 | bwd_microstep: 469.04 | bwd_inner_microstep: 468.77 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.09 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1088 +[2025-05-15 01:03:16,622] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.01 | optimizer_gradients: 2.08 | optimizer_step: 18.37 +[2025-05-15 01:03:16,623] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 118.02 | bwd_microstep: 749.16 | bwd_inner_microstep: 167.50 | bwd_allreduce_microstep: 581.47 | step_microstep: 27.82 +[2025-05-15 01:03:16,623] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2670.22 | bwd: 4220.80 | bwd_inner: 3637.10 | bwd_allreduce: 581.85 | step: 33.11 + 54%|█████▍ | 302/558 [35:12<40:54, 9.59s/it] {'loss': 5.3076, 'grad_norm': 26.341049194335938, 'learning_rate': 4.579489051708499e-16, 'epoch': 0.16} + 54%|█████▍ | 302/558 [35:12<40:54, 9.59s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1887 +[2025-05-15 01:03:17,434] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 276.23 | bwd_microstep: 505.51 | bwd_inner_microstep: 505.45 | bwd_allreduce_microstep: 0.02 | step_microstep: 2.60 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1886 +[2025-05-15 01:03:18,320] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 442.13 | bwd_microstep: 411.94 | bwd_inner_microstep: 411.61 | bwd_allreduce_microstep: 0.28 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-15 01:03:19,367] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 395.35 | bwd_microstep: 628.06 | bwd_inner_microstep: 627.86 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1888 +[2025-05-15 01:03:20,181] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 248.24 | bwd_microstep: 543.96 | bwd_inner_microstep: 543.92 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-15 01:03:21,077] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 434.96 | bwd_microstep: 428.01 | bwd_inner_microstep: 427.71 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-15 01:03:22,119] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 389.70 | bwd_microstep: 632.33 | bwd_inner_microstep: 632.30 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.27 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-15 01:03:22,921] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 292.08 | bwd_microstep: 485.01 | bwd_inner_microstep: 484.97 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1346 +[2025-05-15 01:03:23,956] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 1.69 | optimizer_step: 12.87 +[2025-05-15 01:03:23,956] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 330.71 | bwd_microstep: 650.01 | bwd_inner_microstep: 445.03 | bwd_allreduce_microstep: 204.95 | step_microstep: 20.19 +[2025-05-15 01:03:23,957] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2809.39 | bwd: 4285.02 | bwd_inner: 4078.93 | bwd_allreduce: 205.38 | step: 30.26 + 54%|█████▍ | 303/558 [35:19<37:52, 8.91s/it] {'loss': 4.6408, 'grad_norm': 15.021653175354004, 'learning_rate': 4.550564119418487e-16, 'epoch': 0.16} + 54%|█████▍ | 303/558 [35:19<37:52, 8.91s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1972 +[2025-05-15 01:03:24,544] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 196.45 | bwd_microstep: 368.70 | bwd_inner_microstep: 368.65 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.82 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1905 +[2025-05-15 01:03:25,576] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 413.73 | bwd_microstep: 592.02 | bwd_inner_microstep: 591.77 | bwd_allreduce_microstep: 0.21 | step_microstep: 0.22 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-15 01:03:26,406] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 351.18 | bwd_microstep: 458.80 | bwd_inner_microstep: 458.62 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-15 01:03:27,330] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 302.77 | bwd_microstep: 601.51 | bwd_inner_microstep: 601.46 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.57 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-15 01:03:28,248] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 386.93 | bwd_microstep: 499.02 | bwd_inner_microstep: 498.76 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.26 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 322 +[2025-05-15 01:03:28,494] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.67 | bwd_microstep: 133.68 | bwd_inner_microstep: 133.33 | bwd_allreduce_microstep: 0.15 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-15 01:03:29,453] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 324.01 | bwd_microstep: 613.28 | bwd_inner_microstep: 613.25 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.52 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-15 01:03:30,616] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.01 | optimizer_gradients: 2.11 | optimizer_step: 18.13 +[2025-05-15 01:03:30,616] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 364.17 | bwd_microstep: 736.55 | bwd_inner_microstep: 528.76 | bwd_allreduce_microstep: 207.76 | step_microstep: 27.69 +[2025-05-15 01:03:30,617] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2432.88 | bwd: 4003.60 | bwd_inner: 3794.71 | bwd_allreduce: 208.22 | step: 35.38 + 54%|█████▍ | 304/558 [35:26<34:52, 8.24s/it] {'loss': 5.3063, 'grad_norm': 47.38636016845703, 'learning_rate': 4.521654342679672e-16, 'epoch': 0.16} + 54%|█████▍ | 304/558 [35:26<34:52, 8.24s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1894 +[2025-05-15 01:03:31,459] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 214.73 | bwd_microstep: 599.58 | bwd_inner_microstep: 599.53 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1900 +[2025-05-15 01:03:32,428] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 426.44 | bwd_microstep: 508.85 | bwd_inner_microstep: 508.83 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.96 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-15 01:03:33,181] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 338.15 | bwd_microstep: 394.58 | bwd_inner_microstep: 394.53 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.83 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-15 01:03:34,208] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 409.78 | bwd_microstep: 589.75 | bwd_inner_microstep: 589.50 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.26 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 325 +[2025-05-15 01:03:34,455] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.96 | bwd_microstep: 133.77 | bwd_inner_microstep: 132.82 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.21 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-15 01:03:35,225] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 355.94 | bwd_microstep: 392.81 | bwd_inner_microstep: 392.59 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.10 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1348 +[2025-05-15 01:03:36,013] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 280.88 | bwd_microstep: 481.79 | bwd_inner_microstep: 481.76 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1967 +[2025-05-15 01:03:37,170] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.07 | optimizer_gradients: 2.11 | optimizer_step: 19.32 +[2025-05-15 01:03:37,171] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 390.07 | bwd_microstep: 705.25 | bwd_inner_microstep: 550.60 | bwd_allreduce_microstep: 154.37 | step_microstep: 28.23 +[2025-05-15 01:03:37,172] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2510.94 | bwd: 3806.38 | bwd_inner: 3650.17 | bwd_allreduce: 154.44 | step: 36.31 + 55%|█████▍ | 305/558 [35:32<32:36, 7.73s/it] {'loss': 3.923, 'grad_norm': 15.46550464630127, 'learning_rate': 4.492760696366606e-16, 'epoch': 0.16} + 55%|█████▍ | 305/558 [35:32<32:36, 7.73s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1940 +[2025-05-15 01:03:38,211] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 368.36 | bwd_microstep: 645.84 | bwd_inner_microstep: 645.80 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.29 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1886 +[2025-05-15 01:03:39,117] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 345.25 | bwd_microstep: 525.25 | bwd_inner_microstep: 525.20 | bwd_allreduce_microstep: 0.02 | step_microstep: 1.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1883 +[2025-05-15 01:03:39,904] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 297.82 | bwd_microstep: 466.53 | bwd_inner_microstep: 466.49 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.56 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-15 01:03:40,930] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 442.69 | bwd_microstep: 547.98 | bwd_inner_microstep: 547.95 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.42 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 332 +[2025-05-15 01:03:41,156] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 92.15 | bwd_microstep: 114.55 | bwd_inner_microstep: 114.53 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-15 01:03:41,935] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 294.75 | bwd_microstep: 463.98 | bwd_inner_microstep: 463.93 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-15 01:03:42,960] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 447.35 | bwd_microstep: 544.94 | bwd_inner_microstep: 544.72 | bwd_allreduce_microstep: 0.18 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-15 01:03:44,340] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.01 | optimizer_gradients: 2.12 | optimizer_step: 17.95 +[2025-05-15 01:03:44,341] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 355.28 | bwd_microstep: 978.42 | bwd_inner_microstep: 377.99 | bwd_allreduce_microstep: 600.39 | step_microstep: 26.99 +[2025-05-15 01:03:44,341] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2643.65 | bwd: 4287.50 | bwd_inner: 3686.62 | bwd_allreduce: 600.62 | step: 40.50 + 55%|█████▍ | 306/558 [35:39<31:45, 7.56s/it] {'loss': 5.2647, 'grad_norm': 20.186948776245117, 'learning_rate': 4.463884154809896e-16, 'epoch': 0.16} + 55%|█████▍ | 306/558 [35:39<31:45, 7.56s/it]dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 850 +[2025-05-15 01:03:44,782] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 169.99 | bwd_microstep: 243.90 | bwd_inner_microstep: 243.69 | bwd_allreduce_microstep: 0.18 | step_microstep: 0.18 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1118 +[2025-05-15 01:03:45,215] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 211.12 | bwd_microstep: 202.76 | bwd_inner_microstep: 202.46 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-15 01:03:46,254] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 391.93 | bwd_microstep: 626.86 | bwd_inner_microstep: 626.82 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.28 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-15 01:03:47,070] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 251.53 | bwd_microstep: 540.39 | bwd_inner_microstep: 540.35 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-15 01:03:47,962] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 432.93 | bwd_microstep: 425.82 | bwd_inner_microstep: 425.47 | bwd_allreduce_microstep: 0.14 | step_microstep: 0.19 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 848 +[2025-05-15 01:03:48,423] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 171.17 | bwd_microstep: 271.22 | bwd_inner_microstep: 271.16 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.58 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-15 01:03:49,311] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 448.38 | bwd_microstep: 405.42 | bwd_inner_microstep: 405.26 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-15 01:03:50,529] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.07 | optimizer_gradients: 1.65 | optimizer_step: 15.69 +[2025-05-15 01:03:50,529] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 226.91 | bwd_microstep: 952.19 | bwd_inner_microstep: 604.22 | bwd_allreduce_microstep: 347.91 | step_microstep: 23.02 +[2025-05-15 01:03:50,530] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2303.95 | bwd: 3668.61 | bwd_inner: 3319.58 | bwd_allreduce: 348.34 | step: 30.77 + 55%|█████▌ | 307/558 [35:46<29:54, 7.15s/it] {'loss': 4.5543, 'grad_norm': 18.184589385986328, 'learning_rate': 4.4350256917633587e-16, 'epoch': 0.17} + 55%|█████▌ | 307/558 [35:46<29:54, 7.15s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1896 +[2025-05-15 01:03:51,487] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 311.21 | bwd_microstep: 619.74 | bwd_inner_microstep: 619.71 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.56 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1900 +[2025-05-15 01:03:52,302] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 366.31 | bwd_microstep: 412.51 | bwd_inner_microstep: 412.48 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.84 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 352 +[2025-05-15 01:03:52,577] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 102.27 | bwd_microstep: 147.65 | bwd_inner_microstep: 147.60 | bwd_allreduce_microstep: 0.02 | step_microstep: 2.32 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-15 01:03:53,436] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 430.90 | bwd_microstep: 395.95 | bwd_inner_microstep: 395.89 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-15 01:03:54,479] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 390.97 | bwd_microstep: 628.80 | bwd_inner_microstep: 628.42 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.18 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1349 +[2025-05-15 01:03:55,045] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 199.56 | bwd_microstep: 345.59 | bwd_inner_microstep: 345.55 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.83 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1350 +[2025-05-15 01:03:55,829] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 301.83 | bwd_microstep: 458.55 | bwd_inner_microstep: 458.33 | bwd_allreduce_microstep: 0.19 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-15 01:03:57,095] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.11 | optimizer_step: 35.24 +[2025-05-15 01:03:57,096] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 247.12 | bwd_microstep: 954.37 | bwd_inner_microstep: 536.03 | bwd_allreduce_microstep: 418.28 | step_microstep: 44.86 +[2025-05-15 01:03:57,097] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2350.18 | bwd: 3963.17 | bwd_inner: 3544.01 | bwd_allreduce: 418.70 | step: 53.88 + 55%|█████▌ | 308/558 [35:52<29:03, 6.98s/it] {'loss': 5.993, 'grad_norm': 18.381423950195312, 'learning_rate': 4.4061862803711813e-16, 'epoch': 0.17} + 55%|█████▌ | 308/558 [35:52<29:03, 6.98s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1897 +[2025-05-15 01:03:58,040] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 309.76 | bwd_microstep: 607.15 | bwd_inner_microstep: 607.11 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1893 +[2025-05-15 01:03:58,973] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 380.68 | bwd_microstep: 518.02 | bwd_inner_microstep: 517.99 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.14 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-15 01:03:59,761] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 360.24 | bwd_microstep: 405.87 | bwd_inner_microstep: 405.82 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.77 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-15 01:04:00,769] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 407.17 | bwd_microstep: 573.57 | bwd_inner_microstep: 573.35 | bwd_allreduce_microstep: 0.18 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-15 01:04:01,563] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 283.65 | bwd_microstep: 488.56 | bwd_inner_microstep: 488.53 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.31 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-15 01:04:02,492] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 449.29 | bwd_microstep: 444.70 | bwd_inner_microstep: 444.36 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.22 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-15 01:04:03,496] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 362.05 | bwd_microstep: 620.75 | bwd_inner_microstep: 620.73 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.70 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2050 +[2025-05-15 01:04:04,907] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.01 | optimizer_gradients: 2.18 | optimizer_step: 21.09 +[2025-05-15 01:04:04,909] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 368.91 | bwd_microstep: 979.90 | bwd_inner_microstep: 490.55 | bwd_allreduce_microstep: 489.27 | step_microstep: 32.67 +[2025-05-15 01:04:04,910] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2921.70 | bwd: 4638.55 | bwd_inner: 4148.55 | bwd_allreduce: 489.61 | step: 44.35 + 55%|█████▌ | 309/558 [36:00<29:59, 7.23s/it] {'loss': 4.971, 'grad_norm': 27.215662002563477, 'learning_rate': 4.377366893135106e-16, 'epoch': 0.17} + 55%|█████▌ | 309/558 [36:00<29:59, 7.23s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1927 +[2025-05-15 01:04:05,800] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 241.36 | bwd_microstep: 606.79 | bwd_inner_microstep: 606.75 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-15 01:04:06,669] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 422.76 | bwd_microstep: 410.09 | bwd_inner_microstep: 410.03 | bwd_allreduce_microstep: 0.02 | step_microstep: 1.82 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 337 +[2025-05-15 01:04:06,941] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 101.91 | bwd_microstep: 143.92 | bwd_inner_microstep: 143.86 | bwd_allreduce_microstep: 0.02 | step_microstep: 2.42 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-15 01:04:07,911] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 429.54 | bwd_microstep: 508.46 | bwd_inner_microstep: 508.26 | bwd_allreduce_microstep: 0.18 | step_microstep: 0.17 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-15 01:04:08,793] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 357.09 | bwd_microstep: 504.37 | bwd_inner_microstep: 504.34 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-15 01:04:09,674] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 344.81 | bwd_microstep: 515.00 | bwd_inner_microstep: 514.96 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.13 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-15 01:04:10,567] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 351.94 | bwd_microstep: 520.00 | bwd_inner_microstep: 519.62 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-15 01:04:11,658] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.09 | optimizer_step: 16.22 +[2025-05-15 01:04:11,659] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 355.57 | bwd_microstep: 689.88 | bwd_inner_microstep: 497.97 | bwd_allreduce_microstep: 191.64 | step_microstep: 24.90 +[2025-05-15 01:04:11,659] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2604.98 | bwd: 3898.54 | bwd_inner: 3705.82 | bwd_allreduce: 192.08 | step: 33.20 + 56%|█████▌ | 310/558 [36:07<29:16, 7.08s/it] {'loss': 4.8889, 'grad_norm': 36.590858459472656, 'learning_rate': 4.348568501881629e-16, 'epoch': 0.17} + 56%|█████▌ | 310/558 [36:07<29:16, 7.08s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-15 01:04:12,625] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 328.18 | bwd_microstep: 611.76 | bwd_inner_microstep: 611.72 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.51 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-15 01:04:13,547] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 364.78 | bwd_microstep: 522.56 | bwd_inner_microstep: 522.52 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.92 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-15 01:04:14,432] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 358.27 | bwd_microstep: 508.98 | bwd_inner_microstep: 508.74 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.26 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 331 +[2025-05-15 01:04:14,684] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.12 | bwd_microstep: 140.64 | bwd_inner_microstep: 140.60 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.21 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-15 01:04:15,584] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 355.72 | bwd_microstep: 520.61 | bwd_inner_microstep: 520.57 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.27 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-15 01:04:16,469] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 352.98 | bwd_microstep: 509.77 | bwd_inner_microstep: 509.57 | bwd_allreduce_microstep: 0.18 | step_microstep: 0.17 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2044 +[2025-05-15 01:04:17,424] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 373.85 | bwd_microstep: 562.22 | bwd_inner_microstep: 561.77 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1900 +[2025-05-15 01:04:18,364] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.10 | optimizer_step: 20.50 +[2025-05-15 01:04:18,365] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 360.87 | bwd_microstep: 530.42 | bwd_inner_microstep: 468.79 | bwd_allreduce_microstep: 61.48 | step_microstep: 28.79 +[2025-05-15 01:04:18,365] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2588.75 | bwd: 3906.96 | bwd_inner: 3844.36 | bwd_allreduce: 61.95 | step: 36.37 + 56%|█████▌ | 311/558 [36:13<28:41, 6.97s/it] {'loss': 3.7583, 'grad_norm': 10.96262264251709, 'learning_rate': 4.3197920777292395e-16, 'epoch': 0.17} + 56%|█████▌ | 311/558 [36:13<28:41, 6.97s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-15 01:04:19,415] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 405.08 | bwd_microstep: 611.05 | bwd_inner_microstep: 610.09 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.22 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-15 01:04:20,306] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 353.66 | bwd_microstep: 515.69 | bwd_inner_microstep: 515.65 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.40 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-15 01:04:21,090] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 337.96 | bwd_microstep: 422.42 | bwd_inner_microstep: 422.38 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.76 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-15 01:04:22,072] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 440.52 | bwd_microstep: 517.22 | bwd_inner_microstep: 517.18 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.19 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1088 +[2025-05-15 01:04:22,609] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 210.63 | bwd_microstep: 307.78 | bwd_inner_microstep: 307.43 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-15 01:04:23,409] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 245.89 | bwd_microstep: 533.30 | bwd_inner_microstep: 533.26 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.52 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-15 01:04:24,389] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 441.20 | bwd_microstep: 507.02 | bwd_inner_microstep: 506.72 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.22 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-15 01:04:25,477] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.13 | optimizer_step: 20.03 +[2025-05-15 01:04:25,478] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 355.98 | bwd_microstep: 684.30 | bwd_inner_microstep: 495.15 | bwd_allreduce_microstep: 189.12 | step_microstep: 28.96 +[2025-05-15 01:04:25,479] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2790.93 | bwd: 4098.77 | bwd_inner: 3907.86 | bwd_allreduce: 190.28 | step: 35.45 + 56%|█████▌ | 312/558 [36:21<28:45, 7.01s/it] {'loss': 7.1168, 'grad_norm': 35.95499038696289, 'learning_rate': 4.291038591055668e-16, 'epoch': 0.17} + 56%|█████▌ | 312/558 [36:21<28:45, 7.01s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1899 +[2025-05-15 01:04:26,289] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 280.29 | bwd_microstep: 503.27 | bwd_inner_microstep: 503.22 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1887 +[2025-05-15 01:04:27,311] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 447.74 | bwd_microstep: 537.01 | bwd_inner_microstep: 536.97 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.31 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 342 +[2025-05-15 01:04:27,563] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.03 | bwd_microstep: 135.72 | bwd_inner_microstep: 135.52 | bwd_allreduce_microstep: 0.17 | step_microstep: 0.17 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-15 01:04:28,352] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 283.62 | bwd_microstep: 485.38 | bwd_inner_microstep: 485.34 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-15 01:04:29,283] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 442.61 | bwd_microstep: 454.25 | bwd_inner_microstep: 454.14 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-15 01:04:30,318] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 394.45 | bwd_microstep: 615.26 | bwd_inner_microstep: 615.12 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-15 01:04:30,978] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 231.06 | bwd_microstep: 412.14 | bwd_inner_microstep: 412.10 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.78 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-15 01:04:32,087] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.05 | optimizer_step: 18.13 +[2025-05-15 01:04:32,088] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 300.12 | bwd_microstep: 758.83 | bwd_inner_microstep: 608.20 | bwd_allreduce_microstep: 150.38 | step_microstep: 26.61 +[2025-05-15 01:04:32,089] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2474.91 | bwd: 3901.88 | bwd_inner: 3750.62 | bwd_allreduce: 150.72 | step: 35.88 + 56%|█████▌ | 313/558 [36:27<28:08, 6.89s/it] {'loss': 4.5556, 'grad_norm': 15.109320640563965, 'learning_rate': 4.2623090114651645e-16, 'epoch': 0.17} + 56%|█████▌ | 313/558 [36:27<28:08, 6.89s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1905 +[2025-05-15 01:04:33,079] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 344.85 | bwd_microstep: 619.65 | bwd_inner_microstep: 619.62 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1888 +[2025-05-15 01:04:33,883] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 304.06 | bwd_microstep: 464.80 | bwd_inner_microstep: 464.77 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-15 01:04:34,807] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 449.04 | bwd_microstep: 442.57 | bwd_inner_microstep: 442.42 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-15 01:04:35,831] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 364.24 | bwd_microstep: 641.46 | bwd_inner_microstep: 641.41 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.31 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-15 01:04:36,634] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 286.40 | bwd_microstep: 494.56 | bwd_inner_microstep: 494.51 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-15 01:04:37,534] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 448.41 | bwd_microstep: 416.11 | bwd_inner_microstep: 415.75 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-15 01:04:38,573] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 391.55 | bwd_microstep: 625.62 | bwd_inner_microstep: 625.60 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.31 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1949 +[2025-05-15 01:04:39,808] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.01 | optimizer_gradients: 1.64 | optimizer_step: 17.42 +[2025-05-15 01:04:39,809] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 269.82 | bwd_microstep: 921.61 | bwd_inner_microstep: 418.32 | bwd_allreduce_microstep: 503.27 | step_microstep: 24.92 +[2025-05-15 01:04:39,809] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2858.34 | bwd: 4626.40 | bwd_inner: 4122.51 | bwd_allreduce: 503.51 | step: 34.90 + 56%|█████▋ | 314/558 [36:35<29:02, 7.14s/it] {'loss': 3.8934, 'grad_norm': 10.644084930419922, 'learning_rate': 4.2336043077558e-16, 'epoch': 0.17} + 56%|█████▋ | 314/558 [36:35<29:02, 7.14s/it]dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 932 +[2025-05-15 01:04:40,199] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 132.99 | bwd_microstep: 230.11 | bwd_inner_microstep: 230.07 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.33 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 873 +[2025-05-15 01:04:40,732] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.01 | bwd_microstep: 322.44 | bwd_inner_microstep: 322.40 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-15 01:04:41,569] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 389.33 | bwd_microstep: 413.10 | bwd_inner_microstep: 413.07 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.92 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1105 +[2025-05-15 01:04:42,154] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 169.38 | bwd_microstep: 388.50 | bwd_inner_microstep: 388.46 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-15 01:04:42,982] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 373.56 | bwd_microstep: 420.21 | bwd_inner_microstep: 420.17 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.83 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-15 01:04:43,954] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 438.60 | bwd_microstep: 508.73 | bwd_inner_microstep: 508.58 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-15 01:04:44,897] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 313.78 | bwd_microstep: 609.24 | bwd_inner_microstep: 609.21 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1922 +[2025-05-15 01:04:46,268] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.07 | optimizer_gradients: 2.03 | optimizer_step: 25.38 +[2025-05-15 01:04:46,269] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 357.44 | bwd_microstep: 946.67 | bwd_inner_microstep: 463.41 | bwd_allreduce_microstep: 483.22 | step_microstep: 34.57 +[2025-05-15 01:04:46,269] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2362.06 | bwd: 3839.02 | bwd_inner: 3355.40 | bwd_allreduce: 483.35 | step: 47.84 + 56%|█████▋ | 315/558 [36:41<28:05, 6.94s/it] {'loss': 5.1305, 'grad_norm': 25.88631820678711, 'learning_rate': 4.2049254478867973e-16, 'epoch': 0.17} + 56%|█████▋ | 315/558 [36:41<28:05, 6.94s/it]dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 898 +[2025-05-15 01:04:46,678] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 103.61 | bwd_microstep: 280.44 | bwd_inner_microstep: 280.40 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.77 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 875 +[2025-05-15 01:04:47,213] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.13 | bwd_microstep: 316.48 | bwd_inner_microstep: 316.44 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1903 +[2025-05-15 01:04:48,041] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 343.84 | bwd_microstep: 451.77 | bwd_inner_microstep: 451.38 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1383 +[2025-05-15 01:04:48,832] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 331.81 | bwd_microstep: 431.29 | bwd_inner_microstep: 430.51 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.22 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1897 +[2025-05-15 01:04:49,671] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 217.63 | bwd_microstep: 600.33 | bwd_inner_microstep: 600.29 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.51 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-15 01:04:50,518] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 407.92 | bwd_microstep: 402.77 | bwd_inner_microstep: 402.73 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.78 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-15 01:04:51,539] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 413.17 | bwd_microstep: 583.58 | bwd_inner_microstep: 583.54 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.29 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1962 +[2025-05-15 01:04:52,795] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.23 | optimizer_gradients: 2.11 | optimizer_step: 18.65 +[2025-05-15 01:04:52,796] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 234.87 | bwd_microstep: 972.77 | bwd_inner_microstep: 646.23 | bwd_allreduce_microstep: 326.51 | step_microstep: 27.99 +[2025-05-15 01:04:52,796] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2247.97 | bwd: 4039.42 | bwd_inner: 3711.53 | bwd_allreduce: 326.74 | step: 36.96 + 57%|█████▋ | 316/558 [36:48<27:28, 6.81s/it] {'loss': 3.2879, 'grad_norm': 13.942237854003906, 'learning_rate': 4.1762733989458962e-16, 'epoch': 0.17} + 57%|█████▋ | 316/558 [36:48<27:28, 6.81s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1913 +[2025-05-15 01:04:53,673] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 234.37 | bwd_microstep: 612.03 | bwd_inner_microstep: 611.99 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.37 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-15 01:04:54,502] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 400.28 | bwd_microstep: 394.07 | bwd_inner_microstep: 394.05 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.82 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 335 +[2025-05-15 01:04:54,767] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.63 | bwd_microstep: 142.15 | bwd_inner_microstep: 142.08 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-15 01:04:55,658] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 436.41 | bwd_microstep: 422.55 | bwd_inner_microstep: 422.39 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.11 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1099 +[2025-05-15 01:04:56,286] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 251.71 | bwd_microstep: 355.15 | bwd_inner_microstep: 355.10 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.33 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-15 01:04:57,128] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 402.78 | bwd_microstep: 405.10 | bwd_inner_microstep: 404.74 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.19 +dynamic ViT batch size: 2, images per sample: 2.0, dynamic token length: 580 +[2025-05-15 01:04:57,475] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 143.73 | bwd_microstep: 177.79 | bwd_inner_microstep: 177.76 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.33 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-15 01:04:58,551] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.12 | optimizer_step: 17.72 +[2025-05-15 01:04:58,552] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 442.90 | bwd_microstep: 573.31 | bwd_inner_microstep: 504.72 | bwd_allreduce_microstep: 68.49 | step_microstep: 26.20 +[2025-05-15 01:04:58,553] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2406.81 | bwd: 3082.16 | bwd_inner: 3012.89 | bwd_allreduce: 68.89 | step: 37.71 + 57%|█████▋ | 317/558 [36:54<26:05, 6.50s/it] {'loss': 5.8378, 'grad_norm': 23.509109497070312, 'learning_rate': 4.1476491271167353e-16, 'epoch': 0.17} + 57%|█████▋ | 317/558 [36:54<26:05, 6.50s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1912 +[2025-05-15 01:04:59,590] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 378.48 | bwd_microstep: 633.18 | bwd_inner_microstep: 632.89 | bwd_allreduce_microstep: 0.25 | step_microstep: 0.24 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-15 01:05:00,391] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 284.00 | bwd_microstep: 495.34 | bwd_inner_microstep: 495.30 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-15 01:05:01,321] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 441.71 | bwd_microstep: 453.35 | bwd_inner_microstep: 453.19 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-15 01:05:02,296] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 339.09 | bwd_microstep: 615.54 | bwd_inner_microstep: 615.51 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-15 01:05:03,084] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 345.93 | bwd_microstep: 408.02 | bwd_inner_microstep: 407.98 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.81 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-15 01:05:04,068] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 411.80 | bwd_microstep: 548.33 | bwd_inner_microstep: 548.19 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-15 01:05:04,877] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 199.53 | bwd_microstep: 591.43 | bwd_inner_microstep: 591.37 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-15 01:05:06,297] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.07 | optimizer_step: 18.31 +[2025-05-15 01:05:06,297] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 405.93 | bwd_microstep: 955.56 | bwd_inner_microstep: 393.36 | bwd_allreduce_microstep: 562.17 | step_microstep: 26.56 +[2025-05-15 01:05:06,298] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2806.42 | bwd: 4700.77 | bwd_inner: 4137.84 | bwd_allreduce: 562.58 | step: 35.87 + 57%|█████▋ | 318/558 [37:01<27:28, 6.87s/it] {'loss': 4.6849, 'grad_norm': 19.74532127380371, 'learning_rate': 4.119053597646273e-16, 'epoch': 0.17} + 57%|█████▋ | 318/558 [37:01<27:28, 6.87s/it]dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1403 +[2025-05-15 01:05:06,793] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 143.69 | bwd_microstep: 327.92 | bwd_inner_microstep: 327.88 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.77 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-15 01:05:07,785] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 414.12 | bwd_microstep: 550.91 | bwd_inner_microstep: 550.76 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-15 01:05:08,677] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 263.75 | bwd_microstep: 605.18 | bwd_inner_microstep: 605.13 | bwd_allreduce_microstep: 0.02 | step_microstep: 2.55 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-15 01:05:09,504] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 382.00 | bwd_microstep: 410.32 | bwd_inner_microstep: 410.27 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.85 +dynamic ViT batch size: 6, images per sample: 6.0, dynamic token length: 1606 +[2025-05-15 01:05:10,415] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 354.62 | bwd_microstep: 530.97 | bwd_inner_microstep: 530.70 | bwd_allreduce_microstep: 0.22 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-15 01:05:11,223] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 249.06 | bwd_microstep: 536.20 | bwd_inner_microstep: 536.11 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.28 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-15 01:05:12,101] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 426.55 | bwd_microstep: 416.60 | bwd_inner_microstep: 416.26 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-15 01:05:13,333] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.01 | optimizer_gradients: 2.02 | optimizer_step: 15.62 +[2025-05-15 01:05:13,334] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 340.43 | bwd_microstep: 848.98 | bwd_inner_microstep: 605.78 | bwd_allreduce_microstep: 243.17 | step_microstep: 24.38 +[2025-05-15 01:05:13,334] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2574.21 | bwd: 4227.12 | bwd_inner: 3982.98 | bwd_allreduce: 243.60 | step: 33.31 + 57%|█████▋ | 319/558 [37:08<27:34, 6.92s/it] {'loss': 8.8047, 'grad_norm': 38.07279968261719, 'learning_rate': 4.090487774812244e-16, 'epoch': 0.17} + 57%|█████▋ | 319/558 [37:08<27:34, 6.92s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1953 +[2025-05-15 01:05:14,225] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 234.36 | bwd_microstep: 628.68 | bwd_inner_microstep: 628.64 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1903 +[2025-05-15 01:05:15,084] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 396.77 | bwd_microstep: 427.94 | bwd_inner_microstep: 427.68 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-15 01:05:16,116] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 382.59 | bwd_microstep: 629.46 | bwd_inner_microstep: 629.42 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.50 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-15 01:05:16,895] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 339.93 | bwd_microstep: 417.03 | bwd_inner_microstep: 416.99 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.82 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-15 01:05:17,908] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 441.86 | bwd_microstep: 547.33 | bwd_inner_microstep: 547.09 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.21 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-15 01:05:18,741] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 221.24 | bwd_microstep: 589.14 | bwd_inner_microstep: 589.10 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-15 01:05:19,602] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 407.40 | bwd_microstep: 419.29 | bwd_inner_microstep: 418.99 | bwd_allreduce_microstep: 0.14 | step_microstep: 0.10 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 323 +[2025-05-15 01:05:19,944] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 1.62 | optimizer_step: 12.81 +[2025-05-15 01:05:19,945] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.70 | bwd_microstep: 210.24 | bwd_inner_microstep: 138.63 | bwd_allreduce_microstep: 71.57 | step_microstep: 19.40 +[2025-05-15 01:05:19,945] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2518.82 | bwd: 3869.16 | bwd_inner: 3796.67 | bwd_allreduce: 71.84 | step: 27.86 + 57%|█████▋ | 320/558 [37:15<27:04, 6.83s/it] {'loss': 6.0108, 'grad_norm': 33.721614837646484, 'learning_rate': 4.061952621890628e-16, 'epoch': 0.17} + 57%|█████▋ | 320/558 [37:15<27:04, 6.83s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1975 +[2025-05-15 01:05:20,957] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 451.28 | bwd_microstep: 539.80 | bwd_inner_microstep: 539.49 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-15 01:05:21,899] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 309.60 | bwd_microstep: 612.44 | bwd_inner_microstep: 612.38 | bwd_allreduce_microstep: 0.02 | step_microstep: 2.51 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1883 +[2025-05-15 01:05:22,724] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 369.16 | bwd_microstep: 418.74 | bwd_inner_microstep: 418.71 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.33 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-15 01:05:23,710] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 405.71 | bwd_microstep: 558.49 | bwd_inner_microstep: 557.53 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.23 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-15 01:05:24,504] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 276.71 | bwd_microstep: 493.57 | bwd_inner_microstep: 493.52 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-15 01:05:25,398] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 443.81 | bwd_microstep: 417.94 | bwd_inner_microstep: 417.78 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.26 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1976 +[2025-05-15 01:05:26,480] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 416.33 | bwd_microstep: 647.96 | bwd_inner_microstep: 647.74 | bwd_allreduce_microstep: 0.18 | step_microstep: 0.23 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-15 01:05:27,738] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.12 | optimizer_step: 29.32 +[2025-05-15 01:05:27,738] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 245.85 | bwd_microstep: 953.60 | bwd_inner_microstep: 534.13 | bwd_allreduce_microstep: 419.41 | step_microstep: 38.00 +[2025-05-15 01:05:27,739] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2918.43 | bwd: 4642.55 | bwd_inner: 4221.39 | bwd_allreduce: 419.80 | step: 46.02 + 58%|█████▊ | 321/558 [37:23<28:06, 7.12s/it] {'loss': 5.8899, 'grad_norm': 28.118913650512695, 'learning_rate': 4.033449101123183e-16, 'epoch': 0.17} + 58%|█████▊ | 321/558 [37:23<28:06, 7.12s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-15 01:05:28,654] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 290.08 | bwd_microstep: 599.06 | bwd_inner_microstep: 599.03 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-15 01:05:29,480] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 375.11 | bwd_microstep: 416.17 | bwd_inner_microstep: 416.13 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.86 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-15 01:05:30,457] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 409.74 | bwd_microstep: 541.92 | bwd_inner_microstep: 541.74 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1883 +[2025-05-15 01:05:31,356] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 274.38 | bwd_microstep: 604.08 | bwd_inner_microstep: 604.05 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.42 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-15 01:05:32,194] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 390.20 | bwd_microstep: 414.13 | bwd_inner_microstep: 414.09 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.78 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-15 01:05:33,166] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 412.00 | bwd_microstep: 534.11 | bwd_inner_microstep: 533.92 | bwd_allreduce_microstep: 0.08 | step_microstep: 0.11 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1345 +[2025-05-15 01:05:33,805] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 180.45 | bwd_microstep: 436.76 | bwd_inner_microstep: 436.71 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 831 +[2025-05-15 01:05:34,505] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.12 | optimizer_step: 18.09 +[2025-05-15 01:05:34,506] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 219.70 | bwd_microstep: 422.02 | bwd_inner_microstep: 272.29 | bwd_allreduce_microstep: 149.67 | step_microstep: 26.65 +[2025-05-15 01:05:34,507] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2551.61 | bwd: 3968.26 | bwd_inner: 3818.04 | bwd_allreduce: 149.87 | step: 37.64 + 58%|█████▊ | 322/558 [37:30<27:34, 7.01s/it] {'loss': 4.8625, 'grad_norm': 30.453824996948242, 'learning_rate': 4.004978173684988e-16, 'epoch': 0.17} + 58%|█████▊ | 322/558 [37:30<27:34, 7.01s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1912 +[2025-05-15 01:05:35,510] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 348.78 | bwd_microstep: 628.67 | bwd_inner_microstep: 628.61 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1901 +[2025-05-15 01:05:36,325] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 297.02 | bwd_microstep: 483.22 | bwd_inner_microstep: 483.17 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1883 +[2025-05-15 01:05:37,229] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 438.06 | bwd_microstep: 433.04 | bwd_inner_microstep: 432.86 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.12 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1359 +[2025-05-15 01:05:37,863] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 168.65 | bwd_microstep: 439.49 | bwd_inner_microstep: 439.44 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-15 01:05:38,747] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 425.08 | bwd_microstep: 426.43 | bwd_inner_microstep: 426.16 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-15 01:05:39,782] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 394.86 | bwd_microstep: 621.10 | bwd_inner_microstep: 621.07 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.31 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-15 01:05:40,606] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 251.00 | bwd_microstep: 550.05 | bwd_inner_microstep: 550.01 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.55 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-15 01:05:42,065] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.01 | optimizer_gradients: 2.05 | optimizer_step: 18.46 +[2025-05-15 01:05:42,065] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 430.66 | bwd_microstep: 968.43 | bwd_inner_microstep: 387.10 | bwd_allreduce_microstep: 581.30 | step_microstep: 27.62 +[2025-05-15 01:05:42,066] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2754.08 | bwd: 4550.42 | bwd_inner: 3968.47 | bwd_allreduce: 581.44 | step: 39.89 + 58%|█████▊ | 323/558 [37:37<28:06, 7.18s/it] {'loss': 3.722, 'grad_norm': 17.492069244384766, 'learning_rate': 3.9765407996520366e-16, 'epoch': 0.17} + 58%|█████▊ | 323/558 [37:37<28:06, 7.18s/it]dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1117 +[2025-05-15 01:05:42,509] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 130.96 | bwd_microstep: 285.79 | bwd_inner_microstep: 285.75 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.33 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1366 +[2025-05-15 01:05:43,302] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 300.92 | bwd_microstep: 470.95 | bwd_inner_microstep: 470.92 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.19 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1359 +[2025-05-15 01:05:43,879] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 201.14 | bwd_microstep: 355.49 | bwd_inner_microstep: 355.47 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.74 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-15 01:05:44,884] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 438.71 | bwd_microstep: 542.97 | bwd_inner_microstep: 542.95 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.32 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-15 01:05:45,663] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 306.85 | bwd_microstep: 451.32 | bwd_inner_microstep: 451.11 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.61 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1090 +[2025-05-15 01:05:46,329] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 271.80 | bwd_microstep: 363.59 | bwd_inner_microstep: 363.56 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-15 01:05:47,139] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 246.79 | bwd_microstep: 540.92 | bwd_inner_microstep: 540.86 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-15 01:05:48,262] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.07 | optimizer_gradients: 2.15 | optimizer_step: 18.24 +[2025-05-15 01:05:48,263] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 423.77 | bwd_microstep: 637.93 | bwd_inner_microstep: 517.06 | bwd_allreduce_microstep: 120.81 | step_microstep: 27.74 +[2025-05-15 01:05:48,264] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2320.95 | bwd: 3648.97 | bwd_inner: 3527.67 | bwd_allreduce: 120.87 | step: 37.22 + 58%|█████▊ | 324/558 [37:43<26:50, 6.88s/it] {'loss': 3.652, 'grad_norm': 23.618932723999023, 'learning_rate': 3.9481379379688546e-16, 'epoch': 0.17} + 58%|█████▊ | 324/558 [37:43<26:50, 6.88s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1899 +[2025-05-15 01:05:49,283] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 363.09 | bwd_microstep: 629.73 | bwd_inner_microstep: 629.69 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.50 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-15 01:05:50,084] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 356.22 | bwd_microstep: 418.23 | bwd_inner_microstep: 418.19 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.28 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1371 +[2025-05-15 01:05:50,874] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 299.00 | bwd_microstep: 467.20 | bwd_inner_microstep: 466.83 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-15 01:05:51,684] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 246.46 | bwd_microstep: 541.15 | bwd_inner_microstep: 541.10 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-15 01:05:52,535] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 428.19 | bwd_microstep: 388.07 | bwd_inner_microstep: 388.04 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.64 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-15 01:05:53,562] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 393.82 | bwd_microstep: 612.31 | bwd_inner_microstep: 612.11 | bwd_allreduce_microstep: 0.17 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-15 01:05:54,351] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 318.01 | bwd_microstep: 451.35 | bwd_inner_microstep: 451.09 | bwd_allreduce_microstep: 0.20 | step_microstep: 0.19 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 831 +[2025-05-15 01:05:55,145] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.04 | optimizer_step: 18.31 +[2025-05-15 01:05:55,146] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 224.06 | bwd_microstep: 517.87 | bwd_inner_microstep: 308.93 | bwd_allreduce_microstep: 208.88 | step_microstep: 26.36 +[2025-05-15 01:05:55,146] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2628.84 | bwd: 4025.92 | bwd_inner: 3815.98 | bwd_allreduce: 209.30 | step: 32.69 + 58%|█████▊ | 325/558 [37:50<26:43, 6.88s/it] {'loss': 6.205, 'grad_norm': 33.214111328125, 'learning_rate': 3.9197705464161674e-16, 'epoch': 0.17} + 58%|█████▊ | 325/558 [37:50<26:43, 6.88s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2003 +[2025-05-15 01:05:56,197] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 362.17 | bwd_microstep: 661.67 | bwd_inner_microstep: 661.64 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.31 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1928 +[2025-05-15 01:05:57,049] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 293.02 | bwd_microstep: 538.66 | bwd_inner_microstep: 538.61 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-15 01:05:57,919] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 443.43 | bwd_microstep: 393.46 | bwd_inner_microstep: 393.43 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-15 01:05:58,956] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 393.58 | bwd_microstep: 622.34 | bwd_inner_microstep: 621.95 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-15 01:05:59,768] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 248.11 | bwd_microstep: 541.95 | bwd_inner_microstep: 541.91 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-15 01:06:00,624] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 429.31 | bwd_microstep: 391.12 | bwd_inner_microstep: 390.61 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.65 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-15 01:06:01,650] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 401.29 | bwd_microstep: 605.46 | bwd_inner_microstep: 605.21 | bwd_allreduce_microstep: 0.10 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-15 01:06:02,905] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.02 | optimizer_step: 28.59 +[2025-05-15 01:06:02,906] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 263.62 | bwd_microstep: 938.37 | bwd_inner_microstep: 462.10 | bwd_allreduce_microstep: 476.24 | step_microstep: 37.82 +[2025-05-15 01:06:02,906] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2834.47 | bwd: 4693.03 | bwd_inner: 4215.99 | bwd_allreduce: 476.37 | step: 45.90 + 58%|█████▊ | 326/558 [37:58<27:37, 7.15s/it] {'loss': 4.9213, 'grad_norm': 28.801258087158203, 'learning_rate': 3.891439581578604e-16, 'epoch': 0.18} + 58%|█████▊ | 326/558 [37:58<27:37, 7.15s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1900 +[2025-05-15 01:06:03,826] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 285.10 | bwd_microstep: 609.63 | bwd_inner_microstep: 609.60 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1891 +[2025-05-15 01:06:04,655] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 376.82 | bwd_microstep: 418.38 | bwd_inner_microstep: 418.34 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.79 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1892 +[2025-05-15 01:06:05,621] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 432.43 | bwd_microstep: 510.16 | bwd_inner_microstep: 509.95 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-15 01:06:06,567] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 314.17 | bwd_microstep: 611.13 | bwd_inner_microstep: 611.09 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.50 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-15 01:06:07,386] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 369.01 | bwd_microstep: 415.68 | bwd_inner_microstep: 415.64 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.83 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-15 01:06:08,378] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 407.50 | bwd_microstep: 557.15 | bwd_inner_microstep: 556.94 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 497 +[2025-05-15 01:06:08,650] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 83.31 | bwd_microstep: 172.61 | bwd_inner_microstep: 172.57 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.74 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1966 +[2025-05-15 01:06:09,801] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 1.64 | optimizer_step: 12.73 +[2025-05-15 01:06:09,802] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 420.58 | bwd_microstep: 688.21 | bwd_inner_microstep: 609.92 | bwd_allreduce_microstep: 78.24 | step_microstep: 19.41 +[2025-05-15 01:06:09,803] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2688.87 | bwd: 3982.98 | bwd_inner: 3904.17 | bwd_allreduce: 78.41 | step: 29.87 + 59%|█████▊ | 327/558 [38:05<27:13, 7.07s/it] {'loss': 2.1466, 'grad_norm': 4.47450590133667, 'learning_rate': 3.86314599881244e-16, 'epoch': 0.18} + 59%|█████▊ | 327/558 [38:05<27:13, 7.07s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1907 +[2025-05-15 01:06:10,390] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.42 | bwd_microstep: 375.63 | bwd_inner_microstep: 375.59 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.86 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1887 +[2025-05-15 01:06:11,415] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 416.16 | bwd_microstep: 584.31 | bwd_inner_microstep: 584.09 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.18 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 329 +[2025-05-15 01:06:11,663] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 89.87 | bwd_microstep: 138.74 | bwd_inner_microstep: 138.70 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.33 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-15 01:06:12,691] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 400.86 | bwd_microstep: 605.66 | bwd_inner_microstep: 605.47 | bwd_allreduce_microstep: 0.18 | step_microstep: 0.17 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-15 01:06:13,500] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 218.95 | bwd_microstep: 571.38 | bwd_inner_microstep: 571.33 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-15 01:06:14,355] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 424.37 | bwd_microstep: 395.59 | bwd_inner_microstep: 395.19 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.24 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-15 01:06:15,389] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 393.18 | bwd_microstep: 617.39 | bwd_inner_microstep: 617.18 | bwd_allreduce_microstep: 0.19 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1905 +[2025-05-15 01:06:16,646] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.01 | optimizer_gradients: 2.08 | optimizer_step: 18.71 +[2025-05-15 01:06:16,646] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 249.97 | bwd_microstep: 957.61 | bwd_inner_microstep: 554.84 | bwd_allreduce_microstep: 402.73 | step_microstep: 27.71 +[2025-05-15 01:06:16,647] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2383.76 | bwd: 4246.33 | bwd_inner: 3842.39 | bwd_allreduce: 403.33 | step: 35.02 + 59%|█████▉ | 328/558 [38:12<26:50, 7.00s/it] {'loss': 4.6151, 'grad_norm': 15.622650146484375, 'learning_rate': 3.8348907522133787e-16, 'epoch': 0.18} + 59%|█████▉ | 328/558 [38:12<26:50, 7.00s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 408 +[2025-05-15 01:06:16,913] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 92.35 | bwd_microstep: 149.84 | bwd_inner_microstep: 149.69 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1916 +[2025-05-15 01:06:17,929] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 360.39 | bwd_microstep: 634.82 | bwd_inner_microstep: 634.77 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.54 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1890 +[2025-05-15 01:06:18,727] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 353.81 | bwd_microstep: 417.18 | bwd_inner_microstep: 417.14 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.29 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-15 01:06:19,744] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 414.69 | bwd_microstep: 575.34 | bwd_inner_microstep: 575.30 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.30 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 337 +[2025-05-15 01:06:19,984] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 79.41 | bwd_microstep: 141.98 | bwd_inner_microstep: 141.95 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.78 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-15 01:06:21,018] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 415.92 | bwd_microstep: 590.99 | bwd_inner_microstep: 590.95 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 842 +[2025-05-15 01:06:21,329] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 150.89 | bwd_microstep: 143.31 | bwd_inner_microstep: 143.10 | bwd_allreduce_microstep: 0.19 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-15 01:06:22,583] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.14 | optimizer_step: 18.21 +[2025-05-15 01:06:22,583] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 394.53 | bwd_microstep: 810.11 | bwd_inner_microstep: 617.52 | bwd_allreduce_microstep: 192.36 | step_microstep: 27.13 +[2025-05-15 01:06:22,584] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2261.97 | bwd: 3463.57 | bwd_inner: 3270.44 | bwd_allreduce: 192.66 | step: 34.51 + 59%|█████▉ | 329/558 [38:18<25:30, 6.68s/it] {'loss': 4.9006, 'grad_norm': 24.974180221557617, 'learning_rate': 3.806674794584374e-16, 'epoch': 0.18} + 59%|█████▉ | 329/558 [38:18<25:30, 6.68s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-15 01:06:23,565] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 339.87 | bwd_microstep: 614.27 | bwd_inner_microstep: 614.21 | bwd_allreduce_microstep: 0.02 | step_microstep: 2.37 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-15 01:06:24,338] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 351.94 | bwd_microstep: 387.45 | bwd_inner_microstep: 387.41 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.83 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-15 01:06:25,376] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 401.28 | bwd_microstep: 607.26 | bwd_inner_microstep: 607.23 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.31 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-15 01:06:26,206] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 223.89 | bwd_microstep: 582.75 | bwd_inner_microstep: 582.72 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.30 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-15 01:06:27,045] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 406.21 | bwd_microstep: 398.82 | bwd_inner_microstep: 398.77 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.79 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-15 01:06:28,070] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 401.10 | bwd_microstep: 601.07 | bwd_inner_microstep: 600.68 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-15 01:06:28,880] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 245.75 | bwd_microstep: 542.18 | bwd_inner_microstep: 542.16 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 828 +[2025-05-15 01:06:29,611] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.10 | optimizer_step: 17.98 +[2025-05-15 01:06:29,612] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 223.51 | bwd_microstep: 449.24 | bwd_inner_microstep: 264.80 | bwd_allreduce_microstep: 184.38 | step_microstep: 26.50 +[2025-05-15 01:06:29,612] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2593.54 | bwd: 4183.03 | bwd_inner: 3997.98 | bwd_allreduce: 184.64 | step: 39.62 + 59%|█████▉ | 330/558 [38:25<25:47, 6.79s/it] {'loss': 6.6934, 'grad_norm': 28.62332534790039, 'learning_rate': 3.7784990774035126e-16, 'epoch': 0.18} + 59%|█████▉ | 330/558 [38:25<25:47, 6.79s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1883 +[2025-05-15 01:06:30,598] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 342.21 | bwd_microstep: 617.85 | bwd_inner_microstep: 617.81 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.31 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 342 +[2025-05-15 01:06:30,866] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 91.64 | bwd_microstep: 143.13 | bwd_inner_microstep: 142.68 | bwd_allreduce_microstep: 0.42 | step_microstep: 0.73 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-15 01:06:31,719] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 227.93 | bwd_microstep: 603.28 | bwd_inner_microstep: 603.24 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.28 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-15 01:06:32,546] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 404.59 | bwd_microstep: 388.23 | bwd_inner_microstep: 388.21 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.76 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-15 01:06:33,586] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 405.74 | bwd_microstep: 606.59 | bwd_inner_microstep: 606.55 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.32 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-15 01:06:34,389] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 248.41 | bwd_microstep: 531.54 | bwd_inner_microstep: 531.51 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-15 01:06:35,350] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 429.62 | bwd_microstep: 500.83 | bwd_inner_microstep: 500.68 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-15 01:06:36,576] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.10 | optimizer_step: 18.34 +[2025-05-15 01:06:36,576] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 274.95 | bwd_microstep: 904.41 | bwd_inner_microstep: 601.10 | bwd_allreduce_microstep: 303.27 | step_microstep: 27.11 +[2025-05-15 01:06:36,577] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2425.04 | bwd: 4295.87 | bwd_inner: 3991.80 | bwd_allreduce: 303.80 | step: 38.96 + 59%|█████▉ | 331/558 [38:32<25:52, 6.84s/it] {'loss': 5.8552, 'grad_norm': 10.428556442260742, 'learning_rate': 3.7503645507919175e-16, 'epoch': 0.18} + 59%|█████▉ | 331/558 [38:32<25:52, 6.84s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1886 +[2025-05-15 01:06:37,398] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 243.93 | bwd_microstep: 548.92 | bwd_inner_microstep: 548.90 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.28 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1899 +[2025-05-15 01:06:38,315] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 424.69 | bwd_microstep: 461.86 | bwd_inner_microstep: 461.70 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-15 01:06:39,296] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 346.90 | bwd_microstep: 613.87 | bwd_inner_microstep: 613.83 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-15 01:06:40,098] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 340.82 | bwd_microstep: 425.46 | bwd_inner_microstep: 425.41 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.86 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-15 01:06:41,107] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 440.71 | bwd_microstep: 542.75 | bwd_inner_microstep: 542.45 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-15 01:06:42,008] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 269.67 | bwd_microstep: 608.69 | bwd_inner_microstep: 608.63 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 331 +[2025-05-15 01:06:42,302] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 103.71 | bwd_microstep: 157.79 | bwd_inner_microstep: 157.77 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.71 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-15 01:06:43,534] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.01 | optimizer_gradients: 2.08 | optimizer_step: 19.33 +[2025-05-15 01:06:43,535] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 247.94 | bwd_microstep: 937.36 | bwd_inner_microstep: 446.98 | bwd_allreduce_microstep: 490.35 | step_microstep: 27.45 +[2025-05-15 01:06:43,535] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2418.34 | bwd: 4296.72 | bwd_inner: 3805.78 | bwd_allreduce: 490.57 | step: 37.20 + 59%|█████▉ | 332/558 [38:39<25:53, 6.88s/it] {'loss': 3.9437, 'grad_norm': 20.763408660888672, 'learning_rate': 3.722272163481715e-16, 'epoch': 0.18} + 59%|█████▉ | 332/558 [38:39<25:53, 6.88s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-15 01:06:44,380] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 224.31 | bwd_microstep: 590.97 | bwd_inner_microstep: 590.93 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-15 01:06:45,204] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 405.05 | bwd_microstep: 386.77 | bwd_inner_microstep: 386.74 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.27 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1096 +[2025-05-15 01:06:45,832] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 229.80 | bwd_microstep: 373.35 | bwd_inner_microstep: 373.31 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.47 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-15 01:06:46,653] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 384.82 | bwd_microstep: 400.63 | bwd_inner_microstep: 400.60 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.78 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-15 01:06:47,670] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 410.68 | bwd_microstep: 582.00 | bwd_inner_microstep: 581.04 | bwd_allreduce_microstep: 0.93 | step_microstep: 0.21 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 837 +[2025-05-15 01:06:47,970] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 143.18 | bwd_microstep: 137.02 | bwd_inner_microstep: 136.80 | bwd_allreduce_microstep: 0.19 | step_microstep: 0.18 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 834 +[2025-05-15 01:06:48,455] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 199.16 | bwd_microstep: 262.03 | bwd_inner_microstep: 261.99 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.33 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-15 01:06:49,927] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.01 | optimizer_gradients: 2.06 | optimizer_step: 18.68 +[2025-05-15 01:06:49,928] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 426.22 | bwd_microstep: 986.22 | bwd_inner_microstep: 408.09 | bwd_allreduce_microstep: 578.09 | step_microstep: 27.95 +[2025-05-15 01:06:49,928] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2423.21 | bwd: 3718.98 | bwd_inner: 3139.48 | bwd_allreduce: 578.15 | step: 37.56 + 60%|█████▉ | 333/558 [38:45<25:14, 6.73s/it] {'loss': 4.831, 'grad_norm': 27.219314575195312, 'learning_rate': 3.6942228627840425e-16, 'epoch': 0.18} + 60%|█████▉ | 333/558 [38:45<25:14, 6.73s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1890 +[2025-05-15 01:06:50,754] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 247.54 | bwd_microstep: 549.36 | bwd_inner_microstep: 549.33 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 343 +[2025-05-15 01:06:51,036] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 106.63 | bwd_microstep: 143.14 | bwd_inner_microstep: 143.12 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.48 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-15 01:06:51,829] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 349.06 | bwd_microstep: 412.33 | bwd_inner_microstep: 412.28 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.80 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-15 01:06:52,831] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 409.38 | bwd_microstep: 566.99 | bwd_inner_microstep: 566.70 | bwd_allreduce_microstep: 0.25 | step_microstep: 0.24 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1349 +[2025-05-15 01:06:53,390] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 232.94 | bwd_microstep: 305.13 | bwd_inner_microstep: 305.08 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.81 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 831 +[2025-05-15 01:06:53,926] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 200.70 | bwd_microstep: 309.48 | bwd_inner_microstep: 309.45 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1886 +[2025-05-15 01:06:54,741] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 385.61 | bwd_microstep: 397.55 | bwd_inner_microstep: 397.33 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-15 01:06:55,996] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.16 | optimizer_step: 17.76 +[2025-05-15 01:06:55,997] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 396.35 | bwd_microstep: 810.25 | bwd_inner_microstep: 618.35 | bwd_allreduce_microstep: 191.85 | step_microstep: 26.25 +[2025-05-15 01:06:55,998] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2328.19 | bwd: 3494.23 | bwd_inner: 3301.66 | bwd_allreduce: 192.16 | step: 37.50 + 60%|█████▉ | 334/558 [38:51<24:23, 6.53s/it] {'loss': 4.6441, 'grad_norm': 23.52041244506836, 'learning_rate': 3.6662175945570965e-16, 'epoch': 0.18} + 60%|█████▉ | 334/558 [38:51<24:23, 6.53s/it]dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1384 +[2025-05-15 01:06:56,692] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 218.59 | bwd_microstep: 450.01 | bwd_inner_microstep: 449.97 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 853 +[2025-05-15 01:06:57,210] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 225.56 | bwd_microstep: 263.21 | bwd_inner_microstep: 263.00 | bwd_allreduce_microstep: 0.18 | step_microstep: 0.17 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 339 +[2025-05-15 01:06:57,472] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 97.83 | bwd_microstep: 143.78 | bwd_inner_microstep: 143.74 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.63 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-15 01:06:58,503] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 402.51 | bwd_microstep: 605.43 | bwd_inner_microstep: 605.38 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.25 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-15 01:06:59,132] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 271.65 | bwd_microstep: 335.01 | bwd_inner_microstep: 334.99 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.89 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-15 01:07:00,149] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 405.33 | bwd_microstep: 586.65 | bwd_inner_microstep: 586.43 | bwd_allreduce_microstep: 0.19 | step_microstep: 0.24 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1444 +[2025-05-15 01:07:00,754] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 201.29 | bwd_microstep: 383.97 | bwd_inner_microstep: 383.92 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.23 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 324 +[2025-05-15 01:07:01,395] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.07 | optimizer_step: 19.29 +[2025-05-15 01:07:01,395] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 102.65 | bwd_microstep: 482.11 | bwd_inner_microstep: 150.22 | bwd_allreduce_microstep: 331.85 | step_microstep: 27.63 +[2025-05-15 01:07:01,396] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 1925.43 | bwd: 3250.17 | bwd_inner: 2917.66 | bwd_allreduce: 332.27 | step: 34.40 + 60%|██████ | 335/558 [38:56<23:00, 6.19s/it] {'loss': 3.155, 'grad_norm': 15.79725456237793, 'learning_rate': 3.638257303174246e-16, 'epoch': 0.18} + 60%|██████ | 335/558 [38:56<23:00, 6.19s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1899 +[2025-05-15 01:07:02,262] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 248.27 | bwd_microstep: 588.84 | bwd_inner_microstep: 588.80 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 365 +[2025-05-15 01:07:02,535] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 109.03 | bwd_microstep: 132.96 | bwd_inner_microstep: 132.93 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.20 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1374 +[2025-05-15 01:07:03,074] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 262.11 | bwd_microstep: 258.37 | bwd_inner_microstep: 257.85 | bwd_allreduce_microstep: 0.49 | step_microstep: 0.05 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 340 +[2025-05-15 01:07:03,344] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 106.13 | bwd_microstep: 141.81 | bwd_inner_microstep: 141.76 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-15 01:07:04,302] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 439.18 | bwd_microstep: 486.21 | bwd_inner_microstep: 485.87 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.22 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-15 01:07:05,261] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 322.30 | bwd_microstep: 615.05 | bwd_inner_microstep: 615.01 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.56 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1092 +[2025-05-15 01:07:05,756] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 229.66 | bwd_microstep: 235.91 | bwd_inner_microstep: 235.75 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-15 01:07:06,999] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.01 | optimizer_gradients: 2.04 | optimizer_step: 19.45 +[2025-05-15 01:07:06,999] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 325.90 | bwd_microstep: 872.56 | bwd_inner_microstep: 613.94 | bwd_allreduce_microstep: 258.58 | step_microstep: 27.01 +[2025-05-15 01:07:07,000] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2042.53 | bwd: 3331.75 | bwd_inner: 3072.01 | bwd_allreduce: 259.30 | step: 34.85 + 60%|██████ | 336/558 [39:02<22:15, 6.02s/it] {'loss': 3.7859, 'grad_norm': 29.16095733642578, 'learning_rate': 3.610342931492182e-16, 'epoch': 0.18} + 60%|██████ | 336/558 [39:02<22:15, 6.02s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-15 01:07:07,668] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.73 | bwd_microstep: 449.64 | bwd_inner_microstep: 449.18 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.22 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 851 +[2025-05-15 01:07:08,247] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 225.50 | bwd_microstep: 320.28 | bwd_inner_microstep: 320.22 | bwd_allreduce_microstep: 0.02 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1887 +[2025-05-15 01:07:09,047] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 328.72 | bwd_microstep: 446.59 | bwd_inner_microstep: 446.55 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-15 01:07:10,029] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 439.05 | bwd_microstep: 513.69 | bwd_inner_microstep: 513.54 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 840 +[2025-05-15 01:07:10,348] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.58 | bwd_microstep: 206.62 | bwd_inner_microstep: 206.60 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.86 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-15 01:07:11,373] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 414.51 | bwd_microstep: 585.00 | bwd_inner_microstep: 584.96 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.26 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 829 +[2025-05-15 01:07:11,698] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 130.89 | bwd_microstep: 173.63 | bwd_inner_microstep: 173.60 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.81 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-15 01:07:12,911] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.07 | optimizer_gradients: 2.09 | optimizer_step: 17.84 +[2025-05-15 01:07:12,911] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 400.71 | bwd_microstep: 760.46 | bwd_inner_microstep: 602.16 | bwd_allreduce_microstep: 158.25 | step_microstep: 26.32 +[2025-05-15 01:07:12,912] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2223.65 | bwd: 3455.93 | bwd_inner: 3296.84 | bwd_allreduce: 158.39 | step: 34.98 + 60%|██████ | 337/558 [39:08<22:02, 5.98s/it] {'loss': 5.6369, 'grad_norm': 27.996456146240234, 'learning_rate': 3.5824754208191294e-16, 'epoch': 0.18} + 60%|██████ | 337/558 [39:08<22:02, 5.98s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-15 01:07:13,902] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 344.62 | bwd_microstep: 618.78 | bwd_inner_microstep: 618.75 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1886 +[2025-05-15 01:07:14,715] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 353.16 | bwd_microstep: 425.61 | bwd_inner_microstep: 425.55 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.86 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-15 01:07:15,614] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 426.91 | bwd_microstep: 447.93 | bwd_inner_microstep: 447.78 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-15 01:07:16,303] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 296.12 | bwd_microstep: 376.48 | bwd_inner_microstep: 376.44 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.87 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-15 01:07:17,328] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 414.77 | bwd_microstep: 583.55 | bwd_inner_microstep: 583.30 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-15 01:07:18,160] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 221.90 | bwd_microstep: 588.17 | bwd_inner_microstep: 588.11 | bwd_allreduce_microstep: 0.02 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-15 01:07:18,985] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 408.78 | bwd_microstep: 381.39 | bwd_inner_microstep: 381.17 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 328 +[2025-05-15 01:07:19,761] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.04 | optimizer_step: 17.26 +[2025-05-15 01:07:19,761] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 91.33 | bwd_microstep: 644.23 | bwd_inner_microstep: 154.62 | bwd_allreduce_microstep: 489.57 | step_microstep: 25.65 +[2025-05-15 01:07:19,762] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2557.55 | bwd: 4066.16 | bwd_inner: 3575.84 | bwd_allreduce: 489.93 | step: 34.44 + 61%|██████ | 338/558 [39:15<22:53, 6.24s/it] {'loss': 3.718, 'grad_norm': 9.953930854797363, 'learning_rate': 3.5546557108830925e-16, 'epoch': 0.18} + 61%|██████ | 338/558 [39:15<22:53, 6.24s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1902 +[2025-05-15 01:07:20,620] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 224.44 | bwd_microstep: 602.94 | bwd_inner_microstep: 602.88 | bwd_allreduce_microstep: 0.02 | step_microstep: 2.60 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-15 01:07:21,452] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 406.32 | bwd_microstep: 393.05 | bwd_inner_microstep: 392.84 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-15 01:07:22,495] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 398.76 | bwd_microstep: 622.35 | bwd_inner_microstep: 621.92 | bwd_allreduce_microstep: 0.21 | step_microstep: 0.21 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-15 01:07:23,301] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 282.94 | bwd_microstep: 500.22 | bwd_inner_microstep: 500.16 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.53 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-15 01:07:24,237] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 443.49 | bwd_microstep: 460.15 | bwd_inner_microstep: 459.99 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-15 01:07:25,197] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 329.03 | bwd_microstep: 609.64 | bwd_inner_microstep: 609.60 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-15 01:07:26,012] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 363.42 | bwd_microstep: 416.03 | bwd_inner_microstep: 416.01 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.85 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2131 +[2025-05-15 01:07:27,163] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.07 | optimizer_step: 19.80 +[2025-05-15 01:07:27,164] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 445.04 | bwd_microstep: 652.60 | bwd_inner_microstep: 593.89 | bwd_allreduce_microstep: 58.60 | step_microstep: 28.29 +[2025-05-15 01:07:27,165] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2893.43 | bwd: 4256.97 | bwd_inner: 4197.34 | bwd_allreduce: 58.74 | step: 38.17 + 61%|██████ | 339/558 [39:22<24:03, 6.59s/it] {'loss': 4.5035, 'grad_norm': 16.814441680908203, 'learning_rate': 3.526884739800177e-16, 'epoch': 0.18} + 61%|██████ | 339/558 [39:22<24:03, 6.59s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1939 +[2025-05-15 01:07:28,244] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 416.21 | bwd_microstep: 633.06 | bwd_inner_microstep: 633.02 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-15 01:07:29,050] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 273.66 | bwd_microstep: 510.02 | bwd_inner_microstep: 509.96 | bwd_allreduce_microstep: 0.02 | step_microstep: 2.29 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 847 +[2025-05-15 01:07:29,600] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 224.05 | bwd_microstep: 292.97 | bwd_inner_microstep: 292.91 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.64 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1356 +[2025-05-15 01:07:30,161] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 253.48 | bwd_microstep: 286.98 | bwd_inner_microstep: 286.93 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.74 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-15 01:07:31,195] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 419.65 | bwd_microstep: 587.26 | bwd_inner_microstep: 587.23 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.27 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-15 01:07:31,998] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 285.56 | bwd_microstep: 494.69 | bwd_inner_microstep: 494.65 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-15 01:07:32,922] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 437.97 | bwd_microstep: 455.89 | bwd_inner_microstep: 455.58 | bwd_allreduce_microstep: 0.14 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-15 01:07:34,166] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.12 | optimizer_step: 26.63 +[2025-05-15 01:07:34,167] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 342.99 | bwd_microstep: 846.96 | bwd_inner_microstep: 603.23 | bwd_allreduce_microstep: 243.69 | step_microstep: 36.17 +[2025-05-15 01:07:34,167] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2653.56 | bwd: 4108.77 | bwd_inner: 3863.58 | bwd_allreduce: 243.88 | step: 45.76 + 61%|██████ | 340/558 [39:29<24:23, 6.71s/it] {'loss': 5.7629, 'grad_norm': 42.286895751953125, 'learning_rate': 3.4991634440429543e-16, 'epoch': 0.18} + 61%|██████ | 340/558 [39:29<24:23, 6.71s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1947 +[2025-05-15 01:07:35,117] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 291.39 | bwd_microstep: 634.33 | bwd_inner_microstep: 634.30 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1907 +[2025-05-15 01:07:35,951] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 366.70 | bwd_microstep: 433.06 | bwd_inner_microstep: 433.03 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.79 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1887 +[2025-05-15 01:07:36,914] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 448.43 | bwd_microstep: 486.47 | bwd_inner_microstep: 486.15 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.10 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 337 +[2025-05-15 01:07:37,151] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 81.96 | bwd_microstep: 137.59 | bwd_inner_microstep: 137.56 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.78 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1356 +[2025-05-15 01:07:37,943] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 297.93 | bwd_microstep: 467.25 | bwd_inner_microstep: 467.22 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.24 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-15 01:07:38,734] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 290.97 | bwd_microstep: 477.01 | bwd_inner_microstep: 476.97 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-15 01:07:39,640] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 442.47 | bwd_microstep: 431.02 | bwd_inner_microstep: 430.87 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 317 +[2025-05-15 01:07:40,337] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 1.64 | optimizer_step: 12.71 +[2025-05-15 01:07:40,338] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 89.68 | bwd_microstep: 572.53 | bwd_inner_microstep: 155.57 | bwd_allreduce_microstep: 416.91 | step_microstep: 19.42 +[2025-05-15 01:07:40,338] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2309.48 | bwd: 3639.28 | bwd_inner: 3221.74 | bwd_allreduce: 417.16 | step: 30.14 + 61%|██████ | 341/558 [39:35<23:41, 6.55s/it] {'loss': 6.1052, 'grad_norm': 30.492334365844727, 'learning_rate': 3.471492758408879e-16, 'epoch': 0.18} + 61%|██████ | 341/558 [39:35<23:41, 6.55s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1920 +[2025-05-15 01:07:41,113] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 303.21 | bwd_microstep: 449.07 | bwd_inner_microstep: 449.02 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.01 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-15 01:07:42,125] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 442.61 | bwd_microstep: 538.20 | bwd_inner_microstep: 537.92 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-15 01:07:43,001] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 247.14 | bwd_microstep: 603.80 | bwd_inner_microstep: 603.76 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 334 +[2025-05-15 01:07:43,262] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 103.44 | bwd_microstep: 122.72 | bwd_inner_microstep: 122.69 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.31 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-15 01:07:44,039] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 338.33 | bwd_microstep: 419.17 | bwd_inner_microstep: 419.13 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.79 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-15 01:07:45,044] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 433.74 | bwd_microstep: 547.27 | bwd_inner_microstep: 547.05 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.24 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-15 01:07:45,834] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 320.62 | bwd_microstep: 448.49 | bwd_inner_microstep: 448.27 | bwd_allreduce_microstep: 0.19 | step_microstep: 0.26 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2299 +[2025-05-15 01:07:47,474] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.01 | optimizer_gradients: 2.07 | optimizer_step: 18.46 +[2025-05-15 01:07:47,474] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 498.54 | bwd_microstep: 1080.44 | bwd_inner_microstep: 498.28 | bwd_allreduce_microstep: 582.12 | step_microstep: 27.12 +[2025-05-15 01:07:47,475] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2687.59 | bwd: 4209.14 | bwd_inner: 3626.19 | bwd_allreduce: 582.45 | step: 36.19 + 61%|██████▏ | 342/558 [39:43<24:13, 6.73s/it] {'loss': 6.1136, 'grad_norm': 22.651092529296875, 'learning_rate': 3.4438736159887664e-16, 'epoch': 0.18} + 61%|██████▏ | 342/558 [39:43<24:13, 6.73s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-15 01:07:48,286] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 242.41 | bwd_microstep: 540.53 | bwd_inner_microstep: 540.47 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1361 +[2025-05-15 01:07:49,049] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 329.01 | bwd_microstep: 404.10 | bwd_inner_microstep: 403.95 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-15 01:07:49,903] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 233.72 | bwd_microstep: 597.69 | bwd_inner_microstep: 597.65 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.37 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-15 01:07:50,743] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 398.16 | bwd_microstep: 407.08 | bwd_inner_microstep: 407.03 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.85 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-15 01:07:51,760] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 408.42 | bwd_microstep: 585.37 | bwd_inner_microstep: 585.33 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-15 01:07:52,584] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 221.71 | bwd_microstep: 579.38 | bwd_inner_microstep: 579.34 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.43 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-15 01:07:53,434] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 416.73 | bwd_microstep: 397.87 | bwd_inner_microstep: 397.83 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.80 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-15 01:07:54,679] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.10 | optimizer_step: 17.70 +[2025-05-15 01:07:54,680] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 402.62 | bwd_microstep: 791.04 | bwd_inner_microstep: 600.64 | bwd_allreduce_microstep: 190.34 | step_microstep: 26.37 +[2025-05-15 01:07:54,680] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2652.78 | bwd: 4303.09 | bwd_inner: 4112.26 | bwd_allreduce: 190.47 | step: 37.50 + 61%|██████▏ | 343/558 [39:50<24:37, 6.87s/it] {'loss': 4.7938, 'grad_norm': 20.35024070739746, 'learning_rate': 3.416306948135333e-16, 'epoch': 0.18} + 61%|██████▏ | 343/558 [39:50<24:37, 6.87s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1891 +[2025-05-15 01:07:55,658] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 337.24 | bwd_microstep: 613.98 | bwd_inner_microstep: 613.95 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.55 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1891 +[2025-05-15 01:07:56,474] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 324.35 | bwd_microstep: 456.57 | bwd_inner_microstep: 454.00 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.61 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-15 01:07:57,404] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 437.86 | bwd_microstep: 460.38 | bwd_inner_microstep: 460.07 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.10 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 331 +[2025-05-15 01:07:57,642] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 85.10 | bwd_microstep: 135.31 | bwd_inner_microstep: 135.26 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.81 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-15 01:07:58,644] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 415.23 | bwd_microstep: 561.60 | bwd_inner_microstep: 561.29 | bwd_allreduce_microstep: 0.14 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-15 01:07:59,536] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 267.76 | bwd_microstep: 601.82 | bwd_inner_microstep: 601.80 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.40 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1361 +[2025-05-15 01:08:00,132] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 293.98 | bwd_microstep: 268.64 | bwd_inner_microstep: 268.21 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.31 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-15 01:08:01,348] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.18 | optimizer_step: 18.21 +[2025-05-15 01:08:01,349] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 392.94 | bwd_microstep: 775.18 | bwd_inner_microstep: 620.62 | bwd_allreduce_microstep: 154.32 | step_microstep: 26.94 +[2025-05-15 01:08:01,349] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2554.41 | bwd: 3873.52 | bwd_inner: 3715.33 | bwd_allreduce: 154.63 | step: 36.83 + 62%|██████▏ | 344/558 [39:56<24:17, 6.81s/it] {'loss': 3.247, 'grad_norm': 8.135909080505371, 'learning_rate': 3.3887936844317794e-16, 'epoch': 0.19} + 62%|██████▏ | 344/558 [39:56<24:17, 6.81s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1913 +[2025-05-15 01:08:02,351] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 349.45 | bwd_microstep: 625.79 | bwd_inner_microstep: 625.73 | bwd_allreduce_microstep: 0.02 | step_microstep: 2.29 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1412 +[2025-05-15 01:08:02,938] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 255.84 | bwd_microstep: 297.95 | bwd_inner_microstep: 297.91 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.82 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-15 01:08:03,968] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 409.35 | bwd_microstep: 594.42 | bwd_inner_microstep: 594.37 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.19 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 850 +[2025-05-15 01:08:04,310] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.70 | bwd_microstep: 228.48 | bwd_inner_microstep: 228.44 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.79 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 337 +[2025-05-15 01:08:04,571] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 91.84 | bwd_microstep: 142.82 | bwd_inner_microstep: 142.78 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 844 +[2025-05-15 01:08:05,101] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 223.44 | bwd_microstep: 275.96 | bwd_inner_microstep: 275.75 | bwd_allreduce_microstep: 0.18 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-15 01:08:05,811] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 246.88 | bwd_microstep: 443.47 | bwd_inner_microstep: 443.43 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.23 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1365 +[2025-05-15 01:08:06,736] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.07 | optimizer_gradients: 2.04 | optimizer_step: 18.07 +[2025-05-15 01:08:06,736] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 330.61 | bwd_microstep: 540.34 | bwd_inner_microstep: 426.59 | bwd_allreduce_microstep: 113.69 | step_microstep: 26.73 +[2025-05-15 01:08:06,737] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2002.09 | bwd: 3149.23 | bwd_inner: 3034.99 | bwd_allreduce: 113.94 | step: 35.60 + 62%|██████▏ | 345/558 [40:02<22:39, 6.38s/it] {'loss': 3.8081, 'grad_norm': 11.836846351623535, 'learning_rate': 3.3613347526604558e-16, 'epoch': 0.19} + 62%|██████▏ | 345/558 [40:02<22:39, 6.38s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1902 +[2025-05-15 01:08:07,744] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 361.94 | bwd_microstep: 618.73 | bwd_inner_microstep: 618.67 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1890 +[2025-05-15 01:08:08,564] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 294.38 | bwd_microstep: 491.40 | bwd_inner_microstep: 491.36 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 850 +[2025-05-15 01:08:09,111] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 223.01 | bwd_microstep: 294.01 | bwd_inner_microstep: 293.77 | bwd_allreduce_microstep: 0.20 | step_microstep: 0.28 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-15 01:08:09,912] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 352.70 | bwd_microstep: 425.70 | bwd_inner_microstep: 425.42 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-15 01:08:10,938] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 371.76 | bwd_microstep: 631.71 | bwd_inner_microstep: 631.23 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.27 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-15 01:08:11,782] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 357.04 | bwd_microstep: 462.93 | bwd_inner_microstep: 462.58 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-15 01:08:12,749] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 334.72 | bwd_microstep: 610.52 | bwd_inner_microstep: 610.47 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.62 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 328 +[2025-05-15 01:08:13,238] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.01 | optimizer_gradients: 1.99 | optimizer_step: 18.28 +[2025-05-15 01:08:13,239] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 96.50 | bwd_microstep: 336.95 | bwd_inner_microstep: 127.58 | bwd_allreduce_microstep: 209.35 | step_microstep: 26.88 +[2025-05-15 01:08:13,239] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2392.02 | bwd: 3872.02 | bwd_inner: 3661.22 | bwd_allreduce: 209.85 | step: 35.06 + 62%|██████▏ | 346/558 [40:08<22:40, 6.42s/it] {'loss': 6.9025, 'grad_norm': 24.03380584716797, 'learning_rate': 3.333931078771567e-16, 'epoch': 0.19} + 62%|██████▏ | 346/558 [40:08<22:40, 6.42s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1919 +[2025-05-15 01:08:13,958] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 328.84 | bwd_microstep: 360.47 | bwd_inner_microstep: 360.43 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.83 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1914 +[2025-05-15 01:08:14,995] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 418.11 | bwd_microstep: 591.44 | bwd_inner_microstep: 591.41 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1902 +[2025-05-15 01:08:15,815] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 358.44 | bwd_microstep: 441.06 | bwd_inner_microstep: 440.73 | bwd_allreduce_microstep: 0.14 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-15 01:08:16,809] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 351.79 | bwd_microstep: 624.03 | bwd_inner_microstep: 623.97 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-15 01:08:17,648] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 343.34 | bwd_microstep: 461.91 | bwd_inner_microstep: 461.61 | bwd_allreduce_microstep: 0.14 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-15 01:08:18,630] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 346.10 | bwd_microstep: 616.00 | bwd_inner_microstep: 615.97 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-15 01:08:19,520] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 360.57 | bwd_microstep: 494.35 | bwd_inner_microstep: 494.05 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-15 01:08:20,757] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.01 | optimizer_gradients: 2.08 | optimizer_step: 18.54 +[2025-05-15 01:08:20,758] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 249.79 | bwd_microstep: 939.21 | bwd_inner_microstep: 608.41 | bwd_allreduce_microstep: 330.77 | step_microstep: 27.85 +[2025-05-15 01:08:20,758] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2756.93 | bwd: 4528.48 | bwd_inner: 4196.77 | bwd_allreduce: 331.15 | step: 35.59 + 62%|██████▏ | 347/558 [40:16<23:44, 6.75s/it] {'loss': 5.9683, 'grad_norm': 38.34598159790039, 'learning_rate': 3.306583586851956e-16, 'epoch': 0.19} + 62%|██████▏ | 347/558 [40:16<23:44, 6.75s/it]dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1397 +[2025-05-15 01:08:21,311] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 261.03 | bwd_microstep: 264.33 | bwd_inner_microstep: 264.15 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1883 +[2025-05-15 01:08:22,048] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 191.01 | bwd_microstep: 528.71 | bwd_inner_microstep: 528.65 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-15 01:08:23,036] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 437.51 | bwd_microstep: 515.26 | bwd_inner_microstep: 515.23 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.24 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1360 +[2025-05-15 01:08:23,589] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 251.48 | bwd_microstep: 282.33 | bwd_inner_microstep: 282.12 | bwd_allreduce_microstep: 0.18 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-15 01:08:24,631] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 393.40 | bwd_microstep: 624.05 | bwd_inner_microstep: 623.66 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.18 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 325 +[2025-05-15 01:08:24,878] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 97.17 | bwd_microstep: 131.86 | bwd_inner_microstep: 131.43 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.75 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-15 01:08:25,665] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 317.70 | bwd_microstep: 448.81 | bwd_inner_microstep: 448.59 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.20 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 327 +[2025-05-15 01:08:26,308] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.01 | optimizer_gradients: 2.17 | optimizer_step: 18.69 +[2025-05-15 01:08:26,309] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 104.13 | bwd_microstep: 483.31 | bwd_inner_microstep: 157.01 | bwd_allreduce_microstep: 326.27 | step_microstep: 28.50 +[2025-05-15 01:08:26,310] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2053.41 | bwd: 3278.66 | bwd_inner: 2951.07 | bwd_allreduce: 326.95 | step: 33.52 + 62%|██████▏ | 348/558 [40:21<22:21, 6.39s/it] {'loss': 3.0267, 'grad_norm': 10.637716293334961, 'learning_rate': 3.279293199093931e-16, 'epoch': 0.19} + 62%|██████▏ | 348/558 [40:21<22:21, 6.39s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1900 +[2025-05-15 01:08:27,120] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 358.06 | bwd_microstep: 422.31 | bwd_inner_microstep: 422.26 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.83 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-15 01:08:28,139] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 419.16 | bwd_microstep: 572.99 | bwd_inner_microstep: 572.92 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.81 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1895 +[2025-05-15 01:08:28,900] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 345.24 | bwd_microstep: 396.38 | bwd_inner_microstep: 396.14 | bwd_allreduce_microstep: 0.21 | step_microstep: 0.19 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 855 +[2025-05-15 01:08:29,416] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 205.20 | bwd_microstep: 287.00 | bwd_inner_microstep: 286.97 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-15 01:08:30,385] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 426.46 | bwd_microstep: 510.13 | bwd_inner_microstep: 510.10 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.24 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-15 01:08:31,148] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 347.78 | bwd_microstep: 390.96 | bwd_inner_microstep: 390.92 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.78 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 839 +[2025-05-15 01:08:31,647] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.30 | bwd_microstep: 282.91 | bwd_inner_microstep: 282.86 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 836 +[2025-05-15 01:08:32,391] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.10 | optimizer_step: 18.51 +[2025-05-15 01:08:32,392] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 216.22 | bwd_microstep: 467.90 | bwd_inner_microstep: 245.59 | bwd_allreduce_microstep: 222.11 | step_microstep: 27.73 +[2025-05-15 01:08:32,393] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2506.44 | bwd: 3330.57 | bwd_inner: 3107.76 | bwd_allreduce: 222.39 | step: 37.27 + 63%|██████▎ | 349/558 [40:27<21:56, 6.30s/it] {'loss': 5.1353, 'grad_norm': 23.45457649230957, 'learning_rate': 3.2520608357641814e-16, 'epoch': 0.19} + 63%|██████▎ | 349/558 [40:27<21:56, 6.30s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-15 01:08:33,159] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 349.51 | bwd_microstep: 394.14 | bwd_inner_microstep: 393.91 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-15 01:08:34,198] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 401.27 | bwd_microstep: 613.58 | bwd_inner_microstep: 613.36 | bwd_allreduce_microstep: 0.19 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-15 01:08:35,076] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 356.96 | bwd_microstep: 501.02 | bwd_inner_microstep: 500.86 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-15 01:08:35,977] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 273.33 | bwd_microstep: 604.33 | bwd_inner_microstep: 604.29 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.56 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1352 +[2025-05-15 01:08:36,703] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 296.60 | bwd_microstep: 393.39 | bwd_inner_microstep: 393.33 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.22 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-15 01:08:37,512] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 348.85 | bwd_microstep: 437.45 | bwd_inner_microstep: 437.31 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-15 01:08:38,096] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.20 | bwd_microstep: 375.71 | bwd_inner_microstep: 375.67 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.81 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1346 +[2025-05-15 01:08:39,118] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.54 | optimizer_gradients: 2.00 | optimizer_step: 18.53 +[2025-05-15 01:08:39,119] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 302.22 | bwd_microstep: 672.26 | bwd_inner_microstep: 467.61 | bwd_allreduce_microstep: 203.84 | step_microstep: 26.89 +[2025-05-15 01:08:39,120] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2518.91 | bwd: 3991.90 | bwd_inner: 3787.19 | bwd_allreduce: 204.19 | step: 33.08 + 63%|██████▎ | 350/558 [40:34<22:16, 6.43s/it] {'loss': 7.1429, 'grad_norm': 32.103023529052734, 'learning_rate': 3.2248874151727354e-16, 'epoch': 0.19} + 63%|██████▎ | 350/558 [40:34<22:16, 6.43s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1893 +[2025-05-15 01:08:39,939] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 364.72 | bwd_microstep: 426.37 | bwd_inner_microstep: 426.22 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1883 +[2025-05-15 01:08:40,942] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 359.24 | bwd_microstep: 622.92 | bwd_inner_microstep: 622.88 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.58 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1890 +[2025-05-15 01:08:41,843] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 357.92 | bwd_microstep: 514.42 | bwd_inner_microstep: 514.39 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-15 01:08:42,654] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 244.71 | bwd_microstep: 543.99 | bwd_inner_microstep: 543.92 | bwd_allreduce_microstep: 0.02 | step_microstep: 2.52 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 845 +[2025-05-15 01:08:43,187] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 224.90 | bwd_microstep: 277.54 | bwd_inner_microstep: 277.32 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.23 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-15 01:08:44,063] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 355.62 | bwd_microstep: 499.51 | bwd_inner_microstep: 499.48 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.24 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-15 01:08:44,874] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 243.72 | bwd_microstep: 545.51 | bwd_inner_microstep: 545.46 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.55 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-15 01:08:46,089] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.01 | optimizer_gradients: 2.10 | optimizer_step: 18.06 +[2025-05-15 01:08:46,090] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 426.90 | bwd_microstep: 728.21 | bwd_inner_microstep: 515.46 | bwd_allreduce_microstep: 212.72 | step_microstep: 27.96 +[2025-05-15 01:08:46,090] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2577.71 | bwd: 4158.50 | bwd_inner: 3945.14 | bwd_allreduce: 213.05 | step: 36.39 + 63%|██████▎ | 351/558 [40:41<22:44, 6.59s/it] {'loss': 5.7195, 'grad_norm': 24.006195068359375, 'learning_rate': 3.197773853642e-16, 'epoch': 0.19} + 63%|██████▎ | 351/558 [40:41<22:44, 6.59s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 365 +[2025-05-15 01:08:46,341] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 84.77 | bwd_microstep: 143.14 | bwd_inner_microstep: 142.81 | bwd_allreduce_microstep: 0.15 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1890 +[2025-05-15 01:08:47,325] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 346.70 | bwd_microstep: 617.10 | bwd_inner_microstep: 617.07 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.28 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-15 01:08:48,200] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 343.05 | bwd_microstep: 499.13 | bwd_inner_microstep: 498.99 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.11 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 865 +[2025-05-15 01:08:48,580] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 101.20 | bwd_microstep: 260.56 | bwd_inner_microstep: 260.53 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.76 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-15 01:08:49,588] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 412.61 | bwd_microstep: 566.51 | bwd_inner_microstep: 566.48 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.46 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-15 01:08:50,432] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 356.82 | bwd_microstep: 464.82 | bwd_inner_microstep: 464.67 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 327 +[2025-05-15 01:08:50,668] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 80.10 | bwd_microstep: 139.19 | bwd_inner_microstep: 139.14 | bwd_allreduce_microstep: 0.02 | step_microstep: 1.78 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 333 +[2025-05-15 01:08:51,361] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.05 | optimizer_step: 18.24 +[2025-05-15 01:08:51,362] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.11 | bwd_microstep: 550.12 | bwd_inner_microstep: 156.66 | bwd_allreduce_microstep: 393.43 | step_microstep: 27.51 +[2025-05-15 01:08:51,363] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 1819.32 | bwd: 3240.61 | bwd_inner: 2846.45 | bwd_allreduce: 393.72 | step: 36.11 + 63%|██████▎ | 352/558 [40:46<21:16, 6.19s/it] {'loss': 2.5904, 'grad_norm': 10.151712417602539, 'learning_rate': 3.1707210654758556e-16, 'epoch': 0.19} + 63%|██████▎ | 352/558 [40:46<21:16, 6.19s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1894 +[2025-05-15 01:08:52,223] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 355.36 | bwd_microstep: 477.63 | bwd_inner_microstep: 477.46 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-15 01:08:53,183] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 317.16 | bwd_microstep: 622.11 | bwd_inner_microstep: 622.06 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1360 +[2025-05-15 01:08:53,872] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 273.83 | bwd_microstep: 383.75 | bwd_inner_microstep: 383.71 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.21 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-15 01:08:54,714] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 219.05 | bwd_microstep: 599.41 | bwd_inner_microstep: 599.37 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 2, images per sample: 2.0, dynamic token length: 590 +[2025-05-15 01:08:55,102] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 156.30 | bwd_microstep: 200.23 | bwd_inner_microstep: 200.17 | bwd_allreduce_microstep: 0.02 | step_microstep: 1.27 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-15 01:08:55,884] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 358.86 | bwd_microstep: 403.14 | bwd_inner_microstep: 403.10 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.89 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 324 +[2025-05-15 01:08:56,130] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 92.51 | bwd_microstep: 128.06 | bwd_inner_microstep: 128.04 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.53 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 1002 +[2025-05-15 01:08:56,953] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 1.67 | optimizer_step: 13.16 +[2025-05-15 01:08:56,954] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 244.51 | bwd_microstep: 526.61 | bwd_inner_microstep: 319.13 | bwd_allreduce_microstep: 207.46 | step_microstep: 21.02 +[2025-05-15 01:08:56,955] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2017.57 | bwd: 3340.95 | bwd_inner: 3133.09 | bwd_allreduce: 207.58 | step: 31.73 + 63%|██████▎ | 353/558 [40:52<20:32, 6.01s/it] {'loss': 5.2797, 'grad_norm': 25.87888526916504, 'learning_rate': 3.1437299629288255e-16, 'epoch': 0.19} + 63%|██████▎ | 353/558 [40:52<20:32, 6.01s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-15 01:08:57,754] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 324.24 | bwd_microstep: 448.58 | bwd_inner_microstep: 448.38 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-15 01:08:58,773] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 443.52 | bwd_microstep: 547.04 | bwd_inner_microstep: 547.00 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-15 01:08:59,566] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 283.11 | bwd_microstep: 487.75 | bwd_inner_microstep: 487.70 | bwd_allreduce_microstep: 0.02 | step_microstep: 2.54 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 840 +[2025-05-15 01:09:00,112] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 219.89 | bwd_microstep: 295.03 | bwd_inner_microstep: 294.60 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.42 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-15 01:09:00,880] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 361.58 | bwd_microstep: 385.80 | bwd_inner_microstep: 385.76 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.77 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-15 01:09:01,909] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 395.49 | bwd_microstep: 605.11 | bwd_inner_microstep: 605.05 | bwd_allreduce_microstep: 0.02 | step_microstep: 1.39 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-15 01:09:02,508] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 292.10 | bwd_microstep: 285.93 | bwd_inner_microstep: 285.73 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-15 01:09:03,732] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.01 | optimizer_gradients: 2.14 | optimizer_step: 18.44 +[2025-05-15 01:09:03,733] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 306.16 | bwd_microstep: 875.33 | bwd_inner_microstep: 603.54 | bwd_allreduce_microstep: 271.76 | step_microstep: 28.31 +[2025-05-15 01:09:03,734] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2626.07 | bwd: 3930.60 | bwd_inner: 3657.83 | bwd_allreduce: 271.88 | step: 34.71 + 63%|██████▎ | 354/558 [40:59<21:13, 6.24s/it] {'loss': 7.8591, 'grad_norm': 27.768693923950195, 'learning_rate': 3.1168014561753194e-16, 'epoch': 0.19} + 63%|██████▎ | 354/558 [40:59<21:13, 6.24s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-15 01:09:04,533] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 346.79 | bwd_microstep: 424.48 | bwd_inner_microstep: 424.44 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.85 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-15 01:09:05,556] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 443.96 | bwd_microstep: 553.31 | bwd_inner_microstep: 553.25 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.36 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 344 +[2025-05-15 01:09:05,810] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 90.15 | bwd_microstep: 145.89 | bwd_inner_microstep: 145.73 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1888 +[2025-05-15 01:09:06,811] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 359.49 | bwd_microstep: 621.27 | bwd_inner_microstep: 621.24 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 843 +[2025-05-15 01:09:07,208] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 185.47 | bwd_microstep: 186.97 | bwd_inner_microstep: 186.62 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-15 01:09:08,177] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 341.02 | bwd_microstep: 607.22 | bwd_inner_microstep: 607.19 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-15 01:09:08,963] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 360.98 | bwd_microstep: 393.00 | bwd_inner_microstep: 392.77 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-15 01:09:10,233] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.10 | optimizer_step: 18.50 +[2025-05-15 01:09:10,233] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 393.45 | bwd_microstep: 824.92 | bwd_inner_microstep: 621.02 | bwd_allreduce_microstep: 203.70 | step_microstep: 28.39 +[2025-05-15 01:09:10,234] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2521.25 | bwd: 3757.09 | bwd_inner: 3552.34 | bwd_allreduce: 203.94 | step: 35.81 + 64%|██████▎ | 355/558 [41:05<21:23, 6.32s/it] {'loss': 6.2558, 'grad_norm': 42.54475402832031, 'learning_rate': 3.089936453278937e-16, 'epoch': 0.19} + 64%|██████▎ | 355/558 [41:05<21:23, 6.32s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1896 +[2025-05-15 01:09:10,858] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 300.56 | bwd_microstep: 296.89 | bwd_inner_microstep: 296.86 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.77 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1887 +[2025-05-15 01:09:11,894] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 395.36 | bwd_microstep: 615.43 | bwd_inner_microstep: 615.39 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.21 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-15 01:09:12,705] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 234.04 | bwd_microstep: 554.18 | bwd_inner_microstep: 554.12 | bwd_allreduce_microstep: 0.02 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-15 01:09:13,684] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 423.47 | bwd_microstep: 521.93 | bwd_inner_microstep: 521.72 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-15 01:09:14,528] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 224.61 | bwd_microstep: 596.57 | bwd_inner_microstep: 596.54 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-15 01:09:15,385] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 407.01 | bwd_microstep: 415.31 | bwd_inner_microstep: 415.08 | bwd_allreduce_microstep: 0.08 | step_microstep: 0.09 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 320 +[2025-05-15 01:09:15,625] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.09 | bwd_microstep: 130.36 | bwd_inner_microstep: 130.32 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.79 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-15 01:09:16,679] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.01 | optimizer_gradients: 2.02 | optimizer_step: 18.33 +[2025-05-15 01:09:16,679] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 433.14 | bwd_microstep: 570.77 | bwd_inner_microstep: 510.37 | bwd_allreduce_microstep: 60.24 | step_microstep: 26.87 +[2025-05-15 01:09:16,680] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2511.29 | bwd: 3701.47 | bwd_inner: 3640.51 | bwd_allreduce: 60.34 | step: 35.60 + 64%|██████▍ | 356/558 [41:12<21:24, 6.36s/it] {'loss': 6.7348, 'grad_norm': 32.313690185546875, 'learning_rate': 3.063135860161842e-16, 'epoch': 0.19} + 64%|██████▍ | 356/558 [41:12<21:24, 6.36s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-15 01:09:17,710] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 396.02 | bwd_microstep: 602.99 | bwd_inner_microstep: 602.73 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.21 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 331 +[2025-05-15 01:09:17,955] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.08 | bwd_microstep: 133.31 | bwd_inner_microstep: 133.16 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-15 01:09:18,891] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 311.84 | bwd_microstep: 604.04 | bwd_inner_microstep: 604.01 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-15 01:09:19,713] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 347.76 | bwd_microstep: 440.50 | bwd_inner_microstep: 440.45 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.00 +dynamic ViT batch size: 6, images per sample: 6.0, dynamic token length: 1607 +[2025-05-15 01:09:20,629] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 388.99 | bwd_microstep: 496.28 | bwd_inner_microstep: 496.22 | bwd_allreduce_microstep: 0.02 | step_microstep: 1.76 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1946 +[2025-05-15 01:09:21,558] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 264.33 | bwd_microstep: 641.14 | bwd_inner_microstep: 641.10 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.37 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1922 +[2025-05-15 01:09:22,381] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 391.98 | bwd_microstep: 397.19 | bwd_inner_microstep: 397.15 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.81 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 369 +[2025-05-15 01:09:23,109] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.12 | optimizer_step: 18.49 +[2025-05-15 01:09:23,109] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 108.54 | bwd_microstep: 567.61 | bwd_inner_microstep: 151.18 | bwd_allreduce_microstep: 416.40 | step_microstep: 27.29 +[2025-05-15 01:09:23,110] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2303.52 | bwd: 3883.07 | bwd_inner: 3466.04 | bwd_allreduce: 416.74 | step: 37.88 + 64%|██████▍ | 357/558 [41:18<21:22, 6.38s/it] {'loss': 6.1329, 'grad_norm': 32.90541076660156, 'learning_rate': 3.0364005805742246e-16, 'epoch': 0.19} + 64%|██████▍ | 357/558 [41:18<21:22, 6.38s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-15 01:09:23,971] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 228.49 | bwd_microstep: 604.07 | bwd_inner_microstep: 604.03 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.57 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-15 01:09:24,869] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 403.02 | bwd_microstep: 462.36 | bwd_inner_microstep: 462.14 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1358 +[2025-05-15 01:09:25,561] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 226.29 | bwd_microstep: 446.87 | bwd_inner_microstep: 446.84 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-15 01:09:26,533] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 407.57 | bwd_microstep: 527.79 | bwd_inner_microstep: 527.74 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.00 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 846 +[2025-05-15 01:09:26,872] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.79 | bwd_microstep: 226.45 | bwd_inner_microstep: 226.41 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.32 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-15 01:09:27,889] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 406.01 | bwd_microstep: 583.96 | bwd_inner_microstep: 583.93 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.49 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-15 01:09:28,688] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 360.03 | bwd_microstep: 416.73 | bwd_inner_microstep: 416.69 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.85 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1346 +[2025-05-15 01:09:29,711] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.25 | optimizer_gradients: 2.11 | optimizer_step: 18.43 +[2025-05-15 01:09:29,712] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 300.04 | bwd_microstep: 672.47 | bwd_inner_microstep: 466.31 | bwd_allreduce_microstep: 206.11 | step_microstep: 27.76 +[2025-05-15 01:09:29,713] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2426.19 | bwd: 3940.70 | bwd_inner: 3734.15 | bwd_allreduce: 206.23 | step: 39.45 + 64%|██████▍ | 358/558 [41:25<21:29, 6.45s/it] {'loss': 5.2181, 'grad_norm': 16.10529327392578, 'learning_rate': 3.009731516063813e-16, 'epoch': 0.19} + 64%|██████▍ | 358/558 [41:25<21:29, 6.45s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 376 +[2025-05-15 01:09:29,985] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 88.24 | bwd_microstep: 159.51 | bwd_inner_microstep: 159.48 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.21 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1887 +[2025-05-15 01:09:30,785] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 251.44 | bwd_microstep: 525.72 | bwd_inner_microstep: 525.67 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.29 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-15 01:09:31,765] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 440.85 | bwd_microstep: 506.64 | bwd_inner_microstep: 506.60 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.21 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-15 01:09:32,582] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 242.10 | bwd_microstep: 552.18 | bwd_inner_microstep: 552.12 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1107 +[2025-05-15 01:09:33,215] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 273.06 | bwd_microstep: 329.49 | bwd_inner_microstep: 329.02 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.22 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 328 +[2025-05-15 01:09:33,469] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.96 | bwd_microstep: 140.48 | bwd_inner_microstep: 140.44 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.21 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-15 01:09:34,301] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 222.35 | bwd_microstep: 586.88 | bwd_inner_microstep: 586.86 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1224 +[2025-05-15 01:09:35,188] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.04 | optimizer_step: 18.00 +[2025-05-15 01:09:35,188] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 289.96 | bwd_microstep: 538.28 | bwd_inner_microstep: 344.86 | bwd_allreduce_microstep: 193.39 | step_microstep: 26.86 +[2025-05-15 01:09:35,189] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 1902.94 | bwd: 3339.18 | bwd_inner: 3145.07 | bwd_allreduce: 193.69 | step: 34.69 + 64%|██████▍ | 359/558 [41:30<20:24, 6.16s/it] {'loss': 3.9817, 'grad_norm': 33.2224006652832, 'learning_rate': 2.983129565945484e-16, 'epoch': 0.19} + 64%|██████▍ | 359/558 [41:30<20:24, 6.16s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1894 +[2025-05-15 01:09:35,962] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 205.21 | bwd_microstep: 535.76 | bwd_inner_microstep: 535.74 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.57 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-15 01:09:36,947] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 446.77 | bwd_microstep: 506.48 | bwd_inner_microstep: 506.19 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.25 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-15 01:09:37,781] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 220.16 | bwd_microstep: 592.31 | bwd_inner_microstep: 592.27 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-15 01:09:38,716] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 408.88 | bwd_microstep: 493.46 | bwd_inner_microstep: 493.19 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-15 01:09:39,618] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 273.05 | bwd_microstep: 609.08 | bwd_inner_microstep: 609.05 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-15 01:09:40,432] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 385.27 | bwd_microstep: 396.36 | bwd_inner_microstep: 396.12 | bwd_allreduce_microstep: 0.20 | step_microstep: 0.21 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-15 01:09:41,467] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 395.78 | bwd_microstep: 616.49 | bwd_inner_microstep: 616.27 | bwd_allreduce_microstep: 0.19 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1975 +[2025-05-15 01:09:42,873] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.01 | optimizer_gradients: 2.11 | optimizer_step: 18.13 +[2025-05-15 01:09:42,874] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 370.35 | bwd_microstep: 989.70 | bwd_inner_microstep: 447.50 | bwd_allreduce_microstep: 542.17 | step_microstep: 26.93 +[2025-05-15 01:09:42,875] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2705.44 | bwd: 4739.86 | bwd_inner: 4196.38 | bwd_allreduce: 542.67 | step: 34.93 + 65%|██████▍ | 360/558 [41:38<21:49, 6.61s/it] {'loss': 4.5806, 'grad_norm': 22.89301109313965, 'learning_rate': 2.9565956272709283e-16, 'epoch': 0.19} + 65%|██████▍ | 360/558 [41:38<21:49, 6.61s/it]dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1393 +[2025-05-15 01:09:43,447] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 260.34 | bwd_microstep: 284.86 | bwd_inner_microstep: 284.65 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1893 +[2025-05-15 01:09:44,359] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 331.47 | bwd_microstep: 554.11 | bwd_inner_microstep: 554.07 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1891 +[2025-05-15 01:09:45,281] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 368.44 | bwd_microstep: 520.55 | bwd_inner_microstep: 520.15 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-15 01:09:46,115] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 221.14 | bwd_microstep: 591.12 | bwd_inner_microstep: 591.06 | bwd_allreduce_microstep: 0.02 | step_microstep: 2.34 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 349 +[2025-05-15 01:09:46,406] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 110.00 | bwd_microstep: 146.54 | bwd_inner_microstep: 146.51 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.53 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 843 +[2025-05-15 01:09:46,873] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 185.40 | bwd_microstep: 249.64 | bwd_inner_microstep: 249.61 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.46 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-15 01:09:47,671] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 246.46 | bwd_microstep: 528.63 | bwd_inner_microstep: 528.59 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.56 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-15 01:09:48,879] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.01 | optimizer_gradients: 2.10 | optimizer_step: 18.57 +[2025-05-15 01:09:48,880] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 433.52 | bwd_microstep: 714.89 | bwd_inner_microstep: 511.48 | bwd_allreduce_microstep: 203.37 | step_microstep: 27.12 +[2025-05-15 01:09:48,881] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2156.76 | bwd: 3590.34 | bwd_inner: 3386.13 | bwd_allreduce: 203.62 | step: 39.60 + 65%|██████▍ | 361/558 [41:44<21:07, 6.43s/it] {'loss': 3.6408, 'grad_norm': 13.90239429473877, 'learning_rate': 2.930130594798405e-16, 'epoch': 0.19} + 65%|██████▍ | 361/558 [41:44<21:07, 6.43s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1975 +[2025-05-15 01:09:49,804] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 257.63 | bwd_microstep: 637.34 | bwd_inner_microstep: 637.29 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1923 +[2025-05-15 01:09:50,669] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 404.73 | bwd_microstep: 426.50 | bwd_inner_microstep: 426.46 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.82 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1894 +[2025-05-15 01:09:51,691] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 408.59 | bwd_microstep: 589.56 | bwd_inner_microstep: 589.31 | bwd_allreduce_microstep: 0.21 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-15 01:09:52,217] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 215.27 | bwd_microstep: 289.56 | bwd_inner_microstep: 289.54 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.81 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-15 01:09:53,254] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 404.71 | bwd_microstep: 606.55 | bwd_inner_microstep: 606.50 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.29 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-15 01:09:54,075] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 231.02 | bwd_microstep: 559.42 | bwd_inner_microstep: 559.37 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-15 01:09:54,921] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 424.13 | bwd_microstep: 385.44 | bwd_inner_microstep: 385.38 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.81 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-15 01:09:56,120] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 1.74 | optimizer_step: 16.74 +[2025-05-15 01:09:56,120] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 401.73 | bwd_microstep: 748.06 | bwd_inner_microstep: 610.62 | bwd_allreduce_microstep: 137.38 | step_microstep: 25.24 +[2025-05-15 01:09:56,121] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2747.79 | bwd: 4242.42 | bwd_inner: 4104.47 | bwd_allreduce: 137.68 | step: 35.91 + 65%|██████▍ | 362/558 [41:51<21:48, 6.67s/it] {'loss': 3.8558, 'grad_norm': 17.396514892578125, 'learning_rate': 2.9037353609625695e-16, 'epoch': 0.19} + 65%|██████▍ | 362/558 [41:51<21:48, 6.67s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1893 +[2025-05-15 01:09:57,118] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 349.52 | bwd_microstep: 620.93 | bwd_inner_microstep: 620.88 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.40 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1890 +[2025-05-15 01:09:57,913] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 304.86 | bwd_microstep: 455.93 | bwd_inner_microstep: 455.68 | bwd_allreduce_microstep: 0.21 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-15 01:09:58,852] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 441.08 | bwd_microstep: 465.71 | bwd_inner_microstep: 465.51 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.12 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 852 +[2025-05-15 01:09:59,315] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 170.31 | bwd_microstep: 273.99 | bwd_inner_microstep: 273.93 | bwd_allreduce_microstep: 0.02 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-15 01:10:00,202] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 444.44 | bwd_microstep: 408.01 | bwd_inner_microstep: 407.72 | bwd_allreduce_microstep: 0.14 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-15 01:10:01,058] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 227.56 | bwd_microstep: 607.30 | bwd_inner_microstep: 607.27 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-15 01:10:01,886] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 402.90 | bwd_microstep: 391.03 | bwd_inner_microstep: 390.98 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.83 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-15 01:10:03,012] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 1.66 | optimizer_step: 12.88 +[2025-05-15 01:10:03,012] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 417.28 | bwd_microstep: 664.34 | bwd_inner_microstep: 585.43 | bwd_allreduce_microstep: 78.86 | step_microstep: 19.54 +[2025-05-15 01:10:03,013] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2757.92 | bwd: 3887.27 | bwd_inner: 3807.52 | bwd_allreduce: 79.31 | step: 31.05 + 65%|██████▌ | 363/558 [41:58<21:54, 6.74s/it] {'loss': 6.3883, 'grad_norm': 43.73181915283203, 'learning_rate': 2.877410815844376e-16, 'epoch': 0.2} + 65%|██████▌ | 363/558 [41:58<21:54, 6.74s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1930 +[2025-05-15 01:10:04,049] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 363.89 | bwd_microstep: 649.96 | bwd_inner_microstep: 649.91 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 337 +[2025-05-15 01:10:04,305] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 96.10 | bwd_microstep: 138.14 | bwd_inner_microstep: 137.93 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-15 01:10:05,269] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 327.09 | bwd_microstep: 615.92 | bwd_inner_microstep: 615.88 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-15 01:10:06,085] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 329.63 | bwd_microstep: 453.64 | bwd_inner_microstep: 453.42 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-15 01:10:07,070] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 446.63 | bwd_microstep: 503.64 | bwd_inner_microstep: 503.48 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-15 01:10:08,006] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 305.75 | bwd_microstep: 610.40 | bwd_inner_microstep: 610.36 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 330 +[2025-05-15 01:10:08,285] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.81 | bwd_microstep: 147.62 | bwd_inner_microstep: 147.59 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.31 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1908 +[2025-05-15 01:10:09,414] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.53 | optimizer_gradients: 2.11 | optimizer_step: 18.61 +[2025-05-15 01:10:09,415] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.32 | bwd_microstep: 891.25 | bwd_inner_microstep: 345.32 | bwd_allreduce_microstep: 545.90 | step_microstep: 29.15 +[2025-05-15 01:10:09,415] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2155.16 | bwd: 4010.61 | bwd_inner: 3464.00 | bwd_allreduce: 546.07 | step: 38.91 + 65%|██████▌ | 364/558 [42:04<21:27, 6.64s/it] {'loss': 3.6575, 'grad_norm': 13.272334098815918, 'learning_rate': 2.851157847141064e-16, 'epoch': 0.2} + 65%|██████▌ | 364/558 [42:04<21:27, 6.64s/it]dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1104 +[2025-05-15 01:10:09,872] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 125.32 | bwd_microstep: 304.10 | bwd_inner_microstep: 304.06 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.76 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-15 01:10:10,841] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 429.49 | bwd_microstep: 516.09 | bwd_inner_microstep: 515.94 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-15 01:10:11,783] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 313.83 | bwd_microstep: 607.09 | bwd_inner_microstep: 607.06 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.54 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 849 +[2025-05-15 01:10:12,265] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.13 | bwd_microstep: 252.60 | bwd_inner_microstep: 252.56 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.30 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1096 +[2025-05-15 01:10:12,723] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 116.90 | bwd_microstep: 317.03 | bwd_inner_microstep: 316.99 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.79 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 326 +[2025-05-15 01:10:13,009] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 104.20 | bwd_microstep: 153.66 | bwd_inner_microstep: 153.63 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 838 +[2025-05-15 01:10:13,495] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 215.34 | bwd_microstep: 239.94 | bwd_inner_microstep: 239.88 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.77 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-15 01:10:14,753] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.07 | optimizer_step: 18.37 +[2025-05-15 01:10:14,754] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 268.02 | bwd_microstep: 943.78 | bwd_inner_microstep: 495.59 | bwd_allreduce_microstep: 448.15 | step_microstep: 27.43 +[2025-05-15 01:10:14,755] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 1768.19 | bwd: 3334.30 | bwd_inner: 2885.74 | bwd_allreduce: 448.27 | step: 39.06 + 65%|██████▌ | 365/558 [42:10<20:06, 6.25s/it] {'loss': 6.221, 'grad_norm': 28.626502990722656, 'learning_rate': 2.824977340136227e-16, 'epoch': 0.2} + 65%|██████▌ | 365/558 [42:10<20:06, 6.25s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1883 +[2025-05-15 01:10:15,572] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 237.97 | bwd_microstep: 550.79 | bwd_inner_microstep: 550.75 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-15 01:10:16,492] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 429.88 | bwd_microstep: 457.11 | bwd_inner_microstep: 456.87 | bwd_allreduce_microstep: 0.08 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-15 01:10:17,020] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.08 | bwd_microstep: 320.81 | bwd_inner_microstep: 320.76 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.33 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-15 01:10:18,060] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 405.11 | bwd_microstep: 611.92 | bwd_inner_microstep: 611.71 | bwd_allreduce_microstep: 0.18 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-15 01:10:18,864] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 283.30 | bwd_microstep: 500.40 | bwd_inner_microstep: 500.35 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-15 01:10:19,826] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 440.99 | bwd_microstep: 487.81 | bwd_inner_microstep: 487.48 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-15 01:10:20,735] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 282.93 | bwd_microstep: 605.76 | bwd_inner_microstep: 605.71 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-15 01:10:22,126] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.01 | optimizer_gradients: 2.13 | optimizer_step: 18.37 +[2025-05-15 01:10:22,127] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 378.94 | bwd_microstep: 950.71 | bwd_inner_microstep: 387.72 | bwd_allreduce_microstep: 562.96 | step_microstep: 26.93 +[2025-05-15 01:10:22,127] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2649.17 | bwd: 4485.34 | bwd_inner: 3921.51 | bwd_allreduce: 563.35 | step: 36.81 + 66%|██████▌ | 366/558 [42:17<21:04, 6.59s/it] {'loss': 7.5885, 'grad_norm': 21.27675437927246, 'learning_rate': 2.7988701776699613e-16, 'epoch': 0.2} + 66%|██████▌ | 366/558 [42:17<21:04, 6.59s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1907 +[2025-05-15 01:10:22,932] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 315.43 | bwd_microstep: 461.29 | bwd_inner_microstep: 458.91 | bwd_allreduce_microstep: 2.35 | step_microstep: 2.54 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1891 +[2025-05-15 01:10:23,948] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 449.59 | bwd_microstep: 534.07 | bwd_inner_microstep: 533.84 | bwd_allreduce_microstep: 0.19 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1895 +[2025-05-15 01:10:24,785] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 223.79 | bwd_microstep: 590.89 | bwd_inner_microstep: 590.86 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.52 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 850 +[2025-05-15 01:10:25,299] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 224.40 | bwd_microstep: 261.17 | bwd_inner_microstep: 260.96 | bwd_allreduce_microstep: 0.18 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-15 01:10:26,089] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 319.85 | bwd_microstep: 450.38 | bwd_inner_microstep: 450.14 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-15 01:10:27,103] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 438.86 | bwd_microstep: 546.99 | bwd_inner_microstep: 546.60 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.18 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 835 +[2025-05-15 01:10:27,450] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 126.29 | bwd_microstep: 203.07 | bwd_inner_microstep: 203.04 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.90 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-15 01:10:28,634] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 1.76 | optimizer_step: 17.27 +[2025-05-15 01:10:28,634] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 409.96 | bwd_microstep: 724.60 | bwd_inner_microstep: 581.07 | bwd_allreduce_microstep: 142.56 | step_microstep: 24.99 +[2025-05-15 01:10:28,635] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2508.18 | bwd: 3772.45 | bwd_inner: 3625.43 | bwd_allreduce: 145.49 | step: 32.70 + 66%|██████▌ | 367/558 [42:24<20:53, 6.56s/it] {'loss': 4.0467, 'grad_norm': 17.135120391845703, 'learning_rate': 2.7728372401090806e-16, 'epoch': 0.2} + 66%|██████▌ | 367/558 [42:24<20:53, 6.56s/it]dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1422 +[2025-05-15 01:10:29,400] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 268.52 | bwd_microstep: 470.84 | bwd_inner_microstep: 470.79 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1889 +[2025-05-15 01:10:30,218] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 390.23 | bwd_microstep: 395.50 | bwd_inner_microstep: 395.09 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.43 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1894 +[2025-05-15 01:10:31,261] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 397.67 | bwd_microstep: 623.20 | bwd_inner_microstep: 622.99 | bwd_allreduce_microstep: 0.18 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-15 01:10:32,061] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 321.09 | bwd_microstep: 456.74 | bwd_inner_microstep: 456.51 | bwd_allreduce_microstep: 0.20 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-15 01:10:33,072] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 442.62 | bwd_microstep: 535.95 | bwd_inner_microstep: 535.62 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-15 01:10:33,935] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 240.39 | bwd_microstep: 600.57 | bwd_inner_microstep: 600.53 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.29 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-15 01:10:34,751] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 390.69 | bwd_microstep: 393.13 | bwd_inner_microstep: 392.74 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.24 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-15 01:10:36,023] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 1.83 | optimizer_step: 27.77 +[2025-05-15 01:10:36,024] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 397.26 | bwd_microstep: 817.49 | bwd_inner_microstep: 614.40 | bwd_allreduce_microstep: 202.87 | step_microstep: 36.36 +[2025-05-15 01:10:36,025] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2848.45 | bwd: 4293.42 | bwd_inner: 4088.75 | bwd_allreduce: 203.75 | step: 44.15 + 66%|██████▌ | 368/558 [42:31<21:34, 6.81s/it] {'loss': 4.1765, 'grad_norm': 20.712987899780273, 'learning_rate': 2.7468794053174546e-16, 'epoch': 0.2} + 66%|██████▌ | 368/558 [42:31<21:34, 6.81s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1905 +[2025-05-15 01:10:36,943] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 276.34 | bwd_microstep: 615.32 | bwd_inner_microstep: 615.26 | bwd_allreduce_microstep: 0.02 | step_microstep: 2.35 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 857 +[2025-05-15 01:10:37,400] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 210.80 | bwd_microstep: 214.05 | bwd_inner_microstep: 213.89 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.11 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1117 +[2025-05-15 01:10:37,881] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 128.66 | bwd_microstep: 333.43 | bwd_inner_microstep: 333.39 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.31 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 340 +[2025-05-15 01:10:38,163] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 105.14 | bwd_microstep: 142.59 | bwd_inner_microstep: 142.55 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.42 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-15 01:10:39,014] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 390.65 | bwd_microstep: 422.31 | bwd_inner_microstep: 422.26 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.85 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-15 01:10:40,017] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 411.66 | bwd_microstep: 565.58 | bwd_inner_microstep: 565.43 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-15 01:10:40,886] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 251.99 | bwd_microstep: 594.58 | bwd_inner_microstep: 594.55 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.52 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-15 01:10:42,246] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.27 | optimizer_gradients: 2.08 | optimizer_step: 16.77 +[2025-05-15 01:10:42,247] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 380.91 | bwd_microstep: 921.96 | bwd_inner_microstep: 402.77 | bwd_allreduce_microstep: 519.15 | step_microstep: 26.45 +[2025-05-15 01:10:42,248] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2156.13 | bwd: 3809.84 | bwd_inner: 3290.18 | bwd_allreduce: 519.32 | step: 37.72 + 66%|██████▌ | 369/558 [42:37<20:53, 6.63s/it] {'loss': 3.8583, 'grad_norm': 32.189754486083984, 'learning_rate': 2.720997548626381e-16, 'epoch': 0.2} + 66%|██████▌ | 369/558 [42:37<20:53, 6.63s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1905 +[2025-05-15 01:10:43,121] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 235.73 | bwd_microstep: 607.60 | bwd_inner_microstep: 607.55 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.52 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1908 +[2025-05-15 01:10:43,958] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 394.50 | bwd_microstep: 407.44 | bwd_inner_microstep: 407.41 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.85 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1369 +[2025-05-15 01:10:44,760] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 306.06 | bwd_microstep: 472.24 | bwd_inner_microstep: 472.21 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-15 01:10:45,559] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 274.65 | bwd_microstep: 501.13 | bwd_inner_microstep: 501.09 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-15 01:10:46,449] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 448.20 | bwd_microstep: 408.94 | bwd_inner_microstep: 408.84 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-15 01:10:47,493] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 387.88 | bwd_microstep: 633.01 | bwd_inner_microstep: 632.80 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-15 01:10:48,306] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 248.96 | bwd_microstep: 541.79 | bwd_inner_microstep: 541.77 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.56 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 336 +[2025-05-15 01:10:48,877] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.11 | optimizer_step: 17.73 +[2025-05-15 01:10:48,878] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 106.18 | bwd_microstep: 409.19 | bwd_inner_microstep: 162.19 | bwd_allreduce_microstep: 246.94 | step_microstep: 26.36 +[2025-05-15 01:10:48,879] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2402.13 | bwd: 3981.36 | bwd_inner: 3733.87 | bwd_allreduce: 247.06 | step: 36.25 + 66%|██████▋ | 370/558 [42:44<20:47, 6.63s/it] {'loss': 4.184, 'grad_norm': 13.464975357055664, 'learning_rate': 2.6951925428050805e-16, 'epoch': 0.2} + 66%|██████▋ | 370/558 [42:44<20:47, 6.63s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1883 +[2025-05-15 01:10:49,445] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.04 | bwd_microstep: 350.93 | bwd_inner_microstep: 350.88 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.79 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1883 +[2025-05-15 01:10:50,480] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 416.72 | bwd_microstep: 591.81 | bwd_inner_microstep: 591.77 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.19 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 338 +[2025-05-15 01:10:50,735] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 81.39 | bwd_microstep: 158.27 | bwd_inner_microstep: 158.23 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-15 01:10:51,751] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 407.12 | bwd_microstep: 581.59 | bwd_inner_microstep: 581.55 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.33 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-15 01:10:52,611] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 241.14 | bwd_microstep: 592.99 | bwd_inner_microstep: 592.95 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-15 01:10:53,442] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 390.31 | bwd_microstep: 406.57 | bwd_inner_microstep: 406.53 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.80 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-15 01:10:54,459] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 407.72 | bwd_microstep: 585.99 | bwd_inner_microstep: 585.77 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-15 01:10:55,680] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.01 | optimizer_gradients: 2.13 | optimizer_step: 18.90 +[2025-05-15 01:10:55,681] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 244.18 | bwd_microstep: 928.40 | bwd_inner_microstep: 603.29 | bwd_allreduce_microstep: 325.08 | step_microstep: 27.90 +[2025-05-15 01:10:55,681] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2378.55 | bwd: 4196.55 | bwd_inner: 3870.99 | bwd_allreduce: 325.16 | step: 36.49 + 66%|██████▋ | 371/558 [42:51<20:49, 6.68s/it] {'loss': 5.5114, 'grad_norm': 31.67627716064453, 'learning_rate': 2.669465258031273e-16, 'epoch': 0.2} + 66%|██████▋ | 371/558 [42:51<20:49, 6.68s/it]dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1369 +[2025-05-15 01:10:56,270] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 149.75 | bwd_microstep: 411.20 | bwd_inner_microstep: 411.13 | bwd_allreduce_microstep: 0.02 | step_microstep: 2.53 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1913 +[2025-05-15 01:10:57,172] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 444.47 | bwd_microstep: 424.92 | bwd_inner_microstep: 424.66 | bwd_allreduce_microstep: 0.10 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1915 +[2025-05-15 01:10:58,225] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 389.33 | bwd_microstep: 640.71 | bwd_inner_microstep: 640.68 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.47 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1894 +[2025-05-15 01:10:59,052] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 251.65 | bwd_microstep: 553.34 | bwd_inner_microstep: 553.31 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.52 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1897 +[2025-05-15 01:10:59,913] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 428.64 | bwd_microstep: 395.48 | bwd_inner_microstep: 395.44 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.80 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1099 +[2025-05-15 01:11:00,542] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 234.66 | bwd_microstep: 369.02 | bwd_inner_microstep: 368.99 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.57 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-15 01:11:01,372] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 387.86 | bwd_microstep: 408.60 | bwd_inner_microstep: 408.55 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.90 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-15 01:11:02,535] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.12 | optimizer_step: 17.79 +[2025-05-15 01:11:02,536] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 402.79 | bwd_microstep: 711.90 | bwd_inner_microstep: 596.89 | bwd_allreduce_microstep: 114.77 | step_microstep: 25.90 +[2025-05-15 01:11:02,537] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2689.14 | bwd: 3915.20 | bwd_inner: 3799.71 | bwd_allreduce: 114.92 | step: 39.81 + 67%|██████▋ | 372/558 [42:58<20:52, 6.74s/it] {'loss': 2.6142, 'grad_norm': 6.235260486602783, 'learning_rate': 2.6438165618618127e-16, 'epoch': 0.2} + 67%|██████▋ | 372/558 [42:58<20:52, 6.74s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-15 01:11:03,536] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 357.45 | bwd_microstep: 615.37 | bwd_inner_microstep: 615.31 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-15 01:11:04,343] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 295.56 | bwd_microstep: 476.62 | bwd_inner_microstep: 476.58 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-15 01:11:05,252] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 434.46 | bwd_microstep: 439.88 | bwd_inner_microstep: 439.72 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.13 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-15 01:11:06,254] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 358.59 | bwd_microstep: 623.30 | bwd_inner_microstep: 623.26 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-15 01:11:07,056] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 292.46 | bwd_microstep: 480.41 | bwd_inner_microstep: 480.37 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-15 01:11:07,962] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 443.77 | bwd_microstep: 429.82 | bwd_inner_microstep: 429.65 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 318 +[2025-05-15 01:11:08,213] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 90.65 | bwd_microstep: 143.64 | bwd_inner_microstep: 143.60 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.82 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1895 +[2025-05-15 01:11:09,268] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.01 | optimizer_gradients: 2.05 | optimizer_step: 18.40 +[2025-05-15 01:11:09,269] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 439.00 | bwd_microstep: 563.44 | bwd_inner_microstep: 498.31 | bwd_allreduce_microstep: 65.05 | step_microstep: 27.22 +[2025-05-15 01:11:09,269] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2711.89 | bwd: 3772.51 | bwd_inner: 3706.89 | bwd_allreduce: 65.25 | step: 38.69 + 67%|██████▋ | 373/558 [43:04<20:45, 6.73s/it] {'loss': 6.0593, 'grad_norm': 27.25377082824707, 'learning_rate': 2.618247319203452e-16, 'epoch': 0.2} + 67%|██████▋ | 373/558 [43:04<20:45, 6.73s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1883 +[2025-05-15 01:11:10,308] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 398.95 | bwd_microstep: 607.02 | bwd_inner_microstep: 606.98 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1899 +[2025-05-15 01:11:11,153] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 226.22 | bwd_microstep: 597.82 | bwd_inner_microstep: 597.78 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.28 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-15 01:11:12,001] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 414.88 | bwd_microstep: 399.05 | bwd_inner_microstep: 398.99 | bwd_allreduce_microstep: 0.02 | step_microstep: 1.81 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-15 01:11:13,022] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 399.01 | bwd_microstep: 597.79 | bwd_inner_microstep: 597.38 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.36 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 845 +[2025-05-15 01:11:13,353] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 121.53 | bwd_microstep: 188.99 | bwd_inner_microstep: 188.96 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.79 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-15 01:11:14,368] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 403.77 | bwd_microstep: 588.30 | bwd_inner_microstep: 588.04 | bwd_allreduce_microstep: 0.24 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-15 01:11:15,106] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 209.10 | bwd_microstep: 508.85 | bwd_inner_microstep: 508.81 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.33 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-15 01:11:16,593] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.06 | optimizer_step: 20.08 +[2025-05-15 01:11:16,593] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 441.92 | bwd_microstep: 982.98 | bwd_inner_microstep: 398.93 | bwd_allreduce_microstep: 583.83 | step_microstep: 28.13 +[2025-05-15 01:11:16,594] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2615.38 | bwd: 4470.80 | bwd_inner: 3885.89 | bwd_allreduce: 583.90 | step: 38.78 + 67%|██████▋ | 374/558 [43:12<21:11, 6.91s/it] {'loss': 7.0205, 'grad_norm': 38.868038177490234, 'learning_rate': 2.5927583922836753e-16, 'epoch': 0.2} + 67%|██████▋ | 374/558 [43:12<21:11, 6.91s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1932 +[2025-05-15 01:11:17,408] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 216.77 | bwd_microstep: 571.01 | bwd_inner_microstep: 570.97 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.54 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1906 +[2025-05-15 01:11:18,268] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 435.09 | bwd_microstep: 390.86 | bwd_inner_microstep: 390.81 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.77 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1888 +[2025-05-15 01:11:19,297] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 395.30 | bwd_microstep: 609.74 | bwd_inner_microstep: 609.70 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.25 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-15 01:11:20,104] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 240.82 | bwd_microstep: 543.10 | bwd_inner_microstep: 543.05 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-15 01:11:20,953] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 429.49 | bwd_microstep: 385.70 | bwd_inner_microstep: 385.48 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-15 01:11:22,004] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 393.89 | bwd_microstep: 632.31 | bwd_inner_microstep: 632.28 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.99 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 836 +[2025-05-15 01:11:22,340] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 126.76 | bwd_microstep: 195.19 | bwd_inner_microstep: 194.99 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-15 01:11:23,563] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 1.61 | optimizer_step: 18.90 +[2025-05-15 01:11:23,564] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 304.26 | bwd_microstep: 873.32 | bwd_inner_microstep: 595.10 | bwd_allreduce_microstep: 278.19 | step_microstep: 26.28 +[2025-05-15 01:11:23,564] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2542.37 | bwd: 4201.24 | bwd_inner: 3922.47 | bwd_allreduce: 278.30 | step: 35.50 + 67%|██████▋ | 375/558 [43:19<21:08, 6.93s/it] {'loss': 4.8722, 'grad_norm': 23.60161781311035, 'learning_rate': 2.5673506406216075e-16, 'epoch': 0.2} + 67%|██████▋ | 375/558 [43:19<21:08, 6.93s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1893 +[2025-05-15 01:11:24,458] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 260.70 | bwd_microstep: 603.27 | bwd_inner_microstep: 603.23 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1902 +[2025-05-15 01:11:25,299] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 388.00 | bwd_microstep: 419.15 | bwd_inner_microstep: 419.12 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.82 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-15 01:11:26,299] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 413.11 | bwd_microstep: 560.90 | bwd_inner_microstep: 560.58 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-15 01:11:27,175] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 256.22 | bwd_microstep: 596.89 | bwd_inner_microstep: 596.85 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.33 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-15 01:11:27,998] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 382.98 | bwd_microstep: 406.03 | bwd_inner_microstep: 406.00 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.82 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-15 01:11:29,011] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 406.46 | bwd_microstep: 581.36 | bwd_inner_microstep: 581.16 | bwd_allreduce_microstep: 0.18 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-15 01:11:29,876] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 241.39 | bwd_microstep: 601.17 | bwd_inner_microstep: 601.13 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1371 +[2025-05-15 01:11:30,575] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 1.57 | optimizer_step: 12.68 +[2025-05-15 01:11:30,576] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 305.32 | bwd_microstep: 340.04 | bwd_inner_microstep: 283.46 | bwd_allreduce_microstep: 56.42 | step_microstep: 19.15 +[2025-05-15 01:11:30,576] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2654.13 | bwd: 4108.82 | bwd_inner: 4051.64 | bwd_allreduce: 56.74 | step: 30.02 + 67%|██████▋ | 376/558 [43:26<21:05, 6.95s/it] {'loss': 5.1153, 'grad_norm': 28.928438186645508, 'learning_rate': 2.542024920999047e-16, 'epoch': 0.2} + 67%|██████▋ | 376/558 [43:26<21:05, 6.95s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1896 +[2025-05-15 01:11:31,175] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.18 | bwd_microstep: 384.10 | bwd_inner_microstep: 384.07 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.86 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1892 +[2025-05-15 01:11:32,186] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 411.39 | bwd_microstep: 573.54 | bwd_inner_microstep: 573.24 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-15 01:11:33,059] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 246.31 | bwd_microstep: 603.49 | bwd_inner_microstep: 603.46 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1893 +[2025-05-15 01:11:33,880] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 381.56 | bwd_microstep: 404.98 | bwd_inner_microstep: 404.95 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.96 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-15 01:11:34,901] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 405.75 | bwd_microstep: 589.98 | bwd_inner_microstep: 589.94 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.48 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 333 +[2025-05-15 01:11:35,151] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 87.29 | bwd_microstep: 143.47 | bwd_inner_microstep: 143.43 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.77 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-15 01:11:36,177] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 397.78 | bwd_microstep: 603.27 | bwd_inner_microstep: 603.06 | bwd_allreduce_microstep: 0.18 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-15 01:11:37,415] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.11 | optimizer_step: 29.26 +[2025-05-15 01:11:37,416] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 222.54 | bwd_microstep: 958.99 | bwd_inner_microstep: 589.54 | bwd_allreduce_microstep: 369.41 | step_microstep: 37.82 +[2025-05-15 01:11:37,416] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2342.79 | bwd: 4261.82 | bwd_inner: 3891.74 | bwd_allreduce: 369.76 | step: 48.54 + 68%|██████▊ | 377/558 [43:32<20:52, 6.92s/it] {'loss': 3.0736, 'grad_norm': 15.28421401977539, 'learning_rate': 2.516782087431565e-16, 'epoch': 0.2} + 68%|██████▊ | 377/558 [43:32<20:52, 6.92s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-15 01:11:38,327] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 280.67 | bwd_microstep: 603.30 | bwd_inner_microstep: 603.25 | bwd_allreduce_microstep: 0.02 | step_microstep: 2.54 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-15 01:11:39,146] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 384.89 | bwd_microstep: 400.39 | bwd_inner_microstep: 400.35 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-15 01:11:40,059] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 251.26 | bwd_microstep: 638.32 | bwd_inner_microstep: 637.90 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.23 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-15 01:11:40,853] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 323.92 | bwd_microstep: 450.16 | bwd_inner_microstep: 449.94 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-15 01:11:41,829] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 438.79 | bwd_microstep: 508.37 | bwd_inner_microstep: 508.23 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-15 01:11:42,701] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 257.47 | bwd_microstep: 594.35 | bwd_inner_microstep: 594.31 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.48 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-15 01:11:43,567] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 381.66 | bwd_microstep: 449.37 | bwd_inner_microstep: 449.11 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1948 +[2025-05-15 01:11:44,830] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.01 | optimizer_gradients: 2.07 | optimizer_step: 18.22 +[2025-05-15 01:11:44,831] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 361.30 | bwd_microstep: 858.79 | bwd_inner_microstep: 656.99 | bwd_allreduce_microstep: 201.77 | step_microstep: 26.70 +[2025-05-15 01:11:44,832] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2679.90 | bwd: 4503.25 | bwd_inner: 4300.15 | bwd_allreduce: 201.97 | step: 34.68 + 68%|██████▊ | 378/558 [43:40<21:12, 7.07s/it] {'loss': 6.7562, 'grad_norm': 34.61088562011719, 'learning_rate': 2.4916229911397083e-16, 'epoch': 0.2} + 68%|██████▊ | 378/558 [43:40<21:12, 7.07s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1895 +[2025-05-15 01:11:45,678] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 221.21 | bwd_microstep: 593.95 | bwd_inner_microstep: 593.91 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.57 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-15 01:11:46,544] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 410.25 | bwd_microstep: 423.31 | bwd_inner_microstep: 423.15 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-15 01:11:47,550] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 360.80 | bwd_microstep: 625.16 | bwd_inner_microstep: 625.13 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 332 +[2025-05-15 01:11:47,806] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.57 | bwd_microstep: 140.05 | bwd_inner_microstep: 139.84 | bwd_allreduce_microstep: 0.17 | step_microstep: 0.19 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 839 +[2025-05-15 01:11:48,113] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 119.96 | bwd_microstep: 168.30 | bwd_inner_microstep: 168.25 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.77 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 834 +[2025-05-15 01:11:48,611] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 187.57 | bwd_microstep: 282.61 | bwd_inner_microstep: 282.55 | bwd_allreduce_microstep: 0.02 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-15 01:11:49,432] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 403.53 | bwd_microstep: 385.23 | bwd_inner_microstep: 384.99 | bwd_allreduce_microstep: 0.21 | step_microstep: 0.19 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1342 +[2025-05-15 01:11:50,507] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.01 | optimizer_gradients: 1.82 | optimizer_step: 14.17 +[2025-05-15 01:11:50,507] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 280.68 | bwd_microstep: 749.17 | bwd_inner_microstep: 487.98 | bwd_allreduce_microstep: 261.16 | step_microstep: 22.93 +[2025-05-15 01:11:50,508] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2079.56 | bwd: 3367.78 | bwd_inner: 3105.82 | bwd_allreduce: 261.65 | step: 32.44 + 68%|██████▊ | 379/558 [43:46<19:50, 6.65s/it] {'loss': 3.5384, 'grad_norm': 23.700599670410156, 'learning_rate': 2.466548480520296e-16, 'epoch': 0.2} + 68%|██████▊ | 379/558 [43:46<19:50, 6.65s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-15 01:11:51,395] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 255.78 | bwd_microstep: 601.29 | bwd_inner_microstep: 601.26 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.59 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 334 +[2025-05-15 01:11:51,661] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 103.52 | bwd_microstep: 131.82 | bwd_inner_microstep: 131.77 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-15 01:11:52,431] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 339.00 | bwd_microstep: 410.07 | bwd_inner_microstep: 410.02 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.78 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-15 01:11:53,437] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 410.55 | bwd_microstep: 571.68 | bwd_inner_microstep: 571.65 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.31 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-15 01:11:54,284] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 226.25 | bwd_microstep: 598.53 | bwd_inner_microstep: 598.49 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 835 +[2025-05-15 01:11:54,772] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 215.04 | bwd_microstep: 240.09 | bwd_inner_microstep: 240.04 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.79 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-15 01:11:55,596] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 230.68 | bwd_microstep: 570.85 | bwd_inner_microstep: 570.83 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.50 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 322 +[2025-05-15 01:11:56,127] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.01 | optimizer_gradients: 2.03 | optimizer_step: 18.53 +[2025-05-15 01:11:56,128] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 100.25 | bwd_microstep: 374.08 | bwd_inner_microstep: 145.60 | bwd_allreduce_microstep: 228.45 | step_microstep: 27.27 +[2025-05-15 01:11:56,128] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 1880.84 | bwd: 3498.40 | bwd_inner: 3269.67 | bwd_allreduce: 228.51 | step: 37.80 + 68%|██████▊ | 380/558 [43:51<18:48, 6.34s/it] {'loss': 5.3601, 'grad_norm': 22.14356231689453, 'learning_rate': 2.441559401117815e-16, 'epoch': 0.2} + 68%|██████▊ | 380/558 [43:51<18:48, 6.34s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1905 +[2025-05-15 01:11:56,952] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 245.09 | bwd_microstep: 549.90 | bwd_inner_microstep: 549.84 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.28 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1883 +[2025-05-15 01:11:57,864] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 423.00 | bwd_microstep: 455.61 | bwd_inner_microstep: 455.26 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-15 01:11:58,833] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 341.82 | bwd_microstep: 606.34 | bwd_inner_microstep: 606.28 | bwd_allreduce_microstep: 0.02 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-15 01:11:59,739] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 353.36 | bwd_microstep: 520.43 | bwd_inner_microstep: 520.38 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.32 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-15 01:12:00,580] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 235.09 | bwd_microstep: 582.88 | bwd_inner_microstep: 582.84 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-15 01:12:01,543] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 423.16 | bwd_microstep: 507.96 | bwd_inner_microstep: 507.00 | bwd_allreduce_microstep: 0.93 | step_microstep: 0.21 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 322 +[2025-05-15 01:12:01,811] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 89.38 | bwd_microstep: 161.69 | bwd_inner_microstep: 161.54 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-15 01:12:03,034] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.01 | optimizer_gradients: 2.05 | optimizer_step: 18.19 +[2025-05-15 01:12:03,035] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 267.89 | bwd_microstep: 910.17 | bwd_inner_microstep: 602.12 | bwd_allreduce_microstep: 308.03 | step_microstep: 27.04 +[2025-05-15 01:12:03,036] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2378.76 | bwd: 4295.01 | bwd_inner: 3985.33 | bwd_allreduce: 309.19 | step: 34.89 + 68%|██████▊ | 381/558 [43:58<19:12, 6.51s/it] {'loss': 4.0714, 'grad_norm': 13.243630409240723, 'learning_rate': 2.4166565955958974e-16, 'epoch': 0.2} + 68%|██████▊ | 381/558 [43:58<19:12, 6.51s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1901 +[2025-05-15 01:12:03,771] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 356.61 | bwd_microstep: 352.30 | bwd_inner_microstep: 351.98 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-15 01:12:04,518] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.68 | bwd_microstep: 537.84 | bwd_inner_microstep: 537.80 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1886 +[2025-05-15 01:12:05,479] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 426.87 | bwd_microstep: 501.64 | bwd_inner_microstep: 501.50 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-15 01:12:06,379] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 272.54 | bwd_microstep: 608.58 | bwd_inner_microstep: 608.56 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-15 01:12:07,221] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 382.41 | bwd_microstep: 425.01 | bwd_inner_microstep: 424.70 | bwd_allreduce_microstep: 0.15 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-15 01:12:08,226] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 362.17 | bwd_microstep: 621.33 | bwd_inner_microstep: 621.29 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.29 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-15 01:12:09,016] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 352.81 | bwd_microstep: 405.46 | bwd_inner_microstep: 405.30 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1933 +[2025-05-15 01:12:10,290] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.01 | optimizer_gradients: 2.09 | optimizer_step: 18.57 +[2025-05-15 01:12:10,291] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 381.32 | bwd_microstep: 847.68 | bwd_inner_microstep: 659.13 | bwd_allreduce_microstep: 188.52 | step_microstep: 27.45 +[2025-05-15 01:12:10,291] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2725.36 | bwd: 4299.88 | bwd_inner: 4110.41 | bwd_allreduce: 188.91 | step: 34.82 + 68%|██████▊ | 382/558 [44:05<19:45, 6.73s/it] {'loss': 4.0649, 'grad_norm': 19.45537757873535, 'learning_rate': 2.391840903708911e-16, 'epoch': 0.21} + 68%|██████▊ | 382/558 [44:05<19:45, 6.73s/it]dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 908 +[2025-05-15 01:12:10,760] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 181.48 | bwd_microstep: 263.08 | bwd_inner_microstep: 262.65 | bwd_allreduce_microstep: 0.40 | step_microstep: 0.75 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1896 +[2025-05-15 01:12:11,608] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 222.99 | bwd_microstep: 603.64 | bwd_inner_microstep: 603.59 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.28 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-15 01:12:12,529] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 388.96 | bwd_microstep: 497.04 | bwd_inner_microstep: 497.01 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.33 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-15 01:12:13,334] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 283.48 | bwd_microstep: 499.55 | bwd_inner_microstep: 499.51 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.38 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 842 +[2025-05-15 01:12:13,885] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 224.72 | bwd_microstep: 296.19 | bwd_inner_microstep: 296.15 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.29 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 842 +[2025-05-15 01:12:14,314] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 171.00 | bwd_microstep: 238.93 | bwd_inner_microstep: 238.78 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-15 01:12:15,166] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 241.97 | bwd_microstep: 585.40 | bwd_inner_microstep: 585.35 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.44 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-15 01:12:16,579] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.53 | optimizer_gradients: 2.05 | optimizer_step: 18.65 +[2025-05-15 01:12:16,580] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 402.34 | bwd_microstep: 951.10 | bwd_inner_microstep: 391.57 | bwd_allreduce_microstep: 559.50 | step_microstep: 27.68 +[2025-05-15 01:12:16,580] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2116.92 | bwd: 3934.94 | bwd_inner: 3374.64 | bwd_allreduce: 560.00 | step: 36.25 + 69%|██████▊ | 383/558 [44:12<19:15, 6.60s/it] {'loss': 4.7434, 'grad_norm': 17.4377384185791, 'learning_rate': 2.3671131622736424e-16, 'epoch': 0.21} + 69%|██████▊ | 383/558 [44:12<19:15, 6.60s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1928 +[2025-05-15 01:12:17,420] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 355.61 | bwd_microstep: 456.30 | bwd_inner_microstep: 456.26 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.33 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1892 +[2025-05-15 01:12:18,450] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 444.05 | bwd_microstep: 555.74 | bwd_inner_microstep: 555.70 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.95 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-15 01:12:19,246] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 331.03 | bwd_microstep: 442.92 | bwd_inner_microstep: 442.88 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-15 01:12:20,136] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 447.95 | bwd_microstep: 412.43 | bwd_inner_microstep: 412.23 | bwd_allreduce_microstep: 0.18 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-15 01:12:20,974] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 355.90 | bwd_microstep: 464.44 | bwd_inner_microstep: 464.16 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.10 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1348 +[2025-05-15 01:12:21,636] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 196.47 | bwd_microstep: 446.72 | bwd_inner_microstep: 446.69 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.32 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-15 01:12:22,476] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 424.83 | bwd_microstep: 381.13 | bwd_inner_microstep: 381.06 | bwd_allreduce_microstep: 0.02 | step_microstep: 1.81 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-15 01:12:23,668] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.08 | optimizer_step: 18.12 +[2025-05-15 01:12:23,669] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 394.59 | bwd_microstep: 746.20 | bwd_inner_microstep: 605.52 | bwd_allreduce_microstep: 140.62 | step_microstep: 26.19 +[2025-05-15 01:12:23,669] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2950.43 | bwd: 3905.91 | bwd_inner: 3764.57 | bwd_allreduce: 140.80 | step: 36.24 + 69%|██████▉ | 384/558 [44:19<19:34, 6.75s/it] {'loss': 4.6481, 'grad_norm': 19.850711822509766, 'learning_rate': 2.3424742051410734e-16, 'epoch': 0.21} + 69%|██████▉ | 384/558 [44:19<19:34, 6.75s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1904 +[2025-05-15 01:12:24,670] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 348.97 | bwd_microstep: 625.06 | bwd_inner_microstep: 625.03 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 919 +[2025-05-15 01:12:25,097] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 207.00 | bwd_microstep: 190.66 | bwd_inner_microstep: 190.31 | bwd_allreduce_microstep: 0.15 | step_microstep: 0.13 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-15 01:12:26,096] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 358.02 | bwd_microstep: 620.02 | bwd_inner_microstep: 619.98 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.50 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1893 +[2025-05-15 01:12:26,930] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 359.93 | bwd_microstep: 441.52 | bwd_inner_microstep: 441.21 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-15 01:12:27,926] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 356.88 | bwd_microstep: 619.14 | bwd_inner_microstep: 619.09 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.57 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-15 01:12:28,559] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 326.27 | bwd_microstep: 275.91 | bwd_inner_microstep: 275.60 | bwd_allreduce_microstep: 0.15 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-15 01:12:29,541] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 350.40 | bwd_microstep: 610.37 | bwd_inner_microstep: 610.31 | bwd_allreduce_microstep: 0.02 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-15 01:12:30,858] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.01 | optimizer_gradients: 2.07 | optimizer_step: 18.69 +[2025-05-15 01:12:30,859] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 342.67 | bwd_microstep: 912.35 | bwd_inner_microstep: 425.29 | bwd_allreduce_microstep: 487.02 | step_microstep: 27.95 +[2025-05-15 01:12:30,860] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2650.08 | bwd: 4295.09 | bwd_inner: 3807.00 | bwd_allreduce: 487.48 | step: 38.05 + 69%|██████▉ | 385/558 [44:26<19:50, 6.88s/it] {'loss': 4.0796, 'grad_norm': 16.823331832885742, 'learning_rate': 2.317924863168273e-16, 'epoch': 0.21} + 69%|██████▉ | 385/558 [44:26<19:50, 6.88s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-15 01:12:31,700] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 225.61 | bwd_microstep: 586.43 | bwd_inner_microstep: 586.38 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.57 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-15 01:12:32,537] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 410.16 | bwd_microstep: 394.23 | bwd_inner_microstep: 393.96 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.21 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 841 +[2025-05-15 01:12:33,041] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 199.66 | bwd_microstep: 279.83 | bwd_inner_microstep: 279.80 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.59 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-15 01:12:33,898] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 426.27 | bwd_microstep: 396.79 | bwd_inner_microstep: 396.41 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.20 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 842 +[2025-05-15 01:12:34,408] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 206.50 | bwd_microstep: 278.41 | bwd_inner_microstep: 278.35 | bwd_allreduce_microstep: 0.02 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-15 01:12:35,255] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 421.82 | bwd_microstep: 390.24 | bwd_inner_microstep: 390.20 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-15 01:12:36,287] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 392.12 | bwd_microstep: 618.91 | bwd_inner_microstep: 618.52 | bwd_allreduce_microstep: 0.20 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-15 01:12:37,537] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.01 | optimizer_gradients: 2.09 | optimizer_step: 19.82 +[2025-05-15 01:12:37,538] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 279.30 | bwd_microstep: 924.80 | bwd_inner_microstep: 435.22 | bwd_allreduce_microstep: 489.56 | step_microstep: 28.06 +[2025-05-15 01:12:37,539] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2561.43 | bwd: 3869.66 | bwd_inner: 3378.84 | bwd_allreduce: 489.92 | step: 36.26 + 69%|██████▉ | 386/558 [44:33<19:33, 6.82s/it] {'loss': 5.9184, 'grad_norm': 23.819929122924805, 'learning_rate': 2.293465964190362e-16, 'epoch': 0.21} + 69%|██████▉ | 386/558 [44:33<19:33, 6.82s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 361 +[2025-05-15 01:12:37,813] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 88.19 | bwd_microstep: 159.51 | bwd_inner_microstep: 159.47 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.83 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1887 +[2025-05-15 01:12:38,844] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 412.17 | bwd_microstep: 594.23 | bwd_inner_microstep: 593.80 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.24 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1887 +[2025-05-15 01:12:39,646] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 246.13 | bwd_microstep: 533.16 | bwd_inner_microstep: 533.12 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.55 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-15 01:12:40,537] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 431.28 | bwd_microstep: 425.22 | bwd_inner_microstep: 424.93 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.10 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 849 +[2025-05-15 01:12:40,997] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 172.03 | bwd_microstep: 269.44 | bwd_inner_microstep: 269.41 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-15 01:12:41,919] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 442.53 | bwd_microstep: 445.50 | bwd_inner_microstep: 445.35 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 324 +[2025-05-15 01:12:42,159] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 86.81 | bwd_microstep: 135.67 | bwd_inner_microstep: 135.64 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.80 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-15 01:12:43,259] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.11 | optimizer_step: 18.05 +[2025-05-15 01:12:43,260] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 407.40 | bwd_microstep: 639.65 | bwd_inner_microstep: 565.27 | bwd_allreduce_microstep: 74.23 | step_microstep: 26.96 +[2025-05-15 01:12:43,260] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2286.33 | bwd: 3202.42 | bwd_inner: 3127.13 | bwd_allreduce: 74.44 | step: 35.94 + 69%|██████▉ | 387/558 [44:38<18:29, 6.49s/it] {'loss': 3.1128, 'grad_norm': 33.406497955322266, 'learning_rate': 2.269098332992616e-16, 'epoch': 0.21} + 69%|██████▉ | 387/558 [44:38<18:29, 6.49s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1898 +[2025-05-15 01:12:44,313] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 389.61 | bwd_microstep: 636.04 | bwd_inner_microstep: 636.01 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.32 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1883 +[2025-05-15 01:12:45,155] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 350.85 | bwd_microstep: 471.38 | bwd_inner_microstep: 471.09 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-15 01:12:46,073] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 291.73 | bwd_microstep: 605.41 | bwd_inner_microstep: 605.37 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-15 01:12:46,886] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 372.90 | bwd_microstep: 403.99 | bwd_inner_microstep: 403.92 | bwd_allreduce_microstep: 0.02 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-15 01:12:47,908] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 413.14 | bwd_microstep: 586.11 | bwd_inner_microstep: 585.87 | bwd_allreduce_microstep: 0.19 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-15 01:12:48,748] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 222.45 | bwd_microstep: 597.28 | bwd_inner_microstep: 597.23 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.55 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-15 01:12:49,582] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 408.98 | bwd_microstep: 390.71 | bwd_inner_microstep: 390.16 | bwd_allreduce_microstep: 0.51 | step_microstep: 0.06 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1892 +[2025-05-15 01:12:50,796] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.10 | optimizer_step: 19.31 +[2025-05-15 01:12:50,797] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 393.82 | bwd_microstep: 771.34 | bwd_inner_microstep: 618.82 | bwd_allreduce_microstep: 152.46 | step_microstep: 28.02 +[2025-05-15 01:12:50,798] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2843.47 | bwd: 4462.29 | bwd_inner: 4308.55 | bwd_allreduce: 152.85 | step: 36.95 + 70%|██████▉ | 388/558 [44:46<19:16, 6.80s/it] {'loss': 4.3129, 'grad_norm': 22.37702751159668, 'learning_rate': 2.2448227912826446e-16, 'epoch': 0.21} + 70%|██████▉ | 388/558 [44:46<19:16, 6.80s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1906 +[2025-05-15 01:12:51,794] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 350.70 | bwd_microstep: 619.13 | bwd_inner_microstep: 619.11 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.48 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 366 +[2025-05-15 01:12:52,059] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 91.01 | bwd_microstep: 143.81 | bwd_inner_microstep: 143.76 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.21 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-15 01:12:52,867] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 238.36 | bwd_microstep: 546.66 | bwd_inner_microstep: 546.59 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-15 01:12:53,701] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 422.35 | bwd_microstep: 379.73 | bwd_inner_microstep: 379.51 | bwd_allreduce_microstep: 0.20 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1886 +[2025-05-15 01:12:54,743] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 393.31 | bwd_microstep: 625.25 | bwd_inner_microstep: 624.84 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-15 01:12:55,533] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 320.28 | bwd_microstep: 448.30 | bwd_inner_microstep: 448.25 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-15 01:12:56,504] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 443.27 | bwd_microstep: 499.51 | bwd_inner_microstep: 499.27 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.18 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 322 +[2025-05-15 01:12:57,337] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.01 | optimizer_gradients: 1.87 | optimizer_step: 16.83 +[2025-05-15 01:12:57,338] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 88.70 | bwd_microstep: 702.96 | bwd_inner_microstep: 160.61 | bwd_allreduce_microstep: 542.32 | step_microstep: 25.74 +[2025-05-15 01:12:57,339] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2347.98 | bwd: 3965.35 | bwd_inner: 3421.93 | bwd_allreduce: 542.77 | step: 31.64 + 70%|██████▉ | 389/558 [44:52<18:56, 6.73s/it] {'loss': 4.3804, 'grad_norm': 13.168535232543945, 'learning_rate': 2.220640157662679e-16, 'epoch': 0.21} + 70%|██████▉ | 389/558 [44:52<18:56, 6.73s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1889 +[2025-05-15 01:12:58,160] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 233.61 | bwd_microstep: 559.83 | bwd_inner_microstep: 559.79 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.52 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1904 +[2025-05-15 01:12:59,144] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 430.80 | bwd_microstep: 520.37 | bwd_inner_microstep: 520.22 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1897 +[2025-05-15 01:13:00,023] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 251.81 | bwd_microstep: 604.31 | bwd_inner_microstep: 604.28 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1373 +[2025-05-15 01:13:00,670] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 296.38 | bwd_microstep: 316.16 | bwd_inner_microstep: 315.84 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-15 01:13:01,652] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 348.96 | bwd_microstep: 612.28 | bwd_inner_microstep: 612.25 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-15 01:13:02,456] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 330.91 | bwd_microstep: 440.87 | bwd_inner_microstep: 440.84 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.98 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-15 01:13:03,432] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 445.64 | bwd_microstep: 502.57 | bwd_inner_microstep: 502.30 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-15 01:13:04,645] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.09 | optimizer_step: 18.06 +[2025-05-15 01:13:04,646] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 284.49 | bwd_microstep: 884.42 | bwd_inner_microstep: 600.10 | bwd_allreduce_microstep: 284.24 | step_microstep: 26.88 +[2025-05-15 01:13:04,646] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2622.56 | bwd: 4440.84 | bwd_inner: 4155.77 | bwd_allreduce: 284.57 | step: 36.38 + 70%|██████▉ | 390/558 [45:00<19:19, 6.90s/it] {'loss': 5.3711, 'grad_norm': 25.197633743286133, 'learning_rate': 2.1965512476019722e-16, 'epoch': 0.21} + 70%|██████▉ | 390/558 [45:00<19:19, 6.90s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1899 +[2025-05-15 01:13:05,599] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 316.18 | bwd_microstep: 613.07 | bwd_inner_microstep: 613.04 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.28 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-15 01:13:06,421] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 339.33 | bwd_microstep: 450.92 | bwd_inner_microstep: 450.70 | bwd_allreduce_microstep: 0.18 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-15 01:13:07,403] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 443.26 | bwd_microstep: 507.70 | bwd_inner_microstep: 507.56 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-15 01:13:08,297] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 271.84 | bwd_microstep: 602.51 | bwd_inner_microstep: 602.47 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 323 +[2025-05-15 01:13:08,565] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 102.10 | bwd_microstep: 133.32 | bwd_inner_microstep: 133.07 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.44 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-15 01:13:09,356] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 270.10 | bwd_microstep: 499.06 | bwd_inner_microstep: 499.01 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.51 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-15 01:13:10,265] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 438.47 | bwd_microstep: 437.99 | bwd_inner_microstep: 437.96 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.95 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-15 01:13:11,515] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.10 | optimizer_step: 19.39 +[2025-05-15 01:13:11,516] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 230.68 | bwd_microstep: 969.94 | bwd_inner_microstep: 580.90 | bwd_allreduce_microstep: 389.00 | step_microstep: 28.61 +[2025-05-15 01:13:11,517] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2411.95 | bwd: 4214.52 | bwd_inner: 3824.74 | bwd_allreduce: 389.49 | step: 37.42 + 70%|███████ | 391/558 [45:07<19:10, 6.89s/it] {'loss': 4.3056, 'grad_norm': 17.848203659057617, 'learning_rate': 2.1725568734092999e-16, 'epoch': 0.21} + 70%|███████ | 391/558 [45:07<19:10, 6.89s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1886 +[2025-05-15 01:13:12,337] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 233.52 | bwd_microstep: 558.56 | bwd_inner_microstep: 558.54 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-15 01:13:13,234] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 424.07 | bwd_microstep: 439.22 | bwd_inner_microstep: 438.96 | bwd_allreduce_microstep: 0.10 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-15 01:13:14,218] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 344.97 | bwd_microstep: 617.95 | bwd_inner_microstep: 617.91 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1353 +[2025-05-15 01:13:14,788] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 252.68 | bwd_microstep: 285.11 | bwd_inner_microstep: 284.90 | bwd_allreduce_microstep: 0.19 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-15 01:13:15,835] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 399.13 | bwd_microstep: 625.52 | bwd_inner_microstep: 625.14 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.18 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1109 +[2025-05-15 01:13:16,268] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 212.74 | bwd_microstep: 201.83 | bwd_inner_microstep: 201.67 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-15 01:13:17,309] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 394.95 | bwd_microstep: 624.43 | bwd_inner_microstep: 624.38 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.26 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-15 01:13:18,425] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.01 | optimizer_gradients: 2.06 | optimizer_step: 20.85 +[2025-05-15 01:13:18,426] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 350.43 | bwd_microstep: 717.36 | bwd_inner_microstep: 515.49 | bwd_allreduce_microstep: 201.84 | step_microstep: 28.44 +[2025-05-15 01:13:18,426] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2612.47 | bwd: 4070.01 | bwd_inner: 3867.10 | bwd_allreduce: 202.18 | step: 33.98 + 70%|███████ | 392/558 [45:13<19:04, 6.90s/it] {'loss': 5.2863, 'grad_norm': 28.192224502563477, 'learning_rate': 2.1486578442055672e-16, 'epoch': 0.21} + 70%|███████ | 392/558 [45:13<19:04, 6.90s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1949 +[2025-05-15 01:13:19,252] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 359.60 | bwd_microstep: 439.17 | bwd_inner_microstep: 439.00 | bwd_allreduce_microstep: 0.10 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1900 +[2025-05-15 01:13:20,301] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 391.39 | bwd_microstep: 631.60 | bwd_inner_microstep: 631.58 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.31 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 850 +[2025-05-15 01:13:20,753] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 177.67 | bwd_microstep: 251.66 | bwd_inner_microstep: 251.63 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.42 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-15 01:13:21,515] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 353.37 | bwd_microstep: 387.81 | bwd_inner_microstep: 387.78 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.77 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-15 01:13:22,554] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 400.06 | bwd_microstep: 610.56 | bwd_inner_microstep: 610.27 | bwd_allreduce_microstep: 0.25 | step_microstep: 0.94 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-15 01:13:23,449] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 346.16 | bwd_microstep: 526.31 | bwd_inner_microstep: 526.27 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.80 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1347 +[2025-05-15 01:13:23,998] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 263.96 | bwd_microstep: 262.85 | bwd_inner_microstep: 262.81 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.77 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1954 +[2025-05-15 01:13:25,197] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 1.73 | optimizer_step: 16.88 +[2025-05-15 01:13:25,197] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 420.34 | bwd_microstep: 728.38 | bwd_inner_microstep: 647.32 | bwd_allreduce_microstep: 80.82 | step_microstep: 25.16 +[2025-05-15 01:13:25,198] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2712.56 | bwd: 3838.53 | bwd_inner: 3756.66 | bwd_allreduce: 81.20 | step: 36.37 + 70%|███████ | 393/558 [45:20<18:51, 6.86s/it] {'loss': 4.5464, 'grad_norm': 17.167400360107422, 'learning_rate': 2.1248549658965222e-16, 'epoch': 0.21} + 70%|███████ | 393/558 [45:20<18:51, 6.86s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1925 +[2025-05-15 01:13:26,274] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 375.40 | bwd_microstep: 676.07 | bwd_inner_microstep: 676.02 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.15 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 359 +[2025-05-15 01:13:26,518] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 102.47 | bwd_microstep: 124.00 | bwd_inner_microstep: 123.97 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.62 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-15 01:13:27,405] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 358.42 | bwd_microstep: 509.97 | bwd_inner_microstep: 509.76 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.23 +dynamic ViT batch size: 2, images per sample: 2.0, dynamic token length: 593 +[2025-05-15 01:13:27,715] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 123.12 | bwd_microstep: 168.42 | bwd_inner_microstep: 168.37 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.26 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 842 +[2025-05-15 01:13:28,156] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 175.08 | bwd_microstep: 246.92 | bwd_inner_microstep: 246.68 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-15 01:13:28,948] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 358.51 | bwd_microstep: 411.19 | bwd_inner_microstep: 411.14 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.84 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-15 01:13:29,946] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 405.03 | bwd_microstep: 567.94 | bwd_inner_microstep: 567.51 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.24 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2037 +[2025-05-15 01:13:31,136] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.21 | optimizer_gradients: 2.02 | optimizer_step: 18.77 +[2025-05-15 01:13:31,136] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 378.11 | bwd_microstep: 764.26 | bwd_inner_microstep: 562.80 | bwd_allreduce_microstep: 201.43 | step_microstep: 27.91 +[2025-05-15 01:13:31,137] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2276.12 | bwd: 3468.78 | bwd_inner: 3266.27 | bwd_allreduce: 201.50 | step: 32.43 + 71%|███████ | 394/558 [45:26<17:59, 6.58s/it] {'loss': 4.8847, 'grad_norm': 28.959110260009766, 'learning_rate': 2.1011490411455893e-16, 'epoch': 0.21} + 71%|███████ | 394/558 [45:26<17:59, 6.58s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 376 +[2025-05-15 01:13:31,395] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 101.60 | bwd_microstep: 128.17 | bwd_inner_microstep: 128.13 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.25 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1883 +[2025-05-15 01:13:32,173] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 366.43 | bwd_microstep: 389.31 | bwd_inner_microstep: 389.26 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.85 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-15 01:13:33,217] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 416.64 | bwd_microstep: 601.61 | bwd_inner_microstep: 601.58 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.13 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-15 01:13:34,045] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 214.94 | bwd_microstep: 590.13 | bwd_inner_microstep: 590.09 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-15 01:13:34,899] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 424.47 | bwd_microstep: 393.40 | bwd_inner_microstep: 393.35 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.33 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-15 01:13:35,954] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 399.18 | bwd_microstep: 634.48 | bwd_inner_microstep: 634.07 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-15 01:13:36,764] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 249.03 | bwd_microstep: 538.64 | bwd_inner_microstep: 538.58 | bwd_allreduce_microstep: 0.02 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-15 01:13:38,342] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.01 | optimizer_gradients: 2.12 | optimizer_step: 17.80 +[2025-05-15 01:13:38,343] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 439.26 | bwd_microstep: 1077.52 | bwd_inner_microstep: 437.81 | bwd_allreduce_microstep: 639.63 | step_microstep: 28.26 +[2025-05-15 01:13:38,344] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2611.54 | bwd: 4353.24 | bwd_inner: 3712.90 | bwd_allreduce: 639.68 | step: 37.54 + 71%|███████ | 395/558 [45:33<18:23, 6.77s/it] {'loss': 4.7652, 'grad_norm': 21.81688117980957, 'learning_rate': 2.077540869346788e-16, 'epoch': 0.21} + 71%|███████ | 395/558 [45:33<18:23, 6.77s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1923 +[2025-05-15 01:13:39,233] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 230.81 | bwd_microstep: 629.71 | bwd_inner_microstep: 629.67 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 894 +[2025-05-15 01:13:39,798] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 227.50 | bwd_microstep: 307.06 | bwd_inner_microstep: 306.06 | bwd_allreduce_microstep: 0.96 | step_microstep: 0.26 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-15 01:13:40,600] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 235.65 | bwd_microstep: 543.36 | bwd_inner_microstep: 543.30 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.46 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 858 +[2025-05-15 01:13:41,178] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 225.95 | bwd_microstep: 319.60 | bwd_inner_microstep: 319.56 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.56 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-15 01:13:41,989] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 277.68 | bwd_microstep: 498.07 | bwd_inner_microstep: 498.03 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.47 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-15 01:13:43,019] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 437.13 | bwd_microstep: 561.43 | bwd_inner_microstep: 561.21 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-15 01:13:43,901] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 356.26 | bwd_microstep: 506.27 | bwd_inner_microstep: 506.06 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.35 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1375 +[2025-05-15 01:13:44,797] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.01 | optimizer_gradients: 1.80 | optimizer_step: 18.56 +[2025-05-15 01:13:44,798] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 260.03 | bwd_microstep: 592.35 | bwd_inner_microstep: 387.31 | bwd_allreduce_microstep: 205.00 | step_microstep: 26.05 +[2025-05-15 01:13:44,798] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2250.73 | bwd: 3957.84 | bwd_inner: 3751.21 | bwd_allreduce: 205.06 | step: 36.53 + 71%|███████ | 396/558 [45:40<18:01, 6.68s/it] {'loss': 3.1467, 'grad_norm': 10.129538536071777, 'learning_rate': 2.0540312465977864e-16, 'epoch': 0.21} + 71%|███████ | 396/558 [45:40<18:01, 6.68s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-15 01:13:45,697] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 360.95 | bwd_microstep: 510.93 | bwd_inner_microstep: 510.52 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.24 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1110 +[2025-05-15 01:13:46,241] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 213.07 | bwd_microstep: 312.04 | bwd_inner_microstep: 311.64 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-15 01:13:47,128] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 355.98 | bwd_microstep: 511.76 | bwd_inner_microstep: 511.37 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-15 01:13:48,016] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 362.45 | bwd_microstep: 506.59 | bwd_inner_microstep: 506.36 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.23 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 841 +[2025-05-15 01:13:48,454] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 169.54 | bwd_microstep: 248.19 | bwd_inner_microstep: 248.13 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.72 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-15 01:13:49,230] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 295.84 | bwd_microstep: 457.42 | bwd_inner_microstep: 457.38 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-15 01:13:50,259] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 444.20 | bwd_microstep: 550.41 | bwd_inner_microstep: 550.39 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.26 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1922 +[2025-05-15 01:13:51,428] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.01 | optimizer_gradients: 2.07 | optimizer_step: 18.45 +[2025-05-15 01:13:51,429] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 365.01 | bwd_microstep: 755.77 | bwd_inner_microstep: 549.79 | bwd_allreduce_microstep: 205.96 | step_microstep: 27.82 +[2025-05-15 01:13:51,429] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2567.03 | bwd: 3853.10 | bwd_inner: 3645.58 | bwd_allreduce: 206.21 | step: 34.73 + 71%|███████ | 397/558 [45:46<17:52, 6.66s/it] {'loss': 4.6486, 'grad_norm': 48.437171936035156, 'learning_rate': 2.0306209656730525e-16, 'epoch': 0.21} + 71%|███████ | 397/558 [45:46<17:52, 6.66s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1927 +[2025-05-15 01:13:52,354] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 354.68 | bwd_microstep: 545.75 | bwd_inner_microstep: 545.70 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1887 +[2025-05-15 01:13:53,132] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 357.14 | bwd_microstep: 398.31 | bwd_inner_microstep: 398.27 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.84 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-15 01:13:54,121] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 344.14 | bwd_microstep: 620.37 | bwd_inner_microstep: 619.38 | bwd_allreduce_microstep: 0.96 | step_microstep: 0.22 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 352 +[2025-05-15 01:13:54,375] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 97.72 | bwd_microstep: 137.66 | bwd_inner_microstep: 137.60 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.22 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1358 +[2025-05-15 01:13:55,050] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 259.17 | bwd_microstep: 394.94 | bwd_inner_microstep: 394.89 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.32 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-15 01:13:55,936] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 358.41 | bwd_microstep: 503.15 | bwd_inner_microstep: 502.87 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.93 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1353 +[2025-05-15 01:13:56,612] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 263.70 | bwd_microstep: 391.79 | bwd_inner_microstep: 391.75 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-15 01:13:57,715] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.13 | optimizer_step: 18.12 +[2025-05-15 01:13:57,716] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 353.57 | bwd_microstep: 703.14 | bwd_inner_microstep: 508.49 | bwd_allreduce_microstep: 194.40 | step_microstep: 26.90 +[2025-05-15 01:13:57,716] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2388.54 | bwd: 3695.12 | bwd_inner: 3498.95 | bwd_allreduce: 194.49 | step: 32.83 + 71%|███████▏ | 398/558 [45:53<17:27, 6.55s/it] {'loss': 5.5102, 'grad_norm': 20.82331085205078, 'learning_rate': 2.0073108159971194e-16, 'epoch': 0.21} + 71%|███████▏ | 398/558 [45:53<17:27, 6.55s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1904 +[2025-05-15 01:13:58,672] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 322.01 | bwd_microstep: 608.03 | bwd_inner_microstep: 608.00 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.28 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1890 +[2025-05-15 01:13:59,489] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 333.19 | bwd_microstep: 450.38 | bwd_inner_microstep: 450.32 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.27 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-15 01:14:00,425] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 443.54 | bwd_microstep: 460.75 | bwd_inner_microstep: 460.40 | bwd_allreduce_microstep: 0.15 | step_microstep: 0.22 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-15 01:14:01,402] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 343.63 | bwd_microstep: 612.67 | bwd_inner_microstep: 612.64 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-15 01:14:02,202] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 314.76 | bwd_microstep: 450.56 | bwd_inner_microstep: 450.15 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-15 01:14:03,135] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 439.28 | bwd_microstep: 461.82 | bwd_inner_microstep: 461.56 | bwd_allreduce_microstep: 0.09 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-15 01:14:04,108] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 340.48 | bwd_microstep: 612.21 | bwd_inner_microstep: 612.17 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-15 01:14:05,428] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.17 | optimizer_step: 18.65 +[2025-05-15 01:14:05,429] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 350.05 | bwd_microstep: 910.22 | bwd_inner_microstep: 413.03 | bwd_allreduce_microstep: 497.16 | step_microstep: 28.02 +[2025-05-15 01:14:05,429] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2886.90 | bwd: 4566.69 | bwd_inner: 4068.38 | bwd_allreduce: 497.63 | step: 37.93 + 72%|███████▏ | 399/558 [46:00<18:16, 6.90s/it] {'loss': 4.4071, 'grad_norm': 13.676839828491211, 'learning_rate': 1.9841015836179733e-16, 'epoch': 0.21} + 72%|███████▏ | 399/558 [46:00<18:16, 6.90s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-15 01:14:06,255] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 251.57 | bwd_microstep: 546.55 | bwd_inner_microstep: 546.48 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 341 +[2025-05-15 01:14:06,536] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 106.13 | bwd_microstep: 142.37 | bwd_inner_microstep: 142.35 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1887 +[2025-05-15 01:14:07,353] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 370.26 | bwd_microstep: 414.03 | bwd_inner_microstep: 413.99 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-15 01:14:08,349] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 410.96 | bwd_microstep: 564.65 | bwd_inner_microstep: 563.68 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.21 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-15 01:14:09,181] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 214.81 | bwd_microstep: 593.72 | bwd_inner_microstep: 593.69 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.43 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-15 01:14:10,042] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 407.99 | bwd_microstep: 418.05 | bwd_inner_microstep: 417.85 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-15 01:14:11,087] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 400.38 | bwd_microstep: 624.55 | bwd_inner_microstep: 624.51 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.32 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2001 +[2025-05-15 01:14:12,441] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.08 | optimizer_step: 18.11 +[2025-05-15 01:14:12,442] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 338.33 | bwd_microstep: 969.53 | bwd_inner_microstep: 517.71 | bwd_allreduce_microstep: 451.77 | step_microstep: 26.86 +[2025-05-15 01:14:12,442] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2500.45 | bwd: 4273.45 | bwd_inner: 3820.30 | bwd_allreduce: 451.88 | step: 38.94 + 72%|███████▏ | 400/558 [46:07<18:15, 6.93s/it] {'loss': 4.678, 'grad_norm': 18.559160232543945, 'learning_rate': 1.9609940511805353e-16, 'epoch': 0.22} + 72%|███████▏ | 400/558 [46:07<18:15, 6.93s/it][INFO|trainer.py:3503] 2025-05-15 01:14:15,706 >> Saving model checkpoint to work_dirs/internvl_chat_v2_5/mmvet/checkpoint-400 +[INFO|configuration_utils.py:472] 2025-05-15 01:14:15,709 >> Configuration saved in work_dirs/internvl_chat_v2_5/mmvet/checkpoint-400/config.json +[INFO|configuration_utils.py:807] 2025-05-15 01:14:15,709 >> Configuration saved in work_dirs/internvl_chat_v2_5/mmvet/checkpoint-400/generation_config.json +[INFO|modeling_utils.py:2755] 2025-05-15 01:14:21,098 >> Model weights saved in work_dirs/internvl_chat_v2_5/mmvet/checkpoint-400/model.safetensors +[INFO|tokenization_utils_base.py:2702] 2025-05-15 01:14:21,100 >> tokenizer config file saved in work_dirs/internvl_chat_v2_5/mmvet/checkpoint-400/tokenizer_config.json +[INFO|tokenization_utils_base.py:2711] 2025-05-15 01:14:21,100 >> Special tokens file saved in work_dirs/internvl_chat_v2_5/mmvet/checkpoint-400/special_tokens_map.json +[INFO|tokenization_utils_base.py:2762] 2025-05-15 01:14:21,100 >> added tokens file saved in work_dirs/internvl_chat_v2_5/mmvet/checkpoint-400/added_tokens.json +[2025-05-15 01:14:21,293] [INFO] [logging.py:96:log_dist] [Rank 0] [Torch] Checkpoint global_step400 is about to be saved! +[2025-05-15 01:14:21,315] [INFO] [logging.py:96:log_dist] [Rank 0] Saving model checkpoint: work_dirs/internvl_chat_v2_5/mmvet/checkpoint-400/global_step400/mp_rank_00_model_states.pt +[2025-05-15 01:14:21,315] [INFO] [torch_checkpoint_engine.py:21:save] [Torch] Saving work_dirs/internvl_chat_v2_5/mmvet/checkpoint-400/global_step400/mp_rank_00_model_states.pt... +[2025-05-15 01:14:26,117] [INFO] [torch_checkpoint_engine.py:23:save] [Torch] Saved work_dirs/internvl_chat_v2_5/mmvet/checkpoint-400/global_step400/mp_rank_00_model_states.pt. +[2025-05-15 01:14:26,118] [INFO] [torch_checkpoint_engine.py:21:save] [Torch] Saving work_dirs/internvl_chat_v2_5/mmvet/checkpoint-400/global_step400/bf16_zero_pp_rank_0_mp_rank_00_optim_states.pt... +[2025-05-15 01:14:26,300] [INFO] [torch_checkpoint_engine.py:23:save] [Torch] Saved work_dirs/internvl_chat_v2_5/mmvet/checkpoint-400/global_step400/bf16_zero_pp_rank_0_mp_rank_00_optim_states.pt. +[2025-05-15 01:14:26,300] [INFO] [engine.py:3536:_save_zero_checkpoint] zero checkpoint saved work_dirs/internvl_chat_v2_5/mmvet/checkpoint-400/global_step400/bf16_zero_pp_rank_0_mp_rank_00_optim_states.pt +[2025-05-15 01:14:26,300] [INFO] [torch_checkpoint_engine.py:33:commit] [Torch] Checkpoint global_step400 is ready now! +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1890 +[2025-05-15 01:14:27,128] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 383.50 | bwd_microstep: 405.98 | bwd_inner_microstep: 405.92 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.81 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-15 01:14:28,170] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 413.79 | bwd_microstep: 569.36 | bwd_inner_microstep: 569.33 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.26 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 843 +[2025-05-15 01:14:28,482] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 105.96 | bwd_microstep: 184.38 | bwd_inner_microstep: 184.35 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.76 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-15 01:14:29,503] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 401.63 | bwd_microstep: 594.69 | bwd_inner_microstep: 594.48 | bwd_allreduce_microstep: 0.18 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-15 01:14:30,309] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 247.88 | bwd_microstep: 536.65 | bwd_inner_microstep: 536.60 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.49 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-15 01:14:31,188] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 424.56 | bwd_microstep: 422.41 | bwd_inner_microstep: 422.23 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-15 01:14:31,918] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 194.26 | bwd_microstep: 517.43 | bwd_inner_microstep: 517.39 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-15 01:14:33,155] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.08 | optimizer_gradients: 2.06 | optimizer_step: 29.32 +[2025-05-15 01:14:33,156] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 437.64 | bwd_microstep: 729.84 | bwd_inner_microstep: 522.44 | bwd_allreduce_microstep: 207.19 | step_microstep: 38.12 +[2025-05-15 01:14:33,156] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2609.21 | bwd: 3960.76 | bwd_inner: 3752.78 | bwd_allreduce: 207.50 | step: 47.10 + 72%|███████▏ | 401/558 [46:28<28:57, 11.07s/it] {'loss': 4.6466, 'grad_norm': 25.4945068359375, 'learning_rate': 1.9379889979002703e-16, 'epoch': 0.22} + 72%|███████▏ | 401/558 [46:28<28:57, 11.07s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1906 +[2025-05-15 01:14:34,085] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 295.29 | bwd_microstep: 607.63 | bwd_inner_microstep: 607.61 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.53 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-15 01:14:34,987] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 371.63 | bwd_microstep: 497.58 | bwd_inner_microstep: 497.33 | bwd_allreduce_microstep: 0.10 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-15 01:14:35,883] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 273.10 | bwd_microstep: 602.65 | bwd_inner_microstep: 602.61 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.32 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-15 01:14:36,803] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 381.80 | bwd_microstep: 505.18 | bwd_inner_microstep: 504.97 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-15 01:14:37,630] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 222.87 | bwd_microstep: 582.25 | bwd_inner_microstep: 582.22 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1346 +[2025-05-15 01:14:38,382] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 325.81 | bwd_microstep: 391.27 | bwd_inner_microstep: 391.23 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.31 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-15 01:14:39,150] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 350.23 | bwd_microstep: 394.42 | bwd_inner_microstep: 394.37 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.79 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-15 01:14:40,404] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.01 | optimizer_gradients: 2.12 | optimizer_step: 23.13 +[2025-05-15 01:14:40,404] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 414.74 | bwd_microstep: 783.46 | bwd_inner_microstep: 581.48 | bwd_allreduce_microstep: 201.73 | step_microstep: 31.63 +[2025-05-15 01:14:40,405] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2635.44 | bwd: 4364.44 | bwd_inner: 4161.87 | bwd_allreduce: 201.85 | step: 43.23 + 72%|███████▏ | 402/558 [46:35<25:47, 9.92s/it] {'loss': 5.1515, 'grad_norm': 31.39311408996582, 'learning_rate': 1.9150871995369252e-16, 'epoch': 0.22} + 72%|███████▏ | 402/558 [46:35<25:47, 9.92s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1893 +[2025-05-15 01:14:41,175] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 343.25 | bwd_microstep: 397.91 | bwd_inner_microstep: 397.68 | bwd_allreduce_microstep: 0.20 | step_microstep: 0.22 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1890 +[2025-05-15 01:14:42,225] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 393.54 | bwd_microstep: 630.57 | bwd_inner_microstep: 630.50 | bwd_allreduce_microstep: 0.02 | step_microstep: 1.65 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 348 +[2025-05-15 01:14:42,476] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.99 | bwd_microstep: 138.85 | bwd_inner_microstep: 138.58 | bwd_allreduce_microstep: 0.24 | step_microstep: 0.92 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-15 01:14:43,182] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 212.94 | bwd_microstep: 471.07 | bwd_inner_microstep: 471.03 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-15 01:14:44,189] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 442.84 | bwd_microstep: 528.91 | bwd_inner_microstep: 528.46 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.25 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-15 01:14:44,980] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 357.91 | bwd_microstep: 412.42 | bwd_inner_microstep: 412.38 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.83 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-15 01:14:45,977] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 410.02 | bwd_microstep: 562.52 | bwd_inner_microstep: 561.60 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.24 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-15 01:14:47,356] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.12 | optimizer_step: 18.55 +[2025-05-15 01:14:47,357] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 351.58 | bwd_microstep: 981.21 | bwd_inner_microstep: 390.14 | bwd_allreduce_microstep: 590.86 | step_microstep: 27.24 +[2025-05-15 01:14:47,357] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2606.86 | bwd: 4123.46 | bwd_inner: 3530.36 | bwd_allreduce: 591.35 | step: 34.71 + 72%|███████▏ | 403/558 [46:42<23:19, 9.03s/it] {'loss': 5.8496, 'grad_norm': 23.32976531982422, 'learning_rate': 1.8922894283683536e-16, 'epoch': 0.22} + 72%|███████▏ | 403/558 [46:42<23:19, 9.03s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1886 +[2025-05-15 01:14:48,201] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 357.96 | bwd_microstep: 458.98 | bwd_inner_microstep: 458.79 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1891 +[2025-05-15 01:14:49,146] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 308.41 | bwd_microstep: 616.51 | bwd_inner_microstep: 616.48 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1886 +[2025-05-15 01:14:50,068] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 370.42 | bwd_microstep: 516.87 | bwd_inner_microstep: 516.64 | bwd_allreduce_microstep: 0.19 | step_microstep: 0.21 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1897 +[2025-05-15 01:14:50,866] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 283.75 | bwd_microstep: 493.04 | bwd_inner_microstep: 493.01 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.43 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-15 01:14:51,865] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 438.93 | bwd_microstep: 527.09 | bwd_inner_microstep: 527.05 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.31 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-15 01:14:52,654] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 361.94 | bwd_microstep: 405.81 | bwd_inner_microstep: 405.76 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-15 01:14:53,668] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 419.48 | bwd_microstep: 572.91 | bwd_inner_microstep: 572.70 | bwd_allreduce_microstep: 0.19 | step_microstep: 0.23 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-15 01:14:55,019] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.01 | optimizer_gradients: 2.12 | optimizer_step: 19.34 +[2025-05-15 01:14:55,020] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 353.48 | bwd_microstep: 951.29 | bwd_inner_microstep: 382.75 | bwd_allreduce_microstep: 568.51 | step_microstep: 28.28 +[2025-05-15 01:14:55,021] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2894.35 | bwd: 4542.51 | bwd_inner: 3973.22 | bwd_allreduce: 569.01 | step: 38.04 + 72%|███████▏ | 404/558 [46:50<22:07, 8.62s/it] {'loss': 4.5289, 'grad_norm': 16.389137268066406, 'learning_rate': 1.8695964531644788e-16, 'epoch': 0.22} + 72%|███████▏ | 404/558 [46:50<22:07, 8.62s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 345 +[2025-05-15 01:14:55,295] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.58 | bwd_microstep: 150.22 | bwd_inner_microstep: 149.78 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.74 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1385 +[2025-05-15 01:14:55,855] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 242.57 | bwd_microstep: 296.64 | bwd_inner_microstep: 296.61 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.32 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-15 01:14:56,887] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 406.70 | bwd_microstep: 595.69 | bwd_inner_microstep: 595.65 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.32 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 850 +[2025-05-15 01:14:57,342] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 181.06 | bwd_microstep: 251.08 | bwd_inner_microstep: 251.05 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.27 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-15 01:14:58,174] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 223.52 | bwd_microstep: 583.34 | bwd_inner_microstep: 583.29 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1100 +[2025-05-15 01:14:58,793] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 271.30 | bwd_microstep: 314.55 | bwd_inner_microstep: 314.16 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.36 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 845 +[2025-05-15 01:14:59,232] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 170.82 | bwd_microstep: 247.22 | bwd_inner_microstep: 247.19 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.31 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-15 01:15:00,464] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.10 | optimizer_step: 18.11 +[2025-05-15 01:15:00,465] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 240.07 | bwd_microstep: 943.67 | bwd_inner_microstep: 608.19 | bwd_allreduce_microstep: 335.46 | step_microstep: 26.80 +[2025-05-15 01:15:00,466] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 1830.60 | bwd: 3382.39 | bwd_inner: 3045.93 | bwd_allreduce: 335.69 | step: 39.32 + 73%|███████▎ | 405/558 [46:55<19:33, 7.67s/it] {'loss': 4.5755, 'grad_norm': 13.936663627624512, 'learning_rate': 1.8470090391613737e-16, 'epoch': 0.22} + 73%|███████▎ | 405/558 [46:55<19:33, 7.67s/it]dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 929 +[2025-05-15 01:15:00,955] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 183.99 | bwd_microstep: 281.82 | bwd_inner_microstep: 281.62 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1888 +[2025-05-15 01:15:01,829] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 242.26 | bwd_microstep: 607.60 | bwd_inner_microstep: 607.56 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1370 +[2025-05-15 01:15:02,562] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 309.68 | bwd_microstep: 393.51 | bwd_inner_microstep: 393.47 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-15 01:15:03,360] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 284.44 | bwd_microstep: 491.75 | bwd_inner_microstep: 491.71 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.59 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-15 01:15:04,350] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 442.57 | bwd_microstep: 515.13 | bwd_inner_microstep: 515.10 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.22 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-15 01:15:05,110] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 352.90 | bwd_microstep: 387.27 | bwd_inner_microstep: 387.23 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.82 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-15 01:15:06,129] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 397.52 | bwd_microstep: 596.65 | bwd_inner_microstep: 596.61 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.26 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-15 01:15:07,498] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.07 | optimizer_step: 19.58 +[2025-05-15 01:15:07,499] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 352.39 | bwd_microstep: 967.12 | bwd_inner_microstep: 424.53 | bwd_allreduce_microstep: 542.46 | step_microstep: 28.88 +[2025-05-15 01:15:07,499] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2565.73 | bwd: 4240.86 | bwd_inner: 3698.05 | bwd_allreduce: 542.48 | step: 36.42 + 73%|███████▎ | 406/558 [47:03<18:56, 7.48s/it] {'loss': 5.1732, 'grad_norm': 19.63313102722168, 'learning_rate': 1.8245279480354504e-16, 'epoch': 0.22} + 73%|███████▎ | 406/558 [47:03<18:56, 7.48s/it]dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1522 +[2025-05-15 01:15:08,240] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 277.20 | bwd_microstep: 437.62 | bwd_inner_microstep: 437.41 | bwd_allreduce_microstep: 0.18 | step_microstep: 0.17 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-15 01:15:09,075] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 224.51 | bwd_microstep: 588.91 | bwd_inner_microstep: 588.87 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-15 01:15:10,041] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 407.23 | bwd_microstep: 524.08 | bwd_inner_microstep: 524.04 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.27 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-15 01:15:10,898] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 236.47 | bwd_microstep: 598.92 | bwd_inner_microstep: 598.89 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.28 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-15 01:15:11,845] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 408.05 | bwd_microstep: 504.28 | bwd_inner_microstep: 504.03 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.26 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 326 +[2025-05-15 01:15:12,088] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.57 | bwd_microstep: 131.78 | bwd_inner_microstep: 131.61 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-15 01:15:13,000] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 307.85 | bwd_microstep: 584.39 | bwd_inner_microstep: 584.35 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-15 01:15:14,098] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.10 | optimizer_step: 18.17 +[2025-05-15 01:15:14,099] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 384.44 | bwd_microstep: 654.59 | bwd_inner_microstep: 501.16 | bwd_allreduce_microstep: 153.20 | step_microstep: 26.96 +[2025-05-15 01:15:14,099] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2340.30 | bwd: 4024.80 | bwd_inner: 3870.40 | bwd_allreduce: 153.51 | step: 36.77 + 73%|███████▎ | 407/558 [47:09<18:09, 7.21s/it] {'loss': 4.4844, 'grad_norm': 27.700960159301758, 'learning_rate': 1.802153937877777e-16, 'epoch': 0.22} + 73%|███████▎ | 407/558 [47:09<18:09, 7.21s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-15 01:15:15,086] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 351.10 | bwd_microstep: 609.84 | bwd_inner_microstep: 609.80 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.54 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-15 01:15:15,993] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 357.61 | bwd_microstep: 516.15 | bwd_inner_microstep: 516.10 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.00 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 850 +[2025-05-15 01:15:16,312] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.64 | bwd_microstep: 204.36 | bwd_inner_microstep: 204.31 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.79 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 334 +[2025-05-15 01:15:16,587] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 97.90 | bwd_microstep: 149.95 | bwd_inner_microstep: 149.91 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1365 +[2025-05-15 01:15:17,375] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 333.09 | bwd_microstep: 420.38 | bwd_inner_microstep: 420.34 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.19 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 325 +[2025-05-15 01:15:17,626] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.38 | bwd_microstep: 139.99 | bwd_inner_microstep: 139.94 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.24 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-15 01:15:18,418] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 276.19 | bwd_microstep: 492.24 | bwd_inner_microstep: 492.20 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.28 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 845 +[2025-05-15 01:15:19,209] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.01 | optimizer_gradients: 2.08 | optimizer_step: 16.84 +[2025-05-15 01:15:19,210] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 227.63 | bwd_microstep: 506.41 | bwd_inner_microstep: 304.43 | bwd_allreduce_microstep: 201.76 | step_microstep: 25.25 +[2025-05-15 01:15:19,211] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 1832.54 | bwd: 3039.31 | bwd_inner: 2837.05 | bwd_allreduce: 201.83 | step: 35.64 + 73%|███████▎ | 408/558 [47:14<16:27, 6.58s/it] {'loss': 6.5815, 'grad_norm': 18.758182525634766, 'learning_rate': 1.7798877631685202e-16, 'epoch': 0.22} + 73%|███████▎ | 408/558 [47:14<16:27, 6.58s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1890 +[2025-05-15 01:15:19,980] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 346.70 | bwd_microstep: 396.95 | bwd_inner_microstep: 396.74 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.44 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1898 +[2025-05-15 01:15:21,020] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 398.21 | bwd_microstep: 620.02 | bwd_inner_microstep: 619.80 | bwd_allreduce_microstep: 0.19 | step_microstep: 0.18 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 861 +[2025-05-15 01:15:21,460] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 173.38 | bwd_microstep: 244.49 | bwd_inner_microstep: 244.47 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.31 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-15 01:15:22,255] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 325.74 | bwd_microstep: 447.31 | bwd_inner_microstep: 447.09 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-15 01:15:23,282] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 441.84 | bwd_microstep: 552.46 | bwd_inner_microstep: 552.41 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.16 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-15 01:15:24,039] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 354.21 | bwd_microstep: 381.14 | bwd_inner_microstep: 381.11 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.85 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-15 01:15:25,079] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 402.31 | bwd_microstep: 609.43 | bwd_inner_microstep: 609.40 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.24 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-15 01:15:26,001] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.01 | optimizer_gradients: 2.08 | optimizer_step: 18.14 +[2025-05-15 01:15:26,002] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 351.07 | bwd_microstep: 525.26 | bwd_inner_microstep: 462.22 | bwd_allreduce_microstep: 62.96 | step_microstep: 26.37 +[2025-05-15 01:15:26,003] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2793.44 | bwd: 3777.24 | bwd_inner: 3713.28 | bwd_allreduce: 63.18 | step: 33.51 + 73%|███████▎ | 409/558 [47:21<16:30, 6.65s/it] {'loss': 7.63, 'grad_norm': 33.362579345703125, 'learning_rate': 1.7577301747514925e-16, 'epoch': 0.22} + 73%|███████▎ | 409/558 [47:21<16:30, 6.65s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1898 +[2025-05-15 01:15:27,053] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 401.52 | bwd_microstep: 614.04 | bwd_inner_microstep: 614.00 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.27 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 352 +[2025-05-15 01:15:27,300] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.71 | bwd_microstep: 133.47 | bwd_inner_microstep: 133.32 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-15 01:15:28,347] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 396.40 | bwd_microstep: 628.03 | bwd_inner_microstep: 627.99 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.33 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-15 01:15:29,077] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 252.76 | bwd_microstep: 454.74 | bwd_inner_microstep: 454.61 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-15 01:15:30,007] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 325.76 | bwd_microstep: 587.93 | bwd_inner_microstep: 587.46 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.30 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-15 01:15:30,835] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 219.96 | bwd_microstep: 585.76 | bwd_inner_microstep: 585.73 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-15 01:15:31,668] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 410.09 | bwd_microstep: 386.82 | bwd_inner_microstep: 386.76 | bwd_allreduce_microstep: 0.02 | step_microstep: 1.82 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-15 01:15:32,842] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.12 | optimizer_step: 17.82 +[2025-05-15 01:15:32,843] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 397.00 | bwd_microstep: 724.34 | bwd_inner_microstep: 598.12 | bwd_allreduce_microstep: 126.16 | step_microstep: 26.45 +[2025-05-15 01:15:32,843] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2497.17 | bwd: 4115.17 | bwd_inner: 3988.05 | bwd_allreduce: 126.35 | step: 35.71 + 73%|███████▎ | 410/558 [47:28<16:32, 6.70s/it] {'loss': 3.9417, 'grad_norm': 16.979843139648438, 'learning_rate': 1.7356819198088393e-16, 'epoch': 0.22} + 73%|███████▎ | 410/558 [47:28<16:32, 6.70s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1896 +[2025-05-15 01:15:33,835] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 348.64 | bwd_microstep: 616.41 | bwd_inner_microstep: 616.37 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-15 01:15:34,627] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 307.18 | bwd_microstep: 452.72 | bwd_inner_microstep: 452.50 | bwd_allreduce_microstep: 0.18 | step_microstep: 0.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-15 01:15:35,563] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 437.59 | bwd_microstep: 465.13 | bwd_inner_microstep: 464.91 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-15 01:15:36,556] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 350.60 | bwd_microstep: 622.71 | bwd_inner_microstep: 622.67 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-15 01:15:37,176] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 304.22 | bwd_microstep: 283.84 | bwd_inner_microstep: 283.68 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1102 +[2025-05-15 01:15:37,761] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 218.98 | bwd_microstep: 347.92 | bwd_inner_microstep: 347.87 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.33 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-15 01:15:38,590] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 421.69 | bwd_microstep: 373.95 | bwd_inner_microstep: 373.91 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.79 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-15 01:15:39,775] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.05 | optimizer_step: 16.86 +[2025-05-15 01:15:39,775] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 392.90 | bwd_microstep: 742.55 | bwd_inner_microstep: 602.50 | bwd_allreduce_microstep: 139.50 | step_microstep: 25.40 +[2025-05-15 01:15:39,776] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2781.76 | bwd: 3905.25 | bwd_inner: 3764.98 | bwd_allreduce: 139.85 | step: 34.64 + 74%|███████▎ | 411/558 [47:35<16:35, 6.77s/it] {'loss': 5.5113, 'grad_norm': 21.29913330078125, 'learning_rate': 1.7137437418358422e-16, 'epoch': 0.22} + 74%|███████▎ | 411/558 [47:35<16:35, 6.77s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-15 01:15:40,744] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 347.90 | bwd_microstep: 593.37 | bwd_inner_microstep: 593.32 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-15 01:15:41,559] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 332.53 | bwd_microstep: 450.45 | bwd_inner_microstep: 450.24 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-15 01:15:42,499] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 439.18 | bwd_microstep: 469.38 | bwd_inner_microstep: 469.04 | bwd_allreduce_microstep: 0.14 | step_microstep: 0.14 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-15 01:15:43,473] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 343.78 | bwd_microstep: 610.66 | bwd_inner_microstep: 610.63 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.31 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-15 01:15:44,277] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 314.67 | bwd_microstep: 454.67 | bwd_inner_microstep: 453.04 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-15 01:15:45,210] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 443.02 | bwd_microstep: 457.07 | bwd_inner_microstep: 456.74 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.21 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-15 01:15:45,968] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 193.08 | bwd_microstep: 546.11 | bwd_inner_microstep: 546.09 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.58 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-15 01:15:47,411] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.01 | optimizer_gradients: 2.05 | optimizer_step: 18.58 +[2025-05-15 01:15:47,412] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 421.98 | bwd_microstep: 960.49 | bwd_inner_microstep: 380.40 | bwd_allreduce_microstep: 580.06 | step_microstep: 27.41 +[2025-05-15 01:15:47,413] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2836.07 | bwd: 4542.45 | bwd_inner: 3959.61 | bwd_allreduce: 581.76 | step: 37.38 + 74%|███████▍ | 412/558 [47:42<17:06, 7.03s/it] {'loss': 6.7235, 'grad_norm': 37.202423095703125, 'learning_rate': 1.6919163806158455e-16, 'epoch': 0.22} + 74%|███████▍ | 412/558 [47:42<17:06, 7.03s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1950 +[2025-05-15 01:15:48,301] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 237.11 | bwd_microstep: 622.44 | bwd_inner_microstep: 622.41 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1369 +[2025-05-15 01:15:48,933] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 312.13 | bwd_microstep: 289.98 | bwd_inner_microstep: 289.83 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-15 01:15:49,973] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 393.37 | bwd_microstep: 627.55 | bwd_inner_microstep: 627.50 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.21 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1365 +[2025-05-15 01:15:50,657] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 265.54 | bwd_microstep: 396.68 | bwd_inner_microstep: 396.65 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.89 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 848 +[2025-05-15 01:15:51,000] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 171.22 | bwd_microstep: 154.09 | bwd_inner_microstep: 153.81 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-15 01:15:52,007] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 358.63 | bwd_microstep: 629.27 | bwd_inner_microstep: 629.23 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-15 01:15:52,919] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 353.63 | bwd_microstep: 525.64 | bwd_inner_microstep: 525.43 | bwd_allreduce_microstep: 0.18 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-15 01:15:53,839] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.08 | optimizer_step: 17.78 +[2025-05-15 01:15:53,840] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 356.38 | bwd_microstep: 517.73 | bwd_inner_microstep: 457.01 | bwd_allreduce_microstep: 60.62 | step_microstep: 26.39 +[2025-05-15 01:15:53,840] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2448.00 | bwd: 3764.39 | bwd_inner: 3701.98 | bwd_allreduce: 61.00 | step: 32.60 + 74%|███████▍ | 413/558 [47:49<16:33, 6.85s/it] {'loss': 5.7222, 'grad_norm': 28.838199615478516, 'learning_rate': 1.6702005721953164e-16, 'epoch': 0.22} + 74%|███████▍ | 413/558 [47:49<16:33, 6.85s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1886 +[2025-05-15 01:15:54,900] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 399.14 | bwd_microstep: 630.18 | bwd_inner_microstep: 630.14 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.68 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 847 +[2025-05-15 01:15:55,337] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 174.21 | bwd_microstep: 243.13 | bwd_inner_microstep: 242.90 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.24 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-15 01:15:56,221] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 357.60 | bwd_microstep: 506.21 | bwd_inner_microstep: 505.77 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.25 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-15 01:15:57,006] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 358.69 | bwd_microstep: 408.95 | bwd_inner_microstep: 408.92 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.28 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1355 +[2025-05-15 01:15:57,808] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 300.47 | bwd_microstep: 477.38 | bwd_inner_microstep: 477.33 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.28 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 839 +[2025-05-15 01:15:58,227] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 166.44 | bwd_microstep: 234.27 | bwd_inner_microstep: 234.05 | bwd_allreduce_microstep: 0.19 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-15 01:15:59,113] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 359.00 | bwd_microstep: 506.80 | bwd_inner_microstep: 506.76 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.25 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-15 01:16:00,136] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.07 | optimizer_gradients: 2.09 | optimizer_step: 18.09 +[2025-05-15 01:16:00,136] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 354.49 | bwd_microstep: 622.26 | bwd_inner_microstep: 514.86 | bwd_allreduce_microstep: 107.34 | step_microstep: 26.80 +[2025-05-15 01:16:00,137] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2470.04 | bwd: 3629.17 | bwd_inner: 3520.73 | bwd_allreduce: 107.64 | step: 29.97 + 74%|███████▍ | 414/558 [47:55<16:02, 6.68s/it] {'loss': 6.8714, 'grad_norm': 23.841350555419922, 'learning_rate': 1.6485970488590153e-16, 'epoch': 0.22} + 74%|███████▍ | 414/558 [47:55<16:02, 6.68s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1944 +[2025-05-15 01:16:01,190] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 367.33 | bwd_microstep: 659.80 | bwd_inner_microstep: 659.76 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 2, images per sample: 2.0, dynamic token length: 595 +[2025-05-15 01:16:01,511] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 131.55 | bwd_microstep: 168.24 | bwd_inner_microstep: 168.22 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.24 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 846 +[2025-05-15 01:16:01,948] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 175.97 | bwd_microstep: 242.81 | bwd_inner_microstep: 242.42 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-15 01:16:02,836] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 356.10 | bwd_microstep: 509.10 | bwd_inner_microstep: 509.06 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.24 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-15 01:16:03,586] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 349.01 | bwd_microstep: 378.92 | bwd_inner_microstep: 378.89 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.81 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-15 01:16:04,615] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 399.49 | bwd_microstep: 604.46 | bwd_inner_microstep: 604.07 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.24 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-15 01:16:05,493] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 358.15 | bwd_microstep: 500.51 | bwd_inner_microstep: 500.26 | bwd_allreduce_microstep: 0.21 | step_microstep: 0.22 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-15 01:16:06,786] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.01 | optimizer_gradients: 1.73 | optimizer_step: 17.76 +[2025-05-15 01:16:06,786] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 286.07 | bwd_microstep: 962.34 | bwd_inner_microstep: 492.88 | bwd_allreduce_microstep: 469.42 | step_microstep: 25.47 +[2025-05-15 01:16:06,787] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2423.65 | bwd: 4026.16 | bwd_inner: 3555.58 | bwd_allreduce: 470.05 | step: 30.76 + 74%|███████▍ | 415/558 [48:02<15:54, 6.67s/it] {'loss': 5.7155, 'grad_norm': 29.31334686279297, 'learning_rate': 1.6271065391053015e-16, 'epoch': 0.22} + 74%|███████▍ | 415/558 [48:02<15:54, 6.67s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-15 01:16:07,684] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 351.00 | bwd_microstep: 519.24 | bwd_inner_microstep: 519.21 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.68 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-15 01:16:08,464] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 338.90 | bwd_microstep: 421.10 | bwd_inner_microstep: 420.94 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-15 01:16:09,503] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 394.27 | bwd_microstep: 625.13 | bwd_inner_microstep: 624.87 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.29 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-15 01:16:10,308] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 274.14 | bwd_microstep: 513.35 | bwd_inner_microstep: 512.95 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.22 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-15 01:16:11,204] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 358.65 | bwd_microstep: 515.69 | bwd_inner_microstep: 515.65 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.69 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-15 01:16:11,986] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 342.45 | bwd_microstep: 417.30 | bwd_inner_microstep: 417.24 | bwd_allreduce_microstep: 0.02 | step_microstep: 1.85 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-15 01:16:12,985] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 409.77 | bwd_microstep: 565.68 | bwd_inner_microstep: 565.27 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.24 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-15 01:16:14,094] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.01 | optimizer_gradients: 2.05 | optimizer_step: 18.84 +[2025-05-15 01:16:14,094] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 360.38 | bwd_microstep: 701.89 | bwd_inner_microstep: 501.59 | bwd_allreduce_microstep: 200.28 | step_microstep: 26.94 +[2025-05-15 01:16:14,095] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2829.57 | bwd: 4279.40 | bwd_inner: 4077.75 | bwd_allreduce: 200.78 | step: 31.00 + 75%|███████▍ | 416/558 [48:09<16:14, 6.86s/it] {'loss': 4.597, 'grad_norm': 16.3806095123291, 'learning_rate': 1.6057297676215832e-16, 'epoch': 0.22} + 75%|███████▍ | 416/558 [48:09<16:14, 6.86s/it]dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1391 +[2025-05-15 01:16:14,777] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 258.44 | bwd_microstep: 394.50 | bwd_inner_microstep: 394.46 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.49 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-15 01:16:15,589] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 249.09 | bwd_microstep: 541.23 | bwd_inner_microstep: 541.18 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.55 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 342 +[2025-05-15 01:16:15,872] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 103.20 | bwd_microstep: 147.98 | bwd_inner_microstep: 147.93 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-15 01:16:16,793] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 371.75 | bwd_microstep: 515.98 | bwd_inner_microstep: 515.92 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.23 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-15 01:16:17,676] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 346.17 | bwd_microstep: 516.23 | bwd_inner_microstep: 516.20 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.26 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-15 01:16:18,430] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 338.43 | bwd_microstep: 394.60 | bwd_inner_microstep: 394.57 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.84 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-15 01:16:19,459] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 416.61 | bwd_microstep: 586.68 | bwd_inner_microstep: 586.65 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.26 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2016 +[2025-05-15 01:16:20,637] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.26 | optimizer_gradients: 2.14 | optimizer_step: 17.19 +[2025-05-15 01:16:20,638] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 365.72 | bwd_microstep: 766.43 | bwd_inner_microstep: 554.13 | bwd_allreduce_microstep: 212.10 | step_microstep: 26.66 +[2025-05-15 01:16:20,639] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2449.37 | bwd: 3863.62 | bwd_inner: 3651.06 | bwd_allreduce: 212.17 | step: 36.66 + 75%|███████▍ | 417/558 [48:16<15:54, 6.77s/it] {'loss': 3.8366, 'grad_norm': 21.71257972717285, 'learning_rate': 1.584467455259861e-16, 'epoch': 0.22} + 75%|███████▍ | 417/558 [48:16<15:54, 6.77s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-15 01:16:21,399] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 286.39 | bwd_microstep: 447.00 | bwd_inner_microstep: 446.68 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.21 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-15 01:16:22,381] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 367.63 | bwd_microstep: 596.25 | bwd_inner_microstep: 596.20 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.59 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-15 01:16:23,264] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 354.41 | bwd_microstep: 508.71 | bwd_inner_microstep: 508.48 | bwd_allreduce_microstep: 0.19 | step_microstep: 0.18 +dynamic ViT batch size: 6, images per sample: 6.0, dynamic token length: 1606 +[2025-05-15 01:16:24,050] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 300.31 | bwd_microstep: 467.04 | bwd_inner_microstep: 466.67 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.17 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 835 +[2025-05-15 01:16:24,382] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 166.11 | bwd_microstep: 148.69 | bwd_inner_microstep: 148.37 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1942 +[2025-05-15 01:16:25,435] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 367.42 | bwd_microstep: 665.12 | bwd_inner_microstep: 665.07 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.37 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1937 +[2025-05-15 01:16:26,370] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 373.02 | bwd_microstep: 537.66 | bwd_inner_microstep: 537.63 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.94 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1891 +[2025-05-15 01:16:27,475] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.13 | optimizer_step: 19.38 +[2025-05-15 01:16:27,476] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 339.51 | bwd_microstep: 719.60 | bwd_inner_microstep: 517.35 | bwd_allreduce_microstep: 202.24 | step_microstep: 27.36 +[2025-05-15 01:16:27,477] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2554.78 | bwd: 4090.17 | bwd_inner: 3886.57 | bwd_allreduce: 202.88 | step: 32.97 + 75%|███████▍ | 418/558 [48:23<15:50, 6.79s/it] {'loss': 4.4992, 'grad_norm': 24.917612075805664, 'learning_rate': 1.5633203190124279e-16, 'epoch': 0.22} + 75%|███████▍ | 418/558 [48:23<15:50, 6.79s/it]dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 867 +[2025-05-15 01:16:27,841] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.69 | bwd_microstep: 242.95 | bwd_inner_microstep: 242.92 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.78 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-15 01:16:28,861] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 413.48 | bwd_microstep: 581.49 | bwd_inner_microstep: 581.31 | bwd_allreduce_microstep: 0.17 | step_microstep: 0.17 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1117 +[2025-05-15 01:16:29,402] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 210.73 | bwd_microstep: 310.02 | bwd_inner_microstep: 309.78 | bwd_allreduce_microstep: 0.21 | step_microstep: 0.17 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-15 01:16:30,285] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 357.50 | bwd_microstep: 504.79 | bwd_inner_microstep: 504.75 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.23 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 837 +[2025-05-15 01:16:30,697] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 160.35 | bwd_microstep: 232.02 | bwd_inner_microstep: 231.98 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.24 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 326 +[2025-05-15 01:16:30,925] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 83.01 | bwd_microstep: 128.44 | bwd_inner_microstep: 128.29 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-15 01:16:31,862] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 307.03 | bwd_microstep: 609.12 | bwd_inner_microstep: 609.08 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.33 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 836 +[2025-05-15 01:16:32,554] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.25 | optimizer_gradients: 2.12 | optimizer_step: 18.51 +[2025-05-15 01:16:32,555] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 200.12 | bwd_microstep: 433.68 | bwd_inner_microstep: 237.19 | bwd_allreduce_microstep: 196.29 | step_microstep: 27.46 +[2025-05-15 01:16:32,556] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 1827.89 | bwd: 3042.51 | bwd_inner: 2845.33 | bwd_allreduce: 196.59 | step: 32.50 + 75%|███████▌ | 419/558 [48:28<14:32, 6.28s/it] {'loss': 5.5882, 'grad_norm': 29.823728561401367, 'learning_rate': 1.5422890719876998e-16, 'epoch': 0.23} + 75%|███████▌ | 419/558 [48:28<14:32, 6.28s/it]dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1403 +[2025-05-15 01:16:33,244] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 267.49 | bwd_microstep: 394.52 | bwd_inner_microstep: 394.47 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.11 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1380 +[2025-05-15 01:16:33,861] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 262.25 | bwd_microstep: 334.71 | bwd_inner_microstep: 334.53 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1366 +[2025-05-15 01:16:34,548] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 212.09 | bwd_microstep: 454.90 | bwd_inner_microstep: 454.86 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.50 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-15 01:16:35,518] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 430.06 | bwd_microstep: 505.50 | bwd_inner_microstep: 505.29 | bwd_allreduce_microstep: 0.18 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-15 01:16:36,399] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 357.86 | bwd_microstep: 503.44 | bwd_inner_microstep: 503.40 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.22 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 322 +[2025-05-15 01:16:36,653] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 89.67 | bwd_microstep: 145.66 | bwd_inner_microstep: 145.63 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.25 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-15 01:16:37,431] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 268.82 | bwd_microstep: 485.35 | bwd_inner_microstep: 485.29 | bwd_allreduce_microstep: 0.02 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-15 01:16:38,486] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.08 | optimizer_gradients: 2.10 | optimizer_step: 17.97 +[2025-05-15 01:16:38,487] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 439.72 | bwd_microstep: 554.89 | bwd_inner_microstep: 494.62 | bwd_allreduce_microstep: 60.17 | step_microstep: 27.44 +[2025-05-15 01:16:38,488] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2327.93 | bwd: 3379.01 | bwd_inner: 3318.19 | bwd_allreduce: 60.48 | step: 35.14 + 75%|███████▌ | 420/558 [48:34<14:11, 6.17s/it] {'loss': 4.4709, 'grad_norm': 21.148174285888672, 'learning_rate': 1.5213744233861465e-16, 'epoch': 0.23} + 75%|███████▌ | 420/558 [48:34<14:11, 6.17s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1906 +[2025-05-15 01:16:39,535] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 390.39 | bwd_microstep: 629.35 | bwd_inner_microstep: 629.13 | bwd_allreduce_microstep: 0.18 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-15 01:16:40,334] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 324.24 | bwd_microstep: 454.64 | bwd_inner_microstep: 454.41 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-15 01:16:41,353] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 443.32 | bwd_microstep: 540.77 | bwd_inner_microstep: 540.56 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-15 01:16:42,215] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 243.72 | bwd_microstep: 595.84 | bwd_inner_microstep: 595.78 | bwd_allreduce_microstep: 0.02 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-15 01:16:43,027] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 390.47 | bwd_microstep: 387.85 | bwd_inner_microstep: 387.79 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-15 01:16:43,942] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 334.03 | bwd_microstep: 557.59 | bwd_inner_microstep: 557.55 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.29 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-15 01:16:44,738] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 368.34 | bwd_microstep: 394.28 | bwd_inner_microstep: 394.26 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.77 +dynamic ViT batch size: 6, images per sample: 6.0, dynamic token length: 2163 +[2025-05-15 01:16:45,998] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 1.73 | optimizer_step: 15.90 +[2025-05-15 01:16:45,999] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 448.39 | bwd_microstep: 763.60 | bwd_inner_microstep: 648.38 | bwd_allreduce_microstep: 114.98 | step_microstep: 23.67 +[2025-05-15 01:16:46,000] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2942.88 | bwd: 4323.99 | bwd_inner: 4207.94 | bwd_allreduce: 115.31 | step: 30.67 + 75%|███████▌ | 421/558 [48:41<15:00, 6.57s/it] {'loss': 4.5243, 'grad_norm': 38.7221565246582, 'learning_rate': 1.5005770784764034e-16, 'epoch': 0.23} + 75%|███████▌ | 421/558 [48:41<15:00, 6.57s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1918 +[2025-05-15 01:16:46,999] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 350.34 | bwd_microstep: 622.50 | bwd_inner_microstep: 622.46 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1906 +[2025-05-15 01:16:47,794] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 357.65 | bwd_microstep: 403.60 | bwd_inner_microstep: 403.56 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.88 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1883 +[2025-05-15 01:16:48,834] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 427.77 | bwd_microstep: 585.35 | bwd_inner_microstep: 585.31 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.30 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 842 +[2025-05-15 01:16:49,158] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 170.85 | bwd_microstep: 135.27 | bwd_inner_microstep: 135.19 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.24 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 328 +[2025-05-15 01:16:49,415] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 97.37 | bwd_microstep: 133.51 | bwd_inner_microstep: 133.46 | bwd_allreduce_microstep: 0.02 | step_microstep: 2.33 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-15 01:16:50,403] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 445.37 | bwd_microstep: 513.01 | bwd_inner_microstep: 512.87 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-15 01:16:51,310] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 278.67 | bwd_microstep: 608.60 | bwd_inner_microstep: 608.57 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.46 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-15 01:16:52,272] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.07 | optimizer_step: 18.81 +[2025-05-15 01:16:52,273] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 388.15 | bwd_microstep: 513.95 | bwd_inner_microstep: 308.36 | bwd_allreduce_microstep: 205.46 | step_microstep: 28.69 +[2025-05-15 01:16:52,274] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2516.13 | bwd: 3515.83 | bwd_inner: 3309.87 | bwd_allreduce: 205.57 | step: 38.36 + 76%|███████▌ | 422/558 [48:47<14:42, 6.49s/it] {'loss': 5.0576, 'grad_norm': 17.896717071533203, 'learning_rate': 1.479897738571468e-16, 'epoch': 0.23} + 76%|███████▌ | 422/558 [48:47<14:42, 6.49s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-15 01:16:53,220] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 448.81 | bwd_microstep: 453.58 | bwd_inner_microstep: 453.24 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-15 01:16:54,205] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 344.84 | bwd_microstep: 619.03 | bwd_inner_microstep: 618.99 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.47 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 334 +[2025-05-15 01:16:54,459] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 84.93 | bwd_microstep: 139.32 | bwd_inner_microstep: 139.28 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.23 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-15 01:16:55,165] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 240.81 | bwd_microstep: 444.64 | bwd_inner_microstep: 444.44 | bwd_allreduce_microstep: 0.18 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-15 01:16:56,147] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 444.23 | bwd_microstep: 501.69 | bwd_inner_microstep: 501.54 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 839 +[2025-05-15 01:16:56,525] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 100.53 | bwd_microstep: 258.87 | bwd_inner_microstep: 258.80 | bwd_allreduce_microstep: 0.02 | step_microstep: 1.80 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-15 01:16:57,532] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 439.15 | bwd_microstep: 543.93 | bwd_inner_microstep: 543.66 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-15 01:16:58,744] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.22 | optimizer_gradients: 2.13 | optimizer_step: 18.20 +[2025-05-15 01:16:58,744] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 255.58 | bwd_microstep: 908.46 | bwd_inner_microstep: 595.85 | bwd_allreduce_microstep: 312.59 | step_microstep: 26.56 +[2025-05-15 01:16:58,745] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2358.83 | bwd: 3869.56 | bwd_inner: 3555.94 | bwd_allreduce: 312.90 | step: 31.65 + 76%|███████▌ | 423/558 [48:54<14:34, 6.48s/it] {'loss': 4.2659, 'grad_norm': 18.679738998413086, 'learning_rate': 1.4593371010050607e-16, 'epoch': 0.23} + 76%|███████▌ | 423/558 [48:54<14:34, 6.48s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1920 +[2025-05-15 01:16:59,626] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 241.86 | bwd_microstep: 609.04 | bwd_inner_microstep: 609.00 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.53 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1903 +[2025-05-15 01:17:00,439] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 349.25 | bwd_microstep: 431.26 | bwd_inner_microstep: 430.92 | bwd_allreduce_microstep: 0.15 | step_microstep: 0.22 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 879 +[2025-05-15 01:17:00,836] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 106.40 | bwd_microstep: 271.99 | bwd_inner_microstep: 271.96 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.74 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1886 +[2025-05-15 01:17:01,856] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 441.87 | bwd_microstep: 551.65 | bwd_inner_microstep: 551.62 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.85 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-15 01:17:02,696] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 218.99 | bwd_microstep: 598.32 | bwd_inner_microstep: 598.26 | bwd_allreduce_microstep: 0.02 | step_microstep: 2.37 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-15 01:17:03,525] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 372.93 | bwd_microstep: 421.73 | bwd_inner_microstep: 421.58 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-15 01:17:04,438] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 287.29 | bwd_microstep: 605.60 | bwd_inner_microstep: 605.56 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2012 +[2025-05-15 01:17:05,880] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.23 | optimizer_gradients: 2.10 | optimizer_step: 18.54 +[2025-05-15 01:17:05,881] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 398.28 | bwd_microstep: 983.42 | bwd_inner_microstep: 446.62 | bwd_allreduce_microstep: 536.76 | step_microstep: 27.12 +[2025-05-15 01:17:05,882] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2416.84 | bwd: 4473.06 | bwd_inner: 3935.61 | bwd_allreduce: 537.02 | step: 37.29 + 76%|███████▌ | 424/558 [49:01<14:54, 6.68s/it] {'loss': 3.8816, 'grad_norm': 11.075021743774414, 'learning_rate': 1.438895859108107e-16, 'epoch': 0.23} + 76%|███████▌ | 424/558 [49:01<14:54, 6.68s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1970 +[2025-05-15 01:17:06,742] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 272.78 | bwd_microstep: 560.09 | bwd_inner_microstep: 560.05 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1143 +[2025-05-15 01:17:07,386] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 277.87 | bwd_microstep: 335.75 | bwd_inner_microstep: 335.70 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.52 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1905 +[2025-05-15 01:17:08,242] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 225.57 | bwd_microstep: 608.52 | bwd_inner_microstep: 608.47 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.56 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1883 +[2025-05-15 01:17:09,001] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 360.59 | bwd_microstep: 364.19 | bwd_inner_microstep: 363.98 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-15 01:17:09,931] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 333.55 | bwd_microstep: 572.71 | bwd_inner_microstep: 572.69 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.51 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 838 +[2025-05-15 01:17:10,317] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 175.03 | bwd_microstep: 180.38 | bwd_inner_microstep: 180.12 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.10 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1355 +[2025-05-15 01:17:11,001] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 214.39 | bwd_microstep: 449.61 | bwd_inner_microstep: 449.57 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-15 01:17:12,420] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 1.98 | optimizer_step: 18.87 +[2025-05-15 01:17:12,421] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 408.03 | bwd_microstep: 950.84 | bwd_inner_microstep: 396.45 | bwd_allreduce_microstep: 554.36 | step_microstep: 27.43 +[2025-05-15 01:17:12,422] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2267.78 | bwd: 4022.10 | bwd_inner: 3467.09 | bwd_allreduce: 554.52 | step: 38.04 + 76%|███████▌ | 425/558 [49:07<14:42, 6.64s/it] {'loss': 3.8741, 'grad_norm': 16.928823471069336, 'learning_rate': 1.4185747021853603e-16, 'epoch': 0.23} + 76%|███████▌ | 425/558 [49:07<14:42, 6.64s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-15 01:17:13,267] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 215.20 | bwd_microstep: 601.24 | bwd_inner_microstep: 601.20 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.48 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-15 01:17:14,099] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 408.71 | bwd_microstep: 389.18 | bwd_inner_microstep: 389.15 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.83 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-15 01:17:15,129] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 408.52 | bwd_microstep: 598.15 | bwd_inner_microstep: 597.96 | bwd_allreduce_microstep: 0.17 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-15 01:17:15,961] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 221.96 | bwd_microstep: 587.86 | bwd_inner_microstep: 587.82 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.43 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1354 +[2025-05-15 01:17:16,643] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 325.95 | bwd_microstep: 323.34 | bwd_inner_microstep: 323.19 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-15 01:17:17,197] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 192.05 | bwd_microstep: 343.25 | bwd_inner_microstep: 343.21 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.86 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-15 01:17:18,227] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 413.15 | bwd_microstep: 584.76 | bwd_inner_microstep: 584.72 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.32 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 831 +[2025-05-15 01:17:19,115] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.01 | optimizer_gradients: 2.10 | optimizer_step: 18.35 +[2025-05-15 01:17:19,115] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.39 | bwd_microstep: 747.61 | bwd_inner_microstep: 209.84 | bwd_allreduce_microstep: 537.75 | step_microstep: 27.00 +[2025-05-15 01:17:19,116] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2278.90 | bwd: 4175.39 | bwd_inner: 3634.79 | bwd_allreduce: 538.02 | step: 38.21 + 76%|███████▋ | 426/558 [49:14<14:38, 6.65s/it] {'loss': 6.8887, 'grad_norm': 34.67142105102539, 'learning_rate': 1.3983743154921503e-16, 'epoch': 0.23} + 76%|███████▋ | 426/558 [49:14<14:38, 6.65s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 430 +[2025-05-15 01:17:19,385] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 88.66 | bwd_microstep: 154.14 | bwd_inner_microstep: 154.09 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.78 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1902 +[2025-05-15 01:17:20,417] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 415.79 | bwd_microstep: 586.86 | bwd_inner_microstep: 586.82 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.63 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-15 01:17:21,270] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 227.29 | bwd_microstep: 602.82 | bwd_inner_microstep: 602.77 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-15 01:17:22,105] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 408.68 | bwd_microstep: 391.51 | bwd_inner_microstep: 391.10 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.05 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 325 +[2025-05-15 01:17:22,361] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.02 | bwd_microstep: 136.50 | bwd_inner_microstep: 136.47 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.99 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 321 +[2025-05-15 01:17:22,650] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 112.49 | bwd_microstep: 145.14 | bwd_inner_microstep: 145.09 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-15 01:17:23,474] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 397.35 | bwd_microstep: 392.11 | bwd_inner_microstep: 391.88 | bwd_allreduce_microstep: 0.19 | step_microstep: 0.21 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1890 +[2025-05-15 01:17:24,752] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.02 | optimizer_step: 28.25 +[2025-05-15 01:17:24,753] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 398.78 | bwd_microstep: 819.01 | bwd_inner_microstep: 616.21 | bwd_allreduce_microstep: 202.60 | step_microstep: 36.54 +[2025-05-15 01:17:24,753] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2144.05 | bwd: 3228.08 | bwd_inner: 3024.45 | bwd_allreduce: 202.85 | step: 46.93 + 77%|███████▋ | 427/558 [49:20<13:51, 6.35s/it] {'loss': 4.5891, 'grad_norm': 30.06422996520996, 'learning_rate': 1.378295380211289e-16, 'epoch': 0.23} + 77%|███████▋ | 427/558 [49:20<13:51, 6.35s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1898 +[2025-05-15 01:17:25,646] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 270.64 | bwd_microstep: 596.17 | bwd_inner_microstep: 596.14 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 354 +[2025-05-15 01:17:25,938] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 118.18 | bwd_microstep: 135.78 | bwd_inner_microstep: 135.74 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-15 01:17:26,749] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 291.33 | bwd_microstep: 492.95 | bwd_inner_microstep: 492.90 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-15 01:17:27,725] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 446.57 | bwd_microstep: 497.26 | bwd_inner_microstep: 497.06 | bwd_allreduce_microstep: 0.08 | step_microstep: 0.13 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-15 01:17:28,631] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 277.78 | bwd_microstep: 600.99 | bwd_inner_microstep: 600.95 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-15 01:17:29,463] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 389.30 | bwd_microstep: 406.38 | bwd_inner_microstep: 406.33 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.83 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 841 +[2025-05-15 01:17:29,996] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 192.18 | bwd_microstep: 314.72 | bwd_inner_microstep: 314.67 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.59 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 369 +[2025-05-15 01:17:30,413] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.05 | optimizer_step: 18.07 +[2025-05-15 01:17:30,413] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 106.55 | bwd_microstep: 253.88 | bwd_inner_microstep: 155.45 | bwd_allreduce_microstep: 98.37 | step_microstep: 26.76 +[2025-05-15 01:17:30,414] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2092.48 | bwd: 3298.17 | bwd_inner: 3199.28 | bwd_allreduce: 98.53 | step: 38.57 + 77%|███████▋ | 428/558 [49:25<13:18, 6.14s/it] {'loss': 4.8559, 'grad_norm': 12.653908729553223, 'learning_rate': 1.3583385734300857e-16, 'epoch': 0.23} + 77%|███████▋ | 428/558 [49:25<13:18, 6.14s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 366 +[2025-05-15 01:17:30,667] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 88.79 | bwd_microstep: 140.80 | bwd_inner_microstep: 140.77 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.33 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-15 01:17:31,655] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 411.58 | bwd_microstep: 554.64 | bwd_inner_microstep: 554.34 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.10 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 334 +[2025-05-15 01:17:31,892] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 80.41 | bwd_microstep: 139.07 | bwd_inner_microstep: 139.01 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.78 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-15 01:17:32,917] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 409.62 | bwd_microstep: 588.31 | bwd_inner_microstep: 588.26 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.32 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1102 +[2025-05-15 01:17:33,368] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 117.25 | bwd_microstep: 311.04 | bwd_inner_microstep: 310.99 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.89 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-15 01:17:34,339] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 388.65 | bwd_microstep: 555.18 | bwd_inner_microstep: 554.84 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.19 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1094 +[2025-05-15 01:17:34,813] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 126.84 | bwd_microstep: 327.78 | bwd_inner_microstep: 327.41 | bwd_allreduce_microstep: 0.31 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-15 01:17:35,872] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.08 | optimizer_step: 18.78 +[2025-05-15 01:17:35,872] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 440.59 | bwd_microstep: 561.18 | bwd_inner_microstep: 500.83 | bwd_allreduce_microstep: 60.19 | step_microstep: 27.43 +[2025-05-15 01:17:35,873] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2063.66 | bwd: 3178.03 | bwd_inner: 3116.64 | bwd_allreduce: 60.71 | step: 36.23 + 77%|███████▋ | 429/558 [49:31<12:45, 5.94s/it] {'loss': 8.3235, 'grad_norm': 36.7755126953125, 'learning_rate': 1.3385045681175178e-16, 'epoch': 0.23} + 77%|███████▋ | 429/558 [49:31<12:45, 5.94s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1904 +[2025-05-15 01:17:36,922] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 396.29 | bwd_microstep: 623.47 | bwd_inner_microstep: 623.23 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.21 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1886 +[2025-05-15 01:17:37,730] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 285.00 | bwd_microstep: 500.98 | bwd_inner_microstep: 500.94 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-15 01:17:38,670] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 450.43 | bwd_microstep: 456.45 | bwd_inner_microstep: 456.23 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.11 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 337 +[2025-05-15 01:17:38,920] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 83.46 | bwd_microstep: 151.03 | bwd_inner_microstep: 150.99 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-15 01:17:39,921] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 407.03 | bwd_microstep: 570.09 | bwd_inner_microstep: 569.30 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.23 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 325 +[2025-05-15 01:17:40,172] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 79.78 | bwd_microstep: 150.04 | bwd_inner_microstep: 150.00 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.82 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-15 01:17:41,193] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 412.29 | bwd_microstep: 583.01 | bwd_inner_microstep: 582.78 | bwd_allreduce_microstep: 0.20 | step_microstep: 0.23 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-15 01:17:42,336] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.01 | optimizer_gradients: 2.18 | optimizer_step: 18.25 +[2025-05-15 01:17:42,337] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 210.25 | bwd_microstep: 884.78 | bwd_inner_microstep: 326.62 | bwd_allreduce_microstep: 558.13 | step_microstep: 27.54 +[2025-05-15 01:17:42,338] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2324.51 | bwd: 3919.87 | bwd_inner: 3360.16 | bwd_allreduce: 559.39 | step: 32.55 + 77%|███████▋ | 430/558 [49:37<13:00, 6.10s/it] {'loss': 3.797, 'grad_norm': 19.010658264160156, 'learning_rate': 1.3187940331015504e-16, 'epoch': 0.23} + 77%|███████▋ | 430/558 [49:37<13:00, 6.10s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1918 +[2025-05-15 01:17:43,194] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 217.05 | bwd_microstep: 611.68 | bwd_inner_microstep: 611.64 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1892 +[2025-05-15 01:17:44,039] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 405.85 | bwd_microstep: 404.55 | bwd_inner_microstep: 404.52 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.80 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-15 01:17:45,067] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 408.88 | bwd_microstep: 592.27 | bwd_inner_microstep: 592.24 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.31 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-15 01:17:45,929] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 231.94 | bwd_microstep: 604.55 | bwd_inner_microstep: 604.51 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-15 01:17:46,770] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 400.83 | bwd_microstep: 404.15 | bwd_inner_microstep: 404.09 | bwd_allreduce_microstep: 0.02 | step_microstep: 1.87 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-15 01:17:47,791] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 410.93 | bwd_microstep: 583.56 | bwd_inner_microstep: 583.53 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.31 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-15 01:17:48,647] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 233.17 | bwd_microstep: 599.83 | bwd_inner_microstep: 599.78 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-15 01:17:49,634] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 1.66 | optimizer_step: 13.15 +[2025-05-15 01:17:49,634] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 402.12 | bwd_microstep: 531.25 | bwd_inner_microstep: 399.40 | bwd_allreduce_microstep: 131.79 | step_microstep: 19.69 +[2025-05-15 01:17:49,635] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2710.72 | bwd: 4331.86 | bwd_inner: 4199.74 | bwd_allreduce: 131.88 | step: 35.06 + 77%|███████▋ | 431/558 [49:45<13:39, 6.46s/it] {'loss': 4.4632, 'grad_norm': 21.042682647705078, 'learning_rate': 1.2992076330465642e-16, 'epoch': 0.23} + 77%|███████▋ | 431/558 [49:45<13:39, 6.46s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1917 +[2025-05-15 01:17:50,564] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 289.23 | bwd_microstep: 618.13 | bwd_inner_microstep: 618.08 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.86 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1894 +[2025-05-15 01:17:51,406] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 228.13 | bwd_microstep: 590.77 | bwd_inner_microstep: 590.73 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1892 +[2025-05-15 01:17:52,254] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 416.56 | bwd_microstep: 397.46 | bwd_inner_microstep: 397.41 | bwd_allreduce_microstep: 0.02 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-15 01:17:53,283] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 394.88 | bwd_microstep: 612.11 | bwd_inner_microstep: 612.06 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-15 01:17:54,112] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 222.23 | bwd_microstep: 585.55 | bwd_inner_microstep: 585.49 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-15 01:17:54,938] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 412.93 | bwd_microstep: 378.97 | bwd_inner_microstep: 378.93 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.78 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 833 +[2025-05-15 01:17:55,435] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 198.35 | bwd_microstep: 273.30 | bwd_inner_microstep: 273.25 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.28 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-15 01:17:56,861] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.22 | optimizer_gradients: 2.18 | optimizer_step: 18.68 +[2025-05-15 01:17:56,861] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 415.76 | bwd_microstep: 949.64 | bwd_inner_microstep: 377.87 | bwd_allreduce_microstep: 571.75 | step_microstep: 27.79 +[2025-05-15 01:17:56,862] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2578.04 | bwd: 4405.93 | bwd_inner: 3833.82 | bwd_allreduce: 571.83 | step: 40.97 + 77%|███████▋ | 432/558 [49:52<14:02, 6.69s/it] {'loss': 4.5297, 'grad_norm': 19.89423370361328, 'learning_rate': 1.2797460284309533e-16, 'epoch': 0.23} + 77%|███████▋ | 432/558 [49:52<14:02, 6.69s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1891 +[2025-05-15 01:17:57,710] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 219.06 | bwd_microstep: 600.51 | bwd_inner_microstep: 600.49 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-15 01:17:58,547] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 405.11 | bwd_microstep: 398.04 | bwd_inner_microstep: 398.01 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.89 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-15 01:17:59,569] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 413.86 | bwd_microstep: 581.70 | bwd_inner_microstep: 581.66 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.24 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 340 +[2025-05-15 01:17:59,805] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 81.64 | bwd_microstep: 136.73 | bwd_inner_microstep: 136.67 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.31 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-15 01:18:00,822] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 397.56 | bwd_microstep: 596.33 | bwd_inner_microstep: 596.14 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.17 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-15 01:18:01,552] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 211.57 | bwd_microstep: 497.62 | bwd_inner_microstep: 497.58 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-15 01:18:02,448] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 444.45 | bwd_microstep: 419.02 | bwd_inner_microstep: 418.88 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-15 01:18:03,681] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.06 | optimizer_step: 17.65 +[2025-05-15 01:18:03,682] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 368.50 | bwd_microstep: 820.52 | bwd_inner_microstep: 628.36 | bwd_allreduce_microstep: 191.89 | step_microstep: 26.26 +[2025-05-15 01:18:03,682] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2541.58 | bwd: 4050.49 | bwd_inner: 3857.82 | bwd_allreduce: 192.01 | step: 33.68 + 78%|███████▊ | 433/558 [49:59<14:00, 6.73s/it] {'loss': 4.1529, 'grad_norm': 22.514080047607422, 'learning_rate': 1.260409875524854e-16, 'epoch': 0.23} + 78%|███████▊ | 433/558 [49:59<14:00, 6.73s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1894 +[2025-05-15 01:18:04,664] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 331.71 | bwd_microstep: 622.96 | bwd_inner_microstep: 622.91 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1390 +[2025-05-15 01:18:05,238] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 263.67 | bwd_microstep: 277.29 | bwd_inner_microstep: 277.25 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.80 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1889 +[2025-05-15 01:18:06,271] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 416.78 | bwd_microstep: 588.39 | bwd_inner_microstep: 588.36 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.31 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1888 +[2025-05-15 01:18:06,792] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.84 | bwd_microstep: 308.31 | bwd_inner_microstep: 308.29 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.78 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 848 +[2025-05-15 01:18:07,311] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 207.19 | bwd_microstep: 287.42 | bwd_inner_microstep: 287.38 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 842 +[2025-05-15 01:18:07,820] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 222.72 | bwd_microstep: 255.18 | bwd_inner_microstep: 254.91 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.24 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-15 01:18:08,643] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 219.42 | bwd_microstep: 580.95 | bwd_inner_microstep: 580.89 | bwd_allreduce_microstep: 0.02 | step_microstep: 2.56 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1894 +[2025-05-15 01:18:09,529] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 1.74 | optimizer_step: 16.90 +[2025-05-15 01:18:09,530] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 415.43 | bwd_microstep: 415.30 | bwd_inner_microstep: 349.53 | bwd_allreduce_microstep: 65.62 | step_microstep: 23.63 +[2025-05-15 01:18:09,530] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2266.73 | bwd: 3335.80 | bwd_inner: 3269.58 | bwd_allreduce: 65.67 | step: 37.03 + 78%|███████▊ | 434/558 [50:05<13:21, 6.46s/it] {'loss': 3.4195, 'grad_norm': 6.157909870147705, 'learning_rate': 1.241199826368003e-16, 'epoch': 0.23} + 78%|███████▊ | 434/558 [50:05<13:21, 6.46s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1979 +[2025-05-15 01:18:10,615] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 384.33 | bwd_microstep: 671.60 | bwd_inner_microstep: 671.55 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.28 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1902 +[2025-05-15 01:18:11,430] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 252.55 | bwd_microstep: 538.67 | bwd_inner_microstep: 538.62 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1888 +[2025-05-15 01:18:12,293] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 429.38 | bwd_microstep: 399.53 | bwd_inner_microstep: 399.11 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.20 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 337 +[2025-05-15 01:18:12,561] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 96.86 | bwd_microstep: 146.92 | bwd_inner_microstep: 146.87 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-15 01:18:13,489] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 447.63 | bwd_microstep: 445.89 | bwd_inner_microstep: 445.72 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-15 01:18:14,492] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 358.86 | bwd_microstep: 623.46 | bwd_inner_microstep: 623.42 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-15 01:18:15,103] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 293.71 | bwd_microstep: 293.86 | bwd_inner_microstep: 293.82 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.80 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-15 01:18:16,306] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.06 | optimizer_step: 18.18 +[2025-05-15 01:18:16,307] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 397.22 | bwd_microstep: 754.10 | bwd_inner_microstep: 610.70 | bwd_allreduce_microstep: 143.34 | step_microstep: 26.84 +[2025-05-15 01:18:16,308] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2660.52 | bwd: 3874.07 | bwd_inner: 3729.85 | bwd_allreduce: 142.54 | step: 38.26 + 78%|███████▊ | 435/558 [50:11<13:26, 6.56s/it] {'loss': 2.2161, 'grad_norm': 6.8933424949646, 'learning_rate': 1.222116528747766e-16, 'epoch': 0.23} + 78%|███████▊ | 435/558 [50:11<13:26, 6.56s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1915 +[2025-05-15 01:18:17,308] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 347.83 | bwd_microstep: 627.45 | bwd_inner_microstep: 627.41 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 2, images per sample: 2.0, dynamic token length: 592 +[2025-05-15 01:18:17,607] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 131.81 | bwd_microstep: 137.76 | bwd_inner_microstep: 137.43 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.21 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-15 01:18:18,552] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 310.44 | bwd_microstep: 615.47 | bwd_inner_microstep: 615.43 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-15 01:18:19,378] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 344.71 | bwd_microstep: 445.15 | bwd_inner_microstep: 445.11 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.02 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 839 +[2025-05-15 01:18:19,921] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 215.61 | bwd_microstep: 299.77 | bwd_inner_microstep: 299.72 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.56 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-15 01:18:20,727] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 298.19 | bwd_microstep: 473.49 | bwd_inner_microstep: 473.45 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-15 01:18:21,676] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 440.87 | bwd_microstep: 475.87 | bwd_inner_microstep: 475.58 | bwd_allreduce_microstep: 0.14 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1905 +[2025-05-15 01:18:22,891] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 1.68 | optimizer_step: 13.24 +[2025-05-15 01:18:22,892] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 312.32 | bwd_microstep: 865.23 | bwd_inner_microstep: 622.67 | bwd_allreduce_microstep: 242.50 | step_microstep: 20.06 +[2025-05-15 01:18:22,893] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2401.71 | bwd: 3940.25 | bwd_inner: 3696.93 | bwd_allreduce: 242.81 | step: 32.03 + 78%|███████▊ | 436/558 [50:18<13:20, 6.57s/it] {'loss': 5.0508, 'grad_norm': 18.397905349731445, 'learning_rate': 1.2031606261772804e-16, 'epoch': 0.23} + 78%|███████▊ | 436/558 [50:18<13:20, 6.57s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 4087 +[2025-05-15 01:18:24,548] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 504.77 | bwd_microstep: 1130.61 | bwd_inner_microstep: 1130.29 | bwd_allreduce_microstep: 0.14 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1904 +[2025-05-15 01:18:25,597] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 399.39 | bwd_microstep: 628.90 | bwd_inner_microstep: 628.54 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1900 +[2025-05-15 01:18:26,385] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 280.12 | bwd_microstep: 487.66 | bwd_inner_microstep: 487.61 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-15 01:18:27,278] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 442.10 | bwd_microstep: 416.91 | bwd_inner_microstep: 416.71 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.09 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 860 +[2025-05-15 01:18:27,790] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 210.96 | bwd_microstep: 280.28 | bwd_inner_microstep: 280.22 | bwd_allreduce_microstep: 0.02 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-15 01:18:28,654] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 427.94 | bwd_microstep: 404.17 | bwd_inner_microstep: 404.07 | bwd_allreduce_microstep: 0.04 | step_microstep: 0.22 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-15 01:18:29,684] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 389.02 | bwd_microstep: 618.00 | bwd_inner_microstep: 617.79 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.20 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 833 +[2025-05-15 01:18:30,621] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.01 | optimizer_gradients: 2.13 | optimizer_step: 19.77 +[2025-05-15 01:18:30,622] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 165.16 | bwd_microstep: 726.85 | bwd_inner_microstep: 155.23 | bwd_allreduce_microstep: 571.48 | step_microstep: 28.65 +[2025-05-15 01:18:30,623] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2819.46 | bwd: 4693.42 | bwd_inner: 4120.61 | bwd_allreduce: 571.88 | step: 34.15 + 78%|███████▊ | 437/558 [50:26<13:56, 6.92s/it] {'loss': 3.4883, 'grad_norm': 15.775420188903809, 'learning_rate': 1.1843327578737613e-16, 'epoch': 0.24} + 78%|███████▊ | 437/558 [50:26<13:56, 6.92s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1915 +[2025-05-15 01:18:31,350] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 246.45 | bwd_microstep: 454.92 | bwd_inner_microstep: 454.67 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1927 +[2025-05-15 01:18:32,343] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 459.31 | bwd_microstep: 502.78 | bwd_inner_microstep: 502.64 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 387 +[2025-05-15 01:18:32,640] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.60 | bwd_microstep: 185.80 | bwd_inner_microstep: 185.74 | bwd_allreduce_microstep: 0.02 | step_microstep: 1.82 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 844 +[2025-05-15 01:18:33,199] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 219.84 | bwd_microstep: 313.66 | bwd_inner_microstep: 313.62 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1359 +[2025-05-15 01:18:33,757] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 260.73 | bwd_microstep: 263.87 | bwd_inner_microstep: 263.84 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.81 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 327 +[2025-05-15 01:18:33,991] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.49 | bwd_microstep: 114.70 | bwd_inner_microstep: 114.57 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2037 +[2025-05-15 01:18:34,969] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 465.70 | bwd_microstep: 482.37 | bwd_inner_microstep: 482.23 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.09 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 854 +[2025-05-15 01:18:35,909] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.08 | optimizer_step: 27.90 +[2025-05-15 01:18:35,910] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 172.88 | bwd_microstep: 714.93 | bwd_inner_microstep: 274.86 | bwd_allreduce_microstep: 440.03 | step_microstep: 36.97 +[2025-05-15 01:18:35,910] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2013.98 | bwd: 3033.26 | bwd_inner: 2592.23 | bwd_allreduce: 440.24 | step: 43.54 + 78%|███████▊ | 438/558 [50:31<12:51, 6.43s/it] {'loss': 4.6277, 'grad_norm': 13.20885181427002, 'learning_rate': 1.1656335587369444e-16, 'epoch': 0.24} + 78%|███████▊ | 438/558 [50:31<12:51, 6.43s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 369 +[2025-05-15 01:18:36,156] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 77.61 | bwd_microstep: 146.93 | bwd_inner_microstep: 146.89 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1895 +[2025-05-15 01:18:37,193] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 417.29 | bwd_microstep: 596.31 | bwd_inner_microstep: 596.27 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1898 +[2025-05-15 01:18:38,039] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 224.62 | bwd_microstep: 599.88 | bwd_inner_microstep: 599.83 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1358 +[2025-05-15 01:18:38,739] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 314.78 | bwd_microstep: 353.87 | bwd_inner_microstep: 353.72 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.09 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1100 +[2025-05-15 01:18:39,211] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 130.60 | bwd_microstep: 324.63 | bwd_inner_microstep: 324.49 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1352 +[2025-05-15 01:18:39,878] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 168.32 | bwd_microstep: 482.34 | bwd_inner_microstep: 482.31 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 332 +[2025-05-15 01:18:40,147] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 91.26 | bwd_microstep: 144.66 | bwd_inner_microstep: 144.52 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1352 +[2025-05-15 01:18:41,217] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.11 | optimizer_step: 25.13 +[2025-05-15 01:18:41,218] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 156.12 | bwd_microstep: 863.44 | bwd_inner_microstep: 433.40 | bwd_allreduce_microstep: 430.01 | step_microstep: 34.03 +[2025-05-15 01:18:41,218] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 1580.55 | bwd: 3512.24 | bwd_inner: 3081.48 | bwd_allreduce: 430.21 | step: 39.25 + 79%|███████▊ | 439/558 [50:36<12:04, 6.09s/it] {'loss': 5.0207, 'grad_norm': 12.326010704040527, 'learning_rate': 1.147063659327678e-16, 'epoch': 0.24} + 79%|███████▊ | 439/558 [50:36<12:04, 6.09s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 484 +[2025-05-15 01:18:41,494] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 87.55 | bwd_microstep: 164.46 | bwd_inner_microstep: 162.10 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.82 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1918 +[2025-05-15 01:18:42,511] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 406.24 | bwd_microstep: 588.17 | bwd_inner_microstep: 588.01 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1904 +[2025-05-15 01:18:43,391] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 240.28 | bwd_microstep: 616.80 | bwd_inner_microstep: 616.75 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1366 +[2025-05-15 01:18:44,005] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 298.31 | bwd_microstep: 283.38 | bwd_inner_microstep: 283.08 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-15 01:18:45,046] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 393.75 | bwd_microstep: 624.85 | bwd_inner_microstep: 624.65 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-15 01:18:45,854] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 247.29 | bwd_microstep: 539.20 | bwd_inner_microstep: 539.16 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.32 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-15 01:18:46,710] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 425.69 | bwd_microstep: 397.92 | bwd_inner_microstep: 397.88 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-15 01:18:47,924] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.10 | optimizer_step: 17.91 +[2025-05-15 01:18:47,924] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 393.81 | bwd_microstep: 772.29 | bwd_inner_microstep: 615.09 | bwd_allreduce_microstep: 157.13 | step_microstep: 26.38 +[2025-05-15 01:18:47,925] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2492.88 | bwd: 3987.07 | bwd_inner: 3829.11 | bwd_allreduce: 157.47 | step: 33.51 + 79%|███████▉ | 440/558 [50:43<12:20, 6.28s/it] {'loss': 4.827, 'grad_norm': 15.344511032104492, 'learning_rate': 1.128623685846656e-16, 'epoch': 0.24} + 79%|███████▉ | 440/558 [50:43<12:20, 6.28s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1923 +[2025-05-15 01:18:48,925] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 346.80 | bwd_microstep: 627.14 | bwd_inner_microstep: 627.10 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1900 +[2025-05-15 01:18:49,723] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 304.57 | bwd_microstep: 458.74 | bwd_inner_microstep: 456.36 | bwd_allreduce_microstep: 2.35 | step_microstep: 2.53 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1908 +[2025-05-15 01:18:50,700] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 442.84 | bwd_microstep: 501.76 | bwd_inner_microstep: 501.63 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1889 +[2025-05-15 01:18:51,633] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 306.91 | bwd_microstep: 607.32 | bwd_inner_microstep: 607.30 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 334 +[2025-05-15 01:18:51,880] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 91.26 | bwd_microstep: 124.26 | bwd_inner_microstep: 124.24 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.43 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-15 01:18:52,724] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 222.89 | bwd_microstep: 600.49 | bwd_inner_microstep: 600.43 | bwd_allreduce_microstep: 0.02 | step_microstep: 2.45 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-15 01:18:53,562] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 407.21 | bwd_microstep: 396.31 | bwd_inner_microstep: 396.26 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.81 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-15 01:18:54,766] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.13 | optimizer_step: 19.14 +[2025-05-15 01:18:54,767] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 400.51 | bwd_microstep: 752.63 | bwd_inner_microstep: 599.28 | bwd_allreduce_microstep: 153.29 | step_microstep: 27.90 +[2025-05-15 01:18:54,768] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2522.94 | bwd: 4068.67 | bwd_inner: 3912.63 | bwd_allreduce: 155.75 | step: 41.92 + 79%|███████▉ | 441/558 [50:50<12:34, 6.45s/it] {'loss': 4.5977, 'grad_norm': 22.358482360839844, 'learning_rate': 1.1103142601133099e-16, 'epoch': 0.24} + 79%|███████▉ | 441/558 [50:50<12:34, 6.45s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-15 01:18:55,754] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 346.98 | bwd_microstep: 613.24 | bwd_inner_microstep: 613.18 | bwd_allreduce_microstep: 0.02 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-15 01:18:56,559] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 344.78 | bwd_microstep: 426.51 | bwd_inner_microstep: 426.46 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.85 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-15 01:18:57,566] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 445.97 | bwd_microstep: 534.89 | bwd_inner_microstep: 534.76 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1102 +[2025-05-15 01:18:58,035] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 122.53 | bwd_microstep: 330.41 | bwd_inner_microstep: 330.09 | bwd_allreduce_microstep: 0.24 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-15 01:18:59,026] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 447.63 | bwd_microstep: 515.17 | bwd_inner_microstep: 515.03 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-15 01:18:59,959] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 297.07 | bwd_microstep: 616.56 | bwd_inner_microstep: 616.48 | bwd_allreduce_microstep: 0.02 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-15 01:19:00,781] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 369.00 | bwd_microstep: 420.85 | bwd_inner_microstep: 420.81 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.84 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-15 01:19:01,835] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.01 | optimizer_gradients: 2.09 | optimizer_step: 18.16 +[2025-05-15 01:19:01,835] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 440.91 | bwd_microstep: 559.89 | bwd_inner_microstep: 499.76 | bwd_allreduce_microstep: 59.97 | step_microstep: 26.72 +[2025-05-15 01:19:01,836] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2814.82 | bwd: 4017.56 | bwd_inner: 3956.69 | bwd_allreduce: 60.35 | step: 35.48 + 79%|███████▉ | 442/558 [50:57<12:49, 6.63s/it] {'loss': 5.4732, 'grad_norm': 25.710023880004883, 'learning_rate': 1.092135999544831e-16, 'epoch': 0.24} + 79%|███████▉ | 442/558 [50:57<12:49, 6.63s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-15 01:19:02,875] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 404.14 | bwd_microstep: 603.66 | bwd_inner_microstep: 602.69 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.22 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-15 01:19:03,686] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 245.49 | bwd_microstep: 542.23 | bwd_inner_microstep: 542.18 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-15 01:19:04,541] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 429.74 | bwd_microstep: 388.71 | bwd_inner_microstep: 388.43 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.09 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 330 +[2025-05-15 01:19:04,803] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.85 | bwd_microstep: 140.58 | bwd_inner_microstep: 140.54 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.32 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 324 +[2025-05-15 01:19:05,082] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 103.43 | bwd_microstep: 143.00 | bwd_inner_microstep: 142.96 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-15 01:19:05,915] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 392.08 | bwd_microstep: 407.27 | bwd_inner_microstep: 407.25 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.93 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1913 +[2025-05-15 01:19:06,920] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 406.05 | bwd_microstep: 573.54 | bwd_inner_microstep: 573.41 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.09 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 883 +[2025-05-15 01:19:07,833] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 1.63 | optimizer_step: 21.06 +[2025-05-15 01:19:07,833] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 97.51 | bwd_microstep: 772.96 | bwd_inner_microstep: 247.10 | bwd_allreduce_microstep: 525.82 | step_microstep: 28.25 +[2025-05-15 01:19:07,834] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2174.28 | bwd: 3571.94 | bwd_inner: 3044.57 | bwd_allreduce: 525.94 | step: 38.64 + 79%|███████▉ | 443/558 [51:03<12:20, 6.44s/it] {'loss': 4.6865, 'grad_norm': 24.749282836914062, 'learning_rate': 1.0740895171353493e-16, 'epoch': 0.24} + 79%|███████▉ | 443/558 [51:03<12:20, 6.44s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 405 +[2025-05-15 01:19:08,076] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 75.23 | bwd_microstep: 146.52 | bwd_inner_microstep: 146.48 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.77 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1901 +[2025-05-15 01:19:09,094] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 413.36 | bwd_microstep: 580.33 | bwd_inner_microstep: 580.31 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-15 01:19:09,952] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 244.48 | bwd_microstep: 592.82 | bwd_inner_microstep: 592.80 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-15 01:19:10,783] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 382.89 | bwd_microstep: 415.21 | bwd_inner_microstep: 415.19 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.92 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 344 +[2025-05-15 01:19:11,046] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 91.78 | bwd_microstep: 143.91 | bwd_inner_microstep: 143.89 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.51 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1886 +[2025-05-15 01:19:11,905] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 419.91 | bwd_microstep: 406.43 | bwd_inner_microstep: 406.42 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.18 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 333 +[2025-05-15 01:19:12,148] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 92.55 | bwd_microstep: 130.07 | bwd_inner_microstep: 130.04 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.78 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 843 +[2025-05-15 01:19:12,934] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 1.66 | optimizer_step: 12.87 +[2025-05-15 01:19:12,935] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 219.52 | bwd_microstep: 527.04 | bwd_inner_microstep: 311.48 | bwd_allreduce_microstep: 215.51 | step_microstep: 19.58 +[2025-05-15 01:19:12,936] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 1939.69 | bwd: 2942.33 | bwd_inner: 2726.62 | bwd_allreduce: 215.56 | step: 30.27 + 80%|███████▉ | 444/558 [51:08<11:28, 6.04s/it] {'loss': 4.9243, 'grad_norm': 30.245542526245117, 'learning_rate': 1.0561754214352765e-16, 'epoch': 0.24} + 80%|███████▉ | 444/558 [51:08<11:28, 6.04s/it]dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1400 +[2025-05-15 01:19:13,631] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 225.21 | bwd_microstep: 448.72 | bwd_inner_microstep: 448.70 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.51 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1122 +[2025-05-15 01:19:14,215] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 267.59 | bwd_microstep: 286.05 | bwd_inner_microstep: 285.91 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-15 01:19:15,095] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 269.35 | bwd_microstep: 593.04 | bwd_inner_microstep: 593.02 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 856 +[2025-05-15 01:19:15,558] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 207.47 | bwd_microstep: 225.41 | bwd_inner_microstep: 225.10 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.11 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 844 +[2025-05-15 01:19:15,931] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 98.84 | bwd_microstep: 258.73 | bwd_inner_microstep: 258.71 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.75 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-15 01:19:16,890] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 405.02 | bwd_microstep: 528.02 | bwd_inner_microstep: 527.89 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-15 01:19:17,786] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 285.87 | bwd_microstep: 593.07 | bwd_inner_microstep: 593.05 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.49 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-15 01:19:19,138] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 1.64 | optimizer_step: 13.35 +[2025-05-15 01:19:19,138] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 374.18 | bwd_microstep: 925.42 | bwd_inner_microstep: 418.23 | bwd_allreduce_microstep: 507.18 | step_microstep: 20.31 +[2025-05-15 01:19:19,139] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2133.48 | bwd: 3858.51 | bwd_inner: 3350.73 | bwd_allreduce: 507.43 | step: 29.72 + 80%|███████▉ | 445/558 [51:14<11:28, 6.09s/it] {'loss': 6.4626, 'grad_norm': 25.58173942565918, 'learning_rate': 1.0383943165307697e-16, 'epoch': 0.24} + 80%|███████▉ | 445/558 [51:14<11:28, 6.09s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 349 +[2025-05-15 01:19:19,350] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 67.27 | bwd_microstep: 123.51 | bwd_inner_microstep: 123.49 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.28 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-15 01:19:20,365] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 398.10 | bwd_microstep: 594.31 | bwd_inner_microstep: 594.29 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.17 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 855 +[2025-05-15 01:19:20,689] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 117.97 | bwd_microstep: 188.89 | bwd_inner_microstep: 188.87 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.89 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-15 01:19:21,692] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 397.29 | bwd_microstep: 579.76 | bwd_inner_microstep: 579.73 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.24 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-15 01:19:22,517] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 221.08 | bwd_microstep: 583.27 | bwd_inner_microstep: 583.25 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 331 +[2025-05-15 01:19:22,787] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 99.71 | bwd_microstep: 138.32 | bwd_inner_microstep: 138.30 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.32 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-15 01:19:23,586] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 326.91 | bwd_microstep: 445.16 | bwd_inner_microstep: 444.97 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-15 01:19:24,684] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 1.64 | optimizer_step: 12.87 +[2025-05-15 01:19:24,684] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 436.49 | bwd_microstep: 615.52 | bwd_inner_microstep: 539.99 | bwd_allreduce_microstep: 75.48 | step_microstep: 19.49 +[2025-05-15 01:19:24,685] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2064.79 | bwd: 3268.75 | bwd_inner: 3192.90 | bwd_allreduce: 75.53 | step: 26.91 + 80%|███████▉ | 446/558 [51:20<11:03, 5.93s/it] {'loss': 4.3494, 'grad_norm': 26.329648971557617, 'learning_rate': 1.0207468020233663e-16, 'epoch': 0.24} + 80%|███████▉ | 446/558 [51:20<11:03, 5.93s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1937 +[2025-05-15 01:19:25,720] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 367.91 | bwd_microstep: 647.21 | bwd_inner_microstep: 647.00 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-15 01:19:26,515] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 356.24 | bwd_microstep: 419.07 | bwd_inner_microstep: 419.05 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.92 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 338 +[2025-05-15 01:19:26,784] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 100.32 | bwd_microstep: 142.10 | bwd_inner_microstep: 142.08 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.52 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-15 01:19:27,628] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 401.79 | bwd_microstep: 411.41 | bwd_inner_microstep: 411.28 | bwd_allreduce_microstep: 0.04 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-15 01:19:28,656] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 385.63 | bwd_microstep: 622.46 | bwd_inner_microstep: 622.44 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.98 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 322 +[2025-05-15 01:19:28,876] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 90.86 | bwd_microstep: 113.35 | bwd_inner_microstep: 113.33 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.75 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-15 01:19:29,702] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 223.37 | bwd_microstep: 582.20 | bwd_inner_microstep: 582.18 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 324 +[2025-05-15 01:19:30,217] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 1.63 | optimizer_step: 14.01 +[2025-05-15 01:19:30,217] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 100.11 | bwd_microstep: 363.91 | bwd_inner_microstep: 137.38 | bwd_allreduce_microstep: 226.51 | step_microstep: 20.94 +[2025-05-15 01:19:30,218] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2026.21 | bwd: 3301.73 | bwd_inner: 3074.78 | bwd_allreduce: 226.79 | step: 30.77 + 80%|████████ | 447/558 [51:25<10:44, 5.81s/it] {'loss': 5.6095, 'grad_norm': 28.28999900817871, 'learning_rate': 1.0032334730097715e-16, 'epoch': 0.24} + 80%|████████ | 447/558 [51:25<10:44, 5.81s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 395 +[2025-05-15 01:19:30,448] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 71.53 | bwd_microstep: 138.99 | bwd_inner_microstep: 138.98 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.76 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-15 01:19:31,457] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 406.42 | bwd_microstep: 576.88 | bwd_inner_microstep: 576.86 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.80 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-15 01:19:32,251] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 257.82 | bwd_microstep: 515.73 | bwd_inner_microstep: 515.71 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.49 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-15 01:19:33,113] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 436.69 | bwd_microstep: 392.67 | bwd_inner_microstep: 392.65 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.07 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-15 01:19:34,132] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 389.88 | bwd_microstep: 607.05 | bwd_inner_microstep: 606.86 | bwd_allreduce_microstep: 0.18 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-15 01:19:34,932] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 246.32 | bwd_microstep: 534.34 | bwd_inner_microstep: 534.32 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 934 +[2025-05-15 01:19:35,507] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 240.72 | bwd_microstep: 305.17 | bwd_inner_microstep: 305.15 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.42 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1908 +[2025-05-15 01:19:36,783] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 1.64 | optimizer_step: 14.22 +[2025-05-15 01:19:36,783] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 281.54 | bwd_microstep: 956.80 | bwd_inner_microstep: 502.39 | bwd_allreduce_microstep: 454.39 | step_microstep: 20.47 +[2025-05-15 01:19:36,784] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2330.90 | bwd: 4027.63 | bwd_inner: 3572.93 | bwd_allreduce: 454.60 | step: 30.48 + 80%|████████ | 448/558 [51:32<11:03, 6.04s/it] {'loss': 3.4473, 'grad_norm': 16.573957443237305, 'learning_rate': 9.858549200617734e-17, 'epoch': 0.24} + 80%|████████ | 448/558 [51:32<11:03, 6.04s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1887 +[2025-05-15 01:19:37,620] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 223.85 | bwd_microstep: 588.15 | bwd_inner_microstep: 588.13 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.28 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-15 01:19:38,463] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 398.02 | bwd_microstep: 412.52 | bwd_inner_microstep: 412.51 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-15 01:19:39,488] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 389.78 | bwd_microstep: 613.41 | bwd_inner_microstep: 613.22 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-15 01:19:40,271] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 316.17 | bwd_microstep: 446.84 | bwd_inner_microstep: 446.65 | bwd_allreduce_microstep: 0.18 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-15 01:19:41,230] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 435.78 | bwd_microstep: 490.76 | bwd_inner_microstep: 490.62 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-15 01:19:42,130] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 286.44 | bwd_microstep: 596.49 | bwd_inner_microstep: 596.47 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.52 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1780 +[2025-05-15 01:19:42,874] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 333.16 | bwd_microstep: 379.38 | bwd_inner_microstep: 379.36 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.92 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1927 +[2025-05-15 01:19:44,057] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 1.67 | optimizer_step: 12.86 +[2025-05-15 01:19:44,057] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 423.59 | bwd_microstep: 713.49 | bwd_inner_microstep: 603.78 | bwd_allreduce_microstep: 109.67 | step_microstep: 19.48 +[2025-05-15 01:19:44,058] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2806.77 | bwd: 4241.08 | bwd_inner: 4130.77 | bwd_allreduce: 110.12 | step: 29.02 + 80%|████████ | 449/558 [51:39<11:38, 6.41s/it] {'loss': 4.7335, 'grad_norm': 20.051816940307617, 'learning_rate': 9.686117292063502e-17, 'epoch': 0.24} + 80%|████████ | 449/558 [51:39<11:38, 6.41s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1897 +[2025-05-15 01:19:45,036] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 345.92 | bwd_microstep: 610.12 | bwd_inner_microstep: 610.10 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.48 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1364 +[2025-05-15 01:19:45,602] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 265.90 | bwd_microstep: 268.22 | bwd_inner_microstep: 268.20 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.87 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1888 +[2025-05-15 01:19:46,627] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 398.35 | bwd_microstep: 598.74 | bwd_inner_microstep: 598.39 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.18 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 846 +[2025-05-15 01:19:46,936] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 149.58 | bwd_microstep: 141.90 | bwd_inner_microstep: 141.88 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-15 01:19:47,951] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 386.89 | bwd_microstep: 603.14 | bwd_inner_microstep: 602.95 | bwd_allreduce_microstep: 0.18 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-15 01:19:48,725] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 349.81 | bwd_microstep: 405.53 | bwd_inner_microstep: 405.52 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.93 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-15 01:19:49,730] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 401.72 | bwd_microstep: 575.71 | bwd_inner_microstep: 575.52 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-15 01:19:51,025] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 1.65 | optimizer_step: 13.11 +[2025-05-15 01:19:51,026] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 316.13 | bwd_microstep: 941.79 | bwd_inner_microstep: 445.47 | bwd_allreduce_microstep: 496.13 | step_microstep: 20.97 +[2025-05-15 01:19:51,027] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2614.28 | bwd: 4145.15 | bwd_inner: 3648.03 | bwd_allreduce: 496.50 | step: 27.82 + 81%|████████ | 450/558 [51:46<11:50, 6.58s/it] {'loss': 5.532, 'grad_norm': 17.45709228515625, 'learning_rate': 9.515044819058922e-17, 'epoch': 0.24} + 81%|████████ | 450/558 [51:46<11:50, 6.58s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1897 +[2025-05-15 01:19:51,833] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 283.43 | bwd_microstep: 497.23 | bwd_inner_microstep: 497.21 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 849 +[2025-05-15 01:19:52,377] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 223.41 | bwd_microstep: 290.01 | bwd_inner_microstep: 289.99 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.54 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-15 01:19:53,125] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 334.05 | bwd_microstep: 393.76 | bwd_inner_microstep: 393.75 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.77 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-15 01:19:54,134] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 395.53 | bwd_microstep: 588.29 | bwd_inner_microstep: 588.10 | bwd_allreduce_microstep: 0.18 | step_microstep: 0.17 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-15 01:19:54,921] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 351.77 | bwd_microstep: 415.71 | bwd_inner_microstep: 415.69 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.93 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1353 +[2025-05-15 01:19:55,690] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 301.76 | bwd_microstep: 444.30 | bwd_inner_microstep: 444.04 | bwd_allreduce_microstep: 0.24 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1969 +[2025-05-15 01:19:56,552] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 256.23 | bwd_microstep: 585.63 | bwd_inner_microstep: 585.61 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1904 +[2025-05-15 01:19:57,994] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 1.59 | optimizer_step: 13.87 +[2025-05-15 01:19:57,995] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 420.43 | bwd_microstep: 969.48 | bwd_inner_microstep: 392.30 | bwd_allreduce_microstep: 577.17 | step_microstep: 21.05 +[2025-05-15 01:19:57,996] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2566.60 | bwd: 4184.42 | bwd_inner: 3606.70 | bwd_allreduce: 577.62 | step: 31.36 + 81%|████████ | 451/558 [51:53<11:56, 6.69s/it] {'loss': 5.3279, 'grad_norm': 23.627676010131836, 'learning_rate': 9.345337550385986e-17, 'epoch': 0.24} + 81%|████████ | 451/558 [51:53<11:56, 6.69s/it]dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1155 +[2025-05-15 01:19:58,474] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 125.57 | bwd_microstep: 331.40 | bwd_inner_microstep: 331.11 | bwd_allreduce_microstep: 0.25 | step_microstep: 0.18 +dynamic ViT batch size: 6, images per sample: 6.0, dynamic token length: 1622 +[2025-05-15 01:19:59,350] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 379.80 | bwd_microstep: 467.68 | bwd_inner_microstep: 467.43 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.09 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1095 +[2025-05-15 01:19:59,816] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 126.00 | bwd_microstep: 322.05 | bwd_inner_microstep: 321.82 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-15 01:20:00,739] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 435.11 | bwd_microstep: 455.80 | bwd_inner_microstep: 455.50 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-15 01:20:01,703] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 347.92 | bwd_microstep: 597.90 | bwd_inner_microstep: 597.88 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.52 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-15 01:20:02,494] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 339.09 | bwd_microstep: 417.56 | bwd_inner_microstep: 417.55 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.91 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-15 01:20:03,474] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 431.16 | bwd_microstep: 522.39 | bwd_inner_microstep: 522.09 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.11 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 319 +[2025-05-15 01:20:04,275] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 1.67 | optimizer_step: 18.39 +[2025-05-15 01:20:04,275] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 71.18 | bwd_microstep: 690.01 | bwd_inner_microstep: 144.22 | bwd_allreduce_microstep: 545.78 | step_microstep: 26.77 +[2025-05-15 01:20:04,276] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2255.76 | bwd: 3804.83 | bwd_inner: 3257.80 | bwd_allreduce: 546.33 | step: 34.04 + 81%|████████ | 452/558 [51:59<11:36, 6.57s/it] {'loss': 6.5503, 'grad_norm': 37.273681640625, 'learning_rate': 9.177001208790309e-17, 'epoch': 0.24} + 81%|████████ | 452/558 [51:59<11:36, 6.57s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1888 +[2025-05-15 01:20:05,127] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 233.44 | bwd_microstep: 592.73 | bwd_inner_microstep: 592.71 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1380 +[2025-05-15 01:20:05,794] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 311.92 | bwd_microstep: 323.94 | bwd_inner_microstep: 323.81 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-15 01:20:06,757] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 345.18 | bwd_microstep: 600.66 | bwd_inner_microstep: 600.64 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.53 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-15 01:20:07,551] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 341.44 | bwd_microstep: 418.88 | bwd_inner_microstep: 418.86 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.89 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-15 01:20:08,533] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 430.39 | bwd_microstep: 527.03 | bwd_inner_microstep: 526.88 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.10 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1345 +[2025-05-15 01:20:09,138] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 154.80 | bwd_microstep: 429.29 | bwd_inner_microstep: 429.27 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.51 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1914 +[2025-05-15 01:20:10,034] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 439.41 | bwd_microstep: 424.40 | bwd_inner_microstep: 424.25 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.17 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1909 +[2025-05-15 01:20:11,273] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 1.66 | optimizer_step: 12.87 +[2025-05-15 01:20:11,273] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 389.64 | bwd_microstep: 814.09 | bwd_inner_microstep: 633.97 | bwd_allreduce_microstep: 180.07 | step_microstep: 19.58 +[2025-05-15 01:20:11,274] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2646.19 | bwd: 4131.07 | bwd_inner: 3950.47 | bwd_allreduce: 180.29 | step: 29.21 + 81%|████████ | 453/558 [52:06<11:43, 6.70s/it] {'loss': 5.1159, 'grad_norm': 19.23140525817871, 'learning_rate': 9.010041470788033e-17, 'epoch': 0.24} + 81%|████████ | 453/558 [52:06<11:43, 6.70s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1903 +[2025-05-15 01:20:12,234] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 330.95 | bwd_microstep: 606.81 | bwd_inner_microstep: 606.79 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-15 01:20:13,047] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 356.87 | bwd_microstep: 422.40 | bwd_inner_microstep: 422.38 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.81 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-15 01:20:14,028] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 434.85 | bwd_microstep: 520.75 | bwd_inner_microstep: 520.62 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-15 01:20:14,907] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 272.36 | bwd_microstep: 589.03 | bwd_inner_microstep: 589.01 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.50 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-15 01:20:15,725] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 379.95 | bwd_microstep: 403.96 | bwd_inner_microstep: 403.94 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.51 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-15 01:20:16,739] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 409.27 | bwd_microstep: 580.39 | bwd_inner_microstep: 580.37 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.62 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-15 01:20:17,563] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 222.95 | bwd_microstep: 581.58 | bwd_inner_microstep: 581.56 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 831 +[2025-05-15 01:20:18,218] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 1.62 | optimizer_step: 13.03 +[2025-05-15 01:20:18,218] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 217.73 | bwd_microstep: 388.08 | bwd_inner_microstep: 244.07 | bwd_allreduce_microstep: 143.96 | step_microstep: 19.90 +[2025-05-15 01:20:18,219] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2624.90 | bwd: 4093.02 | bwd_inner: 3948.77 | bwd_allreduce: 144.06 | step: 33.12 + 81%|████████▏ | 454/558 [52:13<11:44, 6.77s/it] {'loss': 6.0048, 'grad_norm': 25.257566452026367, 'learning_rate': 8.844463966474493e-17, 'epoch': 0.24} + 81%|████████▏ | 454/558 [52:13<11:44, 6.77s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 341 +[2025-05-15 01:20:18,440] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 72.81 | bwd_microstep: 130.78 | bwd_inner_microstep: 130.76 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.27 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1371 +[2025-05-15 01:20:19,230] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 301.39 | bwd_microstep: 465.59 | bwd_inner_microstep: 465.57 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.31 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-15 01:20:20,000] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 302.71 | bwd_microstep: 448.12 | bwd_inner_microstep: 448.10 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 839 +[2025-05-15 01:20:20,541] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 213.91 | bwd_microstep: 293.82 | bwd_inner_microstep: 293.80 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.52 +dynamic ViT batch size: 2, images per sample: 2.0, dynamic token length: 591 +[2025-05-15 01:20:20,856] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 130.80 | bwd_microstep: 158.41 | bwd_inner_microstep: 158.28 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-15 01:20:21,731] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 261.82 | bwd_microstep: 593.67 | bwd_inner_microstep: 593.65 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-15 01:20:22,530] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 378.77 | bwd_microstep: 388.37 | bwd_inner_microstep: 388.35 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.90 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-15 01:20:23,665] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 1.63 | optimizer_step: 14.68 +[2025-05-15 01:20:23,666] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 398.12 | bwd_microstep: 690.63 | bwd_inner_microstep: 581.11 | bwd_allreduce_microstep: 109.47 | step_microstep: 21.40 +[2025-05-15 01:20:23,667] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2060.29 | bwd: 3169.59 | bwd_inner: 3059.67 | bwd_allreduce: 109.56 | step: 33.19 + 82%|████████▏ | 455/558 [52:19<10:56, 6.37s/it] {'loss': 4.9954, 'grad_norm': 19.604137420654297, 'learning_rate': 8.680274279334372e-17, 'epoch': 0.24} + 82%|████████▏ | 455/558 [52:19<10:56, 6.37s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-15 01:20:24,647] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 350.49 | bwd_microstep: 608.25 | bwd_inner_microstep: 608.23 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-15 01:20:25,454] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 330.54 | bwd_microstep: 445.34 | bwd_inner_microstep: 445.14 | bwd_allreduce_microstep: 0.18 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-15 01:20:26,415] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 431.20 | bwd_microstep: 503.00 | bwd_inner_microstep: 502.87 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1355 +[2025-05-15 01:20:27,033] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 164.60 | bwd_microstep: 435.92 | bwd_inner_microstep: 435.90 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-15 01:20:27,903] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 422.97 | bwd_microstep: 417.94 | bwd_inner_microstep: 417.82 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-15 01:20:28,883] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 353.56 | bwd_microstep: 608.98 | bwd_inner_microstep: 608.96 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.33 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1353 +[2025-05-15 01:20:29,452] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 243.72 | bwd_microstep: 297.45 | bwd_inner_microstep: 297.43 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.88 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 829 +[2025-05-15 01:20:30,284] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 1.61 | optimizer_step: 12.94 +[2025-05-15 01:20:30,285] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 176.62 | bwd_microstep: 611.52 | bwd_inner_microstep: 298.74 | bwd_allreduce_microstep: 312.74 | step_microstep: 19.47 +[2025-05-15 01:20:30,285] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2473.65 | bwd: 3928.44 | bwd_inner: 3615.14 | bwd_allreduce: 313.06 | step: 28.73 + 82%|████████▏ | 456/558 [52:25<10:57, 6.45s/it] {'loss': 7.5354, 'grad_norm': 35.55685806274414, 'learning_rate': 8.517477946053354e-17, 'epoch': 0.25} + 82%|████████▏ | 456/558 [52:25<10:57, 6.45s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2114 +[2025-05-15 01:20:31,352] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 368.57 | bwd_microstep: 678.51 | bwd_inner_microstep: 678.49 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.26 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1938 +[2025-05-15 01:20:32,192] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 286.36 | bwd_microstep: 533.23 | bwd_inner_microstep: 533.21 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1913 +[2025-05-15 01:20:33,057] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 439.11 | bwd_microstep: 395.13 | bwd_inner_microstep: 394.94 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.18 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 354 +[2025-05-15 01:20:33,305] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 92.46 | bwd_microstep: 135.29 | bwd_inner_microstep: 132.95 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.81 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1913 +[2025-05-15 01:20:34,246] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 439.52 | bwd_microstep: 469.79 | bwd_inner_microstep: 469.66 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-15 01:20:35,209] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 346.17 | bwd_microstep: 599.77 | bwd_inner_microstep: 599.75 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.53 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-15 01:20:35,996] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 294.02 | bwd_microstep: 459.20 | bwd_inner_microstep: 459.18 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.33 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-15 01:20:37,463] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 1.62 | optimizer_step: 13.43 +[2025-05-15 01:20:37,463] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 436.30 | bwd_microstep: 980.85 | bwd_inner_microstep: 437.36 | bwd_allreduce_microstep: 543.44 | step_microstep: 20.29 +[2025-05-15 01:20:37,464] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2702.46 | bwd: 4251.78 | bwd_inner: 3707.90 | bwd_allreduce: 543.68 | step: 29.84 + 82%|████████▏ | 457/558 [52:32<11:13, 6.67s/it] {'loss': 2.4656, 'grad_norm': 15.171329498291016, 'learning_rate': 8.35608045633145e-17, 'epoch': 0.25} + 82%|████████▏ | 457/558 [52:32<11:13, 6.67s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1934 +[2025-05-15 01:20:38,326] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 251.34 | bwd_microstep: 584.98 | bwd_inner_microstep: 584.96 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1388 +[2025-05-15 01:20:39,011] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 332.27 | bwd_microstep: 324.73 | bwd_inner_microstep: 324.60 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1371 +[2025-05-15 01:20:39,696] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 225.12 | bwd_microstep: 442.97 | bwd_inner_microstep: 442.95 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-15 01:20:40,537] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 404.68 | bwd_microstep: 404.74 | bwd_inner_microstep: 404.72 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.92 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-15 01:20:41,545] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 405.30 | bwd_microstep: 576.37 | bwd_inner_microstep: 576.35 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.26 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-15 01:20:42,379] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 228.62 | bwd_microstep: 585.06 | bwd_inner_microstep: 585.04 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.49 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1092 +[2025-05-15 01:20:42,947] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 264.89 | bwd_microstep: 272.40 | bwd_inner_microstep: 272.27 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-15 01:20:44,144] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 1.66 | optimizer_step: 12.87 +[2025-05-15 01:20:44,144] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 287.42 | bwd_microstep: 875.23 | bwd_inner_microstep: 589.26 | bwd_allreduce_microstep: 285.92 | step_microstep: 19.53 +[2025-05-15 01:20:44,145] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2399.61 | bwd: 4066.52 | bwd_inner: 3780.22 | bwd_allreduce: 286.06 | step: 29.05 + 82%|████████▏ | 458/558 [52:39<11:07, 6.67s/it] {'loss': 5.7932, 'grad_norm': 22.88019561767578, 'learning_rate': 8.19608725269791e-17, 'epoch': 0.25} + 82%|████████▏ | 458/558 [52:39<11:07, 6.67s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-15 01:20:45,085] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 319.66 | bwd_microstep: 596.23 | bwd_inner_microstep: 596.21 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.28 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 334 +[2025-05-15 01:20:45,316] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 96.72 | bwd_microstep: 106.30 | bwd_inner_microstep: 106.12 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-15 01:20:46,140] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 222.74 | bwd_microstep: 582.57 | bwd_inner_microstep: 582.55 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.53 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1353 +[2025-05-15 01:20:46,799] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 314.34 | bwd_microstep: 313.87 | bwd_inner_microstep: 313.75 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-15 01:20:47,763] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 348.01 | bwd_microstep: 599.35 | bwd_inner_microstep: 599.33 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.49 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-15 01:20:48,550] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 304.80 | bwd_microstep: 447.33 | bwd_inner_microstep: 447.31 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.51 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-15 01:20:49,467] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 437.41 | bwd_microstep: 447.07 | bwd_inner_microstep: 446.94 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-15 01:20:50,664] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 1.68 | optimizer_step: 12.98 +[2025-05-15 01:20:50,665] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 352.84 | bwd_microstep: 810.37 | bwd_inner_microstep: 603.16 | bwd_allreduce_microstep: 207.16 | step_microstep: 19.70 +[2025-05-15 01:20:50,666] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2396.48 | bwd: 3903.12 | bwd_inner: 3695.40 | bwd_allreduce: 207.31 | step: 29.89 + 82%|████████▏ | 459/558 [52:46<10:55, 6.63s/it] {'loss': 6.8229, 'grad_norm': 22.96026039123535, 'learning_rate': 8.037503730327634e-17, 'epoch': 0.25} + 82%|████████▏ | 459/558 [52:46<10:55, 6.63s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1909 +[2025-05-15 01:20:51,626] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 325.57 | bwd_microstep: 612.99 | bwd_inner_microstep: 612.97 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.51 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1904 +[2025-05-15 01:20:52,433] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 320.28 | bwd_microstep: 452.73 | bwd_inner_microstep: 450.37 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.29 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 870 +[2025-05-15 01:20:53,002] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 226.15 | bwd_microstep: 311.83 | bwd_inner_microstep: 311.81 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.71 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-15 01:20:53,802] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 280.88 | bwd_microstep: 499.90 | bwd_inner_microstep: 499.88 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.48 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-15 01:20:54,673] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 435.95 | bwd_microstep: 405.18 | bwd_inner_microstep: 404.91 | bwd_allreduce_microstep: 0.22 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-15 01:20:55,693] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 390.69 | bwd_microstep: 608.16 | bwd_inner_microstep: 607.97 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.17 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-15 01:20:56,498] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 244.70 | bwd_microstep: 540.43 | bwd_inner_microstep: 540.41 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-15 01:20:57,952] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 1.67 | optimizer_step: 13.27 +[2025-05-15 01:20:57,953] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 417.63 | bwd_microstep: 986.29 | bwd_inner_microstep: 388.33 | bwd_allreduce_microstep: 597.93 | step_microstep: 20.87 +[2025-05-15 01:20:57,954] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2641.84 | bwd: 4417.50 | bwd_inner: 3816.69 | bwd_allreduce: 600.50 | step: 31.58 + 82%|████████▏ | 460/558 [52:53<11:08, 6.83s/it] {'loss': 3.1965, 'grad_norm': 13.713174819946289, 'learning_rate': 7.880335236859283e-17, 'epoch': 0.25} + 82%|████████▏ | 460/558 [52:53<11:08, 6.83s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1899 +[2025-05-15 01:20:58,817] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 242.04 | bwd_microstep: 596.23 | bwd_inner_microstep: 596.21 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.28 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1888 +[2025-05-15 01:20:59,644] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 381.66 | bwd_microstep: 413.92 | bwd_inner_microstep: 413.90 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.80 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-15 01:21:00,639] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 398.67 | bwd_microstep: 571.93 | bwd_inner_microstep: 571.80 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-15 01:21:01,490] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 236.84 | bwd_microstep: 593.79 | bwd_inner_microstep: 593.77 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 855 +[2025-05-15 01:21:01,985] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 222.79 | bwd_microstep: 245.20 | bwd_inner_microstep: 245.07 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-15 01:21:02,836] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 242.79 | bwd_microstep: 588.08 | bwd_inner_microstep: 588.06 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-15 01:21:03,649] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 390.43 | bwd_microstep: 389.99 | bwd_inner_microstep: 389.97 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.52 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-15 01:21:04,828] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 1.71 | optimizer_step: 12.91 +[2025-05-15 01:21:04,828] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 392.94 | bwd_microstep: 744.30 | bwd_inner_microstep: 597.57 | bwd_allreduce_microstep: 146.68 | step_microstep: 19.69 +[2025-05-15 01:21:04,829] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2508.10 | bwd: 4143.49 | bwd_inner: 3996.42 | bwd_allreduce: 146.83 | step: 31.17 + 83%|████████▎ | 461/558 [53:00<11:03, 6.84s/it] {'loss': 3.4561, 'grad_norm': 10.717794418334961, 'learning_rate': 7.724587072214973e-17, 'epoch': 0.25} + 83%|████████▎ | 461/558 [53:00<11:03, 6.84s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 379 +[2025-05-15 01:21:05,069] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 77.91 | bwd_microstep: 142.17 | bwd_inner_microstep: 139.84 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.74 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 341 +[2025-05-15 01:21:05,319] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 87.49 | bwd_microstep: 139.11 | bwd_inner_microstep: 139.09 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 876 +[2025-05-15 01:21:05,856] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 225.45 | bwd_microstep: 281.37 | bwd_inner_microstep: 281.35 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.30 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-15 01:21:06,678] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 229.41 | bwd_microstep: 570.79 | bwd_inner_microstep: 570.77 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.33 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-15 01:21:07,519] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 409.56 | bwd_microstep: 396.44 | bwd_inner_microstep: 396.42 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.32 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-15 01:21:08,529] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 398.24 | bwd_microstep: 587.15 | bwd_inner_microstep: 586.96 | bwd_allreduce_microstep: 0.17 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-15 01:21:09,338] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 244.93 | bwd_microstep: 544.21 | bwd_inner_microstep: 544.19 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 2, images per sample: 2.0, dynamic token length: 601 +[2025-05-15 01:21:09,990] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 1.64 | optimizer_step: 20.32 +[2025-05-15 01:21:09,991] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 153.37 | bwd_microstep: 441.16 | bwd_inner_microstep: 215.85 | bwd_allreduce_microstep: 225.29 | step_microstep: 27.70 +[2025-05-15 01:21:09,991] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 1826.35 | bwd: 3102.40 | bwd_inner: 2874.49 | bwd_allreduce: 225.49 | step: 41.04 + 83%|████████▎ | 462/558 [53:05<10:08, 6.34s/it] {'loss': 4.9661, 'grad_norm': 15.92909049987793, 'learning_rate': 7.570264488421447e-17, 'epoch': 0.25} + 83%|████████▎ | 462/558 [53:05<10:08, 6.34s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1892 +[2025-05-15 01:21:10,870] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 261.97 | bwd_microstep: 592.16 | bwd_inner_microstep: 592.14 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 860 +[2025-05-15 01:21:11,358] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 209.95 | bwd_microstep: 248.23 | bwd_inner_microstep: 248.21 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.30 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-15 01:21:12,191] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 228.26 | bwd_microstep: 580.91 | bwd_inner_microstep: 580.89 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.32 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-15 01:21:13,043] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 405.30 | bwd_microstep: 417.37 | bwd_inner_microstep: 417.24 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-15 01:21:14,069] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 390.14 | bwd_microstep: 617.49 | bwd_inner_microstep: 617.47 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.31 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-15 01:21:14,850] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 315.86 | bwd_microstep: 444.77 | bwd_inner_microstep: 444.71 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.24 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-15 01:21:15,773] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 434.22 | bwd_microstep: 460.83 | bwd_inner_microstep: 460.69 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-15 01:21:16,973] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 1.66 | optimizer_step: 12.94 +[2025-05-15 01:21:16,974] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 344.63 | bwd_microstep: 821.17 | bwd_inner_microstep: 599.08 | bwd_allreduce_microstep: 222.04 | step_microstep: 19.77 +[2025-05-15 01:21:16,975] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2590.29 | bwd: 4182.98 | bwd_inner: 3960.49 | bwd_allreduce: 222.22 | step: 29.47 + 83%|████████▎ | 463/558 [53:12<10:20, 6.53s/it] {'loss': 5.6601, 'grad_norm': 20.3121280670166, 'learning_rate': 7.417372689433122e-17, 'epoch': 0.25} + 83%|████████▎ | 463/558 [53:12<10:20, 6.53s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1908 +[2025-05-15 01:21:17,929] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 327.89 | bwd_microstep: 604.89 | bwd_inner_microstep: 604.87 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 854 +[2025-05-15 01:21:18,321] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 180.50 | bwd_microstep: 183.50 | bwd_inner_microstep: 183.36 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-15 01:21:19,278] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 335.34 | bwd_microstep: 604.39 | bwd_inner_microstep: 604.37 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.43 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-15 01:21:20,078] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 314.40 | bwd_microstep: 448.14 | bwd_inner_microstep: 448.12 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.53 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 326 +[2025-05-15 01:21:20,347] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 99.82 | bwd_microstep: 137.84 | bwd_inner_microstep: 137.82 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-15 01:21:21,177] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 396.75 | bwd_microstep: 401.33 | bwd_inner_microstep: 401.31 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.82 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 846 +[2025-05-15 01:21:21,692] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 180.76 | bwd_microstep: 311.13 | bwd_inner_microstep: 311.11 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.33 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-15 01:21:23,087] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 1.63 | optimizer_step: 14.89 +[2025-05-15 01:21:23,087] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 382.07 | bwd_microstep: 962.68 | bwd_inner_microstep: 398.93 | bwd_allreduce_microstep: 563.73 | step_microstep: 20.65 +[2025-05-15 01:21:23,088] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2217.52 | bwd: 3653.91 | bwd_inner: 3089.94 | bwd_allreduce: 563.81 | step: 34.52 + 83%|████████▎ | 464/558 [53:18<10:02, 6.41s/it] {'loss': 5.2569, 'grad_norm': 37.491973876953125, 'learning_rate': 7.26591683095647e-17, 'epoch': 0.25} + 83%|████████▎ | 464/558 [53:18<10:02, 6.41s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1949 +[2025-05-15 01:21:23,969] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 236.59 | bwd_microstep: 619.67 | bwd_inner_microstep: 619.65 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.32 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-15 01:21:24,788] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 401.38 | bwd_microstep: 383.42 | bwd_inner_microstep: 383.41 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.80 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-15 01:21:25,810] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 396.23 | bwd_microstep: 600.38 | bwd_inner_microstep: 600.36 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.81 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 341 +[2025-05-15 01:21:26,033] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 82.60 | bwd_microstep: 122.24 | bwd_inner_microstep: 122.22 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.69 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-15 01:21:27,052] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 396.30 | bwd_microstep: 596.55 | bwd_inner_microstep: 596.53 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.27 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-15 01:21:27,875] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 222.32 | bwd_microstep: 575.95 | bwd_inner_microstep: 575.93 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-15 01:21:28,726] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 406.41 | bwd_microstep: 414.33 | bwd_inner_microstep: 414.20 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-15 01:21:29,961] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 1.65 | optimizer_step: 15.03 +[2025-05-15 01:21:29,961] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 384.38 | bwd_microstep: 813.79 | bwd_inner_microstep: 615.01 | bwd_allreduce_microstep: 198.73 | step_microstep: 21.74 +[2025-05-15 01:21:29,962] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2526.20 | bwd: 4126.36 | bwd_inner: 3927.35 | bwd_allreduce: 198.83 | step: 34.08 + 83%|████████▎ | 465/558 [53:25<10:08, 6.55s/it] {'loss': 4.589, 'grad_norm': 14.369437217712402, 'learning_rate': 7.115902020276238e-17, 'epoch': 0.25} + 83%|████████▎ | 465/558 [53:25<10:08, 6.55s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1903 +[2025-05-15 01:21:30,912] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 324.29 | bwd_microstep: 604.32 | bwd_inner_microstep: 604.30 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.32 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1887 +[2025-05-15 01:21:31,725] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 358.04 | bwd_microstep: 420.96 | bwd_inner_microstep: 420.94 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.82 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-15 01:21:32,712] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 439.39 | bwd_microstep: 522.49 | bwd_inner_microstep: 522.36 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-15 01:21:33,592] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 270.48 | bwd_microstep: 592.22 | bwd_inner_microstep: 592.20 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-15 01:21:34,405] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 381.80 | bwd_microstep: 397.60 | bwd_inner_microstep: 397.58 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.79 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-15 01:21:35,418] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 407.75 | bwd_microstep: 578.34 | bwd_inner_microstep: 578.32 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.27 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1094 +[2025-05-15 01:21:35,876] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 117.82 | bwd_microstep: 319.74 | bwd_inner_microstep: 319.72 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.02 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1090 +[2025-05-15 01:21:36,736] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 1.63 | optimizer_step: 13.06 +[2025-05-15 01:21:36,736] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 266.67 | bwd_microstep: 544.30 | bwd_inner_microstep: 362.18 | bwd_allreduce_microstep: 182.08 | step_microstep: 19.61 +[2025-05-15 01:21:36,737] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2566.20 | bwd: 3979.99 | bwd_inner: 3797.63 | bwd_allreduce: 182.18 | step: 32.28 + 84%|████████▎ | 466/558 [53:32<10:08, 6.61s/it] {'loss': 4.7168, 'grad_norm': 41.93552780151367, 'learning_rate': 6.967333316083224e-17, 'epoch': 0.25} + 84%|████████▎ | 466/558 [53:32<10:08, 6.61s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1940 +[2025-05-15 01:21:37,744] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 350.80 | bwd_microstep: 634.74 | bwd_inner_microstep: 634.73 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.41 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-15 01:21:38,547] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 293.28 | bwd_microstep: 480.53 | bwd_inner_microstep: 480.50 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.54 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1357 +[2025-05-15 01:21:39,331] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 330.24 | bwd_microstep: 424.78 | bwd_inner_microstep: 424.74 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-15 01:21:40,194] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 247.67 | bwd_microstep: 595.81 | bwd_inner_microstep: 595.77 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.42 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-15 01:21:41,023] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 389.41 | bwd_microstep: 407.31 | bwd_inner_microstep: 407.28 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.83 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-15 01:21:42,024] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 403.33 | bwd_microstep: 571.78 | bwd_inner_microstep: 571.76 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-15 01:21:42,879] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 246.24 | bwd_microstep: 590.38 | bwd_inner_microstep: 590.36 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-15 01:21:44,251] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 1.77 | optimizer_step: 13.29 +[2025-05-15 01:21:44,252] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 386.91 | bwd_microstep: 933.05 | bwd_inner_microstep: 402.31 | bwd_allreduce_microstep: 530.73 | step_microstep: 20.67 +[2025-05-15 01:21:44,252] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2647.82 | bwd: 4638.56 | bwd_inner: 4107.45 | bwd_allreduce: 530.77 | step: 32.12 + 84%|████████▎ | 467/558 [53:39<10:26, 6.88s/it] {'loss': 5.5368, 'grad_norm': 28.126262664794922, 'learning_rate': 6.820215728303625e-17, 'epoch': 0.25} + 84%|████████▎ | 467/558 [53:39<10:26, 6.88s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1932 +[2025-05-15 01:21:45,142] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 253.09 | bwd_microstep: 613.51 | bwd_inner_microstep: 613.49 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.33 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-15 01:21:45,970] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 382.82 | bwd_microstep: 411.24 | bwd_inner_microstep: 411.22 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.93 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-15 01:21:46,950] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 404.85 | bwd_microstep: 551.30 | bwd_inner_microstep: 551.28 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.92 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-15 01:21:47,775] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 222.80 | bwd_microstep: 581.59 | bwd_inner_microstep: 581.57 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.53 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 334 +[2025-05-15 01:21:48,046] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 99.27 | bwd_microstep: 142.04 | bwd_inner_microstep: 142.02 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1346 +[2025-05-15 01:21:48,624] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 243.79 | bwd_microstep: 305.39 | bwd_inner_microstep: 305.37 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.83 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-15 01:21:49,616] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 402.88 | bwd_microstep: 562.81 | bwd_inner_microstep: 562.66 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.14 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-15 01:21:50,831] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 1.70 | optimizer_step: 12.78 +[2025-05-15 01:21:50,832] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 250.96 | bwd_microstep: 928.24 | bwd_inner_microstep: 591.27 | bwd_allreduce_microstep: 336.93 | step_microstep: 19.60 +[2025-05-15 01:21:50,833] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2260.44 | bwd: 4096.13 | bwd_inner: 3758.90 | bwd_allreduce: 337.04 | step: 31.65 + 84%|████████▍ | 468/558 [53:46<10:11, 6.79s/it] {'loss': 4.8503, 'grad_norm': 21.224485397338867, 'learning_rate': 6.674554217930163e-17, 'epoch': 0.25} + 84%|████████▍ | 468/558 [53:46<10:11, 6.79s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1916 +[2025-05-15 01:21:51,790] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 327.20 | bwd_microstep: 607.99 | bwd_inner_microstep: 607.97 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1123 +[2025-05-15 01:21:52,308] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 221.30 | bwd_microstep: 269.16 | bwd_inner_microstep: 269.03 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1887 +[2025-05-15 01:21:53,237] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 305.20 | bwd_microstep: 606.35 | bwd_inner_microstep: 606.32 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-15 01:21:54,042] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 362.25 | bwd_microstep: 408.17 | bwd_inner_microstep: 408.15 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.83 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-15 01:21:55,056] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 405.60 | bwd_microstep: 585.77 | bwd_inner_microstep: 585.48 | bwd_allreduce_microstep: 0.25 | step_microstep: 0.24 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-15 01:21:55,902] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 225.07 | bwd_microstep: 599.74 | bwd_inner_microstep: 599.70 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.30 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-15 01:21:56,714] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 399.20 | bwd_microstep: 381.53 | bwd_inner_microstep: 381.51 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-15 01:21:57,899] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 1.75 | optimizer_step: 13.91 +[2025-05-15 01:21:57,899] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 393.54 | bwd_microstep: 743.83 | bwd_inner_microstep: 599.81 | bwd_allreduce_microstep: 143.98 | step_microstep: 20.74 +[2025-05-15 01:21:57,900] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2639.33 | bwd: 4202.56 | bwd_inner: 4058.02 | bwd_allreduce: 144.32 | step: 29.94 + 84%|████████▍ | 469/558 [53:53<10:11, 6.88s/it] {'loss': 3.4588, 'grad_norm': 7.891175270080566, 'learning_rate': 6.530353696854791e-17, 'epoch': 0.25} + 84%|████████▍ | 469/558 [53:53<10:11, 6.88s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1900 +[2025-05-15 01:21:58,895] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 351.56 | bwd_microstep: 617.52 | bwd_inner_microstep: 617.47 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.54 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-15 01:21:59,694] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 338.69 | bwd_microstep: 425.96 | bwd_inner_microstep: 425.92 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.82 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-15 01:22:00,645] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 438.87 | bwd_microstep: 486.36 | bwd_inner_microstep: 486.22 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.09 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1348 +[2025-05-15 01:22:01,320] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 212.76 | bwd_microstep: 443.39 | bwd_inner_microstep: 443.33 | bwd_allreduce_microstep: 0.02 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-15 01:22:02,155] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 414.20 | bwd_microstep: 387.39 | bwd_inner_microstep: 387.34 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.82 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 837 +[2025-05-15 01:22:02,649] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.46 | bwd_microstep: 275.91 | bwd_inner_microstep: 275.88 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.29 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-15 01:22:03,490] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 407.55 | bwd_microstep: 400.03 | bwd_inner_microstep: 400.00 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.28 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-15 01:22:04,687] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.07 | optimizer_step: 18.25 +[2025-05-15 01:22:04,687] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 395.98 | bwd_microstep: 751.83 | bwd_inner_microstep: 598.17 | bwd_allreduce_microstep: 153.60 | step_microstep: 26.69 +[2025-05-15 01:22:04,688] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2750.04 | bwd: 3788.40 | bwd_inner: 3634.37 | bwd_allreduce: 153.74 | step: 37.91 + 84%|████████▍ | 470/558 [54:00<10:02, 6.85s/it] {'loss': 6.6226, 'grad_norm': 28.02364730834961, 'learning_rate': 6.387619027703019e-17, 'epoch': 0.25} + 84%|████████▍ | 470/558 [54:00<10:02, 6.85s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1985 +[2025-05-15 01:22:05,739] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 368.76 | bwd_microstep: 658.18 | bwd_inner_microstep: 658.13 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1897 +[2025-05-15 01:22:06,534] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 323.92 | bwd_microstep: 448.00 | bwd_inner_microstep: 447.79 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-15 01:22:07,506] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 438.31 | bwd_microstep: 505.57 | bwd_inner_microstep: 505.42 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-15 01:22:08,405] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 280.97 | bwd_microstep: 598.27 | bwd_inner_microstep: 598.24 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-15 01:22:09,239] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 381.53 | bwd_microstep: 418.83 | bwd_inner_microstep: 418.77 | bwd_allreduce_microstep: 0.02 | step_microstep: 1.82 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-15 01:22:10,204] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 426.70 | bwd_microstep: 514.17 | bwd_inner_microstep: 514.04 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-15 01:22:11,115] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 289.41 | bwd_microstep: 601.64 | bwd_inner_microstep: 601.61 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-15 01:22:12,488] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.01 | optimizer_gradients: 2.06 | optimizer_step: 17.22 +[2025-05-15 01:22:12,489] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 381.04 | bwd_microstep: 933.62 | bwd_inner_microstep: 394.58 | bwd_allreduce_microstep: 539.00 | step_microstep: 26.28 +[2025-05-15 01:22:12,489] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2890.60 | bwd: 4678.29 | bwd_inner: 4138.63 | bwd_allreduce: 539.15 | step: 35.54 + 84%|████████▍ | 471/558 [54:08<10:20, 7.14s/it] {'loss': 6.2608, 'grad_norm': 30.31316566467285, 'learning_rate': 6.246355023669959e-17, 'epoch': 0.25} + 84%|████████▍ | 471/558 [54:08<10:20, 7.14s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1883 +[2025-05-15 01:22:13,310] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 257.26 | bwd_microstep: 534.08 | bwd_inner_microstep: 534.05 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.52 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-15 01:22:14,237] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 432.88 | bwd_microstep: 462.22 | bwd_inner_microstep: 462.07 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-15 01:22:15,201] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 332.25 | bwd_microstep: 611.72 | bwd_inner_microstep: 611.68 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.52 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-15 01:22:16,013] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 361.48 | bwd_microstep: 416.53 | bwd_inner_microstep: 416.51 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.80 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 321 +[2025-05-15 01:22:16,273] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.24 | bwd_microstep: 141.69 | bwd_inner_microstep: 141.65 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.53 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 323 +[2025-05-15 01:22:16,552] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 104.09 | bwd_microstep: 142.65 | bwd_inner_microstep: 142.62 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.54 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-15 01:22:17,359] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 331.94 | bwd_microstep: 440.41 | bwd_inner_microstep: 440.36 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.00 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2021 +[2025-05-15 01:22:18,534] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.02 | optimizer_step: 18.70 +[2025-05-15 01:22:18,535] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 469.93 | bwd_microstep: 648.00 | bwd_inner_microstep: 511.38 | bwd_allreduce_microstep: 136.56 | step_microstep: 29.59 +[2025-05-15 01:22:18,536] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2384.08 | bwd: 3397.32 | bwd_inner: 3260.36 | bwd_allreduce: 136.66 | step: 43.60 + 85%|████████▍ | 472/558 [54:14<09:45, 6.81s/it] {'loss': 5.9601, 'grad_norm': 22.389753341674805, 'learning_rate': 6.106566448358026e-17, 'epoch': 0.25} + 85%|████████▍ | 472/558 [54:14<09:45, 6.81s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1887 +[2025-05-15 01:22:19,553] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 413.73 | bwd_microstep: 566.04 | bwd_inner_microstep: 566.00 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.32 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-15 01:22:20,426] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 246.21 | bwd_microstep: 603.31 | bwd_inner_microstep: 603.28 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.28 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-15 01:22:21,247] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 389.40 | bwd_microstep: 397.24 | bwd_inner_microstep: 397.21 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.32 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-15 01:22:22,268] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 397.72 | bwd_microstep: 600.39 | bwd_inner_microstep: 600.35 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-15 01:22:23,099] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 223.03 | bwd_microstep: 586.47 | bwd_inner_microstep: 586.43 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-15 01:22:23,939] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 410.35 | bwd_microstep: 394.73 | bwd_inner_microstep: 394.68 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.32 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 316 +[2025-05-15 01:22:24,190] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 91.72 | bwd_microstep: 134.17 | bwd_inner_microstep: 134.11 | bwd_allreduce_microstep: 0.02 | step_microstep: 2.46 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1938 +[2025-05-15 01:22:25,726] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 1.65 | optimizer_step: 16.37 +[2025-05-15 01:22:25,726] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 456.55 | bwd_microstep: 1022.69 | bwd_inner_microstep: 432.69 | bwd_allreduce_microstep: 589.97 | step_microstep: 25.17 +[2025-05-15 01:22:25,727] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2628.71 | bwd: 4305.04 | bwd_inner: 3714.75 | bwd_allreduce: 590.04 | step: 39.42 + 85%|████████▍ | 473/558 [54:21<09:48, 6.92s/it] {'loss': 7.2519, 'grad_norm': 29.927162170410156, 'learning_rate': 5.968258015616291e-17, 'epoch': 0.25} + 85%|████████▍ | 473/558 [54:21<09:48, 6.92s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1891 +[2025-05-15 01:22:26,577] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 223.70 | bwd_microstep: 597.09 | bwd_inner_microstep: 597.05 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-15 01:22:27,409] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 404.47 | bwd_microstep: 394.22 | bwd_inner_microstep: 394.19 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.85 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-15 01:22:28,443] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 416.84 | bwd_microstep: 589.21 | bwd_inner_microstep: 589.15 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.32 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1891 +[2025-05-15 01:22:29,281] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 227.39 | bwd_microstep: 590.22 | bwd_inner_microstep: 590.17 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-15 01:22:30,115] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 409.22 | bwd_microstep: 392.81 | bwd_inner_microstep: 392.54 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.21 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-15 01:22:31,149] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 393.98 | bwd_microstep: 617.73 | bwd_inner_microstep: 617.53 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.18 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 326 +[2025-05-15 01:22:31,387] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 89.81 | bwd_microstep: 132.55 | bwd_inner_microstep: 132.40 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-15 01:22:32,612] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.01 | optimizer_gradients: 1.95 | optimizer_step: 18.29 +[2025-05-15 01:22:32,613] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 305.84 | bwd_microstep: 874.14 | bwd_inner_microstep: 600.90 | bwd_allreduce_microstep: 273.21 | step_microstep: 28.04 +[2025-05-15 01:22:32,614] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2471.22 | bwd: 4187.97 | bwd_inner: 3913.95 | bwd_allreduce: 273.55 | step: 37.42 + 85%|████████▍ | 474/558 [54:28<09:40, 6.91s/it] {'loss': 3.902, 'grad_norm': 17.129507064819336, 'learning_rate': 5.831434389381546e-17, 'epoch': 0.25} + 85%|████████▍ | 474/558 [54:28<09:40, 6.91s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-15 01:22:33,491] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 253.00 | bwd_microstep: 597.77 | bwd_inner_microstep: 597.72 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 360 +[2025-05-15 01:22:33,775] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 113.83 | bwd_microstep: 137.82 | bwd_inner_microstep: 137.77 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.28 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-15 01:22:34,585] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 248.25 | bwd_microstep: 540.37 | bwd_inner_microstep: 540.33 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.32 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-15 01:22:35,434] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 427.12 | bwd_microstep: 389.57 | bwd_inner_microstep: 389.31 | bwd_allreduce_microstep: 0.23 | step_microstep: 0.21 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-15 01:22:36,467] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 396.74 | bwd_microstep: 613.95 | bwd_inner_microstep: 613.74 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-15 01:22:37,271] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 247.11 | bwd_microstep: 535.59 | bwd_inner_microstep: 535.54 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.54 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-15 01:22:38,125] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 428.82 | bwd_microstep: 393.11 | bwd_inner_microstep: 393.05 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-15 01:22:39,334] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.09 | optimizer_step: 18.04 +[2025-05-15 01:22:39,334] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 395.01 | bwd_microstep: 766.60 | bwd_inner_microstep: 614.79 | bwd_allreduce_microstep: 151.76 | step_microstep: 26.20 +[2025-05-15 01:22:39,335] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2509.87 | bwd: 3974.80 | bwd_inner: 3822.24 | bwd_allreduce: 152.08 | step: 36.27 + 85%|████████▌ | 475/558 [54:34<09:28, 6.85s/it] {'loss': 6.0024, 'grad_norm': 22.249252319335938, 'learning_rate': 5.696100183521003e-17, 'epoch': 0.26} + 85%|████████▌ | 475/558 [54:34<09:28, 6.85s/it]dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1375 +[2025-05-15 01:22:40,027] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 226.91 | bwd_microstep: 442.49 | bwd_inner_microstep: 442.46 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.50 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1108 +[2025-05-15 01:22:40,619] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 273.27 | bwd_microstep: 290.69 | bwd_inner_microstep: 290.55 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-15 01:22:41,503] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 267.26 | bwd_microstep: 597.19 | bwd_inner_microstep: 597.15 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-15 01:22:42,323] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 386.80 | bwd_microstep: 399.41 | bwd_inner_microstep: 399.37 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.77 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 327 +[2025-05-15 01:22:42,575] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.09 | bwd_microstep: 134.28 | bwd_inner_microstep: 134.26 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.29 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 841 +[2025-05-15 01:22:43,129] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 223.63 | bwd_microstep: 300.48 | bwd_inner_microstep: 300.45 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.48 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-15 01:22:43,934] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 247.26 | bwd_microstep: 536.71 | bwd_inner_microstep: 536.68 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.33 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-15 01:22:45,148] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.01 | optimizer_gradients: 2.04 | optimizer_step: 18.41 +[2025-05-15 01:22:45,149] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 443.03 | bwd_microstep: 710.88 | bwd_inner_microstep: 503.38 | bwd_allreduce_microstep: 207.47 | step_microstep: 27.24 +[2025-05-15 01:22:45,149] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2161.21 | bwd: 3412.15 | bwd_inner: 3204.33 | bwd_allreduce: 207.57 | step: 41.05 + 85%|████████▌ | 476/558 [54:40<08:56, 6.54s/it] {'loss': 4.6891, 'grad_norm': 18.652698516845703, 'learning_rate': 5.562259961676692e-17, 'epoch': 0.26} + 85%|████████▌ | 476/558 [54:40<08:56, 6.54s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1893 +[2025-05-15 01:22:46,049] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 354.17 | bwd_microstep: 520.74 | bwd_inner_microstep: 520.52 | bwd_allreduce_microstep: 0.18 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-15 01:22:46,944] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 357.56 | bwd_microstep: 516.50 | bwd_inner_microstep: 516.47 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.98 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1361 +[2025-05-15 01:22:47,608] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 254.07 | bwd_microstep: 390.84 | bwd_inner_microstep: 390.79 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.23 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-15 01:22:48,491] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 356.28 | bwd_microstep: 506.44 | bwd_inner_microstep: 506.38 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.32 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-15 01:22:49,366] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 349.83 | bwd_microstep: 505.78 | bwd_inner_microstep: 505.73 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.27 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-15 01:22:50,173] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 238.70 | bwd_microstep: 546.04 | bwd_inner_microstep: 546.01 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-15 01:22:51,148] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 440.71 | bwd_microstep: 501.49 | bwd_inner_microstep: 501.47 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.26 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-15 01:22:52,268] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.24 | optimizer_gradients: 2.06 | optimizer_step: 18.65 +[2025-05-15 01:22:52,269] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 357.27 | bwd_microstep: 718.60 | bwd_inner_microstep: 511.51 | bwd_allreduce_microstep: 207.05 | step_microstep: 27.75 +[2025-05-15 01:22:52,270] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2708.59 | bwd: 4206.43 | bwd_inner: 3998.89 | bwd_allreduce: 207.30 | step: 33.33 + 85%|████████▌ | 477/558 [54:47<09:04, 6.72s/it] {'loss': 4.7019, 'grad_norm': 34.3962287902832, 'learning_rate': 5.429918237111642e-17, 'epoch': 0.26} + 85%|████████▌ | 477/558 [54:47<09:04, 6.72s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-15 01:22:53,159] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 355.99 | bwd_microstep: 508.41 | bwd_inner_microstep: 508.35 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.26 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-15 01:22:53,951] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 346.61 | bwd_microstep: 424.23 | bwd_inner_microstep: 424.09 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-15 01:22:54,970] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 368.38 | bwd_microstep: 632.67 | bwd_inner_microstep: 632.45 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-15 01:22:55,761] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 321.73 | bwd_microstep: 450.00 | bwd_inner_microstep: 449.68 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-15 01:22:56,772] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 432.35 | bwd_microstep: 547.97 | bwd_inner_microstep: 547.95 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.91 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-15 01:22:57,558] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 319.97 | bwd_microstep: 447.58 | bwd_inner_microstep: 447.38 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-15 01:22:58,577] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 443.38 | bwd_microstep: 548.05 | bwd_inner_microstep: 548.01 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-15 01:22:59,873] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 1.69 | optimizer_step: 17.14 +[2025-05-15 01:22:59,873] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 330.90 | bwd_microstep: 921.86 | bwd_inner_microstep: 442.55 | bwd_allreduce_microstep: 479.29 | step_microstep: 24.21 +[2025-05-15 01:22:59,874] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2919.28 | bwd: 4480.78 | bwd_inner: 4000.52 | bwd_allreduce: 479.80 | step: 28.18 + 86%|████████▌ | 478/558 [54:55<09:18, 6.98s/it] {'loss': 4.3177, 'grad_norm': 16.997873306274414, 'learning_rate': 5.2990794725576225e-17, 'epoch': 0.26} + 86%|████████▌ | 478/558 [54:55<09:18, 6.98s/it]dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 873 +[2025-05-15 01:23:00,208] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 108.23 | bwd_microstep: 198.80 | bwd_inner_microstep: 198.77 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.75 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1890 +[2025-05-15 01:23:01,239] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 414.68 | bwd_microstep: 591.72 | bwd_inner_microstep: 591.70 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.29 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-15 01:23:02,122] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 347.29 | bwd_microstep: 514.25 | bwd_inner_microstep: 514.23 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.31 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-15 01:23:03,008] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 354.76 | bwd_microstep: 512.12 | bwd_inner_microstep: 511.97 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-15 01:23:03,871] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 246.39 | bwd_microstep: 593.40 | bwd_inner_microstep: 593.38 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.47 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-15 01:23:04,680] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 382.14 | bwd_microstep: 395.29 | bwd_inner_microstep: 395.27 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.79 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-15 01:23:05,704] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 400.30 | bwd_microstep: 601.29 | bwd_inner_microstep: 601.23 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.20 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1469 +[2025-05-15 01:23:06,846] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.07 | optimizer_step: 18.81 +[2025-05-15 01:23:06,847] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 272.67 | bwd_microstep: 822.10 | bwd_inner_microstep: 346.76 | bwd_allreduce_microstep: 475.28 | step_microstep: 30.30 +[2025-05-15 01:23:06,848] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2526.42 | bwd: 4228.99 | bwd_inner: 3753.35 | bwd_allreduce: 475.36 | step: 39.22 + 86%|████████▌ | 479/558 [55:02<09:11, 6.98s/it] {'loss': 3.8055, 'grad_norm': 24.261737823486328, 'learning_rate': 5.1697480800646516e-17, 'epoch': 0.26} + 86%|████████▌ | 479/558 [55:02<09:11, 6.98s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1909 +[2025-05-15 01:23:07,743] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 357.92 | bwd_microstep: 505.95 | bwd_inner_microstep: 505.81 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-15 01:23:08,626] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 259.84 | bwd_microstep: 600.53 | bwd_inner_microstep: 600.49 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-15 01:23:09,569] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 396.16 | bwd_microstep: 513.85 | bwd_inner_microstep: 513.81 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.97 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-15 01:23:10,445] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 342.13 | bwd_microstep: 512.73 | bwd_inner_microstep: 512.69 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.29 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-15 01:23:11,216] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 305.96 | bwd_microstep: 446.58 | bwd_inner_microstep: 446.27 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-15 01:23:12,230] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 443.20 | bwd_microstep: 542.89 | bwd_inner_microstep: 542.68 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-15 01:23:13,098] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 349.02 | bwd_microstep: 499.94 | bwd_inner_microstep: 499.90 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.22 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1963 +[2025-05-15 01:23:14,357] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.01 | optimizer_gradients: 2.06 | optimizer_step: 18.34 +[2025-05-15 01:23:14,358] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 241.48 | bwd_microstep: 972.05 | bwd_inner_microstep: 626.56 | bwd_allreduce_microstep: 345.46 | step_microstep: 26.98 +[2025-05-15 01:23:14,358] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2695.71 | bwd: 4594.54 | bwd_inner: 4248.27 | bwd_allreduce: 345.80 | step: 31.26 + 86%|████████▌ | 480/558 [55:09<09:16, 7.14s/it] {'loss': 4.8445, 'grad_norm': 31.936607360839844, 'learning_rate': 5.041928420852299e-17, 'epoch': 0.26} + 86%|████████▌ | 480/558 [55:09<09:16, 7.14s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1934 +[2025-05-15 01:23:15,181] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 330.57 | bwd_microstep: 465.18 | bwd_inner_microstep: 465.16 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.50 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1124 +[2025-05-15 01:23:15,856] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 274.49 | bwd_microstep: 371.15 | bwd_inner_microstep: 370.94 | bwd_allreduce_microstep: 0.19 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-15 01:23:16,632] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 356.75 | bwd_microstep: 397.95 | bwd_inner_microstep: 397.93 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.84 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-15 01:23:17,660] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 413.28 | bwd_microstep: 588.35 | bwd_inner_microstep: 588.32 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.73 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-15 01:23:18,490] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 224.86 | bwd_microstep: 585.35 | bwd_inner_microstep: 585.30 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-15 01:23:19,319] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 403.21 | bwd_microstep: 392.47 | bwd_inner_microstep: 392.26 | bwd_allreduce_microstep: 0.18 | step_microstep: 0.24 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-15 01:23:20,354] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 397.73 | bwd_microstep: 615.39 | bwd_inner_microstep: 615.19 | bwd_allreduce_microstep: 0.18 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-15 01:23:21,610] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.01 | optimizer_gradients: 1.63 | optimizer_step: 15.33 +[2025-05-15 01:23:21,611] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 282.56 | bwd_microstep: 931.91 | bwd_inner_microstep: 469.65 | bwd_allreduce_microstep: 462.24 | step_microstep: 22.93 +[2025-05-15 01:23:21,612] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2683.45 | bwd: 4347.75 | bwd_inner: 3884.74 | bwd_allreduce: 462.81 | step: 30.96 + 86%|████████▌ | 481/558 [55:17<09:12, 7.17s/it] {'loss': 3.7431, 'grad_norm': 24.825153350830078, 'learning_rate': 4.915624805162489e-17, 'epoch': 0.26} + 86%|████████▌ | 481/558 [55:17<09:12, 7.17s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1917 +[2025-05-15 01:23:22,434] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 276.79 | bwd_microstep: 515.98 | bwd_inner_microstep: 515.94 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.28 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-15 01:23:23,343] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 442.21 | bwd_microstep: 436.26 | bwd_inner_microstep: 436.12 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-15 01:23:24,329] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 348.42 | bwd_microstep: 618.46 | bwd_inner_microstep: 618.42 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-15 01:23:25,136] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 357.53 | bwd_microstep: 419.23 | bwd_inner_microstep: 419.08 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.13 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-15 01:23:26,131] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 357.54 | bwd_microstep: 618.77 | bwd_inner_microstep: 618.75 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-15 01:23:26,910] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 346.82 | bwd_microstep: 408.73 | bwd_inner_microstep: 408.71 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.46 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-15 01:23:27,890] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 400.06 | bwd_microstep: 554.99 | bwd_inner_microstep: 554.97 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-15 01:23:29,122] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.01 | optimizer_gradients: 1.67 | optimizer_step: 18.01 +[2025-05-15 01:23:29,122] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 230.01 | bwd_microstep: 958.03 | bwd_inner_microstep: 542.68 | bwd_allreduce_microstep: 415.31 | step_microstep: 25.83 +[2025-05-15 01:23:29,123] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2759.36 | bwd: 4530.47 | bwd_inner: 4114.72 | bwd_allreduce: 415.48 | step: 36.53 + 86%|████████▋ | 482/558 [55:24<09:12, 7.27s/it] {'loss': 5.9859, 'grad_norm': 29.09864044189453, 'learning_rate': 4.790841492114257e-17, 'epoch': 0.26} + 86%|████████▋ | 482/558 [55:24<09:12, 7.27s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1894 +[2025-05-15 01:23:29,981] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 228.34 | bwd_microstep: 603.84 | bwd_inner_microstep: 603.77 | bwd_allreduce_microstep: 0.02 | step_microstep: 2.44 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1889 +[2025-05-15 01:23:30,803] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 405.30 | bwd_microstep: 382.47 | bwd_inner_microstep: 382.39 | bwd_allreduce_microstep: 0.02 | step_microstep: 1.89 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 334 +[2025-05-15 01:23:31,041] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 92.01 | bwd_microstep: 122.57 | bwd_inner_microstep: 122.26 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-15 01:23:32,053] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 446.46 | bwd_microstep: 537.70 | bwd_inner_microstep: 537.66 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.31 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1364 +[2025-05-15 01:23:32,618] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 166.02 | bwd_microstep: 378.84 | bwd_inner_microstep: 378.82 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-15 01:23:33,622] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 445.93 | bwd_microstep: 527.57 | bwd_inner_microstep: 527.54 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.23 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-15 01:23:34,405] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 265.79 | bwd_microstep: 497.69 | bwd_inner_microstep: 497.63 | bwd_allreduce_microstep: 0.02 | step_microstep: 2.52 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-15 01:23:35,457] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.07 | optimizer_gradients: 2.00 | optimizer_step: 19.43 +[2025-05-15 01:23:35,458] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 442.14 | bwd_microstep: 551.33 | bwd_inner_microstep: 491.89 | bwd_allreduce_microstep: 59.34 | step_microstep: 27.28 +[2025-05-15 01:23:35,459] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2492.00 | bwd: 3602.19 | bwd_inner: 3542.00 | bwd_allreduce: 59.46 | step: 36.90 + 87%|████████▋ | 483/558 [55:30<08:44, 6.99s/it] {'loss': 4.1813, 'grad_norm': 16.729984283447266, 'learning_rate': 4.667582689560113e-17, 'epoch': 0.26} + 87%|████████▋ | 483/558 [55:30<08:44, 6.99s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1979 +[2025-05-15 01:23:36,540] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 394.33 | bwd_microstep: 660.57 | bwd_inner_microstep: 660.37 | bwd_allreduce_microstep: 0.18 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1897 +[2025-05-15 01:23:37,323] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 357.40 | bwd_microstep: 406.54 | bwd_inner_microstep: 406.51 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.85 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-15 01:23:38,349] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 410.77 | bwd_microstep: 589.88 | bwd_inner_microstep: 589.85 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-15 01:23:39,165] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 249.94 | bwd_microstep: 543.97 | bwd_inner_microstep: 543.90 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.49 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-15 01:23:40,078] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 420.92 | bwd_microstep: 459.23 | bwd_inner_microstep: 459.08 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-15 01:23:41,035] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 327.15 | bwd_microstep: 610.49 | bwd_inner_microstep: 610.43 | bwd_allreduce_microstep: 0.02 | step_microstep: 2.55 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-15 01:23:41,828] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 368.55 | bwd_microstep: 394.06 | bwd_inner_microstep: 393.86 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-15 01:23:43,074] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.09 | optimizer_step: 15.97 +[2025-05-15 01:23:43,074] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 392.02 | bwd_microstep: 810.01 | bwd_inner_microstep: 621.38 | bwd_allreduce_microstep: 188.58 | step_microstep: 24.62 +[2025-05-15 01:23:43,075] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2921.06 | bwd: 4474.75 | bwd_inner: 4285.38 | bwd_allreduce: 188.88 | step: 33.95 + 87%|████████▋ | 484/558 [55:38<08:51, 7.18s/it] {'loss': 7.661, 'grad_norm': 29.75860023498535, 'learning_rate': 4.5458525539441025e-17, 'epoch': 0.26} + 87%|████████▋ | 484/558 [55:38<08:51, 7.18s/it]dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 923 +[2025-05-15 01:23:43,533] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 141.32 | bwd_microstep: 295.86 | bwd_inner_microstep: 295.83 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1906 +[2025-05-15 01:23:44,493] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 447.22 | bwd_microstep: 480.37 | bwd_inner_microstep: 480.23 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1913 +[2025-05-15 01:23:45,450] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 315.00 | bwd_microstep: 622.68 | bwd_inner_microstep: 622.66 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-15 01:23:46,264] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 332.99 | bwd_microstep: 448.55 | bwd_inner_microstep: 448.35 | bwd_allreduce_microstep: 0.18 | step_microstep: 0.03 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-15 01:23:47,282] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 446.50 | bwd_microstep: 544.34 | bwd_inner_microstep: 544.10 | bwd_allreduce_microstep: 0.20 | step_microstep: 0.22 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1353 +[2025-05-15 01:23:47,849] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 166.55 | bwd_microstep: 381.87 | bwd_inner_microstep: 381.56 | bwd_allreduce_microstep: 0.27 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-15 01:23:48,859] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 441.42 | bwd_microstep: 535.85 | bwd_inner_microstep: 535.71 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.09 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1096 +[2025-05-15 01:23:49,840] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.01 | optimizer_gradients: 2.08 | optimizer_step: 18.50 +[2025-05-15 01:23:49,841] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 119.14 | bwd_microstep: 818.44 | bwd_inner_microstep: 324.08 | bwd_allreduce_microstep: 494.33 | step_microstep: 26.93 +[2025-05-15 01:23:49,841] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2410.09 | bwd: 4127.99 | bwd_inner: 3632.55 | bwd_allreduce: 494.92 | step: 34.47 + 87%|████████▋ | 485/558 [55:45<08:35, 7.06s/it] {'loss': 4.8706, 'grad_norm': 23.048986434936523, 'learning_rate': 4.4256551901616705e-17, 'epoch': 0.26} + 87%|████████▋ | 485/558 [55:45<08:35, 7.06s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1950 +[2025-05-15 01:23:50,682] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 306.53 | bwd_microstep: 504.47 | bwd_inner_microstep: 504.45 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.46 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1923 +[2025-05-15 01:23:51,637] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 459.09 | bwd_microstep: 462.95 | bwd_inner_microstep: 462.81 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1917 +[2025-05-15 01:23:52,638] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 356.29 | bwd_microstep: 624.92 | bwd_inner_microstep: 624.85 | bwd_allreduce_microstep: 0.02 | step_microstep: 2.37 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1886 +[2025-05-15 01:23:53,401] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 351.30 | bwd_microstep: 379.95 | bwd_inner_microstep: 379.91 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1889 +[2025-05-15 01:23:54,436] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 397.83 | bwd_microstep: 613.13 | bwd_inner_microstep: 612.91 | bwd_allreduce_microstep: 0.20 | step_microstep: 0.23 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-15 01:23:55,201] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 354.74 | bwd_microstep: 387.89 | bwd_inner_microstep: 387.83 | bwd_allreduce_microstep: 0.02 | step_microstep: 1.88 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-15 01:23:56,232] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 416.01 | bwd_microstep: 588.51 | bwd_inner_microstep: 588.45 | bwd_allreduce_microstep: 0.02 | step_microstep: 2.28 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-15 01:23:57,475] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 1.94 | optimizer_step: 18.67 +[2025-05-15 01:23:57,476] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 230.08 | bwd_microstep: 964.61 | bwd_inner_microstep: 575.80 | bwd_allreduce_microstep: 388.77 | step_microstep: 27.53 +[2025-05-15 01:23:57,476] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2871.85 | bwd: 4526.44 | bwd_inner: 4137.06 | bwd_allreduce: 389.08 | step: 37.71 + 87%|████████▋ | 486/558 [55:53<08:40, 7.23s/it] {'loss': 4.3463, 'grad_norm': 9.3695650100708, 'learning_rate': 4.3069946514212536e-17, 'epoch': 0.26} + 87%|████████▋ | 486/558 [55:53<08:40, 7.23s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 355 +[2025-05-15 01:23:57,718] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 90.53 | bwd_microstep: 126.61 | bwd_inner_microstep: 126.46 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-15 01:23:58,625] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 285.14 | bwd_microstep: 603.04 | bwd_inner_microstep: 602.99 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.37 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 844 +[2025-05-15 01:23:59,109] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 203.94 | bwd_microstep: 247.79 | bwd_inner_microstep: 247.74 | bwd_allreduce_microstep: 0.02 | step_microstep: 2.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-15 01:23:59,885] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 285.02 | bwd_microstep: 471.47 | bwd_inner_microstep: 471.43 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-15 01:24:00,870] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 441.69 | bwd_microstep: 511.16 | bwd_inner_microstep: 511.02 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-15 01:24:01,744] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 251.29 | bwd_microstep: 601.12 | bwd_inner_microstep: 601.09 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2133 +[2025-05-15 01:24:02,696] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 425.46 | bwd_microstep: 494.11 | bwd_inner_microstep: 494.09 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-15 01:24:03,848] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 1.69 | optimizer_step: 14.61 +[2025-05-15 01:24:03,850] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 442.70 | bwd_microstep: 660.57 | bwd_inner_microstep: 466.40 | bwd_allreduce_microstep: 194.11 | step_microstep: 23.14 +[2025-05-15 01:24:03,851] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2425.72 | bwd: 3715.89 | bwd_inner: 3521.29 | bwd_allreduce: 194.26 | step: 32.67 + 87%|████████▋ | 487/558 [55:59<08:15, 6.97s/it] {'loss': 6.3852, 'grad_norm': 25.854602813720703, 'learning_rate': 4.1898749391075744e-17, 'epoch': 0.26} + 87%|████████▋ | 487/558 [55:59<08:15, 6.97s/it]dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 880 +[2025-05-15 01:24:04,422] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 227.24 | bwd_microstep: 304.36 | bwd_inner_microstep: 304.08 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.24 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-15 01:24:05,221] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 323.24 | bwd_microstep: 456.58 | bwd_inner_microstep: 456.54 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-15 01:24:06,163] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 438.75 | bwd_microstep: 471.96 | bwd_inner_microstep: 471.83 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 336 +[2025-05-15 01:24:06,391] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 80.31 | bwd_microstep: 132.59 | bwd_inner_microstep: 132.54 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.79 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-15 01:24:07,397] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 403.92 | bwd_microstep: 577.46 | bwd_inner_microstep: 577.32 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-15 01:24:08,272] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 249.53 | bwd_microstep: 600.97 | bwd_inner_microstep: 600.93 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-15 01:24:09,099] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 388.27 | bwd_microstep: 406.34 | bwd_inner_microstep: 406.26 | bwd_allreduce_microstep: 0.02 | step_microstep: 1.91 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-15 01:24:10,288] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.17 | optimizer_step: 18.41 +[2025-05-15 01:24:10,289] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 402.51 | bwd_microstep: 736.44 | bwd_inner_microstep: 585.16 | bwd_allreduce_microstep: 151.22 | step_microstep: 27.33 +[2025-05-15 01:24:10,289] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2513.75 | bwd: 3686.72 | bwd_inner: 3534.69 | bwd_allreduce: 151.63 | step: 34.02 + 87%|████████▋ | 488/558 [56:05<07:56, 6.81s/it] {'loss': 5.063, 'grad_norm': 21.1917781829834, 'learning_rate': 4.074300002646742e-17, 'epoch': 0.26} + 87%|████████▋ | 488/558 [56:05<07:56, 6.81s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 358 +[2025-05-15 01:24:10,541] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 86.38 | bwd_microstep: 143.13 | bwd_inner_microstep: 140.77 | bwd_allreduce_microstep: 0.02 | step_microstep: 1.78 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-15 01:24:11,537] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 410.15 | bwd_microstep: 560.40 | bwd_inner_microstep: 560.27 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-15 01:24:12,426] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 263.50 | bwd_microstep: 604.81 | bwd_inner_microstep: 604.77 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-15 01:24:13,250] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 383.53 | bwd_microstep: 406.44 | bwd_inner_microstep: 406.39 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.86 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-15 01:24:14,248] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 406.10 | bwd_microstep: 567.02 | bwd_inner_microstep: 566.88 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.10 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1344 +[2025-05-15 01:24:14,857] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 155.06 | bwd_microstep: 431.42 | bwd_inner_microstep: 431.40 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 829 +[2025-05-15 01:24:15,354] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 173.66 | bwd_microstep: 295.04 | bwd_inner_microstep: 295.01 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.21 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1956 +[2025-05-15 01:24:16,673] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 1.98 | optimizer_step: 24.46 +[2025-05-15 01:24:16,673] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 294.99 | bwd_microstep: 971.71 | bwd_inner_microstep: 559.22 | bwd_allreduce_microstep: 412.43 | step_microstep: 31.65 +[2025-05-15 01:24:16,674] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2173.33 | bwd: 3980.24 | bwd_inner: 3564.74 | bwd_allreduce: 412.60 | step: 40.40 + 88%|████████▊ | 489/558 [56:12<07:41, 6.68s/it] {'loss': 3.841, 'grad_norm': 23.750835418701172, 'learning_rate': 3.960273739373044e-17, 'epoch': 0.26} + 88%|████████▊ | 489/558 [56:12<07:41, 6.68s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1936 +[2025-05-15 01:24:17,646] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 311.32 | bwd_microstep: 634.49 | bwd_inner_microstep: 634.46 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-15 01:24:18,452] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 363.52 | bwd_microstep: 410.28 | bwd_inner_microstep: 410.23 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.88 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-15 01:24:19,483] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 409.79 | bwd_microstep: 595.12 | bwd_inner_microstep: 595.09 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.30 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 330 +[2025-05-15 01:24:19,717] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 77.96 | bwd_microstep: 139.36 | bwd_inner_microstep: 139.29 | bwd_allreduce_microstep: 0.02 | step_microstep: 1.79 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-15 01:24:20,756] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 418.74 | bwd_microstep: 592.86 | bwd_inner_microstep: 592.80 | bwd_allreduce_microstep: 0.02 | step_microstep: 2.32 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-15 01:24:21,587] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 225.46 | bwd_microstep: 583.08 | bwd_inner_microstep: 583.05 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1927 +[2025-05-15 01:24:22,473] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 422.17 | bwd_microstep: 430.00 | bwd_inner_microstep: 429.95 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.87 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1890 +[2025-05-15 01:24:23,753] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.01 | optimizer_gradients: 2.06 | optimizer_step: 18.40 +[2025-05-15 01:24:23,754] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 422.29 | bwd_microstep: 805.69 | bwd_inner_microstep: 589.26 | bwd_allreduce_microstep: 216.40 | step_microstep: 27.69 +[2025-05-15 01:24:23,755] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2651.24 | bwd: 4190.87 | bwd_inner: 3974.13 | bwd_allreduce: 216.47 | step: 42.55 + 88%|████████▊ | 490/558 [56:19<07:42, 6.80s/it] {'loss': 3.7258, 'grad_norm': 28.632556915283203, 'learning_rate': 3.847799994397527e-17, 'epoch': 0.26} + 88%|████████▊ | 490/558 [56:19<07:42, 6.80s/it]dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1390 +[2025-05-15 01:24:24,442] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 264.76 | bwd_microstep: 396.30 | bwd_inner_microstep: 396.25 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.31 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1889 +[2025-05-15 01:24:25,255] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 288.82 | bwd_microstep: 499.54 | bwd_inner_microstep: 499.50 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.43 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-15 01:24:26,258] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 441.46 | bwd_microstep: 529.58 | bwd_inner_microstep: 529.54 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.37 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-15 01:24:27,132] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 344.70 | bwd_microstep: 509.64 | bwd_inner_microstep: 508.66 | bwd_allreduce_microstep: 0.95 | step_microstep: 0.24 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-15 01:24:28,013] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 349.71 | bwd_microstep: 510.93 | bwd_inner_microstep: 510.86 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.38 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-15 01:24:28,802] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 272.46 | bwd_microstep: 496.43 | bwd_inner_microstep: 496.37 | bwd_allreduce_microstep: 0.02 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-15 01:24:29,805] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 441.37 | bwd_microstep: 526.28 | bwd_inner_microstep: 526.25 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.31 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-15 01:24:31,181] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.01 | optimizer_gradients: 1.66 | optimizer_step: 15.40 +[2025-05-15 01:24:31,181] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 355.11 | bwd_microstep: 972.94 | bwd_inner_microstep: 382.24 | bwd_allreduce_microstep: 590.66 | step_microstep: 24.38 +[2025-05-15 01:24:31,182] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2758.38 | bwd: 4441.64 | bwd_inner: 3849.68 | bwd_allreduce: 591.69 | step: 34.78 + 88%|████████▊ | 491/558 [56:26<07:48, 6.99s/it] {'loss': 5.5564, 'grad_norm': 28.427410125732422, 'learning_rate': 3.7368825604783387e-17, 'epoch': 0.26} + 88%|████████▊ | 491/558 [56:26<07:48, 6.99s/it]dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 878 +[2025-05-15 01:24:31,633] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 170.84 | bwd_microstep: 254.47 | bwd_inner_microstep: 254.40 | bwd_allreduce_microstep: 0.02 | step_microstep: 2.28 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1892 +[2025-05-15 01:24:32,462] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 254.17 | bwd_microstep: 549.17 | bwd_inner_microstep: 549.11 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.55 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-15 01:24:33,343] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 425.71 | bwd_microstep: 422.79 | bwd_inner_microstep: 422.64 | bwd_allreduce_microstep: 0.05 | step_microstep: 0.09 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1348 +[2025-05-15 01:24:34,094] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 279.35 | bwd_microstep: 451.72 | bwd_inner_microstep: 451.68 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.54 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-15 01:24:34,911] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 384.57 | bwd_microstep: 398.87 | bwd_inner_microstep: 398.82 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.86 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-15 01:24:35,929] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 411.22 | bwd_microstep: 582.12 | bwd_inner_microstep: 581.12 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.22 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-15 01:24:36,732] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 242.28 | bwd_microstep: 539.66 | bwd_inner_microstep: 539.61 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1993 +[2025-05-15 01:24:38,275] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.01 | optimizer_gradients: 2.13 | optimizer_step: 18.78 +[2025-05-15 01:24:38,276] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 450.43 | bwd_microstep: 1031.22 | bwd_inner_microstep: 441.97 | bwd_allreduce_microstep: 589.22 | step_microstep: 28.65 +[2025-05-15 01:24:38,277] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2618.57 | bwd: 4230.01 | bwd_inner: 3639.37 | bwd_allreduce: 589.35 | step: 40.55 + 88%|████████▊ | 492/558 [56:33<07:43, 7.02s/it] {'loss': 5.5458, 'grad_norm': 27.23273277282715, 'learning_rate': 3.627525177892849e-17, 'epoch': 0.26} + 88%|████████▊ | 492/558 [56:33<07:43, 7.02s/it]dynamic ViT batch size: 6, images per sample: 6.0, dynamic token length: 1631 +[2025-05-15 01:24:38,999] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 182.04 | bwd_microstep: 514.32 | bwd_inner_microstep: 514.28 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.56 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-15 01:24:39,844] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 424.81 | bwd_microstep: 386.77 | bwd_inner_microstep: 386.51 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.56 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-15 01:24:40,872] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 388.94 | bwd_microstep: 611.94 | bwd_inner_microstep: 611.67 | bwd_allreduce_microstep: 0.23 | step_microstep: 0.24 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-15 01:24:41,684] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 244.90 | bwd_microstep: 544.25 | bwd_inner_microstep: 544.23 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-15 01:24:42,538] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 429.04 | bwd_microstep: 394.72 | bwd_inner_microstep: 394.28 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.47 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 333 +[2025-05-15 01:24:42,784] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.68 | bwd_microstep: 132.69 | bwd_inner_microstep: 132.66 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.78 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 332 +[2025-05-15 01:24:43,064] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 103.88 | bwd_microstep: 142.91 | bwd_inner_microstep: 142.87 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.45 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-15 01:24:44,469] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.08 | optimizer_step: 18.82 +[2025-05-15 01:24:44,469] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 405.56 | bwd_microstep: 940.08 | bwd_inner_microstep: 389.43 | bwd_allreduce_microstep: 550.61 | step_microstep: 28.15 +[2025-05-15 01:24:44,470] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2272.87 | bwd: 3667.68 | bwd_inner: 3115.92 | bwd_allreduce: 551.13 | step: 39.10 + 88%|████████▊ | 493/558 [56:40<07:20, 6.77s/it] {'loss': 6.7744, 'grad_norm': 20.791275024414062, 'learning_rate': 3.519731534311471e-17, 'epoch': 0.27} + 88%|████████▊ | 493/558 [56:40<07:20, 6.77s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1895 +[2025-05-15 01:24:45,328] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 234.54 | bwd_microstep: 596.42 | bwd_inner_microstep: 596.39 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.33 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-15 01:24:46,163] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 392.78 | bwd_microstep: 408.26 | bwd_inner_microstep: 408.23 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.80 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-15 01:24:47,181] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 406.29 | bwd_microstep: 588.45 | bwd_inner_microstep: 588.26 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-15 01:24:48,052] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 247.47 | bwd_microstep: 600.29 | bwd_inner_microstep: 600.26 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-15 01:24:48,986] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 401.18 | bwd_microstep: 500.56 | bwd_inner_microstep: 500.52 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.51 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-15 01:24:49,817] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 215.44 | bwd_microstep: 592.61 | bwd_inner_microstep: 592.57 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.28 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-15 01:24:50,656] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 405.39 | bwd_microstep: 397.34 | bwd_inner_microstep: 397.28 | bwd_allreduce_microstep: 0.02 | step_microstep: 1.83 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-15 01:24:51,922] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.01 | optimizer_gradients: 1.79 | optimizer_step: 16.09 +[2025-05-15 01:24:51,923] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 403.77 | bwd_microstep: 812.67 | bwd_inner_microstep: 601.89 | bwd_allreduce_microstep: 210.74 | step_microstep: 25.31 +[2025-05-15 01:24:51,923] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2706.82 | bwd: 4496.59 | bwd_inner: 4285.39 | bwd_allreduce: 210.80 | step: 36.26 + 89%|████████▊ | 494/558 [56:47<07:26, 6.98s/it] {'loss': 6.0709, 'grad_norm': 28.551288604736328, 'learning_rate': 3.4135052646734115e-17, 'epoch': 0.27} + 89%|████████▊ | 494/558 [56:47<07:26, 6.98s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-15 01:24:52,729] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 329.65 | bwd_microstep: 448.96 | bwd_inner_microstep: 448.57 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1887 +[2025-05-15 01:24:53,745] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 447.08 | bwd_microstep: 540.51 | bwd_inner_microstep: 540.09 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.22 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-15 01:24:54,517] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 357.89 | bwd_microstep: 392.46 | bwd_inner_microstep: 392.40 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.86 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-15 01:24:55,547] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 411.39 | bwd_microstep: 591.20 | bwd_inner_microstep: 591.13 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.52 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-15 01:24:56,301] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 347.64 | bwd_microstep: 386.64 | bwd_inner_microstep: 386.62 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.93 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-15 01:24:57,330] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 399.03 | bwd_microstep: 605.34 | bwd_inner_microstep: 605.30 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.21 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-15 01:24:58,090] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 349.18 | bwd_microstep: 389.40 | bwd_inner_microstep: 389.15 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-15 01:24:59,382] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 1.60 | optimizer_step: 16.00 +[2025-05-15 01:24:59,382] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 393.94 | bwd_microstep: 852.47 | bwd_inner_microstep: 623.91 | bwd_allreduce_microstep: 228.52 | step_microstep: 24.03 +[2025-05-15 01:24:59,383] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 3035.79 | bwd: 4206.98 | bwd_inner: 3976.88 | bwd_allreduce: 228.96 | step: 28.88 + 89%|████████▊ | 495/558 [56:54<07:28, 7.12s/it] {'loss': 3.9601, 'grad_norm': 13.469680786132812, 'learning_rate': 3.308849951063953e-17, 'epoch': 0.27} + 89%|████████▊ | 495/558 [56:54<07:28, 7.12s/it]dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1382 +[2025-05-15 01:24:59,955] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 236.86 | bwd_microstep: 307.95 | bwd_inner_microstep: 307.91 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.87 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1883 +[2025-05-15 01:25:00,974] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 404.98 | bwd_microstep: 590.57 | bwd_inner_microstep: 590.37 | bwd_allreduce_microstep: 0.18 | step_microstep: 0.17 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1356 +[2025-05-15 01:25:01,542] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 199.38 | bwd_microstep: 350.60 | bwd_inner_microstep: 350.58 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.75 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-15 01:25:02,554] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 425.33 | bwd_microstep: 562.75 | bwd_inner_microstep: 562.37 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.36 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 323 +[2025-05-15 01:25:02,795] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.72 | bwd_microstep: 128.70 | bwd_inner_microstep: 128.63 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.34 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 838 +[2025-05-15 01:25:03,096] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 116.98 | bwd_microstep: 163.52 | bwd_inner_microstep: 163.48 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.83 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2125 +[2025-05-15 01:25:04,223] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 431.55 | bwd_microstep: 670.70 | bwd_inner_microstep: 670.49 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2031 +[2025-05-15 01:25:05,545] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.01 | optimizer_gradients: 2.10 | optimizer_step: 19.09 +[2025-05-15 01:25:05,546] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 263.83 | bwd_microstep: 1010.52 | bwd_inner_microstep: 611.80 | bwd_allreduce_microstep: 398.69 | step_microstep: 28.61 +[2025-05-15 01:25:05,547] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2173.62 | bwd: 3785.34 | bwd_inner: 3385.63 | bwd_allreduce: 399.12 | step: 34.69 + 89%|████████▉ | 496/558 [57:01<07:03, 6.83s/it] {'loss': 3.6443, 'grad_norm': 16.197893142700195, 'learning_rate': 3.205769122593766e-17, 'epoch': 0.27} + 89%|████████▉ | 496/558 [57:01<07:03, 6.83s/it]dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 902 +[2025-05-15 01:25:06,027] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 194.59 | bwd_microstep: 262.75 | bwd_inner_microstep: 262.45 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1913 +[2025-05-15 01:25:06,907] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 247.57 | bwd_microstep: 610.60 | bwd_inner_microstep: 610.56 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.28 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1890 +[2025-05-15 01:25:07,718] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 387.93 | bwd_microstep: 387.52 | bwd_inner_microstep: 387.27 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.48 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1883 +[2025-05-15 01:25:08,757] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 398.08 | bwd_microstep: 620.57 | bwd_inner_microstep: 620.16 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.24 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-15 01:25:09,551] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 320.04 | bwd_microstep: 454.46 | bwd_inner_microstep: 454.16 | bwd_allreduce_microstep: 0.26 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-15 01:25:10,571] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 442.42 | bwd_microstep: 551.70 | bwd_inner_microstep: 551.65 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-15 01:25:11,430] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 241.28 | bwd_microstep: 595.45 | bwd_inner_microstep: 595.41 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.45 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2004 +[2025-05-15 01:25:12,608] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 1.65 | optimizer_step: 13.01 +[2025-05-15 01:25:12,608] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 419.48 | bwd_microstep: 706.68 | bwd_inner_microstep: 554.77 | bwd_allreduce_microstep: 151.70 | step_microstep: 19.82 +[2025-05-15 01:25:12,609] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2651.35 | bwd: 4189.75 | bwd_inner: 4036.47 | bwd_allreduce: 152.32 | step: 25.66 + 89%|████████▉ | 497/558 [57:08<07:01, 6.90s/it] {'loss': 2.6142, 'grad_norm': 10.20451545715332, 'learning_rate': 3.1042662552798975e-17, 'epoch': 0.27} + 89%|████████▉ | 497/558 [57:08<07:01, 6.90s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1883 +[2025-05-15 01:25:13,725] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 408.64 | bwd_microstep: 603.95 | bwd_inner_microstep: 603.88 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.27 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-15 01:25:14,489] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 346.46 | bwd_microstep: 396.86 | bwd_inner_microstep: 396.65 | bwd_allreduce_microstep: 0.19 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-15 01:25:15,535] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 393.23 | bwd_microstep: 629.08 | bwd_inner_microstep: 629.02 | bwd_allreduce_microstep: 0.02 | step_microstep: 2.33 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 330 +[2025-05-15 01:25:15,778] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 91.45 | bwd_microstep: 130.01 | bwd_inner_microstep: 129.96 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.49 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1353 +[2025-05-15 01:25:16,356] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 263.26 | bwd_microstep: 293.53 | bwd_inner_microstep: 293.38 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-15 01:25:17,352] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 359.47 | bwd_microstep: 617.11 | bwd_inner_microstep: 617.08 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.50 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 835 +[2025-05-15 01:25:17,783] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 179.88 | bwd_microstep: 223.50 | bwd_inner_microstep: 223.36 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 909 +[2025-05-15 01:25:18,718] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 1.72 | optimizer_step: 13.24 +[2025-05-15 01:25:18,719] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 108.48 | bwd_microstep: 789.94 | bwd_inner_microstep: 279.50 | bwd_allreduce_microstep: 510.42 | step_microstep: 21.20 +[2025-05-15 01:25:18,720] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2150.84 | bwd: 3684.01 | bwd_inner: 3172.90 | bwd_allreduce: 510.77 | step: 29.17 + 89%|████████▉ | 498/558 [57:14<06:39, 6.67s/it] {'loss': 7.2948, 'grad_norm': 21.883508682250977, 'learning_rate': 3.0043447719285027e-17, 'epoch': 0.27} + 89%|████████▉ | 498/558 [57:14<06:39, 6.67s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 362 +[2025-05-15 01:25:18,953] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 81.46 | bwd_microstep: 129.22 | bwd_inner_microstep: 129.20 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.64 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1894 +[2025-05-15 01:25:19,989] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 395.72 | bwd_microstep: 613.84 | bwd_inner_microstep: 613.54 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.30 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1890 +[2025-05-15 01:25:20,777] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 361.89 | bwd_microstep: 406.06 | bwd_inner_microstep: 405.79 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.29 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-15 01:25:21,822] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 396.41 | bwd_microstep: 626.93 | bwd_inner_microstep: 626.45 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.23 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-15 01:25:22,623] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 322.16 | bwd_microstep: 457.70 | bwd_inner_microstep: 457.46 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.19 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 340 +[2025-05-15 01:25:22,914] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 105.92 | bwd_microstep: 152.57 | bwd_inner_microstep: 152.49 | bwd_allreduce_microstep: 0.02 | step_microstep: 2.37 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-15 01:25:23,733] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 395.43 | bwd_microstep: 391.12 | bwd_inner_microstep: 390.69 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.21 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-15 01:25:24,996] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 1.70 | optimizer_step: 13.95 +[2025-05-15 01:25:24,996] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 393.23 | bwd_microstep: 828.47 | bwd_inner_microstep: 611.96 | bwd_allreduce_microstep: 216.46 | step_microstep: 20.55 +[2025-05-15 01:25:24,997] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2452.21 | bwd: 3606.11 | bwd_inner: 3387.59 | bwd_allreduce: 217.05 | step: 25.78 + 89%|████████▉ | 499/558 [57:20<06:26, 6.55s/it] {'loss': 3.8035, 'grad_norm': 13.45337200164795, 'learning_rate': 2.9060080420194646e-17, 'epoch': 0.27} + 89%|████████▉ | 499/558 [57:20<06:26, 6.55s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1912 +[2025-05-15 01:25:25,947] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 310.61 | bwd_microstep: 616.93 | bwd_inner_microstep: 616.88 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.57 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1390 +[2025-05-15 01:25:26,654] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 282.43 | bwd_microstep: 394.28 | bwd_inner_microstep: 393.98 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.23 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-15 01:25:27,444] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 279.47 | bwd_microstep: 488.59 | bwd_inner_microstep: 488.55 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-15 01:25:28,439] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 444.51 | bwd_microstep: 518.50 | bwd_inner_microstep: 518.46 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-15 01:25:29,228] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 267.35 | bwd_microstep: 497.93 | bwd_inner_microstep: 497.89 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.54 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-15 01:25:30,201] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 439.45 | bwd_microstep: 501.35 | bwd_inner_microstep: 501.05 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-15 01:25:31,102] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 271.42 | bwd_microstep: 608.70 | bwd_inner_microstep: 608.66 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-15 01:25:32,464] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 1.66 | optimizer_step: 12.78 +[2025-05-15 01:25:32,465] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 381.67 | bwd_microstep: 927.00 | bwd_inner_microstep: 377.24 | bwd_allreduce_microstep: 549.70 | step_microstep: 19.64 +[2025-05-15 01:25:32,465] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2676.91 | bwd: 4553.29 | bwd_inner: 4002.76 | bwd_allreduce: 549.90 | step: 30.01 + 90%|████████▉ | 500/558 [57:27<06:35, 6.82s/it] {'loss': 5.8438, 'grad_norm': 12.02957534790039, 'learning_rate': 2.8092593815927496e-17, 'epoch': 0.27} + 90%|████████▉ | 500/558 [57:27<06:35, 6.82s/it][INFO|trainer.py:3503] 2025-05-15 01:25:35,839 >> Saving model checkpoint to work_dirs/internvl_chat_v2_5/mmvet/checkpoint-500 +[INFO|configuration_utils.py:472] 2025-05-15 01:25:35,842 >> Configuration saved in work_dirs/internvl_chat_v2_5/mmvet/checkpoint-500/config.json +[INFO|configuration_utils.py:807] 2025-05-15 01:25:35,843 >> Configuration saved in work_dirs/internvl_chat_v2_5/mmvet/checkpoint-500/generation_config.json +[INFO|modeling_utils.py:2755] 2025-05-15 01:25:41,036 >> Model weights saved in work_dirs/internvl_chat_v2_5/mmvet/checkpoint-500/model.safetensors +[INFO|tokenization_utils_base.py:2702] 2025-05-15 01:25:41,037 >> tokenizer config file saved in work_dirs/internvl_chat_v2_5/mmvet/checkpoint-500/tokenizer_config.json +[INFO|tokenization_utils_base.py:2711] 2025-05-15 01:25:41,038 >> Special tokens file saved in work_dirs/internvl_chat_v2_5/mmvet/checkpoint-500/special_tokens_map.json +[INFO|tokenization_utils_base.py:2762] 2025-05-15 01:25:41,038 >> added tokens file saved in work_dirs/internvl_chat_v2_5/mmvet/checkpoint-500/added_tokens.json +[2025-05-15 01:25:41,134] [INFO] [logging.py:96:log_dist] [Rank 0] [Torch] Checkpoint global_step500 is about to be saved! +[2025-05-15 01:25:41,159] [INFO] [logging.py:96:log_dist] [Rank 0] Saving model checkpoint: work_dirs/internvl_chat_v2_5/mmvet/checkpoint-500/global_step500/mp_rank_00_model_states.pt +[2025-05-15 01:25:41,159] [INFO] [torch_checkpoint_engine.py:21:save] [Torch] Saving work_dirs/internvl_chat_v2_5/mmvet/checkpoint-500/global_step500/mp_rank_00_model_states.pt... +[2025-05-15 01:25:45,760] [INFO] [torch_checkpoint_engine.py:23:save] [Torch] Saved work_dirs/internvl_chat_v2_5/mmvet/checkpoint-500/global_step500/mp_rank_00_model_states.pt. +[2025-05-15 01:25:45,762] [INFO] [torch_checkpoint_engine.py:21:save] [Torch] Saving work_dirs/internvl_chat_v2_5/mmvet/checkpoint-500/global_step500/bf16_zero_pp_rank_0_mp_rank_00_optim_states.pt... +[2025-05-15 01:25:45,919] [INFO] [torch_checkpoint_engine.py:23:save] [Torch] Saved work_dirs/internvl_chat_v2_5/mmvet/checkpoint-500/global_step500/bf16_zero_pp_rank_0_mp_rank_00_optim_states.pt. +[2025-05-15 01:25:45,919] [INFO] [engine.py:3536:_save_zero_checkpoint] zero checkpoint saved work_dirs/internvl_chat_v2_5/mmvet/checkpoint-500/global_step500/bf16_zero_pp_rank_0_mp_rank_00_optim_states.pt +[2025-05-15 01:25:45,919] [INFO] [torch_checkpoint_engine.py:33:commit] [Torch] Checkpoint global_step500 is ready now! +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 873 +[2025-05-15 01:25:46,499] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 224.19 | bwd_microstep: 320.89 | bwd_inner_microstep: 320.84 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1899 +[2025-05-15 01:25:47,310] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 353.63 | bwd_microstep: 419.45 | bwd_inner_microstep: 419.41 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.87 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-15 01:25:48,318] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 413.61 | bwd_microstep: 570.76 | bwd_inner_microstep: 570.32 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.76 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-15 01:25:49,102] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 313.87 | bwd_microstep: 448.56 | bwd_inner_microstep: 448.35 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.37 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-15 01:25:50,113] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 437.85 | bwd_microstep: 545.44 | bwd_inner_microstep: 545.40 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-15 01:25:50,902] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 320.02 | bwd_microstep: 449.12 | bwd_inner_microstep: 448.89 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.22 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1346 +[2025-05-15 01:25:51,688] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 330.23 | bwd_microstep: 425.04 | bwd_inner_microstep: 424.99 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.25 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-15 01:25:53,000] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.01 | optimizer_gradients: 2.12 | optimizer_step: 18.74 +[2025-05-15 01:25:53,001] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 349.25 | bwd_microstep: 915.15 | bwd_inner_microstep: 406.23 | bwd_allreduce_microstep: 508.90 | step_microstep: 27.75 +[2025-05-15 01:25:53,002] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2742.66 | bwd: 4094.39 | bwd_inner: 3584.45 | bwd_allreduce: 508.96 | step: 33.58 + 90%|████████▉ | 501/558 [57:48<10:23, 10.94s/it] {'loss': 6.494, 'grad_norm': 21.226787567138672, 'learning_rate': 2.7141020531365915e-17, 'epoch': 0.27} + 90%|████████▉ | 501/558 [57:48<10:23, 10.94s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1890 +[2025-05-15 01:25:53,805] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 324.99 | bwd_microstep: 451.94 | bwd_inner_microstep: 451.72 | bwd_allreduce_microstep: 0.18 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-15 01:25:54,823] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 442.23 | bwd_microstep: 545.52 | bwd_inner_microstep: 545.27 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-15 01:25:55,671] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 231.52 | bwd_microstep: 593.52 | bwd_inner_microstep: 593.49 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.33 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-15 01:25:56,500] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 402.86 | bwd_microstep: 392.24 | bwd_inner_microstep: 391.86 | bwd_allreduce_microstep: 0.35 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-15 01:25:57,546] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 393.30 | bwd_microstep: 629.16 | bwd_inner_microstep: 629.13 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.02 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 836 +[2025-05-15 01:25:57,970] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 172.48 | bwd_microstep: 231.15 | bwd_inner_microstep: 231.09 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.27 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-15 01:25:58,757] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 270.84 | bwd_microstep: 493.85 | bwd_inner_microstep: 493.78 | bwd_allreduce_microstep: 0.02 | step_microstep: 2.33 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1895 +[2025-05-15 01:25:59,871] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.01 | optimizer_gradients: 2.08 | optimizer_step: 20.24 +[2025-05-15 01:25:59,872] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 443.01 | bwd_microstep: 606.98 | bwd_inner_microstep: 446.44 | bwd_allreduce_microstep: 160.39 | step_microstep: 31.05 +[2025-05-15 01:25:59,873] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2681.20 | bwd: 3944.37 | bwd_inner: 3782.85 | bwd_allreduce: 160.90 | step: 37.56 + 90%|████████▉ | 502/558 [57:55<09:04, 9.72s/it] {'loss': 4.6853, 'grad_norm': 20.104658126831055, 'learning_rate': 2.620539265477512e-17, 'epoch': 0.27} + 90%|████████▉ | 502/558 [57:55<09:04, 9.72s/it]dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1383 +[2025-05-15 01:26:00,676] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 328.18 | bwd_microstep: 429.79 | bwd_inner_microstep: 429.51 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.21 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1897 +[2025-05-15 01:26:01,517] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 219.48 | bwd_microstep: 598.68 | bwd_inner_microstep: 598.64 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 354 +[2025-05-15 01:26:01,804] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 103.83 | bwd_microstep: 149.02 | bwd_inner_microstep: 148.97 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.60 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-15 01:26:02,610] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 296.22 | bwd_microstep: 482.65 | bwd_inner_microstep: 482.59 | bwd_allreduce_microstep: 0.02 | step_microstep: 2.36 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 343 +[2025-05-15 01:26:02,891] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 104.21 | bwd_microstep: 143.86 | bwd_inner_microstep: 143.81 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-15 01:26:03,686] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 385.60 | bwd_microstep: 376.70 | bwd_inner_microstep: 376.42 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.52 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-15 01:26:04,721] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 397.63 | bwd_microstep: 615.27 | bwd_inner_microstep: 615.04 | bwd_allreduce_microstep: 0.19 | step_microstep: 0.21 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 507 +[2025-05-15 01:26:05,102] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.11 | optimizer_step: 17.58 +[2025-05-15 01:26:05,103] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 109.30 | bwd_microstep: 228.19 | bwd_inner_microstep: 155.65 | bwd_allreduce_microstep: 72.44 | step_microstep: 26.25 +[2025-05-15 01:26:05,103] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 1944.45 | bwd: 3025.09 | bwd_inner: 2950.67 | bwd_allreduce: 72.71 | step: 36.84 + 90%|█████████ | 503/558 [58:00<07:40, 8.37s/it] {'loss': 3.9173, 'grad_norm': 17.329774856567383, 'learning_rate': 2.528574173672049e-17, 'epoch': 0.27} + 90%|█████████ | 503/558 [58:00<07:40, 8.37s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1903 +[2025-05-15 01:26:06,096] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 359.59 | bwd_microstep: 604.58 | bwd_inner_microstep: 604.55 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.48 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 348 +[2025-05-15 01:26:06,348] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 84.59 | bwd_microstep: 132.36 | bwd_inner_microstep: 131.41 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-15 01:26:07,148] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 268.83 | bwd_microstep: 501.76 | bwd_inner_microstep: 501.72 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1378 +[2025-05-15 01:26:07,922] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 332.17 | bwd_microstep: 409.59 | bwd_inner_microstep: 408.44 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-15 01:26:08,735] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 238.89 | bwd_microstep: 551.19 | bwd_inner_microstep: 551.15 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-15 01:26:09,587] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 430.16 | bwd_microstep: 389.13 | bwd_inner_microstep: 388.90 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.19 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 838 +[2025-05-15 01:26:10,083] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 203.39 | bwd_microstep: 269.67 | bwd_inner_microstep: 269.63 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-15 01:26:11,524] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.91 | optimizer_gradients: 2.18 | optimizer_step: 18.62 +[2025-05-15 01:26:11,525] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 429.26 | bwd_microstep: 951.91 | bwd_inner_microstep: 377.40 | bwd_allreduce_microstep: 574.48 | step_microstep: 28.02 +[2025-05-15 01:26:11,525] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2346.87 | bwd: 3810.20 | bwd_inner: 3233.21 | bwd_allreduce: 576.40 | step: 38.15 + 90%|█████████ | 504/558 [58:07<07:00, 7.79s/it] {'loss': 4.4724, 'grad_norm': 19.1683406829834, 'learning_rate': 2.438209878900405e-17, 'epoch': 0.27} + 90%|█████████ | 504/558 [58:07<07:00, 7.79s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-15 01:26:12,344] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 244.71 | bwd_microstep: 543.67 | bwd_inner_microstep: 543.63 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1886 +[2025-05-15 01:26:13,209] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 432.36 | bwd_microstep: 400.10 | bwd_inner_microstep: 399.88 | bwd_allreduce_microstep: 0.18 | step_microstep: 0.18 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 334 +[2025-05-15 01:26:13,461] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.81 | bwd_microstep: 136.74 | bwd_inner_microstep: 136.35 | bwd_allreduce_microstep: 0.19 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-15 01:26:14,433] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 434.75 | bwd_microstep: 510.01 | bwd_inner_microstep: 509.83 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-15 01:26:15,337] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 277.51 | bwd_microstep: 605.14 | bwd_inner_microstep: 605.10 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.54 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-15 01:26:16,160] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 385.98 | bwd_microstep: 400.67 | bwd_inner_microstep: 400.63 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.82 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 326 +[2025-05-15 01:26:16,428] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 91.46 | bwd_microstep: 151.52 | bwd_inner_microstep: 151.46 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 326 +[2025-05-15 01:26:16,979] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.11 | optimizer_step: 16.30 +[2025-05-15 01:26:16,980] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 100.30 | bwd_microstep: 395.48 | bwd_inner_microstep: 150.13 | bwd_allreduce_microstep: 245.32 | step_microstep: 25.75 +[2025-05-15 01:26:16,981] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2060.86 | bwd: 3143.35 | bwd_inner: 2897.25 | bwd_allreduce: 245.81 | step: 35.29 + 91%|█████████ | 505/558 [58:12<06:15, 7.09s/it] {'loss': 5.4969, 'grad_norm': 18.491931915283203, 'learning_rate': 2.3494494283618774e-17, 'epoch': 0.27} + 91%|█████████ | 505/558 [58:12<06:15, 7.09s/it]dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1447 +[2025-05-15 01:26:17,614] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 158.13 | bwd_microstep: 447.87 | bwd_inner_microstep: 447.83 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-15 01:26:18,530] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 444.06 | bwd_microstep: 438.42 | bwd_inner_microstep: 438.08 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1888 +[2025-05-15 01:26:19,522] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 352.75 | bwd_microstep: 618.93 | bwd_inner_microstep: 618.88 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-15 01:26:20,322] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 295.06 | bwd_microstep: 470.99 | bwd_inner_microstep: 470.94 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-15 01:26:21,238] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 444.30 | bwd_microstep: 439.25 | bwd_inner_microstep: 439.11 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-15 01:26:22,233] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 361.00 | bwd_microstep: 614.83 | bwd_inner_microstep: 614.77 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-15 01:26:23,018] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 293.15 | bwd_microstep: 459.11 | bwd_inner_microstep: 459.08 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.32 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-15 01:26:24,396] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.01 | optimizer_gradients: 2.10 | optimizer_step: 18.71 +[2025-05-15 01:26:24,398] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 440.82 | bwd_microstep: 875.16 | bwd_inner_microstep: 445.93 | bwd_allreduce_microstep: 429.15 | step_microstep: 32.66 +[2025-05-15 01:26:24,399] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2789.23 | bwd: 4364.59 | bwd_inner: 3934.73 | bwd_allreduce: 429.38 | step: 44.67 + 91%|█████████ | 506/558 [58:19<06:13, 7.19s/it] {'loss': 5.357, 'grad_norm': 18.691617965698242, 'learning_rate': 2.2622958151720776e-17, 'epoch': 0.27} + 91%|█████████ | 506/558 [58:19<06:13, 7.19s/it]dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1432 +[2025-05-15 01:26:24,957] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 269.92 | bwd_microstep: 243.04 | bwd_inner_microstep: 243.00 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.71 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1933 +[2025-05-15 01:26:26,017] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 408.09 | bwd_microstep: 626.63 | bwd_inner_microstep: 626.42 | bwd_allreduce_microstep: 0.18 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1911 +[2025-05-15 01:26:26,862] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 226.27 | bwd_microstep: 597.48 | bwd_inner_microstep: 597.42 | bwd_allreduce_microstep: 0.02 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1892 +[2025-05-15 01:26:27,709] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 413.02 | bwd_microstep: 398.01 | bwd_inner_microstep: 397.97 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.78 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-15 01:26:28,734] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 398.63 | bwd_microstep: 600.49 | bwd_inner_microstep: 600.26 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.24 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-15 01:26:29,533] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 284.61 | bwd_microstep: 492.90 | bwd_inner_microstep: 492.87 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-15 01:26:30,489] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 442.75 | bwd_microstep: 476.70 | bwd_inner_microstep: 476.65 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.48 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-15 01:26:31,706] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.01 | optimizer_gradients: 2.10 | optimizer_step: 18.84 +[2025-05-15 01:26:31,707] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 241.91 | bwd_microstep: 923.84 | bwd_inner_microstep: 597.15 | bwd_allreduce_microstep: 326.66 | step_microstep: 28.57 +[2025-05-15 01:26:31,708] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2685.19 | bwd: 4359.10 | bwd_inner: 4031.77 | bwd_allreduce: 326.90 | step: 39.65 + 91%|█████████ | 507/558 [58:27<06:08, 7.22s/it] {'loss': 4.1566, 'grad_norm': 15.104080200195312, 'learning_rate': 2.1767519782620093e-17, 'epoch': 0.27} + 91%|█████████ | 507/558 [58:27<06:08, 7.22s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1900 +[2025-05-15 01:26:32,549] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 221.47 | bwd_microstep: 590.08 | bwd_inner_microstep: 590.04 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-15 01:26:33,383] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 411.08 | bwd_microstep: 389.34 | bwd_inner_microstep: 389.30 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.86 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-15 01:26:34,425] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 400.68 | bwd_microstep: 613.52 | bwd_inner_microstep: 613.47 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.48 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-15 01:26:35,246] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 250.42 | bwd_microstep: 549.10 | bwd_inner_microstep: 549.04 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.51 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1366 +[2025-05-15 01:26:35,972] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 328.75 | bwd_microstep: 363.91 | bwd_inner_microstep: 363.61 | bwd_allreduce_microstep: 0.14 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-15 01:26:36,895] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 290.37 | bwd_microstep: 612.85 | bwd_inner_microstep: 612.81 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.43 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-15 01:26:37,704] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 375.07 | bwd_microstep: 400.12 | bwd_inner_microstep: 400.08 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.78 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1103 +[2025-05-15 01:26:38,631] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.01 | optimizer_gradients: 2.00 | optimizer_step: 19.22 +[2025-05-15 01:26:38,631] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 268.08 | bwd_microstep: 607.71 | bwd_inner_microstep: 382.35 | bwd_allreduce_microstep: 225.33 | step_microstep: 28.18 +[2025-05-15 01:26:38,632] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2545.90 | bwd: 4126.65 | bwd_inner: 3900.78 | bwd_allreduce: 225.51 | step: 41.69 + 91%|█████████ | 508/558 [58:34<05:56, 7.13s/it] {'loss': 5.3406, 'grad_norm': 17.763368606567383, 'learning_rate': 2.092820802278994e-17, 'epoch': 0.27} + 91%|█████████ | 508/558 [58:34<05:56, 7.13s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1892 +[2025-05-15 01:26:39,511] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 243.87 | bwd_microstep: 604.79 | bwd_inner_microstep: 604.77 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.54 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1888 +[2025-05-15 01:26:40,333] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 387.29 | bwd_microstep: 400.40 | bwd_inner_microstep: 400.38 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.29 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1360 +[2025-05-15 01:26:41,134] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 292.36 | bwd_microstep: 481.40 | bwd_inner_microstep: 481.38 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-15 01:26:41,940] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 327.70 | bwd_microstep: 447.02 | bwd_inner_microstep: 446.99 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.23 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-15 01:26:42,922] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 449.83 | bwd_microstep: 501.53 | bwd_inner_microstep: 501.20 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-15 01:26:43,840] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 289.65 | bwd_microstep: 607.90 | bwd_inner_microstep: 607.85 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 318 +[2025-05-15 01:26:44,130] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 99.84 | bwd_microstep: 156.44 | bwd_inner_microstep: 156.17 | bwd_allreduce_microstep: 0.25 | step_microstep: 0.92 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 831 +[2025-05-15 01:26:45,025] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.01 | optimizer_gradients: 1.99 | optimizer_step: 18.05 +[2025-05-15 01:26:45,026] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 138.82 | bwd_microstep: 712.70 | bwd_inner_microstep: 141.40 | bwd_allreduce_microstep: 571.04 | step_microstep: 27.30 +[2025-05-15 01:26:45,027] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2229.32 | bwd: 3912.20 | bwd_inner: 3340.21 | bwd_allreduce: 571.46 | step: 35.39 + 91%|█████████ | 509/558 [58:40<05:38, 6.91s/it] {'loss': 4.6279, 'grad_norm': 23.697416305541992, 'learning_rate': 2.0105051174893363e-17, 'epoch': 0.27} + 91%|█████████ | 509/558 [58:40<05:38, 6.91s/it]dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1362 +[2025-05-15 01:26:45,611] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 197.03 | bwd_microstep: 358.33 | bwd_inner_microstep: 358.29 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.76 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-15 01:26:46,600] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 443.00 | bwd_microstep: 520.71 | bwd_inner_microstep: 520.54 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-15 01:26:47,470] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 241.28 | bwd_microstep: 603.92 | bwd_inner_microstep: 603.87 | bwd_allreduce_microstep: 0.02 | step_microstep: 2.49 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-15 01:26:48,293] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 392.92 | bwd_microstep: 396.08 | bwd_inner_microstep: 396.04 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.88 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-15 01:26:49,324] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 407.54 | bwd_microstep: 599.64 | bwd_inner_microstep: 599.26 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.35 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1352 +[2025-05-15 01:26:49,894] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 198.72 | bwd_microstep: 349.29 | bwd_inner_microstep: 349.26 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.71 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 839 +[2025-05-15 01:26:50,404] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 186.28 | bwd_microstep: 299.77 | bwd_inner_microstep: 299.73 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1356 +[2025-05-15 01:26:51,597] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.07 | optimizer_step: 18.60 +[2025-05-15 01:26:51,598] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 276.01 | bwd_microstep: 855.14 | bwd_inner_microstep: 279.73 | bwd_allreduce_microstep: 575.39 | step_microstep: 27.45 +[2025-05-15 01:26:51,598] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2342.77 | bwd: 3982.90 | bwd_inner: 3406.75 | bwd_allreduce: 575.68 | step: 37.92 + 91%|█████████▏| 510/558 [58:47<05:26, 6.81s/it] {'loss': 7.3513, 'grad_norm': 30.00689697265625, 'learning_rate': 1.9298076996829175e-17, 'epoch': 0.27} + 91%|█████████▏| 510/558 [58:47<05:26, 6.81s/it]dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1152 +[2025-05-15 01:26:52,030] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 178.78 | bwd_microstep: 224.84 | bwd_inner_microstep: 224.79 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.80 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1905 +[2025-05-15 01:26:53,064] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 407.64 | bwd_microstep: 602.57 | bwd_inner_microstep: 602.54 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.22 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1883 +[2025-05-15 01:26:53,874] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 241.23 | bwd_microstep: 546.06 | bwd_inner_microstep: 546.01 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 855 +[2025-05-15 01:26:54,404] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 224.88 | bwd_microstep: 275.15 | bwd_inner_microstep: 274.90 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-15 01:26:55,209] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 250.19 | bwd_microstep: 535.92 | bwd_inner_microstep: 535.86 | bwd_allreduce_microstep: 0.02 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-15 01:26:56,101] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 433.03 | bwd_microstep: 427.04 | bwd_inner_microstep: 426.89 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-15 01:26:57,117] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 359.25 | bwd_microstep: 636.42 | bwd_inner_microstep: 636.38 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.39 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 980 +[2025-05-15 01:26:58,099] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.01 | optimizer_gradients: 2.07 | optimizer_step: 18.29 +[2025-05-15 01:26:58,100] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 190.36 | bwd_microstep: 747.43 | bwd_inner_microstep: 164.50 | bwd_allreduce_microstep: 582.90 | step_microstep: 27.57 +[2025-05-15 01:26:58,100] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2285.36 | bwd: 3995.46 | bwd_inner: 3411.96 | bwd_allreduce: 583.08 | step: 35.89 + 92%|█████████▏| 511/558 [58:53<05:15, 6.72s/it] {'loss': 2.4469, 'grad_norm': 6.189762592315674, 'learning_rate': 1.8507312700796255e-17, 'epoch': 0.27} + 92%|█████████▏| 511/558 [58:53<05:15, 6.72s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1908 +[2025-05-15 01:26:58,927] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 248.53 | bwd_microstep: 548.57 | bwd_inner_microstep: 548.53 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1896 +[2025-05-15 01:26:59,808] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 431.10 | bwd_microstep: 417.09 | bwd_inner_microstep: 416.75 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.19 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1380 +[2025-05-15 01:27:00,606] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 286.92 | bwd_microstep: 486.57 | bwd_inner_microstep: 486.53 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.55 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-15 01:27:01,416] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 370.12 | bwd_microstep: 403.86 | bwd_inner_microstep: 403.83 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.86 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-15 01:27:02,420] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 412.60 | bwd_microstep: 565.64 | bwd_inner_microstep: 565.19 | bwd_allreduce_microstep: 0.43 | step_microstep: 0.74 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 840 +[2025-05-15 01:27:02,678] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 110.65 | bwd_microstep: 130.59 | bwd_inner_microstep: 130.38 | bwd_allreduce_microstep: 0.19 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-15 01:27:03,712] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 388.06 | bwd_microstep: 622.83 | bwd_inner_microstep: 622.59 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-15 01:27:04,989] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.02 | optimizer_step: 24.21 +[2025-05-15 01:27:04,990] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 283.96 | bwd_microstep: 940.47 | bwd_inner_microstep: 492.94 | bwd_allreduce_microstep: 447.50 | step_microstep: 33.10 +[2025-05-15 01:27:04,990] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2531.93 | bwd: 4115.62 | bwd_inner: 3666.77 | bwd_allreduce: 448.40 | step: 41.19 + 92%|█████████▏| 512/558 [59:00<05:11, 6.77s/it] {'loss': 5.0151, 'grad_norm': 22.9429988861084, 'learning_rate': 1.7732784952375236e-17, 'epoch': 0.28} + 92%|█████████▏| 512/558 [59:00<05:11, 6.77s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 387 +[2025-05-15 01:27:05,239] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 78.41 | bwd_microstep: 147.26 | bwd_inner_microstep: 147.24 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.74 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1895 +[2025-05-15 01:27:06,267] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 416.56 | bwd_microstep: 586.23 | bwd_inner_microstep: 586.01 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-15 01:27:07,138] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 244.49 | bwd_microstep: 604.26 | bwd_inner_microstep: 604.22 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.58 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-15 01:27:07,973] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 393.89 | bwd_microstep: 404.59 | bwd_inner_microstep: 404.54 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.87 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 330 +[2025-05-15 01:27:08,246] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.83 | bwd_microstep: 154.64 | bwd_inner_microstep: 154.60 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 842 +[2025-05-15 01:27:08,785] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 225.04 | bwd_microstep: 280.72 | bwd_inner_microstep: 280.34 | bwd_allreduce_microstep: 0.18 | step_microstep: 0.17 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 321 +[2025-05-15 01:27:09,042] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 95.27 | bwd_microstep: 144.64 | bwd_inner_microstep: 144.32 | bwd_allreduce_microstep: 0.16 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-15 01:27:10,264] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.22 | optimizer_gradients: 2.16 | optimizer_step: 18.35 +[2025-05-15 01:27:10,265] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 325.65 | bwd_microstep: 851.62 | bwd_inner_microstep: 618.43 | bwd_allreduce_microstep: 233.17 | step_microstep: 26.55 +[2025-05-15 01:27:10,265] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 1874.10 | bwd: 3173.98 | bwd_inner: 2939.79 | bwd_allreduce: 233.62 | step: 35.48 + 92%|█████████▏| 513/558 [59:05<04:44, 6.32s/it] {'loss': 5.1049, 'grad_norm': 35.84596633911133, 'learning_rate': 1.697451986962989e-17, 'epoch': 0.28} + 92%|█████████▏| 513/558 [59:05<04:44, 6.32s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1901 +[2025-05-15 01:27:11,044] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 236.32 | bwd_microstep: 513.75 | bwd_inner_microstep: 513.72 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1891 +[2025-05-15 01:27:12,053] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 449.03 | bwd_microstep: 527.42 | bwd_inner_microstep: 527.34 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-15 01:27:12,917] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 241.52 | bwd_microstep: 599.73 | bwd_inner_microstep: 599.66 | bwd_allreduce_microstep: 0.02 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-15 01:27:13,757] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 397.71 | bwd_microstep: 408.65 | bwd_inner_microstep: 408.63 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.83 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1883 +[2025-05-15 01:27:14,779] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 412.68 | bwd_microstep: 585.54 | bwd_inner_microstep: 585.49 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.30 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-15 01:27:15,566] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 340.75 | bwd_microstep: 424.01 | bwd_inner_microstep: 423.98 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.79 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 844 +[2025-05-15 01:27:16,132] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 225.08 | bwd_microstep: 316.73 | bwd_inner_microstep: 316.69 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.55 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-15 01:27:17,450] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.10 | optimizer_step: 27.28 +[2025-05-15 01:27:17,451] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 309.09 | bwd_microstep: 938.32 | bwd_inner_microstep: 455.73 | bwd_allreduce_microstep: 482.56 | step_microstep: 36.50 +[2025-05-15 01:27:17,451] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2612.18 | bwd: 4314.17 | bwd_inner: 3831.24 | bwd_allreduce: 482.66 | step: 47.81 + 92%|█████████▏| 514/558 [59:12<04:49, 6.58s/it] {'loss': 3.8246, 'grad_norm': 11.672110557556152, 'learning_rate': 1.623254302222599e-17, 'epoch': 0.28} + 92%|█████████▏| 514/558 [59:12<04:49, 6.58s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1896 +[2025-05-15 01:27:18,349] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 261.17 | bwd_microstep: 606.86 | bwd_inner_microstep: 606.83 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.33 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-15 01:27:19,165] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 379.23 | bwd_microstep: 405.74 | bwd_inner_microstep: 405.71 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.80 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-15 01:27:20,165] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 410.44 | bwd_microstep: 562.48 | bwd_inner_microstep: 562.29 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 840 +[2025-05-15 01:27:20,510] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 92.33 | bwd_microstep: 233.18 | bwd_inner_microstep: 233.09 | bwd_allreduce_microstep: 0.02 | step_microstep: 1.82 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-15 01:27:21,516] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 410.61 | bwd_microstep: 570.76 | bwd_inner_microstep: 570.28 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.23 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-15 01:27:22,350] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 222.22 | bwd_microstep: 589.72 | bwd_inner_microstep: 589.68 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 417 +[2025-05-15 01:27:22,683] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 124.57 | bwd_microstep: 175.91 | bwd_inner_microstep: 175.87 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-15 01:27:23,966] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.12 | optimizer_step: 19.22 +[2025-05-15 01:27:23,967] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 291.31 | bwd_microstep: 939.27 | bwd_inner_microstep: 472.24 | bwd_allreduce_microstep: 467.01 | step_microstep: 28.18 +[2025-05-15 01:27:23,968] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2191.86 | bwd: 4083.91 | bwd_inner: 3616.06 | bwd_allreduce: 467.12 | step: 39.16 + 92%|█████████▏| 515/558 [59:19<04:42, 6.56s/it] {'loss': 6.5651, 'grad_norm': 17.093963623046875, 'learning_rate': 1.5506879430569278e-17, 'epoch': 0.28} + 92%|█████████▏| 515/558 [59:19<04:42, 6.56s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1903 +[2025-05-15 01:27:24,864] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 258.60 | bwd_microstep: 610.28 | bwd_inner_microstep: 610.23 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.54 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1890 +[2025-05-15 01:27:25,685] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 389.15 | bwd_microstep: 398.00 | bwd_inner_microstep: 397.96 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.80 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1100 +[2025-05-15 01:27:26,322] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 226.25 | bwd_microstep: 384.76 | bwd_inner_microstep: 384.71 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.31 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-15 01:27:27,129] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 380.63 | bwd_microstep: 394.57 | bwd_inner_microstep: 394.49 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.25 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-15 01:27:28,175] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 391.67 | bwd_microstep: 626.64 | bwd_inner_microstep: 626.60 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.32 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-15 01:27:28,946] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 350.24 | bwd_microstep: 397.50 | bwd_inner_microstep: 397.47 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-15 01:27:29,982] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 388.08 | bwd_microstep: 624.14 | bwd_inner_microstep: 624.10 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-15 01:27:31,281] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.01 | optimizer_gradients: 2.14 | optimizer_step: 19.25 +[2025-05-15 01:27:31,282] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 320.03 | bwd_microstep: 931.87 | bwd_inner_microstep: 445.04 | bwd_allreduce_microstep: 486.61 | step_microstep: 27.78 +[2025-05-15 01:27:31,283] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2704.64 | bwd: 4367.94 | bwd_inner: 3880.78 | bwd_allreduce: 486.69 | step: 37.40 + 92%|█████████▏| 516/558 [59:26<04:45, 6.79s/it] {'loss': 5.5649, 'grad_norm': 26.244035720825195, 'learning_rate': 1.4797553564961764e-17, 'epoch': 0.28} + 92%|█████████▏| 516/558 [59:26<04:45, 6.79s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 355 +[2025-05-15 01:27:31,542] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 87.70 | bwd_microstep: 147.82 | bwd_inner_microstep: 146.69 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.22 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-15 01:27:32,306] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 348.76 | bwd_microstep: 393.11 | bwd_inner_microstep: 393.07 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.85 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-15 01:27:33,357] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 405.10 | bwd_microstep: 619.10 | bwd_inner_microstep: 618.13 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-15 01:27:34,243] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 341.61 | bwd_microstep: 523.24 | bwd_inner_microstep: 523.21 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.78 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1349 +[2025-05-15 01:27:34,642] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 170.34 | bwd_microstep: 208.21 | bwd_inner_microstep: 207.89 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.10 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 837 +[2025-05-15 01:27:35,063] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 145.18 | bwd_microstep: 257.26 | bwd_inner_microstep: 257.21 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.40 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 833 +[2025-05-15 01:27:35,614] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 220.20 | bwd_microstep: 296.38 | bwd_inner_microstep: 296.34 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.37 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1967 +[2025-05-15 01:27:36,712] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.04 | optimizer_step: 18.27 +[2025-05-15 01:27:36,713] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 373.85 | bwd_microstep: 667.23 | bwd_inner_microstep: 547.62 | bwd_allreduce_microstep: 119.54 | step_microstep: 27.08 +[2025-05-15 01:27:36,713] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2092.48 | bwd: 3112.39 | bwd_inner: 2990.23 | bwd_allreduce: 120.67 | step: 35.99 + 93%|█████████▎| 517/558 [59:32<04:21, 6.38s/it] {'loss': 4.6953, 'grad_norm': 19.234590530395508, 'learning_rate': 1.4104589344776542e-17, 'epoch': 0.28} + 93%|█████████▎| 517/558 [59:32<04:21, 6.38s/it]dynamic ViT batch size: 6, images per sample: 6.0, dynamic token length: 1628 +[2025-05-15 01:27:37,574] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 299.47 | bwd_microstep: 536.63 | bwd_inner_microstep: 536.58 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.30 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-15 01:27:38,498] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 383.12 | bwd_microstep: 506.00 | bwd_inner_microstep: 505.96 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.29 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-15 01:27:39,285] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 353.02 | bwd_microstep: 411.14 | bwd_inner_microstep: 411.10 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.85 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-15 01:27:40,292] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 414.49 | bwd_microstep: 567.63 | bwd_inner_microstep: 567.40 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.25 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1098 +[2025-05-15 01:27:40,834] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 212.72 | bwd_microstep: 309.07 | bwd_inner_microstep: 308.68 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-15 01:27:41,715] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 355.45 | bwd_microstep: 504.72 | bwd_inner_microstep: 504.68 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.23 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 838 +[2025-05-15 01:27:42,083] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 164.43 | bwd_microstep: 184.01 | bwd_inner_microstep: 183.87 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-15 01:27:43,372] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.01 | optimizer_gradients: 2.06 | optimizer_step: 19.31 +[2025-05-15 01:27:43,373] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 322.82 | bwd_microstep: 920.55 | bwd_inner_microstep: 609.28 | bwd_allreduce_microstep: 311.23 | step_microstep: 29.05 +[2025-05-15 01:27:43,374] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2505.49 | bwd: 3939.75 | bwd_inner: 3627.59 | bwd_allreduce: 311.52 | step: 34.25 + 93%|█████████▎| 518/558 [59:38<04:18, 6.46s/it] {'loss': 7.1751, 'grad_norm': 34.340232849121094, 'learning_rate': 1.3428010137650938e-17, 'epoch': 0.28} + 93%|█████████▎| 518/558 [59:38<04:18, 6.46s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1896 +[2025-05-15 01:27:44,261] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 360.98 | bwd_microstep: 499.09 | bwd_inner_microstep: 498.85 | bwd_allreduce_microstep: 0.21 | step_microstep: 0.22 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-15 01:27:45,150] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 357.72 | bwd_microstep: 512.99 | bwd_inner_microstep: 512.95 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.25 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-15 01:27:46,023] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 352.89 | bwd_microstep: 499.65 | bwd_inner_microstep: 499.42 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-15 01:27:46,907] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 259.17 | bwd_microstep: 603.53 | bwd_inner_microstep: 603.49 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.53 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-15 01:27:47,715] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 389.56 | bwd_microstep: 386.89 | bwd_inner_microstep: 386.84 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.29 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-15 01:27:48,753] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 404.57 | bwd_microstep: 609.58 | bwd_inner_microstep: 609.54 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.26 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-15 01:27:49,623] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 343.40 | bwd_microstep: 505.47 | bwd_inner_microstep: 505.44 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-15 01:27:50,670] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.00 | optimizer_step: 18.02 +[2025-05-15 01:27:50,670] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 347.82 | bwd_microstep: 651.76 | bwd_inner_microstep: 514.44 | bwd_allreduce_microstep: 137.26 | step_microstep: 26.43 +[2025-05-15 01:27:50,671] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2816.11 | bwd: 4268.97 | bwd_inner: 4131.03 | bwd_allreduce: 137.61 | step: 30.29 + 93%|█████████▎| 519/558 [59:46<04:21, 6.71s/it] {'loss': 5.1954, 'grad_norm': 21.609285354614258, 'learning_rate': 1.2767838758698914e-17, 'epoch': 0.28} + 93%|█████████▎| 519/558 [59:46<04:21, 6.71s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1922 +[2025-05-15 01:27:51,700] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 363.19 | bwd_microstep: 639.69 | bwd_inner_microstep: 639.64 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.57 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1902 +[2025-05-15 01:27:52,612] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 349.34 | bwd_microstep: 527.85 | bwd_inner_microstep: 527.81 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.31 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-15 01:27:53,494] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 359.63 | bwd_microstep: 498.01 | bwd_inner_microstep: 497.65 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.23 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 860 +[2025-05-15 01:27:53,862] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 96.24 | bwd_microstep: 251.65 | bwd_inner_microstep: 251.60 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.82 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-15 01:27:54,878] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 413.12 | bwd_microstep: 576.48 | bwd_inner_microstep: 576.26 | bwd_allreduce_microstep: 0.19 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-15 01:27:55,765] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 356.89 | bwd_microstep: 509.26 | bwd_inner_microstep: 509.21 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.28 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-15 01:27:56,555] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 343.24 | bwd_microstep: 425.15 | bwd_inner_microstep: 424.80 | bwd_allreduce_microstep: 0.14 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-15 01:27:57,813] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.01 | optimizer_gradients: 2.14 | optimizer_step: 18.61 +[2025-05-15 01:27:57,813] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 359.86 | bwd_microstep: 853.22 | bwd_inner_microstep: 620.11 | bwd_allreduce_microstep: 233.08 | step_microstep: 27.59 +[2025-05-15 01:27:57,814] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2641.48 | bwd: 4281.37 | bwd_inner: 4047.23 | bwd_allreduce: 233.58 | step: 35.18 + 93%|█████████▎| 520/558 [59:53<04:20, 6.84s/it] {'loss': 4.2701, 'grad_norm': 13.30276870727539, 'learning_rate': 1.2124097469741469e-17, 'epoch': 0.28} + 93%|█████████▎| 520/558 [59:53<04:20, 6.84s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1943 +[2025-05-15 01:27:58,752] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 365.71 | bwd_microstep: 547.74 | bwd_inner_microstep: 547.52 | bwd_allreduce_microstep: 0.19 | step_microstep: 0.17 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1883 +[2025-05-15 01:27:59,559] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 359.40 | bwd_microstep: 427.75 | bwd_inner_microstep: 427.43 | bwd_allreduce_microstep: 0.14 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-15 01:28:00,254] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 194.33 | bwd_microstep: 482.37 | bwd_inner_microstep: 482.34 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.44 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 321 +[2025-05-15 01:28:00,530] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 100.27 | bwd_microstep: 143.24 | bwd_inner_microstep: 143.20 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.52 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-15 01:28:01,480] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 402.80 | bwd_microstep: 510.09 | bwd_inner_microstep: 510.04 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.31 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-15 01:28:02,363] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 354.53 | bwd_microstep: 505.71 | bwd_inner_microstep: 505.47 | bwd_allreduce_microstep: 0.20 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-15 01:28:03,238] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 355.45 | bwd_microstep: 499.02 | bwd_inner_microstep: 498.75 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.93 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 830 +[2025-05-15 01:28:03,910] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.17 | optimizer_step: 22.47 +[2025-05-15 01:28:03,910] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 166.96 | bwd_microstep: 455.44 | bwd_inner_microstep: 250.51 | bwd_allreduce_microstep: 204.90 | step_microstep: 31.98 +[2025-05-15 01:28:03,911] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2299.43 | bwd: 3571.37 | bwd_inner: 3365.32 | bwd_allreduce: 205.48 | step: 40.27 + 93%|█████████▎| 521/558 [59:59<04:04, 6.62s/it] {'loss': 5.8027, 'grad_norm': 40.547401428222656, 'learning_rate': 1.1496807978556013e-17, 'epoch': 0.28} + 93%|█████████▎| 521/558 [59:59<04:04, 6.62s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1912 +[2025-05-15 01:28:04,822] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 262.09 | bwd_microstep: 619.66 | bwd_inner_microstep: 619.62 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1903 +[2025-05-15 01:28:05,786] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 400.04 | bwd_microstep: 529.27 | bwd_inner_microstep: 529.23 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.02 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1886 +[2025-05-15 01:28:06,677] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 355.82 | bwd_microstep: 515.29 | bwd_inner_microstep: 514.92 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.17 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-15 01:28:07,507] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 222.30 | bwd_microstep: 584.62 | bwd_inner_microstep: 584.60 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-15 01:28:08,473] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 423.69 | bwd_microstep: 508.19 | bwd_inner_microstep: 508.17 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.24 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-15 01:28:09,363] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 350.24 | bwd_microstep: 516.98 | bwd_inner_microstep: 516.94 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.25 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 834 +[2025-05-15 01:28:09,744] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 161.24 | bwd_microstep: 199.65 | bwd_inner_microstep: 199.31 | bwd_allreduce_microstep: 0.12 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-15 01:28:10,983] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.22 | optimizer_step: 15.08 +[2025-05-15 01:28:10,983] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 313.00 | bwd_microstep: 882.39 | bwd_inner_microstep: 613.84 | bwd_allreduce_microstep: 268.53 | step_microstep: 23.94 +[2025-05-15 01:28:10,984] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2488.37 | bwd: 4356.08 | bwd_inner: 4086.68 | bwd_allreduce: 268.70 | step: 31.58 + 94%|█████████▎| 522/558 [1:00:06<04:03, 6.75s/it] {'loss': 5.7281, 'grad_norm': 35.52486801147461, 'learning_rate': 1.088599143814445e-17, 'epoch': 0.28} + 94%|█████████▎| 522/558 [1:00:06<04:03, 6.75s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 382 +[2025-05-15 01:28:11,252] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 103.43 | bwd_microstep: 143.74 | bwd_inner_microstep: 142.79 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1906 +[2025-05-15 01:28:12,158] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 352.37 | bwd_microstep: 531.49 | bwd_inner_microstep: 531.45 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.32 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-15 01:28:12,957] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 288.77 | bwd_microstep: 487.57 | bwd_inner_microstep: 487.52 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.45 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-15 01:28:13,970] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 443.01 | bwd_microstep: 535.52 | bwd_inner_microstep: 535.05 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.21 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-15 01:28:14,852] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 357.55 | bwd_microstep: 503.54 | bwd_inner_microstep: 503.07 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.26 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1933 +[2025-05-15 01:28:15,787] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 365.30 | bwd_microstep: 549.48 | bwd_inner_microstep: 549.28 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-15 01:28:16,654] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 355.98 | bwd_microstep: 491.27 | bwd_inner_microstep: 491.12 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1852 +[2025-05-15 01:28:17,877] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.13 | optimizer_step: 18.13 +[2025-05-15 01:28:17,878] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 262.90 | bwd_microstep: 913.38 | bwd_inner_microstep: 603.79 | bwd_allreduce_microstep: 309.54 | step_microstep: 26.92 +[2025-05-15 01:28:17,879] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2529.30 | bwd: 4156.02 | bwd_inner: 3844.12 | bwd_allreduce: 309.93 | step: 32.66 + 94%|█████████▎| 523/558 [1:00:13<03:57, 6.80s/it] {'loss': 4.107, 'grad_norm': 20.35591697692871, 'learning_rate': 1.0291668446019642e-17, 'epoch': 0.28} + 94%|█████████▎| 523/558 [1:00:13<03:57, 6.80s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-15 01:28:18,851] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 333.53 | bwd_microstep: 612.51 | bwd_inner_microstep: 612.48 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-15 01:28:19,766] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 368.18 | bwd_microstep: 513.39 | bwd_inner_microstep: 513.18 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-15 01:28:20,652] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 356.82 | bwd_microstep: 509.80 | bwd_inner_microstep: 508.84 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.21 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-15 01:28:21,533] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 352.10 | bwd_microstep: 506.67 | bwd_inner_microstep: 506.37 | bwd_allreduce_microstep: 0.27 | step_microstep: 0.94 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-15 01:28:22,322] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 317.95 | bwd_microstep: 450.75 | bwd_inner_microstep: 450.70 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.20 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1349 +[2025-05-15 01:28:23,130] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 330.44 | bwd_microstep: 446.66 | bwd_inner_microstep: 446.27 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-15 01:28:24,008] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 355.56 | bwd_microstep: 501.31 | bwd_inner_microstep: 501.08 | bwd_allreduce_microstep: 0.20 | step_microstep: 0.26 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-15 01:28:25,021] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.07 | optimizer_step: 18.09 +[2025-05-15 01:28:25,022] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 349.99 | bwd_microstep: 616.33 | bwd_inner_microstep: 519.54 | bwd_allreduce_microstep: 96.74 | step_microstep: 26.75 +[2025-05-15 01:28:25,022] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2764.54 | bwd: 4157.60 | bwd_inner: 4058.64 | bwd_allreduce: 97.26 | step: 31.07 + 94%|█████████▍| 524/558 [1:00:20<03:54, 6.90s/it] {'loss': 4.1001, 'grad_norm': 29.04180908203125, 'learning_rate': 9.71385904351102e-18, 'epoch': 0.28} + 94%|█████████▍| 524/558 [1:00:20<03:54, 6.90s/it]dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1397 +[2025-05-15 01:28:25,767] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 261.48 | bwd_microstep: 458.15 | bwd_inner_microstep: 458.10 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1893 +[2025-05-15 01:28:26,721] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 406.81 | bwd_microstep: 514.46 | bwd_inner_microstep: 514.09 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-15 01:28:27,620] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 359.05 | bwd_microstep: 521.03 | bwd_inner_microstep: 520.99 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.78 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1099 +[2025-05-15 01:28:28,170] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 219.99 | bwd_microstep: 307.11 | bwd_inner_microstep: 307.05 | bwd_allreduce_microstep: 0.02 | step_microstep: 2.48 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-15 01:28:29,022] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 230.38 | bwd_microstep: 598.93 | bwd_inner_microstep: 598.88 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.58 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 842 +[2025-05-15 01:28:29,555] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 226.24 | bwd_microstep: 274.50 | bwd_inner_microstep: 274.47 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.19 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 325 +[2025-05-15 01:28:29,809] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 93.07 | bwd_microstep: 144.23 | bwd_inner_microstep: 144.17 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.26 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-15 01:28:30,923] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.01 | optimizer_gradients: 2.14 | optimizer_step: 18.49 +[2025-05-15 01:28:30,924] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 353.36 | bwd_microstep: 713.31 | bwd_inner_microstep: 507.63 | bwd_allreduce_microstep: 205.64 | step_microstep: 27.28 +[2025-05-15 01:28:30,924] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2150.34 | bwd: 3531.73 | bwd_inner: 3323.45 | bwd_allreduce: 205.89 | step: 36.08 + 94%|█████████▍| 525/558 [1:00:26<03:37, 6.60s/it] {'loss': 4.6404, 'grad_norm': 23.441490173339844, 'learning_rate': 9.152582715088676e-18, 'epoch': 0.28} + 94%|█████████▍| 525/558 [1:00:26<03:37, 6.60s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1889 +[2025-05-15 01:28:31,822] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 358.51 | bwd_microstep: 513.20 | bwd_inner_microstep: 512.98 | bwd_allreduce_microstep: 0.19 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-15 01:28:32,511] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 355.55 | bwd_microstep: 314.26 | bwd_inner_microstep: 313.94 | bwd_allreduce_microstep: 0.16 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-15 01:28:33,499] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 349.44 | bwd_microstep: 617.80 | bwd_inner_microstep: 617.76 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-15 01:28:34,425] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 375.37 | bwd_microstep: 515.30 | bwd_inner_microstep: 514.49 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.24 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-15 01:28:35,306] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 346.44 | bwd_microstep: 515.21 | bwd_inner_microstep: 515.17 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.96 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-15 01:28:36,175] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 344.47 | bwd_microstep: 502.90 | bwd_inner_microstep: 502.88 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.25 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1096 +[2025-05-15 01:28:36,714] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 209.16 | bwd_microstep: 311.07 | bwd_inner_microstep: 311.02 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-15 01:28:37,776] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.07 | optimizer_step: 18.12 +[2025-05-15 01:28:37,776] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 350.74 | bwd_microstep: 664.67 | bwd_inner_microstep: 507.91 | bwd_allreduce_microstep: 156.71 | step_microstep: 26.92 +[2025-05-15 01:28:37,777] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2689.66 | bwd: 3954.44 | bwd_inner: 3796.21 | bwd_allreduce: 157.11 | step: 31.22 + 94%|█████████▍| 526/558 [1:00:33<03:33, 6.68s/it] {'loss': 5.0809, 'grad_norm': 31.60796546936035, 'learning_rate': 8.607858387706335e-18, 'epoch': 0.28} + 94%|█████████▍| 526/558 [1:00:33<03:33, 6.68s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1896 +[2025-05-15 01:28:38,768] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 343.55 | bwd_microstep: 621.76 | bwd_inner_microstep: 621.70 | bwd_allreduce_microstep: 0.02 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1892 +[2025-05-15 01:28:39,689] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 376.69 | bwd_microstep: 510.14 | bwd_inner_microstep: 510.10 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.28 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1895 +[2025-05-15 01:28:40,569] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 354.26 | bwd_microstep: 504.12 | bwd_inner_microstep: 504.07 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.27 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1889 +[2025-05-15 01:28:41,455] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 357.75 | bwd_microstep: 507.01 | bwd_inner_microstep: 506.73 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.22 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1888 +[2025-05-15 01:28:42,341] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 358.54 | bwd_microstep: 508.63 | bwd_inner_microstep: 508.38 | bwd_allreduce_microstep: 0.20 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-15 01:28:43,125] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 321.09 | bwd_microstep: 444.77 | bwd_inner_microstep: 444.61 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-15 01:28:44,112] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 375.97 | bwd_microstep: 593.58 | bwd_inner_microstep: 593.54 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.15 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-15 01:28:45,238] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.01 | optimizer_gradients: 2.09 | optimizer_step: 18.28 +[2025-05-15 01:28:45,239] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 355.23 | bwd_microstep: 723.61 | bwd_inner_microstep: 518.33 | bwd_allreduce_microstep: 205.25 | step_microstep: 27.99 +[2025-05-15 01:28:45,240] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2843.05 | bwd: 4413.83 | bwd_inner: 4207.52 | bwd_allreduce: 205.38 | step: 32.56 + 94%|█████████▍| 527/558 [1:00:40<03:34, 6.91s/it] {'loss': 5.3915, 'grad_norm': 21.075862884521484, 'learning_rate': 8.079704430163204e-18, 'epoch': 0.28} + 94%|█████████▍| 527/558 [1:00:40<03:34, 6.91s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1916 +[2025-05-15 01:28:46,131] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 348.30 | bwd_microstep: 516.70 | bwd_inner_microstep: 516.66 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.21 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1918 +[2025-05-15 01:28:47,021] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 346.80 | bwd_microstep: 521.60 | bwd_inner_microstep: 521.56 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.94 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1890 +[2025-05-15 01:28:47,852] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 344.37 | bwd_microstep: 466.70 | bwd_inner_microstep: 466.54 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-15 01:28:48,592] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 312.07 | bwd_microstep: 407.09 | bwd_inner_microstep: 407.06 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-15 01:28:49,606] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 448.94 | bwd_microstep: 531.35 | bwd_inner_microstep: 530.98 | bwd_allreduce_microstep: 0.18 | step_microstep: 0.17 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-15 01:28:50,489] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 356.16 | bwd_microstep: 505.95 | bwd_inner_microstep: 505.73 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.31 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-15 01:28:51,371] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 359.42 | bwd_microstep: 502.09 | bwd_inner_microstep: 501.61 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.97 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-15 01:28:52,485] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.08 | optimizer_step: 18.06 +[2025-05-15 01:28:52,486] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 356.50 | bwd_microstep: 708.89 | bwd_inner_microstep: 499.29 | bwd_allreduce_microstep: 209.40 | step_microstep: 26.62 +[2025-05-15 01:28:52,486] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2872.53 | bwd: 4160.37 | bwd_inner: 3949.46 | bwd_allreduce: 209.68 | step: 31.68 + 95%|█████████▍| 528/558 [1:00:48<03:30, 7.01s/it] {'loss': 4.2667, 'grad_norm': 13.957162857055664, 'learning_rate': 7.568138652484514e-18, 'epoch': 0.28} + 95%|█████████▍| 528/558 [1:00:48<03:30, 7.01s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1947 +[2025-05-15 01:28:53,302] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 351.08 | bwd_microstep: 437.54 | bwd_inner_microstep: 437.50 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.78 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-15 01:28:54,333] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 415.58 | bwd_microstep: 590.32 | bwd_inner_microstep: 590.11 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.17 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-15 01:28:55,221] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 358.71 | bwd_microstep: 510.98 | bwd_inner_microstep: 510.00 | bwd_allreduce_microstep: 0.94 | step_microstep: 0.23 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 854 +[2025-05-15 01:28:55,661] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 179.88 | bwd_microstep: 240.65 | bwd_inner_microstep: 240.43 | bwd_allreduce_microstep: 0.18 | step_microstep: 0.18 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1353 +[2025-05-15 01:28:56,338] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 265.66 | bwd_microstep: 389.66 | bwd_inner_microstep: 389.62 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.27 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-15 01:28:57,107] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 354.62 | bwd_microstep: 391.82 | bwd_inner_microstep: 391.78 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.08 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-15 01:28:58,158] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 398.55 | bwd_microstep: 626.84 | bwd_inner_microstep: 626.77 | bwd_allreduce_microstep: 0.02 | step_microstep: 2.32 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-15 01:28:59,276] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.01 | optimizer_gradients: 2.15 | optimizer_step: 18.23 +[2025-05-15 01:28:59,277] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 358.28 | bwd_microstep: 711.78 | bwd_inner_microstep: 503.19 | bwd_allreduce_microstep: 208.32 | step_microstep: 27.79 +[2025-05-15 01:28:59,278] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2682.35 | bwd: 3899.60 | bwd_inner: 3689.42 | bwd_allreduce: 208.57 | step: 34.83 + 95%|█████████▍| 529/558 [1:00:54<03:21, 6.95s/it] {'loss': 4.0203, 'grad_norm': 22.500808715820312, 'learning_rate': 7.073178305320726e-18, 'epoch': 0.28} + 95%|█████████▍| 529/558 [1:00:54<03:21, 6.95s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1891 +[2025-05-15 01:29:00,071] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 351.78 | bwd_microstep: 412.18 | bwd_inner_microstep: 412.14 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.82 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-15 01:29:01,099] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 414.05 | bwd_microstep: 587.92 | bwd_inner_microstep: 587.86 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-15 01:29:01,984] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 358.91 | bwd_microstep: 506.87 | bwd_inner_microstep: 506.65 | bwd_allreduce_microstep: 0.19 | step_microstep: 0.19 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1100 +[2025-05-15 01:29:02,526] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 212.67 | bwd_microstep: 310.48 | bwd_inner_microstep: 310.27 | bwd_allreduce_microstep: 0.18 | step_microstep: 0.17 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-15 01:29:03,412] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 358.02 | bwd_microstep: 507.08 | bwd_inner_microstep: 506.86 | bwd_allreduce_microstep: 0.18 | step_microstep: 0.24 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-15 01:29:04,296] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 357.18 | bwd_microstep: 507.08 | bwd_inner_microstep: 506.80 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.22 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-15 01:29:05,060] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 222.33 | bwd_microstep: 518.12 | bwd_inner_microstep: 518.09 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-15 01:29:06,299] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.12 | optimizer_step: 19.24 +[2025-05-15 01:29:06,299] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 443.35 | bwd_microstep: 733.37 | bwd_inner_microstep: 524.95 | bwd_allreduce_microstep: 208.40 | step_microstep: 27.63 +[2025-05-15 01:29:06,300] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2718.28 | bwd: 4083.10 | bwd_inner: 3873.63 | bwd_allreduce: 209.00 | step: 32.83 + 95%|█████████▍| 530/558 [1:01:01<03:15, 6.97s/it] {'loss': 3.9999, 'grad_norm': 17.915586471557617, 'learning_rate': 6.594840079366171e-18, 'epoch': 0.29} + 95%|█████████▍| 530/558 [1:01:01<03:15, 6.97s/it]dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 933 +[2025-05-15 01:29:06,784] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 196.46 | bwd_microstep: 262.86 | bwd_inner_microstep: 262.62 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.49 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 370 +[2025-05-15 01:29:07,041] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 103.58 | bwd_microstep: 135.63 | bwd_inner_microstep: 135.21 | bwd_allreduce_microstep: 0.21 | step_microstep: 0.24 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-15 01:29:07,918] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 358.57 | bwd_microstep: 499.34 | bwd_inner_microstep: 498.89 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.26 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1897 +[2025-05-15 01:29:08,809] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 361.22 | bwd_microstep: 508.78 | bwd_inner_microstep: 508.75 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.26 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-15 01:29:09,570] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 355.18 | bwd_microstep: 384.17 | bwd_inner_microstep: 384.12 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.80 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-15 01:29:10,622] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 401.08 | bwd_microstep: 624.74 | bwd_inner_microstep: 624.70 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.97 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-15 01:29:11,498] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 350.44 | bwd_microstep: 505.22 | bwd_inner_microstep: 504.96 | bwd_allreduce_microstep: 0.22 | step_microstep: 0.22 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-15 01:29:12,612] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.01 | optimizer_gradients: 2.09 | optimizer_step: 18.43 +[2025-05-15 01:29:12,613] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 356.87 | bwd_microstep: 710.30 | bwd_inner_microstep: 505.22 | bwd_allreduce_microstep: 204.87 | step_microstep: 27.64 +[2025-05-15 01:29:12,613] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2483.41 | bwd: 3631.04 | bwd_inner: 3424.66 | bwd_allreduce: 205.35 | step: 31.67 + 95%|█████████▌| 531/558 [1:01:08<03:02, 6.77s/it] {'loss': 3.3759, 'grad_norm': 35.06434631347656, 'learning_rate': 6.133140104796098e-18, 'epoch': 0.29} + 95%|█████████▌| 531/558 [1:01:08<03:02, 6.77s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1906 +[2025-05-15 01:29:13,500] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 341.46 | bwd_microstep: 517.36 | bwd_inner_microstep: 517.33 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.29 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1364 +[2025-05-15 01:29:14,173] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 254.91 | bwd_microstep: 398.33 | bwd_inner_microstep: 398.09 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.18 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 860 +[2025-05-15 01:29:14,617] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 173.72 | bwd_microstep: 251.28 | bwd_inner_microstep: 251.26 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.30 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-15 01:29:15,382] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 356.19 | bwd_microstep: 383.51 | bwd_inner_microstep: 383.47 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.84 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-15 01:29:16,405] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 414.17 | bwd_microstep: 583.85 | bwd_inner_microstep: 582.88 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.22 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-15 01:29:17,193] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 353.62 | bwd_microstep: 412.12 | bwd_inner_microstep: 412.08 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.80 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-15 01:29:18,194] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 411.67 | bwd_microstep: 561.74 | bwd_inner_microstep: 561.70 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.31 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1854 +[2025-05-15 01:29:19,398] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.01 | optimizer_gradients: 2.13 | optimizer_step: 18.24 +[2025-05-15 01:29:19,399] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 226.47 | bwd_microstep: 931.33 | bwd_inner_microstep: 594.12 | bwd_allreduce_microstep: 337.18 | step_microstep: 27.28 +[2025-05-15 01:29:19,399] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2532.18 | bwd: 4039.54 | bwd_inner: 3700.94 | bwd_allreduce: 337.25 | step: 37.22 + 95%|█████████▌| 532/558 [1:01:14<02:56, 6.78s/it] {'loss': 4.3946, 'grad_norm': 23.520328521728516, 'learning_rate': 5.688093950722451e-18, 'epoch': 0.29} + 95%|█████████▌| 532/558 [1:01:14<02:56, 6.78s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1898 +[2025-05-15 01:29:20,247] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 231.22 | bwd_microstep: 587.45 | bwd_inner_microstep: 587.40 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-15 01:29:21,052] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 413.37 | bwd_microstep: 359.30 | bwd_inner_microstep: 358.99 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-15 01:29:21,945] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 270.73 | bwd_microstep: 604.74 | bwd_inner_microstep: 604.69 | bwd_allreduce_microstep: 0.02 | step_microstep: 2.62 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 327 +[2025-05-15 01:29:22,225] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 100.17 | bwd_microstep: 147.31 | bwd_inner_microstep: 146.93 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.34 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1349 +[2025-05-15 01:29:22,790] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 233.54 | bwd_microstep: 309.72 | bwd_inner_microstep: 309.68 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.74 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1101 +[2025-05-15 01:29:23,446] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 249.90 | bwd_microstep: 382.48 | bwd_inner_microstep: 382.44 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-15 01:29:24,169] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 345.29 | bwd_microstep: 343.19 | bwd_inner_microstep: 342.88 | bwd_allreduce_microstep: 0.15 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-15 01:29:25,407] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.01 | optimizer_gradients: 2.19 | optimizer_step: 18.21 +[2025-05-15 01:29:25,408] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 353.01 | bwd_microstep: 841.70 | bwd_inner_microstep: 618.21 | bwd_allreduce_microstep: 223.47 | step_microstep: 27.45 +[2025-05-15 01:29:25,408] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2197.19 | bwd: 3575.93 | bwd_inner: 3351.36 | bwd_allreduce: 223.78 | step: 36.89 + 96%|█████████▌| 533/558 [1:01:20<02:43, 6.55s/it] {'loss': 4.6922, 'grad_norm': 18.739233016967773, 'learning_rate': 5.259716624669342e-18, 'epoch': 0.29} + 96%|█████████▌| 533/558 [1:01:20<02:43, 6.55s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1893 +[2025-05-15 01:29:26,217] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 274.47 | bwd_microstep: 504.88 | bwd_inner_microstep: 504.85 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1897 +[2025-05-15 01:29:27,216] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 442.42 | bwd_microstep: 525.00 | bwd_inner_microstep: 524.78 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.37 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1887 +[2025-05-15 01:29:28,017] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 359.07 | bwd_microstep: 419.48 | bwd_inner_microstep: 419.44 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.85 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1888 +[2025-05-15 01:29:29,029] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 435.75 | bwd_microstep: 551.88 | bwd_inner_microstep: 551.42 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-15 01:29:29,562] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 211.42 | bwd_microstep: 299.38 | bwd_inner_microstep: 299.34 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.81 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 846 +[2025-05-15 01:29:30,080] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 206.23 | bwd_microstep: 287.25 | bwd_inner_microstep: 287.22 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.33 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-15 01:29:30,943] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 411.82 | bwd_microstep: 419.24 | bwd_inner_microstep: 418.93 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-15 01:29:32,189] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.01 | optimizer_gradients: 2.15 | optimizer_step: 18.61 +[2025-05-15 01:29:32,189] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 357.47 | bwd_microstep: 842.55 | bwd_inner_microstep: 640.17 | bwd_allreduce_microstep: 202.34 | step_microstep: 27.75 +[2025-05-15 01:29:32,190] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2698.62 | bwd: 3849.67 | bwd_inner: 3646.20 | bwd_allreduce: 202.53 | step: 36.58 + 96%|█████████▌| 534/558 [1:01:27<02:38, 6.62s/it] {'loss': 5.0865, 'grad_norm': 31.051706314086914, 'learning_rate': 4.848022572066569e-18, 'epoch': 0.29} + 96%|█████████▌| 534/558 [1:01:27<02:38, 6.62s/it]dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 875 +[2025-05-15 01:29:32,512] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 135.99 | bwd_microstep: 160.80 | bwd_inner_microstep: 160.78 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.71 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 849 +[2025-05-15 01:29:33,024] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 203.38 | bwd_microstep: 284.84 | bwd_inner_microstep: 284.81 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-15 01:29:33,997] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 409.62 | bwd_microstep: 528.87 | bwd_inner_microstep: 528.82 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.14 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-15 01:29:34,796] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 282.66 | bwd_microstep: 494.60 | bwd_inner_microstep: 494.55 | bwd_allreduce_microstep: 0.02 | step_microstep: 2.35 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1364 +[2025-05-15 01:29:35,570] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 332.04 | bwd_microstep: 409.36 | bwd_inner_microstep: 409.12 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-15 01:29:36,361] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 358.37 | bwd_microstep: 411.66 | bwd_inner_microstep: 411.61 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.78 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-15 01:29:37,357] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 408.86 | bwd_microstep: 562.02 | bwd_inner_microstep: 561.97 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.27 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2014 +[2025-05-15 01:29:38,607] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.13 | optimizer_step: 18.26 +[2025-05-15 01:29:38,608] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 248.30 | bwd_microstep: 955.40 | bwd_inner_microstep: 540.96 | bwd_allreduce_microstep: 414.42 | step_microstep: 27.43 +[2025-05-15 01:29:38,608] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2379.21 | bwd: 3807.54 | bwd_inner: 3392.63 | bwd_allreduce: 414.48 | step: 38.22 + 96%|█████████▌| 535/558 [1:01:34<02:30, 6.56s/it] {'loss': 5.3598, 'grad_norm': 28.34482192993164, 'learning_rate': 4.453025675762834e-18, 'epoch': 0.29} + 96%|█████████▌| 535/558 [1:01:34<02:30, 6.56s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1890 +[2025-05-15 01:29:39,405] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 269.68 | bwd_microstep: 497.00 | bwd_inner_microstep: 496.95 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.29 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1890 +[2025-05-15 01:29:40,330] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 446.11 | bwd_microstep: 446.78 | bwd_inner_microstep: 446.47 | bwd_allreduce_microstep: 0.15 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1906 +[2025-05-15 01:29:41,316] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 344.22 | bwd_microstep: 618.36 | bwd_inner_microstep: 618.32 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-15 01:29:42,103] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 356.20 | bwd_microstep: 396.25 | bwd_inner_microstep: 396.02 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.04 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-15 01:29:43,143] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 395.97 | bwd_microstep: 619.64 | bwd_inner_microstep: 619.25 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-15 01:29:43,930] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 318.52 | bwd_microstep: 449.00 | bwd_inner_microstep: 448.70 | bwd_allreduce_microstep: 0.24 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-15 01:29:44,944] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 444.76 | bwd_microstep: 539.16 | bwd_inner_microstep: 538.94 | bwd_allreduce_microstep: 0.18 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-15 01:29:46,080] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 1.69 | optimizer_step: 12.75 +[2025-05-15 01:29:46,080] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 222.70 | bwd_microstep: 873.83 | bwd_inner_microstep: 592.79 | bwd_allreduce_microstep: 280.98 | step_microstep: 19.49 +[2025-05-15 01:29:46,081] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2798.16 | bwd: 4440.03 | bwd_inner: 4157.49 | bwd_allreduce: 281.57 | step: 24.86 + 96%|█████████▌| 536/558 [1:01:41<02:30, 6.83s/it] {'loss': 4.0684, 'grad_norm': 19.00299644470215, 'learning_rate': 4.074739255557292e-18, 'epoch': 0.29} + 96%|█████████▌| 536/558 [1:01:41<02:30, 6.83s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 359 +[2025-05-15 01:29:46,289] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 76.63 | bwd_microstep: 113.13 | bwd_inner_microstep: 112.95 | bwd_allreduce_microstep: 0.17 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1904 +[2025-05-15 01:29:47,084] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 320.53 | bwd_microstep: 456.94 | bwd_inner_microstep: 456.80 | bwd_allreduce_microstep: 0.08 | step_microstep: 0.37 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-15 01:29:48,102] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 442.68 | bwd_microstep: 543.35 | bwd_inner_microstep: 543.29 | bwd_allreduce_microstep: 0.02 | step_microstep: 1.01 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 857 +[2025-05-15 01:29:48,548] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 173.52 | bwd_microstep: 253.21 | bwd_inner_microstep: 253.17 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.75 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-15 01:29:49,361] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 230.18 | bwd_microstep: 560.07 | bwd_inner_microstep: 560.01 | bwd_allreduce_microstep: 0.02 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-15 01:29:50,332] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 422.73 | bwd_microstep: 509.22 | bwd_inner_microstep: 508.99 | bwd_allreduce_microstep: 0.19 | step_microstep: 0.23 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-15 01:29:51,222] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 355.09 | bwd_microstep: 513.49 | bwd_inner_microstep: 513.45 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.30 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-15 01:29:52,444] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.54 | optimizer_gradients: 1.88 | optimizer_step: 16.89 +[2025-05-15 01:29:52,444] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 220.62 | bwd_microstep: 954.00 | bwd_inner_microstep: 596.76 | bwd_allreduce_microstep: 357.20 | step_microstep: 26.95 +[2025-05-15 01:29:52,445] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2241.97 | bwd: 3903.42 | bwd_inner: 3545.43 | bwd_allreduce: 357.67 | step: 32.94 + 96%|█████████▌| 537/558 [1:01:47<02:20, 6.69s/it] {'loss': 3.706, 'grad_norm': 26.047258377075195, 'learning_rate': 3.713176067750568e-18, 'epoch': 0.29} + 96%|█████████▌| 537/558 [1:01:47<02:20, 6.69s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1928 +[2025-05-15 01:29:53,269] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 371.21 | bwd_microstep: 422.60 | bwd_inner_microstep: 422.56 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.87 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1928 +[2025-05-15 01:29:54,333] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 429.31 | bwd_microstep: 608.70 | bwd_inner_microstep: 608.33 | bwd_allreduce_microstep: 0.17 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-15 01:29:55,166] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 355.03 | bwd_microstep: 461.15 | bwd_inner_microstep: 460.89 | bwd_allreduce_microstep: 0.09 | step_microstep: 0.11 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 355 +[2025-05-15 01:29:55,425] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 102.83 | bwd_microstep: 140.49 | bwd_inner_microstep: 140.45 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.31 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-15 01:29:56,441] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 410.46 | bwd_microstep: 580.16 | bwd_inner_microstep: 579.95 | bwd_allreduce_microstep: 0.18 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-15 01:29:57,338] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 357.70 | bwd_microstep: 517.61 | bwd_inner_microstep: 517.58 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.31 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-15 01:29:58,095] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 218.85 | bwd_microstep: 514.71 | bwd_inner_microstep: 514.66 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.58 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2138 +[2025-05-15 01:29:59,388] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.07 | optimizer_gradients: 2.23 | optimizer_step: 18.20 +[2025-05-15 01:29:59,388] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 469.91 | bwd_microstep: 762.82 | bwd_inner_microstep: 601.08 | bwd_allreduce_microstep: 161.68 | step_microstep: 28.42 +[2025-05-15 01:29:59,389] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2715.28 | bwd: 4008.28 | bwd_inner: 3845.75 | bwd_allreduce: 162.16 | step: 35.98 + 96%|█████████▋| 538/558 [1:01:54<02:15, 6.77s/it] {'loss': 2.9123, 'grad_norm': 7.248489856719971, 'learning_rate': 3.368348304714608e-18, 'epoch': 0.29} + 96%|█████████▋| 538/558 [1:01:54<02:15, 6.77s/it]dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1162 +[2025-05-15 01:30:00,000] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 218.49 | bwd_microstep: 366.68 | bwd_inner_microstep: 366.62 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.45 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1883 +[2025-05-15 01:30:00,987] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 428.55 | bwd_microstep: 526.27 | bwd_inner_microstep: 525.88 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.17 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1897 +[2025-05-15 01:30:01,763] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 359.65 | bwd_microstep: 394.29 | bwd_inner_microstep: 394.25 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.76 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1891 +[2025-05-15 01:30:02,761] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 400.82 | bwd_microstep: 570.34 | bwd_inner_microstep: 570.10 | bwd_allreduce_microstep: 0.08 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-15 01:30:03,576] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 303.08 | bwd_microstep: 496.37 | bwd_inner_microstep: 496.11 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.11 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1108 +[2025-05-15 01:30:04,063] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 131.43 | bwd_microstep: 333.61 | bwd_inner_microstep: 333.55 | bwd_allreduce_microstep: 0.02 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-15 01:30:05,062] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 438.11 | bwd_microstep: 526.17 | bwd_inner_microstep: 526.13 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.25 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-15 01:30:06,089] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.01 | optimizer_step: 16.58 +[2025-05-15 01:30:06,089] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 350.90 | bwd_microstep: 626.58 | bwd_inner_microstep: 516.53 | bwd_allreduce_microstep: 109.98 | step_microstep: 26.66 +[2025-05-15 01:30:06,090] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2630.98 | bwd: 3840.34 | bwd_inner: 3729.32 | bwd_allreduce: 110.38 | step: 33.85 + 97%|█████████▋| 539/558 [1:02:01<02:08, 6.75s/it] {'loss': 3.5969, 'grad_norm': 15.130948066711426, 'learning_rate': 3.0402675944814496e-18, 'epoch': 0.29} + 97%|█████████▋| 539/558 [1:02:01<02:08, 6.75s/it]dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 4333 +[2025-05-15 01:30:08,135] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 703.94 | bwd_microstep: 1316.25 | bwd_inner_microstep: 1315.84 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.24 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1887 +[2025-05-15 01:30:08,954] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 221.18 | bwd_microstep: 572.18 | bwd_inner_microstep: 572.15 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.56 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-15 01:30:09,934] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 426.92 | bwd_microstep: 521.71 | bwd_inner_microstep: 521.49 | bwd_allreduce_microstep: 0.18 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-15 01:30:10,722] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 354.43 | bwd_microstep: 413.16 | bwd_inner_microstep: 413.11 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.79 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-15 01:30:11,724] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 402.61 | bwd_microstep: 571.71 | bwd_inner_microstep: 571.69 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.27 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-15 01:30:12,496] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 347.39 | bwd_microstep: 402.72 | bwd_inner_microstep: 402.67 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.83 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1855 +[2025-05-15 01:30:13,523] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 414.59 | bwd_microstep: 586.29 | bwd_inner_microstep: 585.91 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1899 +[2025-05-15 01:30:14,638] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.21 | optimizer_gradients: 2.14 | optimizer_step: 18.56 +[2025-05-15 01:30:14,638] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 358.75 | bwd_microstep: 709.93 | bwd_inner_microstep: 510.60 | bwd_allreduce_microstep: 199.29 | step_microstep: 27.66 +[2025-05-15 01:30:14,639] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 3229.83 | bwd: 5093.93 | bwd_inner: 4893.47 | bwd_allreduce: 199.69 | step: 36.72 + 97%|█████████▋| 540/558 [1:02:10<02:11, 7.29s/it] {'loss': 6.174, 'grad_norm': 34.222267150878906, 'learning_rate': 2.7289450003510356e-18, 'epoch': 0.29} + 97%|█████████▋| 540/558 [1:02:10<02:11, 7.29s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-15 01:30:15,540] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 354.67 | bwd_microstep: 518.90 | bwd_inner_microstep: 518.52 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.17 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-15 01:30:16,376] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 221.93 | bwd_microstep: 593.05 | bwd_inner_microstep: 593.00 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-15 01:30:17,348] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 426.23 | bwd_microstep: 509.63 | bwd_inner_microstep: 509.36 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.93 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 325 +[2025-05-15 01:30:17,598] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 94.75 | bwd_microstep: 137.62 | bwd_inner_microstep: 137.54 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.43 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-15 01:30:18,363] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 352.32 | bwd_microstep: 391.59 | bwd_inner_microstep: 391.55 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.10 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 322 +[2025-05-15 01:30:18,617] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 97.40 | bwd_microstep: 134.69 | bwd_inner_microstep: 134.52 | bwd_allreduce_microstep: 0.09 | step_microstep: 0.27 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-15 01:30:19,636] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 440.46 | bwd_microstep: 549.08 | bwd_inner_microstep: 549.03 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.92 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 322 +[2025-05-15 01:30:20,125] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.01 | optimizer_gradients: 2.09 | optimizer_step: 18.38 +[2025-05-15 01:30:20,126] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 90.39 | bwd_microstep: 351.15 | bwd_inner_microstep: 153.23 | bwd_allreduce_microstep: 197.89 | step_microstep: 29.01 +[2025-05-15 01:30:20,126] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2078.18 | bwd: 3185.91 | bwd_inner: 2986.76 | bwd_allreduce: 198.20 | step: 35.17 + 97%|█████████▋| 541/558 [1:02:15<01:54, 6.75s/it] {'loss': 4.6676, 'grad_norm': 27.063522338867188, 'learning_rate': 2.434391020518512e-18, 'epoch': 0.29} + 97%|█████████▋| 541/558 [1:02:15<01:54, 6.75s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1899 +[2025-05-15 01:30:21,023] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 345.96 | bwd_microstep: 523.23 | bwd_inner_microstep: 523.19 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.05 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1890 +[2025-05-15 01:30:21,862] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 231.07 | bwd_microstep: 584.60 | bwd_inner_microstep: 584.56 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.49 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-15 01:30:22,833] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 425.19 | bwd_microstep: 510.99 | bwd_inner_microstep: 510.54 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.25 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-15 01:30:23,596] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 358.04 | bwd_microstep: 382.59 | bwd_inner_microstep: 382.54 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.84 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-15 01:30:24,627] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 399.05 | bwd_microstep: 605.24 | bwd_inner_microstep: 604.47 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.22 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-15 01:30:25,512] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 354.85 | bwd_microstep: 508.65 | bwd_inner_microstep: 508.60 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.29 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-15 01:30:26,323] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 239.20 | bwd_microstep: 549.60 | bwd_inner_microstep: 549.54 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-15 01:30:27,541] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.01 | optimizer_gradients: 2.11 | optimizer_step: 18.29 +[2025-05-15 01:30:27,542] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 426.49 | bwd_microstep: 730.56 | bwd_inner_microstep: 511.46 | bwd_allreduce_microstep: 219.07 | step_microstep: 27.33 +[2025-05-15 01:30:27,542] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2779.86 | bwd: 4395.45 | bwd_inner: 4174.90 | bwd_allreduce: 219.88 | step: 35.81 + 97%|█████████▋| 542/558 [1:02:23<01:51, 6.95s/it] {'loss': 7.1714, 'grad_norm': 32.237998962402344, 'learning_rate': 2.1566155877197903e-18, 'epoch': 0.29} + 97%|█████████▋| 542/558 [1:02:23<01:51, 6.95s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1908 +[2025-05-15 01:30:28,348] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 327.22 | bwd_microstep: 450.18 | bwd_inner_microstep: 449.98 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.07 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1891 +[2025-05-15 01:30:29,378] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 443.26 | bwd_microstep: 553.23 | bwd_inner_microstep: 553.21 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.31 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1891 +[2025-05-15 01:30:30,226] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 361.58 | bwd_microstep: 464.87 | bwd_inner_microstep: 464.58 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1890 +[2025-05-15 01:30:31,188] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 325.81 | bwd_microstep: 615.70 | bwd_inner_microstep: 615.68 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1878 +[2025-05-15 01:30:32,097] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 365.36 | bwd_microstep: 509.99 | bwd_inner_microstep: 509.95 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.24 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-15 01:30:32,856] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 351.47 | bwd_microstep: 384.78 | bwd_inner_microstep: 384.73 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.82 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-15 01:30:33,894] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 399.62 | bwd_microstep: 611.36 | bwd_inner_microstep: 611.32 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.26 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-15 01:30:34,814] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.12 | optimizer_step: 19.01 +[2025-05-15 01:30:34,815] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 349.44 | bwd_microstep: 523.19 | bwd_inner_microstep: 460.03 | bwd_allreduce_microstep: 63.02 | step_microstep: 27.18 +[2025-05-15 01:30:34,815] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2923.75 | bwd: 4113.31 | bwd_inner: 4049.59 | bwd_allreduce: 63.14 | step: 34.34 + 97%|█████████▋| 543/558 [1:02:30<01:45, 7.05s/it] {'loss': 3.6789, 'grad_norm': 20.50782585144043, 'learning_rate': 1.8956280688967044e-18, 'epoch': 0.29} + 97%|█████████▋| 543/558 [1:02:30<01:45, 7.05s/it]dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 371 +[2025-05-15 01:30:35,123] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 108.20 | bwd_microstep: 164.62 | bwd_inner_microstep: 164.57 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.56 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-15 01:30:36,111] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 440.82 | bwd_microstep: 514.19 | bwd_inner_microstep: 513.93 | bwd_allreduce_microstep: 0.23 | step_microstep: 0.24 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-15 01:30:36,904] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 356.61 | bwd_microstep: 415.37 | bwd_inner_microstep: 415.35 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.94 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 838 +[2025-05-15 01:30:37,414] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 189.67 | bwd_microstep: 295.32 | bwd_inner_microstep: 295.29 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-15 01:30:38,340] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 380.13 | bwd_microstep: 512.65 | bwd_inner_microstep: 512.61 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.25 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-15 01:30:39,173] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 213.27 | bwd_microstep: 595.78 | bwd_inner_microstep: 595.73 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.37 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-15 01:30:40,130] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 408.08 | bwd_microstep: 515.01 | bwd_inner_microstep: 514.97 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.28 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1345 +[2025-05-15 01:30:41,308] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.17 | optimizer_step: 19.29 +[2025-05-15 01:30:41,308] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 262.47 | bwd_microstep: 865.73 | bwd_inner_microstep: 266.05 | bwd_allreduce_microstep: 599.65 | step_microstep: 28.95 +[2025-05-15 01:30:41,309] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2359.23 | bwd: 3878.67 | bwd_inner: 3278.51 | bwd_allreduce: 599.94 | step: 40.95 + 97%|█████████▋| 544/558 [1:02:36<01:36, 6.88s/it] {'loss': 5.0123, 'grad_norm': 31.58932113647461, 'learning_rate': 1.6514372648813726e-18, 'epoch': 0.29} + 97%|█████████▋| 544/558 [1:02:36<01:36, 6.88s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1910 +[2025-05-15 01:30:42,160] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 359.22 | bwd_microstep: 464.17 | bwd_inner_microstep: 463.85 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-15 01:30:43,136] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 341.75 | bwd_microstep: 614.80 | bwd_inner_microstep: 614.76 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.47 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 342 +[2025-05-15 01:30:43,419] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 103.79 | bwd_microstep: 147.42 | bwd_inner_microstep: 146.47 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-15 01:30:44,253] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 226.66 | bwd_microstep: 585.04 | bwd_inner_microstep: 585.00 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-15 01:30:45,218] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 425.25 | bwd_microstep: 507.18 | bwd_inner_microstep: 506.87 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.22 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1348 +[2025-05-15 01:30:45,887] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 260.87 | bwd_microstep: 387.00 | bwd_inner_microstep: 386.97 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.27 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-15 01:30:46,686] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 322.04 | bwd_microstep: 454.53 | bwd_inner_microstep: 454.31 | bwd_allreduce_microstep: 0.18 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-15 01:30:47,937] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.26 | optimizer_gradients: 2.07 | optimizer_step: 16.65 +[2025-05-15 01:30:47,938] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 443.82 | bwd_microstep: 752.03 | bwd_inner_microstep: 549.76 | bwd_allreduce_microstep: 202.23 | step_microstep: 27.55 +[2025-05-15 01:30:47,939] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2483.38 | bwd: 3912.17 | bwd_inner: 3708.08 | bwd_allreduce: 202.39 | step: 35.37 + 98%|█████████▊| 545/558 [1:02:43<01:28, 6.80s/it] {'loss': 4.4911, 'grad_norm': 19.025190353393555, 'learning_rate': 1.4240514100992141e-18, 'epoch': 0.29} + 98%|█████████▊| 545/558 [1:02:43<01:28, 6.80s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1871 +[2025-05-15 01:30:48,714] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 354.82 | bwd_microstep: 392.19 | bwd_inner_microstep: 392.14 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.78 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-15 01:30:49,752] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 401.34 | bwd_microstep: 608.86 | bwd_inner_microstep: 608.82 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.30 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-15 01:30:50,640] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 360.52 | bwd_microstep: 507.02 | bwd_inner_microstep: 506.98 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.26 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-15 01:30:51,232] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 215.75 | bwd_microstep: 354.07 | bwd_inner_microstep: 354.05 | bwd_allreduce_microstep: 0.00 | step_microstep: 1.89 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1868 +[2025-05-15 01:30:52,249] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 409.31 | bwd_microstep: 580.63 | bwd_inner_microstep: 580.38 | bwd_allreduce_microstep: 0.20 | step_microstep: 0.17 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1864 +[2025-05-15 01:30:53,136] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 358.47 | bwd_microstep: 506.29 | bwd_inner_microstep: 505.79 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.99 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1858 +[2025-05-15 01:30:53,938] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 235.80 | bwd_microstep: 542.36 | bwd_inner_microstep: 542.31 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1870 +[2025-05-15 01:30:55,120] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.06 | optimizer_gradients: 2.19 | optimizer_step: 18.19 +[2025-05-15 01:30:55,120] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 426.12 | bwd_microstep: 693.59 | bwd_inner_microstep: 530.21 | bwd_allreduce_microstep: 163.30 | step_microstep: 28.27 +[2025-05-15 01:30:55,121] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2762.12 | bwd: 4185.00 | bwd_inner: 4020.68 | bwd_allreduce: 163.57 | step: 37.27 + 98%|█████████▊| 546/558 [1:02:50<01:23, 6.92s/it] {'loss': 5.0709, 'grad_norm': 16.50961685180664, 'learning_rate': 1.2134781722912824e-18, 'epoch': 0.29} + 98%|█████████▊| 546/558 [1:02:50<01:23, 6.92s/it]dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1382 +[2025-05-15 01:30:55,859] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 257.94 | bwd_microstep: 453.79 | bwd_inner_microstep: 453.74 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 859 +[2025-05-15 01:30:56,366] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 226.49 | bwd_microstep: 248.35 | bwd_inner_microstep: 248.12 | bwd_allreduce_microstep: 0.18 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-15 01:30:57,243] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 357.14 | bwd_microstep: 500.02 | bwd_inner_microstep: 499.85 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1884 +[2025-05-15 01:30:58,136] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 270.47 | bwd_microstep: 601.93 | bwd_inner_microstep: 601.88 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-15 01:30:59,025] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 391.69 | bwd_microstep: 463.41 | bwd_inner_microstep: 463.22 | bwd_allreduce_microstep: 0.08 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1874 +[2025-05-15 01:30:59,958] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 305.10 | bwd_microstep: 606.35 | bwd_inner_microstep: 606.31 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.29 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 839 +[2025-05-15 01:31:00,412] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 195.35 | bwd_microstep: 226.20 | bwd_inner_microstep: 226.16 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.75 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1862 +[2025-05-15 01:31:01,684] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.18 | optimizer_step: 18.47 +[2025-05-15 01:31:01,684] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 279.05 | bwd_microstep: 944.01 | bwd_inner_microstep: 496.35 | bwd_allreduce_microstep: 447.64 | step_microstep: 29.11 +[2025-05-15 01:31:01,685] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2283.18 | bwd: 4044.06 | bwd_inner: 3595.69 | bwd_allreduce: 448.00 | step: 37.26 + 98%|█████████▊| 547/558 [1:02:57<01:14, 6.81s/it] {'loss': 3.2722, 'grad_norm': 12.19112491607666, 'learning_rate': 1.0197246522557492e-18, 'epoch': 0.29} + 98%|█████████▊| 547/558 [1:02:57<01:14, 6.81s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-15 01:31:02,448] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 335.76 | bwd_microstep: 402.33 | bwd_inner_microstep: 402.29 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.79 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1359 +[2025-05-15 01:31:03,246] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 304.65 | bwd_microstep: 469.32 | bwd_inner_microstep: 469.02 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.96 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-15 01:31:04,012] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 351.28 | bwd_microstep: 395.17 | bwd_inner_microstep: 394.95 | bwd_allreduce_microstep: 0.19 | step_microstep: 0.23 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1860 +[2025-05-15 01:31:05,048] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 390.54 | bwd_microstep: 621.36 | bwd_inner_microstep: 621.14 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-15 01:31:05,806] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 356.62 | bwd_microstep: 379.54 | bwd_inner_microstep: 379.50 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.81 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1961 +[2025-05-15 01:31:06,888] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 422.78 | bwd_microstep: 634.34 | bwd_inner_microstep: 633.92 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.23 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1955 +[2025-05-15 01:31:07,720] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 373.47 | bwd_microstep: 437.55 | bwd_inner_microstep: 437.35 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1904 +[2025-05-15 01:31:09,007] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 1.69 | optimizer_step: 15.56 +[2025-05-15 01:31:09,008] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 398.38 | bwd_microstep: 842.65 | bwd_inner_microstep: 641.05 | bwd_allreduce_microstep: 201.57 | step_microstep: 24.79 +[2025-05-15 01:31:09,009] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2933.48 | bwd: 4182.25 | bwd_inner: 3979.23 | bwd_allreduce: 201.99 | step: 30.21 + 98%|█████████▊| 548/558 [1:03:04<01:09, 6.97s/it] {'loss': 5.2906, 'grad_norm': 26.918663024902344, 'learning_rate': 8.427973836084846e-19, 'epoch': 0.29} + 98%|█████████▊| 548/558 [1:03:04<01:09, 6.97s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1912 +[2025-05-15 01:31:09,798] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 308.97 | bwd_microstep: 451.74 | bwd_inner_microstep: 451.49 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1910 +[2025-05-15 01:31:10,826] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 447.32 | bwd_microstep: 548.43 | bwd_inner_microstep: 548.18 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.17 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-15 01:31:11,612] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 357.62 | bwd_microstep: 404.03 | bwd_inner_microstep: 404.00 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.33 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 854 +[2025-05-15 01:31:12,148] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 196.66 | bwd_microstep: 315.08 | bwd_inner_microstep: 315.04 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-15 01:31:12,987] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 384.12 | bwd_microstep: 422.82 | bwd_inner_microstep: 422.59 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-15 01:31:13,988] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 359.03 | bwd_microstep: 621.07 | bwd_inner_microstep: 621.03 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.33 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 338 +[2025-05-15 01:31:14,265] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 110.85 | bwd_microstep: 137.23 | bwd_inner_microstep: 137.20 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.24 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-15 01:31:15,592] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 1.71 | optimizer_step: 17.78 +[2025-05-15 01:31:15,593] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 351.87 | bwd_microstep: 928.60 | bwd_inner_microstep: 413.80 | bwd_allreduce_microstep: 514.77 | step_microstep: 26.95 +[2025-05-15 01:31:15,593] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2516.42 | bwd: 3829.39 | bwd_inner: 3313.40 | bwd_allreduce: 514.91 | step: 34.69 + 98%|█████████▊| 549/558 [1:03:11<01:01, 6.85s/it] {'loss': 4.9023, 'grad_norm': 16.073734283447266, 'learning_rate': 6.827023325626237e-19, 'epoch': 0.3} + 98%|█████████▊| 549/558 [1:03:11<01:01, 6.85s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1887 +[2025-05-15 01:31:16,487] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 350.52 | bwd_microstep: 515.99 | bwd_inner_microstep: 515.78 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1885 +[2025-05-15 01:31:17,281] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 283.67 | bwd_microstep: 488.46 | bwd_inner_microstep: 488.43 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.34 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1354 +[2025-05-15 01:31:18,078] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 330.86 | bwd_microstep: 429.29 | bwd_inner_microstep: 429.24 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.31 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-15 01:31:18,967] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 358.63 | bwd_microstep: 506.71 | bwd_inner_microstep: 506.69 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.25 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-15 01:31:19,723] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 345.27 | bwd_microstep: 391.88 | bwd_inner_microstep: 391.78 | bwd_allreduce_microstep: 0.04 | step_microstep: 0.26 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1857 +[2025-05-15 01:31:20,766] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 391.21 | bwd_microstep: 624.88 | bwd_inner_microstep: 624.83 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.33 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1940 +[2025-05-15 01:31:21,694] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 368.72 | bwd_microstep: 537.50 | bwd_inner_microstep: 537.46 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.24 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1856 +[2025-05-15 01:31:22,916] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.19 | optimizer_step: 18.36 +[2025-05-15 01:31:22,917] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 214.78 | bwd_microstep: 957.85 | bwd_inner_microstep: 592.51 | bwd_allreduce_microstep: 365.31 | step_microstep: 29.36 +[2025-05-15 01:31:22,918] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2643.65 | bwd: 4453.71 | bwd_inner: 4086.72 | bwd_allreduce: 365.43 | step: 36.27 + 99%|█████████▊| 550/558 [1:03:18<00:55, 6.99s/it] {'loss': 6.7195, 'grad_norm': 43.91684341430664, 'learning_rate': 5.394448977276146e-19, 'epoch': 0.3} + 99%|█████████▊| 550/558 [1:03:18<00:55, 6.99s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1954 +[2025-05-15 01:31:23,844] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 353.39 | bwd_microstep: 545.72 | bwd_inner_microstep: 545.47 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1897 +[2025-05-15 01:31:24,526] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 319.28 | bwd_microstep: 341.61 | bwd_inner_microstep: 341.57 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.93 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1881 +[2025-05-15 01:31:25,569] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 407.99 | bwd_microstep: 610.37 | bwd_inner_microstep: 610.33 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.10 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1879 +[2025-05-15 01:31:26,453] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 359.26 | bwd_microstep: 503.43 | bwd_inner_microstep: 503.39 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.30 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1886 +[2025-05-15 01:31:27,217] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 353.24 | bwd_microstep: 386.81 | bwd_inner_microstep: 386.76 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.95 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-15 01:31:28,253] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 420.98 | bwd_microstep: 588.98 | bwd_inner_microstep: 588.52 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.21 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1354 +[2025-05-15 01:31:28,915] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 260.32 | bwd_microstep: 381.03 | bwd_inner_microstep: 380.27 | bwd_allreduce_microstep: 0.73 | step_microstep: 0.22 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1859 +[2025-05-15 01:31:29,895] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.18 | optimizer_step: 20.95 +[2025-05-15 01:31:29,896] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 341.68 | bwd_microstep: 586.67 | bwd_inner_microstep: 498.49 | bwd_allreduce_microstep: 88.03 | step_microstep: 30.92 +[2025-05-15 01:31:29,896] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2816.13 | bwd: 3944.79 | bwd_inner: 3854.87 | bwd_allreduce: 88.83 | step: 36.81 + 99%|█████████▊| 551/558 [1:03:25<00:48, 6.99s/it] {'loss': 3.4939, 'grad_norm': 21.405439376831055, 'learning_rate': 4.130299099268653e-19, 'epoch': 0.3} + 99%|█████████▊| 551/558 [1:03:25<00:48, 6.99s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1889 +[2025-05-15 01:31:30,955] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 396.26 | bwd_microstep: 631.22 | bwd_inner_microstep: 631.18 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1898 +[2025-05-15 01:31:31,853] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 360.16 | bwd_microstep: 518.03 | bwd_inner_microstep: 517.98 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.29 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1376 +[2025-05-15 01:31:32,412] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 266.98 | bwd_microstep: 272.20 | bwd_inner_microstep: 272.03 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1882 +[2025-05-15 01:31:33,372] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 323.29 | bwd_microstep: 616.45 | bwd_inner_microstep: 616.40 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.42 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1875 +[2025-05-15 01:31:34,288] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 365.49 | bwd_microstep: 517.87 | bwd_inner_microstep: 517.46 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-15 01:31:35,164] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 356.12 | bwd_microstep: 499.29 | bwd_inner_microstep: 498.97 | bwd_allreduce_microstep: 0.13 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1865 +[2025-05-15 01:31:36,053] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 268.10 | bwd_microstep: 601.99 | bwd_inner_microstep: 601.94 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.51 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-15 01:31:37,237] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.16 | optimizer_step: 19.11 +[2025-05-15 01:31:37,237] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 384.34 | bwd_microstep: 736.20 | bwd_inner_microstep: 524.35 | bwd_allreduce_microstep: 211.81 | step_microstep: 29.08 +[2025-05-15 01:31:37,238] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2720.70 | bwd: 4393.26 | bwd_inner: 4180.41 | bwd_allreduce: 212.03 | step: 34.88 + 99%|█████████▉| 552/558 [1:03:32<00:42, 7.09s/it] {'loss': 3.6128, 'grad_norm': 7.910003662109375, 'learning_rate': 3.034616320349293e-19, 'epoch': 0.3} + 99%|█████████▉| 552/558 [1:03:32<00:42, 7.09s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 2087 +[2025-05-15 01:31:38,116] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 369.37 | bwd_microstep: 479.76 | bwd_inner_microstep: 479.49 | bwd_allreduce_microstep: 0.09 | step_microstep: 0.14 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 334 +[2025-05-15 01:31:38,389] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 102.66 | bwd_microstep: 152.32 | bwd_inner_microstep: 152.27 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.09 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1880 +[2025-05-15 01:31:39,416] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 446.46 | bwd_microstep: 549.21 | bwd_inner_microstep: 549.18 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.00 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-15 01:31:40,300] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 337.49 | bwd_microstep: 524.42 | bwd_inner_microstep: 524.39 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.96 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1888 +[2025-05-15 01:31:41,086] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 353.74 | bwd_microstep: 408.85 | bwd_inner_microstep: 408.80 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.86 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1873 +[2025-05-15 01:31:42,107] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 414.28 | bwd_microstep: 579.77 | bwd_inner_microstep: 579.42 | bwd_allreduce_microstep: 0.18 | step_microstep: 0.21 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1867 +[2025-05-15 01:31:43,004] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 358.45 | bwd_microstep: 516.91 | bwd_inner_microstep: 516.86 | bwd_allreduce_microstep: 0.02 | step_microstep: 1.91 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1997 +[2025-05-15 01:31:44,377] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.01 | optimizer_gradients: 2.26 | optimizer_step: 18.78 +[2025-05-15 01:31:44,378] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 338.75 | bwd_microstep: 983.59 | bwd_inner_microstep: 496.51 | bwd_allreduce_microstep: 487.06 | step_microstep: 30.37 +[2025-05-15 01:31:44,379] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2721.18 | bwd: 4194.84 | bwd_inner: 3706.99 | bwd_allreduce: 487.36 | step: 38.54 + 99%|█████████▉| 553/558 [1:03:39<00:35, 7.11s/it] {'loss': 4.2888, 'grad_norm': 18.081457138061523, 'learning_rate': 2.1074375883400888e-19, 'epoch': 0.3} + 99%|█████████▉| 553/558 [1:03:39<00:35, 7.11s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1896 +[2025-05-15 01:31:45,268] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 349.97 | bwd_microstep: 512.59 | bwd_inner_microstep: 511.59 | bwd_allreduce_microstep: 0.02 | step_microstep: 0.24 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1403 +[2025-05-15 01:31:45,843] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 226.86 | bwd_microstep: 327.00 | bwd_inner_microstep: 326.97 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.80 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-15 01:31:46,866] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 416.28 | bwd_microstep: 581.80 | bwd_inner_microstep: 581.58 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.18 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-15 01:31:47,640] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 355.85 | bwd_microstep: 398.63 | bwd_inner_microstep: 398.41 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.20 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-15 01:31:48,686] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 395.18 | bwd_microstep: 625.81 | bwd_inner_microstep: 625.78 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.24 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1863 +[2025-05-15 01:31:49,431] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 275.61 | bwd_microstep: 452.81 | bwd_inner_microstep: 452.64 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1869 +[2025-05-15 01:31:50,407] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 342.86 | bwd_microstep: 612.97 | bwd_inner_microstep: 612.94 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1918 +[2025-05-15 01:31:51,579] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.07 | optimizer_gradients: 2.21 | optimizer_step: 27.03 +[2025-05-15 01:31:51,580] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 367.63 | bwd_microstep: 735.71 | bwd_inner_microstep: 522.02 | bwd_allreduce_microstep: 213.62 | step_microstep: 37.10 +[2025-05-15 01:31:51,581] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2730.21 | bwd: 4247.34 | bwd_inner: 4031.96 | bwd_allreduce: 213.77 | step: 44.24 + 99%|█████████▉| 554/558 [1:03:47<00:28, 7.14s/it] {'loss': 4.8835, 'grad_norm': 23.184085845947266, 'learning_rate': 1.3487941688899996e-19, 'epoch': 0.3} + 99%|█████████▉| 554/558 [1:03:47<00:28, 7.14s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1905 +[2025-05-15 01:31:52,512] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 296.69 | bwd_microstep: 611.93 | bwd_inner_microstep: 611.90 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.28 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 359 +[2025-05-15 01:31:52,810] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 112.91 | bwd_microstep: 152.56 | bwd_inner_microstep: 152.52 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.20 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 344 +[2025-05-15 01:31:53,077] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 105.45 | bwd_microstep: 143.43 | bwd_inner_microstep: 143.41 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.21 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-15 01:31:53,879] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 281.48 | bwd_microstep: 497.61 | bwd_inner_microstep: 497.57 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.53 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 335 +[2025-05-15 01:31:54,173] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 112.42 | bwd_microstep: 146.01 | bwd_inner_microstep: 145.98 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.55 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-15 01:31:55,082] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 382.45 | bwd_microstep: 494.35 | bwd_inner_microstep: 494.06 | bwd_allreduce_microstep: 0.11 | step_microstep: 0.12 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-15 01:31:55,965] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 252.36 | bwd_microstep: 608.48 | bwd_inner_microstep: 608.42 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.55 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1853 +[2025-05-15 01:31:57,135] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.08 | optimizer_gradients: 2.66 | optimizer_step: 17.86 +[2025-05-15 01:31:57,136] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 389.36 | bwd_microstep: 718.37 | bwd_inner_microstep: 511.06 | bwd_allreduce_microstep: 207.25 | step_microstep: 28.43 +[2025-05-15 01:31:57,137] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 1933.07 | bwd: 3372.75 | bwd_inner: 3164.99 | bwd_allreduce: 207.40 | step: 38.90 + 99%|█████████▉| 555/558 [1:03:52<00:19, 6.66s/it] {'loss': 4.4801, 'grad_norm': 29.08262825012207, 'learning_rate': 7.587116444235376e-20, 'epoch': 0.3} + 99%|█████████▉| 555/558 [1:03:52<00:19, 6.66s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1928 +[2025-05-15 01:31:58,124] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 326.06 | bwd_microstep: 634.17 | bwd_inner_microstep: 634.13 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1894 +[2025-05-15 01:31:58,963] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 368.63 | bwd_microstep: 435.60 | bwd_inner_microstep: 435.41 | bwd_allreduce_microstep: 0.07 | step_microstep: 0.11 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-15 01:31:59,957] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 354.40 | bwd_microstep: 619.67 | bwd_inner_microstep: 619.63 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.53 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1365 +[2025-05-15 01:32:00,643] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 262.19 | bwd_microstep: 391.15 | bwd_inner_microstep: 390.75 | bwd_allreduce_microstep: 0.20 | step_microstep: 0.19 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1877 +[2025-05-15 01:32:01,490] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 361.36 | bwd_microstep: 465.52 | bwd_inner_microstep: 465.34 | bwd_allreduce_microstep: 0.06 | step_microstep: 0.10 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1342 +[2025-05-15 01:32:02,176] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 221.54 | bwd_microstep: 444.62 | bwd_inner_microstep: 444.58 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.35 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1900 +[2025-05-15 01:32:03,152] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 413.12 | bwd_microstep: 526.04 | bwd_inner_microstep: 525.99 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.47 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1897 +[2025-05-15 01:32:04,446] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.00 | optimizer_gradients: 2.07 | optimizer_step: 18.86 +[2025-05-15 01:32:04,446] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 282.86 | bwd_microstep: 961.20 | bwd_inner_microstep: 497.34 | bwd_allreduce_microstep: 463.83 | step_microstep: 28.71 +[2025-05-15 01:32:04,447] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2590.11 | bwd: 4477.98 | bwd_inner: 4013.25 | bwd_allreduce: 464.19 | step: 38.83 + 100%|█████████▉| 556/558 [1:03:59<00:13, 6.86s/it] {'loss': 4.1483, 'grad_norm': 21.846261978149414, 'learning_rate': 3.3720991327534924e-20, 'epoch': 0.3} + 100%|█████████▉| 556/558 [1:03:59<00:13, 6.86s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1916 +[2025-05-15 01:32:05,200] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 343.31 | bwd_microstep: 380.37 | bwd_inner_microstep: 380.32 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.83 +dynamic ViT batch size: 4, images per sample: 4.0, dynamic token length: 1123 +[2025-05-15 01:32:05,852] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 233.56 | bwd_microstep: 394.19 | bwd_inner_microstep: 394.12 | bwd_allreduce_microstep: 0.02 | step_microstep: 2.32 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1876 +[2025-05-15 01:32:06,780] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 383.11 | bwd_microstep: 511.22 | bwd_inner_microstep: 511.20 | bwd_allreduce_microstep: 0.00 | step_microstep: 0.96 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1866 +[2025-05-15 01:32:07,570] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 268.59 | bwd_microstep: 499.49 | bwd_inner_microstep: 499.46 | bwd_allreduce_microstep: 0.00 | step_microstep: 2.34 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1872 +[2025-05-15 01:32:08,567] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | 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[logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 371.69 | bwd_microstep: 974.61 | bwd_inner_microstep: 443.84 | bwd_allreduce_microstep: 530.74 | step_microstep: 29.66 +[2025-05-15 01:32:11,759] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2739.73 | bwd: 4339.31 | bwd_inner: 3806.98 | bwd_allreduce: 530.94 | step: 39.67 + 100%|█████████▉| 557/558 [1:04:07<00:06, 6.99s/it] {'loss': 5.5568, 'grad_norm': 28.59225082397461, 'learning_rate': 8.430318902130641e-21, 'epoch': 0.3} + 100%|█████████▉| 557/558 [1:04:07<00:06, 6.99s/it]dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1895 +[2025-05-15 01:32:12,559] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 353.94 | bwd_microstep: 416.42 | bwd_inner_microstep: 416.39 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.82 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1894 +[2025-05-15 01:32:13,568] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 416.36 | bwd_microstep: 567.74 | bwd_inner_microstep: 567.71 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.29 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1889 +[2025-05-15 01:32:14,330] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 338.10 | bwd_microstep: 399.06 | bwd_inner_microstep: 399.02 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.86 +dynamic ViT batch size: 1, images per sample: 1.0, dynamic token length: 331 +[2025-05-15 01:32:14,597] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 106.33 | bwd_microstep: 135.33 | bwd_inner_microstep: 135.29 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.52 +dynamic ViT batch size: 7, images per sample: 7.0, dynamic token length: 1861 +[2025-05-15 01:32:15,591] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 437.23 | bwd_microstep: 524.28 | bwd_inner_microstep: 524.24 | bwd_allreduce_microstep: 0.01 | step_microstep: 0.19 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1353 +[2025-05-15 01:32:16,122] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 257.58 | bwd_microstep: 253.88 | bwd_inner_microstep: 253.86 | bwd_allreduce_microstep: 0.01 | step_microstep: 1.69 +dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1349 +[2025-05-15 01:32:16,917] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 284.04 | bwd_microstep: 483.48 | bwd_inner_microstep: 483.44 | bwd_allreduce_microstep: 0.01 | step_microstep: 2.36 +dynamic ViT batch size: 3, images per sample: 3.0, dynamic token length: 895 +[2025-05-15 01:32:17,500] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | optimizer_allgather: 0.05 | optimizer_gradients: 2.16 | optimizer_step: 16.96 +[2025-05-15 01:32:17,501] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd_microstep: 188.64 | bwd_microstep: 338.23 | bwd_inner_microstep: 246.54 | bwd_allreduce_microstep: 91.53 | step_microstep: 26.92 +[2025-05-15 01:32:17,502] [INFO] [logging.py:96:log_dist] [Rank 0] time (ms) | fwd: 2382.20 | bwd: 3118.46 | bwd_inner: 3026.57 | bwd_allreduce: 91.61 | step: 37.65 + 100%|██████████| 558/558 [1:04:13<00:00, 6.62s/it] {'loss': 4.3931, 'grad_norm': 11.486595153808594, 'learning_rate': 0.0, 'epoch': 0.3} + 100%|██████████| 558/558 [1:04:13<00:00, 6.62s/it][INFO|trainer.py:3503] 2025-05-15 01:32:20,679 >> Saving model checkpoint to work_dirs/internvl_chat_v2_5/mmvet/checkpoint-558 +[INFO|configuration_utils.py:472] 2025-05-15 01:32:20,682 >> Configuration saved in work_dirs/internvl_chat_v2_5/mmvet/checkpoint-558/config.json +[INFO|configuration_utils.py:807] 2025-05-15 01:32:20,683 >> Configuration saved in work_dirs/internvl_chat_v2_5/mmvet/checkpoint-558/generation_config.json +[INFO|modeling_utils.py:2755] 2025-05-15 01:32:28,027 >> Model weights saved in work_dirs/internvl_chat_v2_5/mmvet/checkpoint-558/model.safetensors +[INFO|tokenization_utils_base.py:2702] 2025-05-15 01:32:28,029 >> tokenizer config file saved in work_dirs/internvl_chat_v2_5/mmvet/checkpoint-558/tokenizer_config.json +[INFO|tokenization_utils_base.py:2711] 2025-05-15 01:32:28,029 >> Special tokens file saved in work_dirs/internvl_chat_v2_5/mmvet/checkpoint-558/special_tokens_map.json +[INFO|tokenization_utils_base.py:2762] 2025-05-15 01:32:28,029 >> added tokens file saved in work_dirs/internvl_chat_v2_5/mmvet/checkpoint-558/added_tokens.json +[2025-05-15 01:32:28,120] [INFO] [logging.py:96:log_dist] [Rank 0] [Torch] Checkpoint global_step558 is about to be saved! +[2025-05-15 01:32:28,140] [INFO] [logging.py:96:log_dist] [Rank 0] Saving model checkpoint: work_dirs/internvl_chat_v2_5/mmvet/checkpoint-558/global_step558/mp_rank_00_model_states.pt +[2025-05-15 01:32:28,140] [INFO] [torch_checkpoint_engine.py:21:save] [Torch] Saving work_dirs/internvl_chat_v2_5/mmvet/checkpoint-558/global_step558/mp_rank_00_model_states.pt... +[2025-05-15 01:32:32,964] [INFO] [torch_checkpoint_engine.py:23:save] [Torch] Saved work_dirs/internvl_chat_v2_5/mmvet/checkpoint-558/global_step558/mp_rank_00_model_states.pt. +[2025-05-15 01:32:32,965] [INFO] [torch_checkpoint_engine.py:21:save] [Torch] Saving work_dirs/internvl_chat_v2_5/mmvet/checkpoint-558/global_step558/bf16_zero_pp_rank_0_mp_rank_00_optim_states.pt... +[2025-05-15 01:32:33,152] [INFO] [torch_checkpoint_engine.py:23:save] [Torch] Saved work_dirs/internvl_chat_v2_5/mmvet/checkpoint-558/global_step558/bf16_zero_pp_rank_0_mp_rank_00_optim_states.pt. +[2025-05-15 01:32:33,152] [INFO] [engine.py:3536:_save_zero_checkpoint] zero checkpoint saved work_dirs/internvl_chat_v2_5/mmvet/checkpoint-558/global_step558/bf16_zero_pp_rank_0_mp_rank_00_optim_states.pt +[2025-05-15 01:32:33,152] [INFO] [torch_checkpoint_engine.py:33:commit] [Torch] Checkpoint global_step558 is ready now! +petrel_client is not installed. If you read data locally instead of from ceph, ignore it. +petrel_client is not installed. Using PIL to load images. +petrel_client is not installed. If you read data locally instead of from ceph, ignore it. +petrel_client is not installed. Using PIL to load images. +petrel_client is not installed. If you read data locally instead of from ceph, ignore it. +petrel_client is not installed. Using PIL to load images. +petrel_client is not installed. If you read data locally instead of from ceph, ignore it. +petrel_client is not installed. Using PIL to load images. +[INFO|trainer.py:2394] 2025-05-15 01:32:35,096 >> + +Training completed. Do not forget to share your model on huggingface.co/models =) + + + {'train_runtime': 3870.6705, 'train_samples_per_second': 1.153, 'train_steps_per_second': 0.144, 'train_loss': 5.00184802257032, 'epoch': 0.3} + 100%|██████████| 558/558 [1:04:30<00:00, 6.62s/it] 100%|██████████| 558/558 [1:04:30<00:00, 6.94s/it] +[INFO|trainer.py:3503] 2025-05-15 01:32:37,763 >> Saving model checkpoint to work_dirs/internvl_chat_v2_5/mmvet +[INFO|configuration_utils.py:472] 2025-05-15 01:32:37,766 >> Configuration saved in work_dirs/internvl_chat_v2_5/mmvet/config.json +[INFO|configuration_utils.py:807] 2025-05-15 01:32:37,767 >> Configuration saved in work_dirs/internvl_chat_v2_5/mmvet/generation_config.json +[INFO|modeling_utils.py:2755] 2025-05-15 01:32:45,557 >> Model weights saved in work_dirs/internvl_chat_v2_5/mmvet/model.safetensors +[INFO|tokenization_utils_base.py:2702] 2025-05-15 01:32:45,559 >> tokenizer config file saved in work_dirs/internvl_chat_v2_5/mmvet/tokenizer_config.json +[INFO|tokenization_utils_base.py:2711] 2025-05-15 01:32:45,559 >> Special tokens file saved in work_dirs/internvl_chat_v2_5/mmvet/special_tokens_map.json +[INFO|tokenization_utils_base.py:2762] 2025-05-15 01:32:45,559 >> added tokens file saved in work_dirs/internvl_chat_v2_5/mmvet/added_tokens.json +***** train metrics ***** + epoch = 0.3001 + total_flos = 185455675152GF + train_loss = 5.0018 + train_runtime = 1:04:30.67 + train_samples = 14874 + train_samples_per_second = 1.153 + train_steps_per_second = 0.144 diff --git a/InternVL-main/internvl_chat/work_dirs/internvl_chat_v2_5/train2/checkpoint-500/generation_config.json b/InternVL-main/internvl_chat/work_dirs/internvl_chat_v2_5/train2/checkpoint-500/generation_config.json new file mode 100644 index 0000000000000000000000000000000000000000..918fe50c5a6fd362e537376348091b2bc5f51820 --- /dev/null +++ b/InternVL-main/internvl_chat/work_dirs/internvl_chat_v2_5/train2/checkpoint-500/generation_config.json @@ -0,0 +1,8 @@ +{ + 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a/InternVL-main/internvl_chat/work_dirs/internvl_chat_v2_5/train2/checkpoint-800/generation_config.json b/InternVL-main/internvl_chat/work_dirs/internvl_chat_v2_5/train2/checkpoint-800/generation_config.json new file mode 100644 index 0000000000000000000000000000000000000000..918fe50c5a6fd362e537376348091b2bc5f51820 --- /dev/null +++ b/InternVL-main/internvl_chat/work_dirs/internvl_chat_v2_5/train2/checkpoint-800/generation_config.json @@ -0,0 +1,8 @@ +{ + "_from_model_config": true, + "eos_token_id": [ + 92542, + 92543 + ], + "transformers_version": "4.43.2" +} diff --git a/InternVL-main/internvl_chat/work_dirs/internvl_chat_v2_5/train2/checkpoint-800/latest b/InternVL-main/internvl_chat/work_dirs/internvl_chat_v2_5/train2/checkpoint-800/latest new file mode 100644 index 0000000000000000000000000000000000000000..57729c0be88118cbd582c8c68b4149cee821f0b4 --- /dev/null +++ b/InternVL-main/internvl_chat/work_dirs/internvl_chat_v2_5/train2/checkpoint-800/latest @@ -0,0 +1 @@ +global_step800 \ No newline at end of file diff --git a/InternVL-main/internvl_chat/work_dirs/internvl_chat_v2_5/train2/checkpoint-800/special_tokens_map.json b/InternVL-main/internvl_chat/work_dirs/internvl_chat_v2_5/train2/checkpoint-800/special_tokens_map.json new file mode 100644 index 0000000000000000000000000000000000000000..cbf34a50d27c43ed8d1e2823b800b4e6f66e637a --- /dev/null +++ b/InternVL-main/internvl_chat/work_dirs/internvl_chat_v2_5/train2/checkpoint-800/special_tokens_map.json @@ -0,0 +1,47 @@ +{ + "additional_special_tokens": [ + "<|im_start|>", + "<|im_end|>", + "<|action_start|>", + "<|action_end|>", + "<|interpreter|>", + "<|plugin|>", + "", + "", + "", + "", + "", + "", + "", + "", + "" + ], + "bos_token": { + "content": "", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false + }, + "eos_token": { + "content": "", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false + }, + "pad_token": { + "content": "", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false + }, + "unk_token": { + "content": "", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false + } +} diff --git a/InternVL-main/internvl_chat/work_dirs/internvl_chat_v2_5/train2/checkpoint-800/tokenization_internlm2.py b/InternVL-main/internvl_chat/work_dirs/internvl_chat_v2_5/train2/checkpoint-800/tokenization_internlm2.py new file mode 100644 index 0000000000000000000000000000000000000000..1be581da37ef678de65f2737493fc0ed7160446e --- /dev/null +++ b/InternVL-main/internvl_chat/work_dirs/internvl_chat_v2_5/train2/checkpoint-800/tokenization_internlm2.py @@ -0,0 +1,235 @@ +# Copyright (c) The InternLM team and The HuggingFace Inc. team. All rights reserved. +# +# This code is based on transformers/src/transformers/models/llama/tokenization_llama.py +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +"""Tokenization classes for InternLM.""" +import os +from shutil import copyfile +from typing import Any, Dict, List, Optional, Tuple + +import sentencepiece as spm +from transformers.tokenization_utils import PreTrainedTokenizer +from transformers.utils import logging + +logger = logging.get_logger(__name__) + +VOCAB_FILES_NAMES = {'vocab_file': './tokenizer.model'} + +PRETRAINED_VOCAB_FILES_MAP = {} + + +# Modified from transformers.model.llama.tokenization_llama.LlamaTokenizer +class InternLM2Tokenizer(PreTrainedTokenizer): + """ + Construct a InternLM2 tokenizer. Based on byte-level Byte-Pair-Encoding. + + Args: + vocab_file (`str`): + Path to the vocabulary file. + """ + + vocab_files_names = VOCAB_FILES_NAMES + pretrained_vocab_files_map = PRETRAINED_VOCAB_FILES_MAP + model_input_names = ['input_ids', 'attention_mask'] + _auto_class = 'AutoTokenizer' + + def __init__( + self, + vocab_file, + unk_token='', + bos_token='', + eos_token='', + pad_token='', + sp_model_kwargs: Optional[Dict[str, Any]] = None, + add_bos_token=True, + add_eos_token=False, + decode_with_prefix_space=False, + clean_up_tokenization_spaces=False, + **kwargs, + ): + self.sp_model_kwargs = {} if sp_model_kwargs is None else sp_model_kwargs + self.vocab_file = vocab_file + self.add_bos_token = add_bos_token + self.add_eos_token = add_eos_token + self.decode_with_prefix_space = decode_with_prefix_space + self.sp_model = spm.SentencePieceProcessor(**self.sp_model_kwargs) + self.sp_model.Load(vocab_file) + self._no_prefix_space_tokens = None + super().__init__( + bos_token=bos_token, + eos_token=eos_token, + unk_token=unk_token, + pad_token=pad_token, + clean_up_tokenization_spaces=clean_up_tokenization_spaces, + **kwargs, + ) + + @property + def no_prefix_space_tokens(self): + if self._no_prefix_space_tokens is None: + vocab = self.convert_ids_to_tokens(list(range(self.vocab_size))) + self._no_prefix_space_tokens = {i for i, tok in enumerate(vocab) if not tok.startswith('▁')} + return self._no_prefix_space_tokens + + @property + def vocab_size(self): + """Returns vocab size""" + return self.sp_model.get_piece_size() + + @property + def bos_token_id(self) -> Optional[int]: + return self.sp_model.bos_id() + + @property + def eos_token_id(self) -> Optional[int]: + return self.sp_model.eos_id() + + def get_vocab(self): + """Returns vocab as a dict""" + vocab = {self.convert_ids_to_tokens(i): i for i in range(self.vocab_size)} + vocab.update(self.added_tokens_encoder) + return vocab + + def _tokenize(self, text): + """Returns a tokenized string.""" + return self.sp_model.encode(text, out_type=str) + + def _convert_token_to_id(self, token): + """Converts a token (str) in an id using the vocab.""" + return self.sp_model.piece_to_id(token) + + def _convert_id_to_token(self, index): + """Converts an index (integer) in a token (str) using the vocab.""" + token = self.sp_model.IdToPiece(index) + return token + + def _maybe_add_prefix_space(self, tokens, decoded): + if tokens and tokens[0] not in self.no_prefix_space_tokens: + return ' ' + decoded + else: + return decoded + + def convert_tokens_to_string(self, tokens): + """Converts a sequence of tokens (string) in a single string.""" + current_sub_tokens = [] + out_string = '' + prev_is_special = False + for token in tokens: + # make sure that special tokens are not decoded using sentencepiece model + if token in self.all_special_tokens: + if not prev_is_special: + out_string += ' ' + out_string += self.sp_model.decode(current_sub_tokens) + token + prev_is_special = True + current_sub_tokens = [] + else: + current_sub_tokens.append(token) + prev_is_special = False + out_string += self.sp_model.decode(current_sub_tokens) + out_string = self.clean_up_tokenization(out_string) + out_string = self._maybe_add_prefix_space(tokens=tokens, decoded=out_string) + return out_string[1:] + + def save_vocabulary(self, save_directory, filename_prefix: Optional[str] = None) -> Tuple[str]: + """ + Save the vocabulary and special tokens file to a directory. + + Args: + save_directory (`str`): + The directory in which to save the vocabulary. + + Returns: + `Tuple(str)`: Paths to the files saved. + """ + if not os.path.isdir(save_directory): + logger.error(f'Vocabulary path ({save_directory}) should be a directory') + return + out_vocab_file = os.path.join( + save_directory, (filename_prefix + '-' if filename_prefix else '') + VOCAB_FILES_NAMES['vocab_file'] + ) + + if os.path.abspath(self.vocab_file) != os.path.abspath(out_vocab_file) and os.path.isfile(self.vocab_file): + copyfile(self.vocab_file, out_vocab_file) + elif not os.path.isfile(self.vocab_file): + with open(out_vocab_file, 'wb') as fi: + content_spiece_model = self.sp_model.serialized_model_proto() + fi.write(content_spiece_model) + + return (out_vocab_file,) + + def build_inputs_with_special_tokens(self, token_ids_0, token_ids_1=None): + if self.add_bos_token: + bos_token_ids = [self.bos_token_id] + else: + bos_token_ids = [] + + output = bos_token_ids + token_ids_0 + + if token_ids_1 is not None: + output = output + token_ids_1 + + if self.add_eos_token: + output = output + [self.eos_token_id] + + return output + + def get_special_tokens_mask( + self, token_ids_0: List[int], token_ids_1: Optional[List[int]] = None, already_has_special_tokens: bool = False + ) -> List[int]: + """ + Retrieve sequence ids from a token list that has no special tokens added. This method is called when adding + special tokens using the tokenizer `prepare_for_model` method. + + Args: + token_ids_0 (`List[int]`): + List of IDs. + token_ids_1 (`List[int]`, *optional*): + Optional second list of IDs for sequence pairs. + already_has_special_tokens (`bool`, *optional*, defaults to `False`): + Whether or not the token list is already formatted with special tokens for the model. + + Returns: + `List[int]`: A list of integers in the range [0, 1]: 1 for a special token, 0 for a sequence token. + """ + if already_has_special_tokens: + return super().get_special_tokens_mask( + token_ids_0=token_ids_0, token_ids_1=token_ids_1, already_has_special_tokens=True + ) + + if token_ids_1 is None: + return [1] + ([0] * len(token_ids_0)) + [1] + return [1] + ([0] * len(token_ids_0)) + [1, 1] + ([0] * len(token_ids_1)) + [1] + + def create_token_type_ids_from_sequences( + self, token_ids_0: List[int], token_ids_1: Optional[List[int]] = None + ) -> List[int]: + """ + Create a mask from the two sequences passed to be used in a sequence-pair classification task. 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file mode 100644 index 0000000000000000000000000000000000000000..24cc342e78d1a006c782b3a4cd68d9ce786d8fd8 --- /dev/null +++ b/InternVL-main/internvl_chat/work_dirs/internvl_chat_v2_5/train2/checkpoint-800/zero_to_fp32.py @@ -0,0 +1,604 @@ +#!/usr/bin/env python + +# Copyright (c) Microsoft Corporation. +# SPDX-License-Identifier: Apache-2.0 + +# DeepSpeed Team + +# This script extracts fp32 consolidated weights from a zero 1, 2 and 3 DeepSpeed checkpoints. It gets +# copied into the top level checkpoint dir, so the user can easily do the conversion at any point in +# the future. Once extracted, the weights don't require DeepSpeed and can be used in any +# application. +# +# example: python zero_to_fp32.py . pytorch_model.bin + +import argparse +import torch +import glob +import math +import os +import re +from collections import OrderedDict +from dataclasses import dataclass + +# while this script doesn't use deepspeed to recover data, since the checkpoints are pickled with +# DeepSpeed data structures it has to be available in the current python environment. +from deepspeed.utils import logger +from deepspeed.checkpoint.constants import (DS_VERSION, OPTIMIZER_STATE_DICT, SINGLE_PARTITION_OF_FP32_GROUPS, + FP32_FLAT_GROUPS, ZERO_STAGE, PARTITION_COUNT, PARAM_SHAPES, BUFFER_NAMES, + FROZEN_PARAM_SHAPES, FROZEN_PARAM_FRAGMENTS) + + +@dataclass +class zero_model_state: + buffers: dict() + param_shapes: dict() + shared_params: list + ds_version: int + frozen_param_shapes: dict() + frozen_param_fragments: dict() + + +debug = 0 + +# load to cpu +device = torch.device('cpu') + + +def atoi(text): + return int(text) if text.isdigit() else text + + +def natural_keys(text): + ''' + alist.sort(key=natural_keys) sorts in human order + http://nedbatchelder.com/blog/200712/human_sorting.html + (See Toothy's implementation in the comments) + ''' + return [atoi(c) for c in re.split(r'(\d+)', text)] + + +def get_model_state_file(checkpoint_dir, zero_stage): + if not os.path.isdir(checkpoint_dir): + raise FileNotFoundError(f"Directory '{checkpoint_dir}' doesn't exist") + + # there should be only one file + if zero_stage <= 2: + file = os.path.join(checkpoint_dir, "mp_rank_00_model_states.pt") + elif zero_stage == 3: + file = os.path.join(checkpoint_dir, "zero_pp_rank_0_mp_rank_00_model_states.pt") + + if not os.path.exists(file): + raise FileNotFoundError(f"can't find model states file at '{file}'") + + return file + + +def get_checkpoint_files(checkpoint_dir, glob_pattern): + # XXX: need to test that this simple glob rule works for multi-node setup too + ckpt_files = sorted(glob.glob(os.path.join(checkpoint_dir, glob_pattern)), key=natural_keys) + + if len(ckpt_files) == 0: + raise FileNotFoundError(f"can't find {glob_pattern} files in directory '{checkpoint_dir}'") + + return ckpt_files + + +def get_optim_files(checkpoint_dir): + return get_checkpoint_files(checkpoint_dir, "*_optim_states.pt") + + +def get_model_state_files(checkpoint_dir): + return get_checkpoint_files(checkpoint_dir, "*_model_states.pt") + + +def parse_model_states(files): + zero_model_states = [] + for file in files: + state_dict = torch.load(file, map_location=device) + + if BUFFER_NAMES not in state_dict: + raise ValueError(f"{file} is not a model state checkpoint") + buffer_names = state_dict[BUFFER_NAMES] + if debug: + print("Found buffers:", buffer_names) + + # recover just the buffers while restoring them to fp32 if they were saved in fp16 + buffers = {k: v.float() for k, v in state_dict["module"].items() if k in buffer_names} + param_shapes = state_dict[PARAM_SHAPES] + + # collect parameters that are included in param_shapes + param_names = [] + for s in param_shapes: + for name in s.keys(): + param_names.append(name) + + # update with frozen parameters + frozen_param_shapes = state_dict.get(FROZEN_PARAM_SHAPES, None) + if frozen_param_shapes is not None: + if debug: + print(f"Found frozen_param_shapes: {frozen_param_shapes}") + param_names += list(frozen_param_shapes.keys()) + + # handle shared params + shared_params = [[k, v] for k, v in state_dict["shared_params"].items()] + + ds_version = state_dict.get(DS_VERSION, None) + + frozen_param_fragments = state_dict.get(FROZEN_PARAM_FRAGMENTS, None) + + z_model_state = zero_model_state(buffers=buffers, + param_shapes=param_shapes, + shared_params=shared_params, + ds_version=ds_version, + frozen_param_shapes=frozen_param_shapes, + frozen_param_fragments=frozen_param_fragments) + zero_model_states.append(z_model_state) + + return zero_model_states + + +def parse_optim_states(files, ds_checkpoint_dir): + + total_files = len(files) + state_dicts = [] + for f in files: + state_dict = torch.load(f, map_location=device) + # immediately discard the potentially huge 2 optimizer states as we only care for fp32 master weights + # and also handle the case where it was already removed by another helper script + state_dict["optimizer_state_dict"].pop("optimizer_state_dict", None) + state_dicts.append(state_dict) + + if not ZERO_STAGE in state_dicts[0][OPTIMIZER_STATE_DICT]: + raise ValueError(f"{files[0]} is not a zero checkpoint") + zero_stage = state_dicts[0][OPTIMIZER_STATE_DICT][ZERO_STAGE] + world_size = state_dicts[0][OPTIMIZER_STATE_DICT][PARTITION_COUNT] + + # For ZeRO-2 each param group can have different partition_count as data parallelism for expert + # parameters can be different from data parallelism for non-expert parameters. So we can just + # use the max of the partition_count to get the dp world_size. + + if type(world_size) is list: + world_size = max(world_size) + + if world_size != total_files: + raise ValueError( + f"Expected {world_size} of '*_optim_states.pt' under '{ds_checkpoint_dir}' but found {total_files} files. " + "Possibly due to an overwrite of an old checkpoint, or a checkpoint didn't get saved by one or more processes." + ) + + # the groups are named differently in each stage + if zero_stage <= 2: + fp32_groups_key = SINGLE_PARTITION_OF_FP32_GROUPS + elif zero_stage == 3: + fp32_groups_key = FP32_FLAT_GROUPS + else: + raise ValueError(f"unknown zero stage {zero_stage}") + + if zero_stage <= 2: + fp32_flat_groups = [state_dicts[i][OPTIMIZER_STATE_DICT][fp32_groups_key] for i in range(len(state_dicts))] + elif zero_stage == 3: + # if there is more than one param group, there will be multiple flattened tensors - one + # flattened tensor per group - for simplicity merge them into a single tensor + # + # XXX: could make the script more memory efficient for when there are multiple groups - it + # will require matching the sub-lists of param_shapes for each param group flattened tensor + + fp32_flat_groups = [ + torch.cat(state_dicts[i][OPTIMIZER_STATE_DICT][fp32_groups_key], 0) for i in range(len(state_dicts)) + ] + + return zero_stage, world_size, fp32_flat_groups + + +def _get_fp32_state_dict_from_zero_checkpoint(ds_checkpoint_dir, exclude_frozen_parameters): + """ + Returns fp32 state_dict reconstructed from ds checkpoint + + Args: + - ``ds_checkpoint_dir``: path to the deepspeed checkpoint folder (where the optimizer files are) + + """ + print(f"Processing zero checkpoint '{ds_checkpoint_dir}'") + + optim_files = get_optim_files(ds_checkpoint_dir) + zero_stage, world_size, fp32_flat_groups = parse_optim_states(optim_files, ds_checkpoint_dir) + print(f"Detected checkpoint of type zero stage {zero_stage}, world_size: {world_size}") + + model_files = get_model_state_files(ds_checkpoint_dir) + + zero_model_states = parse_model_states(model_files) + print(f'Parsing checkpoint created by deepspeed=={zero_model_states[0].ds_version}') + + if zero_stage <= 2: + return _get_fp32_state_dict_from_zero2_checkpoint(world_size, fp32_flat_groups, zero_model_states, + exclude_frozen_parameters) + elif zero_stage == 3: + return _get_fp32_state_dict_from_zero3_checkpoint(world_size, fp32_flat_groups, zero_model_states, + exclude_frozen_parameters) + + +def _zero2_merge_frozen_params(state_dict, zero_model_states): + if zero_model_states[0].frozen_param_shapes is None or len(zero_model_states[0].frozen_param_shapes) == 0: + return + + frozen_param_shapes = zero_model_states[0].frozen_param_shapes + frozen_param_fragments = zero_model_states[0].frozen_param_fragments + + if debug: + num_elem = sum(s.numel() for s in frozen_param_shapes.values()) + print(f'rank 0: {FROZEN_PARAM_SHAPES}.numel = {num_elem}') + + wanted_params = len(frozen_param_shapes) + wanted_numel = sum(s.numel() for s in frozen_param_shapes.values()) + avail_numel = sum([p.numel() for p in frozen_param_fragments.values()]) + print(f'Frozen params: Have {avail_numel} numels to process.') + print(f'Frozen params: Need {wanted_numel} numels in {wanted_params} params') + + total_params = 0 + total_numel = 0 + for name, shape in frozen_param_shapes.items(): + total_params += 1 + unpartitioned_numel = shape.numel() + total_numel += unpartitioned_numel + + state_dict[name] = frozen_param_fragments[name] + + if debug: + print(f"{name} full shape: {shape} unpartitioned numel {unpartitioned_numel} ") + + print(f"Reconstructed Frozen fp32 state dict with {total_params} params {total_numel} elements") + + +def _has_callable(obj, fn): + attr = getattr(obj, fn, None) + return callable(attr) + + +def _zero2_merge_trainable_params(state_dict, world_size, fp32_flat_groups, zero_model_states): + param_shapes = zero_model_states[0].param_shapes + + # Reconstruction protocol: + # + # XXX: document this + + if debug: + for i in range(world_size): + for j in range(len(fp32_flat_groups[0])): + print(f"{FP32_FLAT_GROUPS}[{i}][{j}].shape={fp32_flat_groups[i][j].shape}") + + # XXX: memory usage doubles here (zero2) + num_param_groups = len(fp32_flat_groups[0]) + merged_single_partition_of_fp32_groups = [] + for i in range(num_param_groups): + merged_partitions = [sd[i] for sd in fp32_flat_groups] + full_single_fp32_vector = torch.cat(merged_partitions, 0) + merged_single_partition_of_fp32_groups.append(full_single_fp32_vector) + avail_numel = sum( + [full_single_fp32_vector.numel() for full_single_fp32_vector in merged_single_partition_of_fp32_groups]) + + if debug: + wanted_params = sum([len(shapes) for shapes in param_shapes]) + wanted_numel = sum([sum(shape.numel() for shape in shapes.values()) for shapes in param_shapes]) + # not asserting if there is a mismatch due to possible padding + print(f"Have {avail_numel} numels to process.") + print(f"Need {wanted_numel} numels in {wanted_params} params.") + + # params + # XXX: for huge models that can't fit into the host's RAM we will have to recode this to support + # out-of-core computing solution + total_numel = 0 + total_params = 0 + for shapes, full_single_fp32_vector in zip(param_shapes, merged_single_partition_of_fp32_groups): + offset = 0 + avail_numel = full_single_fp32_vector.numel() + for name, shape in shapes.items(): + + unpartitioned_numel = shape.numel() if _has_callable(shape, 'numel') else math.prod(shape) + total_numel += unpartitioned_numel + total_params += 1 + + if debug: + print(f"{name} full shape: {shape} unpartitioned numel {unpartitioned_numel} ") + state_dict[name] = full_single_fp32_vector.narrow(0, offset, unpartitioned_numel).view(shape) + offset += unpartitioned_numel + + # Z2 started to align to 2*world_size to improve nccl performance. Therefore both offset and + # avail_numel can differ by anywhere between 0..2*world_size. Due to two unrelated complex + # paddings performed in the code it's almost impossible to predict the exact numbers w/o the + # live optimizer object, so we are checking that the numbers are within the right range + align_to = 2 * world_size + + def zero2_align(x): + return align_to * math.ceil(x / align_to) + + if debug: + print(f"original offset={offset}, avail_numel={avail_numel}") + + offset = zero2_align(offset) + avail_numel = zero2_align(avail_numel) + + if debug: + print(f"aligned offset={offset}, avail_numel={avail_numel}") + + # Sanity check + if offset != avail_numel: + raise ValueError(f"consumed {offset} numels out of {avail_numel} - something is wrong") + + print(f"Reconstructed fp32 state dict with {total_params} params {total_numel} elements") + + +def _get_fp32_state_dict_from_zero2_checkpoint(world_size, fp32_flat_groups, zero_model_states, + exclude_frozen_parameters): + state_dict = OrderedDict() + + # buffers + buffers = zero_model_states[0].buffers + state_dict.update(buffers) + if debug: + print(f"added {len(buffers)} buffers") + + if not exclude_frozen_parameters: + _zero2_merge_frozen_params(state_dict, zero_model_states) + + _zero2_merge_trainable_params(state_dict, world_size, fp32_flat_groups, zero_model_states) + + # recover shared parameters + for pair in zero_model_states[0].shared_params: + if pair[1] in state_dict: + state_dict[pair[0]] = state_dict[pair[1]] + + return state_dict + + +def zero3_partitioned_param_info(unpartitioned_numel, world_size): + remainder = unpartitioned_numel % world_size + padding_numel = (world_size - remainder) if remainder else 0 + partitioned_numel = math.ceil(unpartitioned_numel / world_size) + return partitioned_numel, padding_numel + + +def _zero3_merge_frozen_params(state_dict, world_size, zero_model_states): + if zero_model_states[0].frozen_param_shapes is None or len(zero_model_states[0].frozen_param_shapes) == 0: + return + + if debug: + for i in range(world_size): + num_elem = sum(s.numel() for s in zero_model_states[i].frozen_param_fragments.values()) + print(f'rank {i}: {FROZEN_PARAM_SHAPES}.numel = {num_elem}') + + frozen_param_shapes = zero_model_states[0].frozen_param_shapes + wanted_params = len(frozen_param_shapes) + wanted_numel = sum(s.numel() for s in frozen_param_shapes.values()) + avail_numel = sum([p.numel() for p in zero_model_states[0].frozen_param_fragments.values()]) * world_size + print(f'Frozen params: Have {avail_numel} numels to process.') + print(f'Frozen params: Need {wanted_numel} numels in {wanted_params} params') + + total_params = 0 + total_numel = 0 + for name, shape in zero_model_states[0].frozen_param_shapes.items(): + total_params += 1 + unpartitioned_numel = shape.numel() + total_numel += unpartitioned_numel + + param_frags = tuple(model_state.frozen_param_fragments[name] for model_state in zero_model_states) + state_dict[name] = torch.cat(param_frags, 0).narrow(0, 0, unpartitioned_numel).view(shape) + + partitioned_numel, partitioned_padding_numel = zero3_partitioned_param_info(unpartitioned_numel, world_size) + + if debug: + print( + f"Frozen params: {total_params} {name} full shape: {shape} partition0 numel={partitioned_numel} partitioned_padding_numel={partitioned_padding_numel}" + ) + + print(f"Reconstructed Frozen fp32 state dict with {total_params} params {total_numel} elements") + + +def _zero3_merge_trainable_params(state_dict, world_size, fp32_flat_groups, zero_model_states): + param_shapes = zero_model_states[0].param_shapes + avail_numel = fp32_flat_groups[0].numel() * world_size + # Reconstruction protocol: For zero3 we need to zip the partitions together at boundary of each + # param, re-consolidating each param, while dealing with padding if any + + # merge list of dicts, preserving order + param_shapes = {k: v for d in param_shapes for k, v in d.items()} + + if debug: + for i in range(world_size): + print(f"{FP32_FLAT_GROUPS}[{i}].shape={fp32_flat_groups[i].shape}") + + wanted_params = len(param_shapes) + wanted_numel = sum(shape.numel() for shape in param_shapes.values()) + # not asserting if there is a mismatch due to possible padding + avail_numel = fp32_flat_groups[0].numel() * world_size + print(f"Trainable params: Have {avail_numel} numels to process.") + print(f"Trainable params: Need {wanted_numel} numels in {wanted_params} params.") + + # params + # XXX: for huge models that can't fit into the host's RAM we will have to recode this to support + # out-of-core computing solution + offset = 0 + total_numel = 0 + total_params = 0 + for name, shape in param_shapes.items(): + + unpartitioned_numel = shape.numel() + total_numel += unpartitioned_numel + total_params += 1 + + partitioned_numel, partitioned_padding_numel = zero3_partitioned_param_info(unpartitioned_numel, world_size) + + if debug: + print( + f"Trainable params: {total_params} {name} full shape: {shape} partition0 numel={partitioned_numel} partitioned_padding_numel={partitioned_padding_numel}" + ) + + # XXX: memory usage doubles here + state_dict[name] = torch.cat( + tuple(fp32_flat_groups[i].narrow(0, offset, partitioned_numel) for i in range(world_size)), + 0).narrow(0, 0, unpartitioned_numel).view(shape) + offset += partitioned_numel + + offset *= world_size + + # Sanity check + if offset != avail_numel: + raise ValueError(f"consumed {offset} numels out of {avail_numel} - something is wrong") + + print(f"Reconstructed Trainable fp32 state dict with {total_params} params {total_numel} elements") + + +def _get_fp32_state_dict_from_zero3_checkpoint(world_size, fp32_flat_groups, zero_model_states, + exclude_frozen_parameters): + state_dict = OrderedDict() + + # buffers + buffers = zero_model_states[0].buffers + state_dict.update(buffers) + if debug: + print(f"added {len(buffers)} buffers") + + if not exclude_frozen_parameters: + _zero3_merge_frozen_params(state_dict, world_size, zero_model_states) + + _zero3_merge_trainable_params(state_dict, world_size, fp32_flat_groups, zero_model_states) + + # recover shared parameters + for pair in zero_model_states[0].shared_params: + if pair[1] in state_dict: + state_dict[pair[0]] = state_dict[pair[1]] + + return state_dict + + +def get_fp32_state_dict_from_zero_checkpoint(checkpoint_dir, tag=None, exclude_frozen_parameters=False): + """ + Convert ZeRO 2 or 3 checkpoint into a single fp32 consolidated state_dict that can be loaded with + ``load_state_dict()`` and used for training without DeepSpeed or shared with others, for example + via a model hub. + + Args: + - ``checkpoint_dir``: path to the desired checkpoint folder + - ``tag``: checkpoint tag used as a unique identifier for checkpoint. If not provided will attempt to load tag in 'latest' file. e.g., ``global_step14`` + - ``exclude_frozen_parameters``: exclude frozen parameters + + Returns: + - pytorch ``state_dict`` + + Note: this approach may not work if your application doesn't have sufficient free CPU memory and + you may need to use the offline approach using the ``zero_to_fp32.py`` script that is saved with + the checkpoint. + + A typical usage might be :: + + from deepspeed.utils.zero_to_fp32 import get_fp32_state_dict_from_zero_checkpoint + # do the training and checkpoint saving + state_dict = get_fp32_state_dict_from_zero_checkpoint(checkpoint_dir) # already on cpu + model = model.cpu() # move to cpu + model.load_state_dict(state_dict) + # submit to model hub or save the model to share with others + + In this example the ``model`` will no longer be usable in the deepspeed context of the same + application. i.e. you will need to re-initialize the deepspeed engine, since + ``model.load_state_dict(state_dict)`` will remove all the deepspeed magic from it. + + If you want it all done for you, use ``load_state_dict_from_zero_checkpoint`` instead. + + """ + if tag is None: + latest_path = os.path.join(checkpoint_dir, 'latest') + if os.path.isfile(latest_path): + with open(latest_path, 'r') as fd: + tag = fd.read().strip() + else: + raise ValueError(f"Unable to find 'latest' file at {latest_path}") + + ds_checkpoint_dir = os.path.join(checkpoint_dir, tag) + + if not os.path.isdir(ds_checkpoint_dir): + raise FileNotFoundError(f"Directory '{ds_checkpoint_dir}' doesn't exist") + + return _get_fp32_state_dict_from_zero_checkpoint(ds_checkpoint_dir, exclude_frozen_parameters) + + +def convert_zero_checkpoint_to_fp32_state_dict(checkpoint_dir, output_file, tag=None, exclude_frozen_parameters=False): + """ + Convert ZeRO 2 or 3 checkpoint into a single fp32 consolidated ``state_dict`` file that can be + loaded with ``torch.load(file)`` + ``load_state_dict()`` and used for training without DeepSpeed. + + Args: + - ``checkpoint_dir``: path to the desired checkpoint folder. (one that contains the tag-folder, like ``global_step14``) + - ``output_file``: path to the pytorch fp32 state_dict output file (e.g. path/pytorch_model.bin) + - ``tag``: checkpoint tag used as a unique identifier for checkpoint. If not provided will attempt to load tag in the file named ``latest`` in the checkpoint folder, e.g., ``global_step14`` + - ``exclude_frozen_parameters``: exclude frozen parameters + """ + + state_dict = get_fp32_state_dict_from_zero_checkpoint(checkpoint_dir, tag, exclude_frozen_parameters) + print(f"Saving fp32 state dict to {output_file}") + torch.save(state_dict, output_file) + + +def load_state_dict_from_zero_checkpoint(model, checkpoint_dir, tag=None): + """ + 1. Put the provided model to cpu + 2. Convert ZeRO 2 or 3 checkpoint into a single fp32 consolidated ``state_dict`` + 3. Load it into the provided model + + Args: + - ``model``: the model object to update + - ``checkpoint_dir``: path to the desired checkpoint folder. (one that contains the tag-folder, like ``global_step14``) + - ``tag``: checkpoint tag used as a unique identifier for checkpoint. If not provided will attempt to load tag in the file named ``latest`` in the checkpoint folder, e.g., ``global_step14`` + + Returns: + - ``model`: modified model + + Make sure you have plenty of CPU memory available before you call this function. If you don't + have enough use the ``zero_to_fp32.py`` utility to do the conversion. You will find it + conveniently placed for you in the checkpoint folder. + + A typical usage might be :: + + from deepspeed.utils.zero_to_fp32 import load_state_dict_from_zero_checkpoint + model = load_state_dict_from_zero_checkpoint(trainer.model, checkpoint_dir) + # submit to model hub or save the model to share with others + + Note, that once this was run, the ``model`` will no longer be usable in the deepspeed context + of the same application. i.e. you will need to re-initialize the deepspeed engine, since + ``model.load_state_dict(state_dict)`` will remove all the deepspeed magic from it. + + """ + logger.info(f"Extracting fp32 weights") + state_dict = get_fp32_state_dict_from_zero_checkpoint(checkpoint_dir, tag) + + logger.info(f"Overwriting model with fp32 weights") + model = model.cpu() + model.load_state_dict(state_dict, strict=False) + + return model + + +if __name__ == "__main__": + + parser = argparse.ArgumentParser() + parser.add_argument("checkpoint_dir", + type=str, + help="path to the desired checkpoint folder, e.g., path/checkpoint-12") + parser.add_argument( + "output_file", + type=str, + help="path to the pytorch fp32 state_dict output file (e.g. path/checkpoint-12/pytorch_model.bin)") + parser.add_argument("-t", + "--tag", + type=str, + default=None, + help="checkpoint tag used as a unique identifier for checkpoint. e.g., global_step1") + parser.add_argument("--exclude_frozen_parameters", action='store_true', help="exclude frozen parameters") + parser.add_argument("-d", "--debug", action='store_true', help="enable debug") + args = parser.parse_args() + + debug = args.debug + + convert_zero_checkpoint_to_fp32_state_dict(args.checkpoint_dir, + args.output_file, + tag=args.tag, + exclude_frozen_parameters=args.exclude_frozen_parameters)